Frontiers in BioinformaticsCancer BiologyPeer-reviewed journal article
PAN-CANCER ANALYSES IDENTIFY ONCOGENIC DRIVERS, EXPRESSION SIGNATURES, AND THERAPEUTIC VULNERABILITIES IN RHO GTPase PATHWAY GENES
Rubén Fernández, Luis Francisco Lorenzo‐MartíniD, Vı́ctor QuesadaiD, Xosé R. BusteloiD
Abstract
RHO family GTPases are key regulators of cancer-related processes such as cytoskeletal dynamics, cell migration, proliferation, and survival. Despite this, a comprehensive understanding of RHO signaling alterations across tumors is still lacking. Here, we present a pan-cancer analysis of 484 genes encoding RHO GTPases, regulators, proximal effectors, distal downstream signaling elements, and components of their proximal interactomes using data from over 10,000 tumor samples and 33 tumor types present in The Cancer Genome Atlas (TCGA). In addition, we have utilized available data from genome-wide functional dependency screens performed in more than 1,000 gene-edited cancer cell lines. This study has uncovered positively selected mutations in both well-known and previously uncharacterized RHO pathway genes. Transcriptomic profiling reveals widespread and tumor-specific differential expression patterns, some of them correlating with copy number changes. Interestingly, certain regulators exhibit consistent expression profiles across tumors opposite to those predicted from their canonical roles. Coexpression and gene set enrichment analyses highlight coordinated transcriptional programs involving some RHO GTPase pathway genes and their linkage to key cancer hallmarks, including extracellular matrix reorganization, cell motility, cell cycle progression, cell survival, and immune modulation. Functional screens further identify context-specific dependencies on several deregulated RHO GTPase pathway genes. Altogether, this study provides a comprehensive map of RHO GTPase pathway alterations in cancer and identifies new oncogenic drivers, expression-based signatures, and therapeutic vulnerabilities that could guide future mechanistic and translational research.
- organism: human
- assay: whole-genome sequencing
- assay: bulk RNA-seq
- research focus: variant calling
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: benchmark study
- Citations
- 4
- FWCI
- 1.81
- Field percentile
- top 14%
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