Evaluation of the 8q24 Prostate Cancer Risk Locus and <i>MYC</i> Expression
Bibliographic record
Abstract
Polymorphisms at 8q24 are robustly associated with prostate cancer risk. The risk variants are located in nonprotein coding regions and their mechanism has not been fully elucidated. To further dissect the function of this locus, we tested two hypotheses: (a) unannotated microRNAs (miRNA) are transcribed in the region, and (b) this region is a cis-acting enhancer. Using next generation sequencing, 8q24 risk regions were interrogated for known and novel miRNAs in histologically normal radical prostatectomy tissue. We also evaluated the association between the risk variants and transcript levels of multiple genes, focusing on the proto-oncogene, MYC. RNA expression was measured in histologically normal and tumor tissue from 280 prostatectomy specimens (from 234 European American and 46 African American patients), and paired germline DNA from each individual was genotyped for six 8q24 risk single nucleotide polymorphisms. No evidence was found for significant miRNA transcription within 8q24 prostate cancer risk loci. Likewise, no convincing association between RNA expression and risk allele status was detected in either histologically normal or tumor tissue. To our knowledge, this is one of the first and largest studies to directly assess miRNA in this region and to systematically measure MYC expression levels in prostate tissue in relation to inherited risk variants. These data will help to direct the future study of this risk locus.
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 | 0.003 | 0.000 |
| 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 | 0.001 |
| 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".