OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes

García-Cárdenas

et al. 2020

Preprint

Breast cancer (BC) is the leading cause of cancer-associated death among women worldwide. Despite treatment efforts, advanced BC with distant organ metastases is considered incurable. A better understanding of BC molecular processes is therefore of great interest to identify new therapeutic targets. Although large-scale efforts, such as The Cancer Genome Atlas (TCGA), have completely redefined cancer drug development, diagnosis, and treatment, additional key aspects of tumor biology remain to be discovered. In that respect, post-transcriptional regulation of tumorigenesis represents an understudied aspect of cancer research. As key regulators of this process, RNA-binding proteins (RBPs) are emerging as critical modulators of tumorigenesis but only few have defined roles in BC. To unravel new putative BC RBPs, we have performed in silico analyses of all human RBPs in three major cancer databases (TCGA-Breast Invasive Carcinoma, the Human Protein Atlas, and the Cancer Dependency Map project) along with complementary bioinformatics resources (STRING protein-protein interactions and the Network of Cancer Genes 6.0). Thus, we have identified six putative BC progressors (MRPL13, SCAMP3, CDC5L, DARS2, PUF60, and PLEC), and five BC suppressors RBPs (SUPT6H, MEX3C, UPF1, CNOT1, and TNKS1BP1). These proteins have never been studied in BC but show similar cancer-associated features than well-known BC proteins. Further research should focus on the mechanisms by which these proteins promote or suppress breast tumorigenesis, holding the promise of new therapeutic pathways along with novel drug development strategies.

Section: Resultsmentioning

confidence: 99%

“…Non-cancer gene list, related to Fig.1A, was constructed as follow: non-cancer genes from Piazza et al . 31 , without RBPs and NCG6 30 cancer genes, were reanalyzed using Piazza’s OncoScore algorithm (http://www.galseq.com/oncoscore.html), giving a final list of 177 non-cancer genes (Supp. Table S1).…”

Section: Methodsmentioning

confidence: 99%

In silico analyses reveal new putative Breast Cancer RNA-binding proteins

García-Cárdenas

et al. 2020

Preprint

“…We analyzed five gene sets in order to compare the frequency mean of genomic alterations among them. The first gene set (n = 177) was integrated by the non-cancer genes 113 . We calculated the OncoScore of non-cancer genes, taking out all genes from our study.…”

Section: Methodsmentioning

confidence: 99%

OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

Paz‐y‐Miño

et al. 2020

Sci Rep

Breast cancer (Bc) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic targets, a better understanding of BC molecular processes is required. Here we focused on elucidating the molecular hallmarks of BC heterogeneity and the oncogenic mutations involved in precision medicine that remains poorly defined. To fill this gap, we established an OncoOmics strategy that consists of analyzing genomic alterations, signaling pathways, protein-protein interactome network, protein expression, dependency maps in cell lines and patient-derived xenografts in 230 previously prioritized genes to reveal essential genes in breast cancer. As results, the OncoOmics BC essential genes were rationally filtered to 140. mRNA up-regulation was the most prevalent genomic alteration. The most altered signaling pathways were associated with basal-like and Her2-enriched molecular subtypes . RAC1, AKT1, CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, BCL2, CTNNB1, EGFR, CDK2, GRB2, MED1 and GATA3 were essential genes in at least three oncoomics approaches. Drugs with the highest amount of clinical trials in phases 3 and 4 were paclitaxel, docetaxel, trastuzumab, tamoxifen and doxorubicin. Lastly, we collected ~3,500 somatic and germline oncogenic variants associated with 50 essential genes, which in turn had therapeutic connectivity with 73 drugs. In conclusion, the OncoOmics strategy reveals essential genes capable of accelerating the development of targeted therapies for precision oncology.Breast cancer (BC) is a complex and heterogeneous disease characterized by an intricate interplay between different biological aspects such as ethnicity, genomic alterations, gene expression deregulation, hormone disruption, signaling pathway alterations, hypoxia, and environmental determinants 1,2 . Over the last years, prevention, treatment and survival strategies have evolved favorably; however, there are BC profiles that remain incurable 3 .

“…We analyzed five gene sets in order to compare the average frequency of genetic alterations among them. The first gene set (n = 177) was integrated by the non-cancer genes 96 . We calculated the OncoScore of non-cancer genes, taking out all genes from our study.…”

Section: Methodsmentioning

confidence: 99%

OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

Paz‐y‐Miño

et al. 2019

Preprint

SUMMARYBreast cancer (BC) is a heterogeneous disease where each OncoOmics approach needs to be fully understood as a part of a complex network. Therefore, the main objective of this study was to analyze genetic alterations, signaling pathways, protein-protein interaction networks, protein expression, dependency maps and enrichment maps in 230 previously prioritized genes by the Consensus Strategy, the Pan-Cancer Atlas, the Pharmacogenomics Knowledgebase and the Cancer Genome Interpreter, in order to reveal essential genes to accelerate the development of precision medicine in BC. The OncoOmics essential genes were rationally filtered to 144, 48 (33%) of which were hallmarks of cancer and 20 (14%) were significant in at least three OncoOmics approaches: RAC1, AKT1 CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, PLCG1, GRB2, MED1, TOP2A, GATA3, BCL2, CTNNB1, EGFR and CDK2. According to the Open Targets Platform, there are 111 drugs that are currently being analyzed in 3151 clinical trials in 39 genes. Lastly, there are more than 800 clinical annotations associated with 94 genes in BC pharmacogenomics.