Comprehensive immunogenomic landscape analysis of prognosis-related genes in head and neck cancer

Li, Lei; Wang, Xiaoli; Lei, Qian; Sun, Chuanzheng; Xi, Yan; Chen, Ran; He, Yongming

doi:10.1038/s41598-020-63148-8

Cited by 31 publications

(30 citation statements)

References 55 publications

(50 reference statements)

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“…Through univariate Cox analysis, we found that 236 IRGs were closely related to the OS of HNSCC patients, indicating that IRGs are very important for the prognosis of HNSCC patients. CCL26, SEMA3G, DKK1, GAST, GNRH1, PDGFA, and ZAP70 genes are related to the OS of HNSCC, which is consistent with the results of Li et al (2020). Analysis of gene function enrichment showed that these prognoses related to immune genes were mainly involved in the interaction of cytokine-cytokine receptor interactions and the nuclear factor (NF)-κB signaling pathway.…”

Section: Discussionsupporting

confidence: 85%

“…In the middle of the last century, Burnt and Thomas proposed the theory of immune surveillance, which suggests that the immune system of the host can recognize precursors of cancer and, in most cases, destroy these precursors before they become clinically apparent (Li et al, 2020). After attack by the innate immune system, tumor antigens (TAs) are released and captured by antigen-presenting cells (APCs) and then processed and loaded onto the major histocompatibility complex (MHC), activating effector T cells.…”

Section: Introductionmentioning

confidence: 99%

“…After attack by the innate immune system, tumor antigens (TAs) are released and captured by antigen-presenting cells (APCs) and then processed and loaded onto the major histocompatibility complex (MHC), activating effector T cells. However, cancer cells can create an immunosuppressive microenvironment through manipulation of their own immunogenicity, production of immunosuppressive mediators, and promotion of immunomodulatory cell types, leading to immune tolerance and escape (Li et al, 2020). Therefore, immune normalization treatments and cancer immunotherapy have been major drivers of personalized medicine, with aggressive efforts to leverage the immune system to fight tumors (Sanmamed and Chen, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Development of an Immunogenomic Landscape-Based Prognostic Index of Head and Neck Squamous Cell Carcinoma

Long

Zhang

Zeng

et al. 2020

Front. Mol. Biosci.

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Head and neck squamous cell carcinoma (HNSCC) is the eighth leading cancer by incidence worldwide, with approximately 700,000 new cases in 2018 (accounting for 11% of all cancers). The occurrence and development of tumors are closely related to the immunological function of the body and sensitivity to treatment schemes as well as prognosis. It is urgent for clinicians to systematically study patients’ immune gene maps to help select a treatment plan and analyze the potential to cure HNSCC. Here, the transcriptomic data of HNSCC samples were downloaded from The Cancer Genome Atlas (TCGA), and 4,793 genes differentially expressed in normal and cancer tissues of HNSCC were identified, including 1,182 downregulated and 3,611 upregulated genes. From these genes, 400 differentially expressed immune-related genes (IRGs) were extracted, including 95 downregulated genes and 305 upregulated genes. The prognostic values of IRGs were evaluated by univariate Cox analysis, and 236 genes that were significantly related to the overall survival (OS) of patients were identified. The signaling pathways that play roles in the prognosis of IRGs were investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and the expression profiles of IRGs and OS in 499 HNSCC patients based on TCGA dataset were integrated. Potential molecular mechanisms and characteristics of these HNSCC-specific IRGs were further explored with the help of a new prognostic index based on IRGs developed by least absolute shrinkage and selection operator (LASSO) Cox analysis. A total of 64 hub genes (IRGs associated with prognosis) were markedly associated with the clinical outcome of HNSCC patients. KEGG functional enrichment analysis revealed that these genes were actively involved in several pathways, e.g., cytokine–cytokine receptor interaction, T-cell receptor signaling, and natural killer cell-mediated cytotoxicity. IRG-based prognostic signatures performed moderately in prognostic predictions. Interestingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells. These data screened several IRGs of clinical significance and revealed drivers of the immune repertoire, demonstrating the importance of a personalized IRG-based immune signature in the recognition, surveillance, and prognosis of HNSCC.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development of an Immunogenomic Landscape-Based Prognostic Index of Head and Neck Squamous Cell Carcinoma

Long

Zhang

Zeng

et al. 2020

Front. Mol. Biosci.

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“…In addition, the researchers revealed a moderate association between the immune checkpoints that contained PD-1, CTLA-4, IDO, and TIGIT and such signature. Li et al [26] used RNA-seq data from 527 head and neck cancer patients from the TCGA database to establish a prognostic prediction model using multivariable Cox regression analysis. Finally, they identi ed a 10-IRG signature including SEMA3G, GNRH1, ZAP70, PLAU, SFTPA2, CCL26, DKK1,…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of An Immune-Related Gene Pair Signature in Skin Cutaneous Melanoma

Xie¹,

Dong²,

Jiang

et al. 2020

Preprint

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Skin cutaneous melanoma (SKCM) is a common skin malignancy worldwide, and its metastasis and mortality rates are high. The molecular characteristics exhibited by tumor-immune interactions have drawn the attention from researchers. Therefore, increased knowledge and new strategies to identify effective immune-related biomarkers may improve the clinical management of SKCM by providing more accurate prognostic information. In this study, we established a prognostic immune-related gene pair (IRGP) signature for predicting the survival of SKCM patients. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided gene expression profiles together with clinical information, and the samples were randomly divided into three groups including the training, testing, and validation datasets. The regression model of least absolute shrinkage and selection operator (LASSO) helped to identify a 13-IRGP signature with a significant relation to the survival of SKCM patients. The training, TCGA, and independent sets have an average value of area under the curve of 0.79, 0.76, and 0.82, respectively. In addition, this 13-IRGP signature can noticeably divide SKCM patients into high-risk group and low-risk group with significantly different prognoses. Many biological activities such as gene family were enriched among the genes in our IRGP signature. While analyzing the risk signature and clinical characteristics, there was a large difference in the risk score between T stage and tumor stage grouping. Finally, we constructed a nomogram and forest plots of the risk score and clinical features. In summary, we developed a robust 13-IRGP prognostic signature in SKCM, which can identify and provide new insights into immunological biomarkers.

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“… 14 In addition, the researchers revealed a moderate association between the immune checkpoints that contained PD-1, CTLA-4, IDO, and TIGIT and such signature. Li et al, 31 used RNA-seq data from 527 head and neck cancer patients from the TCGA database to establish a prognostic prediction model using multivariable Cox regression analysis. Finally, they identified a 10-IRG signature including SEMA3G, GNRH1, ZAP70, PLAU, SFTPA2, CCL26, DKK1, GAST, PDGFA and STC1.…”

Section: Discussionmentioning

confidence: 99%

<p>Development and Validation of an Immune-Related Gene Pair Signature in Skin Cutaneous Melanoma</p>

Xie¹,

Dong²,

Jiang³

et al. 2020

CCID

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Introduction Skin cutaneous melanoma (SKCM) is a common skin malignancy worldwide, and its metastasis and mortality rates are high. The molecular characteristics exhibited by tumor–immune interactions have drawn the attention from researchers. Therefore, increased knowledge and new strategies to identify effective immune-related biomarkers may improve the clinical management of SKCM by providing more accurate prognostic information. Patients and Methods In this study, we established a prognostic immune-related gene pair (IRGP) signature for predicting the survival of SKCM patients. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided gene expression profiles together with clinical information, and the samples were randomly divided into three groups including the training, testing, and validation datasets. The regression model of least absolute shrinkage and selection operator (LASSO) helped to identify a 13-IRGP signature with a significant relation to the survival of SKCM patients. Results The training, TCGA, and independent sets have an average value of area under the curve of 0.79, 0.76, and 0.82, respectively. In addition, this 13-IRGP signature can noticeably divide SKCM patients into high-risk group and low-risk group with significantly different prognoses. Many biological activities such as gene family were enriched among the genes in our IRGP signature. While analyzing the risk signature and clinical characteristics, there was a large difference in the risk score between T stage and tumor stage grouping. Finally, we constructed a nomogram and forest plots of the risk score and clinical features. Conclusion In summary, we developed a robust 13-IRGP prognostic signature in SKCM, which can identify and provide new insights into immunological biomarkers.

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Comprehensive immunogenomic landscape analysis of prognosis-related genes in head and neck cancer

Cited by 31 publications

References 55 publications

Development of an Immunogenomic Landscape-Based Prognostic Index of Head and Neck Squamous Cell Carcinoma

Development of an Immunogenomic Landscape-Based Prognostic Index of Head and Neck Squamous Cell Carcinoma

Development and Validation of An Immune-Related Gene Pair Signature in Skin Cutaneous Melanoma

<p>Development and Validation of an Immune-Related Gene Pair Signature in Skin Cutaneous Melanoma</p>

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