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Record W4405848769 · doi:10.6000/1929-6029.2024.13.36

Statistical Analysis of Gene Variants for Homologous Recombination Pathways of DNA Repair leading to Cancer Susceptibility

2024· article· en· W4405848769 on OpenAlexvenueno aff
Usha Adiga, Bhuvan Jyoti, P. Reddemma, Adam A. Augustine, Sampara Vasishta

Bibliographic record

VenueInternational Journal of Statistics in Medical Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsHomologous recombinationGeneDNA repairHomologous chromosomeGeneticsRecombinationBiologyDNACancer

Abstract

fetched live from OpenAlex

Background: RAD51C, a critical member of the RAD51 paralog family, is essential for homologous recombination (HR)-mediated DNA repair, a pathway crucial for maintaining genomic stability. Mutations in RAD51C have been linked to cancer susceptibility, particularly in breast and ovarian cancers, where impaired DNA repair mechanisms contribute to genomic instability and tumor progression. Despite its clinical significance, the functional impact of specific RAD51C variants remains poorly understood, necessitating a comprehensive investigation into their biological implications. Methods: This study classified RAD51C gene variants into damaging and tolerant categories using computational prediction tools, including SIFT, PolyPhen, CADD, MetaLR, and Mutation Assessor. Variants were prioritized based on consensus scores and classified as high-confidence damaging variants. Correlation and agreement among tools were analyzed to refine predictions. Principal Component Analysis (PCA) and clustering methods were employed to group variants based on prediction patterns. Protein-protein interaction (PPI) networks and pathway enrichment analyses were conducted to contextualize damaging variants within broader biological systems, with a focus on their roles in HR, DNA repair, and cellular processes. Results: A total of 2526 variants were analyzed, with damaging variants showing consistent patterns across tools. Consensus scores highlighted 302 high-confidence damaging variants, which were associated with disrupted biological processes, including double-strand break repair via homologous recombination, telomere maintenance, and regulation of cell cycle checkpoints. PPI analysis revealed an interconnected network with 11 nodes and 54 edges, with a clustering coefficient of 0.982, indicating tightly coordinated interactions among DNA repair proteins. Pathway enrichment analyses identified significant associations with homologous recombination (FDR = 2.55E-17) and the Fanconi anemia pathway (FDR = 2.96E-06). Conclusion: This study provides a comprehensive framework for assessing the functional impacts of RAD51C variants by integrating computational predictions with biological analyses. The findings underscore the importance of RAD51C in HR and DNA repair pathways, offering insights into its role in genomic stability and cancer progression. These results can inform the prioritization of variants for experimental validation and guide therapeutic strategies targeting DNA repair deficiencies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.441
Teacher spread0.389 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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