A genomic strategy for the functional validation of colorectal cancer genes identifies potential therapeutic targets

Abstract

Genes that are highly overexpressed in tumor cells can be required for tumor cell survival and have the potential to be selective therapeutic targets. In an attempt to identify such targets, we combined a functional genomics and a systems biology approach to assess the consequences of RNAi-mediated silencing of overexpressed genes that were selected from 140 gene expression profiles from colorectal cancers (CRCs) and matched normal mucosa. In order to identify credible models for in-depth functional analysis, we first confirmed the overexpression of these genes in 25 different CRC cell lines. We then identified five candidate genes that profoundly reduced the viability of CRC cell lines when silenced with either siRNAs or short-hairpin RNAs (shRNAs), i.e., HMGA1, TACSTD2, RRM2, RPS2 and NOL5A. These genes were further studied by systematic analysis of comprehensive gene expression profiles generated following siRNA-mediated silencing. Exploration of these RNAispecific gene expression signatures allowed the identification of the functional space in which the five genes operate and showed enrichment for cancer-specific signaling pathways, some known to be involved in CRC. By comparing the expression of the RNAi signature genes with their respective expression levels in an independent set of primary rectal carcinomas, we could recapitulate these defined RNAi signatures, therefore, establishing the biological relevance of our observations. This strategy identified the signaling pathways that are affected by the prominent oncogenes HMGA1 and TACSTD2, established a yet unknown link between RRM2 and PLK1 and identified RPS2 and NOL5A as promising potential therapeutic targets in CRC.The application of parallel gene expression profiling techniques to large sets of primary tumor samples has revealed profound alterations in the cancer transcriptome. The catalogs of deregulated genes defined by such approaches are not only important because they provide new insight into tumor biology but also because they reveal those genes that are specifically upregulated in tumors, some of which may represent promising new antitumor molecular targets.Finding such critical genes within a complex expression signature, however, remains a formidable challenge. One possible approach to this problem is to modulate the expression of these genes in cell line models. For example, loss-of-function (LOF) analysis can be used to identify genes whose reduction of expression may have a direct impact on cancer cell survival.We recently presented comprehensive gene expression signatures of colorectal cancer (CRC) and matched normal mucosa.1,2 In order to identify those genes that could directly influence tumor survival and thus, may represent candidate molecular targets, we first identified CRC cell lines in which the expression of these genes was upregulated accordingly. We then used RNAi-mediated gene silencing to reduce their expression and quantified cell survival. To uncover their roles in cell viability, we monitored genome-wide transcriptional c...

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“…Transfections with synthetic small interfering RNA (siRNA) duplexes were performed as previously described (16,17). Briefly, for cellular viability assays, cells were reverse transfected with siRNAs (Qiagen, Hilden, Germany; Dharmacon/Thermo Fisher Scientific, Schwerte, Germany) using RNAiMAX (Invitrogen) or HiPerFect (Qiagen).…”

“…Gene expression profiling was performed as previously described (15,16,19). In brief, 200 ng of total RNA was reverse transcribed, amplified, and labeled with Cy3 using the Low RNA Input Linear Amplification Kit PLUS (Agilent Technologies).…”

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“…Gene expression profiling was performed as previously described (14). In brief, 800 ng of total RNA was reverse transcribed, amplified, and labeled with Cy3 using the Low RNA Input Linear Amplification Kit PLUS (Agilent Technologies).…”