Analysis of extracellular vesicles from patients with advanced pancreatic cancer identifies miRNAs with predictive value for treatment with gemcitabine + nab-paclitaxel

Pancreatic cancer (PC) is the seventh leading cause of cancer death. Despite recent therapy advancements, 5-year survival is 11%. Resistance to therapy is common, and no predictive factors, except for BRCA1/2 and PALB2 mutations, can drive treatment selection. Based on the easy isolation of extracellular vesicles (EVs) from blood and the role of EV-borne miRNAs in chemoresistance, we analyzed EVs and their miRNA content in order to identify predictive factors. First, we analyzed samples from 28 PC patients and 7 healthy subjects, in order to establish methods for isolation and analysis of EVs and their miRNA content. We observed a significantly different expression of 28 miRNAs, including oncogenic or tumor suppressor miRNAs, showing the ability of our approach to detect candidate biomarkers. Then, we analyzed samples of 21 advanced PC patients, collected before first-line treatment with gemcitabine + nab-paclitaxel, and compared findings in responders and non-responders. EVs have been analyzed with Nanoparticle tracking analysis, flow cytometry and RNA-Seq; then, laboratory results have been matched with clinical data. Nanoparticle tracking analysis did not show any significant difference. Flow cytometry showed a lower expression of SSE4 and CD81 in responders. Finally, miRNA analysis showed 25 upregulated and 19 downregulated miRNAs in responders. In particular, in responders we observed upregulation of miR-141-3p, miR-141-5p, miR-200a-3p, miR-200b-3p, miR-200c-3p, miR-375-3p, miR-429, miR-545-5p. These miRNAs have targets with a previously reported role in PC. In conclusion, we show the feasibility of the proposed approach to identify EV-derived biomarkers with predictive value for therapy with gemcitabine + nab-paclitaxel in PC. Our findings highlight the possibility to exploit liquid biopsy for personalized treatment in PC, in order to maximize chances of response and patients’ outcome. These findings are worthy of further investigation: in the same setting, with different chemotherapy schedules, and in different disease settings such as preoperative therapy.