Simin Li1, Xiangqiong Liu2, Yu Zhou3, Aneesha Acharya4, Vuk Savkovic5, Congling Xu6, Ning Wu7, Yupei Deng8, Xianda Hu9, Hanluo Li5, Rainer Haak1, Jana Schmidt1, Wei Shang10, Hongying Pan11, Ren Shang12, Yang Yu13, Dirk Ziebolz14, Gerhard Schmalz1. 1. Department of Cariology, Endodontology and Periodontology, University Leipzig, Liebigstr. 12, 04103 Leipzig, Germany. 2. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China; Shanghai Genomap Technologies, Kongjiang Road 1500, Yangpu District, Shanghai, China. 3. Department of Orthopedics, Civil Aviation Hospital of Shanghai, Shanghai, China. 4. Faculty of Dentistry, University of Hong Kong, Hong Kong, China; Dr D Y Patil Dental College and Hospital, Dr D Y Patil Vidyapeeth, Pimpri, Pune, India. 5. Saxon Incubator for Clinical Translation (SIKT), University of Leipzig, Germany. 6. State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai, China. 7. Ellen Institute for Dental Research and Education, Clinic of Laser Dentistry and Implantology, Arzbergstrasse 30, Steinbach-Hallenberg, Germany. 8. Shanghai Genomap Technologies, Kongjiang Road 1500, Yangpu District, Shanghai, China. 9. Beijing Tibetan Hospital, China Tibetology Research Center, 218 Anwaixiaoguanbeili Street, Chaoyang, Beijing 100029, China. 10. Department of Stomatology, The Heping Affiliated Hospital of Changzhi Medical College, Changzhi City, Shanxi Province, China. 11. School of Dentistry, University of Michigan, USA. 12. Department of Prosthodontics, Stomatological Hospital, Southern Medical University, Guangzhou, Guangdong Province, China. 13. Department of Periodontology, The Stomatology Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China. 14. Department of Cariology, Endodontology and Periodontology, University Leipzig, Liebigstr. 12, 04103 Leipzig, Germany. Electronic address: Dirk.Ziebolz@medizin.uni-leipzig.de.
Abstract
OBJECTIVES: To analyze bioinformatic datasets for detecting genetic and epigenetic mechanisms shared by chronic periodontitis (CP) and oral squamous cell carcinoma (OSCC). MATERIALS AND METHODS: Datasets from GEO and TCGA databases reporting mRNAs, miRNAs or methylation expression in human CP and OSCC tissues were analyzed. Differential expression, functional enrichment and protein-protein interaction (PPI) network analyses were performed. Differentially expressed miRNAs (DEmiRNAs) and genes (DEG) in CP and OSCC were determined. DEmiRNA-target and DEmiRNA-DEG networks were constructed. Directly and indirectly interacting cross-talk genes were screened, and their prediction accuracy and association with OSCC prognosis was determined. RESULTS: 3 DE-miRNAs (miR-375, miR-3609 and miR-3652) expressed in both CP and OSCC critically regulated most DEGs. Among 12 directly interacting cross-talk genes, NCAPH was significantly related with the prognosis of OSCC. NR2F2 had highest differential expression in CP and OSCC. Among 4 cross-talk genes (FN1, MPPED1, NDEL1, and NR2F2) differentially expressed in CP, 3 (FN1, MPPED1, NDEL1) were also expressed in OSCC. Among 12 indirectly interacting cross-talk genes differentially expressed in OSCC, 3 genes (CDCA8, HIST1H3J, and RAD51) were significantly related to its prognosis. Significant pathways involved in CP and OSCC included: chemokine receptors, class I PI3K signaling events, epithelial-to-mesenchymal transition and signaling events by VEGFR1 and VEGFR2, EGF receptor (ErbB1). CONCLUSION: Bioinformatic analysis of available datasets implicated 1 directly interacting cross-talk gene (NCAPH), 4 indirectly interacting cross-talk genes (NCAPH, NR2F2, FN1, and MPPED1) and 3 DE-miRNAs (hsa-miR-375, miR-3609 and miR-3652) as shared genetic and epigenetic expression patterns between CP and OSCC.
OBJECTIVES: To analyze bioinformatic datasets for detecting genetic and epigenetic mechanisms shared by chronic periodontitis (CP) and oral squamous cell carcinoma (OSCC). MATERIALS AND METHODS: Datasets from GEO and TCGA databases reporting mRNAs, miRNAs or methylation expression in human CP and OSCC tissues were analyzed. Differential expression, functional enrichment and protein-protein interaction (PPI) network analyses were performed. Differentially expressed miRNAs (DEmiRNAs) and genes (DEG) in CP and OSCC were determined. DEmiRNA-target and DEmiRNA-DEG networks were constructed. Directly and indirectly interacting cross-talk genes were screened, and their prediction accuracy and association with OSCC prognosis was determined. RESULTS: 3 DE-miRNAs (miR-375, miR-3609 and miR-3652) expressed in both CP and OSCC critically regulated most DEGs. Among 12 directly interacting cross-talk genes, NCAPH was significantly related with the prognosis of OSCC. NR2F2 had highest differential expression in CP and OSCC. Among 4 cross-talk genes (FN1, MPPED1, NDEL1, and NR2F2) differentially expressed in CP, 3 (FN1, MPPED1, NDEL1) were also expressed in OSCC. Among 12 indirectly interacting cross-talk genes differentially expressed in OSCC, 3 genes (CDCA8, HIST1H3J, and RAD51) were significantly related to its prognosis. Significant pathways involved in CP and OSCC included: chemokine receptors, class I PI3K signaling events, epithelial-to-mesenchymal transition and signaling events by VEGFR1 and VEGFR2, EGF receptor (ErbB1). CONCLUSION: Bioinformatic analysis of available datasets implicated 1 directly interacting cross-talk gene (NCAPH), 4 indirectly interacting cross-talk genes (NCAPH, NR2F2, FN1, and MPPED1) and 3 DE-miRNAs (hsa-miR-375, miR-3609 and miR-3652) as shared genetic and epigenetic expression patterns between CP and OSCC.
Authors: Allan Radaic; Sean Ganther; Pachiyappan Kamarajan; Jennifer Grandis; Sue S Yom; Yvonne L Kapila Journal: Periodontol 2000 Date: 2021-10 Impact factor: 7.589