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This summary evaluates the current evidence linking GBP5 (HGNC:19895) to ovarian cancer (MONDO_0008170). Multiple in silico investigations have incorporated GBP5 into prognostic gene signatures and bioinformatic analyses of ovarian cancer, suggesting a potential role in disease pathogenesis and patient outcome. Although the data do not yet include classical segregation or case‐control studies with disjoint affected probands (PMID:35163645, PMID:37760841), the consistent inclusion of GBP5 in these multi‐gene panels lends preliminary support to its involvement.
The genetic evidence is primarily derived from comprehensive multi-patient studies. One study analyzed a total of 976 SNPs/mutations across several genes, where 284 were related to female cancers, and GBP5 was highlighted as part of this in silico screening (PMID:35163645). A second study constructed a 10‑gene signature associated with CD8+ T cell infiltration that further correlated with ovarian cancer prognosis (PMID:37760841). No individual pathogenic coding variants have been reported for GBP5, and in the absence of identifying specific missense or loss‑of‑function variants, the genetic evidence remains at a preliminary stage.
Regarding functional evidence, the available data are exclusively based on computational predictions rather than experimental work. In silico analyses have been used to assess the structural and functional consequences of SNPs across the candidate genes; however, for GBP5, no direct functional assays or model system studies have been performed to validate a mechanistic role in ovarian carcinogenesis. This lack of direct biochemical or cellular validation limits the confidence in pathogenicity inference for GBP5 despite supportive computational metrics.
No robust segregation data across affected relatives were reported in these studies. The association has been largely inferred from gene expression profiling and the construction of prognostic gene signatures in ovarian cancer tissue cohorts. As such, the evidence does not include clear familial segregation, and the number of affected relatives with segregating GBP5 variants remains unreported.
In summary, while GBP5 is recurrently identified in multi-patient in silico studies and prognostic models for ovarian cancer, the overall strength of the gene-disease association is limited by the absence of direct segregation, functional, and variant-level evidence. Additional research integrating experimental validations and family-based genetic studies is needed to substantiate GBP5 as a clinically actionable biomarker in ovarian cancer.
Key Take‑home: GBP5 represents a promising candidate in ovarian cancer prognostication that warrants further functional and clinical validation to support its diagnostic use.
Gene–Disease AssociationLimitedAssociation based on in silico analyses and prognostic gene signatures in ovarian cancer, without direct evidence from segregation or individual pathogenic variants (PMID:35163645, PMID:37760841). Genetic EvidenceLimitedGenetic evidence is derived from computational evaluations of SNPs and gene expression profiles in large ovarian cancer cohorts where GBP5 is included as a candidate biomarker. Functional EvidenceLimitedFunctional support is based solely on in silico predictions, with no experimental or model-based assays to directly demonstrate the impact of GBP5 alterations on ovarian cancer pathogenesis. |