Abstract

Abstract Lung cancer is the leading cause of cancer death, accounting for 1.6 million deaths per year. The prognosis for newly diagnosed cases is overall poor and strongly influenced by clinical stage at time of diagnosis, with dismal survival rates for cases diagnosed at a late stage. However, molecular profiling at diagnosis and advances in precision medicine has vastly improved the clinical management of lung cancer patients. An efficient evaluation of treatment response and early detection of recurrent disease can further improve survival rates. However, response evaluation during treatment is still limited to either radiological evaluation at fixed intervals or the risk-associated trans-thoracic biopsies that cannot be performed frequently. Therefore, there is an imperative need to identify minimally invasive, personalised biomarkers that can longitudinally monitor treatment response as well as early detect and map emerging resistance mechanisms leading to relapse. Employing liquid biopsy platforms to analyse tumor biomarkers in circulating nucleic acids, especially circulating tumor DNA (ctDNA), is a promising approach for longitudinal disease monitoring as it is less invasive and quantitative. Here we present the Umeå Molecular Adaptive Platform (UMAP) aimed for developing personalised tumor biomarkers for disease monitoring of individual lung cancer patients following curative treatment. The UMAP employs matched diagnostic tumor tissue and plasma samples from Swedish lung cancer patients (retrieved from Uppsala-Umeå Comprehensive Cancer Consortium, Sweden) and entails mutational profiling of tumor tissue, specifically identifying disease-associated large structural variants (SVs) and single nucleotide variants (SNVs) by long read sequencing using Oxford Nanopore Technology (ONT) and Illumina TST170 target enrichment sequencing, respectively. Individualized SVs and SNVs biomarker assays are then developed for droplet digital PCR (ddPCR) -based analysis and quantification in ctDNA isolated from corresponding plasma samples. This tailored, patient-specific panel can then be used to longitudinally monitor disease evolution and treatment response during the entire therapy regimen using blood-based sampling. The UMAP workflow has been optimised by mutational profiling of 3 lung cancer cell lines (H1299, H1975 and H2228) and fresh frozen tumor tissues from 12 lung cancer patients using ONT and Illumina TST170 panel followed by development of robust, highly sensitive ddPCR assays for targeting candidate SNVs and SVs with minimal hands-on time and with detection limit as low as 0.001%. Impact of this tailored approach on improving survival can be evaluated by implementing UMAP in a prospective clinical trial with patients with advanced lung cancer disease. Citation Format: Zahra Haider, Linda Köhn, Nicholas Karlowatz, Mikael B. Johansson, Jonas A. Nilsson. UMAP- Personalized lung cancer monitoring platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 530.

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