Sp1-driven up-regulation of miR-19a decreases RHOB and promotes pancreatic cancer Sp1-driven up-regulation of miR-19a decreases RHOB and promotes pancreatic cancer

Methylation of RNA plays an important role in cancer. Classical forms of such modifications include N6-methyladenine (m6A), 5-methylcytosine (m5C), and N1-methyladenine (m1A). Methylation-regulated long non-coding (lnc) RNAs are involved in various biological processes, such as tumor proliferation, apoptosis, immune escape, invasion, and metastasis. Therefore, we performed an analysis of transcriptomic and clinical data of pancreatic cancer samples in The Cancer Genome Atlas (TCGA). Using the co-expression method, we summarized 44 m6A/m5C/m1A-related genes and obtained 218 methylation-associated lncRNAs. Next, with COX regression, we screened 39 lncRNAs that are strongly associated with prognosis and found that their expression differed significantly between normal tissues and pancreatic cancer samples (P < 0.001). We then used the least absolute shrinkage and selection operator (LASSO) to construct a risk model comprising seven lncRNAs. In validation set, the nomogram generated by combining clinical characteristics accurately predicted the survival probability of pancreatic cancer patients at 1, 2, and 3 years after diagnosis (AUC = 0.652, 0.686, and 0.740, respectively). Tumor microenvironment analysis showed that the high-risk group had significantly more resting memory CD4 T cells, M0 macrophages, and activated dendritic cells and fewer naïve B cells, plasma cells, and CD8 T cells than the low-risk group (both P < 0.05). Most immune-checkpoint genes were significantly different between the high- and low-risk groups (P < 0.05). The Tumor Immune Dysfunction and Exclusion score showed that high-risk patients benefited more from treatment with immune checkpoint inhibitors (P < 0.001). Overall survival was also lower in high-risk patients with more tumor mutations than in low-risk patients with fewer mutations (P < 0.001). Finally, we explored the sensitivity of the high- and low-risk groups to seven candidate drugs. Our findings indicated that m6A/m5C/m1A-associated lncRNAs are potentially useful biomarkers for the early diagnosis and estimating the prognosis of, and ascertaining the responses to immunotherapy in, patients with pancreatic cancer.

Pancreatic cancer is the deadliest malignancy of the digestive system and is the seventh most common cause of cancer-related deaths worldwide. The incidence and mortality of pancreatic cancer continue to increase, and its 5-year survival rate remains the lowest among all cancers. N6-methyladenine (m6A) is the most abundant reversible RNA modification in various eukaryotic messenger and long noncoding RNAs and plays crucial roles in the occurrence and development of cancers. However, the role of m6A in pancreatic cancer remains unclear. The present study aimed to explore the role of m6A and its regulators in pancreatic cancer and assess its underlying molecular mechanism associated with pancreatic cancer cell proliferation, invasion, and metastasis. Reduced expression of the m6A demethylase, fat mass and obesity-associated protein (FTO), was responsible for the high levels of m6A RNA modification in pancreatic cancer. Moreover, FTO demethylated the m6A modification of praja ring finger ubiquitin ligase 2 (PJA2), thereby reducing its mRNA decay, suppressing Wnt signaling, and ultimately restraining the proliferation, invasion, and metastasis of pancreatic cancer cells. Altogether, this study describes new, potential molecular therapeutic targets for pancreatic cancer that could pave the way to improve patient outcome.

Background: Despite advances in the understanding of neoplasm, patients with cervical cancer still have a poor prognosis. Identifying prognostic markers of cervical cancer may enable early detection of recurrence and more effective treatment.Methods: Gene expression profiling data were acquired from the Gene Expression Omnibus database. After data normalization, genes with large variation were screened out. Next, we built co-expression modules by using weighted gene co-expression network analysis to investigate the relationship between the modules and clinical traits related to cervical cancer progression. Functional enrichment analysis was also applied on these co-expressed genes. We integrated the genes into a human protein-protein interaction (PPI) network to expand seed genes and build a co-expression network. For further analysis of the dataset, the Cancer Genome Atlas (TCGA) database was used to identify seed genes and their correlation to cervical cancer prognosis. Verification was further conducted by qPCR and the Human Protein Atlas (HPA) database to measure the expression of hub genes.Results: Using WGCNA, we identified 25 co-expression modules from 10,016 genes in 128 human cervical cancer samples. After functional enrichment analysis, the magenta, brown, and darkred modules were selected as the three most correlated modules for cancer progression. Additionally, seed genes in the three modules were combined with a PPI network to identify 31 tumor-specific genes. Hierarchical clustering and Gepia results indicated that the expression quantity of hub genes NDC80, TIPIN, MCM3, MCM6, POLA1, and PRC1 may determine the prognosis of cervical cancer. Finally, TIPIN and POLA1 were further filtered by a LASSO model. In addition, their expression was identified by immunohistochemistry in HPA database as well as a biological experiment.Conclusion: Our research provides a co-expression network of gene modules and identifies TIPIN and POLA1 as stable potential prognostic biomarkers for cervical cancer.

Background: Pancreatic cancer is a fatal malignancy of the digestive system and the 5-year survival rate remains low. Therefore, new molecular therapeutic targets are required to improve treatments, prognosis, and the survival of patients. N6-methyladenosine (m6A) is the most prevalent reversible methylation in mammalian messenger RNA (mRNA) and has critical roles in the tumorigenesis and metastasis of various malignancies. However, the role of m6A in pancreatic cancer is still unclear. Exploring genetic alterations and functional networks of m6A regulators in pancreatic cancer may provide new strategies for its treatment. Methods: In this study, we used data from the Cancer Genome Atlas (TCGA) database and other public databases through cBioPortal, LinkedOmics, UALCAN, GEPIA, STRING, and the database for annotation, visualization, and integrated discovery (DAVID) to systematically analyze the molecular alterations and functions of 20 main m6A regulators in pancreatic cancer. Results: We found that m6A regulators had widespread genetic alterations, and that their expression levels were significantly correlated with pancreatic cancer malignancy. Moreover, m6A regulators were associated with the prognosis of pancreatic cancer patients. Conclusions: m6A regulators play a crucial part in the occurrence and development of pancreatic cancer. Our study will guide further studies of m6A RNA modification in pancreatic cancer and could potentially provide new strategies for pancreatic cancer treatment.