HLA-G Gene Variability Is Associated with Papillary Thyroid Carcinoma Morbidity and the HLA-G Protein Profile
Bibliographic record
Abstract
Human leukocyte antigen (HLA)-G is an immune checkpoint molecule that is highly expressed in papillary thyroid carcinoma (PTC). The HLA-G gene presents several functional polymorphisms distributed across the coding and regulatory regions (5′URR: 5′ upstream regulatory region and 3′UTR: 3′ untranslated region) and some of them may impact HLA-G expression and human malignancy. To understand the contribution of the HLA-G genetic background in PTC, we studied the HLA-G gene variability in PTC patients in association with tumor morbidity, HLA-G tissue expression, and plasma soluble (sHLA-G) levels. We evaluated 185 PTC patients and 154 healthy controls. Polymorphic sites defining coding, regulatory and extended haplotypes were characterized by sequencing analyses. HLA-G tissue expression and plasma soluble HLA-G levels were evaluated by immunohistochemistry and ELISA, respectively. Compared to the controls, the G0104a(5′URR)G*01:04:04(coding)UTR-03(3’UTR) extended haplotype was underrepresented in the PTC patients, while G0104a(5′URR)G*01:04:01(coding)UTR-03(3′UTR) was less frequent in patients with metastatic and multifocal tumors. Decreased HLA-G tissue expression and undetectable plasma sHLA-G were associated with the G010102a(5′URR)G*01:01:02:01(coding)UTR-02(3′UTR) extended haplotype. We concluded that the HLA-G variability was associated with PTC development and morbidity, as well as the magnitude of the encoded protein expression at local and systemic levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".