RESUMO
Tumor mutational signatures have gained prominence in cancer research, yet the lack of standardized methods hinders reproducibility and robustness. Leveraging colorectal cancer (CRC) as a model, we explored the influence of computational parameters on mutational signature analyses across 230 CRC cell lines and 152 CRC patients. Results were validated in three independent datasets: 483 endometrial cancer patients stratified by mismatch repair (MMR) status, 35 lung cancer patients by smoking status and 12 patient-derived organoids (PDOs) annotated for colibactin exposure. Assessing various bioinformatic tools, reference datasets and input data sizes including whole genome sequencing, whole exome sequencing and a pan-cancer gene panel, we demonstrated significant variability in the results. We report that the use of distinct algorithms and references led to statistically different results, highlighting how arbitrary choices may induce variability in the mutational signature contributions. Furthermore, we found a differential contribution of mutational signatures between coding and intergenic regions and defined the minimum number of somatic variants required for reliable mutational signature assignment. To facilitate the identification of the most suitable workflows, we developed Comparative Mutational Signature analysis on Coding and Extragenic Regions (CoMSCER), a bioinformatic tool which allows researchers to easily perform comparative mutational signature analysis by coupling the results from several tools and public reference datasets and to assess mutational signature contributions in coding and non-coding genomic regions. In conclusion, our study provides a comparative framework to elucidate the impact of distinct computational workflows on mutational signatures.
Assuntos
Neoplasias Colorretais , Biologia Computacional , Mutação , Humanos , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Biologia Computacional/métodos , Fluxo de Trabalho , Linhagem Celular Tumoral , Sequenciamento do Exoma/métodos , Feminino , AlgoritmosRESUMO
Multiple strategies are continuously being explored to expand the drug target repertoire in solid tumors. We devised a novel computational workflow for transcriptome-wide gene expression outlier analysis that allows the systematic identification of both overexpression and underexpression events in cancer cells. Here, it was applied to expression values obtained through RNA sequencing in 226 colorectal cancer (CRC) cell lines that were also characterized by whole-exome sequencing and microarray-based DNA methylation profiling. We found cell models displaying an abnormally high or low expression level for 3533 and 965 genes, respectively. Gene expression abnormalities that have been previously associated with clinically relevant features of CRC cell lines were confirmed. Moreover, by integrating multi-omics data, we identified both genetic and epigenetic alternations underlying outlier expression values. Importantly, our atlas of CRC gene expression outliers can guide the discovery of novel drug targets and biomarkers. As a proof of concept, we found that CRC cell lines lacking expression of the MTAP gene are sensitive to treatment with a PRMT5-MTA inhibitor (MRTX1719). Finally, other tumor types may also benefit from this approach.
Assuntos
Neoplasias Colorretais , Regulação Neoplásica da Expressão Gênica , Transcriptoma , Humanos , Neoplasias Colorretais/genética , Neoplasias Colorretais/tratamento farmacológico , Neoplasias Colorretais/patologia , Neoplasias Colorretais/metabolismo , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Linhagem Celular Tumoral , Transcriptoma/genética , Perfilação da Expressão Gênica , Metilação de DNA/genéticaRESUMO
Serine/threonine-protein kinase B-raf (BRAF) mutations are found in 8-15% of colorectal cancer patients and identify a subset of tumors with poor outcome in the metastatic setting. We have previously reported that BRAF-mutant human cells display a high rate of protein production, causing proteotoxic stress, and are selectively sensitive to the proteasome inhibitors bortezomib and carfilzomib. In this work, we tested whether carfilzomib could restrain the growth of BRAF-mutant colorectal tumors not only by targeting cancer cells directly, but also by promoting an immune-mediated antitumor response. In human and mouse colorectal cancer cells, carfilzomib triggered robust endoplasmic reticulum stress and autophagy, followed by the emission of immunogenic-damage-associated molecules. Intravenous administration of carfilzomib delayed the growth of BRAF-mutant murine tumors and mobilized the danger-signal proteins calreticulin and high mobility group box 1 (HMGB1). Analyses of drug-treated samples revealed increased intratumor recruitment of activated cytotoxic T cells and natural killers, concomitant with the downregulation of forkhead box protein P3 (Foxp3)+ T-cell surface glycoprotein CD4 (CD4)+ T cells, indicating that carfilzomib promotes reshaping of the immune microenvironment of BRAF-mutant murine colorectal tumors. These results will inform the design of clinical trials in BRAF-mutant colorectal cancer patients.