Automatic module selection from several microarray gene expression studies

S. Systems and computational analysis of gene expression datasets reveals GRB-2 suppression as an acute immunomodulatory response against enteric infections in endemic settings

Introduction

Enteric infections are a major cause of under-5 (age) mortality in low/middle-income countries. Although vaccines against these infections have already been licensed, unwavering efforts are required to boost suboptimalefficacy and effectiveness in regions that are highly endemic to enteric pathogens. The role of baseline immunological profiles in influencing vaccine-induced immune responses is increasingly becoming clearer for several vaccines. Hence, for the development of advanced and region-specific enteric vaccines, insights into differences in immune responses to perturbations in endemic and non-endemic settings become crucial.

Materials and methods

For this reason, we employed a two-tiered system and computational pipeline (i) to study the variations in differentially expressed genes (DEGs) associated with immune responses to enteric infections in endemic and non-endemic study groups, and (ii) to derive features (genes) of importance that keenly distinguish between these two groups using unsupervised machine learning algorithms on an aggregated gene expression dataset. The derived genes were further curated using topological analysis of the constructed STRING networks. The findings from these two tiers are validated using multilayer perceptron classifier and were further explored using correlation and regression analysis for the retrieval of associated gene regulatory modules.

Results

Our analysis reveals aggressive suppression of GRB-2, an adaptor molecule integral for TCR signaling, as a primary immunomodulatory response against S. typhi infection in endemic settings. Moreover, using retrieved correlation modules and multivariant regression models, we found a positive association between regulators of activated T cells and mediators of Hedgehog signaling in the endemic population, which indicates the initiation of an effector (involving differentiation and homing) rather than an inductive response upon infection. On further exploration, we found STAT3 to be instrumental in designating T-cell functions upon early responses to enteric infections in endemic settings.

Conclusion

Overall, through a systems and computational biology approach, we characterized distinct molecular players involved in immune responses to enteric infections in endemic settings in the process, contributing to the mounting evidence of endemicity being a major determiner of pathogen/vaccine-induced immune responses. The gained insights will have important implications in the design and development of region/endemicity-specific vaccines.

Comprehensive Analysis of Tumor Immune Microenvironment Characteristics for the Prognostic Prediction and Immunotherapy of Oral Squamous Cell Carcinoma

Background: Oral squamous cell carcinoma (OSCC) is the most common cancer of oral and maxillofacial region. A recent clinical research has shown that tumor immune microenvironment (TIME)cells are closely related to immunotherapy sensitivity and OSCC prognosis. Nonetheless, a comprehensive analysis of TIME in OSCC has not been reported.

Methods: Bioinformatics and computational algorithms were employed to determine the significance of TIME cells in 257 OSCC patients. TIME scores were measured by three TIME models, and then used to evaluate the prognosis of OSCC patients.

Results: High TIME score was characterized by better prognosis in OSCC patients less than 60 years old, overexpression of immunotherapy targets (e.g., PD-1 and CLTA-4), and higher T-cell activity to inhibit tumor growth. Besides, poor prognosis was associated with low time score.

Conclusion: TIME score exhibited potential as a prognostic biomarker and an indicator in predict immunotherapeutic outcomes. Through the understanding of TIME model, this study can provide a better scheme for immunotherapy as the effective treatment of OSCC patients in the future.