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Serrano G, Berastegui N, Díaz-Mazkiaran A, García-Olloqui P, Rodriguez-Res C, Huerga-Dominguez S, Ainciburu M, Vilas-Zornoza A, Martin-Uriz PS, Aguirre-Ruiz P, Ullate-Agote A, Ariceta B, Lamo-Espinosa JM, Acha P, Calvete O, Jimenez T, Molero A, Montoro MJ, Díez-Campelo M, Valcarcel D, Solé F, Alfonso-Pierola A, Ochoa I, Prósper F, Ezponda T, Hernaez M. Single-cell transcriptional profile of CD34+ hematopoietic progenitor cells from del(5q) myelodysplastic syndromes and impact of lenalidomide. Nat Commun 2024; 15:5272. [PMID: 38902243 PMCID: PMC11189937 DOI: 10.1038/s41467-024-49529-x] [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: 11/01/2023] [Accepted: 06/06/2024] [Indexed: 06/22/2024] Open
Abstract
While myelodysplastic syndromes with del(5q) (del(5q) MDS) comprises a well-defined hematological subgroup, the molecular basis underlying its origin remains unknown. Using single cell RNA-seq (scRNA-seq) on CD34+ progenitors from del(5q) MDS patients, we have identified cells harboring the deletion, characterizing the transcriptional impact of this genetic insult on disease pathogenesis and treatment response. Interestingly, both del(5q) and non-del(5q) cells present similar transcriptional lesions, indicating that all cells, and not only those harboring the deletion, may contribute to aberrant hematopoietic differentiation. However, gene regulatory network (GRN) analyses reveal a group of regulons showing aberrant activity that could trigger altered hematopoiesis exclusively in del(5q) cells, pointing to a more prominent role of these cells in disease phenotype. In del(5q) MDS patients achieving hematological response upon lenalidomide treatment, the drug reverts several transcriptional alterations in both del(5q) and non-del(5q) cells, but other lesions remain, which may be responsible for potential future relapses. Moreover, lack of hematological response is associated with the inability of lenalidomide to reverse transcriptional alterations. Collectively, this study reveals transcriptional alterations that could contribute to the pathogenesis and treatment response of del(5q) MDS.
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Affiliation(s)
- Guillermo Serrano
- Computational Biology Program CIMA-Universidad de Navarra, Cancer Center Clínica Universidad de Navarra (CCUN), IdISNA, Pamplona, Spain
- Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Nerea Berastegui
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
| | - Aintzane Díaz-Mazkiaran
- Computational Biology Program CIMA-Universidad de Navarra, Cancer Center Clínica Universidad de Navarra (CCUN), IdISNA, Pamplona, Spain
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
| | - Paula García-Olloqui
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
| | - Carmen Rodriguez-Res
- Computational Biology Program CIMA-Universidad de Navarra, Cancer Center Clínica Universidad de Navarra (CCUN), IdISNA, Pamplona, Spain
| | - Sofia Huerga-Dominguez
- Hematology and Cell Therapy Service, Cancer Center Clínica Universidad de Navarra (CCUN), IdISNA, Pamplona, Spain
| | - Marina Ainciburu
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
| | - Amaia Vilas-Zornoza
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
| | - Patxi San Martin-Uriz
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
| | - Paula Aguirre-Ruiz
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
| | - Asier Ullate-Agote
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
| | - Beñat Ariceta
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
| | | | - Pamela Acha
- MDS Research Group, Josep Carreras Leukaemia Research Institut, Universitat Autònoma de Barcelona, Barcelona, Spain
- Service of Hematology, Hospital Universitari Vall d'Hebron, Barcelona; Vall d'Hebron Instituto de Oncología (VHIO), Barcelona, Spain
| | - Oriol Calvete
- MDS Research Group, Josep Carreras Leukaemia Research Institut, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Tamara Jimenez
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
- Department of Hematology, Hospital Universitario de Salamanca-IBSAL, Salamanca, Spain
| | - Antonieta Molero
- Service of Hematology, Hospital Universitari Vall d'Hebron, Barcelona; Vall d'Hebron Instituto de Oncología (VHIO), Barcelona, Spain
| | - Maria Julia Montoro
- Service of Hematology, Hospital Universitari Vall d'Hebron, Barcelona; Vall d'Hebron Instituto de Oncología (VHIO), Barcelona, Spain
| | - Maria Díez-Campelo
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
- Department of Hematology, Hospital Universitario de Salamanca-IBSAL, Salamanca, Spain
| | - David Valcarcel
- Service of Hematology, Hospital Universitari Vall d'Hebron, Barcelona; Vall d'Hebron Instituto de Oncología (VHIO), Barcelona, Spain
| | - Francisco Solé
- MDS Research Group, Josep Carreras Leukaemia Research Institut, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ana Alfonso-Pierola
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain
- Hematology and Cell Therapy Service, Cancer Center Clínica Universidad de Navarra (CCUN), IdISNA, Pamplona, Spain
| | - Idoia Ochoa
- Instituto de Ciencia de los Datos e Inteligencia Artificial (DATAI), University of Navarra, Pamplona, Spain
- Department of Electrical and Electronics engineering, School of Engineering (Tecnun), University of Navarra, Donostia, Spain
| | - Felipe Prósper
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain.
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain.
- Hematology and Cell Therapy Service, Cancer Center Clínica Universidad de Navarra (CCUN), IdISNA, Pamplona, Spain.
| | - Teresa Ezponda
- Hematology-Oncology Program, CIMA, Cancer Center Clínica Universidad de Navarra (CCUN), IdiSNA, Pamplona, Spain.
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain.
| | - Mikel Hernaez
- Computational Biology Program CIMA-Universidad de Navarra, Cancer Center Clínica Universidad de Navarra (CCUN), IdISNA, Pamplona, Spain.
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Madrid, Spain.
- Instituto de Ciencia de los Datos e Inteligencia Artificial (DATAI), University of Navarra, Pamplona, Spain.
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2
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Panchal NK, Samdani P, Sengupta T, Prince SE. Computational Analysis of Non-synonymous SNPs in ATM Kinase: Structural Insights, Functional Implications, and Inhibitor Discovery. Mol Biotechnol 2024:10.1007/s12033-024-01120-x. [PMID: 38489015 DOI: 10.1007/s12033-024-01120-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 02/13/2024] [Indexed: 03/17/2024]
Abstract
Ataxia telangiectasia-mutated (ATM) protein kinase, a key player in cellular integrity regulation, is known for its role in DNA damage response. This study investigates the broader impact of ATM on cellular processes and potential clinical manifestations arising from mutations, aiming to expand our understanding of ATM's diverse functions beyond conventional roles. The research employs a comprehensive set of computational techniques for a thorough analysis of ATM mutations. The mutation data are curated from dbSNP and HuVarBase databases. A meticulous assessment is conducted, considering factors such as deleterious effects, protein stability, oncogenic potential, and biophysical characteristics of the identified mutations. Conservation analysis, utilizing diverse computational tools, provides insights into the evolutionary significance of these mutations. Molecular docking and dynamic simulation analyses are carried out for selected mutations, investigating their interactions with Y2080D, AZD0156, and quercetin inhibitors to gauge potential therapeutic implications. Among the 419 mutations scrutinized, five (V1913C, Y2080D, L2656P, C2770G, and C2930G) are identified as both disease causing and protein destabilizing. The study reveals the oncogenic potential of these mutations, supported by findings from the COSMIC database. Notably, Y2080D is associated with haematopoietic and lymphoid cancers, while C2770G shows a correlation with squamous cell carcinomas. Molecular docking and dynamic simulation analyses highlight strong binding affinities of quercetin for Y2080D and AZD0156 for C2770G, suggesting potential therapeutic options. In summary, this computational analysis provides a comprehensive understanding of ATM mutations, revealing their potential implications in cellular integrity and cancer development. The study underscores the significance of Y2080D and C2770G mutations, offering valuable insights for future precision medicine targeting-specific ATM. Despite informative computational analyses, a significant research gap exists, necessitating essential in vitro and in vivo studies to validate the predicted effects of ATM mutations on protein structure and function.
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Affiliation(s)
- Nagesh Kishan Panchal
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, 632 014, India
| | - Poorva Samdani
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Tiasa Sengupta
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Sabina Evan Prince
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, 632 014, India.
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Yu H, Jiang L, Li CI, Ness S, Piccirillo SGM, Guo Y. Somatic mutation effects diffused over microRNA dysregulation. Bioinformatics 2023; 39:btad520. [PMID: 37624931 PMCID: PMC10474951 DOI: 10.1093/bioinformatics/btad520] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/14/2023] [Accepted: 08/23/2023] [Indexed: 08/27/2023] Open
Abstract
MOTIVATION As an important player in transcriptome regulation, microRNAs may effectively diffuse somatic mutation impacts to broad cellular processes and ultimately manifest disease and dictate prognosis. Previous studies that tried to correlate mutation with gene expression dysregulation neglected to adjust for the disparate multitudes of false positives associated with unequal sample sizes and uneven class balancing scenarios. RESULTS To properly address this issue, we developed a statistical framework to rigorously assess the extent of mutation impact on microRNAs in relation to a permutation-based null distribution of a matching sample structure. Carrying out the framework in a pan-cancer study, we ascertained 9008 protein-coding genes with statistically significant mutation impacts on miRNAs. Of these, the collective miRNA expression for 83 genes showed significant prognostic power in nine cancer types. For example, in lower-grade glioma, 10 genes' mutations broadly impacted miRNAs, all of which showed prognostic value with the corresponding miRNA expression. Our framework was further validated with functional analysis and augmented with rich features including the ability to analyze miRNA isoforms; aggregative prognostic analysis; advanced annotations such as mutation type, regulator alteration, somatic motif, and disease association; and instructive visualization such as mutation OncoPrint, Ideogram, and interactive mRNA-miRNA network. AVAILABILITY AND IMPLEMENTATION The data underlying this article are available in MutMix, at http://innovebioinfo.com/Database/TmiEx/MutMix.php.
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Affiliation(s)
- Hui Yu
- Department of Public Health, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL 33136, U.S.A
| | - Limin Jiang
- Department of Public Health, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL 33136, U.S.A
| | - Chung-I Li
- Department of Statistics, National Cheng Kung University, Tainan 701401, Taiwan
| | - Scott Ness
- Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, United States
| | - Sara G M Piccirillo
- Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, United States
| | - Yan Guo
- Department of Public Health, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL 33136, U.S.A
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Luo J, Mei Z, Lin S, Xing X, Qian X, Lin H. Integrative pan-cancer analysis reveals the importance of PAQR family in lung cancer. J Cancer Res Clin Oncol 2023; 149:10149-10160. [PMID: 37266662 DOI: 10.1007/s00432-023-04922-9] [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: 04/17/2023] [Accepted: 05/23/2023] [Indexed: 06/03/2023]
Abstract
BACKGROUND The progestin and adipoQ receptors (PAQRs) family contains 11 genes involved in the regulation of metabolism and cancer development. However, a comprehensive understanding of the role of PAQRs in cancer remains largely scarce, and the associations between their expression levels and immune signatures also need to be researched. METHODS Here, we applied pan-cancer analysis to explore the associations between PAQRs expression and survival, tumor microenvironment (TME), and drug sensitivity from the UCSC Xena and CellMiner databases. Besides, we further studied the expression, survival and somatic mutations of PAQRs in lung cancer (LC) from TCGA database. RESULTS The results showed that PAQRs had significant heterogeneity with some upregulation and some downregulation in most tumors. Specifically, compared with PAQR3/5/6/9 and MMD2, ADIPOR1/2, PAQR4/7/8 and MMD had higher levels of average expression in all tumor types. PAQRs expression was greatly correlated with survival, immune subtypes, TME, and drug sensitivity. Furthermore, this research concentrated on analyzing the relationship of PAQRs expression with LC prognosis, and proved that ADIPOR2, PAQR4/9 and MMD were independent prognostic factors for LC patients. Finally, based on somatic mutation data, the genetic mutations in LC patients were majorly missense mutations, and TP53 and TTN had the top two highest mutation frequencies. CONCLUSION Collectively, PAQRs may serve as robust biomarkers to predict the prognosis and guide immunotherapy of tumors, especially LC, which enables novel ways for improving cancer treatment.
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Affiliation(s)
- Jingru Luo
- Medical Oncology, The Second Affiliated Hospital of Hainan Medical University, No. 368, Yehai Avenue, Longhua District, Haikou, 570100, Hainan, China
| | - Zhenxin Mei
- Medical Oncology, The Second Affiliated Hospital of Hainan Medical University, No. 368, Yehai Avenue, Longhua District, Haikou, 570100, Hainan, China
| | - Shu Lin
- Medical Oncology, The Second Affiliated Hospital of Hainan Medical University, No. 368, Yehai Avenue, Longhua District, Haikou, 570100, Hainan, China
| | - Xin Xing
- Medical Oncology, The Second Affiliated Hospital of Hainan Medical University, No. 368, Yehai Avenue, Longhua District, Haikou, 570100, Hainan, China
| | - Xiaoying Qian
- Medical Oncology, The Second Affiliated Hospital of Hainan Medical University, No. 368, Yehai Avenue, Longhua District, Haikou, 570100, Hainan, China.
| | - Haifeng Lin
- Medical Oncology, The Second Affiliated Hospital of Hainan Medical University, No. 368, Yehai Avenue, Longhua District, Haikou, 570100, Hainan, China.
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Snyman M, Xu S. The effects of mutations on gene expression and alternative splicing. Proc Biol Sci 2023; 290:20230565. [PMID: 37403507 PMCID: PMC10320348 DOI: 10.1098/rspb.2023.0565] [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: 03/09/2023] [Accepted: 06/12/2023] [Indexed: 07/06/2023] Open
Abstract
Understanding the relationship between mutations and their genomic and phenotypic consequences has been a longstanding goal of evolutionary biology. However, few studies have investigated the impact of mutations on gene expression and alternative splicing on the genome-wide scale. In this study, we aim to bridge this knowledge gap by utilizing whole-genome sequencing data and RNA sequencing data from 16 obligately parthenogenetic Daphnia mutant lines to investigate the effects of ethyl methanesulfonate-induced mutations on gene expression and alternative splicing. Using rigorous analyses of mutations, expression changes and alternative splicing, we show that trans-effects are the major contributor to the variance in gene expression and alternative splicing between the wild-type and mutant lines, whereas cis mutations only affected a limited number of genes and do not always alter gene expression. Moreover, we show that there is a significant association between differentially expressed genes and exonic mutations, indicating that exonic mutations are an important driver of altered gene expression.
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Affiliation(s)
- Marelize Snyman
- Department of Biology, University of Texas at Arlington, Arlington, TX 76019, USA
| | - Sen Xu
- Department of Biology, University of Texas at Arlington, Arlington, TX 76019, USA
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Qin H, Sheng W, Zhang G, Yang Q, Yao S, Yue Y, Zhang P, Zhu Y, Wang Q, Chen Y, Zeng H, Weng J, Yu F, Yang J. Comprehensive analysis of cuproptosis-related prognostic gene signature and tumor immune microenvironment in HCC. Front Genet 2023; 14:1094793. [PMID: 36891150 PMCID: PMC9986498 DOI: 10.3389/fgene.2023.1094793] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 02/06/2023] [Indexed: 02/22/2023] Open
Abstract
Background: Copper is an indispensable mineral element involved in many physiological metabolic processes. Cuproptosis is associated with a variety of cancer such as hepatocellular carcinoma (HCC). The objective of this study was to examine the relationships between the expression of cuproptosis-related genes (CRGs) and tumor characteristics, including prognosis and microenvironment of HCC. Methods: The differentially expressed genes (DEGs) between high and low CRGs expression groups in HCC samples were identified, and further were analyzed for functional enrichment analysis. Then, CRGs signature of HCC was constructed and analyzed utilizing LASSO and univariate and multivariate Cox regression analysis. Prognostic values of CRGs signature were evaluated by Kaplan-Meier analysis, independent prognostic analysis and nomograph. The expression of prognostic CRGs was verified by Real-time quantitative PCR (RT-qPCR) in HCC cell lines. In addition, the relationships between prognostic CRGs expression and the immune infiltration, tumor microenvironment, antitumor drugs response and m6A modifications were further explored using a series of algorithms in HCC. Finally, ceRNA regulatory network based on prognostic CRGs was constructed. Results: The DEGs between high and low CRG expression groups in HCC were mainly enriched in focal adhesion and extracellular matrix organization. Besides, we constructed a prognostic model that consists of CDKN2A, DLAT, DLST, GLS, and PDHA1 CRGs for predicting the survival likelihood of HCC patients. And the elevated expression of these five prognostic CRGs was substantially in HCC cell lines and associated with poor prognosis. Moreover, immune score and m6A gene expression were higher in the high CRG expression group of HCC patients. Furthermore, prognostic CRGs have higher mutation rates in HCC, and are significantly correlated with immune cell infiltration, tumor mutational burden, microsatellite instability, and anti-tumor drug sensitivity. Then, eight lncRNA-miRNA-mRNA regulatory axes that affected the progression of HCC were predicted. Conclusion: This study demonstrated that the CRGs signature could effectively evaluate prognosis, tumor immune microenvironment, immunotherapy response and predict lncRNA-miRNA-mRNA regulatory axes in HCC. These findings extend our knowledge of cuproptosis in HCC and may inform novel therapeutic strategies for HCC.
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Affiliation(s)
- Haotian Qin
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Weibei Sheng
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | | | - Qi Yang
- Department of Medical Ultrasound, Peking University Shenzhen Hospital, Shenzhen, China
| | - Sen Yao
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Yaohang Yue
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Peng Zhang
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Yuanchao Zhu
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Qichang Wang
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Yixiao Chen
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Hui Zeng
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jian Weng
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Fei Yu
- National and Local Joint Engineering Research Center of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, China.,Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jun Yang
- Department of Radiology, Peking University Shenzhen Hospital, Shenzhen, China
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Yu M, Wang H, Xu H, Lv Y, Li Q. High MCM8 expression correlates with unfavorable prognosis and induces immune cell infiltration in hepatocellular carcinoma. Aging (Albany NY) 2022; 14:10027-10049. [PMID: 36575045 PMCID: PMC9831725 DOI: 10.18632/aging.204440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 12/09/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND MCM8 has been reported highly expressed in several human malignancies. However, its role in HCC has not yet been researched. METHODS The prognostic significance of MCM8 mRNA expression was analyzed using datasets from TCGA and GEO databases. Immunohistochemistry (IHC) assay was used to detect the MCM8 protein expression in HCC tissues. The Cox regression analysis was employed to determine the independent prognostic value of MCM8. Then, we established a nomogram for OS and RFS prediction based on MCM8 protein expression. We analyzed the DNA methylation and genetic alteration of MCM8 in HCC. Moreover, GO, KEGG and GSEA were utilized to explore the potential biological functions of MCM8. Subsequently, we evaluate the correlations between MCM8 expression and composition of the tumor microenvironment as well as immunocyte infiltration ratio in HCC. RESULTS MCM8 mRNA and protein were significantly overexpressed in HCC tissues. High MCM8 protein expression was an independent risk factor for OS and RFS of HCC patients. MCM8 expression is altered in 60% of queried HCC patients. In addition, higher methylation of the CpG site cg03098629, cg10518808, and 17230679 correlated with lower MCM8 levels. MCM8 expression correlated with cell cycle and DNA replication signaling. Moreover, MCM8 may be correlated with different compositions of the tumor microenvironment and immunocyte infiltration ratio in HCC. CONCLUSIONS MCM8 was highly expressed in HCC tissues and was associated with poor prognosis. Meanwhile, high expression of MCM8 may induce immune cell infiltration and may be a promising prognostic biomarker for HCC.
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Affiliation(s)
- Meng Yu
- Department of Critical Care Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou 318000, Zhejiang, China
| | - Huaxiang Wang
- Department of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan 442000, Hubei, China
| | - Hongyang Xu
- Department of Critical Care Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou 318000, Zhejiang, China
| | - Yuhang Lv
- Department of Critical Care Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou 318000, Zhejiang, China
| | - Qingsong Li
- Department of Gastroenterology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou 318000, Zhejiang, China
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He S, Yu J, Sun W, Sun Y, Tang M, Meng B, Liu Y, Li J. A comprehensive pancancer analysis reveals the potential value of RAR-related orphan receptor C (RORC) for cancer immunotherapy. Front Genet 2022; 13:969476. [PMID: 36186454 PMCID: PMC9520743 DOI: 10.3389/fgene.2022.969476] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Background: RAR-related orphan receptor C (RORC) plays an important role in autoimmune responses and inflammation. However, its function in cancer immunity is still unclear. Its potential value in cancer immunotherapy (CIT) needs to be further studied. Methods: Expression and clinical data for 33 cancers were obtained from UCSC-Xena. The correlation between RORC expression and clinical parameters was analyzed using the limma software package to assess the prognostic value of RORC. Timer2.0 and DriverDBv3 were used to analyze the RORC mutation and methylation profiles. RORC-associated signaling pathways were identified by GSEA. The correlations of RORC expression with tumor microenvironment factors were further assessed, including immune cell infiltration (obtained by CIBERSORT) and immunomodulators (in pancancer datasets from the Tumor-Immune System Interactions and Drug Bank [TISIDB] database). In addition, the correlations of RORC with four CIT biomarkers (tumor mutational burden, microsatellite instability, programmed death ligand-1, and mismatch repair) were explored. Furthermore, three CIT cohorts (GSE67501, GSE168204, and IMvigor210) from the Gene Expression Omnibus database and a previously published study were used to determine the association between RORC expression and CIT response. Results: RORC was differentially expressed in many tumor tissues relative to normal tissues (20/33). In a small number of cancers, RORC expression was correlated with age (7/33), sex (4/33), and tumor stage (9/33). Furthermore, RORC expression showed prognostic value in many cancers, especially in kidney renal clear cell carcinoma (KIRC), brain lower grade glioma (LGG), and mesothelioma (MESO). The mutation rate of RORC in most cancer types was low, while RORC was hypermethylated or hypomethylated in multiple cancers. RORC was associated with a variety of biological processes and signal transduction pathways in various cancers. Furthermore, RORC was strongly correlated with immune cell infiltration, immunomodulators, and CIT biomarkers. However, no significant association was found between RORC and CIT response in the three CIT cohorts. Conclusion Our findings revealed the potential immunotherapeutic value of RORC for various cancers and provides preliminary evidence for the application of RORC in CIT.
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Affiliation(s)
- Shengfu He
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jiawen Yu
- Department of Oncology, Anqing First People’s Hospital of Anhui Medical University/Anqing First People’s Hospital of Anhui Province, Anqing, China
| | - Weijie Sun
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yating Sun
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mingyang Tang
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Bao Meng
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yanyan Liu
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Institute of Bacterial Resistance, Anhui Medical University, Hefei, China
- Anhui Center for Surveillance of Bacterial Resistance, Hefei, China
| | - Jiabin Li
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Institute of Bacterial Resistance, Anhui Medical University, Hefei, China
- Anhui Center for Surveillance of Bacterial Resistance, Hefei, China
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9
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Wu Q, Wang L, Tsui SKW. Mutational signatures representative transcriptomic perturbations in hepatocellular carcinoma. Front Genet 2022; 13:970907. [PMID: 36081995 PMCID: PMC9445436 DOI: 10.3389/fgene.2022.970907] [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: 06/16/2022] [Accepted: 07/27/2022] [Indexed: 11/17/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a primary malignancy with increasing incidence and poor prognosis. Heterogeneity originating from genomic instability is one of the critical reasons of poor outcomes. However, the studies of underlying mechanisms and pathways affected by mutations are still not intelligible. Currently, integrative molecular-level studies using multiomics approaches enable comprehensive analysis for cancers, which is pivotal for personalized therapy and mortality reduction. In this study, genomic and transcriptomic data of HCC are obtained from The Cancer Genome Atlas (TCGA) to investigate the affected coding and non-coding RNAs, as well as their regulatory network due to certain mutational signatures of HCC. Different types of RNAs have their specific enriched biological functions in mutational signature-specific HCCs, upregulated coding RNAs are predominantly associated with lipid metabolism-related pathways, and downregulated coding RNAs are enriched in axonogenesis for tumor microenvironment generation. Additionally, differentially expressed miRNAs are inclined to concentrate in cancer-related signaling pathways. Some of these RNAs also serve as prognostic factors that help predict the survival outcome of HCCs with certain mutational signatures. Furthermore, deregulation of competing endogenous RNA (ceRNA) regulatory network is identified, which suggests a potential therapy via interference of miRNA activity for mutational signature-specific HCC. This study proposes a projection approach to reduce therapeutic complexity from genomic mutations to transcriptomic alterations. Through this method, we identify genes and pathways critical for mutational signature-specific HCC and further discover a series of prognostic markers indicating patient survival outcome.
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10
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Crawford J, Christensen BC, Chikina M, Greene CS. Widespread redundancy in -omics profiles of cancer mutation states. Genome Biol 2022; 23:137. [PMID: 35761387 PMCID: PMC9238138 DOI: 10.1186/s13059-022-02705-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 06/14/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal remains unclear. RESULTS We consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem that presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. From the TCGA Pan-Cancer Atlas that contains genetic alteration data, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts. Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. We find that one or more other data types for many of the genes are approximately equally effective predictors. Performance is more variable between mutations than that between data types for the same mutation, and there is little difference between the top data types. We also find that combining data types into a single multi-omics model provides little or no improvement in predictive ability over the best individual data type. CONCLUSIONS Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.
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Affiliation(s)
- Jake Crawford
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
| | - Maria Chikina
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Casey S Greene
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA.
- Center for Health AI, University of Colorado School of Medicine, Aurora, CO, USA.
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11
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Wang H, Yang C, Jiang Y, Hu H, Fang J, Yang F. A novel ferroptosis-related gene signature for clinically predicting recurrence after hepatectomy of hepatocellular carcinoma patients. Am J Cancer Res 2022; 12:1995-2011. [PMID: 35693077 PMCID: PMC9185608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 04/14/2022] [Indexed: 06/15/2023] Open
Abstract
High recurrence rate in HCC is the primary cause of the poor prognosis after hepatectomy. Therefore, in this study, we aimed to construct a gene signature for predicting the recurrence rate in HCC. The mRNA expression profiles and clinical information of HCC patients from GEO and TCGA databases were used, and ferroptosis-related gene list was obtained from the FerrDb database. We identified 39 ferroptosis-related genes (FDEGs) that were differentially expressed between HCC samples and normal tissues from the GSE14520 dataset. The univariate and multivariate Cox regression analyses were employed to construct a prognostic signature. Seven FDEGs (MAPK9, SLC1A4, PCK2, ACSL3, STMN1, CDO1, and CXCL2) were included to construct a risk model, which was validated in the TCGA dataset. Patients in high-risk groups exhibited a significantly poor prognosis compared with patients in low-risk groups in both the training set (GSE14520 cohort) and the validation set (TCGA cohort). Multivariate cox regression analyses demonstrated that the 7-gene signature was an independent risk factor for RFS in HCC patients. KEGG analysis showed that FDEGs were mainly enriched in Ferroptosis, Hepatocellular carcinoma pathway, and MAPK signaling pathway. GSEA analysis suggested that the high-risk group was correlated with multiple oncogenic signatures and invasive-related pathways. These results indicated that this risk model can accurately predict recurrence after hepatectomy and offer novel research directions for personalized treatment in HCC patients.
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Affiliation(s)
- Huaxiang Wang
- Department of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of MedicineShiyan, Hubei 442000, China
- The Fuzong Clinical Medical College of Fujian Medical UniversityFuzhou 350025, Fujian, China
| | - Chengkai Yang
- The Fuzong Clinical Medical College of Fujian Medical UniversityFuzhou 350025, Fujian, China
| | - Yi Jiang
- The Fuzong Clinical Medical College of Fujian Medical UniversityFuzhou 350025, Fujian, China
- Department of Hepatobiliary Surgery, 900 Hospital of The Joint Logistics TeamFuzhou 350025, Fujian, China
| | - Huanzhang Hu
- The Fuzong Clinical Medical College of Fujian Medical UniversityFuzhou 350025, Fujian, China
- Department of Hepatobiliary Surgery, 900 Hospital of The Joint Logistics TeamFuzhou 350025, Fujian, China
| | - Jian Fang
- Department of Hepatobiliary Medicine, The Third People’s Hospital of Fujian University of Traditional Chinese MedicineFuzhou 350108, Fujian, China
| | - Fang Yang
- The Fuzong Clinical Medical College of Fujian Medical UniversityFuzhou 350025, Fujian, China
- Department of Hepatobiliary Surgery, 900 Hospital of The Joint Logistics TeamFuzhou 350025, Fujian, China
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12
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Sigamani V, Rajasingh S, Gurusamy N, Panda A, Rajasingh J. In-Silico and In-Vitro Analysis of Human SOS1 Protein Causing Noonan Syndrome - A Novel Approach to Explore the Molecular Pathways. Curr Genomics 2021; 22:526-540. [PMID: 35386434 PMCID: PMC8905634 DOI: 10.2174/1389202922666211130144221] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 11/02/2021] [Accepted: 11/03/2021] [Indexed: 11/22/2022] Open
Abstract
Aims Perform in-silico analysis of human SOS1 mutations to elucidate their pathogenic role in Noonan syndrome (NS). Background NS is an autosomal dominant genetic disorder caused by single nucleotide mutation in PTPN11, SOS1, RAF1, and KRAS genes. NS is thought to affect approximately 1 in 1000. NS patients suffer different pathogenic effects depending on the mutations they carry. Analysis of the mutations would be a promising predictor in identifying the pathogenic effect of NS. Methods We performed computational analysis of the SOS1 gene to identify the pathogenic nonsynonymous single nucleotide polymorphisms (nsSNPs) th a t cause NS. SOS1 variants were retrieved from the SNP database (dbSNP) and analyzed by in-silico tools I-Mutant, iPTREESTAB, and MutPred to elucidate their structural and functional characteristics. Results We found that 11 nsSNPs of SOS1 that were linked to NS. 3D modeling of the wild-type and the 11 nsSNPs of SOS1 showed that SOS1 interacts with cardiac proteins GATA4, TNNT2, and ACTN2. We also found that GRB2 and HRAS act as intermediate molecules between SOS1 and cardiac proteins. Our in-silico analysis findings were further validated using induced cardiomyocytes (iCMCs) derived from NS patients carrying SOS1 gene variant c.1654A>G (NSiCMCs) and compared to control human skin fibroblast-derived iCMCs (C-iCMCs). Our in vitro data confirmed that the SOS1, GRB2 and HRAS gene expressions as well as the activated ERK protein, were significantly decreased in NS-iCMCs when compared to C-iCMCs. Conclusion This is the first in-silico and in vitro study demonstrating that 11 nsSNPs of SOS1 play deleterious pathogenic roles in causing NS.
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Affiliation(s)
- Vinoth Sigamani
- Department of Bioscience Research, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Sheeja Rajasingh
- Department of Bioscience Research, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Narasimman Gurusamy
- Department of Bioscience Research, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Arunima Panda
- Department of Genetic Engineering, SRM Institute of Science and Technology, Chennai, India
| | - Johnson Rajasingh
- Department of Bioscience Research, University of Tennessee Health Science Center, Memphis, Tennessee
- Department of Medicine-Cardiology, University of Tennessee Health Science Center, Memphis, Tennessee
- Department of Microbiology, Immunology & Biochemistry, University of Tennessee Health Science Center, Memphis, Tennessee
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13
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Atout S, Shurrab S, Loveridge C. Evaluation of the Suitability of RNAscope as a Technique to Measure Gene Expression in Clinical Diagnostics: A Systematic Review. Mol Diagn Ther 2021; 26:19-37. [PMID: 34957535 PMCID: PMC8710359 DOI: 10.1007/s40291-021-00570-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/02/2021] [Indexed: 01/01/2023]
Abstract
Objective To evaluate the application of RNAscope in the clinical diagnostic field compared to the current ‘gold standard’ methods employed for testing gene expression levels, including immunohistochemistry (IHC), quantitative real time PCR (qPCR), and quantitative reverse transcriptase PCR (qRT-PCR), and to detect genes, including DNA in situ hybridisation (DNA ISH). Methods This systematic review searched CINAHL, Medline, Embase and Web of Science databases for studies that were conducted after 2012 and that compared RNAscope with one or more of the ‘gold standard’ techniques in human samples. QUADAS-2 test was used for the evaluation of the articles’ risk of bias. The results were reviewed narratively and analysed qualitatively. Results A total of 27 articles (all retrospective studies) were obtained and reviewed. The 27 articles showed a range of low to middle risk of bias scores, as assessed by QUADAS-2 test. 26 articles studied RNAscope within cancer samples. RNAscope was compared to different techniques throughout the included studies (IHC, qPCR, qRT-PCR and DNA ISH). The results confirmed that RNAscope is a highly sensitive and specific method that has a high concordance rate (CR) with qPCR, qRT-PCR, and DNA ISH (81.8–100%). However, the CR with IHC was lower than expected (58.7–95.3%), which is mostly due to the different products that each technique measures (RNA vs. protein). Discussion This is the first systematic review to be conducted on the use of RNAscope in the clinical diagnostic field. RNAscope was found to be a reliable and robust method that could complement gold standard techniques currently used in clinical diagnostics to measure gene expression levels or for gene detection. However, there were not enough data to suggest that RNAscope could stand alone in the clinical diagnostic setting, indicating further prospective studies to validate diagnostic accuracy values, in keeping with relevant regulations, followed by cost evaluation are required. Supplementary Information The online version contains supplementary material available at 10.1007/s40291-021-00570-2.
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Affiliation(s)
- Sameeha Atout
- College of Medical, Veterinary and Life Sciences, University of Glasgow, Room 202, Sir James Black Building, Glasgow, G128QQ, UK
| | - Shaymaa Shurrab
- Division of Biochemical Diseases, Department of Paediatrics, School of Medicine, BC Children's Hospital, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
| | - Carolyn Loveridge
- College of Medical, Veterinary and Life Sciences, University of Glasgow, Room 202, Sir James Black Building, Glasgow, G128QQ, UK.
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Tirado TC, Moura LL, Shigunov P, Figueiredo FB. Methodological Appraisal of Literature Concerning the Analysis of Genetic Variants or Protein Levels of Complement Components on Susceptibility to Infection by Trypanosomatids: A Systematic Review. Front Immunol 2021; 12:780810. [PMID: 34899745 PMCID: PMC8656155 DOI: 10.3389/fimmu.2021.780810] [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: 09/21/2021] [Accepted: 11/09/2021] [Indexed: 11/25/2022] Open
Abstract
Background Trypanosomatids are protozoa responsible for a wide range of diseases, with emphasis on Chagas Disease (CD) and Leishmaniasis, which are in the list of most relevant Neglected Tropical Diseases (NTD) according to World Health Organization (WHO). During the infectious process, immune system is immediately activated, and parasites can invade nucleated cells through a broad diversity of receptors. The complement system − through classical, alternative and lectin pathways − plays a role in the first line of defense against these pathogens, acting in opsonization, phagocytosis and lysis of parasites. Genetic modifications in complement genes, such as Single Nucleotide Polymorphisms (SNPs), can influence host susceptibility to these parasites and modulate protein expression. Methods In March and April 2021, a literature search was conducted at the PubMed and Google Scholar databases and the reference lists obtained were verified. After applying the inclusion and exclusion criteria, the selected studies were evaluated and scored according to eleven established criteria regarding their thematic approach and design, aiming at the good quality of publications. Results Twelve papers were included in this systematic review: seven investigating CD and five focusing on Leishmaniasis. Most articles presented gene and protein approaches, careful determination of experimental groups, and adequate choice of experimental techniques, although several of them were not up-to-date. Ten studies explored the association of polymorphisms and haplotypes with disease progression, with emphasis on lectin complement pathway genes. Decreased and increased patient serum protein levels were associated with susceptibility to CD and Visceral Leishmaniasis, respectively. Conclusion This systematic review shows the influence of genetic alterations in complement genes on the progression of several infectious diseases, with a focus on conditions caused by trypanosomatids, and contributes suggestions and evidence to improve experimental design in future research proposals.
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Affiliation(s)
- Thais Cristina Tirado
- Laboratório de Biologia Celular, Instituto Carlos Chagas, Fundação Oswaldo Cruz (FIOCRUZ), Curitiba, Brazil
| | - Larine Lowry Moura
- Laboratório de Biologia Celular, Instituto Carlos Chagas, Fundação Oswaldo Cruz (FIOCRUZ), Curitiba, Brazil
| | - Patrícia Shigunov
- Laboratório de Biologia Básica de Células-Tronco, Instituto Carlos Chagas, Fundação Oswaldo Cruz (FIOCRUZ), Curitiba, Brazil
| | - Fabiano Borges Figueiredo
- Laboratório de Biologia Celular, Instituto Carlos Chagas, Fundação Oswaldo Cruz (FIOCRUZ), Curitiba, Brazil
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15
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Shafiee MN, Lim WK, Poh Shwen Shi C, Mohamed Yasin IA, Azemi AF, Zakaria ML, Hannaan Abdul Hafizz AM, Mustangin M, Chandralega Kampan N, Abd Aziz NH, Md Zain RR. PTEN protein expression has role in predicting disease-free-interval in endometrioid endometrial carcinoma. Horm Mol Biol Clin Investig 2021; 42:403-410. [PMID: 34364315 DOI: 10.1515/hmbci-2021-0017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 07/11/2021] [Indexed: 11/15/2022]
Abstract
OBJECTIVES To determine the significance of tumour PTEN protein expression in endometrioid endometrial carcinoma (EEC) and it is correlation with tumour characteristics. METHODS A total of 30 eligible archived paraffin-embedded tissue blocks from 61 EEC cases (January 2015-December 2017) were retrieved from the Histopathology Laboratory in Universiti Kebangsaan Malaysia Medical Centre (UKMMC) following institutional ethic approval. For PTEN protein detection, immunohistochemistry (IHC) staining was performed and the data was correlated with clinicopathologic parameters. RESULTS Fourteen samples (46.7%) showed positive PTEN protein expression, while 16 (53.3%) were negative. The mean age was 62.00 ± 9.51 years old, while the mean Body Mass Index (BMI) was 27.28 ± 7.16 kg/m2. There was no significant difference between age (p=0.27, 95% CI: -10.98 to 3.21) and BMI (p=0.67, 95% CI: -4.30 to 6.58) with PTEN protein expression. There were significant correlation between PTEN protein expression with myometrial invasion (p=0.010), but not with lymphovascular space invasion (p=0.743), grade (p=0.532), stage (p=0.733) and CA-125 level (p=0.47). The higher stage correlates with the presence of LVSI (p=0.002). PTEN positive associated with longer disease-free-interval (p=0.025), but not improving the overall survival (p=0.38). CONCLUSIONS Positive PTEN protein expression correlates with less myometrial invasion.
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Affiliation(s)
- Mohamad Nasir Shafiee
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Wei Keith Lim
- Special Study Module, Undergraduate Program, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Cheryl Poh Shwen Shi
- Special Study Module, Undergraduate Program, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Ira Adila Mohamed Yasin
- Special Study Module, Undergraduate Program, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Aina Fatini Azemi
- Special Study Module, Undergraduate Program, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Muhammad Luqman Zakaria
- Special Study Module, Undergraduate Program, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Abdul Muzhill Hannaan Abdul Hafizz
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia.,Department of Pathology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Muaatamarulain Mustangin
- Department of Pathology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Nirmala Chandralega Kampan
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Nor Haslinda Abd Aziz
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
| | - Reena Rahayu Md Zain
- Department of Pathology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, Malaysia
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Almuzzaini B, Alghamdi J, Alomani A, AlGhamdi S, Alsharm AA, Alshieban S, Sayed A, Alhejaily AG, Aljaser FS, Abudawood M, Almajed F, Samman A, Balwi MAA, Aziz MA. Identification of Novel Mutations in Colorectal Cancer Patients Using AmpliSeq Comprehensive Cancer Panel. J Pers Med 2021; 11:jpm11060535. [PMID: 34207827 PMCID: PMC8230213 DOI: 10.3390/jpm11060535] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/25/2021] [Accepted: 05/30/2021] [Indexed: 02/07/2023] Open
Abstract
Biomarker discovery would be an important tool in advancing and utilizing the concept of precision and personalized medicine in the clinic. Discovery of novel variants in local population provides confident targets for developing biomarkers for personalized medicine. We identified the need to generate high-quality sequencing data from local colorectal cancer patients and understand the pattern of occurrence of variants. In this report, we used archived samples from Saudi Arabia and used the AmpliSeq comprehensive cancer panel to identify novel somatic variants. We report a comprehensive analysis of next-generation sequencing results with a coverage of >300X. We identified 466 novel variants which were previously unreported in COSMIC and ICGC databases. We analyzed the genes associated with these variants in terms of their frequency of occurrence, probable pathogenicity, and clinicopathological features. Among pathogenic somatic variants, 174 were identified for the first time in the large intestine. APC, RET, and EGFR genes were most frequently mutated. A higher number of variants were identified in the left colon. Occurrence of variants in ERBB2 was significantly correlated with those of EGFR and ATR genes. Network analyses of the identified genes provide functional perspective of the identified genes and suggest affected pathways and probable biomarker candidates. This report lays the ground work for biomarker discovery and identification of driver gene mutations in local population.
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Affiliation(s)
- Bader Almuzzaini
- King Abdullah International Medical Research Center, Medical Genomics Research Department, Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences, Riyadh 11481, Saudi Arabia;
- Correspondence: (B.A.); (M.A.A.); Tel.: +966-11-429-4533 (B.A.); +966-11-429-4582 (M.A.A.)
| | - Jahad Alghamdi
- King Abdullah International Medical Research Center, Saudi Biobank, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh 11481, Saudi Arabia; (J.A.); (A.S.)
| | - Alhanouf Alomani
- Department of Pathology, College of Medicine, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia;
| | - Saleh AlGhamdi
- Clinical Research Department, Research Center, King Fahad Medical City, Riyadh 11564, Saudi Arabia;
| | - Abdullah A. Alsharm
- Comprehensive Cancer Center, King Fahad Medical City, Riyadh 11564, Saudi Arabia;
| | - Saeed Alshieban
- King Abdul Aziz Medical City-National Guard Health Affairs (NGHA), King Abdullah International Medical Research Center, King Saud Bin Abdul Aziz University for Health Sciences (KSAU-HS), Riyadh 14611, Saudi Arabia;
| | - Ahood Sayed
- King Abdullah International Medical Research Center, Saudi Biobank, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh 11481, Saudi Arabia; (J.A.); (A.S.)
| | | | - Feda S. Aljaser
- Department of Clinical Laboratory Sciences, Chair of Medical and Molecular Genetics Research, College of Applied Medical Sciences, King Saud University Riyadh, Riyadh 11564, Saudi Arabia; (F.S.A.); (M.A.)
| | - Manal Abudawood
- Department of Clinical Laboratory Sciences, Chair of Medical and Molecular Genetics Research, College of Applied Medical Sciences, King Saud University Riyadh, Riyadh 11564, Saudi Arabia; (F.S.A.); (M.A.)
| | - Faisal Almajed
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh 11481, Saudi Arabia;
| | - Abdulhadi Samman
- Department of Pathology, Faculty of Medicine, University of Jeddah, Jeddah 23218, Saudi Arabia;
| | - Mohammed A. Al Balwi
- King Abdullah International Medical Research Center, Medical Genomics Research Department, Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences, Riyadh 11481, Saudi Arabia;
| | - Mohammad Azhar Aziz
- King Abdullah International Medical Research Center, Colorectal Cancer Research Program, Department of Cellular Therapy and Cancer Research, Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences, Riyadh 11481, Saudi Arabia
- Correspondence: (B.A.); (M.A.A.); Tel.: +966-11-429-4533 (B.A.); +966-11-429-4582 (M.A.A.)
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17
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Chen C, Gao D, Huo J, Qu R, Guo Y, Hu X, Luo L. Multiomics analysis reveals CT83 is the most specific gene for triple negative breast cancer and its hypomethylation is oncogenic in breast cancer. Sci Rep 2021; 11:12172. [PMID: 34108519 PMCID: PMC8190062 DOI: 10.1038/s41598-021-91290-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 05/25/2021] [Indexed: 02/05/2023] Open
Abstract
Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer (BrC) subtype lacking effective therapeutic targets currently. The development of multi-omics databases facilities the identification of core genes for TNBC. Using TCGA-BRCA and METABRIC datasets, we identified CT83 as the most TNBC-specific gene. By further integrating FUSCC-TNBC, CCLE, TCGA pan-cancer, Expression Atlas, and Human Protein Atlas datasets, we found CT83 is frequently activated in TNBC and many other cancers, while it is always silenced in non-TNBC, 120 types of normal non-testis tissues, and 18 types of blood cells. Notably, according to the TCGA-BRCA methylation data, hypomethylation on chromosome X 116,463,019 to 116,463,039 is significantly correlated with the abnormal activation of CT83 in BrC. Using Kaplan-Meier Plotter, we demonstrated that activated CT83 is significantly associated with unfavorably overall survival in BrC and worse outcomes in some other cancers. Furthermore, GSEA suggested that the abnormal activation of CT83 in BrC is probably oncogenic by triggering the activation of cell cycle signaling. Meanwhile, we also noticed copy number variations and mutations of CT83 are quite rare in any cancer type, and its role in immune infiltration is not significant. In summary, we highlighted the significance of CT83 for TNBC and presented a comprehensive bioinformatics strategy for single-gene analysis in cancer.
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Affiliation(s)
- Chen Chen
- grid.452884.7Breast and Thyroid Center, The First People’s Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Fenghuang N Rd, Zunyi, 563000 Guizhou China
| | - Dan Gao
- grid.452884.7Breast and Thyroid Center, The First People’s Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Fenghuang N Rd, Zunyi, 563000 Guizhou China
| | - Jinlong Huo
- grid.452884.7Breast and Thyroid Center, The First People’s Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Fenghuang N Rd, Zunyi, 563000 Guizhou China
| | - Rui Qu
- grid.452884.7Breast and Thyroid Center, The First People’s Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Fenghuang N Rd, Zunyi, 563000 Guizhou China
| | - Youming Guo
- grid.452884.7Breast and Thyroid Center, The First People’s Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Fenghuang N Rd, Zunyi, 563000 Guizhou China
| | - Xiaochi Hu
- grid.452884.7Breast and Thyroid Center, The First People’s Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Fenghuang N Rd, Zunyi, 563000 Guizhou China
| | - Libo Luo
- grid.452884.7Breast and Thyroid Center, The First People’s Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Fenghuang N Rd, Zunyi, 563000 Guizhou China
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Zhang Y, Han P, Guo Q, Hao Y, Qi Y, Xin M, Zhang Y, Cui B, Wang P. Oncogenic Landscape of Somatic Mutations Perturbing Pan-Cancer lncRNA-ceRNA Regulation. Front Cell Dev Biol 2021; 9:658346. [PMID: 34079798 PMCID: PMC8166229 DOI: 10.3389/fcell.2021.658346] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 04/19/2021] [Indexed: 12/12/2022] Open
Abstract
Competing endogenous RNAs (ceRNA) are transcripts that communicate with and co-regulate each other by competing for the binding of shared microRNAs (miRNAs). Long non-coding RNAs (lncRNAs) as a type of ceRNA constitute a competitive regulatory network determined by miRNA response elements (MREs). Mutations in lncRNA MREs destabilize their original regulatory pathways. Study of the effects of lncRNA somatic mutations on ceRNA mechanisms can clarify tumor mechanisms and contribute to the development of precision medicine. Here, we used somatic mutation profiles collected from TCGA to characterize the role of lncRNA somatic mutations in the ceRNA regulatory network in 33 cancers. The 31,560 mutation sites identified by TargetScan and miRanda affected the balance of 70,811 ceRNA regulatory pathways. Putative mutations were categorized as high or low based on mutation frequencies. Multivariate multiple regression revealed a significant effect of 162 high-frequency mutations in six cancer types on the expression levels of target mRNAs (ceMs) through the ceRNA mechanism. Low-frequency mutations in multiple cancers perturbing 1624 ceM have been verified by Student’s t-test, indicating a significant mechanism of changes in the expression level of oncogenic genes. Oncogenic signaling pathway studies involving ceMs indicated functional heterogeneity of multiple cancers. Furthermore, we identified that lncRNA, perturbing ceMs associated with patient survival, have potential as biomarkers. Our collective findings revealed individual differences in somatic mutations perturbing ceM expression and impacting tumor heterogeneity.
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Affiliation(s)
- Yuanfu Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Peng Han
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, China.,Heilongjiang Cancer Research Institute, Harbin, China
| | - Qiuyan Guo
- Department of Gynecology, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yangyang Hao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yue Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Mengyu Xin
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yafang Zhang
- Department of Anatomy, Harbin Medical University, Harbin, China
| | - Binbin Cui
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Peng Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
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Zhuang Y, Wang H, Jiang D, Li Y, Feng L, Tian C, Pu M, Wang X, Zhang J, Hu Y, Liu P. Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis. BMC Cancer 2021; 21:380. [PMID: 33836681 PMCID: PMC8034139 DOI: 10.1186/s12885-021-08108-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 03/28/2021] [Indexed: 12/14/2022] Open
Abstract
Background Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. Currently, however, there is still few effective biomarkers for early diagnosis and prognostic judgment in CRC patients. The purpose was to identify novel mutation signatures for the diagnosis and prognosis of CRC. Methods Clinical information of 531 CRC patients and their sequencing data were downloaded from TCGA database (training group), and 53 clinical patients were collected and sequenced with targeted next generation sequencing (NGS) technology (validation group). The relationship between the mutation genes and the diagnosis, pathological type, stage and prognosis of CRC were compared to construct signatures for CRC, and then analyzed their relationship with RNA expression, immunocyte infiltration and tumor microenvironment (TME). Results Mutations of TP53, APC, KRAS, BRAF and ATM covered 97.55% of TCGA population and 83.02% validation patients. Moreover, 57.14% validation samples and 22.06% TCGA samples indicated that patients with mucinous adenocarcinoma tended to have BRAF mutation, but no TP53 mutation. Mutations of TP53, PIK3CA, FAT4, FMN2 and TRRAP had a remarkable difference between I-II and III-IV stage patients (P < 0.0001). Besides, the combination of PIK3CA, LRP1B, FAT4 and ROS1 formed signatures for the prognosis and survival of CRC patients. The mutations of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4, FMN2, TRRAP, LRP1B, and ROS1 formed the signatures for predicting diagnosis and prognosis of CRC. Among them, mutation of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4 and TRRAP significantly reduced their RNA expression level. Stromal score, immune score and ESTIMATE score were lower in patients with TP53, APC, KRAS, PIK3CA mutation compared non-mutation patients. All the 11 gene mutations affected the distributions of immune cells. Conclusion This study constructed gene mutation signatures for the diagnosis, treatment and prognosis in CRC, and proved that their mutations affected RNA expression levels, TME and immunocyte infiltration. Our results put forward further insights into the genotype of CRC. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08108-9.
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Affiliation(s)
- Yan Zhuang
- Department of Colorectal Oncology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Hailong Wang
- Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, No.354 Beima Road, Hongqiao District, Tianjin, 300120, China
| | - Da Jiang
- Department of Medical Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Ying Li
- Department of Medical Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Lixia Feng
- Department of Nursing, Tianjin Cancer Hospital Airport Hospital, Tianjin, 300300, China
| | - Caijuan Tian
- Tianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd, Tianjin, 300381, China
| | - Mingyu Pu
- Tianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd, Tianjin, 300381, China
| | - Xiaowei Wang
- Tianjin Yunquan Intelligent Technology Co., Ltd, Tianjin, 300381, China
| | - Jiangyan Zhang
- Tianjin Yunquan Intelligent Technology Co., Ltd, Tianjin, 300381, China
| | - Yuanjing Hu
- Department of Gynecological Oncology, Tianjin Central Hospital of Obstetrics & Gynecology, No. 156 Nankai Third Road, Nankai District, Tianjin, 300100, China.
| | - Pengfei Liu
- Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, No.354 Beima Road, Hongqiao District, Tianjin, 300120, China.
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20
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Jiang Q, Jin M. Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression. Front Genet 2021; 12:629946. [PMID: 33719339 PMCID: PMC7952975 DOI: 10.3389/fgene.2021.629946] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 01/21/2021] [Indexed: 01/26/2023] Open
Abstract
Exploring the molecular mechanisms of breast cancer is essential for the early prediction, diagnosis, and treatment of cancer patients. The large scale of data obtained from the high-throughput sequencing technology makes it difficult to identify the driver mutations and a minimal optimal set of genes that are critical to the classification of cancer. In this study, we propose a novel method without any prior information to identify mutated genes associated with breast cancer. For the somatic mutation data, it is processed to a mutated matrix, from which the mutation frequency of each gene can be obtained. By setting a reasonable threshold for the mutation frequency, a mutated gene set is filtered from the mutated matrix. For the gene expression data, it is used to generate the gene expression matrix, while the mutated gene set is mapped onto the matrix to construct a co-expression profile. In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. In the stage of evaluation, we propose a weighted metric to modify the traditional accuracy to solve the sample imbalance problem. We apply the proposed method to The Cancer Genome Atlas breast cancer data and identify a mutated gene set, among which the implicated genes are oncogenes or tumor suppressors previously reported to be associated with carcinogenesis. As a comparison with the integrative network, we also perform the optimal model on the individual gene expression and the gold standard PMA50. The results show that the integrative network outperforms the gene expression and PMA50 in the average of most metrics, which indicate the effectiveness of our proposed method by integrating multiple data sources, and can discover the associated mutated genes in breast cancer.
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Affiliation(s)
- Qin Jiang
- College of Computer Science and Electronic Engineering, Hunan University, Changsha, China
| | - Min Jin
- College of Computer Science and Electronic Engineering, Hunan University, Changsha, China
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21
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Wu Q, Yin G, Luo J, Zhang Y, Ai T, Tian J, Jin Y, Lei J, Liu S. Comprehensive Analysis of the Expression and Prognostic Value of SPINT1/2 in Breast Carcinoma. Front Endocrinol (Lausanne) 2021; 12:665666. [PMID: 34381422 PMCID: PMC8351597 DOI: 10.3389/fendo.2021.665666] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 05/26/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Hepatocyte growth factor (HGF) signaling plays a plethora of roles in tumorigenesis and progression in many cancer types. As HGF activator inhibitors, serine protease inhibitor, Kunitz types 1 and 2 (SPINT1 and SPINT2) have been reported to be differentially expressed in breast cancer, but their prognostic significance and functioning mechanism remain unclear. METHODS In our study, multiple databases and bioinformatics tools were used to investigate SPINT1/2 expression profiles, prognostic significance, genetic alteration, methylation, and regulatory network in breast carcinoma. RESULTS SPINT1/2 expression was upregulated in breast cancer, and was relatively higher in human epidermal growth factor receptor 2 (HER2) and node positive patients. Elevated SPINT1/2 expression was significantly correlated with a poorer prognosis. Genetic alterations and SPINT1/2 hypomethylation were observed. In breast carcinoma, SPINT1/2 were reciprocally correlated and shared common co-expressed genes. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that their common co-expressed genes were primarily involved in regulating cell attachment and migration. CONCLUSIONS Our study identified the expression profiles, prognostic significance and potential roles of SPINT1/2 in breast carcinoma. These study results showed that the SPINT1/2 were potential prognostic biomarker for patients with breast cancer.
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Affiliation(s)
- Qiulin Wu
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Guobing Yin
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jing Luo
- Department of Pathology, Chongqing Medical University, Chongqing, China
| | - Yingzi Zhang
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tiantian Ai
- Department of Cardiovascular Sciences, Chongqing Kangxin Hospital, Chongqing, China
| | - Jiao Tian
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yudi Jin
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jinwei Lei
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Shengchun Liu
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Shengchun Liu,
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Wang WJ, Li LY, Cui JW. Chromosome structural variation in tumorigenesis: mechanisms of formation and carcinogenesis. Epigenetics Chromatin 2020; 13:49. [PMID: 33168103 PMCID: PMC7654176 DOI: 10.1186/s13072-020-00371-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 10/29/2020] [Indexed: 12/23/2022] Open
Abstract
With the rapid development of next-generation sequencing technology, chromosome structural variation has gradually gained increased clinical significance in tumorigenesis. However, the molecular mechanism(s) underlying this structural variation remain poorly understood. A search of the literature shows that a three-dimensional chromatin state plays a vital role in inducing structural variation and in the gene expression profiles in tumorigenesis. Structural variants may result in changes in copy number or deletions of coding sequences, as well as the perturbation of structural chromatin features, especially topological domains, and disruption of interactions between genes and their regulatory elements. This review focuses recent work aiming at elucidating how structural variations develop and misregulate oncogenes and tumor suppressors, to provide general insights into tumor formation mechanisms and to provide potential targets for future anticancer therapies.
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Affiliation(s)
- Wen-Jun Wang
- Cancer Center, The First Hospital of Jilin University, Jilin University, Changchun, 130021 Jilin China
| | - Ling-Yu Li
- Cancer Center, The First Hospital of Jilin University, Jilin University, Changchun, 130021 Jilin China
| | - Jiu-Wei Cui
- Cancer Center, The First Hospital of Jilin University, Jilin University, Changchun, 130021 Jilin China
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23
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Li A, Mallik S, Luo H, Jia P, Lee DF, Zhao Z. H19, a Long Non-coding RNA, Mediates Transcription Factors and Target Genes through Interference of MicroRNAs in Pan-Cancer. MOLECULAR THERAPY. NUCLEIC ACIDS 2020; 21:180-191. [PMID: 32585626 PMCID: PMC7321791 DOI: 10.1016/j.omtn.2020.05.028] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 03/17/2020] [Accepted: 05/22/2020] [Indexed: 12/18/2022]
Abstract
Long non-coding RNAs (lncRNAs) have recently been found to be important in gene regulation. lncRNA H19 has been reported to play an oncogenic role in many human cancers. Its specific regulatory role is still elusive. In this study, we developed a novel analytic approach by integrating the synergistic regulation among lncRNAs (e.g., H19), transcription factors (TFs), target genes, and microRNAs (miRNAs) and then applied it to the pan-cancer expression datasets from The Cancer Genome Atlas (TCGA). Using linear regression models, we identified 88 H19-TF-gene co-regulatory triplets, in which 93% of the TF-gene pairs were related to cancer, indicating that our approach was effective to identify disease-related lncRNA-TF-gene co-regulation mechanisms. lncRNAs can function as miRNA sponges. Our further experiments found that H19 might regulate SP1-TGFBR2 through let-7b and miR-200b, ETS1-TGFBR2 through miR-29a and miR-200b, and STAT3-KLF11 through miR-17 in breast cancer cell lines. Our work suggests that miRNA-mediated lncRNA-TF-gene co-regulation is complicated yet important in cancer.
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Affiliation(s)
- Aimin Li
- Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, Shaanxi 710048, China; Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Saurav Mallik
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Haidan Luo
- Department of Integrative Biology and Pharmacology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Department of Pathophysiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Peilin Jia
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Dung-Fang Lee
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Department of Integrative Biology and Pharmacology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Center for Stem Cell and Regenerative Medicine, Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA.
| | - Zhongming Zhao
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA; Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
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Bi F, Chen Y, Yang Q. Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer. Cancer Cell Int 2020; 20:373. [PMID: 32774167 PMCID: PMC7405355 DOI: 10.1186/s12935-020-01472-9] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Accepted: 07/31/2020] [Indexed: 02/07/2023] Open
Abstract
Background Ovarian cancer (OC) is the most malignant tumor in the female reproductive system. About 75% of OC in complete remission of clinical symptoms still develop a recurrence. Therefore, searching for new treatment methods plays an important role in improving the prognosis of OC. Methods We downloaded the MAF files, RNA-seq data and clinical information from the TCGA database. The “maftools” package in R software was used to visualize the OC mutation data. We calculated the tumor mutation burden (TMB) of OC and analyzed its correlation with clinicopathological parameters and prognostic value. Tumor mutation burden related signature model was constructed to predict the overall survival (OS) of OC. Results The results revealed that there was a statistical correlation between TMB and FIGO stage, grade and tumor residual size of ovarian cancer patients. The Kaplan–Meier curve indicated that a high TMB is associated with better clinical outcomes of OC. The difference analysis indicated 24 upregulated genes and 619 downregulated genes in the high-TMB group compared with the low-TMB group. Besides, the TMBRS model based on five hub genes (RBMS3, PLA2G5, CDH2, AMHR2 and ADAMTS8) was constructed to predict the OS of OC. The ROC curve and validation data sets all revealed that the TMBRS model was reliable in predicting recurrence risk. Immune microenvironment analysis indicated the correlations between TMB and infiltrating immune cells. Conclusions Our results suggest that TMB plays an important role in the prognosis and guiding immunotherapy of OC. By detecting the TMB of OC, clinicians can more accurately treat patients with immunotherapy, thereby improving their survival rate.
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Affiliation(s)
- Fangfang Bi
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, NO. 36 Sanhao Road, Shenyang, 110000 China
| | - Ying Chen
- Department of Ultrasound, Jiangnan Hospital Affiliated to Zhejiang University of Traditional Chinese Medicine, Hangzhou, China
| | - Qing Yang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, NO. 36 Sanhao Road, Shenyang, 110000 China
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Multiple m 6A RNA methylation modulators promote the malignant progression of hepatocellular carcinoma and affect its clinical prognosis. BMC Cancer 2020; 20:165. [PMID: 32111180 PMCID: PMC7047390 DOI: 10.1186/s12885-020-6638-5] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 02/17/2020] [Indexed: 12/13/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death in the world. N6-methyladenosine (m6A) RNA methylation is dynamically regulated by m6A RNA methylation modulators (“writer,” “eraser,” and “reader” proteins), which are associated with cancer occurrence and development. The purpose of this study was to explore the relationships between m6A RNA methylation modulators and HCC. Methods First, using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, we compared the expression levels of 13 major m6A RNA methylation modulators between HCC and normal tissues. Second, we applied consensus clustering to the expression data on the m6A RNA methylation modulators to divide the HCC tissues into two subgroups (clusters 1 and 2), and we compared the clusters in terms of overall survival (OS), World Health Organization (WHO) stage, and pathological grade. Third, using least absolute shrinkage and selection operator (LASSO) regression, we constructed a risk signature involving the m6A RNA methylation modulators that affected OS in TCGA and ICGC analyses. Results We found that the expression levels of 12 major m6A RNA methylation modulators were significantly different between HCC and normal tissues. After dividing the HCC tissues into clusters 1 and 2, we found that cluster 2 had poorer OS, higher WHO stage, and higher pathological grade. Four m6A RNA methylation modulators (YTHDF1, YTHDF2, METTL3, and KIAA1429) affecting OS in the TCGA and ICGC analyses were selected to construct a risk signature, which was significantly associated with WHO stage and was also an independent prognostic marker of OS. Conclusions In summary, m6A RNA methylation modulators are key participants in the malignant progression of HCC and have potential value in prognostication and treatment decisions.
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Molecular characterization of surface antigen 10 of Eimeria tenella. Parasitol Res 2019; 118:2989-2999. [PMID: 31473858 DOI: 10.1007/s00436-019-06437-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 08/22/2019] [Indexed: 01/26/2023]
Abstract
Chicken coccidiosis is caused by the apicomplexan parasite Eimeria spp. At present, drug resistance of Eimeria is common because of the indiscriminate use of anticoccidial drugs. The gene encoding surface antigen 10 of Eimeria tenella (EtSAG10) is differentially expressed between drug-resistant and drug-sensitive strains. RNA-seq analysis indicated that this gene was downregulated in strains resistant to maduramicin and diclazuril compared to susceptible strains. EtSAG10 DNA sequence alignment revealed that they contained one and ten mutations in MRR and DZR, compared with DS, respectively. A full-length EtSAG10 cDNA was successfully cloned and expressed, and the polyclonal antibody was prepared. The transcription and translation levels of EtSAG10 were analyzed by quantitative real-time PCR (qPCR) and Western blotting. The localization of EtSAG10 in Spz, Mrz, and parasites in the first asexual stage was determined by indirect immunofluorescence. The potential association of EtSAG10 with sporozoite invasion of host cells was assessed by invasion inhibition assays. The results showed that EtSAG10 had a predicted transmembrane domain at the C-terminal end and a predicted signal peptide at the N-terminal end. EtSAG10 was downregulated in drug-resistant strains, which is consistent with the RNA-seq results. The EtSAG10 protein was localized to the parasite surface and parasitophorous vacuole membrane. This protein was shown to play a role in the infection of chicken intestine by sporozoites.
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Zhang Y, Liao G, Bai J, Zhang X, Xu L, Deng C, Yan M, Xie A, Luo T, Long Z, Xiao Y, Li X. Identifying Cancer Driver lncRNAs Bridged by Functional Effectors through Integrating Multi-omics Data in Human Cancers. MOLECULAR THERAPY. NUCLEIC ACIDS 2019; 17:362-373. [PMID: 31302496 PMCID: PMC6626872 DOI: 10.1016/j.omtn.2019.05.030] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 04/23/2019] [Accepted: 05/15/2019] [Indexed: 01/18/2023]
Abstract
The accumulation of somatic driver mutations in the human genome enables cells to gradually acquire a growth advantage and contributes to tumor development. Great efforts on protein-coding cancer drivers have yielded fruitful discoveries and clinical applications. However, investigations on cancer drivers in non-coding regions, especially long non-coding RNAs (lncRNAs), are extremely scarce due to the limitation of functional understanding. Thus, to identify driver lncRNAs integrating multi-omics data in human cancers, we proposed a computational framework, DriverLncNet, which dissected the functional impact of somatic copy number alteration (CNA) of lncRNAs on regulatory networks and captured key functional effectors in dys-regulatory networks. Applying it to 5 cancer types from The Cancer Genome Atlas (TCGA), we portrayed the landscape of 117 driver lncRNAs and revealed their associated cancer hallmarks through their functional effectors. Moreover, lncRNA RP11-571M6.8 was detected to be highly associated with immunotherapeutic targets (PD-1, PD-L1, and CTLA-4) and regulatory T cell infiltration level and their markers (IL2RA and FCGR2B) in glioblastoma multiforme, highlighting its immunosuppressive function. Meanwhile, a high expression of RP11-1020A11.1 in bladder carcinoma was predictive of poor survival independent of clinical characteristics, and CTD-2256P15.2 in lung adenocarcinoma responded to the sensitivity of methyl ethyl ketone (MEK) inhibitors. In summary, this study provided a framework to decipher the mechanisms of tumorigenesis from driver lncRNA level, established a new landscape of driver lncRNAs in human cancers, and offered potential clinical implications for precision oncology.
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Affiliation(s)
- Yong Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Gaoming Liao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Jing Bai
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Xinxin Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Liwen Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Chunyu Deng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Min Yan
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Aimin Xie
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Tao Luo
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Zhilin Long
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China
| | - Yun Xiao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China; Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang 150086, China.
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China; Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang 150086, China.
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Larmuseau M, Verbeke LPC, Marchal K. Associating expression and genomic data using co-occurrence measures. Biol Direct 2019; 14:10. [PMID: 31072345 PMCID: PMC6507230 DOI: 10.1186/s13062-019-0240-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 04/10/2019] [Indexed: 12/11/2022] Open
Abstract
Abstract Recent technological evolutions have led to an exponential increase in data in all the omics fields. It is expected that integration of these different data sources, will drastically enhance our knowledge of the biological mechanisms behind genomic diseases such as cancer. However, the integration of different omics data still remains a challenge. In this work we propose an intuitive workflow for the integrative analysis of expression, mutation and copy number data taken from the METABRIC study on breast cancer. First, we present evidence that the expression profile of many important breast cancer genes consists of two modes or ‘regimes’, which contain important clinical information. Then, we show how the co-occurrence of these expression regimes can be used as an association measure between genes and validate our findings on the TCGA-BRCA study. Finally, we demonstrate how these co-occurrence measures can also be applied to link expression regimes to genomic aberrations, providing a more complete, integrative view on breast cancer. As a case study, an integrative analysis of the identified MLPH-FOXA1 association is performed, illustrating that the obtained expression associations are intimately linked to the underlying genomic changes. Reviewers This article was reviewed by Dirk Walther, Francisco Garcia and Isabel Nepomuceno. Electronic supplementary material The online version of this article (10.1186/s13062-019-0240-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Maarten Larmuseau
- Department of Information Technology, Ghent University - Imec, Technologiepark-Zwijnaarde 126, 9052, Ghent, Belgium
| | - Lieven P C Verbeke
- Department of Plant Biotechnology and Bioinformatics, Ghent University - Imec, Technologiepark-Zwijnaarde 126, 9052, Ghent, Belgium
| | - Kathleen Marchal
- Department of Plant Biotechnology and Bioinformatics, Ghent University - Imec, Technologiepark-Zwijnaarde 126, 9052, Ghent, Belgium.
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Mamidi TKK, Wu J, Hicks C. Integrating germline and somatic variation information using genomic data for the discovery of biomarkers in prostate cancer. BMC Cancer 2019; 19:229. [PMID: 30871495 PMCID: PMC6417124 DOI: 10.1186/s12885-019-5440-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Accepted: 03/06/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the United States. High-throughput genotyping has enabled discovery of germline genetic susceptibility variants (herein referred to as germline mutations) associated with an increased risk of developing PCa. However, germline mutation information has not been leveraged and integrated with information on acquired somatic mutations to link genetic susceptibility to tumorigenesis. The objective of this exploratory study was to address this knowledge gap. METHODS Germline mutations and associated gene information were derived from genome-wide association studies (GWAS) reports. Somatic mutation and gene expression data were derived from 495 tumors and 52 normal control samples obtained from The Cancer Genome Atlas (TCGA). We integrated germline and somatic mutation information using gene expression data. We performed enrichment analysis to discover molecular networks and biological pathways enriched for germline and somatic mutations. RESULTS We discovered a signature of 124 genes containing both germline and somatic mutations. Enrichment analysis revealed molecular networks and biological pathways enriched for germline and somatic mutations, including, the PDGF, P53, MYC, IGF-1, PTEN and Androgen receptor signaling pathways. CONCLUSION Integrative genomic analysis links genetic susceptibility to tumorigenesis in PCa and establishes putative functional bridges between the germline and somatic variation, and the biological pathways they control.
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Affiliation(s)
- Tarun Karthik Kumar Mamidi
- Department of Genetics and the Bioinformatics and Genomics Program, Louisiana State University Health Sciences Center, School of Medicine, 533 Bolivar, New Orleans, LA, 70112, USA
| | - Jiande Wu
- Department of Genetics and the Bioinformatics and Genomics Program, Louisiana State University Health Sciences Center, School of Medicine, 533 Bolivar, New Orleans, LA, 70112, USA
| | - Chindo Hicks
- Department of Genetics and the Bioinformatics and Genomics Program, Louisiana State University Health Sciences Center, School of Medicine, 533 Bolivar, New Orleans, LA, 70112, USA.
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Liu B, Hu FF, Zhang Q, Hu H, Ye Z, Tang Q, Guo AY. Genomic landscape and mutational impacts of recurrently mutated genes in cancers. Mol Genet Genomic Med 2018; 6:910-923. [PMID: 30107644 PMCID: PMC6305651 DOI: 10.1002/mgg3.458] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 05/29/2018] [Accepted: 07/13/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cancer genes tend to be highly mutated under positive selection. Better understanding the recurrently mutated genes (RMGs) in cancer is critical for explicating the mechanisms of tumorigenesis and providing vital clues for therapy. Although some studies have investigated functional impacts of RMGs in specific cancer types, a comprehensive analysis of RMGs and their mutational impacts across cancers is still needed. METHODS We obtained data from The Cancer Genome Atlas (TCGA) and calculated mutation rate of each gene in 31 cancer types. Functional analysis was performed to identify the important signaling pathways and enriched protein types of RMGs. In order to evaluate functional impacts of RMGs, differential expression, survival, and pairwise mutation patterns analyses were performed. RESULTS Totally, we identified 897 RMGs and 624 of them were specifically mutant in only a single cancer type. Functional analysis demonstrated that these RMGs were enriched in hydrolases, cytoskeletal protein, and pathways like MAPK, cell cycle, PI3K-Akt, ECM receptor interaction, and energy metabolism. The differentially expressed genes potentially affected by the same common RMG showed a relatively low overlap across different cancer types. For the 19 Mucin (MUC) family genes, nine of them were RMGs and four of them (MUC17, MUC5B, MUC4, and MUC16) were common RMGs shared in 8 to 17 cancer types. The results showed that recurrent mutations in MUC genes were significantly associated with better survival prognosis. Only a small part of RMGs was differentially expressed due to their own mutations and most of them were downregulated. In addition, pairwise mutation pattern analysis revealed the high frequency of co-occurred mutations among RMGs in STAD. CONCLUSION Through the functional analysis of RMGs, we found that six signaling pathways were disrupted in most cancer types and that energy metabolism was abnormal in tumors. The results also revealed a strong correlation between recurrently mutated genes from MUC family and human survival. In addition, gene expression and survival prognosis were associated with different mutation types of RMGs.
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Affiliation(s)
- Baolin Liu
- Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Fei-Fei Hu
- Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Qiong Zhang
- Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Hu
- Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Zheng Ye
- Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.,Department of Biochemistry and Molecular Biology, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin, China
| | - Qin Tang
- Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - An-Yuan Guo
- Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
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Identification of cancer genes that are independent of dominant proliferation and lineage programs. Proc Natl Acad Sci U S A 2017; 114:E11276-E11284. [PMID: 29229826 PMCID: PMC5748209 DOI: 10.1073/pnas.1714877115] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Large, multidimensional “landscaping” projects have provided datasets that can be mined to identify potential targets for subgroups of tumors. Here, we analyzed genomic and transcriptomic data from human breast tumors to identify genes whose expression is enriched in tumors harboring specific genetic alterations. However, this analysis revealed that two other factors, proliferation rate and tumor lineage, are more dominant factors in shaping tumor transcriptional programs than genetic alterations. This discovery shifted our attention to identifying genes that are independent of the dominant proliferation and lineage programs. A small subset of these genes represents candidate targets for combination cancer therapies because they are druggable, maintained after treatment with chemotherapy, essential for cell line survival, and elevated in drug-resistant stem-like cancer cells. Large, multidimensional cancer datasets provide a resource that can be mined to identify candidate therapeutic targets for specific subgroups of tumors. Here, we analyzed human breast cancer data to identify transcriptional programs associated with tumors bearing specific genetic driver alterations. Using an unbiased approach, we identified thousands of genes whose expression was enriched in tumors with specific genetic alterations. However, expression of the vast majority of these genes was not enriched if associations were analyzed within individual breast tumor molecular subtypes, across multiple tumor types, or after gene expression was normalized to account for differences in proliferation or tumor lineage. Together with linear modeling results, these findings suggest that most transcriptional programs associated with specific genetic alterations in oncogenes and tumor suppressors are highly context-dependent and are predominantly linked to differences in proliferation programs between distinct breast cancer subtypes. We demonstrate that such proliferation-dependent gene expression dominates tumor transcriptional programs relative to matched normal tissues. However, we also identified a relatively small group of cancer-associated genes that are both proliferation- and lineage-independent. A subset of these genes are attractive candidate targets for combination therapy because they are essential in breast cancer cell lines, druggable, enriched in stem-like breast cancer cells, and resistant to chemotherapy-induced down-regulation.
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Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening. BMC Genomics 2017; 18:678. [PMID: 28984208 PMCID: PMC5629613 DOI: 10.1186/s12864-017-4026-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Background In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC’s prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA). Results With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data. Conclusions Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients’ survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These biomarkers shared a significant overlap, indicating that they were technically replicable. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4026-6) contains supplementary material, which is available to authorized users.
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Allelic imbalance of somatic mutations in cancer genomes and transcriptomes. Sci Rep 2017; 7:1653. [PMID: 28490743 PMCID: PMC5431982 DOI: 10.1038/s41598-017-01966-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 04/06/2017] [Indexed: 02/06/2023] Open
Abstract
Somatic mutations in cancer genomes often show allelic imbalance (AI) of mutation abundance between the genome and transcriptome, but there is not yet a systematic understanding of AI. In this study, we performed large-scale DNA and RNA AI analyses of >100,000 somatic mutations in >2,000 cancer specimens across five tumor types using the exome and transcriptome sequencing data of the Cancer Genome Atlas consortium. First, AI analysis of nonsense mutations and frameshift indels revealed that nonsense-mediated decay is typical in cancer genomes, and we identified the relationship between the extent of AI and the location of mutations in addition to the well-recognized 50-nt rules. Second, the AI with splice site mutations may reflect the extent of intron retention and is frequently observed in known tumor suppressor genes. For missense mutations, we observed that mutations frequently subject to AI are enriched to genes related to cancer, especially those of apoptosis and the extracellular matrix, and C:G > A:T transversions. Our results suggest that mutations in known cancer-related genes and their transcripts are subjected to different levels of transcriptional or posttranscriptional regulation compared to wildtype alleles and may add an additional regulatory layer to the functions of cancer-relevant genes.
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Park Y, Lim S, Nam JW, Kim S. Measuring intratumor heterogeneity by network entropy using RNA-seq data. Sci Rep 2016; 6:37767. [PMID: 27883053 PMCID: PMC5121893 DOI: 10.1038/srep37767] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Accepted: 10/31/2016] [Indexed: 12/27/2022] Open
Abstract
Intratumor heterogeneity (ITH) is observed at different stages of tumor progression, metastasis and reouccurence, which can be important for clinical applications. We used RNA-sequencing data from tumor samples, and measured the level of ITH in terms of biological network states. To model complex relationships among genes, we used a protein interaction network to consider gene-gene dependency. ITH was measured by using an entropy-based distance metric between two networks, nJSD, with Jensen-Shannon Divergence (JSD). With nJSD, we defined transcriptome-based ITH (tITH). The effectiveness of tITH was extensively tested for the issues related with ITH using real biological data sets. Human cancer cell line data and single-cell sequencing data were investigated to verify our approach. Then, we analyzed TCGA pan-cancer 6,320 patients. Our result was in agreement with widely used genome-based ITH inference methods, while showed better performance at survival analysis. Analysis of mouse clonal evolution data further confirmed that our transcriptome-based ITH was consistent with genetic heterogeneity at different clonal evolution stages. Additionally, we found that cell cycle related pathways have significant contribution to increasing heterogeneity on the network during clonal evolution. We believe that the proposed transcriptome-based ITH is useful to characterize heterogeneity of a tumor sample at RNA level.
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Affiliation(s)
- Youngjune Park
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 151-742, Korea
| | - Sangsoo Lim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 151-742, Korea
| | - Jin-Wu Nam
- Department of Life Science, College of Natural Sciences, Hanyang University, Seoul, 133-791, Korea
- Research Institute for Natural Sciences, Hanyang University, Seoul, 133-791, Korea
| | - Sun Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 151-742, Korea
- Department of Computer Science and Engineering, Seoul National University, Seoul, 151-742, Korea
- Bioinformatics Institute, Seoul National University, Seoul, 151-742, Korea
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