Jagtap SV. Evaluation and prediction of Ki-67 expression in hepatocellular carcinoma. World J Gastrointest Oncol 2025; 17(10): 106529 [PMID: 41114092 DOI: 10.4251/wjgo.v17.i10.106529]
Corresponding Author of This Article
Sunil V Jagtap, MD, Professor, Department of Pathology, Krishna Vishwa Vidyapeeth (Deemed To Be University), Krishna Institute of Medical Sciences, Karad 415110, Maharashtra, India. drsvjagtap@gmail.com
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Oncology
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Letter to the Editor
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/
Oct 15, 2025 (publication date) through Oct 25, 2025
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Publication Name
World Journal of Gastrointestinal Oncology
ISSN
1948-5204
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Jagtap SV. Evaluation and prediction of Ki-67 expression in hepatocellular carcinoma. World J Gastrointest Oncol 2025; 17(10): 106529 [PMID: 41114092 DOI: 10.4251/wjgo.v17.i10.106529]
World J Gastrointest Oncol. Oct 15, 2025; 17(10): 106529 Published online Oct 15, 2025. doi: 10.4251/wjgo.v17.i10.106529
Evaluation and prediction of Ki-67 expression in hepatocellular carcinoma
Sunil V Jagtap
Sunil V Jagtap, Department of Pathology, Krishna Vishwa Vidyapeeth (Deemed To Be University), Krishna Institute of Medical Sciences, Karad 415110, Maharashtra, India
Author contributions: Jagtap SV designed the research study; performed the research; contributed new update and analytic tools; analyzed the data and wrote the manuscript; have read and approved the final manuscript.
Conflict-of-interest statement: The author has no competing interests to declare.
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/
Corresponding author: Sunil V Jagtap, MD, Professor, Department of Pathology, Krishna Vishwa Vidyapeeth (Deemed To Be University), Krishna Institute of Medical Sciences, Karad 415110, Maharashtra, India. drsvjagtap@gmail.com
Received: March 9, 2025 Revised: April 16, 2025 Accepted: May 26, 2025 Published online: October 15, 2025 Processing time: 221 Days and 2.6 Hours
Core Tip
Core Tip: The incidence and mortality of liver cancer continue to rise. The various screening methods for hepatocellular carcinoma (HCC) are radiomics, serum biomarkers, immunohistochemistry, genetic and molecular studies. Ki-67 protein in the nucleus is associated with cell proliferation, and indicates the aggressiveness of tumors. Evaluation and prediction of Ki-67 expression in HCC now have a significant role in the diagnosis, treatment, and prognosis of HCC. Elevated levels of Ki67 expression are associated with a poor prognosis and higher risk of HCC recurrence. Recently, radiomics, using machine learning-based ultrasomics, has demonstrated the capability to predict Ki-67 expression as a potential noninvasive tool for preoperative assessment in HCC.
