Plasma extracellular vesicle long RNA profiles in the diagnosis and prediction of treatment response for breast cancer

Yonghui Su,Rong Guo,Jianjing Hou,Zhen Wang,Hongyan Lai,Jingyan Xue,Lun Li,Yayun Chi,Weiru Chi,Jingjing Zhao,Yuchen Li,Shenglin Huang,Jiong Wu,Zhimin Shao,Jia Wang,Yuting Sang

doi:10.1038/s41523-021-00356-z

Abstract

A large number RNAs are enriched and stable in extracellular vesicles (EVs), and they can reflect their tissue origins and are suitable as liquid biopsy markers for cancer diagnosis and treatment efficacy prediction. In this study, we used extracellular vesicle long RNA (exLR) sequencing to characterize the plasma-derived exLRs from 112 breast cancer patients, 19 benign patients and 41 healthy participants. The different exLRs profiling was found between the breast cancer and non-cancer groups. Thus, we constructed a breast cancer diagnostic signature which showed high accuracy with an area under the curve (AUC) of 0.960 in the training cohort and 0.900 in the validation cohort. The signature was able to identify early stage BC (I/II) with an AUC of 0.940. Integrating the signature with breast imaging could increase the diagnosis accuracy for breast cancer patients. Moreover, we enrolled 58 patients who received neoadjuvant treatment and identified an exLR (exMSMO1), which could distinguish pathological complete response (pCR) patients from non-pCR with an AUC of 0.790. Silencing MSMO1 could significantly enhance the sensitivity of MDA-MB-231 cells to paclitaxel and doxorubicin through modulating mTORC1 signaling pathway. This study demonstrated the value of exLR profiling to provide potential biomarkers for early detection and treatment efficacy prediction of breast cancer.

Highlights

Breast cancer (BC) is the most common malignancy in women worldwide[1]
One hundred and seventy-two individuals were included in this study; the participants consisted of 112 BC patients, 19 benign patients, and 41 healthy donors (Table 1)
These results indicate that extracellular vesicle long RNA (exLR) combined with the Breast Imaging Reporting and Data System classification (BI-RADS) system could be utilized as a more accurate biomarker for differential diagnosis of early-stage BC compared with the BI-RADS system only

Summary

Introduction

Breast cancer (BC) is the most common malignancy in women worldwide[1]. BC found at an early stage carries much-improved prognosis compared to advanced stage disease[2]. The detection and efficient treatment of early stage BC has significant potential for reducing its mortality. Mammography and ultrasound are the optimal methods for BC screening and are recommended by different clinical guidelines. Their sensitivity and specificity are not consistent among different studies[3,4,5,6,7].

Methods

Results

Conclusion