BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
2/27/2026 8:35:11 AM | Browse: 21 | Download: 70
 |
Received |
|
2025-10-15 02:19 |
|
Peer-Review Started |
|
2025-10-15 02:19 |
|
First Decision by Editorial Office Director |
|
2025-11-18 10:53 |
|
Return for Revision |
|
2025-11-18 10:53 |
|
Revised |
|
2025-11-22 08:48 |
 |
Publication Fee Transferred |
|
|
|
Second Decision by Editor |
|
2026-01-04 02:39 |
|
Second Decision by Editor-in-Chief |
|
|
|
Final Decision by Editorial Office Director |
|
2026-01-04 06:49 |
|
Articles in Press |
|
2026-01-04 06:49 |
|
Edit the Manuscript by Language Editor |
|
|
|
Typeset the Manuscript |
|
2026-02-09 00:51 |
|
Publish the Manuscript Online |
|
2026-02-27 08:35 |
| 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: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
|
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
|
| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Immunology |
| Manuscript Type |
Letter to the Editor |
| Article Title |
Kill two birds with one stone: Reprogramming tumor microenvironment with growth differentiation factor 11
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Han-Ying Huang and Lin Tian |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Natural Science Foundation of China |
No. 82173278 |
| National Natural Science Foundation of China |
No. 82573221 |
| Young Talents Program of SYSUCC |
No. YTP-SYSUCC-0045 |
| Fostering Program for NSFC Young Applicants (Tulip Talent Training Program) of SYSUCC |
No. TTP-SYSUCC-202406 |
|
| Corresponding Author |
Lin Tian, Assistant Professor, Principal Investigator, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, 651 Dongfeng East Road, Guangzhou 500060, Guangdong Province, China. tianlin@sysucc.org.cn |
| Key Words |
Growth differentiation factor 11; Hepatocellular carcinoma; Tumor-associated macrophage; M1/M2 polarization; Cancer invasion |
| Core Tip |
This preview summarizes the dual function of Growth Differentiation Factor 11 (GDF11) as a novel strategy against hepatocellular carcinoma. Beyond suppressing cancer cells, GDF11 uniquely "re-educates" pro-tumoral M2 macrophages – a key driver of immunosuppression. It reprograms these cells by reducing the immunosuppressive marker CD206, rewiring their metabolism, and boosting reactive oxygen species. This shifts the macrophages to an anti-tumor state, neutralizing their cancer-promoting effects. By simultaneously targeting the tumor and its microenvironment, GDF11 offers a novel approach to break immunotherapy resistance, positioning it as a promising candidate for future combination therapies. |
| Publish Date |
2026-02-27 08:35 |
| Citation |
Huang HY, Tian L. Kill two birds with one stone: Reprogramming tumor microenvironment with growth differentiation factor 11. World J Gastroenterol 2026; 32(9): 115259 |
| URL |
https://www.wjgnet.com/1007-9327/full/v32/i9/115259.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v32.i9.115259 |
All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.
