WO2005071419A2 - Etablissement de profils d'expression de proteines et prognose du cancer du sein - Google Patents

Etablissement de profils d'expression de proteines et prognose du cancer du sein Download PDF

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WO2005071419A2
WO2005071419A2 PCT/IB2005/000261 IB2005000261W WO2005071419A2 WO 2005071419 A2 WO2005071419 A2 WO 2005071419A2 IB 2005000261 W IB2005000261 W IB 2005000261W WO 2005071419 A2 WO2005071419 A2 WO 2005071419A2
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protein
breast
proteins
cytokeratin
expression
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PCT/IB2005/000261
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WO2005071419A3 (fr
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Jocelyne Jacquemier
François BERTUCCI
Daniel Birnbaum
Stéphane DEBONO
Rebecca Tagett
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Ipsogen
Institut National De La Sante Et De La Recherche Medicale (Inserm)
Institut Paoli-Calmettes
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Publication of WO2005071419A2 publication Critical patent/WO2005071419A2/fr
Publication of WO2005071419A3 publication Critical patent/WO2005071419A3/fr

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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
    • G01N33/57407—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
    • 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
    • G01N2333/46—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from vertebrates
    • G01N2333/47—Assays involving proteins of known structure or function as defined in the subgroups
    • G01N2333/4701—Details
    • G01N2333/4739—Cyclin; Prad 1
    • 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
    • G01N2333/46—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from vertebrates
    • G01N2333/47—Assays involving proteins of known structure or function as defined in the subgroups
    • G01N2333/4701—Details
    • G01N2333/4742—Keratin; Cytokeratin
    • 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
    • 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
    • G01N2333/70567—Nuclear receptors, e.g. retinoic acid receptor [RAR], RXR, nuclear orphan receptors
    • 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
    • G01N2333/71—Assays involving receptors, cell surface antigens or cell surface determinants for growth factors; for growth regulators
    • 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
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/914—Hydrolases (3)
    • G01N2333/948—Hydrolases (3) acting on peptide bonds (3.4)
    • G01N2333/95—Proteinases, i.e. endopeptidases (3.4.21-3.4.99)
    • G01N2333/964—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue
    • G01N2333/96425—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals
    • G01N2333/96427—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general
    • G01N2333/9643—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general with EC number
    • G01N2333/96466—Cysteine endopeptidases (3.4.22)

Definitions

  • the present invention relates to protein analysis and, in particular, to protein expression profiling of breast tumors and cancers.
  • Adjuvant systemic therapy has a favorable impact on survival in patients with early breast cancer. 1 ' 2
  • the decision to give or withhold such therapy is based upon a series of histoclinical prognostic criteria reviewed in consensus conferences (i.e. National Institute Health NIH and St-Gallen) . 3 ' 4
  • the heterogeneity of breast tumors remains poorly understood.
  • clinical treatment decisions on whether to treat patients with node-negative breast cancer by surgery and radiotherapy alone, or in combination with adjuvant chemotherapy are currently being made with scant information on patient risk for metastatic relapse. Additionally, identifying among the patients who receive chemotherapy those who will benefit and those who will not benefit from standard anthracyclin-based protocols remains elusive.
  • DNA arrays have recently significantly contributed to enhance understanding of the molecular complexity of breast cancer. 6
  • Several studies have demonstrated the potential clinical utility of gene expression signatures defined by the combined RNA expression of a few tens of genes. These signatures have lead to the development of a new molecular taxonomy of disease, including the identification of previously indistinguishable prognostic subclasses . 7_15
  • the clinical impact of these tests on disease management must be subsequently evaluated in large retrospective and prospective studies of adequate statistical power on fully annotated patient samples, followed by the development of gene expression-based diagnostics adapted to the clinical setting.
  • Unfortunately the cost, technical complexity, and interpretation of DNA microarray technology still complicate investigation with cancer specimens and are currently unsuitable for routine use in the standard clinical setting.
  • TMA tissue microarray
  • the aim of the present invention is to provide means capable of analyzing histopathologic features of breast disease, in particular of classifying breast cancers into prognostically relevant subclasses.
  • the present invention provides a protein expression signature identified by protein expression profiling and which may be used for analysing histopathologic features of breast disease as well as methods for carrying out such analysis.
  • protein expression profiling may be a clinically useful approach to assess breast cancer heterogeneity and prognosis in patients with stage I, II, or III disease.
  • the invention provides in one aspect a method for analyzing differential protein expression associated with histopathologic features of breast disease, in particular breast tumours, e.g., breast carcinomas, comprising the detection of the overexpression or underexpression of a pool of proteins in breast tissues or cells, said pool comprising all or part of a protein set comprising Afadin, Aurora A, a-Catenin, b-Catenin, BCL2, Cyclin Dl, Cyclin E, Cytokeratin 5/6, Cytokeratin 8/18, E-Cadherin, EGFR, ERBB2 , ERBB3, ERBB4, Estrogen receptor, FGFRl, FHIT, GATA3 , Ki67, Mucin 1, P53, P-Cadherin, Progesterone receptor, TACC1, TACC2, TACC3.
  • Cytokeratin 5/6 is meant Cytokeratin 5 and/or Cytokeratin 6. The same is applicable to “Cytokeratin 8/18".
  • the following table displays the proteins of the present invention and their corresponding amino- acid sequences (SEQ ID NO. 1 to 52). These proteins are identified by their common names (first column) in the methods, libraries, sets, pools etc. of the invention. Other names in the literature which designate the same proteins (alias, synonyms etc.)are covered as well, and are incorporated herein by reference.
  • the present invention may also define these proteins by their amino-acid ( polypeptidic ) sequences (SEQ ID NO. ) , or portions or modifications thereof in accordance with the definition of "protein” provided below.
  • Table 0 lists the proteins of the present invention and their corresponding amino- acid sequences (SEQ ID NO. 1 to 52). These proteins are identified by their common names (first column) in the methods, libraries, sets, pools etc. of the invention. Other names in the literature which designate the same proteins (alias, synonyms etc.)are covered as well, and are incorporated herein by reference.
  • the present invention may also define these proteins by their amino-acid ( polypeptidic
  • the invention provides a method for analyzing for analyzing differential protein expression associated with histopathologic features of breast disease comprising the detection of the overexpression or underexpression of a pool of protein in breast tissues comprising a protein set comprising: Aurora A, a-Catenin, b-Catenin, Cyclin Dl, Cytokeratin 8/18, ERBB2, ERBB3 , Estrogen receptor, FGFRl, Ki67, Mucin 1, P53, P-Cadherin, Progesterone receptor, TACC2.
  • the invention provides a method for analyzing differential protein expression associated with histopathologic features of breast disease comprising the detection of the overexpression or underexpression of a pool of protein in breast tissues comprising a protein set comprising: Afadin, Aurora A, a-Catenin, BCL2 , Cyclin Dl,
  • ERBB2 ERBB2, ERBB3, ERBB4, Estrogen receptor, FGFRl, FHIT,
  • Ki67 Mucin 1, P53, P-Cadherin, Progesterone receptor, TACC2, TACC3.
  • the pool of protein comprises a protein set comprising Afadin, Aurora A, a-Catenin, b-Catenin, BCL2 , Cyclin Dl, Cyclin E, Cytokeratin 5/6, Cytokeratin 8/18, E-Cadherin, EGFR, ERBB2, ERBB3, ERBB4, Estrogen receptor, FGFRl, FHIT, GATA3 , Ki67, Mucin 1, P53, P-Cadherin, Progesterone receptor, TACC1, TACC2, TACC3.
  • the pool of protein comprises a protein set comprising all proteins of the Table 0 above.
  • the method further comprises at least one of the following embodiments : - the detection of overexpression of at least one, preferably at least two, three or all of the following proteins : EGFR, P53, Ki67, FGFRl, ERBB2 , ERBB3 , ERBB4 , Cyclin Dl, Cyclin E, Cytokeratin 5/6.
  • Estrogen Receptor FHIT, GATA3 , Mucin 1, P- Cadherin, Progesterone receptor, TACC1, TACC2, TACC3, Afadin, Aurora A, ⁇ -Catenin, ⁇ - Catenin,BCL2, Cytokeratin 8/18, E-Cadherin.
  • a further object of the invention is to provide a protein library useful for the molecular characterization of histopathologic features of breast disease comprising or corresponding to a pool of protein sequences, over or under expressed, in breast tissue or cells, said pool corresponding to the protein sets previously described.
  • said protein librairies may be immobilized on a solid support which may be preferably selected from the group comprising nylon membrane, nitrocellulose membrane, polyvinylidene difluoride, glass slide, glass beads, polystyrene plates, membranes on glass support, silicon chip or gold chip.
  • a solid support which may be preferably selected from the group comprising nylon membrane, nitrocellulose membrane, polyvinylidene difluoride, glass slide, glass beads, polystyrene plates, membranes on glass support, silicon chip or gold chip.
  • the present invention provides a method for analyzing differential protein expression associated with histopathologic features of breast disease comprising the detection of the overexpression or underexpression of a pool of protein in breast tissues comprising : a) obtaining breast tissue cells from a patient, and b) measuring in the tissue cells obtained in step (a) over or underexpression of proteins of a library as previously described.
  • the detection of over or under expression of the pool of protein may be carried out on breast tumor cell lines.
  • the proteins may be directly or indirectly labeled before reaction step (b) with a label which may be selected from the group comprising radioactive, colorimetric , enzymatic, molecular amplification, bioluminescent or fluorescent labels.
  • one or more specific label are used for each protein of the library according to the invention.
  • a person skilled the art will be able to choose appropriate labels and labelling methods to carry out the invention.
  • the measuring of over or under expression of proteins may be carried out on cell or tissue, frozen or embedded in any appropriate material, e.g., paraffin, e.g. tissue microarray.
  • any appropriate material e.g., paraffin, e.g. tissue microarray.
  • Various known method of the prior art may be used as, e.g., ImmunoHistoChemistry (IHC) technologies.
  • the measuring of over or under expression of proteins may be also be carried out by the use of, e.g., protein (micro)arrays, antibody (micro) arrays, antigen (micro) arrays or any other appropriate technology, e.g., by using the previously defined supports .
  • the method for analysing differential protein expression of the invention further comprises: a) obtaining a control sample b) measuring in the control sample obtained in step (a) expression level of each protein corresponding to library according to the invention c) comparing expression level of each protein with the level of equivalent protein in breast tissue cells from a patient, or in cell lines.
  • the present invention is useful for detecting, diagnosing, staging, monitoring, predicting, preventing conditions associated with breast cancer. It is particularly useful for predicting clinical outcome of breast cancer and/or predicting occurrence of metastatic relapse and/or determining the stage or aggressiveness of a breast disease in at least 50%, e.g., at least 55%, e.g., at least 60%, e.g., at least 65%, e.g., at least 70%, e.g., at least 75%, e.g., at least 80%, e.g., at least 85%, e.g., at least 90%, e.g., at least 95%, e.g., 100% of the patients.
  • the invention is also useful for selecting more appropriate doses and/or schedule of chemotherapeutics and/or biopharmaceuticals and/or radiation therapy to circumvent toxicities in a patient.
  • the invention is also useful for selecting appropriate doses and/or schedule of chemotherapeutics and/or (bio)pharmaceuticals , and/or targeted agents, among which one may cite Aromatase Inhibitors (e.g., Exomestane, Anastrazole, Letrozole), Anti-estrogens (e.g., Fluvestrant, Tamoxifen), Taxanes (e.g., PacliTaxol, Docetaxel), Antracyclines (e.g., Doxurubicin, Cyclophosphamide) , CHOP (Doxurubicin, Cyclophosphamide, ocovorin, prednisone when taken in combination).
  • Aromatase Inhibitors e.g., Exomestane, Anastrazole, Letrozole
  • Anti-estrogens e.g., Fluvestrant, Tamoxifen
  • Taxanes e.g., PacliTaxol, Docetaxel
  • Iressa gefitnib, ZD1839, anti-EGFR, PDGFR, c-kit, Astra-
  • GRH Novartis
  • PD-183805 RTK inhibitor, Pfizer
  • EMD72000 (anti-EGFR/VEGF ab, MerckKgaA) ; CI-1033 (HER2/neu & EGF-R dual inhibitor, Pfizer); EGF10004;
  • anti-breast cancer agents are described by Awada et al. in "The pipeline of new anticancer agents for breast cancer treatment in 2003" Critical Reviews in Oncology/Hematology 48 (2003) 45-63, the content of which is incorporated herein by reference.
  • breast tissue cell may be obtained from a patient regardless of whether said patient has received or not a neo-adjuvant or adjuvant, e.g., systemic, therapy.
  • a neo-adjuvant or adjuvant e.g., systemic, therapy.
  • treated or untreated cell lines may be used.
  • breast tissue cell may be obtained from a patient regardless of ER receptor expression.
  • the present invention provides a method for treating a patient with a breast cancer comprising (i) the implementation of a method for analysing differential protein expression according to the invention on a sample from said patient, and (ii) determining a treatment for this patient based on the analysis of differential protein expression profile obtained in step i).
  • the present invention relates to a method for analyzing differential protein expression associated with histopathologic features of breast disease according to the invention wherein the detection of the overexpression or underexpression of said pool of protein in breast tissues comprises the detection of the overexpression or underexpression of nucleic acids coding for said proteins.
  • the present invention further relates to a nucleic acids library useful for the molecular characterization of histopathologic features of breast disease comprising nucelic acids coding for the over or underexpressed proteins according to the invention, or equivalent thereof.
  • the sequences of the nucleic acids of the library according to the invention are easily available for a person skilled in the art that may, for example, use printed publications describing said sequences and/or public databases, e.g., the National Center for Biotechnological Information (NCBI) database, that provide such sequences as well.
  • NCBI National Center for Biotechnological Information
  • aggressiveness of cancer refers to cancer growth rate or potential to metastasise; a so-called “aggressive cancer” will grow or metastasise rapidly or significantly affect overall health status and quality of life
  • adjuvant therapy refers to treatment involving radiation, chemotherapy (drug treatment), biologic therapy (vaccines) or hormone therapy, or any combination given after primary treatment.
  • antibody is intended to include whole antibodies, e.g., of any isotype, and includes fragments thereof which are also specifically reactive with a vertebrate, e.g., mammalian, protein. Antibodies can be fragmented using conventional techniques and the fragments screened for utility in the same manner as described above for whole antibodies. Thus, the term includes segments generated by proteolyticcleavage or prepared recombinant portions of an antibody molecule capable of selectively reacting with a certain protein.
  • Non-limiting examples of such proteolytic and/or recombinant fragments include Fab, F(ab')2, Fab 1 , Fv, and single chain antibodies (scFv) containing a V[L] and/or V[H] domain joined by a peptide linker.
  • the scFv's may be covalently or non-covalently linked to form antibodies having two or more binding sites.
  • Antibodies may include polyclonal, monoclonal, or other purified preparations of antibodies and recombinant antibodies.
  • associated with refers to a disease in a subject which is caused by, contributed to by, or causative of an abnormal level of expression of a protein.
  • control comprises for example proteins from a sample of the same patient or from a pool of different patients, or selected among reference proteins which may be already known to be over or under expressed.
  • the expression level of said control can be an average or an absolute value of the expression of reference proteins. These values may be processed in order to accentuate the difference relative to the expression of the proteins according to the invention.
  • the analysis of the over or under expression of proteins can be carried out on sample such as biological material derived from any mammalian cells, including cell lines, xenografts, human tissues preferably breast tissue, etc.
  • the method according to the invention may be performed on sample from a, e.g., cell lines, healthy donors, patients or an animal (for example for veterinary application or preclinical studies).
  • directly or indirectly labeled include proteins the sub-constituants of which, i.e., amino acids or amino acid groups or atoms, are themselves labeled (directly), as well as proteins labeled by the intermediate of any element able to recognize and bind to the targeted protein, e.g., an antibody.
  • Equivalent includes nucleic acids encoding functionally equivalent proteins.
  • Equivalent nucleotide sequences will include sequences that differ by one or more nucleotide substitutions, additions or deletions, such as allelic variants; and will, therefore, include sequences that differ from the nucleotide sequence of the nucleic acids of the invention because of the degeneracy of the genetic code.
  • good-prognosis and “poor-prognosis” respectively refer to favorable (e.g., remission) or unfavorable (e.g., metastasis, death) patient clinical outcome.
  • histopathologic features of breast diseases includes diseases, disorders or conditions known as, lethaly or not, affecting breast cells and/or tissues, including but not limited to breast tumours, for example i) non cancerous breast diseases, for example, hyperplasias , metaplasias, fibroadenomas , fibrocystic disease, papillomas, sclerosing adenosis or preneoplastic, or ii) breast cancer.
  • breast cancer As “breast cancer” one may cite : A) noninvasive breast cancers including i) ductal carcinoma in situ (also called intraductal carcinoma or DCIS), consisting of cancer cells in the lining of the duct ii) Lobular carcinoma in situ, or LCIS (also known as lobular neoplasia); B) Invasive cancer occurring when cancer cells spread beyond the basement membrane which covers the underlying connective tissue in the breast, and which include i) Infiltrating ductal carcinoma that penetrates the wall of a duct and ii) Infiltrating lobular carcinoma which spread through the wall of a lobule and may sometimes appear in both breasts, sometimes in several separate locations.
  • ductal carcinoma in situ also called intraductal carcinoma or DCIS
  • LCIS also known as lobular neoplasia
  • B) Invasive cancer occurring when cancer cells spread beyond the basement membrane which covers the underlying connective tissue in the breast and which include i) Infiltrating ductal carcinoma that penetrate
  • ImmunoHistoChemistry refers to methods using histochemical localization of immunoreactive substances using antibodies as reagents on cells or tissues by technologies such as, but not limited to flow cytometry, ELISA, Western and Southwestern Blot Analysis, and frozen and paraffin-embedded samples.
  • Nucleic acids refers to polynucleotides, e.g., isolated, such as deoxyribonucleic acid (DNA), and, where appropriate, ribonucleic acid (RNA).
  • DNA deoxyribonucleic acid
  • RNA ribonucleic acid
  • the term should also be understood to include, as equivalents, analogs of RNA or DNA made from nucleotide analogs, and, as applicable to the embodiment being described, single (sense or antisense) and double-stranded polynucleotides.
  • ESTs, chromosomes, cDNAs, mRNAs , and rRNAs are representative examples of molecules that may be referred to as nucleic acids.
  • over or underexpression may comprise the detection of difference in the expression of the proteins according to the present invention in relation to at least one control.
  • predicting clinical outcome refers to the ability for a skilled artisan to classify patients into at least two classes “good prognosis” and “bad prognosis” showing significantly different long- term Metastasis Free Survival (MFS)
  • Protein refers to a polypeptide with a primary, secondary, tertiary or quaternary structure, or any portion or modification, e.g., a mutant, or isoform thereof.
  • a "portion” or “modification” of a protein retains at least one biological or antigenic characteristic of a native (wild-type) protein.
  • Protein microarray refers to a spatially defined and separated collection of individual proteins immobilised on a solid surface.
  • Treating as used herein is intended to encompass treating as well as ameliorating at least one symptom of the condition or disease.
  • Figure 1 represents hierarchical clustering analysis of global protein expression profiles in breast cancer as measured by IHC on TMA.
  • Colored bars to the right and colored branches in the dendrogram indicate the locations of 3 sample clusters of interest zoomed in C.
  • B Dendrogram of proteins. Two major clusters “PI” (basal/stem cells) and “P2" ( luminal/glandular cells) are identified and further divided in 4 smaller clusters designated “proliferation”, “mitosis”, “ER-related” and “adhesion” cluster, respectively.
  • C Expanded view of selected sample clusters showing a partial grouping of tumors with similar histological type (LOB: lobular, DUC : ductal, OTH: other, MIX: mixed; blue bar) or ER status (positive, red bar and negative, orange bar).
  • LOB histological type
  • Figure 2 represents classification of 552 breast cancer samples based on the expression of the 21-protein discriminator set identified by supervised analysis.
  • Each row of the data matrix (left panel) represents a sample and each column represents a protein. Immunostaining results are depicted according to the color scale used in Figure 1.
  • the 21 proteins, listed above the matrix (ER*: means of three independent ER analyses), are ordered from left to right according to decreasing _P (_P is the difference between the probability of positive staining and the probability of negative staining in non-metastatic samples).
  • Tumor samples are numbered from 1 to 552 and are ordered from top to bottom according to their increasing “Metastasis Score” (right panel).
  • the orange dashed line indicates the threshold 0 that separates the two classes of samples, "poor- prognosis” (under the line) and "good-prognosis” (above the line).
  • the middle panel indicates the occurrence (black square) or not (white square) of metastatic relapse for each patient.
  • Figure 3 represents Kaplan-Meier analysis of the metastasis-free survival of patients with breast cancer according to the molecular classification based on the 21-protein expression signature or the St-Gallen and the NIH consensus criteria.
  • Patients were classified in the "good- prognosis” class or the "poor-prognosis” class using the 21-protein signature identified by supervised analysis (A, B, E and F) or in the "low risk” class or the "high risk” class using the St-Gallen and the NIH consensus criteria (C and D) .
  • the P-values are calculated using the log-rank test.
  • Figure 4 represents expression of proteins studied by IHC on tissue microarrays (TMA).
  • TMA tissue microarrays
  • C Examples of IHC staining for 5 proteins with differential expression in cancer tissue (bottom) compared with normal tissue (top).
  • clustering allowed the identification of four major coherent protein clusters designated according to the function of most included proteins: "ER-related cluster”, “adhesion cluster”, “mitosis cluster” and “proliferation cluster”.
  • Correlated expression of proteins may be due to different mechanisms such as coregulation (e.g., ER/BCL2 30 ), functional interaction (e.g., STK6/Taxins 27, 28 ), phenotypic association (e.g., ERBB2/P53 31 ) or chromosomal location (e.g., FGFR1/TACC1 located on 8pll).
  • coregulation e.g., ER/BCL2 30
  • functional interaction e.g., STK6/Taxins 27, 28
  • phenotypic association e.g., ERBB2/P53 31
  • chromosomal location e.g., FGFR1/TACC1 located on 8pll.
  • this cluster also included CDH3/P-Cadherin, present in a "basal cluster” identified in gene expression analyses 9 and previously shown to be overexpressed in a subgroup of breast carcinomas associated with higher proliferation rates and aggressive behavior.
  • 35 Hierarchical clustering sorted tumors into three clusters that correlated with relevant histoclinical parameters, including histological type, SBR grade, ER status, ERBB2 status and the presence or absence of peritumoral vascular emboli. Correlations were found between the characteristics of these tumor clusters and their protein expression profiles.
  • the high number of grade III tumors in cluster B agreed with the frequent strong expression of the "proliferation" cluster - which included ERBB2 - and the "mitosis” cluster in these tumors.
  • 99% of cluster Al samples were ER-positive, and showed a frequent strong expression of the "ER-related” cluster and low expression of the "proliferation cluster”.
  • the tumor clusters also correlated with a breast cancer classification recently proposed in two series of analyses that provided a new conceptual framework of mammary oncogenesis.
  • phenotypic analyses have established a three-cell phenotypic classification of breast cancer cells.
  • cytokeratins cytokeratins
  • basic cells contain mammary gland progenitor cells able to give raise to both "luminal” and “myoepithelial” 38 cells.
  • Progenitor cells express type II keratins CK5 and 6.
  • differentiated "luminal” cells express type II keratin CK8 and type I keratin CK18, which are also observed in normal simple and glandular epithelia.
  • Luminal cells also express ER.
  • Cluster B may consist of tumors with basal/progenitor, ER-negative characteristics, i.e. strong expression of CK5/6 and proliferation markers.
  • A2 tumors, with an intermediate profile, may represent a transitory "baso-luminal" stage, or consist of tumors that have lost ER function. It can be expected that luminal Al tumors, in which the bulk of cells are more differentiated and express ER-related cluster proteins, are of better prognosis, whereas more undifferentiated and proliferative basal B tumors are associated with poor prognosis. The significant differences in clinical outcome observed between the three defined tumor clusters in this study are consistent with this model and recent studies. 9"11 ' 41 In addition, we show that lobular carcinomas are luminal-like tumors, and consist of differentiated luminal cells that express CK8/18.
  • this prognostic signature was validated in an independent set of 184 patients, showing its robustness.
  • Our discriminator set included 10 proteins coded by genes identified across recent gene expression studies, 7"15 as well as other proteins with unclear role in disease progression and sensitivity to systemic therapy.
  • the prognostic value of the signature was increasingly accurate with the addition of other proteins as evidenced by univariate and multivariate analyses, further highlighting the strength of large-scale molecular analyses for understanding tumor heterogeneity through the identification of expression signatures.
  • the classification based on the 21-protein predictor was associated with a highly significant difference in clinical outcome.
  • the 5-year MFS was
  • the 5-year MFS was 90% for ER-positive patients from the "good- prognosis class", and 58% for ER-positive patients from the "poor-prognosis class", suggesting our 21- protein set may provide more accurate clinical information than ER status alone, possibly reflecting functional differences in the ER pathway. Additionally, our molecular classification conserved its predictive impact for patients independent of adjuvant systemic therapy. Since distant metastasis may be influenced by adjuvant therapy, we separately analyzed the 186 patients who did not receive any chemo- and hormone therapy, as well as the 133 patients who exclusively received adjuvant chemotherapy with anthracyclin-based regimen in most cases.
  • the 21- protein signature may facilitate the selection of appropriate treatment options in early breast cancer patients. It may be an important clinical tool to circumvent unnecessary, toxic and costly treatment of node-negative patients, and it may help for selecting, among patients who need adjuvant chemotherapy, those who might benefit from standard protocol and those who would be candidates to other protocol or other form of systemic therapy.
  • Clinical annotation of each sample included patient age, axillary lymph node status, pathological tumor size, Scarff-Bloom-Richardson (SBR) grade, peritumoral vascular invasion, estrogen receptor (ER), progesterone receptor (PR) and ERBB2 status as evaluated by IHC with positivity cut-off values of 1% for hormone receptors and with 2 or 3+ score (HercepTest kit scoring guidelines) for ERBB2.
  • SBR Scarff-Bloom-Richardson
  • PR progesterone receptor
  • ERBB2 status as evaluated by IHC with positivity cut-off values of 1% for hormone receptors and with 2 or 3+ score (HercepTest kit scoring guidelines) for ERBB2.
  • the characteristics of patients are listed in Table 1 (see first column only).
  • Table 1 Histoclinical characteristics of 552 breast cancer patients, according to the membership to the "good-prognosis” or the “poor-prognosis class” as defined using the expression of the 21-protein set.
  • CI denotes confidence interval
  • the median follow-up was 57 months (range, 2 to 182) after diagnosis for the 450 patients who did not experience metastatic relapse as a first event, 37 months (range, 4 to 151) for the 102 patients with metastasis as first event, and 51 months (range, 2 to 182) for all patients.
  • the 5-year MFS rate was 80% [95%CI 76.2 - 83.7].
  • TMA's were prepared as previously described 25 with slight modifications. For each tumor, three representative areas from the primary tumor were carefully selected from a hematoxylin-eosin stained section of a donor block. Core cylinders with a diameter of 0.6 mm each were punched from each of these areas and deposited into three separate recipient paraffin blocks using a specific arraying device (Beecher Instruments, Silver Spring, MD). The technique of TMA allows the analysis of tumors and controls under identical experimental conditions. In addition to tumor tissues, the recipient block also received 10 normal breast tissue samples from 10 healthy women that underwent reductive mammary surgery and pellets from nine mammary cell lines.
  • the selection of the proteins was done according to the following criteria: known or potential importance in breast cancer and availability of a corresponding antibody that performed well in IHC on paraffin-embedded tissues. Twenty-six proteins were selected including hormone receptors (ER, PR), subclass markers (Cytokeratins), oncogenes and proliferation proteins (ERBB family members, BCL2, Cyclins, MIBl, FGFRl, Aurora A, Taxins), tumor suppressors (P53, FHIT), adhesion molecules (Cadherins, Catenins, Afadin), proteins from oncogenes of amplified genomic regions (ERBB2, CCND1, STK6), and other potential prognostic markers identified in specific studies or previous DNA microarray experiments (CCNE, GATA3 , MUCl).
  • ER hormone receptors
  • Cytokeratins oncogenes and proliferation proteins
  • ERBB family members BCL2, Cyclins, MIBl, FGFRl, Aurora A, Taxins
  • Mmab mouse monoclonal antibody
  • Rpab rabbit polyclonal antibody
  • DTRS Dako target retrieval solution.
  • IHC Immunohistochemical analysis
  • IHC was carried out on five- ⁇ m sections of tissue fixed in alcohol formalin for 24 h and embedded in paraffin. Sections were deparaffinized in Histolemon (Carlo Erba Reagenti, Rodano, Italy) and rehydrated in graded alcohol. Antigen retrieval was accomplished by incubating the sections in pre-treatment solutions depending on the antibody used. Pretreatment conditions are listed in Table 2. The reactions were carried out using an autoimmunostainer (Dako Autostainer).
  • Staining was performed at room temperature as follows: rehydrated tissues were washed in phosphate buffer, followed by quenching of endogenous peroxidase activity by treatment with 0.1% H 2 0 2 , slides, incubated with blocking serum (Dako) for 30 min., then with the affinity-purified antibody for one hour. After washes, slides were sequentially incubated with biotinylated antibody against rabbit IgG for 20 min. followed by streptadivin-conjugated peroxidase (Dako LSAB R 2 kit), then visualized with Diaminobenzidine (3-amino-9- ethylcarbazole) .
  • the IHC scores were recorded as negative (negative staining) or positive (weakly and strong positive staining).
  • the classifier was derived through training on a subset of chosen samples (2/3 of population, learning set) and then validated on the remaining subset (1/3 of population, validation set). The assignment of samples to each set was random, but the ratio between tumors with and without metastatic relapse was preserved. An exhaustive testing comprising all combinations of 1 to 5 proteins, as well as the complementary combinations of 21 to 25 proteins was performed to assess their ability to classify tumors into 2 classes ("poor-prognosis" and "good-prognosis") in agreement with their clinical outcome.
  • the number of misclassifications was defined as the number of X tumors classified in the "good-prognosis class" plus the number of Y tumors classified in the "poor-prognosis class".
  • the best classifier protein-set was that with the minimal rate of misclassified tumors.
  • the prognostic power of the classifier was tested on the validation set by classifying the remaining independent tumors using the same approach. Finally, it was assessed on the whole population. For each tumor set, the prognostic impact was further estimated by univariate analyses that compared the rate of metastatic relapses within the two molecularly defined classes of tumors (Fisher exact test) .
  • CI denotes confidence interval
  • Figure IB displays the dendrogram of related proteins.
  • the three interpretations of ER staining made independently by two pathologists were highly correlated (R 2 between 0.87 and 0.96) ( Figure 1C, middle and bottom panels).
  • PI Two major protein clusters - designated "PI” and "P2" - were identified ( Figure IB).
  • ER-related cluster of ER-associated proteins
  • Afadin an "adhesion cluster”
  • the fourth cluster (thereafter designated “proliferation cluster") defined by the routinely used marker Ki67/MIB1, revealed that proteins such as EGFR, ERBB2 , P53 and the Gl cyclin CCNE are preferentially overexpressed in tumors undergoing rapid growth.
  • the combined protein expression patterns defined two major clusters of tumors designated cluster A (462 cases) and cluster B (89 cases) in Figure 1 (1 case that clustered outside of the 2 clusters was excluded from further analysis).
  • Cluster A could be further subdivided into two subclusters, Al (393 cases) and A2 (89 cases).
  • cluster Al tumors displayed a strong expression of the "ER cluster” and the “adhesion cluster” and a low expression of the "proliferation cluster” in most of cases, whereas the "mitosis cluster” was strongly expressed in -50% of samples.
  • cluster B tumors displayed overall a low expression of the "ER cluster” but a strong expression of the three other protein clusters.
  • Cluster A2 included ER-positive and ER-negative tumors that displayed an intermediate profile characterized overall by strong expression of the "adhesion cluster” and a low expression of the "ER cluster", the "proliferation cluster” and the "mitosis cluster”.
  • cluster Al 41% of cases were grade I and 15% were grade III compared with 23% and 35% in cluster A2 , and 7% and 63% in cluster B (p ⁇ 0.0001; Chi-2 test), respectively.
  • cluster B samples were more likely to be ERBB2-positive (2+ or 3+ in IHC, 36% of cases) compared with 8% in cluster Al and 12% in cluster A2 (p ⁇ 0.0001, Chi-2 test).
  • cluster Al samples were more likely to be ER-positive (99% of cases) compared with 35% in cluster A2 and 10% in cluster B (p ⁇ 0.0001, Chi-2 test).
  • the learning set of samples allowed the identification of a combination of proteins (protein expression signature) that correlated with long-term MFS.
  • the number of proteins in the "metastatic predictor” was optimized by iteratively testing all combinations of 1 to 5 proteins and the complementary combinations of 21 to 25 proteins and by assessing their ability for correct classification of samples using a "Metastatic Score".
  • the optimal combination for these tumors contained 21 proteins ( Figure 2C). Examples of IHC staining for these 21 proteins are shown in Figure 4B.
  • Samples from the learning set were ordered using the "Metastatic Score”. Two classes of samples (“poor-prognosis class", positive scores and "good- prognosis class", negative scores) were defined using a cut-off value of 0.
  • OR 6.1 [95%CI 3.3 - 11.3], p ⁇ 0.0001, Fisher exact test).
  • _P is the difference between the probability of positive staining and the probability of negative staining in non-metastatic samples.
  • the orange dashed line indicates the threshold 0 that separates the two classes, "good- prognosis” (above the line) and “poor-prognosis” (under the line).
  • the histoclinical factors that correlated with MFS were pathological tumor size ( ⁇ 20 mm, >20), tumor grade (SBR I, II, III), number of positive axillary lymph nodes (0, 1-3, ⁇ 4), and peritumoral vascular invasion (negative, positive).
  • CI denotes confidence interval.
  • the parameters entered in the model were dichotomised and included the classification based on the discriminator 21-protein set ("good- prognosis class" and "poor-prognosis class"), age of patients ( ⁇ 50 years, >50 years), number of positive axillary lymph nodes (0, 1-3, ⁇ 4 ) , pathological tumor size ( ⁇ 20 mm, >20), tumor grade (SBR I, II, III), estrogen receptor status (negative, positive), progesterone receptor status (negative, positive), peritumoral vascular invasion (negative, positive), chemotherapy (delivery or not), hormone therapy (delivery or not) and each of the proteins (negative, positive) significantly associated with survival in univariate analyses.
  • Results are shown in Table 4.
  • Several independent factors predictive of distant metastasis as first event were evidenced including the prognosis signature based on the 21- protein combination, pathological size of tumors, axillary lymph node status (only when dichotomized ⁇ 3 vs >3), Ki67/MIB1 status and delivery of hormone therapy.
  • the 21-protein signature was the strongest predictor with a hazard ratio of 2.2 for "poor-prognosis class” patients, compared to "good- prognosis class” patients ([95%CI 1.25 - 3.89], p ⁇ 0.0001) .
  • References :
  • Tamoxifen for early breast cancer an overview of the randomised trials .
  • Early Breast Cancer Trialists ' Collaborative Group . Lancet 1998 ;
  • Boecker W Buerger H. Evidence of progenitor cells of glandular and myoepithelial cell lineages in the human adult female breast epithelium: a new progenitor (adult stem) cell concept. Cell Prolif 2003; 36 Suppl 1:73-84.

Abstract

Selon cette méthode d'analyse de l'expression différentielle de protéines associées à des caractéristiques histopathologiques de maladies du sein, on détecte la surexpression ou la sous-expression d'un ensemble de protéines dans les tissus ou cellules du sein, cet ensemble comprenant toutes les protéines suivantes ou seulement certaines de ces protéines, par exemple, une, deux, trois ou plusieurs des protéines suivantes : afadine, aurora A, a-catenine, b-catenine, BCL2, cycline Dl, cycline E, cytokératine 5/6, cytokératine 8/18, E-cadherine, EGFR, ERBB2, ERBB3, ERBB4, récepteur d'oestrogène, FGFR1, FHIT, GATA3, Ki67, mucine 1, P53, P-cadherine, récepteur de progestérone, TACC1, TACC2, TACC3, cytokératine 6, cytokératine 18, angl, auroraB, BCRP1, cathepsine D, CD10, CD44, CK14, Cox2, FGF2, GATA4, Hifla, MMP9, MTA1, NM23, NRG1a, NRGlbeta, P27, parkine, PLAU, S100, SCRIBBLE, actine des muscles lisses, THBS1, TIMP1.
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WO2007072220A2 (fr) * 2005-09-12 2007-06-28 Aurelium Biopharma Inc. Jeu ordonne de microechantillons cible et methodes de diagnostic du cancer
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WO2007072220A2 (fr) * 2005-09-12 2007-06-28 Aurelium Biopharma Inc. Jeu ordonne de microechantillons cible et methodes de diagnostic du cancer
WO2007072220A3 (fr) * 2005-09-12 2007-11-08 Aurelium Biopharma Inc Jeu ordonne de microechantillons cible et methodes de diagnostic du cancer
US8119655B2 (en) 2005-10-07 2012-02-21 Takeda Pharmaceutical Company Limited Kinase inhibitors
US8278450B2 (en) 2007-04-18 2012-10-02 Takeda Pharmaceutical Company Limited Kinase inhibitors
US8580496B2 (en) 2008-02-21 2013-11-12 Universite Libre De Bruxelles Method and kit for the detection of genes associated with PIK3CA mutation and involved in PI3K/AKT pathway activation in the ER-postitive and HER2-positive subtypes with clinical implications
EP2649225A4 (fr) * 2010-12-10 2015-06-10 Nuclea Biotechnologies Inc Biomarqueurs pour la prédiction du cancer du sein
EP3141617A3 (fr) * 2011-01-11 2017-04-19 INSERM (Institut National de la Santé et de la Recherche Médicale) Procédés de prévision du résultat d'un cancer chez un patient par l'analyse de l'expression génique
WO2012095448A1 (fr) * 2011-01-11 2012-07-19 INSERM (Institut National de la Santé et de la Recherche Médicale) Procédés de prédiction de l'évolution d'un cancer chez un patient par l'analyse de l'expression génique
WO2013165008A1 (fr) 2012-05-02 2013-11-07 公益財団法人がん研究会 Petit composé ciblant le tacc3
US9630953B2 (en) 2012-05-02 2017-04-25 Japanese Foundation For Cancer Research Small compounds targeting TACC3
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