Exosome-based liquid biopsies in cancer: opportunities and challenges.

Liquid biopsy in cancer has gained momentum in clinical research and is experiencing a boom for a variety of applications. There are significant efforts to utilize liquid biopsies in cancer for early detection and treatment stratification, as well as residual disease and recurrence monitoring. Although most efforts have used circulating tumor cells and circulating tumor DNA for this purpose, exosomes and other extracellular vesicles have emerged as a platform with potentially broader and complementary applications. Exosomes/extracellular vesicles are small vesicles released by cells, including cancer cells, into the surrounding biofluids. These exosomes contain tumor-derived materials such as DNA, RNA, protein, lipid, sugar structures, and metabolites. In addition, exosomes carry molecules on their surface that provides clues regarding their origin, making it possible to sort vesicle types and enrich signatures from tissue-specific origins. Exosomes are part of the intercellular communication system and cancer cells frequently use them as biological messengers to benefit their growth. Since exosomes are part of the disease process, they have become of tremendous interest in biomarker research. Exosomes are remarkably stable in biofluids, such as plasma and urine, and can be isolated for clinical evaluation even in the early stages of the disease. Exosome-based biomarkers have quickly become adopted in the clinical arena and the first exosome RNA-based prostate cancer test has already helped >50 000 patients in their decision process and is now included in the National Comprehensive Cancer Network guidelines for early prostate cancer detection. This review will discuss the advantages and challenges of exosome-based liquid biopsies for tumor biomarkers and clinical implementation in the context of circulating tumor DNA and circulating tumor cells.

Improved EGFR mutation detection using combined exosomal RNA and circulating tumor DNA in NSCLC patient plasma.

Background: A major limitation of circulating tumor DNA (ctDNA) for somatic mutation detection has been the low level of ctDNA found in a subset of cancer patients. We investigated whether using a combined isolation of exosomal RNA (exoRNA) and cell-free DNA (cfDNA) could improve blood-based liquid biopsy for EGFR mutation detection in non-small-cell lung cancer (NSCLC) patients. Patients and methods: Matched pretreatment tumor and plasma were collected from 84 patients enrolled in TIGER-X (NCT01526928), a phase 1/2 study of rociletinib in mutant EGFR NSCLC patients. The combined isolated exoRNA and cfDNA (exoNA) was analyzed blinded for mutations using a targeted next-generation sequencing panel (EXO1000) and compared with existing data from the same samples using analysis of ctDNA by BEAMing. Results: For exoNA, the sensitivity was 98% for detection of activating EGFR mutations and 90% for EGFR T790M. The corresponding sensitivities for ctDNA by BEAMing were 82% for activating mutations and 84% for T790M. In a subgroup of patients with intrathoracic metastatic disease (M0/M1a; n = 21), the sensitivity increased from 26% to 74% for activating mutations (P = 0.003) and from 19% to 31% for T790M (P = 0.5) when using exoNA for detection. Conclusions: Combining exoRNA and ctDNA increased the sensitivity for EGFR mutation detection in plasma, with the largest improvement seen in the subgroup of M0/M1a disease patients known to have low levels of ctDNA and poses challenges for mutation detection on ctDNA alone. Clinical Trials: NCT01526928.

A molecular signature of PCA3 and ERG exosomal RNA from non-DRE urine is predictive of initial prostate biopsy result.

BACKGROUND: New screening methods that can add predictive diagnostic value for aggressive (high-grade, Gleason score ⩾ 7) prostate cancer (PCa) are needed to reduce unnecessary biopsies for patients with non-aggressive PCa. This is particularly important for men presenting for an initial biopsy with an equivocal PSA in the 2-10 ng ml(-1) range. PCA3 and ERG are biomarkers that can add predictive value for PCa in urine; however, with a limited utility as a digital rectal exam (DRE) is required. METHODS: First-catch urine samples were collected at six sites from men scheduled to undergo a prostate biopsy. Exosomal RNA was extracted, RNA copy numbers of ERG and PCA3 were measured by reverse transcription-quantitative PCR (RT-qPCR), and the EXO106 score (the sum of normalized PCA3 and ERG RNA levels) was computed. Performance was compared with standard of care (SOC; PSA, age, race or family history) parameters. Contingency table, logistic regression, receiver operating characteristics curve and box-plot analyses were performed. RESULTS: In this cohort (N=195), a dichotomous EXO106 score demonstrated good clinical performance in predicting biopsy result for both any cancer and high-grade disease. For high-grade disease, the negative and positive predictive values were 97.5% and 34.5%, respectively. The discrimination between high-grade and Gleason score ⩽ 6 (including benign) biopsy results by a combination of EXO106 and SOC (area under the curve (AUC)=0.803) was significantly improved compared with SOC without EXO106 (AUC=0.6723, P=0.0009). The median EXO106 score correlated (P<0.001; Spearman's rank order) with histologic grade. CONCLUSIONS: A novel molecular signature (EXO106 score) derived from non-DRE urine demonstrated independent, negative predictive value for the diagnosis of high-grade PCa from initial biopsy for men with 'gray zone' serum PSA levels. Its use in the biopsy decision process could result in fewer prostate biopsies for clinically insignificant disease.

Prostate cancer-derived urine exosomes: a novel approach to biomarkers for prostate cancer.

Herein, we describe a novel approach in the search for prostate cancer biomarkers, which relies on the transcriptome within tumour exosomes. As a proof-of-concept, we show the presence of two known prostate cancer biomarkers, PCA-3 and TMPRSS2:ERG the in exosomes isolated from urine of patients, showing the potential for diagnosis and monitoring cancer patients status.