WO2012045019A2 - Déficit en gène brca et méthodes d'utilisation associées - Google Patents

Déficit en gène brca et méthodes d'utilisation associées Download PDF

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WO2012045019A2
WO2012045019A2 PCT/US2011/054369 US2011054369W WO2012045019A2 WO 2012045019 A2 WO2012045019 A2 WO 2012045019A2 US 2011054369 W US2011054369 W US 2011054369W WO 2012045019 A2 WO2012045019 A2 WO 2012045019A2
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expression
genes
ccp
sample
brca
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PCT/US2011/054369
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WO2012045019A9 (fr
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Kirsten Timms
Darl Flake
Jennifer Potter
Jerry Lanchbury
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Myriad Genetics, Inc.
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Priority to CA2813257A priority Critical patent/CA2813257A1/fr
Publication of WO2012045019A2 publication Critical patent/WO2012045019A2/fr
Publication of WO2012045019A9 publication Critical patent/WO2012045019A9/fr
Priority to US13/852,129 priority patent/US20140024028A1/en

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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
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
    • 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
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression

Definitions

  • the invention generally relates to a molecular classification of disease and particularly to methods and compositions for determining BRCA deficiency.
  • BRCA1 and BRCA2 The breast and ovarian cancer susceptibility genes, BRCA1 and BRCA2, were discovered in patients having a family history of breast or ovarian cancer. Miki et al., SCIENCE (1994) 266:66-71.
  • the BRCA genes are tumor suppressors found deficient in a large proportion of solid tumors. For example, a significant proportion of sporadic breast and ovarian cancers harbor somatic BRCA mutations. Due to the critical role of BRCA deficiency in tumor formation and progression, identifying BRCA deficiency can be very important, inter alia, in the individualized clinical management of cancer patients ⁇ e.g., chemoselection). Thus, it is desirable to identify new markers and methods for detecting BRCA deficiency.
  • BRCA cell-cycle progression
  • CCP cell-cycle progression
  • the invention provides a method for determining gene expression comprising measuring the expression of BRCA1 and/or BRCA2 (BRCA expression) in a sample and measuring the expression of a panel of CCP genes in the sample. Some embodiments further comprise determining whether BRCA expression is correlated to CCP expression. Some embodiments further comprise analyzing methylation in BRCA1 and/or BRCA2 in the sample.
  • Another aspect of the invention provides a method for determining whether a sample is BRCA deficient comprising measuring the expression of BRCA1 and/or BRCA2 (BRCA expression) in said sample and measuring the expression of a panel of CCP genes in the sample. Some embodiments further comprise determining whether BRCA expression is correlated to CCP expression. In some embodiments, anti-correlation between BRCA and CCP expression indicates the sample is BRCA deficient. In some embodiments anti-correlation between BRCA and CCP expression indicates the sample has BRCA hypermethylation. Some embodiments further comprise analyzing methylation in BRCA1 and/or BRCA2 in the sample.
  • the panel of CCP genes comprises at least two (or five, or six, or ten, or 15) CCP genes from any of Tables 1 to 5 or Panels A to G. In some embodiments the panel of CCP genes comprises the genes in any of Tables 1 to 5 or Panels A to G.
  • determining the expression of a panel of genes comprising CCP genes involves determining the expression of a plurality of test genes comprising at least 4, 6, 8, 10, 15 or more CCP genes and deriving a test value from the determined expression, wherein the CCP genes are weighted to contribute at least 50%, at least 75% or at least 85% of the test value.
  • the invention provides a method for determining whether a sample is BRCA deficient comprising (1) determining in a sample from a patient (a) the expression of BRCAI and/or BRCA2, and (b) the expression of a panel of genes including at least 4 or at least 8 cell-cycle genes; (2) providing a test value by (a) weighting the determined expression of each of a plurality of test genes selected from the panel of genes with a predefined coefficient, and (b) combining the weighted expression to provide the test value, wherein the cell-cycle genes are weighted to contribute at least 50%, at least 75% or at least 85% of the test value; and (3) comparing the test value to the expression of BRCAI and/or BRCA2 to determine whether these are correlated or anti-correlated.
  • the method further comprises (4) correlating an anti- correlation between the test value and BRCAI and/or BRCA2 expression to BRCA deficiency.
  • BRCA deficiency is associated with various characteristics in tumors.
  • the invention provides a method of classifying a cancer comprising measuring the expression of BRCAI and/or BRCA2 (BRCA expression) in said sample and measuring the expression of two or more CCP genes in the sample. Some embodiments further comprise determining whether BRCA expression is correlated to CCP expression.
  • anti-correlation between BRCA and CCP expression indicates any one of the following: greater likelihood of survival (e.g., progression- free survival, overall survival, etc.), greater likelihood of response to DNA damaging agents (e.g., platinum chemotherapy drugs, etc.), greater likelihood of response to drugs targeting the poly (ADP-ribose) polymerase (PARP) pathway, etc.
  • Some embodiments further comprise determining whether BRCAI and/or BRCA2 is hypermethylated.
  • gene expression is determined using any of the following techniques: quantitative PCRTM (e.g., TaqManTM), microarray hybridization analysis, quantitative sequencing, etc.
  • methylation is analyzed using any of the following techniques: Southern blotting, single nucleotide primer extension, methylation-specific polymerase chain reaction (MSPCR), restriction landmark genomic scanning for methylation (RLGS-M) and CpG island microarray, single nucleotide primer extension (SNuPE), combined bisulfite restriction analysis (COBRA), etc.
  • the invention provides systems related to the above methods of the invention.
  • the invention provides a system for determining gene expression in a tumor sample, comprising: (1) a sample analyzer for determining the expression levels of BRCAI and/or BRCA2 and a panel of genes comprising at least two CCP genes in a sample, wherein the sample analyzer contains the sample, mRNA from the sample and expressed from the panel of genes, or cDNA synthesized from said mRNA; (2) a first computer program for (a) receiving gene expression data on BRCAI and/or BRCA2, (b) receiving gene expression data on at least two test genes selected from the panel of genes, (c) weighting the determined expression of each of the test genes with a predefined coefficient, and (d) combining the weighted expression to provide a CCP test value representing the expression level of the panel of genes.
  • the above system further comprises a computer program for comparing the expression of BRCAI and/or BRCA2 to the CCP test value, wherein high expression of BRCAI and/or BRCA2 coupled with a high CCP test value indicates BRCA and CCP expression are correlated, wherein low expression of BRCAI and/or BRCA2 coupled with a low CCP test value indicates BRCA and CCP expression are correlated, wherein high expression of BRCAI and/or BRCA2 coupled with a low CCP test value indicates BRCA and CCP expression are anti- correlated, and wherein low expression of BRCAI and/or BRCA2 coupled with a high CCP test value indicates BRCA and CCP expression are anti-correlated.
  • the above system further comprises a computer program for receiving data on the correlation between BRCA expression and CCP expression in a patient sample and concluding that the sample is BRCA deficient if BRCA expression and CCP expression are anti-correlated in the sample.
  • the system comprises a sample analyzer for determining the methylation status of BRCAI and/or BRCA2.
  • the invention provides a kit for practicing the methods and for use in the systems of the present invention.
  • the kit may include a carrier for the various components of the kit.
  • the carrier can be a container or support, in the form of, e.g., bag, box, tube, rack, and is optionally compartmentalized.
  • the carrier may define an enclosed confinement for safety purposes during shipment and storage.
  • the kit includes various components useful in determining the expression of
  • the kit many include oligonucleotides specifically hybridizing under high stringency to mRNA or cDNA of BRCAI, BRCA2, or the genes in Tables 1 to 5 or Panels A to F. Such oligonucleotides can be used as PCR primers in RT-PCR reactions, or hybridization probes.
  • BRCA status Various techniques for determining BRCA status are known to those skilled in the art.
  • the whole genome of one or more cells is determined and the sequence of a BRCA gene found within that genome is analyzed for mutations.
  • a BRCA gene is specifically sequenced, which may include exon sequencing, sequencing of exons along with at least some amount of flanking intronic sequence, or sequencing of the entire genomic region containing the BRCA gene of interest. Copy number analysis may also be used.
  • large rearrangement analysis is used to determine whether large portions of the BRCA gene (or even the entire gene) have been deleted or duplicated.
  • methylation analysis is used to determine BRCA status.
  • Figure 1 illustrates how the predictive power of CCP gene signatures varies with the number of CCP genes.
  • Figure 2 illustrates the relationship between BRCA1 and cell-cycle expression.
  • Figure 3 illustrates embodiments of computer systems of the invention.
  • Figure 4 illustrates embodiments of computer-implemented methods of the invention.
  • Figure 5 illustrates the correlation between BRCA-CCP expression anti- correlation and BRCA1 hypermethylation.
  • Figure 6 shows the pairwise relationships between BRCA1 qPCR assays.
  • Figure 7 a histogram of BRCA1 expression as measured by qPCR.
  • Figure 8 shows the relationship between each of the cell-cycle genes and the
  • Figure 9 shows CCP score and BRCA1 expression.
  • Figure 10 shows CCP score and BRCAl expression separated by
  • Figure 11 shows the relationship between BRCAl promoter methylation
  • Figure 12 shows the relationship between CCP score and BRCAl expression in samples with BRCAl methylation data.
  • the size of the points represents the degree of BRCAl methylation.
  • Each point is colored by tumor subtype as identified by IHC
  • the invention generally provides compositions and methods for determining BRCA status.
  • the invention provides a method for determining gene expression comprising measuring the expression of BRCAl and/or BRCAl (BRCA expression) in a sample and measuring the expression of a panel of CCP genes in the sample. Some embodiments further comprise determining whether BRCA expression is correlated to CCP expression. Some embodiments further comprise analyzing methylation in BRCAl and/or BRCAl in the sample.
  • Another aspect of the invention provides a method for determining whether a sample is BRCA deficient comprising measuring the expression of BRCAl and/or BRCAl (BRCA expression) in said sample and measuring the expression of a panel of CCP genes in the sample.
  • BRCA deficient and BRCA deficiency mean attenuated cellular activity of BRCAl and/or BRCA2 protein.
  • CCP gene refers to a gene whose expression level closely tracks the progression of the cell through the cell-cycle. See, e.g., Whitfield et al, MOL. BIOL. CELL (2002) 13: 1977-2000. More specifically, CCP genes show periodic increases and decreases in expression that coincide with certain phases of the cell cycle— e.g., STK15 and PLK show peak expression at G2/M. Id. Often CCP genes have clear, recognized cell- cycle related function— e.g. , in DNA synthesis or repair, in chromosome condensation, in cell- division, etc.
  • CCP genes have expression levels that track the cell-cycle without having an obvious, direct role in the cell-cycle—e.g., UBE2S encodes a ubiquitin-conjugating enzyme, yet its expression closely tracks the cell-cycle.
  • a CCP gene according to the present invention need not have a recognized role in the cell-cycle.
  • Exemplary CCP genes are listed in Tables 1 (Table 1 as shown in U.S. provisional application Serial No.
  • Whether a particular gene is a CCP gene may be determined by any technique known in the art, including that taught in Whitfield et al, MOL. BIOL. CELL (2002) 13: 1977-2000.
  • a sample of cells e.g., HeLa cells
  • RNA is extracted from the cells after arrest in each phase and gene expression is quantitated using any suitable technique—e.g. , expression microarray (genome-wide or specific genes of interest), real-time quantitative PCRTM (RTQ-PCR). Finally, statistical analysis ⁇ e.g., Fourier Transform) is applied to determine which genes show peak expression during particular cell- cycle phases. Genes may be ranked according to a periodicity score describing how closely the gene's expression tracks the cell-cycle— e.g., a high score indicates a gene very closely tracks the cell cycle. Finally, those genes whose periodicity score exceeds a defined threshold level ⁇ see Whitfield et al, MOL. BIOL. CELL (2002) 13: 1977-2000) may be designated CCP genes.
  • PAICS* 10606 Hs00272390_ml NM 001079525.1;
  • ABI Assay ID means the catalogue ID number for the gene expression assay commercially available from Applied Biotech
  • Various embodiments of the invention involve determining the expression of genes (e.g., BRCA1, BRCA2, CCP genes, etc.) in a sample.
  • expression level means the amount (normalized or absolute) of an analyte associated with that gene in a sample.
  • the level of BRCA1 expression can be the amount of BRCA1 transcript (or cDNA reverse transcribed from such transcript) or protein in a sample.
  • Gene expression can be determined either at the R A level (i.e., noncoding RNA (ncRNA), mRNA, miRNA, tRNA, rRNA, snoRNA, siRNA and piRNA) or at the protein level.
  • Expression analysis at the RNA level can be done using, e.g., microarray analysis (e.g., for assaying mRNA or microRNA expression, copy number, etc.), quantitative real-time PCRTM ("qRT-PCRTM", e.g., TaqManTM), etc.
  • Levels of proteins in a tumor sample can be determined by any known techniques in the art, e.g., HPLC, mass spectrometry, or using antibodies specific to selected proteins (e.g., IHC, ELISA, etc.).
  • the activity level of a polypeptide encoded by a gene may be used in much the same way as the expression level of the gene or polypeptide. Often higher activity levels indicate higher expression levels while lower activity levels indicate lower expression levels. Thus, in some embodiments, the activity level of a polypeptide encoded by a gene is determined rather than or in addition to the expression level of the gene.
  • Those skilled in the art are familiar with techniques for measuring the activity of various such proteins, including BRCA1, BRCA2, and those encoded by the genes listed in Tables 1 to 5. The methods of the invention may be practiced independent of the particular technique used.
  • the expression of one or more normalizing genes is also obtained for use in normalizing the expression of test genes.
  • normalizing genes referred to the genes whose expression is used to calibrate or normalize the measured expression of the gene of interest (e.g., test genes).
  • the expression of normalizing genes should be independent of cancer outcome/prognosis, and the expression of the normalizing genes is very similar among all the tumor samples. Normalization ensures accurate comparison of expression of a test gene between different samples. For this purpose, housekeeping genes known in the art can be used.
  • Housekeeping genes are well known in the art, with examples including, but are not limited to, GUSB (glucuronidase, beta), HMBS (hydroxymethylbilane synthase), SDHA (succinate dehydrogenase complex, subunit A, flavoprotein), UBC (ubiquitin C) and YWHAZ (tyrosine 3- monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide).
  • GUSB glucose curonidase, beta
  • HMBS hydroxymethylbilane synthase
  • SDHA succinate dehydrogenase complex, subunit A, flavoprotein
  • UBC ubiquitin C
  • YWHAZ tyrosine 3- monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide.
  • One or more housekeeping genes can be used.
  • at least 2, 5, 10 or 15 housekeeping genes are used to provide a combined normalizing gene set.
  • RNA levels for the genes In the case of measuring RNA levels for the genes, one convenient and sensitive approach is the real-time quantitative PCRTM (qPCRTM) assay, following a reverse transcription reaction. Typically, a cycle threshold (C t ) is determined for each test gene and each normalizing gene, i.e., the number of cycles at which the fluoescence from a qPCR reaction above background is detectable.
  • C t cycle threshold
  • the overall expression of the one or more normalizing genes can be represented by a "normalizing value" which can be generated by combining the expression of all normalizing genes, either weighted equally (straight addition or averaging) or by different predefined coefficients.
  • the normalizing value C can be the cycle threshold (C t ) of one single normalizing gene, or an average of the C t values of 2 or more, preferably 10 or more, or 15 or more normalizing genes, in which case, the predefined coefficient is 1/N, where N is the total number of normalizing genes used.
  • H (Qm + Qm + " C t Hn)/N.
  • the methods of the invention generally involve determining the level of expression of a panel of CCP genes. With modern high-throughput techniques, it is often possible to determine the expression level of tens, hundreds or thousands of genes. Indeed, it is possible to determine the level of expression of the entire transcriptome (i.e. , each transcribed gene in the genome). Once such a global assay has been performed, one may then informatically analyze one or more subsets (i.e. , panels) of genes. For example, one may analyze the expression of a panel comprising primarily CCP genes according to the present invention by combining the expression level values of the individual test genes to obtain a test value.
  • test value represents the overall expression level of the panel of test genes (e.g. , a panel composed of substantially CCP genes).
  • the test value representing the overall expression of the plurality of test genes can be provided by combining the normalized expression of all test genes, either by straight addition or averaging (i.e., weighted equally) or by a different predefined coefficient.
  • test value (AQi + AC T 2 + ' " + AQ n )/n.
  • test value (AQi + AC T 2 + ' " + AQ n )/n.
  • such determining step may comprise: (1) determining the expression of a panel of genes in the sample comprising at least two CCP genes; and (2) providing a test value by (a) weighting the determined expression of each of a plurality of test genes selected from said panel of genes with a predefined coefficient, and (b) combining the weighted expression to provide said test value.
  • This test value represents the level of expression of the panel of genes in the sample.
  • the test value will often be compared to BRCA expression in order to determine whether the two are correlated or anti- correlated.
  • anti-correlation indicates BRCA deficiency.
  • the methods of the invention comprise determining the status of a panel (i.e., a plurality) of test genes comprising a plurality of CCP genes (e.g., to provide a test value representing the average expression of the test genes).
  • a panel i.e., a plurality
  • CCP genes e.g., to provide a test value representing the average expression of the test genes.
  • increased expression in a panel of test genes may refer to the average expression level of all panel genes in a particular patient being higher than the average expression level of these genes in normal patients (or higher than some index value that has been determined to represent the normal average expression level).
  • increased expression in a panel of test genes may refer to increased expression in at least a certain number (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30 or more) or at least a certain proportion (e.g., 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, 100%) of the genes in the panel as compared to the average normal expression level.
  • a certain number e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30 or more
  • a certain proportion e.g., 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, 100%
  • the plurality of test genes (which may itself be a sub- panel analyzed informatically) comprises at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 70, 80, 90, 100, 200, or more CCP genes. In some embodiments the plurality of test genes comprises at least 10, 15, 20, or more CCP genes. In some embodiments the plurality of test genes comprises between 5 and 100 CCP genes, between 7 and 40 CCP genes, between 5 and 25 CCP genes, between 10 and 20 CCP genes, or between 10 and 15 CCP genes. In some embodiments CCP genes comprise at least a certain proportion of the plurality of test genes used to provide a test value.
  • the plurality of test genes comprises at least 25%, 30%>, 40%>, 50%>, 60%>, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or 100% CCP genes.
  • the plurality of test genes comprises at least 10, 15, 20, 25, 30, 35, 40, 45, 50, 70, 80, 90, 100, 200, or more CCP genes, and such CCP genes constitute at least 50%, 60%, 70%, preferably at least 75%, 80%, 85%, more preferably at least 90%, 95%, 96%, 97%, 98%, or 99% or more of the total number of genes in the plurality of test genes.
  • the CCP genes are the genes in any one of Table 1 and
  • test panel comprises at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 25, 30, or more of the genes in any of Tables 1 to 5 and Panels A to F.
  • invention provides methods comprising determining (e.g. , in a sample) the expression of the genes in any one of Tables 1 to 5 and Panels A to F.
  • Assays of 126 CCGs and 47 HK (housekeeping) genes were run against 96 commercially obtained, anonymous prostate tumor FFPE samples without outcome or other clinical data. The working hypothesis was that the assays would measure with varying degrees of accuracy the same underlying phenomenon (cell cycle proliferation within the tumor for the CCGs, and sample concentration for the HK genes). Assays were ranked by the Pearson's correlation coefficient between the individual gene and the mean of all the candidate genes, that being the best available estimate of biological activity. Rankings for these 126 CCGs according to their correlation to the overall CCG mean are reported in Table 6.
  • the individual predictive power of each gene may be used to rank them in importance.
  • the inventors have determined that the CCGs in Panel C can be ranked as shown in Table 10 below according to the predictive power of each individual gene.
  • the CCGs in Panel F can be similarly ranked as shown in Table 11 below.
  • the plurality of test genes comprises the top 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 25, 30, 35, 40 or more genes listed in Table 6, 7, 9, 10, or 11.
  • the plurality of test genes comprises at least some number of CCGs ⁇ e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs) and this plurality of CCGs comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20 of the following genes: ASPM, BIRC5, BUB1B, CCNB2, CDC2, CDC20, CDCA8, CDKN3, CENPF, DLGAP5, FOXM1, KIAA0101, KIF11, KIF2C, KIF4A, MCM10, NUSAP1, PRC1, RACGAPl, and TPX2.
  • the plurality of test genes comprises at least some number of CCGs (e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs) and this plurality of CCGs comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20 of the following genes: TPX2, CCNB2, KIF4A, KIF2C, BIRC5, RACGAP1, CDC2, PRC1, DLGAP5/DLG7, CEP55, CCNB1, TOP2A, CDC20, KIF20A, BUB1B, CDKN3, NUSAP1, CCNA2, KIF11, and CDCA8.
  • CCGs e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs
  • this plurality of CCGs comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20 of the following genes: TPX2, CCNB2, KIF4A, KIF2C, BIRC
  • the plurality of test genes comprises at least some number of CCGs ⁇ e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs) and this plurality of CCGs comprises any one, two, three, four, five, six, seven, eight, nine, or ten or all of gene numbers 1 & 2, 1 to 3, 1 to 4, 1 to 5, 1 to 6, 1 to 7, 1 to 8, 1 to 9, or 1 to 10 of any of Table 6, 7, 9, 10, or 11.
  • the plurality of test genes comprises at least some number of CCGs ⁇ e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs) and this plurality of CCGs comprises any one, two, three, four, five, six, seven, eight, or nine or all of gene numbers 2 & 3, 2 to 4, 2 to 5, 2 to 6, 2 to 7, 2 to 8, 2 to 9, or 2 to 10 of any of Table 6, 7, 9, 10, or 11.
  • the plurality of test genes comprises at least some number of CCGs ⁇ e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs) and this plurality of CCGs comprises any one, two, three, four, five, six, seven, or eight or all of gene numbers 3 & 4, 3 to 5, 3 to 6, 3 to 7, 3 to 8, 3 to 9, or 3 to 10 of any of Table 6, 7, 9, 10, or 11.
  • the plurality of test genes comprises at least some number of CCGs ⁇ e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs) and this plurality of CCGs comprises any one, two, three, four, five, six, or seven or all of gene numbers 4 & 5, 4 to 6, 4 to 7, 4 to 8, 4 to 9, or 4 to 10 of any of Table 6, 7, 9, 10, or 11.
  • the plurality of test genes comprises at least some number of CCGs ⁇ e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more CCGs) and this plurality of CCGs comprises any one, two, three, four, five, six, seven, eight, nine, 10, 11, 12, 13, 14, or 15 or all of gene numbers 1 & 2, 1 to 3, 1 to 4, 1 to 5, 1 to 6, 1 to 7, 1 to 8, 1 to 9, 1 to 10, 1 to 11, 1 to 12, 1 to 13, 1 to 14, or 1 to 15 of any of Table 6, 7, 9, 10, or 11.
  • CCP signatures the particular CCP genes analyzed is often not as important as the total number of CCP genes.
  • the number of CCP genes analyzed can vary depending on many factors, e.g., technical constraints, cost considerations, the classification being made, the cancer being tested, the desired level of predictive power, etc.
  • Increasing the number of CCP genes analyzed in a panel according to the invention is, as a general matter, advantageous because, e.g., a larger pool of genes to be analyzed means less "noise" caused by outliers and less chance of an error in measurement or analysis throwing off the overall predictive power of the test.
  • cost and other considerations will sometimes limit this number and finding the optimal number of CCP genes for a signature is desirable.
  • P is the predictive power (i.e., P Sil is the predictive power of a signature with n genes and P Sil+i is the predictive power of a signature with n genes plus one) and Co is some optimization constant.
  • Predictive power can be defined in many ways known to those skilled in the art including, but not limited to, the signature's p-value.
  • Co can be chosen by the artisan based on his or her specific constraints. For example, if cost is not a critical factor and extremely high levels of sensitivity and specificity are desired, Co can be set very low such that only trivial increases in predictive power are disregarded. On the other hand, if cost is decisive and moderate levels of sensitivity and specificity are acceptable, Co can be set higher such that only significant increases in predictive power warrant increasing the number of genes in the signature.
  • a graph of predictive power as a function of gene number may be plotted (as in FIG.l) and the second derivative of this plot taken.
  • the point at which the second derivative decreases to some predetermined value (Co') may be the optimal number of genes in the signature.
  • Example 1 and FIG.l illustrate the empirical determination of optimal numbers of CCP genes in CCP panels of the invention. Randomly selected subsets of the 31 CCP genes listed in Table 3 were tested as distinct CCP signatures and predictive power (i.e., p-value) for predicting prostate cancer recurrence was determined for each. As FIG.1 shows, p-values ceased to improve significantly beyond about 10 to 15 CCP genes, thus indicating that a preferred number of CCP genes in a diagnostic or prognostic panel is from about 10 to about 15. Thus some
  • embodiments of the invention provide methods comprising determining the expression of a panel of genes, wherein the panel comprises between about 10 and about 15 CCP genes.
  • the panel comprises between about 10 and about 15 CCP genes and the CCP genes constitute at least 25%, 30%, 40%, 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or 100% of the panel. Any other combination of CCP genes (including any of those listed in Table 1 or Panels A through G) can be used to practice the invention.
  • Determining expression levels can be, to varying degrees, quantitative, qualitative, or both. For example, when determining the BRCA1 mRNA transcript levels in a sample, the absolute number of transcripts can be determined. Alternatively, the absolute number of transcripts may be normalized against some standard as discussed above to yield a relative rather than absolute expression level.
  • tissue samples may be stained with an antibody against BRCA1 protein and the level of staining in tumor cells can be assigned certain semi-quantitative numbers (e.g., -1 , 0, +1). Assigning particular expression levels in this way will often be based on an internal control (e.g., surrounding non-tumor cells) or an external control (e.g., unrelated BRCA-intact cells).
  • an internal control e.g., surrounding non-tumor cells
  • an external control e.g., unrelated BRCA-intact cells.
  • a panel plural of genes (e.g., CCP genes).
  • Increased expression in this context will mean the average expression is higher than the average expression level of these genes in normal patients (or higher than some index value, e.g. , a value that has been determined to represent the average expression level in a reference population (e.g.
  • a certain number e.g., 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30 or more
  • a certain proportion e.g., 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, 100%
  • one may determine the expression of a panel of genes by determining the absolute copy number of the mRNA (or protein) of all the genes in the panel and either total or average these across the genes.
  • the test value representing the expression level of a test gene (e.g., BRCA1) or a plurality of test genes (e.g., a panel of CCP genes) is compared to one or more reference values (or index values) to determine if expression of the test gene(s) is high, low, average, etc.
  • a test gene e.g., BRCA1
  • a plurality of test genes e.g., a panel of CCP genes
  • index values may represent the gene expression levels found in a normal sample obtained from the patient of interest, in which case an expression level (e.g., test value) in the test sample significantly above this index value would indicate high expression in the sample.
  • the index value may represent the average expression level for a set of individuals from a diverse population or a subset of the population. For example, one may determine the average expression level of a gene or gene panel in a random sampling of patients. This average expression level may be termed the "threshold index value.”
  • the methods comprise determining whether the expression of one or more test genes is "increased” or "high.”
  • "increased" or "high” expression of a test gene means the patient's expression level is either elevated over a normal index value or a threshold index (e.g. , by at least some threshold amount (e.g. , a standard deviation)) or within the range of expression that has been determined in patients to be high (e.g., top quartile of reference patients).
  • index values may be derived by dividing patients into groups based on expression level. For example, one may determine the level of expression of the test gene(s) for a set of patients and group the patients into terciles, quartiles, quintiles, etc. A threshold may be set at the boundary of each group, with test patients being placed into a group (e.g., quartile) depending on which threshold(s) their determined expression exceeds.
  • index values may be determined thusly:
  • risk groups e.g., high likelihood of having cancer, high likelihood of
  • a threshold value will be set for the cell cycle mean.
  • the optimal threshold value is selected based on the receiver operating characteristic (ROC) curve, which plots sensitivity vs (1 - specificity). For each increment of the cell cycle mean, the sensitivity and specificity of the test is calculated using that value as a threshold.
  • the actual threshold will be the value that optimizes these metrics according to the artisan's requirements (e.g., what degree of sensitivity or specificity is desired, etc.).
  • the invention provides a method for determining whether a sample is BRCA deficient comprising measuring the expression of BRCAI and/or BRCA2 (BRCA expression) in said sample, measuring the expression of a panel of CCP genes in the sample, and determining whether BRCA expression is correlated to CCP expression.
  • BRCA and CCP expression are "correlated" in a sample if BRCA and CCP expression are both high, low, or intermediate in the sample.
  • BRCA and CCP expression are "anti-correlated" in a sample if one is low while the other is high or if one is either high or low and the other is
  • BRCA and CCP expression are anti- correlated if BRCA (especially BRCAI) expression is low and CCP expression (especially expression of one of the panels in Tables 1 to 5 ⁇ e.g., Panels A to F)) is high.
  • the sample is from a patient having (or suspected of having) ovarian cancer, breast cancer, lung cancer, colon cancer, or prostate cancer, or any combination of these.
  • the sample is a tumor tissue sample, a blood or blood derivative ⁇ e.g., serum, plasma) sample, a urine sample, or any other sample derived from the body of a patient.
  • the sample used to determine expression levels is some derivative of these bodily samples ⁇ e.g., an isolate of the RNA, DNA, protein, etc. from a bodily sample).
  • the invention provides a method for determining whether a sample is BRCA deficient comprising measuring the expression of BRCAI and/or BRCA2 (BRCA expression) in said sample, measuring the expression of a panel of CCP genes in the sample, and determining whether BRCA expression is correlated to CCP expression, wherein anti-correlation between BRCA and CCP expression indicates the sample is BRCA deficient.
  • anti-correlation between BRCA and CCP expression indicates the sample has BRCA hypermethylation.
  • Some embodiments further comprise
  • methylation status is used to indicate the presence or absence or the level or extent of methyl group modification in the polynucleotide of at least one gene.
  • methylation level is used to indicate the quantitative measurement of methylated DNA for a given gene, defined as the percentage of total DNA copies of that gene that are determined to be methylated, based on quantitative methylation-specific PCR.
  • any assay that can be employed to determine the methylation status of the gene or gene panel should suffice for the purposes of the present invention.
  • assays are designed to assess the methylation status of individual genes, or portions thereof.
  • types of assays used to assess the methylation pattern include, but are not limited to, Southern blotting, single nucleotide primer extension, methylation-specific polymerase chain reaction (MSPCR), restriction landmark genomic scanning for methylation (RLGS-M) and CpG island microarray, single nucleotide primer extension (SNuPE), and combined bisulfite restriction analysis (COBRA).
  • the COBRA technique is disclosed in Xiong & Laird, NUCLEIC ACIDS RES.
  • methylation arrays may also be employed to determine the methylation status of a gene or panel of genes. Methylation arrays are disclosed in Beier et al, ADV. BIOCHEM. ENG. BIOTECHNOL. (2007) 104: 1-11, which is incorporated by reference. For example, a method for determining the methylation state of nucleic acids is described in U.S. Pat. No. 6,017,704 which is incorporated by reference. Determining the methylation state of the nucleic acid includes amplifying the nucleic acid by means of oligonucleotide primers that distinguishes between methylated and unmethylated nucleic acids.
  • the panel of CCP genes comprises at least two (or five, or six, or ten, or 15, or more) CCP genes from any of Tables 1 to 5. In some embodiments the panel of CCP genes comprises at least two (or five, or six, or ten, or 15, or more) CCP genes from any of Tables 1 to 5. In some embodiments the panel of CCP genes comprises the genes listed in Table 4. In some embodiments the panel of CCP genes comprises the genes in Panel F. In some
  • the panel of CCP genes comprises the genes listed in Table 5.
  • the invention provides a method of classifying a cancer comprising measuring the expression of BRCA1 and/or BRCA2 (BRCA expression) in said sample and measuring the expression of two or more CCP genes in the sample. Some embodiments further comprise determining whether BRCA expression is correlated to CCP expression.
  • anti-correlation between BRCA and CCP expression indicates any one of the following: greater likelihood of survival ⁇ e.g., progression-free survival, overall survival, etc.), greater likelihood of response to DNA damaging agents ⁇ e.g., platinum chemotherapy drugs, etc.), greater likelihood of response to drugs targeting the poly (ADP- ribose) polymerase (PARP) pathway, etc.
  • a patient has an "increased likelihood" of some clinical feature or outcome (e.g., recurrence, progression, response to a particular therapeutic regimen, etc.) if the probability of the patient having the feature or outcome exceeds some reference probability or value.
  • the reference probability may be the probability of the feature or outcome across the general relevant patient population.
  • the probability of recurrence in the general breast cancer population is X% and a particular patient has been determined by the methods of the present invention to have a probability of recurrence of Y%, and if Y > X, then the patient has an "increased likelihood" of recurrence.
  • a threshold or reference value may be determined and a particular patient's probability of recurrence may be compared to that threshold or reference.
  • gene expression is determined using any of the following techniques: quantitative PCRTM (e.g., TaqManTM), microarray hybridization analysis, quantitative sequencing, etc.
  • results of any analyses according to the invention will often be communicated to physicians, genetic counselors and/or patients (or other interested parties such as researchers) in a transmittable form that can be communicated or transmitted to any of the above parties.
  • a transmittable form can vary and can be tangible or intangible.
  • the results can be embodied in descriptive statements, diagrams, photographs, charts, images or any other visual forms. For example, graphs showing expression or activity level or sequence variation information for various genes can be used in explaining the results. Diagrams showing such information for additional target gene(s) are also useful in indicating some testing results.
  • statements and visual forms can be recorded on a tangible medium such as papers, computer readable media such as floppy disks, compact disks, etc., or on an intangible medium, e.g., an electronic medium in the form of email or website on internet or intranet.
  • results can also be recorded in a sound form and transmitted through any suitable medium, e.g., analog or digital cable lines, fiber optic cables, etc., via telephone, facsimile, wireless mobile phone, internet phone and the like.
  • the information and data on a test result can be produced anywhere in the world and transmitted to a different location.
  • the information and data on a test result may be generated, cast in a transmittable form as described above, and then imported into the United States. Accordingly, the present invention also
  • the method comprises the steps of (1) determining at least one of (a) or (b) above according to methods of the present invention; and (2) embodying the result of the determining step in a transmittable form.
  • the transmittable form is the product of such a method.
  • the invention provides a system for determining gene expression in a tumor sample, comprising: (1) a sample analyzer for determining the expression levels of BRCAI and/or BRCA2 and a panel of genes comprising at least two CCP genes in a sample, wherein the sample analyzer contains the sample, mR A from the sample and expressed from the panel of genes, or cDNA synthesized from said mRNA; (2) a first computer program means for (a) receiving gene expression data on BRCAI and/or BRCA2, (b) receiving gene expression data on at least two test genes selected from the panel of genes, (b) weighting the determined expression of each of the test genes with a predefined coefficient, and (c) combining the weighted expression to provide a CCP test value representing the expression level of the panel of genes.
  • the systems of the invention may be used to determine whether BRCA and/or CCP expression in a sample are high, low, etc.
  • the above system further comprises a computer program means of comparing the expression of BRCAI and/or BRCA2 to a reference value, wherein expression of BRCAI and/or BRCA2 above this reference value indicates said BRCAI and/or BRCA2 expression is high.
  • the above system further comprises a computer program means of comparing the CCP test value to a reference value, wherein a CCP test value above this reference value indicates CCP expression is high.
  • the systems of the invention may be used to determine whether BRCA and CCP expression are correlated in a sample.
  • the above system further comprises a computer program means of comparing the expression of BRCA1 and/or BRCA2 to the CCP test value, wherein high expression of BRCA1 and/or BRCA2 coupled with a high CCP test value indicates BRCA and CCP expression are correlated, wherein low expression of BRCA1 and/or BRCA2 coupled with a low CCP test value indicates BRCA and CCP expression are correlated, wherein high expression of BRCA1 and/or BRCA2 coupled with a low CCP test value indicates BRCA and CCP expression are anti-correlated, and wherein low expression of BRCA1 and/or BRCA2 coupled with a high CCP test value indicates BRCA and CCP expression are anti-correlated.
  • the systems of the invention may be used to determine whether the sample is BRCA deficient.
  • the above system further comprises a computer program means of receiving data on the correlation between BRCA expression and CCP expression in a patient sample and concluding that the sample is BRCA deficient if BRCA expression and CCP expression are anti-correlated in the sample.
  • the system comprises a sample analyzer for
  • this sample analyzer is the same as the sample analyzer for determining gene expression.
  • the test genes may comprise at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 70, 80, 90, 100, 200, or more CCP genes.
  • the test genes comprise at least 10, 15, 20, or more CCP genes.
  • the test gene comprises between 5 and 100 CCP genes, between 7 and 40 CCP genes, between 5 and 25 CCP genes, between 10 and 20 CCP genes, or between 10 and 15 CCP genes.
  • CCP genes comprise at least a certain proportion of the test genes used to provide a test value.
  • the test genes comprise at least 25%, 30%, 40%, 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%), or 100%) CCP genes.
  • the test genes comprise at least 10, 15, 20, 25, 30, 35, 40, 45, 50, 70, 80, 90, 100, 200, or more CCP genes, and such CCP genes constitute at least 50%, 60%, 70%, preferably at least 75%, 80%, 85%, more preferably at least 90%, 95%, 96%), 97%), 98%), or 99% or more of the total number of test genes.
  • the system further comprises a display module displaying the comparison between the test value and the one or more reference values, or displaying a result of the comparing step.
  • the amount of R A transcribed from the panel of genes including test genes is measured in the sample.
  • the amount of RNA of one or more housekeeping genes in the sample is also measured, and used to normalize or calibrate the expression of the test genes, as described above.
  • the sample analyzer can be any instrument useful in determining gene expression, including, e.g., a sequencing machine, a real-time PCR machine, a microarray instrument, etc.
  • a sample analyzer for determining methylation status such a sample analyzer can be any instrument useful in determining methylation status.
  • the computer-based analysis function can be implemented in any suitable language and/or browsers. For example, it may be implemented with C language and preferably using object-oriented high-level programming languages such as Visual Basic, SmallTalk, C++, and the like.
  • the application can be written to suit environments such as the Microsoft WindowsTM environment including WindowsTM 98, WindowsTM 2000, WindowsTM NT, and the like.
  • the application can also be written for the MacintoshTM, SUNTM, UNIX or LINUX environment.
  • the functional steps can also be implemented using a universal or platform-independent programming language.
  • multi-platform programming languages include, but are not limited to, hypertext markup language (HTML), JAVATM, JavaScriptTM, Flash programming language, common gateway interface/structured query language (CGI/SQL), practical extraction report language (PERL), AppleScriptTM and other system script languages, programming
  • JavaTM- or JavaScriptTM-enabled browsers such as HotJavaTM, MicrosoftTM ExplorerTM, or NetscapeTM can be used.
  • active content web pages they may include JavaTM applets or ActiveXTM controls or other active content technologies.
  • the analysis function can also be embodied in computer program products and used in the systems described above or other computer- or internet-based systems. Accordingly, another aspect of the present invention relates to a computer program product comprising a computer-usable medium having computer-readable program codes or instructions embodied thereon for enabling a processor to carry out gene expression analysis. These computer program instructions may be loaded onto a computer or other programmable apparatus to produce a machine, such that the instructions which execute on the computer or other programmable apparatus create means for implementing the functions or steps described above.
  • These computer program instructions may also be stored in a computer-readable memory or medium that can direct a computer or other programmable apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory or medium produce an article of manufacture including instruction means which implement the analysis.
  • the computer program instructions may also be loaded onto a computer or other programmable apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other
  • programmable apparatus provide steps for implementing the functions or steps described above.
  • Some embodiments of the present invention provide a system for determining whether a patient sample is BRCA deficient.
  • the system comprises (1) computer program means for receiving, storing, and/or retrieving data on the correlation between BRCA and CCP expression in a patient sample; (2) computer program means for querying this patient data; (3) computer program means for concluding whether there is or is not a correlation; and optionally (4) computer program means for outputting/displaying this conclusion.
  • this means for outputting the conclusion may comprise a computer program means for informing a health care professional of the conclusion.
  • the system further comprises a computer program means for receiving, storing, and/or retrieving data on BRCA and CCP expression in a patient sample and a computer program means for determining if BRCA and CCP expression are correlated in such sample.
  • Computer system [300] may include at least one input module [330] for entering patient data into the computer system [300] .
  • the computer system [300] may include at least one output module [324] for indicating whether a patient has an increased or decreased likelihood of response and/or indicating suggested treatments determined by the computer system [300] .
  • Computer system [300] may include at least one memory module [306] in communication with the at least one input module [330] and the at least one output module [324] .
  • the at least one memory module [306] may include, e.g., a removable storage drive [308], which can be in various forms, including but not limited to, a magnetic tape drive, a floppy disk drive, a VCD drive, a DVD drive, an optical disk drive, etc.
  • the removable storage drive [308] may be compatible with a removable storage unit [310] such that it can read from and/or write to the removable storage unit [310].
  • Removable storage unit [310] may include a computer usable storage medium having stored therein computer-readable program codes or instructions and/or computer readable data.
  • removable storage unit [310] may store patient data.
  • Example of removable storage unit [310] are well known in the art, including, but not limited to, floppy disks, magnetic tapes, optical disks, and the like.
  • the at least one memory module [306] may also include a hard disk drive [312], which can be used to store computer readable program codes or instructions, and/or computer readable data.
  • the at least one memory module [306] may further include an interface [314] and a removable storage unit [316] that is compatible with interface [314] such that software, computer readable codes or instructions can be transferred from the removable storage unit [316] into computer system [300] .
  • interface [314] and removable storage unit [316] pairs include, e.g., removable memory chips (e.g., EPROMs or PROMs) and sockets associated therewith, program cartridges and cartridge interface, and the like.
  • Computer system [300] may also include a secondary memory module [318], such as random access memory (RAM).
  • RAM random access memory
  • Computer system [300] may include at least one processor module [302] . It should be understood that the at least one processor module [302] may consist of any number of devices.
  • the at least one processor module [302] may include a data processing device, such as a microprocessor or microcontroller or a central processing unit.
  • the at least one processor module [302] may include another logic device such as a DMA (Direct Memory Access) processor, an integrated communication processor device, a custom VLSI (Very Large Scale Integration) device or an ASIC (Application Specific Integrated Circuit) device.
  • the at least one processor module [302] may include any other type of analog or digital circuitry that is designed to perform the processing functions described herein.
  • the at least one memory module [306], the at least one processor module [302], and secondary memory module [318] are all operably linked together through communication infrastructure [320] , which may be a
  • Input interface [326] may operably connect the at least one input module [326] to the communication infrastructure [320] .
  • output interface [322] may operably connect the at least one output module [324] to the communication infrastructure [320] .
  • the at least one input module [330] may include, for example, a keyboard, mouse, touch screen, scanner, and other input devices known in the art.
  • the at least one output module [324] may include, for example, a display screen, such as a computer monitor, TV monitor, or the touch screen of the at least one input module [330]; a printer; and audio speakers.
  • Computer system [300] may also include, modems, communication ports, network cards such as Ethernet cards, and newly developed devices for accessing intranets or the internet.
  • the at least one memory module [306] may be configured for storing patient data entered via the at least one input module [330] and processed via the at least one processor module [302] .
  • Patient data relevant to the present invention may include expression level, activity level, copy number and/or sequence information for a CCP and optionally PTEN.
  • Patient data relevant to the present invention may also include clinical parameters relevant to the patient's disease. Any other patient data a physician might find useful in making treatment
  • decisions/recommendations may also be entered into the system, including but not limited to age, gender, and race/ethnicity and lifestyle data such as diet information.
  • Other possible types of patient data include symptoms currently or previously experienced, patient's history of illnesses, medications, and medical procedures.
  • the at least one memory module [306] may include a computer-implemented method stored therein.
  • the at least one processor module [302] may be used to execute software or computer-readable instruction codes of the computer-implemented method.
  • the computer- implemented method may be configured to, based upon the patient data, indicate whether the patient has an increased likelihood of recurrence, progression or response to any particular treatment, generate a list of possible treatments, etc.
  • the computer-implemented method may be configured to identify a patient as having or not having cancer or as having or not having an increased likelihood of recurrence or progression.
  • the computer-implemented method may be configured to inform a physician that a particular patient has cancer, has a quantified probability of having cancer, has an increased likelihood of recurrence, etc.
  • the computer-implemented method may be configured to actually suggest a particular course of treatment based on the answers to/results for various queries.
  • FIG.4 illustrates one embodiment of a computer-implemented method [400] of the invention that may be implemented with the computer system [300] of the invention.
  • the method [400] begins with a query ([410]), either sequentially or substantially simultaneously. If the answer to/result for this query is "Yes" [420] , the method concludes [430] that the sample is BRCA deficient. If the answer to/result for this query is "No" [421] , the method concludes [431] that the sample is not necessarily BRCA deficient.
  • the method [400] may then proceed with more queries, make a particular treatment recommendation ([440] , [441]), or simply end.
  • the apparent first step [410] in FIG.4 may actually form part of a larger process and, within this larger process, need not be the first step/query. Additional steps may also be added onto the core methods discussed above. These additional steps include, but are not limited to, informing a health care professional (or the patient itself) of the conclusion reached; combining the conclusion reached by the illustrated method [400] with other facts or conclusions to reach some additional or refined conclusion regarding the patient's diagnosis, prognosis, treatment, etc.; making a recommendation for treatment; additional queries about additional biomarkers, clinical parameters, or other useful patient information (e.g., age at diagnosis, general patient health, etc.).
  • the answers to queries may be determined by the method instituting a search of patient data for the answer.
  • patient data may be searched for BRCA and CCP expression data. If such a comparison has not already been performed, the method may compare these data to some reference in order to determine if the respective expressions are high, low, average, etc. The method may also compare the respective expressions to determine if BRCA and CCP expression are correlated. Additionally or alternatively, the method may present one or more of the queries (e.g.,
  • the query [410] may be presented via an output module [324] .
  • the user may then answer "Yes” or “No” via an input module [330] .
  • the method may then proceed based upon the answer received.
  • the conclusions [430, 431, 440, 441] may be presented to a user of the computer-implemented method via an output module [324] .
  • "displaying" means communicating any information by any sensory means.
  • Examples include, but are not limited to, visual displays, e.g., on a computer screen or on a sheet of paper printed at the command of the computer, and auditory displays, e.g., computer generated or recorded auditory expression of a patient sample's BRCA status.
  • Computer software products of the invention typically include computer readable media having computer-executable instructions for performing the logic steps of the method of the invention.
  • Suitable computer readable medium include floppy disk, CD- ROM/DVD/DVD-ROM, hard-disk drive, flash memory, ROM/RAM, magnetic tapes and etc.
  • Basic computational biology methods are described in, for example, Setubal et ah, INTRODUCTION TO COMPUTATIONAL BIOLOGY METHODS (PWS Publishing Company, Boston, 1997); Salzberg et al.
  • BIOINFORMATICS A PRACTICAL GUIDE FOR COMPUTATIONAL METHODS IN MOLECULAR BIOLOGY, (Elsevier, Amsterdam, 1998); Rashidi & Buehler, BIOINFORMATICS BASICS : APPLICATION IN BIOLOGICAL SCIENCE AND MEDICINE (CRC Press, London, 2000); and Ouelette & Bzevanis, BIOINFORMATICS: A PRACTICAL GUIDE FOR
  • the present invention may also make use of various computer program products and software for a variety of purposes, such as probe design, management of data, analysis, and instrument operation. See U.S. Pat. Nos. 5,593,839; 5,795,716; 5,733,729; 5,974, 164;
  • the present invention may have embodiments that include methods for providing genetic information over networks such as the Internet as shown in U.S. Ser. Nos. 10/197,621 (U.S. Pub. No.
  • the present invention provides methods of treating a cancer patient comprising determining whether BRCA and CCP expression are correlated in a sample from the patient and (1) recommending, prescribing, or administering a particular treatment regimen if BRCA and CCP expression are anti-correlated in the sample or (2) recommending, prescribing, or administering a particular treatment regimen if BRCA and CCP expression are correlated in the sample.
  • the particular treatment regimen comprises a DNA-damaging agent (e.g., platinum) chemotherapy if BRCA and CCP expression are anti-correlated in the sample.
  • the particular treatment regimen comprises PARP -inhibitor drugs if BRCA and CCP expression are anti-correlated in the sample.
  • the particular treatment regimen comprises a regimen chosen from the group consisting of AC, FEC, FAC, FEC-T, Epirubicin-CMF, TAC, AC-Paclitaxel, AT, TC, T-Carboplatin, Lapatinib, Trastuzumab, Bevacizumab, Sunitinib, Docetaxel, Paclitaxel, Nano Paclitaxel, Docetaxel/capecitabine, Paclitaxel/gemcitabine, Docetaxel/gemcitabine, Gemcitabine, Trastuzumab/Docetaxel, Trastuzumab/Paclitaxel, Capecitabine, Lapatinib/Capecitabine,
  • the methods of the invention are useful, inter alia, in identifying individuals who may benefit from germline BRCA testing but who may not meet the commonly applied criteria for identifying such individuals.
  • commonly used criteria include personal history of cancer and significant family history of cancer.
  • personal history of cancer has its conventional meaning in the art (e.g., a previous cancer in the individual in question).
  • significant family history of cancer also has its conventional meaning in the art.
  • Other widely accepted criteria include individuals with a personal or family history of breast cancer before age 50 or ovarian cancer at any age; individuals with two or more primary diagnoses of breast and/or ovarian cancer; individuals of Ashkenazi Jewish descent with a personal or family history of breast cancer before age 50 or ovarian cancer at any age; male breast cancer patients.
  • a patient lacks a "significant family history of cancer" when one or more of these criteria are not met (usually all).
  • the patient to be assessed by the methods of the invention has a significant family history of cancer.
  • the patient has a personal history of cancer.
  • kits for practicing the methods and for use in the systems of the present invention.
  • the kit may include a carrier for the various components of the kit.
  • the carrier can be a container or support, in the form of, e.g., bag, box, tube, rack, and is optionally compartmentalized.
  • the carrier may define an enclosed confinement for safety purposes during shipment and storage.
  • the kit includes various components useful in determining the expression of
  • the kit many include oligonucleotides specifically hybridizing under high stringency to mRNA or cDNA of BRCA1, BRCA2, or the genes in Tables 1 to 5 or Panels A to F. Such oligonucleotides can be used as PCR primers in RT-PCR reactions, or hybridization probes.
  • the kit comprises reagents (e.g., probes, primers, and or antibodies) for determining the expression level of a panel of genes, where said panel comprises at least 25%, 30%, 40%, 50%>, 60%, 75%, 80%, 90%, 95%, 99%, or 100% CCP genes (e.g., CCP genes in Tables 1 to 5 or Panels A to F).
  • reagents e.g., probes, primers, and or antibodies
  • CCP genes e.g., CCP genes in Tables 1 to 5 or Panels A to F.
  • the kit consists of reagents (e.g., probes, primers, and or antibodies) for determining the expression level of no more than 2500 genes, wherein at least 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 150, 200, 250, or more of these genes are CCP genes (e.g., Tables 1 to 5 or Panels A to F).
  • reagents e.g., probes, primers, and or antibodies
  • the oligonucleotides in the detection kit can be labeled with any suitable detection marker including but not limited to, radioactive isotopes, fluorephores, biotin, enzymes (e.g., alkaline phosphatase), enzyme substrates, ligands and antibodies, etc. See Jablonski et al., Nucleic Acids Res., 14:6115-6128 (1986); Nguyen et al, Biotechniques, 13: 116-123 (1992); Rigby et al., J. Mol. Biol, 113:237-251 (1977).
  • the oligonucleotides included in the kit are not labeled, and instead, one or more markers are provided in the kit so that users may label the oligonucleotides at the time of use.
  • the detection kit of this invention may also be included in the detection kit of this invention.
  • examples of such components include, but are not limited to, Taq polymerase, deoxyribonucleotides, dideoxyribonucleotides, other primers suitable for the amplification of a target DNA sequence, R ase A, and the like.
  • the detection kit preferably includes instructions on using the kit for practice the prognosis method of the present invention using human samples.
  • the study further aimed at determining the optimal number of CCP genes to include in a CCP panel.
  • CCP expression levels are correlated to each other so it was possible that measuring a small number of genes would be sufficient, e.g., to predict prostate cancer outcome.
  • the predictive power of the mean was tested for randomly selected sets of from 1 to 30 of the CCP genes listed above.
  • the study also compared how well the signature predicted outcome as a function of the number of CCP genes included in the signature (FIG.1).
  • Applied Biosystems, Inc. Transcription Kit (Applied Biosystems, Inc.) per manufacturer instructions.
  • a 0.2x probe mix was made by combining 1 of 91 20X gene expression assays from Applied Biosystems Inc. and of low-EDTA TE.
  • Pre-amplification was performed using of 2x TaqMan® PreAmp Master Mix (Applied Biosystems, Inc), 1.25 ⁇ of 0.2x probe mix, and 1.25 ⁇ cDNA.
  • Applied Biosystems TaqMan assays BRCA1:
  • Pre -Amplification was done using a 0.2x probe mix made combining 1 ⁇ of the 48 individual 20X gene expression assays from Applied Biosystems, Inc. and 52 ⁇ of low- EDTA TE. Pre-amplification was performed of TaqMan® PreAmp Master Mix (2X) (Applied Biosystems, Inc.), 1.25 ⁇ 8 of the 0.2x probe mix, and 1.25 ⁇ cDNA.
  • the comparative C T method was used to calculate relative gene expression using the C T for the BRCA2 assay, the average Cj from the BRCA1 assays, and the average Cj from housekeeper genes. qPCR was performed in 220 cancers where high quality RNA was obtained.
  • CCP scores were calculated for each sample in the following manner. C T values less than 8 were considered to be above the limit of detection and were removed from the analysis. Data from the two pre-amplification cycling conditions were normalized by subtracting off the average of the C T values of the genes that were not missing any values and whose C T were between 8 and 23 under both conditions. These centered C T values were averaged for each gene with at least two C T values whose standard deviation was less than or equal to 3. ACV was calculated as the difference in centered C T values between the gene of interest and the average of the housekeeper genes. ACV was then centered for each gene by the average ACV on all the samples that were not missing ACV for any gene. The negative of the average of the centered ACV across the cell- cycle genes is the CCP score.
  • FIG.2 shows the relationship between BRCA1 and cell-cycle gene (as measured by the CCP score) expression.
  • the samples with high CCP scores but low expression of BRCAI are considered to have abnormal expression (i.e., anti-correlation; X's).
  • FIG.5 shows that, upon further analysis, the samples with anti- correlation between BRCAI and CCP expression (those within the shaded circle) generally turned out to have BRCAI hypermethylation (larger points indicate higher extent of methylation). An iterative method was used to identify these samples.
  • a patient sample was considered BRCA deficient (79 out of 242 tested) if it had a mutation in BRCAI /2 (41 out of 227 tested), abnormal expression of BRCAI (47/239), or more than 10% methylation of BRCAI (9 out of 53 tested).
  • ER-patients were PR+. As such, each sample was assigned one of three subtypes based on ER status first and then on HER2 status in the ER-tumors: 113 ER+, 64 triple negative, and 38 ER-/HER2+. One ER- patient was missing HER2 status. As a result her tumor subtype could not be assigned.
  • BRCA1 expression was measured and calculated for 215 patients' tumors.
  • BRCAI expression was calculated as the average -ACV of the three assays.
  • Figure 7 is a histogram of the final BRCAI expression values.
  • Figure 9 is a plot of CCP score and BRCAI expression.
  • Figure 10 is a plot of
  • Figure 11 shows the relationship between BRCAI methylation and expression.
  • Figure 12 shows the relationship between BRCAI expression, CCP score, and BRCAI methylation.
  • a distinct subset of samples with anti-correlated CCP and BRCAI expression can be seen in the lower right quadrant of Figure 7 (shaded circle). Most of these samples show high CCP expression paired with average to low BRCAI expression. It is further notable that such samples generally showed hypermethylation.
  • any embodiment of any method or composition of the invention may be used with respect to any other method or composition of the invention.
  • the name of the gene is generally italicized herein following convention.
  • the italicized gene name is generally to be understood to refer to the gene (i.e., genomic), its mR A (or cDNA) product, and/or its protein product.
  • a non-italicized gene name refers to the gene's protein product.
  • compositions and methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the compositions and methods of this invention have been described in terms of preferred embodiments, it will be apparent to those of skill in the art that variations may be applied to the compositions and methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit and scope of the invention. More specifically, it will be apparent that certain agents that are both chemically and physiologically related may be substituted for the agents described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the invention as defined by the appended claims.

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Abstract

Cette invention concerne d'une manière générale la classification moléculaire de maladies et en particulier des méthodes et des compositions utilisées pour déterminer le déficit en gène BRCA.
PCT/US2011/054369 2010-10-01 2011-09-30 Déficit en gène brca et méthodes d'utilisation associées WO2012045019A2 (fr)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2669682A1 (fr) * 2012-05-31 2013-12-04 Heinrich-Heine-Universität Düsseldorf Nouveaux biomarqueurs pronostiques et prédictifs (marqueurs tumoraux) pour le cancer du sein chez l'homme
WO2015080585A1 (fr) * 2013-11-28 2015-06-04 Stichting Het Nederlands Kanker Instituut-Antoni van Leeuwenhoek Ziekenhuis Méthodes pour la classification moléculaire du cancer du sein et/ou de l'ovaire de type brca
EP3543353A1 (fr) * 2013-09-23 2019-09-25 The University of Chicago Procédés et compositions concernant une thérapie anticancéreuse au moyen d'agents endommageant l'adn

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2669682A1 (fr) * 2012-05-31 2013-12-04 Heinrich-Heine-Universität Düsseldorf Nouveaux biomarqueurs pronostiques et prédictifs (marqueurs tumoraux) pour le cancer du sein chez l'homme
EP3543353A1 (fr) * 2013-09-23 2019-09-25 The University of Chicago Procédés et compositions concernant une thérapie anticancéreuse au moyen d'agents endommageant l'adn
WO2015080585A1 (fr) * 2013-11-28 2015-06-04 Stichting Het Nederlands Kanker Instituut-Antoni van Leeuwenhoek Ziekenhuis Méthodes pour la classification moléculaire du cancer du sein et/ou de l'ovaire de type brca

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