Multi-omics comprehensive analysis reveals the predictive value of N6-methyladenosine- related genes in prognosis and immune escape of bladder cancer.

BACKGROUND: N6-methyladenosine (m6A) is the most frequent RNA modification in mammals, and its role in bladder cancer (BC) remains rarely revealed. OBJECTIVE: To predict the value of m6A-related genes in prognosis and immunity in BC. METHODS: We performed multiple omics analysis of 618 TCGA and GEO patients and used principal component analysis (PCA) to calculate the m6A score for BC patients. RESULTS: We described the multiple omics status of 23 m6A methylation-related genes (MRGs), and four m6A clusters were identified, which showed significant differences in immune infiltration and biological pathways. Next, we intersected the differential genes among m6A clusters, and 11 survival-related genes were identified, which were used to calculate the m6A score for the patients. We found that the high-score (HS) group showed lower tumor mutation burden (TMB) and TP53 mutations and better prognosis than the low-score (LS) group. Lower immune infiltration, higher expression of PD-L1, PD-1, and CTLA4, and higher immune dysfunction and immune exclusion scores were identified in the LS group, suggesting a higher possibility of immune escape. Finally, the experimental verification shows that the m6A related genes, such as IGFBP1, plays an important role in the growth and metastasis of bladder cancer. CONCLUSIONS: These findings revealed the important roles of m6A MRGs in predicting prognosis, TMB status, TP53 mutation, immune functions and immunotherapeutic response in BC.

A new immune-related gene signature predicts the prognosis and immune escape of bladder cancer.

BACKGROUND: The biological roles of immune-related genes (IRGs) in bladder cancer (BC) need to be further elucidated. OBJECTIVE: To elucidate the predictive value of IRGs for prognosis and immune escape in BC. METHODS: We comprehensively analyzed the transcriptomic and clinical information of 430 cases, including 19 normal and 411 BC patients from the TCGA database, and verified 165 BC cases in the GSE13507 dataset. The risk model was constructed based on IRGs by applying LASSO Cox regression and exploring the relationship between the risk score and prognosis, gene mutations, and immune escape in BC patients. RESULTS: We identified 4 survival-related genes (PSMC1, RAC3, ROBO2 and ITGB3) among 6,196 IRGs in both the TCGA and GES13507 datasets,, which were used to establish a gene risk model by applying LASSO Cox regression. The results showed that the high-risk (HR) group was closely associated with poor survival or advanced pathological stage of BC. Furthermore, the risk score was found to be an independent risk factor for prognosis of BC patients. In addition, high-risk individuals showed a greater prevalence of TP53 mutations lower CD8+ T-cell and NK cell infiltration, higher Treg cell infiltration, higher expression of PD-L1, and higher immune exclusion scores than those in the low-risk (LR) group. Finally, the experimental verification shows that the model construction gene, especially PMSC1, plays an important role in the growth and metastasis of bladder cancer. CONCLUSIONS: These evidences revealed the vital role of IRGs in predicting prognosis, TP53 mutation and immune escape in BC patients.

Coral skeletons reveal the impacts of oil pollution on seawater chemistry in the northern South China Sea.

Oil pollution can release trace metals (TMs) with cumulative toxicity into seawater, harming marine ecosystems in the long term. However, the lack of studies has inhibited our understanding of the effects and mechanisms of oil pollution on TMs in seawater. Hence, we investigated the 10-year monthly variation of TMs in Porites coral skeletons from the northern South China Sea (SCS), complemented by spatial distribution of TMs in seawater, sediments and characterization of TMs in fuel oil. The results of principal component-multivariate linear regression showed that the total contribution of oil pollution as a source to TMs in surface seawater was 77.2%, where the residence time of TMs (Ni, V, Cr, Co, Cu, Mn, Fe, and Mo) released from oil spills in surface seawater was approximately 1.4 months. Due to the geochemical nature of the metals, their seasonal variations are controlled by tropical cyclones (Ni, V, Cr, Co, Cu, Mn, Fe, and Mo), winter monsoons (Pb, Cd, Ba, and Zn) and sea surface temperature (Sr). This study shows that coral skeletons can be used as a new tool to study marine oil pollution. This provides valuable reference data for accurately identifying and quantifying the effects of oil pollution on TMs in seawater from a spatial and temporal perspective.

The predictive value of pyroptosis for the prognosis and immune escape of bladder cancer.

OBJECTIVE: To evaluate the predictive value of pyroptosis-related genes for the prognosis and immune escape of bladder cancer (BC). METHODS: Transcriptomic and single nucleotide polymorphisms (SNPs) data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) portal. Least absolute shrinkage and selection operator (LASSO) analysis was carried out to construct a prognostic risk model for BC patients. RESULTS: Based on the expression of 50 pyroptosis-related genes, BC patients from TCGA database were divided into two clusters, which showed significant differences in overall survival and disease specific survival. Furthermore, we intersected the differentially expressed genes between these two clusters with those identified from the GSE13507 dataset and finally identified eight survival related genes, which was used to construct a prognostic risk model by LASSO Cox regression. According to the model, the high-risk (HR) group was closely associated with poor survival or the advanced pathological stage of BC. In addition, the HR group was mainly enriched in cell cycle and immune-related pathways and had a higher TP53 mutation rate than the low-risk (LR) group. Furthermore, these two risk groups were significantly related to immune cell composition, immune cell infiltration, and immune response. Importantly, a higher expression of PD-1, PD-L1, and CTLA4 as well as higher immune exclusion scores were found in the HR group, suggesting a higher possibility of immune escape. CONCLUSION: Our studies revealed the key role of pyroptosis in predicting the prognosis, TP53 mutation, and immune escape of patients with BC.

Comprehensive Exploration of M2 Macrophages and Its Related Genes for Predicting Clinical Outcomes and Drug Sensitivity in Lung Squamous Cell Carcinoma.

Background: M2 macrophages play an important role in cancers. However, the role of M2 macrophages has not been clarified in lung squamous cell carcinoma. Methods: All the open-accessed data were downloaded from The Cancer Genome Atlas database. All the analysis was performed in the R software. The CIBERSORT algorithm was utilized to quantify the immune cell infiltration in the tumor microenvironment. LASSO regression and multivariate Cox regression analysis were carried out for the creation of the prognostic model. Pathway enrichment analysis was performed using the single sample Gene Set Enrichment Analysis (ssGSEA) and clueGO algorithm. Results: In our study, we comprehensively explored the role of M2 macrophages and its related genes in LUSC patients. We found that the patients with high M2 macrophage infiltration tend to have a worse prognosis. Also, some oncogenetic pathways were activated in the patients with high M2 macrophage infiltration. Further, a prognosis model based on six M2 macrophage-related genes was established, including TRIM58, VIPR2, CTNNA3, KIAA0408, CLEC4G, and MATN4, which showed a good prognosis prediction efficiency in both training and validation cohort. Pathway enrichment analysis showed that the pathway of allograft rejection, bile acid metabolism, coagulation, inflammatory response, IL6/JAK/STAT3 signaling, hedgehog signaling, peroxisome, and myogenesis were significantly activated in the high-risk patients. Based on the results of an investigation of immune infiltration, risk score was found to have a positive correlation with M2 macrophages and resting CD4+ memory T cells, but a negative correlation with follicular helper T cells, M1 macrophages, and Tregs. In addition, we discovered that patients in high-risk groups may respond better to immunotherapy than individuals in lower-risk groups. However, low-risk patients might be more sensitive to cisplatin. Conclusions: Our model is a powerful tool to predict LUSC patient prognosis and could indicate the sensitivity of immunotherapy and chemotherapy.