Identification and validation a costimulatory molecule gene signature to predict the prognosis and immunotherapy response for hepatocellular carcinoma

Hu, Yinan; Liu, Jingyi; Yu, Jiahao; Yang, Fangfang; Zhang, Miao; Liu, Yansheng; Ma, Shuoyi; Zhou, Xia; Wang, Jingbo; Han, Ying

doi:10.1186/s12935-022-02514-0

Cited by 9 publications

(5 citation statements)

References 71 publications

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“…To escape immune surveillance, tumor cells increase the expression of immune checkpoints that physiologically attenuate immune response against healthy tissues, and also increase the recruitment of Treg cells [ 66 ]. A recent study identified two clusters of HCC patients, based on a signature of six costimulatory molecule genes (CMGs), that could help in identifying poor-prognosis patients and their ICI outcome [ 35 ]. They observed that the low-risk cluster of patients had a lower TMB, low frequency rate of TP53 mutation, higher immunophenoscore (IPS), IPS-CTLA4, IPS-PD1/PD-L1/PD-L2, and IPS-PD1/PD-L1/PD-L2 + CTLA4 with respect to the high-risk cluster.…”

Section: Tumor Immune Microenvironmentmentioning

confidence: 99%

Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma

Gabbia

Martin

2023

IJMS

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Hepatocellular carcinoma (HCC), the primary hepatic malignancy, represents the second-highest cause of cancer-related death worldwide. Many efforts have been devoted to finding novel biomarkers for predicting both patients’ survival and the outcome of pharmacological treatments, with a particular focus on immunotherapy. In this regard, recent studies have focused on unravelling the role of tumor mutational burden (TMB), i.e., the total number of mutations per coding area of a tumor genome, to ascertain whether it can be considered a reliable biomarker to be used either for the stratification of HCC patients in subgroups with different responsiveness to immunotherapy, or for the prediction of disease progression, particularly in relation to the different HCC etiologies. In this review, we summarize the recent advances on the study of TMB and TMB-related biomarkers in the HCC landscape, focusing on their feasibility as guides for therapy decisions and/or predictors of clinical outcome.

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Section: Tumor Immune Microenvironmentmentioning

confidence: 99%

Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma

Gabbia

Martin

2023

IJMS

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“…Based on previous studies [12][13][14][15] , a total of 59 costimulatory molecules were screened, and their expression was compared between COAD and normal tissues. Based on the expression of costimulatory molecules, correlation analysis was performed to discover interrelationships.…”

Section: Identification Of Costimulatory Moleculesmentioning

confidence: 99%

Prognostic costimulatory molecule-related signature risk model correlates with immunotherapy response in colon cancer

Huang¹,

Liao

et al. 2023

Sci Rep

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Costimulatory molecules can promote the activation and proliferation of T cells and play an essential role in immunotherapy. However, their role in the prognosis of colon adenocarcinoma remains elusive. In this study, the expression data of costimulatory molecules and clinicopathological information of 429 patients with colon adenocarcinoma were obtained from The Cancer Genome Atlas database. The patients were divided into training and verification cohorts. Correlation, Cox regression, and Lasso regression analyses were performed to identify costimulatory molecules related to prognosis. After mentioning the construction of the risk mode, a nomogram integrating the clinical characteristics and risk scores of patients was constructed to predict prognosis. Eventually, three prognostic costimulatory molecules were identified and used for constructing a risk model. High expression of these three molecules indicated a poor prognosis. The predictive accuracy of the risk model was verified in the GSE17536 dataset. Subsequently, multivariate regression analysis showed that the signature based on the three costimulatory molecules was an independent risk factor in the training cohort (HR = 2.12; 95% CI = 1.26, 3.56). Based on the risk model and clinicopathological data, the AUC values for predicting the 1-, 3-, and 5-year survival probability of patients with colon adenocarcinoma were 0.77, 0.77, and 0.71, respectively. To the best of our knowledge, this study is the first to report a risk signature constructed based on the costimulatory molecules TNFRSF10c, TNFRSF13c, and TNFRSF11a. This risk signature can serve as a prognostic biomarker for colon adenocarcinoma and is related to the immunotherapeutic response of patients.

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“…Finally, we assessed the potential response to immunotherapy and chemotherapy among several patient groups classified using the CMGP-based signature. Notably, similar data mining, processing, and model building have been achieved in renal cell carcinoma (21,22), prostate cancer (23), hepatocellular carcinoma (24), etc.…”

Section: Introductionmentioning

confidence: 95%

A Signature Based on Costimulatory Molecules for the Assessment of Prognosis and Immune Characteristics in Patients With Stomach Adenocarcinoma

et al. 2022

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Although costimulatory molecules have been shown to boost antitumor immune responses, their significance in stomach adenocarcinoma (STAD) remains unknown. The purpose of this study was to examine the gene expression patterns of costimulatory molecule genes in patients with STAD and develop a predictive signature to aid in therapy selection and outcome prediction. We used 60 costimulatory family genes from prior research to conduct the first complete costimulatory molecular analysis in patients with STAD. In the two study groups, consensus clustering analysis based on these 60 genes indicated unique distribution patterns and prognostic differences. Using the least absolute shrinkage and selection operator and Cox regression analysis, we identified nine costimulatory molecular gene pairs (CMGPs) with prognostic value. With these nine CMGPs, we were able to develop a costimulatory molecule-related prognostic signature that performed well in an external dataset. For the patients with STAD, the signature was proven to be a risk factor independent of the clinical characteristics, indicating that this signature may be employed in conjunction with clinical considerations. A further connection between the signature and immunotherapy response was discovered. The patients with high mutation rates, an abundance of infiltrating immune cells, and an immunosuppressive milieu were classified as high-risk patients. It is possible that these high-risk patients have a better prognosis for immunotherapy since they have higher cytolytic activity scores and immunophenoscores of CTLA4 and PD-L1/PD-L2 blockers. Therefore, our signature may help clinicians in assessing patient prognosis and developing treatment plans.

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Identification and validation a costimulatory molecule gene signature to predict the prognosis and immunotherapy response for hepatocellular carcinoma

Cited by 9 publications

References 71 publications

Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma

Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma

Prognostic costimulatory molecule-related signature risk model correlates with immunotherapy response in colon cancer

A Signature Based on Costimulatory Molecules for the Assessment of Prognosis and Immune Characteristics in Patients With Stomach Adenocarcinoma

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