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Zeng F, Zhang Y, Luo T, Wang C, Fu D, Wang X. Daidzein Inhibits Non-small Cell Lung Cancer Growth by Pyroptosis. Curr Pharm Des 2025; 31:884-924. [PMID: 39623715 DOI: 10.2174/0113816128330530240918073721] [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: 07/01/2024] [Accepted: 08/08/2024] [Indexed: 04/24/2025]
Abstract
INTRODUCTION Non-small cell lung cancer (NSCLC) represents the leading cause of cancer deaths in the world. We previously found that daidzein, one of the key bioactivators in soy isoflavone, can inhibit NSCLC cell proliferation and migration, while the molecular mechanisms of daidzein in NSCLC remain unclear. METHODS We developed an NSCLC nude mouse model using H1299 cells and treated the mice with daidzein (30 mg/kg/day). Mass spectrometry analysis of tumor tissues from daidzein-treated mice identified 601 differentially expressed proteins (DEPs) compared to the vehicle-treated group. Gene enrichment analysis revealed that these DEPs were primarily associated with immune regulatory functions, including B cell receptor and chemokine pathways, as well as natural killer cell-mediated cytotoxicity. Notably, the NOD-like receptor signaling pathway, which is closely linked to pyroptosis, was significantly enriched. RESULTS Further analysis of key pyroptosis-related molecules, such as ASC, CASP1, GSDMD, and IL-1β, revealed differential expression in NSCLC versus normal tissues. High levels of ASC and CASP1 were associated with a favorable prognosis in NSCLC, suggesting that they may be critical effectors of daidzein's action. In NSCLC-bearing mice treated with daidzein, RT-qPCR and Western blot analyses showed elevated mRNA and protein levels of ASC, CASP1, and IL-1β but not GSDMD, which was consistent with the proteomic data. CONCLUSION In summary, this study demonstrated that daidzein inhibits NSCLC growth by inducing pyroptosis. Key pathway modulators ASC, CASP1, and IL-1β were identified as primary targets of daidzein. These findings offer insights into the molecular mechanisms underlying the anti-NSCLC effects of daidzein and could offer dietary recommendations for managing NSCLC.
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Affiliation(s)
- Fanfan Zeng
- Jiangxi Provincial Key Laboratory of Cell Precision Therapy, School of Basic Medical Sciences, Jiujiang University, Jiujiang, 332005, Jiangxi, China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - Yu Zhang
- Jiangxi Provincial Key Laboratory of Cell Precision Therapy, School of Basic Medical Sciences, Jiujiang University, Jiujiang, 332005, Jiangxi, China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - Ting Luo
- Jiangxi Provincial Key Laboratory of Cell Precision Therapy, School of Basic Medical Sciences, Jiujiang University, Jiujiang, 332005, Jiangxi, China
- Department of Infection Control, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - Chengman Wang
- Jiangxi Provincial Key Laboratory of Cell Precision Therapy, School of Basic Medical Sciences, Jiujiang University, Jiujiang, 332005, Jiangxi, China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - Denggang Fu
- College of Medicine, Medical University of South Carolina, Columbia, Charleston, SC 29425, United States
| | - Xin Wang
- Jiangxi Provincial Key Laboratory of Cell Precision Therapy, School of Basic Medical Sciences, Jiujiang University, Jiujiang, 332005, Jiangxi, China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China
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Meng Y, Zhang M, Li X, Wang X, Dong Q, Zhang H, Zhai Y, Song Q, He F, Tian C, Sun A. Myeloid cell-expressed MNDA enhances M2 polarization to facilitate the metastasis of hepatocellular carcinoma. Int J Biol Sci 2024; 20:2814-2832. [PMID: 38904028 PMCID: PMC11186364 DOI: 10.7150/ijbs.91877] [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: 11/04/2023] [Accepted: 04/27/2024] [Indexed: 06/22/2024] Open
Abstract
Stable infiltration of myeloid cells, especially tumor-associated M2 macrophages, acts as one of the essential features of the tumor immune microenvironment by promoting the malignant progression of hepatocellular carcinoma (HCC). However, the factors affecting the infiltration of M2 macrophages are not fully understood. In this study, we found the molecular subtypes of HCC with the worst prognosis are characterized by immune disorders dominated by myeloid cell infiltration. Myeloid cell nuclear differentiation antigen (MNDA) was significantly elevated in the most aggressive subtype and exhibited a positively correlation with M2 infiltration and HCC metastasis. Moreover, MNDA functioned as an independent prognostic predictor and has a good synergistic effect with some existing prognostic clinical indicators. We further confirmed that MNDA was primarily expressed in tumor M2 macrophages and contributed to the enhancement of its polarization by upregulating the expression of the M2 polarization enhancers. Furthermore, MNDA could drive the secretion of M2 macrophage-derived pro-metastasis proteins to accelerate HCC cells metastasis both in vivo and in vitro. In summary, MNDA exerts a protumor role by promoting M2 macrophages polarization and HCC metastasis, and can serve as a potential biomarker and therapeutic target for HCC.
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Affiliation(s)
- Yanru Meng
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, China
| | - Mengxin Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Xinli Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Xinxin Wang
- Department of Pathology, Beijing You'an Hospital, Capital Medical University, Beijing 100069, China
| | - Qian Dong
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Hu Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yuanjun Zhai
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Qin Song
- College of Life Sciences, Hebei University, Baoding 071002, Hebei, China
| | - Fuchu He
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, China
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
- Research Unit of Proteomics Dirven Cancer Precision Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Chunyan Tian
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
- Research Unit of Proteomics Dirven Cancer Precision Medicine, Chinese Academy of Medical Sciences, Beijing, China
- College of Life Sciences, Hebei University, Baoding 071002, Hebei, China
| | - Aihua Sun
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China
- Research Unit of Proteomics Dirven Cancer Precision Medicine, Chinese Academy of Medical Sciences, Beijing, China
- College of Life Sciences, Hebei University, Baoding 071002, Hebei, China
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Yuan X, Ouedraogo SY, Trawally M, Tan Y, Bajinka O. Cancer energy reprogramming and the immune responses. Cytokine 2024; 177:156561. [PMID: 38430694 DOI: 10.1016/j.cyto.2024.156561] [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: 01/22/2024] [Revised: 02/22/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024]
Abstract
Cancer as an uncontrolled growth of cells due to existing mutation in host cells that may proliferate, induce angiogenesis and sometimes metastasize due to the favorable tumor microenvironment (TME). Since it kills more than any disease, biomedical science does not relent in studying the exact pathogenesis. It was believed to be a problem that lies in the nucleus of the host cells; however, recent oncology findings are shifting attention to the mitochondria as an adjuvant to cancer pathogenesis. The changes in the gene are strongly related to cellular metabolism and metabolic reprogramming. It is now understood that reprogramming the TME will have a direct effect on the immune cells' metabolism. Although there are a number of studies on immune cells' response towards tumor energy reprogramming and cancer progression, there is still no existence with the updated collation of these immune cells' response to distinct energy reprogramming in cancer studies. To this end, this mini review shed some light on cancer energy reprogramming mechanisms and enzyme degradation pathways, the cancer pathogenicity activity series involved with reduced lactate production, the specific immune cell responses due to the energy reprogramming. This study highlighted some prospects and future experiments in harnessing the host immune response towards the altered energy metabolism due to cancer.
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Affiliation(s)
- Xingxing Yuan
- Department of Gastroenterology, Heilongjiang Academy of Traditional Chinese Medicine, Harbin 150006, China; First Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin 150040, China
| | - Serge Yannick Ouedraogo
- Medical Science and Technology Innovation Center, Shandong Key Laboratory of Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117, China
| | - Muhammed Trawally
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Istanbul University, Beyazıt, Istanbul, Türkiye
| | - Yurong Tan
- Department of Medical Microbiology, Central South University, Changsha, Hunan Provinces, China.
| | - Ousman Bajinka
- Medical Science and Technology Innovation Center, Shandong Key Laboratory of Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117, China; Department of Medical Microbiology, Central South University, Changsha, Hunan Provinces, China; School of Medicine and Allied Health Sciences, University of The Gambia, The Gambia.
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Han T, Wu J, Liu Y, Zhou J, Miao R, Guo J, Xu Z, Xing Y, Bai Y, Hu D. Integrating bulk-RNA sequencing and single-cell sequencing analyses to characterize adenosine-enriched tumor microenvironment landscape and develop an adenosine-related prognostic signature predicting immunotherapy in lung adenocarcinoma. Funct Integr Genomics 2024; 24:19. [PMID: 38265702 DOI: 10.1007/s10142-023-01281-z] [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: 09/02/2023] [Revised: 12/19/2023] [Accepted: 12/29/2023] [Indexed: 01/25/2024]
Abstract
The adenosine-signaling axis has been recognized as an important immunomodulatory pathway in tumor immunity. However, the biological role of the adenosine-signaling axis in the remodeling of the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Here, we quantified adenosine signaling (ado_sig) in LUAD samples using the GSVA method and assessed the prognostic value of adenosine in LUAD. Afterward, we explored the heterogeneity of the tumor-immune microenvironment at different adenosine levels. In addition, we analyzed the potential biological pathways engaged by adenosine. Next, we established single-cell transcriptional profiles of LUAD and analyzed cellular composition and cell-cell communication analysis under different adenosine microenvironments. Moreover, we established adenosine-related prognostic signatures (ARS) based on comprehensive bioinformatics analysis and evaluated the efficacy of ARS in predicting immunotherapy. The results demonstrated that adenosine signaling adversely impacted the survival of immune-enriched LUAD. The high-adenosine microenvironment exhibited elevated pro-tumor-immune infiltration, including M2 macrophages and displayed notably increased epithelial-mesenchymal transition (EMT) transformation. Furthermore, adenosine signaling displayed significant associations with the expression patterns and prognostic value of immunomodulators within the TME. Single-cell sequencing data revealed increased fibroblast occupancy and a prominent activation of the SPP1 signaling pathway in the high adenosine-signaling microenvironment. The ARS exhibited promising effectiveness in prognostication and predicting immunotherapy response in LUAD. In summary, overexpression of adenosine can cause a worsened prognosis in the LUAD with abundant immune infiltration. Moreover, increased adenosine levels are associated with pro-tumor-immune infiltration, active EMT transformation, pro-tumor angiogenesis, and other factors promoting cancer progression, which collectively contribute to the formation of an immunosuppressive microenvironment. Importantly, the ARS developed in this study demonstrate high efficacy in evaluating the response to immunotherapy.
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Affiliation(s)
- Tao Han
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China.
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, People's Republic of China.
| | - Jing Wu
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, People's Republic of China
| | - Yafeng Liu
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, People's Republic of China
| | - Jiawei Zhou
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, People's Republic of China
| | - Rui Miao
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China
| | - Jianqiang Guo
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, People's Republic of China
| | - Zhi Xu
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China
| | - Yingru Xing
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China
- Department of Clinical Laboratory, Anhui Zhongke Gengjiu Hospital, Hefei, People's Republic of China
| | - Ying Bai
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China.
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, People's Republic of China.
| | - Dong Hu
- School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, People's Republic of China.
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, People's Republic of China.
- Key Laboratory of Industrial Dust Prevention and Control & Occupational Safety and Health of the Ministry of Education, Anhui University of Science and Technology, Huainan, People's Republic of China.
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
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Giriyappagoudar M, Vastrad B, Horakeri R, Vastrad C. Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis. Biomedicines 2023; 11:3109. [PMID: 38137330 PMCID: PMC10740779 DOI: 10.3390/biomedicines11123109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 10/31/2023] [Accepted: 11/02/2023] [Indexed: 12/24/2023] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.
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Affiliation(s)
- Muttanagouda Giriyappagoudar
- Department of Radiation Oncology, Karnataka Institute of Medical Sciences (KIMS), Hubballi 580022, Karnataka, India;
| | - Basavaraj Vastrad
- Department of Pharmaceutical Chemistry, K.L.E. Socitey’s College of Pharmacy, Gadag 582101, Karnataka, India;
| | - Rajeshwari Horakeri
- Department of Computer Science, Govt First Grade College, Hubballi 580032, Karnataka, India;
| | - Chanabasayya Vastrad
- Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India
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6
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Sadeghi MS, Lotfi M, Soltani N, Farmani E, Fernandez JHO, Akhlaghitehrani S, Mohammed SH, Yasamineh S, Kalajahi HG, Gholizadeh O. Recent advances on high-efficiency of microRNAs in different types of lung cancer: a comprehensive review. Cancer Cell Int 2023; 23:284. [PMID: 37986065 PMCID: PMC10661689 DOI: 10.1186/s12935-023-03133-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 11/09/2023] [Indexed: 11/22/2023] Open
Abstract
Carcinoma of the lung is among the most common types of cancer globally. Concerning its histology, it is categorized as a non-small cell carcinoma (NSCLC) and a small cell cancer (SCLC) subtype. MicroRNAs (miRNAs) are a member of non-coding RNA whose nucleotides range from 19 to 25. They are known to be critical regulators of cancer via epigenetic control of oncogenes expression and by regulating tumor suppressor genes. miRNAs have an essential function in a tumorous microenvironment via modulating cancer cell growth, metastasis, angiogenesis, metabolism, and apoptosis. Moreover, a wide range of information produced via several investigations indicates their tumor-suppressing, oncogenic, diagnostic assessment, and predictive marker functions in different types of lung malignancy. miRNA mimics or anti-miRNAs can be transferred into a lung cancer cell, with possible curative implications. As a result, miRNAs hold promise as targets for lung cancer treatment and detection. In this study, we investigate the different functions of various miRNAs in different types of lung malignancy, which have been achieved in recent years that show the lung cancer-associated regulation of miRNAs expression, concerning their function in lung cancer beginning, development, and resistance to chemotherapy, also the probability to utilize miRNAs as predictive biomarkers for therapy reaction.
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Affiliation(s)
- Mohammad Saleh Sadeghi
- Department of Pharmaceutics, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohadeseh Lotfi
- School of Medicine, Tehran University of Medical Science, Tehran, Iran
| | - Narges Soltani
- School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
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7
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Hu Y, Lv X, Wei W, Li X, Zhang K, Zhu L, Gan T, Zeng H, Yang J, Rao N. Quantitative Analysis on Molecular Characteristics Evolution of Gastric Cancer Progression and Prognosis. Adv Biol (Weinh) 2023; 7:e2300129. [PMID: 37357148 DOI: 10.1002/adbi.202300129] [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: 04/04/2023] [Revised: 05/16/2023] [Indexed: 06/27/2023]
Abstract
The dynamic changes of key biological characteristics from gastric low-grade intraepithelial neoplasia (LGIN) to high-grade intraepithelial neoplasia (HGIN) to early gastric cancer (EGC) are still unclear, which greatly affect the accurate diagnosis and treatment of EGC and prognosis evaluation of gastric cancer (GC). In this study, bioinformatics methods/tools are applied to quantitatively analyze molecular characteristics evolution of GC progression, and a prognosis model is constructed. This study finds that some dysregulated differentially expressed mRNAs (DEmRNAs) in the LGIN stage may continue to promote the occurrence and development of EGC. Among the LGIN, HGIN, and EGC stages, there are differences and relevance in the transcription expression patterns of DEmRNAs, and the activation related to immune cells is very different. The biological functions continuously changed during the progression from LGIN to HGIN to EGC. The COX model constructed based on the three EGC-related DEmRNAs has GC prognostic risk prediction ability. The evolution of biological characteristics during the development of EGC mined by the authors provides new insight into understanding the molecular mechanism of EGC occurrence and development. The three-gene prognostic risk model provides a new method for assisting GC clinical treatment decisions.
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Affiliation(s)
- Yeting Hu
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Xiaoqin Lv
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Wenwu Wei
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Xiang Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Kaixuan Zhang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Linlin Zhu
- Digestive Endoscopic Center of West China Hospital, Sichuan University, Chengdu, 610017, China
| | - Tao Gan
- Digestive Endoscopic Center of West China Hospital, Sichuan University, Chengdu, 610017, China
| | - Hongjuan Zeng
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Jinlin Yang
- Digestive Endoscopic Center of West China Hospital, Sichuan University, Chengdu, 610017, China
| | - Nini Rao
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
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8
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Liang WW, Lu RJH, Jayasinghe RG, Foltz SM, Porta-Pardo E, Geffen Y, Wendl MC, Lazcano R, Kolodziejczak I, Song Y, Govindan A, Demicco EG, Li X, Li Y, Sethuraman S, Payne SH, Fenyö D, Rodriguez H, Wiznerowicz M, Shen H, Mani DR, Rodland KD, Lazar AJ, Robles AI, Ding L. Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin. Cancer Cell 2023; 41:1567-1585.e7. [PMID: 37582362 PMCID: PMC11613269 DOI: 10.1016/j.ccell.2023.07.013] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 05/30/2023] [Accepted: 07/31/2023] [Indexed: 08/17/2023]
Abstract
DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.
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Affiliation(s)
- Wen-Wei Liang
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Rita Jui-Hsien Lu
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Reyka G Jayasinghe
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Steven M Foltz
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Eduard Porta-Pardo
- Josep Carreras Leukaemia Research Institute (IJC), 08916 Badalona, Spain; Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain
| | - Yifat Geffen
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Michael C Wendl
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63130, USA; Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Rossana Lazcano
- Departments of Pathology & Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Iga Kolodziejczak
- International Institute for Molecular Oncology, 60-203 Poznań, Poland; Postgraduate School of Molecular Medicine, Medical University of Warsaw, 02-091 Warsaw, Poland
| | - Yizhe Song
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Akshay Govindan
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Elizabeth G Demicco
- Department of Pathology and Laboratory Medicine, Mount Sinai Hospital and Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Xiang Li
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Yize Li
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Sunantha Sethuraman
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Samuel H Payne
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - David Fenyö
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Maciej Wiznerowicz
- International Institute for Molecular Oncology, 60-203 Poznań, Poland; Heliodor Swiecicki Clinical Hospital in Poznań, Ul. Przybyszewskiego 49, 60-355 Poznań, Poland; Poznań University of Medical Sciences, 61-701 Poznań, Poland
| | - Hui Shen
- Van Andel Research Institute, Grand Rapids, MI 49503, USA
| | - D R Mani
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Karin D Rodland
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA; Department of Cell, Developmental, and Cancer Biology, Oregon Health & Science University, Portland, OR 97221, USA
| | - Alexander J Lazar
- Departments of Pathology & Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Ana I Robles
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 631110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA.
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Lung microRNAs Expression in Lung Cancer and COPD: A Preliminary Study. Biomedicines 2023; 11:biomedicines11030736. [PMID: 36979715 PMCID: PMC10045129 DOI: 10.3390/biomedicines11030736] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/21/2023] [Accepted: 02/24/2023] [Indexed: 03/05/2023] Open
Abstract
Non-small cell lung cancer (NSCLC) is one of the deadliest diseases worldwide and represents an impending burden on the healthcare system. Despite increasing attention, the mechanisms underlying tumorigenesis in cancer-related diseases such as COPD remain unclear, making novel biomarkers necessary to improve lung cancer early diagnosis. MicroRNAs (miRNAs) are short non-coding RNA that interfere with several pathways and can act as oncogenes or tumor suppressors. This study aimed to compare miRNA lung expression between subjects with NSCLC and COPD and healthy controls to obtain the miRNA expression profile by analyzing shared pathways. Lung specimens were collected from a prospective cohort of 21 sex-matched subjects to determine the tissue miRNA expression of hsa-miR-34a-5p, 33a-5p, 149-3p, 197-3p, 199-5p, and 320a-3p by RT-PCR. In addition, an in silico prediction of miRNA target genes linked to cancer was performed. We found a specific trend for has-miR-149-3p, 197-3p, and 34a-5p in NSCLC, suggesting their possible role as an index of the tumor microenvironment. Moreover, we identified novel miRNA targets, such as the Cyclin-Dependent Kinase (CDK) family, linked to carcinogenesis by in silico analysis. In conclusion. this study identified lung miRNA signatures related to the tumorigenic microenvironment, suggesting their possible role in improving the evaluation of lung cancer onset.
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