Multiple Comprehensive Analyses Identify Lysine Demethylase KDM as a Potential Therapeutic Target for Pancreatic Cancer.

Pancreatic cancer (PC) is a challenging and heterogeneous disease with a high mortality rate. Despite advancements in treatment, the prognosis for PC patients remains poor, with a high chance of disease recurrence. Biomarkers are crucial for diagnosing cancer, predicting patient prognosis and selecting treatments. However, the current lack of effective biomarkers for PC could contribute to the insufficiency of existing treatments. These findings underscore the urgent need to develop novel strategies to fight this disease. This study utilized multiple comprehensive bioinformatic analyses to identify potential therapeutic target genes in PC, focusing on histone lysine demethylases (KDMs). We found that high expression levels of KDM family genes, particularly KDM1A, KDM5A and KDM5B, were associated with improved overall survival in the cohort. Furthermore, the infiltration of various immune cells, including B cells, neutrophils, CD8+ T cells, dendritic cells, and macrophages, was positively correlated with KDM1A, KDM5A, and KDM5B expression. Moreover, MetaCore pathway analysis revealed interesting connections between KDM1A and the cell cycle and proliferation, between KDM5A and DNA damage and double-strand break repair through homologous recombination, and between KDM5B and WNT/ß-catenin signaling. These findings suggest that KDM1A, KDM5A and KDM5B may serve as promising biomarkers and therapeutic targets for PC, a disease of high importance due to its aggressive nature and urgent need for novel biomarkers to improve diagnosis and treatment.

Comprehensive analysis of bulk and single-cell RNA sequencing data reveals Schlafen-5 (SLFN5) as a novel prognosis and immunity.

Recent advancements have elucidated the multifaceted roles of the Schlafen (SLFN) family, including SLFN5, SLFN11, SLFN12, SLFN13, and SLFN14, which are implicated in immunological responses. However, little is known about the roles of this gene family in relation to malignancy development. The current study aimed to explore the diagnostic and prognostic potential of Schlafen family genes in colorectal adenocarcinoma (COAD) through bioinformatics analysis. Leveraging advanced bioinformatics tools of bulk RNA-sequencing and single-cell sequencing, we conducted in-depth analyses of gene expressions, functional enrichment, and survival patterns of patients with colorectal cancer compared to normal tissue. Among Schlafen family genes, the transcription levels of SLFN5 in COAD tissues were significantly elevated and correlated with poor survival outcomes. Furthermore, SLFN5 regulated the immune response via Janus kinase (JAK)/signal transduction and activator of transcription (STAT)/interferon (IFN)-alpha/beta signaling. These chemokines in inflammation are associated with diabetes and metabolism, suggesting their involvement in altered cellular energetics for COAD progress. In addition, an immune cell deconvolution analysis indicated a correlation between SLFN5 expression and immune-related cell populations, such as regulatory T cells (Tregs). These findings highlighted the potential clinical significance of SLFN5 in COAD and provided insights into its involvement in the tumor microenvironment and immune regulation. Meanwhile, the drug discovery data of SFLN5 with potential targeted small molecules suggested its therapeutic potential for COAD. Collectively, the current research demonstrated that SFLN5 play crucial roles in tumor development and serve as a prospective biomarker for COAD.

Dysbindin Domain-Containing 1 in Prostate Cancer: New Insights into Bioinformatic Validation of Molecular and Immunological Features.

Prostate cancer (PCa) is one of the most prevalent cancers in men, yet its pathogenic pathways remain poorly understood. Transcriptomics and high-throughput sequencing can help uncover cancer diagnostic targets and understand biological circuits. Using prostate adenocarcinoma (PRAD) datasets of various web-based applications (GEPIA, UALCAN, cBioPortal, SR Plot, hTFtarget, Genome Browser, and MetaCore), we found that upregulated dysbindin domain-containing 1 (DBNDD1) expression in primary prostate tumors was strongly correlated with pathways involving the cell cycle, mitotic in KEGG, WIKI, and REACTOME database, and transcription factor-binding sites with the DBNDD1 gene in prostate samples. DBNDD1 gene expression was influenced by sample type, cancer stage, and promoter methylation levels of different cancers, such as PRAD, liver hepatocellular carcinoma (LIHC), and lung adenocarcinoma (LUAD). Regulation of glycogen synthase kinase (GSK)-3ß in bipolar disorder and ATP/ITP/GTP/XTP/TTP/CTP/UTP metabolic pathways was closely correlated with the DBNDD1 gene and its co-expressed genes in PCa. DBNDD1 gene expression was positively associated with immune infiltration of B cells, Myeloid-derived suppressor cell (MDSC), M2 macrophages, andneutrophil, whereas negatively correlated with CD8+ T cells, T follicular helper cells, M1 macrophages, and NK cells in PCa. These findings suggest that DBNDD1 may serve as a viable prognostic marker not only for early-stage PCa but also for immunotherapies.

Integrated bioinformatics approaches to investigate alterations in transcriptomic profiles of monkeypox infected human cell line model.

BACKGROUND: The recent re-emergence of the monkeypox (mpox) epidemic in nonendemic regions has raised concerns regarding a potential global outbreak. The mpox virus (MPV) is a smallpox-like virus belonging to the genus Orthopoxvirus (family: Poxviridae). Although studies suggest that MPV infection suppresses the Toll-like receptor-3- and tumor necrosis factor-α-related signaling pathways, whether MPV regulates other immune-related pathways remains unclear. METHODS: In this study, two distinct temporal patterns were used for establishing an MPV-infected human immortal epithelial cancer cell line (HeLa). These two durations 2 and 12 h of incubation were selected to identify the coregulated genes and pathways affected by MPV infection. RESULTS: The use of the Gene Ontology framework, Kyoto Encyclopedia of Genes and Genome database, and MetaCore software yielded valuable insights. Specifically, various pathways were found to be enriched in HeLa cells infected with MPV for 2 and 12 h. These pathways included Notch, CD40, CD95, hypoxia-inducible factor-1-α, interleukin (IL)- 1, IL-6, phosphoinositide 3-kinase, nuclear factor-κB, mitogen-activated protein kinase, and oxidative stress-induced signalling pathways. Clusters and pathways of metabolism and viral replication cycles were significantly associated with the 2-hour infection group. This association was identified based on the regulation of genes such as HSPG2, RHPN2, MYL1, ASPHD2, CA9, VIPR1, SNX12, MGC2752, SLC25A1, PEX19, and AREG. Furthermore, clusters and pathways related to immunity and cell movement were found to be associated with the 12-hour infection group. This association was identified based on the regulation of genes such as C1orf21, C19orf48, HRK, IL8, GULP1, SCAND2, ATP5C1, FEZ1, SGSH, TACC2, CYP4X1, MMP1, CPB1, P2RY13, WDR27, PRPF4, and ENDOD1. CONCLUSIONS: This study can improve our understanding of the mechanisms underlying the pathophysiology and post-infection sequelae of mpox. Our findings provide valuable insights into the various modes of MPV infection.

Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies.

Glioblastoma multiforme (GBM) is one of the most aggressive cancers with a low overall survival rate. The treatment of GBM is challenging due to the presence of the blood-brain barrier (BBB), which hinders drug delivery. Invasive procedures alone are not effective at completely removing such tumors. Hence, identifying the crucial pathways and biomarkers for the treatment of GBM is of prime importance. We conducted this study to identify the pathways associated with GBM. We used The Cancer Genome Atlas (TCGA) GBM genomic dataset to identify differentially expressed genes (DEGs). We investigated the prognostic values of the guanine nucleotide-binding protein G(i) alpha subunit (GNAI) family of genes in GBM using a Chinese Glioma Genome Atlas (CGGA) dataset. Within this dataset, we observed the association in the tumor microenvironment between the gene expression of GNAI subunit 3 (GNAI3) and a poor prognosis. MetaCore and gene ontology (GO) analyses were conducted to explore the role of GNAI3 in co-expressed genes and associated signaling pathways using a transcript analysis. Notable pathways included "Cytoskeleton remodeling regulation of actin cytoskeleton organization by the kinase effectors of Rho GTPases" and "Immune response B cell antigen receptor (BCR) pathway". A single-cell analysis was used to assess GNAI3 expression in GBM. The results demonstrated that GNAI family genes, specifically GNAI3, were significantly associated with carcinogenesis and malignancy in GBM patients. Our findings suggest that the GNAI3 gene holds potential as a prognostic biomarker for GBM.