Search

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. [ABSTRACT FROM AUTHOR]

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.

Abstract Background Extracellular vesicles (EVs) are actively secreted by cells into body fluids and contain nucleic acids of the cells they originate from. The goal of this study was to detect circulating tumor-derived EVs (ctEVs) by mutant mRNA transcripts (EV-RNA) in plasma of patients with solid cancers and compare the occurrence of ctEVs with circulating tumor DNA (ctDNA) in cell-free DNA (cfDNA). Methods For this purpose, blood from 20 patients and 15 healthy blood donors (HBDs) was collected in different preservation tubes (EDTA, BCT, CellSave) and processed into plasma within 24 h from venipuncture. EVs were isolated with the ExoEasy protocol from this plasma and from conditioned medium of 6 cancer cell lines and characterized according to MISEV2018-guidelines. RNA from EVs was isolated with the ExoRNeasy protocol and evaluated for transcript expression levels of 96 genes by RT-qPCR and genotyped by digital PCR. Results Our workflow applied on cell lines revealed a high concordance between cellular mRNA and EV-RNA in expression levels as well as variant allele frequencies for PIK3CA, KRAS and BRAF. Plasma CD9-positive EV and GAPDH EV-RNA levels were significantly different between the preservation tubes. The workflow detected only ctEVs with mutant transcripts in plasma of patients with high amounts (> 20%) of circulating tumor DNA (ctDNA). Expression profiling showed that the EVs from patients resemble healthy donors more than tumor cell lines supporting that most EVs are derived from healthy tissue. Conclusions We provide a workflow for ctEV detection by spin column-based generic isolation of EVs and PCR-based measurement of gene expression and mutant transcripts in EV-RNA derived from cancer patients’ blood plasma. This workflow, however, detected tumor-specific mutations in blood less often in EV-RNA than in cfDNA.

Growing bodies of evidence have demonstrated that the identification of prostate cancer (PCa) biomarkers in the patients' blood and urine may remarkably improve PCa diagnosis and progression monitoring. Among diverse cancer-derived circulating materials, extracellular RNA molecules (exRNAs) represent a compelling component to investigate cancer-related alterations. Once outside the intracellular environment, exRNAs circulate in biofluids either in association with protein complexes or encapsulated inside extracellular vesicles (EVs). Notably, EV-associated RNAs (EV-RNAs) were used for the development of several assays (such as the FDA-approved Progensa Prostate Cancer Antigen 3 (PCA3 test) aiming at improving early PCa detection. EV-RNAs encompass a mixture of species, including small non-coding RNAs (e.g. miRNA and circRNA), lncRNAs and mRNAs. Several methods have been proposed to isolate EVs and relevant RNAs, and to perform RNA-Seq studies to identify potential cancer biomarkers. However, EVs in the circulation of a cancer patient include a multitude of diverse populations that are released by both cancer and normal cells from different tissues, thereby leading to a heterogeneous EV-RNA-associated transcriptional signal. Decrypting the complexity of such a composite signal is nowadays the major challenge faced in the identification of specific tumor-associated RNAs. Multiple deconvolution algorithms have been proposed so far to infer the enrichment of cancer-specific signals from gene expression data. However, novel strategies for EVs sorting and sequencing of RNA associated to single EVs populations will remarkably facilitate the identification of cancer-related molecules. Altogether, the studies summarized here demonstrate the high potential of using EV-RNA biomarkers in PCa and highlight the urgent need of improving technologies and computational approaches to characterize specific EVs populations and their relevant RNA cargo. [ABSTRACT FROM AUTHOR]

Background: Extracellular vesicles (EVs) are actively secreted by cells into body fluids and contain nucleic acids of the cells they originate from. The goal of this study was to detect circulating tumor-derived EVs (ctEVs) by mutant mRNA transcripts (EV-RNA) in plasma of patients with solid cancers and compare the occurrence of ctEVs with circulating tumor DNA (ctDNA) in cell-free DNA (cfDNA).Methods: For this purpose, blood from 20 patients and 15 healthy blood donors (HBDs) was collected in different preservation tubes (EDTA, BCT, CellSave) and processed into plasma within 24 h from venipuncture. EVs were isolated with the ExoEasy protocol from this plasma and from conditioned medium of 6 cancer cell lines and characterized according to MISEV2018-guidelines. RNA from EVs was isolated with the ExoRNeasy protocol and evaluated for transcript expression levels of 96 genes by RT-qPCR and genotyped by digital PCR.Results: Our workflow applied on cell lines revealed a high concordance between cellular mRNA and EV-RNA in expression levels as well as variant allele frequencies for PIK3CA, KRAS and BRAF. Plasma CD9-positive EV and GAPDH EV-RNA levels were significantly different between the preservation tubes. The workflow detected only ctEVs with mutant transcripts in plasma of patients with high amounts (> 20%) of circulating tumor DNA (ctDNA). Expression profiling showed that the EVs from patients resemble healthy donors more than tumor cell lines supporting that most EVs are derived from healthy tissue.Conclusions: We provide a workflow for ctEV detection by spin column-based generic isolation of EVs and PCR-based measurement of gene expression and mutant transcripts in EV-RNA derived from cancer patients' blood plasma. This workflow, however, detected tumor-specific mutations in blood less often in EV-RNA than in cfDNA. [ABSTRACT FROM AUTHOR]

In non-small cell lung cancer (NSCLC), identifying the presence of sensitizing and resistance epidermal growth factor receptor (EGFR) mutations dictates treatment plans. Extracellular vesicles (EVs) are emerging as abundant, stable potential liquid biopsy targets that offer the potential to quantify EGFR mutations in NSCLC patients at the RNA and protein level at multiple points through treatment. In this study, we present a systematic approach for serial mutation profiling of 34 EV samples from 10 metastatic NSCLC patients with known EGFR mutations through treatment. Using western blot and droplet digital PCR (ddPCR), sensitizing (exon 19 deletion, L858R) mutations were detected in EV-Protein, and both sensitizing and resistance (T790M) mutations were quantified in EV-RNA. EGFR mutations were detected in EV-Protein from four patients at multiple time points through treatment. Using EV-RNA, tumor biopsy matched sensitizing mutations were detected in 90% of patients and resistance mutations in 100% of patients. Finally, mutation burden in EV-RNA at each time point was compared to disease status, described as either stable or progressing. For 6/7 patients who were longitudinally monitored through treatment, EV mutation burden mirrored clinical trajectory. When comparing mutation detection between EV-RNA and ctDNA using ddPCR, EVs had a better detection rate for exon 19 deletions and the L858R point mutation. In conclusion, this study demonstrates that integrating EV analysis into liquid biopsy mutation screening has the potential to advance beyond the current standard of care "rule in" test. The multi-analyte testing allows future integration of EGFR mutation monitoring with additional EV-markers for a comprehensive patient monitoring biomarker., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Purcell, Owen, Prantzalos, Radomski, Carman, Lo, Zeinali, Subramanian, Ramnath and Nagrath.)