EP2457096A2 - Phénotypage des leucocytes infiltrant les tumeurs - Google Patents

Phénotypage des leucocytes infiltrant les tumeurs

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Publication number
EP2457096A2
EP2457096A2 EP10802804A EP10802804A EP2457096A2 EP 2457096 A2 EP2457096 A2 EP 2457096A2 EP 10802804 A EP10802804 A EP 10802804A EP 10802804 A EP10802804 A EP 10802804A EP 2457096 A2 EP2457096 A2 EP 2457096A2
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European Patent Office
Prior art keywords
outcome
patient
tumor
sample
cancer
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German (de)
English (en)
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EP2457096A4 (fr
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Lisa M. Coussens
David G. Denardo
Donal J. Brennan
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University College Dublin
University of California
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University College Dublin
University of California
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Publication of EP2457096A2 publication Critical patent/EP2457096A2/fr
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Withdrawn legal-status Critical Current

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    • 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
    • G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
    • G01N33/57492—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites involving compounds localized on the membrane of tumor or cancer cells
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P35/00—Antineoplastic agents
    • C—CHEMISTRY; METALLURGY
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    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • 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
    • G01N33/57415—Specifically defined cancers of breast
    • 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
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/70503—Immunoglobulin superfamily, e.g. VCAMs, PECAM, LFA-3
    • G01N2333/70514—CD4
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/70503—Immunoglobulin superfamily, e.g. VCAMs, PECAM, LFA-3
    • G01N2333/70517—CD8
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/70596—Molecules with a "CD"-designation not provided for elsewhere in G01N2333/705
    • 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

Definitions

  • the present disclosure relates to an immune signature of tumor infiltrating leukocytes.
  • the disclosure provides methods and kits for determining the immune signature of tumor infiltrating leukocytes for use in assessing risk of cancer recurrence and long term survival, and for developing a treatment regimen for a cancer patient.
  • Cancer is a heterogeneous disease. There is widespread interest in identifying molecular characteristics of tumors indicative of their behavior and response to therapy in order to reduce morbidity and mortality. A better understanding of the molecular characteristics of tumors and their immune environment would also be valuable in reducing the use of toxic chemotherapy drugs on patients for whom these medicines would be ineffective and/or unnecessary for treating their cancers.
  • Basal subtype tumors are referred to as “triple negatives" because they do not express the estrogen receptor (ER), the progesterone receptor (PR) or the human epidermal growth factor receptor 2 (HER2/nue or ErbB2). As such basal subtype tumors are not expected to be sensitive to anti-estrogen therapies or trastuzumab.
  • ER estrogen receptor
  • PR progesterone receptor
  • HER2/nue or ErbB2 human epidermal growth factor receptor 2
  • breast cancer and ovarian cancer are the first and eighth most prevalent cancers in women, and the second and fifth most common cause of cancer- related death in women (U.S. Cancer Statistics Working Group, United States Cancer Statistics: 1999-2006 Incidence and Mortality Web-based Report, Atlanta: U.S. Department of Health and Human Services, Center for Disease Control and Prevention, and National Cancer Institute).
  • the poor ratio of survival to incidence of ovarian cancer is a consequence of late diagnosis and the lack of effective therapies for advanced refractory disease.
  • survival of ovarian cancer patients is 45% at five years (Jemal et al., CA Cancer J Clin, 58:71-96, 2008).
  • New tools to facilitate epithelial ovarian cancer diagnosis and patient stratification are therefore needed to improve the efficacy of available treatment options.
  • Adjuvant systemic chemotherapy for ovarian cancer is empiric and initial treatment involves paclitaxel-platinum-based regimens that continue to show improved outcomes compared to other cytotoxic agents such as gecitabine, topotecan and liposomal doxorubicin (Bookman et al., J Clin Oncol, 27:1419-1425, 2009).
  • cytotoxic agents such as gecitabine, topotecan and liposomal doxorubicin
  • epithelial ovarian cancer There are separate histological subgroups of epithelial ovarian cancer, including serous subgroups and non-serous subgroups (e.g., endometroid, clear cell and mucinous tumors), which are characterized by different clinical behaviors. Approximately 70% of tumors are serous and have a distinctly worse prognosis than other forms of ovarian cancer (Kobel et al., PLoS Med, 5:e232, 2008). Patient stratification according to histological subtypes is therefore desirable.
  • serous subgroups e.g., endometroid, clear cell and mucinous tumors
  • Ovarian cancer patients are further stratified based on their treatment-free interval after platinum-based chemotherapy (Markman and Hoskins, J Clin Oncol, 10:513-514, 1992). Patients were classified as having platinum-resistant ovarian cancer if progression occurred on primary platinum-based therapy, less than a partial response to a platinum-based regimen (Therasse et al., J Natl Cancer Inst, 92:205-216, 2000), or recurrence within six months of completing a platinum-based regimen. Alternatively, patients were classified as having platinum-sensitive ovarian cancer if they demonstrated at least a partial response to a platinum- based regimen and had a treatment-free interval of more than six months. This classification is particularly relevant in determining treatment regimens for recurrent disease as the probability of response to platinum-retreatment is closely related to the duration of platinum-free interval (Markman, Trends Pharmacol Sci, 29:515-519, 2008).
  • leukocytes While some subsets of leukocytes exhibit anti-tumor activity, including cytotoxic CD8 + T lymphocytes (CTLs) and natural killer (NK) cells (Dunn et al., Immunity, 21:137-148, 2004), other leukocytes exhibit more bipolar roles. Most notably, mast cells, CD4 + T lymphocytes, B lymphocytes, dendritic cells, granulocytes and macrophages, have the capacity to either hinder or potentiate tumor progression (Ostrand-Rosenberg, Curr Opin Genet Dev, 18:11-18, 2008; and de Visser et al., Cancer Cell, 7:411-423, 2005).
  • CTLs cytotoxic CD8 + T lymphocytes
  • NK natural killer cells
  • interferon- ⁇ (IFN- ⁇ ) (Marth et al., AM J Obstet Gynecol, 191:1598-1605; and Kusuda et al., Oncol Rep, 12: 1153-1158, 2005), the IFN- ⁇ receptor (Duncan et al., Clin Cancer Res, 13:4139- 4145, 2007), TNF ⁇ (Kusuda, 2005, supra) and MHC class I (Rolland et al., Clin Cancer Res, 13:3591-3596, 2007; and Leffers et al., Gynecol Oncol, 110:365-373, 2008).
  • IFN- ⁇ interferon- ⁇
  • the present disclosure relates to an immune signature of tumor infiltrating leukocytes.
  • the disclosure provides methods and kits for determining the immune signature of tumor infiltrating leukocytes for use in assessing risk of cancer recurrence and long term survival, and for developing a treatment regimen for a cancer patient.
  • the present disclosure provides methods for assessing risk of poor clinical outcome for a human cancer patient, the method comprising: a) subjecting a tumor sample from the patient to a procedure for quantitation of expression of leukocyte biomarkers comprising CD4, CD8 and CD68; and b) detecting the presence of an immune signature of poor outcome comprising CD4 hl /CD8 lo /CD68 hl or an immune signature of favorable outcome comprising CD4 lo /CD8 h 7CD68 lo in the tumor sample, wherein the immune signature of poor outcome is associated with an increased risk of poor clinical outcome as compared to the immune signature of favorable outcome.
  • the sample is from a solid tumor.
  • the procedure for quantitation comprises an antibody-based technique.
  • the antibody-based technique comprises a procedure selected from but not limited to immunohistochemistry, flow cytometry, antibody microarray, ELISA, western blotting, and magnetic resonance imaging.
  • the procedure for quantitation comprises a nucleic-acid based technique.
  • the nucleic acid based technique comprises a procedure selected from but not limited to RT-PCR, nucleic acid microarray, serial analysis of gene expression, massively parallel signature sequencing, in situ hybridization, and northern blotting.
  • the poor clinical outcome comprises a relative reduction in one or more of overall survival, recurrence-free survival (cancer relapse), and distant recurrence-free survival (cancer metastasis).
  • the methods further comprise: c) treating the patient with an aggressive treatment regimen when the immune signature of poor outcome is detected.
  • the favorable clinical outcome comprises a relative increase in one or more of overall survival, recurrence-free survival, and distant recurrence-free survival.
  • the methods further comprise: c) treating the patient with a conservative treatment regimen when the immune signature of favorable outcome is detected.
  • the methods further comprise: c) treating the patient with a platinum-based chemotherapy drug when the immune signature of favorable outcome is detected (e.g., indicative of a platinum-sensitive tumor).
  • the methods further comprise: c) treating the patient with a taxane-based chemotherapy drug (e.g., paclitaxel, docetaxel, etc.) when the immune signature of poor outcome is detected (e.g., indicative of a platinum-resistant tumor).
  • a taxane-based chemotherapy drug e.g., paclitaxel, docetaxel, etc.
  • the tumor sample is from a breast cancer biopsy, lumpectomy or resection.
  • the tumor sample is selected from but not limited to a breast (e.g., invasive ductal carcinoma, invasive lobular carcinoma, ductal carcinoma in situ, and lobular carcinoma in situ), bladder, cervical, colon, lung, mouth, ovarian, prostate, rectal, renal, testicular, and uterine cancer biopsy.
  • the methods further comprise determining subtype of the solid tumor.
  • the subtype is selected from the group consisting of basal, luminal A, and triple negative.
  • the ovarian cancer is epithelial ovarian cancer of a serous subtype. In other embodiments, the ovarian cancer is epithelial ovarian cancer of a non-serous subtype.
  • the methods further comprise: c) treating the patient with a regimen suitable for a basal or luminal A subtype of breast cancer. In some embodiments, the methods further comprise: c) treating the patient with a regimen suitable for a serous type of epithelial ovarian cancer.
  • the methods further comprise: c) treating the patient with an immune modulator.
  • the immune modulator is an anti-Th2 or a pro-Thl immune modulator.
  • the immune modulator is an inhibitor of colony stimulating factor 1 (CSFl, also known as monocyte colony stimulator factor, or M-CSF) or its receptor.
  • the methods further comprise one or both steps before a) of obtaining the tumor sample from the patient, and establishing a cut-off value for distinguishing between high and low expression of the leukocyte biomarkers.
  • the present disclosure provides methods for assessing risk of poor clinical outcome for a human breast cancer or ovarian cancer patient, the method comprising: a) subjecting a breast cancer or epithelial ovarian cancer sample from the patient to an antibody- based technique for quantitation of expression of leukocyte biomarkers comprising CD4, CD8 and CD68; and b) detecting the presence of an immune signature of poor outcome comprising CD4 h 7CD8 lo /CD68 hl or an immune signature of favorable outcome comprising
  • the antibody-based technique comprises
  • the poor clinical outcome comprises a relative reduction in one or more of overall survival, recurrence-free survival (cancer relapse), and distant recurrence-free survival (cancer metastasis).
  • the methods further comprise: c) treating the patient with an aggressive treatment regimen when the immune signature of poor outcome is detected.
  • the favorable clinical outcome comprises a relative increase in one or more of overall survival, recurrence-free survival, and distant recurrence-free survival.
  • the breast cancer subtype is selected from the group consisting of basal, luminal A, and triple negative.
  • the epithelial ovarian cancer of a serous subtype is selected from the group consisting of basal, luminal A, and triple negative.
  • the epithelial ovarian cancer of a non-serous subtype further comprises: c) treating the patient with a conservative treatment regimen when the immune signature of favorable outcome is detected.
  • the methods further comprise: c) treating the patient with a regimen suitable for a basal or luminal A subtype of breast cancer.
  • the methods further comprise: c) treating the patient with a regimen suitable for a serous type of epithelial ovarian cancer.
  • the methods further comprise: c) treating the patient with an immune modulator.
  • the immune modulator is an anti-Th2 or a pro-Thl immune modulator.
  • the immune modulator is an inhibitor of colony stimulating factor 1 (CSFl, also known as monocyte colony stimulator factor, or M-CSF) or its receptor.
  • CSFl colony stimulating factor 1
  • the methods further comprise one or both steps before a) of obtaining the breast or epithelial ovarian cancer sample from the patient, and establishing a cut-off value for distinguishing between high and low expression of the leukocyte biomarkers.
  • the present disclosure provides kits for assessing risk of poor clinical outcome for a human cancer patient, the kit comprising biomarker- specific reagents consisting essentially of: a) a CD4-specific reagent; b) a CD8-specific reagent; and c) a CD68-specific reagent.
  • the CD4-specific reagent, the CD8-specific reagent and the CD68-specific reagent are antibodies. In other preferred embodiments, the CD4-specific reagent, the CD8-specific reagent and the CD68-specific reagent are nucleic acids.
  • FIG. 1 illustrated that a CD68/CD4/CD8 immune-based signature is a significant independent predictor of patient survival.
  • A-C Representative high power images (4Ox) with 6Ox inlays of representative human breast cancer specimens showing expression of CD68 + (A), CD4 + (B) and CD8 + (C).
  • D-F Automated analysis of CD68 + (D), CD4 + (E) and CD8 + (F) immuno-detection reveals a relationship between leukocyte density and overall survival. Kaplan- Meier estimate of overall survival comparing autoscore leukocyte high and low infiltration groups is shown. 179 samples were used in all analyses and log rank (mantel- cox) p values are denoted for difference in overall survival.
  • Figure 2 illustrates that a CD68/CD4/CD8 immune -based signature predicts patient survival independently.
  • A-B A Kaplan-Meier estimate of overall survival is shown comparing CD68 h 7CD4 h 7CD8 lD and CD68 lo /CD4 lo /CD8 hl immune profiles for Luminal A and Basal tumor subtypes in Cohort II.
  • Figure 3 illustrates that a CD68/CD4/CD8 immune-based signature is a significant independent predictor of recurrence-free survival in ovarian cancer.
  • Representative high power images (2Ox) are provided of representative human ovarian cancer specimens showing expression of CD4 + (A), CD68 + (B), and CD8 + (C).
  • D-F The automated analysis of CD4 + (D), CD68 + (E), and CD8 + (F) immuno-detection reveals a relationship between leukocyte density and overall survival.
  • a Kaplan- Meier estimate of recurrence-free survival comparing autoscore leukocyte high and low infiltration groups is shown. 76 samples were used in all analyses and log rank (mantel-cox) p values are denoted for the difference in overall survival.
  • Figure 4 illustrates that a CD68/CD4/CD8 immune -based signature is a significant independent predictor of recurrence-free survival in ovarian cancer.
  • a Kaplan- Meier estimate of overall survival comparing CD68 hl /CD4 hl /CD8 l0 and CD68 1 7CD4 lo /CD8 hl immune profiles as assigned by decision tree analysis and 10-fold cross validation was employed. 76 samples were assessed; the log rank (mantel-cox) p value is denoted for difference in overall survival.
  • H Results from multivariate Cox regression analysis are provided for a 3-marker immune based "signature" considering tumor stage, grade, patient's age at diagnosis and residual disease after primary surgery.
  • Figure 5 illustrates that a CD68/CD4/CD8 immune -based signature is a predictor of recurrence-free survival in serous ovarian cancer tumors.
  • Figure 6 illustrates that immune infiltrates are different in serous compared to non-serous ovarian tumors.
  • A-D Analysis of mean cell density for CD68 + (A), CD20 + (B), CD8 + (C), and CD4 + (D). Error bars represent 2 SEM. * P ⁇ 0.05.
  • a three-marker (CD4, CD8 and CD68) immune-based profile is provided to robustly evaluate a cancer patient's immune response to malignancy at the time of biopsy and/or surgery. Characterization of tumor-infiltrating leukocytes permits predictions to be made regarding clinical outcome and likelihood of progression and/or relapse. As immune signatures are not apparently linked to the molecular and genetic heterogeneity of the tumor subtype; assessing immune responses to solid tumors provides an additional dimension to existing gene expression-based prognostic tools, which heretofore were solely reliant on the underlying tumor cell genetic and epigenetic features.
  • CD68 hl /CD4 hl /CD8 l0 immune profile are identified as being at a greater risk for cancer metastasis and/or relapse, and as having a reduced overall survival rate or rate of recurrence-free survival, as compared to cancer patients having cancer samples without a CD68 hl /CD4 hl /CD8 ° immune profile.
  • CD68 lo /CD4 lo /CD8 hl immune profile are identified as being at a reduced risk for cancer metastasis and/or relapse, and as having a greater overall survival rate or rate of recurrence-free ssuurrvviivvaall,, aass ccoomm]pared to cancer patients having cancer samples without a CD68 lo /CD4 lo /CD8 hl immune profile.
  • threshold levels of each marker are established to define a 'high' or 'low' level of expression of the marker. Depending on the cancer type analyzed, the technique used and the marker examined, different values may be used to define a 'high' or 'low' level of expression of the marker. In order to define 'high' or 'low' levels of expression of a marker, statistical analysis such as random forest clustering may be used in order to identify optimum threshold levels.
  • CD4, CD8, and CD68 levels are determined by using antibody-based methods to determine the levels of each biomarker protein in the tumor sample.
  • Antibody-based methods include various techniques that involve the recognition of CD4, CD8, and CD68 antigens using specific antibodies. For most techniques, monoclonal antibodies are used. However, for some techniques polyclonal antibodies can be used. Commonly used antibody -based techniques to detect the level of one or more proteins in a sample include immunohistochemistry, flow cytometry, antibody microarray, ELISA, western blotting, and magnetic resonance imaging.
  • Immunohistochemistry is the general process of determining the location and/or approximate level of one or more antigens in a tissue sample using antibodies directed against the antigens of interest. Typically, a thin slice of tumor tissue sample is cut from a larger tumor sample and mounted onto a slide, followed by treating the slice of tumor tissue with one or more reagents (including antibodies) to detect the antigens of interest. Immunohistochemistry can also be performed on tissue slices that are not mounted on a slide. In some instances, formalin-fixed and/or paraffin-embedded tissue samples are used for immunohistochemistry. Paraffinized samples can also be deparaffinized in order retrieve antigenicity of proteins.
  • antibody- antigen interactions can be detected through various mechanisms, including conjugating the antibody to an enzyme that can catalyze a color-producing reaction, such as a peroxidase, or conjugating the antibody to a fluorophore.
  • a fluorophore is a molecule that will absorb energy at a specific wavelength and release energy at a different specific wavelength, e.g. fluorescein.
  • the typical immunohistochemistry process involves treating first treating the thin tissue sample with blocking solution to reduce nonspecific background staining, followed by exposing the tissue sample the antibody or antibodies of interest, washing the tissue sample, and then visualizing the antibody-antigen complexes of interest. [00030] Flow Cytometry.
  • the tumor sample is processed to separate the tumor into individual cells.
  • the cells are incubated with fluorophore-tagged antibodies of interest, and the collection of cells is processed through a flow cytometer.
  • the flow cytometer uses different wavelengths of light to excite and detect different fluorophores.
  • Antibody Microarray The general process for an antibody microarray is to bind a collection of antibodies against antigens of interest to a fixed surface (to create the
  • a tumor sample is prepared by a homogenization technique which eliminates large tumor particles which could interfere with the function of the antibody microarray, but which preserves the integrity of the antigens of interest.
  • Reagents that can be used for detection of antibody microarray-bound antigens of interest include fluorophore or enzyme-tagged antibodies.
  • Enzyme-linked Immunosorbent Assay To detect protein levels in a sample by ELISA, what is commonly known as a 'Sandwich ELISA' is performed.
  • a Sandwich ELISA antibodies against an antigen of interest are linked to a surface. The surface- linked antibodies are exposed to a non-specific blocking agent, and then they are incubated with a sample containing the antigens of interest (e.g. in this case, a tumor sample). After incubation, the antibodies are washed to remove unbound material, and then antibodies which bind to the antigen are added.
  • These antibodies can be directly linked to a fluorophore or an enzyme to allow for their detection, or a secondary antibody linked to a fluorophore or an enzyme can be used to detect these antibodies.
  • a secondary antibody linked to a fluorophore or an enzyme can be used to detect these antibodies.
  • a sample of the tumor is separated by polyacrylamide gel electrophoresis.
  • the electrophoresis step separates proteins in the sample applied to the gel, and the proteins in the gel are next transferred to a membrane.
  • a membrane typically, PVDF or nitrocellulose membranes are used.
  • the membrane is treated with a non-specific blocking agent, and then incubated with antibodies against an antigen of interest.
  • the membrane is washed, and then treated with a secondary antibody which binds to the specific antibody.
  • the secondary antibody is typically linked to an enzyme, which can be used to create a reaction to detect the location and approximate level of the antigen of interest on the membrane.
  • Probes include antibodies directed against antigens of interest in the tumor, which are linked to molecules which can be visualized in the body. Through the use of these techniques, the level of one or more proteins of interest in a tumor inside the body can be determined.
  • CD4, CD8, and CD68 levels are determined by using nucleic acid-based methods to determine the levels of each biomarker mRNA in the tumor sample.
  • methods of mRNA level and gene expression profiling can be divided into two large groups: methods based on hybridization analysis of polynucleotides, and methods based on sequencing of polynucleotides.
  • RT-PCR is a method for comparing mRNA levels in different sample populations, in normal and tumor tissues, with or without drug treatment, to characterize patterns of gene expression, to discriminate between closely related mRNAs, and to analyze RNA structure.
  • the first step is the isolation of mRNA from a target sample.
  • the starting material is typically total RNA isolated from human tumors or tumor cell lines, and
  • RNA can be isolated from a variety of primary tumors, including breast, lung, colon, prostate, brain, liver, kidney, pancreas, spleen, thymus, testis, ovary, uterus, etc., tumor, or tumor cell lines, with pooled DNA from healthy donors. If the source of mRNA is a primary tumor, mRNA can be extracted, for example, from frozen or archived paraffin-embedded and fixed (e.g. formalin-fixed) tissue samples. [00038] General methods for mRNA extraction are well known in the art and are disclosed in standard textbooks of molecular biology, including Ausubel et al., Current Protocols of Molecular Biology, John Wiley and Sons (1997).
  • RNA isolation can be performed using purification kit, buffer set and protease from commercial manufacturers, such as Qiagen, according to the manufacturer's instructions.
  • Other commercially available RNA isolation kits include MasterPureTM Complete DNA and RNA Purification Kit (EPICENTRE®, Madison, Wis.), and Paraffin Block RNA Isolation Kit (Ambion, Inc.).
  • Total RNA from tissue samples can be isolated using RNA Stat-60 (Tel-Test).
  • RNA prepared from tumor can be isolated, for example, by cesium chloride density gradient centrifugation.
  • RNA cannot serve as a template for PCR
  • the first step in gene expression profiling by RT-PCR is the reverse transcription of the RNA template into cDNA, followed by its exponential amplification in a PCR reaction.
  • the two most commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MMLV-RT).
  • AMV-RT avilo myeloblastosis virus reverse transcriptase
  • MMLV-RT Moloney murine leukemia virus reverse transcriptase
  • the reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending on the circumstances and the goal of expression profiling.
  • extracted RNA can be reverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, Calif., USA), following the manufacturer's instructions.
  • the derived cDNA can then be used as a template
  • the PCR step can use a variety of thermostable DNA-dependent DNA polymerases, it typically employs the Taq DNA polymerase, which has a 5'-3' nuclease activity but lacks a 3'-5' proofreading endonuclease activity.
  • TaqMan® PCR typically utilizes the 5 '-nuclease activity of Taq or Tth polymerase to hydrolyze a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5' nuclease activity can be used.
  • Two oligonucleotide primers are used to generate an amplicon typical of a PCR reaction.
  • a third oligonucleotide, or probe is designed to detect nucleotide sequence located between the two PCR primers.
  • the probe is non-extendible by Taq DNA polymerase enzyme, and is labeled with a reporter fluorescent dye and a quencher fluorescent dye. Any laser-induced emission from the reporter dye is quenched by the quenching dye when the two dyes are located close together as they are on the probe.
  • the Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner.
  • the resultant probe fragments disassociate in solution, and signal from the released reporter dye is free from the quenching effect of the second fluorophore.
  • One molecule of reporter dye is liberated for each new molecule synthesized, and detection of the unquenched reporter dye provides the basis for quantitative interpretation of the data.
  • TAQMAN® RT-PCR can be performed using commercially available equipment, such as, for example, ABI PRISM 7700TM Sequence Detection SystemTM (Perkin- Elmer-Applied Biosystems, Foster City, Calif., USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany).
  • the 5' nuclease procedure is run on a real-time quantitative PCR device such as the ABI PRISM 7700TM Sequence Detection SystemTM.
  • the system consists of a thermocycler, laser, charge-coupled device (CCD), camera and computer.
  • the system amplifies samples in a 96-well format on a thermocycler. During amplification, laser-induced fluorescent signal is detected at the CCD.
  • the system includes software for running the instrument and for analyzing the data.
  • 5 '-Nuclease assay data are initially expressed as CT, or the threshold cycle.
  • fluorescence values are recorded during every cycle and represent the amount of product amplified to that point in the amplification reaction.
  • the point when the fluorescent signal is first recorded as statistically significant is the threshold cycle (C T ).
  • RT-PCR is usually performed using one or more reference genes as internal standards.
  • the ideal internal standard is expressed at a constant level among different tissues.
  • RNAs most frequently used to normalize patterns of gene expression are mRNAs for the housekeeping genes glyceraldehyde- 3-phosphate-dehydrogenase (GAPDH) and ⁇ -actin (ACTB).
  • GPDH glyceraldehyde- 3-phosphate-dehydrogenase
  • ACTB ⁇ -actin
  • RT-PCR A more recent variation of the RT-PCR technique is the real time quantitative PCR, which measures PCR product accumulation through a dual-labeled fluorigenic probe (i.e., TAQMAN® probe).
  • Real time PCR is compatible both with quantitative competitive PCR, where internal competitor for each target sequence is used for normalization, and with quantitative comparative PCR using a normalization gene contained within the sample, or a housekeeping gene for RT-PCR.
  • TAQMAN® probe dual-labeled fluorigenic probe
  • RNA isolation, purification, primer extension and amplification are given in various published journal articles for example: T. E. Godfrey et al. J. Molec. Diagnostics 2: 84-91 (2000); K. Specht et al., Am. J. Pathol. 158: 419- 29 (2001); Cronin et al., Am J Pathol 164:35-42 (2004). Briefly, a representative process starts with cutting about 10 ⁇ m thick sections of paraffin-embedded tumor tissue samples. The RNA is then extracted, and protein and DNA are removed. After analysis of the RNA concentration, RNA repair and/or amplification steps may be included, if necessary, and RNA is reverse transcribed using gene specific promoters followed by RT-PCR.
  • Microarrays Differential gene expression can also be identified, or confirmed using the microarray technique.
  • the expression profile of breast cancer-associated genes can be measured in either fresh or paraffin-embedded tumor tissue, using microarray technology.
  • polynucleotide sequences of interest including cDNAs and oligonucleotides
  • the arrayed sequences are then hybridized with specific probes from cells or tissues of interest.
  • the source of mRNA typically is total RNA isolated from human tumors or tumor cell lines, and
  • RNA can be isolated from a variety of primary tumors or tumor cell lines. If the source of mRNA is a primary tumor, mRNA can be extracted, for example, from frozen or archived paraffin-embedded and fixed (e.g. formalin-fixed) tissue samples, which are routinely prepared and preserved in everyday clinical practice.
  • the microarrayed genes are suitable for hybridization under stringent conditions.
  • Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After stringent washing to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pairwise to the array.
  • the relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously.
  • the miniaturized scale of the hybridization affords a convenient and rapid evaluation of the expression pattern for large numbers of genes. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et al., Proc. Natl. Acad. ScL USA 93(2): 106-149 (1996)).
  • Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Incyte's microarray technology.
  • Serial analysis of gene expression is a method that allows the simultaneous and quantitative analysis of a large number of gene transcripts, without the need of providing an individual hybridization probe for each transcript.
  • a short sequence tag (about 10-14 bp) is generated that contains sufficient information to uniquely identify a transcript, provided that the tag is obtained from a unique position within each transcript.
  • many transcripts are linked together to form long serial molecules, that can be sequenced, revealing the identity of the multiple tags simultaneously.
  • the expression pattern of any population of transcripts can be quantitatively evaluated by determining the abundance of individual tags, and identifying the gene corresponding to each tag. For more details see, e.g. Velculescu et al., Science 270:484-487 (1995); and Velculescu et al., Cell 88:243-51 (1997).
  • the free ends of the cloned templates on each microbead are analyzed simultaneously, using a fluorescence-based signature sequencing method that does not require DNA fragment separation. This method has been shown to simultaneously and accurately provide, in a single operation, hundreds of thousands of gene signature sequences from a yeast cDNA library.
  • RNA repair and/or amplification steps may be included, if necessary, and RNA is reverse transcribed using gene specific promoters followed by RT-PCR. Finally, the data are analyzed to identify the best treatment option(s) available to the patient on the basis of the characteristic gene expression pattern identified in the tumor sample examined, dependent on the predicted likelihood of cancer recurrence.
  • determination of CD4, CD8, and CD68 levels in a cancer patient is used to determine an optimal cancer treatment regimen for the patient.
  • an aggressive cancer treatment regimen may be indicated.
  • Aggressive cancer treatment regimens include but are not limited to local surgical resection of regional tumor tissue, and adjuvant systemic therapies. Surgical resection of regional disease includes lumpectomy, modified mastectomy or total mastectomy.
  • Adjuvant systemic therapies include external radiation, combinatorial chemotherapy (for example six cycles of fluorouracil, doxorubicin and cyclophosphamide), as well as hormone and/or growth factor targeted therapy for patients with ER, PR or HER2 positive disease (e.g., tamoxifen or trastuzumab).
  • a conservative cancer treatment regimen may be indicated.
  • Conservative cancer treatment regimens include but are not limited to local surgical resection and hormonal therapy, and would be similar to patients with low risk or Stage I disease with no lymph node involvement.
  • aggressive cancer treatment regimens include initial surgical debulking, which includes total abdominal hysterectomy, bilateral salpingo-oophorectomy and omentectomy with cytological evaluation of peritoneal fluid or washings.
  • Adjuvant systemic therapies include combinatorial chemotherapy (e.g. paclitaxel- platinum-based regimens, gecitabine, topotecan, liposomal doxorubicin).
  • drugs that can be used for invasive breast cancer or epithelial ovarian cancer treatment include but are not limited to: bevacizumab, carboplatin, chlorambucil, cisplatin, cetuximab, cyclophosphamide, cytarabine liposomal, docetaxel, epirubicin, erlotinib, fluorouracil, gefitinib, imatinib, mechlorethamine, methotrexate, mitomycin, mitoxantrone, PARP (poly ADP-ribose polymerase) inhibitors, paclitaxel, thiotepa, vinblastine, vinorelbine, trastuzumab, abraxane, doxorubicin, pamidronate disodium, anastrozole, exemestane, raloxifene, toremifene, letrozole, megestrol, tamoxifen,
  • the prognostic and treatment methods further comprise the classification of solid tumor subtype, using methods known in the art.
  • Breast cancers are categorized as basal, luminal A, luminal B, or triple-negative subtypes using immunohistochemistry as previously described (Carey et al., JAMA, 295, 2492- 2502, 2006).
  • Basal tumors are defined as estrogen receptor (ER) negative, progesterone receptor (PR) negative, HER2 negative and epidermal growth factor receptor (EGFR) positive.
  • Luminal A tumors are defined as ER, PR and HER2 positive.
  • Luminal B tumors are defined as ER and PR positive, and HER2 negative.
  • Triple negative tumors are as ER, PR and HER2 negative.
  • Basal tumors are a subset of triple negative tumors.
  • kits of reagents capable of detecting CD4, CD8, and CD68 molecules in a tumor sample are provided.
  • Reagents capable of detecting CD4, CD8 and CD68 molecules include but are not limited to anti-CD4, anti-CD8, and anti-CD68 antibodies, and nucleic acids capable of forming duplexes with CD4, CD8, or CD68 mRNA.
  • Nucleic acids capable of forming duplexes with CD4, CD8 or CD68 mRNA include DNA or RNA sequences which are complementary to the respective mRNA sequence.
  • Reagents capable of detecting CD4, CD8 and CD68 molecules are also typically directly or indirectly linked to a molecule such as a fluorophore or an enzyme which can catalyze detectable reaction, in order to indicate the binding of the reagents to their respective targets.
  • a molecule such as a fluorophore or an enzyme which can catalyze detectable reaction
  • Aggressive treatment regimen A cancer treatment regimen in which the emphasis is on killing and/or removing the cancer from the body as thoroughly as possible, to the possible detriment of patient comfort and/or safety.
  • an aggressive treatment regimen may, for example, use higher doses of anticancer therapeutics, higher total treatment times, and more radical surgeries.
  • Conservative treatment regimen A cancer treatment regimen in which efforts are made to kill and/or remove the cancer from the body, but which also heavily takes into account patient comfort and/or safety.
  • a conservative treatment regimen may, for example, use lower doses of anti-cancer therapeutics, lower total treatment times, and less radical surgeries.
  • Immuno-based / Antibody-based Any technique that involves the use of an antibody to detect an antigen. Immuno-based techniques include immunostaining, ELISA, antibody microarray, flow cytometry, and western blotting.
  • Nucleic acid-based Any technique that involves the use of a nucleic acid to detect another nucleic acid.
  • Nucleic acid includes both DNA and RNA.
  • Nucleic acid-based techniques include nucleic acid microarray, RT-PCR, northern blotting, nuclease protection assays, and in situ hybridization.
  • RNA ribonucleic acid
  • ssDNA single stranded DNA
  • dsDNA double stranded DNA
  • dNTP deoxyribonucleotide triphosphate
  • RNA ribonucleic acid
  • OD optical density
  • PCR polymerase chain reaction
  • RT-PCR reverse transcription PCR
  • CTL cytotoxic T lymphocyte
  • Th helper T lymphocyte
  • NK natural killer cell
  • EOC epidermal ovarian cancer
  • ER estrogen receptor
  • PR progesterone receptor
  • OS overall survival
  • IHC immunohistochemistry
  • TMA tissue microarrays
  • This example describes methods for immunophenotyping tumor-infiltrating leukocytes, and provides results of immune signature analyses in two cohorts of breast cancer patients.
  • the second (validation) cohort includes 498 patients with primary invasive breast cancer diagnosed at the Malmo University Hospital between 1988 and 1992 These cases belonged to an original cohort of 512 patients as previously described in detail (Paulsson et al., Am J Pathol, 175:334-341, 2009; and Borgquist et al., J Clin Pathol, 61:197-203, 2008).
  • the median age at diagnosis was 65 years and median follow-up time to first breast cancer event was 128 months.
  • Information regarding the date of death was obtained from the regional cause-of-death registries for all patients in both cohorts.
  • Complete treatment data was available for 379 patients, 160 of whom had received adjuvant tamoxifen.
  • Information on adjuvant chemotherapy was available for 382 patients, of which 23 patients received treatment. 200 patients received no adjuvant treatment.
  • a classification tree procedure was used to create a tree-based classification model and cases were classified into groups based on a the values of dependent predictor variable(target).
  • Patient survival was used as the target variable for building the predictions trees.
  • These tree models were evaluated in terms prediction accuracy using a 10-fold cross-validation approach.
  • Kaplan- Meier analysis and the log-rank test were used to illustrate differences between overall survival (OS) according to individual CD68, CD4, and CD8 expression.
  • a Cox regression proportional hazards model was employed to estimate the relationship to OS of the CD68/CD4/CD8 immune profile, lymph node status, tumor grade, and HER2, PR and ER status in the patient cohorts.
  • Multivariate models included any variable that displayed a significant association with outcome following univariate analysis.
  • a p-value of ⁇ 0.05 was considered statistically significant and all calculations were performed using Statistical Package for the Social Sciences (SPSS, Inc.).
  • Random forest clustering (RFC) was performed using R software.
  • TMA tissue microarray
  • FIG. IA-F immunohistochemistry using a tissue microarray (TMA) consisting of tumor tissue representing two independent cohorts of breast cancers.
  • TMA-F tissue microarray
  • a fully automated nuclear algorithm was used to discriminate tumor from "normal” tissue, and to quantify CD4 + , CD8 + and CD68 + cells.
  • Random forest clustering was employed to identify optimum thresholds for survival analysis.
  • Kaplan Myer analysis for overall survival demonstrates that as single variables "high" infiltration by CD4 + cells and low CD8 + cell density predict reduced overall survival while CD68 + cell density alone showed no statistical difference in overall survival (FIG. ID-F).
  • CD68 lo /CD4 lo /CD8 hl was predicted to represent individuals whose breast tumors were controlled by local resection of primary tumor and adjuvant therapy (e.g., patients exhibiting longer relapse-free survival).
  • patients bearing an immune response characterized as CD68 h 7CD4 h 7CD8 l0 were predicted to represent a population of patients at risk for metastasis, relapse and reduced overall survival.
  • Random forest clustering was employed to identify optimum thresholds for discriminating CD68 hl /CD4 h 7CD8 l0 and CD68 lo /CD4 lo /CD8 hl in survival analysis using patient cohort I.
  • the three-marker immune -based signature is a useful predictor of overall survival for multiple breast cancer subtypes, and as such is an improvement to existing gene expression-based prognostic profiling methods to evaluate risk.
  • this immune signature is predictive for patients with low-risk ER + tumors (such as in the luminal A subtype) or alternatively high-risk triple negative breast tumors.
  • Tissue microarrays containing specimens representing various grades of ductal carcinoma in situ are also prepared and examined.
  • the three marker immune-based signature is also expected to stratify patients with this common noninvasive type of breast cancer.
  • This example describes methods for assessing mRNA levels of three biomarkers of tumor-infiltrating leukocytes, and for retrospectively analyzing the immune signature in published gene expression data sets.
  • RNA is used a template for cDNA synthesis.
  • oligo-dT primers dT17
  • 1 microliter 10 nM dNTPmix (Clonetech) is added to 5 microliters of each resuspended RNA solution. The mixtures are heated for 10 minutes at 65 degrees Celsius, and then immediately chilled on ice.
  • 4 microliters of first strand buffer, 2 microliters DTT, 1 microliter RNAsin (Promega) and 1 microliter Superscript II reverse transcriptase (Invitrogen) are added, and then the reactions are kept at 42 degrees Celsius for 1 hour to allow reverse transcription to occur.
  • RNAseH (Clonetech) at 37 degrees Celsius for 30 minutes.
  • 2 microliters of the cDNA solution (10%) is used for each 40-cycle Sybgreen PCR assay using the Sybrgreen Universal PCR Master Mix (Applied Biosystems) with forward and backward primers for the CD4, CD8, or CD68 cDNA.
  • the PCR reaction is performed with an ABI PRISM 7000HT real-time PCR cycler (Applied Biosystems) using conditions recommended by the manufacturer. Gene expression levels are normalized to expression of the housekeeping gene glyceraldehyde-3 -phosphate dehydrogenase (GAPDH).
  • GPDH housekeeping gene glyceraldehyde-3 -phosphate dehydrogenase
  • a profile of a combination of high CD68, high CD4, and low CD8 mRNA levels is contemplated to be associated with a greater risk of tumor relapse and/or metastasis as compared to a profile of a combination of low CD68, low CD4, and high CD8 mRNA levels.
  • the CD68/CD4/CD8 gene expression prognostic signature is assessed by multi- variant analysis using random forest clustering to evaluate cut off points, and the signature is used to improve risk stratification independently of known clinicopathologic factors and previously established prognostic signatures based on unsupervised hierarchical clustering ("molecular subtypes") or supervised predictors of metastasis ("multi-gene prognosis signature").
  • This example describes methods for immunophenotyping tumor-infiltrating leukocytes, and provides results of immune signature analyses in a cohort of epithelial ovarian cancer (EOC) patients.
  • EOC epithelial ovarian cancer
  • TMA tissue microarray
  • Tissue microarrays Seventy six paraffin-embedded tumor specimens were used for tissue microarray construction as previously described (Brennan et al., 2009, supra). Areas representative of invasive cancer were marked on haematoxylin and eosin-stained slides and the tissue microarray was constructed using a manual tissue arrayer (MTA-I, Beecher Inc, WI). The array consisted of four cores per patient. Two 1.0 mm cores were extracted from each donor block and assembled in a recipient block. Recipient blocks were limited to approximately 100 cores each. In general, cores were taken from the peripheral part of the tumor in cases where the tumor had well-defined borders. In more diffusely growing tumors, areas with the highest tumor cell density were primarily targeted. Necrotic tissue was avoided.
  • a Cox regression proportional hazards models was employed to estimate the relationship between recurrence free survival and the CD68/CD4/CD8 immune profile, disease stage, tumor grade, age at diagnosis and residual disease after primary surgery.
  • a P value of ⁇ 0.05 was considered statistically significant and all calculations were performed using SPSS version 12.0 (SPSS Inc, Chicago, IL).
  • CD68/CD4/CD8 signature had an increased survival hazard ratio of 2.26 and no statistical correlation with disease grade, stage, age at diagnosis or post-operative residual disease (FIG. 4B), indicating that the immune signature predicts epithelial ovarian cancer survival independently of the typical clinical and histopathological markers currently employed.

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Abstract

La présente invention a pour objet une signature immunitaire des leucocytes infiltrant les tumeurs. En particulier, la présente invention concerne des méthodes et des kits permettant de déterminer la signature immunitaire des leucocytes infiltrant les tumeurs et destinés à être utilisés dans l’évaluation du risque de récidive du cancer et de la survie à long terme, et permettant de développer un régime de traitement pour un patient atteint du cancer.
EP10802804A 2009-07-20 2010-07-20 Phénotypage des leucocytes infiltrant les tumeurs Withdrawn EP2457096A4 (fr)

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WO2012078803A1 (fr) * 2010-12-07 2012-06-14 The Regents Of The University Of California Phénotypage de leucocytes infiltrant les tumeurs
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US12031975B2 (en) * 2017-11-01 2024-07-09 Juno Therapeutics, Inc. Methods of assessing or monitoring a response to a cell therapy
AU2022238685A1 (en) * 2021-03-19 2023-09-21 Artur MEZHEYEUSKI Novel biomarker

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* Cited by examiner, † Cited by third party
Title
AL MURRI A M ET AL: "The relationship between the systemic inflammatory response, tumour proliferative activity, T-lymphocytic and macrophage infiltration, microvessel density and survival in patients with primary operable breast cancer", BRITISH JOURNAL OF CANCER, HARCOURT PUBLISHERS, vol. 99, no. 7, 7 October 2008 (2008-10-07), pages 1013-1019, XP009164409, ISSN: 0007-0920 *
EIICHI SATO ET AL: "Intraepithelial CD8+ tumor-infiltrating lymphocytes and a high CD8+/regulatory T cell ratio are associated with favorable prognosis in ovarian cancer", PNAS, vol. 102, no. 51, 20 December 2005 (2005-12-20), pages 18538-18543, XP002687398, *
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WAN T ET AL: "Prognostic significance of tumor-associated macrophage infiltration in advanced epithelial ovarian carcinoma", AIZHENG - CHINESE JOURNAL OF CANCER, GAI KAN BIANJIBU, GUANGZHOU, CN, vol. 28, no. 3, 1 January 2009 (2009-01-01), pages 323-327, XP009164471, ISSN: 1000-467X *

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