An inflammatory liquid fingerprint predicting tumor recurrence after liver transplantation for hepatocellular carcinoma

Author:

Yang Modan12,Lin Zuyuan34,Zhuang Li5,Pan Linhui6,Wang Rui4,Chen Hao4,Hu Zhihang4,Shen Wei4,Zhuo Jianyong6,Yang Xinyu34,Li Huigang4,He Chiyu4,Yang Zhe5,Xie Qinfen5,Dong Siyi7,Chen Junli7,Su Renyi4,Wei Xuyong36,Yin Junjie6,Zheng Shusen257,Lu Di8,Xu Xiao89ORCID

Affiliation:

1. Department of Breast Surgery The Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China

2. NHC Key Laboratory of Combined Multi‐Organ Transplantation Zhejiang University Hangzhou China

3. Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University Hangzhou China

4. Zhejiang University School of Medicine Hangzhou China

5. Department of Hepatobiliary and Pancreatic Surgery Shulan (Hangzhou) Hospital Hangzhou China

6. Department of Hepatobiliary and Pancreatic Surgery Affiliated Hangzhou First People's Hospital School of Medicine Westlake University Hangzhou China

7. National Center for Healthcare Quality Management in Liver Transplant Hangzhou China

8. Department of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery Zhejiang Provincial People's Hospital (Affiliated People's Hospital) School of Clinical Medicine Hangzhou Medical College Hangzhou China

9. Institute of Translational Medicine Zhejiang University School of Medicine Hangzhou China

Abstract

AbstractTumor recurrence is a life‐threatening complication after liver transplantation (LT) for hepatocellular carcinoma (HCC). Precise recurrence risk stratification before transplantation is essential for the management of recipients. Here, we aimed to establish an inflammation‐related prediction model for posttransplant HCC recurrence based on pretransplant peripheral cytokine profiling. Two hundred and ninety‐three patients who underwent LT in two independent medical centers were enrolled, and their pretransplant plasma samples were sent for cytokine profiling. We identified four independent risk factors, including alpha‐fetoprotein, systemic immune‐inflammation index, interleukin 6, and osteocalcin in the training cohort (n = 190) by COX regression analysis. A prediction model named inflammatory fingerprint (IFP) was established based on the above factors. The IFP effectively predicted posttransplant recurrence (area under the receiver operating characteristic curve [AUROC]: 0.792, C‐index: 0.736). The high IFP group recipients had significantly worse 3‐year recurrence‐free survival rates (37.9 vs. 86.9%, p < 0.001). Simultaneous T‐cell profiling revealed that recipients with high IFP were characterized by impaired T cell function. The IFP also performed well in the validation cohort (n = 103, AUROC: 0.807, C‐index: 0.681). In conclusion, the IFP efficiently predicted posttransplant HCC recurrence and helped to refine pretransplant risk stratification. Impaired T cell function might be the intrinsic mechanism for the high recurrence risk of recipients in the high IFP group.

Funder

National Key Research and Development Program of China

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3