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Huang Y, Liu H, Liu B, Chen X, Li D, Xue J, Li N, Zhu L, Yang L, Xiao J, Liu C. Quantified pathway mutations associate epithelial-mesenchymal transition and immune escape with poor prognosis and immunotherapy resistance of head and neck squamous cell carcinoma. BMC Med Genomics 2024; 17:49. [PMID: 38331768 PMCID: PMC10854145 DOI: 10.1186/s12920-024-01818-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 01/23/2024] [Indexed: 02/10/2024] Open
Abstract
BACKGROUND Pathway mutations have been calculated to predict the poor prognosis and immunotherapy resistance in head and neck squamous cell carcinoma (HNSCC). To uncover the unique markers predicting prognosis and immune therapy response, the accurate quantification of pathway mutations are required to evaluate epithelial-mesenchymal transition (EMT) and immune escape. Yet, there is a lack of score to accurately quantify pathway mutations. MATERIAL AND METHODS Firstly, we proposed Individualized Weighted Hallmark Gene Set Mutation Burden (IWHMB, https://github.com/YuHongHuang-lab/IWHMB ) which integrated pathway structure information and eliminated the interference of global Tumor Mutation Burden to accurately quantify pathway mutations. Subsequently, to further elucidate the association of IWHMB with EMT and immune escape, support vector machine regression model was used to identify IWHMB-related transcriptomic features (IRG), while Adversarially Regularized Graph Autoencoder (ARVGA) was used to further resolve IRG network features. Finally, Random walk with restart algorithm was used to identify biomarkers for predicting ICI response. RESULTS We quantified the HNSCC pathway mutation signatures and identified pathway mutation subtypes using IWHMB. The IWHMB-related transcriptomic features (IRG) identified by support vector machine regression were divided into 5 communities by ARVGA, among which the Community 1 enriching malignant mesenchymal components promoted EMT dynamically and regulated immune patterns associated with ICI responses. Bridge Hub Gene (BHG) identified by random walk with restart was key to IWHMB in EMT and immune escape, thus, more predictive for ICI response than other 70 public signatures. CONCLUSION In summary, the novel pathway mutation scoring-IWHMB suggested that the elevated malignancy mediated by pathway mutations is a major cause of poor prognosis and immunotherapy failure in HNSCC, and is capable of identifying novel biomarkers to predict immunotherapy response.
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Affiliation(s)
- Yuhong Huang
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
- Academician Laboratory of Immunology and Oral Development & Regeneration, Dalian Medical University, Dalian, China
| | - Han Liu
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
- Academician Laboratory of Immunology and Oral Development & Regeneration, Dalian Medical University, Dalian, China
| | - Bo Liu
- Institute for Genome Engineered Animal Models of Human Diseases, Dalian Medical University, Dalian, China
| | - Xiaoyan Chen
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
| | - Danya Li
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
| | - Junyuan Xue
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
| | - Nan Li
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
- Academician Laboratory of Immunology and Oral Development & Regeneration, Dalian Medical University, Dalian, China
| | - Lei Zhu
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
- Academician Laboratory of Immunology and Oral Development & Regeneration, Dalian Medical University, Dalian, China
| | - Liu Yang
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China
| | - Jing Xiao
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China.
- Academician Laboratory of Immunology and Oral Development & Regeneration, Dalian Medical University, Dalian, China.
| | - Chao Liu
- Department of Oral Pathology, Dalian Medical University School of Stomatology, Dalian, China.
- Academician Laboratory of Immunology and Oral Development & Regeneration, Dalian Medical University, Dalian, China.
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2
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Kang H, Zhu X, Cui Y, Xiong Z, Zong W, Bao Y, Jia P. A Comprehensive Benchmark of Transcriptomic Biomarkers for Immune Checkpoint Blockades. Cancers (Basel) 2023; 15:4094. [PMID: 37627121 PMCID: PMC10452274 DOI: 10.3390/cancers15164094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 08/10/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023] Open
Abstract
Immune checkpoint blockades (ICBs) have revolutionized cancer therapy by inducing durable clinical responses, but only a small percentage of patients can benefit from ICB treatments. Many studies have established various biomarkers to predict ICB responses. However, different biomarkers were found with diverse performances in practice, and a timely and unbiased assessment has yet to be conducted due to the complexity of ICB-related studies and trials. In this study, we manually curated 29 published datasets with matched transcriptome and clinical data from more than 1400 patients, and uniformly preprocessed these datasets for further analyses. In addition, we collected 39 sets of transcriptomic biomarkers, and based on the nature of the corresponding computational methods, we categorized them into the gene-set-like group (with the self-contained design and the competitive design, respectively) and the deconvolution-like group. Next, we investigated the correlations and patterns of these biomarkers and utilized a standardized workflow to systematically evaluate their performance in predicting ICB responses and survival statuses across different datasets, cancer types, antibodies, biopsy times, and combinatory treatments. In our benchmark, most biomarkers showed poor performance in terms of stability and robustness across different datasets. Two scores (TIDE and CYT) had a competitive performance for ICB response prediction, and two others (PASS-ON and EIGS_ssGSEA) showed the best association with clinical outcome. Finally, we developed ICB-Portal to host the datasets, biomarkers, and benchmark results and to implement the computational methods for researchers to test their custom biomarkers. Our work provided valuable resources and a one-stop solution to facilitate ICB-related research.
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Affiliation(s)
- Hongen Kang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiuli Zhu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ying Cui
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhuang Xiong
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Wenting Zong
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Yiming Bao
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
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3
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Qi D, Geng Y, Cardenas J, Gu J, Yi SS, Huang JH, Fonkem E, Wu E. Transcriptomic analyses of patient peripheral blood with hemoglobin depletion reveal glioblastoma biomarkers. NPJ Genom Med 2023; 8:2. [PMID: 36697401 PMCID: PMC9877004 DOI: 10.1038/s41525-022-00348-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 12/21/2022] [Indexed: 01/26/2023] Open
Abstract
Peripheral blood is gaining prominence as a noninvasive alternative to tissue biopsy to develop biomarkers for glioblastoma (GBM); however, widely utilized blood-based biomarkers in clinical settings have not yet been identified due to the lack of a robust detection approach. Here, we describe the application of globin reduction in RNA sequencing of whole blood (i.e., WBGR) and perform transcriptomic analysis to identify GBM-associated transcriptomic changes. By using WBGR, we improved the detection sensitivity of informatic reads and identified differential gene expression in GBM blood. By analyzing tumor tissues, we identified transcriptomic traits of GBM blood. Further functional enrichment analyses retained the most changed genes in GBM. Subsequent validation elicited a 10-gene panel covering mRNA, long noncoding RNA, and microRNA (i.e., GBM-Dx panel) that has translational potential to aid in the early detection or clinical management of GBM. Here, we report an integrated approach, WBGR, with comprehensive analytic capacity for blood-based marker identification.
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Affiliation(s)
- Dan Qi
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76508, USA
| | - Yiqun Geng
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76508, USA
- Laboratory of Molecular Pathology, Shantou University Medical College, 515041, Shantou, China
| | - Jacob Cardenas
- Baylor Scott & White Research Institute, Dallas, TX, 75204, USA
| | - Jinghua Gu
- Baylor Scott & White Research Institute, Dallas, TX, 75204, USA
| | - S Stephen Yi
- Institute for Cellular and Molecular Biology (ICMB), College of Natural Sciences, The University of Texas at Austin, Austin, TX, 78712, USA
- Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX, 78712, USA
- Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, 78712, USA
- Department of Oncology, LIVESTRONG Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX, 78712, USA
| | - Jason H Huang
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76508, USA.
- Texas A & M University School of Medicine, Temple, TX, 76508, USA.
| | - Ekokobe Fonkem
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76508, USA.
- Texas A & M University School of Medicine, Temple, TX, 76508, USA.
| | - Erxi Wu
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76508, USA.
- Department of Oncology, LIVESTRONG Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX, 78712, USA.
- Texas A & M University School of Medicine, Temple, TX, 76508, USA.
- Texas A & M University School of Pharmacy, College Station, TX, 77843, USA.
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Wang X, Guo S, Zhou H, Sun Y, Gan J, Zhang Y, Zheng W, Zhang C, Zhao X, Xiao J, Wang L, Gao Y, Ning S. Immune Pathways with Aging Characteristics Improve Immunotherapy Benefits and Drug Prediction in Human Cancer. Cancers (Basel) 2023; 15:cancers15020342. [PMID: 36672292 PMCID: PMC9856581 DOI: 10.3390/cancers15020342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/15/2022] [Accepted: 12/26/2022] [Indexed: 01/06/2023] Open
Abstract
(1) Background: Perturbation of immune-related pathways can make substantial contributions to cancer. However, whether and how the aging process affects immune-related pathways during tumorigenesis remains largely unexplored. (2) Methods: Here, we comprehensively investigated the immune-related genes and pathways among 25 cancer types using genomic and transcriptomic data. (3) Results: We identified several pathways that showed aging-related characteristics in various cancers, further validated by conventional aging-related gene sets. Genomic analysis revealed high mutation burdens in cytokines and cytokines receptors pathways, which were strongly correlated with aging in diverse cancers. Moreover, immune-related pathways were found to be favorable prognostic factors in melanoma. Furthermore, the expression level of these pathways had close associations with patient response to immune checkpoint blockade therapy in melanoma and non-small cell lung cancer. Applying a net-work-based method, we predicted immune- and aging-related genes in pan-cancer and utilized these genes for potential immunotherapy drug discovery. Mapping drug target data to our top-ranked genes identified potential drug targets, FYN, JUN, and SRC. (4) Conclusions: Taken together, our systematic study helped interpret the associations among immune-related pathways, aging, and cancer and could serve as a resource for promoting clinical treatment.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Yue Gao
- Correspondence: (Y.G.); (S.N.)
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5
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Li J, Wu J, Han J. Analysis of Tumor Microenvironment Heterogeneity among Breast Cancer Subtypes to Identify Subtype-Specific Signatures. Genes (Basel) 2022; 14:44. [PMID: 36672784 PMCID: PMC9858482 DOI: 10.3390/genes14010044] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/18/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022] Open
Abstract
Breast cancer is one of the most frequent malignancies in women worldwide. According to 50-gene signature, Prediction Analysis of Microarray 50 (PAM50), breast cancer can be categorized into five molecular subtypes, and these subtypes are highly heterogeneous in different molecular characteristics. However, the landscape of their tumor microenvironment (TME) heterogeneity has not been fully researched. Using the multi-omics dataset of breast cancer from the METABRIC cohort (n = 1699), we conducted extensive analyses of TME-related features to investigate TME heterogeneity in each breast cancer subtype. We then developed a cell-based subtype set enrichment analysis to identify the subtype-specific TME cells, and further evaluate their prognostic effects. Our results illustrate that different breast cancer subtypes exhibit different TME patterns. Basal-like and HER2-enriched subtypes are associated with high immune scores, expression of most immune regulatory targets, and immune cell infiltration, suggesting that these subtypes could be defined as "immune hot" tumors and suitable for immune checkpoint blockade (ICB) therapy. In contrast, Luminal A and Luminal B subtypes are associated with low immune scores and immune cell infiltration, suggesting that these subtypes could be defined as "immune cold" tumors. Additionally, the Normal-like subtype has relatively high levels of both immune and stromal features, which indicates that the Normal-like subtype may be suitable for more diverse treatment strategies. Our study reveals the breast cancer tumor microenvironment heterogeneity across subtypes. The comprehensive analysis of breast cancer TME-related characteristics may help us to adopt a tailored treatment strategy for different subtypes of patients.
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Affiliation(s)
- Ji Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China
| | - Jiashuo Wu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China
| | - Junwei Han
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China
- Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Harbin 150086, China
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6
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Chen L, Lin Y, Wei W, Wang Y, Li F, Du W, Yang Z, Hu Y, Ying X, Tang Q, Xie J, Yu H. Combining Single-Cell and Transcriptomic Data Revealed the Prognostic Significance of Glycolysis in Pancreatic Cancer. Front Genet 2022; 13:903783. [PMID: 35865013 PMCID: PMC9294390 DOI: 10.3389/fgene.2022.903783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 05/18/2022] [Indexed: 11/27/2022] Open
Abstract
Background: Pancreatic cancer (PC), the most common fatal solid malignancy, has a very dismal prognosis. Clinical computerized tomography (CT) and pathological TNM staging are no longer sufficient for determining a patient’s prognosis. Although numerous studies have suggested that glycolysis is important in the onset and progression of cancer, there are few publications on its impact on PC. Methods: To begin, the single-sample gene set enrichment analysis (ssGSEA) approach was used to quantify the glycolysis pathway enrichment fraction in PC patients and establish its prognostic significance. The genes most related to the glycolytic pathway were then identified using weighted gene co-expression network analysis (WGCNA). The glycolysis-associated prognostic signature in PC patients was then constructed using univariate Cox regression and lasso regression methods, which were validated in numerous external validation cohorts. Furthermore, we investigated the activation of the glycolysis pathway in PC cell subtypes at the single-cell level, performed a quasi-time series analysis on the activated cell subtypes and then detected gene changes in the signature during cell development. Finally, we constructed a decision tree and a nomogram that could divide the patients into different risk subtypes, according to the signature score and their different clinical characteristics and assessed the prognosis of PC patients. Results: Glycolysis plays a risky role in PC patients. Our glycolysis-related signature could effectively discriminate the high-risk and low-risk patients in both the trained cohort and the independent externally validated cohort. The survival analysis and multivariate Cox analysis indicated this gene signature to be an independent prognostic factor in PC. The prognostic ROC curve analysis suggested a high accuracy of this gene signature in predicting the patient prognosis in PC. The single-cell analysis suggested that the glycolytic pathway may be more activated in epithelial cells and that the genes in the signature were also mainly expressed in epithelial cells. The decision tree analysis could effectively identify patients in different risk subgroups, and the nomograms clearly show the prognostic assessment of PC patients. Conclusion: Our study developed a glycolysis-related signature, which contributes to the risk subtype assessment of patients with PC and to the individualized management of patients in the clinical setting.
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Affiliation(s)
- Liang Chen
- Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, China
| | - Yunhua Lin
- The First Clinical Medical College, Guangxi Medical University, Nanning, China
| | - Wei Wei
- Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, China
| | - Yue Wang
- Department of Pathology, School of Basic Medical Sciences, Anhui Medical University, Fuyang, China
| | - Fangyue Li
- Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, China
| | - Wang Du
- Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, China
| | - Zhonghua Yang
- Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, China
| | - Yiming Hu
- College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Xiaomei Ying
- Department of General Surgery, Suzhou Hospital of Anhui Province, Suzhou, China
| | - Qikai Tang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
| | - Jiaheng Xie
- Department of Burn and Plastic Surgery, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
- *Correspondence: Jiaheng Xie, ; Hongzhu Yu,
| | - Hongzhu Yu
- Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, China
- *Correspondence: Jiaheng Xie, ; Hongzhu Yu,
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7
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Li Y, Xu S, Xu D, Pan T, Guo J, Gu S, Lin Q, Li X, Li K, Xiang W. Pediatric Pan-Central Nervous System Tumor Methylome Analyses Reveal Immune-Related LncRNAs. Front Immunol 2022; 13:853904. [PMID: 35603200 PMCID: PMC9114481 DOI: 10.3389/fimmu.2022.853904] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/11/2022] [Indexed: 01/10/2023] Open
Abstract
Pediatric central nervous system (CNS) tumors are the second most common cancer diagnosis among children. Long noncoding RNAs (lncRNAs) emerge as critical regulators of gene expression, and they play fundamental roles in immune regulation. However, knowledge on epigenetic changes in lncRNAs in diverse types of pediatric CNS tumors is lacking. Here, we integrated the DNA methylation profiles of 2,257 pediatric CNS tumors across 61 subtypes with lncRNA annotations and presented the epigenetically regulated landscape of lncRNAs. We revealed the prevalent lncRNA methylation heterogeneity across pediatric pan-CNS tumors. Based on lncRNA methylation profiles, we refined 14 lncRNA methylation clusters with distinct immune microenvironment patterns. Moreover, we found that lncRNA methylations were significantly correlated with immune cell infiltrations in diverse tumor subtypes. Immune-related lncRNAs were further identified by investigating their correlation with immune cell infiltrations and potentially regulated target genes. LncRNA with methylation perturbations potentially regulate the genes in immune-related pathways. We finally identified several candidate immune-related lncRNA biomarkers (i.e., SSTR5-AS1, CNTN4-AS1, and OSTM1-AS1) in pediatric cancer for further functional validation. In summary, our study represents a comprehensive repertoire of epigenetically regulated immune-related lncRNAs in pediatric pan-CNS tumors, and will facilitate the development of immunotherapeutic targets.
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Affiliation(s)
- Yongsheng Li
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Sicong Xu
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Dahua Xu
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Tao Pan
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Jing Guo
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Shuo Gu
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Qiuyu Lin
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Xia Li
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China.,College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Kongning Li
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Wei Xiang
- College of Biomedical Information and Engineering, NHC Key Laboratory of Control of Tropical Diseases, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
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8
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Dai K, Liu C, Guan G, Cai J, Wu L. Identification of immune infiltration-related genes as prognostic indicators for hepatocellular carcinoma. BMC Cancer 2022; 22:496. [PMID: 35513781 PMCID: PMC9074323 DOI: 10.1186/s12885-022-09587-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 04/18/2022] [Indexed: 12/29/2022] Open
Abstract
Hepatocellular carcinoma (HCC) has a high degree of malignancy and a poor prognosis. Immune infiltration-related genes have shown good predictive value in the prognosis of many solid tumours. In this study, we established and verified prognostic biomarkers consisting of immune infiltration-related genes in HCC. Gene expression data and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Differential gene expression analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression algorithm were used to screen prognostic immune infiltration-related genes and to construct a risk scoring model. Kaplan-Meier (KM) survival plots and receiver operating characteristic (ROC) curve analysis were used to evaluate the prognostic performance of the risk scoring model in the TCGA-HCC cohort. In addition, a nomogram model with a risk score was established, and its predictive performance was verified by ROC analysis and calibration plot analysis in the TCGA-HCC cohort. Gene set enrichment analysis (GSEA) identified pathways and biological processes that may be enriched in the high-risk group. Finally, immune infiltration analysis was used to explore the characteristics of the tumour microenvironment related to the risk score. We identified 17 immune infiltration-related genes with prognostic value and constructed a risk scoring model. ROC analysis showed that the risk scoring model can accurately predict the 1-year, 3-year, and 5-year overall survival (OS) of HCC patients in the TCGA-HCC cohort. KM analysis showed that the OS of the high-risk group was significantly lower than that of the low-risk group (P < 0.001). The nomogram model effectively predicted the OS of HCC patients in the TCGA-HCC cohort. GSEA indicated that the immune infiltration-related genes may be involved in biological processes such as amino acid and lipid metabolism, matrisome and small molecule transportation, immune system regulation, and hepatitis virus infection. Immune infiltration analysis showed that the level of immune cell infiltration in the high-risk group was low, and the risk score was negatively correlated with infiltrating immune cells. Our prognostic model based on immune infiltration-related genes in HCC could help the prognostic assessment of HCC patients and provide potential targets for HCC inhibition.
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Affiliation(s)
- Kunfu Dai
- Liver Disease Center, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao, 266003, China
| | - Chao Liu
- Liver Disease Center, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao, 266003, China
| | - Ge Guan
- Liver Disease Center, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao, 266003, China
| | - Jinzhen Cai
- Liver Disease Center, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao, 266003, China
| | - Liqun Wu
- Liver Disease Center, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao, 266003, China.
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9
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Wang S, Wang R, Gao F, Huang J, Zhao X, Li D. Pan-cancer analysis of the DNA methylation patterns of long non-coding RNA. Genomics 2022; 114:110377. [PMID: 35513292 DOI: 10.1016/j.ygeno.2022.110377] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 03/23/2022] [Accepted: 04/27/2022] [Indexed: 11/04/2022]
Abstract
Long non-coding RNA (lncRNA) regulated by abnormal DNA methylation (ADM-lncRNA) emerges as a biomarker for cancer diagnosis and treatment. This study comprehensively described the methylation patterns of lncRNA in pan-cancer using the cancer data set in The Cancer Genome Atlas (TCGA). Based on the cancer heterogeneity of ADM-lncRNA in pan-cancer, we constructed a co-expression network of pan-cancer ADM-lncRNA (pADM-lncRNA) in 10 cancers, highlighting the combined action mode of abnormal DNA methylation, and indicating the internal connection among different cancers. Functional analysis revealed the pan-carcinogenic pathway of pADM-lncRNA and suggested potential factors for cancer heterogeneity and tumor immune microenvironment changes. Survival analysis showed the potential of pADM-lncRNA-mRNA co-expression pair as cancer biomarkers. Revealing the action mode of lncRNA and DNA methylation in cancer may help understand the key molecular mechanisms of cell carcinogenesis.
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Affiliation(s)
- Shijia Wang
- School of Biomedical Engineering, Capital Medical University, 10 You An Men Wai, Xi Tou Tiao, Beijing 100069, China; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical, Capital Medical University, Beijing 100069, China
| | - Rendong Wang
- School of Biomedical Engineering, Capital Medical University, 10 You An Men Wai, Xi Tou Tiao, Beijing 100069, China; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical, Capital Medical University, Beijing 100069, China
| | - Fang Gao
- Health Management Center, Binzhou People's Hospital, Shandong Province, China
| | - Jun Huang
- School of Biomedical Engineering, Capital Medical University, 10 You An Men Wai, Xi Tou Tiao, Beijing 100069, China; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical, Capital Medical University, Beijing 100069, China
| | - Xiaoxiao Zhao
- School of Biomedical Engineering, Capital Medical University, 10 You An Men Wai, Xi Tou Tiao, Beijing 100069, China; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical, Capital Medical University, Beijing 100069, China
| | - Dongguo Li
- School of Biomedical Engineering, Capital Medical University, 10 You An Men Wai, Xi Tou Tiao, Beijing 100069, China; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical, Capital Medical University, Beijing 100069, China.
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Li Y, Yang C, Liu Z, Du S, Can S, Zhang H, Zhang L, Huang X, Xiao Z, Li X, Fang J, Qin W, Sun C, Wang C, Chen J, Chen H. Integrative analysis of CRISPR screening data uncovers new opportunities for optimizing cancer immunotherapy. Mol Cancer 2022; 21:2. [PMID: 34980132 PMCID: PMC8722047 DOI: 10.1186/s12943-021-01462-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 11/11/2021] [Indexed: 12/15/2022] Open
Abstract
Background In recent years, the application of functional genetic immuno-oncology screens has showcased the striking ability to identify potential regulators engaged in tumor-immune interactions. Although these screens have yielded substantial data, few studies have attempted to systematically aggregate and analyze them. Methods In this study, a comprehensive data collection of tumor immunity-associated functional screens was performed. Large-scale genomic data sets were exploited to conduct integrative analyses. Results We identified 105 regulator genes that could mediate resistance or sensitivity to immune cell-induced tumor elimination. Further analysis identified MON2 as a novel immune-oncology target with considerable therapeutic potential. In addition, based on the 105 genes, a signature named CTIS (CRISPR screening-based tumor-intrinsic immune score) for predicting response to immune checkpoint blockade (ICB) and several immunomodulatory agents with the potential to augment the efficacy of ICB were also determined. Conclusion Overall, our findings provide insights into immune oncology and open up novel opportunities for improving the efficacy of current immunotherapy agents. Supplementary Information The online version contains supplementary material available at 10.1186/s12943-021-01462-z.
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Affiliation(s)
- Yan Li
- State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, Shanghai Jiao Tong University School of Medicine, 145 Middle Shandong Road, Shanghai, 200001, China.,Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Chen Yang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200001, China
| | - Zhicheng Liu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Shangce Du
- Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Susan Can
- Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Hailin Zhang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200001, China
| | - Linmeng Zhang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200001, China
| | - Xiaowen Huang
- State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, Shanghai Jiao Tong University School of Medicine, 145 Middle Shandong Road, Shanghai, 200001, China
| | - Zhenyu Xiao
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xiaobo Li
- State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, Shanghai Jiao Tong University School of Medicine, 145 Middle Shandong Road, Shanghai, 200001, China
| | - Jingyuan Fang
- State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, Shanghai Jiao Tong University School of Medicine, 145 Middle Shandong Road, Shanghai, 200001, China
| | - Wenxin Qin
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200001, China
| | - Chong Sun
- Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany.
| | - Cun Wang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200001, China.
| | - Jun Chen
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China. .,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China. .,Key Laboratory of Tropical Disease Control of the Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China. .,Guangdong Engineering & Technology Research Center for Disease-Model Animals, Laboratory Animal Center, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China. .,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Huimin Chen
- State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, Shanghai Jiao Tong University School of Medicine, 145 Middle Shandong Road, Shanghai, 200001, China.
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Jin Y, Qin X. Significance of TP53 mutation in treatment and prognosis in head and neck squamous cell carcinoma. Biomark Med 2021; 15:15-28. [PMID: 33427498 DOI: 10.2217/bmm-2020-0400] [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: 12/09/2022] Open
Abstract
Background: TP53 is ranked as the most common mutated gene in head and neck squamous cell carcinoma (HNSCC). Results: The status of TP53 mutation was investigated on International Cancer Genome Consortium and The Cancer Genome Atlas database and TP53-related differentially expressed genes were screened out from transcriptome data and mutation information. A TP53-related prognostic gene signature (TIMP4, ONECUT2, CGNL1, DMRTA2 and NKX2.3) was constructed based on Cox regression analysis and LASSO algorithm. Univariate and multivariate analyses were carried out to identify promising prognosticators for HNSCC. Conclusion: Our findings provide a well-rounded landscape of TP53 mutation in HNSCC and pave the groundwork for developing innovative and effective cancer treatment methods for HNSCC.
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Affiliation(s)
- Yu Jin
- Department of General Dentistry, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, PR China.,Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research Center of Stomatology, Shanghai 200000, PR China
| | - Xing Qin
- Department of Oral & Maxillofacial-Head & Neck Oncology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, PR China.,Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research Center of Stomatology, Shanghai 200000, PR China
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