WO2009094318A2 - Molecular staging of stage ii and iii colon cancer and prognosis - Google Patents
Molecular staging of stage ii and iii colon cancer and prognosis Download PDFInfo
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- WO2009094318A2 WO2009094318A2 PCT/US2009/031389 US2009031389W WO2009094318A2 WO 2009094318 A2 WO2009094318 A2 WO 2009094318A2 US 2009031389 W US2009031389 W US 2009031389W WO 2009094318 A2 WO2009094318 A2 WO 2009094318A2
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- C12Q2600/00—Oligonucleotides characterized by their use
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Definitions
- a diagnostic includes a 7-gene signature for determining whether colon cancer is in Stage II or Stage II.
- a diagnostic in another aspect of the invention, includes reagents for detecting the expression of 7-genes used to distinguish between Stage II and Stage III colon cancer.
- kits for distinguishing between Stage II and Stage III colon cancer and/or providing a prognosis of outcome include reagents for detecting the expression of 7-Marker genes and, optionally, a group of constitutive Iy expressed genes.
- Stage II and III samples using RTQ-PCR were evaluated using RTQ-PCR.
- B. Kaplan-Meier curve and log rank test of 123 FPE samples using the 7-gene signature. The high and low risk groups differ significantly (P 0.0271).
- a Biomarker is any indicia of an indicated Marker nucleic acid/protein.
- Nucleic acids can be any known in the art including, without limitation, nuclear, mitochondrial (homeoplasmy, heteroplasmy), viral, bacterial, fungal, mycoplasmal, etc.
- the indicia can be direct or indirect and measure over- or under-expression of the gene given the physiologic parameters and in comparison to an internal control, placebo, normal tissue or another carcinoma.
- Biomarkers include, without limitation, nucleic acids and proteins (both over and under-expression and direct and indirect).
- nucleic acids as Biomarkers can include any method known in the art including, without limitation, measuring DNA amplification, deletion, insertion, duplication, RNA, microRNA (miRNA), loss of heterozygosity (LOH), single nucleotide polymorphisms (SNPs, Brookes (1999)), copy number polymorphisms (CNPs) either directly or upon genome amplification, microsatellite DNA, epigenetic changes such as DNA hypo- or hyper-methylation and FISH.
- miRNA microRNA
- LH loss of heterozygosity
- SNPs single nucleotide polymorphisms
- CNPs copy number polymorphisms
- Biomarkers includes any method known in the art including, without limitation, measuring amount, activity, modifications such as glycosylation, phosphorylation, ADP-ribosylation, ubiquitination, etc., or imunohistochemistry (IHC) and turnover.
- Other Biomarkers include imaging, molecular profiling, cell count and apoptosis Markers.
- a Marker gene corresponds to the sequence designated by a SEQ ID NO when it contains that sequence.
- a gene segment or fragment corresponds to the sequence of such gene when it contains a portion of the referenced sequence or its complement sufficient to distinguish it as being the sequence of the gene.
- a gene expression product corresponds to such sequence when its RNA, mRNA, or cDNA hybridizes to the composition having such sequence (e.g. a probe) or, in the case of a peptide or protein, it is encoded by such mRNA.
- a segment or fragment of a gene expression product corresponds to the sequence of such gene or gene expression product when it contains a portion of the referenced gene expression product or its complement sufficient to distinguish it as being the sequence of the gene or gene expression product.
- inventive methods, compositions, articles, and kits of described and claimed in this specification include one or more Marker genes.
- Marker or “Marker gene” is used throughout this specification to refer to genes and gene expression products that correspond with any gene the over- or under-expression of which is associated with an indication or tissue type.
- Preferred methods for establishing gene expression profiles include determining the amount of RNA that is produced by a gene that can code for a protein or peptide. This is accomplished by reverse transcriptase PCR (RT-PCR), competitive RT-PCR, real time RT-PCR, differential display RT-PCR, Northern Blot analysis and other related tests.
- RT-PCR reverse transcriptase PCR
- competitive RT-PCR competitive RT-PCR
- real time RT-PCR real time RT-PCR
- differential display RT-PCR Northern Blot analysis and other related tests.
- cDNA complementary DNA
- cRNA complementary RNA
- a number of different array configurations and methods for their production are known to those of skill in the art and are described in for instance, 5445934; 5532128; 5556752; 5242974; 5384261; 5405783; 5412087; 5424186; 5429807; 5436327; 5472672; 5527681; 5529756; 5545531; 5554501; 5561071; 5571639; 5593839; 5599695; 5624711; 5658734; and 5700637.
- Microarray technology allows for the measurement of the steady- state mRNA level of thousands of genes simultaneously thereby presenting a powerful tool for identifying effects such as the onset, arrest, or modulation of uncontrolled cell proliferation.
- Two microarray technologies are currently in wide use. The first are cDNA arrays and the second are oligonucleotide arrays. Although differences exist in the construction of these chips, essentially all downstream data analysis and output are the same.
- the product of these analyses are typically measurements of the intensity of the signal received from a labeled probe used to detect a cDNA sequence from the sample that hybridizes to a nucleic acid sequence at a known location on the microarray.
- the intensity of the signal is proportional to the quantity of cDNA, and thus mRNA, expressed in the sample cells.
- mRNA mRNA
- Analysis of the expression levels is conducted by comparing such signal intensities. This is best done by generating a ratio matrix of the expression intensities of genes in a test sample versus those in a control sample. For instance, the gene expression intensities from a diseased tissue can be compared with the expression intensities generated from benign or normal tissue of the same type. A ratio of these expression intensities indicates the fold-change in gene expression between the test and control samples.
- the selection can be based on statistical tests that produce ranked lists related to the evidence of significance for each gene's differential expression between factors related to the tumor's original site of origin. Examples of such tests include ANOVA and Kruskal-Wallis.
- the rankings can be used as weightings in a model designed to interpret the summation of such weights, up to a cutoff, as the preponderance of evidence in favor of one class over another. Previous evidence as described in the literature may also be used to adjust the weightings.
- a preferred embodiment is to normalize each measurement by identifying a stable control set and scaling this set to zero variance across all samples. This control set is defined as any single endogenous transcript or set of endogenous transcripts affected by systematic error in the assay, and not known to change independently of this error.
- All Markers are adjusted by the sample specific factor that generates zero variance for any descriptive statistic of the control set, such as mean or median, or for a direct measurement. Alternatively, if the premise of variation of controls related only to systematic error is not true, yet the resulting classification error is less when normalization is performed, the control set will still be used as stated. Non-endogenous spike controls could also be helpful, but are not preferred.
- Gene expression profiles can be displayed in a number of ways. The most common is to arrange raw fluorescence intensities or ratio matrix into a graphical dendogram where columns indicate test samples and rows indicate genes. The data are arranged so genes that have similar expression profiles are proximal to each other. The expression ratio for each gene is visualized as a color. For example, a ratio less than one (down-regulation) appears in the blue portion of the spectrum while a ratio greater than one (up-regulation) appears in the red portion of the spectrum.
- Commercially available computer software programs are available to display such data including "Genespring” (Silicon Genetics, Inc.) and “Discovery” and “Infer” (Partek, Inc.)
- protein levels can be measured by binding to an antibody or antibody fragment specific for the protein and measuring the amount of antibody-bound protein.
- Antibodies can be labeled by radioactive, fluorescent or other detectable reagents to facilitate detection. Methods of detection include, without limitation, enzyme-linked immunosorbent assay (ELISA) and immunoblot techniques.
- ELISA enzyme-linked immunosorbent assay
- the genes that are differentially expressed are either up regulated or down regulated in patients with carcinoma of a particular origin relative to those with carcinomas from different origins. Up regulation and down regulation are relative terms meaning that a detectable difference (beyond the contribution of noise in the system used to measure it) is found in the amount of expression of the genes relative to some baseline. In this case, the baseline is determined based on the algorithm. The genes of interest in the diseased cells are then either up regulated or down regulated relative to the baseline level using the same measurement method.
- Diseased in this context, refers to an alteration of the state of a body that interrupts or disturbs, or has the potential to disturb, proper performance of bodily functions as occurs with the uncontrolled proliferation of cells.
- someone is diagnosed with a disease when some aspect of that person's genotype or phenotype is consistent with the presence of the disease.
- the act of conducting a diagnosis or prognosis may include the determination of disease/status issues such as determining the likelihood of relapse, type of therapy and therapy monitoring.
- therapy monitoring clinical judgments are made regarding the effect of a given course of therapy by comparing the expression of genes over time to determine whether the gene expression profiles have changed or are changing to patterns more consistent with normal tissue.
- Genes can be grouped so that information obtained about the set of genes in the group provides a sound basis for making a clinically relevant judgment such as a diagnosis, prognosis, or treatment choice. These sets of genes make up the portfolios of the invention. As with most diagnostic Markers, it is often desirable to use the fewest number of Markers sufficient to make a correct medical judgment. This prevents a delay in treatment pending further analysis as well unproductive use of time and resources.
- One method of establishing gene expression portfolios is through the use of optimization algorithms such as the mean variance algorithm widely used in establishing stock portfolios. This method is described in detail in 20030194734.
- the method calls for the establishment of a set of inputs (stocks in financial applications, expression as measured by intensity here) that will optimize the return (e.g., signal that is generated) one receives for using it while minimizing the variability of the return.
- Many commercial software programs are available to conduct such operations. "Wagner Associates Mean- Variance Optimization Application,” referred to as “Wagner Software” throughout this specification, is preferred. This software uses functions from the “Wagner Associates Mean-Variance Optimization Library" to determine an efficient frontier and optimal portfolios in the Markowitz sense is preferred. Markowitz (1952). Use of this type of software requires that microarray data be transformed so that it can be treated as an input in the way stock return and risk measurements are used when the software is used for its intended financial analysis purposes.
- the process of selecting a portfolio can also include the application of heuristic rules.
- such rules are formulated based on biology and an understanding of the technology used to produce clinical results. More preferably, they are applied to output from the optimization method.
- the mean variance method of portfolio selection can be applied to microarray data for a number of genes differentially expressed in subjects with cancer. Output from the method would be an optimized set of genes that could include some genes that are expressed in peripheral blood as well as in diseased tissue. If samples used in the testing method are obtained from peripheral blood and certain genes differentially expressed in instances of cancer could also be differentially expressed in peripheral blood, then a heuristic rule can be applied in which a portfolio is selected from the efficient frontier excluding those that are differentially expressed in peripheral blood.
- the rule can be applied prior to the formation of the efficient frontier by, for example, applying the rule during data pre-selection.
- heuristic rules can be applied that are not necessarily related to the biology in question. For example, one can apply a rule that only a prescribed percentage of the portfolio can be represented by a particular gene or group of genes.
- Commercially available software such as the Wagner Software readily accommodates these types of heuristics. This can be useful, for example, when factors other than accuracy and precision (e.g., anticipated licensing fees) have an impact on the desirability of including one or more genes.
- the gene expression profiles of this invention can also be used in conjunction with other non-genetic diagnostic methods useful in cancer diagnosis, prognosis, or treatment monitoring.
- CA 27.29 Cancer Antigen 27.29
- blood is periodically taken from a treated patient and then subjected to an enzyme immunoassay for one of the serum Markers described above.
- an enzyme immunoassay for one of the serum Markers described above When the concentration of the Marker suggests the return of tumors or failure of therapy, a sample source amenable to gene expression analysis is taken. Where a suspicious mass exists, a fine needle aspirate (FNA) is taken and gene expression profiles of cells taken from the mass are then analyzed as described above.
- tissue samples may be taken from areas adjacent to the tissue from which a tumor was previously removed. This approach can be particularly useful when other testing produces ambiguous results.
- DNA analysis can be any known in the art including, without limitation, methylation, de-methylation, karyotyping, ploidy (aneuploidy, polyploidy), DNA integrity (assessed through gels or spectrophotometry), translocations, mutations, gene fusions, activation - de-activation, single nucleotide polymorphisms (SNPs), copy number or whole genome amplification to detect genetic makeup.
- RNA analysis includes any known in the art including, without limitation, q-RT-PCR, miRNA or post-transcription modifications.
- Protein analysis includes any known in the art including, without limitation, antibody detection, post-translation modifications or turnover.
- the proteins can be cell surface markers, preferably epithelial, endothelial, viral or cell type. The Biomarker can be related to viral / bacterial infection, insult or antigen expression.
- Kits made according to the invention include formatted assays for determining the gene expression profiles. These can include all or some of the materials needed to conduct the assays such as reagents and instructions and a medium through which Biomarkers are assayed.
- Articles of this invention include representations of the gene expression profiles useful for treating, diagnosing, prognosticating, and otherwise assessing diseases. These profile representations are reduced to a medium that can be automatically read by a machine such as computer readable media (magnetic, optical, and the like).
- the articles can also include instructions for assessing the gene expression profiles in such media.
- the articles may comprise a CD ROM having computer instructions for comparing gene expression profiles of the portfolios of genes described above.
- the articles may also have gene expression profiles digitally recorded therein so that they may be compared with gene expression data from patient samples. Alternatively, the profiles can be recorded in different representational format. A graphical recordation is one such format. Clustering algorithms such as those incorporated in "DISCOVERY” and "INFER” software from Partek, Inc. mentioned above can best assist in the visualization of such data.
- articles of manufacture are media or formatted assays used to reveal gene expression profiles. These can comprise, for example, microarrays in which sequence complements or probes are affixed to a matrix to which the sequences indicative of the genes of interest combine creating a readable determinant of their presence.
- articles according to the invention can be fashioned into reagent kits for conducting hybridization, amplification, and signal generation indicative of the level of expression of the genes of interest for detecting cancer.
- Example 1 The following examples are provided to illustrate but not limit the invention. Example 1.
- Post-surgery patient surveillance was carried out according to general practice for colon cancer patients including physical exam, blood counts, liver function tests, serum CEA, and colonoscopy for the patients. Selected patients had abdominal CT scan and chest X-ray. If cancer recurrence was suspected, the patient underwent diagnostic work-up including colonoscopy, chest/abdominal/pelvic CT and MRI for selected patients. Diagnostic biopsy to confirm metastatic lesion was performed in all patients where feasible. Time to recurrence or disease-free time was defined as the time period from the date of surgery to confirmed tumor relapse date for relapsed patients and from the date of surgery to the date of last follow-up for disease-free patients.
- FPE tumor specimens from 85 Stage II and 38 Stage III colon cancer patients were also obtained. There were also 180 Stage II colon cancer FPE specimens acquired separately. The histopathology of each specimen was reviewed to confirm diagnosis and tumor content. Patient eligibility criteria and follow-up procedures were the same as for the selection of the frozen samples. Microarray Analysis
- RNA isolation was processed for RNA isolation.
- RNA sample was quantified by OD 260/280 readings using spectrophotometer and diluted to a final concentration of 50 ng/uL.
- the isolated RNA samples were stored in RNase-free water at -80 0 C until use.
- the gene signature and the housekeeping control genes were evaluated using a one-step multiplex RTQ-PCR assay with the RNA samples isolated from FPE tissues.
- three housekeeping control genes including ⁇ - actin, HMBS, and RPL13A, were used to normalize the input quantity of RNA.
- PCR primers or probes for RTQ-PCR assay were designed to span an intron so that the assay would not amplify any residual genomic DNA.
- One hundred nanograms of total RNA were used for the one-step RTQ-PCR reaction.
- the reverse transcription was carried out using 40 x Multiscribe and RNase inhibitor mix contained in the TaqMan® one-step PCR Master Mix reagents kit (Applied Biosystems, Fresno, CA).
- the cDNA was then subjected to the 2 x Master Mix without uracil-N-glycosylase (UNG).
- PCR amplification was performed on the ABI 7900HT sequence detection system (Applied Biosystems, Frenso, CA) using the 384-well block format with 10 ⁇ L reaction volume. The concentrations of the primers and the probes were 4 and 2.5 ⁇ mol/L, respectively.
- the reaction mixture was incubated at 48°C for 30 minutes for the reverse transcription, followed by an Amplitaq® activation step at 95 0 C for 10 minutes and then 40 cycles of 95 0 C for 15 seconds for denaturing and of 60 0 C for 1 minute for annealing and extension.
- a standard curve was generated from a range of 100 pg to 100 ng of the starting materials, and when the R 2 value was >0.99, the cycle threshold (Ct) values were accepted.
- all primers and probes were optimized towards the same amplification efficiency according to the manufacturer's protocol. Sequences of the primers and probes for the 7 genes and the 3 housekeeping control genes were as follows, each written in the 5' to 3' direction:
- EP2MA reverse CACGT ACACGATGTGTCCCTTCT
- EP2MA probe FAM-CAGGCGGTGTGCCTGCTGCAT-BHQ.
- KLF5 probe FAM-CAAGTGT ACCTGGGAAGGCTGCGACTG-BHQ.
- CAPG forward CGCAGCTCTGTATAAGGTCTCTGA
- CAPG reverse GATATCAGCAGTTCAAGGGCAA
- CAPG probe FAM-AACCTGACCAAGGTGGCTGACTCCAG-BHQ.
- LILRB3 forward AGATGGACACTGAGGCTGCTG;
- LILRB3probe FAM-CCCAGGATGTGACCTACGCCCAG-BHQ. LAT forward, CTCCCACCGGACGCCATC;
- CHCl reverse CGGAGTTCCAAGCTGATGGTA; CHCl probe, FAM-CCACGTGTACGGCTTCGGCCTC-BHQ.
- YWHAH probe FAM- ATC ATGGGCATTGCTGGACTGATGG-BHQ.
- ⁇ -actin forward AAGCCACCCCACTTCTCTCTAA
- ⁇ -actin reverse AATGCTATCACCTCCCCTGTGT
- ⁇ -actin probe FAM-AGAATGGCCCAGTCCTCTCCCAAGTC-BHQ.
- HMBS probe FAM-CTGGCTTCACCATCG-BHQ.
- RPL 13 A forward, C GG AAG AAG AAAC AGC TCATGA;
- RPL13A reverse CCTCTGTGT ATTTGTC AATTTTCTTCTC; RPL13A probe, FAM-CGGAAACAGGCCGAGAA-BHQ.
- ROC Receiver's Operating Characteristic
- Table 1 Patient and tumor characteristics Cleveland Clinic Foundation Fresh Frozen and FPE samples
- Table 2 Patient and tumor characteristics of 180 validation samples (FPE tissues)
- RTQ-PCR assay was developed and performed first on 123 FPE samples from Stage II and III colon tumors. Since the RTQ-PCR assay is entirely different from the microarray analysis, in terms of the sample type and assay platform, the Stage discrimination power of the 7 genes were reevaluated by t test. A model to evaluate the likelihood of each patient being Stage III or Stage II was built again using logistic regression on these 123 -patient RTQ-PCR dataset. First, the ROC curve was evaluated (Fig. 2A). The 7-gene predictor gave an AUC value of 0.77.
- the 7-gene signature has been tested on clinically defined Stage II and III colon cancers and it was demonstrated that the signature has the ability to differentiate these two classes with fresh frozen specimen on microarray platform and with FPE specimen on RTQ-PCR platform.
- 180 test-set samples were used to assess the 7-gene utility.
- 150 of the 180 clinical Stage II patients were classified as predicted Stage II cancers and 30 clinical Stage II patients were classified as predicted Stage III cancers.
Abstract
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EP09703499A EP2240609A4 (en) | 2008-01-22 | 2009-01-19 | Molecular staging of stage ii and iii colon cancer and prognosis |
BRPI0907440A BRPI0907440A2 (en) | 2008-01-22 | 2009-01-19 | Stage II and III colon cancer molecular staging prognosis |
CA2712773A CA2712773A1 (en) | 2008-01-22 | 2009-01-19 | Molecular staging of stage ii and iii colon cancer and prognosis |
MX2010008008A MX2010008008A (en) | 2008-01-22 | 2009-01-19 | Molecular staging of stage ii and iii colon cancer and prognosis. |
JP2010544379A JP2011509689A (en) | 2008-01-22 | 2009-01-19 | Molecular staging and prognosis of stage II and III colon cancer |
CN200980107672XA CN101960022A (en) | 2008-01-22 | 2009-01-19 | Molecular staging of stage II and III colon cancer and prognosis |
IL206991A IL206991A0 (en) | 2008-01-22 | 2010-07-14 | Molecular staging of stage ii and iii colon cancer and prognosis |
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- 2009-01-19 US US12/355,906 patent/US20090192045A1/en not_active Abandoned
- 2009-01-19 JP JP2010544379A patent/JP2011509689A/en active Pending
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- 2009-01-19 EP EP09703499A patent/EP2240609A4/en not_active Withdrawn
- 2009-01-19 MX MX2010008008A patent/MX2010008008A/en unknown
- 2009-01-19 CA CA2712773A patent/CA2712773A1/en not_active Abandoned
- 2009-01-19 KR KR1020107017876A patent/KR20100120657A/en not_active Application Discontinuation
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CA2712773A1 (en) | 2009-07-30 |
EP2240609A4 (en) | 2011-08-03 |
KR20100120657A (en) | 2010-11-16 |
JP2011509689A (en) | 2011-03-31 |
CN101960022A (en) | 2011-01-26 |
BRPI0907440A2 (en) | 2016-11-01 |
MX2010008008A (en) | 2010-08-10 |
WO2009094318A3 (en) | 2009-12-30 |
EP2240609A2 (en) | 2010-10-20 |
IL206991A0 (en) | 2010-12-30 |
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