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Yue Y, Zhang Q, Sun Z. CX3CR1 Acts as a Protective Biomarker in the Tumor Microenvironment of Colorectal Cancer. Front Immunol 2022; 12:758040. [PMID: 35140706 PMCID: PMC8818863 DOI: 10.3389/fimmu.2021.758040] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 12/28/2021] [Indexed: 12/12/2022] Open
Abstract
The tumor microenvironment (TME) plays an important role in the pathogenesis of many cancers. We aimed to screen the TME-related hub genes of colorectal adenoma (CRAD) and identify possible prognostic biomarkers. The gene expression profiles and clinical data of 464 CRAD patients in The Cancer Genome Atlas (TCGA) database were downloaded. The Estimation of STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm was performed to calculate the ImmuneScore, StromalScore, and EstimateScore. Thereafter, differentially expressed genes (DEGs) were screened. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein–protein interaction (PPI) analysis were performed to explore the roles of DEGs. Furthermore, univariate and multivariate Cox analyses were accomplished to identify independent prognostic factors of CRAD. CX3CR1 was selected as a hub gene, and the expression was confirmed in colorectal cancer (CRC) patients and cell lines. The correlations between CX3CR1 and tumor-infiltrating immune cells were estimated by Tumor IMmune Estimation Resource database (TIMER) and CIBERSORT analysis. Besides, we investigated the effects of coculture with THP-1-derived macrophages with HCT8 cells with low CX3CR1 expression on immune marker expression, cell viability, and migration. There were significant differences in the ImmuneScore and EstimateScore among different stages. Patients with low scores presented significantly lower lifetimes than those in the high-score group. Moreover, we recognized 1,578 intersection genes in ImmuneScore and StromalScore, and these genes were mainly enriched in numerous immune-related biological processes. CX3CR1 was found to be associated with immune cell infiltration levels, immune marker expression, and macrophage polarization. Simultaneous silencing of CX3CR1 and coculture with THP-1 cells further regulated macrophage polarization and promoted the cell proliferation and migration of CRC cells. CX3CR1 was decreased in CRAD tissues and cell lines and was related to T and N stages, tumor differentiation, and prognosis. Our results suggest that CX3CR1 contributes to the recruitment and regulation of immune-infiltrating cells and macrophage polarization in CRC and TAM-induced CRC progression. CX3CR1 may act as a prognostic biomarker in CRC.
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Affiliation(s)
- Yuanyi Yue
- Department of Gastroenterology Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qiang Zhang
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zhengrong Sun
- BioBank, Shengjing Hospital of China Medical University, Shenyang, China
- *Correspondence: Zhengrong Sun,
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2
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Yuan L, Zhang X, Cheng K, Li L, Guo Z, Zeng L. IRF1 Inhibits Autophagy-Mediated Proliferation of Colorectal Cancer via Targeting ATG13. Cancer Invest 2021; 40:35-45. [PMID: 34313498 DOI: 10.1080/07357907.2021.1961265] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
IRF1 is a nuclear transcription factor that mediates interferon effects and appears to have anti-tumor activity. To determine the roles of IRF1 in colorectal cancer (CRC), we investigated the effects of IRF1 in CRC cells. We found that IRF1 inhibit cell proliferation and tumor growth. Under starvation conditions, IRF1 enhanced apoptosis and reduced autophagic flux. ATG13, an important factor of autophagy complex, was confirmed as a target of IRF1. These findings indicated that IRF1 function as a tumor suppressor in CRC and inhibit autophagy through ATG13, targeting this pathway may provide new insights into the molecular mechanisms of CRC progression.
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Affiliation(s)
- Li Yuan
- Department of Pathology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Xiao Zhang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Cheng
- Department of Pathology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Liping Li
- Department of Pathology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Zhongming Guo
- Department of Pathology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Liang Zeng
- Department of Pathology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
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3
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Shi D, Mu S, Pu F, Zhong B, Hu B, Liu J, He T, Zhang Z, Shao Z. Development of a Novel Immune Infiltration-Related ceRNA Network and Prognostic Model for Sarcoma. Front Cell Dev Biol 2021; 9:652300. [PMID: 34277600 PMCID: PMC8281254 DOI: 10.3389/fcell.2021.652300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 06/01/2021] [Indexed: 12/13/2022] Open
Abstract
Due to the rarity and heterogeneity, it is challenging to explore and develop new therapeutic targets for patients with sarcoma. Recently, immune cell infiltration in the tumor microenvironment (TME) was widely studied, which provided a novel potential approach for cancer treatment. The competing endogenous RNA (ceRNA) regulatory network has been reported as a critical molecular mechanism of tumor development. However, the role of the ceRNA regulatory network in the TME of sarcoma remains unclear. In this study, gene expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) sarcoma datasets, and an immune infiltration-related ceRNA network was constructed, which comprised 14 lncRNAs, 13 miRNAs, and 23 mRNAs. Afterward, we constructed an immune infiltration-related risk score model based on the expression of IRF1, MFNG, hsa-miR-940, and hsa-miR-378a-5p, presenting a promising performance in predicting the prognosis of patients with sarcoma.
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Affiliation(s)
- Deyao Shi
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Molecular Oncology Laboratory, Department of Orthopaedic Surgery and Rehabilitation Medicine, The University of Chicago Medical Center, Chicago, IL, United States
| | - Shidai Mu
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Feifei Pu
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Binlong Zhong
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Binwu Hu
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianxiang Liu
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tongchuan He
- Molecular Oncology Laboratory, Department of Orthopaedic Surgery and Rehabilitation Medicine, The University of Chicago Medical Center, Chicago, IL, United States
| | - Zhicai Zhang
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zengwu Shao
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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4
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Liu S, Zeng F, Fan G, Dong Q. Identification of Hub Genes and Construction of a Transcriptional Regulatory Network Associated With Tumor Recurrence in Colorectal Cancer by Weighted Gene Co-expression Network Analysis. Front Genet 2021; 12:649752. [PMID: 33897765 PMCID: PMC8058478 DOI: 10.3389/fgene.2021.649752] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 03/15/2021] [Indexed: 12/26/2022] Open
Abstract
Tumor recurrence is one of the most important risk factors that can negatively affect the survival rate of colorectal cancer (CRC) patients. However, the key regulators dictating this process and their exact mechanisms are understudied. This study aimed to construct a gene co-expression network to predict the hub genes affecting CRC recurrence and to inspect the regulatory network of hub genes and transcription factors (TFs). A total of 177 cases from the GSE17536 dataset were analyzed via weighted gene co-expression network analysis to explore the modules related to CRC recurrence. Functional annotation of the key module genes was assessed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein and protein interaction network was then built to screen hub genes. Samples from the Cancer Genome Atlas (TCGA) were further used to validate the hub genes. Construction of a TFs-miRNAs–hub genes network was also conducted using StarBase and Cytoscape approaches. After identification and validation, a total of five genes (TIMP1, SPARCL1, MYL9, TPM2, and CNN1) were selected as hub genes. A regulatory network of TFs-miRNAs-targets with 29 TFs, 58 miRNAs, and five hub genes was instituted, including model GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. In conclusion, the identification of these hub genes and the prediction of the Regulatory relationship of TFs-miRNAs-hub genes may provide a novel insight for understanding the underlying mechanism for CRC recurrence.
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Affiliation(s)
- Shengwei Liu
- Department of Pharmacy, Yongchuan Hospital of Chongqing Medical University, Chongqing, China.,Chongqing Key Laboratory of Biochemistry and Molecular Pharmacology, School of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Fanping Zeng
- Department of Pharmacy, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Guangwen Fan
- Department of Pharmacy, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Qiyong Dong
- Department of Pharmacy, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
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Kim Y, Kang JW, Kang J, Kwon EJ, Ha M, Kim YK, Lee H, Rhee JK, Kim YH. Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT. Oncoimmunology 2021; 10:1904573. [PMID: 33854823 PMCID: PMC8018482 DOI: 10.1080/2162402x.2021.1904573] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 02/22/2021] [Accepted: 03/13/2021] [Indexed: 01/13/2023] Open
Abstract
The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered from the publicly accessible data of patients with head and neck cancer in The Cancer Genome Atlas (TCGA) using hierarchical clustering where patients were regrouped into binary risk groups based on the clustering-measuring scores and survival patterns associated with individual groups. Based on this analysis, clinically reasonable differences were identified in 16 out of 22 TIL fractions between groups. A deep neural network classifier was trained using the TIL fraction patterns. This internally validated classifier was used on another individual ORCA dataset from the International Cancer Genome Consortium data portal, and patient survival patterns were precisely predicted. Seven common differentially expressed genes between the two risk groups were obtained. This new approach confirms the importance of TILs in the TME and provides a direction for the use of a novel deep-learning approach for cancer prognosis.
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Affiliation(s)
- Yeongjoo Kim
- Interdisplinary Program of Genomic Science, Pusan National University, Yangsan, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Ji Wan Kang
- Interdisplinary Program of Genomic Science, Pusan National University, Yangsan, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Junho Kang
- Interdisplinary Program of Genomic Science, Pusan National University, Yangsan, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Eun Jung Kwon
- Interdisplinary Program of Genomic Science, Pusan National University, Yangsan, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Mihyang Ha
- Interdisplinary Program of Genomic Science, Pusan National University, Yangsan, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Yoon Kyeong Kim
- Interdisplinary Program of Genomic Science, Pusan National University, Yangsan, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Hansong Lee
- Interdisplinary Program of Genomic Science, Pusan National University, Yangsan, Republic of Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Je-Keun Rhee
- School of Systems Biomedical Science, Soongsil University, Seoul, Republic of Korea
| | - Yun Hak Kim
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea
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Huang S, Song Z, Zhang T, He X, Huang K, Zhang Q, Shen J, Pan J. Identification of Immune Cell Infiltration and Immune-Related Genes in the Tumor Microenvironment of Glioblastomas. Front Immunol 2020; 11:585034. [PMID: 33193404 PMCID: PMC7606992 DOI: 10.3389/fimmu.2020.585034] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Accepted: 09/28/2020] [Indexed: 12/20/2022] Open
Abstract
Glioblastoma (GBM) is one of the most prevalent malignant brain tumors with poor prognosis. Increasing evidence has revealed that infiltrating immune cells and other stromal components in the tumor microenvironment (TME) are associated with prognosis of GBM. The aim of the present study was to identify immune cells and immune-related genes extracted from TME in GBM. RNA-sequencing and clinical data of GBM were downloaded from The Cancer Genome Atlas (TCGA). Four survival-related immune cells were identified via Kaplan-Meier survival analysis and immune-related differentially expressed genes (DEGs) screened. Functional enrichment and protein-protein interaction (PPI) networks for the genes were constructed. In addition, we identified 24 hub genes and the expressions of 6 of the genes were significantly associated with prognosis of GBM. Finally, the genes were validated in single-cell sequencing studies of GBM, and the immune cells validated in an independent GBM cohort from the Chinese Glioma Genome Atlas (CGGA). Overall, 24 immune-related genes infiltrating the tumor microenvironment were identified in the present study, which could serve as novel biomarkers and immune therapeutic targets.
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Affiliation(s)
- Sicong Huang
- Department of Neurosurgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zijun Song
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Tiesong Zhang
- Department of Neurosurgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xuyan He
- The First Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Kaiyuan Huang
- Department of Neurosurgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qihui Zhang
- Department of Neurology, Dong Fang Hospital, Beijing University of Chinese Medicine, Beijing, China.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Jian Shen
- Department of Neurosurgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianwei Pan
- Department of Neurosurgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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