Abstract LB-226: Exosomal liquid biopsy reveals mRNA and lincRNA biomarkers in early stage breast cancer patient plasma
Authors: Chakrabortty Sudipto K. , Kitchen Robert R. , Coticchia Christine M. , Tadigotla Vasisht R. , Eitan Erez , Castellanos-Rizaldos Elena , Bedford Lisa , Badola Sunita , Valentino Michael D. , Colafemina Nicholas , Uchiyama Hidefumi , Morken Mario , Williams Miguel , Vincent Sylvie , Danaee Hadi , Yu Seth , Skog Johan 
Published: August 2018

Introduction

Breast cancer is the most prevalent cancer in women, with approximately 250,000 diagnoses per year in the US. Non-invasive detection of breast cancer is of critical importance but has proven challenging due to the rate of false-positive diagnoses with current tests. Liquid biopsies including circulating tumor cells (CTCs) or cell-free DNA (cfDNA) have struggled with the detection of early stage disease. For example, a recent multi-analyte (cfDNA+protein) analysis, ‘cancerSEEK', achieved a sensitivity of just 33% in breast cancer, highlighting the challenges facing the development of more sensitive and specific diagnostics for this disease.

Exosome-based liquid biopsy is a promising approach for minimally-invasive and highly sensitive diagnostics and it has been demonstrated that combining exosomal RNA and cfDNA greatly enhances mutation detection compared to profiling cfDNA alone. While most liquid biopsies profile mutations, studying RNA abundance in exosomes adds a new dimension to these non-invasive diagnostics. To date, much of the focus on exosomal RNA expression profiling has been on the small-RNA fraction. Here we demonstrate that whole-transcriptome profiling of mRNAs and lincRNAs greatly expands the landscape of potential biomarkers to clinically actionable genes.

Results

We have developed a novel platform designed to perform long-RNA sequencing on transcripts obtained from exosomes. We used this platform to compare expression profiles of total plasma exosomes versus subpopulations enriched for breast cancer-derived exosomes (CDE) versus depleted of non-cancer exosomes (NCE). The NCE-depleted and CDE-enriched exosomes equally outperformed total plasma exosomes, each detecting significantly more genes exhibiting breast cancer vs. healthy expression differences.

We performed NCE-depletion on 1.5 mL of input plasma from 15 stage I & II ER+/Her2- breast cancer patients and 12 healthy women matched for age & menopausal-status. RNA-seq data from these samples detected over 10,000 mRNAs and over 1,000 lincRNAs. Of these, we observed significantly increased abundance in over 100 mRNAs and lincRNAs in these early stage breast cancer patients. These mRNAs are enriched for gene-sets including those previously implicated in ‘breast cancer', ‘chromatin remodeling', and ‘immune response'.

We also performed RNA-seq on formalin-fixed paraffin-embedded (FFPE) samples from healthy and matched breast cancer tissue. The &gt;100 genes found to be more abundant in breast cancer plasma exosomes significantly (p&lt;0.05) separate the FFPE samples into two clusters corresponding to breast cancer patients and normal individuals, lending confidence to the exosomal signature.

Conclusions

This preliminary analysis highlights the exciting potential of exosomal long RNA based liquid biopsy for non-invasive early-stage detection of breast cancer. The platform is readily applicable to other disease areas and other biofluids such as urine or CSF.

Citation Format: Sudipto K. Chakrabortty, Robert R. Kitchen, Christine M. Coticchia, Vasisht R. Tadigotla, Erez Eitan, Elena Castellanos-Rizaldos, Lisa Bedford, Sunita Badola, Michael D. Valentino, Nicholas Colafemina, Hidefumi Uchiyama, Mario Morken, Miguel Williams, Sylvie Vincent, Hadi Danaee, Seth Yu, Johan Skog. Exosomal liquid biopsy reveals mRNA and lincRNA biomarkers in early stage breast cancer patient plasma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-226.