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Zhou X, Liang B, Lin W, Zha L. Identification of MACC1 as a potential biomarker for pulmonary arterial hypertension based on bioinformatics and machine learning. Comput Biol Med 2024; 173:108372. [PMID: 38552277 DOI: 10.1016/j.compbiomed.2024.108372] [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: 01/21/2024] [Revised: 03/13/2024] [Accepted: 03/24/2024] [Indexed: 04/17/2024]
Abstract
BACKGROUND Pulmonary arterial hypertension (PAH) is a life-threatening disease characterized by abnormal early activation of pulmonary arterial smooth muscle cells (PASMCs), yet the underlying mechanisms remain to be elucidated. METHODS Normal and PAH gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database and analyzed using gene set enrichment analysis (GSEA) to uncover the underlying mechanisms. Weighted gene co-expression network analysis (WGCNA) and machine learning methods were deployed to further filter hub genes. A number of immune infiltration analysis methods were applied to explore the immune landscape of PAH. Enzyme-linked immunosorbent assay (ELISA) was employed to compare MACC1 levels between PAH and normal subjects. The important role of MACC1 in the progression of PAH was verified through Western blot and real-time qPCR, among others. RESULTS 39 up-regulated and 7 down-regulated genes were identified by 'limma' and 'RRA' packages. WGCNA and machine learning further narrowed down the list to 4 hub genes, with MACC1 showing strong diagnostic capacity. In vivo and in vitro experiments revealed that MACC1 was highsly associated with malignant features of PASMCs in PAH. CONCLUSIONS These findings suggest that targeting MACC1 may offer a promising therapeutic strategy for treating PAH, and further clinical studies are warranted to evaluate its efficacy.
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Affiliation(s)
- Xinyi Zhou
- Department of Cardiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Benhui Liang
- Department of Cardiology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Wenchao Lin
- Department of Nephrology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Lihuang Zha
- Department of Cardiology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
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2
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Cruz-Miranda GM, Olarte-Carrillo I, Bárcenas-López DA, Martínez-Tovar A, Ramírez-Bello J, Ramos-Peñafiel CO, García-Laguna AI, Cerón-Maldonado R, May-Hau D, Jiménez-Morales S. Transcriptome Analysis in Mexican Adults with Acute Lymphoblastic Leukemia. Int J Mol Sci 2024; 25:1750. [PMID: 38339034 PMCID: PMC10855968 DOI: 10.3390/ijms25031750] [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: 11/23/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 02/12/2024] Open
Abstract
Acute lymphoblastic leukemia (ALL) represents around 25% of adult acute leukemias. Despite the increasing improvement in the survival rate of ALL patients during the last decade, the heterogeneous clinical and molecular features of this malignancy still represent a major challenge for treatment and achieving better outcomes. To identify aberrantly expressed genes in bone marrow (BM) samples from adults with ALL, transcriptomic analysis was performed using Affymetrix Human Transcriptome Array 2.0 (HTA 2.0). Differentially expressed genes (DEGs) (±2-fold change, p-value < 0.05, and FDR < 0.05) were detected using the Transcriptome Analysis Console. Gene Ontology (GO), Database for Annotation, Visualization, and Integrated Discovery (DAVID), and Ingenuity Pathway Analysis (IPA) were employed to identify gene function and define the enriched pathways of DEGs. The protein-protein interactions (PPIs) of DEGs were constructed. A total of 871 genes were differentially expressed, and DNTT, MYB, EBF1, SOX4, and ERG were the top five up-regulated genes. Meanwhile, the top five down-regulated genes were PTGS2, PPBP, ADGRE3, LUCAT1, and VCAN. An association between ERG, CDK6, and SOX4 expression levels and the probability of relapse and death was observed. Regulation of the immune system, immune response, cellular response to stimulus, as well as apoptosis signaling, inflammation mediated by chemokines and cytokines, and T cell activation were among the most altered biological processes and pathways, respectively. Transcriptome analysis of ALL in adults reveals a group of genes consistently associated with hematological malignancies and underscores their relevance in the development of ALL in adults.
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Affiliation(s)
- Gabriela Marisol Cruz-Miranda
- Programa de Doctorado, Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (G.M.C.-M.)
- Laboratorio de Innovación en Medicina de Precisión Núcleo A, Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico;
| | - Irma Olarte-Carrillo
- Laboratorio de Biología Molecular, Servicio de Hematología, Hospital General de México Dr. Eduardo Liceaga, Mexico City 06720, Mexico; (I.O.-C.); (A.M.-T.)
| | - Diego Alberto Bárcenas-López
- Programa de Doctorado, Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (G.M.C.-M.)
- Laboratorio de Innovación en Medicina de Precisión Núcleo A, Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico;
| | - Adolfo Martínez-Tovar
- Laboratorio de Biología Molecular, Servicio de Hematología, Hospital General de México Dr. Eduardo Liceaga, Mexico City 06720, Mexico; (I.O.-C.); (A.M.-T.)
| | - Julian Ramírez-Bello
- Subdirección de Investigación Clínica, Instituto Nacional de Cardiología Ignacio Chávez, Mexico City 14080, Mexico
| | | | - Anel Irais García-Laguna
- Laboratorio de Biología Molecular, Servicio de Hematología, Hospital General de México Dr. Eduardo Liceaga, Mexico City 06720, Mexico; (I.O.-C.); (A.M.-T.)
| | - Rafael Cerón-Maldonado
- Programa de Doctorado, Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (G.M.C.-M.)
- Laboratorio de Biología Molecular, Servicio de Hematología, Hospital General de México Dr. Eduardo Liceaga, Mexico City 06720, Mexico; (I.O.-C.); (A.M.-T.)
| | - Didier May-Hau
- Laboratorio de Innovación en Medicina de Precisión Núcleo A, Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico;
| | - Silvia Jiménez-Morales
- Laboratorio de Innovación en Medicina de Precisión Núcleo A, Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico;
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Jung J, Han H. The diverse influences of relaxin-like peptide family on tumor progression: Potential opportunities and emerging challenges. Heliyon 2024; 10:e24463. [PMID: 38298643 PMCID: PMC10828710 DOI: 10.1016/j.heliyon.2024.e24463] [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: 10/21/2023] [Revised: 01/05/2024] [Accepted: 01/09/2024] [Indexed: 02/02/2024] Open
Abstract
Relaxin-like peptide family exhibit differential expression patterns in various types of cancers and play a role in cancer development. This family participates in tumorigenic processes encompassing proliferation, migration, invasion, tumor microenvironment, immune microenvironment, and anti-cancer resistance, ultimately influencing patient prognosis. In this review, we explore the mechanisms underlying the interaction between the RLN-like peptide family and tumors and provide an overview of therapeutic approaches utilizing this interaction.
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Affiliation(s)
| | - Hyunho Han
- Department of Urology, Urological Science Institute, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
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4
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Wang B, Fan W, Tao Y, Zhang S, Wang J, Fan Z, Liu L, Wang Y. The impact of SLC10A3 on prognosis and immune microenvironment in colorectal adenocarcinoma. Eur J Med Res 2024; 29:20. [PMID: 38178258 PMCID: PMC10765936 DOI: 10.1186/s40001-023-01526-4] [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: 07/27/2023] [Accepted: 11/14/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND SLC10A3, a gene upregulated in pan-cancer, lacks full understanding regarding its prognostic implications and association with immune infiltration in colorectal cancer (CRC). This study comprehensively analyzed SLC10A3 in CRC, evaluating its prognostic significance and influence on the tumor's immune microenvironment. METHODS Transcriptomic data from TCGA were obtained to compare SLC10A3 expression in both colorectal cancer (CRC) and normal tissues. Prognostic value was assessed for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). DNA methylation patterns of SLC10A3 and correlation with DNA mismatch repair (MMR) were explored. Genetic alterations in SLC10A3 were scrutinized. The study also delved into the influence of SLC10A3 on the immune microenvironment of CRC, including immune cell infiltration and chemokines. Involvement of cancer-associated fibroblasts (CAFs) was explored. Methylation status of specific CpG islands in the SLC10A3 gene correlated with CRC patient prognosis. CRC tissue microarray was performed to verify the expression of SLC10A3 and its relationship with prognosis. RESULTS The research revealed that SLC10A3 is significantly upregulated in CRC and holds promise as a potential diagnostic marker. Elevated SLC10A3 expression was linked to poorer OS, DSS, and PFI. Methylation patterns of SLC10A3 displayed prognostic relevance, and genetic alterations in the gene were identified. SLC10A3 was shown to impact the immune microenvironment, with significant correlations observed between its expression and various immune cell types, chemokines, and markers associated with CAFs. Furthermore, an inverse relationship between SLC10A3 and MMR molecules was established. Methylation status of specific CpG islands within the SLC10A3 gene was associated with CRC patient prognosis. Tissue microarray showed that SLC10A3 was highly expressed in CRC and significantly correlated with poor prognosis. CONCLUSION The study underscores the importance of elevated SLC10A3 in CRC, associating it with decreased survival and immune infiltration, proposing it as a diagnostic biomarker and appealing immunotherapy target, given its significant overexpression and influence on the immune microenvironment and prognosis through methylation patterns.
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Affiliation(s)
- Bangting Wang
- Digestive Endoscopy Department, The First Affiliated Hospital With Nanjing Medical University and Jiangsu Province Hospital, Nanjing, Jiangsu, China
| | - Wentao Fan
- Gastroenterology Department, The Forth Affiliated Hospital With Nanjing Medical University, Nanjing, China
| | - Yuwen Tao
- Digestive Endoscopy Department, The First Affiliated Hospital With Nanjing Medical University and Jiangsu Province Hospital, Nanjing, Jiangsu, China
| | - Shijie Zhang
- Digestive Endoscopy Department, The First Affiliated Hospital With Nanjing Medical University and Jiangsu Province Hospital, Nanjing, Jiangsu, China
| | - Jiankun Wang
- Digestive Endoscopy Department, The First Affiliated Hospital With Nanjing Medical University and Jiangsu Province Hospital, Nanjing, Jiangsu, China
| | - Zhining Fan
- Digestive Endoscopy Department, The First Affiliated Hospital With Nanjing Medical University and Jiangsu Province Hospital, Nanjing, Jiangsu, China
| | - Li Liu
- Digestive Endoscopy Department, The First Affiliated Hospital With Nanjing Medical University and Jiangsu Province Hospital, Nanjing, Jiangsu, China.
| | - Yan Wang
- Digestive Endoscopy Department, The First Affiliated Hospital With Nanjing Medical University and Jiangsu Province Hospital, Nanjing, Jiangsu, China.
- The Friendship Hospital of Ili Kazkh Autonomous Prefecture, Ili & Jiangsu Joint Institute of Health, Yining, China.
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5
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Sardari A, Usefi H. Machine learning-based meta-analysis of colorectal cancer and inflammatory bowel disease. PLoS One 2023; 18:e0290192. [PMID: 38134011 PMCID: PMC10745176 DOI: 10.1371/journal.pone.0290192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 11/30/2023] [Indexed: 12/24/2023] Open
Abstract
Colorectal cancer (CRC) is a major global health concern, resulting in numerous cancer-related deaths. CRC detection, treatment, and prevention can be improved by identifying genes and biomarkers. Despite extensive research, the underlying mechanisms of CRC remain elusive, and previously identified biomarkers have not yielded satisfactory insights. This shortfall may be attributed to the predominance of univariate analysis methods, which overlook potential combinations of variants and genes contributing to disease development. Here, we address this knowledge gap by presenting a novel multivariate machine-learning strategy to pinpoint genes associated with CRC. Additionally, we applied our analysis pipeline to Inflammatory Bowel Disease (IBD), as IBD patients face substantial CRC risk. The importance of the identified genes was substantiated by rigorous validation across numerous independent datasets. Several of the discovered genes have been previously linked to CRC, while others represent novel findings warranting further investigation. A Python implementation of our pipeline can be accessed publicly at https://github.com/AriaSar/CRCIBD-ML.
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Affiliation(s)
- Aria Sardari
- Department of Computer Science, Memorial University of Newfoundland, St. John’s, NL, Canada
| | - Hamid Usefi
- Department of Computer Science, Memorial University of Newfoundland, St. John’s, NL, Canada
- Department of Mathematics & Statistics, Memorial University of Newfoundland, St. John’s, NL, Canada
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Kalajahi HG, Yari A, Amini M, Catal T, Ahmadpour Youshanlui M, Pourbagherian O, Zhmurov CS, Mokhtarzadeh A. Therapeutic effect of microRNA-21 on differentially expressed hub genes in gastric cancer based on systems biology. Sci Rep 2023; 13:21906. [PMID: 38081950 PMCID: PMC10713559 DOI: 10.1038/s41598-023-49225-8] [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: 05/28/2023] [Accepted: 12/05/2023] [Indexed: 12/18/2023] Open
Abstract
Gastric cancer (GC) is a leading cause of mortality for many people. Cancer's initiating factors are poorly understood. miR-21 has a crucial function in several malignancies, particularly GC. Furthermore, it has been shown that miR-21 is critical for the emergence and advancement of GC. This work intends to identify new genes which expression is associated with the activity of mir-21 in GC and to investigate the effect of downregulation of mir-21 on these genes and gastric tumorigenesis. We utilized the gene expression profiles of GCs from an Array database (GSE13911) from the Gene Expression Omnibus (GEO) dataset to find differentially expressed genes (DEGs) between control and gastric cancer groups. Using weighted gene correlation network analysis (WGCNA) in R, the Gene co-expression network was reconstructed. The microRNA-mRNA network was then reconstructed using the miRWalk database, and by investigating the microRNA-mRNA network, the genes that have an association with mir-21 were found. To implement the functional investigation, MKN and AGS cell lines were transfected with anti-miR-21 next. Subsequently, MTT proliferation was utilized to assess the cell's vitality. qRT-PCR was then used to evaluate the anticipated levels of gene expression in both GC cell lines. This study discovered and predicted CCL28, NR3C2, and SNYPO2 as the targets of miR-21 (GC), which are downregulated through gastric tumorigenesis, showing great potential as therapeutic and diagnostic targets. The suppression of miR-21 in gastric GC cells led to the inhibition of cell proliferation and decreased expression of CCL28, NR3C2, and SNYPO2 genes. This study established that miR-21, via downregulating these genes, contributes significantly to the development of GC. In addition, systems biology techniques identified CCL28, NR3C2, and SNYPO2 genes as possible GC surveillance and therapy components.
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Affiliation(s)
- Hesam Ghafouri Kalajahi
- Department of Molecular Biology and Genetics, Uskudar University, Uskudar, 34662, Istanbul, Turkey
| | - AmirHossein Yari
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mohammad Amini
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Tunc Catal
- Department of Molecular Biology and Genetics, Uskudar University, Uskudar, 34662, Istanbul, Turkey
| | | | - Omid Pourbagherian
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Cigdem Sezer Zhmurov
- Department of Molecular Biology and Genetics, Uskudar University, Uskudar, 34662, Istanbul, Turkey.
| | - Ahad Mokhtarzadeh
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
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7
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Dobbs Spendlove M, M. Gibson T, McCain S, Stone BC, Gill T, Pickett BE. Pathway2Targets: an open-source pathway-based approach to repurpose therapeutic drugs and prioritize human targets. PeerJ 2023; 11:e16088. [PMID: 37790614 PMCID: PMC10544355 DOI: 10.7717/peerj.16088] [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: 03/28/2023] [Accepted: 08/22/2023] [Indexed: 10/05/2023] Open
Abstract
Background Recent efforts to repurpose existing drugs to different indications have been accompanied by a number of computational methods, which incorporate protein-protein interaction networks and signaling pathways, to aid with prioritizing existing targets and/or drugs. However, many of these existing methods are focused on integrating additional data that are only available for a small subset of diseases or conditions. Methods We have designed and implemented a new R-based open-source target prioritization and repurposing method that integrates both canonical intracellular signaling information from five public pathway databases and target information from public sources including OpenTargets.org. The Pathway2Targets algorithm takes a list of significant pathways as input, then retrieves and integrates public data for all targets within those pathways for a given condition. It also incorporates a weighting scheme that is customizable by the user to support a variety of use cases including target prioritization, drug repurposing, and identifying novel targets that are biologically relevant for a different indication. Results As a proof of concept, we applied this algorithm to a public colorectal cancer RNA-sequencing dataset with 144 case and control samples. Our analysis identified 430 targets and ~700 unique drugs based on differential gene expression and signaling pathway enrichment. We found that our highest-ranked predicted targets were significantly enriched in targets with FDA-approved therapeutics for colorectal cancer (p-value < 0.025) that included EGFR, VEGFA, and PTGS2. Interestingly, there was no statistically significant enrichment of targets for other cancers in this same list suggesting high specificity of the results. We also adjusted the weighting scheme to prioritize more novel targets for CRC. This second analysis revealed epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase (PI3K), and two mitogen-activated protein kinases (MAPK14 and MAPK3). These observations suggest that our open-source method with a customizable weighting scheme can accurately prioritize targets that are specific and relevant to the disease or condition of interest, as well as targets that are at earlier stages of development. We anticipate that this method will complement other approaches to repurpose drugs for a variety of indications, which can contribute to the improvement of the quality of life and overall health of such patients.
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Affiliation(s)
- Mauri Dobbs Spendlove
- Microbiology and Molecular Biology, Brigham Young University, Provo, UT, United States of America
| | - Trenton M. Gibson
- Microbiology and Molecular Biology, Brigham Young University, Provo, UT, United States of America
| | - Shaney McCain
- Microbiology and Molecular Biology, Brigham Young University, Provo, UT, United States of America
| | - Benjamin C. Stone
- Microbiology and Molecular Biology, Brigham Young University, Provo, UT, United States of America
| | | | - Brett E. Pickett
- Microbiology and Molecular Biology, Brigham Young University, Provo, UT, United States of America
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Mokhtari K, Peymani M, Rashidi M, Hushmandi K, Ghaedi K, Taheriazam A, Hashemi M. Colon cancer transcriptome. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 180-181:49-82. [PMID: 37059270 DOI: 10.1016/j.pbiomolbio.2023.04.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/31/2023] [Accepted: 04/06/2023] [Indexed: 04/16/2023]
Abstract
Over the last four decades, methodological innovations have continuously changed transcriptome profiling. It is now feasible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples using RNA sequencing (RNA-seq). These transcriptomes serve as a connection between cellular behaviors and their underlying molecular mechanisms, such as mutations. This relationship, in the context of cancer, provides a chance to unravel tumor complexity and heterogeneity and uncover novel biomarkers or treatment options. Since colon cancer is one of the most frequent malignancies, its prognosis and diagnosis seem to be critical. The transcriptome technology is developing for an earlier and more accurate diagnosis of cancer which can provide better protectivity and prognostic utility to medical teams and patients. A transcriptome is a whole set of expressed coding and non-coding RNAs in an individual or cell population. The cancer transcriptome includes RNA-based changes. The combined genome and transcriptome of a patient may provide a comprehensive picture of their cancer, and this information is beginning to affect treatment decision-making in real-time. A full assessment of the transcriptome of colon (colorectal) cancer has been assessed in this review paper based on risk factors such as age, obesity, gender, alcohol use, race, and also different stages of cancer, as well as non-coding RNAs like circRNAs, miRNAs, lncRNAs, and siRNAs. Similarly, they have been examined independently in the transcriptome study of colon cancer.
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Affiliation(s)
- Khatere Mokhtari
- Department of Modern Biology, ACECR Institute of Higher Education (Isfahan Branch), Isfahan, Iran
| | - Maryam Peymani
- Department of Biology, Faculty of Basic Sciences, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran.
| | - Mohsen Rashidi
- Department Pharmacology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, 4815733971, Iran; The Health of Plant and Livestock Products Research Center, Mazandaran University of Medical Sciences, Sari, 4815733971, Iran
| | - Kiavash Hushmandi
- Department of Food Hygiene and Quality Control, Division of Epidemiology, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
| | - Kamran Ghaedi
- Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran.
| | - Afshin Taheriazam
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Orthopedics, Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
| | - Mehrdad Hashemi
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
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9
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Zafari N, Bathaei P, Velayati M, Khojasteh-Leylakoohi F, Khazaei M, Fiuji H, Nassiri M, Hassanian SM, Ferns GA, Nazari E, Avan A. Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer. Comput Biol Med 2023; 155:106639. [PMID: 36805214 DOI: 10.1016/j.compbiomed.2023.106639] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/14/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.
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Affiliation(s)
- Nima Zafari
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Parsa Bathaei
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mahla Velayati
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Fatemeh Khojasteh-Leylakoohi
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran; Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Majid Khazaei
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hamid Fiuji
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mohammadreza Nassiri
- Recombinant Proteins Research Group, The Research Institute of Biotechnology, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Seyed Mahdi Hassanian
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Gordon A Ferns
- Brighton & Sussex Medical School, Division of Medical Education, Falmer, Brighton, Sussex, BN1 9PH, UK
| | - Elham Nazari
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Amir Avan
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran; Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
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10
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Ershov P, Poyarkov S, Konstantinova Y, Veselovsky E, Makarova A. Transcriptomic Signatures in Colorectal Cancer Progression. Curr Mol Med 2023; 23:239-249. [PMID: 35490318 DOI: 10.2174/1566524022666220427102048] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 11/05/2021] [Accepted: 03/09/2022] [Indexed: 02/08/2023]
Abstract
AIMS Due to a large number of identified hub-genes encoding key molecular regulators, which are involved in signal transduction and metabolic pathways in cancers, it is relevant to systemize and update these findings. BACKGROUND Colorectal cancer (CRC) is the third leading cause of cancer death in the world, with high metastatic potential. Elucidating the pathogenic mechanisms and selection of novel biomarkers in CRC is of great clinical significance. OBJECTIVE This analytical review aims at the systematization of bioinformatics and experimental identification of hub-genes associated with CRC for a more consolidated understanding of common features in networks and pathways in CRC progression as well as hub-genes selection. RESULTS In total, 301 hub-genes were derived from 40 articles. The "core" consisted of 28 hub-genes (CCNB1, LPAR1, BGN, CXCL3, COL1A2, UBE2C, NMU, COL1A1, CXCL2, CXCL11, CDK1, TOP2A, AURKA, SST, CXCL5, MMP3, CCND1, TIMP1, CXCL8, CXCL1, CXCL12, MYC, CCNA2, GCG, GUCA2A, PAICS, PYY and THBS2) mentioned in not less than three articles and having clinical significance in cancerassociated pathways. Of them, there were two discrete clusters enriched in chemokine signaling and cell cycle regulatory genes. High expression levels of BGN and TIMP1 and low expression levels of CCNB1, CXCL3, CXCL2, CXCL2 and PAICS were associated with unfavorable overall survival of patients with CRC. Differently expressed genes such as LPAR1, SST, CXCL12, GUCA2A, and PYY were shown as down regulated, whereas BGN, CXCL3, UBE2C, NMU, CXCL11, CDK1, TOP2A, AURKA, MMP3, CCND1, CXCL1, MYC, CCNA2, PAICS were up regulated genes in CRC. It was also found that MMP3, THBS2, TIMP1 and CXCL12 genes were associated with metastatic CRC. Network analysis in ONCO.IO showed that upstream master regulators RELA, STAT3, SOX2, FOXM1, SMAD3 and NF-kB were connected with "core" hub-genes. Conclusión: Results obtained are of useful fundamental information on revealing the mechanism of pathogenicity, cellular target selection for optimization of therapeutic interventions, as well as transcriptomics prognostic and predictive biomarkers development.
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Affiliation(s)
- Pavel Ershov
- Department of Analysis and Forecasting of Medical and Biological Health Risks, Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - Stanislav Poyarkov
- Department of Analysis and Forecasting of Medical and Biological Health Risks, Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - Yulia Konstantinova
- Oncology Department, Federal Research and Clinical Center of Specialized Kinds of Medical Care and Medical Technology of the Federal Medical Biological Agency, Moscow, Russia
| | - Egor Veselovsky
- Department of Analysis and Forecasting of Medical and Biological Health Risks, Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - Anna Makarova
- Department of Analysis and Forecasting of Medical and Biological Health Risks, Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
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11
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Chen D, Ye Z, Lew Z, Luo S, Yu Z, Lin Y. Expression of NMU, PPBP and GNG4 in colon cancer and their influences on prognosis. Transl Cancer Res 2022; 11:3572-3583. [PMID: 36388046 PMCID: PMC9641087 DOI: 10.21037/tcr-22-1377] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 08/17/2022] [Indexed: 01/24/2023]
Abstract
BACKGROUND This study aims to identify the core genes that influence the prognosis of colon cancer (CC) and analyze their relationships with clinical characteristics. METHODS The gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were identified. The top ten core genes were selected by bioinformatics tools and screened through the Oncomine database. The expression of core genes in CC tissues and cells was validated by immunohistochemistry, immunoblotting and quantitative real-time polymerase chain reaction. Spearman correlation was used to analyze the relationship between different parameters. Overall survival was assessed by the Kaplan-Meier method. The area under the curve (AUC) and the receiver operating curve (ROC) were applied to assess the accuracy of genes for predicting prognosis. RESULTS There were 1,665 DEGs that were identified from TCGA database. Bioinformatics analysis found that GNGT1, NMU, PPBP, AGT, and GNG4 were differentially expressed in CC tissue. Overexpression of NMU, PPBP, AGT, and GNG4 in CC was associated with shortened survival time (P<0.05). In the validation studies, the high expression levels of NMU, PPBP and GNG4 in CC cells and tissues were confirmed compared to the control groups (P<0.05) and were adverse prognostic biomarkers (P<0.01). The combination prognostic model of the three core genes predicted the 1-, 3-, and 5-year survival of CC with AUCs of 0.868, 0.635 and 0.770, respectively. CONCLUSIONS High levels of NMU, PPBP, and GNG4 were associated with poor prognosis in CC. The combination prognostic model of these three genes could be a new option.
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Affiliation(s)
- Danyu Chen
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China;,Department of Gastroenterology and Hepatology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhen Ye
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China;,Department of Gastroenterology and Hepatology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhenxian Lew
- Department of Surgery, Guangzhou Concord Cancer Center, Guangzhou, China
| | - Simin Luo
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China;,Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhong Yu
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China;,Department of Gastroenterology and Hepatology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Lin
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China;,Department of Gastroenterology and Hepatology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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12
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Rodriguez A, Corchete LA, Alcazar JA, Montero JC, Rodriguez M, Chinchilla-Tábora LM, Vidal Tocino R, Moyano C, Muñoz-Bravo S, Sayagués JM, Abad M. Dysregulated Expression of Three Genes in Colorectal Cancer Stratifies Patients into Three Risk Groups. Cancers (Basel) 2022; 14:cancers14174076. [PMID: 36077612 PMCID: PMC9454483 DOI: 10.3390/cancers14174076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/18/2022] [Accepted: 08/19/2022] [Indexed: 11/16/2022] Open
Abstract
Despite advances in recent years in the study of the molecular profile of sporadic colorectal cancer (sCRC), the specific genetic events that lead to increased aggressiveness or the development of the metastatic process of tumours are not yet clear. In previous studies of the gene expression profile (GEP) using a high-density array (50,000 genes and 6000 miRNAs in a single assay) in sCRC tumours, we identified a 28-gene signature that was found to be associated with an adverse prognostic value for predicting patient survival. Here, we analyse the differential expression of these 28 genes for their possible association with tumour local aggressiveness and metastatic processes in 66 consecutive sCRC patients, followed for >5 years, using the NanoString nCounter platform. The global transcription profile (expression levels of the 28 genes studied simultaneously) allowed us to discriminate between sCRC tumours and nontumoral colonic tissues. Analysis of the biological and functional significance of the dysregulated GEPs observed in our sCRC tumours revealed 31 significantly altered canonical pathways. Among the most commonly altered pathways, we observed the increased expression of genes involved in signalling pathways and cellular processes, such as the PI3K-Akt pathway, the interaction with the extracellular matrix (ECM), and other functions related to cell signalling processes (SRPX2). From a prognostic viewpoint, the altered expression of BST2 and SRPX2 genes were the only independent variables predicting for disease-free survival (DFS). In addition to the pT stage at diagnosis, dysregulated transcripts of ADH1B, BST2, and FER1L4 genes showed a prognostic impact on OS in the multivariate analysis. Based on the altered expression of these three genes, a scoring system was built to stratify patients into low-, intermediate-, and high-risk groups with significantly different 5-year OS rates: 91%, 83%, and 52%, respectively. The prognostic impact was validated in two independent series of sCRC patients from the public GEO database (n = 562 patients). In summary, we show a strong association between the altered expression of three genes and the clinical outcome of sCRC patients, making them potential markers of suitability for adjuvant therapy after complete tumour resection. Additional prospective studies in larger series of patients are required to confirm the clinical utility of the newly identified biomarkers because the number of patients analysed remains small.
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Affiliation(s)
- Alba Rodriguez
- Department of Pathology and IBSAL, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Luís Antonio Corchete
- Cancer Research Center and Hematology Service, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - José Antonio Alcazar
- General and Gastrointestinal Surgery Service, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Juan Carlos Montero
- Department of Pathology and IBSAL, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Marta Rodriguez
- Department of Pathology and IBSAL, University Hospital of Salamanca, 37007 Salamanca, Spain
| | | | - Rosario Vidal Tocino
- Medical Oncology Service and IBSAL, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Carlos Moyano
- Clinical Biochemistry Service, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Saray Muñoz-Bravo
- Department of Pathology and IBSAL, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - José María Sayagués
- Department of Pathology and IBSAL, University Hospital of Salamanca, 37007 Salamanca, Spain
- Correspondence: (J.M.S.); (M.A.)
| | - Mar Abad
- Department of Pathology and IBSAL, University Hospital of Salamanca, 37007 Salamanca, Spain
- Correspondence: (J.M.S.); (M.A.)
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13
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van den Driest L, Johnson CH, Rattray NJW, Rattray Z. Development of an Accessible Gene Expression Bioinformatics Pipeline to Study Driver Mutations of Colorectal Cancer. Altern Lab Anim 2022; 50:282-292. [PMID: 35765262 DOI: 10.1177/02611929221107546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Colorectal cancer (CRC) is a global cause of cancer-related mortality driven by genetic and environmental factors which influence therapeutic outcomes. The emergence of next-generation sequencing technologies enables the rapid and extensive collection and curation of genetic data for each cancer type into clinical gene expression biobanks. We report the application of bioinformatics tools for investigating the expression patterns and prognostic significance of three genes that are commonly dysregulated in colon cancer: adenomatous polyposis coli (APC); B-Raf proto-oncogene (BRAF); and Kirsten rat sarcoma viral oncogene homologue (KRAS). Through the use of bioinformatics tools, we show the patterns of APC, BRAF and KRAS genetic alterations and their role in patient prognosis. Our results show mutation types, the frequency of mutations, tumour anatomical location and differential expression patterns for APC, BRAF and KRAS for colorectal tumour and matched healthy tissue. The prognostic value of APC, BRAF and KRAS genetic alterations was investigated as a function of their expression levels in CRC. In the era of precision medicine, with significant advancements in biobanking and data curation, there is significant scope to use existing clinical data sets for evaluating the role of mutational drivers in carcinogenesis. This approach offers the potential for studying combinations of less well-known genes and the discovery of novel biomarkers, or for studying the association between various effector proteins and pathways.
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Affiliation(s)
- Lisa van den Driest
- Strathclyde Institute of Pharmacy and Biomedical Sciences, 3527University of Strathclyde, Glasgow, UK
| | | | - Nicholas J W Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences, 3527University of Strathclyde, Glasgow, UK
| | - Zahra Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences, 3527University of Strathclyde, Glasgow, UK
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14
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Lin W, Tang Y, Zhang M, Liang B, Wang M, Zha L, Yu Z. Integrated Bioinformatic Analysis Reveals TXNRD1 as a Novel Biomarker and Potential Therapeutic Target in Idiopathic Pulmonary Arterial Hypertension. Front Med (Lausanne) 2022; 9:894584. [PMID: 35646965 PMCID: PMC9133447 DOI: 10.3389/fmed.2022.894584] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 04/27/2022] [Indexed: 01/03/2023] Open
Abstract
Idiopathic pulmonary arterial hypertension (IPAH) is a life-threatening cardiopulmonary disease lacking specific diagnostic markers and targeted therapy, and its mechanism of development remains to be elucidated. The present study aimed to explore novel diagnostic biomarkers and therapeutic targets in IPAH by integrated bioinformatics analysis. Four eligible datasets (GSE117261, GSE15197, GSE53408, GSE48149) was firstly downloaded from GEO database and subsequently integrated by Robust rank aggregation (RRA) method to screen robust differentially expressed genes (DEGs). Then functional annotation of robust DEGs was performed by GO and KEGG enrichment analysis. The protein-protein interaction (PPI) network was constructed followed by using MCODE and CytoHubba plug-in to identify hub genes. Finally, 10 hub genes were screened including ENO1, TALDO1, TXNRD1, SHMT2, IDH1, TKT, PGD, CXCL10, CXCL9, and CCL5. The GSE113439 dataset was used as a validation cohort to appraise these hub genes and TXNRD1 was selected for verification at the protein level. The experiment results confirmed that serum TXNRD1 concentration was lower in IPAH patients and the level of TXNRD1 had great predictive efficiency (AUC:0.795) as well as presents negative correlation with mean pulmonary arterial pressure (mPAP) and pulmonary vascular resistance (PVR). Consistently, the expression of TXNRD1 was proved to be inhibited in animal and cellular model of PAH. In addition, GSEA analysis was performed to explore the functions of TXNRD1 and the results revealed that TXNRD1 was closely correlated with mTOR signaling pathway, MYC targets, and unfolded protein response. Finally, knockdown of TXNRD1 was shown to exacerbate proliferative disorder, migration and apoptosis resistance in PASMCs. In conclusion, our study demonstrates that TXNRD1 is a promising candidate biomarker for diagnosis of IPAH and plays an important role in PAH pathogenesis, although further research is necessary.
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15
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Li L, Lu Y, Liu Y, Wang D, Duan L, Cheng S, Liu G. Network Pharmacology Analysis of Huangqi Jianzhong Tang Targets in Gastric Cancer. Front Pharmacol 2022; 13:882147. [PMID: 35462892 PMCID: PMC9024123 DOI: 10.3389/fphar.2022.882147] [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: 02/23/2022] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
Background: The Chinese medicine, Huangqi Jianzhong Tang (HJT), is widely used to treat gastric cancer (GC). In this study, network pharmacological methods were used to analyze the potential therapeutic targets and pharmacological mechanisms of HJT in GC. Methods: Bioactive components and targets of HJT and GC-related targets were identified using public databases. The protein-protein interaction network of potential targets of HJT in GC was constructed using the Cytoscape plug-in (v3.8.0), CytoHubba. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, in addition to molecular docking and animal experiments to verify the results of network pharmacology analysis. Results: A total of 538 GC-related targets were identified. The bioactive components of HJT were selected for drug-likeness evaluation and binomial statistical model screening, which revealed 63 bioactive components and 72 targets. Based on GO enrichment analysis, all targets in the protein-protein interaction network were mainly involved in the response to oxidative stress and neuronal death. Further, KEGG enrichment analysis suggested that the treatment of GC with HJT mainly involved the Wnt signaling pathway, PI3K-Akt signaling pathway, TGF-β signaling pathway, and MAPK signaling pathway, thereby providing insights into the mechanism of the effects of HJT on GC. Conclusion: This study revealed the potential bioactive components and molecular mechanisms of HJT, which may be useful for the treatment of GC, and provided insights into the development of new drugs for GC.
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Affiliation(s)
- Long Li
- School of Medicine, Xiamen University, Xiamen, China
| | - Yizhuo Lu
- Department of General Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.,Institute of Gastrointestinal Oncology, School of Medicine, Xiamen University, Xiamen, China
| | - Yanling Liu
- School of Pharmaceutical Sciences, Xiamen University, Xiamen, China
| | - Dan Wang
- School of Medicine, Xiamen University, Xiamen, China
| | - Linshan Duan
- School of Pharmaceutical Sciences, Xiamen University, Xiamen, China
| | - Shuyu Cheng
- School of Medicine, Xiamen University, Xiamen, China
| | - Guoyan Liu
- Institute of Gastrointestinal Oncology, School of Medicine, Xiamen University, Xiamen, China.,School of Pharmaceutical Sciences, Xiamen University, Xiamen, China.,Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
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16
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Colorectal Cancer Diagnosis: The Obstacles We Face in Determining a Non-Invasive Test and Current Advances in Biomarker Detection. Cancers (Basel) 2022; 14:cancers14081889. [PMID: 35454792 PMCID: PMC9029324 DOI: 10.3390/cancers14081889] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/04/2022] [Accepted: 04/06/2022] [Indexed: 02/07/2023] Open
Abstract
Simple Summary Colorectal cancer (CRC) is one of the most common cancers in the western world. CRC originates from precursor adenomatous polyps, which may over time develop into cancer. Endoscopic evaluation remains the gold-standard investigation for the disease. In the absence of molecular tools for early detection, the removal of neoplastic adenomas via polypectomy remains an important measure to prevent dysplastic adenomas from evolving into invasive carcinoma. Colonoscopy is an intrusive procedure that provides an uncomfortable experience for patients. Kits for testing for the presence of blood hemoglobin in the stool are now widely used, and DNA methylation-based detection kits have been approved in the USA for testing the stool and plasma, but few other molecular biomarkers have found their way into medical practice. This review summarizes current trends in the detection and screening of CRC and provides a definitive review of emerging molecular biomarkers for CRC. Abstract Globally, colorectal cancer (CRC) is the third most common cancer, with 1.4 million new cases and over 700,000 deaths per annum. Despite being one of the most common cancers, few molecular approaches to detect CRC exist. Carcinoembryonic antigen (CEA) is a known serum biomarker that is used in CRC for monitoring disease recurrence or response to treatment. However, it can also be raised in multiple benign conditions, thus having no value in early detection or screening for CRC. Molecular biomarkers play an ever-increasing role in the diagnosis, prognosis, and outcome prediction of disease, however, only a limited number of biomarkers are available and none are suitable for early detection and screening of CRC. A PCR-based Epi proColon® blood plasma test for the detection of methylated SEPT9 has been approved by the USFDA for CRC screening in the USA, alongside a stool test for methylated DNA from CRC cells. However, these are reserved for patients who decline traditional screening methods. There remains an urgent need for the development of non-invasive molecular biomarkers that are highly specific and sensitive to CRC and that can be used routinely for early detection and screening. A molecular approach to the discovery of CRC biomarkers focuses on the analysis of the transcriptome of cancer cells to identify differentially expressed genes and proteins. A systematic search of the literature yielded over 100 differentially expressed CRC molecular markers, of which the vast majority are overexpressed in CRC. In terms of function, they largely belong to biological pathways involved in cell division, regulation of gene expression, or cell proliferation, to name a few. This review evaluates the current methods used for CRC screening, current availability of biomarkers, and new advances within the field of biomarker detection for screening and early diagnosis of CRC.
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17
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Chen Y, Yang J, Wang Y, Shen W, Liu J, Yuan M, Hao X, Zhong L, Guo R. Identification and Analysis of Hub Genes in Diabetic Cardiomyopathy: Potential Role of Cytochrome P450 1A1 in Mitochondrial Metabolism and STZ-Induced Myocardial Dysfunction. Front Cardiovasc Med 2022; 9:835244. [PMID: 35387435 PMCID: PMC8977650 DOI: 10.3389/fcvm.2022.835244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 02/25/2022] [Indexed: 11/23/2022] Open
Abstract
Diabetic cardiomyopathy (DCM) is a primary cause of death in diabetic patients; however, its molecular mechanism is not yet clear, and there is no uniform standard for diagnosis. The aim of this study is to discover the pathogenesis and potential therapeutic targets of DCM through screening and analysis of differentially expressed genes (DEGs) in heart ventricles of DCM, and to testify the role of key hub genes in DCM-induced myocardial dysfunction. Datasets GSE4745 and GSE6880 were downloaded from the GEO database. The difference analysis, visual analysis, cluster analysis and enrichment analysis were performed by using R language, python scripts and bioinformatics software followed by the construction of protein-protein interaction (PPI) network to obtain hub genes. The DCM models were established by streptozocin (STZ) injection to the male mice. The cardiac function and the expressions of hub genes were examined by using echocardiography and real-time quantitative poly-merase chain reaction (RT-qPCR), followed by multiple statistical analyses. Bioinformatic results indicate that mitochondrial dysfunction, disturbed lipid metabolism and decreased collagen synthesis are the main causes of the DCM development. In particular, the hub gene Cyp1a1 that encodes Cytochrome P450 1A1 (CYP4501A1) enzyme has the highest connectivity in the interaction network, and is associated with mitochondrial homeostasis and energy metabolism. It plays a critical role in the oxidation of endogenous or exogenous substrates. Our RT-qPCR results confirmed that ventricular Cyp1a1 mRNA level was nearly 12-fold upregulated in DCM model compared to normal control, which was correlated with abnormal cardiac function in diabetic individuals. CYP4501A1 protein expression in mitochondria was also increased in diabetic hearts. However, we found no significant changes in collagen expressions in cardiac ventricles of mice with DCM. This study provided compact data support for understanding the pathogenesis of DCM. CYP4501A1 might be considered as a potential candidate targeting for DCM therapy. Follow-up animal and clinical verifications need to be further explored.
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Affiliation(s)
- Yinliang Chen
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
| | - Jinbao Yang
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
| | - Ying Wang
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
| | - Weike Shen
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
| | - Jinlin Liu
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
| | - Meng Yuan
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
| | - Xiaoyu Hao
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
| | - Li Zhong
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA, United States
| | - Rui Guo
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
- The Key Laboratory of Zoological Systematics and Application, College of Life Sciences, Hebei University, Baoding, China
- *Correspondence: Rui Guo
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18
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Luo D, Yang J, Liu J, Yong X, Wang Z. Identification of four novel hub genes as monitoring biomarkers for colorectal cancer. Hereditas 2022; 159:11. [PMID: 35093172 PMCID: PMC8801129 DOI: 10.1186/s41065-021-00216-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/29/2021] [Indexed: 11/30/2022] Open
Abstract
Background It must be admitted that the incidence of colorectal cancer (CRC) was on the rise all over the world, but the related treatment had not caught up. Further research on the underlying pathogenesis of CRC was conducive to improving the survival status of current CRC patients. Methods Differentially expressed genes (DEGs) screening were conducted based on “limma” and “RobustRankAggreg” package of R software. Weighted gene co-expression network analysis (WGCNA) was performed in the integrated DEGs that from The Cancer Genome Atlas (TCGA), and all samples of validation were from Gene Expression Omnlbus (GEO) dataset. Results The terms obtained in the functional annotation for primary DEGs indicated that they were associated with CRC. The MEyellow stand out whereby showed the significant correlation with clinical feature (disease), and 4 hub genes, including ABCC13, AMPD1, SCNN1B and TMIGD1, were identified in yellow module. Nine datasets from Gene Expression Omnibus database confirmed these four genes were significantly down-regulated and the survival estimates for the low-expression group of these genes were lower than for the high-expression group in Kaplan-Meier survival analysis section. MEXPRESS suggested that down-regulation of some top hub genes may be caused by hypermethylation. Receiver operating characteristic curves indicated that these genes had certain diagnostic efficacy. Moreover, tumor-infiltrating immune cells and gene set enrichment analysis for hub genes suggested that there were some associations between these genes and the pathogenesis of CRC. Conclusion This study identified modules that were significantly associated with CRC, four novel hub genes, and further analysis of these genes. This may provide a little new insights and directions into the potential pathogenesis of CRC. Supplementary Information The online version contains supplementary material available at 10.1186/s41065-021-00216-7.
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Recurrent Superenhancer of the Oncogene POU5F1B in Colorectal Cancers. BIOMED RESEARCH INTERNATIONAL 2021; 2021:5405060. [PMID: 34934770 PMCID: PMC8684575 DOI: 10.1155/2021/5405060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 11/16/2021] [Indexed: 11/17/2022]
Abstract
Superenhancer usages in single cancer form such as colorectal cancer (CRC) may provide novel efficient targeting candidates. It is unclear whether CRC contains recurrent superenhancers that confer a predisposition to malignancy. We investigated the superenhancer profile of CRC cell line HCT116 and compared it to that of a healthy sigmoid colon. We found that HCT116 had lost most of the normal colon superenhancer activities but gained a new set of tumor-favoring superenhancers that facilitate tumor proliferation, growth signalling, and hypoxia resistance. Inhibiting the superenhancers by JQ-1 treatment had significantly decreased the colony formation capability of HCT116. Then, by comparing the superenhancer genes and robust CRC upregulated genes, we identified a superenhancer associated with a common CRC upregulated oncogene, POU5f1B. POU5f1B overexpression is related to the worse outcome in CRCs. Via performing ChIP-PCR in 35 clinical samples and investigating CRC anti-H3K27ac ChiP-seq public dataset consisting of 36 samples, we further identified that the superenhancer of oncogene POU5F1B is recurrently activated in CRCs, taking 62 and 72 per cent, respectively. Moreover, JQ-1 treatment successfully inhibited the POU5F1B expression in 5 out of 6 POU5F1B superenhancer-positive samples. Therefore, we concluded that the superenhancer activation of POU5F1B contributes partially to its high expression in CRCs, in addition to the well-known gene amplification aetiology.
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20
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Zou D, Bai J, Lu E, Yang C, Liu J, Wen Z, Liu X, Jin Z, Xu M, Jiang L, Zhang Y, Zhang Y. Identification of Novel Drug Candidate for Epithelial Ovarian Cancer via In Silico Investigation and In Vitro Validation. Front Oncol 2021; 11:745590. [PMID: 34745968 PMCID: PMC8568458 DOI: 10.3389/fonc.2021.745590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 09/28/2021] [Indexed: 12/24/2022] Open
Abstract
Epithelial ovarian cancer (EOC) has a poor prognosis and high mortality rate; patients are easy to relapse with standard therapies. So, there is an urgent need to develop novel drugs. In this study, differentially expressed genes (DEGs) of EOC were identified in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Enrichment and protein–protein interaction (PPI) analyses were performed. The drug candidate which has the possibility to treat EOC was predicted by Connectivity Map (CMAP) databases. Moreover, molecular docking was selected to calculate the binding affinity between drug candidate and hub genes. The cytotoxicity of drug candidates was assessed by MTT and colony formation analysis, the proteins coded by hub genes were detected by Western blots, and apoptosis analysis was evaluated by flow cytometry. Finally, 296 overlapping DEGs (|log 2 fold change|>1; q-value <0.05), which were principally involved in the cell cycle (p < 0.05), and cyclin-dependent kinase 1 (CDK1) were screened as the significant hub gene from the PPI network. Furthermore, the 21 drugs were extracted from CMAPs; among them, piperlongumine (PL) showed a lower CMAP score (-0.80, -62.92) and was regarded as the drug candidate. Furthermore, molecular docking results between PL and CDK1 with a docking score of –8.121 kcal/mol were close to the known CDK1 inhibitor (–8.24 kcal/mol). Additionally, in vitro experiments showed that PL inhibited proliferation and induced apoptosis via targeting CDK1 in EOC SKOV3 cells. Our results reveal that PL may be a novel drug candidate for EOC by inhibiting cell cycle.
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Affiliation(s)
- Dan Zou
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China.,Department of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China
| | - Jin Bai
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China.,Department of Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Enting Lu
- Department of Gynecology, First Hospital of China Medical University, Shenyang, China
| | - Chunjiao Yang
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China
| | - Jiaqing Liu
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China
| | - Zhenpeng Wen
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China
| | - Xuqin Liu
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China
| | - Zi Jin
- The First Department of Oncology, Shenyang Fifth People's Hospital, Shenyang, China
| | - Mengdan Xu
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China
| | - Lei Jiang
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China
| | - Ye Zhang
- The First Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang, China
| | - Yi Zhang
- Department of Gynecology, First Hospital of China Medical University, Shenyang, China
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21
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Hammad A, Elshaer M, Tang X. Identification of potential biomarkers with colorectal cancer based on bioinformatics analysis and machine learning. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:8997-9015. [PMID: 34814332 DOI: 10.3934/mbe.2021443] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Colorectal cancer (CRC) is one of the most common malignancies worldwide. Biomarker discovery is critical to improve CRC diagnosis, however, machine learning offers a new platform to study the etiology of CRC for this purpose. Therefore, the current study aimed to perform an integrated bioinformatics and machine learning analyses to explore novel biomarkers for CRC prognosis. In this study, we acquired gene expression microarray data from Gene Expression Omnibus (GEO) database. The microarray expressions GSE103512 dataset was downloaded and integrated. Subsequently, differentially expressed genes (DEGs) were identified and functionally analyzed via Gene Ontology (GO) and Kyoto Enrichment of Genes and Genomes (KEGG). Furthermore, protein protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape software to identify hub genes; however, the hub genes were subjected to Support Vector Machine (SVM), Receiver operating characteristic curve (ROC) and survival analyses to explore their diagnostic values. Meanwhile, TCGA transcriptomics data in Gene Expression Profiling Interactive Analysis (GEPIA) database and the pathology data presented by in the human protein atlas (HPA) database were used to verify our transcriptomic analyses. A total of 105 DEGs were identified in this study. Functional enrichment analysis showed that these genes were significantly enriched in biological processes related to cancer progression. Thereafter, PPI network explored a total of 10 significant hub genes. The ROC curve was used to predict the potential application of biomarkers in CRC diagnosis, with an area under ROC curve (AUC) of these genes exceeding 0.92 suggesting that this risk classifier can discriminate between CRC patients and normal controls. Moreover, the prognostic values of these hub genes were confirmed by survival analyses using different CRC patient cohorts. Our results demonstrated that these 10 differentially expressed hub genes could be used as potential biomarkers for CRC diagnosis.
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Affiliation(s)
- Ahmed Hammad
- Department of Biochemistry and Department of Thoracic Surgery of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
- Radiation Biology Department, National Center for Radiation Research and Technology, Egyptian Atomic Energy Authority, Cairo 13759, Egypt
| | - Mohamed Elshaer
- Department of Biochemistry and Department of Thoracic Surgery of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
- Labeled Compounds Department, Hot Labs Center, Egyptian Atomic Energy Authority, Cairo 13759, Egypt
| | - Xiuwen Tang
- Department of Biochemistry and Department of Thoracic Surgery of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
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22
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Lin J, Xu Z, Xie J, Deng X, Jiang L, Chen H, Peng C, Li H, Zhang J, Shen B. Oncogene APOL1 promotes proliferation and inhibits apoptosis via activating NOTCH1 signaling pathway in pancreatic cancer. Cell Death Dis 2021; 12:760. [PMID: 34341330 PMCID: PMC8329288 DOI: 10.1038/s41419-021-03985-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 06/22/2021] [Accepted: 06/22/2021] [Indexed: 12/11/2022]
Abstract
APOL1 encodes a secreted high-density lipoprotein, which has been considered as an aberrantly expressed gene in multiple cancers. Nevertheless, the role of APOL1 in the regulatory mechanisms of pancreatic cancer remains unknown and should be explored. We identified APOL1 was abnormally elevated in human pancreatic cancer tissues compared with that in adjacent tissues and was associated with poor prognosis. The effects of APOL1 in PC cell proliferation, cell cycle, and apoptosis was verified via functional in vitro and in vivo experiments. The results showed that knockdown of APOL1 significantly inhibited the proliferation and promoted apoptosis of pancreatic cancer. In addition, we identified APOL1 could be a regulator of NOTCH1 signaling pathway using bioinformatics tools, qRT-PCR, dual-luciferase reporter assay, and western blotting. In summary, APOL1 could function as an oncogene to promote proliferation and inhibit apoptosis through activating NOTCH1 signaling pathway expression in pancreatic cancer; therefore, it may act as a novel therapeutic target for pancreatic cancer.
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Affiliation(s)
- Jiewei Lin
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zhiwei Xu
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Junjie Xie
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaxing Deng
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Lingxi Jiang
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hao Chen
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chenghong Peng
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hongwei Li
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jiaqiang Zhang
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. .,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China. .,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China. .,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - Baiyong Shen
- Pancreatic Disease Center, Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. .,Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China. .,State Key Laboratory of Oncogenes and Related Genes, Shanghai, China. .,Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
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23
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Yin J, Lin C, Jiang M, Tang X, Xie D, Chen J, Ke R. CENPL, ISG20L2, LSM4, MRPL3 are four novel hub genes and may serve as diagnostic and prognostic markers in breast cancer. Sci Rep 2021; 11:15610. [PMID: 34341433 PMCID: PMC8328991 DOI: 10.1038/s41598-021-95068-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 07/14/2021] [Indexed: 12/18/2022] Open
Abstract
As a highly prevalent disease among women worldwide, breast cancer remains in urgent need of further elucidation its molecular mechanisms to improve the patient outcomes. Identifying hub genes involved in the pathogenesis and progression of breast cancer can potentially help to unveil mechanism and also provide novel diagnostic and prognostic markers. In this study, we integrated multiple bioinformatic methods and RNA in situ detection technology to identify and validate hub genes. EZH2 was recognized as a key gene by PPI network analysis. CENPL, ISG20L2, LSM4, MRPL3 were identified as four novel hub genes through the WGCNA analysis and literate search. Among these, many studies on EZH2 in breast cancer have been reported, but no studies are related to the roles of CENPL, ISG20L2, MRPL3 and LSM4 in breast cancer. These four novel hub genes were up-regulated in tumor tissues and associated with cancer progression. The receiver operating characteristic analysis and Kaplan–Meier survival analysis indicated that these four hub genes are promising candidate genes that can serve as diagnostic and prognostic biomarkers for breast cancer. Moreover, these four newly identified hub genes as aberrant molecules in the maintenance of breast cancer development, their exact functional mechanisms deserve further in-depth study.
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Affiliation(s)
- Jinbao Yin
- School of Medicine, Huaqiao University, Quanzhou, 362021, Fujian, China.,Department of Pathology, Guangdong Medical University, Dongguan, 523808, Guangdong, China
| | - Chen Lin
- School of Medicine, Huaqiao University, Quanzhou, 362021, Fujian, China
| | - Meng Jiang
- School of Medicine, Huaqiao University, Quanzhou, 362021, Fujian, China
| | - Xinbin Tang
- School of Medicine, Huaqiao University, Quanzhou, 362021, Fujian, China
| | - Danlin Xie
- School of Medicine, Huaqiao University, Quanzhou, 362021, Fujian, China
| | - Jingwen Chen
- School of Medicine, Huaqiao University, Quanzhou, 362021, Fujian, China
| | - Rongqin Ke
- School of Medicine, Huaqiao University, Quanzhou, 362021, Fujian, China.
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24
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Maurya NS, Kushwaha S, Chawade A, Mani A. Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer. Sci Rep 2021; 11:14304. [PMID: 34253750 PMCID: PMC8275802 DOI: 10.1038/s41598-021-92692-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 05/04/2021] [Indexed: 12/20/2022] Open
Abstract
Colorectal cancer (CRC) is a common cause of cancer-related deaths worldwide. The CRC mRNA gene expression dataset containing 644 CRC tumor and 51 normal samples from the cancer genome atlas (TCGA) was pre-processed to identify the significant differentially expressed genes (DEGs). Feature selection techniques Least absolute shrinkage and selection operator (LASSO) and Relief were used along with class balancing for obtaining features (genes) of high importance. The classification of the CRC dataset was done by ML algorithms namely, random forest (RF), K-nearest neighbour (KNN), and artificial neural networks (ANN). The significant DEGs were 2933, having 1832 upregulated and 1101 downregulated genes. The CRC gene expression dataset had 23,186 features. LASSO had performed better than Relief for classifying tumor and normal samples through ML algorithms namely RF, KNN, and ANN with an accuracy of 100%, while Relief had given 79.5%, 85.05%, and 100% respectively. Common features between LASSO and DEGs were 38, from them only 5 common genes namely, VSTM2A, NR5A2, TMEM236, GDLN, and ETFDH had shown statistically significant survival analysis. Functional review and analysis of the selected genes helped in downsizing the 5 genes to 2, which are VSTM2A and TMEM236. Differential expression of TMEM236 was statistically significant and was markedly reduced in the dataset which solicits appreciation for assessment as a novel biomarker for CRC diagnosis.
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Affiliation(s)
- Neha Shree Maurya
- Department of Biotechnology, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India
| | - Sandeep Kushwaha
- National Institute of Animal Biotechnology, Hyderabad, 500032, India
| | - Aakash Chawade
- Department of Plant Breeding, Swedish University of Agricultural Sciences, 230 53, Alnarp, Sweden.
| | - Ashutosh Mani
- Department of Biotechnology, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India.
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25
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Singh MP, Rai S, Singh NK, Srivastava S. Transcriptomic landscape of early age onset of colorectal cancer identifies novel genes and pathways in Indian CRC patients. Sci Rep 2021; 11:11765. [PMID: 34083590 PMCID: PMC8175339 DOI: 10.1038/s41598-021-91154-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 05/17/2021] [Indexed: 02/07/2023] Open
Abstract
Past decades of the current millennium have witnessed an unprecedented rise in Early age Onset of Colo Rectal Cancer (EOCRC) cases in India as well as across the globe. Unfortunately, EOCRCs are diagnosed at a more advanced stage of cancer. Moreover, the aetiology of EOCRC is not fully explored and still remains obscure. This study is aimed towards the identification of genes and pathways implicated in the EOCRC. In the present study, we performed high throughput RNA sequencing of colorectal tumor tissues for four EOCRC (median age 43.5 years) samples with adjacent mucosa and performed subsequent bioinformatics analysis to identify novel deregulated pathways and genes. Our integrated analysis identifies 17 hub genes (INSR, TNS1, IL1RAP, CD22, FCRLA, CXCL3, HGF, MS4A1, CD79B, CXCR2, IL1A, PTPN11, IRS1, IL1B, MET, TCL1A, and IL1R1). Pathway analysis of identified genes revealed that they were involved in the MAPK signaling pathway, hematopoietic cell lineage, cytokine-cytokine receptor pathway and PI3K-Akt signaling pathway. Survival and stage plot analysis identified four genes CXCL3, IL1B, MET and TNS1 genes (p = 0.015, 0.038, 0.049 and 0.011 respectively), significantly associated with overall survival. Further, differential expression of TNS1 and MET were confirmed on the validation cohort of the 5 EOCRCs (median age < 50 years and sporadic origin). This is the first approach to find early age onset biomarkers in Indian CRC patients. Among these TNS1 and MET are novel for EOCRC and may serve as potential biomarkers and novel therapeutic targets in future.
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Affiliation(s)
- Manish Pratap Singh
- Department of Biotechnology, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India
| | - Sandhya Rai
- Department of Biotechnology, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India
| | - Nand K Singh
- Department of Biotechnology, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India
| | - Sameer Srivastava
- Department of Biotechnology, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India.
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26
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Li X, Xie M, Yin S, Xiong Z, Mao C, Zhang F, Chen H, Jin L, Lan P, Lian L. Identification and Validation of a Six Immune-Related Genes Signature for Predicting Prognosis in Patients With Stage II Colorectal Cancer. Front Genet 2021; 12:666003. [PMID: 34017356 PMCID: PMC8129521 DOI: 10.3389/fgene.2021.666003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 04/14/2021] [Indexed: 01/20/2023] Open
Abstract
Background Immune-related genes (IRGs) play important roles in the tumor immune microenvironment and can affect the prognosis of cancer. This study aimed to construct a novel IRG signature for prognostic evaluation of stage II colorectal cancer (CRC). Methods Gene expression profiles and clinical data for stage II CRC patients were collected from the Cancer Genome Atlas and Gene Expression Omnibus database. Univariate, multivariate Cox regression, and least absolute shrinkage and selection operator regression were used to develop the IRG signature, namely IRGCRCII. A nomogram was constructed, and the “Cell Type Identification by Estimating Relative Subsets of RNA Transcripts” (CIBERSORT) method was used to estimate immune cell infiltration. The expression levels of genes and proteins were validated by qRT-PCR and immunohistochemistry in 30 pairs of primary stage II CRC and matched normal tissues. Results A total of 466 patients with stage II CRC were included, and 274 differentially expressed IRGs were identified. Six differentially expressed IRGs were detected and used to construct the IRGCRCII signature, which could significantly stratify patients into high-risk and low-risk groups in terms of disease-free survival in three cohorts: training, test, and external validation (GSE39582). Receiver operating characteristics analysis revealed that the area under the curves of the IRGCRCII signature were significantly greater than those of the OncotypeDX colon signature at 1 (0.759 vs. 0.623), 3 (0.875 vs. 0.629), and 5 years (0.906 vs. 0.698) disease-free survival, respectively. The nomogram performed well in the concordance index (0.779) and calibration curves. The high-risk group had a significantly higher percentage of infiltrated immune cells (e.g., M2 macrophages, plasma cells, resting mast cells) than the low-risk group. Finally, the results of qRT-PCR and immunohistochemistry experiments performed on 30 pairs of clinical specimens were consistent with bioinformatics analysis. Conclusion This study developed and validated a novel immune prognostic signature based on six differentially expressed IRGs for predicting disease-free survival and immune status in patients with stage II CRC, which may reflect immune dysregulation in the tumor immune microenvironment.
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Affiliation(s)
- Xianzhe Li
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Minghao Xie
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shi Yin
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhizhong Xiong
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Chaobin Mao
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Fengxiang Zhang
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Huaxian Chen
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Longyang Jin
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Ping Lan
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Lei Lian
- Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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27
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Zhan C, Wang Z, Xu C, Huang X, Su J, Chen B, Wang M, Qi Z, Bai P. Development and Validation of a Prognostic Gene Signature in Clear Cell Renal Cell Carcinoma. Front Mol Biosci 2021; 8:609865. [PMID: 33968978 PMCID: PMC8098777 DOI: 10.3389/fmolb.2021.609865] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Accepted: 01/19/2021] [Indexed: 12/14/2022] Open
Abstract
Clear cell renal cell carcinoma (ccRCC), one of the most common urologic cancer types, has a relatively good prognosis. However, clinical diagnoses are mostly done during the medium or late stages, when mortality and recurrence rates are quite high. Therefore, it is important to perform real-time information tracking and dynamic prognosis analysis for these patients. We downloaded the RNA-seq data and corresponding clinical information of ccRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 3,238 differentially expressed genes were identified between normal and ccRCC tissues. Through a series of Weighted Gene Co-expression Network, overall survival, immunohistochemical and the least absolute shrinkage selection operator (LASSO) analyses, seven prognosis-associated genes (AURKB, FOXM1, PTTG1, TOP2A, TACC3, CCNA2, and MELK) were screened. Their risk score signature was then constructed. Survival analysis showed that high-risk scores exhibited significantly worse overall survival outcomes than low-risk patients. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic curve and was further validated using another cohort. Gene set enrichment analysis showed that some cancer-associated phenotypes were significantly prevalent in the high-risk group. Overall, these findings prove that this risk model can potentially improve individualized diagnostic and therapeutic strategies.
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Affiliation(s)
| | - Zichu Wang
- Zhongshan Hospital, Xiamen University, Xiamen, China
| | - Chao Xu
- Shaoxing people's Hospital, Shaoxing, China
| | - Xiao Huang
- Nanchang Five Elements Bio-Technology Co., Ltd, Nanchang, China
| | - Junzhou Su
- Zhongshan Hospital, Xiamen University, Xiamen, China
| | - Bisheng Chen
- Zhongshan Hospital, Xiamen University, Xiamen, China
| | - Mingshan Wang
- Zhongshan Hospital, Xiamen University, Xiamen, China
| | - Zhihong Qi
- Zhongshan Hospital, Xiamen University, Xiamen, China
| | - Peiming Bai
- Zhongshan Hospital, Xiamen University, Xiamen, China
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28
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Hui Z, Zhang J, Zheng Y, Yang L, Yu W, An Y, Wei F, Ren X. Single-Cell Sequencing Reveals the Transcriptome and TCR Characteristics of pTregs and in vitro Expanded iTregs. Front Immunol 2021; 12:619932. [PMID: 33868236 PMCID: PMC8044526 DOI: 10.3389/fimmu.2021.619932] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 02/23/2021] [Indexed: 01/29/2023] Open
Abstract
Regulatory T cells (Tregs) play a critical role in the maintenance of immune tolerance and tumor evasion. However, the relative low proportion of these cells in peripheral blood and tissues has hindered many studies. We sought to establish a rapamycin-based in vitro Treg expansion procedure in patients diagnosed with colorectal cancer and perform single-cell sequencing to explore the characteristics of Treg cells. CD25+ cells enriched from peripheral blood mononuclear cells (PBMC) of colorectal tumor patients were cultured in X-VIVO15 medium, supplemented with 5% human AB serum, L-glutamine, rapamycin, interleukin-2 (IL-2), and Dynabeads human Treg expander for 21 days to expand Tregs. Treg cells with satisfactory phenotype and function were successfully expanded from CD4+CD25+ cells in patients with colorectal cancer. The median expansion fold was 75 (range, 20-105-fold), and >90.0% of the harvest cells were CD4+CD25+CD127dim/- cells. The ratio of CD4+CD25+Foxp3+ cells exceeded 60%. Functional assays showed that iTregs significantly inhibited CD8+T cell proliferation in vitro. Single-cell sequencing showed that the transcriptome of pTreg (CD4+CD25+CD127dim/- cells isolated from PBMC of colorectal cancer patients) and iTreg (CD4+CD25+CD127dim/- cells expanded in vitro according to the above regimen) cells were interlaced. pTregs exhibited enhanced suppressive function, whereas iTregs exhibited increased proliferative capacity. TCR repertoire analysis indicated minimal overlap between pTregs and iTregs. Pseudo-time trajectory analysis of Tregs revealed that pTregs were a continuum composed of three main branches: activated/effector, resting and proliferative Tregs. In contrast, in vitro expanded iTregs were a mixture of proliferating and activated/effector cells. The expression of trafficking receptors was also different in pTregs and iTregs. Various chemokine receptors were upregulated in pTregs. Activated effector pTregs overexpressed the chemokine receptor CCR10, which was not expressed in iTregs. The chemokine CCL28 was overexpressed in colorectal cancer and associated with poor prognosis. CCR10 interacted with CCL28 to mediate the recruitment of Treg into tumors and accelerated tumor progression. Depletion of CCR10+Treg cells from tumor microenvironment (TME) could be used as an effective treatment strategy for colorectal cancer patients. Our data distinguished the transcriptomic characteristics of different subsets of Treg cells and revealed the context-dependent functions of different populations of Treg cells, which was crucial to the development of alternative therapeutic strategies for Treg cells in autoimmune disease and cancer.
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Affiliation(s)
- Zhenzhen Hui
- Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Jiali Zhang
- Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yu Zheng
- National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Lili Yang
- National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Wenwen Yu
- National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yang An
- National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Feng Wei
- National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Xiubao Ren
- Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
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29
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CLCA4 and MS4A12 as the significant gene biomarkers of primary colorectal cancer. Biosci Rep 2021; 40:226087. [PMID: 32797167 PMCID: PMC7441370 DOI: 10.1042/bsr20200963] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 08/13/2020] [Accepted: 08/14/2020] [Indexed: 02/07/2023] Open
Abstract
Background: Primary colorectal cancer (PCRC) is a common digestive tract cancer in the elderly. However, the treatment effect of PCRC is still limited, and the long-term survival rate is low. Therefore, further exploring the pathogenesis of PCRC, and searching for specific molecular targets for diagnosis are the development trends of precise medical treatment, which have important clinical significance. Methods: The public data were downloaded from Gene Expression Omnibus (GEO) database. Verification for repeatability of intra-group data was performed by Pearson’s correlation test and principal component analysis. Differentially expressed genes (DEGs) between normal and PCRC were identified, and the protein–protein interaction (PPI) network was constructed. Significant module and hub genes were found in the PPI network. A total of 192 PCRC patients were recruited between 2010 and 2019 from the Fourth Hospital of Hebei Medical University. RT-PCR was used to measure the relative expression of CLCA4 and MS4A12. Furthermore, the study explored the effect of expression of CLCA4 and MS4A12 for overall survival. Results: A total of 53 DEGs were identified between PCRC and normal colorectal tissues. Ten hub genes concerned to PCRC were screened, namely CLCA4, GUCA2A, GCG, SST, MS4A12, PLP1, CHGA, PYY, VIP, and GUCA2B. The PCRC patients with low expression of CLCA4 and MS4A12 has a worse overall survival than high expression of CLCA4 and MS4A12 (P<0.05). Conclusion: The research of DEGs in PCRC (53 DEGs, 10 hub genes, especially CLCA4 and MS4A12) and related signaling pathways is conducive to the differential analysis of the molecular mechanism of PCRC.
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A comprehensive analysis of tumor microenvironment-related genes in colon cancer. Clin Transl Oncol 2021; 23:1769-1781. [PMID: 33689097 DOI: 10.1007/s12094-021-02578-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 02/23/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND The development and progression of colon cancer are significantly affected by the tumor microenvironment, which has attracted much attention. The goal of our study was primarily to find out all possible tumor microenvironment-related genes in colon cancer. METHOD This study quantified the immune and stromal landscape using the ESTIMATION algorithm using the gene expression matrix obtained from the UCSC Xena database. Dysregulated genes were harvested using the limma R package, and relevant pathways and biofunctions were identified using enrichment analysis. A least absolute shrinkage and selection operator (LASSO) regression was used to select the pivotal genes from the DEGs. Then, survival analysis was performed to determine the hub genes and a prognostic model was constructed by these hub genes with (or) TNM stage. Besides, associations between hub gene expressions and immune cell infiltration were assessed. RESULTS A total of 725 DEGs were identified. Most of the results of the enrichment analysis were immune-related items. 13 genes were selected as the hub genes and a moderate-to-strong positive correlation between most hub genes and several immune cells were observed. Besides, the prognostic value of the hub genes were comparable to TNM staging. CONCLUSIONS Our study provides a better understanding of how interactions between the 13 immune-prognostic hub genes and immune cells in the tumor microenvironment affect biological processes in colon cancer. These genes exhibit an equivalent ability to TNM staging in prognosis prediction. They are particularly expected to become novel prognostic biomarkers and targets of immunotherapies for colon cancer.
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Sun Z, Liu C, Cheng SY. Identification of four novel prognosis biomarkers and potential therapeutic drugs for human colorectal cancer by bioinformatics analysis. J Biomed Res 2021; 35:21-35. [PMID: 33361643 PMCID: PMC7874272 DOI: 10.7555/jbr.34.20200021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Colorectal cancer (CRC) is one of the most deadly cancers in the world with few reliable biomarkers that have been selected into clinical guidelines for prognosis of CRC patients. In this study, mRNA microarray datasets GSE113513, GSE21510, GSE44076, and GSE32323 were obtained from the Gene Expression Omnibus (GEO) and analyzed with bioinformatics to identify hub genes in CRC development. Differentially expressed genes (DEGs) were analyzed using the GEO2R tool. Gene ontology (GO) and KEGG analyses were performed through the DAVID database. STRING database and Cytoscape software were used to construct a protein-protein interaction (PPI) network and identify key modules and hub genes. Survival analyses of the DEGs were performed on GEPIA database. The Connectivity Map database was used to screen potential drugs. A total of 865 DEGs were identified, including 374 upregulated and 491 downregulated genes. These DEGs were mainly associated with metabolic pathways, pathways in cancer, cell cycle and so on. The PPI network was identified with 863 nodes and 5817 edges. Survival analysis revealed that HMMR, PAICS, ETFDH, and SCG2 were significantly associated with overall survival of CRC patients. And blebbistatin and sulconazole were identified as candidate drugs. In conclusion, our study found four hub genes involved in CRC, which may provide novel potential biomarkers for CRC prognosis, and two potential candidate drugs for CRC.
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Affiliation(s)
- Zhen Sun
- Department of Medical Genetics, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China.,Department of Pathology and Pathophysiology, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Chen Liu
- Department of Medical Genetics, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Steven Y Cheng
- Department of Medical Genetics, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
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Wang J, Yu S, Chen G, Kang M, Jin X, Huang Y, Lin L, Wu D, Wang L, Chen J. A novel prognostic signature of immune-related genes for patients with colorectal cancer. J Cell Mol Med 2020; 24:8491-8504. [PMID: 32564470 PMCID: PMC7412433 DOI: 10.1111/jcmm.15443] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 05/03/2020] [Accepted: 05/07/2020] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with an estimated 1.8 million new cases worldwide and associated with high mortality rates of 881 000 CRC-related deaths in 2018. Screening programs and new therapies have only marginally improved the survival of CRC patients. Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets. The aim of this study was to identify an immune-related prognostic signature for CRC. To this end, we combined gene expression and clinical data from the CRC data sets of The Cancer Genome Atlas (TCGA) into an integrated immune landscape profile. We identified a total of 476 IRGs that were differentially expressed in CRC vs normal tissues, of which 18 were survival related according to univariate Cox analysis. Stepwise multivariate Cox proportional hazards analysis established an immune-related prognostic signature consisting of SLC10A2, FGF2, CCL28, NDRG1, ESM1, UCN, UTS2 and TRDC. The predictive ability of this signature for 3- and 5-year overall survival was determined using receiver operating characteristics (ROC), and the respective areas under the curve (AUC) were 79.2% and 76.6%. The signature showed moderate predictive accuracy in the validation and GSE38832 data sets as well. Furthermore, the 8-IRG signature correlated significantly with tumour stage, invasion, lymph node metastasis and distant metastasis by univariate Cox analysis, and was established an independent prognostic factor by multivariate Cox regression analysis for CRC. Gene set enrichment analysis (GSEA) revealed a relationship between the IRG prognostic signature and various biological pathways. Focal adhesions and ECM-receptor interactions were positively correlated with the risk scores, while cytosolic DNA sensing and metabolism-related pathways were negatively correlated. Finally, the bioinformatics results were validated by real-time RT-qPCR. In conclusion, we identified and validated a novel, immune-related prognostic signature for patients with CRC, and this signature reflects the dysregulated tumour immune microenvironment and has a potential for better CRC patient management.
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Affiliation(s)
- Jun Wang
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Shaojun Yu
- Department of Surgical Oncologythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Guofeng Chen
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Muxing Kang
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Xiaoli Jin
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Yi Huang
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Lele Lin
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Dan Wu
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Lie Wang
- Bone Marrow Transplantation Center of the First Affiliated HospitalInstitute of ImmunologyZhejiang University School of MedicineHangzhouChina
| | - Jian Chen
- Department of Surgerythe Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
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Gao P, Hu Y, Wang J, Ni Y, Zhu Z, Wang H, Yang J, Huang L, Fang L. Underlying Mechanism of Insulin Resistance: A Bioinformatics Analysis Based on Validated Related-Genes from Public Disease Databases. Med Sci Monit 2020; 26:e924334. [PMID: 32651353 PMCID: PMC7370576 DOI: 10.12659/msm.924334] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Background The underlying mechanism of insulin resistance is complex; bioinformatics analysis is used to explore the mechanism based differential expression genes (DEGs) obtained from omics analysis. However, the expression and role of most DEGs involved in bioinformatics analysis are invalidated. This study aimed to disclose the mechanism of insulin resistance via bioinformatics analysis based on validated insulin resistance-related genes (IRRGs) collected from public disease-gene databases. Material/Methods IRRGs were collected from 4 disease databases including NCBI-Gene, CTD, RGD, and Phenopedia. GO and KEGG analysis of IRRGs were performed by DAVID. Then, the STRING database was employed to construct a protein–protein interaction (PPI) network of IRRGs. The module analysis and hub genes identification were carried out by MCODE and cytoHubba plugin of Cytoscape based on the primary PPI network, respectively. Results A total of 1195 IRRGs were identified. Response to drug, hypoxia, insulin, positive regulation of transcription from RNA polymerase II promoter, cell proliferation, inflammatory response, negative regulation of apoptotic process, glucose homeostasis, cellular response to insulin stimulus, and aging were proposed as the crucial functions related to insulin resistance. Ten insulin resistance-related pathways included the pathways of insulin resistance, pathways in cancer, adipocytokine, prostate cancer, PI3K-Akt, insulin, AMPK, HIF-1, prolactin, and pancreatic cancer signaling pathway were revealed. INS, AKT1, IL-6, TP53, TNF, VEGFA, MAPK3, EGFR, EGF, and SRC were identified as the top 10 hub genes. Conclusions The current study presented a landscape view of possible underlying mechanism of insulin resistance by bioinformatics analysis based on validated IRRGs.
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Affiliation(s)
- Peng Gao
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Yan Hu
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Junyan Wang
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Yinghua Ni
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Zhengyi Zhu
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Huijuan Wang
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Jufei Yang
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Lingfei Huang
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
| | - Luo Fang
- Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China (mainland)
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SLC1A1, SLC16A9, and CNTN3 Are Potential Biomarkers for the Occurrence of Colorectal Cancer. BIOMED RESEARCH INTERNATIONAL 2020; 2020:1204605. [PMID: 32566650 PMCID: PMC7273407 DOI: 10.1155/2020/1204605] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 04/29/2020] [Accepted: 05/01/2020] [Indexed: 12/13/2022]
Abstract
Background This study is aimed at identifying unknown clinically relevant genes involved in colorectal cancer using bioinformatics analysis. Methods Original microarray datasets GSE107499 (ulcerative colitis), GSE8671 (colorectal adenoma), and GSE32323 (colorectal cancer) were downloaded from the Gene Expression Omnibus. Common differentially expressed genes were filtered from the three datasets above. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed, followed by construction of a protein-protein interaction network to identify hub genes. Kaplan-Meier survival analysis and TIMER database analysis were used to screen the genes related to the prognosis and tumour-infiltrating immune cells of colorectal cancer. Receiver operating characteristic curves were used to assess whether the genes could be used as markers for the diagnosis of ulcerative colitis, colorectal adenoma, and colorectal cancer. Results A total of 237 differentially expressed genes common to the three datasets were identified, of which 60 were upregulated, 125 were downregulated, and 52 genes that were inconsistently up- and downregulated. Common differentially expressed genes were mainly enriched in the cellular component of extracellular exosome and integral component of membrane categories. Eight hub genes, i.e., CXCL3, CXCL8, CEACAM7, CNTN3, SLC1A1, SLC16A9, SLC4A4, and TIMP1, were related to the prognosis and tumour-infiltrating immune cells of colorectal cancer, and these genes have diagnostic value for ulcerative colitis, colorectal adenoma, and colorectal cancer. Conclusion Three novel genes, CNTN3, SLC1A1, and SLC16A9 were shown to have diagnostic value with respect to the occurrence of colorectal cancer and should be verified in future studies.
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Vahkal B, Yegorov S, Onyilagha C, Donner J, Reddick D, Shrivastav A, Uzonna J, Good SV. Immune System Effects of Insulin-Like Peptide 5 in a Mouse Model. Front Endocrinol (Lausanne) 2020; 11:610672. [PMID: 33519716 PMCID: PMC7841425 DOI: 10.3389/fendo.2020.610672] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 11/16/2020] [Indexed: 12/25/2022] Open
Abstract
INTRODUCTION Insulin-like peptide 5 (INSL5) is a peptide hormone with proposed actions in glucose homeostasis and appetite regulation via its cognate receptor, relaxin family peptide receptor 4 (RXFP4). Here, we look for evidence for their involvement in the immune system using a mouse model. METHODS In silico analyses: we queried public databases for evidence of expression of INSL5-RXFP4 in immune system tissues/cells (NCBI's SRA and GeoProfiles) and disorders (EMBO-EBI) and performed phylogenetic footprinting to look for evidence that they are regulated by immune-associated transcription factors (TFs). Experimental analyses: We characterized the expression and correlation of INSL5/RXFP4 and other immune system markers in central and peripheral immune organs from C57/bl6 mice in seven cohorts. We tested whether fluctuations in circulating INSL5 induce an immune response, by injecting mice with 30 μg/kg of INSL5 peptide in the peritoneum, and examining levels of immune markers and metabolic peptides in plasma. Lastly, we quantified the expression of Rxfp4 in T-cells, dendritic cells and cell lines derived from human and mouse and tested the hypothesis that co-incubation of ANA-1 cells in INSL5 and LPS alters cytokine expression. RESULTS We find Insl5 expression only in thymus (in addition to colon) where its expression was highly correlated with Il-7, a marker of thymocyte development. This result is consistent with our in silico findings that Insl5 is highly expressed in thymic DP, DN thymocytes and cortical TEC's, and with evidence that it is regulated by thymocyte-associated TF's. We find Rxfp4 expression in all immune organs, and moderately high levels in DCs, particularly splenic DCs, and evidence that it is regulated by immune-associated TF's, such as STAT's and GATA. Systemic effects: We observed significantly elevated concentrations of blood GLP-1, GIP, GCG and PYY following intraperitoneal injection of INSL5, and significantly altered expression of cytokines IL-5, IL-7, M-CSF, IL-15, IL-27 and MIP-2. Immune cell effects: Incubation of ANA-1 cells with INSL5 impeded cell growth and led to a transient elevation of IL-15 and sustained reduction in IL-1β, IL-6 and TNFα. CONCLUSION We propose that INSL5-RXFP4 play a novel role in both central and peripheral immune cell signaling.
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Affiliation(s)
- Brett Vahkal
- Department of Biology, University of Winnipeg, Winnipeg, MB, Canada
- *Correspondence: Brett Vahkal, ; Sara V. Good,
| | - Sergey Yegorov
- Department of Biology, University of Winnipeg, Winnipeg, MB, Canada
| | | | | | - Dean Reddick
- Department of Biology, University of Winnipeg, Winnipeg, MB, Canada
| | | | - Jude Uzonna
- Department of Immunology, University of Manitoba, Winnipeg, MB, Canada
| | - Sara V. Good
- Department of Biology, University of Winnipeg, Winnipeg, MB, Canada
- *Correspondence: Brett Vahkal, ; Sara V. Good,
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Mo X, Su Z, Yang B, Zeng Z, Lei S, Qiao H. Identification of key genes involved in the development and progression of early-onset colorectal cancer by co-expression network analysis. Oncol Lett 2019; 19:177-186. [PMID: 31897128 PMCID: PMC6924089 DOI: 10.3892/ol.2019.11073] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 09/24/2019] [Indexed: 02/06/2023] Open
Abstract
A number of studies have revealed that there is an increasing incidence of early-onset colorectal cancer (CRC) in young adults (before the age of 50 years) and a progressive decline in CRC among older patients, after the age of 50 years (late-onset CRC). However, the etiology of early-onset CRC is not fully understood. The aim of the present study was to identify key genes associated with the development of early-onset CRC through weighted gene co-expression network analysis (WGCNA). The GSE39582 dataset was downloaded from the Gene Expression Omnibus database, and the data profiles of tissues from patients diagnosed before the age of 50 years were selected. The top 10,000 genes with the highest variability were used to construct the WGCNA. Hub genes were identified from the modules associated with clinical traits using gene significance >0.2 and module membership >0.8 as the cut-off criteria. Gene Ontology and pathway analyses were subsequently performed on the hub genes and a protein-protein interaction network (PPI) was constructed. The diagnostic value of module hub genes with a degree score >5 in the PPI network was verified in samples from patients with CRC diagnosed before the age of 50 years obtained from The Cancer Genome Atlas. Eight co-expressed gene modules were identified in the WGCNA and two modules (blue and turquoise) were associated with the tumor-node-metastasis stage. A total of 140 module hub genes were identified and found to be enriched in 'mitochondrial large ribosomal subunit', 'structural constituent of ribosome', 'poly (A) RNA binding', 'collagen binding', 'protein ubiquitination' and 'ribosome pathway'. Twenty-six module hub genes were found to have a degree score >5 in the PPI network, seven of which [secreted protein acidic and cysteine rich (SPARC), decorin (DCN), fibrillin 1 (FBN1), WW domain containing transcription regulator 1 (WWTR1), transgelin (TAGLN), DEAD-box helicase 28 (DDX28) and cold shock domain containing C2 (CSDC2)], had good prognostic values for patients with early-onset CRC, but not late-onset CRC. Therefore, SPARC, DCN, FBN1, WWTR1, TAGLN, DDX28 and CSDC2 may contribute to the development of early-onset CRC and may serve as potential diagnostic biomarkers.
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Affiliation(s)
- Xiaoqiong Mo
- Department of Nursing, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Zexin Su
- Department of Joint Surgery, Huadu District People's Hospital, Southern Medical University, Guangzhou, Guangdong 510800, P.R. China
| | - Bingsheng Yang
- Department of Orthopedics, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong 510282, P.R. China
| | - Zhirui Zeng
- Guizhou Provincial Key Laboratory of Pathogenesis and Drug Research on Common Chronic Diseases, Department of Physiology, School of Basic Medicine, Guizhou Medical University, Guiyang, Guizhou 550009, P.R. China
| | - Shan Lei
- Guizhou Provincial Key Laboratory of Pathogenesis and Drug Research on Common Chronic Diseases, Department of Physiology, School of Basic Medicine, Guizhou Medical University, Guiyang, Guizhou 550009, P.R. China
| | - Hui Qiao
- Department of Nursing, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
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Wang J, Wang Y, Kong F, Han R, Song W, Chen D, Bu L, Wang S, Yue J, Ma L. Identification of a six‐gene prognostic signature for oral squamous cell carcinoma. J Cell Physiol 2019; 235:3056-3068. [PMID: 31538341 DOI: 10.1002/jcp.29210] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 09/03/2019] [Indexed: 12/24/2022]
Affiliation(s)
- Jiaying Wang
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
| | - Yuanyong Wang
- Department of Thoracic Surgery Affiliated Hospital of Qingdao University Qingdao China
| | - Fanzhi Kong
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
| | - Rui Han
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
| | - Wenbin Song
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
| | - Di Chen
- Department of Gastroenterology Affiliated Hospital of Qingdao University Qingdao China
| | - Lingxue Bu
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
| | - Shuangyi Wang
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
| | - Jin Yue
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
| | - Lei Ma
- Department of Stomatology Affiliated Hospital of Qingdao University Qingdao Shandong China
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Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis. Cardiovasc Ther 2019; 2019:8490707. [PMID: 31772617 PMCID: PMC6739802 DOI: 10.1155/2019/8490707] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 06/25/2019] [Indexed: 12/14/2022] Open
Abstract
Background Acute myocardial infarction (AMI) is a common disease with high morbidity and mortality around the world. The aim of this research was to determine the differentially expressed genes (DEGs), which may serve as potential therapeutic targets or new biomarkers in AMI. Methods From the Gene Expression Omnibus (GEO) database, three gene expression profiles (GSE775, GSE19322, and GSE97494) were downloaded. To identify the DEGs, integrated bioinformatics analysis and robust rank aggregation (RRA) method were applied. These DEGs were performed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses by using Clusterprofiler package. In order to explore the correlation between these DEGs, the interaction network of protein-protein internet (PPI) was constructed using the STRING database. Utilizing the MCODE plug-in of Cytoscape, the module analysis was performed. Utilizing the cytoHubba plug-in, the hub genes were screened out. Results 57 DEGs in total were identified, including 2 down- and 55 upregulated genes. These DEGs were mainly enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and so on. The module analysis filtered out 18 key genes, including Cxcl5, Arg1, Cxcl1, Spp1, Selp, Ptx3, Tnfaip6, Mmp8, Serpine1, Ptgs2, Il6, Il1r2, Il1b, Ccl3, Ccr1, Hmox1, Cxcl2, and Ccl2. Ccr1 was the most fundamental gene in PPI network. 4 hub genes in total were identified, including Cxcl1, Cxcl2, Cxcl5, and Mmp8. Conclusion This study may provide credible molecular biomarkers in terms of screening, diagnosis, and prognosis for AMI. Meanwhile, it also serves as a basis for exploring new therapeutic target for AMI.
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Zhang B, Wu Q, Wang Z, Xu R, Hu X, Sun Y, Wang Q, Ju F, Ren S, Zhang C, Qin L, Ma Q, Zhou YL. The promising novel biomarkers and candidate small molecule drugs in kidney renal clear cell carcinoma: Evidence from bioinformatics analysis of high-throughput data. Mol Genet Genomic Med 2019; 7:e607. [PMID: 30793530 PMCID: PMC6503072 DOI: 10.1002/mgg3.607] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 01/14/2019] [Indexed: 01/05/2023] Open
Abstract
Background Kidney renal clear cell carcinoma (KIRC) is the most common subtype of renal tumor. However, the molecular mechanisms of KIRC pathogenesis remain little known. The purpose of our study was to identify potential key genes related to the occurrence and prognosis of KIRC, which could serve as novel diagnostic and prognostic biomarkers for KIRC. Methods Three gene expression profiles from gene expression omnibus database were integrated to identify differential expressed genes (DEGs) using limma package. Enrichment analysis and PPI construction for these DEGs were performed by bioinformatics tools. We used Gene Expression Profiling Interactive Analysis (GEPIA) database to further analyze the expression and prognostic values of hub genes. The GEPIA database was used to further validate the bioinformatics results. The Connectivity Map was used to identify candidate small molecules that could reverse the gene expression of KIRC. Results A total of 503 DEGs were obtained. The PPI network with 417 nodes and 1912 interactions was constructed. Go and KEGG pathway analysis revealed that these DEGs were most significantly enriched in excretion and valine, leucine, and isoleucine degradation, respectively. Six DEGs with high degree of connectivity (ACAA1, ACADSB, ALDH6A1, AUH, HADH,and PCCA) were selected as hub genes, which significantly associated with worse survival of patients. Finally, we identified the top 20 most significant small molecules and pipemidic acid was the most promising small molecule to reverse the KIRC gene expression. Conclusions This study first uncovered six key genes in KIRC which contributed to improving our understanding of the molecular mechanisms of KIRC pathogenesis. ACAA1, ACADSB, ALDH6A1, AUH, HADH,and PCCA could serve as the promising novel biomarkers for KIRC diagnosis, prognosis, and treatment.
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Affiliation(s)
- Bo Zhang
- Medical School of Nantong University, Nantong, P.R. China.,The Hand Surgery Research Center, Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong, P.R. China
| | - Qiong Wu
- Medical School of Nantong University, Nantong, P.R. China.,The Hand Surgery Research Center, Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong, P.R. China
| | - Ziheng Wang
- The Hand Surgery Research Center, Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong, P.R. China.,Department of Medicine, Nantong University Xinling college, Nantong, P.R. China
| | - Ran Xu
- Medical School of Nantong University, Nantong, P.R. China
| | - Xinyi Hu
- Department of Medicine, Nantong University Xinling college, Nantong, P.R. China
| | - Yidan Sun
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, P.R. China
| | - Qiuhong Wang
- The Hand Surgery Research Center, Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong, P.R. China
| | - Fei Ju
- The Hand Surgery Research Center, Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong, P.R. China
| | - Shiqi Ren
- Department of Medicine, Nantong University Xinling college, Nantong, P.R. China
| | - Chenlin Zhang
- Department of Spine, Chinese medicine hospital, Wuxi, P.R. China
| | - Lin Qin
- Department of Urology, The First people's Hospital of Taicang City, Taicang Affiliated Hospital of Soochow University, Suzhou, P.R. China
| | - Qianqian Ma
- Emergency office, Wuxi Center for disease control and prevention, Wuxi, P.R. China
| | - You Lang Zhou
- The Hand Surgery Research Center, Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong, P.R. China
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