ReviewThe oncologist2024
Understanding variants of unknown significance and classification of genomic alterations.
Review in The oncologist, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Carboplatin with or without nivolumab in metastatic triple-negative breast cancer: a randomized phase II trial.Nature communications · 2026Trial
- Genomic profiling of Mexican patients with B-cell precursor acute lymphoblastic leukemia reveals clinically significant somatic and potential germline variants.The journal of pathology. Clinical research · 2026Article
- First European case of Geller syndrome complicated with hypokalemic nephropathy: A case report and literature review.Metabolism open · 2026Review
- Functional characterization of BRCA1 variants of unknown significance using homologous recombination repair assays.Breast cancer research : BCR · 2025Article
- Evaluating Liquid Biopsy for Circulating Tumor DNA (ctDNA) Detection as a Complementary Diagnostic Tool in Thyroid Cancer Among Ecuadorian Women.International journal of molecular sciences · 2025Article
- Investigation of a germline variant of uncertain significance (MRE11:c.1138C > T) identified by exome sequencing in a cancer-affected individual and co-segregation analysis in affected and unaffected family members.Molecular biology reports · 2025Article
- Understanding variants of unknown significance: the computational frontier.The oncologist · 2024Review
- Variants of uncertain significance in precision oncology: nuance or nuisance?The oncologist · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite recent efforts to issue clinical guidelines outlining strategies to define the pathogenicity of genomic variants, there is currently no standardized framework for which to make these assertions. This review does not present a step-by-step methodology, but rather takes a holistic approach to discuss many aspects which should be taken into consideration when determining variant pathogenicity. Categorization should be curated to reflect relevant findings within the scope of the specific medical context. Functional characterization should evaluate all available information, including results from literature reviews, different classes of genomic data repositories, and applicable computational predictive algorithms. This article further proposes a multidimensional view to infer pathogenic status from many genomic measurements across multiple axes. Notably, tumor suppressors and oncogenes exhibit fundamentally different biology which helps refine the importance of effects on splicing, mutation interactions, copy number thresholds, rearrangement annotations, germline status, and genome-wide signatures. Understanding these relevant datapoints with thoughtful perspective could aid in the reclassification of variants of unknown significance (VUS), which are ambiguously understood and currently have uncertain clinical implications. Ongoing assessments of VUS examining these relevant biological axes could lead to more accurate classification of variant pathogenicity interpretation in diagnostic oncology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.