Abstract 5058: Genomic alterations predictive of outcome in early staged cervical cancer: <i>A translational investigation from the SENTICOL III trial</i>
Bibliographic record
Abstract
Abstract Background: The risk of relapse in patients with early-stage cervical cancer (ESCC) ranges from 4-14% (LACC study). Risk-factors for recurrence are mainly derived from histopathological factors. Senticol III is a large multicenter international randomized prospective study aims to validate sentinel lymph node biopsy in the surgical management of ESCC. Our objective is to characterize prognostic and actionable biomarkers in ESCC. Methods: FFPE-fixed tumoral slides of the first 150 randomized patients were analyzed based on SEDLIS criteria. We characterized TIL’s infiltration, PD-L1 expression and HPV status. Sequencing of tumor DNA was carried out using an in-house targeted next-generation sequencing panel (571 genes). Relapse-free survival (RFS) was defined as the time between randomization and relapse of any type. We performed Fisher’s exact test and Student’s t-test to compare distributions of categorical variables and Log Rank test. Results: The sequencing quality control criteria were met for 135 samples. PIK3CA was the most commonly altered gene (17%). Loss-of-function variants in KMT2-family genes (KTM2C 9%, KMT2D 6%, KMT2A 1%) were found in 16% of samples. The loss-of-function variant of ARID1A was mostly non-sense mutation (6%). Activations of ERBB2 (5%) were 3 focal amplifications and 4 hotspot missense mutations. Two samples were found to have microsatellite instability due to an alteration of MLH1. The Pik3/AKT/mTOR (26%) and the chromatin remodeling (23%) pathways were the most altered pathways. The median follow-up period was 20 months. There were 6 relapses, of which 80% were considered as low risk based on SEDLIS criteria. Recurrences were local and occurred 9-23 months following surgery. Multiparity was the only clinical feature associated with RFS (p < 0,001). Tumor size, histological subtypes, PD-L1 status, number of TIL’s, presence or absence of lymphovascular emboli and deep stromal invasion were not associated with RFS in our cohort.KMT2C (p=0,018) and ARID1A (p < 0,001) pathogen variants were significantly associated with RFS. The pathway chromatin remodeling (p=0,063) showed a trend toward association with RFS. We found 32% of genomic alterations actionable for a target therapy including mutations of PIK3CA, ERBB2, ARID1A, PTEN, BRCA2, KRAS, BRAF, CDK12, FGFR2, NF1, AKT1, BRCA1, TP53 and MSI-high. Conclusion: Our prospective, randomized and multicentric study suggests a genomic profile from a homogeneous cohort of 150 patients. We identified genes involved in chromatin remodeling (ARID1A and KMT2C) as prognostic biomarkers of clinical interest and suggesting the relevance of epidrugs in ESCC. Theranostic annotations of variants identify a matched to target therapy for 32% of alterations. Those targets represent multiple tracks for personalized therapy in ESCC. Citation Format: Maryame El Gani, Sabrina Ibadioune, Zakhia El Beaino, Abderraouf Hamza, Sophie Vacher, Emmanuelle Jeannot, Julien Masliah-Planchon, Anne Salomon, Alexandre Degnieau, Anne-Sophie Bats, Martin Koskas, Virginie Fourchotte, Estelle Wafo, Nicolas Bourdel, Raffaele Fauvet, Marie Plante, Patrice Mathevet, Maud Kamal, Fabrice Lecuru, Ivan Bièche. Genomic alterations predictive of outcome in early staged cervical cancer: A translational investigation from the SENTICOL III trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5058.
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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 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".