Weighted gene coexpression network analysis and machine learning reveal oncogenome associated microbiome plays an important role in tumor immunity and prognosis in pan-cancer

An immune biomarker associated with EMT serves as a predictor for prognosis and drug response in bladder cancer

BACKGROUND

Bladder cancer (BLCA), which develops from the upper endometrial of the bladder, is the sixth most prevalent cancer across the globe. WDHD1 (WD repeat and HMG-box DNA binding protein 1 gene) directly affects signaling, the cell cycle, and the development of the cell skeleton. Uncertainty surrounds WDHD1's function in BLCA immunity and prognosis, though.

MATERIALS AND METHODS

Using weighed gene co-expression network analysis (WGCNA), initially, we first identified 32 risk factors in genes with differential expression for this investigation. Then, using a variety of bioinformatic techniques and experimental validation, we examined the connections between WDHD1 and BLCA expression, clinical pathological traits, WDHD1-related proteins, upper-skin-intermediate conversion (EMT), immune cell immersion, convergence factors, immune markers, and drug sensitivity.

RESULT

The findings demonstrated that we constructed a 32-gene risk-predicting model where WDHD1 was elevated as a representative gene expression in BLCA and related to a range of clinical traits. Furthermore, high WDHD1 expression was a standalone predictor associated with a worse survival rate. The most commonly recruited cells and their evolutionary patterns were highlighted to better comprehend WDHD1's function in cancer. High WDHD1 expression was associated with many aspects of immunology. Finally, the study found that individuals with high expression of WDHD1 were drug-sensitive to four different broad-spectrum anti-cancer drugs.

CONCLUSION

These results describe dynamic changes in the tumor microenvironment in BLCA and provide evidence for the hypothesis that WDHD1 is a novel biomarker of tumor development. WDHD1 may therefore be a useful target for the detection and management of BLCA.

Unveiling the gastric microbiota: implications for gastric carcinogenesis, immune responses, and clinical prospects

High-throughput sequencing has ushered in a paradigm shift in gastric microbiota, breaking the stereotype that the stomach is hostile to microorganisms beyond H. pylori. Recent attention directed toward the composition and functionality of this 'community' has shed light on its potential relevance in cancer. The microbial composition in the stomach of health displays host specificity which changes throughout a person's lifespan and is subject to both external and internal factors. Distinctive alterations in gastric microbiome signature are discernible at different stages of gastric precancerous lesions and malignancy. The robust microbes that dominate in gastric malignant tissue are intricately implicated in gastric cancer susceptibility, carcinogenesis, and the modulation of immunosurveillance and immune escape. These revelations offer fresh avenues for utilizing gastric microbiota as predictive biomarkers in clinical settings. Furthermore, inter-individual microbiota variations partially account for differential responses to cancer immunotherapy. In this review, we summarize current literature on the influence of the gastric microbiota on gastric carcinogenesis, anti-tumor immunity and immunotherapy, providing insights into potential clinical applications.

Dysconnectivity of the brain functional network and abnormally expressed peripheral transcriptional profiles in patients with anxious depression

BACKGROUND

Major depressive disorder (MDD) is a heterogeneous mental disorder, and accompanying anxiety symptoms, known as anxious depression (AD), are the most common subtype. However, the pathophysiology of AD may be distinct in depressed patients without anxiety (NAD) and remains unknown. This study aimed to investigate the relationship between functional connectivity and peripheral transcriptional profiles in patients with AD and NAD.

METHODS

Functional imaging data were collected to identify differences in functional networks among patients with AD (n = 66), patients with NAD (n = 115), and healthy controls (HC, n = 200). The peripheral transcriptional data were clustered as co-expression modules, and their associations with AD, AND, and HC were analyzed. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of the genes in the significant module were performed. Correlation analysis was performed to identify functional network-associated gene co-expression modules.

RESULTS

A network was identified which consisted of 23 nodes and 28 edges that were significantly different among three sample groups. The regions of the network were located in temporal and occipital lobe. Two gene co-expression modules were shown to be associated with NAD, and one of which was correlated with the disrupted network in the AD group. The biological function of this module was enriched in immune regulation pathways.

CONCLUSION

The results suggested that immune-related mechanisms were associated with functional networks in AD.