Development and validation of a TP53-associated immune prognostic model for hepatocellular carcinoma

Long, Junyu; Wang, Anqiang; Bai, Yi; Lin, Jianzhen; Xu, Yang; Wang, Dongxu; Yang, Xiaobo; Jiang, Yan; Zhao, Hong

doi:10.1016/j.ebiom.2019.03.022

Cited by 272 publications

(250 citation statements)

References 62 publications

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“…Another study also constructed a sixgene prognostic signature for HCC overall survival prediction based on gene expression data from TCGA [33]. A recent study investigating the prognostic value of TP53-associated immune genes in HCC identified and validated a two-gene (TREM1 and EXO1) prognostic model [34]. However, these studies did not use a large number of samples to comprehensively explore the relationship between immune genes and prognosis of HCC.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

et al. 2020

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Background: Growing evidence has suggested that immune-related genes play crucial roles in the development and progression of hepatocellular carcinoma (HCC). Nevertheless, the utility of immune-related genes for evaluating the prognosis of HCC patients are still lacking. The study aimed to explore gene signatures and prognostic values of immune-related genes in HCC. Methods:We comprehensively integrated gene expression data acquired from 374 HCC and 50 normal tissues in The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) analysis and univariate Cox regression analysis were performed to identify DEGs that related to overall survival. An immune prognostic model was constructed using the Lasso and multivariate Cox regression analyses. Furthermore, Cox regression analysis was applied to identify independent prognostic factors in HCC. The correlation analysis between immune-related signature and immune cells infiltration were also investigated. Finally, the signature was validated in an external independent dataset.Results: A total of 329 differentially expressed immune-related genes were detected. 64 immune-related genes were identified to be markedly related to overall survival in HCC patients using univariate Cox regression analysis. Then we established a TF-mediated network for exploring the regulatory mechanisms of these genes. Lasso and multivariate Cox regression analyses were applied to construct the immune-based prognostic model, which consisted of nine immune-related genes. Further analysis indicated that this immune-related prognostic model could be an independent prognostic indicator after adjusting to other clinical factors. The relationships between the risk score model and immune cell infiltration suggested that the nine-gene signature could reflect the status of tumor immune microenvironment. The prognostic value of this nine-gene prognostic model was further successfully validated in an independent database.Conclusions: Together, our study screened potential prognostic immune-related genes and established a novel immune-based prognostic model of HCC, which not only provides new potential prognostic biomarkers and therapeutic targets, but also deepens our understanding of tumor immune microenvironment status and lays a theoretical foundation for immunotherapy.

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Section: Discussionmentioning

confidence: 99%

Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

et al. 2020

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“…40 This may result in increased immunosuppressive cells (e.g., regulatory T cells and tumor-associated macrophages), decreased immunoreactive cells (e.g., T cells follicular helper), and increased expression of immunosuppressive molecules (e.g., CTLA-4 and PD-1) in the tumor. 41 PD-1 is a central regulator of T cells CD8 exhaustion and blockade of this inhibitory pathway enhances T cell immunity in several different types of cancers. 42,43 Thus, we hypothesized that patients in different groups would have different immunotherapeutic responses.…”

Section: Discussionmentioning

confidence: 99%

A TP53 -associated gene signature for prediction of prognosis and therapeutic responses in lung squamous cell carcinoma

Lin

et al. 2020

OncoImmunology

106

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The tumor-suppressor gene tumor protein p53 (TP53) is one of the most commonly mutated genes in human lung cancer, and TP53 mutations are associated with a worsened prognosis and causes resistance to cancer therapy. RNA sequencing and TP53 mutation data were downloaded to determine specific TP53associated signature based on differentially expressed genes between patients with lung squamous cell carcinoma (LUSC) with wild type (TP53 WT) and mutated (TP53 MUT) TP53. We investigated the predictive value of this signature on the immune microenvironment, tumor mutational burden (TMB), and likelihood of response to immunotherapy and chemotherapy. In total, 1,556 differentially expressed genes were identified based on TP53 mutation status. Three genes (KLK6, MUC22 and CSN1S1) identified by univariate and multivariate Cox regression analyses, comprised the prognostic signature which was an independent and specific prognostic marker of overall survival in patients with LUSC. A nomogram was also established to validate this signature for clinical use. Moreover, the high-risk group was characterized by increased infiltration of monocytes and macrophages M1, and decreased T cells CD8 and T cells follicular helper. Highrisk group exhibited a higher TMB, and was much more sensitive to immunotherapy and chemotherapy. KLK6 and CSN1S1 expression and the prognostic prediction values were further validated in clinical samples. The derived TP53-associated signature is a specific and independent prognostic biomarker for LUSC patients, and could provide potential prognostic biomarker or therapeutic targets for the development of novel immunotherapies and chemotherapies.

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“…11,12 Additionally, several immune prognostic signatures have been reported to predict the prognosis of patients with cancer, such as lung cancer, 13 ovarian cancer, 14 colorectal cancer, 15 and hepatocellular carcinoma. 16 These studies indicate that IRGs or TIME can serve as promising biomarkers for estimating survival in corresponding cancer. However, limited studies have explored whether immune-related genes (IRGs) or TIME could be indicators for the prognosis of CC.…”

Section: Introductionmentioning

confidence: 93%

Identification of a prognostic immune signature for cervical cancer to predict survival and response to immune checkpoint inhibitors

et al. 2019

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2019) Identification of a prognostic immune signature for cervical cancer to predict survival and response to immune checkpoint inhibitors, OncoImmunology, 8:12, e1659094, ABSTRACT Cervical cancer (CC) is a leading cause of cancer-related death in women. Limited studies have investigated whether immune-related genes (IRGs) or tumor immune microenvironment (TIME) could be indicators for CC prognoses. The aim of this study was to develop an improved prognostic signature for CC based on IRGs or TIME to predict survival and response to immune checkpoint inhibitors (ICIs). A prognostic signature was constructed using bioinformatics method and its predictive capability was validated. The mechanisms underlying the signature's predictive capability were explored with CIBERSORT algorithm and mutation analysis. Immunophenoscore (IPS) is validated for ICIs response, and was therefore explored in relation to the signature. A prognostic signature based on 11 IRGs was developed. A multivariate analysis revealed that the 11-IRG signature was an independent prognostic factor for overall survival (OS) and progression-free interval in CC patients. In the 11-IRG signature highrisk group, CD8 T cells and resting mast cells, which are found to associate with better OS in our study, were lower; activated mast cells, associated with poorer OS, were higher, compared with the low-risk group. An IPS analysis suggested that the 11-IRG signature low-risk group, which possessed a higher IPS, represented a more immunogenic phenotype that was more inclined to respond to ICIs. In short, an 11-IRG prognostic signature for predicting CC patients' survival and response to ICIs was firmly established. The predictive capability of this model in CC requires further testing with the goal of better prognostic stratification and treatment management. ARTICLE HISTORY

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Development and validation of a TP53-associated immune prognostic model for hepatocellular carcinoma

Cited by 272 publications

References 62 publications

Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

A TP53 -associated gene signature for prediction of prognosis and therapeutic responses in lung squamous cell carcinoma

Identification of a prognostic immune signature for cervical cancer to predict survival and response to immune checkpoint inhibitors

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