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Background: Although the efficacy of molecularly target agents in vitro, their use in routine setting is limited mainly to the use of anti‐HER2 and antiEGFR agents in vivo. Moreover, core biopsy of a single cancer site may not be representative of the whole expanding clones and cancer molecular profile at relapse may differ with respect to the primary tumor. Methods: We assessed the status of a large panel of cancer driver genes by cell‐free DNA (cfDNA) analysis in a cohort of 68 patients with 13 different solid tumors at disease progression. Whenever possible, a second cfDNA analysis was performed after a mean of 2.5 months, in order to confirm the identified clone(s) and to check the correlation with clinical evolution. Results: The approach was able to identify clones plausibly involved in the disease progression mechanism in about 65% of cases. A mean of 1.4 mutated genes (range 1‐3) for each tumor was found. Point mutations in TP53, PIK3CA, and KRAS and copy number variations in FGFR3 were the gene alterations more commonly observed, with a rate of 48%, 20%, 16%, and 20%, respectively. Two‐points‐Next‐Generation Sequencing (NGS) analysis demonstrated statistically significant correlation between allele frequency variation and clinical outcome (P =.026). Conclusions: Irrespective of the primary tumor mutational burden, few mutated genes are present at disease progression. Clinical outcome is consistent with variation of allele frequency of specific clones indicating that cfDNA two‐point‐NGS analysis of cancer driver genes could be an efficacy tool for precision oncology. [ABSTRACT FROM AUTHOR]

Objectives A polygenic model is commonly assumed for the predisposition to common cancers. With respect to lung cancer, Genome Wide Association Studies (GWAS) have identified three loci at 15q25, 5p15.33, and 6p21. However, the relative risks associated with alleles at these loci are low; in addition, the data are limited to smokers, and have not been quite reproducible. Materials and methods In order to investigate genetic susceptibility we have adopted an entirely novel patient selection strategy. First, we have selected for adenocarcinoma (ADCA) histology only; second, we have selected non-smokers; third we have selected patients who developed ADCA of lung before the age of 60 and who had an older unaffected sib: we have identified 31 such sib-pairs. Among them, we selected two patients with very early age at disease onset (37- and 49-years old), and having a healthy sibling available for genome comparison older than at least 7 years. Results On germline DNA samples of four subjects of two such pairs we have carried out whole exome sequencing. Truncating mutations were detected in 8 'cancer genes' in one affected, and in 5 cancer genes in the other affected subject: but none in the two healthy sibs (p=0.0026). Some of these mutant genes (such as BAG6, SPEN and WISP3) are recognized as major cancer players in lung tumors; others have been previously identified in other human cancers (JAK2, TCEB3C, NELFE, TAF1B, EBLN2), in mouse models (GON4L, NOP58, and RBMX) or in genome-wide association studies (KIAA2018, ZNF311). Conclusions This study identifies for the first time in non-smokers with lung adenocarcinoma specific sets of germline mutations that, together, may predispose to this tumor. [ABSTRACT FROM AUTHOR]