Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer
收藏DataCite Commons2025-12-23 更新2026-05-04 收录
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https://data.ru.nl/collections/ru/rumc/libimrdn_t0000662a_dsc_233
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This data was collected in the context of our real-world exploratory multi-center cohort study in two cohorts of patients with advanced non-small cell lung cancer (NSCLC) who were treated with immune checkpoint inhibitors (ICIs) (BTO cohort and DEDICATION-1 cohort). In this study, we first expanded our next-generation sequencing (NGS) data analysis pipeline with an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples in terms of presence or absence of circulating tumor DNA (ctDNA). Second, we explored the potential value of ctDNA-based minimal residual disease (MRD) monitoring with this algorithm for risk stratification and decision-making. Last, we explored whether simultaneous serum tumor marker (STM) monitoring could improve risk stratification and decision-making. Between May 2018 and December 2023, 107 patients were recruited from 15 thoracic oncology outpatient clinics across The Netherlands. In the "Patient characteristics across the three cohorts at baseline" file, clinical and tumor characteristics of all included patients can be found. In the "Patient serum tumor marker data DEDICATION-1 cohort" file, serum tumor marker data of all patients from the DEDICATION-1 cohort can be found. In the "Serological response patterns and survival data" file, serological response patterns and survival data of all patients from the DEDICATION-1 cohort can be foud. The "prepare_sample_data" and "classify_sample_data" files include the first and second part of the algorithm developed within the study. The last part of the algorithm is currently being developed.
提供机构:
Radboud University
创建时间:
2025-11-04



