Interferon Regulatory Factor 4 Correlated With Immune Cells Infiltration Could Predict Prognosis for Patients With Lung Adenocarcinoma

The role of B cell immunity in lung adenocarcinoma

Lung cancer is the deadliest cancer globally. Non-small cell lung cancer (NSCLC), including adenocarcinoma, squamous cell carcinoma, and large cell carcinoma, constitutes a significant portion of cases. Adenocarcinoma, the most prevalent type, has seen a rising incidence. Immune checkpoint inhibitors (ICIs) have improved outcomes in lung adenocarcinoma (LUAD), yet response rates remain unsatisfactory. PD-1/PD-L1 inhibitors are primary ICIs for LUAD, targeting the PD-1/PD-L1 pathway between CD8+ T cells and tumor cells. However, LUAD presents a "cold tumor" phenotype with fewer CD8+ T cells and lower PD-1 expression, leading to resistance to ICIs. Thus, understanding the function of other immune cell in tumor microenvironment is crucial for developing novel immunotherapies for LUAD. B cells, which is part of the adaptive immune system, have gained attention for its role in cancer immunology. While research on B cells lags behind T cells, recent studies reveal their close correlation with prognosis and immunotherapy effectiveness in various solid tumors, including lung cancer. B cells show higher abundance, activity, and prognostic significance in LUAD than that in LUSC. This review summarizes the difference of B cell immunity between LUAD and other lung cancers, outlines the role of B cell immunity in LUAD.

Compound Bacillus improves eggshell quality and egg metabolites of hens by promoting the metabolism balance of calcium and phosphorus and uterine cell proliferation

Probiotics have beneficial effects on improving egg quality, but there is little research about the effect of probiotics on metabolite composition, and the mechanisms are not yet fully understood. The aim of this study was to investigate the potential mechanisms by which compound Bacillus improves egg quality and metabolite composition. A total of 20,000 Jingfen No. 6 laying hens at 381 d old were randomly divided into two treatments: control group with a basal diet, and the basal diet with 5 × 108 CFU/kg compound Bacillus supplementation (Ba) group. The trial lasted eight weeks. The results showed that compound Bacillus improved the gloss and strength of eggshells and reduced the ratio of sand-shell eggs by 23.8%. Specifically, the effective layer of eggshell was thicker and its calcite column was closely connected. Compound Bacillus increased the contents of beneficial fatty acids in the egg yolk, and lipids and lipid-like molecules in the albumen (P < 0.01), while decreased the contents of total cholesterol, triglycerides, and benzene ring compounds in the egg yolk and organic oxygen compounds in the albumen (P < 0.01). In addition, the compound Bacillus increased the calcium absorption in the duodenum by up-regulating the expression of transporters and serum hormone synergism (P < 0.05), and promoted metabolic balance of calcium and phosphorus. Simultaneously, uterine transcriptome showed that the expression of ChaC glutathione specific gamma-glutamylcyclotransferase 1 (CHAC1), glycoprotein-N-acetylgalactosamine 3-beta-galactosyltransferase 1 (C1GALT1), phosphatidylinositol-4-phosphate 5-kinase type 1 beta (PIP5K1B), methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), brain enriched myelin associated protein 1 (BCAS1), and squalene epoxidase (SQLE) genes were increased (P < 0.01), indicating that nutrient metabolism activity was enhanced. The expression of the BCAS1, C1GALT1, KLF transcription factor 13 (KLF13), and leucine rich repeat neuronal 1 (LRRN1) was increased (P < 0.01), indicating that the cell proliferation was enhanced, which slowed uterus aging. In conclusion, compound Bacillus improved the eggshell strength and metabolite composition in the egg by promoting metabolic balance of calcium and phosphorus, cell proliferation, and nutrient metabolism in the uterus.

Unraveling the genetic landscape of susceptibility to multiple primary cancers

With advances in cancer screening and treatment, there is a growing population of cancer survivors who may develop subsequent primary cancers. While hereditary cancer syndromes account for only a portion of multiple cancer cases, we sought to explore the role of common genetic variation in susceptibility to multiple primary tumors. We conducted a cross-ancestry genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) of 10,983 individuals with multiple primary cancers, 84,475 individuals with single cancer, and 420,944 cancer-free controls from two large-scale studies. Our GWAS identified six lead variants across five genomic regions that were significantly associated (P<5×10-8) with the risk of developing multiple primary tumors (overall and invasive) relative to cancer-free controls (at 3q26, 8q24, 10q24, 11q13.3, and 17p13). We also found one variant significantly associated with multiple cancers when comparing to single cancer cases (at 22q13.1). Multi-tissue TWAS detected associations with genes involved in telomere maintenance in two of these regions (ACTRT3 in 3q26 and SLK and STN1 in 10q24) and the development of multiple cancers. Additionally, the TWAS also identified several novel genes associated with multiple cancers, including two immune-related genes, IRF4 and TNFRSF6B. Telomere maintenance and immune dysregulation emerge as central, common pathways influencing susceptibility to multiple cancers. These findings underscore the importance of exploring shared mechanisms in carcinogenesis, offering insights for targeted prevention and intervention strategies.

The multiple roles of interferon regulatory factor family in health and disease

Interferon Regulatory Factors (IRFs), a family of transcription factors, profoundly influence the immune system, impacting both physiological and pathological processes. This review explores the diverse functions of nine mammalian IRF members, each featuring conserved domains essential for interactions with other transcription factors and cofactors. These interactions allow IRFs to modulate a broad spectrum of physiological processes, encompassing host defense, immune response, and cell development. Conversely, their pivotal role in immune regulation implicates them in the pathophysiology of various diseases, such as infectious diseases, autoimmune disorders, metabolic diseases, and cancers. In this context, IRFs display a dichotomous nature, functioning as both tumor suppressors and promoters, contingent upon the specific disease milieu. Post-translational modifications of IRFs, including phosphorylation and ubiquitination, play a crucial role in modulating their function, stability, and activation. As prospective biomarkers and therapeutic targets, IRFs present promising opportunities for disease intervention. Further research is needed to elucidate the precise mechanisms governing IRF regulation, potentially pioneering innovative therapeutic strategies, particularly in cancer treatment, where the equilibrium of IRF activities is of paramount importance.

Plasma cell-free DNA methylome profiling in pre- and post-surgery oral cavity squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous disease that involves multiple anatomic sites, is a leading cause of cancer-related mortality worldwide. Although the utility of noninvasive biomarkers based on circulating cell-free DNA (cfDNA) methylation profiling has been widely recognized, limited studies have been reported so far regarding the dynamics of cfDNA methylome in oral cavity squamous cell carcinoma (OCSCC). It is hypothesized in this study that comparison of methylation profiles in pre- and postsurgery plasma samples will reveal OCSCC-specific prognostic and diagnostic biomarkers. As a strategy to further prioritize tumor-specific targets, top differential methylated regions (DMRs) were called by reanalyzing methylation data from paired tumor and normal tissue collected in the the cancer genome atlas head-neck squamous cell carcinoma (TCGA) head and neck cancer cohort. Matched plasma samples from eight patients with OCSCC were collected at Moffitt Cancer Center before and after surgical resection. Plasma-derived cfDNA was analyzed by cfMBD-seq, which is a high-sensitive methylation profiling assay. Differential methylation analysis was then performed based on the matched samples profiled. In the top 200 HNSCC-specific DMRs detected based on the TCGA data set, a total of 23 regions reached significance in the plasma-based DMR test. The top five validated DMR regions (ranked by the significance in the plasma study) are located in the promoter regions of genes PENK, NXPH1, ZIK1, TBXT, and CDO1, respectively. The genome-wide cfDNA DMR analysis further highlighted candidate biomarkers located in genes SFRP4, SOX1, IRF4, and PCDH17. The prognostic relevance of candidate genes was confirmed by survival analysis using the TCGA data. This study supports the utility of cfDNA-based methylome profiling as a promising noninvasive biomarker source for OCSCC and HNSCC.

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.