Integrating genomic features for non-invasive early lung cancer detection.
2020; 580 (7802): 245-251
Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.
View details for DOI 10.1038/s41586-020-2140-0
View details for PubMedID 32269342
Circulating tumor DNA analysis to assess risk of progression after long-term response to PD-(L)1 blockade in NSCLC.
Clinical cancer research : an official journal of the American Association for Cancer Research
Treatment with PD-(L)1 blockade can produce remarkably durable responses in non-small cell lung cancer (NSCLC) patients. However, a significant fraction of long-term responders ultimately progress and predictors of late progression are unknown. We hypothesized that circulating tumor DNA (ctDNA) analysis of long-term responders to PD-(L)1 blockade may differentiate those who will achieve ongoing benefit from those at risk of eventual progression.In patients with advanced NSCLC achieving long-term benefit from PD-(L)1 blockade (PFS≥12 months), plasma was collected at a surveillance timepoint late during/after treatment to interrogate ctDNA by Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq). Tumor tissue was available for 24 patients and was profiled by whole-exome sequencing (n=18) or by targeted sequencing (n=6).31 NSCLC patients with long-term benefit to PD-(L)1 blockade were identified and ctDNA was analyzed in surveillance blood samples collected at a median of 26.7 months after initiation of therapy. Nine patients also had baseline plasma samples available, and all had detectable ctDNA prior to therapy initiation. At the surveillance timepoint, 27 patients had undetectable ctDNA and 25 (93%) have remained progression-free; by contrast, all four patients with detectable ctDNA eventually progressed (Fisher's p<0.0001; PPV 1 [95% CI 0.51-1]; NPV 0.93 [95% CI 0.80-0.99]).ctDNA analysis can noninvasively identify minimal residual disease in patients with long-term responses to PD-(L)1 and predict the risk of eventual progression. If validated, ctDNA surveillance may facilitate personalization of the duration of immune checkpoint blockade and enable early intervention in patients at high risk for progression.
View details for DOI 10.1158/1078-0432.CCR-19-3418
View details for PubMedID 32046999