Seven immune‐related genes prognostic power and correlation with tumor‐infiltrating immune cells in hepatocellular carcinoma

Liu, Tiantian; Wu, Hao; Qi, Jianni; Qin, Chengyong; Zhu, Qing

doi:10.1002/cam4.3406

Cited by 28 publications

(20 citation statements)

References 57 publications

(116 reference statements)

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“…Next, we compared the performance of our established risk model with those of four other prognostic models: the seven immune-related–gene signature ( Liu et al, 2020 ), the twelve-gene signature ( Ouyang et al, 2020 ), the HCC prognostic evaluation model ( Zhang et al, 2020 ), and another HCC immune signature ( Pan et al, 2020 ) published in recent years ( Table 1 ).…”

Section: Resultsmentioning

confidence: 99%

Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma

Yang

et al. 2021

Front. Mol. Biosci.

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Background: Hepatocellular carcinoma (HCC) is one of the highly heterogeneous cancers that lacks an effective risk model for prognosis prediction. Therefore, we searched for angiogenesis-related immune genes that affected the prognosis of HCC to construct a risk model and studied the role of this model in HCC.Methods: In this study, we collected the transcriptome data of HCC from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. Pearson correlation analysis was performed to identify the association between immune genes and angiogenesis-related genes. Consensus clustering was applied to divide patients into clusters A and B. Subsequently, we studied the differentially expressed angiogenesis-related immune genes (DEari-genes) that affected the prognosis of HCC. The most significant features were identified by least absolute shrinkage and selection operator (LASSO) regression, and a risk model was constructed. The reliability of the risk model was evaluated in the TCGA discovery cohort and the ICGC validation cohort. In addition, we compared the novel risk model to the previous models based on ROC analysis. ssGSEA analysis was used for function evaluation, and pRRophetic was utilized to predict the sensitivity of administering chemotherapeutic agents.Results: Cluster A patients had favorable survival rates. A total of 23 DEari-genes were correlated with the prognosis of HCC. A five-gene (including BIRC5, KITLG, PGF, SPP1, and SHC1) signature-based risk model was constructed. After regrouping the HCC patients by the median score, we could effectively discriminate between them based on the adverse survival outcome, the unique tumor immune microenvironment, and low chemosensitivity.Conclusion: The five-gene signature-based risk score established by ari-genes showed a promising clinical prediction value.

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Section: Resultsmentioning

confidence: 99%

Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma

Yang

et al. 2021

Front. Mol. Biosci.

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“…Timedependent ROC curves were constructed, and AUC values for 1 and 3 years were calculated. In addition, we conducted a hierarchical analysis to evaluate whether the relationship between the risk score models and OS was independent of clinical risk factors (16).…”

Section: Construction Of a Risk Score Model For Five Immune-related Lncrnasmentioning

confidence: 99%

Bioinformatics Profiling of Five Immune-Related lncRNAs for a Prognostic Model of Hepatocellular Carcinoma

Wei

Liu

et al. 2021

Front. Oncol.

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Hepatocellular carcinoma (HCC), one of the most common tumors worldwide, has the fifth highest mortality rate, which is increasing every year. At present, many studies have revealed that immunotherapy has an important effect on many malignant tumors. The main purpose of our research was to verify and establish a new immune-related lncRNA model and to explore the potential immune mechanisms. We analysed the pathways and mechanisms of immune-related lncRNAs by bioinformatics analysis, screened key lncRNAs based on Cox regression analysis, and determined the characteristics of the immune-related lncRNAs. On this basis, a predictive model was established. Through a comparison of specificity and sensitivity, we found that the constructed model was superior to the known markers of HCC. Then, the cell types were identified by the relative subgroup (CIBERSORT) algorithm for RNA transcripts. A signature model was eventually constructed, and we proved that it was a survival factor for HCC. Moreover, five kinds of immune cells were significantly positively correlated with the signature. The results indicated that these five kinds of lncRNAs may be related to the immune infiltration of hepatocellular carcinoma. To verify these findings, we selected the top coexpressed lncRNA, AC099850.3, for further study. We found that AC099850.3 could promote the migration and proliferation of hepatocellular carcinoma cells in vitro. RT-PCR experiments found that AC099850.3 could promote the expression of the cell cycle molecules BUB1, CDK1, PLK1, and TTK, and western blotting to prove that the expression of the molecules CD155 and PD-L1 was inhibited in the interference group. In conclusion, we used five kinds of immune-related lncRNAs to construct prognostic signatures to explore the mechanism, which provides a new way to study therapies for HCC.

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“…In addition, the prognostic efficacy of IRGs is closely related to the tumor immune microenvironment (TIME) and studies have reported that an IRG-immunocyte-TIME interaction network plays a crucial role in tumorigenesis and progression 10,11 . Various prognostic signatures based on IRGs have recently been constructed to predict the prognosis of patients with cancer and have proven to effectively predict OS and aid the exploration of novel biomarkers [12][13][14] . Recently, few reliable prognostic signatures have been reported in patients with pancreatic cancer and the mechanisms underlying IRGs have been confirmed.…”

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confidence: 99%

Up-regulation of S100P predicts the poor long-term survival and construction of prognostic signature for survival and immunotherapy in patients with pancreatic cancer

Zou

Wang

et al. 2021

Bioengineered

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Pancreatic cancer is associated with a high mortality rate, and the prognosis is positively related to immune status. In this study, we constructed a prognostic signature from survival-and immunerelated genes (IRGs) to guide treatment and assess prognosis of patients with pancreatic cancer. The transcriptomic data were obtained from The Cancer Genome Atlas (TCGA) database, and IRGs were extracted from the ImmPort database. Univariate and LASSO regression analysis were used to obtain survival-related IRGs. Finally, the prognostic signature was constructed using multivariate regression analysis. The laboratory experiments were conducted to verify the key IRG expression. Immune cells infiltration was analyzed using the CIBERSORT algorithm and TIMER database. Prognostic signature containing four IRGs (ADA2, TLR1, PTPN6, S100P) was constructed with good predictive performance; in particular, S100P played a significant role in the immune microenvironment, and tumorigenesis of pancreatic cancer. Moreover, we found that CD8 + T cell and activated CD4 + memory T cell tumor infiltration was lower in the high-risk group, while high-risk score correlated positively with higher tumor mutational burden, and the higher half inhibitory centration 50 of chemotherapeutic agents Docetaxel and Sunitinib. In summary, this study identified and constructed an immune-related prognostic signature that can predict overall survival, besides suggests that S100P was a novel immune-related biomarker. We hope that this signature will aid the identification of new biomarkers for the individualized immunotherapy of pancreatic cancer.

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Seven immune‐related genes prognostic power and correlation with tumor‐infiltrating immune cells in hepatocellular carcinoma

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 28 publications

References 57 publications

Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma

Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma

Bioinformatics Profiling of Five Immune-Related lncRNAs for a Prognostic Model of Hepatocellular Carcinoma

Up-regulation of S100P predicts the poor long-term survival and construction of prognostic signature for survival and immunotherapy in patients with pancreatic cancer

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