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A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection

INTRODUCTION: Due to the high recurrence, the HCC prognosis remains poor. Yet, the biomarkers for predicting the recurrence of high‐risk patients are currently lacking. We aimed to develop a signature to predict the recurrence of HCC based on NKG2D ligands. METHODS: The multivariate Cox proportional...

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Autores principales: Chen, Dongbo, Gao, Jie, Ren, Liying, Chen, Pu, Yang, Yao, She, Shaoping, Xie, Yong, Liao, Weijia, Chen, Hongsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028019/
https://www.ncbi.nlm.nih.gov/pubmed/36210637
http://dx.doi.org/10.1002/cam4.5318
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author Chen, Dongbo
Gao, Jie
Ren, Liying
Chen, Pu
Yang, Yao
She, Shaoping
Xie, Yong
Liao, Weijia
Chen, Hongsong
author_facet Chen, Dongbo
Gao, Jie
Ren, Liying
Chen, Pu
Yang, Yao
She, Shaoping
Xie, Yong
Liao, Weijia
Chen, Hongsong
author_sort Chen, Dongbo
collection PubMed
description INTRODUCTION: Due to the high recurrence, the HCC prognosis remains poor. Yet, the biomarkers for predicting the recurrence of high‐risk patients are currently lacking. We aimed to develop a signature to predict the recurrence of HCC based on NKG2D ligands. METHODS: The multivariate Cox proportional hazards regression was used to select recurrence‐related variables of NKG2D ligands in HCC patients from The Cancer Genome Atlas (TCGA). HCC patients from the OEP000321 dataset and Guilin cohort were used to validate the predictive signature. The mRNA expression of NKG2D ligands was measured by QRT‐PCR. Immunohistochemistry analysis of HCC tissue microarray samples was used to identify the expression of NKG2D ligands. RESULTS: In this study, NKG2D ligands expression in the mRNA and protein level was both abnormally expressed in HCC and associated with recurrence‐free survival (RFS). Then, the recurrence‐related variables of NKG2D ligands in HCC were selected by the multivariate Cox proportional hazards regression. Among the eight NKG2D ligands, MICA (HR = 1.347; 95% CI = 1.012–1.793; p = 0.041), ULBP3 (HR = 0.453; 95% CI = 0.231–0.889; p = 0.021) and ULBP5 (HR = 3.617; 95% CI = 1.819–7.194; p < 0.001) were significantly correlated with RFS in the TCGA‐LIHC cohort. Then, the signature was constructed by the three NKG2D ligands. The predictive effectiveness of this signature was also validated in the OEP000321 dataset and Guilin cohort. Further, HCC patients were classified into low‐risk and high‐risk subgroups by the predictive score. Compared with the low‐risk group, the high‐risk group had poor RFS in both training and validation cohorts. Importantly, compared with the low‐risk patients with the G1‐G2 stage, the levels of infiltrated NK‐activated cells and NKG2D expression were both lower in the high‐risk patients. CONCLUSIONS: The signature based on MICA, ULBP3, and ULBP5 could predict HCC recurrence.
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spelling pubmed-100280192023-03-22 A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection Chen, Dongbo Gao, Jie Ren, Liying Chen, Pu Yang, Yao She, Shaoping Xie, Yong Liao, Weijia Chen, Hongsong Cancer Med Research Articles INTRODUCTION: Due to the high recurrence, the HCC prognosis remains poor. Yet, the biomarkers for predicting the recurrence of high‐risk patients are currently lacking. We aimed to develop a signature to predict the recurrence of HCC based on NKG2D ligands. METHODS: The multivariate Cox proportional hazards regression was used to select recurrence‐related variables of NKG2D ligands in HCC patients from The Cancer Genome Atlas (TCGA). HCC patients from the OEP000321 dataset and Guilin cohort were used to validate the predictive signature. The mRNA expression of NKG2D ligands was measured by QRT‐PCR. Immunohistochemistry analysis of HCC tissue microarray samples was used to identify the expression of NKG2D ligands. RESULTS: In this study, NKG2D ligands expression in the mRNA and protein level was both abnormally expressed in HCC and associated with recurrence‐free survival (RFS). Then, the recurrence‐related variables of NKG2D ligands in HCC were selected by the multivariate Cox proportional hazards regression. Among the eight NKG2D ligands, MICA (HR = 1.347; 95% CI = 1.012–1.793; p = 0.041), ULBP3 (HR = 0.453; 95% CI = 0.231–0.889; p = 0.021) and ULBP5 (HR = 3.617; 95% CI = 1.819–7.194; p < 0.001) were significantly correlated with RFS in the TCGA‐LIHC cohort. Then, the signature was constructed by the three NKG2D ligands. The predictive effectiveness of this signature was also validated in the OEP000321 dataset and Guilin cohort. Further, HCC patients were classified into low‐risk and high‐risk subgroups by the predictive score. Compared with the low‐risk group, the high‐risk group had poor RFS in both training and validation cohorts. Importantly, compared with the low‐risk patients with the G1‐G2 stage, the levels of infiltrated NK‐activated cells and NKG2D expression were both lower in the high‐risk patients. CONCLUSIONS: The signature based on MICA, ULBP3, and ULBP5 could predict HCC recurrence. John Wiley and Sons Inc. 2022-10-09 /pmc/articles/PMC10028019/ /pubmed/36210637 http://dx.doi.org/10.1002/cam4.5318 Text en © 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Chen, Dongbo
Gao, Jie
Ren, Liying
Chen, Pu
Yang, Yao
She, Shaoping
Xie, Yong
Liao, Weijia
Chen, Hongsong
A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection
title A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection
title_full A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection
title_fullStr A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection
title_full_unstemmed A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection
title_short A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection
title_sort signature based on nkg2d ligands to predict the recurrence of hepatocellular carcinoma after radical resection
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028019/
https://www.ncbi.nlm.nih.gov/pubmed/36210637
http://dx.doi.org/10.1002/cam4.5318
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