Promoter hypermethylation in Indian primary oral squamous cell carcinoma
Bibliographic record
Abstract
We evaluated promoter hypermethylation of a panel of tumor suppressor genes as a means to detect epigenetic alterations in oral squamous cell carcinomas (OSCC) of Indian-origin and compare with North-American head and neck squamous cell carcinomas (HNSCC). Quantitative-methylation-specific PCR was used to investigate the promoter methylation status of DCC, EDNRB, p16(INK4a) and KIF1A in 92 OSCC, and compared to 48 paired normal tissues and 30 saliva and sera samples from healthy control subjects. Aberrant methylation of at-least one of these genes was detected in 74/92 (80.4%) OSCC; 72.8% at EDNRB, 71.7% at KIF1A, 47.8% at p16(INK4a) and 58.7% at DCC; and in 5 of 48 (10.4%) normal oral tissues. None of the saliva and sera samples from controls exhibited DNA methylation in these four target genes. Thirty-two of 72 node positive cases harbored p16(INK4a) and DCC hypermethylation (p = 0.005). Thus, promoter hypermethylation in genes analyzed herein is a common event in Indian OSCC and may represent promising markers for the molecular staging of OSCC patients. We found higher frequency of p16(INK4a) methylation (47.8%) in this Indian cohort in comparison with a North-American cohort (37.5%). In conclusion, aberrant methylation of EDNRB, KIF1A, DCC and p16(INK4a) genes is a common event in Indian OSCC, suggesting that epigenetic alterations of these genes warrant validation in larger studies for their potential use as biomarkers.
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 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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".