biostudies-literatureUnknown9(5)Ho GYF<h4>Background</h4>Most studies associating circulating tumor DNA (ctDNA) with outcome in lung cancer treatment were either cross-sectional or, if longitudinal, only analyzed a limited number of genes. This study evaluated the potential of utilizing ctDNA profiled by a panel of common cancer genes to monitor tumor burden and to reveal molecular characteristics of tumor along treatment course.<h4>Methods</h4>Twenty Chinese non-small cell lung cancer (NSCLC) patients with serial plasma samples collected (I) before starting on either first- or second-line treatment, (II) at stable disease on treatment, and (III) upon disease progression, were analyzed for mutations in ctDNA using the PGDx 64-gene panel. Paired statistics compared mutation profiles between any two of the three time points.<h4>Translational lung cancer research1873-1884https://www.ebi.ac.uk/biostudies/studies/S-EPMC7653134biostudies-literatureLongitudinal multi-gene panel assessment of circulating tumor DNA revealed tumor burden and molecular characteristics along treatment course of non-small cell lung cancer.PMC7653134Guzman MHo GYFIp MSMWang TKwok HHLam DCLRasul RPeila RfalseLongitudinal multi-gene panel assessment of circulating tumor DNA revealed tumor burden and molecular characteristics along treatment course of non-small cell lung cancer.<h4>Background</h4>Most studies associating circulating tumor DNA (ctDNA) with outcome in lung cancer treatment were either cross-sectional or, if longitudinal, only analyzed a limited number of genes. This study evaluated the potential of utilizing ctDNA profiled by a panel of common cancer genes to monitor tumor burden and to reveal molecular characteristics of tumor along treatment course.<h4>Methods</h4>Twenty Chinese non-small cell lung cancer (NSCLC) patients with serial plasma samples collected (I) before starting on either first- or second-line treatment, (II) at stable disease on treatment, and (III) upon disease progression, were analyzed for mutations in ctDNA using the PGDx 64-gene panel. Paired statistics compared mutation profiles between any two of the three time points.<h4>2020-01-01T00:00:00Z2020 Oct2025-04-19T23:40:17.099Z2025-04-19T23:40:17.099ZS-EPMC76531343320960910.21037/tlcr-20-675