Identification of immunological subtypes of hepatocellular carcinoma with expression profiling of immune-modulating genes

Cao, Di; Chen, Meng-Ke; Zhou, Yufeng; Zhang, Mei‐Yin; Mai, Shi-Juan; Zhang, Yaojun; Chen, Minshan; Li, Xiaoxing; Wang, Huiyun

doi:10.18632/aging.103395

Cited by 15 publications

(14 citation statements)

References 70 publications

(84 reference statements)

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“…Multiple studies have uncovered that liver cancer cells acquire aggressive characteristics relying on a series of genome changes [ 61 – 63 ]. Tumor mutation burden (TMB) is strictly correlated to the number of neoantigens arising in a tumor and has emerged as a novel potential biomarker in ICI therapy [ 64 – 66 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma

Peng

Liu

et al. 2021

Cancer Cell Int

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Background Hepatocellular carcinoma (HCC) is one of the most prevalent and inflammation-associated cancers. The tumor microenvironment (TME) plays an essential role in HCC development and metastasis, leading to poor prognosis. The overall TME immune cells infiltration characterizations mediated by immune-related genes (IRGs) remain unclear. In this study, we aimed to investigate whether immune-related genes could be indicators for the prognosis of HCC patients and TME cell infiltration characterization as well as responses to immunotherapy. Methods We obtained differentially expressed immune-related genes (DE IRGs) between normal liver tissues and liver cancer tissues from The Cancer Genome Atlas (TCGA) database. To identify the prognostic genes and establish an immune risk signature, we performed univariable Cox regression survival analysis and the Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the DE IRGs by robust rank aggregation method. Cox regression analysis was used to identify independent prognostic factors in HCC. We estimated the immune cell infiltration in TME via CIBERSORT and immunotherapy response through TIDE algorithm. Results We constructed an immune signature and validated its predictive capability. The immune signature included 7 differentially expressed IRGs: BIRC5, CACYBP, NR0B1, RAET1E, S100A8, SPINK5, and SPP1. The univariate and multivariate cox analysis showed that the 7-IRGs signature was a robust independent prognostic factor in the overall survival of HCC patients. The 7-IRG signature was associated with some clinical features, including gender, vascular invasion, histological grade, clinical stage, T stage. We also found that the 7-IRG signature could reflect the infiltration characterization of different immunocytes in the tumor microenvironment (TME) and had a good correlation with immune checkpoint molecules, revealing that the poor prognosis might be partly due to immunosuppressive TME. The Tumour Immune Dysfunction and Exclusion (TIDE) analysis data showed that the 7-IRG signature had great potential for indicating the immunotherapy response in HCC patients. The mutation analysis demonstrated a significant difference in the tumor mutation burden (TMB) between the high- and low-risk groups, partially explaining this signature's predictive value. Conclusion In a word, we constructed and validated a novel, immune-related prognostic signature for HCC patients. This signature could effectively indicate HCC patients' survival and immunotherapy response. And it might act as potential immunotherapeutic targets for HCC patients.

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Section: Discussionmentioning

confidence: 99%

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma

Peng

Liu

et al. 2021

Cancer Cell Int

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“…In recent years, more and more research has focused on the importance of the tumor microenvironment in driving malignancy, including in digestive system tumors ( 9 – 12 ). Most of the previous studies have only focused on tumor cells themselves and their internal mechanisms, but mutual communication and regulation exist between tumor cells and other components of their microenvironment ( 13 – 15 ).…”

Section: Introductionmentioning

confidence: 99%

Re-Clustering and Profiling of Digestive System Tumors According to Microenvironment Components

Wang¹,

Guo²,

Chen³

et al. 2021

Front. Oncol.

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BackgroundImmunotherapy has become the most promising therapy in digestive system tumors besides conventional chemotherapy and radiotherapy. But only a few patients can benefit from different types of immunotherapies, such as immune checkpoint blockade (ICB). To identify these ICB-susceptible patients, methods are urgently needed to screen and profile subgroups of patients with different responsiveness to ICB.MethodsThis study carried out analysis on patients with digestive system tumors that were obtained from Cancer Genome Atlas (TCGA) cohorts. The analyses were mainly performed using GraphPad Prism 7 and R language.ResultsWe have quantified the microenvironmental components of eight digestive system tumor patients in TCGA cohorts and evaluated their clinical value. We re-clustered patients based on their microenvironment composition and divided these patients into six clusters. The differences between these six clusters were profiled, including survival conditions, enriched biological processes, genomic mutations, and microenvironment traits. Cluster 3 was the most immune-related cluster, exhibiting a high infiltration of non-tumor components and poor survival status, along with an inhibitory immune status, and we found that patients with high stromal score indicated a poor response in ICB cohort.ConclusionsOur research provides a new strategy based on the microenvironment components for the reclassification of digestive system tumors, which could provide guidance for prognosis judgment and treatment response prediction like ICB.

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“…Currently, there is no detailed classification available for accurate prognostic evaluation and effective treatment. Various tumor scores and immunotypes are based on immune cell infiltration in the tumor, has and have been used in liver cancer and are effective in evaluating prognosis of patients (Maecker et al, 2012;Cao et al, 2020). However, no studies have explored tumor scores in TNBC patients.…”

Section: Discussionmentioning

confidence: 99%

Identification of Immune-Related Risk Characteristics and Prognostic Value of Immunophenotyping in TNBC

Shuang

Zhong

et al. 2021

Front. Genet.

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Background: Triple-negative breast cancer (TNBC) is not sensitive to targeted therapy with HER-2 monoclonal antibody and endocrine therapy due to lack of ER, PR, and HER-2 receptors. TNBC is a breast cancer subtype with the worst prognosis and the highest mortality rate compared with other subtypes.Materials and Methods: Breast cancer-related data were retrieved from The Cancer Genome Atlas (TCGA) database, and 116 cases of triple-negative breast cancer were identified from the data. GSE31519 dataset was retrieved from Gene Expression Omnibus (GEO) database, comprising a total of 68 cases with TNBC. Survival analysis was performed based on immune score, infiltration score and mutation score to explore differences in prognosis of different immune types. Analysis of differentially expressed genes was conducted and GSEA analysis based on these genes was conducted to explore the potential mechanism.Results: The findings showed that comprehensive immune typing is highly effective and accurate in assessing prognosis of TNBC patients. Analysis showed that MMP9, CXCL9, CXCL10, CXCL11 and CD7 are key genes that may affect immune typing of TNBC patients and play an important role in prediction of prognosis in TNBC patients.Conclusion: The current study presents an evaluation system based on immunophenotyping, which provides a more accurate prognostic evaluation tool for TNBC patients. Differentially expressed genes can be targeted to improve treatment of TNBC.

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Identification of immunological subtypes of hepatocellular carcinoma with expression profiling of immune-modulating genes

Cited by 15 publications

References 70 publications

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma

Re-Clustering and Profiling of Digestive System Tumors According to Microenvironment Components

Identification of Immune-Related Risk Characteristics and Prognostic Value of Immunophenotyping in TNBC

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