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Qian Z, Shang D, Fan L, Zhang J, Ji L, Chen K, Zhao R. Heterogeneity analysis of the immune microenvironment in laryngeal carcinoma revealed potential prognostic biomarkers. Hum Mol Genet 2021; 31:1487-1499. [PMID: 34791236 DOI: 10.1093/hmg/ddab332] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 11/08/2021] [Accepted: 11/08/2021] [Indexed: 11/14/2022] Open
Abstract
Laryngeal squamous cell cancer (LSCC) is the second most prevalent malignancy occurring in the head and neck with a high incidence and mortality rate. Immunotherapy has recently become an emerging treatment for cancer. It is therefore essential to explore the role of tumour immunity in laryngeal cancer. Our study first delineated and evaluated the comprehensive immune infiltration landscapes of the tumour microenvironment in LSCC. A hierarchical clustering method was applied to classify the LSCC samples into two groups (high- and low-infiltration groups). We found that individuals with low immune infiltration characteristics had significantly better survival than those in the high-infiltration group, possibly because of the elevated infiltration of immune suppressive cells, such as regulatory T cells and myeloid-derived suppressor cells (MDSCs), in the high-infiltration group. Differentially expressed genes (DEGs) between two groups were involved in some immune-related terms, such as antigen processing and presentation. A univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis were performed to identify an immune gene-set-based prognostic signature (IBPS) to assess the risk of LSCC. The prognostic model comprising six IBPSs was successfully verified to be robust in different cohorts. The expression of the six IBPSs was detected by immunohistochemistry (IHC) in 110 cases of LSCC. In addition, different inflammatory profiles and immune checkpoint landscape of LSCC were found between two groups. Hence, our model could serve as a candidate immunotherapeutic biomarker and potential therapeutic target for laryngeal cancer.
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Affiliation(s)
- Zhipeng Qian
- The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, PR China.,College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Desi Shang
- The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, PR China.,College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Lin Fan
- Department of Otolaryngology-Head and Neck Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jiarui Zhang
- Department of Otolaryngology-Head and Neck Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Linhao Ji
- Department of Otolaryngology-Head and Neck Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Kexin Chen
- Department of Pathology, the Third Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Rui Zhao
- Department of Otolaryngology-Head and Neck Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
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52
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Tang X, Liu M, Luo X, Zhu M, Huang S, Pan X. The Prognostic Value of a Tumor Microenvironment-Based Immune Cell Infiltration Score Model in Colon Cancer. Front Oncol 2021; 11:728842. [PMID: 34737949 PMCID: PMC8561118 DOI: 10.3389/fonc.2021.728842] [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: 06/22/2021] [Accepted: 09/06/2021] [Indexed: 11/16/2022] Open
Abstract
The current study aimed to construct a prognostic predictive model based on tumor microenvironment. CIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration (ICI) landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. ICI scores of each patient were determined by principal component analysis. Patients were divided into high and low ICI score groups. Survival, gene expression, and somatic mutation of the two groups were compared. We found that patients with no lymph node invasion, no metastasis, T1–2 disease, and stage I–II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and Wnt signaling pathway were enriched in the high ICI score group. Immune-checkpoint and immune-activity associated genes were decreased in high ICI score patients. Patients in the high ICI score group had better survival. Prognostic value of ICI score was independent of tumor mutational burden (TMB). The ICI score model constructed in the current study may serve as an independent prognostic biomarker in colon cancer.
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Affiliation(s)
- Xingkui Tang
- Department of General Surgery, Guangzhou Panyu Central Hospital, Guangzhou, China
| | - Minling Liu
- Department of Oncology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Xijun Luo
- Department of General Surgery, Guangzhou Panyu Central Hospital, Guangzhou, China
| | - Mengyuan Zhu
- Department of Oncology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Shan Huang
- Department of Oncology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Xiaofen Pan
- Department of Oncology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
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53
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Mo S, Pei Z, Dai L. Construction of a Signature Composed of 14 Immune Genes to Judge the Prognosis and Immune Infiltration of Colon Cancer. Genet Test Mol Biomarkers 2021; 25:163-178. [PMID: 33734891 DOI: 10.1089/gtmb.2020.0141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: Colon cancer (CC) is an immunogenic tumor and immune-targeting disease. In this study, we analyzed differentially expressed genes (DEGs) from the expression profile data in CC of The Cancer Genome Atlas. Methods and Results: Using univariate and multivariate Cox regression analysis, an immune gene-risk model containing 14 immune genes was established. Four hundred seventeen CC samples were divided into high-risk and low-risk groups, and Kaplan-Meier analysis revealed that high-risk score predicted poor survival. Meanwhile, we found the model was an independent prognostic factor for CC. Weighted gene coexpression network analysis was used to identify key gene modules between high- and low-risk groups. The methods of CIBERSORT and single-sample Gene Set Enrichment Analysis were used to evaluate the correlation between immune cells and our model. Conclusion: Taken together, our study suggested that the immune gene-related risk model may be developed as a potential tool in the prognostic assessment of CC.
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Affiliation(s)
- Shaocong Mo
- Department of Digestive Diseases, Huashan Hospital, Fudan University, Shanghai, PR China.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, PR China
| | - Zhenle Pei
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, PR China
| | - Leijie Dai
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, PR China
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54
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Zhong H, Liu S, Cao F, Zhao Y, Zhou J, Tang F, Peng Z, Li Y, Xu S, Wang C, Yang G, Li ZQ. Dissecting Tumor Antigens and Immune Subtypes of Glioma to Develop mRNA Vaccine. Front Immunol 2021; 12:709986. [PMID: 34512630 PMCID: PMC8429949 DOI: 10.3389/fimmu.2021.709986] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 07/28/2021] [Indexed: 01/02/2023] Open
Abstract
Background Nowadays, researchers are leveraging the mRNA-based vaccine technology used to develop personalized immunotherapy for cancer. However, its application against glioma is still in its infancy. In this study, the applicable candidates were excavated for mRNA vaccine treatment in the perspective of immune regulation, and suitable glioma recipients with corresponding immune subtypes were further investigated. Methods The RNA-seq data and clinical information of 702 and 325 patients were recruited from TCGA and CGGA, separately. The genetic alteration profile was visualized and compared by cBioPortal. Then, we explored prognostic outcomes and immune correlations of the selected antigens to validate their clinical relevance. The prognostic index was measured via GEPIA2, and infiltration of antigen-presenting cells (APCs) was calculated and visualized by TIMER. Based on immune-related gene expression, immune subtypes of glioma were identified using consensus clustering analysis. Moreover, the immune landscape was visualized by graph learning-based dimensionality reduction analysis. Results Four glioma antigens, namely ANXA5, FKBP10, MSN, and PYGL, associated with superior prognoses and infiltration of APCs were selected. Three immune subtypes IS1-IS3 were identified, which fundamentally differed in molecular, cellular, and clinical signatures. Patients in subtypes IS2 and IS3 carried immunologically cold phenotypes, whereas those in IS1 carried immunologically hot phenotype. Particularly, patients in subtypes IS3 and IS2 demonstrated better outcomes than that in IS1. Expression profiles of immune checkpoints and immunogenic cell death (ICD) modulators showed a difference among IS1-IS3 tumors. Ultimately, the immune landscape of glioma elucidated considerable heterogeneity not only between individual patients but also within the same immune subtype. Conclusions ANXA5, FKBP10, MSN, and PYGL are identified as potential antigens for anti-glioma mRNA vaccine production, specifically for patients in immune subtypes 2 and 3. In summary, this study may shed new light on the promising approaches of immunotherapy, such as devising mRNA vaccination tailored to applicable glioma recipients.
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Affiliation(s)
- Hua Zhong
- College of Life Sciences, Wuhan University, Wuhan, China
| | - Shuai Liu
- Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, Mississippi State University, Starkville, MS, United States
| | - Fang Cao
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Yi Zhao
- Department of Medical Genetics, School of Basic Medical Science, Demonstration Center for Experimental Basic Medicine Education, Wuhan University, Wuhan, China
| | - Jianguo Zhou
- Department of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, China
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Feng Tang
- Department of Neurosurgery, Zhongnan Hospital, Wuhan University, Wuhan, China
| | - Zhaohua Peng
- Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, Mississippi State University, Starkville, MS, United States
| | - Yangsheng Li
- College of Life Sciences, Wuhan University, Wuhan, China
| | - Shen Xu
- Department of Neurosurgery, No. 901 Hospital of the Chinese People’s Liberation Army Logistic Support Force, Hefei, China
| | - Chunlin Wang
- Department of Neurosurgery, No. 901 Hospital of the Chinese People’s Liberation Army Logistic Support Force, Hefei, China
| | - Guohua Yang
- Department of Medical Genetics, School of Basic Medical Science, Demonstration Center for Experimental Basic Medicine Education, Wuhan University, Wuhan, China
| | - Zhi-Qiang Li
- Department of Neurosurgery, Zhongnan Hospital, Wuhan University, Wuhan, China
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Li H, Li Y, Zhang Y, Tan B, Huang T, Xiong J, Tan X, Ermolaeva MA, Fu L. MAPK10 Expression as a Prognostic Marker of the Immunosuppressive Tumor Microenvironment in Human Hepatocellular Carcinoma. Front Oncol 2021; 11:687371. [PMID: 34408980 PMCID: PMC8366563 DOI: 10.3389/fonc.2021.687371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 05/31/2021] [Indexed: 11/13/2022] Open
Abstract
Hepatocellular carcinoma (HCC) remains a devastating malignancy worldwide due to lack of effective therapy. The immune-rich contexture of HCC tumor microenvironment (TME) makes this tumor an appealing target for immune-based therapies; however, the immunosuppressive TME is still a major challenge for more efficient immunotherapy in HCC. Using bioinformatics analysis based on the TCGA database, here we found that MAPK10 is frequently down-regulated in HCC tumors and significantly correlates with poor survival of HCC patients. HCC patients with low MAPK10 expression have lower expression scores of tumor infiltration lymphocytes (TILs) and stromal cells in the TME and increased scores of tumor cells than those with high MAPK10 expression. Further transcriptomic analyses revealed that the immune activity in the TME of HCC was markedly reduced in the low-MAPK10 group of HCC patients compared to the high-MAPK10 group. Additionally, we identified 495 differentially expressed immune-associated genes (DIGs), with 482 genes down-regulated and 13 genes up-regulated in parallel with the decrease of MAPK10 expression. GO enrichment and KEGG pathway analyses indicated that the biological functions of these DIGs included cell chemotaxis, leukocyte migration and positive regulation of the response to cytokine–cytokine receptor interaction, T cell receptor activation and MAPK signaling pathway. Protein–protein interaction (PPI) analyses of the 495 DIGs revealed five potential downstream hub genes of MAPK10, including SYK, CBL, VAV1, LCK, and CD3G. Several hub genes such as SYK, LCK, and VAV1 could respond to the immunological costimulatory signaling mediated by the transmembrane protein ICAM1, which was identified as a down-regulated DIG associated with low-MAPK10 expression. Moreover, ectopic overexpression or knock-down of MAPK10 could up-regulate or down-regulate ICAM1 expression via phosphorylation of c-jun at Ser63 in HCC cell lines, respectively. Collectively, our results demonstrated that MAPK10 down-regulation likely contributes to the immunosuppressive TME of HCC, and this gene might serve as a potential immunotherapeutic target and a prognostic factor for HCC patients.
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Affiliation(s)
- Huahui Li
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China.,Group of Homeostasis and Stress Tolerance, Leibniz Institute on Aging-Fritz Lipmann Institute, Jena, Germany.,Shenzhen University-Friedrich Schiller Universitat Jena Joint PhD Program in Biomedical Sciences, Shenzhen University School of Medicine, Shenzhen, China
| | - Yuting Li
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China.,Group of Homeostasis and Stress Tolerance, Leibniz Institute on Aging-Fritz Lipmann Institute, Jena, Germany.,Shenzhen University-Friedrich Schiller Universitat Jena Joint PhD Program in Biomedical Sciences, Shenzhen University School of Medicine, Shenzhen, China
| | - Ying Zhang
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China
| | - Binbin Tan
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China
| | - Tuxiong Huang
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China
| | - Jixian Xiong
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China
| | - Xiangyu Tan
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China
| | - Maria A Ermolaeva
- Group of Homeostasis and Stress Tolerance, Leibniz Institute on Aging-Fritz Lipmann Institute, Jena, Germany
| | - Li Fu
- Guangdong Province Key Laboratory of Regional Immunity and Diseases, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, China
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56
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Xing XL, Zhang T, Yao ZY, Xing C, Wang C, Liu YW, Huang M. Immune-Related Gene Expression Analysis Revealed Three lncRNAs as Prognostic Factors for Colon Cancer. Front Genet 2021; 12:690053. [PMID: 34306030 PMCID: PMC8299306 DOI: 10.3389/fgene.2021.690053] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 06/21/2021] [Indexed: 01/02/2023] Open
Abstract
Colorectal cancer (CRC) is one of the most common cancers. Almost 80% of CRC cases are colon adenocarcinomas (COADs). Several studies have indicated the role of immunotherapy in the treatment of various cancers. Our study aimed to identify immune-related long non-coding RNAs (lncRNAs) and to use them to construct a risk assessment model for evaluating COAD prognosis. Using differential expression, correlation, and Cox regression analyses, we identified three immune-related differentially expressed lncRNAs (IR-DELs) and used them to construct a risk assessment model. The area under the curve (AUC) for each receiver operating characteristic (ROC) curve at 3-, 5-, and 10-years were greater than 0.6. In addition, the risk assessment model was correlated with several immune cells and factors. The three IR-DELs (AC124067.4, LINC02604, and MIR4435-2HG) identified in this study can be used to predict outcomes for patients with COAD and might help in identifying those who can benefit from anti-tumor immunotherapy.
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Affiliation(s)
- Xiao-Liang Xing
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Ti Zhang
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Zhi-Yong Yao
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Chaoqun Xing
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Chunxiao Wang
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Yuan-Wu Liu
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing, China
| | - Minjiang Huang
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
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57
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Shi Z, Shen J, Qiu J, Zhao Q, Hua K, Wang H. CXCL10 potentiates immune checkpoint blockade therapy in homologous recombination-deficient tumors. Theranostics 2021; 11:7175-7187. [PMID: 34158843 PMCID: PMC8210593 DOI: 10.7150/thno.59056] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 05/12/2021] [Indexed: 12/13/2022] Open
Abstract
Background: Homologous recombination deficiency (HRD) is a common molecular characteristic of genomic instability, and has been proven to be a biomarker for target therapy. However, until now, no research has explored the changes in the transcriptomics landscape of HRD tumors. Methods: The HRD score was established from SNP array data of breast cancer patients from the cancer genome atlas (TCGA) database. The transcriptome data of patients with different HRD scores were analyzed to identify biomarkers associated with HRD. The candidate biomarkers were validated in the gene expression omnibus (GEO) database and immunotherapy cohorts. Results: Based on data from the gene expression profile and clinical characteristics from 1310 breast cancer patients, including TCGA database and GEO database, we found that downstream targets of the cGAS-STING pathway, such as CXCL10, were upregulated in HRD tumors and could be used as a predictor of survival outcome in triple-negative breast cancer (TNBC) patients. Further comprehensive analysis of the tumor immune microenvironment (TIME) revealed that the expression of CXCL10 was positively correlated with neoantigen load and infiltrating immune cells. Finally, in vivo experimental data and clinical trial data confirmed that the expression of CXCL10 could be used as a biomarker for anti-PD-1/PD-L1 therapy. Conclusions: Together, our study not only revealed that CXCL10 is associated with HRD but also introduced a potential new perspective for identifying prognostic biomarkers of immunotherapy.
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Affiliation(s)
- Zhiwen Shi
- Obstetrics and Gynecology Hospital, NHC Key Laboratory of Reproduction Regualtion, Shanghai Institute of Planned Parenthood Research, State Key Laboratory of Genetic Engineering at School of Life Sciences, Institute of Reproduction and Development, Fudan University, Shanghai 200032, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Institute of Metabolism and Integrative Biology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Jianfeng Shen
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200025, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200025, China
| | - Junjun Qiu
- Obstetrics and Gynecology Hospital, NHC Key Laboratory of Reproduction Regualtion, Shanghai Institute of Planned Parenthood Research, State Key Laboratory of Genetic Engineering at School of Life Sciences, Institute of Reproduction and Development, Fudan University, Shanghai 200032, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Institute of Metabolism and Integrative Biology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Qingguo Zhao
- Obstetrics and Gynecology Hospital, NHC Key Laboratory of Reproduction Regualtion, Shanghai Institute of Planned Parenthood Research, State Key Laboratory of Genetic Engineering at School of Life Sciences, Institute of Reproduction and Development, Fudan University, Shanghai 200032, China
| | - Keqin Hua
- Obstetrics and Gynecology Hospital, NHC Key Laboratory of Reproduction Regualtion, Shanghai Institute of Planned Parenthood Research, State Key Laboratory of Genetic Engineering at School of Life Sciences, Institute of Reproduction and Development, Fudan University, Shanghai 200032, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Institute of Metabolism and Integrative Biology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Hongyan Wang
- Obstetrics and Gynecology Hospital, NHC Key Laboratory of Reproduction Regualtion, Shanghai Institute of Planned Parenthood Research, State Key Laboratory of Genetic Engineering at School of Life Sciences, Institute of Reproduction and Development, Fudan University, Shanghai 200032, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Institute of Metabolism and Integrative Biology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
- Children's Hospital of Fudan University, Shanghai 201100, China
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58
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Lin Q, Luo L, Wang H. A New Oxaliplatin Resistance-Related Gene Signature With Strong Predicting Ability in Colon Cancer Identified by Comprehensive Profiling. Front Oncol 2021; 11:644956. [PMID: 34026619 PMCID: PMC8138443 DOI: 10.3389/fonc.2021.644956] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/12/2021] [Indexed: 12/13/2022] Open
Abstract
Numerous colon cancer cases are resistant to chemotherapy based on oxaliplatin and suffer from relapse. A number of survival- and prognosis-related biomarkers have been identified based on database mining for patients who develop drug resistance, but the single individual gene biomarker cannot attain high specificity and sensitivity in prognosis prediction. This work was conducted aiming to establish a new gene signature using oxaliplatin resistance-related genes to predict the prognosis for colon cancer. To this end, we downloaded gene expression profile data of cell lines that are resistant and not resistant to oxaliplatin from the Gene Expression Omnibus (GEO) database. Altogether, 495 oxaliplatin resistance-related genes were searched by weighted gene co-expression network analysis (WGCNA) and differential expression analysis. As suggested by functional analysis, the above genes were mostly enriched into cell adhesion and immune processes. Besides, a signature was built based on four oxaliplatin resistance-related genes selected from the training set to predict the overall survival (OS) by stepwise regression and least absolute shrinkage and selection operator (LASSO) Cox analysis. Relative to the low risk score group, the high risk score group had dismal OS (P < 0.0001). Moreover, the area under the curve (AUC) value regarding the 5-year OS was 0.72, indicating that the risk score was accurate in the prediction of OS for colon cancer patients (AUC >0.7). Additionally, multivariate Cox regression suggested that the signature constructed based on four oxaliplatin resistance-related genes predicted the prognosis for colon cancer cases [hazard ratio (HR), 2.77; 95% CI, 2.03–3.78; P < 0.001]. Finally, external test sets were utilized to further validate the stability and accuracy of oxaliplatin resistance-related gene signature for prognosis of colon cancer patients. To sum up, this study establishes a signature based on four oxaliplatin resistance-related genes for predicting the survival of colon cancer patients, which sheds more light on the mechanisms of oxaliplatin resistance and helps identify colon cancer cases with a dismal prognostic outcome.
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Affiliation(s)
- Qiu Lin
- Department of Colorectal Surgery, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Li Luo
- Department of Colorectal Surgery, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Hua Wang
- Department of Colorectal Surgery, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
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59
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Li ZZ, Liu PF, An TT, Yang HC, Zhang W, Wang JX. Construction of a prognostic immune signature for lower grade glioma that can be recognized by MRI radiomics features to predict survival in LGG patients. Transl Oncol 2021; 14:101065. [PMID: 33761371 PMCID: PMC8020484 DOI: 10.1016/j.tranon.2021.101065] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 02/25/2021] [Accepted: 03/02/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND This study aimed to identify a series of prognostically relevant immune features by immunophenoscore. Immune features were explored using MRI radiomics features to prediction the overall survival (OS) of lower-grade glioma (LGG) patients and their response to immune checkpoints. METHOD LGG data were retrieved from TCGA and categorized into training and internal validation datasets. Patients attending the First Affiliated Hospital of Harbin Medical University were included in an external validation cohort. An immunophenoscore-based signature was built to predict malignant potential and response to immune checkpoint inhibitors in LGG patients. In addition, a deep learning neural network prediction model was built for validation of the immunophenoscore-based signature. RESULTS Immunophenotype-associated mRNA signatures (IMriskScore) for outcome prediction and ICB therapeutic effects in LGG patients were constructed. Deep learning of neural networks based on radiomics showed that MRI radiomic features determined IMriskScore. Enrichment analysis and ssGSEA correlation analysis were performed. Mutations in CIC significantly improved the prognosis of patients in the high IMriskScore group. Therefore, CIC is a potential therapeutic target for patients in the high IMriskScore group. Moreover, IMriskScore is an independent risk factor that can be used clinically to predict LGG patient outcomes. CONCLUSIONS The IMriskScore model consisting of a sets of biomarkers, can independently predict the prognosis of LGG patients and provides a basis for the development of personalized immunotherapy strategies. In addition, IMriskScore features were predicted by MRI radiomics using a deep learning approach using neural networks. Therefore, they can be used for the prognosis of LGG patients.
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Affiliation(s)
- Zi-Zhuo Li
- Department of Abdominal Ultrasound, The First Affiliated Hospital of Harbin Medical University China
| | - Peng-Fei Liu
- Department of Magnetic Resonance, The First Affiliated Hospital of Harbin Medical University China.
| | - Ting-Ting An
- Department of Abdominal Ultrasound, The First Affiliated Hospital of Harbin Medical University China
| | - Hai-Chao Yang
- Department of Abdominal Ultrasound, The First Affiliated Hospital of Harbin Medical University China
| | - Wei Zhang
- Department of Abdominal Ultrasound, The First Affiliated Hospital of Harbin Medical University China
| | - Jia-Xu Wang
- Department of Abdominal Ultrasound, The First Affiliated Hospital of Harbin Medical University China
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60
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Li H, Hu J, Yu A, Othmane B, Guo T, Liu J, Cheng C, Chen J, Zu X. RNA Modification of N6-Methyladenosine Predicts Immune Phenotypes and Therapeutic Opportunities in Kidney Renal Clear Cell Carcinoma. Front Oncol 2021; 11:642159. [PMID: 33816290 PMCID: PMC8013979 DOI: 10.3389/fonc.2021.642159] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 02/23/2021] [Indexed: 12/16/2022] Open
Abstract
RNA modification of N6-methyladenosine (m6A) plays critical roles in various biological processes, such as cancer development, inflammation, and the anticancer immune response. However, the role played by a comprehensive m6A modification pattern in regulating anticancer immunity in kidney renal clear cell carcinoma (KIRC) has not been fully elucidated. In this study, we identified two independent m6A modification patterns with distinct biological functions, immunological characteristics, and prognoses in KIRC. Next, we developed an m6A score algorithm to quantify an individual's m6A modification pattern, which was independently validated in external cohorts. The m6A cluster 1 and low m6A score groups were characterized by a hot tumor microenvironment with an increased infiltration level of cytotoxic immune cells, higher tumor mutation burden, higher immune checkpoint expression, and decreased stroma-associated signature enrichment. In general, the m6A cluster 1 and low m6A score groups reflected an inflammatory phenotype, which may be more sensitive to anticancer immunotherapy. The m6A cluster 2 and high m6A score groups indicated a non-inflammatory phenotype, which may not be sensitive to immunotherapy but rather to targeted therapy. In this study, we first identified m6A clusters and m6A scores to elucidate immune phenotypes and to predict the prognosis and immunotherapy response in KIRC, which can guide urologists for making more precise clinical decisions.
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Affiliation(s)
- Huihuang Li
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
| | - Jiao Hu
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
| | - Anze Yu
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China.,Immunobiology & Transplant Science Center, Houston Methodist Research Institute, Texas Medical Center, Houston, TX, United States
| | - Belaydi Othmane
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
| | - Tao Guo
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
| | - Jinhui Liu
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
| | - Chunliang Cheng
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
| | - Jinbo Chen
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiongbing Zu
- Department of Urology, Xiangya Hospital, Central South University, Changsha, China
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A comprehensive analysis of tumor microenvironment-related genes in colon cancer. Clin Transl Oncol 2021; 23:1769-1781. [PMID: 33689097 DOI: 10.1007/s12094-021-02578-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 02/23/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND The development and progression of colon cancer are significantly affected by the tumor microenvironment, which has attracted much attention. The goal of our study was primarily to find out all possible tumor microenvironment-related genes in colon cancer. METHOD This study quantified the immune and stromal landscape using the ESTIMATION algorithm using the gene expression matrix obtained from the UCSC Xena database. Dysregulated genes were harvested using the limma R package, and relevant pathways and biofunctions were identified using enrichment analysis. A least absolute shrinkage and selection operator (LASSO) regression was used to select the pivotal genes from the DEGs. Then, survival analysis was performed to determine the hub genes and a prognostic model was constructed by these hub genes with (or) TNM stage. Besides, associations between hub gene expressions and immune cell infiltration were assessed. RESULTS A total of 725 DEGs were identified. Most of the results of the enrichment analysis were immune-related items. 13 genes were selected as the hub genes and a moderate-to-strong positive correlation between most hub genes and several immune cells were observed. Besides, the prognostic value of the hub genes were comparable to TNM staging. CONCLUSIONS Our study provides a better understanding of how interactions between the 13 immune-prognostic hub genes and immune cells in the tumor microenvironment affect biological processes in colon cancer. These genes exhibit an equivalent ability to TNM staging in prognosis prediction. They are particularly expected to become novel prognostic biomarkers and targets of immunotherapies for colon cancer.
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Chong W, Shang L, Liu J, Fang Z, Du F, Wu H, Liu Y, Wang Z, Chen Y, Jia S, Chen L, Li L, Chen H. m 6A regulator-based methylation modification patterns characterized by distinct tumor microenvironment immune profiles in colon cancer. Am J Cancer Res 2021; 11:2201-2217. [PMID: 33500720 PMCID: PMC7797678 DOI: 10.7150/thno.52717] [Citation(s) in RCA: 148] [Impact Index Per Article: 49.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 11/21/2020] [Indexed: 12/28/2022] Open
Abstract
Recent studies have highlighted the biological significance of RNA N6-methyladenosine (m6A) modification in tumorigenicity and progression. However, it remains unclear whether m6A modifications also have potential roles in immune regulation and tumor microenvironment (TME) formation. Methods: In this study, we curated 23 m6A regulators and performed consensus molecular subtyping with NMF algorithm to determine m6A modification patterns and the m6A-related gene signature in colon cancer (CC). The ssGSEA and CIBERSORT algorithms were employed to quantify the relative infiltration levels of various immune cell subsets. An PCA algorithm based m6Sig scoring scheme was used to evaluate the m6A modification patterns of individual tumors with an immune response. Results: Three distinct m6A modification patterns were identified among 1307 CC samples, which were also associated with different clinical outcomes and biological pathways. The TME characterization revealed that the identified m6A patterns were highly consistent with three known immune profiles: immune-inflamed, immune-excluded, and immune-desert, respectively. Based on the m6Sig score, which was extracted from the m6A-related signature genes, CC patients can be divided into high and low score subgroups. Patients with lower m6Sig score was characterized by prolonged survival time and enhanced immune infiltration. Further analysis indicated that lower m6Sig score also correlated with greater tumor mutation loads, PD-L1 expression, and higher mutation rates in SMGs (e.g., PIK3CA and SMAD4). In addition, patients with lower m6Sig scores showed a better immune responses and durable clinical benefits in three independent immunotherapy cohorts. Conclusions: This study highlights that m6A modification is significantly associated with TME diversity and complexity. Quantitatively evaluating the m6A modification patterns of individual tumors will strengthen our understanding of TME characteristics and promote more effective immunotherapy strategies.
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