LncRNA THOR promotes endometrial cancer progression through the AKT and ERK signaling pathways

The Promotive and Inhibitory Role of Long Non-Coding RNAs in Endometrial Cancer Course-A Review

Endometrial cancer is one of the most common malignant tumours in women. The development of this tumour is associated with several genetic disorders, many of which are still unknown. One type of RNA molecules currently being intensively studied in many types of cancer are long non-coding RNAs (lncRNAs). LncRNA-coding genes occupy a large fraction of the human genome. LncRNAs regulate many aspects of cell development, metabolism, and other physiological processes. Diverse types of lncRNA can function as a tumour suppressor or an oncogene that can alter migration, invasion, cell proliferation, apoptosis, and immune system response. Recent studies suggest that selected lncRNAs are important in an endometrial cancer course. Our article describes over 70 lncRNAs involved in the development of endometrial cancer, which were studied via in vivo and in vitro research. It was proved that lncRNAs could both promote and inhibit the development of endometrial cancer. In the future, lncRNAs may become an important therapeutic target. The aim of this study is to review the role of lncRNAs in the development of carcinoma of uterine body.

Machine learning combined with single-cell analysis reveals predictive capacity and immunotherapy response of T cell exhaustion-associated lncRNAs in uterine corpus endometrial carcinoma

BACKGROUND

The exhaustion of T-cells is a primary factor contributing to immune dysfunction in cancer. Long non-coding RNAs (lncRNAs) play a significant role in the advancement, survival, and treatment of Uterine Corpus Endometrial Carcinoma (UCEC). Nevertheless, there has been no investigation into the involvement of lncRNAs associated with T-cell exhaustion (TEXLs) in UCEC. The goal of this work is to establish predictive models for TEXLs in UCEC and study their related immune features.

METHODS

Using transcriptome and single-cell sequencing data from The Cancer Genome Atlas and Gene Expression Omnibus databases, we employed co-expression analysis and univariate Cox regression to identify prognostic-associated TEXLs (pTEXLs). The prognostic model was developed using the Least Absolute Contraction and Selection Operator. The immunotherapy characteristics of the prognostic model risk score were studied. Then molecular subgroups were identified through non-negative Matrix Factorization based on pTEXLs. The identification of co-expressed genes was done using a weighted correlation network analysis. Subsequently, a diagnostic model for UCEC was created. In-depth investigations, both in vitro and in vivo, were carried out to elucidate the molecular mechanism of the key gene within the diagnostic model.

RESULTS

Receiver operating characteristic curve, calibration curve, and decision curve analysis proved the validity of the predictive models established according to pTEXLs. The subgroup with lower risk scores in the prognostic model has better responses to blocking immune checkpoint therapy. Single-cell analysis suggests that the expression level of MIEN1 is relatively high in immune cells among diagnostic genes. Furthermore, the targeted suppression of MIEN1 via sh-MIEN1 diminishes the proliferative, migratory, and invasive capacities of UCEC cells, potentially associated with CD8+ T cell exhaustion.

CONCLUSIONS

The association between TEXLs and UCEC was methodically elucidated by our investigation. A stable pTEXLs risk prediction model and a diagnosis model for UCEC were also established.

Developing a non-invasive diagnostic model for pediatric Crohn's disease using RNA-seq analysis

Introduction: Pediatric Crohn's disease is a chronic inflammatory condition that affects the digestive system in children and adolescents. It is characterized by symptoms such as abdominal pain, diarrhea, weight loss, and malnutrition, and can also cause complications like growth delays and delayed puberty. However, diagnosing pediatric Crohn's disease can be difficult, especially when it comes to non-invasive methods. Methods: In this study, we developed a diagnostic model using RNA-seq to analyze gene expression in ileal biopsy samples from children with Crohn's disease and non-pediatric Crohn's controls. Results: Our results showed that pediatric Crohn's disease is associated with altered expression of genes involved in immune response, inflammation, and tissue repair. We validated our findings using two independent datasets from the Gene Expression Omnibus (GEO) database, as well as through one prospective independent dataset, and found that our model had a high accuracy rate. Discussion: These findings suggest the possibility of non-invasive diagnosis for pediatric Crohn's disease and may inform the development of targeted therapies for this condition.