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Chen X, Liu G, Wu B. Analysis and experimental validation of the innate immune gene PSMD1 in liver hepatocellular carcinoma and pan-cancer. Heliyon 2023; 9:e21164. [PMID: 37928041 PMCID: PMC10623288 DOI: 10.1016/j.heliyon.2023.e21164] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/09/2023] [Accepted: 10/17/2023] [Indexed: 11/07/2023] Open
Abstract
This work intends to examine the diagnostic, prognostic, and biological roles of PSMD1 (proteasome 26S subunit, non-ATPase 1) in liver hepatocellular carcinoma (LIHC) and other malignancies, using bioinformatics techniques. PSMD1 is an innate immune gene that has been identified as a biomarker for several cancers. By analyzing TCGA data, we determined that PSMD1 has excellent diagnostic and prognostic value in LIHC. We also examined its correlation with stage-matching clinical features, particularly T staging and stage staging. Independent prognostic analysis, nomogram, and Decision Curve Analysis (DCA) analysis confirmed the predictive ability of PSMD1 on patient clinical outcomes. Our focus was on exploring the biological process, immune infiltration, and genetic variation in which PSMD1 is involved in LIHC. We found a close relationship between PSMD1 and the tumor microenvironment (TME), as well as various immune cell infiltration, immune function, and immune checkpoints. Furthermore, our results suggested that liver cancer patients with low PSMD1 expression were more actively responsive to immunotherapy according to TIDE predictions. Additionally, we observed significant differences in patient survival based on the different immune molecular types of tumors and their correlation with PSMD1 expression. The close relationship between PSMD1 and copy number variation (CNV), tumor mutational burden (TMB), and methylation was also confirmed, showing a significant impact on patient survival. Moreover, the pan-cancer analysis revealed that PSMD1 is closely related to the diagnosis and prognosis of various cancers, as well as immune infiltration across different cancer types. In summary, PSMD1 has the potential to be a useful diagnostic and prognostic biomarker for LIHC and other types of cancers. It is closely associated with indicators such as immune infiltration, CNV, TMB, and methylation. The identification of PSMD1 may offer a potential intervention target for LIHC and various cancers.
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Affiliation(s)
- Xing Chen
- Hepatobiliary Surgery, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi 046000, China
- Changzhi Medical College, Changzhi, Shanxi 046000, China
| | - Guihai Liu
- Clinical Drug Experiment Center, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi 046000, China
| | - Buqiang Wu
- Hepatobiliary Surgery, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi 046000, China
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Bevilacqua G. The Viral Origin of Human Breast Cancer: From the Mouse Mammary Tumor Virus (MMTV) to the Human Betaretrovirus (HBRV). Viruses 2022; 14:1704. [PMID: 36016325 PMCID: PMC9412291 DOI: 10.3390/v14081704] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/25/2022] [Accepted: 07/29/2022] [Indexed: 02/04/2023] Open
Abstract
A Human Betaretrovirus (HBRV) has been identified in humans, dating as far back as about 4500 years ago, with a high probability of it being acquired by our species around 10,000 years ago, following a species jump from mice to humans. HBRV is the human homolog of the MMTV (mouse mammary tumor virus), which is the etiological agent of murine mammary tumors. The hypothesis of a HMTV (human mammary tumor virus) was proposed about 50 years ago, and has acquired a solid scientific basis during the last 30 years, with the demonstration of a robust link with breast cancer and with PBC, primary biliary cholangitis. This article summarizes most of what is known about MMTV/HMTV/HBRV since the discovery of MMTV at the beginning of last century, to make evident both the quantity and the quality of the research supporting the existence of HBRV and its pathogenic role. Here, it is sufficient to mention that scientific evidence includes that viral sequences have been identified in breast-cancer samples in a worldwide distribution, that the complete proviral genome has been cloned from breast cancer and patients with PBC, and that saliva contains HBRV, as a possible route of inter-human infection. Controversies that have arisen concerning results obtained from human tissues, many of them outdated by new scientific evidence, are critically discussed and confuted.
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Zhao Y, Li D, Han Y, Wang H, Du R, Yan Z. The ester derivatives obtained by C‐ring modification of podophyllotoxin induced apoptosis and inhibited proliferation in Hemangioma Endothelial Cells via down‐regulation of PI3K/Akt signaling pathway. Chem Biol Drug Des 2022; 99:828-838. [PMID: 35184389 DOI: 10.1111/cbdd.14034] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 10/12/2021] [Accepted: 01/15/2022] [Indexed: 12/01/2022]
Affiliation(s)
- Yan Zhao
- College of Chinese Medicinal Materials Jilin Agricultural University Changchun 130118 China
| | - Danyao Li
- College of Chinese Medicinal Materials Jilin Agricultural University Changchun 130118 China
| | - Yun Han
- Department of Pharmacy TCM Hospital Nanjing University of Chinese Medicine Suzhou 215009 China
| | - Haohao Wang
- College of Chinese Medicinal Materials Jilin Agricultural University Changchun 130118 China
| | - Rui Du
- College of Chinese Medicinal Materials Jilin Agricultural University Changchun 130118 China
| | - Zhaowei Yan
- Department of Pharmacy The First Affiliated Hospital of Soochow University Suzhou 215006 China
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Li Y, Wang K, Chen Y, Cai J, Qin X, Lu A, Guan D, Qin G, Chen W. A System Pharmacology Model for Decoding the Synergistic Mechanisms of Compound Kushen Injection in Treating Breast Cancer. Front Pharmacol 2021; 12:723147. [PMID: 34899291 PMCID: PMC8660088 DOI: 10.3389/fphar.2021.723147] [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: 06/10/2021] [Accepted: 10/15/2021] [Indexed: 11/29/2022] Open
Abstract
Breast cancer (BC) is one of the most common malignant tumors among women worldwide and can be treated using various methods; however, side effects of these treatments cannot be ignored. Increasing evidence indicates that compound kushen injection (CKI) can be used to treat BC. However, traditional Chinese medicine (TCM) is characterized by “multi-components” and “multi-targets”, which make it challenging to clarify the potential therapeutic mechanisms of CKI on BC. Herein, we designed a novel system pharmacology strategy using differentially expressed gene analysis, pharmacokinetics synthesis screening, target identification, network analysis, and docking validation to construct the synergy contribution degree (SCD) and therapeutic response index (TRI) model to capture the critical components responding to synergistic mechanisms of CKI in BC. Through our designed mathematical models, we defined 24 components as a high contribution group of synergistic components (HCGSC) from 113 potentially active components of CKI based on ADME parameters. Pathway enrichment analysis of HCGSC targets indicated that Rhizoma Heterosmilacis and Radix Sophorae Flavescentis could synergistically target the PI3K-Akt signaling pathway and the cAMP signaling pathway to treat BC. Additionally, TRI analysis showed that the average affinity of HCGSC and targets involved in the key pathways reached -6.47 kcal/mmol, while in vitro experiments proved that two of the three high TRI-scored components in the HCGSC showed significant inhibitory effects on breast cancer cell proliferation and migration. These results demonstrate the accuracy and reliability of the proposed strategy.
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Affiliation(s)
- Yi Li
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kexin Wang
- Institute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong SAR, China.,Neurosurgery Center, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yupeng Chen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.,Guangdong Key Laboratory of Biochip Technology, Southern Medical University, Guangzhou, China
| | - Jieqi Cai
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.,Guangdong Key Laboratory of Biochip Technology, Southern Medical University, Guangzhou, China
| | - Xuemei Qin
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China
| | - Aiping Lu
- Institute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong SAR, China
| | - Daogang Guan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.,Guangdong Key Laboratory of Biochip Technology, Southern Medical University, Guangzhou, China
| | - Genggeng Qin
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Weiguo Chen
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
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Liu C, Han Y, Tong P, Kuang D, Li N, Lu C, Sun X, Wang W, Dai J. Genome-wide DNA methylome and whole-transcriptome landscapes of spontaneous intraductal papilloma in tree shrews. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:688. [PMID: 33987386 PMCID: PMC8106051 DOI: 10.21037/atm-21-1293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Background Breast intraductal papilloma (IP) is mainly caused by the abnormal proliferation of ductal epithelial cells. Tree shrews have potential as an animal model for the study of breast tumours; however, little is known regarding the transcriptome and DNA methylome landscapes of breast IP in tree shrews. In this research, we conducted whole-genome DNA methylation and transcriptome analyses of breast IP and normal mammary glands in tree shrews. Methods DNA methylation profiles were generated from the whole-genome bisulfite sequencing and whole-transcriptome landscapes of IP and control groups of tree shrews through strand-specific library construction and RNA sequencing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses and gene set enrichment analysis were performed. Spearman’s correlation analysis was used to identify statistical relationships between gene expression and DNA methylation. Results A genome-wide perspective of the epigenetic regulation of protein-coding genes in breast IP in tree shrews was obtained. The methylation levels at CG sites were considerably higher than those at CHG or CHH sites, and were highest in gene body regions. In total, 3,486, 82 and 361 differentially methylated regions (DMRs) were identified in the context of CG, CHG, and CHH, respectively, and 701 differentially methylated genes (DMGs) were found. Further, through transcriptomic analysis, 62 differentially expressed genes, 50 long noncoding RNAs, and 32 circular RNAs were identified in breast IP compared to normal mammary glands. Correlation analysis between the DNA methylation and transcriptome data revealed that 25 DMGs were also differentially expressed genes, among which the expression levels of 9 genes were negatively correlated with methylation levels in gene body regions. Importantly, integrated analysis identified 3 genes (PDZ domain-containing 1, ATPase plasma membrane Ca2+ transporting 4 and Lymphocyte cytosolic protein 1) that could serve as candidates for further study of breast IP in tree shrews. Conclusions This research has unearthed the comprehensive landscape of the transcriptome and DNA methylome of spontaneous IP in tree shrews, as well as candidate tumorigenesis related genes in IP. These results will contribute to the use of tree shrews in animal models of breast tumours.
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Affiliation(s)
- Chengxiu Liu
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Yuanyuan Han
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Pinfen Tong
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Dexuan Kuang
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Na Li
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Caixia Lu
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Xiaomei Sun
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Wenguang Wang
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Jiejie Dai
- The Center of Tree Shrew Germplasm Resources, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
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Ghulam A, Lei X, Guo M, Bian C. A Review of Pathway Databases and Related Methods Analysis. Curr Bioinform 2020. [DOI: 10.2174/1574893614666191018162505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Pathway analysis integrates most of the computational tools for the investigation of
high-level and complex human diseases. In the field of bioinformatics research, biological pathways
analysis is an important part of systems biology. The molecular complexities of biological
pathways are difficult to understand in human diseases, which can be explored through pathway
analysis. In this review, we describe essential information related to pathway databases and their
mechanisms, algorithms and methods. In the pathway database analysis, we present a brief introduction
on how to gain knowledge from fundamental pathway data in regard to specific human
pathways and how to use pathway databases and pathway analysis to predict diseases during an
experiment. We also provide detailed information related to computational tools that are used in
complex pathway data analysis, the roles of these tools in the bioinformatics field and how to store
the pathway data. We illustrate various methodological difficulties that are faced during pathway
analysis. The main ideas and techniques for the pathway-based examination approaches are presented.
We provide the list of pathway databases and analytical tools. This review will serve as a
helpful manual for pathway analysis databases.
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Affiliation(s)
- Ali Ghulam
- School of Computer Science, Shaanxi Normal University, Xian, China
| | - Xiujuan Lei
- School of Computer Science, Shaanxi Normal University, Xian, China
| | - Min Guo
- School of Computer Science, Shaanxi Normal University, Xian, China
| | - Chen Bian
- School of Computer Science, Shaanxi Normal University, Xian, China
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