Hypoxia promotes immune escape of pancreatic cancer cells by lncRNA NNT-AS1/METTL3-HuR-mediated ITGB1 m6A modification

Identification of the biological functions and chemo-therapeutic responses of ITGB superfamily in ovarian cancer

BACKGROUND

Patients with ovarian cancer (OC) tend to face a poor prognosis due to a lack of typical symptoms and a high rate of recurrence and chemo-resistance. Therefore, identifying representative and reliable biomarkers for early diagnosis and prediction of chemo-therapeutic responses is vital for improving the prognosis of OC.

METHODS

Expression levels, IHC staining, and subcellular distribution of eight ITGBs were analyzed using The Cancer Genome Atlas (TCGA)-Ovarian Serous Cystadenocarcinoma (OV) database, GEO DataSets, and the HPA website. PrognoScan and Univariate Cox were used for prognostic analysis. TIDE database, TIMER database, and GSCA database were used to analyze the correlation between immune functions and ITGBs. Consensus clustering analysis was performed to subtype OC patients in the TCGA database. LASSO regression was used to construct the predictive model. The Cytoscape software was used for identifying hub genes. The 'pRRophetic' R package was applied to predict chemo-therapeutic responses of ITGBs.

RESULTS

ITGBs were upregulated in OC tissues except ITGB1 and ITGB3. High expression of ITGBs correlated with an unfavorable prognosis of OC except ITGB2. In OC, there was a strong correlation between immune responses and ITGB2, 6, and 7. In addition, the expression matrix of eight ITGBs divided the TCGA-OV database into two subgroups. Subgroup A showed upregulation of eight ITGBs. The predictive model distinguishes OC patients from favorable prognosis to poor prognosis. Chemo-therapeutic responses showed that ITGBs were able to predict responses of common chemo-therapeutic drugs for patients with OC.

CONCLUSIONS

This article provides evidence for predicting prognosis, immuno-, and chemo-therapeutic responses of ITGBs in OC and reveals related biological functions of ITGBs in OC.

Non-coding RNA-Mediated N6-Methyladenosine (m6A) deposition: A pivotal regulator of cancer, impacting key signaling pathways in carcinogenesis and therapy response

The emergence of RNA modifications has recently been considered as critical post-transcriptional regulations which governed gene expression. N6-methyladenosine (m6A) modification is the most abundant type of RNA modification which is mediated by three distinct classes of proteins called m6A writers, readers, and erasers. Accumulating evidence has been made in understanding the role of m6A modification of non-coding RNAs (ncRNAs) in cancer. Importantly, aberrant expression of ncRNAs and m6A regulators has been elucidated in various cancers. As the key role of ncRNAs in regulation of cancer hallmarks is well accepted now, it could be accepted that m6A modification of ncRNAs could affect cancer progression. The present review intended to discuss the latest knowledge and importance of m6A epigenetic regulation of ncRNAs including mircoRNAs, long non-coding RNAs, and circular RNAs, and their interaction in the context of cancer. Moreover, the current insight into the underlying mechanisms of therapy resistance and also immune response and escape mediated by m6A regulators and ncRNAs are discussed.

Methyltransferase-like 3 modifications of RNAs: Implications for the pathology in the endocrine system

Methyltransferase-like 3 (METTL3) is the most well-known element of N6-methyladenosine modification on RNAs. METTL3 deposits a methyl group onto target RNAs to modify their expression, ultimately regulating various physiological and pathological events. Numerous studies have suggested the significant role of METTL3 in endocrine dysfunction and related disorders. However, reviews that summarize and interpret these studies are lacking. In this review, we systematically analyze such studies, including obesity, type 2 diabetes mellitus (T2DM), T2DM-induced diseases, pancreatic cancer, and thyroid carcinoma. This review indicates that METTL3 contributes remarkably to the endocrine dysfunction and progression of obesity, T2DM, T2DM-induced diseases, pancreatic cancer, and thyroid carcinoma. In conclusion, this review provides a comprehensive interpretation of the mechanism via which METTL3 functions on RNAs and regulates various endocrine dysfunction events and suggest potential associated correlations. Our review, thus, provides a valuable reference for further fundamental studies and clinical applications.