Abstract 544: Recurrent DICER1 hotspot mutations in endometrial cancer and their impact on microRNA biogenesis
Bibliographic record
Abstract
Abstract Alternation in genes associated with microRNA (miRNA) biogenesis pathway may lead to miRNA dysregulation, and is implicated in a variety of human malignancies. Previously our group identified recurrent somatic “hotspot” mutations (E1705, D1709, D1810, E1813) in a critical miRNA-processing gene, DICER1, in rare sex cord-stromal tumors. During miRNA biogenesis, the two RNase III domains of DICER1 form an intramolecular dimer, which leads to the cleavage of the precursor miRNA (pre-miRNA) hairpin and generate mature 5p and 3p miRNAs from 5’ and 3’ arms of the precursor hairpin respectively. Studies have shown that the hotspot mutations in the RNase IIIb metal binding domain could impair DICER1's ability to generate mature 5p miRNAs, leading to global loss of 5p miRNAs. Recently, in collaboration with The Cancer Genome Atlas (TCGA), we identified DICER1 hotspot mutations in a small subset of endometrial cancer from TCGA cohort (6/248) as well as our own tumor bank (6/307), suggesting disruption of DICER1 is implicated in a common malignancy. We also found an additional recurrent mutation G1809R and demonstrated that it has similar detrimental effects on miRNA biogenesis as hotspot mutations through deep sequencing and realtime PCR. Using Illumina Miseq targeted resequencing and Sanger sequencing, we observed biallelic DICER1 mutations in RNase IIIb domain in some but not all cases. miRNA deep sequencing confirmed that 5p miRNAs are decreased in both cell line models and endometrial tumors with hotspot mutations. Bioinformatic analysis of RNA sequencing profiles from TCGA dataset predicted hotspot DICER1 mutations to have greater functional impact than non-hotspot DICER1 mutations on gene expression. The oncogenic properties of DICER1 hotspot mutations are currently under investigation. Citation Format: Jiamin Chen, Yemin Wang, Melissa McConechy, Michael Anglesio, Janine Senz, Winnie Yang, Jamie Rosner, Andy Chu, Grace Cheng, Gregg Morin, David Huntsman. Recurrent DICER1 hotspot mutations in endometrial cancer and their impact on microRNA biogenesis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 544. doi:10.1158/1538-7445.AM2014-544
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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 | 0.000 |
| 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) | 0.001 | 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".