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WO2010076322A1 - Prédiction de la réponse à une chimiothérapie à base de taxane/d'anthracycline lors d'un cancer du sein - Google Patents

Prédiction de la réponse à une chimiothérapie à base de taxane/d'anthracycline lors d'un cancer du sein Download PDF

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Publication number
WO2010076322A1
WO2010076322A1 PCT/EP2009/067990 EP2009067990W WO2010076322A1 WO 2010076322 A1 WO2010076322 A1 WO 2010076322A1 EP 2009067990 W EP2009067990 W EP 2009067990W WO 2010076322 A1 WO2010076322 A1 WO 2010076322A1
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Prior art keywords
response
chemotherapy
genes
tumor
gene
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PCT/EP2009/067990
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English (en)
Inventor
Ralf Kronenwett
Christian VON TÖRNE
Jan Budczies
Carsten Denkert
Manfred Dietel
Martina Komor
Sibylle Loibl
Marc Roller
Gunther Von Minckwitz
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Siemens Healthcare Diagnostics Inc.
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Publication of WO2010076322A1 publication Critical patent/WO2010076322A1/fr

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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
    • 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
    • C12Q2600/112—Disease subtyping, staging or classification

Definitions

  • the present invention relates to methods for prediction of the therapeutic success of cancer therapy.
  • breast cancer is one of the leading causes of cancer death in women in western countries. More specifically breast cancer claims the lives of approximately 40,000 women and is diagnosed in approximately 200,000 women annually in the United States alone. Over the last few decades, adjuvant systemic therapy has led to markedly improved survival in early breast cancer. This clinical experience has led to consensus recommendations offering adjuvant systemic therapy for the vast majority of breast cancer patients. In breast cancer a multitude of treatment options are available which can be applied in addition to the routinely performed surgical removal of the tumour and subsequent radiation of the tumor bed.
  • malignant tumors constitute a complex micro-ecosystem that dependents on the interplay between tumor cells, stromal cells and host inflammatory cells.
  • Several studies have shown that the presence of a lymphocytic infiltrate in cancer tissue is associated with an improved clinical outcome. From animal experiments, there is evidence that the immune system participates in the elimination of tumor cells and the control of tumor growth. Recently, it has been suggested that immunological mechanisms may also be involved in the response to cytotoxic chemotherapy, and that the presence of a low level immunological response might trigger the effects of existing conventional chemotherapy approaches.
  • Neoadjuvant chemotherapy of early breast cancer leads to high clinical response rates of 70-90%.
  • pathological assessment of the tumor after surgery reveals the presence of residual tumor cell foci.
  • a complete absence of residual invasive tumor, the so- called pathological complete response (pCR) is observed only in 10-25% of patients.
  • the pCR is a surrogate marker for disease-free survival and a strong indicator of benefit from chemotherapy .
  • neoadjuvant chemotherapy constitutes an in vivo chemoresistance test, it is an excellent basis for the analysis of predictive biological factors in pretherapeutic core biopsies, in order to identify those patients that would benefit most from chemotherapy.
  • Accepted parameters linked to response to neoadjuvant chemotherapy are hormone receptor status as well as tumor grade.
  • the present invention is based on the hypothesis that the presence of an inflammatory lymphocyte-mediated response to tumor cells may predict the response to neoadjuvant chemotherapy.
  • Chemotherapy may be applied postoperative, i.e. in the adjuvant setting or preoperative, that is in the neoadjuvant setting in which patients receive several cycles of drug treatment over a limited period of time, before remaining tumor cells are removed by surgery.
  • Neoadjuvant chemotherapy is used for patients with large tumors and locally advanced breast cancer. Primary goal is a reduction of tumor size in order to increase the possibility of breast-conserving treatment .
  • NASH histopathological changes
  • pCR pathological complete remission
  • hormone receptor status As well as tumor grade.
  • reaction relates to the reaction of an individual under a defined therapy. Reactions as used in this document can for example be beneficial or adverse. Possible reactions include prolongation or shortening of time to local and/or distant recurrence, prolongation or shortening of time to death, prolongation or shortening of disease progression, and prolongation or shortening of time to metastasis in an adjuvant or neoadjuvant setting. In a neoadjuvant setting, reactions to therapy additionally include the shrinkage, growth, or absence of change of the primary tumor within a given time frame and is usually measured as a quantification of change, usually given as a percentage, e.g. diameter or volume, or as a class as, for example, defined by WHO.
  • pathological complete response relates to a complete disappearance or absence of invasive tumor cells in the breast and/or lymph nodes as assessed by a histopathological examination of the surgical specimen following neoadjuvant chemotherapy.
  • tissue response relates to at least limited response with residual invasive tumor ⁇ 0.5cm as assessed by a histopathological examination of the surgical specimen following neoadjuvant chemotherapy.
  • No tissue response was defined as no changes or limited cellular response (sclerosis, resorption, inflammation, zytopathic changes) in the tumor.
  • prognosis relates to an individual assessment of the malignancy of a tumor, or to the expected response if there is no drug therapy.
  • prediction relates to an individual assessment of the malignancy of a tumor, or to the expected response if the therapy contains a drug in comparison to the malignancy or response without this drug.
  • prognosis under therapy relates to an individual assessment of the malignancy of a tumor, or to the expected response if there is any drug therapy without considering malignancy or response without this drug.
  • response marker relates to a marker which can be used to predict the pathological and/or clinical response and/or clinical outcome of a patient towards a given treatment .
  • the term “therapy modality”, “therapy mode”, “regimen” as well as “therapy” refers to a timely sequential or simultaneous administration of anti-tumor, and/or anti vascular, and/or anti stroma, and/or immune stimulating or suppressive, and/or blood cell proliferative agents, and/or radiation therapy, and/or hyperthermia, and/or hypothermia for cancer therapy.
  • the administration of these can be performed in an adjuvant and/or neoadjuvant mode.
  • the composition of such "protocol” may vary in the dose of each of the single agents, timeframe of application and frequency of administration within a defined therapy window.
  • various combinations of various drugs and/or physical methods, and various schedules are under investigation.
  • a "taxane/anthracycline-containing chemotherapy” is a therapy modality comprising the administration of taxane and/or anthracycline and therapeutically effective derivates thereof .
  • the term "neoadjuvant chemotherapy” relates to a preoperative therapy regimen consisting of a panel of hormonal, chemotherapeutic and/or antibody agents, which is aimed to shrink the primary tumor, thereby rendering local therapy
  • sample refers to a sample obtained from a patient.
  • the sample may be of any biological tissue or fluid.
  • samples include, but are not limited to, sputum, blood, serum, plasma, blood cells (e.g. white cells), circulating cells (e.g. stem cells or endothelial cells in the blood, tissue, core or fine needle biopsy samples, cell-containing body fluids, free floating nucleic acids, urine, stool, peritoneal fluid, and pleural fluid, liquor cerebrospinalis, tear fluid, or cells there from.
  • Biological samples may also include sections of tissues such as frozen or fixed sections taken for histological purposes or microdissected cells or extracellular parts thereof.
  • a “tumor sample” is a sample containing tumor material e.g. tissue material from a neoplastic lesion taken by aspiration or puncture, excision or by any other surgical method leading to biopsy or resected cellular material, including preserved material such as fresh frozen material, formalin fixed material, paraffin embedded material and the like.
  • a biological sample may comprise cells obtained from a patient. The cells may be found in a cell "smear" collected, for example, by a nipple aspiration, ductal lavage, fine needle biopsy or from provoked or spontaneous nipple discharge.
  • the sample is a body fluid.
  • Such fluids include, for example, blood fluids, serum, plasma, lymph, ascitic fluids, gynecological fluids, or urine but not limited to these fluids.
  • the term "marker” or “biomarker” refers to a biological molecule, e.g., a nucleic acid, peptide, protein, hormone, etc., whose presence or concentration can be detected and correlated with a known condition, such as a disease state.
  • marker gene refers to a differentially expressed gene whose expression pattern may be utilized as part of a predictive, prognostic or diagnostic process in healthy conditions, premalignant disease status, malignant neoplasia or cancer evaluation, or which, alternatively, may be used in methods for identifying compounds useful for the treatment or prevention of malignant neoplasia and head and neck, colon or breast cancer in particular.
  • a marker gene may also have the characteristics of a target gene.
  • expression level refers, e.g., to a determined level of gene expression.
  • pattern of expression levels refers to a determined level of gene expression compared either to a reference gene (e.g. housekeeper or inversely regulated genes) or to a computed average expression value (e.g. in DNA-chip analyses) .
  • a pattern is not limited to the comparison of two genes but is more related to multiple comparisons of genes to reference genes or samples.
  • a certain “pattern of expression levels” may also result and be determined by comparison and measurement of several genes disclosed hereafter and display the relative abundance of these transcripts to each other.
  • determining the expression level of a gene/protein on a non-protein basis relates to methods which are not restricted to the secondary gene translation products, i.e proteins, but on other levels of the gene expression, like the mRNA, premRNA and genomic DNA structures.
  • a differentially expressed gene disclosed herein may be used in methods for identifying reagents and compounds and uses of these reagents and compounds for the treatment of cancer as well as methods of treatment.
  • the differential regulation of the gene is not limited to a specific cancer cell type or clone, but rather displays the interplay of cancer cells, muscle cells, stromal cells, connective tissue cells, other epithelial cells, endothelial cells of blood vessels as well as cells of the immune system (e.g. lymphocytes, macrophages, killer cells) .
  • modulated or “modulation” or “regulated” or “regulation” and “differentially regulated” or
  • “differentially expressed” as used herein refer to both upregulation (i.e., activation or stimulation (e.g., by agonizing or potentiating) and down regulation [i.e., inhibition or suppression (e.g., by antagonizing, decreasing or inhibiting) ] .
  • a "reference pattern of expression levels”, within the meaning of the invention shall be understood as being any pattern of expression levels that can be used for the comparison to another pattern of expression levels.
  • a reference pattern of expression levels is, e.g., an average pattern of expression levels observed in a group of healthy or diseased individuals, serving as a reference group.
  • Primer pairs and “probes”, within the meaning of the invention, shall have the ordinary meaning of this term which is well known to the person skilled in the art of molecular biology.
  • “primer pairs” and “probes” shall be understood as being polynucleotide molecules having a sequence identical, complementary, homologous, or homologous to the complement of regions of a target polynucleotide which is to be detected or quantified.
  • nucleotide analogues and /or morpholinos are also comprised for usage as primers and/or probes.
  • “Individually labeled probes”, within the meaning of the invention, shall be understood as being molecular probes comprising a polynucleotide, oligonucleotide or nucleotide analogue and a label, helpful in the detection or quantification of the probe.
  • Preferred labels are fluorescent molecules, luminescent molecules, radioactive molecules, enzymatic molecules and/or quenching molecules.
  • arrayed probes within the meaning of the invention, shall be understood as being a collection of immobilized probes, preferably in an orderly arrangement.
  • the individual “arrayed probes” can be identified by their respective position on the solid support, e.g., on a "chip”.
  • array or “matrix” an arrangement of addressable locations or “addresses” on a device is meant.
  • the locations can be arranged in two dimensional arrays, three dimensional arrays, or other matrix formats.
  • the number of locations can range from several to at least hundreds of thousands. Most importantly, each location represents a totally independent reaction site.
  • Arrays include but are not limited to nucleic acid arrays, protein arrays and antibody arrays.
  • a “nucleic acid array” refers to an array containing nucleic acid probes, such as oligonucleotides, nucleotide analogues, polynucleotides, polymers of nucleotide analogues, morpholinos or larger portions of genes.
  • the nucleic acid and/or analogue on the array is preferably single stranded.
  • Arrays wherein the probes are oligonucleotides are referred to as “oligonucleotide arrays" or “oligonucleotide chips.”
  • the regions in a microarray have typical dimensions, e.g., diameters, in the range of between about 10-250 ⁇ m, and are separated from other regions in the array by about the same distance.
  • a “protein array” refers to an array containing polypeptide probes or protein probes which can be in native form or denatured.
  • An “antibody array” refers to an array containing antibodies which include but are not limited to monoclonal antibodies (e.g. from a mouse), chimeric antibodies, humanized antibodies or phage antibodies and single chain antibodies as well as fragments from antibodies .
  • a PCR based method refers to methods comprising a polymerase chain reaction (PCR) .
  • PCR polymerase chain reaction
  • This is a method of exponentially amplifying nucleic acids, e.g. DNA by enzymatic replication in vitro.
  • PCR is an in vitro technique, it can be performed without restrictions on the form of DNA, and it can be extensively modified to perform a wide array of genetic manipulations.
  • a PCR based method may for example be used to detect the presence of a given mRNA by (1) reverse transcription of the complete mRNA pool (the so called transcriptome) into cDNA with help of a reverse transcriptase enzyme, and (2) detecting the presence of a given cDNA with help of respective primers.
  • rtPCR reverse transcriptase PCR
  • PCR-based methods comprise e.g. real time PCR, and, particularly suited for the analysis of expression levels, kinetic or quantitative PCR (qPCR) .
  • Quantitative PCR refers to any type of a PCR method which allows the quantification of the template in a sample.
  • Quantitative real-time PCR comprise different techniques of performance or product detection as for example the TaqMan technique or the LightCycler technique.
  • the TaqMan technique for examples, uses a dual-labelled fluorogenic probe.
  • the TaqMan real-time PCR measures accumulation of a product via the fluorophore during the exponential stages of the PCR, rather than at the end point as in conventional PCR.
  • the exponential increase of the product is used to determine the threshold cycle, CT, i.e.
  • the set up of the reaction is very similar to a conventional PCR, but is carried out in a real-time thermal cycler that allows measurement of fluorescent molecules in the PCR tubes.
  • a probe is added to the reaction, i.e., a single-stranded oligonucleotide complementary to a segment of 20-60 nucleotides within the DNA template and located between the two primers.
  • a fluorescent reporter or fluorophore e.g., 6- carboxyfluorescein, acronym: FAM, or tetrachlorofluorescin, acronym: TET
  • quencher e.g., tetramethylrhodamine, acronym: TAMRA, of dihydrocyclopyrroloindole tripeptide "minor groove binder'', acronym: MGB
  • the 5' to 3 ' exonuclease activity of the Taq polymerase degrades that proportion of the probe that has annealed to the template (Hence its name: Taq polymerase + PacMan) .
  • Degradation of the probe releases the fluorophore from it and breaks the close proximity to the quencher, thus relieving the quenching effect and allowing fluorescence of the fluorophore.
  • fluorescence detected in the real-time PCR thermal cycler is directly proportional to the fluorophore released and the amount of DNA template present in the PCR.
  • immunohistochemistry refers to the process of localizing proteins in cells of a tissue section exploiting the principle of antibodies binding specifically to antigens in biological tissues. Immunohistochemical staining is widely used in the diagnosis and treatment of cancer. Specific molecular markers are characteristic of particular cancer types. IHC is also widely used in basic research to understand the distribution and localization of biomarkers in different parts of a tissue. "Prediction of recurrence” or “prediction of therapeutic success” does refer to the methods described in this invention. Wherein a tumor specimen is analyzed for its gene expression and furthermore classified based on correlation of the expression pattern to known ones from reference samples.
  • This classification may either result in the statement that such given tumor will develop recurrence or will not achieve a pathological complete response or a tissue response following neoadjuvant chemotherapy and therefore is considered as a "non-responding" tumor to the given therapy, or may result in a classification as a tumor with a prolonged disease free post therapy time or as tumor that will achieve a pathological complete response or a tissue response.
  • hybridization-based method refers to methods imparting a process of combining complementary, single-stranded nucleic acids or nucleotide analogues into a single double stranded molecule. Nucleotides or nucleotide analogues will bind to their complement under normal conditions, so two perfectly complementary strands will bind to each other readily. In bioanalytics, very often labeled, single stranded probes are in order to find complementary target sequences. If such sequences exist in the sample, the probes will hybridize to said sequences which can then be detected due to the label. Other hybridization based methods comprise microarray and/or biochip methods.
  • probes are immobilized on a solid phase, which is then exposed to a sample. If complementary nucleic acids exist in the sample, these will hybridize to the probes and can thus be detected.
  • array based methods Yet another hybridization based method is PCR, which is described above. When it comes to the determination of expression levels, hybridization based methods may for example be used to determine the amount of mRNA for a given gene.
  • determining the protein level refers to methods which allow the quantitative and/or qualitative determination of one or more proteins in a sample. These methods include, among others, protein purification, including ultracentrifugation, precipitation and chromatography, as well as protein analysis and determination, including immunohistochemistry, immunofluorescence, ELISA (enzyme linked immuno assay) , RIA (radioimmunoassay) or the use of protein microarrays, two- hybrid screening, blotting methods including western blot, one- and two dimensional gelelectrophoresis, isoelectric focusing as well as methods being based on mass spectrometry like MALDI-TOF and the like.
  • nucleic acid molecule is intended to indicate any single- or double stranded nucleic acid molecule comprising DNA (cDNA and/or genomic DNA) , RNA (preferably mRNA) , PNA, LNA and/or Morpholino, or fractions, derivatives, fragments or analogues thereof.
  • the disclosed method can be used to select a suitable therapy for a neoplastic disease, particularly breast cancers.
  • the invention relates to a method for predicting a response to and/or benefit from chemotherapy in a patient suffering from cancer comprising the steps of a) classifying a tumor into at least two classes said at least two classes being selected from the group consisting of a a Her 2/neu negative, ESR negative (basal / triple negative) class of tumors, and a Her 2/neu negative, ESR positive (luminal class) class of tumors,
  • said at least one marker gene comprises a plurality of genes for predicting a response to and/or benefit from chemotherapy in Her 2/neu negative, ESR positive (luminal class) tumors said plurality of genes comprising the genes CD3D, CXCL9, UBE2C, and, optionally ESRl; or
  • said at least one marker gene comprises a plurality of genes for predicting a response to and/or benefit from chemotherapy in Her 2/neu negative, ESR negative (basal or triple negative class) tumors, said plurality of genes comprising the genes STMNl, HER2/NEU, and NFKBIA.
  • the plurality of genes is used for predicting a response to and/or benefit from chemotherapy in Her 2/neu negative, ESR positive (luminal class) tumors further comprising the gene ESRl.
  • the invention provides a method for predicting a response to and/or benefit from chemotherapy in a patient suffering from cancer comprising the steps of a) classifying a tumor as belonging to at least one class,
  • said at least one marker gene comprises a gene selected from the group consisting of TMSL8, ABCCl, EGFR, MVP, ACOX2 , HER2/NEU, MYHIl, TOBl, AKRlCl, ERBB4, NFKBIA, TOP2A, AKR1C3, ESRl, OLFMl, TOP2B, ALCAM, FRAPl, PGR, TP53, BCL2, GADD45A, PRKABl, TUBAlA, C16orf45, HIFlA, PTPRC, TUBB, CA12, IGKC, RACGAPl, UBE2C, CD14, IKBKB, S100A7, VEGFA, CD247, KRT5, SEPT8, YBXl, CD3D, MAPK3, SLC2A1, CDKNlA, MAPT, SLC7A8, CHPTl, MLPH, SPONl, CXCL13, MMPl, STATl, CXCL9, MMP
  • the methods of the invention particularly suited for predicting a response to cytotoxic chemotherapy, preferably taxane/anthracycline-containing chemotherapy, preferably in the neodajuvant mode.
  • said tumor is classified into HER2/NEU positive or negative, Luminal and Basal / triple negative classes.
  • said at least one marker gene for predicting a response to and/or benefit from chemotherapy in Her 2/neu positive tumors is selected from the group consisting of ERBB4, CHPTl, BCL2, MLPH, SPONl and combinations thereof.
  • said classification is performed by determining in a tumor sample the expression of at least one gene indicative for each class as described in this disclosure and depending on said gene expression, classifying the tumor.
  • said gene expression is determined on a RNA level by a PCR based method and/or a microarray based method.
  • Gene expression may further be determined at a protein level or non-protein level, by any suitable method, e.g. hybridization based methods or array based methods .
  • said at least one marker gene is selected from the group consisting of ERBB4, CHPTl, BCL2 MLPH, and the combinations of CHPT1/ERBB4, and CHPTl /SPONl .
  • said at least one marker gene is selected from the group consisting of CXCL9, MUCl, IGKC, CD3Z, and the combinations of CD3D/MUC1, FRAPl /MUCl, ACOX2/CD3D, ACOX2/CD3Z, and AKR1C3/EGFR.
  • said at least one marker gene is selected from the group consisting of TMSL8, ERBB2 (HER2/NEU), MUCl and the combinations of STMNl, HER2/NEU/STMN1, HER2/NEU/TMSL8 , HER2/NEU/NFKBIA.
  • the expression level of no more than five marker genes are determined in a given class, preferably no more than 4, 3, 2, or 1 marker genes.
  • a low number of genes is preferred, as it reduces the amount of measurements needed to obtain a predictive result.
  • Preferred embodiments of the invention allow a predictive determination to be made using just 5, 4, 3, 2, or even 1 marker gene (s) .
  • the expression level of said at least one marker gene is determined as a pattern of expression relative to at least one reference gene or to a computed average expression value.
  • the expression level of said at least on marker gene may be determined relative to a combination of several reference genes.
  • Preferred reference genes are RPL37A CALM2, and OAZl.
  • the gene TMSL8 has been determined as a new marker which is predictive for pCR in all Tumors (tables 4 and 5) , especially in ESRl negative tumors (table 8), in triple-negative / basal tumors (table 12) and in Her2/neu positive tumors (table 14) .
  • the expression levels of a plurality of marker genes are mathematically combined to give a score indicative of a response to and/or benefit from chemotherapy.
  • This mathematical combination may include, but is not limited to summation, weighted summation, correlation coefficients, discriminant functions, and statistical functions.
  • Gene expression values of marker genes may be used relative values normalized to one or more reference genes.
  • the invention further provides a kit for performing the method of any of the preceding claims comprising at least one probe specific for a gene or gene product for each at least one marker gene indicative of a response to chemotherapy for a tumor in each respective class.
  • the invention further provides a use of the kit described above for performing the methods according to the invention
  • AKR1C3/EGFR The following genes and gene combinations are especially predictive for basal / triple negative tumors:
  • the combination of genes comprising CD3D, CXCL9, and UBE2C are used for the prediction of response to chemotherapy in luminal tumors.
  • This combination of marker genes allows for a particularly reliable response to chemotherapy.
  • the combination of genes comprising CD3D, CXCL9, ESRl, and UBE2C are used for the predicition of response to chemotherapy in luminal tumors.
  • This combination of marker genes allows for a particularly reliable response to chemotherapy.
  • the combination of genes comprising STMNl, HER2/NEU, NFKBIA are used for the prediction of response to chemotherapy in basal / triple negative tumors.
  • This combination of marker genes allows for a particularly reliable response to chemotherapy. Description of the invention
  • Fig. 1 schematically shows the basic classification of the finding cohort in molecular subgroups.
  • Fig. 2 schematically shows a block diagram of an exemplary embodiment of the inventive method including exemplary cutoff values for classifying tumors according to the basic classification shown in figure 1.
  • Fig.3 shows a Receiver Operator Characteristics Curve (ROC) for the algorithm NLRS for luminal tumors in a training cohort (top panel) and a validation cohort (bottom panel) .
  • ROC Receiver Operator Characteristics Curve
  • Fig. 4 shows the sensitivity and specificity for an exemplary cutoff value of -3 for the algorithm NLRS for luminal tumors in a training cohort (top panel) and a validation cohort (bottom panel) .
  • Fig. 5 shows Receiver Operator Characteristics (ROC) for the algorithm NTRS for triple negative (basal) tumors in a training cohort (top panel) and a validation cohort (bottom panel) .
  • ROC Receiver Operator Characteristics
  • Fig. 6 shows the sensitivity and specificity for an exemplary cutoff value of -0.2 for the algorithm NTRS for triple negative (basal) tumors.
  • Fig. 7 shows a decision tree for the algorithm C_NLRS for luminal tumors .
  • Fig. 8 to 13 show additional data regarding the performance of exemplary best model algorithms in different tumor classes.
  • Top panels each show the area under curve (AUC) of an R.O.C. curve (left scale) and the Bayesian information criterion (BIC, right scale) relative of the number of genes used to predict pCR.
  • Middle panels show the probability of pCR relative to the selected cutoff value.
  • Bottom panels each show the AUC.
  • An embodiment of the invention is based upon a classification of tumor samples according to the diagram shown in Figure 1 :
  • the tumor of the patient is classified according to Her2/neu (also referred to as ERBB2) status into Her2/neu positive or negative tumors and Her2/neu negative tumors are further classified into estrogen receptor (also referred to as "ER” or “ESR) negative tumors (so called “triple negative” or “basal” class of tumors) or Her2/neu negative ER positive tumors (so called “luminal” class of tumors) .
  • ESR estrogen receptor
  • TSR Her2/neu negative ER positive tumors
  • luminal Her2/neu negative ER positive tumors
  • the inventors For each of these classes (Her2/neu positive, basal / triple negative and luminal class) , the inventors have identified genes which are differentially expressed in patients which are responsive to chemotherapy vs. nonresponsive patients as assessed by pathological complete response (pCR) or non- response. Determining expression status of one of these genes (univariate classifier) or a plurality of these genes (multivariate classifier) thus allows prediction of a response to chemotherapy.
  • TMSL8 TMSL8
  • ABCCl EGFR
  • MVP EGFR
  • ACOX2 HER2/NEU
  • MYHIl MYHIl
  • TOBl quantitative Polymerase Chain Reaction
  • the genes or gene combinations identified by classifier training were then validated in different patient cohorts.
  • lntratumoral lymphocytes Percentage of tumor cell Only those mononuclear cells (iTu-Ly) '• / - nests with intraepithelial that are within the epithelium mononuclear cells. of the invasive tumor cell nests are evaluated. Any infiltrate of intraductal carcinoma is not included. The infiltrate must consist of mononuclear cells, any granulocyte infiltrate in the area of tumor necrosis is not included.
  • Stromal lymphocytes Percentage of tumor Only tumor stroma of the (str-Ly) " > '- stroma with mononuclear invasive carcinoma is inflammatory cells. included, stromal infiltrate adjacent to intraductal carcinoma is not included. Furthermore, any inflammatory infiltrate around the normal breast tissue adjacent to the tumor is not included.
  • lymphocyte-predominant those carcinomas with Although LPBC is used as a breast cancer (LPBC) either more than 60% subgroup of carcinomas for intratumoral lymphocytes this evaluation, it should be or more than 60% stromal noted that the data suggests lymphocytes. that the response to The designation indicates chemotherapy is dependent that in those tumors the on the lymphocytic infiltrate as lymphocytes are the a continuous parameter, as predominant host cells seen in the logistic regression within the as well as in comparison of microecosystem of the subgroups with different tumor. percentages of lymphocytes. Therefore LPBC should be used as a working category to indicate an increased odds ratio for pathological complete response rather than a separate tumor entity.
  • lymphocyte infiltrate No detectable lymphocytes in tumor cell nests and tumor stromal.
  • stromal and intratumoral lymphocytes were a strong predictor of pCR in univariate (p ⁇ 0.0005) and multivariate logistic regression (p ⁇ 0.0005) .
  • the stromal lymphocytes were significantly correlated with iTu-Ly (Pearson correlation coefficient 0.80, p ⁇ 0.0005) .
  • Table 2 Validation cohort (GeparTrio) - Factors associated with a pathological complete response in the GeparTrio cohort in univariate and multivariate analysis. Results of univariate and multivariate logistic regression are shown.
  • the parameter str-Ly is not included in multivariate analysis as it is correlated with iTu-Ly. In a separate multivariate analysis the parameter str-Ly is significant as well (OR 1.02 (1.01- 1.02), p ⁇ 0.0005, data not shown)
  • Intratumoral 1.03 1.02-1.04 ⁇ 0.0005 1.02 (1.01-1.03) ⁇ 0.0005 lymphocytes (iTu- Ly) (%) Stromal 1.02 (1.03-1.03) ⁇ 0.0005 lymphocytes (str-Ly)
  • the lymphocytic infiltrate was evaluated as a continuous parameter.
  • an evaluation of grouped iTu-Ly and str-Ly as well as known predictive parameters was performed.
  • the odds ratio for pCR increases with the extent of iTu-Ly and str-Ly, with a maximal OR of 13.39 (95% CI 6.1-29.37, p ⁇ 0.0005) for tumors with more than 60% of iTu-Ly in tumor cell nests. Both parameters were combined in the subgroup of lymphocyte- predominant breast cancer (LPBC) as those cases with more than 60% of either iTu-Ly or str-Ly.
  • LPBC lymphocyte- predominant breast cancer
  • a hierarchical cluster analysis and a heat map of the expression data showed a co-regulation of the lymphocyte markers and an association of all of those markers with the achievement of a pCR and the presence of a lymphocyte infiltration. This indicates that the infiltration consisted of both, T and B cells. Moreover, the relative mRNA expression level of the lymphocyte markers significantly increased with the proportion of tumor infiltrating cells. The expression levels of the B and T cell markers were 2- to 12-fold higher in samples from patients achieving pCR in comparison with those who did not achieve pCR ( Figure x) . Finally, logistic regression analysis showed a significant association between the T cell markers CD3D, CXCL9 and CD247 whereas the B cell markers did not.
  • the inventors show by using two large independent cohorts of samples from neo-adjuvant clinical trials that it is possible to identify a distinct inflammatory subgroup of tumors by standard H&E histopathological analysis of pretherapeutic core biopsies.
  • This subgroup of tumors is characterized by a lymphocytic infiltrate in the tumor tissue and a particular strong response to cytotoxic chemotherapy.
  • This tumor subtype may be called "lymphocyte predominant breast cancer" (LPBC) .
  • LPBC lymphocyte predominant breast cancer
  • MBC medullary breast cancer
  • lymphocyte infiltrate In contrast an increased intratumoral lymphocyte infiltrate (>10%) was observed in 51% of cases in the GeparTrio study, and 12% of cases were LPBC. Therefore, the lymphocyte infiltrate is observed in a much larger subset of cases than the MBC group.
  • chemokine CXCL9 is involved in the regulation of tumor growth and metastasis in animal models .
  • lymphocyte infiltrates associated with increased response to chemotherapy is interesting in the light of other studies that have shown that parameters that are relevant for immune system function are also involved in response to chemotherapy. It may be speculated that the destruction of tumor cells by chemotherapeutic agents may release tumor-associated antigens. This may trigger an immune response directed against the tumor cells which will be particularly strong in those cases where a sensitization of the immune system against some tumor antigens is present before the onset of chemotherapy. Therefore, the chemotherapy may act as a functional immunotherapy in those tumor types and the combination of chemotherapeutic destruction of tumor cells as well as increased immune response may lead to a pathological complete remission. At present, it is not clear if this hypothesis may be the basis for further therapeutic approaches that may use a combination of stimulation of immune responses with classical chemotherapy to improve the rates of pathological complete remission in neoadjuvant chemotherapy .
  • the inventors established and independently validated that the presence of a mononuclear infiltrate in tumor stroma as well as within the tumor cells nests is associated with an increased response to neo-adjuvant chemotherapy in univariate and multivariate analysis. This might be the basis for new therapeutic approaches of the combination of conventional chemotherapy with immune therapy, to use the synergies between both types of therapy.
  • iTu-Ly and str-Ly are promising additional parameters for routine diagnostic reporting in combination with grading and hormone receptor status.
  • the analysis of the inflammatory infiltrate in histopathological analysis of breast cancer core biopsies gives useful information to oncologists to identify the subgroup of patients with an increased chance of response to chemotherapy.
  • Table 3 Single genes and gene combinations predictive in various tumor classes.
  • class designates the respective tumor class
  • Objective designates whether the algorithm was obtained with respect to pathological complete response or tissue response
  • Gene indicates the name of the marker gene used
  • model indicates the algorithm used to obtain the score which indicates the probability of achieving the objective in the respective sample
  • p value indicates the p value of the respective gene
  • AUC indicates the "area under curve” for the respective receiver operator curve associated with the respective algorithm given under "model”.
  • T cellular immune metagene can be constructed using the first principal component of a principal component analysis (PCA) involving CD3D and CXCL9 in order to improve robustness of algorithms.
  • PCA principal component analysis
  • a positive coefficient or score indicates that increased expression of a gene is associated with a high probability of pCR, whereas a negative coefficient indicates an inverse association of the gene expression value with the probability of pCR.
  • a positive coefficient or score indicates that increased expression of a gene is associated with a high probability of pCR
  • a negative coefficient indicates an inverse association of the gene expression value with the probability of pCR.
  • higher scores therefore indicate a higher likelihood of achieving a pCR.
  • IMG Immunmetagene
  • Proliferation metagene PMG
  • UBE2C 0.439843 * RACGAPl + 0.554379 * TOP2A + 0.488023 * STMNl.
  • Table 5 AUC values for the gene combinations/algorithms of table 4.
  • DNase I Ambion/Applied Biosystems, Darmstadt, Germany
  • Relative expression of CD3D, CD247 (CD3z) , CD45 (PTPRC), IGKC, CXCL9 and CXCL13 as well as RPL37A used for normalization was assessed by one-step kinetic reverse transcription PCR (kPCR) using the Superscript III Platinum One-Step Quantitative RT-PCR System with ROX (Invitrogen, Düsseldorf, Germany) according to manufacturer's instructions in an ABI PRISM 7900HT (Applied Biosystems, Darmstadt, Germany) .
  • ⁇ Ct values positively correlate with relative gene expression. All PCR assays were performed in triplicate. STATISTICAL EVALUATION
  • the combination of genes comprising CD3D, CXCL9, ESRl, and UBE2C are used for the prediction of response to chemotherapy in luminal tumors .
  • the expression values for these genes may be linked in the algorithm NLRS, wherein ::
  • CD3D, CXCL9 and UBE2C represent the expression values for the respective genes obtained as described below, and wherein a value of NLRS above a predetermined cutoff value in the range of -8 to 0, preferably -4 to - 2, more preferably at -3 represents a higher likelihood of a breast cancer patient having a luminal tumor responding to chemotherapy.
  • a cutoff of -3 was selected for high sensitivity.
  • the combination of genes comprising CD3D, CXCL9, and UBE2C are used for the prediction of response to chemotherapy in luminal tumors.
  • UBE2C, CD3D, and CXCL9 represent the expression values for the respective genes obtained as described below and "no pCR” represents a higher likelihood of the patient having no response to chemotherapy and "pCR” represents a higher likelihood of the patient having a response to chemotherapy, measured as pathological complete response.
  • the combination of genes comprising STMNl, NFKBIA and HER2/NEU are used for the prediction of response to chemotherapy in basal / triple negative tumors.
  • STMNl, NFKBIA and HER2/NEU represent the expression values for the respective genes obtained as described below, and wherein a value of NTRS above a predetermined cutoff value in the range of -1 to 1, preferably -0.4 to 0.4, more preferably at -0.2 represents a higher likelihood of a breast cancer patient having a basal / triple negative tumor responding to chemotherapy (example shown in figure 6) .
  • PCR assays were performed in duplicate in the GeparTrio training cohort and in triplicate in a further validation cohort. The PCR assays were performed blinded to the clinical outcome data. Means of the Ct values for each gene were calculated. If all duplicates or triplicates of a gene in a specific sample had no PCR signal the Ct value was set as 40 and was censored. If at least on duplicate or triplicate had a Ct value below 40 and at least one duplicate or triplicate had no PCR signal the Ct value for the well without signal was set as 40 and the mean of the duplicates or triplicates was calculated.
  • ⁇ Ct values positively correlate with relative gene expression. Assuming an amplification efficacy of 100% increase of one unit corresponds to a doubling of the amount of mRNA. ⁇ Ct values ranged from 4 to
  • the minus sign is to facilitate a straight-forward interpretation (higher values indicate higher expression) , the arbitrary number of 20 was added solely to ensure positivity of the values.
  • These values (Delta Ct values) were used for all subsequent calculations. If the expression of a gene of interest was so low that no signal could be picked up before the last amplification cycle, this partial information was conserved when computing relative expression values; this lead to censored (one-sided) expression values ("Expression of gene is at most") . Calculations of classifiers and the prediction of response classes used this partial information whenever possible, e.g. when computing score values and comparing them with a threshold.
  • T cellular immune metagene was constructed using the first principal component of a principal component analysis (PCA) involving CD3D and CXCL9 in order to improve robustness of the algorithm.
  • PCA principal component analysis
  • TIMG 0.526610 x CD3D + 0.850107 x CXCL9.
  • a positive coefficient indicates that increased expression of a gene is associated with a high probability of pCR, whereas a negative coefficient indicates an inverse association of the gene expression value with the probability of pCR.
  • NLRS ranged between -8.5 and 1.0 in the GeparTrio training cohort, and higher scores indicate a higher likelihood of achieving a pCR.
  • correlation clusters which were based on the discovery of a reference profile in a set of at least three genes (a smaller number of genes does not allow such a thing) . If the correlation of a given sample to the reference profile is large (close to 1), the patient is likely to achieve a pCR. If the correlation is negative (close to -1), she is likely not to achieve a pCR.
  • the training and feature selection of this model involved a constraint non-linear optimization which is not in the scope of this publication.
  • centroids are characteristic for each cluster, usually the vector of the class means of the gene expressions. Unknown samples are classified such that distance to each centroid is computed, and classification is then performed by comparison of these distances. Usually, the unknown sample is classified into the class whose centroid is nearest.
  • this single reference profile is determined as the parameter set fulfilling the constraints while minimizing square sum of the residuals (1-corr (ref, sample) ) A 2 for pCRs, (1+corr (ref, sample) ) A 2 for non-pCRs . Since we lose two degrees of freedom to the constraints, this approach is useful only when using sets of at least three genes .
  • a positive value indicates a positive association of expression level with the achievement of pCR whereas a negative value indicates a negative association.
  • ESRl estrogen receptor
  • PGR progesterone receptor
  • Her-2/neu status by immunohistochemistry and/or fluorescence in situ hybridization as well as to assess tumor grade by histopathology at diagnosis of breast cancer.
  • Combining these markers with clinical response after 2 cycles of neo-adjuvant chemotherapy (in-vivo chemoresistance test) it is possible to select a patient group in which the pCR rate will be up to 50%. Using this approach, patients still get 2 cycles of chemotherapy and there is still a substantial number of patients who do not benefit from chemotherapy and need other therapies .
  • Measurement of the markers for the algorithm can be performed on mRNA level using RT-kPCR or gene expression array platforms such as for example Affymetrix, Illumina or Planar Wave Guide or on protein level by, for example, immunological techniques such as immunohistochemistry .
  • the combined marker genes can be used in breast cancer for prediction of response to a taxane/anthracycline-containing chemotherapy in the adjuvant as well as in the neo-adjuvant setting.
  • the combined marker genes may be useful for prediction of taxane/anthracycline-response also in other cancer types.
  • the advantage of the here presented biomarker test is that prediction of therapy response is possible by a molecular test prior to start of chemotherapy.
  • the use of an "in-vivo chemoresistance test" by 2 cycles of chemotherapy is not necessary.
  • the combined assessment of several genes in an algorithm helps to overcome one main issue: This approach allows the resolution of the fact that there might be not one, but multiple reasons for a given response behaviour which is the case in a heterogeneous disease such as breast cancer. This situation cannot satisfactorily be resolved using single markers.
  • Tissue samples were obtained by core needle biopsies from patients with breast cancer (T4/T>2 cm, NO-3, MO) before start of neo-adjuvant chemotherapy with 4 or 6 cycles of docetaxel (75 mg/m 2 ) , doxorubin (50 mg/m 2 ) and cyclophosphamide (500 mg/m 2 ) (TAC) .
  • Pathological response was assessed in each patient following completion of therapy using the tissue preparation from surgery.
  • pCR no invasive tumor left in the breast or lymph nodes
  • TR tissue response
  • AKRlCl ERBB4, NFKBIA, TOP2A, AKR1C3, ESRl, OLFMl, TOP2B, ALCAM, FRAPl, PGR, TP53, BCL2, GADD45A, PRKABl, TUBAlA, C16orf45, HIFlA, PTPRC, TUBB, CA12, IGKC, RACGAPl, UBE2C, CD14, IKBKB, S100A7, VEGFA, CD247, KRT5, SEPT8, YBXl, CD3D, MAPK3, SLC2A1, CDKNlA, MAPT, SLC7A8, CHPTl, MLPH, SPONl,
  • Training was performed by using uni- and bivariate logistic regression. Since single extreme values (e.g. outliers) can adversely impact feature selection discovery was repeated for various subsets of training data to assess robustness. Random selection of m samples (out of n original samples) with putting back was used for training. In each discovery step, best genes (significance of regression coefficient less than some cutoff value, e.g. 5%) are selected.
  • informative genes predictive of response to taxane/anthracycline-containing neo-adjuvant cytotoxic chemotherapy were also identified in fresh-frozen breast cancer samples profiled by Affymetrix U133A microarrays. Again, samples were divided in three molecular subgroups according to ESRl and HER2/NEU mRNA expression: Luminal (HER2/NEU neg.;ESRl pos.), Basal / triple negative (HER2/NEU neg., ESRl neg.) and HER2 (HER2/NEU pos.) . Best significant informative genes for univariate separation of patients with pCR vs. patients without pCR were identified by standard t test statistics. Genuine multivariate classifiers can be built from that.
  • the genes examined in this approach were ABCCl, ACOX2, AKR1C3,
  • ESRl ESRl, FRAPl, IGKC, MAPK3, MAPT, MLPH, MMPl,
  • MUCl MVP, NFKBIA, PGR, PTPRC, RACGAPl,
  • Table 7 Differentially expressed genes, pCR, all tumors Genes expressed differentially with regard to tissue response vs. no tissue response in all tumors are shown in table 8, below.
  • Table 12 tissue response vs. no tissue response in ER- tumors Genes expressed differentially with regard to pCR vs. no pCR in luminal tumors are shown in table 13, below.
  • Table 16 tissue response vs. no tissue response in basal / triple negative tumors Genes expressed differentially with regard to pCR vs. no pCR in HER+ tumors are shown in table 17, below.
  • Luminal pCR ⁇ CD3D 0,00089 43,4 0,86 86%/86%/71% 0.16/0.16/0.0
  • TissueResponse ⁇ MMP1 + 1 ,60E-06 33,2 0,97 100%/93%/87% 0.85/0.68/0.5
  • p designates the significance from Omnibus-Test for logistic Model
  • AUC designates the Area under ROC-Curve
  • BIC designates the Bayesian information criterion Specificity refers to the specificity for sensitivities of 70%, 80%, 90% respectively.
  • Threshold refers to threshold for fitted probability, to reach sensitivities of 70%, 80%, 90% respectively.
  • Fig. 8 all tumors
  • Fig. 9 ER+
  • Fig. 10 ER- tumors
  • Fig. 11 luminal tumors
  • Fig. 8 all tumors
  • Fig. 9 ER+
  • Fig. 10 ER- tumors
  • Fig. 11 luminal tumors
  • Fig. 8 all tumors
  • Fig. 9 ER+
  • Fig. 10 ER- tumors
  • Fig. 11 luminal tumors
  • Figs. 8 to 13 shows the values for BIC and AUC as related to the number of genes used in the respective algorithm.
  • the middle panel of Figs. 8 to 13 shows the fitted probabilities of the exemplary algorithm as indicated in the middle panel.
  • FIG. 13 shows the ROC curve of the exemplary algorithm as indicated in the middle panel.
  • Table 17 shows 4 informative genes obtained through this approach.
  • Neoadjuvant chemotherapy in breast cancer significantly enhanced response with docetaxel. J Clin Oncol. 2002 Mar 15; 20 ( 6) : 1456-66.
  • Perez SA Karamouzis MV, Skarlos DV, Ardavanis A, Sotiriadou NN, Iliopoulou EG, Salagianni ML, Orphanos G,
  • the erbB2+ cluster of the intrinsic gene set predicts tumor response of breast cancer patients receiving neoadjuvant chemotherapy with docetaxel, doxorubicin and cyclophosphamide within the GEPARTRIO trial.

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Abstract

L'invention porte sur une méthode permettant de prédire une réponse à une chimiothérapie et/ou le bénéfice apportée par celle-ci chez un patient souffrant d'un cancer. La méthode comprend les étapes consistant à (i) classifier une tumeur en au moins deux classes, (ii) déterminer dans un échantillon de tumeur l'expression d'au moins un gène marqueur indicateur d'une réponse à une chimiothérapie pour une tumeur dans chaque classe respective, (iii) selon ladite expression génique, prédire ladite réponse et/ou ledit bénéfice; ledit ou lesdits gènes marqueurs comprenant un gène choisi dans le groupe constitué par les gènes TMSL8, ABCC1, EGFR, MVP, ACOX2, HER2/NEU, MYH11, TOB1, AKR1C1, ERBB4, NFKB1A, TOP2A, AKR1C3, ESR1, OLFM1, TOP2B, ALCAM, FRAP1, PGR, TP53, BCL2, GADD45A, PRKAB1, TUBA1A, C16orf45, HIF1A, PTPRC, TUBB, CA12, 1GKC, RACGAP1, UBE2C, CD14, 1KBKB, S100A7, VEGFA, CD247, KRT5, SEPT8, YBX1, CD3D, MAPK3, SLC2A1, CDKN1A, MAPT, SLC7A8, CHPT1, MLPH, SPON1, CXCL13, MMP1, STAT1, CXCL9, MMP7, STC2, DCN, MUC1, STMN1 et les associations de ceux-ci.
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