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Updated: Sep 6, 2025
Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
Genomic Landscape of Advanced Solid Tumors in Circulating Tumor DNA and Correlation With Tissue Sequencing: A Single
Lorenzo Gerratana1,2,3,4, Michael Movarek5, Firas Wehbe2
1Division of Hematology and Oncology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
Purpose:
Circulating tumor DNA (ctDNA) has emerged as a promising noninvasive biomarker for baseline characterization and longitudinal monitoring of a tumor throughout disease management. The aim of this study was to evaluate the utility of ctDNA across a wide spectrum of tumor types.
Methods:
We retrospectively identified 1,763 patients with advanced cancers who had next-generation sequencing of ctDNA or tumor tissue completed by a designated commercial assay at Northwestern University.
Results:
ctDNA identified at least one gene alteration in 90% of patients. The number of detected alterations (NDA) and mutant allele frequency (MAF) of the most frequently mutated genes varied significantly across tumor types, with the highest MAF observed in gastric, colorectal, and breast cancers and the highest NDA observed in colorectal, lung squamous, and ovarian/endometrial cancers. TP53 was the most mutated gene in all tumor types. PIK3CA, ERBB2, BRCA1, and FGFR1 alterations were associated with breast cancer, and ESR1 mutations were exclusively detected in this tumor type. Colorectal cancer was characterized by alterations in KRAS and APC mutations, whereas KRAS, EGFR, PIK3CA, and BRAF mutations were common in lung adenocarcinoma. Concordance between blood and tissue sequencing was notably observed for truncal gene alterations (eg, APC and KRAS), whereas low concordance was often observed in genes associated with treatment resistance mechanisms (eg, RB1 and NF1). Tumor mutational burden (TMB) varied significantly across tumor types, and patients with high MAF or NDA had a significantly higher TMB score with one of the investigated platforms.
Conclusion:
The study provided new insights into the ctDNA mutational landscape across solid tumors, suggesting new hypotheses-generating data and caveats for future histotype-agnostic workflows integrated with tissue-based biomarkers such as TMB.
