Thymic epithelial tumors: examining the GTF2I mutation and developing a novel prognostic signature with LncRNA pairs to predict tumor recurrence

GTF2I acts as a novel tumor suppressor transcription factor and shows Favorable prognosis in renal cancer

The role of GTF2I (General Transcription Factor2I) alteration has already been reported in thymic cancer as a valuable biomarker. However, the association of GTF2I mutation with renal cancer for prognosis of immunotherapy is not yet examined. The biologic and oncologic significance of GTF2I in renal cancer was examined at multiomics level such as mutation, copy number alteration, structural variants. The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA) were used to retrieve the omics data. The expression of GTF2I mRNA was quite significant in case of renal caner. Correlation among the GTF2I mRNA, mutation, CNA and structural variants was also studied. Interactome of GTF2I was also constructed using STRING database. Gain, amplification, and missense mutation exhibited a positive correlation between GTF2I mRNA expression and non-structural variants. Similarly, GTF2I mRNA expression and copy number alterations from GISTIC were positively correlated. High expression of GTF2I was associated with better overall survival indicating the less aggressive clinical features. Insight Box Investigating GTF2I's complex function as a tumor suppressor transcription factor in renal carcinoma provides fresh insights into its biologic and oncologic importance, especially when considering the prognosis of immunotherapy. Little is known about its possible use as a biomarker for renal cancer. Using a multiomics approach and utilizing information from the Human Protein Atlas (HPA) and The Cancer Genome Atlas (TCGA), our study clarifies the intricate relationship between mRNA expression, GTF2I changes, and clinical outcomes in renal cancer. Our results indicate that GTF2I expression may be used as a prognostic indicator because it is positively correlated with favorable survival outcomes. Furthermore, the molecular interactions behind GTF2I's functional significance in renal cancer are revealed by interactome analysis utilizing the STRING database, providing important information for further study and treatment approaches.

Monocyte-macrophages modulate intestinal homeostasis in inflammatory bowel disease

BACKGROUND

Monocytes and macrophages play an indispensable role in maintaining intestinal homeostasis and modulating mucosal immune responses in inflammatory bowel disease (IBD). Although numerous studies have described macrophage properties in IBD, the underlying mechanisms whereby the monocyte-macrophage lineage modulates intestinal homeostasis during gut inflammation remain elusive.

MAIN BODY

In this review, we decipher the cellular and molecular mechanisms governing the generation of intestinal mucosal macrophages and fill the knowledge gap in understanding the origin, maturation, classification, and functions of mucosal macrophages in intestinal niches, particularly the phagocytosis and bactericidal effects involved in the elimination of cell debris and pathogens. We delineate macrophage-mediated immunoregulation in the context of producing pro-inflammatory and anti-inflammatory cytokines, chemokines, toxic mediators, and macrophage extracellular traps (METs), and participating in the modulation of epithelial cell proliferation, angiogenesis, and fibrosis in the intestine and its accessory tissues. Moreover, we emphasize that the maturation of intestinal macrophages is arrested at immature stage during IBD, and the deficiency of MCPIP1 involves in the process via ATF3-AP1S2 signature. In addition, we confirmed the origin potential of IL-1B+ macrophages and defined C1QB+ macrophages as mature macrophages. The interaction crosstalk between the intestine and the mesentery has been described in this review, and the expression of mesentery-derived SAA2 is upregulated during IBD, which contributes to immunoregulation of macrophage. Moreover, we also highlight IBD-related susceptibility genes (e.g., RUNX3, IL21R, GTF2I, and LILRB3) associated with the maturation and functions of macrophage, which provide promising therapeutic opportunities for treating human IBD.

CONCLUSION

In summary, this review provides a comprehensive, comprehensive, in-depth and novel description of the characteristics and functions of macrophages in IBD, and highlights the important role of macrophages in the molecular and cellular process during IBD.

Molecular and Functional Key Features and Oncogenic Drivers in Thymic Carcinomas

Thymic epithelial tumors, comprising thymic carcinomas and thymomas, are rare neoplasms. They differ in histology, prognosis, and association with autoimmune diseases such as myasthenia gravis. Thymomas, but not thymic carcinomas, often harbor GTF2I mutations. Mutations of CDKN2A, TP53, and CDKN2B are the most common thymic carcinomas. The acquisition of mutations in genes that control chromatin modifications and epigenetic regulation occurs in the advanced stages of thymic carcinomas. Anti-angiogenic drugs and immune checkpoint inhibitors targeting the PD-1/PD-L1 axis have shown promising results for the treatment of unresectable tumors. Since thymic carcinomas are frankly aggressive tumors, this report presents insights into their oncogenic drivers, categorized under the established hallmarks of cancer.

Unlocking the predictive potential of long non-coding RNAs: a machine learning approach for precise cancer patient prognosis

The intricate web of cancer biology is governed by the active participation of long non-coding RNAs (lncRNAs), playing crucial roles in cancer cells' proliferation, migration, and drug resistance. Pioneering research driven by machine learning algorithms has unveiled the profound ability of specific combinations of lncRNAs to predict the prognosis of cancer patients. These findings highlight the transformative potential of lncRNAs as powerful therapeutic targets and prognostic markers. In this comprehensive review, we meticulously examined the landscape of lncRNAs in predicting the prognosis of the top five cancers and other malignancies, aiming to provide a compelling reference for future research endeavours. Leveraging the power of machine learning techniques, we explored the predictive capabilities of diverse lncRNA combinations, revealing their unprecedented potential to accurately determine patient outcomes.

HNRNPA2B1 as a potential therapeutic target for thymic epithelial tumor recurrence: An integrative network analysis

Thymic epithelial tumors (TETs) are rare malignant tumors, and the molecular mechanisms of both primary and recurrent TETs are poorly understood. Here we established comprehensive proteomic signatures of 15 tumors (5 recurrent and 10 non-recurrent) and 15 pair wised tumor adjacent normal tissues. We then proposed an integrative network approach for studying the proteomics data by constructing protein-protein interaction networks based on differentially expressed proteins and a machine learning-based score, followed by network modular analysis, functional enrichment annotation and shortest path inference analysis. Network modular analysis revealed that primary and recurrent TETs shared certain common molecular mechanisms, including a spliceosome module consisting of RNA splicing and RNA processing, but the recurrent TET was specifically related to the ribosome pathway. Applying the shortest path inference to the collected seed gene module identified that the ribonucleoprotein hnRNPA2B1 probably serves as a potential target for recurrent TET therapy. The drug repositioning combined molecular dynamics simulations suggested that the compound ergotamine could potentially act as a repurposing drug to treat recurrent TETs by targeting hnRNPA2B1. Our study demonstrates the value of integrative network analysis to understand proteotype robustness and its relationships with genotype, and provides hits for further research on cancer therapeutics.