Molecular diagnosis & therapy · 2026
Development of a Nomogram to Predict Therapeutic Resistance in Metastatic Melanoma Using Longitudinal ctDNA Kinetics.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Miller Hunter A, Fischer Annalara G, Egger Michael E, Yaddanapudi Kavitha, Kong Maiying, Hall Melissa B, Linder Mark W
Аннотация
BACKGROUND AND OBJECTIVE: Early detection of treatment resistance and progression in metastatic melanoma may improve outcomes, but current surveillance relies on intermittent radiographic imaging that may lag behind dynamic tumor biology. Circulating tumor DNA (ctDNA), a minimally invasive and increasingly validated biomarker, enables real-time disease monitoring. Longitudinal (kinetic) changes in ctDNA over time have been proposed to provide greater insight into disease activity than isolated measurements; however, few studies have evaluated the prognostic significance of longitudinal ctDNA kinetics across extended timepoints. We aimed to assess the relationship between ctDNA concentration, ctDNA longitudinal kinetics, and future radiographic progression in patients receiving systemic therapy.
METHODS: We quantified BRAF V600E/V600K, or NRAS Q61 ctDNA using droplet digital polymerase chain reaction from longitudinal plasma samples from patients with metastatic cutaneous melanoma. A multivariate Cox proportional hazards model using a time-to-event framework was fit, treating each patient as contributing multiple 100-day landmark intervals. Predictors of future progression included percent variant allele frequency at each follow-up assessment and Δ% variant allele frequency/month (velocity).
RESULTS: The model incorporating both single timepoint measures and kinetic ctDNA features achieved strong internal discrimination between progression versus non-progression events within 100 days (100-day time-dependent area under the curve = 0.88) and was used to build a nomogram. Compared with nomogram derived high-risk visits, low-risk visits showed significantly improved progression-free survival (p = 0.00021).
CONCLUSIONS: Using a longitudinal time-to-event modeling framework, this proof-of-concept study demonstrates the feasibility of kinetic ctDNA-based risk estimation throughout systemic treatment. Both single-point ctDNA measures and their kinetics may serve as indicators of future disease progression.
METHODS: We quantified BRAF V600E/V600K, or NRAS Q61 ctDNA using droplet digital polymerase chain reaction from longitudinal plasma samples from patients with metastatic cutaneous melanoma. A multivariate Cox proportional hazards model using a time-to-event framework was fit, treating each patient as contributing multiple 100-day landmark intervals. Predictors of future progression included percent variant allele frequency at each follow-up assessment and Δ% variant allele frequency/month (velocity).
RESULTS: The model incorporating both single timepoint measures and kinetic ctDNA features achieved strong internal discrimination between progression versus non-progression events within 100 days (100-day time-dependent area under the curve = 0.88) and was used to build a nomogram. Compared with nomogram derived high-risk visits, low-risk visits showed significantly improved progression-free survival (p = 0.00021).
CONCLUSIONS: Using a longitudinal time-to-event modeling framework, this proof-of-concept study demonstrates the feasibility of kinetic ctDNA-based risk estimation throughout systemic treatment. Both single-point ctDNA measures and their kinetics may serve as indicators of future disease progression.