Towards establishing extracellular vesicle-associated RNAs as biomarkers for HER2+ breast cancer

Extracellular vesicles (EVs) are emerging as key players in breast cancer progression and hold immense promise as cancer biomarkers. However, difficulties in obtaining sufficient quantities of EVs for the identification of potential biomarkers hampers progress in this area. To circumvent this obstacle, we cultured BT-474 breast cancer cells in a two-chambered bioreactor with CDM-HD serum replacement to significantly improve the yield of cancer cell-associated EVs and eliminate bovine EV contamination. Cancer-relevant mRNAs BIRC5 (Survivin) and YBX1, as well as long-noncoding RNAs HOTAIR, ZFAS1, and AGAP2-AS1 were detected in BT-474 EVs by quantitative RT-PCR. Bioinformatics meta-analyses showed that BIRC5 and HOTAIR RNAs were substantially upregulated in breast tumours compared to non-tumour breast tissue, warranting further studies to explore their usefulness as biomarkers in patient EV samples. We envision this effective procedure for obtaining large amounts of cancer-specific EVs will accelerate discovery of EV-associated RNA biomarkers for cancers including HER2+ breast cancer.

Methods
Bioreactor culture

To prevent bovine EVs present in foetal calf serum (FCS) from contaminating the cancer-specific EVs, we cultured BT-474 cells from ATCC (ATCC® HTB-20™ ) (seeded at 4.5 x 108 cells/mL) in 15 mL Advanced DMEM/F-12 medium (Gibco, ThermoFisher Scientific, Waltham, USA) supplemented with 2% CDM-HD serum replacement (FiberCell Systems, New Market, USA) in the lower cell chamber of a CELLine AD 1000 bioreactor flask (Argos, Elgin, USA). The same media (150 mL) was used in the upper media chamber but supplemented with 2% FCS (Figure 1A). The dialysis membrane that separates the cell and media compartments allows FCS-specific nutrients <10 kDa but not EVs to pass through and nourish the cells. Every three to four days, the 15 mL of conditioned medium from the cell chamber was harvested for EV isolation, and the media from the upper chamber was replaced.

EV isolation and purification

EVs were isolated using differential centrifugation and size exclusion chromatography (SEC) as outlined in Figure 1. Conditioned medium (15 mL) was first centrifuged at 2,000 x g for 10 min to remove large debris, 10,000 x g for 30 min to isolate large EVs, and 100,000 x g for 70 min to isolate small EVs (Figure 1A). The resulting small EV suspension (in 500 µL PBS) was loaded onto a 35 nm qEV original size exclusion column (Izon, Christchurch, New Zealand), and fractions 7 through 24 were collected using an automated fraction collector (500 µL per fraction). BCA protein quantitation assay (Cat # 23225, Pierce, ThermoFisher Scientific, Waltham, USA) and Nanosight NS300 nanoparticle tracking analysis (NTA; Malvern Panalytical, Malvern, UK) were performed to quantitate protein and particle concentrations in each fraction, respectively. EV concentrations and size distributions were quantified on NTA by recording three 30 seconds videos under low flow conditions, with large EVs diluted at 1:100 in PBS and small EVs diluted at 1:500 in PBS. Small EV-rich fractions (7-11) were pooled, quantified again using NTA and BCA, and concentrated by ultracentrifugation (Avanti, Beckman Coulter, Brea, USA) at 100,000 x g for 70 min.

EV visualisation by transmission electron microscopy (TEM)

Negative staining TEM of pooled EV fractions was conducted by adsorption onto Formvar-coated copper grids (Electron Microscopy Sciences, Hatfield, USA) for 2 min, then treated with 2% uranyl acetate for 2 min. Grids were then visualised on a Tecnai G2 Spirit TWIN (FEI, Hillsboro, OR, USA) transmission electron microscope at 120 kV accelerating voltage and images were captured using a Morada digital camera (SIS GmbH, Munster, Germany).

Protein analysis by western blotting

This procedure was carried out as described previously.26 Breast cancer cell lines were grown to log-phase, washed twice with ice-cold PBS, and lysed in an sodium dodecyl sulphate (SDS) lysis buffer [60 mM Tris-HCl (pH 6.8 at 25°C), 2% (w/v) SDS, 10% glycerol]. Proteins (25 μg) were separated by SDS-polyacrylamide gel electrophoresis (PAGE) and transferred to PVDF membranes. Membranes were subsequently immunoblotted with antibodies recognising human HER2 (mouse monoclonal, anti-Neu, Santa Cruz, Cat # sc-33684, RRID:AB_627996), human EpCAM (rabbit monoclonal, AbCAM, Cat # ab223582, RRID:AB_2762366), human alpha-Tubulin (mouse monoclonal, Sigma-Aldrich Cat# T6074, RRID:AB_477582) and human TSG101 (rabbit polyclonal, AbCAM, Cat # ab30871, RRID:AB_2208084) and corresponding secondary antibodies. Bound antibodies were visualized using Pierce™ ECL Western Blotting Substrate (ThermoFisher Scientific, Waltham, USA) and the chemiluminescence was measured using a BioRad ChemiDoc MP imaging system (Bio-Rad Laboratories, Inc., Hercules, USA).

RNA quantitation by qRT-PCR

Trizol-purified RNA were reverse transcribed into cDNA using qScript Flex cDNA kit (Cat # 95049, Quantabio, Beverly, USA) primed with equal molar ratio of oligo-dT and random primers according to the manufacturer’s instructions. Quantitative RT-PCR was carried out using SYBR Green MasterMix (Life Technologies, Carlsbad, USA) and gene-specific primers previously validated in the literature (Table 1). These included protein-coding mRNAs EpCAM,21 BIRC5,22 YBX1,23 GAPDH, and HPRT1, and lncRNAs ZFAS1,17 HOTAIR,19 and AGAP2-AS1.20 Three independent experiments were performed with duplicate PCR reactions per sample.  RT-qPCR data were presented as cycle threshold (CT) values. Expression values were normalized relative to GAPDH mRNA expression. Statistical analysis was performed using multiple T-test.  

Bioinformatic meta-analyses

For this meta-analysis, the “RSEM expected count (DESeq2 standardized)” dataset was downloaded on 31st March 2020 from the TCGA_GTEx_TARGET cohort included in the UCSC Xena portal (https://xenabrowser.net/datapages/) and was manually annotated. This procedure has resulted in a dataset called “Figure 2B and C_meta_analysis_rawdata.xlsx” deposited in the DRYAD Digital Repository and used for all subsequent analyses. All data manipulations, plotting and statistical analyses were carried out in R computing environment (v 3.5.3) running in R Studio (v 1.1.414) on a Windows 10 x64 machine. The ggplot2 package (v 3.3.0) was used to render Figures 2B and 2C. Magnitude of the gene expression difference between non-tumour breast tissues and breast tumours (Hedges g effect size) was calculated using the cohen.d function included in the effsize R package (v 0.8.0). The R script containing the code for all the above computations and visualisations is available in the DRYAD Digital Repository.

An earlier version of this article can be found on bioRxiv (doi: https://doi.org/10.1101/2020.09.27.309252).