Molecular residual disease (MRD) detection using bespoke circulating tumor DNA (ctDNA) assays in localized soft tissue sarcoma (STS).
Bibliographic record
Abstract
11509 Background: Surgery and (neo)adjuvant radiotherapy (RT) are the mainstay curative treatments for localized STS. Despite treatment, up to 50% of STS patients experience metastatic relapse, and routine use of adjuvant systemic therapy (AST) remains controversial. The presence of ctDNA following curative-intent treatment of STS is a potential biomarker for MRD and may identify patients who are likely to benefit from AST. Given the genomic heterogeneity of STS, a histology-agnostic approach to ctDNA detection in this population is desirable. Methods: Patients (pts) with localized, high risk (size ≥ 5cm, grade ≥ 2) STS were enrolled prior to (neo)adjuvant RT and surgery. Pts who received (neo)adjuvant systemic treatment were excluded. Blood samples for ctDNA analysis were collected at diagnosis, post-RT, post-surgery and every 3 months for up to 2 years. Whole exome sequencing (WES) of archival tumor and matched normal were carried out to identify patient-specific, somatic, single nucleotide variants. Personalized and tumor-informed, multiplex PCR next generation sequencing-based ctDNA (Signatera) assays were then developed to track ctDNA in serially collected plasma samples. ctDNA levels were expressed as mean tumor molecules per milliliter (MTM/ml) of plasma. Radiologic surveillance was performed every 3 months following surgery. The primary endpoint was a ctDNA detection rate of >70% at diagnosis. Secondary endpoints included MRD detection after local therapy and correlation of ctDNA levels with disease relapse. Results: A total of 140 plasma samples from 22 pts [18 male and 4 female; median age: 65 years, range: 30 – 84] were obtained. RT was preoperative in 19/22 pts. Of the 22 tumor samples, 20 had adequate tissue quality for WES to enable ctDNA assay design. Tumor histologic subtypes included undifferentiated pleomorphic sarcoma (n = 6), myxofibrosarcoma (n = 5), and liposarcoma (n = 9). A median of 7 plasma samples per patient (range: 2 – 10) were analyzed. ctDNA was detected in 80% of pts (16/20) at diagnosis, with median ctDNA level of 3.4 MTM/mL (range: 0.2 – 1393.9). Of these 16 pts, 15 (94%) became ctDNA negative at the immediate post-surgical timepoint. In addition, ctDNA was detected in 4 pts (80%) prior to or around radiologic relapse with a median lead time of 92 days. Conclusions: Personalized, tumor-informed ctDNA assays can detect MRD after definitive local therapy and/or prior to radiologic recurrence in patients with localized high-risk STS. As such, serial ctDNA monitoring provides prognostic value and may further identify patients that will benefit from AST treatment. Additional studies evaluating ctDNA as a predictive biomarker for AST benefit are ongoing.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".