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.

Long noncoding RNA MIR31HG is a bona fide prognostic marker with colorectal cancer cell‐intrinsic properties

“…MIR31HG outlier expression was also observed among PDX models, which similarly to cell lines also lack a human tumor microenvironment, and in colorectal tumors with different microenvironments, including primary and metastatic lesions ( n = 29, 51, 409 and 37 respectively, Fig. b ).…”

“…( a ) Barplot depicts MIR31HG expression across the Cancer Cell Line Encyclopedia with colorectal cancer samples highlighted in black. ( b ) Beanplot illustrates distributions in median centered MIR31HG expression estimates across normal colonic mucosa, primary and metastatic lesions as well as cell line and PDX models. Numbers below labels indicate the number of samples.…”

“…Estevez‐Garcia et al . Affymetrix Human Genome U133 Plus 2.0 (HGU133p2) metastatic CRC (mCRC) gene expression data ( n = 37) were downloaded from GEO with accession identifier GSE52735 . CCLE and Astra‐Zeneca CRC cell line HGU133p2 were retrieved from GEO with accession identifiers GSE57083 [no reference] and GSE36133 ( n = 28 and n = 17 respectively, after exclusion of non‐CRC and overlapping samples).…”

Melittin inhibits proliferation, migration and invasion of bladder cancer cells by regulating key genes based on bioinformatics and experimental assays

“…17,18 In fact, many gene expression profiles involved in various aspects cancers have been documented. [19][20][21] However, additional critical genes and pathways associated with BC remain to be investigated.…”

Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine

“…One of the ways to use tissue ‘prior’ is to utilize data on high-throughput characterization of cancer cells, connecting genomic and transcriptomic alterations to drug response pharmacologic profiles. For some cancer localizations different high-throughput-based classification schemes (sometimes non-NGS) have been proposed leading to survival or treatment outcome predictions [126–129]. Ideally it would be perfect to obtain comprehensive omics data across large cohorts of patients but this approach is prohibitively expensive and limited in the scope of drugs that can be tested [130].…”