Ziyan Rao1,2,6, Min Zhang3,6, Shaodong Huang1,2, Chenyang Wu1,2, Yuheng Zhou1, Weijie Zhang4,5, Xia Lin3 and Dongyu Zhao1,2 1Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China; 2State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China; 3Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; 4Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China; 5Department of Orthopaedic Surgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China Corresponding authors: zhaodongyubjmu.edu.cn, minzhzju.edu.cn Abstract

Cancer long noncoding RNAs (lncRNAs) have been identified by experimental and in silico methods. However, current approaches for identifying cancer lncRNAs are not sufficient and effective. To uncover them, we focus on the core cancer driver lncRNAs, which directly interact with cancer driver protein-coding genes (PCGs). We investigate various aspects of cancer lncRNAs, including their expression patterns, genomic locations, and direct interactions with cancer driver PCGs, and developed a pipeline to identify candidate cancer driver lncRNAs. Finally, we validate the reliability of potential cancer driver lncRNAs through functional analysis of bioinformatics data and CRISPR-Cas9 knockout experiments. We find that cancer lncRNAs are more concentrated in cancer driver topologically associated domains (CDTs), and CDT is an important feature in identifying cancer lncRNAs. Moreover, cancer lncRNAs show a high tendency to be coexpressed with and bind to cancer driver PCGs. Utilizing these distinctive characteristics, we develop a pipeline CAncer Driver Topologically Associated Domains (CADTAD) to identify candidate cancer driver lncRNAs in pan-cancer, including 256 oncogenic lncRNAs, 177 tumor-suppressive lncRNAs, and 75 dual-function lncRNAs, as well as in three individual cancer types, and validate their cancer-related functions. More importantly, the function of 10 putative cancer driver lncRNAs in prostate cancer is subsequently validated to influence cancer phenotype through cell studies. In light of these findings, our study offers a new perspective from the 3D genome to study the roles of lncRNAs in cancer. Furthermore, we provide a valuable set of potential lncRNAs that could deepen our understanding of the oncogenic mechanism of cancer driver lncRNAs.

Received November 26, 2024. Accepted May 15, 2025.