Pharmacogenomics, biomarker network and allele frequencies in colorectal cancer

Abstract

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Over the last decades, several studies have shown that tumor-related genomic alterations predict tumor prognosis, drug response and toxicity. These observations have led to the development of a number of precision therapies based on individual genomic profiles. As part of these approaches, pharmacogenomics analyses genomic alterations that may predict an efficient therapeutic response. Studying these mutations as biomarkers for predicting drug response is of a great interest to improve precision medicine. Here we conduct a comprehensive review of the main pharmacogenomics biomarkers and genomic alterations affecting enzyme activity, transporter capacity, channels and receptors, and therefore the new advances in CRC precision medicine to select the best therapeutic strategy in populations worldwide, with a focus on Latin America. mutations in the transforming growth factor-β (TGFβ), WNT-β-catenin, PI3K, EGFR and downstream MAPK pathways induces CRC 11,[13][14][15] .On the other hand, the development of CRC also occurs when chromosomal instability (CIN) occurs, progress due to defects in telomere stability, chromosomal segregation and mutations in TP53 gene 16 . The 15% of early-stage colorectal tumors present mismatch repair-deficient (MMRd) system, triggering hypermutation and microsatellite instability (MSI) 14 . According to Dienstmann et al., the epigenetic profile of tumors with CIN present mutations in APC, KRAS, TP53, SMAD4 and PIK3CA, promoting the formation of the non-hypermutated consensus molecular subtypes (CMSs): CMS2, CMS3 and CMS4 1 .Whereas tumors with MSI harbor mutations in the MSH6, RNF43, ATM, TGFBR2, BRAF and PTEN genes of the hypermutated molecular subtype CMS1 1 . A consensus of molecular subtypesGene expression-based subtyping is widely accepted as a relevant source of disease stratification 17 . Nevertheless, the translational utility is hampered by divergent results that are probably related to differences in algorithms applied to sample preparation methods, gene expression platforms and racial/ethnic disparities 18,19 . Inspection of the published gene expression-based CRC classification revealed an absence of a clear methodological 'gold standard' 8,9,16,[20][21][22][23] . To facilitate clinical translation, the CRC Subtyping Consortium (CRCSC) was formed to assess the core subtype patterns among existing gene expressionbased CRC subtyping algorithms 18,24 .

Post-transcriptional Regulation of Colorectal Cancer: A Focus on RNA-Binding Proteins

“…Therefore, it has been suggested that inhibition of both MSIs' RNA binding activity could fully abrogate tumor growth in CRC (Potten et al, 2003; Cheng et al, 2015; Gao et al, 2015; Lan et al, 2015; Kharas and Lengner, 2017). Besides, MSI increases colorectal cancer stem cells (CSCs) survival, migration, and resistance to 5-FU, the chemotherapy drug that constitutes the backbone of the most currently used one in colon cancer treatment (Yuqi et al, 2008; Voutsadakis, 2018; López-Cortés et al, 2019).…”

“…For example, ELAVL1 promotes the stability and translation of COX-2 mRNA by binding to its ARE sequences located within the 3′UTR in an advanced tumor stage of CRC tissues (Fan and Steitz, 1998; Dixon et al, 2001; Denkert et al, 2006; Badawi et al, 2017). COX-2 is a major facilitator of several cellular activities (e.g., proliferation, cell death resistance, angiogenesis, and metastasis) (Fan and Steitz, 1998; Denkert et al, 2006; Jang et al, 2017; López-Cortés et al, 2019). ELAVL1 is normally found in the nucleus, where it participates in splicing and polyadenylation, but in CRC cells ELAVL1 is localized in the cytoplasm promoting mRNA stabilization of its targets (Fan and Steitz, 1998; Brennan and Steitz, 2001; López de Silanes et al, 2011; Akaike et al, 2014; Liu et al, 2018).…”

Prediction of druggable proteins using machine learning and functional enrichment analysis: a focus on cancer-related proteins and RNA-binding proteins

“…In our previous study [44], we revealed essential proteins associated with BC pathogenesis through deep analyses of genetic alterations, signaling pathways [52], protein-protein interaction networks [55, 56], protein expression [57, 58], dependency maps [57], and enrichment maps [49] of previously prioritized genes by the Consensus Strategy [59], the Pan-Cancer Atlas project [60–64], the Pharmacogenomics Knowledgebase (PharmGKB) [2], and the Cancer Genome Interpreter [65]. The druggable prediction of BC proteins through ML approaches will provide us relevant information regarding potential biomarkers, therapeutic targets and future clinical trials, avoiding ethnicity bias and improving cancer pharmacogenomics and precision medicine worldwide [66–76].…”

C677T and A1298C MTHFR gene polymorphisms and response to fluoropyrimidine-based chemotherapy in Mestizo patients with metastatic colorectal cancer

“…These contradictory findings can be the result of different methodologies and techniques, or due to different chemotherapy regimens employed in each trial. Moreover, the prevalence of each of the aforementioned SNPs varies according to ethnicity [26,27], a fact that may further contribute to explain these contradictory findings.…”