Long Non-Coding RNA MIR31HG Promotes the Transforming Growth Factor β-Induced Epithelial-Mesenchymal Transition in Pancreatic Ductal Adenocarcinoma Cells

Unboxing the network among long non-coding RNAs and TGF-β signaling in cancer

Deeper analysis of molecular mechanisms arising in tumor cells is an unmet need to provide new diagnostic and therapeutic strategies to prevent and treat tumors. The transforming growth factor β (TGF-β) signaling has been steadily featured in tumor biology and linked to poor prognosis of cancer patients. One pro-tumorigenic mechanism induced by TGF-β is the epithelial-to-mesenchymal transition (EMT), which can initiate cancer dissemination, enrich the tumor stem cell population, and increase chemoresistance. TGF-β signals via SMAD proteins, ubiquitin ligases, and protein kinases and modulates the expression of protein-coding and non-coding RNA genes, including those encoding larger than 500 nt transcripts, defined as long non-coding RNAs (lncRNAs). Several reports have shown lncRNAs regulating malignant phenotypes by directly affecting epigenetic processes, transcription, and post-transcriptional regulation. Thus, this review aims to update and summarize the impact of TGF-β signaling on the expression of lncRNAs and the function of such lncRNAs as regulators of TGF-β signaling, and how these networks might impact specific hallmarks of cancer.

Targeting the RAS/RAF/MAPK pathway for cancer therapy: from mechanism to clinical studies

Metastatic dissemination of solid tumors, a leading cause of cancer-related mortality, underscores the urgent need for enhanced insights into the molecular and cellular mechanisms underlying metastasis, chemoresistance, and the mechanistic backgrounds of individuals whose cancers are prone to migration. The most prevalent signaling cascade governed by multi-kinase inhibitors is the mitogen-activated protein kinase (MAPK) pathway, encompassing the RAS-RAF-MAPK kinase (MEK)-extracellular signal-related kinase (ERK) pathway. RAF kinase is a primary mediator of the MAPK pathway, responsible for the sequential activation of downstream targets, such as MEK and the transcription factor ERK, which control numerous cellular and physiological processes, including organism development, cell cycle control, cell proliferation and differentiation, cell survival, and death. Defects in this signaling cascade are associated with diseases such as cancer. RAF inhibitors (RAFi) combined with MEK blockers represent an FDA-approved therapeutic strategy for numerous RAF-mutant cancers, including melanoma, non-small cell lung carcinoma, and thyroid cancer. However, the development of therapy resistance by cancer cells remains an important barrier. Autophagy, an intracellular lysosome-dependent catabolic recycling process, plays a critical role in the development of RAFi resistance in cancer. Thus, targeting RAF and autophagy could be novel treatment strategies for RAF-mutant cancers. In this review, we delve deeper into the mechanistic insights surrounding RAF kinase signaling in tumorigenesis and RAFi-resistance. Furthermore, we explore and discuss the ongoing development of next-generation RAF inhibitors with enhanced therapeutic profiles. Additionally, this review sheds light on the functional interplay between RAF-targeted therapies and autophagy in cancer.

The Role of the Transforming Growth Factor-β Signaling Pathway in Gastrointestinal Cancers

Transforming growth factor-β (TGF-β) has attracted attention as a tumor suppressor because of its potent growth-suppressive effect on epithelial cells. Dysregulation of the TGF-β signaling pathway is considered to be one of the key factors in carcinogenesis, and genetic alterations affecting TGF-β signaling are extraordinarily common in cancers of the gastrointestinal system, such as hereditary nonpolyposis colon cancer and pancreatic cancer. Accumulating evidence suggests that TGF-β is produced from various types of cells in the tumor microenvironment and mediates extracellular matrix deposition, tumor angiogenesis, the formation of CAFs, and suppression of the anti-tumor immune reaction. It is also being considered as a factor that promotes the malignant transformation of cancer, particularly the invasion and metastasis of cancer cells, including epithelial-mesenchymal transition. Therefore, elucidating the role of TGF-β signaling in carcinogenesis, cancer invasion, and metastasis will provide novel basic insight for diagnosis and prognosis and the development of new molecularly targeted therapies for gastrointestinal cancers. In this review, we outline an overview of the complex mechanisms and functions of TGF-β signaling. Furthermore, we discuss the therapeutic potentials of targeting the TGF-β signaling pathway for gastrointestinal cancer treatment and discuss the remaining challenges and future perspectives on targeting this pathway.

MIR31HG, a potential lncRNA in human cancers and non-cancers

Long non-coding RNAs have recently attracted considerable attention due to their aberrant expression in human diseases. LncMIR31HG is a novel lncRNA that is abnormally expressed in multiple diseases and implicated in various stages of disease progression. A large proportion of recent studies have indicated that MIR31HG has biological functions by triggering various signalling pathways in the pathogenesis of human diseases, especially cancers. More importantly, the abnormal expression of MIR31HG makes it a potential biomarker in diagnosis and prognosis, as well as a promising target for treatments. This review aims to systematically summarize the gene polymorphism, expression profiles, biological roles, underlying mechanisms, and clinical applications of MIR31HG in human diseases.

Prognostic biomarkers of pancreatic cancer identified based on a competing endogenous RNA regulatory network

BACKGROUND

Pancreatic cancer is an insidious and heterogeneous malignancy with poor prognosis that is often locally unresectable. Therefore, determining the underlying mechanisms and effective prognostic indicators of pancreatic cancer may help optimize clinical management. This study was conducted to develop a prognostic model for pancreatic cancer based on a competing endogenous RNA (ceRNA) network.

METHODS

We obtained transcriptomic data and corresponding clinicopathological information of pancreatic cancer samples from The Cancer Genome Atlas (TCGA) database (training set). Based on the ceRNA interaction network, we screened candidate genes to build prediction models. Univariate Cox regression analysis was performed to screen for genes associated with prognosis, and least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to construct a predictive model. A receiver operating characteristic (ROC) curve was drawn, and the C-index was calculated to evaluate the accuracy of the prediction model. Furthermore, we downloaded transcriptomic data and related clinical information of pancreatic cancer samples from the Gene Expression Omnibus database (validation set) to evaluate the robustness of our prediction model.

RESULTS

Eight genes (ANLN, FHDC1, LY6D, SMAD6, ACKR4, RAB27B, AUNIP, and GPRIN3) were used to construct the prediction model, which was confirmed as an independent predictor for evaluating the prognosis of patients with pancreatic cancer through univariate and multivariate Cox regression analysis. By plotting the decision curve, we found that the risk score model is an independent predictor has the greatest impact on survival compared to pathological stage and targeted molecular therapy.

CONCLUSIONS

An eight-gene prediction model was constructed for effectively and independently predicting the prognosis of patients with pancreatic cancer. These eight genes identified show potential as diagnostic and therapeutic targets.