RNA dynamics: destabilizing mRNAs promotes metastasis

Identification of heterogeneous nuclear ribonucleoprotein as a candidate biomarker for diagnosis and prognosis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high mortality rate. However, spliceosomal genes are still lacking in the diagnosis and prognosis of HCC.

Methods

Identification of differentially expressed genes (DEGs) was performed using the limma package in R software. Modules highly related to HCC were obtained by weighted gene co-expression network analysis (WGCNA), and the module genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The biomarker for diagnosing HCC was determined by receiver operating characteristic (ROC) curve analysis, and the effect of the biomarker in the diagnosis of HCC was evaluated by performing five-fold cross-validation with logistic regression. HCC specimens from preoperatively treated patients were tested for biomarker by real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-Meier analysis was used to assess the relationship between biomarker and patient survival. The role of biomarker was evaluated using ESTIMATE analysis in the tumor microenvironment.

Results

In this study, 389 DEGs were screened out from three Gene Expression Omnibus (GEO) datasets. We also found that the turquoise module of 123 genes from The Cancer Genome Atlas (TCGA) data was the key module with the highest correlation with HCC traits. Then, 123 genes were analyzed using the KEGG enrichment pathway, and eight genes were found to be most significantly related to the spliceosome pathway. We selected 8 genes and 389 DEGs shared genes, and finally got the only gene, heterogeneous nuclear ribonucleoprotein (hnRNPU). The high expression of hnRNPU was associated with poor prognosis of HCC, and hnRNPU was a biomarker for diagnosing HCC. In the tissues of patients with excellent HCC treatment hnRNPU messenger RNA (mRNA) was lower than in the tissues of patients with poor HCC treatment. High expression of hnRNPU was significantly increased in HCC patients with low stromal (P<0.05), low immune (P<0.05), and low estimation scores (P<0.05), and with high tumor purity (P<0.05) and high malignant progression (P<0.05) of the HCC.

Conclusions

The hnRNPU gene identified in this study may become a new biomarker for the diagnosis and prognosis of HCC.

The splicing regulatory factor hnRNPU is a novel transcriptional target of c-Myc in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common liver cancer with high mortality. Here, we found that hnRNPU is overexpressed in HCC tissues and is correlated with the poor prognosis of HCC patients. Besides, hnRNPU is of high significance in regulating the proliferation, apoptosis, self-renewal, and tumorigenic potential of HCC cells. Mechanismly, c-Myc regulates hnRNPU expression at the transcriptional level, and meanwhile, hnRNPU stabilizes the mRNA of c-MYC. We found that the hnRNPU and c-Myc regulatory loop exerts a synergistic effect on the proliferation and self-renewal of HCC, and promotes the HCC progression. Taken together, hnRNPU functions as a novel transcriptional target of c-Myc and promotes HCC progression, which may become a promising target for the treatment of c-Myc-driven HCC.

The genetic script of metastasis

Metastasis is a pivotal event that changes the course of cancers from benign and treatable to malignant and difficult to treat, resulting in the demise of patients. Understanding the genetic control of metastasis is thus crucial to develop efficient and sustainable targeted therapies. Here we discuss the alterations in epigenetic mechanisms, transcription, chromosomal instability, chromosome imprinting, non-coding RNAs, coding RNAs, mutant RNAs, enhancers, G-quadruplexes, and copy number variation to dissect the genetic control of metastasis. We conclude that the genetic control of metastasis is predominantly executed through epithelial to mesenchymal transition and evasion of cell death. We discuss how genetic regulatory mechanisms can be harnessed for therapeutic purposes to achieve sustainable control over cancer metastasis.

FAM46 proteins are novel eukaryotic non-canonical poly(A) polymerases

FAM46 proteins, encoded in all known animal genomes, belong to the nucleotidyltransferase (NTase) fold superfamily. All four human FAM46 paralogs (FAM46A, FAM46B, FAM46C, FAM46D) are thought to be involved in several diseases, with FAM46C reported as a causal driver of multiple myeloma; however, their exact functions remain unknown. By using a combination of various bioinformatics analyses (e.g. domain architecture, cellular localization) and exhaustive literature and database searches (e.g. expression profiles, protein interactors), we classified FAM46 proteins as active non-canonical poly(A) polymerases, which modify cytosolic and/or nuclear RNA 3′ ends. These proteins may thus regulate gene expression and probably play a critical role during cell differentiation. A detailed analysis of sequence and structure diversity of known NTases possessing PAP/OAS1 SBD domain, combined with state-of-the-art comparative modelling, allowed us to identify potential active site residues responsible for catalysis and substrate binding. We also explored the role of single point mutations found in human cancers and propose that FAM46 genes may be involved in the development of other major malignancies including lung, colorectal, hepatocellular, head and neck, urothelial, endometrial and renal papillary carcinomas and melanoma. Identification of these novel enzymes taking part in RNA metabolism in eukaryotes may guide their further functional studies.

EPMA position paper in cancer: current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision.