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Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer.

ABSTRACT: Fluoropyrimidine-based chemotherapy (CT) has been the mainstay of care of metastatic colorectal cancer (mCRC) for years. Response rates are only observed, however, in about half of treated patients, and there are no reliable tools to prospectively identify patients more likely to benefit from therapy. The purpose of our study was to identify a gene expression profile predictive of CT response in mCRC. Whole genome expression analyses (Affymetrix GeneChip HG-U133 Plus 2.0) were performed in fresh frozen tumor samples of 37 mCRC patients (training cohort). Differential gene expression profiles among the two study conditions (responders versus non-responders) were assessed using supervised class prediction algorithms. A set of 161 differentially expressed genes in responders (23 patients; 62%) versus non-responders (14 patients; 38%) was selected for further assessment and validation by RT-qPCR (TaqMan Low Density Arrays (TLDA) 7900 HT Micro Fluidic Cards) in an independent multi-institutional cohort (53 mCRC patients). Seven of these genes were confirmed as significant predictors of response. Patients with a favorable predictive signature had significantly greater response rate (58% vs. 13%, p = 0.024), progression-free survival (61% vs. 13% at 1 year, HR = 0.32, p = 0.009) and overall survival (32 vs. 16 months, HR = 0.21, p = 0.003) than patients with an unfavorable gene signature. This is the first study to validate a gene-expression profile predictive of response to CT in mCRC patients. Larger and prospective confirmatory studies are required, however, in order to successfully provide oncologists with adequate tools to optimize treatment selection in routine clinical practice.

SUBMITTER: Estevez-Garcia P

PROVIDER: S-EPMC4467428 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer.

Estevez-Garcia Purificacion P Rivera Fernando F Molina-Pinelo Sonia S Benavent Marta M Gómez Javier J Limón Maria Luisa ML Pastor Maria Dolores MD Martinez-Perez Julia J Paz-Ares Luis L Carnero Amancio A Garcia-Carbonero Rocio R

Oncotarget 20150301 8

Fluoropyrimidine-based chemotherapy (CT) has been the mainstay of care of metastatic colorectal cancer (mCRC) for years. Response rates are only observed, however, in about half of treated patients, and there are no reliable tools to prospectively identify patients more likely to benefit from therapy. The purpose of our study was to identify a gene expression profile predictive of CT response in mCRC. Whole genome expression analyses (Affymetrix GeneChip HG-U133 Plus 2.0) were performed in fresh ...[more]

PMID: 25730906

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Project description:BackgroundThe clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC.MethodsGene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study.ResultsIn the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p = 0.007; OS, p = 0.006) and the validation dataset (RFS, p = 0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells.ConclusionsOnly a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as a potential predictor could be helpful to distinguish this sub-group with favorable outcome.

Project description:Resistance to 5-Fluorouracil (5-FU) is a major obstacle to the successful treatment of colorectal cancer (CRC) and posed an increased risk of recurrence. DNA methylation has been suggested as one of the underlying mechanisms for recurrent disease and its contribution to the development of drug resistance remains to be clarified. This study aimed to determine the methylation phenotype in CRC for identification of predictive markers for chemotherapy response. We performed DNA methylation profiling on 43 non-recurrent and five recurrent CRC patients using the Illumina Infinium HumanMethylation450 Beadchip assay. In addition, CRC cells with different genetic backgrounds, response to 5-FU and global methylation levels (HT29 and SW48) were treated with 5-FU and DNA methylation inhibitor 5-aza-2'-deoxycytidine (5-azadC). The singular and combined effects of these two drug classes on cell viability and global methylation profiles were investigated. Our genome-wide methylation study on the clinical specimens showed that recurrent CRCs exhibited higher methylation levels compared to non-recurrent CRCs. We identified 4787 significantly differentially methylated genes (P < 0.05); 3112 genes were hyper- while 1675 genes were hypomethylated in the recurrent group compared to the non-recurrent. Fifty eight and 47 of the significantly hypermethylated and hypomethylated genes have an absolute recurrent/non-recurrent methylation difference of ?20%. Most of the hypermethylated genes were involved in the MAPK signaling pathway which is a key regulator for apoptosis while the hypomethylated genes were involved in the PI3K-AKT signaling pathway and proliferation process. We also demonstrate that 5-azadC treatment enhanced response to 5-FU which resulted in significant growth inhibition compared to 5-FU alone in hypermethylated cell lines SW48. In conclusion, we found the evidence of five potentially biologically important genes in recurrent CRCs that could possibly serve as a new potential therapeutic targets for patients with chemoresistance. We postulate that aberrant methylation of CCNEI, CCNDBP1, PON3, DDX43, and CHL1 in CRC might be associated with the recurrence of CRC and 5-azadC-mediated restoration of 5-FU sensitivity is mediated at least in part by MAPK signaling pathway.

Project description:BackgroundThe randomized phase III study (WJOG4407G) showed equivalent efficacy between FOLFOX and FOLFIRI in combination with bevacizumab as the first-line treatment for metastatic colorectal cancer (mCRC). We studied whole genome copy number profiles using array-based comparative genomic hybridization (aCGH) analysis of tumor tissue samples obtained in this study. The aim of this study was to identify gene copy number alterations that could aid in selecting either FOLFOX or FOLFIRI in combination with bevacizumab for patients with mCRC.Materials and methodsDNA was purified from 154 pretreatment formalin-fixed paraffin-embedded tissue samples (75 from the FOLFOX arm and 79 from the FOLFIRI arm) of 395 patients enrolled in the WJOG4407G trial and analyzed by aCGH. Genomic regions greater than 1.2-fold were regarded as copy number gain (CNG).ResultsPatient characteristics between the treatment arms were well balanced except for tumor laterality (left side; 64% in FOLFOX arm and 80% in FOLFIRI arm, p = .07). FOLFIRI showed a trend toward better response rate (RR), progression-free survival (PFS) and overall survival (OS) than FOLFOX in the patients with CNG of chromosome 8q24.1 (Fisher's exact test, p = .134 for RR; interaction test, p = .102 for PFS and p = .003 for OS) and 8q24.2 (Fisher's exact test, p = .179 for RR; interaction test, p = .144 for PFS and p = .002 for OS).ConclusionChromosome 8q24.1-q24.2 may contain genes that could potentially serve as predictive markers for selecting either FOLFOX or FOLFIRI in combination with bevacizumab for treatment of patients with mCRC.Implications for practiceBevacizumab has been used as a standard first-line treatment for patients with metastatic colorectal cancer (mCRC) in combination with either oxaliplatin-based or irinotecan-based chemotherapy. Until now, there has been no predictive marker to choose between the two combination chemotherapies. This array-based comparative genomic hybridization analysis revealed that the difference in therapeutic effect between the two combination chemotherapies is prominent in patients with mCRC with gene copy number gain in chromosome 8p24.1-p24.2. Such patients showed more favorable response and survival when treated with irinotecan-based combination chemotherapy. Overlapping genes commonly found in this region may be predictive biomarkers of the efficacy of the combination chemotherapy with bevacizumab.

Project description:To examine the predictive effects of baseline serum bilirubin levels and UDP-glucuronosyltransferase (UGT) 1A1*28 polymorphism on response of colorectal cancer to irinotecan-based chemotherapy.The present study was based on a prospective multicenter longitudinal trial of Chinese metastatic colorectal cancer (mCRC) patients treated with irinotecan-based chemotherapy (NCT01282658). Baseline serum bilirubin levels, including total bilirubin (TBil) and unconjugated bilirubin (UBil), were measured, and genotyping of UGT1A1*28 polymorphism was performed. Receiver operating characteristic curve (ROC) analysis was used to determine cutoff values of TBil and UBil. The TBil values were categorized into > 13.0 or ? 13.0 groups; the UBil values were categorized into > 4.1 or ? 4.1 groups. Combining the cutoff values of TBil and UBil, which was recorded as CoBil, patients were classified into three groups. The classifier's performance of UGT1A1*28 and CoBil for predicting treatment response was evaluated by ROC analysis. Associations between response and CoBil or UGT1A1*28 polymorphism were estimated using simple and multiple logistic regression models.Among the 120 mCRC patients, the serum bilirubin level was significantly different between the UGT1A1*28 wild-type and mutant genotypes. Patients with the mutant genotype had an increased likelihood of a higher TBil (P = 0.018) and a higher UBil (P = 0.014) level compared with the wild-type genotype. Patients were stratified into three groups based on CoBil. Group 1 was patients with TBil > 13.0 and UBil > 4.1; Group 2 was patients with TBil ? 13.0 and UBil > 4.1; and Group 3 was patients with TBil ? 13.0 and UBil ? 4.1. Patients in Group 3 had more than a 10-fold higher likelihood of having a response in the simple (OR = 11.250; 95%CI: 2.286-55.367; P = 0.003) and multiple (OR = 16.001; 95%CI: 2.802 -91.371; P = 0.002) analyses compared with the Group 1 individuals. Patients carrying the UGT1A1*28 (TA)7 allele were 4-fold less likely to present with a response compared with the individuals harboring a homozygous (TA)6 genotype in the simple (OR = 0.267; 95%CI: 0.100-0.709; P = 0.008) and multiple (OR = 0.244; 95%CI: 0.088-0.678; P = 0.007) analyses. Classifier's performance of CoBil and UGT1A1*28 were comparable.CoBil and UGT1A1*28 are both independent biomarkers for predicting the treatment response of mCRC patients to irinotecan-based chemotherapy. After validation, CoBil, an easily determinable index in the clinic, might be helpful in facilitating stratification of mCRC patients for individualized treatment options.

Project description:BackgroundClinical grading systems using clinical features alongside nomograms lack precision in guiding treatment decisions in prostate cancer (PCa). There is a critical need for identification of biomarkers that can more accurately stratify patients with primary PCa.ObjectiveTo identify a robust prognostic signature to better distinguish indolent from aggressive prostate cancer (PCa).Design, setting, and participantsTo develop the signature, whole-genome and whole-transcriptome sequencing was conducted on five PCa patient-derived xenograft (PDX) models collected from independent foci of a single primary tumor and exhibiting variable metastatic phenotypes. Multiple independent clinical cohorts including an intermediate-risk cohort were used to validate the biomarkers.Outcome measurements and statistical analysisThe outcome measurement defining aggressive PCa was metastasis following radical prostatectomy. A generalized linear model with lasso regularization was used to build a 93-gene stroma-derived metastasis signature (SDMS). The SDMS association with metastasis was assessed using a Wilcoxon rank-sum test. Performance was evaluated using the area under the curve (AUC) for the receiver operating characteristic, and Kaplan-Meier curves. Univariable and multivariable regression models were used to compare the SDMS alongside clinicopathological variables and reported signatures. AUC was assessed to determine if SDMS is additive or synergistic to previously reported signatures.Results and limitationsA close association between stromal gene expression and metastatic phenotype was observed. Accordingly, the SDMS was modeled and validated in multiple independent clinical cohorts. Patients with higher SDMS scores were found to have worse prognosis. Furthermore, SDMS was an independent prognostic factor, can stratify risk in intermediate-risk PCa, and can improve the performance of other previously reported signatures.ConclusionsProfiling of stromal gene expression led to development of an SDMS that was validated as independently prognostic for the metastatic potential of prostate tumors.Patient summaryOur stroma-derived metastasis signature can predict the metastatic potential of early stage disease and will strengthen decisions regarding selection of active surveillance versus surgery and/or radiation therapy for prostate cancer patients. Furthermore, profiling of stroma cells should be more consistent than profiling of diverse cellular populations of heterogeneous tumors.

Dataset Information

Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer.

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Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer.

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