Abstract 08: Impaired H3K36 methylation defines a subset of head and neck squamous cell carcinomas
Bibliographic record
Abstract
Abstract Human papillomavirus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs) are deadly and common cancers. Recent genomic studies implicate multiple genetic pathways, including cell signaling, cell cycle and immune evasion, in their development. Here we analyze public data sets and uncover a previously unappreciated role of epigenome deregulation in the genesis of 13% of HPV-negative HNSCCs. Specifically, we identify novel recurrent mutations encoding p.Lys36Met (K36M) alterations in multiple H3 histone genes. We further validate the presence of these alterations in multiple independent HNSCC data sets and show that, along with previously described NSD1 mutations, they correspond to a specific DNA methylation cluster. The K36M substitution and NSD1 defects converge on altering methylation of histone H3 at K36 (H3K36), subsequently blocking cellular differentiation and promoting oncogenesis. Our data further indicate limited redundancy for NSD family members in HPV-negative HNSCCs and suggest a potential role for impaired H3K36 methylation in their development. Further investigation of drugs targeting chromatin regulators is warranted in HPV-negative HNSCCs driven by aberrant H3K36 methylation. Citation Format: Chao Lu, Simon Papillon-Cavanagh, Tenzin Gayden, Leonie G. Mikael, Denise Bechet, Christina Karamboulas, Laurie Ailles, Jason Karamchandani, Dylan M. Marchione, Benjamin A. Garcia, Ilan Weinreb, David Goldstein, Peter W. Lewis, Octavia-Maria Dancu, Sandeep Dhaliwal, William Stecho, Christopher J. Howlett, Joe S. Mymryk, John W. Barrett, Anthony C. Nichols, C David Allis, Jacek Majewski, Nada Jabado. Impaired H3K36 methylation defines a subset of head and neck squamous cell carcinomas [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; April 23-25, 2017; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(23_Suppl):Abstract nr 08.
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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 | 0.001 |
| 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) | 0.006 | 0.001 |
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".