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Jain R, Xu W. Artificial Intelligence based wrapper for high dimensional feature selection. BMC Bioinformatics 2023; 24:392. [PMID: 37853338 PMCID: PMC10585895 DOI: 10.1186/s12859-023-05502-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: 09/29/2022] [Accepted: 09/27/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Feature selection is important in high dimensional data analysis. The wrapper approach is one of the ways to perform feature selection, but it is computationally intensive as it builds and evaluates models of multiple subsets of features. The existing wrapper algorithm primarily focuses on shortening the path to find an optimal feature set. However, it underutilizes the capability of feature subset models, which impacts feature selection and its predictive performance. METHOD AND RESULTS This study proposes a novel Artificial Intelligence based Wrapper (AIWrap) algorithm that integrates Artificial Intelligence (AI) with the existing wrapper algorithm. The algorithm develops a Performance Prediction Model using AI which predicts the model performance of any feature set and allows the wrapper algorithm to evaluate the feature subset performance in a model without building the model. The algorithm can make the wrapper algorithm more relevant for high-dimensional data. We evaluate the performance of this algorithm using simulated studies and real research studies. AIWrap shows better or at par feature selection and model prediction performance than standard penalized feature selection algorithms and wrapper algorithms. CONCLUSION AIWrap approach provides an alternative algorithm to the existing algorithms for feature selection. The current study focuses on AIWrap application in continuous cross-sectional data. However, it could be applied to other datasets like longitudinal, categorical and time-to-event biological data.
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Affiliation(s)
- Rahi Jain
- Biostatistics Department, Princess Margaret Cancer Research Centre, Toronto, ON, Canada
| | - Wei Xu
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
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Hayat S, Ishrat R. Exploring potential genes and pathways related to lung cancer: a graph theoretical analysis. Bioinformation 2023; 19:954-963. [PMID: 37928493 PMCID: PMC10625372 DOI: 10.6026/97320630019954] [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: 09/01/2023] [Revised: 09/30/2023] [Accepted: 09/30/2023] [Indexed: 11/07/2023] Open
Abstract
Lung cancer is the primary and third most frequently detected form of cancer in both males and females. The present study tries to perform integrated analysis in male as well as female patients inclusively both smoker and non-smokers. This study aims to identify diagnostic biomarkers and therapeutic targets for lung cancer patients using human microarray profile datasets. Differentially expressed genes (DEGs) were identified using a PPI network from the String database, and major modules or clusters were extracted using MCODE. The Cytohubba plug-in was used to find hub genes from the PPI network using centralities approaches. Twenty significant hub genes (CCND1, CDK1, CCNB1, CDH1, TP53, CTNNB1, EGFR, ESR1, CDK2, CCNA2, RHOA, EGF, FN1, HSP90AA1, STAT3, JUN, NOTCH1, IL6, SRC, and CD44) were identified as promising diagnostic biomarkers and therapeutic targets for lung cancer treatment. Survival analysis and hub gene validation were also conducted. GO enrichment and pathway analysis were conducted to identify their important functions. These hub genes were also used to identify targeted drugs. The findings suggest that the identified genes have the potential to be used as diagnostic biomarkers and therapeutic targets for lung cancer treatment.
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Affiliation(s)
- Shaheen Hayat
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025
| | - Romana Ishrat
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025
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Kadeerhan G, Xue B, Wu X, Hu X, Tian J, Wang D. Novel gene signature for predicting biochemical recurrence-free survival of prostate cancer and PRAME modulates prostate cancer progression. Am J Cancer Res 2023; 13:2861-2877. [PMID: 37559989 PMCID: PMC10408486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 06/02/2023] [Indexed: 08/11/2023] Open
Abstract
Biochemical recurrence (BCR) is considered as an early sign of prostate cancer (PCa) progression after initial treatment, such as radical prostatectomy and radiotherapy; hence, it is important to stratify patients at risk of BCR. In this study, we established a robust 8-gene signature (APOF, Clorf64, RPE65, SEMG1, ARHGDIG, COMP, MKI67 and PRAME) based on the PCa transcriptome profiles in the Cancer Genome Atlas (TCGA) for predicting BCR-free survival of PCa, which was further validated in the MSK-IMPACT Clinical Sequencing Cohort (MSKCC) PCa cohort. Moreover, we found that one risk-related gene (PRAME) was upregulated in tumor samples, particularly in high-risk group was well as in patients metastatic tumor and was correlated with chemotherapeutic drug response. In vitro experiments showed that knocking down PRAME reduced the proliferation, migration, and invasion of PCa cells. Therefore, our study established a new 8-gene signature that could accurately predict the BCR risk of PCa. Inhibition of PRAME attenuated the proliferation, invasion, and migration of PCa cells. These findings provide a novel tool for stratifying high-risk PCa patient and shed light on the mechanism of PCa progression.
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Affiliation(s)
- Gaohaer Kadeerhan
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
| | - Bo Xue
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
- Shanxi Medical UniversityShanxi 030012, China
| | - Xiaolin Wu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
| | - Xiaofeng Hu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
- Shanxi Medical UniversityShanxi 030012, China
| | - Jun Tian
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
| | - Dongwen Wang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
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Li Z, Fei H, Lei S, Hao F, Yang L, Li W, Zhang L, Fei R. Identification of HMMR as a prognostic biomarker for patients with lung adenocarcinoma via integrated bioinformatics analysis. PeerJ 2022; 9:e12624. [PMID: 35036134 PMCID: PMC8710063 DOI: 10.7717/peerj.12624] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 11/19/2021] [Indexed: 12/11/2022] Open
Abstract
Background Lung adenocarcinoma (LUAD) is the most prevalent tumor in lung carcinoma cases and threatens human life seriously worldwide. Here we attempt to identify a prognostic biomarker and potential therapeutic target for LUAD patients. Methods Differentially expressed genes (DEGs) shared by GSE18842, GSE75037, GSE101929 and GSE19188 profiles were determined and used for protein-protein interaction analysis, enrichment analysis and clinical correlation analysis to search for the core gene, whose expression was further validated in multiple databases and LUAD cells (A549 and PC-9) by quantitative real-time PCR (qRT-PCR) and western blot analyses. Its prognostic value was estimated using the Kaplan-Meier method, meta-analysis and Cox regression analysis based on the Cancer Genome Atlas (TCGA) dataset and co-expression analysis was conducted using the Oncomine database. Gene Set Enrichment Analysis (GSEA) was performed to illuminate the potential functions of the core gene. Results A total of 115 shared DEGs were found, of which 24 DEGs were identified as candidate hub genes with potential functions associated with cell cycle and FOXM1 transcription factor network. Among these candidates, HMMR was identified as the core gene, which was highly expressed in LUAD as verified by multiple datasets and cell samples. Besides, high HMMR expression was found to independently predict poor survival in patients with LUAD. Co-expression analysis showed that HMMR was closely related to FOXM1 and was mainly involved in cell cycle as suggested by GSEA. Conclusion HMMR might be served as an independent prognostic biomarker for LUAD patients, which needs further validation in subsequent studies.
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Affiliation(s)
- Zhaodong Li
- Department of Cell Biology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - Hongtian Fei
- Department of Pharmacology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - Siyu Lei
- Department of Cell Biology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - Fengtong Hao
- Department of Cell Biology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - Lijie Yang
- Department of Cell Biology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - Wanze Li
- Department of Cell Biology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - Laney Zhang
- The College of Arts and Sciences, Cornell University, New York, USA
| | - Rui Fei
- Department of Cell Biology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China.,Key Laboratory of Lymphatic Surgery Jilin Province, Jilin University, Changchun, Jilin, China
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Zhu K, Xu A, Xia W, Li P, Han R, Wang E, Zhou S, Wang R. Integrated analysis of the molecular mechanisms in idiopathic pulmonary fibrosis. Int J Med Sci 2021; 18:3412-3424. [PMID: 34522168 PMCID: PMC8436110 DOI: 10.7150/ijms.61309] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/30/2021] [Indexed: 12/29/2022] Open
Abstract
Rationale: Idiopathic pulmonary fibrosis (IPF) is one of the most aggressive forms of idiopathic interstitial pneumonia. Some miRNAs may be associated with IPF and may affect the occurrence and development of IPF in various pathways. Many miRNAs and genes that may be involved in the development of IPF have been discovered using chip and high throughput technologies. Methods: We analyzed one miRNA and four mRNA databases. We identified hub genes and pathways related to IPF using GO, KEGG enrichment analysis, gene set variation analysis (GSVA), PPI network construction, and hub gene analysis. A comprehensive analysis of differentially expressed miRNAs (DEMs), predicted miRNA target genes, and differentially expressed genes (DEGs) led to the creation of a miRNA-mRNA regulatory network in IPF. Results: We found 203 DEGs and 165 DEMs that were associated with IPF. The findings of enrichment analyses showed that these DEGs were mainly involved in antimicrobial humoral response, antimicrobial humoral immune response mediated by antimicrobial peptide, extracellular matrix organization, cell killing, and organ or tissue specific immune response. The VEGFA, CDH5, and WNT3A genes overlapped between hub genes and the miRNA-mRNA regulatory network. The miRNAs including miR-199b-5p, miR-140-5p, miR-199a-5p, miR-125A-5p, and miR-107 that we predicted would regulate the VEGFA, CDH5, and WNT3A genes, which were also associated with IPF or other fibrosis-related diseases. GSVA indicated that metabolic processes of UTP and IMP, immune response, regulation of Th2 cell cytokine production, and positive regulation of NK cell-mediated immunity are associated with the pathogenesis and treatment of IPF. These pathways also interact with VEGFA, CDH5, and WNT3A. Conclusion: These findings provide a new research direction for the diagnosis and treatment of IPF.
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Affiliation(s)
- Ke Zhu
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Aiqun Xu
- Department of General Medicine, Hefei Second People's Hospital, Hefei 230001, China
| | - Wanli Xia
- Department of Thoracic Surgery, the first affiliated hospital of Anhui medical university, Hefei 230022, China
| | - Pulin Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Rui Han
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Enze Wang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Sijing Zhou
- Hefei Third Clinical College of Anhui Medical University, Hefei 230022, China.,Hefei Prevention and Treatment Center for Occupational Diseases, Hefei 230022, China
| | - Ran Wang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
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Zhou Z, Gu G, Luo Y, Li W, Li B, Zhao Y, Liu J, Shuai X, Wu L, Chen J, Fan C, Huang Q, Han B, Wen J, Jiao H. Immunological pathways of macrophage response to Brucella ovis infection. Innate Immun 2020; 26:635-648. [PMID: 32970502 PMCID: PMC7556187 DOI: 10.1177/1753425920958179] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
As the molecular mechanisms of Brucella ovis pathogenicity are not completely clear, we have applied a transcriptome approach to identify the differentially expressed genes (DEGs) in RAW264.7 macrophage infected with B. ovis. The DEGs related to immune pathway were identified by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional enrichment analysis. Quantitative real-time PCR (qRT-PCR) was performed to validate the transcriptome sequencing data. In total, we identified 337 up-regulated and 264 down-regulated DEGs in B. ovis-infected group versus mock group. Top 20 pathways were enriched by KEGG analysis and 20 GO by functional enrichment analysis in DEGs involved in the molecular function, cellular component, and biological process and so on, which revealed multiple immunological pathways in RAW264.7 macrophage cells in response to B. ovis infection, including inflammatory response, immune system process, immune response, cytokine activity, chemotaxis, chemokine-mediated signaling pathway, chemokine activity, and CCR chemokine receptor binding. qRT-PCR results showed Ccl2 (ENSMUST00000000193), Ccl2 (ENSMUST00000124479), Ccl3 (ENSMUST00000001008), Hmox1 (ENSMUST00000005548), Hmox1 (ENSMUST00000159631), Cxcl2 (ENSMUST00000075433), Cxcl2 (ENSMUST00000200681), Cxcl2 (ENSMUST00000200919), and Cxcl2 (ENSMUST00000202317). Our findings firstly elucidate the pathways involved in B. ovis-induced host immune response, which may lay the foundation for revealing the bacteria–host interaction and demonstrating the pathogenic mechanism of B. ovis.
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Affiliation(s)
- Zhixiong Zhou
- College of Veterinary Medicine, Southwest University, Chongqing, China
| | - Guojing Gu
- College of Veterinary Medicine, Southwest University, Chongqing, China
| | - Yichen Luo
- Immunology Research Center, Medical Research Institute, Southwest University, Chongqing, China.,College of Veterinary Medicine, Southwest University, Chongqing, China.,Veterinary Scientific Engineering Research Center, Chongqing, China
| | - Wenjie Li
- College of Veterinary Medicine, Southwest University, Chongqing, China
| | - Bowen Li
- College of Veterinary Medicine, Southwest University, Chongqing, China
| | - Yu Zhao
- College of Veterinary Medicine, Southwest University, Chongqing, China
| | - Juan Liu
- Immunology Research Center, Medical Research Institute, Southwest University, Chongqing, China.,College of Veterinary Medicine, Southwest University, Chongqing, China.,Veterinary Scientific Engineering Research Center, Chongqing, China
| | - Xuehong Shuai
- Immunology Research Center, Medical Research Institute, Southwest University, Chongqing, China.,College of Veterinary Medicine, Southwest University, Chongqing, China.,Veterinary Scientific Engineering Research Center, Chongqing, China
| | - Li Wu
- College of Veterinary Medicine, Southwest University, Chongqing, China.,Veterinary Scientific Engineering Research Center, Chongqing, China
| | - Jixuan Chen
- College of Veterinary Medicine, Southwest University, Chongqing, China.,Veterinary Scientific Engineering Research Center, Chongqing, China
| | - Cailiang Fan
- College of Veterinary Medicine, Southwest University, Chongqing, China.,Animal Disease Prevention and Control Center of Rongchang, Chongqing, China
| | - Qingzhou Huang
- College of Veterinary Medicine, Southwest University, Chongqing, China.,Veterinary Scientific Engineering Research Center, Chongqing, China
| | - Baoru Han
- College of Medical Informatics, Chongqing Medical University, Chongqing, China
| | - Jianjun Wen
- Department of Microbiology and Immunology, University of Texas Medical Branch at Galveston, Galveston, USA
| | - Hanwei Jiao
- Immunology Research Center, Medical Research Institute, Southwest University, Chongqing, China.,College of Veterinary Medicine, Southwest University, Chongqing, China.,Veterinary Scientific Engineering Research Center, Chongqing, China
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Identification of Candidate Genes Associated with Charcot-Marie-Tooth Disease by Network and Pathway Analysis. BIOMED RESEARCH INTERNATIONAL 2020; 2020:1353516. [PMID: 33029488 PMCID: PMC7532371 DOI: 10.1155/2020/1353516] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 07/21/2020] [Accepted: 08/12/2020] [Indexed: 12/15/2022]
Abstract
Charcot-Marie-Tooth Disease (CMT) is the most common clinical genetic disease of the peripheral nervous system. Although many studies have focused on elucidating the pathogenesis of CMT, few focuses on achieving a systematic analysis of biology to decode the underlying pathological molecular mechanisms and the mechanism of its disease remains to be elucidated. So our study may provide further useful insights into the molecular mechanisms of CMT based on a systematic bioinformatics analysis. In the current study, by reviewing the literatures deposited in PUBMED, we identified 100 genes genetically related to CMT. Then, the functional features of the CMT-related genes were examined by R software and KOBAS, and the selected biological process crosstalk was visualized with the software Cytoscape. Moreover, CMT specific molecular network analysis was conducted by the Molecular Complex Detection (MCODE) Algorithm. The biological function enrichment analysis suggested that myelin sheath, axon, peripheral nervous system, mitochondrial function, various metabolic processes, and autophagy played important roles in CMT development. Aminoacyl-tRNA biosynthesis, metabolic pathways, and vasopressin-regulated water reabsorption were significantly enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway network, suggesting that these pathways may play key roles in CMT occurrence and development. According to the crosstalk, the biological processes could be roughly divided into a correlative module and two separate modules. MCODE clusters showed that in top 3 clusters, 13 of CMT-related genes were included in the network and 30 candidate genes were discovered which might be potentially related to CMT. The study may help to update the new understanding of the pathogenesis of CMT and expand the potential genes of CMT for further exploration.
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Characterisation of the Expression of Neurotensin and Its Receptors in Human Colorectal Cancer and Its Clinical Implications. Biomolecules 2020; 10:biom10081145. [PMID: 32764278 PMCID: PMC7464404 DOI: 10.3390/biom10081145] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 07/29/2020] [Accepted: 08/02/2020] [Indexed: 01/22/2023] Open
Abstract
Introduction: Colorectal Cancer (CRC) accounts for 9% of cancer deaths globally. Hormonal pathways play important roles in some cancers. This study investigated the association of CRC expression of neurotensin (NTS), NTS receptors 1 and 3 (NTSR1 and NTSR3) and clinical outcomes. Methods: A prospective cohort study which quantifies the protein expression of NTS, NTSR1 and NTSR3 in human CRCs using immunohistochemistry. Expression levels were then compared with clinico-pathological outcome including histological grade, overall survival (OS) and disease-free survival (DFS). Results: Sixty-four patients were enrolled with median follow-up of 44.0 months. There was significantly higher expression of NTS in cancer tissue in CRC with higher T stages (p < 0.01), N stages (p = 0.03), and AJCC clinical stages (p = 0.04). There was significantly higher expression of NTS, NTSR1 and NTSR3 in cancer tissue compared to surrounding normal epithelium (median H-score 163.5 vs 97.3, p < 0.01). There was significantly shorter DFS in individuals with CRC with high levels of NTS compared to lower levels of NTS (35.8 months 95% CI 28.7–42.8 months vs 46.4 months 95% CI 42.2–50.5 months, respectively, p = 0.02). Above median NTS expression in cancer tissue was a significant risk factor for disease recurrence (HR 4.10, 95% CI 1.14–14.7, p = 0.03). Discussion: The expression of NTS and its receptors has the potential to be utilised as a predictive and prognostic marker in colorectal cancer for postoperative selection for adjuvant therapy and identify individuals for novel therapies targeting the neurotensinergic pathways. Conclusions: High NTS expression appears to be associated with more advanced CRC and worse DFS.
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