Functions of the identified genes that were involved in gene networks were cellular development, cell growth and proliferation, cellular movement, cell-cell signaling and interaction, humoral immune response, protein synthesis, cell death and survival, cell population and organization, organismal injury and abnormalities, molecular transport, and small-molecule biochemistry. The data suggest new networks that have important functions as humoral immune response and organismal injury/abnormalities. Future analyses may facilitate proteomic profiling analyses to identify gene-expression patterns related to clinical outcome.

Background:To elucidate molecular signatures of chronic periodontitis (CP) using gingival tissue samples through omics-based whole-genome transcriptomic and whole protein profiling.Methods: Gingival tissues from 18 CP and 25 controls were analyzed using gene expression microarrays to identify gene expression patterns and the proteins isolated from these samples were subjected to comparative proteomic analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data from transcriptomics and proteomics were integrated to reveal common shared genes and proteins. Results:The most upregulated genes in CP compared with controls were found as MZB1, BMS1P20, IGLL1/IGLL5, TNFRSF17, ALDH1A1, KIAA0125, MMP7, PRL, MGC16025, ADAM11, and the most upregulated proteins in CP compared with controls were BPI, ITGAM, CAP37, PCM1, MMP-9, MZB1, UGTT1, PLG, RAB1B, HSP90B1. Functions of the identified genes were involved cell death/survival, DNA replication, recombination/repair, gene expression, organismal development, cell-tocell signaling/interaction, cellular development, cellular growth/proliferation, cellular assembly/organization, cellular function/maintenance, cellular movement, B-cell development, and identified proteins were involved in protein folding, response to stress, single-organism catabolic process, regulation of peptidase activity, and negative regulation of cell death. The integration and validation analysis of the transcriptomics and proteomics data revealed two common shared genes and proteins, MZB1 and ECH1. Conclusion:Integrative data from transcriptomics and proteomics revealed MZB1 as a potent candidate for chronic periodontitis.

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BackgroundOur previous study explored the molecular signatures of generalized aggressive periodontitis (GAgP) using gingival tissues through omics‐based‐whole‐genome transcriptomic analysis. This continuation study aimed to investigate the whole protein profiling of these gingival samples through liquid chromatography‐mass spectroscopy/mass spectroscopy (LC‐MS/MS) analysis and to validate the identified proteins through immunohistochemistry to provide further evidence for the quality of the results.MethodsIn previous study, gene expression patterns were identified in gingival tissues from 23 GAgP and 25 control individuals. In the current study, comparative proteomic analysis was performed on isolated proteins from the same study groups using LC‐MS/MS analysis. The data from the transcriptomics study published before and the proteomics data were integrated to reveal any common genes and proteins. Additionally, immunohistochemical analysis was conducted to further investigate the findings.ResultsThe most upregulated proteins in patients compared to controls were ITGAM, AZU1, MMP9, BPI, UGGG1, MZB1, TRFL, PDIA6, PRDX4, and PLG. The top six pathways associated with these proteins were involved in innate immune system, post‐translational protein phosphorylation, interleukin‐4 and ‐13 signaling, toll‐like receptors cascades, and extracellular matrix organization. Based on the integration and validation analysis of transcriptomics and proteomics data, as well as immunohistochemical analysis, MZB1 was identified as a shared gene and protein that were upregulated in the patients.ConclusionsMZB1 is a protein that is involved in the development of B cells and the production of antibodies. Its upregulation in periodontitis suggests that there may be a dysregulation of the immune response in this condition, and MZB1 may be a potent biomarker for periodontitis.

Introduction: Breast cancer is the most prevalent malignancy in women worldwide. Although pathogenic variants in the BRCA1/2 genes are responsible for the majority of hereditary breast cancer cases, a substantial proportion of patients are negative for pathogenic variations in these genes. In cancers, the signal transduction pathways of the cell are usually affected first. Therefore, this study aimed to detect and classified genetic variations in non-BRCA signaling genes and investigate the underlying genetic causes of susceptibility to breast cancer. Methods: Ninety-six patients without pathogenic variants in the BRCA1/2 genes who met the inclusion criteria were enrolled in the study, and 34 genes were analyzed using next-generation sequencing (NGS) for genetic analysis.Results: Based on the ClinVar database or American College of Medical Genetics criteria, a total of 55 variants of 16 genes were detected in 43 (44.8%) of the 96 patients included in the study. The pathogenic variants were found in the TP53, CHEK2, and RET genes, whereas the likely pathogenic variants were found in the FGFR1, FGFR3, EGFR, and NOTCH1 genes. Conclusion:The examination of signaling genes in patients who met the established criteria for hereditary breast cancer but were negative for BRCA1/2 pathogenic variants provided additional information for approximately 8% of the families. The results of the present study suggest that NGS is a powerful tool for investigating the underlying genetic causes of occurrence and progression of breast cancer.