Inflammation-Related LncRNAs Signature for Prognosis and Immune Response Evaluation in Uterine Corpus Endometrial Carcinoma

Pan-cancer analysis of super-enhancer-induced LINC00862 and validation as a SIRT1-promoting factor in cervical cancer and gastric cancer

Immune checkpoints inhibitors are effective but it needs more precise biomarkers for patient selection. We explored the biological significance of LINC00862 in pan-cancer by bioinformatics. And we studied its regulatory mechanisms using chromatin immunoprecipitation and RNA immunoprecipitation assays etc. TCGA and single-cell sequencing data analysis indicated that LINC00862 was overexpressed in the majority of tumor and stromal cells, which was related with poor prognosis. LINC00862 expression was related with immune cell infiltration and immune checkpoints expression, and had a high predictive value for immunotherapy efficacy. Mechanistically, LINC00862 competitively bound to miR-29c-3p to unleash SIRT1's tumor-promoting function. SIRT1 inhibitor-EX527 were screened by virtual screening and verified by in vitro and vivo assays. Notably, acetyltransferase P300-mediated super-enhancer activity stimulated LINC00862 transcription. Collectively, LINC00862 could be a diagnostic and prognostic biomarker. LINC00862 could also be a predictive biomarker for immunotherapy efficacy. Super-enhancer activity is the driver for LINC00862 overexpression in cervical cancer and gastric cancer.

The Analysis of ceRNA Networks and Tumor Microenvironment in Endometrial Cancer

Background: Endometrial carcinoma is a life-threatening and aggressive tumor that affects women worldwide. ceRNAs and carcinoma-infiltrating immunocytes can be associated with tumor formation and progression. Therefore, investigating the unique mechanisms underlying endometrial carcinoma is crucial. Methods: Prognostic nomograms were constructed based on the differentially expressed genes between normal and tumor tissues. Twenty types of tumor immune infiltrating cells in uterine corpus endometrial carcinoma (UCEC) were examined using CIBERSORT. To identify the potential signaling pathways, the associations among essential ceRNA network genes and important immunocytes were investigated using the co-expression assay. Results: Differential analysis identified 3636 mRNAs, 249 miRNAs, and 252 lncRNAs unique to UCEC. The ceRNA network was constructed using the interplays between 19 lncRNA-miRNA pairs and 434 miRNA-mRNA pairs. Furthermore, CIBERSORT and ceRNA integration analysis revealed that immune cells, including dendritic cells and natural killer cells, and associated ceRNAs such as LRP8, HDGF, PPARGC1B, and TEAD1 can appropriately predict prognosis. A receiver operating characteristic curve was constructed to predict patient outcomes. Conclusions: Using a nomogram, we predicted the outcomes of patients with UCEC Furthermore, we revealed its significance in improving clinical management.

Deciphering DNA repair gene mutational landscape in uterine corpus endometrial carcinoma patients using next generation sequencing

Uterine Corpus Endometrial Carcinoma (UCEC) is a significant health concern with a complex genetic landscape impacting disease susceptibility and progression. This study aimed to unravel the spectrum of DNA repair gene mutations in Pakistani UCEC patients through Next Generation Sequencing (NGS) and explore their potential functional consequences via downstream analyses. NGS analysis of genomic DNA from 30 UCEC patients was conducted to identify clinically significant pathogenic mutations in DNA repair genes. This analysis revealed mutations in 4 key DNA repair genes: BRCA1, BRCA2, APC, and CDH1. Kaplan-Meier (KM) analysis was employed to assess the prognostic value of these mutations on patient overall survival (OS) in UCEC. To delve into the functional impact of these mutations, we performed RT-qPCR, immunohistochemistry (IHC), and western blot analyses on the mutated UCEC samples compared to their non-mutated counterparts. These results unveiled the up-regulation in the expression of the mutated genes, suggesting a potential association between the identified mutations and enhanced gene activity. Additionally, targeted bisulfite sequencing analysis was utilized to evaluate DNA methylation patterns in the promoters of the mutated genes. Strikingly, hypomethylation in the promoters of BRCA1, BRCA2, APC, and CDH1 was observed in the mutated UCEC samples relative to the non-mutated, indicating the involvement of epigenetic mechanisms in the altered gene expression. In conclusion, this study offers insights into the genetic landscape of DNA repair gene mutations in Pakistani UCEC patients. The presence of pathogenic mutations in BRCA1, BRCA2, APC, and CDH1, coupled with their down-regulation and hypermethylation, suggests a convergence of genetic and epigenetic factors contributing to genomic instability in UCEC cells. These findings enhance our understanding of UCEC susceptibility and provide potential avenues for targeted therapeutic interventions in Pakistani UCEC patients.

Multi-omics analysis reveals cuproptosis and mitochondria-based signature for assessing prognosis and immune landscape in osteosarcoma

Background

Osteosarcoma (OSA), the most common primary mesenchymal bone tumor, is a health threat to children and adolescents with a dismal prognosis. While cuproptosis and mitochondria dysfunction have been demonstrated to exert a crucial role in tumor progression and development, the mechanisms by which they are regulated in OSA still await clarification.

Methods

Two independent OSA cohorts containing transcriptome data and clinical information were collected from public databases. The heterogeneity of OSA were evaluated by single cell RNA (scRNA) analysis. To identify a newly molecular subtype, unsupervised consensus clustering was conducted. Cox relevant regression methods were utilized to establish a prognostic gene signature. Wet lab experiments were performed to confirm the effect of model gene in OSA cells.

Results

We determined 30 distinct cell clusters and assessed OSA heterogeneity and stemness scRNA analysis. Then, univariate Cox analysis identified 24 candidate genes which were greatly associated with the prognosis of OSA. Based on these prognostic genes, we obtained two molecular subgroups. After conducting step Cox regression, three model genes were selected to construct a signature showing a favorable performance to forecast clinical outcome. Our proposed signature could also evaluate the response to chemotherapy and immunotherapy of OSA cases.

Conclusion

We generated a novel risk model based on cuproptosis and mitochondria-related genes in OSA with powerful predictive ability in prognosis and immune landscape.

Cross-talk of pyroptosis-based subtypes, the development of a risk classifier and immune responses in cervical cancer

BACKGROUND

Cervical cancer (CC) is one of the most common gynecology malignancies and has a dismal survival outcome. The prognostic value of pyroptosis and its role in the regulation of immune metabolism in CC remain unclear.

METHODS

Two independent CC cohorts collected from public databases were integrated for unsupervised cluster analysis. All CC cases were assigned to different subsets based on the pyroptosis-related genes (PRGs). The differentially expressed genes (DEGs) between different subclusters were included in stepwise Cox regression for the risk classifier establishment. Next, single-cell sequencing analysis was conducted to explore the cellular location of each model gene. The CIBERSORT algorithm was applied to estimate immunocytes infiltration. Finally, a series of functional experiments were performed to detect the role of CDH3 in CC.

RESULTS

Based on the 52 PRGs, the combined CC cohort was clustered into two subsets (C1 (n = 259) and C2 (n = 242)). Survival and Cox regression methods were used to create a pyroptosis-based risk classifier including four PRGs (PEG3, FSCN1, CDH3 and SLC2A1). For the immune environment in CC, the high-risk group had a lower infiltration level of B cells, memory-activated CD4 T cells and CD8 T cells and a higher infiltration abundance of neutrophils. The expression pattern of model genes was confirmed in CC cell lines by PCR assay. Furthermore, we observed that knockdown of CDH3 could suppress CC cell proliferation.

CONCLUSION

Our project could offer promising reference for prognosis assessment, immune metabolism prediction and clinical decision-making of patients with CC.

miRNA, lncRNA and circRNA: targeted molecules with therapeutic promises in Mycoplasma pneumoniae infection

Mycoplasma pneumoniae (MP) is primarily recognized as a respiratory pathogen that causes community-acquired pneumonia, which can lead to acute upper and lower airway inflammation and extrapulmonary syndrome. Refractory pneumonia caused by MP can cause severe complications and even be life-threatening, particularly in infants and the elderly. It is well-known that non-coding RNAs (ncRNAs) represented by miRNAs, lncRNAs and circRNAs have been manifested to be widely involved in the regulation of gene expression. Growing evidence indicates that these ncRNAs have distinct differentiated expression in MP infection and affect multiple biological processes, playing an indispensable role in the initiation and promotion of MP infection. However, the epigenetic mechanisms involved in the development of MP infection remain unclear. This article reviews the mechanisms by which miRNAs, lncRNAs, and circRNAs mediate MP infection, such as inflammatory responses, apoptosis and pulmonary fibrosis. Focusing on miRNAs, lncRNAs and circRNAs associated with MP infection could provide new insights into this disease's early diagnosis and therapeutic approaches.

Construction of a ferroptosis scoring system and identification of LINC01572 as a novel ferroptosis suppressor in lung adenocarcinoma

Background: Ferroptosis is a novel process of programmed cell death driven by excessive lipid peroxidation that is associated with the development of lung adenocarcinoma. N6-methyladenosine (m6a) modification of multiple genes is involved in regulating the ferroptosis process, while the predictive value of N6-methyladenosine- and ferroptosis-associated lncRNA (FMRlncRNA) in the prognosis of patients remains with LUAD remains unknown. Methods: Unsupervised cluster algorithm was applied to generate subcluster in LUAD according to ferroptosis-associated lncRNA. Stepwise Cox analysis and LASSO algorithm were applied to develop a prognostic model. Cellular location was detected by single-cell analysis. Also, we conducted Gene set enrichment analysis (GSEA) enrichment, immune microenvironment and drug sensitivity analysis. In addition, the expression and function of the LINC01572 were investigated by several in vitro experiments including qRT-PCR, cell viability assays and ferroptosis assays. Results: A novel ferroptosis-associated lncRNAs-based molecular subtype containing two subclusters were determined in LUAD. Then, we successfully created a risk model according to five ferroptosis-associated lncRNAs (LINC00472, MBNL1-AS1, LINC01572, ZFPM2-AS1, and TMPO-AS1). Our nominated model had good stability and predictive function. The expression patterns of five ferroptosis-associated lncRNAs were confirmed by polymerase chain reaction (PCR) in LUAD cell lines. Knockdown of LINC01572 significantly inhibited cell viability and induced ferroptosis in LUAD cell lines. Conclusion: Our data provided a risk score system based on ferroptosis-associated lncRNAs with prognostic value in LUAD. Moreover, LINC01572 may serve as a novel ferroptosis suppressor in LUAD.