Abstract B022: Subclonal somatic copy number alterations emerge and dominate in relapsed/refractory osteosarcoma
Bibliographic record
Abstract
Abstract Objective: Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. Methods: We performed 30-80x whole genome sequencing (WGS) of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and one sample from a metastatic or relapse site. A set of high confidence single nucleotide variants (SNV), copy number alterations (CNA), structural variations (SV) were called for each sample using our pediatric expanded genomics pipeline and an evolutionary analysis was performed using a custom pipeline of computational tools. Results: Of the 8 patients in our cohort, 4 had localized disease at diagnosis (OSCE4, OSCE5, OSCE6, OSCE9) and 4 had metastatic disease at diagnosis (OSCE1, OSCE2, OSCE3, OSCE10). There were 17 samples from primary sites, 7 were pretreatment biopsies, 10 from on therapy primary resections. 20 samples came from metastatic sites, 15 of which were from lung metastases. Driver gene SNV’s were identified in 5 of 8 patients, including TP53 (OSCE1), ATRX (OSCE3, OSCE10), RB1 (OSCE4), and CDKN2A (OSCE9). There were no new driver SNV’s that emerged post-therapy in any patient. HATCHet, an algorithm that infers clone-specific copy number alterations, identified subclonal CNAs in all but one patient (OSCE2). In the 7 patients with subclonal CNAs, 6 had two copy number clones identified, and 1 patient (OSCE10) had three copy number clones identified. In 5 patients (OSCE1, OSCE4, OSCE5, OSCE6, OSCE10) there is a copy number clone that is subclonal in the primary tumor which emerges and dominates at subsequent relapses. The resistant clone in each of these cases had either MYC gain/amplification. Amplifications in CCNE1 (OSCE1), RAD21 (OSCE4, OSCE5, OSCE10), VEGFA (OSCE1, OSCE9), IGF1R (OSCE6) were also identified as potential drivers in the resistant copy number clones. In two of these patients (OSCE1, OSCE6), this treatment-resistant subclone becomes the dominant copy number clone by the time of primary resection. SNV based phylogenies revealed a heterogenous mix of monoclonal and polyclonal seeding of metastases and monophyletic and polyphyletic modes of dissemination. Over half the new mutations acquired in recurrent disease were attributed to HRD or cisplatin mutational signatures. TP53 structural variants were seen in 6/8 patients (OSCE2, OSCE3, OSCE4, OSCE6, OSCE9, OSCE10). New structural variants involving driver genes were only detected in one relapse sample from patient OSCE10 (DMD deletion). Conclusion: Subclonal copy number clones emerge and dominate in relapsed osteosarcoma, with MYC gain/amplification a defining characteristic in our cohort. Selective pressure from neoadjuvant chemotherapy reveals this clone at the time of primary resection, highlighting that genomic profiling at this time point may be more reflective of its metastatic potential. Citation Format: Michael D. Kinnaman, Simone Zaccaria, Alvin Makohon-Moore, Gunes Gundem, Juan E. Arango Ossa, Nancy Bouvier, Filemon S. Dela Cruz, Meera Hameed, Julia Lynne Glade Bender, William D. Tap, Paul Meyers, Elli Papaemmanuil, Andrew Kung, Christine A. Iacobuzio-Donahue. Subclonal somatic copy number alterations emerge and dominate in relapsed/refractory osteosarcoma [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B022.
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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 | 0.001 | 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".