Evaluating the Prognostic Value of a Pan-Cancer Circulating Tumor DNA Next-Generation Sequencing Panel in Advanced Cancer Patients
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Bibliographic record
Abstract
Purpose: This study aimed to evaluate the clinical utility of a pan-cancer circulating tumor DNA (ctDNA) next-generation sequencing (NGS) panel for predicting treatment response and progression-free survival (PFS) in patients with advanced solid tumors. Patients and Methods: A total of 41 patients with advanced solid tumors, including gastric cancer (n=13), non-small cell lung cancer (n=10), head and neck cancer (n=9), esophageal cancer (n=7), breast cancer (n=1), and colon cancer (n=1), were prospectively enrolled and included in the analysis. ctDNA was analyzed at three time points: pretreatment (41 patients), post-treatment evaluation (37 patients), and follow-up (18 patients). Results: Among 41 patients analyzed at pretreatment, 35 (85.4%) exhibited tier 1 or 2 somatic variants in ctDNA, with TP53 being the most frequently mutated gene. At the post-treatment evaluation, ctDNA was assessed in 37 patients (3 with rapid deterioration and 1 lost to follow-up were not evaluable). Newly emerging variants after treatment were strongly associated with poor clinical outcomes. Consistent with the Kaplan–Meier analysis, Cox proportional hazards regression confirmed that post-treatment ctDNA positivity was significantly associated with inferior PFS (HR 10.5, 95% CI 1.4– 80.0, P=0.024). At follow-up, 18 patients were evaluable, while the others were not due to follow-up loss, rapid deterioration, or study termination. ctDNA positivity at post-treatment evaluation was significantly associated with shorter PFS (median PFS, 5.0 months [95% CI: 2.0– 12.0] vs not reached; HR, 4.87; 95% CI: 1.69– 14.09; P = 0.0035). Conclusion: Longitudinal monitoring of ctDNA using a pan-cancer NGS panel provides meaningful prognostic information in patients with advanced cancers. Post-treatment ctDNA dynamics may better reflect disease progression than baseline ctDNA status alone, highlighting the need for further validation in larger cohorts, particularly in gastric, lung, head and neck, and esophageal cancers. Plain Language Summary: Cancer cells can release small fragments of their DNA into the bloodstream, known as circulating tumor DNA (ctDNA). These fragments can be detected through a blood test, often called a “liquid biopsy.” By monitoring changes in ctDNA over time, doctors can better understand how a patient’s cancer is responding to treatment. In this study, we analyzed blood samples from 41 patients with advanced cancers, including stomach, lung, and esophageal cancers. Using a genetic test called next-generation sequencing (NGS), we examined cancer-related DNA changes at three time points: before treatment, after the first round of treatment, and during follow-up care. We then assessed how these changes related to the time patients lived without their cancer worsening, a measure known as progression-free survival (PFS). We found that over 85% of patients had significant cancer-related DNA changes before starting treatment. After treatment, many patients developed new mutations, which were associated with shorter PFS. In contrast, patients without new ctDNA changes after treatment generally had better outcomes. These results suggest that ctDNA monitoring after treatment may provide better information about a patient’s status than testing before treatment alone. Ongoing blood-based monitoring could help guide future treatment decisions. However, larger studies are needed to validate these findings. Keywords: circulating tumor DNA, next-generation sequencing, liquid biopsy, prognostic biomarker, longitudinal monitoring
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it