Abstract: Genomic analyses in oncologic care allow for the development of more precise clinical laboratory tests that will be critical for personalized pharmacotherapy. Traditional biopsy-based approaches are limited by the availability of sequential tissue specimens to detect resistance. Blood-based genomic profiling (“liquid biopsy”) is useful for longitudinal monitoring of tumor genomes and can complement biopsies. Tumor-associated mutations can be identified in cell-free tumor DNA (ctDNA) from patient blood samples and used for monitoring disease activity. The US Food and Drug Administration approved a liquid biopsy test for EGFR-activating mutations in patients with non–small-cell lung cancer as a companion diagnostic for therapy selection. ctDNA also allows for the identification of mutations selected by treatment such as EGFR T790M in non–small-cell lung cancer. ctDNA can also detect mutations such as KRAS G12V in colorectal cancer and BRAF V600E/V600K in melanoma. Chromosomal aberration pattern analysis by low-coverage whole genome sequencing is a new, broader approach. Genomic imbalances detected in cell-free DNA (cfDNA) can be used to compute a copy number instability (CNI) score. In clinical studies, it was demonstrated that the change in CNI score can serve as an early predictor of therapeutic response to chemotherapy/immunotherapy of many cancer types. In multivariable models, it could be shown that the CNI score was superior to clinical parameters for prediction of overall survival in patients with head and neck cancer. There is emerging evidence for the clinical validity of ctDNA testing regarding identification of candidates for targeted therapies, prediction of therapeutic response, early detection of recurrence, resistance mutation detection, measuring genetic heterogeneity, tumor burden monitoring, and risk stratification. Improvement of sensitivity to detect tumors at very early stages is difficult due to insufficient mutant DNA fraction of ≤0.01%. Further developments will include validation in prospective multicenter interventional outcome studies and the development of digital platforms to integrate diagnostic data.