A systematic review of genome-wide association studies on bladder cancer
Bibliographic record
Abstract
Abstract Background Bladder cancer (BC) is the most common cancer of the urinary tract worldwide with over 550,000 new cases each year, bladder cancer has drawn relatively limited research attention and healthcare interventions despite the escalating incidence and mortality rates, particularly in Africa. Historically, the clinical handling of bladder cancer remained largely unchanged for many years. However, novel research initiatives have heralded a fresh epoch in its diagnosis and treatment, fueled by detailed probing of molecular changes. Aim This study aimed to identify genetic susceptibility loci associated with bladder cancer by systematically reviewing previous Genome-Wide Association Studies (GWAS). Methods In line with this objective, comprehensive literature searches were conducted across PubMed, Google Scholar, and relevant genetic databases, focusing on bladder cancer GWAS studies from 2000 through to November 2022. This systematic review adhered to the robust PRISMA standards. To evaluate the credibility of the studies under scrutiny, the Newcastle-Ottawa Scale was employed, further assessing any potential bias risk. Results The investigation identified chromosome 18q12.3 as the most vulnerable to bladder cancer, revealing four polymorphisms at this locus: rs7238033, rs10775480, rs11082469, and rs17674580. Furthermore, chromosome 5p15.3 emerged as the second most susceptible, with three noted polymorphisms: rs2736098 and two instances of rs401681. Conclusion Despite these findings, our understanding of genetic predisposition to bladder cancer remains rudimentary, with the majority of substantial data deriving from GWAS. No additional genetic association evidence emerged from this systematic review. Given the relatively minor influence of our current knowledge of genetic susceptibility to bladder cancer on public health, a call for larger cohort studies is necessary. These expanded studies can potentially unveil a broader range of significant polymorphisms across the genome, thereby enhancing our understanding and approach to bladder cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".