Cytotoxic T-lymphocyte antigen 4 polymorphisms and breast cancer susceptibility: Evidence from a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Cytotoxic T-lymphocyte antigen 4 (CTLA-4) is an immune checkpoint and regulates the immune function of T cells. However, previous findings regarding the association of CTLA-4 polymorphisms and breast cancer remain inconclusive. Therefore, we performed a meta-analysis to investigate the potential effects of five polymorphisms (-1722 T/C, -1661 A/G -318 C/T, +49 A/G, and CT60 A/G) in the CTLA-4 gene on breast cancer susceptibility. METHODS: Relevant literatures were systematically searched through electronic databases including PubMed, EMBASE, and Web of Science up to October 10, 2021. Available data were extracted and odds ratios (ORs) with 95% confidence intervals were used to estimate the pooling effect size. The Newcastle-Ottawa Scale was applied for assessing the quality of included studies. We conducted subgroup analyses based on ethnicity and control sources to explore levels of heterogeneity. Moreover, sensitivity analysis and publication bias were assessed. RESULTS: Finally, a total of 12 eligible studies regarding CTLA-4 polymorphisms and breast cancer were included. For overall analyses, only the +49 A/G polymorphism was significantly associated with breast cancer under allelic (OR = 1.19), dominant (OR = 1.27), and recessive (OR = 1.27) models. Ethnicity-based subgroup analysis found that the +49 A/G polymorphism has a significant risk (OR = 2.03) of breast cancer under the recessive model in the non-Asian population. Studies with hospital-based controls showed that the +49 A/G polymorphism has significant breast cancer risks under allelic (OR = 1.44), dominant (OR = 1.86), and recessive (OR = 1.60) models. In addition, those with population-based controls found that -1722 T/C polymorphism has a significant breast cancer risk under allelic (OR = 1.19) and dominant (OR = 1.26) models. CONCLUSION: This meta-analysis suggested that CTLA-4 + 49 A/G polymorphism may significantly associate with breast cancer susceptibility. Future studies containing various populations are helpful for evaluating the impacts of CTLA-4 polymorphisms on breast cancer susceptibility.
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 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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.043 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".