Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma
BackgroundTumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed.MethodsCommon inflammation-immune factors were reviewed and selected to const...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-06-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.893268/full |
| _version_ | 1818205137949163520 |
|---|---|
| author | Xin Xu Xin Xu Ao Huang Ao Huang De-Zhen Guo De-Zhen Guo Yu-Peng Wang Yu-Peng Wang Shi-Yu Zhang Shi-Yu Zhang Jia-Yan Yan Jia-Yan Yan Xin-Yu Wang Xin-Yu Wang Ya Cao Jia Fan Jia Fan Jia Fan Jia Fan Jian Zhou Jian Zhou Jian Zhou Jian Zhou Xiu-Tao Fu Xiu-Tao Fu Ying-Hong Shi Ying-Hong Shi |
| author_facet | Xin Xu Xin Xu Ao Huang Ao Huang De-Zhen Guo De-Zhen Guo Yu-Peng Wang Yu-Peng Wang Shi-Yu Zhang Shi-Yu Zhang Jia-Yan Yan Jia-Yan Yan Xin-Yu Wang Xin-Yu Wang Ya Cao Jia Fan Jia Fan Jia Fan Jia Fan Jian Zhou Jian Zhou Jian Zhou Jian Zhou Xiu-Tao Fu Xiu-Tao Fu Ying-Hong Shi Ying-Hong Shi |
| author_sort | Xin Xu |
| collection | DOAJ |
| description | BackgroundTumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed.MethodsCommon inflammation-immune factors were reviewed and selected to construct novel models. The model consisting of preoperative aspartate aminotransferase, C-reactive protein, and lymphocyte count, named ACLR, was selected and evaluated for clinical significance.ResultsAmong the nine novel inflammation-immune models, ACLR showed the highest accuracy for overall survival (OS) and time to recurrence (TTR). At the optimal cutoff value of 80, patients with high ACLR (> 80) had larger tumor size, higher Edmondson’s grade, more vascular invasion, advanced tumor stage, and poorer survival than those with low ACLR (≤ 80) in the training cohort (5-year OS: 43.3% vs. 80.1%, P < 0.0001; 5-year TTR: 74.9% vs. 45.3%, P < 0.0001). Multivariate Cox analysis identified ACLR as an independent risk factor for OS [hazard ratio (HR) = 2.22, P < 0.001] and TTR (HR = 2.36, P < 0.001). Such clinical significance and prognostic value were verified in validation cohort. ACLR outperformed extant models, showing the highest area under receiver operating characteristics curve for 1-, 3-, and 5-year OS (0.737, 0.719, and 0.708) and 1-, 3-, and 5-year TTR (0.696, 0.650, and 0.629). High ACLR correlated with early recurrence (P < 0.001) and extremely early recurrence (P < 0.001). In patients with high ACLR, wide resection margin might confer survival benefit by decreasing recurrence (median TTR, 25.5 vs. 11.4 months; P = 0.037).ConclusionsThe novel inflammation-immune model, ACLR, could effectively predict prognosis, and the presence of MRD before hepatectomy and might guide the decision on resection margin for patients with HCC. |
| first_indexed | 2024-12-12T03:52:22Z |
| format | Article |
| id | doaj.art-2c3267de46674958a686769bfd135065 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-12T03:52:22Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-2c3267de46674958a686769bfd1350652022-12-22T00:39:21ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-06-011210.3389/fonc.2022.893268893268Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular CarcinomaXin Xu0Xin Xu1Ao Huang2Ao Huang3De-Zhen Guo4De-Zhen Guo5Yu-Peng Wang6Yu-Peng Wang7Shi-Yu Zhang8Shi-Yu Zhang9Jia-Yan Yan10Jia-Yan Yan11Xin-Yu Wang12Xin-Yu Wang13Ya Cao14Jia Fan15Jia Fan16Jia Fan17Jia Fan18Jian Zhou19Jian Zhou20Jian Zhou21Jian Zhou22Xiu-Tao Fu23Xiu-Tao Fu24Ying-Hong Shi25Ying-Hong Shi26Liver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Oncology, Zhongshan Hospital, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaCancer Research Institute, Xiangya School of Medicine, Central South University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Xiangya Hospital, Central South University, Changsha, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaInstitute of Biomedical Sciences, Fudan University, Shanghai, ChinaState Key Laboratory of Genetic Engineering, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaInstitute of Biomedical Sciences, Fudan University, Shanghai, ChinaState Key Laboratory of Genetic Engineering, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaLiver Cancer Institute, Zhongshan Hospital, Fudan University and Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Liver Surgery and Transplantation, Zhongshan Hospital, Fudan University, Shanghai, ChinaBackgroundTumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed.MethodsCommon inflammation-immune factors were reviewed and selected to construct novel models. The model consisting of preoperative aspartate aminotransferase, C-reactive protein, and lymphocyte count, named ACLR, was selected and evaluated for clinical significance.ResultsAmong the nine novel inflammation-immune models, ACLR showed the highest accuracy for overall survival (OS) and time to recurrence (TTR). At the optimal cutoff value of 80, patients with high ACLR (> 80) had larger tumor size, higher Edmondson’s grade, more vascular invasion, advanced tumor stage, and poorer survival than those with low ACLR (≤ 80) in the training cohort (5-year OS: 43.3% vs. 80.1%, P < 0.0001; 5-year TTR: 74.9% vs. 45.3%, P < 0.0001). Multivariate Cox analysis identified ACLR as an independent risk factor for OS [hazard ratio (HR) = 2.22, P < 0.001] and TTR (HR = 2.36, P < 0.001). Such clinical significance and prognostic value were verified in validation cohort. ACLR outperformed extant models, showing the highest area under receiver operating characteristics curve for 1-, 3-, and 5-year OS (0.737, 0.719, and 0.708) and 1-, 3-, and 5-year TTR (0.696, 0.650, and 0.629). High ACLR correlated with early recurrence (P < 0.001) and extremely early recurrence (P < 0.001). In patients with high ACLR, wide resection margin might confer survival benefit by decreasing recurrence (median TTR, 25.5 vs. 11.4 months; P = 0.037).ConclusionsThe novel inflammation-immune model, ACLR, could effectively predict prognosis, and the presence of MRD before hepatectomy and might guide the decision on resection margin for patients with HCC.https://www.frontiersin.org/articles/10.3389/fonc.2022.893268/fullprognostic modelinflammationimmunityhepatocellular carcinomaprognosis |
| spellingShingle | Xin Xu Xin Xu Ao Huang Ao Huang De-Zhen Guo De-Zhen Guo Yu-Peng Wang Yu-Peng Wang Shi-Yu Zhang Shi-Yu Zhang Jia-Yan Yan Jia-Yan Yan Xin-Yu Wang Xin-Yu Wang Ya Cao Jia Fan Jia Fan Jia Fan Jia Fan Jian Zhou Jian Zhou Jian Zhou Jian Zhou Xiu-Tao Fu Xiu-Tao Fu Ying-Hong Shi Ying-Hong Shi Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma Frontiers in Oncology prognostic model inflammation immunity hepatocellular carcinoma prognosis |
| title | Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma |
| title_full | Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma |
| title_fullStr | Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma |
| title_full_unstemmed | Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma |
| title_short | Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma |
| title_sort | integration of inflammation immune factors to build prognostic model predictive of prognosis and minimal residual disease for hepatocellular carcinoma |
| topic | prognostic model inflammation immunity hepatocellular carcinoma prognosis |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.893268/full |
| work_keys_str_mv | AT xinxu integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT xinxu integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT aohuang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT aohuang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT dezhenguo integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT dezhenguo integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT yupengwang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT yupengwang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT shiyuzhang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT shiyuzhang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jiayanyan integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jiayanyan integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT xinyuwang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT xinyuwang integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT yacao integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jiafan integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jiafan integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jiafan integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jiafan integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jianzhou integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jianzhou integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jianzhou integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT jianzhou integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT xiutaofu integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT xiutaofu integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT yinghongshi integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma AT yinghongshi integrationofinflammationimmunefactorstobuildprognosticmodelpredictiveofprognosisandminimalresidualdiseaseforhepatocellularcarcinoma |