Ovarian Cancers Harboring Inactivating Mutations in <i>CDK12</i> Display a Distinct Genomic Instability Pattern Characterized by Large Tandem Duplications
Bibliographic record
Abstract
CDK12 is a recurrently mutated gene in serous ovarian carcinoma, whose downregulation is associated with impaired expression of DNA damage repair genes and subsequent hypersensitivity to DNA-damaging agents and PARP1/2 inhibitors. In this study, we investigated the genomic landscape associated with CDK12 inactivation in patients with serous ovarian carcinoma. We show that CDK12 loss was consistently associated with a particular genomic instability pattern characterized by hundreds of tandem duplications of up to 10 megabases (Mb) in size. Tandem duplications were characterized by a bimodal (∼0.3 and ∼3 Mb) size distribution and overlapping microhomology at the breakpoints. This genomic instability, denoted as the CDK12 TD-plus phenotype, is remarkably distinct from other alteration patterns described in breast and ovarian cancers. The CDK12 TD-plus phenotype was associated with a greater than 10% gain in genomic content and occurred at a 3% to 4% rate in The Cancer Genome Atlas-derived and in-house cohorts of patients with serous ovarian carcinoma. Moreover, CDK12-inactivating mutations together with the TD-plus phenotype were also observed in prostate cancers. Our finding provides new insight toward deciphering the function of CDK12 in genome maintenance and oncogenesis. Cancer Res; 76(7); 1882-91. ©2016 AACR.
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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 | 0.000 |
| 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".