Abstract Introduction: Analysis of cell-free DNA (cfDNA) provides a rapid, repeatable, and non-invasive window into tumor biology, yet tissue biopsies are still often needed for accurate phenotyping and treatment guidance. A liquid biopsy approach that captures both genomic alterations and expression-like features could strengthen patient monitoring and lessen biopsy reliance. Here, we integrate a custom hybrid-capture panel targeting gene regulatory regions with a comprehensive genomic profiling (CGP) panel into a single cfDNA sequencing assay. Our bioinformatic pipeline calculates variant allele frequencies (VAF) and extracts fragmentomic features that reproducibly correlate with gene expression, enabling non-invasive tumor phenotyping.Top of FormBottom of Form Experimental Procedures: Matched FFPE tumor and plasma samples from 31 breast cancer patients were collected and analyzed, along with 11 additional unmatched plasma samples; all patients provided consent. Plasma cfDNA underwent sequencing in a single assay that integrated custom hybrid-capture baits for regulatory regions of 2,704 genes (2.44 Mb) with a CGP panel covering 562 genes (2.4 Mb). Matched FFPE RNA was profiled by RNA sequencing. cfDNA reads were processed through a multi-omic pipeline for quantifying fragmentomic properties across predefined regions assigned to nearby genes and a gene alteration analysis for VAF. Fragmentomic signals were correlated with RNA expression for the same genes. Association of fragmentomic signal, gene expression, and associated tumor biology was assessed. Results: Fragmentomic features with high Pearson correlation to matched tissue RNA-seq were observed and were used to train a breast cancer model comprised of 34 features. Model-selected features showed a more distinctly matched correlation structure to breast tumor tissue RNA-seq than did randomly sampled features. Mapping model-selected genes to 31 breast tumor gene expression ontologies showed an enrichment for genes, such as EZH1, previously associated with breast cancer. Additional associations with ER status, Ki67%, and HER2 status demonstrated the potential utility of this assay for measuring these markers in blood. Summary and Conclusions: Our findings show that cfDNA fragmentomic patterns captured using both CGP and custom panels, together with AI modeling, can recapitulate gene-level expression traits and enable tissue-free, plasma-based inference of tumor molecular phenotypes. By integrating fragmentomic signals with standard DNA-alteration profiling, hybrid-capture cfDNA sequencing provides two complementary molecular data layers from the same assay. Combining these capabilities can enhance biomarker discovery and may ultimately support clinical decision-making in precision oncology. Citation Format: Gregory M. Mayhew, Jonathan H. Shepherd, Yoichiro Shibata, Jeff Burdine, Gabriel V. Milburn, Kirk L. Pappan, Nripesh Prasad, Michael V. Milburn, James M. Davison, Kirk Beebe. Combining gene expression and mutation profiling in a single cfDNA assay through the addition of a custom hybrid capture panel targeting gene regulatory regions to a commercial CGP panel abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5314.
Mayhew et al. (Fri,) studied this question.