Identification of The Immune Subtype Among Muscle-invasive Bladder Cancer Patients by Multiple Datasets

Background: Immunotherapies including PD-1/PD-L1 antibodies have been approved for the treatment of Muscle-invasive Bladder Cancer (MIBC) patients. However, immunotherapies could only be beneficial for about 20% MIBC patients. Thus, identification of the immune subtype is becoming increasingly important. This study aimed to explore the immune subtype by analyzing the gene expression profiles. Methods: A total of 6 datasets including (GSE13507, GSE31684, GSE32548, GSE32894, GSE69795, and TCGA-BLCA) were downloaded. The gene expression profiles from different datasets were combined since the batch effects were removed. We performed unsupervised clustering analysis to identify the immune subtype by the combined gene expression profiles. The tumor-infiltration levels of 22 immune cells, immune scores, and tumor purity were calculated, and the survival analysis was performed to investigate the prognosis difference between immune subtypes. The enriched pathways for each immune subtype were obtained. Results: We identified four novel immune subtypes (referred to S1, S2, S3, and S4) among MIBC patients. We found that S1 was enriched in immune scores had the best prognosis. In contrast, S3 was poor in immune scores and had the worst prognosis. Subtype S1, S2, S3, and S4 were enriched in immune-related pathways, extracellular matrix-related pathways, metabolism-related pathways, and cancer-related pathways, respectively. Conclusion: The current study suggests that the immune subtypes based on gene expression profiles could contribute to select the appropriate MIBC patient for immunotherapies

Novel high-risk missense mutations identification in FAT4 gene causing Hennekam syndrome and Van Maldergem syndrome 2 through molecular dynamics simulation

Hennekam syndrome (HS) is an autosomal recessive disease in the pathogenesis of which lymphangiectasia and lymphedema plays a key role. HS is associated with mutations in CCBE1, FAT4, and ADAMTS3 proteins that somehow affect the activation of the primary lymphangiogenic growth factor VEGF-C. We used several in silico methods to test this theory. According to NCBI, FAT4 gene contains 3,343 non-synonymous SNPs, of which 298 were predicted to be deleterious using SIFT and Polyphen2. These 298 SNPs were further studied using various mutation prediction tools. Our results showed that eleven nsSNPs (D2978G, V986D, Y1912C, R4799C, D1022G, G4786R, D2439E, E2426Q, R4643C, N1309I, and Y2909H) detected by these tools are deleterious. Additionally, three mutations in FAT4 gene (rs12650153, rs1567047, and rs1039808) in patient suspected with HS were discovered through candidate variant filtering of whole-exome sequencing, and in silico study of these mutations revealed that these are highly destabilizing the protein structure and function. Using molecular dynamics simulation (MDS) we focused on the mutations (11 mutations predicted by our insilco study, 3 reported in the patient and 5 already published mutations for HS and VMS), while one mutation (G4786R) was detected in the MPDZ domain. The RMSD and RMSF supports the destability of mutant protein compared to wild type. The mutations found in this cohort of studies have not previously been reported for HS. These mutations may contribute to better understanding of disease predisposition associated with FAT4 Cadherin-like domain activation and further aid to effective approaches for diagnosis and treatment of the disorder

Recent Advances in Genomics-Based Approaches for the Development of Intracellular Bacterial Pathogen Vaccines

Infectious diseases continue to be a leading cause of morbidity and mortality worldwide. The majority of infectious diseases are caused by intracellular pathogenic bacteria (IPB). Historically, conventional vaccination drives have helped control the pathogenesis of intracellular bacteria and the emergence of antimicrobial resistance, saving millions of lives. However, in light of various limitations, many diseases that involve IPB still do not have adequate vaccines. In response to increasing demand for novel vaccine development strategies, a new area of vaccine research emerged following the advent of genomics technology, which changed the paradigm of vaccine development by utilizing the complete genomic data of microorganisms against them. It became possible to identify genes related to disease virulence, genetic patterns linked to disease virulence, as well as the genetic components that supported immunity and favorable vaccine responses. Complete genomic databases, and advancements in transcriptomics, metabolomics, structural genomics, proteomics, immunomics, pan-genomics, synthetic genomics, and population biology have allowed researchers to identify potential vaccine candidates and predict their effects in patients. New vaccines have been created against diseases for which previously there were no vaccines available, and existing vaccines have been improved. This review highlights the key issues and explores the evolution of vaccines. The increasing volume of IPB genomic data, and their application in novel genome-based techniques for vaccine development, were also examined, along with their characteristics, and the opportunities and obstacles involved. Critically, the application of genomics technology has helped researchers rapidly select and evaluate candidate antigens. Novel vaccines capable of addressing the limitations associated with conventional vaccines have been developed and pressing healthcare issues are being addressed