Abstract A012: Genomic landscape of somatic alterations identified in endometrial cancer using liquid biopsy
Bibliographic record
Abstract
Abstract Background: With advances in understanding the biology of endometrial cancer, molecular sub-groups have been defined to assess prognosis and guide treatment decisions. This classification is based on surrogate markers in archival paraffin-embedded tissues. The landscape of somatic alterations as detected by liquid biopsy has not been well described in advanced endometrial cancer. Methods: A retrospective analysis was performed using de-identified genomic data collected from patients with advanced endometrial cancer who underwent liquid biopsy testing with a 74-83 gene panel as part of clinical care (Guardant360, Guardant Health, Inc.). Results: 1,988 females with a median age of 68 [range 23-95] years were included in the analysis. 45% of patients were tested at diagnosis of advanced disease; 43% were tested at time of disease progression. 91.6% of patients had ≥1 somatic alteration detected and 12% of patients were MSI-High. The most frequently altered genes included TP53 (65%), PIK3CA (31%), PTEN (27%), ARID1A (24%), like prior reports of genomic alterations detected in tissue samples. CCNE1 amplifications were enriched in 11% of samples with TP53 alterations (p<0.0001; q<0.0001) and EGFR amplifications were enriched in samples without TP53 alterations (p<0.0001; q<0.0001). MSI-H samples were enriched for alterations in ARID1A, PTEN, PIK3CA, ATM, MSH6 and others, while samples without MSI were enriched for alterations in TP53 and CCNE1 (p<0.0001; q<0.0001). Oncogenic fusions were rare in this cohort (0.2%) and included FGFR1 and FGFR3 rearrangements. Activating, druggable alterations were identified in PIK3CA, KRAS, ERBB2, and BRCA1/2. Putative pathogenic germline alterations were detected in 61 (3%) patients and included ATM (18%), BRCA1 (33%), BRCA2 (21%), and lower frequencies of CHEK2, FANCA, MLH1, MSH2, MSH6, and PALB2. Conclusions: While descriptive in nature, this analysis is the largest cohort of advanced endometrial cancer analyzed using a clinically available liquid biopsy assay and demonstrates the feasibility of somatic alteration detection. This report paves the way for using liquid biopsy as a potential tool for guiding targeted chemotherapeutic strategies. Citation Format: Leylah Drusbosky, Ginger Haynes, Brooke Grant, Pamela Sobernis, Stephanie Lheureux. Genomic landscape of somatic alterations identified in endometrial cancer using liquid biopsy [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr A012.
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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 | 0.001 | 0.002 |
| 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) | 0.003 | 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".