Abstract B70: Clonal evolution of chemotherapy-resistant rhabdomyosarcoma via multifocal genomic analysis of pretreatment and treatment-resistant autopsy specimens
Bibliographic record
Abstract
Abstract Objective: Outcomes for patients with rhabdomyosarcoma (RMS) who have relapsed or refractory disease remain poor. Multiple large-scale tumor genomic profiling efforts have been undertaken; however, little is known about its spatial intratumoral heterogeneity (ITH) and temporal clonal evolutionary processes. Methods: To address this issue, we performed 80x whole-genome sequencing of 23 metastases and 2 pretreatment samples from two patients with lethal rhabdomyosarcoma. Multiregion and spatially separated metastases were available through our research autopsy donation program. RA 17-1 had fusion-positive alveolar RMS, while RA 17-10 had Li-Fraumeni syndrome and anaplastic embryonal RMS. Results: We observed on average 65 and 98 coding single-nucleotide variants (SNV) per sample in RA 17-1 and RA 17-10, respectively. RA 17-1 was found to have the canonical PAX03-FOX01 fusion along with MYC-N amplification, which was truncal to all samples. A somatic TP53 mutation in combination with TP53 loss of heterozygosity (LOH) was present in all metastases sequenced at autopsy. A TP53 mutation was not identified in the pretreatment biopsy sample selected for sequencing; however, TP53 immunohistochemistry demonstrated the presence of a TP53 mutation in at least 2 out of 6 pretreatment biopsy cores. In RA 17-10 each sample exhibited numerous copy number alterations and complex structural variants, including LOH of TP53, a TSC2 mutation with LOH, and MYC amplification, which were truncal to all samples. PTCH1 amplification was private to all relapse specimens in RA 17-10. RA 17-10 had more structural and copy number variations per sample than RA 17-1. Phylogenies were derived based on SNVs and demonstrated a branched evolutionary pattern for each patient. When comparing related samples’ mutational signatures, several dynamics were apparent, including the predominance of signatures 3 and 8 (DNA double-strand break repair pathways) in metastatic samples, consistent with the fact that both patients harbored TP53 mutations. Conclusion: Defining important elements of ITH within metastases remains a goal for genomic study in pediatrics, especially in patients with germline predisposition syndromes. Our findings demonstrate the dynamic nature of genomic instability processes, highlighting the importance of longitudinal sampling at the time of recurrence to define treatment effect and the changing mutational landscape in these tumors. The case of RA 17-1 demonstrates the limitations of targeted sequencing on a single sample at diagnosis, as the subclonal TP53 mutation was not originally identified on the clinical assay. TP53 mutations in fusion-positive RMS have rarely been described and likely contributed to this patient’s refractory disease course. Both RA 17-1 and RA 17-10 had more structural variants per sample then what has previously been reported for fusion-positive and fusion-negative RMS, respectively, likely highlighting the contribution of the TP53 mutation to genomic instability in each patient. Citation Format: Michael D. Kinnaman, Alvin Makohon-Moore, Nancy Bouvier, Dominik Glodzik, Max Levine, Ellie Papaemmanuil, Filemon Dela Cruz, Leonard Wexler, Andrew Kung, Christine Iacobuzio-Donahue. Clonal evolution of chemotherapy-resistant rhabdomyosarcoma via multifocal genomic analysis of pretreatment and treatment-resistant autopsy specimens [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B70.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".