WO2013106913A1 - Biomarqueurs pour le pronostic et le traitement du cancer du sein - Google Patents

Biomarqueurs pour le pronostic et le traitement du cancer du sein Download PDF

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WO2013106913A1
WO2013106913A1 PCT/CA2013/000042 CA2013000042W WO2013106913A1 WO 2013106913 A1 WO2013106913 A1 WO 2013106913A1 CA 2013000042 W CA2013000042 W CA 2013000042W WO 2013106913 A1 WO2013106913 A1 WO 2013106913A1
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level
hsp90b1
dcn
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breast cancer
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PCT/CA2013/000042
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Susan Jane DONE
Thomas Richard CAWTHORN
Juan Carlos MORENO
Kenneth Robert Evans
Jian Chen
Suzanne Zobeeda ACKLOO
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University Health Network
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    • 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
    • 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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P35/00—Antineoplastic agents
    • 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
    • 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
    • C12Q2600/158—Expression markers
    • 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

Definitions

  • the present disclosure relates to biomarkers for breast cancer, and more specifically to methods for providing a prognosis for subjects with breast cancer as well as associated compositions and kits.
  • the clinical challenge is to correctly identify those patients that have or will develop LN or distant metastasis and that therefore will behave poorly, and use this information to offer supplemental treatment after local therapy.
  • a sensitive and specific biomarker able to accurately predict disease recurrence and LN or distant metastasis is lacking and markers of disease progression continue to be needed to improve patient classification.
  • Biomarkers such as CA 15-3 and CEA are employed to monitor the progress of the disease as an indirect measurement of tumour burden but with somewhat limited success and are not currently widely used in clinical practice [8][9],
  • proteomics can be used to differentiate between two physiologic states using tissue samples that represent underlying biology and pathology. Isotopic labelling [10] and label-free mass spectrometry (MS) [1 1] proteomics enable the quantification of proteins and thus allow direct comparison of protein expression between two sample sets [12][13].
  • HSP90B1 also helps cells escape apoptosis and preserves the function of various proto-oncogenes important for breast cancer growth [15].
  • HSP90 proteins have several client proteins including mutated p53 and B-RAF, BCR-ABL, v-Src, ErbB-2, AKT, RAF-1 , CDK4, VEGF and PIK3 [16][17],
  • the HSP90 family is comprised of 17 genes.
  • HSP90A alpha
  • HSP90B beta
  • HSP90B is the major form of HSP90 involved in normal cellular functions, such as maintenance of the cytoarchitecture, differentiation and cytoprotection [18][ 9].
  • HSP90B1 has 2 known splice variants HSP90B1-201 and -202; data is lacking as to any functional difference between the two splice variants.
  • the present disclosure describes the identification of biomarkers for breast cancer, and in particular biomarkers useful for providing a prognosis for a subject having or suspected of having breast cancer.
  • the biomarkers listed in Table 1 were identified as differentially expressed in subjects with cancer with or without lymph node metastasis using selected reaction monitoring mass spectroscopy (SRM-MS).
  • SRM-MS reaction monitoring mass spectroscopy
  • the biomarkers HSP90B1 , Decorin (DCN), HMGN2, USP34 and G6PD were then observed to be associated with lymph node (LN) status in a tissue microarray (TMA) of invasive ductal carcinoma.
  • TMA expression levels of HSP90B1 and DCN were significantly higher in LN positive tumours relative to LN negative tumours.
  • HSP90B1 and DCN are a useful prognostic biomarker for breast cancer and in particular for predicting metastasis, lymph node metastasis, overall survival and disease free survival.
  • HSP90B1 was shown to be a useful biomarker for predicting metastasis, distant metastasis, overall survival and disease free survival.
  • HSP90B1 and DCN are also shown in the present disclosure to be useful biomarkers for identifying subjects with breast cancer who benefit from hormone treatment.
  • the method comprises:
  • a determining a level of one or more biomarkers in a test sample from the test subject, the one or more biomarkers selected from Table 1 , b. comparing the level of one or more biomarkers in the test sample with a control, and
  • the evaluation provides an indication of the subject's prognosis and/or response to hormone treatment.
  • the prognosis comprises an indication of one or more of metastasis and survival time.
  • a method of providing a prognosis for a test subject having or suspected of having breast cancer comprising:
  • the biomarkers are selected from HSP90B1 , Decorin (DCN), HMGN2, USP34 and G6PD.
  • the biomarker is HSP90B1.
  • the biomarker is Decorin (DCN).
  • the biomarkers include both HSP90B1 and DCN, optionally with one or more of the biomarkers listed in Table 1.
  • the prognosis for the test subject is a likelihood of metastasis such as lymph node metastasis or distant metastasis, or a survival time such as overall survival or disease free survival.
  • control represents subjects with breast cancer without metastasis and an increase in the level of HSP90B1 and/or DCN the test sample relative to the control indicates an increased likelihood of metastasis in the test subject.
  • control represents subjects with breast cancer without lymph node metastasis and an increase in the level of DCN in the test sample relative to the control indicates an increased likelihood of lymph node metastasis in the test subject.
  • control sample represents subjects with breast cancer without distant metastasis and an increase in the level of HSP90B1 in the test sample relative to the control indicates an increased likelihood of distant metastasis in the test subject.
  • the control represents subjects with breast cancer without metastasis and a similar level of HSP90B1 and/or DCN in the test sample relative to the control indicates a low likelihood of metastasis in the test subject.
  • the control represents subjects with breast cancer without metastasis and a similar level of DCN in the test sample and the control indicates a low likelihood of lymph node metastasis.
  • the control represents subjects with breast cancer without metastasis and similar level of HSP90B1 in the test sample and the control indicates a low likelihood of distant metastasis in the test subject.
  • the methods described herein are used to provide a prognosis related to the survival time of a test subject with breast cancer.
  • a difference or similarity in the level of one or more biomarkers between the test sample and the control is used to estimate a survival time for the test subject. For example, in one embodiment an increase in the level of HSP90B1 and/or DCN in a test sample from the test subject relative to a control indicates a decreased overall survival (OS) and/or disease free survival (DFS) for the test subject.
  • OS overall survival
  • DFS disease free survival
  • control represents subject with cancer who survived for at least 2 years, 5 years or 10 years from diagnosis with breast cancer and an increase in the level of HSP90B1 and/or DCN in a test sample from the test subject relative to the control indicates a decreased estimated overall survival for the test subject relative to the control.
  • control represents subjects with breast cancer who survived for at least 2 years, 5 years or 10 years from diagnosis with breast cancer without recurrence of breast cancer and the method is useful for providing a prognosis of disease free survival for the test subject.
  • the methods described herein are also useful for providing a prognosis for the survival of the test subject relative to other time periods, or to estimate a survival time based on the levels of one or more biomarkers listed in Table 1 , such as HSP90B1 and/or DCN.
  • the levels of two or more biomarkers in a test sample are used to generate an expression profile for the test subject.
  • the methods described herein include determining a level for two or more biomarkers in the test sample, generating a test sample expression profile based on the level of the two or more biomarkers and comparing the test sample expression profile to a control expression profile. A difference or similarity in the test sample expression profile and the control expression profile is then used to provide a prognosis for the test subject.
  • a method of selecting treatment for a test subject with breast cancer or suspected of having breast cancer comprises:
  • selecting a treatment for the test subject based on a difference or similarity in the level of HSP90B1 and/or DCN in the test sample compared to the control.
  • the control represents subjects with breast cancer who are not responsive to hormone treatment and a test subject with an increase in the level of HSP90B1 and/or DCN in the test sample relative to the control is selected for hormone treatment.
  • the method comprises treating a test subject with an increase in the level of HSP90B1 and/or DCN relative to the control with hormone treatment.
  • the method further comprises administering a hormone treatment to a test subject selected for hormone treatment.
  • the hormone treatment includes Tamoxifen, or an aromatase inhibitor or other agent acting upon estrogen receptors, progesterone receptors or their signaling pathways.
  • the present disclosure also provides a method of identifying a test subject with breast cancer with an increased likelihood of being responsive to hormone treatment.
  • the method comprises: determining a level of HSP90B1 and/or DCN in a test sample from the test subject,
  • the method further comprises treating the test subject identified as having an increased likelihood of being responsive to hormone treatment with hormone treatment.
  • the control represents subjects with breast cancer who are not responsive to hormone treatment and an increase in the level of HSP90B1 and/or DCN in the test sample relative to the control indicates that the test subject has an increased likelihood of being responsive to hormone treatment.
  • a method of treating a subject with breast cancer comprising:
  • test subject identifying the test subject as having an increased likelihood of being responsive to hormone treatment based on a difference or similarity in the level of HSP90B1 and/or DCN in the test sample compared to the control, and
  • One embodiment includes the use of hormone therapy for treating breast cancer in a subject, wherein the level of HSP90B1 and/or DCN in a test sample from the subject is increased relative to a control level. There is also provided the use of hormone therapy for treating a breast cancer with an increased level of HSP90B1 and/or DCN compared to a control level. In one embodiment, the use is for treating breast cancer in a subject with metastasis, such as lymph node metastasis. [0026] In one embodiment the methods and uses described herein include determining a level of HSP90B1 in a test sample and comparing the level of HSP90B1 in the test sample with a control.
  • the method or use comprises determining a level of DCN and comparing the level of DCN in the test sample with a control. In one embodiment, the method or use comprises determining a level of both HSP90B1 and DCN and comparing the levels of HSP90B1 and DCN with control levels of HSP90B1 and DCN.
  • the hormone treatment includes Tamoxifen, or an aromatase inhibitor or other agent acting upon estrogen receptors, progesterone receptors or their signaling pathways.
  • the methods described herein optionally include obtaining a test sample from the test subject prior to determining a level of one or more biomarkers in the test sample.
  • the method comprises processing or purifying a test sample such as to isolate one or biomarkers prior to determining a level of one or more biomarkers in the test sample.
  • the methods and/or uses described herein include determining a level of one or more biomarkers.
  • the level of the one or more biomarkers is determined by measuring or detecting the level of a nucleic acid such as mRNA, or the level of a protein or polypeptide.
  • the methods described herein include detecting a biomarker using immunohistochemistry, such as by using an antibody specific for the biomarker or another biomarker- specific detection agent.
  • the methods described herein include contacting a test sample with one or more biomarker-specific detection agents.
  • compositions and kits that include at least two biomarker-specific detection agents, each of which specifically binds a biomarker selected from Table 1.
  • the compositions or kits include two or more antibodies selected from Table 2b.
  • Figure 1 shows a scoring system used for DCN and HSP90B1 immunohistochemistry.
  • A Strong DCN positivity in stroma (3+) and negative in carcinoma (0) (magnification 200x).
  • B Strong DCN positivity in carcinoma (3+), weak stromal positivity (1+) (200x).
  • C Moderate HSP90B1 positivity in carcinoma (1+) (200x).
  • D Strong HSP90B1 positivity in carcinoma (3+) (200x).
  • Decorin antibody Sigma-Aldrich, St. Louis, MO
  • HSP90B1 antibody Sigma-Aldrich, St. Louis, MO used at a dilution of 1 :4000.
  • Figure 2 Venn diagram of differentially expressed proteins. Number of proteins differentially expressed for each comparison group as well as overlapping proteins. Node-negative breast cancer tissue (group A), node positive BC tissue (group B), and normal breast tissue (group N).
  • Figure 3 Overall and Disease-free survival based on high and low DCN and HSP90B1 staining.
  • A OS curve for DE. B, DFS curve for DE. C, OS curve for HE. D, DFS curve for HE.
  • DE Decorin staining in malignant epithelial tissue.
  • HE HSP90B1 staining in malignant epithelial tissue.
  • OS Time from diagnosis to death from any cause.
  • DFS Time from diagnosis to any recurrence or death from any cause.
  • Figure 4 Overall survival curves using combinations of DE and
  • DE Decorin staining in malignant epithelial tissue.
  • HE HSP90B1 staining in malignant epithelial tissue.
  • HR Hazard ratio.
  • Figure 5 Overall survival curves for high and low DE staining based on tumour molecular subtype. Univariate Cox regression used to determine HR; logrank p-values reported. Molecular subtypes were defined by IHC expression of ER, HER2 and Ki-67 as suggested by Cheang et al. (2009) and Hugh er a/. (2009). DE: Decorin staining in malignant epithelial tissue. HR: Hazard ratio.
  • Figure 7 Overall survival curves based on DE/HE expression and hormone treatment.
  • A Survival curves for cases with high and low DE that did not receive hormone treatment.
  • B Survival curves for cases with high and low DE that received hormone treatment.
  • C Survival curves for cases with high and low HE that did not receive hormone treatment.
  • D Survival curves for cases with high and low HE that received hormone treatment.
  • DE Decorin staining in malignant epithelial tissue.
  • HE HSP90B1 staining in malignant epithelial tissue.
  • AFC Absolute fold-change
  • DCN Decorin
  • DE Decorin staining in cancer epithelial cells
  • DFS Disease-free survival
  • DS Decorin staining in normal stromal cells
  • HE HSP90B1 staining in cancer epithelial cells
  • HER2 v-erb- b2 erythroblastic leukemia viral oncogene homolog 2
  • HR Hazard Ratio
  • HSP90B1 Heat shock protein 90kDa beta (Grp94), member 1
  • lavg Intensity Average
  • IHC Immunohistochemical
  • iTRAQ isobaric tags for relative and absolute quantitation
  • LC-MS/MS Liquid chromatography tandem mass spectrometry
  • LN Lymph Node
  • MS Mass spectrometry
  • NCI National Cancer Institute
  • OR Odds ratio
  • OS Overall survival
  • SID Stable isotope dilution
  • SRM Selected reaction monitoring
  • SRM-MS Selected reaction monitoring
  • providing a prognosis for a test subject refers to determining the likelihood of a particular outcome for a test subject having or suspected of having breast cancer.
  • the prognosis may relate to the presence of absence of breast cancer, the severity of the disease, likelihood of survival of the test subject, likelihood of disease recurrence, the presence of a particular form or subtype of the disease, and/or the likelihood that a subject is responsive to a particular treatment.
  • "providing a prognosis for a test subject” includes estimating the likelihood of metastasis in the test subject.
  • prognosis for a test subject refers to estimating the survival time, such as overall survival, or disease-free survival for the test subject.
  • the methods and biomarkers described herein are useful for estimating the likelihood of a particular outcome related to breast cancer such as metastasis and/or survival time.
  • prognosis for a test subject refers to determining the likelihood of the test subject being responsive to hormone treatment.
  • biomarker refers to an expression product such as an mRNA, polypeptide, polypeptide antigen, or a fragment thereof, of a gene listed in Table 1 , the level of which can be used to provide a prognosis for a test subject having or suspected of having cancer as described herein.
  • HSP90B1 Decorin (DCN), HMGN2, USP34 and G6PD and/or any combination thereof are biomarkers whose levels can be used to provide a prognosis for a test subject having or suspected of having breast cancer.
  • biomarker-specific detection agent refers to an agent that selectively binds its cognate biomarker compared to another molecule and which can be used to detect a level and/or the presence of the biomarker.
  • biomarker-specific detection agent includes any molecule or compound that can bind to a biomarker expression product including polypeptides such as antibodies, nucleic acids and peptide mimetics.
  • a suitable antibody for detecting the level of a biomarker that is a transmembrane protein includes an antibody that binds an extracellular portion of the protein.
  • the "detection agent” can for example be coupled to or labeled with a detectable marker.
  • the label is preferably capable of producing, either directly or indirectly, a detectable signal.
  • the label may be radio-opaque or a radioisotope, such as 3 H, 4 C, 32 P, 35 S, 123 l, 125 l, 31 1; a fluorescent (fluorophore) or chemiluminescent (chromophore) compound, such as fluorescein isothiocyanate, rhodamine or luciferin; an enzyme, such as alkaline phosphatase, beta-galactosidase or horseradish peroxidase; an imaging agent; or a metal ion.
  • a radioisotope such as 3 H, 4 C, 32 P, 35 S, 123 l, 125 l, 31 1
  • a fluorescent (fluorophore) or chemiluminescent (chromophore) compound such as fluorescein isothiocyanate, rhodamine or luciferin
  • an enzyme
  • An antibody or fragment (e.g. binding fragment) thereof that specifically binds a biomarker refers to an antibody or fragment that selectively binds its cognate biomarker compared to another molecule. "Selective" is used contextually, to characterize the binding properties of an antibody. An antibody that binds specifically or selectively to a given biomarker or epitope thereof will bind to that biomarker and/or epitope either with greater avidity or with more specificity, relative to other, different molecules. For example, the antibody can bind 3-5 fold, 5-7 fold, 7-10, 10-15, 5-15, or 5-30 fold more efficiently to its cognate biomarker compared to another molecule.
  • biomarker-specific detection agent also includes an agent that selectively binds a nucleic acid such as an mRNA or cDNA that encodes for a biomarker and can be used to detect the level and/or the presence of the biomarker in a test sample.
  • the term "level” as used herein refers to an amount (e.g. relative amount or concentration) of biomarker that is detectable or measurable in a sample.
  • the level can be a concentration such as g/L or a relative amount such as 1 .2, 1.3, 1.4, 1 .5, 1 .6, 1 .7, 1 .8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.2, 3.4, 3.6, 3.8, 4.0, 4.2, 4.4, 4.6, 4.8, 5.0, 10, 15, 20, 25, 30, 40, 60, 80 and/or 100 times or greater a control level.
  • a control is a level such as the average or median level in a control sample.
  • the level of biomarker can be, for example, the level of protein, or of an mRNA encoding for the biomarker.
  • a test subject having or suspected of having breast cancer refers to a subject that has been diagnosed with breast cancer, or a test subject for whom a diagnosis of breast cancer is uncertain.
  • a test subject suspected of having breast cancer may present with one or more symptoms of breast cancer.
  • a test subject suspected of having breast cancer may have breast cancer or a benign breast disease, such as mastitis or fibroadenoma.
  • breast cancer refers to a cancer that starts in a tissue of the breast, such a ductal carcinoma or lobular carcinoma and includes both early stage and late stage breast cancer.
  • Breast cancer may be invasive or non-invasive and/or comprise malignant epithelial cells.
  • breast cancer may be classified according to molecular subtypes such as ER and/or Her2 positive or negative as known in the art.
  • metastasis refers to the spread of breast cancer from the breast to a non-adjacent part, tissue or organ of the test subject.
  • metastasis includes “lymph node metastasis” and/or "distant metastasis”.
  • lymph node metastasis refers to the spread of cancer to the lymph system of a test subject.
  • lymph node metastasis includes the presence of malignant cells in one or more lymph nodes of a test subject, such as in the lymph nodes that are proximal to the breast cancer, for example in one or more sentinel lymph nodes.
  • disant metastasis refers to metastasis that is present in another non-adjacent part, tissue or organ of a test subject such as in lung, liver, brain or bone or in a distal lymph node.
  • subject refers to any member of the animal kingdom, preferably a human being including for example a subject having or suspected of having breast cancer. In one embodiment, the subject is a mammal.
  • test sample refers to any biological fluid, cell or tissue sample from a subject (e.g. test subject), which can be assayed for one or more biomarkers.
  • the test sample can comprise breast tissue such as a biopsy, including a needle biopsy, an excisional biopsy and/or a laparoscopic biopsy.
  • the test sample is a frozen sample.
  • the test sample is a fixed-tissue sample such as a formalin-fixed paraffin embedded (FFPE) sample.
  • the test sample comprises malignant epithelial cells, optionally at least 80%, 90%, 95% or 99% malignant epithelial cells.
  • the sample comprises stromal cells.
  • the biological fluid is blood, serum, lymph or a fluid that has been in contact with a breast cancer tumour in vivo.
  • control refers to a level of one or more biomarkers that has been associated with a prognosis in one or a plurality of subjects with breast cancer.
  • the control is a level, such as a median, average or threshold level of a biomarker that is associated with a prognosis in a plurality of subjects with breast cancer.
  • the control is an expression profile that comprises a level of two or more biomarkers.
  • control refers to the level or one more biomarkers that is representative of subjects with breast cancer who do not have metastasis, optionally lymph node metastasis or distant metastasis.
  • control refers to the level of one or more biomarkers that is representative of subjects with breast cancer who have metastasis, optionally lymph node metastasis or distant metastasis.
  • control refers to a level of one or more biomarkers that is representative of subjects that have survived for a certain time period after diagnosis.
  • the control represents subjects with breast cancer who are still alive 3-months, 6-months, 1 , 2, 3, 4, 5, 6, 7, 8, 9, or 10 years after diagnosis with breast cancer.
  • the control represents subjects with breast cancer who did not survive 3-months, 6- months, 1 , 2, 3, 4, 5, 6, 7, 8, 9, or 10 years after diagnosis with breast cancer.
  • the control represents subjects with breast cancer who are not responsive to hormonal treatment.
  • the control represents subjects with breast cancer who are responsive to hormonal treatment.
  • the control is an age-matched control or matched for subjects of a particular breast cancer molecule subtype, such as subjects that Her2 or ER positive or negative.
  • control is a predetermined threshold derived from a plurality of subjects with known outcome, wherein a test subject with a level of a biomarker described herein above the threshold is identified as having increased likelihood of metastasis and/or decreased survival and/or increased responsiveness to a breast cancer hormone treatment.
  • all survival refers to the time from diagnosis to death from any cause.
  • disease free survival refers to the time from cancer diagnosis to any recurrence of cancer or death from any cause.
  • hormone treatment refers to the use of Tamoxifen, an aromatase inhibitor or other agent acting upon estrogen receptors, progesterone receptors or their signaling pathways for the treatment of cancer.
  • a subject who is "responsive to hormone treatment” refers to a subject with breast cancer for whom hormone treatment ameliorates or helps prevent recurrence of the disease relative to the absence of hormone treatment.
  • antibody as used herein is intended to include monoclonal antibodies, polyclonal antibodies, and chimeric antibodies.
  • the antibody may be from recombinant sources and/or produced in transgenic animals.
  • Antibodies can be fragmented using conventional techniques. For example, F(ab')2 fragments can be generated by treating the antibody with pepsin. The resulting F(ab')2 fragment can be treated to reduce disulfide bridges to produce Fab' fragments. Papain digestion can lead to the formation of Fab fragments.
  • Antibody fragments mean binding fragments.
  • Antibodies having specificity for a specific protein may be prepared by conventional methods.
  • a mammal e.g. a mouse, hamster, or rabbit
  • an immunogenic form of the peptide which elicits an antibody response in the mammal.
  • Techniques for conferring immunogenicity on a peptide include conjugation to carriers or other techniques well known in the art.
  • the peptide can be administered in the presence of adjuvant.
  • the progress of immunization can be monitored by detection of antibody titers in plasma or serum. Standard ELISA or other immunoassay procedures can be used with the immunogen as antigen to assess the levels of antibodies.
  • antisera can be obtained and, if desired, polyclonal antibodies isolated from the sera.
  • antibody producing cells can be harvested from an immunized animal and fused with myeloma cells by standard somatic cell fusion procedures thus immortalizing these cells and yielding hybridoma cells.
  • myeloma cells can be harvested from an immunized animal and fused with myeloma cells by standard somatic cell fusion procedures thus immortalizing these cells and yielding hybridoma cells.
  • somatic cell fusion procedures thus immortalizing these cells and yielding hybridoma cells.
  • Such techniques are well known in the art, (e.g. the hybridoma technique originally developed by Kohler and Milstein (Nature 256:495-497 (1975)) as well as other techniques such as the human B-cell hybridoma technique (Kozbor et al., Immunol.
  • Hybridoma cells can be screened immunochemically for production of antibodies specifically reactive with the peptide and the monoclonal antibodies can be isolated.
  • the present disclosure provides methods for providing a prognosis for a test subject having or suspected of having breast cancer.
  • breast cancer tissue and normal tissue samples from subjects with breast cancer were assigned to two groups based on axillary lymph node (LN) status.
  • Quantitative proteomic profiling using mass spectroscopy was then used to identify proteins that were differentially expressed between LN positive and LN negative cancer tissues or between cancer and normal samples.
  • the differential expression of the 49 proteins listed in Table 1 was confirmed using selected reaction monitoring mass spectroscopy (SRM-MS).
  • TMAs tissue microarrays
  • HMGN2, USP34, and G6PD were negatively correlated with lymph node status.
  • the expression of HSPB901 and DCN was then analyzed in an independent cohort of 967 breast cancer TMAs with the clinicopathological characteristics set out in Table 4.
  • levels of HSP90B1 and/or DCN were found to be useful for providing a prognosis for subjects with breast cancer, such as for predicting the likelihood of lymph node status, overall survival or disease free survival.
  • Levels of HSP90B1 and/or DCN were also found to be useful for identifying subjects with breast cancer who are responsive to hormone treatment.
  • the methods described herein include evaluating a test subject having or suspected of having breast cancer.
  • the method comprises:
  • the method comprises detecting an increased level of one or more biomarkers between the test sample and the control, the increased level providing an evaluation of the test subject.
  • the evaluation provides an indication of the subject's prognosis and/or response to treatment.
  • the prognosis may be an indication of one or more of metastasis such as lymph node metastasis, or survival time such as disease free survival.
  • the method comprises:
  • comparing the level of one or more biomarkers in the test sample with a control wherein a difference or similarity in the level of the one or more biomarkers between the test sample and the control is used to provide a prognosis for the test subject.
  • the one or more biomarkers are selected from HSP90B1 , Decorin (DCN), HMGN2, USP34 and G6PD.
  • the control represents subjects with breast cancer without metastasis and an increase in the level of HSP90B1 and/or DCN relative to the control is indicative of metastasis such as lymph node metastasis or distant metastasis in the test subject.
  • the control represents subjects with breast cancer without metastasis and a decrease in the level of HMGN2, USP34 and/or G6PD is indicative of metastasis such as lymph node metastasis or distant metastasis in the test subject.
  • the level of HSP90B1 , USP34 and/or HMGN2 are negatively associated with tumour grade.
  • one of the biomarkers is HSP90B1 and the level of HSP90B1 in the test sample used to provide a prognosis for the test subject.
  • one of the biomarkers is Decorin (DCN) and the level of DCN in the test sample is used to provide a prognosis for the test subject.
  • the biomarkers include both HSP90B1 and Decorin (DCN) and the levels of both HSP90B1 and Decorin in the test sample are used to provide a prognosis for the test subject.
  • HSP90B1 and/or DCN are prognostic biomarkers for the presence of metastasis in a test subject.
  • High levels of DCN expression were significantly associated with lymph node metastasis and high levels of HSP90B1 expression were significantly associated with distant metastasis.
  • the methods described herein include providing a prognosis with respect to the likelihood of metastasis in a test subject with cancer or suspected of having cancer.
  • the methods described herein involve comparing the level of one or more biomarkers in a test sample from a test subject with a control.
  • control represents a sample taken from a single subject or a plurality of subjects with breast cancer known to have metastasis, lymph node metastasis or distant metastasis.
  • control represents a sample taken from a single subject or a plurality of subjects with breast cancer who do not have metastasis, lymph node metastasis or distant metastasis.
  • control is a predetermined level or threshold associated with the presence or absence of a prognostic outcome in a population of subjects with breast cancer such as the presence of absence of metastasis, lymph node metastasis or distant metastasis.
  • the control represents subjects with breast cancer without metastasis and an increase in the level of HSP90B1 and/or DCN in the test sample relative to the control indicates an increased likelihood of metastasis in the test subject.
  • the control represents subjects with breast cancer without lymph node metastasis and an increase in the level of DCN in the test sample relative to the control indicates an increased likelihood of lymph node metastasis in the test subject.
  • the control represents subjects with breast cancer without distant metastasis and an increase in the level of HSP90B1 in the test sample relative to the control indicates an increased likelihood of distant metastasis in the test subject.
  • the control represents subjects with breast cancer with metastasis and a similarity in the level of HSP90B1 and/or DCN in the test sample relative to the control indicates metastasis in the test subject.
  • HSP90B1 and/or DCN are prognostic biomarkers for the survival of a test subject with breast cancer.
  • high levels of HSP90B1 and/or DCN are associated with lower overall survival and disease free survival in subjects with breast cancer relative to subjects with low levels of HSP90B1 and/or DCN. Accordingly, the methods described herein are useful for providing a prognosis related to overall survival or disease free survival for a test subject with breast cancer or suspected or having breast cancer.
  • the methods described herein include comparing the levels of HSP90B1 and/or DCN in a test sample to the levels in a control, wherein the control represents subjects with a known survival time such as overall survival or disease free survival.
  • the biomarker is DCN and the test subject has a luminal B tumour molecular subtype.
  • an increase in the level of HSP90B1 and/or DCN in the test sample relative to the control indicates a decreased overall survival (OS) relative to the control for the test subject.
  • OS overall survival
  • the control represents subjects who survived for at least 2 years, 5 years or 10 years from diagnosis with breast cancer, or any other suitable time period for which an association between the levels of the biomarkers and survival time is available.
  • the levels of one or more biomarkers described herein are used to predict the overall survival time of a test subject.
  • an increase in the level of HSP90B1 and/or DCN in the test sample relative to the control indicates a decreased disease- free survival (DFS) for the test subject.
  • the control represents subjects who survived for at least 2 years, 5 years or 10 years from diagnosis with breast cancer without recurrence of breast cancer, or another suitable time period for which an association between the levels of the biomarkers and disease free survival time is available.
  • the levels of one or more biomarkers described herein are used to predict the disease free survival time of a test subject.
  • the present disclosure includes methods for predicting the survival time of a test subject, such as the overall survival or disease free survival.
  • comparing the level of the one or more biomarkers in the test sample with a control includes estimating a survival time by statistical methods such as linear regression.
  • One aspect of the present disclosure includes determining the level of two or more of the biomarkers listed in Table 1 in a test sample and generating an expression profile for a test subject.
  • the methods described herein use multivariate statistical methods known to a skilled person for comparing the expression levels of two or more biomarkers in a test sample with the expression level of two or more biomarkers in a control.
  • a method comprising determining a level for two or more biomarkers in the test sample, generating a test sample expression profile based on the level of the two or more biomarkers and comparing the test sample expression profile to a control expression profile, wherein a difference or similarity in the test sample expression profile and the control expression profile is used to provide a prognosis for the test subject.
  • the two or more biomarkers include DCN and HSP90B1.
  • HSP90B1 and/or DCN are prognostic biomarkers for determining whether a test subject with breast cancer is responsive to hormone treatment. Test subjects with high levels of HSP90B1 and/or DCN were found to benefit significantly from hormone treatments. Accordingly, in one embodiment there is provided a method of selecting treatment for a test subject with breast cancer or suspected of having breast cancer. In one embodiment, the method comprises:
  • selecting a treatment for the test subject based on a difference or similarity in the level of HSP90B1 and/or DCN in the test sample compared to the control.
  • the method further comprises treating a test subject with an increase in the level of HSP90B1 and/or DCN relative to the control with hormone treatment.
  • the control represents subjects with breast cancer who are not responsive to hormone treatment and a test subject with an increase in the level of HSP90B1 and/or DCN in the test sample relative to the control is selected for hormone treatment.
  • the control represents subjects with breast cancer who are responsive to hormone treatment and a test subject with a similar level of HSP90B1 and/or DCN in the test sample relative to the control is selected for hormone treatment.
  • the methods described herein can be used to exclude subjects from hormone treatment.
  • the method comprises: determining a level of HSP90B1 and/or DCN in a test sample from the test subject,
  • test subject identifying the test subject as having an increased likelihood of being responsive to hormone treatment based on a difference or similarity in the level of HSP90B1 and/or DCN in the test sample compared to the control.
  • the method further comprises treating a subject identified as having an increased likelihood of being responsive to hormone treatment with hormone treatment.
  • the methods described herein include administering to a test subject identified as having an increased likelihood of being responsive to hormone treatment, a hormone treatment.
  • a method of treating a subject with breast cancer comprising:
  • test subject identifying the test subject as having an increased likelihood of being responsive to hormone treatment based on a difference or similarity in the level of HSP90B1 and/or DCN in the test sample compared to the control, and treating a test subject identified as having an increased likelihood of being responsive to hormone treatment with hormone treatment.
  • hormone therapy for treating breast cancer in a subject wherein the level of HSP90B1 and/or DCN in a test sample from the subject is increased relative to a control level.
  • hormone therapy for treating a breast cancer with an increased level of HSP90B1 and/or DCN relative to a control is also provided.
  • the control level represents a level of HSP90B1 and/or DCN in subjects with breast cancer who are not responsive to hormone treatment.
  • Other embodiments include the use of control levels as described herein that are representative of cancers with a known subtype or treatment outcome.
  • the use is for treating breast cancer in a subject with metastasis, optionally lymph node metastasis or distant metastasis.
  • the hormone treatment comprises Tamoxifen, an aromatase inhibitor or other agent acting upon estrogen receptors, progesterone receptors or their signaling pathways
  • control represents subjects with breast cancer who are not responsive to hormone treatment and an increase in the level of HSP90B1 and/or DCN in the test sample relative to the control indicates that the test subject has an increased likelihood of being responsive to hormone treatment.
  • methods described herein can be used to identify a subject who is not responsive to hormone treatment.
  • the control represents subjects with breast cancer who are not responsive to hormone treatment.
  • hormone treatments for subjects with breast cancer include, but are not limited to, Tamoxifen, an aromatase inhibitor or other agent acting upon estrogen receptors, progesterone receptors or their signaling pathways.
  • the methods and/or uses described herein optionally include obtaining a test sample from the test subject prior to determining a level of one or more of the biomarkers listed in Table 1 as described herein.
  • the test sample comprises malignant epithelial cells.
  • the test sample comprises stromal cells and a high level of DCN expression in the stroma is indicative of lower tumor grade.
  • the test sample is a fresh tissue sample or a frozen tissue sample.
  • the test sample is a fixed tissue sample.
  • the test sample is a formalin-fixed, paraffin embedded (FFPE) sample.
  • FFPE formalin-fixed, paraffin embedded
  • the test sample is fresh tumour tissue, snap frozen tumour tissue or a fine needle aspirate of a tumour.
  • the test sample is processed prior to detecting the biomarker level.
  • a sample may be fractionated (e.g. by centrifugation or using a column for size exclusion), concentrated or proteolytically processed such as trypsinized, depending on the method of determining the level of biomarker employed.
  • the methods and/or uses described herein involve determining the level of one or more biomarkers in a test sample.
  • the level of the biomarker is a protein level or polypeptide level.
  • the level of the biomarker is a level of a nucleic acid encoding for the biomarker such as an mRNA or cDNA.
  • the biomarker is a protein, polypeptide, or fragment thereof and the level of the biomarker is determined by mass spectroscopy, immunohistochemistry, or an immunoassay such as an enzyme-linked immunosorbant assay (ELISA).
  • the biomarker is a protein and the level of the biomarker in the test sample is determined by contacting the sample with a detection agent, for example an antibody, such as a monoclonal antibody or antibody fragment, wherein the detection agent forms a complex with the biomarker.
  • the detection agent comprises an antibody selected from Table 2b.
  • the detection agent comprises a commercially available antibody for HSP90B1 or DCN such as HPA003901 or HPA003315 respectively, available from Sigma-Aldrich, St. Louis, MO.
  • the biomarker is a nucleic acid encoding for a protein or polypeptide listed in Table 1 , such as an mRNA or cDNA.
  • the level of an mRNA encoding for a biomarker is determined by quantitative PCR such as RT-PCR, serial analysis of gene expression (SAGE), use of a microarray, digital molecular barcoding technology or Northern blot.
  • the step of determining the biomarker level comprises using immunohistochemistry and/or an immunoassay.
  • the immunoassay is an ELISA.
  • the ELISA is a sandwich type ELISA.
  • the level of two or more markers can be determined for example using mass spectrometry-based methods such as single or multiple reaction monitoring assays.
  • An example of such an assay is the "Product-ion monitoring" PIM assay.
  • This method is a hybrid assay wherein an antibody for a biomarker is used to extract and purify the biomarker from a sample e.g. a biological fluid, the biomarker is then trypsinized in a microtitre well and a proteolytic peptide is monitored with a triple-quadrapole mass spectrometer, during peptide fragmentation in the collision cell.
  • antibodies or antibody fragments are used to determine the level of polypeptide of one or more biomarkers of the disclosure.
  • the antibody or antibody fragment is labeled with a detectable marker.
  • the antibody or antibody fragment is, or is derived from, a monoclonal antibody.
  • a person skilled in the art will be familiar with the procedure for determining the level of a biomarker by using said antibodies or antibody fragments, for example, by contacting the sample from the subject with an antibody or antibody fragment labeled with a detectable marker, wherein said antibody or antibody fragment forms a complex with the biomarker.
  • the label is preferably capable of producing, either directly or indirectly, a detectable signal.
  • the label may be radio-opaque or a radioisotope, such as 3 H, 1 C, 32 P, 35 S, 23 l, 125 l, 131 1; a fluorescent (fluorophore) or chemiluminescent (chromophore) compound, such as fluorescein isothiocyanate, rhodamine or luciferin; an enzyme, such as alkaline phosphatase, beta-galactosidase or horseradish peroxidase; an imaging agent; or a metal ion.
  • a radioisotope such as 3 H, 1 C, 32 P, 35 S, 23 l, 125 l, 131 1
  • a fluorescent (fluorophore) or chemiluminescent (chromophore) compound such as fluorescein isothiocyanate, rhodamine or luciferin
  • an enzyme
  • the level of biomarker of the disclosure is detectable indirectly.
  • a secondary antibody that is specific for a primary antibody that is in turn specific for a biomarker of the disclosure wherein the secondary antibody contains a detectable label can be used to detect the target polypeptide biomarker.
  • the level of the biomarker is normalized to an internal control.
  • the level of a biomarker may be normalized to an internal normalization control such as a polypeptide that is present in the sample type being assayed, for example a house keeping gene protein, such as beta- actin, glyceraldehyde-3-phosphate dehydrogenase, or beta-tubulin, or total protein, e.g. any level which is relatively constant between subjects for a given volume.
  • compositions and/or kits that include two or more agents for detecting a biomarker listed in Table 1.
  • composition that includes at least two biomarker specific detection agents, each of which specifically binds a biomarker selected from Table 1.
  • the composition includes biomarker-specific detection agents for HSP90B1 and DCN.
  • the composition includes a suitable carrier, diluent or additive as are known in the art.
  • the suitable carrier can be a protein such as BSA.
  • kits for detecting two or more of the biomarkers listed in Table 1 are provided.
  • the kit is useful for practicing a method as described herein, such as for providing a prognosis for a test subject having or suspected of having breast cancer.
  • the kit includes at least two biomarker-specific detections agents, each of which binds a biomarker selected from Table 1 , preferably selected from HSP90B1 and DCN.
  • the kit includes instructions for use, such as instructions for performing one of the methods described herein.
  • the kit includes at least one standard and/or control.
  • the kit includes a control representing tissue from one or more subjects with breast cancer who do not have metastasis.
  • the kit includes a quantity of a purified standard, such as a known quantity of a biomarker polypeptide.
  • a purified standard such as a known quantity of a biomarker polypeptide.
  • the kit includes biomarker specific detection agents for HSP90B1 and DCN.
  • the kit can include ancillary agents such as vessels for storing or transporting the detection agents and/or buffers or stabilizers.
  • the biomarker specific detection agents bind to a protein, polypeptide, or fragment thereof of one of the biomarkers listed in Table 1.
  • the biomarker specific detection agents are antibodies, optionally one or more of the antibodies listed in Table 2b.
  • the biomarker specific detection agents bind to a nucleic acid encoding for one or more of the biomarkers listed in Table 1.
  • the biomarker-specific detection agent is a nucleic acid such as a primer, that hybridizes to a nucleic acid encoding for one or more of the biomarkers listed in Table 1 .
  • the biomarker-specific detection agent is a primer suitable for T-PCR or quantitative RT-PCR.
  • the biomarker specific detection agent further comprises a detectable label.
  • the label is preferably capable of producing, either directly or indirectly, a detectable signal.
  • the label may be radio-opaque or a radioisotope, such as 3 H, 14 C, 32 P, 35 S, 23 l, 2 l, 131 1; a fluorescent (fluorophore) or chemiluminescent (chromophore) compound, such as fluorescein isothiocyanate, rhodamine or luciferin; an enzyme, such as alkaline phosphatase, beta-galactosidase or horseradish peroxidase; an imaging agent; or a metal ion.
  • Breast cancer is the most common malignancy among women worldwide in terms of incidence and mortality. About 10% of North American women will be diagnosed with breast cancer during their lifetime and 20% of those will die of the disease. Breast cancer is a heterogeneous disease and biomarkers able to correctly classify patients into prognostic groups are needed to better tailor treatment options and improve outcomes.
  • One powerful method used for biomarker discovery is sample screening with mass spectrometry, as it allows direct comparison of protein expression between normal and pathological states.
  • the present Example describes the use of a systematic and objective method to identify biomarkers with possible prognostic value in breast cancer patients, particularly in identifying cases most likely to have lymph node metastasis and to validate their prognostic ability using breast cancer tissue microarrays.
  • HSP90B1 endoplasmin
  • DCN decorin
  • HSP90B1 prognostic and predictive markers
  • Example 2 Further details are explained in Example 2.
  • tumour tissue samples from nineteen breast cancer patients (estrogen receptor (ER) positive and HER2 receptor negative) were identified and collected from the UHN BioBank. Normal samples from tissues adjacent to the tumour were collected from thirteen of nineteen patients. Cancer tissues were assigned to two groups based on axillary LN status and the thirteen normal tissue samples were used as controls for protein quantification.
  • Trypsin digested and labeled samples were randomly assigned to six 4-plex iTRAQ sets for LC-MS/MS analysis, with each set consisting of the universal control and three tumour samples (either two LN-negative samples and one LN-positive sample or vice versa).
  • Stable isotope dilution (SID) experiments were performed using spike-ins of six isotope-enriched peptides in all tissue samples and analysis by selected reaction monitoring mass spectrometry (SRM-MS).
  • Peptides were obtained from Biomatik Corporation (Canada) for HSP90B1 (P14625), 40S ribosomal protein S25 (P62851 ), hemoglobin subunit alpha (P69905) and alpha actin cardiac muscle 1 (P68032), additional peptides were obtained from Thermo Scientific (USA) for GTP binding nuclear protein RAN (P62826) and 14-3-3 protein zeta/delta (P63104).
  • An information dependant data acquisition experiment was carried out with the following parameters: 250 or 500 millisecond TOF MS scan of m/z 400 to m/z 1500, MS/MS triggered on ions greater than m/z 400 and less than m/z 1500 with charge state 2 to 4 that exceeded 50 counts, former precursors excluded for 180 seconds, one survey scan and three MS/MS scans per cycle, 50 mDa mass tolerance, automatic collision energy and automatic MS/MS accumulation with a maximum accumulation of 2 seconds and a fragment intensity multiplier of 2.
  • the second quadrupole (Q2) was manually set up with parameters optimal for sequencing and iTRAQ quantification. Data acquisition was conducted using Analyst QS 2.0 software (AB SCIEX, USA). Analysis of iTRAQ Dataset
  • Protein identification and-relative quantification analyses were conducted on iTRAQ data using ProteinPilot 2.01 software (AB SCIEX, USA) based on the Paragon algorithm [21], using the following parameters: 4-plex iTRAQ, MMTS (Cys alkylation), trypsin, post-translational modifications including multiple phosphorylations, glycosylation, and other post-translational modifications due to sample processing; 66% minimum identification confidence score.
  • Absolute fold-changes (AFC) were derived for each protein in each of the iTRAQ sets for 3 comparisons: LN negative vs LN positive; LN negative vs normal and LN positive vs normal. Requirements for putative differential expression were: LN negative vs LN positive AFC ⁇ 1.5 (1 13 proteins); or AFC ⁇ 1.5 in any two comparisons ( 189 proteins); or AFC > 3.0 in any one comparison (12 proteins).
  • Tissue microarrays were constructed at UHN from samples obtained from primary breast cancer patients admitted to Princess Margaret Hospital between January and December of 2006.
  • FFPE paraffin embedded
  • Tissue sections were dewaxed in five changes of xylene and brought down to water through graded alcohols.
  • Tissue sections were microwaved in Tris-EDTA Buffer (pH 9.0) for antigen retrieval.
  • HSP90B1 HPA003901 - Sigma-Aldrich, St. Louis, MO
  • Ki-67 SP6, LabVision, Fremont, CA
  • ER SP1 , LabVision
  • HER2 4B5, Ventana, Arlington, AZ
  • Tissue microarray IHC staining was evaluated under light microscopy and with software-based image analysis (Aperio Technologies, Vista, CA,). Decorin staining intensity was assessed in both normal stromal cells and cancer epithelial cells separately under light microscopy, HSP90B1 staining was scored in the invasive cancer only. The average staining intensity of DCN (Decorinjavg) and HSP90B1 (HSP90B1_lavg) was quantified using Aperio image analysis.
  • TMAs were analyzed blindly and independently by two pathologists (DTT and JM) using a four point semiquantitative scale for intensity: 3+ (very strong), 2+ (strong), 1 + (moderate / weak), and 0 (no staining) ( Figure 1 ). In case of disagreement cores were reviewed together and consensus was reached. TMAs were scanned at 20x and the ImageScope Positive Pixel Count algorithm version 9.1 used for software-based analysis on the entire core. An average intensity of positive pixels is calculated by the software generating a continuous variable of intensity scores in which higher scores (pixel colour closer to white) mean lower staining intensity.
  • Luminal A ER-positive, HER2-negative and low Ki67
  • luminal B ER-positive, HER2-positive and/or high Ki67
  • HER2 ER-negative and HER2-positive
  • basal-like ER-negative and HER2-negative
  • Quantitative proteomic profiling using iTRAQ-labelling identified 988 proteins of which a subset of 477 were determined to be differentially expressed between LN positive and LN negative cancer tissues or between cancer and normal tissues based on a minimum absolute fold-change of 1.5 (Figure 2). Differential expression was verified by targeted quantification using label-free and SID SRM-MS [1 1 ] on breast tumour tissue. Over 70% of the significant proteins identified by iTRAQ-MS were detected by label-free SRM- MS, and differential expression of 49 proteins was confirmed (18 p ⁇ 0.05 and 31 0.05 ⁇ p ⁇ 0.10), of which 23 displayed increased expression and, 26 displayed decreased expression in LN positive tissues (Table 1 ).
  • TMA tissue microarray
  • HSP90B1 , HMGN2, USP34, DCN and G6PD Five candidates (HSP90B1 , HMGN2, USP34, DCN and G6PD) showed a tentative association with LN status. HSP90B1 and DCN were positively correlated and USP34, G6PD and HMGN2 were negatively correlated with axillary LN status.
  • HSP90B1 and DCN play important roles in several biological pathways related to tumorigenesis.
  • Decorin is a key modulator of the tumour microenvironment [27] through interactions with EGFR and MAPK [28] pathways.
  • Decorin also activates insulin-like growth factor-l receptor [29], attenuates Erb2 signalling [30], binds to TGF-Beta, activates Met and up- regulates p21 [31][32]. While in most studies DCN has been found to have an antioncogenic role, others correlate DCN with increased migration of human osteosarcoma cells [33] and high expression in endothelial cells undergoing angiogenesis [34].
  • HSP90B1 is a heat shock chaperone protein that stabilizes and refolds denatured proteins after stress, facilitating cell survival during conditions commonly seen in the tumour microenvironment [33].
  • HSP90 proteins are involved in the glucocorticoid receptor and the AKT signalling pathways [35][36], through these interactions they increase glucose metabolism, cell proliferation, transcription and cell migration and decreased apoptosis.
  • HSP90 proteins have been found increased in metastatic melanoma compared to the primary [37] and high HSP90 expression predicts worse OS in patients with acute lymphocytic leukemia [38] and breast cancer [39], and decreased DFS in gastrointestinal stromal tumours [40].
  • phase II and III trials are evaluating the anticancer activity of HSP90 inhibitors in several types of cancer.
  • Described herein is the verification of iTRAQ-based discoveries using quantitative SRM-MS in fresh frozen tissue, as well as preliminary validation of two markers using another analytical technology (i.e. IHC), a different sample preparation (FFPE), and two independent sample populations.
  • IHC analytical technology
  • FFPE sample preparation
  • 10 had commercially available antibodies suitable for use on FFPE tissue.
  • 5 of the 10 antibodies showed statistically significant correlation with LN status when protein expression was analyzed by IHC in an independent cohort of 39 patients (UHN).
  • UHN independent cohort of 39 patients
  • HSP90B1 and DCN remained statistically significant.
  • This Example presents the proteomics' discovery results and their correlation with IHC focusing on their prognostic capability. Using an inexpensive and ubiquitous technique such as IHC, it was possible to corroborate that both groups (LN positive vs. LN negative breast cancers) have significant differences in respect to these two proteins, and that these differences are associated with decreased overall survival.
  • HSP90B1 Epithelium Low 1.00 ⁇ 0.0001 1.00 ⁇ 0.0001
  • Endocytosis of the dermatan sulfate proteoglycan decorin utilizes multiple pathways and is modulated by epidermal growth factor receptor signaling.
  • Fiedler LR Eble JA (2009) Decorin regulates endothelial cell-matrix interactions during angiogenesis.
  • Binding of hsp90 to the glucocorticoid receptor requires a specific 7-amino acid sequence at the amino terminus of the hormone-binding domain. J. Biol. Chem 273: 13918-13924.
  • Hacihanefioglu A Gonullu E, Mehtap O, Keski H, Yavuz M, et al. (2010) Effect of heat shock protein-90 (HSP90) and vascular endothelial growth factor (VEGF) on survival in acute lymphoblastic leukemia: an

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Abstract

L'invention concerne une méthode pour fournir un pronostic pour un sujet ayant ou étant susceptible d'avoir un cancer du sein, par la détermination du taux d'un ou plusieurs biomarqueurs dans un échantillon d'essai. Une différence ou une similarité du taux d'un ou plusieurs biomarqueurs dans l'échantillon d'essai avec un témoin est utilisée pour fournir un pronostic pour le sujet d'essai. L'invention concerne également des méthodes d'identification d'un sujet atteint d'un cancer du sein qui est sensible à un traitement hormonal. Eventuellement, les biomarqueurs comprennent la Décorine (DCN) et/ou l'Endoplasmine (HSP90B1). L'invention concerne également des trousses et des compositions qui comprennent des agents de détection spécifiques d'un biomarqueur, utiles pour la mise en œuvre des méthodes de la présente invention.
PCT/CA2013/000042 2012-01-19 2013-01-18 Biomarqueurs pour le pronostic et le traitement du cancer du sein WO2013106913A1 (fr)

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