Association and in silico investigations of miR‐302c insertion/deletion variant as a novel biomarker with susceptibility to gastric cancer
Bibliographic record
Abstract
Gastric cancer (GC) is the fifth most prevalent malignant tumor and the third most frequent cause of cancer mortality worldwide. rs199971565 is an insertion/deletion (INDEL) located in microRNA-302c (miR-302c) seed site, which may affect its function and biogenesis. There is no genetic association study investigating this INDEL with any disease till now. Thus, the current study was conducted to investigate the association of rs199971565 with susceptibility to GC in an Iranian population. In addition, in silico studies were performed to reveal the possible functional significance of this INDEL. A total of 378 subjects were genotyped through amplification refractory mutation system PCR (ARMS-PCR) after DNA extraction from peripheral blood by the salting out procedure. Also, in silico analyses were performed through databases and web tools including MiRNASNP V2.0, miRWalk V2.0, miRTarBase, DAVID V6.8, RNAfold, PHDcleave, miRmap, and STarMir. Results revealed that there was an association between rs199971565 and the incidence risk of GC under a recessive (P = .04, odds ratio [OR] = 18.73; 95% confidence interval [CI] = 1.07-326.95) model of inheritance. Also, compared to the Ins allele, the Del allele significantly increased the risk of GC (P = .01, OR = 2.02; 95% CI = 1.11-3.66). Further analyses showed no significant association in age and sex between two study groups (P = .216 and P = .798, respectively). In conclusion, for the first time, this study indicated the association and in silico investigations of rs199971565 and suggested it as a novel INDEL biomarker located in the seed site of miR-302c, which may have crucial roles in the susceptibility to GC and its incidence risk.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".