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Robust rank aggregation and cibersort algorithm applied to the identification of key genes in head and neck squamous cell cancer

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2021年第4期18卷 4491-4507页

作者： Chen, Tingting Hua, Wei Xu, Bing Chen, Hui Xie, Minhao Sun, Xinchen Ge, Xiaolin Nanjing Med Univ Affiliated Hosp 1 Dept Radiat Oncol Nanjing 210000 Jiangsu Peoples R China Northern Jiangsu Peoples Hosp Dept Oncol Yangzhou 225000 Jiangsu Peoples R China Nanjing Med Univ Sch Clin Med 1 Nanjing 210000 Jiangsu Peoples R China

Objective: Although multiple hub genes have been identified in head and neck squamous cell cancer (HNSCC) in recent years, because of the limited sample size and inconsistent bioinformatics analysis methods, the results are not reliable. Therefore, it is urgent to use reliable algorithms to find new prognostic markers of HNSCC. Method: The Robust Rank Aggregation (RRA) method was used to integrate 8 microarray datasets of HNSCC downloaded from the Gene Expression Omnibus (GEO) database to screen differentially expressed genes (DEGs). Later, Gene Ontology (GO) functional annotation together with Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was carried out to discover functions of those discovered DEGs. According to the KEGG results, those discovered DEGs showed tight association with the occurrence and development of HNSCC. Then cibersort algorithm was used to analyze the infiltration of immune cells of HNSCC and we found that the main infiltrated immune cells were B cells, dendritic cells and macrophages. A protein-protein interaction (PPI) network was established;moreover, key modules were also constructed to select 5 hub genes from the whole network using cytoHubba. 3 hub genes showed significant relationship with prognosis for TCGA-derived HNSCC patients. Result: The potent DEGs along with hub genes were selected by the combined bioinformatic approach. AURKA, BIRC5 and UBE2C genes may be the potential prognostic biomarker and therapeutic targets of HNSCC. Conclusions: The Robust Rank Aggregation method and cibersort algorithm method can accurately predict the potential prognostic biomarker and therapeutic targets of HNSCC throughmultiple GEO datasets.

关键词： bioinformatics differentially expressed genes biomarkers robust rank aggregation method cibersort algorithm

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Study of the Immune Infiltration and Sonic Hedgehog Expression Mechanism in Synovial Tissue of Rheumatoid Arthritis-Related Interstitial Lung Disease under Machine Learning cibersort algorithm

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MOLECULAR BIOTECHNOLOGY 2024年 1-17页

作者： Lu, Qunqun Jiang, Yizhen Cang, Xiaofeng Pan, Jiaojiao Shen, Xiaowen Tang, Ruoyu Zhou, Zhe Zhu, Yiwen Suzhou Ninth Peoples Hosp Dept Rheumatol & Immunol Suzhou 215299 Peoples R China

Rheumatoid arthritis-related interstitial lung disease (RA-ILD) is one of the common complications in patients with RA, which affects their quality of life. The cibersort algorithm is widely employed to determine the proportion of immune cells (ICs) in diseased tissues, while the Sonic Hedgehog (Shh) signaling pathway, as an imperative regulatory factor, has also attracted attention in the pathology of RA-ILD. This work was to explore the mechanisms of RA-ILD immune infiltration and synovial tissue (ST) Shh expression based on the cibersort algorithm. The differential genes of RA-ILD were subjected to pathway enrichment analysis using R language. The content and proportion of 22 types of ICs in RA-ILD lung tissues were analyzed using machine learning-based cibersort algorithm. Meanwhile, immunoblotting was employed to detect and analyze the expression of Shh, Smoothened (Smo), and bone morphogenetic proteins (BMPs) proteins in ST samples from RA-ILD and Ctrl groups (RA patients without ILD). The hub target genes in the protein network associated with RA-ILD include BSG, CCL2, CTLA4, FGFBP1, GLI1, HHIP, HLA-DRB1, IFNAR1, IL17A, IL23A, IL-6, INPP4A, LILRB1, MUC5B, PADI4, PPM1A, PTCH1, PTPN22, RSPO4, Shh, SMO, STAT4, SUFU, TAOK2, TIMP2, and TWSG1, which are involved in multiple pathways, such as B cell regulation, transcription factors of the Shh pathway, and ST immune tolerance-related pathways. In the immunological analysis of RA-ILD using the cibersort algorithm, HLA (r = - 0.26), PTPN22 (r = - 0.36), STAT4 (r = - 0.18), IL-6 (r = - 0.17), CTLA4 (r = - 0.27), and PADI4 (r = - 0.21) were all found to exhibit negative correlations with CD4+T cells (P < 0.05). Monocytes were found to be more abundant in RA-ILD patients' serum versus the Ctrl group. Shh, Smo, and BMP expressions were drastically lower in the RA-ILD group versus Ctrl group (P < 0.05). Significant immune cell infiltration was observed in the lung tissues of RA-ILD patients. Further analysis utilizing the

关键词： cibersort algorithm RA-ILD Lung disease immune infiltration Synovial tissue Expression of Shh

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New Insights into Roles of IL-7R Gene as a Therapeutic Target Following Intracerebral Hemorrhage

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JOURNAL OF INFLAMMATION RESEARCH 2024年 17卷 399-415页

作者： Cui, Jie Wang, Hongbin Liu, Shiyao Zhao, Yiming Soochow Univ Jiangsu Inst Hematol Affiliated Hosp 1 Suzhou 215006 Peoples R China Soochow Univ Natl Clin Res Ctr Hematol Dis Affiliated Hosp 1 Suzhou 215000 Peoples R China Soochow Univ NHC Key Lab Thrombosis & Hemostasis Affiliated Hosp 1 Suzhou 215006 Peoples R China Soochow Univ Collaborat Innovat Ctr Hematol Suzhou 215006 Peoples R China Jiangyin Hosp Tradit Chinese Med Dept Gastroenterol Jiangyin 214400 Peoples R China Soochow Univ Dept Intens Care Unit Affiliated Hosp 1 Suzhou 215006 Peoples R China Soochow Univ Natl Clin Res Ctr Hematol Dis NHC Key Lab Thrombosis & Hemostasis Jiangsu Inst HematolAffiliated Hosp 1 Suzhou 215006 Peoples R China

Background: Spontaneous intracerebral hemorrhage (ICH) is a subtype of stroke leading to high rates of morbidity and mortality in adults. Recent studies showed that immune and inflammatory responses might play essential roles in secondary brain injury. The purpose of this article was to provide a reference for further therapeutic strategies for ICH patients. Methods: GSE206971 and GSE216607 datasets from the gene expression omnibus (GEO) database were used to screen the highly immune-related differentally expressed genes (IRDEGs). We used the cibersort algorithm to assess the level of immune signatures infiltration and got the possible function of IRDEGs which was analyzed through Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Protein-protein interaction (PPI) networks and six hub genes were identified in the Cytoscape plug-in. GSVA algorithm was performed to evaluate the potential pathways of six hub genes in ICH samples. The expression level of IL-7R chosen from six hub genes was further validated by Western blotting. The cell models of ICH were established for the research of IL-7/IL-7R signaling way. Results: A total of six hub genes (ITGAX, ITGAM, CCR2, CD28, SELL, and IL-7R) were identified. IL-7R was highly expressed in the mice ICH group, as shown by immunoblotting. Next, we constructed ICH cell models in RAW264.7 cells and BV2 cells. After treatment with IL-7, iNOS expression (M1 marker) was greatly inhibited while Arg-1(M2 marker) was enhanced, and it might function via the JAK3/STAT5 signaling pathway. Conclusion: The hypothesis is proposed that the IL-7/IL-7R signaling pathway might regulate the inflammatory process following ICH by regulating microglia polarization. Our study is limited and requires more in-depth experimental confirmation.

关键词： immune infiltration intracerebral hemorrhage cibersort algorithm IL-7 receptor

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CSF1R is a Prognostic Biomarker and Correlated with Immune Cell Infiltration in the Gastric Cancer Microenvironment

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PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021年 14卷 445-457页

作者： Chen, Di Xiong, Lina Zhang, Li Yu, Honglu Xu, Yushuang Wang, Mengmeng Jiang, Xin Xiong, Zhifan Huazhong Univ Sci & Technol Liyuan Hosp Tongji Med Coll Dept Gastroenterol Wuhan 430061 Peoples R China

Purpose: The tumor microenvironment (TME) plays a crucial role in the progression and prognosis of gastric cancer (GC). This study investigated TME-associated genes and explored their roles in the GC microenvironment. Methods: A total of 330 GC samples were extracted from TCGA. ESTIMATE and cibersort algorithms were utilized to evaluate the stromal and immune scores of GC samples and the fraction of 22 immune cells infiltrated in the TME. Then, the TME-related differentially expressed genes (DEGs) were determined through integrative analysis. Protein-protein interaction (PPI) network and Cox regression analysis were conducted to analyze DEGs, and CSF1R was determined as the most crucial gene. We further probed the role of CSF1R in the GC microenvironment and evaluated the prognostic value of CSF1R. Results: We identified 560 TME-related DEGs and found CSF1R associated with the development and prognosis of GC. Further analysis showed that CSF1R was involved in immune-related signaling pathways. Furthermore, cibersort analysis revealed that CSF1R expression correlated with several kinds of infiltrating immune cells, including tumor-associated macrophages (TAMs), B cells, NK cells, neutrophils, eosinophils, T cells, dendritic cells, and so on. Conclusion: In summary, CSF1R might take part in the modulation of immune-active status in the GC microenvironment and could be a promising biomarker for GC therapy and prognosis.

关键词： CSF1R gastric cancer tumor microenvironment infiltrating immune cells ESTIMATE algorithm cibersort algorithm

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Identification of immune-based prostate cancer subtypes using mRNA expression

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BIOSCIENCE REPORTS 2021年第1期41卷 p1-19页

作者： Song, Jukun Wang, Wei Yuan, Yiwen Ban, Yong Su, Jiaming Yuan, Dongbo Chen, Weihong Zhu, Jianguo Guizhou Univ Sch Med Guiyang Guizhou Peoples R China Guizhou Prov Peoples Hosp Dept Oral & Maxillofacial Surg Guiyang Guizhou Peoples R China Guizhou Prov Peoples Hosp Dept Urol Guiyang Guizhou Peoples R China Guizhou Med Univ Dept Clin Med Guiyang Guizhou Peoples R China

Immune infiltration in Prostate Cancer (PCa) was reported to be strongly associated with clinical outcomes. However, previous research could not elucidate the diversity of different immune cell types that contribute to the functioning of the immune response system. In the present study, the cibersort method was employed to evaluate the relative proportions of immune cell profiling in PCa samples, adjacent tumor samples and normal samples. Three types of molecular classification were identified in tumor samples using the 'CancerSubtypes' package of the R software. Each subtype had specific molecular and clinical characteristics. In addition, functional enrichment was analyzed in each subtype. The submap and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were also used to predict clinical response to the immune checkpoint blockade. Moreover, the Genomics of Drug Sensitivity in Cancer (GDSC) database was employed to screen for potential chemotherapeutic targets for the treatment of PCa. The results showed that Cluster I was associated with advanced PCa and was more likely to respond to immunotherapy. The findings demonstrated that differences in immune responses may be important drivers of PCa progression and response to treatment. Therefore, this comprehensive assessment of the 22 immune cell types in the PCa Tumor Environment (TEM) provides insights on the mechanisms of tumor response to immunotherapy and may help clinicians explore the development of new drugs.

关键词： cibersort algorithm Clinical application Immunotherapy Prostate cancer Tumor-infiltrating immune cells

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Identification of three molecular subtypes based on immune infiltration in ovarian cancer and its prognostic value

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BIOSCIENCE REPORTS 2020年第10期40卷 BSR20201431页

作者： Liu, Juan Tan, Zongjian He, Jun Jin, Tingting Han, Yuanyuan Hu, Li Song, Jukun Huang, Shengwen Guizhou Univ Sch Med Guiyang Peoples R China Guizhou Prov Peoples Hosp Dept Reprod Med Guiyang Peoples R China Guizhou Prov Peoples Hosp Prenatal Diag Ctr Guiyang Peoples R China Guizhou Prov Peoples Hosp Dept Oral & Maxillofacial Surg Guiyang Peoples R China Guizhou Prov Peoples Hosp NHC Key Lab Pulm Immunol Dis Guiyang Peoples R China

Background: Increasing studies suggest that tumor immune infiltration is a relative fac-tor of prognosis in ovarian cancer (OvCa). The present study explored the composition of tumor-infiltrating immune cells (TIICs) in OvCa using cibersort algorithm and further assessed their values for prognosis and therapeutic strategies by molecular subtypes. Methods: Publicly available databases including The Cancer Genome Atlas (TCGA) and GTEx were searched. Ovarian tumor samples were available from TCGA, and normal ovarian samples were obtained from the GTEx dataset. The relative proportions of immune cell profiling in OvCa and normal samples were evaluated by cibersort algorithm. Association between each immune cell subtype and survival was inferred by the fractions of 22 immune cell types. "CancerSubtypes" R-package was employed to identify the three types of molecular classification and analyze the functional enrichment in each subclass. Response to immunotherapy and anticancer drug targets was predicted via TIDE algorithm and GDSC dataset. Results: Substantial variation reflecting individual difference was identified between cancer and normal tissues in the immune infiltration profiles. T cells CD4 memory activated, macrophages M1 were associated with improved overall survival (OS) as evaluated by univariate Cox regression and multivariate Cox. Three subtypes were identified by CancerSubtypes' R-package and every sub-cluster possessed specific immune cell characterization. Meanwhile, Cluster II exhibited poor prognosis and sensitive response to immunotherapy. Conclusions: The cellular component of immune infiltration shows remarkable variation in OvCa. Profiling of immune infiltration is useful in prediction of prognosis of OvCa. The results from profiling might be considered in therapeutic modulation.

关键词： cibersort algorithm Immunotherapy Ovarian cancer Prognostic value Tumor-infiltrating immune cells

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Comprehensive Analysis of a Competing Endogenous RNA Co-Expression Network in Chronic Obstructive Pulmonary Disease

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INTERNATIONAL JOURNAL OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE 2023年 18卷 2417-2429页

作者： Wang, Jingwei Xia, Bowen Ma, Ruimin Ye, Qiao Capital Med Univ Beijing Chaoyang Hosp Beijing Inst Resp Med Beijing Peoples R China Capital Med Univ Beijing Chaoyang Hosp Clin Ctr Interstitial Lung Dis Dept Occupat Med & Toxicol Beijing Peoples R China Capital Med Univ Beijing Chao Yang Hosp Dept Urol Beijing Peoples R China Capital Med Univ Beijing Chaoyang Hosp Clin Ctr Interstitial Lung Dis Dept Occupat Med & Toxicol 8 Workers Stadium Beijing 100020 Peoples R China

Purpose: Chronic obstructive pulmonary disease (COPD) is the main cause of mortality world widely. Non-coding RNAs (lncRNAs) and associated competitive endogenous RNAs (ceRNAs) networks were recently proved to lead to mRNA gene expression down-regulation but were still unclear in COPD. This study aims to investigate and elucidate the mechanisms underlying the involvement of ceRNA co-expression networks in COPD ***: Obtained expression signature of data from the Gene Expression Omnibus database and compared the differentially expression of mRNAs and miRNAs between COPD patients and healthy smokers. Predicted the miRNA-lncRNA and miRNA- mRNA interaction using online library and employed cibersort to measure the proportions of the 22 immune cells in the COPD and control ***: Established a ceRNA-network comprising 11 lncRNAs, 5 miRNAs, and 16 mRNAs. Using the weighted correlation network analysis method, we identified hub genes and hub miRNAs and obtained one core sub-network, XIST, FGD5-AS1, KCNQ1OT1, HOXA11-AS, LINC00667, H19, PRKCQ-AS1, NUTM2A-AS1/has-mir-454-3p/ZNF678, PRRG4. COPD patients had different proportions of immune cells than controls, and these variations were associated with the magnitude of pulmonary function ***: The ceRNA-network, particularly the core sub-network, may be a putative goal for COPD, in which specific immune cells were involved.

关键词： chronic obstructive pulmonary disease competing endogenous RNA network microRNAs miRNAs cibersort algorithm gene expression omnibus

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Identification and verification of promising diagnostic biomarkers in patients with hypertrophic cardiomyopathy associate with immune cell infiltration characteristics

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LIFE SCIENCES 2021年第0期285卷 119956-119956页

作者： Zheng, Xifeng Yang, Yu Fu, Changmei Huang Huang, Ruina Guangzhou Med Univ Affiliated Hosp Dept Geriatr Guangzhou Guangdong Peoples R China Guangzhou Med Univ Affiliated Hosp Dept Cardiol 57 South Renming Rd Guangzhou 524001 Guangdong Peoples R China

Aims: To explore immune cell infiltration characteristics of, and hub genes associated with, hypertrophic cardiomyopathy (HCM). Materials and methods: The GSE130036 dataset was downloaded and the differentially expressed genes (DEGs) were identified. The DEGs were analyzed via the cibersort algorithm to understand the composition of 22 immune cell types between the HCM and normal myocardial tissue specimens. Weighted gene co-expression network analysis (WGCNA) was performed to segregate the DEGs into several modules and explore correlation between the key modules and specific immune cells enriched in the myocardial tissues of HCM patients. The biofunctional and disease enrichment of the genes among the modules was explored, and hub genes serving as potential biomarkers of HCM were identified. These genes were validated by GSE36961 dataset, and the discrimination ability was assessed by receiver operating characteristic curve analysis. Key findings: cibersort analysis showed that neutrophils and B-cells (naive and memory B-cells) were highly abundant in HCM samples, while macrophages (M0, M1, M2) were highly abundant in normal samples. WGCNA analysis of the DEGs yielded seven modules, and the gray and yellow modules were strongly associated with neutrophils and B-cells, and with macrophages, respectively. Yellow module genes were mainly functional in immune and inflammation processes. Gray module genes were mainly functional in the transportation of intercellular substances. SLITRK4 and CD163 showed a notably high area under the curve values in both datasets and may serve as potential biomarkers for HCM. Significance: SLITRK4 and CD163 may be promising Diagnostic Biomarkers of Hypertrophic Cardiomyopathy.

关键词： Diagnostic biomarkers Hypertrophic cardiomyopathy cibersort algorithm WGCNA CD163

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CD1C is associated with breast cancer prognosis and immune infiltrates

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BMC CANCER 2023年第1期23卷 129-129页

作者： Chen, Xiao Zhang, Jianzhong Lei, Xinhan Yang, Lei Li, Wanwan Zheng, Lu Zhang, Shuai Ding, Yihan Shi, Jianing Zhang, Lei Li, Jia Tang, Tong Jia, WenJun Anhui Med Univ Gen Surg Dept Hosp 2 Hefei Peoples R China Anhui Med Univ Hefei Peoples R China

BackgroundThe tumor microenvironment (TME) in breast cancer plays a vital role in occurrence, development, and therapeutic responses. However, immune and stroma constituents in the TME are major obstacles to understanding and treating breast cancer. We evaluated the significance of TME-related genes in breast *** breast cancer (BRCA) samples were retrieved from the TCGA and GEO databases. Stroma and immune scores of samples as well as the proportion of tumor infiltrating immune cells (TICs) were calculated using the ESTIMATE and cibersort algorithms. TME-related differentially expressed genes (DEGs) were analyzed by a protein interaction (PPI) network and univariate Cox regression to determine CD1C as a hub gene. Subsequently, the prognostic value of CD1C, its response to immunotherapy, and its mechanism in the TME were further *** BRCA, DEGs were determined to identify CD1C as a hub gene. The expression level of CD1C in BRCA patients was verified based on the TCGA database, polymerase chain reaction (PCR) results, and western blot analysis. Immunohistochemical staining (IHC) results revealed a correlation between prognosis, clinical features, and CD1C expression in BRCA. Enrichment analysis of GSEA and GSVA showed that CD1C participates in immune-associated signaling pathways. cibersort showed that CD1C levels were associated with tumor immune infiltrating cells (TILs), such as different kinds of T cells. Gene co-expression analysis showed that CD1C and the majority of immune-associated genes were co-expressed in BRCA. In renal cell carcinoma, patients with a high expression of CD1C had a better immunotherapy ***1C is an important part of the TME and participates in immune activity regulation in breast tumors. CD1C is expected to become a prognostic marker and a new treatment target for breast cancer.

关键词： CD1C Breast cancer Tumor microenvironment ESTIMATE algorithm cibersort algorithm

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