Whole-exome Sequencing of Prostate Cancer in Sardinian Identify Recurrent UDP-glucuronosyltransferase Amplifications
Bibliographic record
Abstract
Globally, prostate cancer is the third most common cancer in the world, and the second most common cancer in men. However, rates for incidence and mortality vary considerably with race, ethnicity, and geography. Over 97 significantly mutated genes that have been identified in prostate cancer; however, a lack of genomic prostate cancer studies focusing on different racial and ethnic groups and racial mixing pose a serious challenge to universalize these findings. The Sardinian population is an isolated Mediterranean population that has a high frequency of centenarians and a much lower incidence of prostate cancer than found in males in mainland Europe. Here, we conducted a genomic prostate cancer study on a Sardinian cohort diagnosed with local prostate cancer. Our data reveals a low rate of ERG fusion in Sardinian prostate cancer. Interestingly, we identified a novel BTBD7-SLC2A5 fusion that occurred in 13% of the patients. We also found that the UGT2B4 on 4q13.2 was amplified in 20% of the Sardinian patients but rarely amplified in patients of other population. These observations underscore the importance of the inter-population molecular heterogeneity of prostate cancer. In addition, we examined the expression of UGT2B4 in 497 prostate cancer patients derived from The Cancer Genome Atlas database. We found that high expression of UGT2B4 was associated with low-grade prostate cancer and upregulation of UGT2B4 in tumors was associated with upregulation of metabolism pathways such as 'de novo' IMP biosynthetic process, glutamine and monocarboxylic acid metabolism. These data provide insight into clinical relevance and functional mechanism of UGT2B4. Further understanding functional mechanism of UGT2B4 amplification and BTBD7-SLC2A5 fusion will aid in developing drugs to benefit the prostate cancer patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".