WO2012116122A2 - A protein expression-based classifier for prediction of recurrence in adenocarcinoma - Google Patents
A protein expression-based classifier for prediction of recurrence in adenocarcinoma Download PDFInfo
- Publication number
- WO2012116122A2 WO2012116122A2 PCT/US2012/026201 US2012026201W WO2012116122A2 WO 2012116122 A2 WO2012116122 A2 WO 2012116122A2 US 2012026201 W US2012026201 W US 2012026201W WO 2012116122 A2 WO2012116122 A2 WO 2012116122A2
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- patient
- expression
- surgery
- score
- catenin
- Prior art date
Links
- 208000009956 adenocarcinoma Diseases 0.000 title claims description 38
- 108090000623 proteins and genes Proteins 0.000 title description 19
- 102000004169 proteins and genes Human genes 0.000 title description 18
- 108010017324 STAT3 Transcription Factor Proteins 0.000 claims abstract description 227
- 102100024040 Signal transducer and activator of transcription 3 Human genes 0.000 claims abstract description 227
- 206010028980 Neoplasm Diseases 0.000 claims abstract description 223
- 238000000034 method Methods 0.000 claims abstract description 182
- 108060000903 Beta-catenin Proteins 0.000 claims abstract description 119
- 102000015735 Beta-catenin Human genes 0.000 claims abstract description 119
- 108010020382 Hepatocyte Nuclear Factor 1-alpha Proteins 0.000 claims abstract description 116
- 102100022057 Hepatocyte nuclear factor 1-alpha Human genes 0.000 claims abstract description 116
- 108010057966 Thyroid Nuclear Factor 1 Proteins 0.000 claims abstract description 107
- 102000002658 Thyroid Nuclear Factor 1 Human genes 0.000 claims abstract description 107
- 239000000090 biomarker Substances 0.000 claims abstract description 95
- 201000011510 cancer Diseases 0.000 claims abstract description 84
- 238000004393 prognosis Methods 0.000 claims abstract description 18
- 238000001356 surgical procedure Methods 0.000 claims description 134
- 230000004083 survival effect Effects 0.000 claims description 125
- 102000016736 Cyclin Human genes 0.000 claims description 116
- 108050006400 Cyclin Proteins 0.000 claims description 116
- 238000009098 adjuvant therapy Methods 0.000 claims description 70
- 210000004027 cell Anatomy 0.000 claims description 59
- 201000005249 lung adenocarcinoma Diseases 0.000 claims description 57
- 206010058467 Lung neoplasm malignant Diseases 0.000 claims description 36
- 230000008901 benefit Effects 0.000 claims description 36
- 238000010191 image analysis Methods 0.000 claims description 36
- 201000005202 lung cancer Diseases 0.000 claims description 36
- 208000020816 lung neoplasm Diseases 0.000 claims description 36
- 238000002560 therapeutic procedure Methods 0.000 claims description 34
- 238000011282 treatment Methods 0.000 claims description 25
- 230000007170 pathology Effects 0.000 claims description 21
- 238000002512 chemotherapy Methods 0.000 claims description 17
- 230000001086 cytosolic effect Effects 0.000 claims description 16
- 238000012545 processing Methods 0.000 claims description 12
- 210000004072 lung Anatomy 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 7
- 238000001000 micrograph Methods 0.000 claims description 3
- 210000002919 epithelial cell Anatomy 0.000 claims description 2
- 108010058546 Cyclin D1 Proteins 0.000 abstract description 2
- 102100024165 G1/S-specific cyclin-D1 Human genes 0.000 abstract 1
- 239000000523 sample Substances 0.000 description 108
- 210000001519 tissue Anatomy 0.000 description 49
- 238000001574 biopsy Methods 0.000 description 18
- 238000004458 analytical method Methods 0.000 description 17
- 238000012549 training Methods 0.000 description 16
- 208000002154 non-small cell lung carcinoma Diseases 0.000 description 15
- 208000029729 tumor suppressor gene on chromosome 11 Diseases 0.000 description 15
- 201000010099 disease Diseases 0.000 description 14
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 14
- 238000010200 validation analysis Methods 0.000 description 14
- 208000010507 Adenocarcinoma of Lung Diseases 0.000 description 12
- 230000001225 therapeutic effect Effects 0.000 description 11
- 239000000463 material Substances 0.000 description 10
- 230000005754 cellular signaling Effects 0.000 description 9
- SDUQYLNIPVEERB-QPPQHZFASA-N gemcitabine Chemical compound O=C1N=C(N)C=CN1[C@H]1C(F)(F)[C@H](O)[C@@H](CO)O1 SDUQYLNIPVEERB-QPPQHZFASA-N 0.000 description 9
- 229960000397 bevacizumab Drugs 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 8
- AAKJLRGGTJKAMG-UHFFFAOYSA-N erlotinib Chemical compound C=12C=C(OCCOC)C(OCCOC)=CC2=NC=NC=1NC1=CC=CC(C#C)=C1 AAKJLRGGTJKAMG-UHFFFAOYSA-N 0.000 description 8
- 229960005277 gemcitabine Drugs 0.000 description 8
- WBXPDJSOTKVWSJ-ZDUSSCGKSA-L pemetrexed(2-) Chemical compound C=1NC=2NC(N)=NC(=O)C=2C=1CCC1=CC=C(C(=O)N[C@@H](CCC([O-])=O)C([O-])=O)C=C1 WBXPDJSOTKVWSJ-ZDUSSCGKSA-L 0.000 description 8
- 238000012360 testing method Methods 0.000 description 8
- 102000001301 EGF receptor Human genes 0.000 description 7
- 108060006698 EGF receptor Proteins 0.000 description 7
- -1 Ki67 Proteins 0.000 description 7
- 239000005551 L01XE03 - Erlotinib Substances 0.000 description 7
- 229960001433 erlotinib Drugs 0.000 description 7
- 229960005079 pemetrexed Drugs 0.000 description 7
- 238000003364 immunohistochemistry Methods 0.000 description 6
- 238000004445 quantitative analysis Methods 0.000 description 6
- 238000003556 assay Methods 0.000 description 5
- 229940079593 drug Drugs 0.000 description 5
- 239000003814 drug Substances 0.000 description 5
- 238000005259 measurement Methods 0.000 description 5
- 238000012552 review Methods 0.000 description 5
- ZKHQWZAMYRWXGA-KQYNXXCUSA-J ATP(4-) Chemical compound C1=NC=2C(N)=NC=NC=2N1[C@@H]1O[C@H](COP([O-])(=O)OP([O-])(=O)OP([O-])([O-])=O)[C@@H](O)[C@H]1O ZKHQWZAMYRWXGA-KQYNXXCUSA-J 0.000 description 4
- ZKHQWZAMYRWXGA-UHFFFAOYSA-N Adenosine triphosphate Natural products C1=NC=2C(N)=NC=NC=2N1C1OC(COP(O)(=O)OP(O)(=O)OP(O)(O)=O)C(O)C1O ZKHQWZAMYRWXGA-UHFFFAOYSA-N 0.000 description 4
- MLDQJTXFUGDVEO-UHFFFAOYSA-N BAY-43-9006 Chemical compound C1=NC(C(=O)NC)=CC(OC=2C=CC(NC(=O)NC=3C=C(C(Cl)=CC=3)C(F)(F)F)=CC=2)=C1 MLDQJTXFUGDVEO-UHFFFAOYSA-N 0.000 description 4
- 206010009944 Colon cancer Diseases 0.000 description 4
- 239000005411 L01XE02 - Gefitinib Substances 0.000 description 4
- 239000005511 L01XE05 - Sorafenib Substances 0.000 description 4
- ZDZOTLJHXYCWBA-VCVYQWHSSA-N N-debenzoyl-N-(tert-butoxycarbonyl)-10-deacetyltaxol Chemical compound O([C@H]1[C@H]2[C@@](C([C@H](O)C3=C(C)[C@@H](OC(=O)[C@H](O)[C@@H](NC(=O)OC(C)(C)C)C=4C=CC=CC=4)C[C@]1(O)C3(C)C)=O)(C)[C@@H](O)C[C@H]1OC[C@]12OC(=O)C)C(=O)C1=CC=CC=C1 ZDZOTLJHXYCWBA-VCVYQWHSSA-N 0.000 description 4
- 229960000074 biopharmaceutical Drugs 0.000 description 4
- 229960004316 cisplatin Drugs 0.000 description 4
- DQLATGHUWYMOKM-UHFFFAOYSA-L cisplatin Chemical compound N[Pt](N)(Cl)Cl DQLATGHUWYMOKM-UHFFFAOYSA-L 0.000 description 4
- 230000034994 death Effects 0.000 description 4
- 231100000517 death Toxicity 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 229960003668 docetaxel Drugs 0.000 description 4
- 238000003379 elimination reaction Methods 0.000 description 4
- XGALLCVXEZPNRQ-UHFFFAOYSA-N gefitinib Chemical compound C=12C=C(OCCCN3CCOCC3)C(OC)=CC2=NC=NC=1NC1=CC=C(F)C(Cl)=C1 XGALLCVXEZPNRQ-UHFFFAOYSA-N 0.000 description 4
- 229960002584 gefitinib Drugs 0.000 description 4
- 239000003550 marker Substances 0.000 description 4
- 238000000491 multivariate analysis Methods 0.000 description 4
- 239000002777 nucleoside Substances 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 229960003787 sorafenib Drugs 0.000 description 4
- 238000007473 univariate analysis Methods 0.000 description 4
- 102100021569 Apoptosis regulator Bcl-2 Human genes 0.000 description 3
- 108091003079 Bovine Serum Albumin Proteins 0.000 description 3
- 206010006187 Breast cancer Diseases 0.000 description 3
- 208000026310 Breast neoplasm Diseases 0.000 description 3
- 101001012157 Homo sapiens Receptor tyrosine-protein kinase erbB-2 Proteins 0.000 description 3
- 102000011782 Keratins Human genes 0.000 description 3
- 108010076876 Keratins Proteins 0.000 description 3
- 241000283973 Oryctolagus cuniculus Species 0.000 description 3
- 102000014160 PTEN Phosphohydrolase Human genes 0.000 description 3
- 108010011536 PTEN Phosphohydrolase Proteins 0.000 description 3
- 102100030086 Receptor tyrosine-protein kinase erbB-2 Human genes 0.000 description 3
- 238000011226 adjuvant chemotherapy Methods 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 3
- 229940098773 bovine serum albumin Drugs 0.000 description 3
- 238000003745 diagnosis Methods 0.000 description 3
- 230000008030 elimination Effects 0.000 description 3
- 208000021045 exocrine pancreatic carcinoma Diseases 0.000 description 3
- OVBPIULPVIDEAO-LBPRGKRZSA-N folic acid Chemical compound C=1N=C2NC(N)=NC(=O)C2=NC=1CNC1=CC=C(C(=O)N[C@@H](CCC(O)=O)C(O)=O)C=C1 OVBPIULPVIDEAO-LBPRGKRZSA-N 0.000 description 3
- 238000010166 immunofluorescence Methods 0.000 description 3
- 230000002055 immunohistochemical effect Effects 0.000 description 3
- 238000002493 microarray Methods 0.000 description 3
- 239000003068 molecular probe Substances 0.000 description 3
- 150000003833 nucleoside derivatives Chemical class 0.000 description 3
- 208000008443 pancreatic carcinoma Diseases 0.000 description 3
- 238000010837 poor prognosis Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000012216 screening Methods 0.000 description 3
- 238000010186 staining Methods 0.000 description 3
- 238000007619 statistical method Methods 0.000 description 3
- 239000003656 tris buffered saline Substances 0.000 description 3
- KDCGOANMDULRCW-UHFFFAOYSA-N 7H-purine Chemical compound N1=CNC2=NC=NC2=C1 KDCGOANMDULRCW-UHFFFAOYSA-N 0.000 description 2
- 108091012583 BCL2 Proteins 0.000 description 2
- 241000283707 Capra Species 0.000 description 2
- 208000005623 Carcinogenesis Diseases 0.000 description 2
- 206010061819 Disease recurrence Diseases 0.000 description 2
- WSFSSNUMVMOOMR-UHFFFAOYSA-N Formaldehyde Chemical compound O=C WSFSSNUMVMOOMR-UHFFFAOYSA-N 0.000 description 2
- 101000575639 Homo sapiens Ribonucleoside-diphosphate reductase subunit M2 Proteins 0.000 description 2
- 241000709991 Plateros Species 0.000 description 2
- 101710100969 Receptor tyrosine-protein kinase erbB-3 Proteins 0.000 description 2
- 102100029986 Receptor tyrosine-protein kinase erbB-3 Human genes 0.000 description 2
- 102100029981 Receptor tyrosine-protein kinase erbB-4 Human genes 0.000 description 2
- 101710100963 Receptor tyrosine-protein kinase erbB-4 Proteins 0.000 description 2
- 102100026006 Ribonucleoside-diphosphate reductase subunit M2 Human genes 0.000 description 2
- 102000001742 Tumor Suppressor Proteins Human genes 0.000 description 2
- 108010040002 Tumor Suppressor Proteins Proteins 0.000 description 2
- 102000009524 Vascular Endothelial Growth Factor A Human genes 0.000 description 2
- 108010073929 Vascular Endothelial Growth Factor A Proteins 0.000 description 2
- 102000005789 Vascular Endothelial Growth Factors Human genes 0.000 description 2
- 108010019530 Vascular Endothelial Growth Factors Proteins 0.000 description 2
- 239000012190 activator Substances 0.000 description 2
- 239000002246 antineoplastic agent Substances 0.000 description 2
- 230000006907 apoptotic process Effects 0.000 description 2
- 229940120638 avastin Drugs 0.000 description 2
- 201000008275 breast carcinoma Diseases 0.000 description 2
- 230000036952 cancer formation Effects 0.000 description 2
- 231100000504 carcinogenesis Toxicity 0.000 description 2
- 230000010261 cell growth Effects 0.000 description 2
- 239000003153 chemical reaction reagent Substances 0.000 description 2
- 229940044683 chemotherapy drug Drugs 0.000 description 2
- 230000003247 decreasing effect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000009509 drug development Methods 0.000 description 2
- 238000007876 drug discovery Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 235000019152 folic acid Nutrition 0.000 description 2
- 239000011724 folic acid Substances 0.000 description 2
- 230000002962 histologic effect Effects 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000003119 immunoblot Methods 0.000 description 2
- 238000011534 incubation Methods 0.000 description 2
- 230000002401 inhibitory effect Effects 0.000 description 2
- 238000007477 logistic regression Methods 0.000 description 2
- 201000005243 lung squamous cell carcinoma Diseases 0.000 description 2
- 210000004698 lymphocyte Anatomy 0.000 description 2
- 230000010534 mechanism of action Effects 0.000 description 2
- 239000002609 medium Substances 0.000 description 2
- 239000012528 membrane Substances 0.000 description 2
- 230000002246 oncogenic effect Effects 0.000 description 2
- 210000002741 palatine tonsil Anatomy 0.000 description 2
- 239000013641 positive control Substances 0.000 description 2
- 150000003230 pyrimidines Chemical class 0.000 description 2
- 102000005962 receptors Human genes 0.000 description 2
- 108020003175 receptors Proteins 0.000 description 2
- 230000002829 reductive effect Effects 0.000 description 2
- 238000013518 transcription Methods 0.000 description 2
- 230000035897 transcription Effects 0.000 description 2
- 230000004614 tumor growth Effects 0.000 description 2
- 238000011179 visual inspection Methods 0.000 description 2
- 238000001262 western blot Methods 0.000 description 2
- VEEGZPWAAPPXRB-BJMVGYQFSA-N (3e)-3-(1h-imidazol-5-ylmethylidene)-1h-indol-2-one Chemical compound O=C1NC2=CC=CC=C2\C1=C/C1=CN=CN1 VEEGZPWAAPPXRB-BJMVGYQFSA-N 0.000 description 1
- 108091032973 (ribonucleotides)n+m Proteins 0.000 description 1
- UHDGCWIWMRVCDJ-UHFFFAOYSA-N 1-beta-D-Xylofuranosyl-NH-Cytosine Natural products O=C1N=C(N)C=CN1C1C(O)C(O)C(CO)O1 UHDGCWIWMRVCDJ-UHFFFAOYSA-N 0.000 description 1
- CKTSBUTUHBMZGZ-SHYZEUOFSA-N 2'‐deoxycytidine Chemical compound O=C1N=C(N)C=CN1[C@@H]1O[C@H](CO)[C@@H](O)C1 CKTSBUTUHBMZGZ-SHYZEUOFSA-N 0.000 description 1
- 241001502050 Acis Species 0.000 description 1
- CIWBSHSKHKDKBQ-JLAZNSOCSA-N Ascorbic acid Chemical compound OC[C@H](O)[C@H]1OC(=O)C(O)=C1O CIWBSHSKHKDKBQ-JLAZNSOCSA-N 0.000 description 1
- 101150033765 BAG1 gene Proteins 0.000 description 1
- 208000003174 Brain Neoplasms Diseases 0.000 description 1
- RAXZSEGXMBWYQK-SNVBAGLBSA-N C[C@H](C1=CC=CC=C1)NC(=O)NC2=NC(=C3C=NNC3=C2)CO Chemical compound C[C@H](C1=CC=CC=C1)NC(=O)NC2=NC(=C3C=NNC3=C2)CO RAXZSEGXMBWYQK-SNVBAGLBSA-N 0.000 description 1
- 101100454807 Caenorhabditis elegans lgg-1 gene Proteins 0.000 description 1
- 201000009030 Carcinoma Diseases 0.000 description 1
- 102000014914 Carrier Proteins Human genes 0.000 description 1
- 102000003952 Caspase 3 Human genes 0.000 description 1
- 108090000397 Caspase 3 Proteins 0.000 description 1
- KRKNYBCHXYNGOX-UHFFFAOYSA-K Citrate Chemical compound [O-]C(=O)CC(O)(CC([O-])=O)C([O-])=O KRKNYBCHXYNGOX-UHFFFAOYSA-K 0.000 description 1
- 241000581364 Clinitrachus argentatus Species 0.000 description 1
- 208000001333 Colorectal Neoplasms Diseases 0.000 description 1
- 102000006311 Cyclin D1 Human genes 0.000 description 1
- 102000003909 Cyclin E Human genes 0.000 description 1
- 108090000257 Cyclin E Proteins 0.000 description 1
- UHDGCWIWMRVCDJ-PSQAKQOGSA-N Cytidine Natural products O=C1N=C(N)C=CN1[C@@H]1[C@@H](O)[C@@H](O)[C@H](CO)O1 UHDGCWIWMRVCDJ-PSQAKQOGSA-N 0.000 description 1
- 102000004127 Cytokines Human genes 0.000 description 1
- 108090000695 Cytokines Proteins 0.000 description 1
- 108020004414 DNA Proteins 0.000 description 1
- 230000004543 DNA replication Effects 0.000 description 1
- CKTSBUTUHBMZGZ-UHFFFAOYSA-N Deoxycytidine Natural products O=C1N=C(N)C=CN1C1OC(CO)C(O)C1 CKTSBUTUHBMZGZ-UHFFFAOYSA-N 0.000 description 1
- 102100027274 Dual specificity protein phosphatase 6 Human genes 0.000 description 1
- KCXVZYZYPLLWCC-UHFFFAOYSA-N EDTA Chemical compound OC(=O)CN(CC(O)=O)CCN(CC(O)=O)CC(O)=O KCXVZYZYPLLWCC-UHFFFAOYSA-N 0.000 description 1
- GHASVSINZRGABV-UHFFFAOYSA-N Fluorouracil Chemical compound FC1=CNC(=O)NC1=O GHASVSINZRGABV-UHFFFAOYSA-N 0.000 description 1
- 101000971171 Homo sapiens Apoptosis regulator Bcl-2 Proteins 0.000 description 1
- 101001057587 Homo sapiens Dual specificity protein phosphatase 6 Proteins 0.000 description 1
- 101001011441 Homo sapiens Interferon regulatory factor 4 Proteins 0.000 description 1
- 101001131670 Homo sapiens PWWP domain-containing DNA repair factor 3A Proteins 0.000 description 1
- 101000581880 Homo sapiens Protein NCBP2AS2 Proteins 0.000 description 1
- 101000895882 Homo sapiens Transcription factor E2F4 Proteins 0.000 description 1
- 102100030126 Interferon regulatory factor 4 Human genes 0.000 description 1
- 238000010824 Kaplan-Meier survival analysis Methods 0.000 description 1
- 102100040487 Keratin, type I cytoskeletal 13 Human genes 0.000 description 1
- 102100033511 Keratin, type I cytoskeletal 17 Human genes 0.000 description 1
- 102100025756 Keratin, type II cytoskeletal 5 Human genes 0.000 description 1
- 108010065070 Keratin-13 Proteins 0.000 description 1
- 108010066325 Keratin-17 Proteins 0.000 description 1
- 108010070553 Keratin-5 Proteins 0.000 description 1
- 102000007298 Mucin-1 Human genes 0.000 description 1
- 108010008707 Mucin-1 Proteins 0.000 description 1
- OVBPIULPVIDEAO-UHFFFAOYSA-N N-Pteroyl-L-glutaminsaeure Natural products C=1N=C2NC(N)=NC(=O)C2=NC=1CNC1=CC=C(C(=O)NC(CCC(O)=O)C(O)=O)C=C1 OVBPIULPVIDEAO-UHFFFAOYSA-N 0.000 description 1
- 239000000020 Nitrocellulose Substances 0.000 description 1
- CTQNGGLPUBDAKN-UHFFFAOYSA-N O-Xylene Chemical compound CC1=CC=CC=C1C CTQNGGLPUBDAKN-UHFFFAOYSA-N 0.000 description 1
- 108091000080 Phosphotransferase Proteins 0.000 description 1
- 102100027342 Protein NCBP2AS2 Human genes 0.000 description 1
- 102000004022 Protein-Tyrosine Kinases Human genes 0.000 description 1
- 108090000412 Protein-Tyrosine Kinases Proteins 0.000 description 1
- 206010037394 Pulmonary haemorrhage Diseases 0.000 description 1
- 102000004265 STAT2 Transcription Factor Human genes 0.000 description 1
- 108010081691 STAT2 Transcription Factor Proteins 0.000 description 1
- 101150099493 STAT3 gene Proteins 0.000 description 1
- 102000013530 TOR Serine-Threonine Kinases Human genes 0.000 description 1
- 108010065917 TOR Serine-Threonine Kinases Proteins 0.000 description 1
- 102100021783 Transcription factor E2F4 Human genes 0.000 description 1
- 239000007983 Tris buffer Substances 0.000 description 1
- 102000004243 Tubulin Human genes 0.000 description 1
- 108090000704 Tubulin Proteins 0.000 description 1
- 230000004156 Wnt signaling pathway Effects 0.000 description 1
- 239000002671 adjuvant Substances 0.000 description 1
- 238000011256 aggressive treatment Methods 0.000 description 1
- 229940110282 alimta Drugs 0.000 description 1
- 238000000627 alternating current impedance spectroscopy Methods 0.000 description 1
- 230000033115 angiogenesis Effects 0.000 description 1
- 239000004037 angiogenesis inhibitor Substances 0.000 description 1
- 229940121369 angiogenesis inhibitor Drugs 0.000 description 1
- 230000000340 anti-metabolite Effects 0.000 description 1
- 238000011319 anticancer therapy Methods 0.000 description 1
- 239000000427 antigen Substances 0.000 description 1
- 108091007433 antigens Proteins 0.000 description 1
- 102000036639 antigens Human genes 0.000 description 1
- 229940100197 antimetabolite Drugs 0.000 description 1
- 239000002256 antimetabolite Substances 0.000 description 1
- 229940041181 antineoplastic drug Drugs 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000035578 autophosphorylation Effects 0.000 description 1
- 208000036815 beta tubulin Diseases 0.000 description 1
- 108091008324 binding proteins Proteins 0.000 description 1
- OWMVSZAMULFTJU-UHFFFAOYSA-N bis-tris Chemical compound OCCN(CCO)C(CO)(CO)CO OWMVSZAMULFTJU-UHFFFAOYSA-N 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 239000000872 buffer Substances 0.000 description 1
- 239000003560 cancer drug Substances 0.000 description 1
- 230000021164 cell adhesion Effects 0.000 description 1
- 230000006369 cell cycle progression Effects 0.000 description 1
- 239000013592 cell lysate Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 230000002113 chemopreventative effect Effects 0.000 description 1
- 210000000038 chest Anatomy 0.000 description 1
- 208000029742 colonic neoplasm Diseases 0.000 description 1
- 238000010411 cooking Methods 0.000 description 1
- UHDGCWIWMRVCDJ-ZAKLUEHWSA-N cytidine Chemical compound O=C1N=C(N)C=CN1[C@H]1[C@H](O)[C@@H](O)[C@H](CO)O1 UHDGCWIWMRVCDJ-ZAKLUEHWSA-N 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 238000010790 dilution Methods 0.000 description 1
- 239000012895 dilution Substances 0.000 description 1
- 238000001378 electrochemiluminescence detection Methods 0.000 description 1
- 210000000981 epithelium Anatomy 0.000 description 1
- 238000011354 first-line chemotherapy Methods 0.000 description 1
- 238000000799 fluorescence microscopy Methods 0.000 description 1
- 125000001153 fluoro group Chemical group F* 0.000 description 1
- 229960002949 fluorouracil Drugs 0.000 description 1
- 229940014144 folate Drugs 0.000 description 1
- 229960000304 folic acid Drugs 0.000 description 1
- 239000000499 gel Substances 0.000 description 1
- 229940020967 gemzar Drugs 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 239000010931 gold Substances 0.000 description 1
- 229910052737 gold Inorganic materials 0.000 description 1
- 230000012010 growth Effects 0.000 description 1
- 239000003102 growth factor Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 239000000710 homodimer Substances 0.000 description 1
- 125000004435 hydrogen atom Chemical group [H]* 0.000 description 1
- 238000003018 immunoassay Methods 0.000 description 1
- 238000013388 immunohistochemistry analysis Methods 0.000 description 1
- 238000012744 immunostaining Methods 0.000 description 1
- 230000003116 impacting effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
- 230000003834 intracellular effect Effects 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 208000037841 lung tumor Diseases 0.000 description 1
- 238000000386 microscopy Methods 0.000 description 1
- 239000012120 mounting media Substances 0.000 description 1
- 238000010202 multivariate logistic regression analysis Methods 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 239000013642 negative control Substances 0.000 description 1
- 229920001220 nitrocellulos Polymers 0.000 description 1
- 102000039446 nucleic acids Human genes 0.000 description 1
- 108020004707 nucleic acids Proteins 0.000 description 1
- 150000007523 nucleic acids Chemical class 0.000 description 1
- 125000003835 nucleoside group Chemical group 0.000 description 1
- 231100000590 oncogenic Toxicity 0.000 description 1
- 239000012188 paraffin wax Substances 0.000 description 1
- 230000037361 pathway Effects 0.000 description 1
- 238000011338 personalized therapy Methods 0.000 description 1
- 230000003285 pharmacodynamic effect Effects 0.000 description 1
- RLZZZVKAURTHCP-UHFFFAOYSA-N phenanthrene-3,4-diol Chemical compound C1=CC=C2C3=C(O)C(O)=CC=C3C=CC2=C1 RLZZZVKAURTHCP-UHFFFAOYSA-N 0.000 description 1
- 239000003944 phosphoribosylglycinamide formyltransferase inhibitor Substances 0.000 description 1
- 102000020233 phosphotransferase Human genes 0.000 description 1
- 238000011518 platinum-based chemotherapy Methods 0.000 description 1
- 239000002243 precursor Substances 0.000 description 1
- MFDFERRIHVXMIY-UHFFFAOYSA-N procaine Chemical compound CCN(CC)CCOC(=O)C1=CC=C(N)C=C1 MFDFERRIHVXMIY-UHFFFAOYSA-N 0.000 description 1
- 210000002307 prostate Anatomy 0.000 description 1
- 239000002213 purine nucleotide Substances 0.000 description 1
- 239000002719 pyrimidine nucleotide Substances 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000002271 resection Methods 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 238000005204 segregation Methods 0.000 description 1
- 238000002415 sodium dodecyl sulfate polyacrylamide gel electrophoresis Methods 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 206010041823 squamous cell carcinoma Diseases 0.000 description 1
- 230000004960 subcellular localization Effects 0.000 description 1
- 229940120982 tarceva Drugs 0.000 description 1
- ANRHNWWPFJCPAZ-UHFFFAOYSA-M thionine Chemical compound [Cl-].C1=CC(N)=CC2=[S+]C3=CC(N)=CC=C3N=C21 ANRHNWWPFJCPAZ-UHFFFAOYSA-M 0.000 description 1
- LENZDBCJOHFCAS-UHFFFAOYSA-N tris Chemical compound OCC(N)(CO)CO LENZDBCJOHFCAS-UHFFFAOYSA-N 0.000 description 1
- 239000000107 tumor biomarker Substances 0.000 description 1
- YCOYDOIWSSHVCK-UHFFFAOYSA-N vatalanib Chemical compound C1=CC(Cl)=CC=C1NC(C1=CC=CC=C11)=NN=C1CC1=CC=NC=C1 YCOYDOIWSSHVCK-UHFFFAOYSA-N 0.000 description 1
- 229950000578 vatalanib Drugs 0.000 description 1
- 239000008096 xylene Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
- G01N33/57407—Specifically defined cancers
- G01N33/57449—Specifically defined cancers of ovaries
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
- G01N33/57407—Specifically defined cancers
- G01N33/57423—Specifically defined cancers of lung
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/54—Determining the risk of relapse
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/60—Complex ways of combining multiple protein biomarkers for diagnosis
Definitions
- This invention relates to the field of predicting recurrences of adenocarcinoma and stratifying low stage lung adenocarcinoma patients into groups that will or will not benefit from adjuvant therapy .
- Lung cancer predominantly nonsmall-cell lung cancer (NSCLC)
- NSCLC nonsmall-cell lung cancer
- Immunohistochemistry is often used to assess the expression and localization of biomarkers in tumor specimens; however this technique has several shortcomings. IHC is generally poorly standardized and results are typically evaluated by eye in a subjective manner. However, quantitative IHC (qlHC) , often based on image analysis , for example AQUA technology can be used to obtain highly standardized, reproducible and quantitative measurements of biomarkers in situ. (US Patent No 7,219,016; and publications US2009/0034823 and US2010/136549) .
- Biomarkers having prognostic potential for lung cancer were recently reviewed (Zhu, et al Immunohistochemical markers of prognosis in non-small cell lung cancer: a review and proposal for a multiphase approach to marker evaluation. J Clin Pathol 2006; 59:790-800) .
- biomarkers EGFR, HER2, Ki67, p53 and Bcl-2 were reported to have shown prognostic potential in the literature but have not been proven to have clinical value.
- p27 kipl , VEGF A, Cyclin E and pl6 INK4A were considered promising but requiring further study.
- STAT3 Signal transducer and activator of transcription 3 (STAT3) is phosphorylated by receptor associated kinases in response to cytokines and growth factors, and then act as a transcription activator, impacting cell growth and apoptosis. STAT3 is known to promote oncogenesis (Klampfer L., 2006 "Signal transducers and activators of transcription (STATs) : Novel targets of chemopreventive and chemotherapeutic drugs”.
- Cyclin Dl Cyclin family members are critical players in cell cycle progression, and thereby frequently associated with cancer and tumorigenesis . Cyclin Dl is associated with Gl progression and known to be upregulated in lung cancer (Kim JK et al, Nuclear cyclin Dl : an oncogenic driver in human cancer. J Cell Physiol 2009; 220:292- 296.) but was deemed not statistically significantly associated with poor prognosis (Zhang et al, 2011 Clinical Lung Cancer doi:10.1016/j . cllc.2011.20.003) .
- TTF1 Thyroid transcription factor 1 is commonly used as a marker for lung tumors that when positive generally indicates a tumor is of the adenocarcinoma type. TTF1 has also been found to be an independent marker of good prognosis in adenocarcinoma lung cancer patients (Perner S, et al 2009 J Pathol 217:65-72) . Beta catenin: Beta catenin, a member of the Wnt signaling pathway regulates epithelial cell growth and adhesion. Loss of beta catenin is associated with poor prognosis in lung cancer patients. (Kase S et al, Clin Cancer Res 2000; 6:4789-4796)
- a critical clinical problem in management of adenocarcinoma of the lung is to determine which low stage patients are cured by surgery alone, versus which will benefit from adjuvant chemotherapy. While there are only 20% of all lung cancer patients diagnosed at low stage, that still represents over 30,000 patients in the United States .
- This invention is a protein-based test that can stratify low stage lung adenocarcinoma patients into groups that do or do not benefit from additional therapeutic treatment such as chemotherapy.
- the new process assesses the level of four (a) key proteins using, for example, the AQUA technology method of standardized quantitative immunofluorescence IHC as previously described (Camp et al 2002 Nature Medicine 8(11)1323-1327, US Patent 7,219,016; Gustavson et al AQUA Technology and Molecular Pathology in Pathology in Drug Discovery and Development, Platero ed. John Wiley & Sons, lnc, Hoboken, NJ 2009) .
- the method may be used on formalin-fixed, paraffin-embedded tumor specimens, fine-needle aspirates, or other histological samples.
- the four proteins that are measured are:
- TTF1 Thyroid Transcription Factor-1
- STAT3 Signal transducer and activator of transcription -3
- Beta-Catenin beta-Catenin
- Cyclin Dl Cyclin Dl
- Stage 1 lung cancer patients with adenocarcinoma in the low risk group have a 95% chance of survival at 5 years, compared to a 40% chance in the high risk group.
- stage I patients are not usually given chemotherapy or other therapeutic treatment, utilizing this assay and algorithm a study would select a subset (as many as 66% of patients) that fall into the high risk group that would then benefit from additional therapeutic treatment such as chemotherapy.
- the invention provides a method for making a prognosis for a patient afflicted with a type of cancer which comprises: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- the invention provides a method for classifying a patient diagnosed with cancer as being at a low risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a low risk of developing a recurrence of cancer if the score obtained in step (b) is less than the predetermined reference score cutpoint.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- the invention provides a method for classifying a patient diagnosed with cancer as being at a high risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a high risk of developing a recurrence of cancer if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient diagnosed with cancer will develop a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with high risk and low risk patients; so as to thereby determine the likelihood that the patient will develop a recurrence of cancer.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non- nuclear compartments combined in cells of interest in the sample from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score based on the levels of expression determined in steps (a), (b) and (c) by: (i) adding the level of expression in step (a) with the level of expression obtained in step (b) ;
- the invention provides for a kit comprising at least three of the following: a first stain specific for thyroid transcription factor- 1 (TTF1); a second stain specific for signal transducer and activator of transcription-3 (STAT-3) ; a third stain specific for beta-catenin; a fourth stain specific for cyclin Dl ; and instructions for using the kit.
- TTF1 thyroid transcription factor- 1
- STAT-3 second stain specific for signal transducer and activator of transcription-3
- STAT-3 signal transducer and activator of transcription-3
- a third stain specific for beta-catenin a fourth stain specific for cyclin Dl
- instructions for using the kit comprising at least three of the following: a first stain specific for thyroid transcription factor- 1 (TTF1); a second stain specific for signal transducer and activator of transcription-3 (STAT-3) ; a third stain specific for beta-catenin; a fourth stain specific for cyclin Dl ; and instructions for using the kit.
- the invention provides for a non-transitory computer readable medium having program code recorded thereon that, when executed on a computing system, automatically processes data, the program code comprising: code for processing a digital microscopy image of a stained tumor specimen taken from a cancer patient to extract data related to intensity values associated with one or more stains; code for processing the extracted data to arrive at a value for intensity per pixel for each of the one or more stains; code for processing pixel intensity of at least one stain for determining pixels associated with a preselected subcompartment and determining the area of the subcompartment for use as a denominator; code for processing pixel intensity of a second stain for determining an expression level of a biomarker and a value for total biomarker intensity in the same preselected subcompartment for use as a numerator; code for calculating from the numerator and denominator ascore of the biomarker expression per area; code for collecting thescore of each of at least three of the following four biomarkers, including thyroid transcription
- a method for making a prognosis for a patient having a tumor associated with adenocarcimona of the lung which comprises: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the level of expression measured in step (a) for each of the biomarkers; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for identifying a patient having a tumor associated with adenocarcimona of the lung as having a 40% or less chance of survival after five years if treated only by surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with probability of survival after five years if treated only by surgery; wherein if the score obtained in step (b) is greater than the predetermined reference score the patient has a 40% or less chance of survival after five years if treated only by surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will not survive after five years if treated only by surgery a) measuring in a sample of the patient's tumor a level of expression for at each of least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with surival; so as to thereby determine the likelihood that the patient will not survive after five years if treated only by surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl a biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (ST
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl a level of expression for each of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score based on the levels of expression measured in steps (a) , (b) and (c) by: (
- a method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transduc
- a method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transduc
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjucunt therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjunct therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival of reference patients having tumors associated with adenocarcinomas of the lung; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjunct therapy in addition to surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- Figure 1 Is a flow chart showing the steps used to develop the prognostic algorithm.
- Figure 2 Shows linear regression analyses (XY scatter plots with indicated Pearson's R coefficients) for determining the day-to-day reproducibility of expression scores for each of the antibodies used to detect each of the biomarkers in the final lung adenocarcinoma prognostic algorithm including TTF1 (Figure 2A) , STAT3 ( Figure 2B) , Beta-catenin (Figure 2C) and Cyclin Dl ( Figure 2D) . Also, provided are Western blot results (inset) of cell lysates demonstrating specificity of the antibody for the indicated biomarkers.
- Figure 3 Shows linear regression analyses (XY scatter plots with indicated Pearson's R coefficients) for determining the day-to-day reproducibility of expression scores for each of the antibodies used to detect each of the biomarkers in the final lung adenocarcinoma prognostic algorithm including TTF1 (Figure 2A) , STAT3 ( Figure 2B) , Beta-catenin (Figure 2C) and Cyclin Dl ( Figure 2D)
- Figure 4 Kaplan Meier 8-year disease specific-survival analyses with indicated log-Rank P-values for the lung adenocarcinoma prognostic scores.
- Prognostic scores for the training set were divided into 3 equal groups representing high, intermediate, and low risk and the respective cutpoints were subsequently applied to validation cohort ( Figure 4B and 4D) .
- Figure 7 Forest plot showing mean hazard ratios and 95% confidence intervals for the training set and the validation set. Hazard ratios and 95% confidence intervals are above one indicating significant prediction of decreased overall survival. Values for both univariate risk score and risk scores adjusted for Stage (adjusted) are provided. These data represent a summary of data in Tables 5-7, discussed in the Examples section.
- a "predetermined reference score cutpoint" associated with high risk and low risk patients refers to a cutpoint associated with dividing a group of patients into high risk and low risk patients.
- the invention provides a method for making a prognosis for a patient afflicted with a type of cancer which comprises: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin beta-catenin
- cyclin Dl cyclin Dl
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin beta- catenin
- cyclin Dl cyclin Dl
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin beta- catenin
- cyclin Dl cyclin Dl
- AQUA® technology procedures as described in issued U.S. Patent No. 7,219,016, U.S. Patent No. 8,036,833 and U.S. Patent No. 8,121,794, which are incorporated by reference in to this application in its entirety .
- Other quantitative image analysis procedures may include the Bliss system, the ACIS system, the IVision and GenoMx system, the ScanScope Systems, the Ariol SL-50 System, the Vectra and Nuance systems, Leica microscope systems, and the LSC system which are available from the following respective manufacturers: Bacus Laboratories, Inc., Clarient, Inc., BioGenex, DakoCytomation, Applied Imaging Corporation, Perkin Elmer (Caliper) , Leica and CompuCyte Corporation (for more information, please see Immunohistochemistry and Quantitative Analysis of Protein Expression , by Melissa Cregger, Aaron J. Berger, and David L.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered relatively high risk if the patient has a 40% or less chance of survival at five years.
- a patient may be considered at relatively high risk if the patient has a survival profile such as those shown in Figure 5, with a high score (lower curve) .
- a patient may be considered relatively low risk if the patient has a 95%or more chance of survival at five years.
- a patient may be considered at relatively low risk if the patient has a survival profile such as those shown in Figure 5, with a low score (upper curve)
- the invention provides a method for classifying a patient diagnosed with cancer as being at a low risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a low risk of developing a recurrence of cancer if the score obtained in step (b) is less than the predetermined reference score cutpoint.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin beta-catenin and cyclin Dl
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- the levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system .
- the levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure. Numerous quantitative image analysis procedures are known in the art as described above.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40% chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin beta-catenin and cyclin Dl
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- the levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system .
- the levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure. Numerous quantitative image analysis procedures are known in the art as described above. Other quantitative image analysis procedures can be used such as those described above.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40% chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- the invention provides a method for classifying a patient diagnosed with cancer as being at a high risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a high risk of developing a recurrence of cancer if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
- the levels of expression of all four biomarkers , thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl may
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using an automated pathology system.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen.
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40 £ chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- a method for determining the likelihood that a patient diagnosed with cancer will develop a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with high risk and low risk patients; so as to thereby determine the likelihood that the patient will develop a recurrence of cancer.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- the series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin beta-catenin
- cyclin Dl cyclin Dl
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using an automated pathology system .
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40% chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- the series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin beta-catenin
- cyclin Dl cyclin Dl
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- the adjuvant therapy may be chemotherapy.
- the therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using an automated pathology system .
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types .
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40% chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl a level of expression for thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-
- the series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- the adjuvant therapy may be chemotherapy.
- the therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin beta- catenin
- cyclin Dl cyclin Dl
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40 £ chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non- nuclear compartments combined in cells of interest in the sample from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as
- the series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- the adjuvant therapy may be chemotherapy.
- the therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin beta- catenin
- cyclin Dl cyclin Dl
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40 £ chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- a method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score based on the levels of expression determined in steps (a), (b) and (c) by: (i) adding the level of expression in step (a) with the level of expression obtained in step (b) ;
- the series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
- the cancer may be a lung cancer.
- the lung cancer may be adenocarcinoma.
- the adenocarcinoma of the lung may be a stage I cancer.
- the adjuvant therapy may be chemotherapy.
- the therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin beta- catenin
- cyclin Dl cyclin Dl
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
- sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
- the tissue sample may be a fixed tissue section.
- the method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
- the method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
- a patient may be considered high risk if the patient has a 40% chance of survival at five years.
- a patient may be considered low risk if the patient has a 95% chance of survival at five years.
- the invention provides for a kit comprising at least three of the following: a first stain specific for thyroid transcription factor- 1 (TTF1) ; a second stain specific for signal transducer and activator of transcription-3 (STAT-3) ; a third stain specific for beta-catenin; a fourth stain specific for cyclin Dl ; and instructions for using the kit.
- the kit may further comprise predetermined reference score cutpoints associated with high risk patients and with low risk patients.
- the invention provides for a non-transitory computer readable medium having program code recorded thereon that, when executed on a computing system, automatically processes data, the program code comprising: code for processing a digital microscopy image of a stained tumor specimen taken from a cancer patient to extract data related to intensity values associated with one or more stains; code for processing the extracted data to arrive at a value for intensity per pixel for each of the one or more stains; code for processing pixel intensity of at least one stain for determining pixels associated with a preselected subcompartment and determining the area of the subcompartment for use as a denominator; code for processing pixel intensity of a second stain for determining an expression level of a biomarker and a value for total biomarker intensity in the same preselected subcompartment for use as a numerator; code for calculating from the numerator and denominator ascore of the biomarker expression per area; code for collecting thescore of each of at least three of the following four biomarkers, including thyroid transcription
- a method for making a prognosis for a patient having a tumor associated with adenocarcimona of the lung which comprises: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the level of expression measured in step (a) for each of the biomarkers; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for identifying a patient having a tumor associated with adenocarcimona of the lung as having a 40% or less chance of survival after five years if treated only by surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with probability of survival after five years if treated only by surgery; wherein if the score obtained in step (b) is greater than the predetermined reference score the patient has a 40% or less chance of survival after five years if treated only by surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will not survive after five years if treated only by surgery a) measuring in a sample of the patient's tumor a level of expression for at each of least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with surival; so as to thereby determine the likelihood that the patient will not survive after five years if treated only by surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl a biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (ST
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl beta-catenin and cyclin Dl
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl a level of expression for each of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score based on the levels of expression measured in steps (a) , (b) and (c) by: (
- the series of predetermined reference scores may be used to generate a predetermined reference score associated with survival wherein there is a likelihood that the patient will not survive after five years if treated only by surgery if the score obtained in step (b) is greater than the predetermined reference score.
- a method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transduc
- a method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transduc
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjucunt therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- a method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjunct therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival of reference patients having tumors associated with adenocarcinomas of the lung; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjunct therapy in addition to surgery.
- TTF1 thyroid transcription factor-1
- STAT-3 signal transducer and activator of transcription-3
- beta-catenin and cyclin Dl
- the present invention provides, among other things, methods for determining the prognosis for a patient diagnosed with cancer and the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy. While specific embodiments of the subject invention have been discussed, the specification is illustrative and not restrictive. Many variations of the invention will become apparent to those skilled in the art upon review of this specification. The appended claims are not intended to claim all such embodiments and variations, and the full scope of the invention should be determined by reference to the claims, along with their full scope of equivalents, and the specification, along with such variations .
- a critical clinical problem in management of adenocarcinoma of the lung is to determine which patients are cured by surgery alone, versus which will benefit from adjuvant therapy such as chemotherapy. In particular it is critically important to determine which low stage patients are cured by surgery alone, vs. those which will benefit from adjuvant therapy such as chemotherapy. While there are only 20% of all lung cancer patients diagnosed at low stage, that still represents over 30,000 patients in the United States .
- This invention is a protein-based test that can stratify lung adenocarcinoma patients, including specifically low stage lung adenocarcinoma patients, into groups are likely to, or not liely to benefit from additional therapeutic treatment such as chemotherapy.
- the new process assesses the level of four (a) key proteins using, for example, AQUA technology method of standardized quantitative immunofluorescence as previously described (Camp et al 2002 Nature Medicine 8(11)1323-1327, US Patent 7,219,016; Gustavson et al AQUA@ Technology and Molecular Pathology in Pathology in Drug Discovery and Development, Platero ed. John Wiley & Sons, lnc, Hoboken, NJ 2009) .
- the method may be used on formalin-fixed, paraffin-embedded tumor specimens, fine-needle aspirates, or other histological samples .
- the four proteins that are measured are:
- TTF1 Thyroid Transcription Factor-1
- STAT3 Signal transducer and activator of transcription-3
- Beta-Catenin beta-Catenin
- Cyclin Dl Cyclin Dl
- Stage 1 lung cancer patients with adenocarcinoma in the low risk group have a 95% chance of survival at 5 years, compared to a 40% chance in the high risk group.
- stage I patients are not usually given chemotherapy or other therapeutic treatment, this study would select a subset (as many as 66% of patients) that fall into the high risk group that would then benefit from additional therapeutic treatment such as chemotherapy.
- the protein biomarkers are measured in a quantitative manner using standard curves to assure accuracy and precision in measurement. From these data the risk score is then calculated using the following equation:
- equation may be adjusted or optimized as additional cohorts of patients are analyzed. For example, the coefficients for each marker may be optimized relative to broader patient populations.
- Lung cancer predominantly non-small cell lung cancer (NSCLC)
- NSCLC non-small cell lung cancer
- NSCLC diagnosis and histologic leads to several subclassification of disease with adenocarcinoma being the most frequent type of NSCLC.
- Low stage adenocarcinoma is generally treated with surgery without adjuvant therapy. However 35-50% of patients who first present with low stage disease and are treated surgically without adjuvant therapy will suffer recurrence and death due to their disease (Jenal A, et al Cancer Statistics 2010. CA Cancer J Clin 2010; 60:277- 300) . Therefore a prognostic test that could identify patients at risk for recurrence of disease is needed and would provide the opportunity to treat such patients more aggressively to improve outcome .
- the diagnostic test should be simple to perform, avoiding methodologies that are technically challenging requiring that they be conducted in a central laboratory.
- the assay methodology should be standardized and have high reproducibility so that the assay can be provided in a decentralized fashion by multiple laboratories and each can expect to get concordant results. See, for example, the standardization described in Gustavson et al . , Standardization of HER2 Immunohistochemistry in Breast Cancer by Automated Quantitative Analysis, published September 2009 in Arch. Pathol. Lab. Med., the disclosure of which is hereby incorporated by reference into this application .
- Two cohorts of formalin-fixed paraffin-embedded primary NSCLC tumors were used for this study.
- a cohort of 117 adenocarcinoma patients was used as the training set and a second independent cohort of 137 adenocarcinoma patients was used as the validation set.
- N number, AC; adenocarcinoma, SE; standard error
- Tissue specimens were prepared in a tissue microarray (TMA) format: representative tumor areas were obtained from formalin fixed paraffin embedded (FFPE) specimens of the primary tumor and two 0.6mm cores from each tumor block were arrayed in a recipient block.
- TMA tissue microarray
- BSA bovine serum albumin
- Alexa 546-conjugated goat anti-mouse secondary antibody (A11003, Molecular Probes, Eugene, OR) diluted 1:100 in rabbit Envision reagent (K4003, Dako, Carpinteria, CA) or Alexa 546-conjugated goat anti-rabbit secondary antibody (A11010, Molecular Probes, Eugene, OR) diluted 1:100 in mouse Envision reagent (K4001, Dako, Carpinteria, CA) .
- Cyanine 5 (Cy5) directly conjugated to tyramide (FP1117, Perkin-Elmer , Boston, MA) at a 1:50 dilution was used as the fluorescent chromagen for target detection.
- Prolong mounting medium ProLong Gold, P36931, Molecular Probes, Eugene, OR
- DAPI 6-Diamidino-2- phenylindole
- AQUA ® technology allows exact measurement of protein concentration within subcellular compartments, as described in detail elsewhere ( Camp RL, Chung GG, Rimm DL : Automated subcellular localization and quantification of protein expression in tissue microarrays . Nat Med 8:1323-7, 2002) .
- a series of high resolution monochromatic images were captured by the PM-2000TM digital imaging microscopy instrument (HistoRx, Branford, CT) .
- images were obtained using the signal from the DAPI, cytokeratin-Alexa 546 and target-Cy5 channel.
- Target proteins were measured using a channel with emission maxima above 620nm, in order to minimize tissue autofluorescence .
- Tumor was distinguished from stromal and non-stromal elements by creating an epithelial tumor "mask" from the cytokeratin signal. This created a binary mask (each pixel being either "on” or "off”) on the basis of an intensity threshold set by visual inspection of histospots.
- AQUA score of target proteins in the tumor mask and subcellular compartment were calculated by dividing the target compartment pixel intensities by the area of the compartment within they were measured. AQUA scores were normalized to the exposure time and bit depth at which the images were captured, allowing scores collected at different exposure times to be directly comparable. Specimens with less that 5% tumor area per spot were not included in automated quantitative analysis for not being representative of the corresponding tumor specimen.
- the image collection and analysis can also be accomplished using clustering AQUA® software, as described in U.S. Patent Application Publication No. 20090034823, entitled Compartment Segregation by Pixel Characterization Using Image Data Clustering, the contents of which is hereby incorporated by reference into this application, and as described in Gustavson et al., Development of an unsupervised pixel-based clustering algorithm for compartmentalization of immunohistochemical expression using Automated Quantitative Analysis, Appl . Immunohistochemical Mol. Morphol . 2009 Jul; 1794) : 329-37, the contents of which is hereby incorporated by reference into this application.
- This method and system uses autoexposure and is done automatically instead of by visual inspection of histospots.
- AQUA scores were Log2 normalized and scores of the validation sets were further normalized for run to run variability. Missing values were tested by Little's test for missing complete at random; cases with missing values were excluded from analysis. Pearson's correlation coefficient (R) was used to assess the correlation between AQUA scores from redundant tumor cores. An R 2 greater than 0.4 was indicative of good inter- and intra-array reproducibility and thus the average values for all target proteins AQUA scores from duplicate samples were calculated and treated as independent continuous variables .
- FIG. 1 A flowchart of the statistical analysis used to develop the prognostic indicator is shown in Figure 1.
- the expression of an initial set of 42 biomarkers was assessed in 117 primary lung adenocarcinoma cases in cohort 1.
- Biomarkers with expression in non-epithelial tissue (markers exclusively expressed on lymphocytes "contaminating" the tumor e.g. MUM1 , LCK were excluded) , and those for whom assay results were not reproducible (e.g. VEGF, MET, EGFR) were excluded from further analysis.
- Cox multivariate analysis of the 16 chosen markers was performed incorporating the selected biomarkers in a stepwise selection /backward elimination process.
- 1000 bootstrap samples were generated and a backward elimination logistic regression model was developed for each bootstrap sample; the final multivariable model included those variables that were significant at the 0.05 level (Table 3) .
- a risk score was generated as a linear combination of weig hted expression of biomarkers in the reduced (final model) based on coefficients of the multivariate model:
- the final classifier was applied to the testing and validation cohorts. All p values were based on two-sided testing and differences were considered significant at p ⁇ 0.05. All statistical analyses were done using the SPSS software program (version 13.0 for Windows, SPSS Inc., Chicago, IL) and the R-statistics software (version 2.9.0) . Specimen score
- Biomarker Clone/lsotype Antigen Retrieval Concentration Incubation Positive Control Source
- Cytokeratin 13 DE-K13/m lgG 2a , kappa HIAR-pH 9 15min 57 g/ml ON 4°C A431 cells Dako, Carpinteria, CA
- Cytokeratin 17 2D10/m lgG1 HIAR-pH 6 15min O. l Mg/ml ON 4°C A431 cells Abnova, Walnut, CA
- HIAR-pH 6 15min 1/200- ON 4°C A431 cells Cell Signaling, Danvers, MA
- ERK m pnlyr.lnnal HIAR-pH -j I Smin I M OO' ON 4°C A431 cells Cell Signaling. Danvers. MA
- DUSP6 3G /m k;G1 , kappa HIAR-pH 6 15min U. Mg ml ON 4 U C Pancreatic carcinoma Novus Biologicals, Littleton, CO
- CC3 5A1/r HIAR-pH 6 15min 1/500 * ON 4°C Pancreatic carcinoma Cell Signaling, Danvers, MA
- Bag-1 2D3'm lgG 2a , kappa HIAR-pH 6 20min 0.5pg/ml ON 4°C To nsil Novus Biological s, Littleton, CO
- TTFKn -1.213 0.440 0.297 0.125 0.706 0.005 beta Catenin(c) -0.775 0.520 0.461 0.165 1.285 0.130
- Coef coefficient, HR; hazard ratio, CI; confidence interval, tm; tumor mask, n; nuclear, c; cytoplasmic
- Cyclin Dl, STAT3, TTF1 and beta catenin continuous AQUA scores were then incorporated in a multivariate nominal logistic regression model following a backward elimination stepwise selection process for each of the 1000 bootstrap samples; the probability of prediction of recurrence of disease was calculated as linear combination of Cyclin Dl , STAT3, TTF1 and beta catenin log2 normalized AQUA scores weighted as follows:
- Table 5 Cox univariate analyses for the classifier in all, stage I and stage IA AC patients (training set).
- Table 7 Cox multivariate analysis for the classifier adjusting for clinical characteristics (validation set).
- Stage III 1.476 0.473 4.375 1.730 11.067 0.002
- Stage IV 1.933 0.506 6.908 2.560 18.640 ⁇ 0.001
- the prognostic model is not prognostic in squamous cell lung carcinoma ( Figure 6) .
- Figure 7 represents a Forest plot summary of hazard ratio and 95% confidence interval data from Tables 5-7. All hazard ratios and 95% CIs are above one indicating that the continuous risk classifier is a significant predictor of decreased overall survival.
- Adjuvant platinum based chemotherapy with or without gemcitabine is a common therapy for the treatment of NSCLC, which may be guided by the use of additional assessment of biomarker expression (Reynolds J Clinical Oncology 2009, 27:5808-5815) .
- Pemetrexed is chemically similar to folic acid and is in the class of chemotherapy drugs called folate antimetabolites. It works by inhibiting three enzymes used in purine and pyrimidine synthesis—thymidylate synthase (TS), dihydrofolate reductase (DHFR) , and glycinamide ribonucleotide formyltransferase J_McLeod, Howard L.; James Cassidy, Robert H. Powrie, David G. Priest, Mark A. Zorbas, Timothy W. Synold, Stephen Shibata, Darcy Spicer, Donald Bissett, Yazdi K. Pithavala, Mary A. Collier, Linda J. Paradiso, John D.
- TS thymidylate synthase
- DHFR dihydrofolate reductase
- J_McLeod glycinamide ribonucleotide formyltransferase J_McLeod,
- erlotinib specifically targets the epidermal growth factor receptor (EGFR) tyrosine kinase, which is highly expressed and occasionally mutated in various forms of cancer. It binds in a reversible fashion to the adenosine triphosphate (ATP) binding site of the receptor (Raymond E, Faivre S, Armand J (2000) . "Epidermal growth factor receptor tyrosine kinase as a target for anticancer therapy". Drugs 60 Suppl 1: 15-23; discussion 41-2. PMID 11129168) . For the signal to be transmitted, two members of the EGFR family need to come together to form a homodimer.
- EGFR epidermal growth factor receptor
- ATP adenosine triphosphate
- Bevacizumab (trade name Avastin, Genentech/Roche ) is a monoclonal antibody against vascular endothelial growth factor-A (VEGF-A) (Los M, Roodhart JM, Voest EE (April 2007) . "Target practice: lessons from phase III trials with bevacizumab and vatalanib in the treatment of advanced colorectal cancer".
- Bevacizumab was the first clinically available angiogenesis inhibitor in the United States .
- Gemcitabine is a nucleoside analog used as chemotherapy. It is marketed as Gemzar by Eli Lilly and Company. Chemically gemcitabine is a nucleoside analog in which the hydrogen atoms on the 2 ' carbons of deoxycytidine are replaced by fluorine atoms.
- the drug replaces one of the building blocks of nucleic acids, in this case cytidine, during DNA replication.
- the process arrests tumor growth, as new nucleosides cannot be attached to the "faulty" nucleoside, resulting in apoptosis.
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Immunology (AREA)
- Urology & Nephrology (AREA)
- Chemical & Material Sciences (AREA)
- Biomedical Technology (AREA)
- Molecular Biology (AREA)
- Hematology (AREA)
- Medicinal Chemistry (AREA)
- Analytical Chemistry (AREA)
- Biotechnology (AREA)
- Hospice & Palliative Care (AREA)
- Oncology (AREA)
- Food Science & Technology (AREA)
- Microbiology (AREA)
- Physics & Mathematics (AREA)
- Cell Biology (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Pathology (AREA)
- Investigating Or Analysing Biological Materials (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
A method for making a prognosis for a patient afflicted with a type of cancer which comprises (a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta- catenin and cyclin D1; (b) calculating a score based on the levels of expression determined in step (a); (c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
Description
A PROTEIN EXPRESSION-BASED CLASSIFIER FOR PREDICTION OF RECURRENCE
IN ADENOCARCINOMA
This invention was made with support under Grant No. 2009-0097 from the Connecticut Department of Health.
This application claims priority of U.S. Provisional Application No. 61/463,715, filed February 22, 2011, the entire content of which is hereby incorporated by reference into this application.
Throughout this application, various publications are referenced by footnotes and/or parentheses. The disclosures of each of the publications found in this specification is hereby incorporated by reference into this application in order to more fully describe the state of the art as known to those skilled therein as of the date of this application.
Field of the Invention
This invention relates to the field of predicting recurrences of adenocarcinoma and stratifying low stage lung adenocarcinoma patients into groups that will or will not benefit from adjuvant therapy .
Background of the Invention
Lung cancer, predominantly nonsmall-cell lung cancer (NSCLC) , is the most common cause of death from cancer worldwide, with 226,160 new cases and 160, 340 deaths due to disease estimated to occur in 2012 in the US alone (National Cancer Institute) . Survival rates, depending on stage at diagnosis range from 49% to 16% to 2% for local regional and distant stage disease respectively (Ries L, Eisner M, Kosary C, et al . , eds . : Cancer Statistics Review, 1975- 2002. Bethesda, Md: National Cancer Institute, 2005) . Screening patients for early detection of disease has not been shown to impact mortality (Bach PB, Silvestri GA, Hanger M, et al . : Screening for lung cancer: ACCP evidence-based clinical practice guidelines (2nd edition) . Chest 132 (3 Suppl) : 69S-77S, 2007) , perhaps due in part to current treatment paradigms . Early stage treatment includes surgical resection but no adjuvant chemotherapy, resulting in poor overall 5 year survival rate, generally due to recurrence of disease (Mountain CF. The international system for staging lung cancer. Semin Surg Oncol 2000; 18; 106-115) . If those patients at greatest risk for recurrence could be identified, more aggressive treatment could be pursued. For example adjuvant chemotherapy could be considered for those early stage patients that could be subclassified as having a particularly poor prognosis.
Immunohistochemistry (IHC) is often used to assess the expression and localization of biomarkers in tumor specimens; however this technique has several shortcomings. IHC is generally poorly standardized and results are typically evaluated by eye in a subjective manner. However, quantitative IHC (qlHC) , often based on image analysis , for example AQUA technology can be used to obtain highly standardized, reproducible and quantitative measurements of biomarkers in situ. (US Patent No 7,219,016; and publications US2009/0034823 and US2010/136549) .
Biomarkers having prognostic potential for lung cancer were recently reviewed (Zhu, et al Immunohistochemical markers of prognosis in non-small cell lung cancer: a review and proposal for a multiphase approach to marker evaluation. J Clin Pathol 2006; 59:790-800) . In
this review biomarkers EGFR, HER2, Ki67, p53 and Bcl-2 were reported to have shown prognostic potential in the literature but have not been proven to have clinical value. Furthermore, p27kipl, VEGF A, Cyclin E and pl6INK4A were considered promising but requiring further study.
STAT3: Signal transducer and activator of transcription 3 (STAT3) is phosphorylated by receptor associated kinases in response to cytokines and growth factors, and then act as a transcription activator, impacting cell growth and apoptosis. STAT3 is known to promote oncogenesis (Klampfer L., 2006 "Signal transducers and activators of transcription (STATs) : Novel targets of chemopreventive and chemotherapeutic drugs". Curr Cancer Drug Targets 6 (2) : 107-121; Alvarez JV et al 2006, "Signal transducer and activator of transcription 3 is required for the oncogenic effects of non-small-cell lung cancer-associated mutations of the epidermal growth factor receptor", Cancer Res 66 (6) : 3162-3168) , but also has been reported to function in a tumor suppressor role, (de la Iglesia N, et al . , 2008 "Identification of a PTEN-regulated STAT3 brain tumor suppressor pathway", Genes Dev. 22 (4) : 449-462) .
Cyclin Dl : Cyclin family members are critical players in cell cycle progression, and thereby frequently associated with cancer and tumorigenesis . Cyclin Dl is associated with Gl progression and known to be upregulated in lung cancer (Kim JK et al, Nuclear cyclin Dl : an oncogenic driver in human cancer. J Cell Physiol 2009; 220:292- 296.) but was deemed not statistically significantly associated with poor prognosis (Zhang et al, 2011 Clinical Lung Cancer doi:10.1016/j . cllc.2011.20.003) .
TTF1 : Thyroid transcription factor 1 is commonly used as a marker for lung tumors that when positive generally indicates a tumor is of the adenocarcinoma type. TTF1 has also been found to be an independent marker of good prognosis in adenocarcinoma lung cancer patients (Perner S, et al 2009 J Pathol 217:65-72) .
Beta catenin: Beta catenin, a member of the Wnt signaling pathway regulates epithelial cell growth and adhesion. Loss of beta catenin is associated with poor prognosis in lung cancer patients. (Kase S et al, Clin Cancer Res 2000; 6:4789-4796)
A critical clinical problem in management of adenocarcinoma of the lung is to determine which low stage patients are cured by surgery alone, versus which will benefit from adjuvant chemotherapy. While there are only 20% of all lung cancer patients diagnosed at low stage, that still represents over 30,000 patients in the United States .
This invention is a protein-based test that can stratify low stage lung adenocarcinoma patients into groups that do or do not benefit from additional therapeutic treatment such as chemotherapy.
The new process assesses the level of four (a) key proteins using, for example, the AQUA technology method of standardized quantitative immunofluorescence IHC as previously described (Camp et al 2002 Nature Medicine 8(11)1323-1327, US Patent 7,219,016; Gustavson et al AQUA Technology and Molecular Pathology in Pathology in Drug Discovery and Development, Platero ed. John Wiley & Sons, lnc, Hoboken, NJ 2009) . The method may be used on formalin-fixed, paraffin-embedded tumor specimens, fine-needle aspirates, or other histological samples.
The four proteins that are measured are:
Thyroid Transcription Factor-1 (TTF1), Signal transducer and activator of transcription -3 (STAT3), Beta-Catenin, and Cyclin Dl .
These are measured in a quantitative manner using standard curves to assure accuracy and precision in measurement. From these data a risk score is then calculated.
Patients can then be divided into either high risk or low risk groups based on cut-points determined from previous studies . Stage 1 lung cancer patients with adenocarcinoma in the low risk group have a 95% chance of survival at 5 years, compared to a 40% chance
in the high risk group. Although stage I patients are not usually given chemotherapy or other therapeutic treatment, utilizing this assay and algorithm a study would select a subset (as many as 66% of patients) that fall into the high risk group that would then benefit from additional therapeutic treatment such as chemotherapy.
Summary of the Invention
The invention provides a method for making a prognosis for a patient afflicted with a type of cancer which comprises: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
The invention provides a method for classifying a patient diagnosed with cancer as being at a low risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a low risk of developing a recurrence of cancer if the score obtained in step (b) is less than the predetermined reference score cutpoint.
The invention provides a method for classifying a patient diagnosed with cancer as being at a high risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a high risk of developing a recurrence of cancer if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
A method for determining the likelihood that a patient diagnosed with cancer will develop a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with high risk and low risk patients; so as to thereby determine the likelihood that the patient will develop a recurrence of cancer. A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non- nuclear compartments combined in cells of interest in the sample from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score based on the levels of expression determined in steps (a), (b) and (c) by: (i) adding the level of expression in step (a) with the level of expression
obtained in step (b) ; (ii) subtracting the level of expression obtained in step (c) from the sum obtained in step (i) ; (iii) subtracting the level of expression obtained in step (d) from the difference obtained in step (ii) ; and f) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy..
The invention provides for a kit comprising at least three of the following: a first stain specific for thyroid transcription factor- 1 (TTF1); a second stain specific for signal transducer and activator of transcription-3 (STAT-3) ; a third stain specific for beta-catenin; a fourth stain specific for cyclin Dl ; and instructions for using the kit.
The invention provides for a non-transitory computer readable medium having program code recorded thereon that, when executed on a computing system, automatically processes data, the program code comprising: code for processing a digital microscopy image of a stained tumor specimen taken from a cancer patient to extract data related to intensity values associated with one or more stains; code for processing the extracted data to arrive at a value for intensity per pixel for each of the one or more stains; code for processing pixel intensity of at least one stain for determining pixels associated with a preselected subcompartment and determining the area of the subcompartment for use as a denominator; code for processing pixel intensity of a second stain for determining an expression level of a biomarker and a value for total biomarker intensity in the same preselected subcompartment for use as a numerator; code for calculating from the numerator and denominator ascore of the biomarker expression per area; code for collecting thescore of each of at least three of the following four biomarkers, including thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin
Dl ; and code for incorporating the scores of the at least three biomarkers into a score model for arriving at a prognostic score.
A method for making a prognosis for a patient having a tumor associated with adenocarcimona of the lung which comprises: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the level of expression measured in step (a) for each of the biomarkers; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
A method for identifying a patient having a tumor associated with adenocarcimona of the lung as having a 40% or less chance of survival after five years if treated only by surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with probability of survival after five years if treated only by surgery; wherein if the score obtained in step (b) is greater than the predetermined reference score the patient has a 40% or less chance of survival after five years if treated only by surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will not survive after five years if treated only by surgery: a) measuring in a sample of the patient's tumor a level of expression for at each of least three biomarkers selected from the following group: thyroid
transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with surival; so as to thereby determine the likelihood that the patient will not survive after five years if treated only by surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score
based on the levels of expression measured in steps (a) , (b) and (c) by: (i) adding the level of expression in step (a) with the level of expression obtained in step (b) ; (ii) subtracting the level of expression obtained in step (c) from the sum obtained in step (i); (iii) subtracting the level of expression obtained in step (d) from the difference obtained in step (ii); and f) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
A method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
A method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at
least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjucunt therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjunct therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival of reference patients having tumors associated with adenocarcinomas of the lung;
so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjunct therapy in addition to surgery.
Brief Description of the Figures
Figure 1. Is a flow chart showing the steps used to develop the prognostic algorithm.
Figure 2. Shows linear regression analyses (XY scatter plots with indicated Pearson's R coefficients) for determining the day-to-day reproducibility of expression scores for each of the antibodies used to detect each of the biomarkers in the final lung adenocarcinoma prognostic algorithm including TTF1 (Figure 2A) , STAT3 (Figure 2B) , Beta-catenin (Figure 2C) and Cyclin Dl (Figure 2D) . Also, provided are Western blot results (inset) of cell lysates demonstrating specificity of the antibody for the indicated biomarkers. Figure 3. Representative grayscale digital images of biomarker staining in lung adenocarcinoma specimens including staining for TTF1 (Figure 3A) , STAT3 (Figure 3B) , Beta catenin (Figure 3C) and Cyclin Dl (Figure 3D) . Expected patterns of expression are observed indicating specificity of the assay in FFPE tissue specimens (TTF: nuclear; STAT3: cytoplasmic/nuclear; Beta-catenin: membrane/cytoplasmic ; and Cyclin Dl : nuclear)
Figure 4. Kaplan Meier 8-year disease specific-survival analyses with indicated log-Rank P-values for the lung adenocarcinoma prognostic scores. Prognostic scores for the training set (Figure 4A and 4C) were divided into 3 equal groups representing high, intermediate, and low risk and the respective cutpoints were subsequently applied to validation cohort (Figure 4B and 4D) . Analysis was done for all adenocarcinoma patients (Figure 4A and 4B) and Stage 1 patients only (Figure 4C and 4D) . There was significant prediction of survival in the training set for all patients (Figure 4A, Log rank p=0.002) and Stage 1 patients (Figure 4C, Log rank p=0.017) . This finding was validated in the second cohort, for all patients (Figure 4B, Log rank p=0.037) and for stage 1 pateints (Figure 4D, Log rank p=0.006) .
Figure 5. Kaplan Meier 8-year disease specific-survival analysis with indicated log-rank P-values for the lung adenocarcinoma prognostic scores for the same validation cohort as in Figure 4B and D. This analysis demonstrates that the high and intermediate prognostic groups can be combined into one group (Figure 5B; red line, N=71) while maintaining significant survival prediction (Log rank p=0.028) . This is also the case for the Stage 1 (Figure 5C, Log rank p=0.043) and Stage la patients (Figure 5D; Log rank p=0.055, significant at the 10% level) .
Figure 6. Kaplan Meier 8-year disease specific-survival analysis with indicated log-rank P-values for the squamous cell lung carcinoma prognostic scores and probability of survival showing that the lung adenocarcinoma prognostic scores are not applicable to squamous cell carcinoma (log rank p=0.47) .
Figure 7. Forest plot showing mean hazard ratios and 95% confidence intervals for the training set and the validation set. Hazard ratios and 95% confidence intervals are above one indicating significant prediction of decreased overall survival. Values for both univariate risk score and risk scores adjusted for Stage (adjusted) are provided. These data represent a summary of data in Tables 5-7, discussed in the Examples section.
Detailed Description of the Invention
A "predetermined reference score cutpoint" associated with high risk and low risk patients refers to a cutpoint associated with dividing a group of patients into high risk and low risk patients.
The invention provides a method for making a prognosis for a patient afflicted with a type of cancer which comprises: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
The levels of expression of all four biomarkers, thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl , may be determined .
The cancer may be a lung cancer. The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer.
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
Numerous quantitative image analysis procedures are known in the art. An example of a quantitative image analysis procedure that may be used to determine the levels of expression include AQUA® technology procedures, as described in issued U.S. Patent No. 7,219,016, U.S. Patent No. 8,036,833 and U.S. Patent No. 8,121,794, which are incorporated by reference in to this application in its entirety . Other quantitative image analysis procedures may include the Bliss system, the ACIS system, the IVision and GenoMx system, the ScanScope Systems, the Ariol SL-50 System, the Vectra and Nuance systems, Leica microscope systems, and the LSC system which are available from the following respective manufacturers: Bacus Laboratories, Inc., Clarient, Inc., BioGenex, DakoCytomation, Applied Imaging Corporation, Perkin Elmer (Caliper) , Leica and CompuCyte Corporation (for more information, please see Immunohistochemistry and Quantitative Analysis of Protein Expression , by Melissa Cregger, Aaron J. Berger, and David L. Rimm, published July 2006 in Archives of Pathology and Laboratory Medicine) ; the procedure described in The Relative Distribution of Membranous and Cytoplasmic Met is a Prognostic Indicator in Stage I and II Colon Cancer, by Fiora Ginty, Sudeshna Adak, Ali Can, Michael Gerdes, Melinda Larsen, h arvey Cline, Robert Filkins, Zhengyu Pang, Qing Li, and Michael C. Montalto, published June 15, 2008 in Clinical Cancer Research; and the procedure described in Quantitative Fluorescence Imaging Analysis for Cancer Biomarker Discovery: Applications to β-Catenin in Archives Prostate Specimens, by Dali Huang, George P. Casale, Jun Tian, Nizar K. Wehbi, Neil A. Abrahams, Zahid Kaleem, Lynette M. Smith, Sonny L. Johansson, Johny E. Elkahwaji, and George P. Hemstreet III published July 2007 in Cancer Epidemiology Biomarkers) . The disclosures of these publications is hereby incorporated by reference into this application .
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen . The tissue sample may be a fixed tissue section.
The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered relatively high risk if the patient has a 40% or less chance of survival at five years. Alternatively a patient may be considered at relatively high risk if the patient has a survival profile such as those shown in Figure 5, with a high score (lower curve) .
A patient may be considered relatively low risk if the patient has a 95%or more chance of survival at five years. Alternatively a patient may be considered at relatively low risk if the patient has a survival profile such as those shown in Figure 5, with a low score (upper curve)
The invention provides a method for classifying a patient diagnosed with cancer as being at a low risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a low risk of developing a
recurrence of cancer if the score obtained in step (b) is less than the predetermined reference score cutpoint.
The levels of expression of all four biomarkers, thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl , may be determined .
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer. The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system . The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure. Numerous quantitative image analysis procedures are known in the art as described above.
Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen . The tissue sample may be a fixed tissue section.
The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types. The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40% chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years.
The levels of expression of all four biomarkers, thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl , may be determined .
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer. The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system . The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure. Numerous quantitative image analysis procedures are known in the art as described above.
Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
The tissue sample may be a fixed tissue section. The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40% chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years.
The invention provides a method for classifying a patient diagnosed with cancer as being at a high risk for a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients; wherein the patient is at a high risk of developing a recurrence of cancer if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
The levels of expression of all four biomarkers , thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl , may be determined .
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma. The adenocarcinoma of the lung may be a stage I cancer.
The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system.
The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
Numerous quantitative image analysis procedures are known in the art as described above. Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen.
The tissue sample may be a fixed tissue section.
The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40£ chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years.
A method for determining the likelihood that a patient diagnosed with cancer will develop a recurrence of cancer comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with high risk and low risk patients; so as to thereby determine the likelihood that the patient will develop a recurrence of cancer.
The series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
The levels of expression of all four biomarkers, thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl , may be determined .
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer.
The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system .
The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
Numerous quantitative image analysis procedures are known in the art as described above.
Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
The tissue sample may be a fixed tissue section. The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40% chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years.
A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
The series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
The levels of expression of all four biomarkers, thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl , may be determined .
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer.
The adjuvant therapy may be chemotherapy.
The therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
Numerous quantitative image analysis procedures are known in the art as described above.
Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
The tissue sample may be a fixed tissue section.
The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types .
The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40% chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years.
A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
The series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer.
The adjuvant therapy may be chemotherapy.
The therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-
catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
Numerous quantitative image analysis procedures are known in the art as described above.
Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
The tissue sample may be a fixed tissue section.
The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40£ chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years.
A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non- nuclear compartments combined in cells of interest in the sample
from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
The series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer.
The adjuvant therapy may be chemotherapy.
The therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may determined using an automated pathology system .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-
catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
Numerous quantitative image analysis procedures are known in the art as described above.
Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
The tissue sample may be a fixed tissue section.
The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types.
The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40£ chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years.
A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) determining a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in
the tumor tissue sample from the patient; c) determining a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) determining a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score based on the levels of expression determined in steps (a), (b) and (c) by: (i) adding the level of expression in step (a) with the level of expression obtained in step (b) ; (ii) subtracting the level of expression obtained in step (c) from the sum obtained in step (i) ; (iii) subtracting the level of expression obtained in step (d) from the difference obtained in step (ii) ; and f) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
The series of predetermined reference scores may be used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
The cancer may be a lung cancer.
The lung cancer may be adenocarcinoma.
The adenocarcinoma of the lung may be a stage I cancer. The adjuvant therapy may be chemotherapy.
The therapeutic treatments may invlude erlotinib, gefitinib, bevacizumab, sorafenib, docetaxel, gemcitabine, pemetrexed, and cisplatin .
The levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-
catenin and cyclin Dl may determined using an automated pathology system .
The levels of expression of thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl may be determined using a quantitative image analysis procedure.
Numerous quantitative image analysis procedures are known in the art as described above.
Other quantitative image analysis procedures can be used such as those described above.
As used in this application, the term sample can refer to various kinds of sample, for example, a tissue sample and a cytology specimen .
The tissue sample may be a fixed tissue section.
The method of this invention may be used in formalin-fixed paraffin- embedded sections, fine needle aspirate and other histological sample types. The method of this invention may be applied to tumor material obtained by surgical biopsy, bronchoscopic biopsies and fine-needle aspirations .
A patient may be considered high risk if the patient has a 40% chance of survival at five years.
A patient may be considered low risk if the patient has a 95% chance of survival at five years. The invention provides for a kit comprising at least three of the following: a first stain specific for thyroid transcription factor- 1 (TTF1) ; a second stain specific for signal transducer and
activator of transcription-3 (STAT-3) ; a third stain specific for beta-catenin; a fourth stain specific for cyclin Dl ; and instructions for using the kit. The kit may further comprise predetermined reference score cutpoints associated with high risk patients and with low risk patients.
The invention provides for a non-transitory computer readable medium having program code recorded thereon that, when executed on a computing system, automatically processes data, the program code comprising: code for processing a digital microscopy image of a stained tumor specimen taken from a cancer patient to extract data related to intensity values associated with one or more stains; code for processing the extracted data to arrive at a value for intensity per pixel for each of the one or more stains; code for processing pixel intensity of at least one stain for determining pixels associated with a preselected subcompartment and determining the area of the subcompartment for use as a denominator; code for processing pixel intensity of a second stain for determining an expression level of a biomarker and a value for total biomarker intensity in the same preselected subcompartment for use as a numerator; code for calculating from the numerator and denominator ascore of the biomarker expression per area; code for collecting thescore of each of at least three of the following four biomarkers, including thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl ; and code for incorporating the scores of the at least three biomarkers into a score model for arriving at a prognostic score. A method for making a prognosis for a patient having a tumor associated with adenocarcimona of the lung which comprises: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1) , signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the level of expression measured in step (a) for each of the biomarkers; and c) correlating the score
obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses; so as to thereby make a prognosis for the patient.
A method for identifying a patient having a tumor associated with adenocarcimona of the lung as having a 40% or less chance of survival after five years if treated only by surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with probability of survival after five years if treated only by surgery; wherein if the score obtained in step (b) is greater than the predetermined reference score the patient has a 40% or less chance of survival after five years if treated only by surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will not survive after five years if treated only by surgery: a) measuring in a sample of the patient's tumor a level of expression for at each of least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression measured in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with surival; so as to thereby determine the likelihood that the patient will not survive after five years if treated only by surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring in a sample of the patient's tumor a level of expression for each of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the
nuclear compartment and the non-nuclear compartments combined in cells of interest in the sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient; e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and f ) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient; c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient; d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient; e) calculating a score based on the levels of expression measured in steps (a) , (b) and (c) by: (i) adding the level of expression in step (a) with the level of expression obtained in step (b) ; (ii) subtracting the level of expression obtained in step (c) from the sum obtained in step (i); (iii) subtracting the level of expression obtained in step (d) from the difference obtained in step (ii); and f) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood
that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
The series of predetermined reference scores may be used to generate a predetermined reference score associated with survival wherein there is a likelihood that the patient will not survive after five years if treated only by surgery if the score obtained in step (b) is greater than the predetermined reference score.
A method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
A method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score
associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjucunt therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl; b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone; so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjunct therapy in addition to the surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3), beta-catenin and cyclin Dl ; b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival of reference patients having tumors associated with adenocarcinomas of the lung; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjunct therapy in addition to surgery.
The present invention provides, among other things, methods for determining the prognosis for a patient diagnosed with cancer and the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy. While specific embodiments of the subject invention have been discussed, the specification is illustrative and not restrictive. Many variations of the invention will become apparent to those skilled in the art upon review of this specification. The appended claims are not intended to claim all such embodiments and variations, and the full scope of the invention should be determined by reference to the claims, along with their full scope of equivalents, and the specification, along with such variations .
The following Experimental Details are set forth to aid in an understanding of the subject matter of this disclosure, but are not intended to, and should not be construed to, limit in any way the claims which follow thereafter.
Experimental Details
Synopsis
A critical clinical problem in management of adenocarcinoma of the lung is to determine which patients are cured by surgery alone, versus which will benefit from adjuvant therapy such as chemotherapy. In particular it is critically important to determine which low stage patients are cured by surgery alone, vs. those which will benefit from adjuvant therapy such as chemotherapy. While there are only 20% of all lung cancer patients diagnosed at low stage, that still represents over 30,000 patients in the United States .
This invention is a protein-based test that can stratify lung adenocarcinoma patients, including specifically low stage lung adenocarcinoma patients, into groups are likely to, or not liely to benefit from additional therapeutic treatment such as chemotherapy.
The new process assesses the level of four (a) key proteins using, for example, AQUA technology method of standardized quantitative immunofluorescence as previously described (Camp et al 2002 Nature Medicine 8(11)1323-1327, US Patent 7,219,016; Gustavson et al AQUA@ Technology and Molecular Pathology in Pathology in Drug Discovery and Development, Platero ed. John Wiley & Sons, lnc, Hoboken, NJ 2009) . The method may be used on formalin-fixed, paraffin-embedded tumor specimens, fine-needle aspirates, or other histological samples .
The four proteins that are measured are:
Thyroid Transcription Factor-1 (TTF1) , Signal transducer and activator of transcription-3 (STAT3) , Beta-Catenin, and Cyclin Dl .
Patients can then be divided into either high risk or low risk groups based on cut-points determined from previous studies . Stage 1 lung cancer patients with adenocarcinoma in the low risk group have a 95% chance of survival at 5 years, compared to a 40% chance
in the high risk group. Although stage I patients are not usually given chemotherapy or other therapeutic treatment, this study would select a subset (as many as 66% of patients) that fall into the high risk group that would then benefit from additional therapeutic treatment such as chemotherapy.
In a particular embodiment, the protein biomarkers are measured in a quantitative manner using standard curves to assure accuracy and precision in measurement. From these data the risk score is then calculated using the following equation:
1.322*CyclinDl (tm) + 1.0126*Stat3 (tm) - 1.2131*TTF1 (n) 0.7748*beta-Catenin (c) .
Where (tm) (n) and (c) indicate the subcellular compartment used for measuring each variable using the AQUA technology (tm = total under the tumor mask, n = nuclear, c = cytoplasmic) .
It would be understood by one of skill in the art that equation may be adjusted or optimized as additional cohorts of patients are analyzed. For example, the coefficients for each marker may be optimized relative to broader patient populations.
Purpose: The importance of definitive histologic prognosticator has significantly increased as improved cancer screening methods are identifying more lung cancer patients, and at an earlier stage of disease. Here we describe the development and validation of a 4- protein classifier that is prognostic for risk of disease recurrence in lung adenocarcinomas (AC) .
Introduction
Lung cancer, predominantly non-small cell lung cancer (NSCLC) , is the most common cause of death from cancer worldwide. An estimated 226,160 new cases were diagnosed in the United States in 2012. NSCLC diagnosis and histologic leads to several subclassification of disease with adenocarcinoma being the most frequent type of NSCLC. Low stage adenocarcinoma is generally treated with surgery without adjuvant therapy. However 35-50% of patients who first present with
low stage disease and are treated surgically without adjuvant therapy will suffer recurrence and death due to their disease (Jenal A, et al Cancer Statistics 2010. CA Cancer J Clin 2010; 60:277- 300) . Therefore a prognostic test that could identify patients at risk for recurrence of disease is needed and would provide the opportunity to treat such patients more aggressively to improve outcome .
Ideally the diagnostic test should be simple to perform, avoiding methodologies that are technically challenging requiring that they be conducted in a central laboratory. The assay methodology should be standardized and have high reproducibility so that the assay can be provided in a decentralized fashion by multiple laboratories and each can expect to get concordant results. See, for example, the standardization described in Gustavson et al . , Standardization of HER2 Immunohistochemistry in Breast Cancer by Automated Quantitative Analysis, published September 2009 in Arch. Pathol. Lab. Med., the disclosure of which is hereby incorporated by reference into this application .
Materials and Methods
Cohorts
Two cohorts of formalin-fixed paraffin-embedded primary NSCLC tumors were used for this study. A cohort of 117 adenocarcinoma patients was used as the training set and a second independent cohort of 137 adenocarcinoma patients was used as the validation set.
Both cohorts were retrospectively collected from surgical patients from Yale-New Haven Hospital (New Haven, CT) . Demographics and details of these cohorts are shown in Table 1. The study was approved by the institutional review boards of all centers; written informed consent was obtained for each case prior to inclusion in the study.
Table 1 Tumor and clinical characteristics of the training and validation adenocarcinoma cohorts
Training AC Cohi qrt (n=117l Va IJdatioriAC Ci
r
nge
Median (range) 64 (33-90) 62 (34-84)
i iedi ii at ou.y ±u. / y
Male 45 38.5 1 15 84.1 stage
1 61 52.1 38 27.7
I irU . Qy
III 28 23.9 41 29.9
IV 14 12 28 20.5
Abbreviations: N; number, AC; adenocarcinoma, SE; standard error
Tissue Microarrays
Tissue specimens were prepared in a tissue microarray (TMA) format: representative tumor areas were obtained from formalin fixed paraffin embedded (FFPE) specimens of the primary tumor and two 0.6mm cores from each tumor block were arrayed in a recipient block.
Western Blotting
Equivalent amounts of protein (15 g) were resolved by SDS-PAGE in 4- 12% bis-tris gels (150V for lhr) and transferred at 45V for 2 hrs to a nitrocellulose membrane. Immunoblots were probed with primary antibodies, followed by anti-rabbit or anti-mouse HRP conjugated secondary antibodies (Santa Cruz Biotechnology, Santa Cruz, CA) diluted 1/4000 and detected using enhanced chemiluminescence (GH Healthcare) . β-tubulin (rabbit polyclonal, Cell Signaling Technology, Danvers, MA) immunoblotting was used to visualize the total protein loading.
Quantitative Immunofluorescence
The arrays were deparaffinized with xylene, rehydrated and antigen- retrieved by pressure cooking for 15 minutes in lOmM citrate (pH=6) or lOmM Tris/lmM EDTA buffer (pH=9) for all primary antibodies.
Slides were pre-incubated with 0.3% bovine serum albumin (BSA) in 0.1M tris-buffered saline (TBS, pH=8) for 30 minutes at room temperature. Slides were then incubated with a cocktail of the primary antibody (Table 2) and a mouse monoclonal anti-human cytokeratin antibody (clone AE1/AE3, M3515, Dako, Carpinteria, CA) or a wide-spectrum rabbit anti-cow cytokeratin antibody (Z0622, Dako, Carpinteria, CA) diluted 1:100 in BSA/ TBS overnight at 4°C. This was followed by an 1-hour incubation with Alexa 546-conjugated goat anti-mouse secondary antibody (A11003, Molecular Probes, Eugene, OR) diluted 1:100 in rabbit Envision reagent (K4003, Dako, Carpinteria, CA) or Alexa 546-conjugated goat anti-rabbit secondary antibody (A11010, Molecular Probes, Eugene, OR) diluted 1:100 in mouse Envision reagent (K4001, Dako, Carpinteria, CA) . Cyanine 5 (Cy5) directly conjugated to tyramide (FP1117, Perkin-Elmer , Boston, MA) at a 1:50 dilution was used as the fluorescent chromagen for target detection. Prolong mounting medium (ProLong Gold, P36931, Molecular Probes, Eugene, OR) containing 4 ' , 6-Diamidino-2- phenylindole (DAPI) was used to identify tissue nuclei. Positive controls used are described in detail in Supplementary Table 2. Negative control sections, in which the primary antibody was omitted, were used for each immunostaining run.
Image Collection and Analysis
Automated Quantitative Analysis (AQUA®technology) allows exact measurement of protein concentration within subcellular compartments, as described in detail elsewhere ( Camp RL, Chung GG, Rimm DL : Automated subcellular localization and quantification of protein expression in tissue microarrays . Nat Med 8:1323-7, 2002) .
In brief, a series of high resolution monochromatic images were captured by the PM-2000™ digital imaging microscopy instrument (HistoRx, Branford, CT) . For each histospot, images were obtained using the signal from the DAPI, cytokeratin-Alexa 546 and target-Cy5 channel. Target proteins were measured using a channel with emission maxima above 620nm, in order to minimize tissue autofluorescence . Tumor was distinguished from stromal and non-stromal elements by
creating an epithelial tumor "mask" from the cytokeratin signal. This created a binary mask (each pixel being either "on" or "off") on the basis of an intensity threshold set by visual inspection of histospots. AQUA score of target proteins in the tumor mask and subcellular compartment were calculated by dividing the target compartment pixel intensities by the area of the compartment within they were measured. AQUA scores were normalized to the exposure time and bit depth at which the images were captured, allowing scores collected at different exposure times to be directly comparable. Specimens with less that 5% tumor area per spot were not included in automated quantitative analysis for not being representative of the corresponding tumor specimen.
The image collection and analysis can also be accomplished using clustering AQUA® software, as described in U.S. Patent Application Publication No. 20090034823, entitled Compartment Segregation by Pixel Characterization Using Image Data Clustering, the contents of which is hereby incorporated by reference into this application, and as described in Gustavson et al., Development of an unsupervised pixel-based clustering algorithm for compartmentalization of immunohistochemical expression using Automated Quantitative Analysis, Appl . Immunohistochemical Mol. Morphol . 2009 Jul; 1794) : 329-37, the contents of which is hereby incorporated by reference into this application. This method and system uses autoexposure and is done automatically instead of by visual inspection of histospots.
Statistical analysis
AQUA scores were Log2 normalized and scores of the validation sets were further normalized for run to run variability. Missing values were tested by Little's test for missing complete at random; cases with missing values were excluded from analysis. Pearson's correlation coefficient (R) was used to assess the correlation between AQUA scores from redundant tumor cores. An R2 greater than 0.4 was indicative of good inter- and intra-array reproducibility and thus the average values for all target proteins AQUA scores from
duplicate samples were calculated and treated as independent continuous variables .
A flowchart of the statistical analysis used to develop the prognostic indicator is shown in Figure 1. The expression of an initial set of 42 biomarkers was assessed in 117 primary lung adenocarcinoma cases in cohort 1. Biomarkers with expression in non-epithelial tissue (markers exclusively expressed on lymphocytes "contaminating" the tumor e.g. MUM1 , LCK were excluded) , and those for whom assay results were not reproducible (e.g. VEGF, MET, EGFR) were excluded from further analysis. There were 16 markers chosen for further analysis based on Cox Univariate analysis showing P<0.5. (Table 3) .
Cox multivariate analysis of the 16 chosen markers was performed incorporating the selected biomarkers in a stepwise selection /backward elimination process. To address the issue of model over fitting, 1000 bootstrap samples were generated and a backward elimination logistic regression model was developed for each bootstrap sample; the final multivariable model included those variables that were significant at the 0.05 level (Table 3) .
A risk score was generated as a linear combination of weig hted expression of biomarkers in the reduced (final model) based on coefficients of the multivariate model:
Risk equation: 1.322 *CyclinDl+ l .0126*STAT3-1.2131*TTFl-0.7748*Bcate nin
The final classifier was applied to the testing and validation cohorts. All p values were based on two-sided testing and differences were considered significant at p<0.05. All statistical analyses were done using the SPSS software program (version 13.0 for Windows, SPSS Inc., Chicago, IL) and the R-statistics software (version 2.9.0) .
Specimen score
Average Cyclin Dl , STAT3, TTF1, and beta catenin AQUA scores from redundant cores were normalized for run-to-run variability, log2 transformed and a score was calculated only for tumors with all 4 measurements available using the formula Risk equation: 1.322*CyclinDl+l .0126*STAT3-1.2131*TTFl-0.7748*Bcatenin .
Results
Identification of predictors
We used automated quantitative analysis to identify biomarkers that identify patients at risk for recurrence of disease. Among 42 biomarkers initially assessed, 29 were chosen for further analysis (Table 2) .
Table 2: Eligible biomarkers used for the prognostic model development
Biomarker Clone/lsotype Antigen Retrieval Concentration Incubation Positive Control Source
Cytokeratin 5 Nr.L-L-CKJVm ΗΙΛΚ-ρΗ-f» I 5min 5.2|jg- ml I hr NT Λ 13 I nfills Novocain. Newcastle. UK
Cytokeratin 13 DE-K13/m lgG2a, kappa HIAR-pH=9 15min 57 g/ml ON 4°C A431 cells Dako, Carpinteria, CA
Cytokoratin 14 LL002-m IgG , HIAR-pH-5 15min 0.2pg/ml ON 4°C A431 cells Thermo Fisher. Fremont. CA
Cytokeratin 17 2D10/m lgG1 HIAR-pH=6 15min O. l Mg/ml ON 4°C A431 cells Abnova, Walnut, CA
HFR? r polyclonal HIAR- H=! I Smin ? \ \Q.:m ON 4°C HFR? transferred Γ.ΗΟ cells Dako "arpinteria Γ.Α
HER3 D1 1 E5/r IgG ΗΙΛΚ-ρΗ-'J 15min U.2»opg ml ON 4°C HER3 transfected BaF3 cells Cell Signaling, Danvers, MA
HER4 SPM338 IH IgG HIAR-pH 5 15miii 0.4|jy iril ON 4^C HER4 Imi lauded CHO culL Suiilu Cruz. Santa Cru . CA
ΛΚΤ1 2H10/m HIAR-pH=6 15min 1/200- ON 4°C A431 cells Cell Signaling, Danvers, MA
ERK m pnlyr.lnnal HIAR-pH=-j I Smin I M OO' ON 4°C A431 cells Cell Signaling. Danvers. MA
DUSP6 3G /m k;G1 , kappa HIAR-pH=6 15min U. Mg ml ON 4UC Pancreatic carcinoma Novus Biologicals, Littleton, CO
8TAT1 42I I3.'r lc,G I IIAR-pl l=G 15min 1 750- ON 4°C Colon carcinoma Cell Signaling. Danvers. MA
STAT2 Y 141. r kjG HIAR-pH=6 15min 1:200' ON 4CC Breast carcinoma Novus Biologicals, Littleton, CO
STAT3 124H6/m HIAR-pH=o 15min 1/500' ON 4CC H 1550. HCC2279 cells Cell Signaling. Danvers. MA mTOR 7C10/r HIAR-pH=6 15min 1/1000* ON 4°C A431 and H1299 cells Cell Signaling, Danvers, MA pS6K 1A5. ni HIAR-pH-o 15mii i 1/200' ON 4CC H 1299 cells Cell Signaling. Danvers. MA pS6 9 I B2.Y IgG
I Smin I/400- ON 4°C Colon carcinoma, HCC.193 cells Cell Signaling, Danvers, MA
TTF1 8G7G3/m lqG1 . kappa HIAR pH-3 l Omin 20Mg.'m ON 4CC H2126 cells Dako. Carpinteria. CA
E2F4 SPM 179/iri IgG 1 kappa HIAR-pH=6 15min 2pg/ml ON 4°C Tonsil Novus Biologicals, Littleton, CO
BCL2 I 24.'m IgG I . kappa HIAR-pH-0 I 5min 2.>i|jg/ml ON 4CC Lymphocytes Dako. Carpinteria. CA
CC3 5A1/r HIAR-pH=6 15min 1/500* ON 4°C Pancreatic carcinoma Cell Signaling, Danvers, MA
ΜΕΝΛ 21. m k;A HIAR-pH-3 15min 1 pg/ml ON 4CC Λ431 cells BD Biosciences. San Jose. CA
RRM2 1 E1/m IgG 1 . kappa HIAR-pH=6 15min 0.05pg/ml ON 4CC Pancreatic carcinoma Novus Biologicals, Littleton, CO
PTEN fiH2 I 'm IgG kappa HIAR-pH= 15min n.C)R|ifi- nl ON 4°C H I Sfi cells Dako. '"arpinteria. CA
p53 DO-7/rn lgG2b, kappa HIAR-pH=9 20min 1/5000 ON 4°C Tonsil Dako, Carpinteria, CA
KM Bbb.rn lgU1 . kappa -IAK-pH=b 1 bmin 1 g;ml 'JN 4 C A!> 4y cells BU Biosciences. San Jose, CA
Cyclin D1 SP4:r gG HIAR-pH=6 20min 1.25 1 hr RT Br< 3ast carcinoma LabVision, Frem ont, CA
Mucin 1 MaGSG'm IgGI -IAR-pH=G 20min 1 Ί00 ON 4 C Breast Carcinoma LabVision, Fremont, CA
Bag-1 2D3'm lgG2a, kappa HIAR-pH=6 20min 0.5pg/ml ON 4°C To nsil Novus Biological s, Littleton, CO
Eeta-catenin 1 -l m IgG I -IAR-pH-6 20min 0. 1 'ml ON; -I c A4 31 cells BD Biosciences.; San Jose, CA
*T he exact concentration was not provided by the manufacturer.
Of these 16 predictor biomarkers were selected as a result of Cox univariate analysis that showed P-values < 0.5 (Table 3) .
Table 3 Selected predictors in Cox univariate analysis
Biomarker Coefficient SE(Coef) HR 95 % CI (Lower/Upper) p value
"~CycNnD~ (frnj~ 0.99 0.453 2.69 1.107 6.539 iiiiiiiii
TTF1 (n) -0.832 0.415 0.435 0.193 0.982 0.045
pS6K(tm) -1.586 0.808 0.205 0.042 0.998
HER2(tm) 0.813 0.538 2.254 0.785 6.468 0.131
CK14(c) 1.301 0.947 3.672 0.574 23.503
RRM2(tm) 0.584 0.44 1.794 0.757 4.247 0.184
DUSP6itmi 1.122 0.849 3.072 0.581 16.237
STAT3(tm) 0.788 0.67 2.198 0.591 8.177 0.24
CC3(tm) 0.779 0.676 2.18 0.58 8.198
beta Catenin(c) -0.529 0.47 0.589 0.235 1.481 0.261
p53(n) 0.277 0.248 1.319 0.81 1 2.144
Mucinl (tm) 0.39 0.369 1.477 0.717 3.043 0.29
ERKi tmi 0.686 0.649 1.986 0.556 7.092
BCL2(tm) -0.46 0.451 0.631 0.261 1.529 0.308
CK5(tm) -0.604 0.696 0.547 0.14 2.14
PTEN(n) 0.424 0.514 1.527 0.558 4.181 0.41
Abbreviations: Coef; coefficient, HR; hazard ratio, CI; confidence interval, tm; tumor mask, n; nuclear, c; cytoplasmic, CC3; cleaved caspase 3
Subsequent to stepwise Cox multivariable analysis and backward elimination followed by 1000 bootstrap samples, 4 biomarkers were identified as significantly associated with risk of recurrence (Table 4) .
Table 4: Reduced Cox multivariable model (training
Biomarker Coefficient SE(Coef) HR 95% CI (Lower/Upper) p value
Cyclin DKtm) 1.322 0.460 3.751 1.496 9.407 0.004
STAT3(tm) 1.013 0.640 2.753 0.777 9.751 0.1 10
TTFKn) -1.213 0.440 0.297 0.125 0.706 0.005 beta Catenin(c) -0.775 0.520 0.461 0.165 1.285 0.130
Abbreviations: Coef; coefficient, HR; hazard ratio, CI; confidence interval, tm; tumor mask, n; nuclear, c; cytoplasmic
Development of the Molecular Classifier (training cohort)
Cyclin Dl, STAT3, TTF1 and beta catenin continuous AQUA scores were then incorporated in a multivariate nominal logistic regression model following a backward elimination stepwise selection process for each of the 1000 bootstrap samples; the probability of prediction of recurrence of disease was calculated as linear combination of Cyclin Dl , STAT3, TTF1 and beta catenin log2 normalized AQUA scores weighted as follows:
Risk equation: 1.322 *CyclinDl+l .0126*STAT3-1.2131*TTFl-0.7748*Bcate nin
Reproducibility of assessment of biomarker assessment is shown in Figure 2.
Representative staining patterns for adenocarcinoma tumors of the training cohort are shown in Figure 3.
The performance of the classifier, as determined using Cox univariate analysis for in all patients in the training cohort, as well as for selected subsets, those that were stage 1 and stage 1A adenocarcinoma is shown in Table 5 and demonstrates the continuous risk classifier significantly predicts survival in all subpopulations .
Table 5: Cox univariate analyses for the classifier in all, stage I and stage IA AC patients (training set).
Coefficient SE(Coef) HR 95.0% CI for HR p value
Lower Upper
AII ACs (n=117)
Risk Score(Cont.) 1 000 0 251 2.718 1 661 4.449 6.96E-05
Stage I ACs (n=61)
Risk Score(Cont.) 1.298 0.431 3.662 1.573 8.527 0.003
Stage IA ACs (n=46)
Risk Score(Cont.) 1 506 0 499 4.510 696 1 1 994 0 003
Abbreviations: Coef; coefficient, HR; hazard ratio, CI; confidence interval, AC; adenocarcinoma, Cont.; continuous
The performance of the continuous risk classifier as determined using Cox multivariate analysis, adjusting for clinical characteristics was assessed for all patients in the training cohort as shown in Table 6 demonstrating the continuous risk classifier significantly predicts outcome even when adjusted for stage and/or age and gender.
Table 6: Cox multivariate analysis for the classifier adjusting for clinical characteristics (training
Variable Coefficient SE(Coef) HR 95.0% CI for HR p value
Lower Upper
1st Step Risk Score (Cont.) 0.821 0.278 2.273 1.319 3.919 0.003
Gender (M vs. F) 0.456 0.284 1.577 0.903 2.754 0.109
Age 0.008 0.014 1.008 0.981 1.035 0.576
Stage I 1.000
Stage II 0.831 0.425 2.295 0.998 5.276 0.051
Stage III 1.104 0.348 3.017 1.524 5.973 0.002
Stage IV 0.982 0.435 2.670 1.138 6.266 0.024
Last Step Risk Score (Cont.) 0.751 0.269 2.120 1.250 3.593 0.005
Stage I 1.000
Stage II 0.885 0.406 2.424 1.094 5.373 0.029
Stage III 1.053 0.326 2.867 1.512 5.435 0.001
Stage IV 1.203 0.412 3.330 1.486 7.463 0.003
Abbreviations: Coef; coefficient, HR; hazard ratio, CI; confidence interval, Cont.; continuous, M; male, F; female
Classifier Validation (validation cohorts)
The power of the molecular classifier was tested in a validation cohort of retrospectively collected cohort of 137 NSCLC patients (Yale University Lung Cancer Cohort) (Table 1) . Results are shown in Table 7 indicating the continuous risk classifier developed in the training set significantly predicts survival in the validation set even when adjusted for stage and/or age and gender.
Table 7: Cox multivariate analysis for the classifier adjusting for clinical characteristics (validation set).
Variable Coefficient SE(Coef) HR 95.0% CI for HR p value
1st Step Gender (M vs. F) -0.472 0.440 0.623 0.263 1.478 0.283
Age 0.008 0.016 1.008 0.976 1.041 0.625
Stage 1 1.000
St 1 083 0 4^8 2 QS4 1 113 7.834 0.030
Stage III 1.476 0.473 4.375 1.730 11.067 0.002 Stage IV 1.933 0.506 6.908 2.560 18.640 <0.001
Risk Score (Cont.) 0.555 0.235 1.742 1.098 2.763 0.018
Last Step Stage 1 1.000
Stage II 1.077 0.496 2.934 1.111 7.754 0.030
Stage III 1.430 0.470 4.180 1.663 10.504 0.002 Staeo IV 1 0 506 6 816 ? 529 IS 367 <0 001
Risk Score (Cont.) 0.552 0.245 1.737 1.074 2.807 0.024
Abbreviations: Coef; coefficient, HR; hazard ratio, CI; confidence interval, Cont.; continuous, M; male, F; female
The Kaplan-Meier analysis of the prognostic algorithm in the training set is shown in Figure 4. All adenocarcinoma patients in the training cohort could be placed into one of three prognostic groups with relatively good, moderate or poor outcome (Figure 4A)with a statistical significance of log rank p=0.002. A subset analysis using the prognostic algorithm for adenocarcinoma patients that were stage 1 at diagnosis was also significant (Figure 4C) log rank p=0.017. Similar results were obtained in the analysis of the validation cohort (Figure 4 B and D) with a log rank p=0.037 for all adenocarcinomas ( Figure 4B) and log rank p=0.006 for stage 1 patients
only (Figure 4D) . Of the three prognostic groups with relatively good, moderate or poor outcome, the moderate and poor prognostic groups were combined for the results shown in Figure 5B (log rank p=0.028) . Subset analysis for Stage 1 patients is shown in Figure 5C, and for Stage la patients is shown in Figure 5D.
As would be expected the prognostic model is not prognostic in squamous cell lung carcinoma (Figure 6) .
Figure 7 represents a Forest plot summary of hazard ratio and 95% confidence interval data from Tables 5-7. All hazard ratios and 95% CIs are above one indicating that the continuous risk classifier is a significant predictor of decreased overall survival.
Discussion
In conclusion, we have developed a highly reproducible, objective, easily applicable quantitative immuno-assay based test for prognosis of lung adenocarcinoma. This test could easily be translated into a robust diagnostic platform for broad clinical application. Moreover, we believe that identifying those patients, especially stage 1 and 1A patients at risk for disease recurrence provides the opportunity to consider adjuvant treatment and will result in the fine tuning of personalized therapy towards the goal of maximizing survival outcomes for lung cancer patients.
PART II
THERAPEUTIC TREATMENTS FOR NSCLC
Adjuvant platinum based chemotherapy with or without gemcitabine is a common therapy for the treatment of NSCLC, which may be guided by the use of additional assessment of biomarker expression (Reynolds J Clinical Oncology 2009, 27:5808-5815) .
Pemetrexed (Alimta, Lilly)
Mechanism of Action: Pemetrexed is chemically similar to folic acid and is in the class of chemotherapy drugs called folate antimetabolites. It works by inhibiting three enzymes used in purine and pyrimidine synthesis—thymidylate synthase (TS), dihydrofolate reductase (DHFR) , and glycinamide ribonucleotide formyltransferase J_McLeod, Howard L.; James Cassidy, Robert H. Powrie, David G. Priest, Mark A. Zorbas, Timothy W. Synold, Stephen Shibata, Darcy Spicer, Donald Bissett, Yazdi K. Pithavala, Mary A. Collier, Linda J. Paradiso, John D. Roberts (Jul-2000) . "Pharmacokinetic and Pharmacodynamic Evaluation of the Glycinamide Ribonucleotide Formyltransferase Inhibitor AG2034" . Clinical Cancer Research (American Association for Cancer Research) 6 (7) : 2677-2684. PMID 10914709.
http : //clincaricerres . aacrj ournals . org/ cgi/ content /abstract / 6/7 /2677. Retrieved 2-Dec-2008. Avendano, Carmen; Menendez, J. Carlos (16-Apr- 2008) . Medicinal Chemistry of Anticancer Drugs (GARFT) . By inhibiting the formation of precursor purine and pyrimidine nucleotides, pemetrexed prevents the formation of DNA and RNA, which are required for the growth and survival of both normal cells and cancer cells . Adenocarcinoma has a better response than squamous (but squamous can respond) .
Erlotinib (OSI-774, Tarceva, Genenetech & OSI in U.S.; Roche in ROW)
Mechanism of Action: erlotinib specifically targets the epidermal growth factor receptor (EGFR) tyrosine kinase, which is highly expressed and occasionally mutated in various forms of cancer. It binds in a reversible fashion to the adenosine triphosphate (ATP) binding site of the receptor (Raymond E, Faivre S, Armand J (2000) .
"Epidermal growth factor receptor tyrosine kinase as a target for anticancer therapy". Drugs 60 Suppl 1: 15-23; discussion 41-2. PMID 11129168) . For the signal to be transmitted, two members of the EGFR family need to come together to form a homodimer. These then use the molecule of ATP to autophosphorylate each other, which causes a conformational change in their intracellular structure, exposing a further binding site for binding proteins that cause a signal cascade to the nucleus. By inhibiting the ATP, autophosphorylation is not possible and the signal is stopped.
Response: It is reported that responses among patients with lung cancer are seen most often in females who were never smokers, particularly Asian women and those with adenocarcinoma cell type. Bevacuzimab (Avastin, Genentech/Roche)
Bevacizumab (trade name Avastin, Genentech/Roche ) is a monoclonal antibody against vascular endothelial growth factor-A (VEGF-A) (Los M, Roodhart JM, Voest EE (April 2007) . "Target practice: lessons from phase III trials with bevacizumab and vatalanib in the treatment of advanced colorectal cancer". The Oncologist 12 (4) : 443-50. doi : 10.1634 /theoncologist .12-4-443. PMID 17470687) . It is used in the treatment of cancer, where it inhibits tumor growth by blocking the formation of new blood vessels (angiogenesis ) . Bevacizumab was the first clinically available angiogenesis inhibitor in the United States .
In 2006, the FDA approved bevacizumab for use in lung cancer in combination with standard first-line chemotherapy. A study conducted by the Eastern Cooperative Oncology Group (ECOG) demonstrated a 2- month improvement in overall survival in patients with Stage Illb/IV non-small cell lung cancer (NSCLC) . Due to the observance of severe pulmonary hemorrhage in patients with NSCLC with squamous histology in an earlier study, patients with such histology were excluded from the pivotal ECOG trial.
Gemcitabine
Gemcitabine is a nucleoside analog used as chemotherapy. It is marketed as Gemzar by Eli Lilly and Company. Chemically gemcitabine is a nucleoside analog in which the hydrogen atoms on the 2 ' carbons of deoxycytidine are replaced by fluorine atoms.
As with fluorouracil and other analogues of pyrimidines, the drug replaces one of the building blocks of nucleic acids, in this case cytidine, during DNA replication. The process arrests tumor growth, as new nucleosides cannot be attached to the "faulty" nucleoside, resulting in apoptosis.
Claims
1. A method for making a prognosis for a patient having a tumor associated with adenocarcimona of the lung which comprises:
a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl;
b) calculating a score based on the level of expression measured in step (a) for each of the biomarkers; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses ;
so as to thereby make a prognosis for the patient.
2. The method of claim 1, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined.
3. The method of claim 1, wherein the adenocarcinoma of the lung is a stage I cancer.
4. The method of claim 1, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using an automated pathology system.
5. The method of claim 1, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using a quantitative image analysis procedure.
6. The method of claim 1, wherein the sample is a tissue sample.
7. The method of claim 1, wherein the sample is a cytology specimen .
8. A method for identifying a patient having a tumor associated with adenocarcimona of the lung as having a 40% or less chance of survival after five years if treated only by surgery comprising: a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression measured in step (a) ; and
c) comparing the score obtained in step (b) with a predetermined reference score associated with probability of survival after five years if treated only by surgery;
wherein if the score obtained in step (b) is greater than the predetermined reference score the patient has a 40% or less chance of survival after five years if treated only by surgery.
9. The method of claim 8, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined.
10. The method of claim 8, wherein the adenocarcinoma of the lung is a stage I cancer.
11. The method of claim 8, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using an automated pathology system.
12. The method of claim 8, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using a quantitative image analysis procedure.
13. The method of claim 8, wherein the sample is a tissue sample.
14. The method of claim 8, wherein the sample is a cytology specimen .
15. A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will not survive after five years if treated only by surgery:
a) measuring in a sample of the patient' s tumor a level of expression for at each of least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl;
b) calculating a score based on the levels of expression measured in step (a) ; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with surival;
so as to thereby determine the likelihood that the patient will not survive after five years if treated only by surgery.
16. The method of claim 15, wherein the series of predetermined reference scores are used to generate a predetermined reference score associated with survival wherein there is a likelihood that the patient will not survive after five years if treated only by surgery if the score obtained in step (b) is greater than the predetermined reference score.
17. The method of claim 15, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined.
18. The method of claim 15, wherein the adenocarcinoma of the lung is a stage I cancer.
19. The method of claim 15, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using an automated pathology system.
20. The method of claim 15, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using a quantitative image analysis procedure.
21. The method of claim 15, wherein the sample is a tissue sample.
22. The method of claim 15, wherein the sample is a cytology specimen .
23. A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising:
a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival;
so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
24. The method of claim 23, wherein the series of predetermined reference scores are used to generate a predetermined reference score associated with chance of survival wherein there is a likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery if the score obtained in step (b) is greater than the predetermined reference score.
25. The method of claim 23, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined.
26. The method of claim 23, wherein the adenocarcinoma of the lung is a stage I cancer.
27. The method of claim 23, wherein the adjuvant therapy comprises chemotherapy .
28. The method of claim 23, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using an automated pathology system.
29. The method of claim 23, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using a quantitative image analysis procedure.
30. The method of claim 23, wherein the sample is a tissue sample.
31. The method of claim 23, wherein the sample is a cytology specimen .
32. A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising:
a) measuring in a sample of the patient' s tumor a level of expression for each of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival;
so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
33. The method of claim 32, wherein the series of predetermined reference scores are used to generate a predetermined reference score associated with chance of survival wherein there is a likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery if the score obtained in step (b) is greater than the predetermined reference score.
34. The method of claim 32, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined.
35. The method of claim 32, wherein the cancer is a lung cancer.
36. The method of claim 33, wherein the lung cancer is
adenocarcinoma .
37. The method of claim 36, wherein the adenocarcinoma of the lung is a stage I cancer.
38. The method of claim 32, wherein the adjuvant therapy comprises chemotherapy .
39. The method of claim 32, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using an automated pathology system.
40. The method of claim 32, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using a quantitative image analysis procedure.
41. The method of claim 32, wherein the sample is a tissue sample.
42. The method of claim 32, wherein the sample is a cytology specimen .
43. A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor sample from the patient;
b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the sample from the patient;
c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the sample from the patient;
d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the sample from the patient;
e) calculating a score based on the levels of expression determined in steps (a) through (d) ; and
f) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
44. The method of claim 43, wherein the series of predetermined reference scores are used to generate a predetermined reference score associated with chance of survival wherein there is a likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery if the score obtained in step (b) is greater than the predetermined reference score.
45. The method of claim 43, wherein the adenocarcinoma of the lung is a stage I cancer.
46. The method of claim 43, wherein the adjuvant therapy comprises chemotherapy .
47. The method of claim 43, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using an automated pathology system.
48. The method of claim 43, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using a quantitative image analysis procedure.
49. The method of claim 43, wherein the sample is a tissue sample.
50. The method of claim 43, wherein the sample is a cytology specimen .
51. A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have a higher chance of survival after surgery from adjuvant therapy in addition to the surgery comprising: a) measuring a total level of expression of cyclin Dl within a nuclear compartment and non-nuclear compartments combined in cells of interest in a tumor tissue sample from the patient; b) measuring a total level of expression of signal transducer and activator of transcription-3 (STAT-3) within the nuclear compartment and the non-nuclear compartments combined in cells of interest in the tumor tissue sample from the patient;
c) measuring a level of expression of thyroid transcription factor-1 (TTF1) in the nuclear compartment in cells of interest in the tumor tissue sample from the patient;
d) measuring a level of expression of beta-catenin in a cytoplasmic compartment in cells of interest in the tumor tissue sample from the patient;
e) calculating a score based on the levels of expression measured in steps (a), (b) and (c) by:
i. adding the level of expression in step (a) with the level of expression obtained in step (b) ;
ii . subtracting the level of expression obtained in step
(c) from the sum obtained in step (i);
iii. subtracting the level of expression obtained in step
(d) from the difference obtained in step (ii); and f) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival; so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery.
52. The method of claim 51, wherein the series of predetermined reference scores are used to generate a predetermined reference score associated with chance of survival wherein there is a likelihood that the patient will have a higher chance of survival after surgery from adjuvant therapy in addition to surgery if the score obtained in step (b) is greater than the predetermined reference score.
53. The method of claim 52, wherein the adenocarcinoma of the lung is a stage I cancer.
54. The method of claim 51, wherein the adjuvant therapy comprises chemotherapy .
55. The method of claim 51, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using an automated pathology system.
56. The method of claim 51, wherein the levels of expression of thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl are determined using a quantitative image analysis procedure.
57. The method of claim 51, wherein the sample is a tissue sample.
58. The method of claim 51, wherein the sample is a cytology specimen .
59. A kit comprising:
At least three of the following:
a) a first stain specific for thyroid transcription factor-1 (TTF1) ;
b) a second stain specific for signal transducer and activator of transcription-3 (STAT-3);
c) a third stain specific for beta-catenin;
d) a fourth stain specific for cyclin Dl ; and
e) instructions for using the kit.
60. The kit of claim 59, further comprising predetermined reference scores associated with high risk patients and with low risk patients.
61. The kit of claim 59, further comprising a fifth stain specific for a nuclear compartment and a sixth stain specific for a non- nuclear compartment in epithelial cells.
62. A non-transitory computer readable medium having program code recorded thereon that, when executed on a computing system,
automatically processes data, the program code comprising:
code for processing a digital microscopy image of a stained tumor specimen taken from a cancer patient to extract data related to intensity values associated with one or more stains;
code for processing the extracted data to arrive at a value for intensity per pixel for each of the one or more stains;
code for processing pixel intensity of at least one stain for determining pixels associated with a preselected subcompartment and determining the area of the subcompartment for use as a denominator; code for processing pixel intensity of a second stain for determining an expression level of a biomarker and a value for total biomarker intensity in the same preselected subcompartment for use as a numerator;
code for calculating from the numerator and denominator a score of the biomarker expression per area;
code for collecting the score of each of at least three of the following four biomarkers, including thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl; and
code for incorporating the scores of the at least three biomarkers into a score model for arriving at a prognostic score.
63. A method for making a prognosis for a patient afflicted with a type of cancer which comprises:
a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of prognoses ;
so as to thereby make a prognosis for the patient.
64. A method for classifying a patient diagnosed with cancer as being at a high risk for a recurrence of cancer comprising:
a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and
c) comparing the score obtained in step (b) with a predetermined reference score cutpoint separating high risk from low risk patients ;
wherein the patient is at a high risk of developing a recurrence of cancer if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
65. A method for determining the likelihood that a patient diagnosed with cancer will develop a recurrence of cancer comprising :
a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with high risk and low risk patients; so as to thereby determine the likelihood that the patient will develop a recurrence of cancer.
66. A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for at least three biomarkers from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients;
so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
67. The method of claim 66, wherein the series of predetermined reference scores are used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
68. A method for determining the likelihood that a patient diagnosed with cancer will benefit from adjuvant therapy comprising: a) determining in a sample of a tumor from the patient a level of expression for thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with a series of high risk and low risk patients; so as to thereby determine the likelihood that the patient will benefit from adjuvant therapy.
69. The method of claim 68, wherein the series of predetermined reference scores are used to generate a predetermined reference score cutpoint separating high risk from low risk patients wherein there is a likelihood that the patient will benefit from adjuvant therapy if the score obtained in step (b) is greater than the predetermined reference score cutpoint.
70. A method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising:
a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and
c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone;
so as to determine if the patient' s probability of survival would be greater if treated by surgery and adjunct therapy.
71. A method for determining whether a patient having a tumor associated with adenocarcinoma of the lung will have a greater probability of survival after a predetermined period of time if treated by surgery and adjunct therapy than if treated by surgery alone comprising:
a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and
c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone;
so as to determine if the patient' s probability of survival would be greater if treated by surgery and adjunct therapy.
72. A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjucunt therapy in addition to the surgery comprising:
a) measuring in a sample of the patient' s tumor a level of expression for at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta- catenin and cyclin Dl;
b) calculating a score based on the levels of expression of such at least three biomarkers measured in step (a) ; and
c) comparing the score obtained in step (b) with a predetermined reference score associated with an increased probability of survival after such predetermined period of time if treated by surgery and adjunct therapy as compared with treatment by surgery alone;
so as to determine if the patient's probability of survival would be greater if treated by surgery and adjunct therapy.
73. A method for determining the likelihood that a patient having a tumor associated with adenocarcinoma of the lung will have an increased chance of survival after surgery and adjunct therapy in addition to the surgery comprising:
a) measuring in a sample of the patient' s tumor a level of expression for each of at least three biomarkers selected from the following group: thyroid transcription factor-1 (TTF1), signal transducer and activator of transcription-3 (STAT-3) , beta-catenin and cyclin Dl;
b) calculating a score based on the levels of expression determined in step (a) ; and
c) correlating the score obtained in step (b) with a series of predetermined reference scores associated with survival of reference patients having tumors associated with adenocarcinomas of the lung;
so as to thereby determine the likelihood that the patient will have a higher chance of survival after surgery from adjunct therapy in addition to surgery.
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP12749461.5A EP2678676A4 (en) | 2011-02-22 | 2012-02-22 | A protein expression-based classifier for prediction of recurrence in adenocarcinoma |
US14/000,821 US20140148353A1 (en) | 2011-02-22 | 2012-02-22 | Protein expression-based classifier for prediction of recurrence in adenocarcinoma |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201161463715P | 2011-02-22 | 2011-02-22 | |
US61/463,715 | 2011-02-22 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2012116122A2 true WO2012116122A2 (en) | 2012-08-30 |
WO2012116122A3 WO2012116122A3 (en) | 2012-10-18 |
Family
ID=46721435
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2012/026201 WO2012116122A2 (en) | 2011-02-22 | 2012-02-22 | A protein expression-based classifier for prediction of recurrence in adenocarcinoma |
Country Status (3)
Country | Link |
---|---|
US (1) | US20140148353A1 (en) |
EP (1) | EP2678676A4 (en) |
WO (1) | WO2012116122A2 (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8497080B2 (en) | 2006-05-05 | 2013-07-30 | Historx, Inc. | Methods for determining signal transduction activity in tumors |
US8639450B2 (en) | 2001-04-20 | 2014-01-28 | Yale University | Systems and methods for automated analysis of cells and tissues |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2002101357A2 (en) * | 2001-06-10 | 2002-12-19 | Irm Llc | Molecular signatures of commonly fatal carcinomas |
US20060024692A1 (en) * | 2002-09-30 | 2006-02-02 | Oncotherapy Science, Inc. | Method for diagnosing non-small cell lung cancers |
US20080255243A1 (en) * | 2007-04-13 | 2008-10-16 | Petricoin Emanuel F | Stat3 as a theranostic indicator |
WO2008151110A2 (en) * | 2007-06-01 | 2008-12-11 | The University Of North Carolina At Chapel Hill | Molecular diagnosis and typing of lung cancer variants |
AU2008259930B2 (en) * | 2007-06-01 | 2014-05-29 | The Regents Of The University Of California | Multigene prognostic assay for lung cancer |
WO2009153775A2 (en) * | 2008-06-17 | 2009-12-23 | Rosetta Genomics Ltd. | Methods for distinguishing between specific types of lung cancers |
JP2012100536A (en) * | 2009-03-02 | 2012-05-31 | Genescience Co Ltd | Genetic testing method for cancer by analysis of expression of cancer-relating gene utilizing monocyte contained in blood sample |
-
2012
- 2012-02-22 EP EP12749461.5A patent/EP2678676A4/en not_active Withdrawn
- 2012-02-22 WO PCT/US2012/026201 patent/WO2012116122A2/en active Application Filing
- 2012-02-22 US US14/000,821 patent/US20140148353A1/en not_active Abandoned
Non-Patent Citations (1)
Title |
---|
See references of EP2678676A4 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8639450B2 (en) | 2001-04-20 | 2014-01-28 | Yale University | Systems and methods for automated analysis of cells and tissues |
US8497080B2 (en) | 2006-05-05 | 2013-07-30 | Historx, Inc. | Methods for determining signal transduction activity in tumors |
Also Published As
Publication number | Publication date |
---|---|
EP2678676A2 (en) | 2014-01-01 |
US20140148353A1 (en) | 2014-05-29 |
WO2012116122A3 (en) | 2012-10-18 |
EP2678676A4 (en) | 2014-10-29 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US8497080B2 (en) | Methods for determining signal transduction activity in tumors | |
JP5750152B2 (en) | Test method using signature gene associated with hepatocellular carcinoma, and array or kit used in the method | |
US20180045730A1 (en) | Methods for predicting tumor response to targeted therapies | |
US20120245051A1 (en) | Objective, quantitative method to predict histological subtype in non-small cell lung cancer | |
Kapur et al. | Primary adenocarcinoma of the urinary bladder: value of cell cycle biomarkers | |
Anagnostou et al. | Molecular classification of nonsmall cell lung cancer using a 4‐protein quantitative assay | |
US8377648B2 (en) | Autoimmune regulation of prostate cancer by annexin A3 | |
Zhao et al. | Cortactin is a sensitive biomarker relative to the poor prognosis of human hepatocellular carcinoma | |
Dimou et al. | Standardization of epidermal growth factor receptor (EGFR) measurement by quantitative immunofluorescence and impact on antibody-based mutation detection in non–small cell lung cancer | |
JP6626037B2 (en) | Methods for determining the survival potential of cancer patients and predicting the likelihood of metastasis in cancer patients | |
Reggiani Bonetti et al. | Prognostic significance of CDX2 immunoexpression in poorly differentiated clusters of colorectal carcinoma | |
US20140148353A1 (en) | Protein expression-based classifier for prediction of recurrence in adenocarcinoma | |
US8557527B2 (en) | Correlation of molecular markers with clinical outcome in GBM patients radiation treated with or without gefitinib | |
EP2472263A1 (en) | Methods for the prognostic assessment of breast cancer | |
Noguchi et al. | h-Prune is an independent prognostic marker for survival in esophageal squamous cell carcinoma | |
US20160327559A1 (en) | Hepatocyte growth factor as marker of prognosis in small cell lung cancer (sclc) | |
Fujimoto et al. | Variation in the expression levels of predictive chemotherapy biomarkers in histological subtypes of lung adenocarcinoma: an immunohistochemical study of tissue samples | |
Poster | MP55-01 | |
CN118318153A (en) | Method of predicting response to immunotherapy | |
De Petris | Discovery and validation of protein biomarkers for lung cancer | |
Scoggin et al. | Interobserver Agreement and Assay Reproducibility of Folate Receptor a Expression in Lung Adenocarcinoma: A Prognostic Marker and Potential Therapeutic Target |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 12749461 Country of ref document: EP Kind code of ref document: A2 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2012749461 Country of ref document: EP |
|
WWE | Wipo information: entry into national phase |
Ref document number: 14000821 Country of ref document: US |