Epigenetically silenced miR-34b/c as a novel faecal-based screening marker for colorectal cancer
Bibliographic record
Abstract
BACKGROUND: MicroRNAs are tiny non-coding small endogenous RNAs that regulate gene expression by translational repression, mRNA cleavage and mRNA inhibition. The aim of this study was to investigate the hypermethylation of miR-34b/c and miR-148a in colorectal cancer, and correlate this data to clinicopathological features. We also aimed to evaluate the hypermethylation of miR-34b/c in faeces specimens as a novel non-invasive faecal-DNA-based screening marker. METHODS: The 5-aza-2'-deoxycytidine treatment and methylation-specific PCR were carried out to detect the hypermethylation of miR-34b/c and miR-148a. RESULTS: The miR-34b/c hypermethylation was found in 97.5% (79 out of 82) of primary colorectal tumours, P=0.0110. In 75% (21 out of 28) of faecal specimens we found a hypermethylation of miR-34b/c while only in 16% (2 out of 12) of high-grade dysplasia. In addition, miR-148a was found to be hypermethylated in 65% (51 out of 78) of colorectal tumour tissues with no significant correlation to clinicopathological features. However, a trend with female gender and advanced age was found, P=0.083. We also observed a trend to lower survival rate in patients with miR-148a hypermethylation with 10-year survival probability: 48 vs 65%, P=0.561. CONCLUSIONS: These findings show that aberrant hypermethylation of miR-34b/c could be an ideal class of early screening marker, whereas miR-148a could serve as a disease progression follow-up marker.
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".