<i>GHSR</i> DNA hypermethylation is a new epigenetic biomarker for gastric adenocarcinoma and beyond
Bibliographic record
Abstract
Aberrations of DNA methylation are early events in the development of tumors. In this study, we investigated the DNA methylation status of growth hormone secretagogue receptor (GHSR), a promising pan-cancer biomarker, in gastric cancer (GC). Initially, data sets from DNA methylation and gene expression studies available at Gene Expression Omnibus (GEO) were analyzed. Confirmation was done on primary tumor specimens and adjacent normal stomach tissue samples. Both analyses showed significant hypermethylation of GHSR. For further validation, The Cancer Genome Atlas data on stomach cancer was used. A receiver operating characteristic curve analysis yielded an area under the curve value of 0.85, corroborating its usefulness as a diagnostic marker. A genome-wide comethylation analysis revealed several correlated genes. CREB1 was found to act as an upstream regulator of this gene network. Furthermore, GHSR methylation was found to be a biomarker in several other tumor entities, namely cancers of the bladder, endometrium, esophagus, head and neck, liver, thyroid, kidney, and ovary. Our findings along with previous reports on other types of cancer suggest a high potential of GHSR gene methylation as a pan-cancer biomarker, which could be considered for liquid biopsy applications.
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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 | 0.000 | 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".