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Shah AA, Daud A, Bukhari A, Alshemaimri B, Ahsan M, Younis R. DEL-Thyroid: deep ensemble learning framework for detection of thyroid cancer progression through genomic mutation. BMC Med Inform Decis Mak 2024; 24:198. [PMID: 39039464 DOI: 10.1186/s12911-024-02604-1] [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: 03/26/2024] [Accepted: 07/10/2024] [Indexed: 07/24/2024] Open
Abstract
Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which can lead to cancer. Machine learning and deep learning methods have emerged as vital tools in identifying mutations associated with cancer. Thyroid cancer ranks as the 5th most prevalent cancer in the USA, with thousands diagnosed annually. This paper presents an ensemble learning model leveraging deep learning techniques such as Long Short-Term Memory (LSTM), Gated Recurrent Units (GRUs), and Bi-directional LSTM (Bi-LSTM) to detect thyroid cancer mutations early. The model is trained on a dataset sourced from asia.ensembl.org and IntOGen.org, consisting of 633 samples with 969 mutations across 41 genes, collected from individuals of various demographics. Feature extraction encompasses techniques including Hahn moments, central moments, raw moments, and various matrix-based methods. Evaluation employs three testing methods: self-consistency test (SCT), independent set test (IST), and 10-fold cross-validation test (10-FCVT). The proposed ensemble learning model demonstrates promising performance, achieving 96% accuracy in the independent set test (IST). Statistical measures such as training accuracy, testing accuracy, recall, sensitivity, specificity, Mathew's Correlation Coefficient (MCC), loss, training accuracy, F1 Score, and Cohen's kappa are utilized for comprehensive evaluation.
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Affiliation(s)
- Asghar Ali Shah
- Center of Excellence in Artificial Intelligence (CoE-AI), Department of Computer Science, Bahria University, Islamabad, 04408, Pakistan
| | - Ali Daud
- Faculty of Resilience, Rabdan Academy, Abu Dhabi, United Arab Emirates.
| | - Amal Bukhari
- Department of Information Systems and Technology, Collage of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia
| | - Bader Alshemaimri
- Software Engineering Department, College of Computing and Information Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Muhammad Ahsan
- Department of Computer Science, University of Alabama at Birmingham, 1402 10th Avenue S, Birmingham, AL, 35294, USA
| | - Rehmana Younis
- College of Letters and Sciences, Graduate Student of Robotics Engineering, Columbus State University, Columbus, USA
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Sun W, Jiang C, Liu Q, Wang N, Huang R, Jiang G, Yang Y. Exosomal noncoding RNAs: decoding their role in thyroid cancer progression. Front Endocrinol (Lausanne) 2024; 15:1337226. [PMID: 38933820 PMCID: PMC11199389 DOI: 10.3389/fendo.2024.1337226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 05/31/2024] [Indexed: 06/28/2024] Open
Abstract
Exosomes, as pivotal entities within the tumor microenvironment, orchestrate intercellular communication through the transfer of diverse molecules, among which non-coding RNAs (ncRNAs) such as miRNAs, lncRNAs, and circRNAs play a crucial role. These ncRNAs, endowed with regulatory functions, are selectively incorporated into exosomes. Emerging evidence underscores the significance of exosomal ncRNAs in modulating key oncogenic processes in thyroid cancer (TC), including proliferation, metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and immunoediting. The unique composition of exosomes shields their cargo from enzymatic and chemical degradation, ensuring their integrity and facilitating their specific expression in plasma. This positions exosomal ncRNAs as promising candidates for novel diagnostic and prognostic biomarkers in TC. Moreover, the potential of exosomes in the therapeutic landscape of TC is increasingly recognized. This review aims to elucidate the intricate relationship between exosomal ncRNAs and TC, fostering a deeper comprehension of their mechanistic involvement. By doing so, it endeavors to propel forward the exploration of exosomal ncRNAs in TC, ultimately paving the way for innovative diagnostic and therapeutic strategies predicated on exosomes and their ncRNA content.
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Affiliation(s)
- Weiming Sun
- The First Hospital of Lanzhou University, Endocrinology Department, Lanzhou, China
| | - Chenjun Jiang
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Qianqian Liu
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Na Wang
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Runchun Huang
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Gengchen Jiang
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Yuxuan Yang
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
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Agarwal S, Gupta S, Raj R. Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis. Endocrine 2024:10.1007/s12020-024-03836-x. [PMID: 38676768 DOI: 10.1007/s12020-024-03836-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 04/14/2024] [Indexed: 04/29/2024]
Abstract
PURPOSE To perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC). METHODS Thirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation. RESULTS There were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data. CONCLUSIONS The findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas.
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Affiliation(s)
- Shipra Agarwal
- Department of Pathology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
| | - Shikha Gupta
- Department of Computer Science, S.S. College of Business Studies, University of Delhi, New Delhi, India.
| | - Rishav Raj
- Department of Computer Science, S.S. College of Business Studies, University of Delhi, New Delhi, India
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Liu Y, Wei C, Wang S, Ding S, Li Y, Li Y, Zhang D, Zhu G, Meng Z. Role of prognostic gene DKK1 in oral squamous cell carcinoma. Oncol Lett 2024; 27:52. [PMID: 38268623 PMCID: PMC10806357 DOI: 10.3892/ol.2023.14184] [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: 12/13/2022] [Accepted: 10/25/2023] [Indexed: 01/26/2024] Open
Abstract
Oral squamous cell carcinoma (OSCC) is one of the most common squamous cell carcinomas of the head and neck. The morbidity and mortality rates of OSCC have increased in recent years. However, the pathogenesis of this disease remains unknown. The present study aimed to identify predictive biomarkers and therapeutic targets for OSCC. Bioinformatics screening of differentially expressed genes in OSCC was performed based on data from The Cancer Genome Atlas and Gene Expression Omnibus databases. Dickkopf Wnt signaling pathway inhibitor 1 (DKK1) was identified to be associated with survival, tumor immunity and DNA repair in OSCC. Furthermore, the effects of DKK1 were evaluated by the knockdown of DKK1 in two OSCC cell lines. The proliferation, clonogenicity, migration and invasion of the cells were assessed in vitro using Cell Counting Kit-8, colony formation, wound healing and Transwell assays, respectively, and were found to be inhibited by DKK1 knockdown. The present study suggests that DKK1 may be used in the prognosis of patients with OSCC and that targeting DKK1 is a potential strategy for OSCC therapy.
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Affiliation(s)
- Yujiao Liu
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Shandong University and Shandong Provincial Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong 250000, P.R. China
- Department of Stomatology & Precision Biomedical Laboratory, Liaocheng People's Hospital, Liaocheng University, Liaocheng, Shandong 252000, P.R. China
| | - Congcong Wei
- Department of Stomatology & Precision Biomedical Laboratory, Liaocheng People's Hospital, Liaocheng University, Liaocheng, Shandong 252000, P.R. China
| | - Song Wang
- Department of Stomatology & Precision Biomedical Laboratory, Liaocheng People's Hospital, Liaocheng University, Liaocheng, Shandong 252000, P.R. China
| | - Shuxin Ding
- School of Stomatology, Weifang Medical University, Weifang, Shandong 261000, P.R. China
| | - Yanan Li
- Biomedical Laboratory, Medical School of Liaocheng University, Liaocheng, Shandong 252000, P.R. China
| | - Yongguo Li
- Department of Stomatology & Precision Biomedical Laboratory, Liaocheng People's Hospital, Liaocheng University, Liaocheng, Shandong 252000, P.R. China
| | - Dongping Zhang
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Shandong University and Shandong Provincial Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong 250000, P.R. China
- Department of Stomatology & Precision Biomedical Laboratory, Liaocheng People's Hospital, Liaocheng University, Liaocheng, Shandong 252000, P.R. China
| | - Guoxiong Zhu
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Shandong University and Shandong Provincial Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong 250000, P.R. China
- Department of Stomatology, PLA 960th Hospital, Jinan, Shandong 250000, P.R. China
| | - Zhen Meng
- Department of Stomatology & Precision Biomedical Laboratory, Liaocheng People's Hospital, Liaocheng University, Liaocheng, Shandong 252000, P.R. China
- Biomedical Laboratory, Medical School of Liaocheng University, Liaocheng, Shandong 252000, P.R. China
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Goud TJ. Epigenetic and Long-Term Effects of Nicotine on Biology, Behavior, and Health. Pharmacol Res 2023; 192:106741. [PMID: 37149116 DOI: 10.1016/j.phrs.2023.106741] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/15/2023] [Accepted: 03/20/2023] [Indexed: 05/08/2023]
Abstract
Tobacco and nicotine use are associated with disease susceptibility and progression. Health challenges associated with nicotine and smoking include developmental delays, addiction, mental health and behavioral changes, lung disease, cardiovascular disease, endocrine disorders, diabetes, immune system changes, and cancer. Increasing evidence suggests that nicotine-associated epigenetic changes may mediate or moderate the development and progression of a myriad of negative health outcomes. In addition, nicotine exposure may confer increased lifelong susceptibility to disease and mental health challenges through alteration of epigenetic signaling. This review examines the relationship between nicotine exposure (and smoking), epigenetic changes, and maladaptive outcomes that include developmental disorders, addiction, mental health challenges, pulmonary disease, cardiovascular disease, endocrine disorders, diabetes, immune system changes, and cancer. Overall, findings support the contention that nicotine (or smoking) associated altered epigenetic signaling is a contributing factor to disease and health challenges.
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Affiliation(s)
- Thomas J Goud
- Department of Biobehavioral Health, The Pennsylvania State University, Penn State University, University Park, PA, USA.
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Zeng Y, Ma W, Li L, Zhuang G, Luo G, Zhou H, Hao W, Liu Y, Guo F, Tian M, Ruan X, Gao M, Zheng X. Identification and validation of eight estrogen-related genes for predicting prognosis of papillary thyroid cancer. Aging (Albany NY) 2023; 15:1668-1684. [PMID: 36917092 PMCID: PMC10042678 DOI: 10.18632/aging.204582] [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: 10/17/2022] [Accepted: 02/06/2023] [Indexed: 03/16/2023]
Abstract
Papillary thyroid cancer (PTC) is one of the most common malignant tumors in female, and estrogen can affect its progression. However, the targets and mechanisms of estrogen action in PTC remain unclear. Therefore, this study focuses on the relationship between estrogen-related genes (ERGs) expression and prognosis in PTC, particularly neuropeptide U (NMU), and its important role in tumor progression. Based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, differentially expressed genes (DEGs) predominantly enriched in ERGs were identified between PTC and normal tissue. Then, we identified ERGs that contributed most to PTC prognosis, including Transducer of ERBB2 1 (TOB1), trefoil factor 1 (TFF1), phospholipase A and acyltransferase 3 (PLAAT3), NMU, kinesin family member 20A (KIF20A), DNA topoisomerase II alpha (TOP2A), tetraspanin 13 (TSPAN13), and carboxypeptidase E (CPE). In addition, we confirmed that NMU was highly expressed in PTC and explored the effect of NMU on PTC cells proliferation in vitro and in vivo. The results showed that the proliferative capacity of PTC cells was significantly reduced with NMU knockdown. Moreover, the phosphorylation levels of the Kirsten rat sarcoma virus (KRAS) signaling pathway were significantly lower with NMU knockdown. These results suggest that ERGs, especially NMU, may be novel prognostic indicators in PTC.
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Affiliation(s)
- Yu Zeng
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
| | - Weike Ma
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
| | - Lijuan Li
- Department of Cancer Prevention Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
| | - Gaojian Zhuang
- The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan 511500, China
| | - Guoqing Luo
- The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan 511500, China
| | - Hong Zhou
- The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan 511500, China
| | - Weijing Hao
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
| | - Yu Liu
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
| | - Fengli Guo
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
| | - Mengran Tian
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
- Department of Thyroid and Breast Surgery, Tianjin Union Medical Center, Tianjin 300121, China
- School of Medicine, Nankai University, Tianjin 300071, China
| | - Xianhui Ruan
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
| | - Ming Gao
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
- Department of Thyroid and Breast Surgery, Tianjin Union Medical Center, Tianjin 300121, China
- Tianjin Key Laboratory of General Surgery in Construction, Tianjin Union Medical Center, Tianjin 300121, China
| | - Xiangqian Zheng
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
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Yu JW, Pang R, Liu B, Zhang L, Zhang JW. Bioinformatics identify the role of chordin-like 1 in thyroid cancer. Medicine (Baltimore) 2023; 102:e32778. [PMID: 36749222 PMCID: PMC9901988 DOI: 10.1097/md.0000000000032778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
The abnormal expression of chordin-like 1 (CHRDL1) is identified in many cancers, while the effect of CHRDL1 in thyroid cancer (THCA) remains unclear. The University of California Santa Cruz, Gene Expression Profiling Interactive Analysis, University of Alabama at Birmingham Cancer, and Gene Expression Omnibus database (GSE33570, GSE33630, and GSE60542) were used for determining the mRNA and methylation expression of CHRDL1 in tumor and normal tissues. Human Protein Atlas was used for exploring the protein expression level of CHRDL1. The genes correlated to CHRDL1 were assessed by cBioPortal database. The prognostic value of CHRDL1 was evaluated through Kaplan-Meier method, cox regression, and nomogram analysis. Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and gene set enrichment analysis were used for predicting potential function of CHRDL1. The relationship between CHRDL1 and immune cell infiltration was determined by Pearson method. The downregulated mRNA and protein expressions of CHRDL1 were identified in THCA through the analysis of data from The Cancer Genome Atlas, Gene Expression Omnibus, and Human Protein Atlas database. The survival analysis showed that the CHRDL1 expression significantly affected disease-free interval (DFI) and progression-free interval, and CHRDL1 was an independent predictor of DFI. Besides, we found that C-C motif chemokine ligand 21 could significantly affect DFI time when it was co-expressed with CHRDL1. Additionally, the function of CHRDL1 was enriched in cell migration, apoptosis, and immune cell receptor. The downregulated expression of CHRDL1 was observed in THCA and caused poor prognosis. CHRDL1 may be involved in signal pathway related to cancer development and immune response, which suggested it could be a potential biomarker.
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Affiliation(s)
- Jia-Wei Yu
- Department of Head and Neck Thyroid, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Rui Pang
- Department of Head and Neck Thyroid, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Bo Liu
- Department of Head and Neck Thyroid, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Liang Zhang
- Department of Head and Neck Thyroid, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Jie-Wu Zhang
- Department of Head and Neck Thyroid, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
- * Correspondence: Jie-Wu Zhang, Department of Head and Neck Thyroid, Harbin Medical University Cancer Hospital, No.150, Baojian Road, Nangang District, Harbin 150041, Heilongjiang, China (e-mail: )
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Identification of potential biomarkers for papillary thyroid carcinoma by comprehensive bioinformatics analysis. Mol Cell Biochem 2023:10.1007/s11010-022-04606-x. [PMID: 36635603 DOI: 10.1007/s11010-022-04606-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: 12/14/2021] [Accepted: 10/28/2022] [Indexed: 01/14/2023]
Abstract
To perform bioinformatics analysis on the papillary thyroid carcinoma (PTC) gene chip dataset to explore new biological markers for PTC. The gene expression profiles of GSE3467 and GSE6004 chip data were collected by GEO2R, and the differentially expressed genes (DEGs) were selected for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Protein-protein interaction (PPI) relationship analysis was achieved using STRING, and the hub genes were obtained using the Cytoscape software. GEPIA was used to validate the expressions of the hub genes in the normal and tumor tissues and to conduct survival analyses. Pertinent genetic pathology results were fetched using the HPA database. Finally, the key genes were clinically verified by reverse transcription-polymerase chain reaction. 97 genes were jointly up-regulated and 107 genes were jointly down-regulated in GSE3467 and GSE6004. GO function enrichment analysis revealed that the DEGs were involved in the regulation of calcium ion transport into cytosol, integrin binding, and cell adhesion molecule binding. KEGG pathway enrichment analysis indicated that the DEGs were chiefly associated with thyroid cancer and non-small cell lung cancer. According to the PPI network, 30 key target genes were identified. Only the expressions of ANK2, TLE1, and TCF4 matched between the normal and tumor tissues, and were associated with disease prognosis. When compared with the normal thyroid tissues, the protein and mRNA expressions of ANK2, TLE1, and TCF4 were down-regulated in PTC. Significant differences exist in overall gene expression between the thyroid tissues of patients with PTC and those of healthy people. Furthermore, the differential genes ANK2, TLE1, and TCF4 are expected to be reliable molecular markers for the mechanism study and diagnosis of PTC.
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Bansal R, Saxena U. Integrative Analysis of Potential Biomarkers Involved in the Progression of Papillary Thyroid Cancer. Appl Biochem Biotechnol 2022; 195:2917-2932. [PMID: 36445679 DOI: 10.1007/s12010-022-04244-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2022] [Indexed: 11/30/2022]
Abstract
This study aims to explore key prognostic and diagnostic biomarkers involved in the pathogenesis of papillary thyroid cancer (PTC) which is one of the most common endocrine cancers and whose occurrence is rapidly increasing. Papillary thyroid cancer datasets containing normal and tumor samples were collected from Gene Expression Omnibus. Protein-protein interaction (PPI) network for common upregulated differentially expressed genes (DEGs) was constructed, and hub genes were studied. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to identify the vital biological behaviors and pathways involved in PTC. PPI network analysis demonstrated the interaction between 134 common upregulated DEGs, and top 15 pivotal genes with highest degree of connectivity were retrieved. Three of the hub genes (DPP4, ITGA2, FN1) were linked to the prognosis of PTC patients and considered clinically relevant core genes via survival analysis. We suggest that the identification of key genes associated with PTC development help us in understanding molecular mechanisms related to disease. These genes could also be considered the diagnostic biomarkers or as therapeutic targets in the future treatment for PTC.
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Affiliation(s)
- Ritu Bansal
- Department of Biotechnology, National Institute of Technology Warangal, Warangal, 506004, Telangana, India
| | - Urmila Saxena
- Department of Biotechnology, National Institute of Technology Warangal, Warangal, 506004, Telangana, India.
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Evolution of intra-tumoral heterogeneity across different pathological stages in papillary thyroid carcinoma. Cancer Cell Int 2022; 22:263. [PMID: 35996174 PMCID: PMC9394008 DOI: 10.1186/s12935-022-02680-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 08/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Intra-tumor heterogeneity (ITH) results from the continuous accumulation of mutations during disease progression, thus impacting patients' clinical outcome. How the ITH evolves across papillary thyroid carcinoma (PTC) different tumor stages is lacking. METHODS We used the whole-exome sequencing data from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) cohort to track the ITH and assessed its relationship with clinical features through different stages of the PTC progression. We further assayed the expression levels of the specific genes in papillary thyroid cancer cell lines compared to an immortalized normal thyroid epithelial cell line by qRT-PCR. RESULTS We revealed the timing of mutational processes and the dynamics of the temporal acquisition of somatic events during the lifetime of the PTC. ITH significantly influences the PTC patient's survival rate and, as genetic heterogeneity increases, the prognosis gets worse in advanced tumor stages. ITH also affects the mutational architecture of each clinical stage which is subject to periodic fluctuations. Different mutational processes may cooperate to shape a stage-specific mutational spectrum during the progression from early to advanced tumor stages. Moreover, different evolutionary paths characterize PTC progression across pathological stages due to both mutations recurrently occurring in all stages in hotspot positions and distinct codon changes dominating in different stages. A different expression level of specific genes also exists in different thyroid cancer cell lines. CONCLUSIONS Our findings suggest ITH as a potential unfavorable prognostic factor in PTC and highlight the dynamic changes in different clinical stages of PTC, providing some clues for the precision medicine and suggesting different diagnostic decisions depending on the clinical stages of patients. Finally, complete clear guidelines to define risk stratification of PTC patients are lacking; thus, this work could contribute to defining patients who need more aggressive treatments and, in turn, could reduce the social burden of this cancer.
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Wu Q, Zheng Z, Zhang J, Piao Z, Xin M, Xiang X, Wu A, Zhao T, Huang S, Qiao Y, Zhou J, Xu S, Cheng H, Wu L, Ouyang K. Chordin-Like 1 Regulates Epithelial-to-Mesenchymal Transition and Metastasis via the MAPK Signaling Pathway in Oral Squamous Cell Carcinoma. Front Oncol 2022; 12:862751. [PMID: 35494000 PMCID: PMC9046701 DOI: 10.3389/fonc.2022.862751] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundAccumulating evidence suggests that dysregulation of Chordin-like 1 (CHRDL1) is associated with malignant biological behaviors in multiple cancers. However, the exact function and molecular mechanism of CHRDL1 in oral squamous cell carcinoma (OSCC) remain unclear.MethodsThe expression levels of CHRDL1 in OSCC tissues and CAL27 cells were determined by RT-qPCR. Immunohistochemical staining was applied to detect CHRDL1 protein expression in sample tissues from OSCC patients. Gain of function and knockdown by lentivirus were further used to examine the effects of CHRDL1 on cell proliferation, migration, invasion, and adhesion in OSCC. Tail vein injection of CAL27 cells with dysregulated CHRDL1 expression was further used to examine the effect of CHRDL1 on lung colonization. RNA sequencing was performed to explore the molecular mechanisms of CHRDL1 that underlie the progression of OSCC.ResultsCHRDL1 was significantly downregulated in OSCC tissues and CAL27 cells compared to controls. CHRDL1 knockdown enhanced migration, invasion, adhesion, and EMT, but not proliferation, in CAL27 cells. Overexpression of CHRDL1 had the opposite effects. Moreover, CHRDL1 was proven to inhibit tumor metastasis in vivo. Mechanistically, MAPK signaling pathway components, including ERK1/2, p38, and JNK, were found to regulate the malignant biological behaviors of CAL27 cells.ConclusionsOur results suggest that CHRDL1 has an inhibitory effect on OSCC metastasis via the MAPK signaling pathway, which provides a new possible potential therapeutic target against OSCC.
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Affiliation(s)
- Qiuyu Wu
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
- Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-sen University, Jiangmen, China
| | - Zhichao Zheng
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Junwei Zhang
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Zhengguo Piao
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Mengyu Xin
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Xi Xiang
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Antong Wu
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Tianyu Zhao
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Songkai Huang
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Yu Qiao
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Jiayu Zhou
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Shaofen Xu
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Haoyu Cheng
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Lihong Wu
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
- *Correspondence: Kexiong Ouyang, ; Lihong Wu,
| | - Kexiong Ouyang
- Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
- *Correspondence: Kexiong Ouyang, ; Lihong Wu,
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12
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Zhang S, He Y, Xuan Q, Ling X, Men K, Zhao X, Xue D, Li L, Zhang Y. TMEM139 prevents NSCLC metastasis by inhibiting lysosomal degradation of E-cadherin. Cancer Sci 2022; 113:1999-2007. [PMID: 35302694 PMCID: PMC9207374 DOI: 10.1111/cas.15341] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/10/2022] [Accepted: 03/12/2022] [Indexed: 11/29/2022] Open
Abstract
Non‐small‐cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases and has the highest mortality rate among all solid tumors. It is characterized by early metastasis, and investigations of the molecular mechanisms underlying the progression and metastasis of NSCLC are urgently needed for the development of therapeutic targets. Here, we report that the transmembrane protein TMEM139 is significantly downregulated in NSCLC and that reduced expression of TMEM139 is correlated with a poor prognosis in NSCLC patients. Mechanistically, we found that TMEM139 directly interacts with E‐cadherin at the plasma membrane and at focal adhesion sites. Moreover, TMEM139 can prevent the lysosomal degradation of E‐cadherin, which inhibits epithelial‐mesenchymal transition, migration and invasion of NSCLC cells both in vitro and in vivo. Our study not only expands our understanding of NSCLC metastasis but also provides a foundation to develop novel therapeutic strategies.
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Affiliation(s)
- Shuai Zhang
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yunlong He
- Department of radiation oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Qijia Xuan
- Department of Medical Oncology, The Fourth Affiliated Hospital Zhejiang University School of Medicine, Yiwu, Zhejiang Province, China
| | - Xiaodong Ling
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Kaiya Men
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xu Zhao
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Dinglong Xue
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ling Li
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yingyin Zhang
- Department of Medical Oncology, Hu Lun Bei Er Ren Min Hospital, Inner Mongolia Province, China
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13
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Luo Y, Chen R, Ning Z, Fu N, Xie M. Identification of a Four-Gene Signature for Determining the Prognosis of Papillary Thyroid Carcinoma by Integrated Bioinformatics Analysis. Int J Gen Med 2022; 15:1147-1160. [PMID: 35153506 PMCID: PMC8824688 DOI: 10.2147/ijgm.s346058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 01/21/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose Although well-differentiated papillary thyroid carcinoma (PTC) has an indolent nature and usually an excellent prognosis, some patients experience disease recurrence or death. The aim of this study was to identify prognostic markers to stratify PTC patients. Patients and Methods Eight gene-expression profiles (GSE3467, GSE3678, GSE5364, GSE27155, GSE33630, GSE53157, GSE60542, and GSE104005) were obtained from the Gene Expression Omnibus and used to analyze differentially expressed genes (DEGs) between PTC tissues and non-tumor tissues. Univariable Cox regression survival analysis and Lasso-penalized Cox regression analysis were performed to identify prognostic genes and establish a risk-score model based on the integrated DEGs. Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves were used to validate the prognostic performance of the risk score. A nomogram was constructed based on The Cancer Genome Atlas dataset and Multivariable Cox regression analysis. Results A total of 165 upregulated and 207 downregulated DEGs were screened. A four-gene signature including PAPSS2, PCOLCE2, PTX3, and TGFBR3 was identified. The risk-score model showed a strong diagnosis performance for identifying patients with a poor prognosis. KM analysis showed that patients with low risk scores had a significantly more favorable overall survival (OS) than those with high risk scores (p = 0.0002). ROC curves based on the four-gene signature showed better performances in predicting 1-, 3-, and 5-year survival than did the American Joint Committee on Cancer staging system (area under the curve: 0.86 vs 0.84, 0.80 vs 0.63, and 0.79 vs 0.73, respectively). Furthermore, when combined with age and tumor status from the nomogram, the four-gene signature achieved a good performance in guiding postoperative follow-up surveillance of patients with PTC. Conclusion The four-gene signature was found to be a novel and reliable biomarker with great potential for clinical application in risk stratification and OS prediction in patients with PTC.
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Affiliation(s)
- Yuting Luo
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Rong Chen
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Zhikun Ning
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Nantao Fu
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Minghao Xie
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China
- Correspondence: Minghao Xie, Department of General Surgery, The First Affiliated Hospital of Nanchang University, 17 Yongwai Road, Nanchang, Jiangxi, 330006, People’s Republic of China, Tel +8613672207521, Email
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14
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Deng B, Chen X, Xu L, Zheng L, Zhu X, Shi J, Yang L, Wang D, Jiang D. Chordin-like 1 is a novel prognostic biomarker and correlative with immune cell infiltration in lung adenocarcinoma. Aging (Albany NY) 2022; 14:389-409. [PMID: 35021154 PMCID: PMC8791215 DOI: 10.18632/aging.203814] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 12/29/2021] [Indexed: 11/25/2022]
Abstract
Chordin-like 1 (CHRDL1), an inhibitor of bone morphogenetic proteins(BMPs), has been recently reported to participate in the progression of numerous tumors, however, its role in lung adenocarcinoma (LUAD) remains unclear. Our study aimed to demonstrate relationship between CHRDL1 and LUAD based on data from The Cancer Genome Atlas (TCGA). Among them, CHRDL1 expression revealed promising power for distinguishing LUAD tissues form normal sample. Low CHRDL1 was correlated with poor clinicopathologic features, including high T stage (OR=0.45, P<0.001), high N stage (OR=0.57, P<0.003), bad treatment effect (OR=0.64, P=0.047), positive tumor status (OR=0.63, P=0.018), and TP53 mutation (OR=0.49, P<0.001). The survival curve illustrated that low CHRDL1 was significantly correlative with a poor overall survival (HR=0.60, P<0.001). At multivariate Cox regression analysis, CHRDL1 remained independently correlative with overall survival. GSEA identified that the CHRDL1 expression was related to cell cycle and immunoregulation. Immune infiltration analysis suggested that CHRDL1 was significantly correlative with 7 kinds of immune cells. Immunohistochemical validation showed that CHRDL1 was abnormally elevated and negatively correlated with Th2 cells in LUAD tissues. In conclusion, CHRDL1 might become a novel prognostic biomarker and therapy target in LUAD. Moreover, CHRDL1 may improve the effectiveness of immunotherapy by regulating immune infiltration.
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Affiliation(s)
- Bing Deng
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaorui Chen
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lingfang Xu
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Zheng
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaoqian Zhu
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Junwei Shi
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lei Yang
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Dian Wang
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Depeng Jiang
- Department of Respiratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
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15
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Noncoding RNAs in Papillary Thyroid Cancer: Interaction with Cancer-Associated Fibroblasts (CAFs) in the Tumor Microenvironment (TME) and Regulators of Differentiation and Lymph Node Metastasis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1350:145-155. [PMID: 34888848 DOI: 10.1007/978-3-030-83282-7_7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
A large majority of all thyroid cancers are papillary thyroid carcinomas (PTC), named for the specific papillary architecture observed histologically. Despite the high rate of success with modern diagnostic and therapeutic algorithms, there are significant areas where the management of PTC can be improved. Aggressive PTC subtypes that are refractory to radioactive iodine (RAI) therapy carry a more severe prognosis and account for most of PTC-related deaths. As lymph node metastasis is present in roughly 40% of all adult PTC cases, higher specificity in these tests is a clinical need, especially since lymph node metastases are associated with reduced survival and higher recurrence rates. Additionally, this cancer can progress to more dedifferentiated and aggressive variants, such as poorly differentiated papillary thyroid cancer (PDPTC) and anaplastic thyroid cancer (ATC). Therefore, development of more sensitive and specific detection methods that allow unnecessary surgeries to be avoided is of the utmost importance. The body of large-scale, unbiased gene expression analysis in PTC has focused on the coding transcriptome, specifically mRNAs and microRNAs. However, there have been implications for the potential use of long noncoding RNAs (lncRNAs) in PTC diagnosis, prognosis, and treatment via the utilization of genome-wide studies of patient samples. lncRNAs have diverse regulatory potential in gene expression, alternative splicing, posttranscriptional mRNA modification, and epigenomic alterations. Many lncRNAs have tissue-specific expression and are demonstrated to play key roles in cancer progression and prognosis. However, lncRNAs are not being exploited as biomarkers or therapeutic targets currently, despite their elucidated effects on oncogenesis. These potent biomarkers would be revolutionary in detection at early stages, as this significantly increases the chances of survival. Their aberrant expression in cancer and correlation with steps in tumorigenesis as well as their role in differentiation would allow for a promising role as a prognostic and diagnostic biomarker in thyroid cancer. This would help prevent the more aggressive ATC that derives from dedifferentiation of the less aggressive PTC and FTC. The targeting of the specific lncRNAs could also pose a valuable treatment option via preventing or reversing this dedifferentiation process and making this usually refractory form of thyroid cancer more responsive to standard treatment options.
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16
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Arora C, Kaur D, Naorem LD, Raghava GPS. Prognostic biomarkers for predicting papillary thyroid carcinoma patients at high risk using nine genes of apoptotic pathway. PLoS One 2021; 16:e0259534. [PMID: 34767591 PMCID: PMC8589158 DOI: 10.1371/journal.pone.0259534] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 10/20/2021] [Indexed: 12/12/2022] Open
Abstract
Aberrant expressions of apoptotic genes have been associated with papillary thyroid carcinoma (PTC) in the past, however, their prognostic role and utility as biomarkers remains poorly understood. In this study, we analysed 505 PTC patients by employing Cox-PH regression techniques, prognostic index models and machine learning methods to elucidate the relationship between overall survival (OS) of PTC patients and 165 apoptosis related genes. It was observed that nine genes (ANXA1, TGFBR3, CLU, PSEN1, TNFRSF12A, GPX4, TIMP3, LEF1, BNIP3L) showed significant association with OS of PTC patients. Five out of nine genes were found to be positively correlated with OS of the patients, while the remaining four genes were negatively correlated. These genes were used for developing risk prediction models, which can be utilized to classify patients with a higher risk of death from the patients which have a good prognosis. Our voting-based model achieved highest performance (HR = 41.59, p = 3.36x10-4, C = 0.84, logrank-p = 3.8x10-8). The performance of voting-based model improved significantly when we used the age of patients with prognostic biomarker genes and achieved HR = 57.04 with p = 10−4 (C = 0.88, logrank-p = 1.44x10-9). We also developed classification models that can classify high risk patients (survival ≤ 6 years) and low risk patients (survival > 6 years). Our best model achieved AUROC of 0.92. Further, the expression pattern of the prognostic genes was verified at mRNA level, which showed their differential expression between normal and PTC samples. Also, the immunostaining results from HPA validated these findings. Since these genes can also be used as potential therapeutic targets in PTC, we also identified potential drug molecules which could modulate their expression profile. The study briefly revealed the key prognostic biomarker genes in the apoptotic pathway whose altered expression is associated with PTC progression and aggressiveness. In addition to this, risk assessment models proposed here can help in efficient management of PTC patients.
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Affiliation(s)
- Chakit Arora
- Indraprastha Institute of Information Technology-Delhi, Department of Computational Biology, New Delhi, India
| | - Dilraj Kaur
- Indraprastha Institute of Information Technology-Delhi, Department of Computational Biology, New Delhi, India
| | - Leimarembi Devi Naorem
- Indraprastha Institute of Information Technology-Delhi, Department of Computational Biology, New Delhi, India
| | - Gajendra P. S. Raghava
- Indraprastha Institute of Information Technology-Delhi, Department of Computational Biology, New Delhi, India
- * E-mail:
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17
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Ling Y, Jia L, Li K, Zhang L, Wang Y, Kang H. Development and validation of a novel 14-gene signature for predicting lymph node metastasis in papillary thyroid carcinoma. Gland Surg 2021; 10:2644-2655. [PMID: 34733714 DOI: 10.21037/gs-21-361] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/02/2021] [Indexed: 12/16/2022]
Abstract
Background There is still no reasonably accurate method of preoperatively predicting central lymph node metastasis (LNM), and it is essential to develop an effective evaluation model for predicting LNM in papillary thyroid carcinoma (PTC) patients. Methods PTC samples were collected from The Cancer Genome Atlas database. Candidate genes were identified as continuously upregulated or downregulated genes in the process of N0 to N1a and N1a to N1b. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct the predictive model for LNM. Multivariate logistic regression analysis was performed to screen the potential factors related to LNM, and a nomogram was established. The risk score of the gene signature model for predicting disease-free survival (DFS) was evaluated by Kaplan-Meier analysis. Results A 14-gene signature was developed by LASSO regression for predicting LNM based on 69 differential expression genes (DEGs) that were continuously upregulated or downregulated in the progress of PTC. The receiver operating characteristic (ROC) curves of the 14-gene signature predicting LNM, central LNM and lateral LNM were generated. The area under the ROC (AUC) values were 0.806 [95% confidence interval (CI): 0.7608-0.8815], 0.755 (95% CI: 0.6839-0.8263) and 0.821 (95% CI: 0.7608-0.8815). The nomogram's C-index value, including the 14-gene signature and other potential risk factors, was 0.786 (95% CI: 0.7296-0.8425), and the calibration exhibited fairly good consistency with the perfect prediction. Based on the 14-gene risk score, high-risk PTC patients had a worse DFS. Conclusions A novel 14-gene signature was developed for predicting LNM in PTC patients. The risk score also correlated with DFS in PTC patients.
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Affiliation(s)
- Yuwei Ling
- Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Luyao Jia
- Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Kaifu Li
- Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lina Zhang
- Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yajun Wang
- Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Hua Kang
- Center for Thyroid and Breast Surgery, Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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18
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Zhou Q, Guan P, Zhu Z, Cheng S, Zhou C, Wang H, Xu Q, Sung WK, Li G. ASMdb: a comprehensive database for allele-specific DNA methylation in diverse organisms. Nucleic Acids Res 2021; 50:D60-D71. [PMID: 34664666 PMCID: PMC8728259 DOI: 10.1093/nar/gkab937] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/27/2021] [Accepted: 09/30/2021] [Indexed: 11/18/2022] Open
Abstract
DNA methylation is known to be the most stable epigenetic modification and has been extensively studied in relation to cell differentiation, development, X chromosome inactivation and disease. Allele-specific DNA methylation (ASM) is a well-established mechanism for genomic imprinting and regulates imprinted gene expression. Previous studies have confirmed that certain special regions with ASM are susceptible and closely related to human carcinogenesis and plant development. In addition, recent studies have proven ASM to be an effective tumour marker. However, research on the functions of ASM in diseases and development is still extremely scarce. Here, we collected 4400 BS-Seq datasets and 1598 corresponding RNA-Seq datasets from 47 species, including human and mouse, to establish a comprehensive ASM database. We obtained the data on DNA methylation level, ASM and allele-specific expressed genes (ASEGs) and further analysed the ASM/ASEG distribution patterns of these species. In-depth ASM distribution analysis and differential methylation analysis conducted in nine cancer types showed results consistent with the reported changes in ASM in key tumour genes and revealed several potential ASM tumour-related genes. Finally, integrating these results, we constructed the first well-resourced and comprehensive ASM database for 47 species (ASMdb, www.dna-asmdb.com).
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Affiliation(s)
- Qiangwei Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Pengpeng Guan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zhixian Zhu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Sheng Cheng
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Cong Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Huanhuan Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Qian Xu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wing-Kin Sung
- Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.,Department of Computer Science, National University of Singapore, Singapore 117417, Singapore.,Department of Computational and Systems Biology, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Guoliang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
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19
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Ma J, Han W, Lu K. Comprehensive Pan-Cancer Analysis and the Regulatory Mechanism of ASF1B, a Gene Associated With Thyroid Cancer Prognosis in the Tumor Micro-Environment. Front Oncol 2021; 11:711756. [PMID: 34490109 PMCID: PMC8417739 DOI: 10.3389/fonc.2021.711756] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 07/23/2021] [Indexed: 12/24/2022] Open
Abstract
Background The incidence of thyroid cancer, whose local recurrence and metastasis lead to death, has always been high and the pathogenesis of papillary thyroid carcinoma (PTC) has not been clearly elucidated. Therefore, the research for more accurate prognosis-related predictive biomarkers is imminent, and a key gene can often be a prognostic marker for multiple tumors. Methods Gene expression profiles of various cancers in the TCGA and GTEx databases were downloaded, and genes significantly associated with the prognosis of THCA were identified by combining differential analysis with survival analysis. Then, a series of bioinformatics tools and methods were used to analyze the expression of the gene in each cancer and the correlation of each expression with prognosis, tumor immune microenvironment, immune neoantigens, immune checkpoints, DNA repair genes, and methyltransferases respectively. The possible biological mechanisms were also investigated by GSEA enrichment analysis. Results 656 differentially expressed genes were identified from two datasets and 960 DEGs that were associated with disease-free survival in THCA patients were screened via survival analysis. The former and the latter were crossed to obtain 7 key genes, and the gene with the highest risk factor, ASF1B, was selected for this study. Differential analysis of multiple databases showed that ASF1B was commonly and highly expressed in pan-cancer. Survival analysis showed that high ASF1B expression was significantly associated with poor patient prognosis in multiple cancers. In addition, ASF1B expression levels were found to be associated with tumor immune infiltration in THCA, KIRC, LGG, and LIHC, and with tumor microenvironment in BRCA, LUSC, STAD, UCEC, and KIRC. Further analysis of the relationship between ASF1B expression and immune checker gene expression suggested that ASF1B may regulate tumor immune patterns in most tumors by regulating the expression levels of specific immune checker genes. Finally, GSEA enrichment analysis showed that ASF1B high expression was mainly enriched in cell cycle, MTORC1 signaling system, E2F targets, and G2M checkpoints pathways. Conclusions ASF1B may be an independent prognostic marker for predicting the prognosis of THCA patients. The pan-cancer analysis suggested that ASF1B may play an important role in the tumor micro-environment and tumor immunity and it has the potential of serving as a predictive biomarker for multiple cancers.
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Affiliation(s)
- Jing Ma
- Department of Thyroid and Breast Surgery, Nanjing Hospital of Chinese Medicine affiliated to Nanjing University of Chinese Medicine, Nanjing, China
| | - Wei Han
- Department of Thyroid and Breast Surgery, Nanjing Hospital of Chinese Medicine affiliated to Nanjing University of Chinese Medicine, Nanjing, China
| | - Kai Lu
- Department of Thyroid and Breast Surgery, Nanjing Hospital of Chinese Medicine affiliated to Nanjing University of Chinese Medicine, Nanjing, China
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20
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Qin AC, Qian Y, Ma YY, Jiang Y, Qian WF. Long Non-coding RNA RP11-395G23.3 Acts as a Competing Endogenous RNA of miR-124-3p to Regulate ROR1 in Anaplastic Thyroid Carcinoma. Front Genet 2021; 12:673242. [PMID: 34421987 PMCID: PMC8375390 DOI: 10.3389/fgene.2021.673242] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 06/10/2021] [Indexed: 12/12/2022] Open
Abstract
Anaplastic thyroid carcinoma (ATC) is one of the most aggressive human malignancies with poor prognosis. However, the underlying mechanisms of ATC remain to be elucidated. Recently, increasing studies have focused on competitive endogenous RNA (ceRNA) to discover valuable biomarkers for the diagnosis of ATC. The present study identified 705 differentially expressed mRNAs and 47 differentially expressed lncRNAs. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were also conducted. Additionally, an lncRNA/miRNA/mRNA network was constructed which included 1103 regulatory relations. The upregulation of RP11-395G23.3 in ATC cells was confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). In the loss of function assays, results suggested silencing of RP11-395G23.3 inhibited cell proliferation and induced cell apoptosis. Mechanically, RP11-395G23.3 could increase ROR1 via sponging miR-124-3p as a ceRNA. Moreover, ROR1 expression was decreased with the downregulation of RP11-395G23.3, but was rescued by the co-transfection of the miR-124-3p inhibitor in ATC cells. Our research suggested that the RP11-395G23.3/miR-124-3p/ROR1 axis potentially acted as a potential target for the diagnosis of ATC.
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Affiliation(s)
- An-Cheng Qin
- The Third Affiliated Hospital of Soochow University, Changzhou, China.,The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Yi Qian
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Yu-Yuan Ma
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Yong Jiang
- The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Wei-Feng Qian
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
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Zhong A, Ding N, Zhou Y, Yang G, Peng Z, Zhang H, Chai X. Identification of Hub Genes Associated with the Pathogenesis of Intracranial Aneurysm via Integrated Bioinformatics Analysis. Int J Gen Med 2021; 14:4039-4050. [PMID: 34354366 PMCID: PMC8331219 DOI: 10.2147/ijgm.s320396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 07/09/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND At present, the pathogenesis of intracranial aneurysms (IA) remains unclear, which significantly hinders the development of novel strategies for the clinical treatment. In this study, bioinformatics methods were used to identify the potential hub genes and pathways associated with the pathogenesis of IA. METHODS The gene expression datasets of patients with intracranial aneurysm were downloaded from the Gene Expression Database (GEO), and the different data sets were integrated by the robust rank aggregation (RRA) method to identify the differentially expressed genes between patients with intracranial aneurysm and the controls. The functional enrichment analyses of the significant differentially expressed genes (DEGs) were performed and the protein-protein interaction (PPI) network was constructed; thereafter, the hub genes were screened by cytoHubba plug-in of Cytoscape, and finally sequencing dataset GSE122897 was used to verify the hub genes. RESULTS The GSE15629, GSE75436, GSE26969, and GSE6551 expression profiles have been included in this study, including 34 intracranial aneurysm samples and 26 control samples. The four datasets obtained 136 significant DEGs (45 up-regulated, 91 down-regulated). Enrichment analysis showed that the extracellular matrix structural constituent and the ECM-receptor interaction were closely related to the occurrence of IA. It was finally determined that eight hub genes associated with the development of IA, including VCAN, COL1A1, COL11A1, COL5A1, COL5A2, POSTN, THBS2, and CDH2. CONCLUSION The discovery of potential hub genes and pathways could enhance the understanding of the molecular mechanisms associated with the development of IA. These hub genes may be potential therapeutic targets for the management and new biomarker for the diagnosis of IA.
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Affiliation(s)
- Aifang Zhong
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Trauma center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
| | - Ning Ding
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Trauma center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
| | - Yang Zhou
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Trauma center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
| | - Guifang Yang
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Trauma center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
| | - Zhenyu Peng
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Emergency Medicine and Difficult Disease Institute, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
| | - Hongliang Zhang
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Emergency Medicine and Difficult Disease Institute, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
| | - Xiangping Chai
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Trauma center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
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Kaur D, Arora C, Raghava GPS. Prognostic Biomarker-Based Identification of Drugs for Managing the Treatment of Endometrial Cancer. Mol Diagn Ther 2021; 25:629-646. [PMID: 34155607 DOI: 10.1007/s40291-021-00539-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/27/2021] [Indexed: 12/26/2022]
Abstract
INTRODUCTION Uterine corpus endometrial carcinoma (UCEC) causes thousands of deaths per year. To improve the overall survival of patients with UCEC, there is a need to identify prognostic biomarkers and potential drugs. OBJECTIVES The aim of this study was twofold: the identification of prognostic gene signatures from expression profiles of pattern recognition receptor (PRR) genes and identification of the most effective existing drugs using the prognostic gene signature. METHODS This study was based on the expression profile of PRR genes of 541 patients with UCEC obtained from The Cancer Genome Atlas. Key prognostic signatures were identified using various approaches, including survival analysis, network, and clustering. Hub genes were identified by constructing a co-expression network. Representative genes were identified using k-means and k-medoids-based clustering. Univariate Cox proportional hazard (PH) analysis was used to identify survival-associated genes. 'cmap2' was used to identify potential drugs that can suppress/enhance the expression of prognostic genes. RESULTS Models were developed using hub genes and achieved a maximum hazard ratio (HR) of 1.37 (p = 0.294). Then, a clustering-based model was developed using seven genes (HR 9.14; p = 1.49 × 10-12). Finally, a nine gene-based risk stratification model was developed (CLEC1B, CLEC3A, IRF7, CTSB, FCN1, RIPK2, NLRP10, NLRP9, and SARM1) and achieved HR 10.70; p = 1.1 × 10-12. The performance of this model improved significantly in combination with the clinical stage and achieved HR 15.23; p = 2.21 × 10-7. We also developed a model for predicting high-risk patients (survival ≤ 4.3 years) and achieved an area under the receiver operating characteristic curve (AUROC) of 0.86. CONCLUSION We identified potential immunotherapeutic agents based on prognostic gene signature: hexamethonium bromide and isoflupredone. Several novel candidate drugs were suggested, including human interferon-α-2b, paclitaxel, imiquimod, MESO-DAP1, and mifamurtide. These biomolecules and repurposed drugs may be utilised for prognosis and treatment for better survival.
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Affiliation(s)
- Dilraj Kaur
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi, Okhla Industrial Estate, New Delhi, 110020, India
| | - Chakit Arora
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi, Okhla Industrial Estate, New Delhi, 110020, India
| | - Gajendra Pal Singh Raghava
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi, Okhla Industrial Estate, New Delhi, 110020, India.
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Deng H, Hang Q, Shen D, Zhang Y, Chen M. Low expression of CHRDL1 and SPARCL1 predicts poor prognosis of lung adenocarcinoma based on comprehensive analysis and immunohistochemical validation. Cancer Cell Int 2021; 21:259. [PMID: 33980221 PMCID: PMC8117659 DOI: 10.1186/s12935-021-01933-9] [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: 03/15/2021] [Accepted: 04/13/2021] [Indexed: 12/13/2022] Open
Abstract
Purpose Exploring the molecular mechanisms of lung adenocarcinoma (LUAD) is beneficial for developing new therapeutic strategies and predicting prognosis. This study was performed to select core genes related to LUAD and to analyze their prognostic value. Methods Microarray datasets from the GEO (GSE75037) and TCGA-LUAD datasets were analyzed to identify differentially coexpressed genes in LUAD using weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. Functional enrichment analysis was conducted, and a protein–protein interaction (PPI) network was established. Subsequently, hub genes were identified using the CytoHubba plug-in. Overall survival (OS) analyses of hub genes were performed. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (THPA) databases were used to validate our findings. Gene set enrichment analysis (GSEA) of survival-related hub genes were conducted. Immunohistochemistry (IHC) was carried out to validate our findings. Results We identified 486 differentially coexpressed genes. Functional enrichment analysis suggested these genes were primarily enriched in the regulation of epithelial cell proliferation, collagen-containing extracellular matrix, transforming growth factor beta binding, and signaling pathways regulating the pluripotency of stem cells. Ten hub genes were detected using the maximal clique centrality (MCC) algorithm, and four genes were closely associated with OS. The CPTAC and THPA databases revealed that CHRDL1 and SPARCL1 were downregulated at the mRNA and protein expression levels in LUAD, whereas SPP1 was upregulated. GSEA demonstrated that DNA-dependent DNA replication and catalytic activity acting on RNA were correlated with CHRDL1 and SPARCL1 expression, respectively. The IHC results suggested that CHRDL1 and SPARCL1 were significantly downregulated in LUAD. Conclusions Our study revealed that survival-related hub genes closely correlated with the initiation and progression of LUAD. Furthermore, CHRDL1 and SPARCL1 are potential therapeutic and prognostic indicators of LUAD. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-021-01933-9.
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Affiliation(s)
- Huan Deng
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, 100049, China.,Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institute of Cancer Research and Basic Medical (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China.,Department of Radiation Oncology, Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China
| | - Qingqing Hang
- Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institute of Cancer Research and Basic Medical (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China.,Department of Radiation Oncology, Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China.,Zhejiang Chinese Medicinal University, Hangzhou, 310022, China
| | - Dijian Shen
- Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institute of Cancer Research and Basic Medical (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China.,Department of Radiation Oncology, Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China
| | - Yibi Zhang
- Jiangxi Medical College, Nanchang University, Nanchang, 331800, China
| | - Ming Chen
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, 100049, China. .,Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China. .,Institute of Cancer Research and Basic Medical (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China. .,Department of Radiation Oncology, Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China.
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Guo S, Wu J, Zhou W, Liu X, Liu Y, Zhang J, Jia S, Li J, Wang H. Identification and analysis of key genes associated with acute myocardial infarction by integrated bioinformatics methods. Medicine (Baltimore) 2021; 100:e25553. [PMID: 33847684 PMCID: PMC8052032 DOI: 10.1097/md.0000000000025553] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 03/25/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Acute myocardial infarction (AMI) is a common disease leading threat to human health around the world. Here we aimed to explore new biomarkers and potential therapeutic targets in AMI through adopting integrated bioinformatics tools. METHODS The gene expression Omnibus (GEO) database was used to obtain genes data of AMI and no-AMI whole blood. Furthermore, differentially expressed genes (DEGs) were screened using the "Limma" package in R 3.6.1 software. Functional and pathway enrichment analyses of DEGs were performed via "Bioconductor" and "GOplot" package in R 3.6.1 software. In order to screen hub DEGs, the STRING version 11.0 database, Cytoscape and molecular complex detection (MCODE) were applied. Correlation among the hub DEGs was evaluated using Pearson's correlation analysis. RESULTS By performing DEGs analysis, 289 upregulated and 62 downregulated DEGs were successfully identified from GSE66360, respectively. And they were mainly enriched in the terms of neutrophil activation, immune response, cytokine, nuclear factor kappa-B (NF-κB) signaling pathway, IL-17 signaling pathway, and tumor necrosis factor (TNF) signaling pathway. Based on the data of protein-protein interaction (PPI), the top 10 hub genes were ranked, including interleukin-8 (CXCL8), TNF, N-formyl peptide receptor 2 (FPR2), growth-regulated alpha protein (CXCL1), transcription factor AP-1 (JUN), interleukin-1 beta (IL1B), platelet basic protein (PPBP), matrix metalloproteinase-9 (MMP9), toll-like receptor 2 (TLR2), and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G). What's more, the results of correlation analysis demonstrated that there was positive correlation between the 10 hub DEGs. CONCLUSION Ten DEGs were identified as potential candidate diagnostic biomarkers for patients with AMI in present study. However, further experiments are needed to confirm the functional pathways and hub genes associated with AMI.
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Chen Z, Liu B, Yi M, Qiu H, Yuan X. A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer. Front Oncol 2020; 10:584733. [PMID: 33330065 PMCID: PMC7732649 DOI: 10.3389/fonc.2020.584733] [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] [Received: 07/18/2020] [Accepted: 10/21/2020] [Indexed: 12/22/2022] Open
Abstract
PURPOSE The exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC). METHODS The mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters. RESULTS 5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139-0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group. CONCLUSION We construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.
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Affiliation(s)
| | | | | | | | - Xianglin Yuan
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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