Abstract A04: Molecular characterization of undifferentiated pleomorphic sarcomas
Bibliographic record
Abstract
Abstract Objective: Undifferentiated pleomorphic sarcomas (UPS) are high-grade soft-tissue sarcomas (STS) with no apparent line of differentiation. Despite overall gains in the management of STS, progress in therapies based on molecular targets and understanding the unknown genetic diversity is needed, especially in UPS where response to therapy is limited. Using integrated multi-omic analysis, we aim to characterize UPS for recurrent genetic mutations, altered pathways, and the mutational spectrum. These insights into UPS may enable robust classification, identify prognostic markers, and lead to novel treatment approaches. Methods: Clinically well-annotated cases of UPS with matched blood specimens were retrieved from the Sarcoma Tumor Bank at Mount Sinai Hospital, Toronto. Using current World Health Organization histopathologic classification, reevaluated cases were subjected to whole-genome (WGS) or whole-exome sequencing (WES) and RNA sequencing (RNA-seq). Cell lines and/or mouse xenografts were established from some of the UPS tumors. The goal of this study was to integrate annotated somatic mutations, expressed transcripts, mRNA fusions, structural rearrangements, and copy number aberrations to detect recurrent molecular features in UPS. Results: At present, 43 UPS tumor, 8 matched metastatic samples, 6 mouse xenografts, and 4 cell lines have been sequenced by WGS or WES and RNA-seq. Among the 34 cases analyzed by WES, known cancer genes TP53, LRP1B, ATRX, and RB1 are found to recurrently contain somatic variants. Among these genes, nonsilent somatic variants were found in 18/34 tumors. The somatic variant burden among the WES tumors is approximately 5 muts/Mb. Two UPS cases were hypermutated with a somatic variant burden >10 muts/Mb. In examining the base changes in the hypermutated cases, the two display a C>A bias, in which the 5' and 3' bases flanking the C>A alterations in the hypermutated cases have a distinct pattern (TpCpN, CpCpA) that differ from the other samples. These somatic C>A biases in their trinucleotide context were not detected in >10K tumor cases across 33 cancer types sequenced by TCGA. An RB1 and ATXN10 fusion transcript that lacks the RB1 tumor-suppressing domain was confirmed in one case, while the derived cell line also expressed the RB1-ATXN10 fusion. The cell lines and xenograft models retained 8-71% of their matched tumors' somatic variants. The metastatic samples contained between 13-63% of the somatic variants also identified in their matched primary tumors, among the 4 WES metastatic samples analyzed thus far. Conclusion: Initial analyzes of UPS tumors has identified recurrently mutated cancer-related genes and a unique pattern of C>A bias not previously seen. Ongoing multi-omic analysis, integrating the RNA-seq with the somatic alterations, of UPS tumors may reveal further genomic events that may aid in stratification of UPS, understand the drivers of the disease, identify actionable targets, and realize novel therapeutics. Citation Format: Andrew Seto, Nalan Gokgoz, Qingxia Wei, Yael Babichev, Brendan C. Dickson, Benjamin Alman, Rebecca A. Gladdy, Adam Shlien, Jay Wunder, Irene L. Andrulis. Molecular characterization of undifferentiated pleomorphic sarcomas [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr A04.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".