ORIGINAL RESEARCH article
Front. Pharmacol.
Sec. Experimental Pharmacology and Drug Discovery
This article is part of the Research TopicAdvances in Biomarkers and Drug Targets: Harnessing Traditional and AI Approaches for Novel Therapeutic MechanismsView all 14 articles
Exploring HSP90α and hs-CRP Using AI Models to Predict Prognosis in Advanced Hepatocellular Carcinoma Treated with PD-1 Inhibitors and Targeted Therapy
Provisionally accepted
Pan Wang1*
Zhen-Ying Wu2
Li Xueting3Lu Yang4Yuhui Shi3Xianguo Liu3Lianbin Wen5Yanqiong Song6Wanyun Du7Yulin Tu7Qian Wei7Junqi Liu2- 1The Affiliated Hospital of Southwest Medical University, Luzhou, China
- 2Panzhihua University, Panzhihua, China
- 3No 363 Hospital, Chengdu, China
- 4Chongqing General Hospital, Chongqing, China
- 5Sichuan Academy of Medical Sciences and Sichuan People's Hospital Emergency Center, Chengdu, China
- 6Sichuan Cancer Hospital and Institute, Chengdu, China
- 7Southwest Medical University, Luzhou, China
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Abstract Objective This study investigates the roles of heat shock protein 90α (HSP90α) and high-sensitivity C-reactive protein (hs-CRP) in the progression and prognosis of advanced hepatocellular carcinoma (HCC) patients undergoing immunotherapy. By integrating these biomarkers with artificial intelligence (AI), we aim to elucidate the complex interactions between tumor stress, immune responses, and tumor progression. Methods This retrospective analysis includes 644 patients with advanced HCC who received PD-1 inhibitors and targeted therapy across 3 tertiary hospitals in China from 2016 to 2023. The patients were randomly divided into training (70%) and validation (30%) sets. Independent prognostic factors for overall survival (OS) were identified using LASSO and stepwise Cox regression. Five machine learning models were built, and their performance was evaluated using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. Results Patients with high HSP90α expression had a median OS of 7.7 months compared to 20.6 months for those with low expression (p < 0.001). Similarly, high hs-CRP levels were associated with OS of 11.6 months versus 30.8 months for low CRP (p < 0.001). LASSO and stepwise Cox regression identified age, CRP, HSP90α, Child-Pugh classification, tumor number, metastatic (M) status, and portal vein tumor thrombosis (PVTT) as independent prognostic markers. The Random Survival Forests (RSF) model achieved the highest C-index of 0.679, and in the validation set, it demonstrated AUC-ROC values of 0.803 at 6 months, 0.801 at 12 months, and 0.761 at 18 months. The RSF model demonstrated good calibration across all time points, and DCA showed consistently higher net benefit compared with "Treat
Keywords: artificial intelligence, PD-1 inhibitors, Hepatocellular Carcinoma, Hsp90α, Hs-CRP
Received: 17 Oct 2025; Accepted: 25 Nov 2025.
Copyright: © 2025 Wang, Wu, Xueting, Yang, Shi, Liu, Wen, Song, Du, Tu, Wei and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Pan Wang
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