Low Tristetraprolin Expression Is Associated with Lethal Prostate Cancer

Precision Medicine and Novel Therapeutic Strategies in Detection and Treatment of Cancer: Highlights from the 58th IACR Annual Conference

Innovation in both detection and treatment of cancer is necessary for the constant improvement in therapeutic strategies, especially in patients with novel or resistant variants of cancer. Cancer mortality rates have declined by almost 30% since 1991, however, depending on the cancer type, acquired resistance can occur to varying degrees. To combat this, researchers are looking towards advancing our understanding of cancer biology, in order to inform early detection, and guide novel therapeutic approaches. Through combination of these approaches, it is believed that a more complete and thorough intervention on cancer can be achieved. Here, we will discuss the advances and approaches in both detection and treatment of cancer, presented at the 58th Irish Association for Cancer Research (IACR) annual conference.

A polymorphism in the promoter of FRAS1 is a candidate SNP associated with metastatic prostate cancer

BACKGROUND

Inflammation and one of its mediators, NF-kappa B (NFκB), have been implicated in prostate cancer carcinogenesis. We assessed whether germline polymorphisms associated with NFκB are associated with the risk of developing lethal disease (metastases or death from prostate cancer).

METHODS

Using a Bayesian approach leveraging NFκB biology with integration of publicly available datasets we used a previously defined genome-wide functional association network specific to NFκB and lethal prostate cancer. A dense-module-searching method identified modules enriched with significant genes from a genome-wide association study (GWAS) study in a discovery data set, Physicians' Health Study and Health Professionals Follow-up Study (PHS/HPFS). The top 48 candidate single nucleotide polymorphisms (SNPs) from the dense-module-searching method were then assessed in an independent prostate cancer cohort and the one SNP reproducibly associated with lethality was tested in a third cohort. Logistic regression models evaluated the association between each SNP and lethal prostate cancer. The candidate SNP was assessed for association with lethal prostate cancer in 6 of 28 studies in the prostate cancer association group to investigate cancer associated alterations in the genome (PRACTICAL) Consortium where there was some medical record review for death ascertainment which also had SNP data from the ONCOARRAY platform. All men self-identified as Caucasian.

RESULTS

The rs1910301 SNP which was reproducibly associated with lethal disease was nominally associated with lethal disease (odds ratio [OR] = 1.40; p = .02) in the discovery cohort and the minor allele was also associated with lethal disease in two independent cohorts (OR = 1.35; p = .04 and OR = 1.35; p = .07). Fixed effects meta-analysis of all three cohorts found an association: OR = 1.37 (95% confidence interval [CI]: 1.15-1.62, p = .0003). This SNP is in the promoter region of FRAS1, a gene involved in epidermal-basement membrane adhesion and is present at a higher frequency in men with African ancestry. No association was found in the subset of studies from the PRACTICAL consortium studies which had a total of 106 deaths out total of 3263 patients and a median follow-up of 4.4 years.

CONCLUSIONS

Through its connection with the NFκB pathway, a candidate SNP with a higher frequency in men of African ancestry without cancer was found to be associated with lethal prostate cancer across three well-annotated independent cohorts of Caucasian men.

Tristetraprolin, a Potential Safeguard Against Carcinoma: Role in the Tumor Microenvironment

Tristetraprolin (TTP), a well-known RNA-binding protein, primarily affects the expression of inflammation-related proteins by binding to the targeted AU-rich element in the 3' untranslated region after transcription and subsequently mediates messenger RNA decay. Recent studies have focused on the role of TTP in tumors and their related microenvironments, most of which have referred to TTP as a potential tumor suppressor involved in regulating cell proliferation, apoptosis, and metastasis of various cancers, as well as tumor immunity, inflammation, and metabolism of the microenvironment. Elevated TTP expression levels could aid the diagnosis and treatment of different cancers, improving the prognosis of patients. The aim of this review is to describe the role of TTP as a potential safeguard against carcinoma.

The oncogenic and tumor suppressive roles of RNA-binding proteins in human cancers

Posttranscriptional regulation is a mechanism for the cells to control gene regulation at the RNA level. In this process, RNA-binding proteins (RBPs) play central roles and orchestrate the function of RNA molecules in multiple steps. Accumulating evidence has shown that the aberrant regulation of RBPs makes  contributions to the initiation and progression of tumorigenesis via numerous mechanisms such as genetic changes, epigenetic alterations, and noncoding RNA-mediated regulations. In this article, we review the effects caused by RBPs and their functional diversity in the malignant transformation of cancer cells that occurs through the involvement of these proteins in various stages of RNA regulation including alternative splicing, stability, polyadenylation, localization, and translation. Besides this, we review the various interactions between RBPs and other crucial posttranscriptional regulators such as microRNAs and long noncoding RNAs in the pathogenesis of cancer. Finally, we discuss the potential approaches for targeting RBPs in human cancers.

Accessible Pipeline for Translational Research Using TCGA: Examples of Relating Gene Mechanism to Disease-Specific Outcomes

Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools to conduct common statistical analyses of The Cancer Genome Atlas (TCGA) data. These tools have been developed in response to requests from our collaborators to ask questions, validate findings, and better understand the function of their gene of interest. We describe here what data we have used, how to obtain it, and what figures we have found useful.