Allele-informed copy number evaluation of plasma DNA samples from metastatic prostate cancer patients: the PCF_SELECT consortium assay.

Sequencing of cell-free DNA (cfDNA) in cancer patients' plasma offers a minimally-invasive solution to detect tumor cell genomic alterations to aid real-time clinical decision-making. The reliability of copy number detection decreases at lower cfDNA tumor fractions, limiting utility at earlier stages of the disease. To test a novel strategy for detection of allelic imbalance, we developed a prostate cancer bespoke assay, PCF_SELECT, that includes an innovative sequencing panel covering ∼25 000 high minor allele frequency SNPs and tailored analytical solutions to enable allele-informed evaluation. First, we assessed it on plasma samples from 50 advanced prostate cancer patients. We then confirmed improved detection of genomic alterations in samples with <10% tumor fractions when compared against an independent assay. Finally, we applied PCF_SELECT to serial plasma samples intensively collected from three patients previously characterized as harboring alterations involving DNA repair genes and consequently offered PARP inhibition. We identified more extensive pan-genome allelic imbalance than previously recognized in prostate cancer. We confirmed high sensitivity detection of BRCA2 allelic imbalance with decreasing tumor fractions resultant from treatment and identified complex ATM genomic states that may be incongruent with protein losses. Overall, we present a framework for sensitive detection of allele-specific copy number changes in cfDNA

Allele-informed copy number evaluation of plasma DNA samples from metastatic prostate cancer patients: the PCF_SELECT consortium assay

Sequencing of cell-free DNA (cfDNA) in cancer patients' plasma offers a minimally-invasive solution to detect tumor cell genomic alterations to aid real-time clinical decision-making. The reliability of copy number detection decreases at lower cfDNA tumor fractions, limiting utility at earlier stages of the disease. To test a novel strategy for detection of allelic imbalance, we developed a prostate cancer bespoke assay, PCF_SELECT, that includes an innovative sequencing panel covering ∼25 000 high minor allele frequency SNPs and tailored analytical solutions to enable allele-informed evaluation. First, we assessed it on plasma samples from 50 advanced prostate cancer patients. We then confirmed improved detection of genomic alterations in samples with <10% tumor fractions when compared against an independent assay. Finally, we applied PCF_SELECT to serial plasma samples intensively collected from three patients previously characterized as harboring alterations involving DNA repair genes and consequently offered PARP inhibition. We identified more extensive pan-genome allelic imbalance than previously recognized in prostate cancer. We confirmed high sensitivity detection of BRCA2 allelic imbalance with decreasing tumor fractions resultant from treatment and identified complex ATM genomic states that may be incongruent with protein losses. Overall, we present a framework for sensitive detection of allele-specific copy number changes in cfDNA

Integrating extracellular vesicle and circulating cell‐free DNA analysis using a single plasma aliquot improves the detection of HER2 positivity in breast cancer patients

Abstract Multi‐analyte liquid biopsies represent an emerging opportunity for non‐invasive cancer assessment. We developed ONCE (One Aliquot for Circulating Elements), an approach for the isolation of extracellular vesicles (EV) and cell‐free DNA (cfDNA) from a single aliquot of blood. We assessed ONCE performance to classify HER2‐positive early‐stage breast cancer (BrCa) patients by combining EV‐associated RNA (EV‐RNA) and cfDNA signals on n = 64 healthy donors (HD) and non–metastatic BrCa patients. Specifically, we isolated EV‐enriched samples by a charge‐based (CB) method and investigated EV‐RNA and cfDNA by next‐generation sequencing (NGS) and by digital droplet PCR (ddPCR). Sequencing of cfDNA and EV‐RNA from HER2‐ and HER2+ patients demonstrated concordance with in situ molecular analyses of matched tissues. Combined analysis of the two circulating analytes by ddPCR showed increased sensitivity in ERBB2/HER2 detection compared to single nucleic acid components. Multi‐analyte liquid biopsy prediction performance was comparable to tissue‐based sequencing results from TCGA. Also, imaging flow cytometry analysis revealed HER2 protein on the surface of EV isolated from the HER2+ BrCa plasma, thus corroborating the potential relevance of studying EV as companion analyte to cfDNA. This data confirms the relevance of combining cfDNA and EV‐RNA for HER2 cancer assessment and supports ONCE as a valuable tool for multi‐analytes liquid biopsies’ clinical implementation

Supplementary Figures S1-S7 from Noninvasive Detection of Neuroendocrine Prostate Cancer through Targeted Cell-free DNA Methylation

Supp. Fig. 1 Differential methylation across prostate cancer disease states Supp. Fig. 2 NEMO panel design Supp. Fig. 3 Tumor content estimation with a minimal set of informative regions Supp. Fig. 4 Scoring CRPC-NE in circulation with the phenotype evidence (PE) score Supp. Fig. 5 Probing the CRPC spectrum with NEMO Supp. Fig. 6 Clinical utility of the NEMO assay Supp. Fig. 7 Copy number estimation using the NEMO assay</p

Supplementary Tables S1-S10 from Noninvasive Detection of Neuroendocrine Prostate Cancer through Targeted Cell-free DNA Methylation

S1: Motif enrichment results around differentially methylated sites in CRPC-NE vs CRPC-Adeno solid tissue biopsy eRRBS data (Beltran2016) S2A: PSA and treatment timepoints for the PRIME cohort S2BPSA and treatment timepoints for the Wu2020 cohort S3Sequencings statistics for samples profiled with the NEMO panel (Notice that sequencing run and Dataset might differ) S4: NEMO tumor content (TC) and PE score estimation of all study samples (NEMO generated and reprocessed data) S5: Association between gene expression and proximal DNA methylation for the PDX EPIC cohort (pdx) and WCDT cohort (biopsies) S6A: Alisertib cohort survival data S6B: Chemo trial cohort survival data S7: Inclusion criteria for the two phase 2 trial cohorts S8:References of masked samples and samples sequenced in this work S9: Description of informative regions included in the NEMO panel S10: Mean CpG coverage in NEMO regions for reprocessed data (only CpG sites with at least 10x coverage are retained)</p