Integration of GWAS and eQTL Analysis to Identify Risk Loci and Susceptibility Genes for Gastric Cancer

Mendelian randomization analysis identified potential genes pleiotropically associated with gout

Background

This study aims to prioritize genes potentially involved in multifactorial or causal relationships with gout.

Methods

Using the Summary Data-based Mendelian Randomization (SMR) approach, this research analyzed expression quantitative trait loci (eQTL) data from blood and renal tissues and genome-wide association study (GWAS) data related to gout. It sought to identify genetic loci potentially involved in gout. Heterogeneity testing was conducted with the HEIDI test, and results were adjusted for the False Discovery Rate (FDR). Blood cis-eQTL data were sourced from the eQTLGen Consortium's summary-level data, and renal tissue data came from the V8 release of the GTEx eQTL summary data. Gout GWAS data was sourced from the FinnGen Documentation of the R10 release.

Result

SMR analysis identified 14 gene probes in the eQTLGen blood summary-level data significantly associated with gout. The top five ranked genes are: ENSG00000169231 (labeled THBS3, PSMR = 4.16 × 10-13), ENSG00000231064 (labeled THBS3-AS1, PSMR = 1.88 × 10-8), ENSG00000163463 (labeled KRTCAP2, PSMR = 3.88 × 10-6), ENSG00000172977 (labeled KAT5, PSMR = 1.70 × 10-5), and ENSG00000161395 (labeled PGAP3, PSMR = 3.24 × 10-5). Notably, increased expression of KRTCAP2 and PGAP3 is associated with an increased risk of gout, whereas increased expression of THBS3, THBS3-AS1, and KAT5 is associated with a reduced gout risk. No significant gene associations with gout were observed in renal tissue, likely due to the limited sample size of kidney tissue.

Conclusion

Our findings have highlighted several genes potentially involved in the pathogenesis of gout. These results offer valuable insights into the mechanisms of gout and identify potential therapeutic targets for its treatment.

FBXO43 promotes cell cycle progression in cancer cells through stabilizing SKP2

FBXO43 is a member of the FBXO subfamily of F-box proteins, known to be a regulatory hub during meiosis. A body of data showed that FBXO43 is overexpressed in a number of human cancers. However, whether and how FBXO43 affects cell cycle progression and growth of cancer cells remain elusive. In this study, we provide first piece of evidence, showing a pivotal role of FBXO43 in cell cycle progression and growth of cancer cells. Specifically, FBXO43 acts as a positive cell cycle regulator with an oncogenic activity in variety types of human cancer, including non-small cell lung cancer, hepatocellular carcinoma and sarcoma. Mechanistically, FBXO43 interacts with phosphorylated SKP2 induced by AKT1, leading to reduced SKP2 auto-ubiquitylation and subsequent proteasome degradation. Taken together, our study demonstrates that FBXO43 promotes cell cycle progression by stabilizing SKP2, and FBXO43 could serve as a potential anti-cancer target.

Role of F-box proteins in human upper gastrointestinal tumors

Protein ubiquitination and degradation is an essential physiological process in almost all organisms. As the key participants in this process, the E3 ubiquitin ligases have been widely studied and recognized. F-box proteins, a crucial component of E3 ubiquitin ligases that regulates diverse biological functions, including cell differentiation, proliferation, migration, and apoptosis by facilitating the degradation of substrate proteins. Currently, there is an increasing focus on studying the role of F-box proteins in cancer. In this review, we present a comprehensive overview of the significant contributions of F-box proteins to the development of upper gastrointestinal tumors, highlighting their dual roles as both carcinogens and tumor suppressors. We delve into the molecular mechanisms underlying the involvement of F-box proteins in upper gastrointestinal tumors, exploring their interactions with specific substrates and their cross-talks with other key signaling pathways. Furthermore, we discuss the implications of F-box proteins in radiotherapy resistance in the upper gastrointestinal tract, emphasizing their potential as clinical therapeutic and prognostic targets. Overall, this review provides an up-to-date understanding of the intricate involvement of F-box proteins in human upper gastrointestinal tumors, offering valuable insights for the identification of prognostic markers and the development of targeted therapeutic strategies.

metGWAS 1.0: an R workflow for network-driven over-representation analysis between independent metabolomic and meta-genome-wide association studies

MOTIVATION

The method of genome-wide association studies (GWAS) and metabolomics combined provide an quantitative approach to pinpoint metabolic pathways and genes linked to specific diseases; however, such analyses require both genomics and metabolomics datasets from the same individuals/samples. In most cases, this approach is not feasible due to high costs, lack of technical infrastructure, unavailability of samples, and other factors. Therefore, an unmet need exists for a bioinformatics tool that can identify gene loci-associated polymorphic variants for metabolite alterations seen in disease states using standalone metabolomics.

RESULTS

Here, we developed a bioinformatics tool, metGWAS 1.0, that integrates independent GWAS data from the GWAS database and standalone metabolomics data using a network-based systems biology approach to identify novel disease/trait-specific metabolite-gene associations. The tool was evaluated using standalone metabolomics datasets extracted from two metabolomics-GWAS case studies. It discovered both the observed and novel gene loci with known single nucleotide polymorphisms when compared to the original studies.

AVAILABILITY AND IMPLEMENTATION

The developed metGWAS 1.0 framework is implemented in an R pipeline and available at: https://github.com/saifurbd28/metGWAS-1.0.

F-Box Protein 43, Stabilized by N6-Methyladenosine Methylation, Enhances Hepatocellular Carcinoma Cell Growth and Invasion via Promoting p53 Degradation in a Ubiquitin Conjugating Enzyme E2 C-Dependent Manner

The roles of F-box protein 43 (FBXO43) in carcinogenesis have been rarely revealed. The present study investigates the expression, function, and underlying mechanism of FBXO43 in hepatocellular carcinoma (HCC). Firstly, the expression and clinical significance of FBXO43 in HCC were investigated bioinformatically and experimentally using online omics data and local tissue samples. The role of N6-methyladenosine modification (m6A) of mRNA in regulating FBXO43 expression and the effects of m6A/FBXO43 axis alteration on cell proliferation and invasion were investigated further. Moreover, the underlying mechanism of the oncogenic FBXO43 was also explored. The results demonstrated that FBXO43 was significantly upregulated in HCC and was positively correlated with advanced progression and poor prognosis in patients. METTL3 and IGF2BP2 expressions were positively correlated with FBXO43 expression and served as the writer and reader of FBXO43 m6A, respectively, which stabilized and upregulated FBXO43 mRNA in HCC. FBXO43 silencing significantly reduced cell proliferation and invasion, and ectopic expression of FBXO43 could significantly restore the inhibitory effects caused by METTL3 and IGF2BP2 depletion in HCC cells. Mechanistically, FBXO43 depletion reduced the expression of UBE2C, a p53 ubiquitin-conjugating enzyme, suppressed proteasomal degradation of p53, and thus inhibited cell proliferation and invasion in HCC. In summary, the present study revealed that METTL3/IGF2BP2 mediated m6A contributed to the upregulation of FBXO43 that promoted the malignant progression of HCC by stimulating p53 degradation in a UBE2C-dependent manner, highlighting the promising application of FBXO43 as a target in HCC treatment.

Association between F-box-only protein 43 overexpression and hepatocellular carcinoma pathogenesis and prognosis

BACKGROUND

Despite great advances in the prevention, diagnosis, treatment, and management regarding hepatocellular carcinoma (HCC), the overall prognosis of HCC remains unfavorable. The expression profile, prognostic role, and biological functions of F-box-only protein 43 (FBXO43) in HCC remain unclear. Here, we determine the expression profile and prognostic value of FBXO43 in patients with HCC.

MATERIALS AND METHODS

A total of 467 HCC patients and their clinicopathological data were collected from the Second Affiliated Hospital of Jiaxing University, the Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx) databases. The expression profile, prognostic value, biological functions, and underlying mechanism of its involvement of FBXO43 were explored based on TCGA, Gene Expression Omnibus (GEO), LinkedOmics, and Cancer Dependency Map (DepMap). The expression of FBXO43 in 93 paired liver tissues was investigated via immunohistochemical staining, tissue microarray analysis, and Western blot. The prognostic value was assessed using survival analysis.

RESULTS

FBXO43 RNA was upregulated in HCC liver tissues and was associated with an unfavorable prognosis (p < 0.05). Furthermore, FBXO43 protein was overexpressed in HCC liver tissues compared with that in paired normal liver tissues. Overexpression of FBXO43 protein was significantly associated with advanced TNM stage, large tumor size, lymphatic invasion, distant metastasis, earlier cancer recurrence, and decreased overall survival after radical surgery (p < 0.05). Cox regression analysis showed that FBXO43 had significant prognostic value in HCC. Importantly, FBXO43 and its co-expressed genes were mainly involved in cell cycle regulation, DNA replication, metabolic regulation, and so on. FBXO43 knockdown could significantly affect the HCC cell lines growth and proliferation.

CONCLUSIONS

We first revealed that FBXO43 was overexpressed in liver HCC tissues at the RNA and protein levels and served as an independent prognostic factor for HCC patients. Therefore, FBXO43 is worth investigating as a potential HCC treatment target.

IsomiR-eQTL: A Cancer-Specific Expression Quantitative Trait Loci Database of miRNAs and Their Isoforms

The identification of expression quantitative trait loci (eQTL) is an important component in efforts to understand how genetic variants influence disease risk. MicroRNAs (miRNAs) are short noncoding RNA molecules capable of regulating the expression of several genes simultaneously. Recently, several novel isomers of miRNAs (isomiRs) that differ slightly in length and sequence composition compared to their canonical miRNAs have been reported. Here we present isomiR-eQTL, a user-friendly database designed to help researchers find single nucleotide polymorphisms (SNPs) that can impact miRNA (miR-eQTL) and isomiR expression (isomiR-eQTL) in 30 cancer types. The isomiR-eQTL includes a total of 152,671 miR-eQTLs and 2,390,805 isomiR-eQTLs at a false discovery rate (FDR) of 0.05. It also includes 65,733 miR-eQTLs overlapping known cancer-associated loci identified through genome-wide association studies (GWAS). To the best of our knowledge, this is the first study investigating the impact of SNPs on isomiR expression at the genome-wide level. This database may pave the way for researchers toward finding a model for personalised medicine in which miRNAs, isomiRs, and genotypes are utilised.

Prognostic and Therapeutic Significance of BTN3A Proteins in Tumors

The Butyrophilin 3A (BTN3A) family is a type I transmembrane protein belonging to the immunoglobulin (Ig) superfamily. The family contains three members: BTN3A1, BTN3A2 and BTN3A3, which share 95% homology in the extracellular domain. The expression of BTN3A family members is different in different types of tumors, which plays an important role in tumor prognosis. Among them, there are many studies on tumor immunity of BTN3A1, which shows that it is essential for the activation of Vγ9Vδ2 T cells, while BTN3A3 is expected to become a potential therapeutic target for breast cancer. Recent studies have shown that the BTN3A family is closely related to the occurrence and development of tumors. Now the BTN3A family has become one of the research hotspots and is expected to become new tumor prediction and treatment targets.