Abstract 550: Cell-free DNA alterations in the AR/enhancer locus measured before AR signaling inhibition portend poor overall survival in metastatic castration resistant prostate cancer patients

Background: We previously developed a liquid biopsy assay called Enhancer and neighboring loci of Androgen Receptor Sequencing (EnhanceAR-Seq) (Dang & Chauhan et al, JCO PO, 2020). We applied it to a heterogeneous cohort of metastatic prostate cancer patients after the start of AR-directed therapy, and showed that alterations in the AR locus were associated with worse survival. Here we asked if AR/enhancer genomic alterations detected in plasma cell-free DNA prior to the administration of first-line AR-selective inhibitors (ARSIs) can predict survival in metastatic castration resistant prostate cancer (mCRPC) patients.

Methods: We applied EnhanceAR-Seq to plasma cell-free DNA isolated from 20 mCRPC patients from Tulane University collected between April 2015 and June 2017. Assay results were correlated with patient overall survival (OS) and progression-free survival (PFS) from the time of blood collection.

Results: Median follow up time was 32 months. Seventeen patients had blood plasma analyzed before first-line ARSI treatment, while three patients had received prior ARSI treatment before blood collection. EnhanceAR-Seq revealed that the most frequent genomic events detected were AR/enhancer alterations (copy number gain, tandem duplication or missense mutations) in 9 patients (45%), of which 5 patients had both AR gene body and enhancer copy number gain. The other 4 patients each had a single genomic event detected by EnhanceAR-Seq: AR amplification, AR enhancer amplification, AR and AR enhancer tandem duplication, and AR W742C single nucleotide variation. Cell-free DNA-detected alterations in the full AR locus including the AR enhancer were highly significant for inferior OS (P = 0.0009; HR = 17.0) but not for PFS (P = 0.2; HR = 2.2) by Kaplan-Meier analysis across all 20 patients. Subset analysis of the 17 patients with plasma analyzed prior to first-line ARSI treatment revealed that AR/enhancer alterations again predicted significantly worse OS with a median survival of 16.1 months vs. not-reached (P = 0.0009; HR = 14.1).

Conclusions: AR locus alterations detected by EnhanceAR-seq in plasma cell-free DNA collected prior to ARSI administration correlated with significantly worse overall survival in patients with mCRPC. If corroborated, our results suggest that AR/enhancer genomic alterations represent a potent pre-treatment prognostic biomarker in mCRPC patients.

Citation Format: Pradeep Singh Chauhan, Steven H. Hartman, Ha X. Dang, Jace Webster, Haley Ellis, Wenjia Feng, Peter K. Harris, Elisa M. Ledet, Ellen B. Jaeger, Patrick J. Miller, Sydney A. Caputo, Russell K. Pachynski, Oliver Sartor, Christopher A. Maher, Aadel A. Chaudhuri. Cell-free DNA alterations in the AR/enhancer locus measured before AR signaling inhibition portend poor overall survival in metastatic castration resistant prostate cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 550.

Abstract 577: A unified pipeline to detect small mutations, structural variations and copy number alterations from targeted cell-free DNA sequencing in cancer

Introduction: Analysis of cell-free DNA (cfDNA) has recently emerged as a non-invasive modality for guiding cancer diagnostics and treatment decisions. However, efforts have predominantly focused on the analysis of single nucleotide variants (SNVs) and insertions/deletions (indels). Despite the clinical significance of many larger variants such as structural variations (SVs) and copy number alterations (CNAs), detecting them in cfDNA remains a challenge. Given the lack of existing tools we seek to develop an integrated bioinformatic pipeline for SV and CNA detection in cfDNA following targeted hybrid-capture next-generation sequencing (NGS), along with standard SNV and indel analysis.

Methods: SVs were first detected using Manta, Lumpy and Delly in plasma cfDNA in comparison with matched peripheral blood leukocyte (PBL) DNA samples from cancer patients, then combined to identify consensus SVs and genotyped throughout samples from patients and healthy individuals. Next, consensus SVs were called somatic events if they were supported by split reads and discordant read pairs in cfDNA samples from patients but not in matched PBL or healthy donor cfDNA samples. For CNA analysis, the ratio of read depth between patient-derived plasma cfDNA and a panel of healthy controls was calculated across genomic bins using the CNVkit tool, followed by bias correction and recentralization using CNA negative control genes to account for read coverage imbalances in targeted NGS. Last, SNV and indel analysis was integrated from the CAPP-Seq pipeline.

Results: We applied our pipeline to targeted hybrid-capture NGS data from 48 patients across two independent cohorts of metastatic castration resistant prostate cancer (mCRPC). The targeted panel covered the full-length AR gene body and a hotspot region of TMPRSS2-ERG fusion break points. Consistent with earlier whole genome studies, we confirmed known CNAs and SVs in tumor suppressors, oncogenes and regulatory elements including AR gene and AR enhancer duplications (22/48, 46% of patients), TMPRSS2-ERG gene fusions (9/48, 19%), PTEN and TP53 loss (8/48, 17%). Notably, our pipeline outperformed FACTERA which did not detect any TMPRSS2-ERG gene fusions or AR/enhancer tandem duplications. Subsequent analysis showed high concordance between plasma cfDNA and matched tumor biopsies, and our pipeline recapitulated the landscape of SVs and CNAs in an in silico cfDNA simulation from tumor biopsies. Finally, we showed that alterations of the AR/enhancer locus detected by our pipeline were strongly associated with treatment resistance, patient progression-free and overall survival in mCRPC.

Conclusion: We developed a unified pipeline for detection of SVs, CNAs and small mutations in cfDNA targeted sequencing with potential applications in monitoring cancer progression and predicting patient treatment response.

Citation Format: Ha X. Dang, Jace Webster, Pradeep S. Chauhan, Steven H. Hartman, Wenjia Feng, Elisa M. Ledet, Haley Ellis, Patrick J. Miller, Ellen B. Jaeger, Sydney A. Caputo, Peter K. Harris, A. Oliver Sartor, Russell K. Pachynski, Aadel A. Chaudhuri, Christopher A. Maher. A unified pipeline to detect small mutations, structural variations and copy number alterations from targeted cell-free DNA sequencing in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 577.