Genomic screening of cancer patients for predisposing variants is traditionally based on age at onset, family history and type of cancer. Whereas the clinical guidelines have proven efficient in identifying families exhibiting classical attributes of hereditary cancer, the frequency of patients with alternative presentations is unclear. We identified and characterized germline variants in 636 patients with advanced solid cancer using whole exome sequencing.
View Article and Find Full Text PDFBackground: Selecting patients for early clinical trials is a challenging process and clinicians lack sufficient tools to predict overall survival (OS). Circulating cell-free DNA (cfDNA) has recently been shown to be a promising prognostic biomarker. The aim of this study was to investigate whether baseline cfDNA measurement could improve the prognostic information of the Royal Marsden Hospital (RMH) score.
View Article and Find Full Text PDFPurpose: We evaluated the clinical benefit of tumor molecular profiling to select treatment in the phase I setting.
Experimental Design: Patients with advanced solid cancers and exhausted treatment options referred to a phase I unit were included in a prospective, single-center, single-arm open-label study (NCT02290522). Tumor biopsies were obtained for comprehensive genomic analysis including whole-exome sequencing and RNA sequencing.
Purpose: We evaluated longitudinal tracking of BRAF V600E in circulating cell-free DNA (cfDNA) as a marker of treatment response to BRAF inhibitor (BRAFi) combination therapies in non-melanoma solid tumors included in the Copenhagen Prospective Personalized Oncology (CoPPO) program.
Experimental Design: Patients with BRAF V600E-mutated tumors were treated with combination therapies including BRAFi. Quantification of mutant cfDNA from plasma was determined and correlated to clinical outcomes.
Improvements in cancer genomics and tumor biology have reinforced the evidence of cancer development driven by numerous genomic alterations. Advanced genomics technology can be used to characterize genomic alterations that potentially drive tumor growth. With the possibility of screening thousands of genes simultaneously, personalized molecular medicine has become an option.
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