Detecting small cell transformation in patients with advanced EGFR mutant lung adenocarcinoma through epigenomic cfDNA profiling.

PURPOSE: Histologic transformation to small cell lung cancer (SCLC) is a mechanism of treatment resistance in patients with advanced oncogene-driven lung adenocarcinoma (LUAD) that currently requires histologic review for diagnosis. Herein, we sought to develop an epigenomic cell-free (cf)DNA-based approach to non-invasively detect small cell transformation in patients with EGFR mutant (EGFRm) LUAD. EXPERIMENTAL DESIGN: To characterize the epigenomic landscape of transformed (t)SCLC relative to LUAD and de novo SCLC, we performed chromatin immunoprecipitation sequencing (ChIP-seq) to profile the histone modifications H3K27ac, H3K4me3, and H3K27me3, methylated DNA immunoprecipitation sequencing (MeDIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), and RNA sequencing on 26 lung cancer patient-derived xenograft (PDX) tumors. We then generated and analyzed H3K27ac ChIP-seq, MeDIP-seq, and whole genome sequencing cfDNA data from 1 ml aliquots of plasma from patients with EGFRm LUAD with or without tSCLC. RESULTS: Analysis of 126 epigenomic libraries from the lung cancer PDXs revealed widespread epigenomic reprogramming between LUAD and tSCLC, with a large number of differential H3K27ac (n=24,424), DNA methylation (n=3,298), and chromatin accessibility (n=16,352) sites between the two histologies. Tumor-informed analysis of each of these three epigenomic features in cfDNA resulted in accurate non-invasive discrimination between patients with EGFRm LUAD versus tSCLC (AUROC=0.82-0.87). A multi-analyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LUAD versus tSCLC with an AUROC of 0.94. CONCLUSIONS: These data demonstrate the feasibility of detecting small cell transformation in patients with EGFRm LUAD through epigenomic cfDNA profiling of 1 ml of patient plasma.

Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma.

Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and FOSL1 expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy.

Liquid biopsy epigenomic profiling for cancer subtyping.

Although circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1 ml of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling has the potential to unlock clinically actionable information that is currently accessible only via direct tissue sampling.