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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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2
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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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3
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Luo X, Tai J, Zhao Y, Zhao P, Sun D, Wang L. Associations of C‑X‑C motif chemokine ligands 1/2/8/13/14 with clinicopathological features and survival profile in patients with colorectal cancer. Oncol Lett 2022; 24:348. [PMID: 36072008 PMCID: PMC9434714 DOI: 10.3892/ol.2022.13468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 06/15/2022] [Indexed: 11/09/2022] Open
Affiliation(s)
- Xiaofan Luo
- Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, Jilin 130032, P.R. China
| | - Jiandong Tai
- Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, Jilin 130032, P.R. China
| | - Yuhang Zhao
- Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, Jilin 130032, P.R. China
| | - Pingwei Zhao
- Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, Jilin 130032, P.R. China
| | - Di Sun
- Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, Jilin 130032, P.R. China
| | - Lei Wang
- Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, Jilin 130032, P.R. China
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4
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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: 8] [Impact Index Per Article: 2.7] [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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5
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Li Y, Gao W, Cai X, Jin A, Shen J, Zhang Y, Chen Y, Hu B, Zeng T, Yu X, Zheng Y, Wang Y. Exploring Somatic Alteration Associating With Aggressive Behaviors of Papillary Thyroid Carcinomas by Targeted Sequencing. Front Oncol 2021; 11:722814. [PMID: 34692499 PMCID: PMC8529196 DOI: 10.3389/fonc.2021.722814] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 09/16/2021] [Indexed: 12/21/2022] Open
Abstract
Wisely differentiating high-risk papillary thyroid carcinoma (PTC) patients from low-risk PTC patients preoperatively is necessary when comes to making a personalized treatment plan. It is not easy to stratify the risk of patients according to sonography or lab results before surgery. This study aims to seek out potential mutation gene markers that may be helpful in stratifying the risk of PTC. A custom panel of 439 PTC relevant and classic tumor metabolic pathway relevant genes was designed. Targeted capture sequencing was performed on 35 pairs of samples from 35 PTC tumors and 35 para-tumor thyroid tissues obtained during surgery. Variant calling and detection of cancer gene mutations were identified by bio-information analysis. Ingenuity Pathway Analysis (IPA) was performed to do functional enrichment analysis of high-frequency mutant genes. Immunohistochemistry (IHC) was performed on 6 PTC patients to explore the expression of protein associated with interested genes. Event-free survival (EFS) was calculated to determine which genes might affect the prognosis of patients. We have identified 32 high-frequency mutant genes in PTC including BRAF. RBL2 was found to be significantly correlated to event-free survival, FOXO1, MUC6, PCDHB9, NOTCH1, FIZ1, and RTN1 were significantly associated with EFS, while BRAF mutant was not correlated to any of the prognosis indicators. Our findings in this study might open more choices when designing thyroid gene panels used in FNA samples to diagnose PTC and predict the potentially aggressive behavior of PTC.
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Affiliation(s)
- Yi Li
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Wei Gao
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Xiaojun Cai
- Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Anqi Jin
- Department of Ultrasound Medicine, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Jian Shen
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Yichun Zhang
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Yutong Chen
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Bing Hu
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China.,Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Tao Zeng
- CAS Key Laboratory of Computational Biology, Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China
| | - Xiangtian Yu
- Clinical Research Center, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yuanyi Zheng
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China.,Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Yan Wang
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China.,Shanghai Institute of Ultrasound in Medicine, Shanghai, China
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6
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Pan Y, Wu L, He S, Wu J, Wang T, Zang H. Identification of hub genes in thyroid carcinoma to predict prognosis by integrated bioinformatics analysis. Bioengineered 2021; 12:2928-2940. [PMID: 34167437 PMCID: PMC8806580 DOI: 10.1080/21655979.2021.1940615] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The aim of this study was to identify hub genes closely related to the pathogenesis and prognosis of thyroid carcinoma (THCA) by integrated bioinformatics analysis. In this study, through differential gene expression analysis, 1916 and 665 differentially expressed genes (DEGs) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, and 7 and 11 co-expressed modules were identified from the TCGA-THCA and GSE153659 datasets, respectively, by weighted gene co-expression network analysis. We identified 162 overlapping genes between the DEGs and co-expression module genes as candidate hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the 162 overlapping DEGs identified significant functions and pathways of THCA, such as thyroid hormone generation and metabolic process. A protein-protein interaction (PPI) analysis detected the top 10 hub genes (QSOX1, WFS1, EVA1A, FSTL3, CHRDL1, FABP4, PRDM16, PPARGC1A, PPARG, COL23A1). Finally, survival analysis, clinical correlation analysis, and protein abundance validation confirmed that 3 of the 10 hub genes were associated with survival prognosis of patients with THCA, and 8 of them were associated with the clinical stages of THCA. In summary, we identified hub genes and key modules that were closely related to THCA, and validated these genes by survival analysis, clinical correlation analysis, and Human Protein Atlas image analysis. Our results provide important information that will help to elucidate the pathogenesis of THCA and identify novel candidate prognostic biomarkers and potential therapeutic targets.
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Affiliation(s)
- Yangwang Pan
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Bejing, People's Republic of China
| | - Linjing Wu
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Bejing, People's Republic of China
| | - Shuai He
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Bejing, People's Republic of China
| | - Jun Wu
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Bejing, People's Republic of China
| | - Tong Wang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Bejing, People's Republic of China
| | - Hongrui Zang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Bejing, People's Republic of China
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7
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Gowthami J, Gururaj N, Mahalakshmi V, Sathya R, Sabarinath TR, Doss DM. Genetic predisposition and prediction protocol for epithelial neoplasms in disease-free individuals: A systematic review. J Oral Maxillofac Pathol 2020; 24:293-307. [PMID: 33456239 PMCID: PMC7802851 DOI: 10.4103/jomfp.jomfp_348_19] [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: 12/11/2019] [Revised: 03/23/2020] [Accepted: 04/24/2020] [Indexed: 01/13/2023] Open
Abstract
Background Epithelial neoplasm is an important global health-care problem, with high morbidity and mortality rates. Early diagnosis and appropriate treatment are essential for increased life survival. Prediction of occurrence of malignancy in a disease-free individual by any means will be a great breakthrough for healthy living. Aims and Objectives The aims and objectives were to predict the genetic predisposition and propose a prediction protocol for epithelial malignancy of various systems in our body, in a disease-free individual. Methods We have searched databases both manually and electronically, published in English language in Cochrane group, Google search, MEDLINE and PubMed from 2000 to 2019. We have included all the published, peer-reviewed, narrative reviews; randomized controlled trials; case-control studies; and cohort studies and excluded the abstract-only articles and duplicates. Specific words such as "etiological factors," "pathology and mutations," "signs and symptoms," "genetics and IHC marker," and "treatment outcome" were used for the search. A total of 1032 citations were taken, and only 141 citations met the inclusion criteria and were analyzed. Results After analyzing various articles, the etiological factors, clinical signs and symptoms, genes and the pathology involved and the commonly used blood and tissue markers were analyzed. A basic investigation strategy using immunohistochemistry markers was established. Conclusion The set of proposed biomarkers should be studied in future to predict genetic predisposition in disease-free individuals.
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Affiliation(s)
- J Gowthami
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - N Gururaj
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - V Mahalakshmi
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - R Sathya
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - T R Sabarinath
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - Daffney Mano Doss
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
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