Abstract

e23068 Background: Analysis of cell-free circulating tumor DNA (ctDNA) by next-generation sequencing (NGS) is a promising method for detecting and monitoring earlier stage cancers. Liquid biopsies have a large potential to detect cancer earlier upon initial recurrence and to aid in adjuvant decision making through a non-invasive and highly accurate mechanism. Methods: We developed a 30kb ctDNA capture panel based on the landscape of genomic alterations in ctDNA of over 10,000 advanced cancer patients with high theoretical clinical sensitivity for colorectal (96%) and lung (87-93%) cancers. The panel was validated with high analytical PPV (86% at MAFs < 0.025%, 96% at MAFs > 0.025%). We applied the panel to a clinical study of 63 healthy donors and also 40 early stage (II/III) CRC and lung cancer patients with both pre- and post-tumor resection blood draws. Tumor samples were also collected at the time of the surgical resection. Results: Overall, the detection rate of ctDNA in pre-op blood draws was 72% (13/18) in CRC and 67% (12/18) in lung cancer patients. In the post-op blood draws ctDNA was detectable in 11% (2/18) of CRC and 11% (2/18) of lung cancer cases. For lung cancer patients, the median MAF in pre-op was 0.06% (0.01%-8.47%, n = 51) and in post-op was 0.06% (0.02%-4.14%, n = 38). For CRC patients, the median MAF in pre-op was 0.18% (0.01%-9.26%, n = 51) and in post-op was 0.36% (0.04%-9.5%, n = 18). Sixty-three healthy donor plasma samples were screened at similar cfDNA input amounts and nine (14%) had mutations; the majority of the mutations were also detected in matched leukocyte DNA. To assess a clinically relevant biological false positive background rate in lung cancer patients, screening of cancer-free smokers is ongoing. Conclusions: We have developed a highly sensitive and specific universal assay for the detection of ctDNA in early stage CRC and lung cancer patients without the requirement of a priori knowledge of tumor mutations. This technology allows for a promising non-invasive route for molecular monitoring of residual disease post-surgery and for early detection of relapse compared to traditional methodologies.

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