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Articles Published Processes
10/14/2025 7:42:33 AM | Browse: 11 | Download: 14
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Received |
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2025-06-12 03:54 |
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Peer-Review Started |
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2025-06-12 03:54 |
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To Make the First Decision |
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Return for Revision |
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2025-07-04 10:12 |
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Revised |
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2025-07-16 06:11 |
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Second Decision |
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2025-08-22 02:36 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-08-22 08:38 |
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Articles in Press |
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2025-08-22 08:38 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2025-10-08 09:29 |
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Publish the Manuscript Online |
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2025-10-14 07:42 |
| ISSN |
1948-5204 (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: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Review |
| Article Title |
Multidimensional decoding of colorectal cancer heterogeneity: Artificial intelligence-enabled precision exploration of single-cell and spatial transcriptomics
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Wen-Yu Luan, Qi Zhao, Zheng Zhang, Zhen-Xi Xu, Si-Xiang Lin and Yan-Dong Miao |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Shandong Province Medical and Health Science and Technology Development Plan Project |
No. 202203030713 |
| Yantai Science and Technology Program |
No. 2024YD005 |
| Yantai Science and Technology Program |
No. 2024YD007 |
| Yantai Science and Technology Program |
No. 2024YD010 |
| Science and Technology Program of Yantai Affiliated Hospital of Binzhou Medical University |
No. YTFY2022KYQD06 |
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| Corresponding Author |
Yan-Dong Miao, Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The Second Medical College of Binzhou Medical University, No. 717 Jinbu Street, Muping District, Yantai 264100, Shandong Province, China. miaoyd_22@bzmc.edu.cn |
| Key Words |
Artificial intelligence; Single-cell transcriptomics; Spatial transcriptomics; Colorectal cancer; Tumor heterogeneity |
| Core Tip |
Colorectal cancer remains a major global health threat with rising incidence in younger populations and limited response to immunotherapy in most patients, largely due to its complex tumor microenvironment and high cellular heterogeneity. Recent advances in single-cell transcriptomics and spatial transcriptomics have opened new avenues for decoding this heterogeneity, offering unprecedented resolution into tumor biology and immune interactions. However, the massive and multidimensional nature of these datasets poses significant analytical challenges. This paper explores how the integration of artificial intelligence (AI), particularly machine learning and deep learning techniques, can enhance data interpretation in single-cell and spatial transcriptomics, improve the identification of novel biomarkers and tumor subtypes, and ultimately support personalized treatment strategies. By systematically reviewing current progress and proposing AI-driven solutions, this study aims to bridge the gap between complex omics data and clinically actionable insights in colorectal cancer precision medicine. |
| Publish Date |
2025-10-14 07:42 |
| Citation |
<p>Luan WY, Zhao Q, Zhang Z, Xu ZX, Lin SX, Miao YD. Multidimensional decoding of colorectal cancer heterogeneity: Artificial intelligence-enabled precision exploration of single-cell and spatial transcriptomics. <i>World J Gastrointest Oncol</i> 2025; 17(10): 110661</p> |
| URL |
https://www.wjgnet.com/1948-5204/full/v17/i10/110661.htm |
| DOI |
https://dx.doi.org/10.4251/wjgo.v17.i10.110661 |
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