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Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma

BACKGROUND: Hepatitis B virus (HBV) has been recognized as a leading cause of hepatocellular carcinoma (HCC). Numerous reports suggest that immune infiltration can predict the prognosis of HCC. Nonetheless, no creditable markers for prognosis of HBV-related HCC have been established by systematicall...

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Autores principales: Chen, Qi-Feng, Li, Wang, Wu, Pei-Hong, Shen, Lu-Jun, Huang, Zi-Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761238/
https://www.ncbi.nlm.nih.gov/pubmed/31558872
http://dx.doi.org/10.3748/wjg.v25.i35.5266
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author Chen, Qi-Feng
Li, Wang
Wu, Pei-Hong
Shen, Lu-Jun
Huang, Zi-Lin
author_facet Chen, Qi-Feng
Li, Wang
Wu, Pei-Hong
Shen, Lu-Jun
Huang, Zi-Lin
author_sort Chen, Qi-Feng
collection PubMed
description BACKGROUND: Hepatitis B virus (HBV) has been recognized as a leading cause of hepatocellular carcinoma (HCC). Numerous reports suggest that immune infiltration can predict the prognosis of HCC. Nonetheless, no creditable markers for prognosis of HBV-related HCC have been established by systematically assessing the immune-related markers based on tumor transcriptomes. AIM: To establish an immune-related marker based on the cell compositions of immune infiltrate obtained based on tumor transcriptomes, so as to enhance the prediction accuracy of HBV-related HCC prognosis. METHODS: RNA expression patterns as well as the relevant clinical data of HCC patients were obtained from The Cancer Genome Atlas. Twenty-two immunocyte fraction types were estimated by cell type identification by estimating relative subsets of RNA transcripts. Subsequently, the least absolute shrinkage and selection operator (LASSO) Cox regression model was employed to construct an immunoscore based on the immunocyte fraction types. Afterwards, the receiver operating characteristic (ROC) curve, Kaplan-Meier, and multivariate Cox analyses were performed. Additionally, a nomogram for prognosis that integrated the immunoscore as well as the clinical features was established. Meanwhile, the correlation of immunoscore with immune genes was also detected, and gene set enrichment analysis (GSEA) of the immunoscore was conducted. RESULTS: A total of 22 immunocyte fraction types were predicted and compared among the tumor as well as non-tumor samples. An immunoscore was constructed through adopting the LASSO model, which contained eight immunocyte fraction types. Meanwhile, the areas under the ROC curves for the immunoscore biomarker prognostic model were 0.971, 0.912, and 0.975 for 1-, 3-, and 5-year overall survival (OS), respectively. Difference in OS between the high-immunoscore group and the low-immunoscore group was statistically significant [hazard ratio (HR) = 66.007, 95% confidence interval (CI): 8.361-521.105; P < 0.0001]. Moreover, multivariable analysis showed that the immunoscore was an independent factor for predicting the prognosis (HR = 2.997, 95%CI: 1.737-5.170). A nomogram was established, and the C-index was 0.757 (95%CI: 0.648-0.866). The immunoscore showed a significant negative correlation with the expression of PD-1 (P = 0.024), PD-L1 (P = 0.026), PD-L2 (P = 0.029), and CD27 (P = 0.033). Eight pathways were confirmed by GSEA. CONCLUSION: The established immunoscore can potentially serve as a candidate marker to estimate the OS for HBV-related HCC cases.
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spelling pubmed-67612382019-09-26 Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma Chen, Qi-Feng Li, Wang Wu, Pei-Hong Shen, Lu-Jun Huang, Zi-Lin World J Gastroenterol Basic Study BACKGROUND: Hepatitis B virus (HBV) has been recognized as a leading cause of hepatocellular carcinoma (HCC). Numerous reports suggest that immune infiltration can predict the prognosis of HCC. Nonetheless, no creditable markers for prognosis of HBV-related HCC have been established by systematically assessing the immune-related markers based on tumor transcriptomes. AIM: To establish an immune-related marker based on the cell compositions of immune infiltrate obtained based on tumor transcriptomes, so as to enhance the prediction accuracy of HBV-related HCC prognosis. METHODS: RNA expression patterns as well as the relevant clinical data of HCC patients were obtained from The Cancer Genome Atlas. Twenty-two immunocyte fraction types were estimated by cell type identification by estimating relative subsets of RNA transcripts. Subsequently, the least absolute shrinkage and selection operator (LASSO) Cox regression model was employed to construct an immunoscore based on the immunocyte fraction types. Afterwards, the receiver operating characteristic (ROC) curve, Kaplan-Meier, and multivariate Cox analyses were performed. Additionally, a nomogram for prognosis that integrated the immunoscore as well as the clinical features was established. Meanwhile, the correlation of immunoscore with immune genes was also detected, and gene set enrichment analysis (GSEA) of the immunoscore was conducted. RESULTS: A total of 22 immunocyte fraction types were predicted and compared among the tumor as well as non-tumor samples. An immunoscore was constructed through adopting the LASSO model, which contained eight immunocyte fraction types. Meanwhile, the areas under the ROC curves for the immunoscore biomarker prognostic model were 0.971, 0.912, and 0.975 for 1-, 3-, and 5-year overall survival (OS), respectively. Difference in OS between the high-immunoscore group and the low-immunoscore group was statistically significant [hazard ratio (HR) = 66.007, 95% confidence interval (CI): 8.361-521.105; P < 0.0001]. Moreover, multivariable analysis showed that the immunoscore was an independent factor for predicting the prognosis (HR = 2.997, 95%CI: 1.737-5.170). A nomogram was established, and the C-index was 0.757 (95%CI: 0.648-0.866). The immunoscore showed a significant negative correlation with the expression of PD-1 (P = 0.024), PD-L1 (P = 0.026), PD-L2 (P = 0.029), and CD27 (P = 0.033). Eight pathways were confirmed by GSEA. CONCLUSION: The established immunoscore can potentially serve as a candidate marker to estimate the OS for HBV-related HCC cases. Baishideng Publishing Group Inc 2019-09-21 2019-09-21 /pmc/articles/PMC6761238/ /pubmed/31558872 http://dx.doi.org/10.3748/wjg.v25.i35.5266 Text en ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ 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.
spellingShingle Basic Study
Chen, Qi-Feng
Li, Wang
Wu, Pei-Hong
Shen, Lu-Jun
Huang, Zi-Lin
Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma
title Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma
title_full Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma
title_fullStr Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma
title_full_unstemmed Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma
title_short Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma
title_sort significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis b virus-related hepatocellular carcinoma
topic Basic Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761238/
https://www.ncbi.nlm.nih.gov/pubmed/31558872
http://dx.doi.org/10.3748/wjg.v25.i35.5266
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