Abstract 987: Comprehensive characterization of urothelial bladder cancer: a TCGA Project update
Bibliographic record
Abstract
Abstract Urothelial carcinoma (UC) is a major cause of morbidity and mortality for which there are no approved molecularly targeted agents and few good treatment options beyond cisplatin-based chemotherapy. As part of The Cancer Genome Atlas (TCGA) Project, we analyzed 131 chemotherapy-naive, muscle-invasive UC tumors for somatic mutations, DNA copy number variants (CNVs), mRNA and microRNA expression, protein expression and phosphorylation, DNA methylation, transcript splicing, gene fusion, viral integration, pathway perturbation, clinical correlates, and histopathology (TCGA Research Network, Nature, in press). Whole-exome sequencing showed 29 recurrently mutated genes. Potential therapeutic targets include altered PIK3CA, ERBB2, FGFR3, TSC1, and ERBB3, plus mutated chromatin-regulating genes MLL, MLL2, MLL3, CREBBP, CHD7, SRCAP, ARID1A, KDM6A (UTX), and EP300. There were 22 arm-level CNVs and 27 focally amplified or deleted regions. CDKN2A was deleted in 47%. Low-pass whole genome sequencing identified FGFR3-TACC3 fusions. Viral DNA was identified in 6% (CMV, HHV6B, HPV16, BK polyoma), and viral transcripts were identified in 4% (CMV, BK polyoma, HPV16). . mRNA-seq identified 4 tumor clusters. Cluster I shows papillary morphology and FGFR3 dysregulation. Clusters I and II express high HER2 (ERBB2) and estrogen receptor beta signaling signature, sharing features with Luminal A breast cancer. Cluster III shows similarities to Basal-like breast and squamous cell head and neck carcinomas. . Integrated analyses confirm alteration of multiple pathways, including cell cycle regulation (93%), kinase and PI3-K signaling (72%), and epigenetic regulation (histone-modifiers: 89%; SWI/SNF nucleosome remodeling complex: 64%). Recurrent alterations in the PI3-kinase/AKT/mTOR pathway (42%) and RTK/RAS pathway (44%) are potentially actionable. . Overall, this study and others have identified multiple druggable targets in UC. FGFR3 is activated by mutation, gene fusion, and overexpression, suggesting clinical trials of FGFR3 inhibitors. PI3-kinase/mTOR/AKT/TSC1 pathway alterations are frequent, and mutation in TSC1 has been associated with response to mTOR inhibitors. ERBB2 amplifications and activating mutations may be targetable with agents such as trastuzumab, trastuzumab-DM1, lapatinib, and neratinib. The frequent alterations in epigenetic regulatory pathways suggest trials of agents such as the bromodomain inhibitors. The project is now being updated on the basis of data on 117 additional tumors. Citation Format: John N. Weinstein, Jaegil Kim, Chad J. Creighton, Rehan Akbani, Katherine A. Hoadley, William Y. Kim, Margaret B. Morgan, Toshinori Hinoue, Andrew Cherniack, Xiaoping Su, Andrew J. Mungall, Michael C. Ryan, Jonathan E. Rosenberg, Dean F. Bajorin, Bogdan Czerniak, Donna Hansel, Victor E. Reuter, Brian D. Robinson, Hikmat A. Al-Ahmadie, Jeffrey S. Damrauer, Wei Zhang, Yuexin Liu, Dmitry Gordenin, Joshua M. Stuart, Nikolaus Schultz, Gordon Robertson, Raju Kucherlapati, Peter W. Laird, Gordon B. Mills, David J. Kwiatkowski, Seth P. Lerner, representing TCGA's Bladder Cancer Working Group. Comprehensive characterization of urothelial bladder cancer: a TCGA Project update. [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 987. doi:10.1158/1538-7445.AM2014-987
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".