1
|
Fan L, Li M, Zhou X, Jia X, Tian H, Wen Q. T cell-related circRNA pairs to predict prognosis of patients with esophageal squamous cell carcinoma. Int Immunopharmacol 2024; 141:112909. [PMID: 39154531 DOI: 10.1016/j.intimp.2024.112909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/26/2024] [Accepted: 08/05/2024] [Indexed: 08/20/2024]
Abstract
The prognosis for esophageal squamous cell carcinoma (ESCC), a prevalent and aggressive form of cancer, remains poor despite advancements in treatment options. Addressing the gap in comprehensive prognostic information derived from circRNA expression profiles for ESCC, our study aimed to establish a linkage between circRNA expressions and ESCC prognosis. To achieve this, we first developed an optimized prognostic model named T cell-related risk score (TRRS), which integrates T cell-associated features with machine learning algorithms. In parallel, we re-analyzed existing RNA-seq datasets to redefine the expression profiles of circRNAs and mRNAs. Utilizing the TRRS as a foundational "bridge," we identified circRNAs correlated with TRRS, leading to the development of a novel circRNA pair-based prognostic model, the TCRS, which is independent of specific expression levels. Further investigations uncovered two circRNAs, circNLK(5,6,7).1 and circRC3H1(2).1, with potential functional significance. These findings underscore the utility of these risk scores as tools for predicting overall survival and identifying potential therapeutic targets for ESCC patients.
Collapse
Affiliation(s)
- Liyuan Fan
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
| | - Mian Li
- Biomedical Sciences College & Shandong Medicinal Biotechnology Centre, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Xinyuan Zhou
- College of Artificial Intelligence and Big Data For Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Xiao Jia
- School of Control Science and Engineering, Shandong University, Jinan, China
| | - Hui Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Qiang Wen
- Department of Radiation Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, China.
| |
Collapse
|
2
|
Ahmadi M, Mohajeri Khorasani A, Morshedzadeh F, Saffarzadeh N, Ghaderian SMH, Ghafouri-Fard S, Mousavi P. HLF is a promising prognostic, immunological, and therapeutic biomarker in human tumors. Biochem Biophys Rep 2024; 38:101725. [PMID: 38711550 PMCID: PMC11070826 DOI: 10.1016/j.bbrep.2024.101725] [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: 03/09/2024] [Revised: 04/14/2024] [Accepted: 04/27/2024] [Indexed: 05/08/2024] Open
Abstract
Despite past research linking HLF mutations to cancer development, no pan-cancer analyses of HLF have been published. As a result, we utilized multiple databases to illustrate the potential roles of HLF in diverse types of cancers. Several databases were used to assess HLF expression in the TCGA cancer samples. Additional assessments were undertaken to investigate the relationship between HLF and overall survival, immune cell infiltration, genetic alterations, promoter methylation, and protein-protein interaction. HLF's putative roles and the relationship between HLF expression and drug reactivity were investigated. HLF expression was shown to be lower in tumor tissues from a variety of malignancies when compared to normal tissues. There was a substantial link found between HLF expression and patient survival, genetic mutations, and immunological infiltration. HLF influenced the pathways of apoptosis, cell cycle, EMT, and PI3K/AKT signaling. Abnormal expression of HLF lowered sensitivity to numerous anti-tumor drugs and small compounds. According to our findings, reduced HLF expression drives cancer growth, and it has the potential to be identified as a vital biomarker for use in prognosis, immunotherapy, and targeted treatment of a range of malignancies.
Collapse
Affiliation(s)
- Mohsen Ahmadi
- Department of Medical Genetics, Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Firouzeh Morshedzadeh
- Department of Genetics, Faculty of Basic Sciences, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Negin Saffarzadeh
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Soudeh Ghafouri-Fard
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Pegah Mousavi
- Molecular Medicine Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| |
Collapse
|
3
|
Li X, Yang L, Jiang F, Jiao X. Integration of Radiomics and Immune-Related Genes Signatures for Predicting Axillary Lymph Node Metastasis in Breast Cancer. Clin Breast Cancer 2024:S1526-8209(24)00179-4. [PMID: 39019727 DOI: 10.1016/j.clbc.2024.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 06/19/2024] [Accepted: 06/20/2024] [Indexed: 07/19/2024]
Abstract
BACKGROUND To develop a radiogenomics nomogram for predicting axillary lymph node (ALN) metastasis in breast cancer and reveal underlying associations between radiomics features and biological pathways. MATERIALS AND METHODS This study included 1062 breast cancer patients, 90 patients with both DCE-MRI and gene expression data. The optimal immune-related genes and radiomics features associated with ALN metastasis were firstly calculated, and corresponding feature signatures were constructed to further validate their performances in predicting ALN metastasis. The radiogenomics nomogram for predicting the risk of ALN metastasis was established by integrating radiomics signature, immune-related genes (IRG) signature, and critical clinicopathological factors. Gene modules associated with key radiomics features were identified by weighted gene co-expression network analysis (WGCNA) and submitted to functional enrichment analysis. Gene set variation analysis (GSVA) and correlation analysis were performed to investigate the associations between radiomics features and biological pathways. RESULTS The radiogenomics nomogram showed promising predictive power for predicting ALN metastasis, with AUCs of 0.973 and 0.928 in the training and testing groups, respectively. WGCNA and functional enrichment analysis revealed that gene modules associated with key radiomics features were mainly enriched in breast cancer metastasis-related pathways, such as focal adhesion, ECM-receptor interaction, and cell adhesion molecules. GSVA also identified pathway activities associated with radiomics features such as glycogen synthesis, integration of energy metabolism. CONCLUSION The radiogenomics nomogram can serve as an effective tool to predict the risk of ALN metastasis. This study provides further evidence that radiomics phenotypes may be driven by biological pathways related to breast cancer metastasis.
Collapse
Affiliation(s)
- Xue Li
- College of Biomedical Engineering, Taiyuan University of Technology, Jinzhong, Shanxi, China
| | - Lifeng Yang
- College of Computer Science and Technology, Taiyuan University of Technology, Jinzhong, Shanxi, China
| | - Fa Jiang
- College of Biomedical Engineering, Taiyuan University of Technology, Jinzhong, Shanxi, China
| | - Xiong Jiao
- College of Biomedical Engineering, Taiyuan University of Technology, Jinzhong, Shanxi, China.
| |
Collapse
|
4
|
Zhang M, Xu G, Xi C, Yu E. Identification of immune-related tumor antigens and immune subtypes in osteosarcoma. Heliyon 2024; 10:e32231. [PMID: 38912457 PMCID: PMC11190600 DOI: 10.1016/j.heliyon.2024.e32231] [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: 01/09/2024] [Revised: 05/29/2024] [Accepted: 05/30/2024] [Indexed: 06/25/2024] Open
Abstract
Purpose The development of tumor vaccines has become a hot topic in immunotherapy for osteosarcoma (OS); however, more tumor antigens with stronger immunogenicity need to be identified. Methods We downloaded six sets of gene expression profile data from online databases. The overexpressed genes were analyzed, intersected, and used to calculate the immune infiltration abundance in the TARGET OS dataset based on their expression matrix. Potential tumor antigen genes were identified based on whether they exhibited a high correlation with the antigen-presenting cells (APCs). A total of 1330 immune-related genes (IRGs) from the ImmPort website were retrieved based on their expression, and the Consensus Cluster method was used to obtain immune subtypes of the OS samples. Prognosis, immune microenvironment, and sensitivity to drugs were compared among the immune subtypes. Results In total, 680 genes were overexpressed in at least two datasets, of which TREM2, TNFRSF12A, and THY1 were positively correlated with different APCs. Based on the expression matrix of 1330 IRGs in TARGET-OS, two immune subtypes, IS1 and IS2, were identified. The prognosis of the IS1 subtype was better than that of IS2, the expression of immune checkpoint (ICP)-related genes was higher in patients with the IS1 subtype, and immune cell infiltration and sensitivity to 16 drugs were generally higher in IS1 subtype patients. Conclusion We identified three APC-correlated genes that can be considered to code for potential novel tumor antigens for OS vaccines. Two immune subtypes in patients with OS were identified to implement personalized treatments using mRNA vaccines.
Collapse
Affiliation(s)
- Mingshu Zhang
- Department of Orthopedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Gongping Xu
- Department of Orthopedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chunyang Xi
- Department of Orthopedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Enming Yu
- Department of Orthopedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| |
Collapse
|
5
|
Lu Z, Wang Z, Li G. High expression of CCNB2 is an independent predictive poor prognostic biomarker and correlates with immune infiltrates in breast carcinoma. Heliyon 2024; 10:e31586. [PMID: 38831807 PMCID: PMC11145498 DOI: 10.1016/j.heliyon.2024.e31586] [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: 03/12/2024] [Revised: 05/17/2024] [Accepted: 05/20/2024] [Indexed: 06/05/2024] Open
Abstract
Background Cyclin B2 (CCNB2) is associated with cell cycle progression, acting as a cell cycle checkpoint in progression of G2/M transition. In many cancer patients, it has been observed that overexpression of CCNB2 enhances tumor invasiveness and leads to adverse prognosis. However, the association of CCNB2 with the tumor microenvironment remains unclear. Therefore, it is necessary to clarify the associations of CCNB2 with the immune status and prognosis of breast carcinoma (BRCA). Methods Gene expression and clinical data for BRCA were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, followed by association analyses of CCNB2 expression with prognosis, immune cell infiltration, and immune checkpoints. This study further performed drug sensitivity analysis and constructed a prognostic nomogram for CCNB2. Results 3619 differentially expressed genes were identified in BRCA, including CCNB2 that emerged as a key gene in the network. High CCNB2 expression correlated with poor prognosis. Functional analysis demonstrated enrichment of CCNB2 co-expressed genes with the cell cycle, cancer progression, cell energy, and immune pathways. Microsatellite instability and tumor mutation burden analyses indicated CCNB2 as a candidate immunotherapy target. Tumor-infiltrating myeloid-derived suppressor cells, regulatory T cells, and T helper 2 cells were associated with CCNB2-related tumor progression and metastasis. CCNB2 expression positively correlated with immune checkpoints, indicating that high CCNB2 expression might facilitate tumor immune escape. Tumors with high CCNB2 expression showed sensitivity to phosphoinositide 3-kinase-protein kinase B-mammalian target of rapamycin and cyclin-dependent kinase (CDK) 4/6 inhibitors, and the nomogram had good prognostic predictive ability for patients with BRCA. Conclusions CCNB2 may play a crucial role in tumorigenesis and serve as an independent prognostic biomarker associated with tumor microenvironment, tumor immune infiltration and immunotherapy in BRCA.
Collapse
Affiliation(s)
- Zonghong Lu
- Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Zhihong Wang
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, GI Cancer Research Institute, Wuhan, Hubei, 430030, China
| | - Guodong Li
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, GI Cancer Research Institute, Wuhan, Hubei, 430030, China
| |
Collapse
|
6
|
Lin S, Yong J, Zhang L, Chen X, Qiao L, Pan W, Yang Y, Zhao H. Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma. Comput Biol Med 2024; 173:108365. [PMID: 38537563 DOI: 10.1016/j.compbiomed.2024.108365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/19/2024] [Accepted: 03/21/2024] [Indexed: 04/17/2024]
Abstract
BACKGROUND Most of the methods using digital pathological image for predicting Hepatocellular carcinoma (HCC) prognosis have not considered paracancerous tissue microenvironment (PTME), which are potentially important for tumour initiation and metastasis. This study aimed to identify roles of image features of PTME in predicting prognosis and tumour recurrence of HCC patients. METHODS We collected whole slide images (WSIs) of 146 HCC patients from Sun Yat-sen Memorial Hospital (SYSM dataset). For each WSI, five types of regions of interests (ROIs) in PTME and tumours were manually annotated. These ROIs were used to construct a Lasso Cox survival model for predicting the prognosis of HCC patients. To make the model broadly useful, we established a deep learning method to automatically segment WSIs, and further used it to construct a prognosis prediction model. This model was tested by the samples of 225 HCC patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC). RESULTS In predicting prognosis of the HCC patients, using the image features of manually annotated ROIs in PTME achieved C-index 0.668 in the SYSM testing dataset, which is higher than the C-index 0.648 reached by the model only using image features of tumours. Integrating ROIs of PTME and tumours achieved C-index 0.693 in the SYSM testing dataset. The model using automatically segmented ROIs of PTME and tumours achieved C-index of 0.665 (95% CI: 0.556-0.774) in the TCGA-LIHC samples, which is better than the widely used methods, WSISA (0.567), DeepGraphSurv (0.593), and SeTranSurv (0.642). Finally, we found the Texture SumAverage Skew HV on immune cell infiltration and Texture related features on desmoplastic reaction are the most important features of PTME in predicting HCC prognosis. We additionally used the model in prediction HCC recurrence for patients from SYSM-training, SYSM-testing, and TCGA-LIHC datasets, indicating the important roles of PTME in the prediction. CONCLUSIONS Our results indicate image features of PTME is critical for improving the prognosis prediction of HCC. Moreover, the image features related with immune cell infiltration and desmoplastic reaction of PTME are the most important factors associated with prognosis of HCC.
Collapse
Affiliation(s)
- Siying Lin
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510006, China; Department of Pathology, Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
| | - Juanjuan Yong
- Department of Pathology, Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
| | - Lei Zhang
- Department of Pancreatic-Hepato-Biliary-Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, China
| | - Xiaolong Chen
- Department of Hepatic Surgery, Liver Transplantation, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, China
| | - Liang Qiao
- Storr Liver Centre, Westmead Institute for Medical Research, University of Sydney at Westmead Hospital, Westmead, NSW, 2145, Australia
| | - Weidong Pan
- Department of Pancreatic-Hepato-Biliary-Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, China
| | - Yuedong Yang
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510006, China.
| | - Huiying Zhao
- Department of Pathology, Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
| |
Collapse
|
7
|
Zhang Y, Shen N, Jiang A, Zhao J, Sang Y, Wang A, Shen W, Gao Y. Multiomics-based classifier to decipher immune landscape of uveal melanoma and predict patient outcomes. J Biomol Struct Dyn 2024:1-17. [PMID: 38468495 DOI: 10.1080/07391102.2024.2318656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 02/08/2024] [Indexed: 03/13/2024]
Abstract
Uveal melanoma (UVM) prognosis and the possibilities for targeted therapy depend on a thorough understanding of immune infiltration features and the analysis of genomic and immune signatures. Leveraging multi-omics data from The Cancer Genome Atlas and GEO datasets, we employed an unsupervised clustering algorithm to categorize UVM into immune-related subgroups. Subsequent multi-omics analysis revealed two distinct UVM subtypes, each characterized by unique genomic mutations and immune microenvironment disparities. The aggressive UMCS2 subtype exhibited higher TNM stage and poorer survival, marked by elevated metabolism and increased immune infiltration. However, UMCS2 displayed heightened tumor mutational burden and immune dysfunction, leading to reduced responsiveness to immunotherapy. Importantly, these subtypes demonstrated differential sensitivity to targeted drugs due to significant variances in metabolic and immune environments, with UMCS2 displaying lower sensitivity. We developed a robust, subtype-specific marker-based risk scoring system. This system's diagnostic accuracy was validated through ROC curves, decision curve analysis, and calibration curves, all yielding satisfactory results. Additionally, cell experiments identified the pivotal function of HTR2B, the most crucial factor in this risk model. Knocking down HTR2B significantly reduced the activity, proliferation, and invasion ability of the UVM cell line. These findings underscored the impact of gene and immune microenvironment alterations in driving distinct molecular subtypes, emphasizing the need for precise treatment strategies. The molecular subtyping-based risk assessment system not only aids in predicting patient prognosis but also guides the identification of populations suitable for combined treatment. Molecules represented by HTR2B in the model may serve as effective therapeutic targets for UVM.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Yuan Zhang
- Department of Ophthalmology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Ni Shen
- Department of Ophthalmology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Aimin Jiang
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Jiawei Zhao
- Department of Ophthalmology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Yanzhi Sang
- Department of Ophthalmology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Anbang Wang
- Department of Urology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Wei Shen
- Department of Ophthalmology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Yu Gao
- Department of Ophthalmology, Changhai Hospital, Naval Medical University, Shanghai, China
| |
Collapse
|
8
|
Zheng H, Han X, Liu Q, Zhou L, Zhu Y, Wang J, Hu W, Zhu F, Liu R. Construction of immune-related molecular diagnostic and predictive models of hepatocellular carcinoma based on machine learning. Heliyon 2024; 10:e24854. [PMID: 38312556 PMCID: PMC10835357 DOI: 10.1016/j.heliyon.2024.e24854] [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: 08/13/2023] [Revised: 01/10/2024] [Accepted: 01/16/2024] [Indexed: 02/06/2024] Open
Abstract
Background To exploit hepatocellular carcinoma (HCC) diagnostic substances, we identify potential predictive markers based on machine learning and to explore the significance of immune cell infiltration in this pathology. Method Three HCC gene expression datasets were used for weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest were applied to identify candidate biomarkers. The diagnostic value of HCC diagnostic gene biomarkers was further assessed by the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from HCC patients and to analyze their correlation with diagnostic markers. In addition, the prognostic value of the markers and the sensitivity of the drugs were analyzed. Result WGCNA and differential expression analysis were used to screen 396 distinct gene signatures in HCC tissues. They were mostly engaged in cytoplasmic fusion and the cell division cycle, according to gene enrichment analyses. Five genes were shown to have a high diagnostic value for use as diagnostic biomarkers for HCC, including EFHD1 (AUC = 0.77), KIF4A (AUC = 0.97), UBE2C (AUC = 0.96), SMYD3 (AUC = 0.91), and MCM7 (AUC = 0.93). T cells, NK cells, macrophages, and dendritic cells were found to be related to diagnostic markers in HCC tissues by immune cell infiltration analysis, indicating that these cells are intimately linked to the onset and spread of HCC. Concurrently, these five genes and their constructed models have considerable prognostic value. Conclusion These five genes (EFHD1, KIF4A, UBE2C, SMYD3, and MCM7) may serve as new candidate molecular markers for HCC, providing new insights for future diagnosis, prognosis, and molecular therapy of HCC.
Collapse
Affiliation(s)
- Hui Zheng
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
| | - Xu Han
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Qian Liu
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
| | - Li Zhou
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Yawen Zhu
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Jiaqi Wang
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
| | - Wenjing Hu
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
| | - Fengcai Zhu
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
- National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu Province, China
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Ran Liu
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
| |
Collapse
|
9
|
Zheng Q, Gong Z, Li B, Cheng R, Luo W, Huang C, Wang H. Identification and characterization of CLEC11A and its derived immune signature in gastric cancer. Front Immunol 2024; 15:1324959. [PMID: 38348052 PMCID: PMC10859539 DOI: 10.3389/fimmu.2024.1324959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 01/05/2024] [Indexed: 02/15/2024] Open
Abstract
Introduction C-type lectin domain family 11 member A (CLEC11A) was characterized as a growth factor that mainly regulates hematopoietic function and differentiation of bone cells. However, the involvement of CLEC11A in gastric cancer (GC) is not well understood. Methods Transcriptomic data and clinical information pertaining to GC were obtained and analyzed from publicly available databases. The relationships between CLEC11A and prognoses, genetic alterations, tumor microenvironment (TME), and therapeutic responses in GC patients were analyzed by bioinformatics methods. A CLEC11A-derived immune signature was developed and validated, and its mutational landscapes, immunological characteristics as well as drug sensitivities were explored. A nomogram was established by combining CLEC11A-derived immune signature and clinical factors. The expression and carcinogenic effects of CLEC11A in GC were verified by qRT-PCR, cell migration, invasion, cell cycle analysis, and in vivo model analysis. Myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), M2 macrophages, and T cells in tumor samples extracted from mice were analyzed utilizing flow cytometry analysis. Results CLEC11A was over-expressed in GC, and the elevated CLEC11A expression indicated an unfavorable prognosis in GC patients. CLEC11A was involved in genomic alterations and associated with the TME in GC. Moreover, elevated CLEC11A was found to reduce the benefit of immunotherapy according to immunophenoscore (IPS) and the tumor immune dysfunction, exclusion (TIDE). After validation, the CLEC11A-derived immune signature demonstrated a consistent ability to predict the survival outcomes in GC patients. A nomogram that quantifies survival probability was constructed to improve the accuracy of prognosis prediction in GC patients. Using shRNA to suppress the expression of CLEC11A led to significant inhibitions of cell cycle progression, migration, and invasion, as well as a marked reduction of in vivo tumor growth. Moreover, the flow cytometry assay showed that the knock-down of CLEC11A increased the infiltration of cytotoxic CD8+ T cells and helper CD4+ T into tumors while decreasing the percentage of M2 macrophages, MDSCs, and Tregs. Conclusion Collectively, our findings revealed that CLEC11A could be a prognostic and immunological biomarker in GC, and CLEC11A-derived immune signature might serve as a new option for clinicians to predict outcomes and formulate personalized treatment plans for GC patients.
Collapse
Affiliation(s)
- Qing Zheng
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Zhenqi Gong
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Baizhi Li
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Runzi Cheng
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Weican Luo
- Shantou University Medical College, Shantou, China
| | - Cong Huang
- Department of Ultrasound, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Huaiming Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| |
Collapse
|
10
|
He C, Guo Z, Zhang H, Yang G, Gao J, Mo Z. Identification and validation of methylation-CpG prognostic signature for prognosis of hepatocellular carcinoma. Aging (Albany NY) 2024; 16:1733-1749. [PMID: 38244582 PMCID: PMC10866447 DOI: 10.18632/aging.205454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 12/06/2023] [Indexed: 01/22/2024]
Abstract
Epigenetic biomarkers help predict the prognosis of cancer patients and evaluating the clinical outcome of immunization therapy. In this study, we present a personalized gene methylation-CpG signature to enhance the accuracy of survival prediction for individuals with hepatocellular carcinoma (HCC). Utilizing RNA sequencing and methylation datasets from GEO as well as TCGA, we conducted single sample GSEA (ssGSEA), WGCNA, as well as Cox regression. Through these analyses, we identified 175 oxidative stress and immune-related genes along with 4 CpG loci that are associated with the prognosis of HCC. Subsequently, we constructed a prognostic signature for HCC utilizing these 4 CpG sites, referred to as the HCC Prognostic Signature of Methylation-CpG sites (HPSM). Further investigation revealed an enrichment of immune-related signal pathways in the HPSM-low group, which demonstrated a positive correlation with better survival among HCC patients. Moreover, the methylation of the CpG sites in HPSM was found to be closely linked to drug sensitivity. In vitro experiments tentatively confirmed that promoter methylation regulated the expression of BMPER, one of the CpG sites within HPSM. The expression of BMPER was significantly correlated with cell death in the oxidative stress pathway, and overexpression of BMPER effectively inhibited HCC cell proliferation. Consequently, our findings suggest that HPSM is an independent predictive factor and holds promise for accurately predicting the prognosis of HCC patients.
Collapse
Affiliation(s)
- Chunmei He
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, Guangxi, China
- Chandi Precision Medical Technology, Foshan 528000, Guangdong, China
| | - Zehao Guo
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, Guangxi, China
- Key Laboratory of Biochemistry and Molecular Biology (Guilin Medical University), Education Department of Guangxi Zhuang Autonomous Region, Guilin 541199, Guangxi, China
| | - Hao Zhang
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, Guangxi, China
- Key Laboratory of Biochemistry and Molecular Biology (Guilin Medical University), Education Department of Guangxi Zhuang Autonomous Region, Guilin 541199, Guangxi, China
| | - Ganqing Yang
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, Guangxi, China
| | - Jintao Gao
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, Guangxi, China
- Key Laboratory of Biochemistry and Molecular Biology (Guilin Medical University), Education Department of Guangxi Zhuang Autonomous Region, Guilin 541199, Guangxi, China
| | - Zhijing Mo
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, Guangxi, China
- Key Laboratory of Biochemistry and Molecular Biology (Guilin Medical University), Education Department of Guangxi Zhuang Autonomous Region, Guilin 541199, Guangxi, China
| |
Collapse
|
11
|
Wu W, Li H, Wang Z, Dai Z, Liang X, Luo P, Liu K, Zhang H, Zhang N, Li S, Zhang C. The tertiary lymphoid structure-related signature identified PTGDS in regulating PD-L1 and promoting the proliferation and migration of glioblastoma. Heliyon 2024; 10:e23915. [PMID: 38205335 PMCID: PMC10777022 DOI: 10.1016/j.heliyon.2023.e23915] [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: 06/20/2023] [Revised: 12/12/2023] [Accepted: 12/15/2023] [Indexed: 01/12/2024] Open
Abstract
Background Tertiary lymphoid structure (TLS) is a unique organ that carries out tumor cell elimination at tumor sites. It is continuously stimulated by inflammatory tumor signals and has been found to augment immunotherapy response. However, the detailed mechanisms behind it still need to be defined. Methods To explore and grasp the whole picture of TLS from a pan-cancer view, we collected nine TLS-related genes from previous studies. We performed a comprehensive analysis of 9637 samples across 33 tumor types accessed from The Cancer Genome Atlas (TCGA) database. EdU, Transwell, and flow cytometry were performed on the feature gene PTGDS in U251 cells. The regulatory role of PTGDS on PD-L1 expression and macrophage polarization was verified. Results Alteration analysis showed that mutations of TLS-related genes were widespread and relatively high. Clustering analysis based on the expression of these nine genes obtained two distinct clusters, with high EIF1AY and PTGDS in cluster 2 and better overall survival in cluster 1. To distinguish the two clusters, we utilized six machine learning algorithms and filtrated EIF1AY, PTGDS, SKAP1, and RBP5 as the characteristic genes, among which the former two genes were proved to be hazardous. PTGDS was found to regulate PD-L1 expression and also promoted the proliferation and migration of U251 cells. The knockdown of PTGDS could reduce the migration of macrophages and inhibit the polarization of macrophages into M2-phenotype. In addition, we established a TLS score to demonstrate patients' TLS activity. The low TLS-score group overlapped with cluster 1 and displayed a better prognosis. Besides, the low TLS-score group was related to better immunotherapy responses. The HE staining of histopathological sections confirmed that the low TLS-score group exhibited higher infiltration of immune cells. Conclusion This study reveals broad molecular, tumorigenic, and immunogenic signatures for further functional and therapeutic studies of tertiary lymphoid structure. The TLS score we established effectively predicted immunotherapy response and patients' survival. Its future application and combination await more research.
Collapse
Affiliation(s)
- Wantao Wu
- The Animal Laboratory Center, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
| | - He Li
- The Animal Laboratory Center, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
- Changsha Medical University, Changsha, China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Xisong Liang
- Department of Neurosurgery, Xiangya Hospital, Central South University Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Kun Liu
- Department of Neurosugery, The Second People's Hospital of Hunan Province, The Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Hao Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Nan Zhang
- College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- College of Bioinformatics Science and Technology, Harbin Medical University Harbin, China
| | - Shuyu Li
- Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Chi Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| |
Collapse
|
12
|
Zhang W, Xiao Y, Zhou Q, Zhu X, Zhang Y, Xiang Q, Wu S, Song X, Zhao J, Yuan R, Xiao B, Li L. KNSTRN Is a Prognostic Biomarker That Is Correlated with Immune Infiltration in Breast Cancer and Promotes Cell Cycle and Proliferation. Biochem Genet 2024:10.1007/s10528-023-10615-2. [PMID: 38198023 DOI: 10.1007/s10528-023-10615-2] [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: 09/25/2023] [Accepted: 11/29/2023] [Indexed: 01/11/2024]
Abstract
Kinetochore-localized astrin/SPAG5-binding protein (KNSTRN) promotes the progression of bladder cancer and lung adenocarcinoma. However, its expression and biological function in breast cancer remain largely unknown. Therefore, this study aimed to analyze KNSTRN expression, prognoses, correlation with immune infiltration, expression-associated genes, and regulated signaling pathways to characterize its role in regulating the cell cycle using both bioinformatics and in vitro functional experiments. Analyses of The Cancer Genome Atlas, Gene Expression Omnibus, TIMER, and The Human Protein Atlas databases revealed a significant upregulation of KNSTRN transcript and protein levels in breast cancer. Kaplan-Meier survival analyses demonstrated a significant association between high expression of KNSTRN and poor overall survival, relapse-free survival, post-progression survival, and distant metastases-free survival in patients with breast cancer. Furthermore, multivariate Cox regression analyses confirmed that KNSTRN is an independent prognostic factor for breast cancer. Immune infiltration analysis indicated a positive correlation between KNSTRN expression and T regulatory cell infiltration while showing a negative correlation with Tgd and natural killer cell infiltration. Gene set enrichment analysis along with single-cell transcriptome data analysis suggested that KNSTRN promoted cell cycle progression by regulating the expression of key cell cycle proteins. The overexpression and silencing of KNSTRN in vitro, respectively, promoted and inhibited the proliferation of breast cancer cells. The overexpression of KNSTRN enhanced the expression of key cell cycle regulators, including CDK4, CDK6, and cyclin D3, thereby accelerating the G1/S phase transition and leading to aberrant proliferation of breast cancer cells. In conclusion, our study demonstrates that KNSTRN functions as an oncogene in breast cancer by regulating immune response, promoting G1/S transition, and facilitating breast cancer cell proliferation. Moreover, KNSTRN has potential as a molecular biomarker for diagnostic and prognostic prediction in breast cancer.
Collapse
Affiliation(s)
- Wenwu Zhang
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
- Department of Laboratory Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, China
| | - Yuhan Xiao
- School of Public Health, Dali University, Dali, 671000, China
| | - Quan Zhou
- Department of Laboratory Medicine, General Hospital of Southern Theater Command of People's Liberation Army (PLA), Guangzhou, 510010, China
| | - Xin Zhu
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Yanxia Zhang
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Qin Xiang
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Shunhong Wu
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Xiaoyu Song
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Junxiu Zhao
- School of Public Health, Dali University, Dali, 671000, China
| | - Ruanfei Yuan
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Bin Xiao
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China.
| | - Linhai Li
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China.
- Department of Laboratory Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, China.
| |
Collapse
|
13
|
Cheng M, Wang L, Xuan Y, Zhai Z. Identification of genes and pathways associated with menopausal status in breast cancer patients using two algorithms. BMC Womens Health 2024; 24:4. [PMID: 38166892 PMCID: PMC10763477 DOI: 10.1186/s12905-023-02846-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 12/14/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Menopausal status has a known relationship with the levels of estrogen, progesterone, and other sex hormones, potentially influencing the activity of ER, PR, and many other signaling pathways involved in the initiation and progression of breast cancer. However, the differences between premenopausal and postmenopausal breast cancer patients at the molecular level are unclear. METHODS We retrieved eight datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) associated with menopausal status in breast cancer patients were identified using the MAMA and LIMMA methods. Based on these validated DEGs, we performed Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) networks were constructed. We used DrugBank data to investigate which of these validated DEGs are targetable. Survival analysis was performed to explore the influence of these genes on breast cancer patient prognosis. RESULTS We identified 762 DEGs associated with menopausal status in breast cancer patients. PPI network analysis indicated that these genes are primarily involved in pathways such as the cell cycle, oocyte meiosis and progesterone-mediated oocyte maturation pathways. Notably, several genes played roles in multiple signaling pathways and were associated with patient survival. These genes were also observed to be targetable according to the DrugBank database. CONCLUSION We identified DEGs associated with menopausal status in breast cancer patients. The association of these genes with several key pathways may promote understanding of the complex characterizations of breast cancer. Our findings offer valuable insights for developing new therapeutic strategies tailored to the menopausal status of breast cancer patients.
Collapse
Affiliation(s)
- Minzhang Cheng
- Jiangxi Clinical Research Center for Respiratory Diseases, Jiangxi Institute of Respiratory Disease, the Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China
- Jiangxi Key Laboratory of Molecular Diagnostics and Precision Medicine, Center for Experimental Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China
| | - Lingchen Wang
- School of Public Health, University of Nevada, Reno, Reno, Nevada, 89557, USA
| | - Yanlu Xuan
- Jiangxi Clinical Research Center for Respiratory Diseases, Jiangxi Institute of Respiratory Disease, the Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China
| | - Zhenyu Zhai
- Jiangxi Key Laboratory of Molecular Diagnostics and Precision Medicine, Center for Experimental Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China.
| |
Collapse
|
14
|
Ali N, Wolf C, Kanchan S, Veerabhadraiah SR, Bond L, Turner MW, Jorcyk CL, Hampikian G. 9S1R nullomer peptide induces mitochondrial pathology, metabolic suppression, and enhanced immune cell infiltration, in triple-negative breast cancer mouse model. Biomed Pharmacother 2024; 170:115997. [PMID: 38118350 PMCID: PMC10872342 DOI: 10.1016/j.biopha.2023.115997] [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: 09/30/2023] [Revised: 12/04/2023] [Accepted: 12/06/2023] [Indexed: 12/22/2023] Open
Abstract
Nullomers are the shortest strings of absent amino acid (aa) sequences in a species or group of species. Primes are those nullomers that have not been detected in the genome of any species. 9S1R is a 5-aa peptide prime sequence attached to 5-arginine aa, used to treat triple negative breast cancer (TNBC) in an in vivo mouse model. This unique peptide, administered with a trehalose carrier (9S1R-NulloPT), offers enhanced solubility and exhibits distinct anti-cancer effects against TNBC. In our study, we investigated the effect of 9S1R-NulloPT on tumor growth, metabolism, metastatic burden, tumor immune-microenvironment (TME), and transcriptome of aggressive mouse TNBC tumors. Notably, treated mice had smaller tumors in the initial phase of the treatment, as compared to untreated control, and diminished in vivo and ex vivo bioluminescence at later-stages - indicative of metabolically quiescent, dying tumors. The treatment also caused changes in TME with increased infiltration of immune cells and altered tumor transcriptome, with 365 upregulated genes and 710 downregulated genes. Consistent with in vitro data, downregulated genes were enriched in cellular metabolic processes (179), specifically mitochondrial TCA cycle/oxidative phosphorylation (44), and translation machinery/ribosome biogenesis (45). The upregulated genes were associated with the developmental (13), ECM organization (12) and focal adhesion pathways (7). In conclusion, our study demonstrates that 9S1R-NulloPT effectively reduced tumor growth during its initial phase, altering the TME and tumor transcriptome. The treatment induced mitochondrial pathology which led to a metabolic deceleration in tumors, aligning with in vitro observations.
Collapse
Affiliation(s)
- Nilufar Ali
- Department of Biological Sciences, Boise State University, Boise, ID, USA.
| | - Cody Wolf
- Department of Biological Sciences, Boise State University, Boise, ID, USA; Biomolecular Sciences Graduate Programs, Boise State University, Boise, ID, USA
| | - Swarna Kanchan
- Department of Biological Sciences, Boise State University, Boise, ID, USA; Department of Biomedical Sciences, Jaon C. Edwards School of Medicine, Marshall University, Huntington, WV, USA
| | - Shivakumar R Veerabhadraiah
- Department of Orthopaedics, University of Utah, Salt Lake City, UT, USA; Biomolecular Sciences Graduate Programs, Boise State University, Boise, ID, USA
| | - Laura Bond
- Center of Biomedical Research Excellence in Matrix Biology, Boise State University, Boise, ID, USA
| | - Matthew W Turner
- Biomolecular Research Center, Boise State University, Boise, ID, USA; Biomolecular Sciences Graduate Programs, Boise State University, Boise, ID, USA
| | - Cheryl L Jorcyk
- Department of Biological Sciences, Boise State University, Boise, ID, USA; Biomolecular Research Center, Boise State University, Boise, ID, USA; Biomolecular Sciences Graduate Programs, Boise State University, Boise, ID, USA
| | - Greg Hampikian
- Department of Biological Sciences, Boise State University, Boise, ID, USA.
| |
Collapse
|
15
|
Huang C, Deng M, Leng D, Sun B, Zheng P, Zhang XD. MIRS: An AI scoring system for predicting the prognosis and therapy of breast cancer. iScience 2023; 26:108322. [PMID: 38026206 PMCID: PMC10665820 DOI: 10.1016/j.isci.2023.108322] [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: 10/22/2022] [Revised: 09/25/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023] Open
Abstract
Tumor-infiltrating immune cells (TIICs) and metastasis are crucial characteristics for tumorigenesis. However, the potential role of their combination in breast cancer (BRCA) remains elusive. Herein, on the basis of quantifying TIICs and tumor metastasis together, we established a precise prognostic scoring system named metastatic and immunogenomic risk score (MIRS) using a neural network model. MIRS showed better performance when compared with other published signatures. MIRS stratifies patients into a high risk subtype (MIRShigh) and a low risk subtype (MIRSlow). The MIRShigh patients exhibit significantly lower survival rate compared with MIRSlow patients (P < 0.0001 ), higher response to chemotherapy, but lower response to immunotherapy. Conversely, higher infiltration level of TIICs and significantly prolonged survival (P = 0.029 ) are observed in MIRSlow patients, indicating sensitive response in immunotherapy. This work presents a promising indicator to guide treatment options of the BRCA population and provides a predicted webtool that is almost universally applicable to BRCA patients.
Collapse
Affiliation(s)
- Chen Huang
- Dr. Neher’s Biophysics Laboratory for Innovative Drug Discovery, Macau University of Science and Technology, Macau SAR 999078, China
- State Key laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau SAR 999078, China
| | - Min Deng
- CRDA, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR 999078, China
| | - Dongliang Leng
- CRDA, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR 999078, China
| | - Baoqing Sun
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 511436, China
| | - Peiyan Zheng
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 511436, China
| | - Xiaohua Douglas Zhang
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY 40536, USA
| |
Collapse
|
16
|
Li Y, Tang M, Dang W, Zhu S, Wang Y. Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in colorectal cancer. J Cancer Res Clin Oncol 2023; 149:13995-14014. [PMID: 37543978 DOI: 10.1007/s00432-023-05211-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 07/25/2023] [Indexed: 08/08/2023]
Abstract
BACKGROUND Colorectal cancer is the second leading cause of cancer-related deaths, which imposes a significant societal burden. Regular screening and emerging molecular tumor markers have important implications for detecting the progression and development of colorectal cancer. Disulfidptosis is a newly defined type of programmed cell death triggered by abnormal accumulation of disulfide compounds in cells that stimulate disulfide stress. Currently, there is no relevant discussion on this mechanism and colorectal cancer. METHODS We classified the disulfidptosis-related subtypes of colorectal cancer using bioinformatics methods. Through secondary clustering of differentially expressed genes between subtypes, we identified characteristic genes of the disulfidptosis subtype, constructed a prognostic model, and searched for potential biomarkers through clinical validation. RESULTS Using disulfidptosis-related genes collected from the literature, we classified colorectal cancer patients from public databases into three subtypes. The differentially expressed genes between subtypes were clustered into three gene subtypes, and eight characteristic genes were screened to construct a prognostic model. CONCLUSION The disulfidptosis mechanism has important value in the classification of colorectal cancer patients, and characteristic genes selected based on this mechanism can serve as a new potential biological marker for colorectal cancer.
Collapse
Affiliation(s)
- Ying Li
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Mengyao Tang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Wei Dang
- The First College for Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Shu Zhu
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
- Department of Gastroenterology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jingshi Street, Lixia District, Jinan, Shandong, China.
| | - Yunpeng Wang
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
- Department of Gastroenterology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jingshi Street, Lixia District, Jinan, Shandong, China.
| |
Collapse
|
17
|
Hanxiao Y, Boyun Y, Minyue J, Xiaoxiao S. Identification of a novel competing endogenous RNA network and candidate drugs associated with ferroptosis in aldosterone-producing adenomas. Aging (Albany NY) 2023; 15:9193-9216. [PMID: 37709486 PMCID: PMC10522391 DOI: 10.18632/aging.205028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 08/22/2023] [Indexed: 09/16/2023]
Abstract
Aldosterone-producing adenoma (APA), characterized by unilaterally excessive aldosterone production, is a common cause of primary aldosteronism. Ferroptosis, a recently raised iron-dependent mode of programmed cell death, has been involved in the development and therapy of various diseases. This study obtained datasets of the mRNA and lncRNA expression profiles for APA and adjacent adrenal gland (AAG) from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and lncRNAs (DE lncRNAs) associated with ferroptosis were identified. Enrichment analyses indicated 89 ferroptosis-related DEGs were primarily enriched in ROS related processes and ferroptosis. Two physical cores, and one combined core were identified in the protein-protein interaction (PPI). DEGs and clinical traits were used in conjunction to screen eight hub genes from two hub modules and 89 DEGs. A competitive endogenous RNA (ceRNA) network was constructed via co-express analysis. Thereafter, molecular docking was used to identify potential targets. Two active compounds, QL-X-138 and MK-1775, bound to AURKA and DUOX1, respectively, with the lowest binding energies. Molecular dynamics simulation verified the stability of the two complexes. In summary, our studies identified eight hub genes and a novel ceRNA regulatory network associated with ferroptosis, wherein QL-X-138 and MK-1775 were considered to be potential drugs for treating APA.
Collapse
Affiliation(s)
- Yu Hanxiao
- Clinical Research Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yang Boyun
- Department of Allergy, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jia Minyue
- Department of Ultrasound, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Song Xiaoxiao
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| |
Collapse
|
18
|
Ali N, Wolf C, Kanchan S, Veerabhadraiah SR, Bond L, Turner MW, Jorcyk CL, Hampikian G. Nullomer peptide increases immune cell infiltration and reduces tumor metabolism in triple negative breast cancer mouse model. RESEARCH SQUARE 2023:rs.3.rs-3097552. [PMID: 37461536 PMCID: PMC10350184 DOI: 10.21203/rs.3.rs-3097552/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Background Nullomers are the shortest strings of absent amino acid (aa) sequences in a species or group of species. Primes are those nullomers that have not been detected in the genome of any species. 9S1R is a 5-aa peptide derived from a prime sequence that is tagged with 5 arginine aa, used to treat triple negative breast cancer (TNBC) in an in vivo TNBC mouse model. 9S1R is administered in trehalose (9S1R-NulloPT), which enhances solubility and exhibits some independent effects against tumor growth and is thus an important component in the drug preparation. Method We examined the effect of 9S1R-NulloPT on tumor growth, metabolism, metastatic burden, necrosis, tumor immune microenvironment, and the transcriptome of aggressive mouse TNBC tumors. Results The peptide-treated mice had smaller tumors in the initial phase of the treatment, as compared to the untreated control, and reduced in vivo bioluminescence at later stages, which is indicative of metabolically inactive tumors. A decrease in ex vivo bioluminescence was also observed in the excised tumors of treated mice, but not in the secondary metastasis in the lungs. The treatment also caused changes in tumor immune microenvironment with increased infiltration of immune cells and margin inflammation. The treatment upregulated 365 genes and downregulated 710 genes in tumors compared to the untreated group. Consistent with in vitro findings in breast cancer cell lines, downregulated genes in the treated TNBC tumors include Cellular Metabolic Process Related genes (179), specifically mitochondrial genes associated with TCA cycle/oxidative phosphorylation (44), and translation machinery/ribosome biogenesis genes (45). Among upregulated genes, the Developmental Pathway (13), ECM Organization (12) and Focal Adhesion Related Pathways (7) were noteworthy. We also present data from a pilot study using a bilateral BC mouse model, which supports our findings. Conclusion In conclusion, although 9S1R-NulloPT was moderate at reducing the tumor volume, it altered the tumor immune microenvironment as well as the tumor transcriptome, rendering tumors metabolically less active by downregulating the mitochondrial function and ribosome biogenesis. This corroborates previously published in vitro findings.
Collapse
|
19
|
Bauer M, Vetter M, Stückrath K, Yohannes M, Desalegn Z, Yalew T, Bekuretsion Y, Kenea TW, Joffe M, van den Berg EJ, Nikulu JI, Bakarou K, Manraj SS, Ogunbiyi OJ, Ekanem IO, Igbinoba F, Diomande M, Adebamowo C, Dzamalala CP, Anele AA, Zietsman A, Galukande M, Foerster M, dos-Santos-Silva I, Liu B, Santos P, Jemal A, Abebe T, Wickenhauser C, Seliger B, McCormack V, Kantelhardt EJ. Regional Variation in the Tumor Microenvironment, Immune Escape and Prognostic Factors in Breast Cancer in Sub-Saharan Africa. Cancer Immunol Res 2023; 11:720-731. [PMID: 37058582 PMCID: PMC10552870 DOI: 10.1158/2326-6066.cir-22-0795] [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: 10/07/2022] [Revised: 01/18/2023] [Accepted: 04/10/2023] [Indexed: 04/16/2023]
Abstract
The low overall survival rates of patients with breast cancer in sub-Saharan Africa (SSA) are driven by regionally differing tumor biology, advanced tumor stages at diagnosis, and limited access to therapy. However, it is not known whether regional differences in the composition of the tumor microenvironment (TME) exist and affect patients' prognosis. In this international, multicentre cohort study, 1,237 formalin-fixed, paraffin-embedded breast cancer samples, including samples of the "African Breast Cancer-Disparities in Outcomes (ABC-DO) Study," were analyzed. The immune cell phenotypes, their spatial distribution in the TME, and immune escape mechanisms of breast cancer samples from SSA and Germany (n = 117) were investigated using histomorphology, conventional and multiplex IHC, and RNA expression analysis. The data revealed no regional differences in the number of tumor-infiltrating lymphocytes (TIL) in the 1,237 SSA breast cancer samples, while the distribution of TILs in different breast cancer IHC subtypes showed regional diversity, particularly when compared with German samples. Higher TIL densities were associated with better survival in the SSA cohort (n = 400), but regional differences concerning the predictive value of TILs existed. High numbers of CD163+ macrophages and CD3+CD8+ T cells accompanied by reduced cytotoxicity, altered IL10 and IFNγ levels and downregulation of MHC class I components were predominantly detected in breast cancer samples from Western SSA. Features of nonimmunogenic breast cancer phenotypes were associated with reduced patient survival (n = 131). We therefore conclude that regional diversity in the distribution of breast cancer subtypes, TME composition, and immune escape mechanisms should be considered for therapy decisions in SSA and the design of personalized therapies. See related Spotlight by Bergin et al., p. 705.
Collapse
Affiliation(s)
- Marcus Bauer
- Department of Pathology, University Hospital Halle, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Global Health Working Group, Institute of Medical Epidemiology, Biometrics and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Martina Vetter
- Department of Gynecology, University Hospital Halle, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Kathrin Stückrath
- Department of Gynecology, University Hospital Halle, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Meron Yohannes
- Department of Medical Laboratory Science, College of Health sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Zelalem Desalegn
- Department of Microbiology, Immunology & Parasitology, School of Medicine, College of Health Sciences, Tikur Anbessa Specialized Hospital, Addis Ababa University, Addis Ababa, Ethiopia
| | - Tewodros Yalew
- Department of Pathology, Tikur Anbessa Specialized University Hospital, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Yonas Bekuretsion
- Department of Pathology, Tikur Anbessa Specialized University Hospital, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Tariku W. Kenea
- Department of Surgery, Aira General Hospital, Aira, Ethiopia
| | - Maureen Joffe
- Noncommunicable Diseases Research Division, Wits Health Consortium (PTY) Ltd, Johannesburg, South Africa and U Witwatersrand, Faculty of Health Sciences, Strengthening Oncology Services Research Unit
- SAMRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Eunice J van den Berg
- Department of Anatomical Pathology, University of the Witwatersrand, National Health Laboratory Service, Johannesburg, South Africa
| | - Julien I. Nikulu
- Ligue congolaise contre le cancer, l’Unité Pilote du GFAOP, Lubumbashi, Democratic Republic of the Congo
| | - Kamate Bakarou
- Service d’anatomie, Cytologie Pathologique au C.H.U. du point G BP:333, Bamako, Mali
| | - Shyam S. Manraj
- Central Health Laboratory, Victoria Hospital, Candos, Mauritius
| | - Olufemi J. Ogunbiyi
- Department of Pathology, University College Hospital, Ibadan, Oyo state, Nigeria
| | - Ima-Obong Ekanem
- Department of Pathology, Calabar Cancer Registry, University of Calabar Teaching Hospital, Calabar, Nigeria
| | | | - Mohenou Diomande
- Service d’anatomie et cytologie pathologiques, Abidjan, Côte d’Ivoire
| | - Clement Adebamowo
- Department of Epidemiology and Public Health, and the Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore
| | | | | | - Annelle Zietsman
- AB May Cancer Centre, Windhoek Central Hospital, Windhoek, Namibia
| | - Moses Galukande
- College of Health Sciences, Makerere University, Kampala, Uganda
| | - Milena Foerster
- International Agency for Research on Cancer (IARC/WHO), Environment and Lifestyle Epidemiology Branch, Lyon, France
| | - Isabel dos-Santos-Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine (LSHTM)
| | - Biying Liu
- African Cancer Registry Network, Oxford, United Kingdom
| | - Pablo Santos
- Global Health Working Group, Institute of Medical Epidemiology, Biometrics and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Ahmedin Jemal
- Surveillance and Health Equity Science, American Cancer Society, Atlanta, Georgia, USA
| | - Tamrat Abebe
- Department of Medical Laboratory Science, College of Health sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Claudia Wickenhauser
- Department of Pathology, University Hospital Halle, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Barbara Seliger
- Medical Faculty, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Institute of Translational Immunology, Medical School ‘Theodor Fontane, Brandenburg an der Havel, Germany
- Fraunhofer Institute for Immunology, Leipzig, Germany
| | - Valerie McCormack
- International Agency for Research on Cancer (IARC/WHO), Environment and Lifestyle Epidemiology Branch, Lyon, France
| | - Eva J. Kantelhardt
- Global Health Working Group, Institute of Medical Epidemiology, Biometrics and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Department of Gynecology, University Hospital Halle, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| |
Collapse
|
20
|
Song L, Wang Y, Feng Y, Peng H, Wang C, Duan J, Liu K, Shen X, Gu W, Qi Y, Jin S, Pang L. Bioinformatics-Based Identification of CircRNA-MicroRNA-mRNA Network for Calcific Aortic Valve Disease. Genet Res (Camb) 2023; 2023:8194338. [PMID: 37234568 PMCID: PMC10208756 DOI: 10.1155/2023/8194338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 02/13/2023] [Accepted: 04/24/2023] [Indexed: 05/28/2023] Open
Abstract
Background Calcific aortic valve disease (CAVD) is the most common native valve disease. Valvular interstitial cell (VIC) osteogenic differentiation and valvular endothelial cell (VEC) dysfunction are key steps in CAVD progression. Circular RNA (circRNAs) is involved in regulating osteogenic differentiation with mesenchymal cells and is associated with multiple disease progression, but the function of circRNAs in CAVD remains unknown. Here, we aimed to investigate the effect and potential significance of circRNA-miRNA-mRNA networks in CAVD. Methods Two mRNA datasets, one miRNA dataset, and one circRNA dataset of CAVD downloaded from GEO were used to identify DE-circRNAs, DE-miRNAs, and DE-mRNAs. Based on the online website prediction function, the common mRNAs (FmRNAs) for constructing circRNA-miRNA-mRNA networks were identified. GO and KEGG enrichment analyses were performed on FmRNAs. In addition, hub genes were identified by PPI networks. Based on the expression of each data set, the circRNA-miRNA-hub gene network was constructed by Cytoscape (version 3.6.1). Results 32 DE-circRNAs, 206 DE-miRNAs, and 2170 DE-mRNAs were identified. Fifty-nine FmRNAs were obtained by intersection. The KEGG pathway analysis of FmRNAs was enriched in pathways in cancer, JAK-STAT signaling pathway, cell cycle, and MAPK signaling pathway. Meanwhile, transcription, nucleolus, and protein homodimerization activity were significantly enriched in GO analysis. Eight hub genes were identified based on the PPI network. Three possible regulatory networks in CAVD disease were obtained based on the biological functions of circRNAs including: hsa_circ_0026817-hsa-miR-211-5p-CACNA1C, hsa_circ_0007215-hsa-miR-1252-5p-MECP2, and hsa_circ_0007215-hsa-miR-1343-3p- RBL1. Conclusion The present bionformatics analysis suggests the functional effect for the circRNA-miRNA-mRNA network in CAVD pathogenesis and provides new targets for therapeutics.
Collapse
Affiliation(s)
- Linghong Song
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Yubing Wang
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Yufei Feng
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Hao Peng
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Chengyan Wang
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Juncang Duan
- Department of Cardiology, Jinhua Municipal Central Hospital, Jinhua, Zhejiang, China
| | - Kejian Liu
- Department of Cardiology, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Xihua Shen
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Wenyi Gu
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | - Yan Qi
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
- Department of Pathology, Central People's Hospital of Zhanjiang and Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Shan Jin
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
| | - Lijuan Pang
- NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China
- Department of Pathology, Central People's Hospital of Zhanjiang and Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong, China
| |
Collapse
|
21
|
Hou X, Ma B, Liu M, Zhao Y, Chai B, Pan J, Wang P, Li D, Liu S, Song F. The transcriptional risk scores for kidney renal clear cell carcinoma using XGBoost and multiple omics data. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:11676-11687. [PMID: 37501415 DOI: 10.3934/mbe.2023519] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Most kidney cancers are kidney renal clear cell carcinoma (KIRC) that is a main cause of cancer-related deaths. Polygenic risk score (PRS) is a weighted linear combination of phenotypic related alleles on the genome that can be used to assess KIRC risk. However, standalone SNP data as input to the PRS model may not provide satisfactory result. Therefore, Transcriptional risk scores (TRS) based on multi-omics data and machine learning models were proposed to assess the risk of KIRC. First, we collected four types of multi-omics data (DNA methylation, miRNA, mRNA and lncRNA) of KIRC patients from the TCGA database. Subsequently, a novel TRS method utilizing multiple omics data and XGBoost model was developed. Finally, we performed prevalence analysis and prognosis prediction to evaluate the utility of the TRS generated by our method. Our TRS methods exhibited better predictive performance than the linear models and other machine learning models. Furthermore, the prediction accuracy of combined TRS model was higher than that of single-omics TRS model. The KM curves showed that TRS was a valid prognostic indicator for cancer staging. Our proposed method extended the current definition of TRS from standalone SNP data to multi-omics data and was superior to the linear models and other machine learning models, which may provide a useful implement for diagnostic and prognostic prediction of KIRC.
Collapse
Affiliation(s)
- Xiaoyu Hou
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Baoshan Ma
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Ming Liu
- Physical Department of Science and Technology, Dalian University, Dalian 116622, China
| | - Yuxuan Zhao
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Bingjie Chai
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Jianqiao Pan
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Pengcheng Wang
- Department of Mechanical Engineering, University of Houston, Houston 77204, USA
| | - Di Li
- Department of Neuro Intervention, Dalian Medical University affiliated Dalian Municipal Central Hospital, Dalian 116033, China
| | - Shuxin Liu
- Department of Nephrology, Dalian Medical University affiliated Dalian Municipal Central Hospital, Dalian 116033, China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| |
Collapse
|
22
|
Wang Y, Liu X, Yu K, Xu S, Qiu P, Zhang X, Wang M, Xu Y. A generalized non-linear model predicting efficacy of neoadjuvant therapy in HER2+ breast cancer. iScience 2023; 26:106330. [PMID: 36950120 PMCID: PMC10025957 DOI: 10.1016/j.isci.2023.106330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 01/12/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Neoadjuvant therapy (NAT) is currently recommended to patients with human epidermal growth factor receptor 2-positive breast cancer (HER2+ BC) that typically exhibit a poor prognosis. The tumor immune microenvironment profoundly affects the efficacy of NAT. However, the correlation between tumor-infiltrating lymphocytes or their specific subpopulations and the response to NAT in HER2+ BC remains largely unknown. In our study, the immune infiltration status of 295 patients was classified as "immune-rich" or "immune-poor" phenotypes. The "immune-rich" phenotype was significantly positively related to pathological complete response (pCR). Ten genes were correlated with both pCR and the immune phenotype based on the results of spline and logistic regression. We constructed a generalized non-linear model combining linear and non-linear gene effects and successfully validated its predictive power using an internal and external validation set (AUC = 0.819, 0.797; respectively) and a clinical set (accuracy = 0.75).
Collapse
Affiliation(s)
- Yusong Wang
- Department of Breast Surgery, The First Hospital of China Medical University, Shenyang, Liaoning Province 110001, China
| | - Xiaoyan Liu
- Department of Breast Surgery, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, Liaoning Province 110801, China
| | - Keda Yu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Cancer Institute, Shanghai 200032, China
| | - Shouping Xu
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province 150081, China
| | - Pengfei Qiu
- Breast Cancer Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, Shandong Province 250117, China
| | - Xinwen Zhang
- Center of Implant Dentistry, School and Hospital of Stomatology, China Medical University, Liaoning Provincial Key Laboratory of Oral Disease, Shenyang, Liaoning Province 110001, China
| | - Mozhi Wang
- Department of Breast Surgery, The First Hospital of China Medical University, Shenyang, Liaoning Province 110001, China
- Corresponding author
| | - Yingying Xu
- Department of Breast Surgery, The First Hospital of China Medical University, Shenyang, Liaoning Province 110001, China
- Corresponding author
| |
Collapse
|
23
|
Vishnubalaji R, Alajez NM. Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes. Cells 2023; 12:cells12081182. [PMID: 37190091 DOI: 10.3390/cells12081182] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 03/18/2023] [Accepted: 03/22/2023] [Indexed: 05/17/2023] Open
Abstract
Breast cancer (BC) is a heterogeneous disease, which is primarily classified according to hormone receptors and HER2 expression. Despite the many advances in BC diagnosis and management, the identification of novel actionable therapeutic targets expressed by cancerous cells has always been a daunting task due to the large heterogeneity of the disease and the presence of non-cancerous cells (i.e., immune cells and stromal cells) within the tumor microenvironment. In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER+), HER2+, ER+HER2+, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells' publicly available transcriptomic data derived from 26 BC patients. Restricting the analysis to EPCAM+Lin- tumor epithelial cells, we identified the enriched gene sets in each BC molecular subtype. Integration of single-cell transcriptomic with CRISPR-Cas9 functional screen data identified 13 potential therapeutic targets for ER+, 44 potential therapeutic targets for HER2+, and 29 potential therapeutic targets for TNBC. Interestingly, several of the identified therapeutic targets outperformed the current standard of care for each BC subtype. Given the aggressive nature and lack of targeted therapies for TNBC, elevated expression of ENO1, FDPS, CCT6A, TUBB2A, and PGK1 predicted worse relapse-free survival (RFS) in basal BC (n = 442), while elevated expression of ENO1, FDPS, CCT6A, and PGK1 was observed in the most aggressive BLIS TNBC subtype. Mechanistically, targeted depletion of ENO1 and FDPS halted TNBC cell proliferation, colony formation, and organoid tumor growth under 3-dimensional conditions and increased cell death, suggesting their potential use as novel therapeutic targets for TNBC. Differential expression and gene set enrichment analysis in TNBC revealed enrichment in the cycle and mitosis functional categories in FDPShigh, while ENO1high was associated with numerous functional categories, including cell cycle, glycolysis, and ATP metabolic processes. Taken together, our data are the first to unravel the unique gene signatures and to identify novel dependencies and therapeutic vulnerabilities for each BC molecular subtype, thus setting the foundation for the future development of more effective targeted therapies for BC.
Collapse
Affiliation(s)
- Radhakrishnan Vishnubalaji
- Translational Cancer and Immunity Center (TCIC), Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Doha P.O. Box 34110, Qatar
| | - Nehad M Alajez
- Translational Cancer and Immunity Center (TCIC), Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Doha P.O. Box 34110, Qatar
- College of Health & Life Sciences, Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Doha P.O. Box 34110, Qatar
| |
Collapse
|
24
|
Liu M, Zhou J, Xi Q, Liang Y, Li H, Liang P, Guo Y, Liu M, Temuqile T, Yang L, Zuo Y. A computational framework of routine test data for the cost-effective chronic disease prediction. Brief Bioinform 2023; 24:7034465. [PMID: 36772998 DOI: 10.1093/bib/bbad054] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 01/04/2023] [Accepted: 01/26/2023] [Indexed: 02/12/2023] Open
Abstract
Chronic diseases, because of insidious onset and long latent period, have become the major global disease burden. However, the current chronic disease diagnosis methods based on genetic markers or imaging analysis are challenging to promote completely due to high costs and cannot reach universality and popularization. This study analyzed massive data from routine blood and biochemical test of 32 448 patients and developed a novel framework for cost-effective chronic disease prediction with high accuracy (AUC 87.32%). Based on the best-performing XGBoost algorithm, 20 classification models were further constructed for 17 types of chronic diseases, including 9 types of cancers, 5 types of cardiovascular diseases and 3 types of mental illness. The highest accuracy of the model was 90.13% for cardia cancer, and the lowest was 76.38% for rectal cancer. The model interpretation with the SHAP algorithm showed that CREA, R-CV, GLU and NEUT% might be important indices to identify the most chronic diseases. PDW and R-CV are also discovered to be crucial indices in classifying the three types of chronic diseases (cardiovascular disease, cancer and mental illness). In addition, R-CV has a higher specificity for cancer, ALP for cardiovascular disease and GLU for mental illness. The association between chronic diseases was further revealed. At last, we build a user-friendly explainable machine-learning-based clinical decision support system (DisPioneer: http://bioinfor.imu.edu.cn/dispioneer) to assist in predicting, classifying and treating chronic diseases. This cost-effective work with simple blood tests will benefit more people and motivate clinical implementation and further investigation of chronic diseases prevention and surveillance program.
Collapse
Affiliation(s)
- Mingzhu Liu
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
- Inner Mongolia International Mongolian Hospital, Hohhot 010065, China
| | - Jian Zhou
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
| | - Qilemuge Xi
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Yuchao Liang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
| | - Haicheng Li
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
| | - Pengfei Liang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Yuting Guo
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Ming Liu
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Temuqile Temuqile
- Inner Mongolia International Mongolian Hospital, Hohhot 010065, China
| | - Lei Yang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
| | - Yongchun Zuo
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
- Inner Mongolia International Mongolian Hospital, Hohhot 010065, China
| |
Collapse
|
25
|
Yang Y, Wang Z, He M, Diao L, Yu B, Li D. NAD+ biosynthesis metabolism predicts prognosis and indicates immune microenvironment for breast cancer. Pathol Oncol Res 2023; 29:1610956. [PMID: 37006438 PMCID: PMC10063816 DOI: 10.3389/pore.2023.1610956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 02/28/2023] [Indexed: 03/19/2023]
Abstract
The growing evidence implies that tumor cells need to increase NAD+ levels by upregulating NAD+ biosynthesis to satisfy their growth demand. NAD+ biosynthesis metabolism is implicated in tumor progression. Breast cancer (BC) is the most common malignant malignancy in the world. Nevertheless, the prognostic significance of NAD+ biosynthesis and its relationship with the tumor immune microenvironment in breast cancer still need further investigation. In this study, we obtained the mRNA expression data and clinical information of BC samples from public databases and calculated the level of NAD+ biosynthesis activity by single-sample gene set enrichment analysis (ssGSEA). We then explored the relationship between the NAD+ biosynthesis score, infiltrating immune cells, prognosis significance, immunogenicity and immune checkpoint molecules. The results demonstrated that patients with high NAD+ biosynthetic score displayed poor prognosis, high immune infiltration, high immunogenicity, elevated PD-L1 expression, and might more benefit from immunotherapy. Taken together, our studies not only deepened the understanding of NAD+ biosynthesis metabolism of breast cancer but also provided new insights into personalized treatment strategies and immunological therapies to improve the outcomes of breast cancer patients.
Collapse
Affiliation(s)
- Yuting Yang
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong, China
| | - Ze Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Mengqi He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Lihong Diao
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Biyue Yu
- School of Life Sciences, Hebei University, Baoding, Hebei, China
| | - Dong Li
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong, China
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
- *Correspondence: Dong Li,
| |
Collapse
|
26
|
Liu Z, Georgakopoulos-Soares I, Ahituv N, Wong KC. Risk scoring based on DNA methylation-driven related DEGs for colorectal cancer prognosis with systematic insights. Life Sci 2023; 316:121413. [PMID: 36682524 DOI: 10.1016/j.lfs.2023.121413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/13/2023] [Accepted: 01/16/2023] [Indexed: 01/22/2023]
Abstract
Colorectal cancer is a common malignant tumor of the digestive tract. Despite advances in diagnostic techniques and medications. Its prognosis remains challenging. DNA methylation-driven related circulating tumor cells have attracted enormous interest in diagnosing owing to their non-invasive nature and early recognition properties. However, the mechanism through which risk biomarkers act remains elusive. Here, we designed a risk model based on differentially expressed genes, DNA methylation, robust, and survival-related factors in the framework of Cox regression. The model has satisfactory performance and is independently verified by an external and isolated dataset in terms of C-index value, ROC, and tROC. The model was applied to Colorectal cancer patients who were subsequently divided into high- and low-risk groups. Functional annotations, genomic alterations, tumor immune environment, and drug sensitivity were analyzed. We observed that up-regulated genes are associated with epithelial cell differentiation and MAPK signaling pathways. The down-regulated genes are related to IL-7 signaling and apoptosis-induced DNA fragmentation. Interestingly, the immune system was inhibited in high-risk groups. High-frequency mutation genes tend to co-occur. High-risk score patients are related to copy number amplification events. To address the challenges, we suggested eleven and twenty-one drugs that are sensitive to low- and high-risk patients. Finally, an artificial neural network was provided to evaluate the immunotherapeutic efficiency. Taken together, the findings demonstrated that our risk score model is robust and reliable for evaluating the prognosis with novel diagnostic and treatment targets. It also yields benefits for the treatment and provides unique insights into developing therapeutic strategies.
Collapse
Affiliation(s)
- Zhe Liu
- Department of Computer Science, City University of Hong Kong, Hong Kong, China
| | - Ilias Georgakopoulos-Soares
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Ka-Chun Wong
- Department of Computer Science, City University of Hong Kong, Hong Kong, China.
| |
Collapse
|
27
|
Hoffmann E, Gerwing M, Niland S, Niehoff R, Masthoff M, Geyer C, Wachsmuth L, Wilken E, Höltke C, Heindel WL, Hoerr V, Schinner R, Berger P, Vogl T, Eble JA, Maus B, Helfen A, Wildgruber M, Faber C. Profiling specific cell populations within the inflammatory tumor microenvironment by oscillating-gradient diffusion-weighted MRI. J Immunother Cancer 2023; 11:jitc-2022-006092. [PMID: 36918222 PMCID: PMC10016257 DOI: 10.1136/jitc-2022-006092] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND The inflammatory tumor microenvironment (TME) is formed by various immune cells, being closely associated with tumorigenesis. Especially, the interaction between tumor-infiltrating T-cells and macrophages has a crucial impact on tumor progression and metastatic spread. The purpose of this study was to investigate whether oscillating-gradient diffusion-weighted MRI (OGSE-DWI) enables a cell size-based discrimination between different cell populations of the TME. METHODS Sine-shaped OGSE-DWI was combined with the Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion (IMPULSED) approach to measure microscale diffusion distances, here relating to cell sizes. The accuracy of IMPULSED-derived cell radii was evaluated using in vitro spheroid models, consisting of either pure cancer cells, macrophages, or T-cells. Subsequently, in vivo experiments aimed to assess changes within the TME and its specific immune cell composition in syngeneic murine breast cancer models with divergent degrees of malignancy (4T1, 67NR) during tumor progression, clodronate liposome-mediated depletion of macrophages, and immune checkpoint inhibitor (ICI) treatment. Ex vivo analysis of IMPULSED-derived cell radii was conducted by immunohistochemical wheat germ agglutinin staining of cell membranes, while intratumoral immune cell composition was analyzed by CD3 and F4/80 co-staining. RESULTS OGSE-DWI detected mean cell radii of 8.8±1.3 µm for 4T1, 8.2±1.4 µm for 67NR, 13.0±1.7 for macrophage, and 3.8±1.8 µm for T-cell spheroids. While T-cell infiltration during progression of 4T1 tumors was observed by decreasing mean cell radii from 9.7±1.0 to 5.0±1.5 µm, increasing amount of intratumoral macrophages during progression of 67NR tumors resulted in increasing mean cell radii from 8.9±1.2 to 12.5±1.1 µm. After macrophage depletion, mean cell radii decreased from 6.3±1.7 to 4.4±0.5 µm. T-cell infiltration after ICI treatment was captured by decreasing mean cell radii in both tumor models, with more pronounced effects in the 67NR tumor model. CONCLUSIONS OGSE-DWI provides a versatile tool for non-invasive profiling of the inflammatory TME by assessing the dominating cell type T-cells or macrophages.
Collapse
Affiliation(s)
- Emily Hoffmann
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Mirjam Gerwing
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Stephan Niland
- Institute of Physiological Chemistry and Pathobiochemistry, University of Münster, Münster, Germany
| | - Rolf Niehoff
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Max Masthoff
- Clinic of Radiology, University of Münster, Münster, Germany
| | | | - Lydia Wachsmuth
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Enrica Wilken
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Carsten Höltke
- Clinic of Radiology, University of Münster, Münster, Germany
| | | | - Verena Hoerr
- Clinic of Radiology, University of Münster, Münster, Germany.,Department of Internal Medicine II, Heart Center Bonn, University Hospital Bonn, Bonn, Germany
| | - Regina Schinner
- Department of Radiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Philipp Berger
- Institute of Immunology, University of Münster, Münster, Germany
| | - Thomas Vogl
- Institute of Immunology, University of Münster, Münster, Germany
| | - Johannes A Eble
- Institute of Physiological Chemistry and Pathobiochemistry, University of Münster, Münster, Germany
| | - Bastian Maus
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Anne Helfen
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Moritz Wildgruber
- Clinic of Radiology, University of Münster, Münster, Germany.,Department of Radiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Cornelius Faber
- Clinic of Radiology, University of Münster, Münster, Germany
| |
Collapse
|
28
|
Liang X, Wang Z, Dai Z, Zhang H, Zhang J, Luo P, Liu Z, Liu Z, Yang K, Cheng Q, Zhang M. Glioblastoma glycolytic signature predicts unfavorable prognosis, immunological heterogeneity, and ENO1 promotes microglia M2 polarization and cancer cell malignancy. Cancer Gene Ther 2023; 30:481-496. [PMID: 36494582 PMCID: PMC10014583 DOI: 10.1038/s41417-022-00569-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 11/01/2022] [Accepted: 11/17/2022] [Indexed: 12/13/2022]
Abstract
Glioblastomas are the most malignant brain tumors, whose progress was promoted by aberrate aerobic glycolysis. The immune environment was highly engaged in glioblastoma formation, while its interaction with aerobic glycolysis remained unclear. Herein, we build a 7-gene Glycolytic Score (GS) by Elastic Net in the training set and two independent validating sets. The GS predicted malignant features and poor survival with good performances. Immune functional analyses and Cibersort calculation identified depressed T cells, B cells, natural killer cells immunity, and high immunosuppressive cell infiltration in the high-GS group. Also, high expressions of the immune-escape genes were discovered. Subsequently, the single-cell analyses validated the glycolysis-related immunosuppression. The functional results manifested the high-GS neoplastic cells' association with T cells, NK cells, and macrophage function regulation. The intercellular cross-talk showed strong associations between high-GS neoplastic cells and M2 macrophages/microglia in several immunological pathways. We finally confirmed that ENO1, the key gene of the GS, promoted M2 microglia polarization and glioblastoma cell malignant behaviors via immunofluorescence, clone formation, CCK8, and transwell rescue experiments. These results indicated the interactions between cancerous glycolysis and immunosuppression and glycolysis' role in promoting glioblastoma progression. Conclusively, we built a robust model and discovered strong interaction between GS and immune, shedding light on prognosis management improvement and therapeutic strategies development for glioblastoma patients.
Collapse
Affiliation(s)
- Xisong Liang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China.,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China.,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China.,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China
| | - Hao Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China.,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China
| | - Jian Zhang
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, 510000, P. R. China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, 510000, P. R. China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zhixiong Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China.,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China
| | - Kui Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China.,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China. .,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China.
| | - Mingyu Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, P. R. China. .,National Clinical Research Center for Geriatric Disorders, Changsha, 410008, P. R. China.
| |
Collapse
|
29
|
MARCO is a potential prognostic and immunotherapy biomarker. Int Immunopharmacol 2023; 116:109783. [PMID: 36773567 DOI: 10.1016/j.intimp.2023.109783] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 01/11/2023] [Accepted: 01/21/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Macrophage receptor with collagenous structure (MARCO), a novel immune checkpoint expressed on tumor-associated macrophages, has antitumor therapeutic properties. However, the association between MARCO and patient prognosis, immune infiltration, and ICI immunotherapy needs to be studied urgently. METHODS MARCO distribution in cancer tissues was investigated using the TCGA and GTEx databases. The PrognoScan and KM Plotter databases was used to assess the MARCO prognosis. TIMER2.0, GEPIA, cBioPortal, and GSEA all confirmed the link between MARCO and immune infiltration, mutation profile, and enrichment pathway analysis. Data visualization was implemented by R language. RESULTS In general, MARCO had a substantial impact on the prognosis of cancer patients and was expressed differently in cancer and adjacent normal tissues. High expression of MARCO was associated with poorer OS in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), lung squamous cell carcinoma (LUSC), colon adenocarcinoma (COAD), and prostate adenocarcinoma (PRAD). However, high expression of MARCO had a better PFI in brain lower-grade glioma (LGG) and skin cutaneous melanoma (SKCM). We discovered that MARCO expression was lowest in pancreatic adenocarcinoma (PAAD) and rectum adenocarcinoma (READ) stage 1, BLCA stage 2, LUSC and stomach adenocarcinoma (STAD) stage 3, and liver hepatocellular carcinoma (LIHC) stage 4. Subsequently, we analyzed the correlation between MARCO and 47 immune checkpoints and observed that MARCO was positively connected with CD80, CD86, and leukocyte-associated immunoglobulin-like receptor 1(LAIR1) in most cancers. In COAD, MARCO has the most microsatellite instability (MSI). In addition, we discovered that high expression of MARCO patients had a better prognosis after immune checkpoint inhibitor (ICI) treatment in SKCM. Finally, GSEA revealed a significant correlation between MARCO and TNF/NFκB signaling, KRAS signaling, PI3K/AKT/mTOR pathway, IL-6-STAT3 signaling, TGFβ pathway, and p53 pathway. CONCLUSION This study comprehensively investigated the relationship between MARCO and clinical prognosis, immune infiltration, and ICI immunotherapy in various cancers. We demonstrated the potential of MARCO as an emerging biomarker, exploring new avenues for future tumor immunotherapy.
Collapse
|
30
|
Prognostic Significance of the CXCLs and Its Impact on the Immune Microenvironment in Ovarian Cancer. DISEASE MARKERS 2023; 2023:5223657. [PMID: 36798787 PMCID: PMC9926335 DOI: 10.1155/2023/5223657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 01/18/2023] [Accepted: 01/19/2023] [Indexed: 02/08/2023]
Abstract
The chemokine (C-X-C motif) ligand (CXCL) family in tumor tissue is closely related to tumor growth, metastasis, and survival. However, the differential expression profile and prognostic value of the CXCLs in ovarian cancer (OC) have not been elucidated. Therefore, we studied the expression levels and mutations of CXCLs in OC patient in TCGA and various public databases. The expression differences of CXCLs in OC cancer tissues and normal tissues were compared through the Gene Expression Profiling Interactive Analysis (GEPIA) database. The effect of CXCLs on OC prognosis was analyzed using the Kaplan-Meier curves in GEPIA database. The impact of CXCLs on immune infiltration and clinicopathological outcomes in OC was assessed using the TIMER algorithm. Compared with normal tissues, we found that eight CXCLs were significantly differentially expressed in OC. The expression levels of CXCL9 (P = 0.0201), CXCL11 (P = 0.0385), and CXCL13 (P = 0.0288) were significantly associated with tumor stage. CXCL13 was the only gene that significantly affected both disease-free survival (DFS) and overall survival (OS) in OC, and higher CXCL13 transcript levels implied longer DFS and OS. Although there was no significant impact on DFS, CXCL10 (P = 0.0079) and CXCL11 (P = 0.0011) expression levels had a significant effect on OS in OC. At the same time, CXCLs were significantly associated with several immune-infiltrating cells in OC tissues. The CXCLs were significantly associated with one or more immune-infiltrating cells in OC tissue. CXCL13 was differentially expressed in OC and significantly affected the prognosis of patients and was a potential marker of OC prognosis.
Collapse
|
31
|
Su X, Gao H, Qi Z, Xu T, Wang G, Luo H, Cheng P. Prediction of immune subtypes and overall survival in lung squamous cell carcinoma. Curr Med Res Opin 2023; 39:289-298. [PMID: 36245361 DOI: 10.1080/03007995.2022.2129231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
OBJECTIVE Lung squamous cell carcinoma (LUSC), one of the most common subtypes of lung cancer, is a leading cause of cancer-caused deaths in the world. It has been well demonstrated that a deep understanding of the tumor environment in cancer would be helpful to predict the prognosis of patients. This study aimed to evaluate the tumor environment in LUSC, and to construct an efficient prognosis model involved in specific subtypes. METHODS Four expression files were downloaded from the Gene Expression Omnibus (GEO) database. Three datasets (GSE19188, GSE2088, GSE6044) were considered as the testing group and the other dataset (GSE11969) was used as the validation group. By performing LUSC immune subtype consensus clustering (CC), LUSC patients were separated into two immune subtypes comprising subtype 1 (S1) and subtype 2 (S2). Weighted gene co-expression network (WGCNA) and least absolute shrinkage and selection operator (LASSO) were performed to identify and narrow down the key genes among subtype 1 related genes that were closely related to the overall survival (OS) of LUSC patients. Using immune subtype related genes, a prognostic model was also constructed to predict the OS of LUSC patients. RESULTS It showed that LUSC patients in the S1 immune subtype exhibited a better OS than in the S2 immune subtype. WGCNA and LASSO analyses screened out important immune subtype related genes in specific modules that were closely associated with LUSC prognosis, followed by construction of the prognostic model. Both the testing datasets and validation dataset confirmed that the prognostic model could be efficiently used to predict the OS of LUSC patients in subtype 1. CONCLUSION We explored the tumor environment in LUSC and established a risk prognostic model that might have the potential to be applied in clinical practice.
Collapse
Affiliation(s)
- Xiaomei Su
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Hui Gao
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Zhongchun Qi
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Tao Xu
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Guangjie Wang
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Hong Luo
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Peng Cheng
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| |
Collapse
|
32
|
Zhang X, Xie J, He D, Yan X, Chen J. Cell Pair Algorithm-Based Immune Infiltrating Cell Signature for Improving Outcomes and Treatment Responses in Patients with Hepatocellular Carcinoma. Cells 2023; 12:cells12010202. [PMID: 36611994 PMCID: PMC9818873 DOI: 10.3390/cells12010202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 12/07/2022] [Accepted: 12/29/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Immune interactions play important roles in the regulation of T cells' cytotoxic function, further impacting the anti-tumor efficacy of immunotherapy. A comprehensive analysis of immune cell types in HCC and immune-cell-related signatures predicting prognosis and monitoring immunotherapy efficacy is still absent. METHODS More than 1,300 hepatocellular carcinomas (HCC) patients were collected from public databases and included in the present study. The ssGSEA algorithm was applied to calculate the infiltration level of 28 immunocyte subpopulations. A cell pair algorithm was applied to construct an immune-cell-related prognostic index (ICRPI). Survival analyses were performed to measure the survival difference across ICRPI risk groups. Spearman's correlation analyses were used for the relevance assessment. A Wilcoxon test was used to measure the expression level's differences. RESULTS In this study, 28 immune subpopulations were retrieved, and 374 immune cell pairs (ICPs) were established, 38 of which were picked out by the least absolute shrinkage and selection operator (LASSO) algorithm. By using the selected ICPs, the ICRPI was constructed and validated to play crucial roles in survival stratification and dynamic monitoring of immunotherapy effect. We also explored several candidate drugs targeting ICRPI. A composite ICRPI and clinical prognostic index (ICPI) was then constructed, which achieved a more accurate estimation of HCC's survival and is a better choice for prognosis predictions in HCC. CONCLUSIONS In conclusion, we constructed and validated ICRPI based on the cell pair algorithm in this study, which might provide some novel insights for increasing the survival estimation and clinical response to immune therapy for individual HCC patients and contribute to the personalized precision immunotherapy strategy of HCC.
Collapse
Affiliation(s)
- Xiao Zhang
- Department of General Surgery, Hospital of Chengdu Office of People’s Government of Tibet Autonomous Region, Chengdu 610041, China
- The Second Clinical College, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Jun Xie
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen 361004, China
| | - Dan He
- Department of General Surgery, Hospital of Chengdu Office of People’s Government of Tibet Autonomous Region, Chengdu 610041, China
| | - Xin Yan
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Correspondence: (X.Y.); (J.C.)
| | - Jian Chen
- Department of Emergency Department, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu 322000, China
- Correspondence: (X.Y.); (J.C.)
| |
Collapse
|
33
|
Ding M, Xu Q, Jin X, Han Z, Jiang H, Sun H, Jin Y, Piao Z, Zhang S. Novel exosome-related risk signature as prognostic biomarkers in glioblastoma. Front Immunol 2023; 14:1071023. [PMID: 36865549 PMCID: PMC9971586 DOI: 10.3389/fimmu.2023.1071023] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 02/02/2023] [Indexed: 02/16/2023] Open
Abstract
Exosomes are progressively being detected as an indicator for the diagnosis and prognosis of cancer in clinical settings. Many clinical trials have confirmed the impact of exosomes on tumor growth, particularly in anti-tumor immunity and immunosuppression of exosomes. Therefore, we developed a risk score based on genes found in glioblastoma-derived exosomes. In this study, we used the TCGA dataset as the training queue and GSE13041, GSE43378, GSE4412, and CGGA datasets as the external validation queue. Based on machine algorithms and bioinformatics methods, an exosome-generalized risk score was established. We found that the risk score could independently predict the prognosis of patients with glioma, and there were significant differences in the outcomes of patients in the high- and low-risk groups. Univariate and multivariate analyses showed that risk score is a valid predictive biomarker for gliomas. Two immunotherapy datasets, IMvigor210 and GSE78220, were obtained from previous studies. A high-risk score showed a significant association with multiple immunomodulators that could act on cancer immune evasion. The exosome-related risk score could predict the effectiveness of anti-PD-1 immunotherapy. Moreover, we compared the sensitivity of patients with high- and low-risk scores to various anti-cancer drugs and found that patients with high-risk scores had better responses to a variety of anti-cancer drugs. The risk-scoring model established in this study provides a useful tool to predict the total survival time of patients with glioma and guide immunotherapy.
Collapse
Affiliation(s)
- Mingyan Ding
- Department of Oncology, Yanbian University Hospital, Yanji, China
| | - Qiang Xu
- Department of Oncology, Yanbian University Hospital, Yanji, China
| | - Xiuying Jin
- Department of Oncology, Yanbian University Hospital, Yanji, China
| | - Zhezhu Han
- Department of Oncology, Yanbian University Hospital, Yanji, China
| | - Hao Jiang
- Department of Oncology, Yanbian University Hospital, Yanji, China
| | - Honghua Sun
- Department of Oncology, Yanbian University Hospital, Yanji, China
| | - Yongmin Jin
- Department of Oncology, Yanbian University Hospital, Yanji, China
| | - Zhengri Piao
- Department of Radiation Oncology, Yanbian University Hospital, Yanji, China
| | - Songnan Zhang
- Department of Oncology, Yanbian University Hospital, Yanji, China
| |
Collapse
|
34
|
Identification of an Immune-Related Gene Signature Associated with Prognosis and Tumor Microenvironment in Esophageal Cancer. BIOMED RESEARCH INTERNATIONAL 2022; 2022:7413535. [PMID: 36588538 PMCID: PMC9803573 DOI: 10.1155/2022/7413535] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/30/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022]
Abstract
Background Esophageal cancer (EC) is a common malignant tumor of the digestive system with high mortality and morbidity. Current evidence suggests that immune cells and molecules regulate the initiation and progression of EC. Accordingly, it is necessary to identify immune-related genes (IRGs) affecting the biological behaviors and microenvironmental characteristics of EC. Methods Bioinformatics methods, including differential expression analysis, Cox regression, and immune infiltration prediction, were conducted using R software to analyze the Gene Expression Omnibus (GEO) dataset. The Cancer Genome Atlas (TCGA) cohort was used to validate the prognostic signature. Patients were stratified into high- and low-risk groups for further analyses, including functional enrichment, immune infiltration, checkpoint relevance, clinicopathological characteristics, and therapeutic sensitivity analyses. Results A prognostic signature was established based on 21 IRGs (S100A7, S100A7A, LCN1, CR2, STAT4, GAST, ANGPTL5, TRAV39, F2RL2, PGLYRP3, KLRD1, TRIM36, PDGFA, SLPI, PCSK2, APLN, TICAM1, ITPR3, MAPK9, GATA4, and PLAU). Compared with high-risk patients, better overall survival rates and clinicopathological characteristics were found in low-risk patients. The areas under the curve of the two cohorts were 0.885 and 0.718, respectively. Higher proportions of resting CD4+ memory T lymphocytes, M2 macrophages, and resting dendritic cells and lower proportions of follicular helper T lymphocytes, plasma cells, and neutrophils were found in the high-risk tumors. Moreover, the high-risk group showed higher expression of CD44 and TNFSF4, lower expression of PDCD1 and CD40, and higher TIDE scores, suggesting they may respond poorly to immunotherapy. High-risk patients responded better to chemotherapeutic agents such as docetaxel, doxorubicin, and gemcitabine. Furthermore, IRGs associated with tumor progression, including PDGFA, ITPR3, SLPI, TICAM1, and GATA4, were identified. Conclusion Our immune-related signature yielded reliable value in evaluating the prognosis, microenvironmental characteristics, and therapeutic sensitivity of EC and may help with the precise treatment of this patient population.
Collapse
|
35
|
Dai Y, Yang L, Sakandar A, Zhang D, Du F, Zhang X, Zou L, Zhao Y, Wang J, Zhang Z, Wu X, Li M, Ling X, Yu L, Dong L, Shen J, Xiao Z, Wen Q. Vemurafenib inhibits immune escape biomarker BCL2A1 by targeting PI3K/AKT signaling pathway to suppress breast cancer. Front Oncol 2022; 12:906197. [DOI: 10.3389/fonc.2022.906197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 11/07/2022] [Indexed: 12/03/2022] Open
Abstract
ObjectivesTo investigate the role of immune escape encoding genes on the prognosis of BC, and to predict the novel targeting agents.MethodsHuman immune genes and immune escape encoding genes were obtained from the IMMPORT database and the previous study. Sample information and clinical data on BC were obtained from the TCGA and GTEX databases. Obtaining differentially expressed protein data from cBioportal database. To construct a risk score model by lasso analysis, and nomogram was used to predict score core. GSCA, TIMER and CELLMINER databases were used for immune and drug susceptibility correlation analyses. Cell experiments were verified by MTT, Western blotting, and RT-qPCR.ResultsWe found prognostic models consisting of eleven immune escape related protein-coding genes with ROC curves that performed well in the ontology data (AUC for TCGA is 0.672) and the external data (AUC for GSE20685 is 0.663 and for GES42568 is 0.706). Five core prognostic models are related to survival (EIF4EBP1, BCL2A1, NDRG1, ERRFI1 and BRD4) were summarized, and a nomogram was constructed to validate a C-index of 0.695, which was superior to other prognostic models. Relevant drugs targeting core genes were identified based on drug sensitivity analysis, and found that Vemurafenib downregulates the PI3K-AKT pathway and BCL2A1 protein in BC, as confirmed by external data and cellular assays.ConclusionsBriefly, our work establishes and validates an 11-immune escape risk model, and five core prognostic factors that are mined deeply from this model, and elucidates in detail that Vemurafenib suppresses breast cancer by targeting the PI3K/AKT signaling pathway to inhibit the immune escape biomarker BCL2A1, confirms the validity of the prognostic model, and provides corresponding targeted agents to guide individualized treatment of BC patients.
Collapse
|
36
|
Li K, Tan G, Zhang X, Lu W, Ren J, Si Y, Adu-Gyamfi EA, Li F, Wang Y, Xie B, Wang M. EIF4G1 Is a Potential Prognostic Biomarker of Breast Cancer. Biomolecules 2022; 12:biom12121756. [PMID: 36551184 PMCID: PMC9776011 DOI: 10.3390/biom12121756] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/18/2022] [Accepted: 11/20/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Breast cancer (BRCA) is one of the most common cancers in women worldwide and a leading cause of death from malignancy. This study was designed to identify a novel biomarker for prognosticating the survival of BRCA patients. METHODS The prognostic potential of eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) was assessed using RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) as training cohort and validation set, respectively. The functional enrichment analysis of differentially expressed genes (DEGs) was performed. The relationship between EIF4G1 and tumor microenvironment (TME) was analyzed. Immunotherapy responses were explored by the immunophenoscores (IPS) and tumor immune dysfunction and exclusion (TIDE) score. The Connectivity Map (CMap) was used to discover potentially effective therapeutic molecules against BRCA. Immunohistochemistry (IHC) was applied to compare the protein levels of EIF4G1 in normal and cancer tissues and to verify the prognostic value of EIF4G1. RESULTS BRCA patients with increased expression of EIF4G1 had a shorter overall survival (OS) in all cohorts and results from IHC. EIF4G1-related genes were mainly involved in DNA replication, BRCA metastasis, and the MAPK signaling pathway. Infiltration levels of CD4+-activated memory T cells, macrophages M0, macrophages M1, and neutrophils were higher in the EIF4G1 high-expression group than those in the EIF4G1 low-expression group. EIF4G1 was positively correlated with T cell exhaustion. Lower IPS was revealed in high EIF4G1 expression patients. Five potential groups of drugs against BRCA were identified. CONCLUSION EIF4G1 might regulate the TME and affect BRCA metastasis, and it is a potential prognostic biomarker and therapeutic target for BRCA.
Collapse
Affiliation(s)
- Kun Li
- Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Guangqing Tan
- Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Xin Zhang
- Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Weiyu Lu
- Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Jingyi Ren
- Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Yuewen Si
- Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Enoch Appiah Adu-Gyamfi
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Fangfang Li
- Joint International Research Laboratory of Reproduction, Development of the Ministry of Education of China, School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
| | - Yingxiong Wang
- Joint International Research Laboratory of Reproduction, Development of the Ministry of Education of China, School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
| | - Biao Xie
- Department of Biostatistics, School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
- Correspondence: (B.X.); (M.W.)
| | - Meijiao Wang
- Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
- Joint International Research Laboratory of Reproduction, Development of the Ministry of Education of China, School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
- Correspondence: (B.X.); (M.W.)
| |
Collapse
|
37
|
Bao M, Li H, Li J. Identification of potential
lncRNA‐miRNA‐mRNA
regulatory network contributing to aldosterone‐producing adenoma. J Cell Mol Med 2022; 26:5614-5623. [DOI: 10.1111/jcmm.17586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 09/27/2022] [Accepted: 10/05/2022] [Indexed: 11/28/2022] Open
Affiliation(s)
- Minghui Bao
- Department of Cardiology, Peking University First Hospital Peking University Beijing China
| | - Haotong Li
- National Center for Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
| | - Jianping Li
- Department of Cardiology, Peking University First Hospital Peking University Beijing China
| |
Collapse
|
38
|
Li H, Gu J, Tian Y, Li S, Zhang H, Dai Z, Wang Z, Zhang N, Peng R. A prognostic signature consisting of metabolism-related genes and SLC17A4 serves as a potential biomarker of immunotherapeutic prediction in prostate cancer. Front Immunol 2022; 13:982628. [PMID: 36325340 PMCID: PMC9620963 DOI: 10.3389/fimmu.2022.982628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 09/05/2022] [Indexed: 12/24/2022] Open
Abstract
Background Prostate cancer (PCa), a prevalent malignant cancer in males worldwide, screening for patients might benefit more from immuno-/chemo-therapy remained inadequate and challenging due to the heterogeneity of PCa patients. Thus, the study aimed to explore the metabolic (Meta) characteristics and develop a metabolism-based signature to predict the prognosis and immuno-/chemo-therapy response for PCa patients. Methods Differentially expressed genes were screened among 2577 metabolism-associated genes. Univariate Cox analysis and random forest algorithms was used for features screening. Multivariate Cox regression analysis was conducted to construct a prognostic Meta-model based on all combinations of metabolism-related features. Then the correlation between MetaScore and tumor was deeply explored from prognostic, genomic variant, functional and immunological perspectives, and chemo-/immuno-therapy response. Multiple algorithms were applied to estimate the immunotherapeutic responses of two MeteScore groups. Further in vitro functional experiments were performed using PCa cells to validate the association between the expression of hub gene SLC17A4 which is one of the model component genes and tumor progression. GDSC database was employed to determine the sensitivity of chemotherapy drugs. Results Two metabolism-related clusters presented different features in overall survival (OS). A metabolic model was developed weighted by the estimated regression coefficients in the multivariate Cox regression analysis (0.5154*GAS2 + 0.395*SLC17A4 - 0.1211*NTM + 0.2939*GC). This Meta-scoring system highlights the relationship between the metabolic profiles and genomic alterations, gene pathways, functional annotation, and tumor microenvironment including stromal, immune cells, and immune checkpoint in PCa. Low MetaScore is correlated with increased mutation burden and microsatellite instability, indicating a superior response to immunotherapy. Several medications that might improve patients` prognosis in the MetaScore group were identified. Additionally, our cellular experiments suggested knock-down of SLC17A4 contributes to inhibiting invasion, colony formation, and proliferation in PCa cells in vitro. Conclusions Our study supports the metabolism-based four-gene signature as a novel and robust model for predicting prognosis, and chemo-/immuno-therapy response in PCa patients. The potential mechanisms for metabolism-associated genes in PCa oncogenesis and progression were further determined.
Collapse
Affiliation(s)
- He Li
- The Animal Laboratory Center, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Jie Gu
- Department of Geriatric Urology, Xiangya International Medical Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Yuqiu Tian
- Department of Infectious Disease, Zhuzhou Central Hospital, Zhuzhou, Hunan, China
| | - Shuyu Li
- Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hao Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Nan Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- One‑Third Lab, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Hei Longjiang, China
- *Correspondence: Renjun Peng, ; Nan Zhang,
| | - Renjun Peng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- *Correspondence: Renjun Peng, ; Nan Zhang,
| |
Collapse
|
39
|
Yu W, Lu J, Wu C. Construction of a novel prognostic signature based on the composition of tumor-infiltrating immune cells in clear cell renal cell carcinoma. Front Genet 2022; 13:1024096. [DOI: 10.3389/fgene.2022.1024096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 10/03/2022] [Indexed: 11/13/2022] Open
Abstract
Emerging evidence has uncovered that tumor-infiltrating immune cells (TIICs) play significant roles in regulating the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the exact composition of TIICs and their prognostic values in ccRCC have not been well defined. A total of 534 ccRCC samples with survival information and TIIC data from The Cancer Genome Atlas (TCGA) dataset were included in our research. The ImmuCellAI tool was employed to estimate the abundance of 24 TIICs and further survival analysis explored the prognostic values of TIICs in ccRCC. In addition, the expression levels of immunosuppressive molecules (PDL1, PD1, LAG3, and CTLA4) in the high- and low-risk groups were explored. Various subtypes of TIICs had distinct infiltrating features and most TIICs exhibited dysregulated abundance between normal and tumor tissues. Moreover, specific kinds of TIICs had encouraging prognostic values in ccRCC. Further analysis constructed a 4-TIICs signature to evaluate the prognosis of ccRCC patients. Cox regression analyses confirmed the independent prognostic role of the signature in ccRCC. Moreover, immunosuppressive molecules, including PD1, LAG3, and CTLA4, were significantly upregulated in the high-risk group and predicted poor prognosis. However, PDL1 was not changed between high- and low-risk groups and could not predict poor prognosis. To sum up, our research explored the landscape of TIICs in ccRCC and established a novel 4-TIIC prognostic signature, which could effectively predict the prognosis for patients with ccRCC. Based on this signature, we also concluded that PDL1 may not predict prognosis in ccRCC.
Collapse
|
40
|
Luo Y, Zong Y, Hua H, Gong M, Peng Q, Li C, Neculai D, Zeng X. Immune-infiltrating signature-based classification reveals CD103 +CD39 + T cells associate with colorectal cancer prognosis and response to immunotherapy. Front Immunol 2022; 13:1011590. [PMID: 36311750 PMCID: PMC9596778 DOI: 10.3389/fimmu.2022.1011590] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 09/26/2022] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND Current stratification systems for tumor prognostic prediction and immunotherapeutic efficacy evaluation are less satisfying in colorectal cancer (CRC). As infiltrating immune cells in tumor microenvironment (TME) played a key role in tumor progression and responses to immune checkpoint blockade (ICB) therapy, we want to construct an immune-related scoring system with detailed immune profiles to stratify CRC patients. METHODS We developed a scoring system based on immune-related signatures and validated its ability to predict prognosis and immunotherapeutic outcomes in CRC. CD45+ cells from CRC patients were sorted to investigate detailed immune profiles of the stratification system using mass cytometry. A single-cell RNA sequencing dataset was used to analyze transcriptomic profiles. RESULTS We constructed an immune-related signature score (IRScore) based on 54 recurrence-free survival (RFS)-related immune signatures to stratify CRC patients. We revealed that IRScore was positively correlated with RFS and favorable outcomes in ICB treatment. Moreover, we depicted a detailed immune profile in TME using mass cytometry and identified that CD103+CD39+ T cells, characterized by an exhaustive, cytotoxic and proliferative phenotype, were enriched in CRC patients with high IRScore. As a beneficial immune signature, CD103+CD39+ T cells could predict prognosis and responses to ICB therapy in CRC. CONCLUSIONS All the analyses above revealed that IRScore could be a valuable tool for predicting prognosis and facilitating the development of new therapeutic strategies in CRC, and CD103+CD39+ T cells were one of defined immune signatures in IRScore, which might be a key factor for antitumor immunity.
Collapse
Affiliation(s)
- Yang Luo
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Cell Biology, Department of Pathology Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yunfeng Zong
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Research Units of Infectious disease and Microecology, Chinese Academy of Medical Sciences, Hangzhou, China
| | - Hanju Hua
- Colorectal Surgery Department, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Meiting Gong
- Zhejiang University-University of Edinburgh Institute (ZJU-UoE Institute), Zhejiang University School of Medicine, Zhejiang University, Haining, China
| | - Qiao Peng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Research Units of Infectious disease and Microecology, Chinese Academy of Medical Sciences, Hangzhou, China
| | - Chen Li
- Department of Human Genetics, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, China
| | - Dante Neculai
- Department of Cell Biology, Department of Pathology Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xun Zeng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Research Units of Infectious disease and Microecology, Chinese Academy of Medical Sciences, Hangzhou, China
| |
Collapse
|
41
|
Cuproptosis Combined with lncRNAs Predicts the Prognosis and Immune Microenvironment of Breast Cancer. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:5422698. [PMID: 36213577 PMCID: PMC9536992 DOI: 10.1155/2022/5422698] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 09/10/2022] [Indexed: 11/17/2022]
Abstract
Breast cancer (BC), the most common cancer in women, is caused by the uncontrolled proliferation of mammary epithelial cells under the action of a variety of carcinogenic factors. Cuproptosis-related targets have been found to be closely associated with breast cancer development. TCGA obtained 1226 tumor samples, 1073 clinical data, and 37 lncRNAs during univariate Cox multivariate analysis. We used nonnegative matrix factoring (NMF) agglomeration to spot thirty-three potential molecular subsets with totally different cuproptosis-related lncRNA expression patterns. The least absolute shrinkage and selection operator (LASSO) formula and variable Cox multivariate analysis were not used to construct the best prognostic model. The variations in neoplasm mutation burden and factor gene ontology (GO) and gene set enrichment analysis (GSEA) within the high- and low-risk teams were analyzed, and therefore, the potential mechanism of the development of carcinoma was analyzed. We created a prognostic profile consisting of nineteen cuproptosis-related genes (NFE2L2, LIPT1, LIPT2, DLD, etc.) and their connected targets. The correlation between tumor mutational burden (TMB) and clinical manifestations of tumors demonstrates the importance of high- and low-expression bunch data on the incidence of clinical manifestations of tumors. The area under the curve (AUC) shows moderate prophetic power for copper mortality. GO enrichment analysis showed that immunorelated responses were enriched. Correlation analysis of immune cells showed that pathology could play an important role in the prevalence and prognosis of tumors, and there were variations in immune cells between the probable and low-risk groups. Our study suggests that the prognostic characteristic genes associated with cuproptosis can be used as new biomarkers to predict the prognosis of breast cancer patients. In addition, we found that immunotherapy may play a key role in breast cancer treatment regimens. Levels of immune-associated cells and pathways vary significantly among risk groups of breast cancer patients.
Collapse
|
42
|
Wang F, Wang X, Liu L, Deng S, Ji W, Liu Y, Wang X, Wang R, Zhao X, Gao E. Comprehensive analysis of PTPN gene family revealing PTPN7 as a novel biomarker for immuno-hot tumors in breast cancer. Front Genet 2022; 13:981603. [PMID: 36226189 PMCID: PMC9548886 DOI: 10.3389/fgene.2022.981603] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 07/26/2022] [Indexed: 11/23/2022] Open
Abstract
Background: The non-receptor protein tyrosine phosphatase (PTPN) gene family has been considered to be involved in the oncogenesis and development of multiple cancers. However, its prognostic utility and immunological relevance in breast cancer (BrCa) have not been clarified. Methods: A transcriptional level interpretation of the expressions and prognostic values was analyzed using the data from The Cancer Genome Atlas (TCGA) cohort. In addition, GO and DAVID pinpoint the functional enrichment of PTPNs. Moreover, the immune correlations of PTPN7 in BrCa and pan-cancer were further investigated based on the TCGA cohort and were testified using the in-house and the Gene Expression Omnibus (GEO) cohorts. Results: For systematic analysis of the PTPN family, we found that the expression levels of PTPN1, PTPN6, PTPN7, PTPN18, PTPN20, and PTPN22 was promoted in tumor tissues while comparing with paraneoplastic tissues during our study. We further investigated their functions and protein-protein interactions (PPI), and these results strongly suggested that PTPN family was associated with protein dephosphorylation. Next, we performed an immunological relevance analysis and found that PTPN7 was correlated with immune infiltration, suggesting a stronger association of PTPN7 with immuno-hot tumors in BrCa. In addition, results from the in-house cohort confirmed the positive correlation between PTPN7 and PD-L1. The pan-cancer analysis revealed that PTPN7 was related to PD-L1 and CTLA-4 expression in almost all cancer types. Finally, the predictive value of PTPN7 for immunotherapy was significant in two independent GEO cohorts. Conclusion: In conclusion, this is the first extensive research on the correlation between PTPN family expression and immune characterization in BrCa. As results, PTPN7 expression is associated with immuno-hot tumors and could be a promising predictive biomarker for immunotherapy in not only BrCa but multiple cancers.
Collapse
Affiliation(s)
- Fengxu Wang
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Xuehai Wang
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Lei Liu
- Department of Pathology, Affiliated Hospital of Nantong University, Nantong, China
| | - Siyuan Deng
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Wenqian Ji
- College of International Studies, Southwest University, Chongqing, China
| | - Yang Liu
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Xiangdong Wang
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Rui Wang
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Xinyuan Zhao
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
- *Correspondence: Xinyuan Zhao, ; Erli Gao,
| | - Erli Gao
- Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- *Correspondence: Xinyuan Zhao, ; Erli Gao,
| |
Collapse
|
43
|
Ren L, Yi J, Yang Y, Li W, Zheng X, Liu J, Li S, Yang H, Zhang Y, Ge B, Zhang S, Fu W, Dong D, Du G, Wang X, Wang J. Systematic pan-cancer analysis identifies APOC1 as an immunological biomarker which regulates macrophage polarization and promotes tumor metastasis. Pharmacol Res 2022; 183:106376. [PMID: 35914680 DOI: 10.1016/j.phrs.2022.106376] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/24/2022] [Accepted: 07/28/2022] [Indexed: 10/16/2022]
Abstract
Apolipoprotein C1 (APOC1) has been found to play an essential part in proliferation and metastasis of numerous cancers, but related mechanism has not been elucidated, especially its function and role in tumor immunity. Through systematic pan-cancer analysis, we identified that APOC1 was closely associated with the infiltration of various immune cells in multiple cancers. Besides, APOC1 was significantly co-expressed with the immune checkpoints, major histocompatibility complex (MHC) molecules, chemokines and other immune-related genes. Furthermore, single-cell sequencing analysis suggested that the vast majority of APOC1 was expressed in macrophages or tumor-associated macrophages (TAMs). Additionally, the expression of APOC1 was significantly related to the prognosis of different cancers. Since APOC1 was most significantly abnormally expressed in renal cell cancer (RCC), subsequent experiments were carried out in RCC to explore the role of APOC1 in tumor immunity. The expression of APOC1 was significantly elevated in the tumor and serum of RCC patients. Besides, APOC1 was mainly expressed in the macrophage and it was closely related to the immune cell infiltration of RCC. Co-culture with RCC cells could induce the generation of TAMs with M2 phenotype which be blocked by silencing APOC1. The expression of APOC1 was elevated in the M2 or TAMs and APOC1 promoted M2 polarization of macrophages through interacting with CD163 and CD206. Furthermore, macrophages overexpressing APOC1 promoted the metastasis of RCC cells via secreting CCL5. Together, these data indicate that APOC1 is an immunological biomarker which regulates macrophage polarization and promotes tumor metastasis.
Collapse
Affiliation(s)
- Liwen Ren
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Jie Yi
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Beijing 100730, China
| | - Yihui Yang
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Wan Li
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Xiangjin Zheng
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Jinyi Liu
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Sha Li
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Hong Yang
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Yizhi Zhang
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Binbin Ge
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Sen Zhang
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Weiqi Fu
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Dexin Dong
- Department of Urology, Peking Union Medical College Hospital, Beijing 100730, China
| | - Guanhua Du
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Xifu Wang
- Department of Emergency and Critical Care Center, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China.
| | - Jinhua Wang
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China.
| |
Collapse
|
44
|
Pan-Cancer Analysis Reveals the Relation between TRMT112 and Tumor Microenvironment. JOURNAL OF ONCOLOGY 2022; 2022:1445932. [PMID: 36081672 PMCID: PMC9448524 DOI: 10.1155/2022/1445932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 07/29/2022] [Accepted: 08/09/2022] [Indexed: 11/17/2022]
Abstract
Dysregulated epigenetic modifications play a critical role in cancer development where TRMT112 is a member of the transfer RNA (tRNA) methyltransferase family. Till now, no studies have revealed the linkage between TRMT112 expression and diverse types of tumors. Based on TCGA data, we first probed into the relation between TRMT112 and prognosis and the potential role of TRMT112 in tumor microenvironment across 33 types of tumor. TRMT112 presented with increased expression in most cancers, which was significantly prognostic. Furthermore, TRMT112 was associated with tumor-associated fibroblasts in a variety of cancers. Additionally, a positive relationship was identified between TRMT112 expression and multiple tumor-related immune infiltrations, such as dendritic cells, CD8+ T cells, macrophages, CD4+ T cells, neutrophils, and B cells in lung adenocarcinoma and breast invasive carcinoma. In summary, our results suggest that TRMT112 might be a potential prognostic predictor of cancers and involved in regulating multiple cancer-related immune responses to some extent.
Collapse
|
45
|
Cai C, Zhang Y, Hu X, Yang S, Ye J, Wei Z, Chu T. Spindle and Kinetochore-associated Family Genes are Prognostic and Predictive Biomarkers in Hepatocellular Carcinoma. J Clin Transl Hepatol 2022; 10:627-641. [PMID: 36062274 PMCID: PMC9396317 DOI: 10.14218/jcth.2021.00216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/07/2021] [Accepted: 10/08/2021] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND AND AIMS Hepatocellular carcinoma (HCC) is one of the most frequent malignant tumors. Spindle and kinetochore-associated (SKA) family genes are essential for the maintenance of the metaphase plate and spindle checkpoint silencing during mitosis. Recent studies have indicated that dysregulation of SKA family genes induces tumorigenesis, tumor progression, and chemoresistance via modulation of cell cycle and DNA replication. However, the differential transcription of SKAs in the context of HCC and its prognostic significance has not been demonstrated. METHODS Bioinformatics analyses were performed using TCGA, ONCOMINE, HCCDB, Kaplan-Meier plotter, STRING, GEPIA databases. qRT-PCR, western blot, and functional assays were utilized for in vitro experiments. RESULTS We found remarkable upregulation of transcripts of SKA family genes in HCC samples compared with normal liver samples on bioinformatics analyses and in vitro validation. Interaction analysis and enrichment analysis showed that SKA family members were mainly related to microtubule motor activity, mitosis, and cell cycle. Immuno-infiltration analysis showed a correlation of all SKA family genes with various immune cell subsets, especially T helper 2 (Th2) cells. Transcriptional levels of SKA family members were positively associated with histologic grade, T stage, and α-fetoprotein in HCC patients. Receiver operating characteristic curve analysis demonstrated a strong predictive ability of SKA1/2/3 for HCC. Increased expression of these SKAs was associated with unfavorable overall survival, progression-free survival, and disease-specific survival. On Cox proportional hazards regression analyses, SKA1 upregulation and pathological staging were independent predictors of overall survival and disease-specific survival of HCC patients. Finally, clinical tissue microarray validation and in vitro functional assays revealed SKA1 acts an important regulatory role in tumor malignant behavior. CONCLUSIONS SKA family members may potentially serve as diagnostic and prognostic markers in the context of HCC. The correlation between SKAs and immune cell infiltration provides a promising research direction for SKA-targeted immunotherapeutics for HCC.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Tongwei Chu
- Correspondence to: Tongwei Chu, Department of Orthopedics, Xinqiao Hospital, Third Military Medical University (Army Medical University), No.83 Xinqiao Main Street, Shapingba District, Chongqing 400037, China. ORCID: https://orcid.org/0000-0003-0309-7082. Tel: +86-13708388336, E-mail:
| |
Collapse
|
46
|
Pan J, Ma B, Hou X, Li C, Xiong T, Gong Y, Song F. The construction of transcriptional risk scores for breast cancer based on lightGBM and multiple omics data. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:12353-12370. [PMID: 36654001 DOI: 10.3934/mbe.2022576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
BACKGROUND Polygenic risk score (PRS) can evaluate the individual-level genetic risk of breast cancer. However, standalone single nucleotide polymorphisms (SNP) data used for PRS may not provide satisfactory prediction accuracy. Additionally, current PRS models based on linear regression have insufficient power to leverage non-linear effects from thousands of associated SNPs. Here, we proposed a transcriptional risk score (TRS) based on multiple omics data to estimate the risk of breast cancer. METHODS The multiple omics data and clinical data of breast invasive carcinoma (BRCA) were collected from the cancer genome atlas (TCGA) and the gene expression omnibus (GEO). First, we developed a novel TRS model for BRCA utilizing single omic data and LightGBM algorithm. Subsequently, we built a combination model of TRS derived from each omic data to further improve the prediction accuracy. Finally, we performed association analysis and prognosis prediction to evaluate the utility of the TRS generated by our method. RESULTS The proposed TRS model achieved better predictive performance than the linear models and other ML methods in single omic dataset. An independent validation dataset also verified the effectiveness of our model. Moreover, the combination of the TRS can efficiently strengthen prediction accuracy. The analysis of prevalence and the associations of the TRS with phenotypes including case-control and cancer stage indicated that the risk of breast cancer increases with the increases of TRS. The survival analysis also suggested that TRS for the cancer stage is an effective prognostic metric of breast cancer patients. CONCLUSIONS Our proposed TRS model expanded the current definition of PRS from standalone SNP data to multiple omics data and outperformed the linear models, which may provide a powerful tool for diagnostic and prognostic prediction of breast cancer.
Collapse
Affiliation(s)
- Jianqiao Pan
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Baoshan Ma
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Xiaoyu Hou
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Chongyang Li
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Tong Xiong
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Yi Gong
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| |
Collapse
|
47
|
Identification of Potential Biomarkers of Platelet RNA in Glioblastoma by Bioinformatics Analysis. BIOMED RESEARCH INTERNATIONAL 2022; 2022:2488139. [PMID: 35996545 PMCID: PMC9391609 DOI: 10.1155/2022/2488139] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 07/24/2022] [Accepted: 07/28/2022] [Indexed: 11/18/2022]
Abstract
Objective Glioblastoma is one of the most common and fatal malignancies in adults. Current treatment is still not optimistic. Glioblastoma (GBM) transports RNA to platelets in the blood system via microvesicles, suggesting that platelet RNA can be a potential diagnostic and therapeutic target. The roles of specific platelet RNAs in treatment of GBM are not well understood. Methods Platelet RNA profiling of 8 GBM and 12 normal samples were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified between tumors and normal samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to elucidate the functions of up- and downregulated genes. miRNA was predicted by miRTarBase, TargetScan, and miRDB databases. circBase and circBank were used for circRNA prediction. ceRNA (circRNA-mRNA-miRNA) network was constructed to investigate the potential interactions. Results 22 genes were upregulated and 9 genes were downregulated. There are only two genes (CCR7 and FAM102A) that connect to miRNAs (hsa-let-7a-5p, hsa-miR-1-3p). We assessed the overall survival rates by Kaplan-Meier plotter, and relative expression of GBM and subtypes for overlapped mRNA (CCR7 and FAM102A) were evaluated, and further, we obtained circRNAs (has-circ-0015164, hsa-circ-0003243) by circBank and circBase and bind sites through the CSCD database. Finally, a ceRNA network (circRNA-mRNA-miRNA) was constructed based on 2 miRNAs, 2 mRNAs, and 2 circRNAs by Cytoscape. This study focused on potential mRNA and ceRNA biomarkers to targeted treatment of GBM and provided ideas for clinical treatment through the combination of hematology and oncology. Conclusion The findings of this study contribute to better understand the relationship between GBM and the blood system (platelets) and might lay a solid foundation for improving GBM molecule and gene diagnosis and prognosis.
Collapse
|
48
|
Xu L. Crosstalk of three novel types of programmed cell death defines distinct microenvironment characterization and pharmacogenomic landscape in breast cancer. Front Immunol 2022; 13:942765. [PMID: 36032140 PMCID: PMC9403178 DOI: 10.3389/fimmu.2022.942765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 07/13/2022] [Indexed: 11/14/2022] Open
Abstract
Background Prior studies have highlighted that novel programmed cell death (PCD) modalities, including ferroptosis, pyroptosis, and necroptosis, are correlated with tumor progression and antitumor immunity. Nonetheless, comprehensive analysis of tumor microenvironment (TME) profiles mediated by the crosstalk of distinct PCD forms has not been conducted in breast cancer (BC). Methods Here, we curated 34 identified PCD-associated genes (PCDAGs) and applied the consensus clustering algorithm to establish PCD-mediated tumor patterns in BC. Subsequently, based on prognostic differentially expressed genes extracted from distinct PCD-mediated patterns, we applied the LASSO algorithm to construct CD_Score. Furthermore, the correlation analysis between CD_Score and TME features, molecular subtypes, clinicopathological characteristics, drug response, and immunotherapeutic efficacy was performed. Results Three distinct PCD-clusters were determined among 2,038 BC samples, which did not only display different clinical outcomes but highly correlated to the established immunological tumor phenotypes: “desert,” “excluded,” and “inflamed” immune profiles. Based on the CD_Score derived from the PCD-related gene signature, BC patients could be stratified into CD_Score-low and -high group, of which the former displayed satisfactory survival outcome and enhanced immune infiltration. Further exploration identified that the CD_Score-high group significantly correlated with elevated neoantigen load and higher mutation frequency in SMGs (e.g., TP53 and MAP3K1) and reduced expression of immune checkpoint proteins. Conclusions This research is the first to emphasize the close relationship between distinct cell death modalities and the diversity and complexity of immune infiltration in TME. We established the CD_Score, which could help enhance our cognition of TME features and facilitate the clinical application of immunotherapy.
Collapse
|
49
|
Guo C, Tang Y, Yang Z, Li G, Zhang Y. Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates. Front Immunol 2022; 13:958161. [PMID: 36032071 PMCID: PMC9399518 DOI: 10.3389/fimmu.2022.958161] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 07/18/2022] [Indexed: 11/13/2022] Open
Abstract
Hepatocellular carcinoma (HCC), accounting for ~90% of all primary liver cancer, is a prevalent malignancy worldwide. The intratumor heterogeneity of its causative etiology, histology, molecular landscape, and immune phenotype makes it difficult to precisely recognize individuals with high mortality risk or tumor-intrinsic treatment resistance, especially immunotherapy. Herein, we comprehensively evaluated the activities of cancer hallmark gene sets and their correlations with the prognosis of HCC patients using gene set variation analysis (GSVA) and identified two HCC subtypes with distinct prognostic outcomes. Based on these subtypes, seven immune-related genes (TMPRSS6, SPP1, S100A9, EPO, BIRC5, PLXNA1, and CDK4) were used to construct a novel prognostic gene signature [hallmark-guided subtypes-based immunologic signature (HGSIS)] via multiple statistical approaches. The HGSIS-integrated nomogram suggested an enhanced predictive performance. Interestingly, oncogenic hallmark pathways were significantly enriched in the high-risk group and positively associated with the risk score. Distinct mutational landscapes and immune profiles were observed between different risk groups. Moreover, immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analysis showed different sensitivities of HGSIS risk groups for immune therapy efficacy, and the pRRophetic algorithm indicated distinguishable responses for targeted/chemotherapies in different groups. KIF2C was picked out as the key target concerning HGSIS, and the top 10 small molecules were predicted to bind to the active site of KIF2C via molecular docking, which might be further used for candidate drug discovery of HCC. Taken together, our study offers novel insights for clinically significant subtype recognition, and the proposed signature may be a helpful guide for clinicians to improve the treatment regimens.
Collapse
Affiliation(s)
- Chengbin Guo
- Guangzhou Institute of Pediatrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Yuqin Tang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhao Yang
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Gen Li
- Guangzhou Institute of Pediatrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
- *Correspondence: Yongqiang Zhang, ; Gen Li,
| | - Yongqiang Zhang
- Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China
- *Correspondence: Yongqiang Zhang, ; Gen Li,
| |
Collapse
|
50
|
Li H, Liu H, Hao Q, Liu X, Yao Y, Cao M. Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer. Front Immunol 2022; 13:891175. [PMID: 35990668 PMCID: PMC9386474 DOI: 10.3389/fimmu.2022.891175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe clinical outcomes of breast cancer (BC) are unpredictable due to the high level of heterogeneity and complex immune status of the tumor microenvironment (TME). When set up, multiple long non-coding RNA (lncRNA) signatures tended to be employed to appraise the prognosis of BC. Nevertheless, predicting immunotherapy responses in BC is still essential. LncRNAs play pivotal roles in cancer development through diverse oncogenic signal pathways. Hence, we attempted to construct an oncogenic signal pathway–based lncRNA signature for forecasting prognosis and immunotherapy response by providing reliable signatures.MethodsWe preliminarily retrieved RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and extracted lncRNA profiles by matching them with GENCODE. Following this, Gene Set Variation Analysis (GSVA) was used to identify the lncRNAs closely associated with 10 oncogenic signaling pathways from the TCGA-BRCA (breast-invasive carcinoma) cohort and was further screened by the least absolute shrinkage and selection operator Cox regression model. Next, an lncRNA signature (OncoSig) was established through the expression level of the final 29 selected lncRNAs. To examine survival differences in the stratification described by the OncoSig, the Kaplan–Meier (KM) survival curve with the log-rank test was operated on four independent cohorts (n = 936). Subsequently, multiple Cox regression was used to investigate the independence of the OncoSig as a prognostic factor. With the concordance index (C-index), the time-dependent receiver operating characteristic was employed to assess the performance of the OncoSig compared to other publicly available lncRNA signatures for BC. In addition, biological differences between the high- and low-risk groups, as portrayed by the OncoSig, were analyzed on the basis of statistical tests. Immune cell infiltration was investigated using gene set enrichment analysis (GSEA) and deconvolution tools (including CIBERSORT and ESTIMATE). The combined effect of the Oncosig and immune checkpoint genes on prognosis and immunotherapy was elucidated through the KM survival curve. Ultimately, a pan-cancer analysis was conducted to attest to the prevalence of the OncoSig.ResultsThe OncoSig score stratified BC patients into high- and low-risk groups, where the latter manifested a significantly higher survival rate and immune cell infiltration when compared to the former. A multivariate analysis suggested that OncoSig is an independent prognosis predictor for BC patients. In addition, compared to the other four publicly available lncRNA signatures, OncoSig exhibited superior predictive performance (AUC = 0.787, mean C-index = 0.714). The analyses of the OncoSig and immune checkpoint genes clarified that a lower OncoSig score meant significantly longer survival and improved response to immunotherapy. In addition to BC, a high OncoSig score in several other cancers was negatively correlated with survival and immune cell infiltration.ConclusionsOur study established a trustworthy and discriminable prognostic signature for BC patients with similar clinical profiles, thus providing a new perspective in the evaluation of immunotherapy responses. More importantly, this finding can be generalized to be applicable to the vast majority of human cancers.
Collapse
Affiliation(s)
- Huamei Li
- Department of General Surgery, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Hongjia Liu
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, China
| | - Qiongyu Hao
- Division of Cancer Research and Training, Charles R. Drew University of Medicine and Science, Los Angeles, CA, United States
| | - Xianglin Liu
- Department of General Surgery, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Yongzhong Yao
- Department of General Surgery, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- *Correspondence: Yongzhong Yao, ; Meng Cao,
| | - Meng Cao
- Department of General Surgery, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- *Correspondence: Yongzhong Yao, ; Meng Cao,
| |
Collapse
|