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Niu L, Hu G. EHMT2 Suppresses ARRB1 Transcription and Activates the Hedgehog Signaling to Promote Malignant Phenotype and Stem Cell Property in Oral Squamous Cell Carcinoma. Mol Biotechnol 2024:10.1007/s12033-024-01130-9. [PMID: 38573544 DOI: 10.1007/s12033-024-01130-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 02/20/2024] [Indexed: 04/05/2024]
Abstract
Oral squamous cell carcinoma (OSCC) represents the primary subtype of head and neck squamous cell carcinoma (HNSCC), characterized by a high morbidity and mortality rate. Although previous studies have established specific correlations between euchromatic histone lysine methyltransferase 2 (EHMT2), a histone lysine methyltransferase, and the malignant phenotype of OSCC cells, its biological functions in OSCC remain largely unknown. This study, grounded in bioinformatics predictions, aims to clarify the influence of EHMT2 on the malignant behavior of OSCC cells and delve into the underlying mechanisms. EHMT2 exhibited high expression in OSCC tissues and demonstrated an association with poor patient outcomes. Artificial EHMT2 silencing in OSCC cells, achieved through lentiviral vector infection, significantly inhibited colony formation, migration, invasion, and cell survival. Regarding the mechanism, EHMT2 was found to bind the promoter of arrestin beta 1 (ARRB1), thereby suppressing its transcription through H3K9me2 modification. ARRB1, in turn, was identified as a negative regulator of the Hedgehog pathway, leading to a reduction in the proteins GLI1 and PTCH1. Cancer stem cells (CSCs) were enriched through repeated sphere formation assays in two OSCC cell lines. EHMT2 was found to activate the Hedgehog pathway, thus promoting sphere formation, migration and invasion, survival, and tumorigenic activity of the OSCC-CSCs. Notably, these effects were counteracted by the additional overexpression of ARRB1. In conclusion, this study provides novel evidence suggesting that EHMT2 plays specific roles in enhancing stem cell properties in OSCC by modulating the ARRB1-Hedgehog signaling cascade.
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Affiliation(s)
- Ling Niu
- Department of Stomatology, Affiliated Hospital of Beihua University, No. 3999, Binjiang East Road, Fengman District, Jilin, 132011, Jilin, People's Republic of China
| | - Guangyao Hu
- Department of Stomatology, Affiliated Hospital of Beihua University, No. 3999, Binjiang East Road, Fengman District, Jilin, 132011, Jilin, People's Republic of China.
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2
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Ulusan M, Bireller S, Ertugrul B, Kasarci G, Atas MN, Aydemir L, Ergen A, Cakmakoglu B. What if amoxicillin/clavulanic acid reduces the cisplatin anticancer impact on oral cancer treatment? J Stomatol Oral Maxillofac Surg 2023; 124:101502. [PMID: 37192700 DOI: 10.1016/j.jormas.2023.101502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 05/13/2023] [Indexed: 05/18/2023]
Abstract
Antibiotics-chemotherapeutics combination have become on the table for many cancer treatments. For this reason, we thought that further progress and development of studies to support chemotherapeutic approaches with the use of antibiotics may be beneficial in the clinical field. Cell lines (SCC-15, HTB-41, and MRC-5) were treated with 5-100 μM/ml concentrations of cisplatin (cisp) and amoxicillin/clavulanic acid (amx/cla) with combination (amx/cla-cisp) and alone in three different incubation periods. The all-cells viability was examined with WST-1 and apoptotic activity of the drugs were investigated via cell death ELISA assay kit. The cytotoxic impact of the 100 μM amx/cla-cisp combination was found to be reduced by up to 21.8%, which was significant given that the cytotoxic effect of only cisplatin therapy was 86.1%. Because our findings demonstrated that solo amx/cla therapy have almost no impact on proliferation or death, we focused on the amx/cla-cisp combination effect. It was found that the amx/cla-cisp combination has reduced the apoptotic fragment when comparing with the solely cisp-treated cells. Due to amx/cla-cisp combination on both cells but significantly on SCC-15 recovered the sole cisplatin effect, we believe that there might be a second thought when prescribing antibiotics while treating cancer patients. Not only the antibiotic's type but also the cancer type might interact to lessen the chemotherapeutic agent's impact which is clinically a dilemma to focus on.
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Affiliation(s)
- Murat Ulusan
- Department of Otolaryngology, Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Sinem Bireller
- Department of Biochemistry, Faculty of Pharmacy, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey
| | - Baris Ertugrul
- Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey; Graduate School of Health Sciences, Istanbul University, Istanbul, Turkey
| | - Goksu Kasarci
- Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey; Graduate School of Health Sciences, Istanbul University, Istanbul, Turkey
| | - Merve Nur Atas
- Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey; Graduate School of Health Sciences, Istanbul University, Istanbul, Turkey
| | - Levent Aydemir
- Department of Otolaryngology, Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Arzu Ergen
- Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Bedia Cakmakoglu
- Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey.
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Nelakurthi VM, Paul P, Reche A. Bioinformatics in Early Cancer Detection. Cureus 2023; 15:e46931. [PMID: 38021627 PMCID: PMC10640668 DOI: 10.7759/cureus.46931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 10/12/2023] [Indexed: 12/01/2023] Open
Abstract
Bioinformatics is a pretty recent branch of biology that encompasses the use of algebraic, analytic, and computing approaches to the processing and interpretation of biological information. A wide term, "bioinformatics" refers to the use of digital technology to study biological processes using high-dimensional data collected from many resources. The design and testing of the software tools required to evaluate the information are the core of bioinformatics research, which is conducted in great portions in silico and typically involves the synthesis of new learning from available data. Early diagnosis of cancer results in improved prognosis, but at the same time, it is difficult to conform to diagnosis at a very early stage. The use of DNA microarrays and proteomics studies for large-scale gene expression research has advanced technology, thus elevating the significance of bioinformatics tools. In today's research, wet experimentation and the application of bioinformatics analytics go side by side. Molecular profiling of tumor biopsies is becoming more and more crucial to both cancer research and the treatment of cancer.
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Affiliation(s)
- Vidya Maheswari Nelakurthi
- Public Health Dentistry, Sharad Pawar Dental College and Hospital, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Priyanka Paul
- Public Health Dentistry, Sharad Pawar Dental College and Hospital, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Amit Reche
- Public Health Dentistry, Sharad Pawar Dental College and Hospital, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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Jagomast T, Idel C, Klapper L, Kuppler P, Proppe L, Beume S, Falougy M, Steller D, Hakim SG, Offermann A, Roesch MC, Bruchhage KL, Perner S, Ribbat-Idel J. Comparison of manual and automated digital image analysis systems for quantification of cellular protein expression. Histol Histopathol 2022; 37:527-541. [PMID: 35146728 DOI: 10.14670/hh-18-434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Quantifying protein expression in immunohistochemically stained histological slides is an important tool for oncologic research. The use of computer-aided evaluation of IHC-stained slides significantly contributes to objectify measurements. Manual digital image analysis (mDIA) requires a user-dependent annotation of the region of interest (ROI). Others have built-in machine learning algorithms with automated digital image analysis (aDIA) and can detect the ROIs automatically. We aimed to investigate the agreement between the results obtained by aDIA and those derived from mDIA systems. METHODS We quantified chromogenic intensity (CI) and calculated the positive index (PI) in cohorts of tissue microarrays (TMA) using mDIA and aDIA. To consider the different distributions of staining within cellular sub-compartments and different tumor architecture our study encompassed nuclear and cytoplasmatic stainings in adenocarcinomas and squamous cell carcinomas. RESULTS Within all cohorts, we were able to show a high correlation between mDIA and aDIA for the CI (p<0.001) along with high agreement for the PI. Moreover, we were able to show that the cell detections of the programs were comparable as well and both proved to be reliable when compared to manual counting. CONCLUSION mDIA and aDIA show a high correlation in acquired IHC data. Both proved to be suitable to stratify patients for evaluation with clinical data. As both produce the same level of information, aDIA might be preferable as it is time-saving, can easily be reproduced, and enables regular and efficient output in large studies in a reasonable time period.
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Affiliation(s)
- T Jagomast
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany.
| | - C Idel
- Department of Otorhinolaryngology, University of Luebeck, Luebeck, Germany.
| | - L Klapper
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
| | - P Kuppler
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
| | - L Proppe
- Department of Gynecology and Obstetrics, University of Luebeck, Luebeck, Germany
| | - S Beume
- Department of Gynecology and Obstetrics, University of Luebeck, Luebeck, Germany
| | - M Falougy
- Department of Oral and Maxillofacial Surgery, University of Luebeck, Luebeck, Germany
| | - D Steller
- Department of Oral and Maxillofacial Surgery, University of Luebeck, Luebeck, Germany
| | - S G Hakim
- Department of Oral and Maxillofacial Surgery, University of Luebeck, Luebeck, Germany
| | - A Offermann
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
| | - M C Roesch
- Department of Urology, University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
| | - K L Bruchhage
- Department of Otorhinolaryngology, University of Luebeck, Luebeck, Germany
| | - S Perner
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany.,Pathology, Research Center Borstel, Leibniz Lung Center, Borstel, Germany
| | - J Ribbat-Idel
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
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Silva MC, Eugénio P, Faria D, Pesquita C. Ontologies and Knowledge Graphs in Oncology Research. Cancers (Basel) 2022; 14:cancers14081906. [PMID: 35454813 PMCID: PMC9029532 DOI: 10.3390/cancers14081906] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 03/25/2022] [Accepted: 04/07/2022] [Indexed: 11/16/2022] Open
Abstract
The complexity of cancer research stems from leaning on several biomedical disciplines for relevant sources of data, many of which are complex in their own right. A holistic view of cancer—which is critical for precision medicine approaches—hinges on integrating a variety of heterogeneous data sources under a cohesive knowledge model, a role which biomedical ontologies can fill. This study reviews the application of ontologies and knowledge graphs in cancer research. In total, our review encompasses 141 published works, which we categorized under 14 hierarchical categories according to their usage of ontologies and knowledge graphs. We also review the most commonly used ontologies and newly developed ones. Our review highlights the growing traction of ontologies in biomedical research in general, and cancer research in particular. Ontologies enable data accessibility, interoperability and integration, support data analysis, facilitate data interpretation and data mining, and more recently, with the emergence of the knowledge graph paradigm, support the application of Artificial Intelligence methods to unlock new knowledge from a holistic view of the available large volumes of heterogeneous data.
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Wu M, Wei B, Duan SL, Liu M, Ou-Yang DJ, Huang P, Chang S. Methylation-Driven Gene PLAU as a Potential Prognostic Marker for Differential Thyroid Carcinoma. Front Cell Dev Biol 2022; 10:819484. [PMID: 35141223 PMCID: PMC8818873 DOI: 10.3389/fcell.2022.819484] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 01/07/2022] [Indexed: 11/16/2022] Open
Abstract
Purpose: Aberrant DNA methylation plays a crucial role in the tumorigenesis of differentiated thyroid cancer (DTC); nevertheless, the factors leading to the local and regional recurrence of DTC are not well understood. This study aimed to establish the connection between DNA methylation-driven genes and the recurrence of DTC. Methods: RNA sequencing profiles and DNA methylation profiles of DTC were downloaded from The Cancer Genome Atlas (TCGA) database. Combined application of the methylmix R package and univariate Cox regression analyses were used to screen and distinguish prognosis-related methylation-driven genes. Multivariate Cox regression analyses were utilized to identify the target genes that were closely associated with the recurrence of DTC. Then, correlations between the expression levels of the target genes and the clinicopathological features were verified, as well as their potential biological functions. Results: A total of 168 Methylation-driven genes were differentially expressed in thyroid cancer, among which 10 genes (GSTO2, GSTM5, GSTM1, GPX7, FGF2, LIF, PLAU, BCL10, SHARPIN and TNFRSF1A) were identified as Hub genes. We selected PLAU for further analysis because PLAU was most strongly correlated with DTC recurrence and the DNA methylation levels of PLAU were closely associated with multiple clinicopathological features of DTC. PLAU was significantly upregulated in DTC, and patients with a high expression level of PLAU had a higher risk of recurrence (p < 0.05). Functional predictions suggested that PLAU-related genes were mainly involved in the regulation of immune-related signaling pathways. Moreover, the mRNA level of PLAU was found to be positively correlated with the cell markers of neutrophils and dendritic cells. In addition, we found that two DNA methylation sites (cg06829584, cg19399285) were associated with abnormal expression of PLAU in DTC. Conclusion: The methylation-driven gene PLAU is an independent risk factor for the recurrence of DTC and it functions as an oncogene through the regulation of immune-related signaling pathways, which offers new insight into the molecular mechanisms of thyroid cancer and provides new possibilities for individualized treatment of thyroid cancer patients.
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Affiliation(s)
- Min Wu
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, China
| | - Bo Wei
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, China
| | - Sai-Li Duan
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, China
| | - Mian Liu
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, China
| | - Deng-Jie Ou-Yang
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, China
| | - Peng Huang
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, China
- *Correspondence: Peng Huang,
| | - Shi Chang
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China
- Clinical Research Center for Thyroid Disease in Hunan Province, Changsha, China
- Hunan Provincial Engineering Research Center for Thyroid and Related Diseases Treatment Technology, Changsha, China
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7
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Mahapatra S, Bhuyan R, Das J, Swarnkar T. Integrated multiplex network based approach for hub gene identification in oral cancer. Heliyon 2021; 7:e07418. [PMID: 34258466 PMCID: PMC8258848 DOI: 10.1016/j.heliyon.2021.e07418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 01/27/2021] [Accepted: 06/23/2021] [Indexed: 02/01/2023] Open
Abstract
Background: The incidence of Oral Cancer (OC) is high in Asian countries, which goes undetected at its early stage. The study of genetics, especially genetic networks holds great promise in this endeavor. Hub genes in a genetic network are prominent in regulating the whole network structure of genes. Thus identification of such genes related to specific cancer types can help in reducing the gap in OC prognosis. Methods: Traditional study of network biology is unable to decipher the inter-dependencies within and across diverse biological networks. Multiplex network provides a powerful representation of such systems and encodes much richer information than isolated networks. In this work, we focused on the entire multiplex structure of the genetic network integrating the gene expression profile and DNA methylation profile for OC. Further, hub genes were identified by considering their connectivity in the multiplex structure and the respective protein-protein interaction (PPI) network as well. Results: 46 hub genes were inferred in our approach with a high prediction accuracy (96%), outstanding Matthews coefficient correlation value (93%) and significant biological implications. Among them, genes PIK3CG, PIK3R5, MYH7, CDC20 and CCL4 were differentially expressed and predominantly enriched in molecular cascades specific to OC. Conclusions: The identified hub genes in this work carry ontological signatures specific to cancer, which may further facilitate improved understanding of the tumorigenesis process and the underlying molecular events. Result indicates the effectiveness of our integrated multiplex network approach for hub gene identification. This work puts an innovative research route for multi-omics biological data analysis.
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Affiliation(s)
- S. Mahapatra
- Department of Computer Application, Siksha O Anusandhan Deemed to be University, Bhubaneswar, India
| | - R. Bhuyan
- Department of Oral Pathology & Microbiology, Siksha O Anusandhan Deemed to be University, Bhubaneswar, India
| | - J. Das
- Centre for Genomics & Biomedical Informatics, Siksha O Anusandhan Deemed to be University, Bhubaneswar, India
| | - T. Swarnkar
- Department of Computer Application, Siksha O Anusandhan Deemed to be University, Bhubaneswar, India
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Routray S, Kumar R, Datta KK, Puttamallesh VN, Chatterjee A, Gowda H, Mohanty N, Dash R, Dixit A. An integrated approach for identification of a panel of candidate genes arbitrated for invasion and metastasis in oral squamous cell carcinoma. Sci Rep 2021; 11:6208. [PMID: 33739025 DOI: 10.1038/s41598-021-85729-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 03/01/2021] [Indexed: 12/24/2022] Open
Abstract
Oral squamous cell carcinoma (OSCC) is known for its aggressiveness associated with poor prognosis. The molecular mechanisms underlying the invasion and metastasis are still poorly understood. An improved understanding of these mechanisms shall precede the development of new diagnostic tools and targeted therapies. We report an integrated approach using bioinformatics to predict candidate genes, coupled with proteomics and immunohistochemistry for validating their presence and involvement in OSCC pathways heralding invasion and metastasis. Four genes POSTN, TNC, CAV1 and FSCN1 were identified. A protein–protein interaction network analysis teamed with pathway analysis led us to propose the role of the identified genes in invasion and metastasis in OSCC. Further analyses of archived FFPE blocks of various grades of oral cancer was carried out using TMT-based mass spectrometry and immunohistochemistry. Results of this study expressed a strong communiqué and interrelationship between these candidate genes. This study emphasizes the significance of a molecular biomarker panel as a diagnostic tool and its correlation with the invasion and metastatic pathway of OSCC. An insight into the probable association of CAF's and these biomarkers in the evolution and malignant transformation of OSCC further magnifies the molecular-biological spectrum of OSCC tumour microenvironment.
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Wang L, Chen Y, Yan Y, Guo X, Fang Y, Su Y, Wang L, Pathak JL, Ge L. miR-146a Overexpression in Oral Squamous Cell Carcinoma Potentiates Cancer Cell Migration and Invasion Possibly via Targeting HTT. Front Oncol 2020; 10:585976. [PMID: 33282738 DOI: 10.3389/fonc.2020.585976] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 10/14/2020] [Indexed: 01/04/2023] Open
Abstract
Huntingtin (HTT) is one of the target genes of miR-146-a and regulates various cancer cell activities. This study aims to explore the miR-146a expression pattern in oral squamous cell carcinoma (OSCC) and its role and mechanism in OSCC progression and metastasis via targeting the HTT gene. OSCC tissue and non-cancerous matched tissue (NCMT) were obtained from 14 patients. OSCC cell lines and normal HOK cells were used to analyze migration and invasion assay. OSCC-induced miR-146a knockout mice (B6.Cg-Mir146tm1.1Bal) model was developed. Transwell cell migration/invasion and scratch wound assays were used to investigate the OSCC cell migration and invasion in vitro. Kaplan-Meier survival analysis was used to investigate the association of HTT expression patterns in cancer tissue with patient survival percentage and duration. Pearson's correlation analysis tested the association between miR-146a and HTT expression in OSCC tissues. miR-146a mimic and inhibitor transfection were performed to overexpress and knockdown the miR-146a in OSCC cells, respectively. miR-146a expression was highly upregulated in OSCC tissues and OSCC cell lines. Cancer cell migration/invasion was enhanced in miR-146a overexpressed cells and reduced in mi-R146a knockdowned cells. HTT expression was reduced in OSCC tissues and cell lines compared to NCMT and HOK cells, respectively. HTT expression was downregulated in miR-146a overexpressed OSCC cells and upregulated in miR-146a knockdowned OSCC cells. The expression pattern of miR-146a in OSCC cell lines and tissues was inversely correlated with HTT expression. Prediction of miRNA target analysis showed that HTT possesses the binding sites for miR-146a. HTT overexpression in OSCC tissues was associated with patients' higher survival percentage and duration. HTT knockdown in OSCC cells enhanced miR-146a expression and cell migration/invasion. Inducing OSCC in miR-146a knockout mice increased the HTT expression in tongue tissue and alleviated the cancer aggressiveness and epithelial damage. Overexpressed miR-146a in OSCC targets the HTT gene and enhances cancer cell migration/invasion unraveling the possible role of HTT in miR146a-mediated OSCC cell migration and invasion.
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Affiliation(s)
- Liping Wang
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Yunxin Chen
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Yongyong Yan
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China.,Institute of Oral Disease, Guangzhou Medical University, Guangzhou, China
| | - Xueqi Guo
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Ying Fang
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China
| | - Yucheng Su
- Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Lijing Wang
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China.,School of Life Science and Biopharmaceutics, Vascular Biology Research Institute, Guangdong Pharmaceutical University, Guangzhou, China
| | - Janak L Pathak
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China.,Institute of Oral Disease, Guangzhou Medical University, Guangzhou, China
| | - Linhu Ge
- Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China.,Institute of Oral Disease, Guangzhou Medical University, Guangzhou, China
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Jeng MJ, Sharma M, Sharma L, Huang SF, Chang LB, Wu SL, Chow L. Novel Quantitative Analysis Using Optical Imaging (VELscope) and Spectroscopy (Raman) Techniques for Oral Cancer Detection. Cancers (Basel) 2020; 12:E3364. [PMID: 33202869 DOI: 10.3390/cancers12113364] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 10/27/2020] [Accepted: 11/10/2020] [Indexed: 12/15/2022] Open
Abstract
Simple Summary Our study aims to develop a novel quantitative analysis method that can increase the oral cancer detection rate for screening oral cancer. We used two different optical techniques, a light-based detection technique (VELScope) and a vibrational spectroscopic technique (Raman spectroscopy). First, we analyzed and evaluated the performance of these two techniques individually using PCA–LDA, and PCA–QDA classifiers. The PCA–LDA of Raman spectroscopy had 82.9% accuracy, 80% sensitivity, and 85.7% specificity, while the region of interests on the autofluorescence images were differentiated with 90% accuracy, 100% sensitivity, and 80% specificity. Afterward, we combined both techniques and evaluated their performance. The combination of two optical techniques can differentiate the cancer and normal groups with 97.14% accuracy, 100% sensitivity, and 94.3% specificity. The main advantage of our study is that we can confirm our results by using two different techniques that are completely independent of each other. That is the reason that the combination of two techniques can increase the sensitivity and specificity. Abstract In this study, we developed a novel quantitative analysis method to enhance the detection capability for oral cancer screening. We combined two different optical techniques, a light-based detection technique (visually enhanced lesion scope) and a vibrational spectroscopic technique (Raman spectroscopy). Materials and methods: Thirty-five oral cancer patients who went through surgery were enrolled. Thirty-five cancer lesions and thirty-five control samples with normal oral mucosa (adjacent to the cancer lesion) were analyzed. Thirty-five autofluorescence images and 70 Raman spectra were taken from 35 cancer and 35 control group cryopreserved samples. The normalized intensity and heterogeneity of the 70 regions of interest (ROIs) were calculated along with 70 averaged Raman spectra. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to differentiate the cancer and control groups (normal). The classifications rates were validated using two different validation methods, leave-one-out cross-validation (LOOCV) and k-fold cross-validation. Results: The cryopreserved normal and tumor tissues were differentiated using the PCA–LDA and PCA–QDA models. The PCA–LDA of Raman spectroscopy (RS) had 82.9% accuracy, 80% sensitivity, and 85.7% specificity, while ROIs on the autofluorescence images were differentiated with 90% accuracy, 100% sensitivity, and 80% specificity. The combination of two optical techniques differentiated cancer and normal group with 97.14% accuracy, 100% sensitivity, and 94.3% specificity. Conclusion: In this study, we combined the data of two different optical techniques. Furthermore, PCA–LDA and PCA–QDA quantitative analysis models were used to differentiate tumor and normal groups, creating a complementary pathway for efficient tumor diagnosis. The error rates of RS and VELcope analysis were 17.10% and 10%, respectively, which was reduced to 3% when the two optical techniques were combined.
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11
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Karunakaran K, Muniyan R. Genetic alterations and clinical dimensions of oral cancer: a review. Mol Biol Rep 2020; 47:9135-48. [DOI: 10.1007/s11033-020-05927-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 10/16/2020] [Indexed: 12/19/2022]
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12
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Bashiri H, Rahmani H, Bashiri V, Módos D, Bender A. EMDIP: An Entropy Measure to Discover Important Proteins in PPI networks. Comput Biol Med 2020; 120:103740. [PMID: 32421645 DOI: 10.1016/j.compbiomed.2020.103740] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 03/30/2020] [Accepted: 03/30/2020] [Indexed: 12/24/2022]
Abstract
Discovering important proteins in Protein-Protein Interaction (PPI) networks has attracted a lot of attention in recent years. Most of the previous work applies different network centrality measures such as Closeness, Betweenness, PageRank and many others to discover the most influential proteins in PPI networks. Although entropy is a well-known graph-based method in computer science, according to our knowledge, it is not used in the biology domain for this purpose. In this paper, first, we annotate the human PPI network with available annotation data. Second, we introduce a new concept called annotation-context that describes each protein according to annotation data of its neighbors. Third, we apply an entropy measure to discover proteins with varied annotation-context. Empirical results indicate that our proposed method succeeded in (1) differentiating essential and non-essential proteins in PPI networks with annotation data; (2) outperforming centrality measures in the task of discovering essential nodes; (3) predicting new annotated proteins based on existing annotation data.
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Affiliation(s)
- Hamid Bashiri
- School of Computer engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran
| | - Hossein Rahmani
- School of Computer engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran.
| | - Vahid Bashiri
- School of Computer engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran
| | - Dezső Módos
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom
| | - Andreas Bender
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom
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Singh P, Rai A, Dohare R, Arora S, Ali S, Parveen S, Syed MA. Network-based identification of signature genes KLF6 and SPOCK1 associated with oral submucous fibrosis. Mol Clin Oncol 2020; 12:299-310. [PMID: 32190310 PMCID: PMC7058035 DOI: 10.3892/mco.2020.1991] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 10/08/2019] [Indexed: 12/16/2022] Open
Abstract
The molecular mechanism of oral submucous fibrosis (OSF) is yet to be fully elucidated. The identification of reliable signature genes to screen patients with a high risk of OSF and to provide oral cancer surveillance is therefore required. The present study produced a filtering criterion based on network characteristics and principal component analysis, and identified the genes that were involved in OSF prognosis. Two gene expression datasets were analyzed using meta-analysis, the results of which revealed 1,176 biologically significant genes. A co-expression network was subsequently constructed and weighted gene modules were detected. The pathway and functional enrichment analyses of the present study allowed for the identification of modules 1 and 2, and their respective genes, SPARC (osteonectin), cwcv and kazal like domain proteoglycan 1 (SPOCK1) and kruppel like factor 6 (KLF6), which were involved in the occurrence of OSF. The results revealed that both genes had a prominent role in epithelial to mesenchymal transition during OSF progression. The genes identified in the present study require further exploration and validation within clinical settings to determine their roles in OSF.
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Affiliation(s)
- Prithvi Singh
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Arpita Rai
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
- Department of Oral Medicine and Radiology, Faculty of Dentistry, Jamia Millia Islamia, New Delhi 110025, India
| | - Ravins Dohare
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Shweta Arora
- Translational Research Lab, Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Sher Ali
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Shama Parveen
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Mansoor Ali Syed
- Translational Research Lab, Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India
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Rivera C, Crisóstomo MF, Peña C, González-Díaz P, González-Arriagada WA. Oral lichen planus interactome reveals CXCR4 and CXCL12 as candidate therapeutic targets. Sci Rep 2020; 10:5454. [PMID: 32214134 DOI: 10.1038/s41598-020-62258-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Accepted: 03/12/2020] [Indexed: 01/03/2023] Open
Abstract
Today, we face difficulty in generating new hypotheses and understanding oral lichen planus due to the large amount of biomedical information available. In this research, we have used an integrated bioinformatics approach assimilating information from data mining, gene ontologies, protein–protein interaction and network analysis to predict candidate genes related to oral lichen planus. A detailed pathway analysis led us to propose two promising therapeutic targets: the stromal cell derived factor 1 (CXCL12) and the C-X-C type 4 chemokine receptor (CXCR4). We further validated our predictions and found that CXCR4 was upregulated in all oral lichen planus tissue samples. Our bioinformatics data cumulatively support the pathological role of chemokines and chemokine receptors in oral lichen planus. From a clinical perspective, we suggest a drug (plerixafor) and two therapeutic targets for future research.
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Jeng MJ, Sharma M, Chao TY, Li YC, Huang SF, Chang LB, Chow L. Multiclass classification of autofluorescence images of oral cavity lesions based on quantitative analysis. PLoS One 2020; 15:e0228132. [PMID: 32017775 PMCID: PMC6999883 DOI: 10.1371/journal.pone.0228132] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2019] [Accepted: 01/08/2020] [Indexed: 12/24/2022] Open
Abstract
Background Oral cancer is one of the most common diseases globally. Conventional oral examination and histopathological examination are the two main clinical methods for diagnosing oral cancer early. VELscope is an oral cancer-screening device that exploited autofluorescence. It yields inconsistent results when used to differentiate between normal, premalignant and malignant lesions. We develop a new method to increase the accuracy of differentiation. Materials and methods Five samples (images) of each of 21 normal mucosae, as well as 31 premalignant and 16 malignant lesions of the tongue and buccal mucosa were collected under both white light and autofluorescence (VELscope, 400-460 nm wavelength). The images were developed using an iPod (Apple, Atlanta Georgia, USA). Results The normalized intensity and standard deviation of intensity were calculated to classify image pixels from the region of interest (ROI). Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) classifiers were used. The performance of both of the classifiers was evaluated with respect to accuracy, precision, and recall. These parameters were used for multiclass classification. The accuracy rate of LDA with un-normalized data was increased by 2% and 14% and that of QDA was increased by 16% and 25% for the tongue and buccal mucosa, respectively. Conclusion The QDA algorithm outperforms the LDA classifier in the analysis of autofluorescence images with respect to all of the standard evaluation parameters.
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Affiliation(s)
- Ming-Jer Jeng
- Department of Electronic Engineering, Chang Gung University, Taoyuan, Taiwan
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Ting-Yu Chao
- Department of Electronic Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Ying-Chang Li
- Green Technology Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou, Taiwan
- Department of Public Health, Chang Gung University, Taoyuan, Taiwan
- * E-mail: (SFH); (LBC)
| | - Liann-Be Chang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou, Taiwan
- Green Technology Research Center, Chang Gung University, Taoyuan, Taiwan
- * E-mail: (SFH); (LBC)
| | - Lee Chow
- Department of Physics, University of Central Florida, Orlando, FL, United States of America
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Jeng MJ, Sharma M, Sharma L, Chao TY, Huang SF, Chang LB, Wu SL, Chow L. Raman Spectroscopy Analysis for Optical Diagnosis of Oral Cancer Detection. J Clin Med 2019; 8:jcm8091313. [PMID: 31461884 PMCID: PMC6780219 DOI: 10.3390/jcm8091313] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 08/17/2019] [Accepted: 08/22/2019] [Indexed: 12/11/2022] Open
Abstract
Raman spectroscopy (RS) is widely used as a non-invasive technique in screening for the diagnosis of oral cancer. The potential of this optical technique for several biomedical applications has been proved. This work studies the efficacy of RS in detecting oral cancer using sub-site-wise differentiation. A total of 80 samples (44 tumor and 36 normal) were cryopreserved from three different sub-sites: The tongue, the buccal mucosa, and the gingiva of the oral mucosa during surgery. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to classify the samples and the classifications were validated by leave-one-out-cross-validation (LOOCV) and k-fold cross-validation methods. The normal and tumor tissues were differentiated under the PCA-LDA model with an accuracy of 81.25% (sensitivity: 77.27%, specificity: 86.11%). The PCA-QDA classifier model differentiated these tissues with an accuracy of 87.5% (sensitivity: 90.90%, specificity: 83.33%). The PCA-QDA classifier model outperformed the PCA-LDA-based classifier. The model studies revealed that protein, amino acid, and beta-carotene variations are the main biomolecular difference markers for detecting oral cancer.
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Affiliation(s)
- Ming-Jer Jeng
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
| | - Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan
| | - Lokesh Sharma
- AI Innovation Research Center, Chang Gung University, Taoyuan 333, Taiwan
| | - Ting-Yu Chao
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan.
- Department of Public Health, Chang Gung University, Taoyuan 333, Taiwan.
| | - Liann-Be Chang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan.
- Green Technology Research Center, Chang Gung University, Taoyuan 333, Taiwan.
| | - Shih-Lin Wu
- AI Innovation Research Center, Chang Gung University, Taoyuan 333, Taiwan
- Department of Cardiology, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 333, Taiwan
| | - Lee Chow
- Department of Physics, University of Central Florida, Orlando, FL 32816, USA
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Li Z, Jiang C, Yuan Y. TCGA based integrated genomic analyses of ceRNA network and novel subtypes revealing potential biomarkers for the prognosis and target therapy of tongue squamous cell carcinoma. PLoS One 2019; 14:e0216834. [PMID: 31141819 PMCID: PMC6541473 DOI: 10.1371/journal.pone.0216834] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 04/29/2019] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVES The study aimed to investigate the ceRNA network in biological development of Tongue Squamous Cell Carcinoma (TSCC) and to identify novel molecular subtypes of TSCC to screen potential biomarkers for target therapy and prognosis by using integrated genomic analysis based on The Cancer Genome Atlas (TCGA) database. MATERIAL AND METHODS Data on gene expressions were downloaded from TCGA and GEO database. Differentially expressed RNAs(DERNAs) were shown by DESeq2 package in R. Functional enrichment analysis of DEmRNAs was performed using clusterprofilers in R. PPI network was established by referring to String website. Survival analysis of DERNAs was carried out by survival package in R. Interactions among mRNAs, miRNAs and lncRNAs were obtained from Starbase v3.0 and used to construct ceRNA network. Consensus Cluster Plus package was applied to identify molecular subtypes. All key genes were validated by comparing them with GEO microarray data. Statistical analyses of clinical features among different subtypes were performed using SPSS 22.0. RESULTS A total of 2907 mRNAs (1366 up-regulated and 1541 down-regulated), 191miRNAs (98 up-regulated and 93 down-regulated) and 1831 lncRNAs (1151 up-regulated and 680 down-regulated) were identified from tumor and normal tissues. A ceRNA network was successfully constructed and 15 DEmRNAs, 1 DEmiRNA, 2 DElncRNAs associated with prognosis were employed. Furthermore, we firstly identified 2 molecular subtypes, basal and differentiated, and found that differentiated subtype consumed less alcohol and was related to a better overall survival. CONCLUSION The study constructed a ceRNA network and identified molecular subtypes of TSCC, and our findings provided a novel insight into this intractable cancer and potential therapeutic targets and prognostic indicators.
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Affiliation(s)
- Zaiye Li
- Department of Oral and Maxillofacial Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Canhua Jiang
- Department of Oral and Maxillofacial Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yongxiang Yuan
- Department of Oral and Maxillofacial Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
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Ren J, Shang L, Wang Q, Li J. Ranking Cancer Proteins by Integrating PPI Network and Protein Expression Profiles. Biomed Res Int 2019; 2019:3907195. [PMID: 30723737 DOI: 10.1155/2019/3907195] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 12/06/2018] [Accepted: 12/12/2018] [Indexed: 12/16/2022]
Abstract
Proteomics, the large-scale analysis of proteins, is contributing greatly to understanding gene function in the postgenomic era. However, disease protein ranking using shotgun proteomics data has not been fully evaluated. In this study, we prioritized disease-related proteins by integrating the protein-protein interaction (PPI) network and protein differential expression profiles from colon and rectal cancer (CRC) or breast cancer (BC) proteomics. We applied Local Ranking (LR) and Global Ranking (GR) methods in network with three kinds of protein sets as a priori knowledge, which were known disease proteins (KDPs) that were collected from the Online Mendelian Inheritance in Man (OMIM) database, differentially expressed proteins (DEPs), and the collection of KDPs and their direct neighborhood with differential expression (eKDPs). The cross-validations showed that GR method outperformed LR method while using eKDPs as the initial training showed significantly higher accuracy compared to using the other two a priori sets. And then we validated the top ranked proteins using RNAi-based loss-of-function screens in the DepMap database. The results showed that 75% of top 20 proteins in CRC are necessary for tumor survival. In summary, the network-based Global Ranking with protein differential expression can efficiently prioritize cancer-related proteins and discover new candidate cancer genes or proteins.
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Lee S, Chun HS, Lee J, Park HJ, Kim KT, Kim CH, Yoon S, Kim WK. Plausibility of the zebrafish embryos/larvae as an alternative animal model for autism: A comparison study of transcriptome changes. PLoS One 2018; 13:e0203543. [PMID: 30180205 PMCID: PMC6122816 DOI: 10.1371/journal.pone.0203543] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 08/22/2018] [Indexed: 11/25/2022] Open
Abstract
Autism spectrum disorder (ASD) is a serious neurodevelopmental disorder characterized by impaired or abnormal social interaction and communication and by restricted and repetitive behaviour. ASD is highly prevalent in Asia, Europe, and the United States, and the frequency of ASD is growing each year. Recent epidemiological studies have indicated that ASD may be caused or triggered by exposure to chemicals in the environment, such as those in the air or water. Thus, toxicological studies are needed to examine chemicals that might be implicated. However, the experimental efficiency of existing experimental models is limited, and many models represent challenges in terms of animal welfare. Thus, alternative ASD animal models are necessary. To address this, we examined the efficacy of the zebrafish embryo/larva as an alternative model of ASD. Specifically, we exposed zebrafish to valproic acid (0, 12.5, 25, 50, or 100 μM), which is a chemical known to induce autism-like effects. We then analysed subsequent developmental, behavioural, and transcriptomic changes. We found that 100 μM and 50 μM valproic acid decreased the hatching rate and locomotor activity of zebrafish embryos/larvae. Transcriptomic analysis revealed significant alterations in a number of genes associated with autism, such as adsl, mbd5, shank3, and tsc1b. Additionally, we found changes in gene ontology that were also reported in previous studies. Our findings indicate that zebrafish embryos/larvae and humans with ASD might have common physiological pathways, indicating that this animal model may represent an alternative tool for examining the causes of and potential treatments for this illness.
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Affiliation(s)
- Sangwoo Lee
- System Toxicology Research Center, Korea Institute of Toxicology, Daejeon, Republic of Korea
| | - Hang-Suk Chun
- System Toxicology Research Center, Korea Institute of Toxicology, Daejeon, Republic of Korea
| | - Jieon Lee
- System Toxicology Research Center, Korea Institute of Toxicology, Daejeon, Republic of Korea
| | - Han-Jin Park
- Predictive Model Research Center, Korea Institute of Toxicology, Daejeon, Republic of Korea
| | - Ki-Tae Kim
- Department of Environmental Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea
| | - Cheol-Hee Kim
- Department of Biology, Chungnam National University, Daejeon, Republic of Korea
| | - Seokjoo Yoon
- System Toxicology Research Center, Korea Institute of Toxicology, Daejeon, Republic of Korea
| | - Woo-Keun Kim
- System Toxicology Research Center, Korea Institute of Toxicology, Daejeon, Republic of Korea
- * E-mail:
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Bhushan A, Singh A, Kapur S, Borthakar BB, Sharma J, Rai AK, Kataki AC, Saxena S. Identification and Validation of Fibroblast Growth Factor 12 Gene as a Novel Potential Biomarker in Esophageal Cancer Using Cancer Genomic Datasets. OMICS 2018; 21:616-631. [PMID: 29049013 DOI: 10.1089/omi.2017.0116] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Esophageal squamous cell carcinoma (ESCC) has a complex, multifactorial etiology in which environmental, geographical, and genetic factors play major roles. It is the second most common cancer among men and the fourth most common among women in India, with a particularly high prevalence in Northeast India. In this study, an integrative in silico [DAVID, NCG5.0, Oncomine, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas (TCGA)] approach was used to identify the potential biomarkers by using the available three genomic datasets on ESCC from Northeast India followed by its in vitro functional validation. Fibroblast Growth Factor 12 (FGF12) gene was overexpressed in ESCC. The upregulation of FGF12 was also observed on ESCC of TCGA OncoPrint portal, whereas very low expression of FGF12 gene was mapped in normal esophageal tissue on the GTEx database. Silencing of FGF12 showed significant inhibition in activity of tumor cell proliferation, colony formation, and cell migration. The upregulation of FGF12 showed significantly reduced survival in ESCC patients. The protein interaction analysis of FGF12 found the binding with MAPK8IP2 and MAPK13. High expression of FGF12 along with MAPK8IP2, and MAPK13 proteins correlate with poor survival in ESCC patients. Tissue microarray also showed expression of these proteins in patients with ESCC. These results indicate that FGF12 has a potential role in ESCC and suggest that cancer genomic datasets with application of in silico approaches are instrumental for biomarker discovery research broadly and specifically, for the identification of FGF12 as a putative biomarker in ESCC.
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Affiliation(s)
- Ashish Bhushan
- 1 National Institute of Pathology (ICMR) , New Delhi, India .,2 Faculty of Health and Biomedical Sciences, Symbiosis International University , Pune, India
| | - Avninder Singh
- 1 National Institute of Pathology (ICMR) , New Delhi, India
| | - Sujala Kapur
- 1 National Institute of Pathology (ICMR) , New Delhi, India
| | | | | | - Avdhesh K Rai
- 3 Dr. B. Borooah Cancer Institute (BBCI) , Guwahati, India
| | - Amal C Kataki
- 3 Dr. B. Borooah Cancer Institute (BBCI) , Guwahati, India
| | - Sunita Saxena
- 1 National Institute of Pathology (ICMR) , New Delhi, India
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Yang S, Xu Y, Wang Y, Ren F, Li S, Ding W, Ma Y, Zhang W. The Biological Properties and Potential Interacting Proteins of d-Alanyl-d-alanine Ligase A from Mycobacterium tuberculosis. Molecules 2018; 23:E324. [PMID: 29401644 DOI: 10.3390/molecules23020324] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 01/23/2018] [Accepted: 02/01/2018] [Indexed: 12/12/2022] Open
Abstract
(1) Background: d-alanine-d-alanine ligase (DdlA), an effective target for drug development to combat against Mycobacterium tuberculosis (Mtb), which threatens human health globally, supplies a substrate of d-alanyl-d-alanine for peptidoglycan crosslinking by catalyzing the dimerization of two d-alanines. To obtain a better understanding of DdlA profiles and develop a colorimetric assay for high-throughput inhibitor screening, we focused on explicating and characterizing Tb-DdlA. (2) Methods and Results: Rv2981c (ddlA) was expressed in Escherichia coli, and the purified Tb-DdlA was identified using (anti)-polyhistidine antibody followed by DdlA activity confirmation by measuring the released orthophosphate via colorimetric assay and the yielded d-alanyl-d-alanine through high performance thin layer chromatography (HP-TLC). The kinetic assays on Tb-DdlA indicated that Tb-DdlA exhibited a higher affinity to ATP (KmATP: 50.327 ± 4.652 μmol/L) than alanine (KmAla: 1.011 ± 0.094 mmol/L). A colorimetric assay for Tb-DdlA activity was developed for high-throughput screening of DdlA inhibitors in this study. In addition, we presented an analysis on Tb-DdlA interaction partners by pull-down assay and MS/MS. Eight putative interaction partners of Tb-DdlA were identified. (3) Conclusions: Our dataset provided a valuable resource for exploring Tb-DdlA biology, and developed an easy colorimetric assay for screening of Tb-DdlA inhibitors.
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Behera PM, Kumar R, Dixit A. Prediction and validation of potential candidate genes for type II diabetes mellitus using bioinformatics analysis. Can J Biotech 2017. [DOI: 10.24870/cjb.2017-a225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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