Identification of N7-methylguanosine-related lncRNAs for the risk stratification of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world. The N7-methylguanosine (m7G) modification is related to the biological processes and regulation of various diseases. This study investigated the role and predictive value of m7G-related long non-coding RNAs (lncRNAs) in HCC.

Methods

HCC patients were clustered by consensus clustering, and a prognostic signature was developed using Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression analysis. The immune landscape and clinicopathological features of the distinct clusters and subgroups were investigated.

Results

A total of 32 m7G-related lncRNAs were confirmed to be prognostic lncRNAs. Two molecular clusters showed significant differences in terms of their clinicopathological features, prognoses, and immune checkpoint gene (ICG) expression levels. Cluster II was associated with upregulated ICG expression and poor overall survival (OS). The Cancer Genome Atlas training cohort was then used to create an m7G-related lncRNA signature for predicting OS. The signature exhibited excellent predictive performance in the training, test, and all cohorts. The high-risk patients had worse clinical outcomes than the low-risk patients. Further study revealed that this signature was an independent prognostic indicator, and a predictive nomogram was developed based on the clinicopathological features and risk score. In addition, we discovered that this model was correlated with ICG expression and tumor immune cell infiltration.

Conclusions

Our findings demonstrated that m7G-related lncRNAs are associated with the tumor immune landscape and prognosis and can serve as independent prognostic markers for HCC. These findings provide new insights into the functions of m7G-related lncRNAs in HCC.

Profiling Prostate Cancer Therapeutic Resistance

The major challenge in the treatment of patients with advanced lethal prostate cancer is therapeutic resistance to androgen-deprivation therapy (ADT) and chemotherapy. Overriding this resistance requires understanding of the driving mechanisms of the tumor microenvironment, not just the androgen receptor (AR)-signaling cascade, that facilitate therapeutic resistance in order to identify new drug targets. The tumor microenvironment enables key signaling pathways promoting cancer cell survival and invasion via resistance to anoikis. In particular, the process of epithelial-mesenchymal-transition (EMT), directed by transforming growth factor-β (TGF-β), confers stem cell properties and acquisition of a migratory and invasive phenotype via resistance to anoikis. Our lead agent DZ-50 may have a potentially high efficacy in advanced metastatic castration resistant prostate cancer (mCRPC) by eliciting an anoikis-driven therapeutic response. The plasticity of differentiated prostate tumor gland epithelium allows cells to de-differentiate into mesenchymal cells via EMT and re-differentiate via reversal to mesenchymal epithelial transition (MET) during tumor progression. A characteristic feature of EMT landscape is loss of E-cadherin, causing adherens junction breakdown, which circumvents anoikis, promoting metastasis and chemoresistance. The targetable interactions between androgens/AR and TGF-β signaling are being pursued towards optimized therapeutic regimens for the treatment of mCRPC. In this review, we discuss the recent evidence on targeting the EMT-MET dynamic interconversions to overcome therapeutic resistance in patients with recurrent therapeutically resistant prostate cancer. Exploitation of the phenotypic landscape and metabolic changes that characterize the prostate tumor microenvironment in advanced prostate cancer and consequential impact in conferring treatment resistance are also considered in the context of biomarker discovery.