Abstract 3381: TERT promoter mutation in granulosa cell tumours of the ovary: Prevalence and prognostic significance
Bibliographic record
Abstract
Abstract Granulosa cell tumours (GCTs) of the ovary account for 90% of sex cord-stromal tumours and have a high recurrence rate up to 50%. A missense mutation in the FOXL2 gene (c.402C>G; pC134W) is a defining feature of GCT and is used as a robust marker for diagnosis. However, other than the FOXL2 mutation the pathogenesis and the driving pathways remain unknown. Determining secondary genetic events in GCTs is essential to understanding and improving prognosis. In a pilot study, we completed an analysis of whole genome sequencing of ten GCTs and matched normal cases to generate a comprehensive catalogue of coding and non-coding events. We identified a TERT promoter mutation (c.228C>T) in 50% of these cases. TERT is normally inactivated in somatic tissues; however, this promoter mutation has been shown to re-activate transcription of TERT. We validated this TERT mutation in an international cohort of 300 GCTs and found it was present in approximately 25% of cases overall. These TERT promoter mutations have been used to revise the molecular classification of other cancer types such as gliomas. In GCT, we found that this TERT mutation was correlated with a significantly worse survival outcome in patients with primary GCT (p<0.005). Further, we found that this TERT mutation was present in a larger proportion of recurrent cases. Thus, this mutation may denote a novel subtype of GCT with a worse prognosis. Previous research has shown that TERT activation is evident in over 90% of cancers and is a fundamental step in tumourigenesis that enables unlimited proliferation. This TERT promoter mutation in GCT provides an explanation of how granulosa cells escape atresia and attain immortality. Thus, we hypothesize a mechanism in which the FOXL2 mutation prevents apoptosis and the TERT mutation allows limitless proliferation for oncogenes to transform granulosa cells. However, the current cell models of GCT lack relevant functional pathways and do not recapitulate the biology of these tumours. Therefore, we are developing more suitable cell models to test our hypothesis. We believe that understanding the interaction between these TERT and FOXL2 mutations may lead to novel cancer cell-specific targeted therapies. Citation Format: Jessica A. Pilsworth, Dawn R. Cochrane, Zhouchunyang Xia, Hugo M. Horlings, Winnie Yang, Melissa K. McConechy, Satoshi Yanagida, Anniina E. Färkkilä, Adele P. Wong, Genny Trigo-Gonzalez, S.W. Grace Cheng, Yikan Wang, Ali Bashashati, Gregg B. Morin, Esther Oliva, Sohrab P. Shah, David G. Huntsman. TERT promoter mutation in granulosa cell tumours of the ovary: Prevalence and prognostic significance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3381. doi:10.1158/1538-7445.AM2017-3381
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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) | 0.003 | 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".