4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      8-Gene signature related to CD8 + T cell infiltration by integrating single-cell and bulk RNA-sequencing in head and neck squamous cell carcinoma

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background: CD8 + T cells, a critical component of the tumor immune microenvironment, have become a key target of cancer immunotherapy. Considering the deficiency of robust biomarkers for head and neck squamous cell carcinoma (HNSCC), this study aimed at establishing a molecular signature associated with CD8+T cells infiltration.

          Methods: Single-cell RNA sequencing data retrieved from the Gene Expression Omnibus (GEO) database was analyzed to obtain the different cell types. Next, the cell proportions were investigated through deconvolution of RNA sequencing in the Cancer Genome Atlas (TCGA) database, and then the immune-related genes (IRGs) were identified by weighted gene co-expression network analysis (WGCNA). LASSO-Cox analysis was employed to establish a gene signature, followed by validation using a GEO dataset. Finally, the molecular and immunological properties, and drug responses between two subgroups were explored by applying “CIBERSORT”, “ESTIMATE”, and single sample gene set enrichment analysis (ssGSEA) methods.

          Results: A total of 215 differentially expressed IRGs were identified, of which 45 were associated with the overall survival of HNSCC. A risk model was then established based on eight genes, including DEFB1, AICDA, TYK2, CCR7, SCARB1, ULBP2, STC2, and LGR5. The low-risk group presented higher infiltration of memory activated CD4 + T cells, CD8 + T cells, and plasma cells, as well as a higher immune score, suggesting that they could benefit more from immunotherapy. On the other hand, the high-risk group showed higher abundance of activated mast cells and M2 macrophages, as well as a lower immune score.

          Conclusion: It was evident that the 8-gene signature could accurately predict HNSCC prognosis and thus it may serve as an index for clinical treatment.

          Related collections

          Most cited references48

          • Record: found
          • Abstract: found
          • Article: not found

          Cancer statistics, 2020

          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            WGCNA: an R package for weighted correlation network analysis

            Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Robust enumeration of cell subsets from tissue expression profiles

              We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen, and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content, and closely related cell types. CIBERSORT should enable large-scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu).
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                22 July 2022
                2022
                : 13
                : 938611
                Affiliations
                [1] 1 Department of Oral and Maxillofacial Surgery , Tianjin Medical University School and Hospital of Stomatology , Tianjin, China
                [2] 2 Department of Prosthodontics , Tianjin Medical University School and Hospital of Stomatology , Tianjin, China
                Author notes

                Edited by: Geng Chen, GeneCast Biotechnology Co., Ltd., China

                Reviewed by: Qingjia Chi, Wuhan University of Technology, China

                Ting Li, National Center for Toxicological Research (FDA), United States

                *Correspondence: Jian Zhang, zj301doctor@ 123456126.com

                This article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics

                Article
                938611
                10.3389/fgene.2022.938611
                9355512
                35938006
                4d5e223f-e995-4447-b057-60991239eaa6
                Copyright © 2022 Zhang, Zhang and Zhang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 May 2022
                : 04 July 2022
                Categories
                Genetics
                Original Research

                Genetics
                cd8+ t cells,head and neck squamous cell carcinoma,immunotherapy,prognosis,weighted gene co-expression network analysis

                Comments

                Comment on this article

                scite_

                Similar content176

                Cited by3

                Most referenced authors1,769