Genetic polymorphisms of HOTAIR gene are associated with the risk of breast cancer in a sample of southeast Iranian population
Bibliographic record
Abstract
There is an increasing body of evidence which highlights the critical functions of long non-coding RNAs in the carcinogenicity mechanism of a variety of cancers. It has been reported that HOX transcript antisense intergenic RNA, a member of long non-coding RNA family, increases breast cancer risk. To date, no data regarding the association between HOX transcript antisense intergenic RNA polymorphisms and the risk of breast cancer development has been reported in Iran. Here, we examine the possible association between HOX transcript antisense intergenic RNA gene polymorphisms and breast cancer in a sample of southeast Iranian female population. The HOX transcript antisense intergenic RNA rs920778, rs12826786, rs4759314, and 1899663 gene polymorphisms were genotyped in 220 cases and 231 controls by polymerase chain reaction-restriction fragment length polymorphism. Our findings indicated that rs920778 polymorphism has significant positive association with breast cancer; rs12826786 and rs1899663 polymorphisms demonstrated significant negative association with breast cancer; and the rs4759314 variant was not associated with breast cancer risk. Haplotype analysis revealed that TGAC, CTAT, and TTAT haplotypes significantly decreased the risk of breast cancer compared with rs920778T/rs1899663G/rs4759314A/rs12826786T haplotype. In conclusion, we investigated only four variants of HOX transcript antisense intergenic RNA gene, and the findings suggest that HOX transcript antisense intergenic RNA rs920778, rs12826786, and rs1899663 polymorphisms may be associated with breast cancer risk in a sample of southeast Iranian population. Further replication studies with other polymorphisms of HOX transcript antisense intergenic RNA gene involving a greater sample size and different ethnicities are necessary to verify our findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".