The local immune system of the lungs is essential for the defense against pathogens, and respiratory bacterial infections remain a major cause of mortality in patients with lower respiratory tract diseases. However, the precise mechanisms underlying immune–pathogen interactions and the modulatory roles of commensal bacteria remain incompletely understood. This review discusses the mechanisms of immune recognition and inflammatory responses during bacterial respiratory bacterial infections, highlighting the importance of pattern recognition receptors, including toll-like receptors, nucleotide oligomerization domain-like receptors, and C-type lectin receptors in detecting pathogens and triggering immune signaling pathways. We also explore how commensal bacteria influence the respiratory immune microenvironment and discuss the complex interplay among pathogenic bacteria, commensals, and the host pulmonary immune system. This analysis provides a theoretical foundation for the development of targeted therapeutics against bacterial respiratory infections.

The immune-related genes in the colorectal cancer (CRC) microenvironment are closely associated with patient prognosis and the efficacy of immunotherapy. In this study, a CRC risk model was established utilizing the expression profiles of immune-related genes. The risk prediction framework for CRC was created by integrating clinical and transcriptomic data through machine learning techniques. We incorporated 13 core immune-related genes (IL18BP, RSAD2, G0S2, SIGLEC1, SFRP2, IFI44L, ISG20, IFIT1, OLR1, SAMHD1, HK3, PTAFR, and CSF1), constructed a prognostic model and established Immune Response-related Risk Score (IRRS) model in CRC. IRRS strongly correlated with cancer staging, immune cell infiltration, immune cell activation, and the expression of genes associated with immunotherapy targets. Furthermore, this IRRS model outperformed the Tumor Immune Dysfunction and Exclusion (TIDE) tool in predicting immunotherapy response. Therefore, by integrating patient clinical and transcriptomic data and applying machine learning algorithms, we developed a predictive model with enhanced accuracy and clinical utility for risk stratification and immunotherapy response prediction in CRC patients.

The local immune defenses of respiratory system play a crucial role in safeguarding against pathogens and eliminating infected cells. In this article, we review the current knowledge regarding the establishment and regulation of local immune responses within the lungs, with a particular focus on the formation of inducible bronchus-associated lymphoid tissue (iBALT), which has demonstrated a capacity to mount protective immune responses against several pathogens, including influenza virus, severe acute respiratory syndrome coronavirus (SARS-CoV)/SARS-CoV-2, and Mycobacterium tuberculosis (Mtb). Furthermore, we explore the development and regulation of long-term immune memory within the lungs, which may be facilitated by iBALT. This review aims to provide a summary of potential targets within iBALT for pathogen defense and vaccine design.