Detecting ctDNA using personalized structural variants to forecast recurrence in localized soft tissue sarcoma (STS).
Bibliographic record
Abstract
11511 Background: The current standard for definitive management of localized STS involves surgery and (neo)adjuvant radiation (RT). Unfortunately, up to 50% of these patients (pts) recur but the role of adjuvant systemic therapy remains controversial. Circulating tumor DNA (ctDNA) is a promising biomarker for molecular residual disease (MRD) in STS but its clinical validity and utility remains unclear. Given that structural variants (SVs) are prevalent in the tumor genome of STS pts, this longitudinal study aims to utilize an ultra-sensitive, tumor-informed MRD assay that tracks somatic SVs for the detection of ctDNA. Methods: Pts with newly diagnosed, localized, high-risk (≥ 5cm, grade ≥2) STS planned for curative-intent (neo)adjuvant RT and surgery were recruited from Feb 2019 to Aug 2023. Blood samples for ctDNA analyses were collected at diagnosis, post RT, post-surgery and every 3 months for up to two years in tandem with radiologic surveillance. The MRD window was defined as the first 8 weeks after surgery. Whole genome sequencing (WGS) was performed on archival tumor samples to detect all genomic SVs. A personalized multiplex digital PCR assay was then designed based on WGS data to track up to 16 somatic SVs in cell-free DNA from serial plasma samples for ctDNA detection and quantification. ctDNA data was then correlated to clinical outcomes (last updated on Jan 2025). Results: A total of 228 plasma samples from 32 pts were analyzed with a median follow-up of 20.1 months. STS subtypes included myxofibrosarcoma (12), undifferentiated pleomorphic sarcoma (10), dedifferentiated liposarcoma (6), pleomorphic liposarcoma (2), myxoid liposarcoma (1) and leiomyosarcoma (1). The ctDNA detection rate at diagnosis was 97% (31/32 pts). Of the cohort, 22 pts received preoperative RT and had blood collected within the MRD window. ctDNA was detectable at baseline and in the MRD window in 4/22 pts (18%). All 4 (100%) developed metastatic disease with a median lead time of 136 days (range: 28-210 days) in ctDNA detection prior to radiologic relapse. Of the 18 pts who were ctDNA-negative in the MRD window, 3 (17%) developed metastatic recurrence, all of which was preceded by detectable ctDNA with a median lead time of 87 days (range: 80-147 days). The median time from surgery to recurrence was 153 days (range: 57-224 days) vs 521 days (range: 406-631 days) for pts with detectable vs undetectable ctDNA within the MRD window, respectively. Conclusions: Detection of ctDNA using personalized tumor-informed assays for somatic SV tracking was feasible and highly sensitive in localized high-risk STS pts prior to surgery. Positive ctDNA within the MRD window was predictive of subsequent and earlier radiologic relapse. Based on this data, an interception trial of adjuvant systemic therapy for MRD-positive STS pts is planned. Future analysis, including the measurement of circulating extrachromosomal DNA (ecDNA) is planned. Clinical trial information: NCT03818412 .
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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 | 0.000 |
| 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) | 0.001 | 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".