Publication Name	World Journal of Gastroenterology
Manuscript ID	90768
Country	China

Received	2023-12-13 10:18
Peer-Review Started	2023-12-13 10:18
To Make the First Decision
Return for Revision	2023-12-27 17:54
Revised	2024-01-09 14:47
Second Decision	2024-03-04 02:52
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2024-03-04 05:02
Articles in Press	2024-03-04 05:02
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-03-18 04:01
Publish the Manuscript Online	2024-03-21 11:37

ISSN	1007-9327 (print) and 2219-2840 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
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Category	Immunology
Manuscript Type	Basic Study
Article Title	Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication
Manuscript Source	Invited Manuscript
All Author List	Jun-Tao Li, Hong-Mei Zhang, Wei Wang and Dong-Qing Wei
ORCID	Author(s) ORCID Number Jun-Tao Li http://orcid.org/0000-0002-3288-4395 Hong-Mei Zhang http://orcid.org/0009-0003-0914-1539 Wei Wang http://orcid.org/0000-0002-9616-1145 Dong-Qing Wei http://orcid.org/0000-0003-4200-7502
Funding Agency and Grant Number	Funding Agency Grant Number Scientific and Technological Project of Henan Province 212102210140
Corresponding Author	Hong-Mei Zhang, MPhil, Master's Student, College of Mathematics and Information Science, Henan Normal University, Jianshe East Road, Xinxiang 453007, Henan Province, China. zhanghmmail@163.com
Key Words	Liver cancer; Cell-cell communication; Gene signature; Prognosis; Immunotherapy; Single-cell RNA sequencing
Core Tip	In this study, CellChat was employed to infer cell-cell communication, thereby selecting highly active cell groups in immune-related pathways on single-cell RNA-sequencing data. Highly active immune cells were identified by intersecting these groups with B and T cells. Subsequently, significantly differentially expressed genes between highly active immune cells and the remaining cells were incorporated into the Lasso regression model. Ultimately, incorporating genes selected more than 5 times in 10 Lasso regression experiments into a multivariable Cox regression model, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified to construct a gene signature.
Publish Date	2024-03-21 11:37
Citation	Li JT, Zhang HM, Wang W, Wei DQ. Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication. World J Gastroenterol 2024; 30(11): 1609-1620
URL	https://www.wjgnet.com/1007-9327/full/v30/i11/1609.htm
DOI	https://dx.doi.org/10.3748/wjg.v30.i11.1609

Full Article (PDF)	WJG-30-1609-with-cover.pdf
Manuscript File	90768_Auto_Edited-YJP.docx
Answering Reviewers	90768-Answering reviewers.pdf
Audio Core Tip	90768-Audio core tip.mp3
Biostatistics Review Certificate	90768-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form	90768-Conflict-of-interest statement.pdf
Copyright License Agreement	90768-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	90768-Grant application form(s).pdf
Institutional Review Board Approval Form or Document	90768-Institutional review board statement.pdf
Non-Native Speakers of English Editing Certificate	90768-Language certificate.pdf
Peer-review Report	90768-Peer-review(s).pdf
Scientific Misconduct Check	90768-Bing-Wang JJ-2.png
Scientific Editor Work List	90768-Scientific editor work list.pdf