*Result*: An isoform-resolution transcriptomic atlas of colorectal cancer from long-read single-cell sequencing.

Title:
An isoform-resolution transcriptomic atlas of colorectal cancer from long-read single-cell sequencing.
Authors:
Li Z; Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia; Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia; Center of Excellence on Generative AI, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia., Zhang B; Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia; Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia; Center of Excellence on Generative AI, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia. Electronic address: bin.zhang@kaust.edu.sa., Chan JJ; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore., Tabatabaeian H; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore., Tong QY; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore., Chew XH; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore., Fan X; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore., Driguez P; Core Labs, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia., Chan C; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore., Cheong F; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore., Wang S; Department of Pathology, National University Health System, Singapore 119228, Singapore., Siew BE; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore., Tan IJ; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Division of Colorectal Surgery, University Surgical Cluster, National University Health System, Singapore 119228, Singapore., Lee KY; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Division of Colorectal Surgery, University Surgical Cluster, National University Health System, Singapore 119228, Singapore., Lieske B; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Division of Colorectal Surgery, University Surgical Cluster, National University Health System, Singapore 119228, Singapore., Cheong WK; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Division of Colorectal Surgery, University Surgical Cluster, National University Health System, Singapore 119228, Singapore., Kappei D; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore; NUS Centre for Cancer Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore., Tan KK; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Division of Colorectal Surgery, University Surgical Cluster, National University Health System, Singapore 119228, Singapore., Gao X; Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia; Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia; Center of Excellence on Generative AI, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia. Electronic address: xin.gao@kaust.edu.sa., Tay Y; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore; NUS Centre for Cancer Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore. Electronic address: yvonnetay@nus.edu.sg.
Source:
Cell genomics [Cell Genom] 2024 Sep 11; Vol. 4 (9), pp. 100641. Date of Electronic Publication: 2024 Aug 30.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier, Inc Country of Publication: United States NLM ID: 9918284260106676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2666-979X (Electronic) Linking ISSN: 2666979X NLM ISO Abbreviation: Cell Genom Subsets: MEDLINE
Imprint Name(s):
Original Publication: [New York] : Elsevier, Inc., [2021]-
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Contributed Indexing:
Keywords: colorectal cancer; long-read RNA-seq; neoantigen; scRNA-seq
Substance Nomenclature:
0 (Protein Isoforms)
Entry Date(s):
Date Created: 20240831 Date Completed: 20240912 Latest Revision: 20241019
Update Code:
20260130
PubMed Central ID:
PMC11480860
DOI:
10.1016/j.xgen.2024.100641
PMID:
39216476
Database:
MEDLINE

*Further Information*

*Colorectal cancer (CRC) ranks as the second leading cause of cancer deaths globally. In recent years, short-read single-cell RNA sequencing (scRNA-seq) has been instrumental in deciphering tumor heterogeneities. However, these studies only enable gene-level quantification but neglect alterations in transcript structures arising from alternative end processing or splicing. In this study, we integrated short- and long-read scRNA-seq of CRC samples to build an isoform-resolution CRC transcriptomic atlas. We identified 394 dysregulated transcript structures in tumor epithelial cells, including 299 resulting from various combinations of splicing events. Second, we characterized genes and isoforms associated with epithelial lineages and subpopulations exhibiting distinct prognoses. Among 31,935 isoforms with novel junctions, 330 were supported by The Cancer Genome Atlas RNA-seq and mass spectrometry data. Finally, we built an algorithm that integrated novel peptides derived from open reading frames of recurrent tumor-specific transcripts with mass spectrometry data and identified recurring neoepitopes that may aid the development of cancer vaccines.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)*

*Declaration of interests The authors declare no competing interests.*