Meta-analysis reveals an association between signal transducer and activator of transcription-4 polymorphism and hepatocellular carcinoma risk

Assessment of STAT4 Variants and Risk of Hepatocellular Carcinoma in Latin Americans and Europeans

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. The STAT4 rs7574865 genetic variant has been associated with an increased risk of developing HCC in Asian populations. However, this association has not been studied in Latin America and is poorly assessed in European populations. This case-control study investigated the association between STAT4 rs7574865 and HCC risk in these populations. We evaluated DNA samples from seven medical institutions across six Latin American countries and one Dutch institution in 1060 individuals (344 HCC and 716 controls). STAT4 rs7574865 SNP was genotyped using TaqMan-genotyping assay and analyzed using logistic regression. We found no significant association between the homozygous risk allele (G) of STAT4 and HCC development in either population, with odds ratios (OR) for GG versus TT of 0.85 (CI: 0.48-1.52, p = 0.58) and 0.81 (CI: 0.34-1.93, p = 0.67) for Latin Americans and Europeans respectively. No correlation was found between the risk allele and HCC based on underlying liver disease. However, we found that Latin Americans of European ancestry were more likely to carry the risk allele. Our results suggest that the STAT4 SNP rs7574865 does not influence the risk of developing HCC in Latin American or European populations, highlighting the importance of evaluating genetic risk factors in various ethnic groups and understanding the possible influence of ancestry on the genetic basis of disease.

Gene variations related to the hepatocellular carcinoma: Results from a field synopsis and Bayesian revaluation

Hepatocellular carcinoma (HCC) is considered as the second cause of cancer-related deaths worldwide. Genetic variations are associated with HCC risk, an issue that has been the subject of several meta-analyses. However, meta-analyses have an important limitation on the likelihood of false positive data. Henceforth, this study aimed to assess the level of noteworthiness in the meta-analyses by means of a Bayesian approach. A systematic search was performed for meta-analyses with associations between gene polymorphisms and HCC. The calculations for the False-Positive Rate Probability (FPRP) and the Bayesian False Discovery Probability (BFDP) were performed to assess the noteworthiness with a statistical power of 1.2 and 1.5 of Odds Ratio at a prior probability of 10^-3 and 10^-5. The quality of studies was evaluated by the Venice criteria. As additional analyses, the gene-gene and protein-protein networks were designed for these genes and products. As results, we found 33 meta-analytic studies on 45 polymorphisms occurring in 35 genes. A total of 1,280 values for FPRP and BFDP were obtained. Seventy-five for FPRP (5.86%) and 95 for BFDP (14.79%) were noteworthy. In conclusion, the polymorphisms in CCND1, CTLA4, EGF, IL6, IL12A, KIF1B, MDM2, MICA, miR-499, MTHFR, PNPLA3, STAT4, TM6SF2, and XPD genes were considered as noteworthy biomarkers for HCC risk.

STAT4 genetic polymorphism significantly affected HBeAg seroconversion in HBeAg-positive chronic hepatitis B patients receiving Peginterferon-α therapy: A prospective cohort study in China Running title: STAT4 variation affecting response to PegIFN-α therapy

AIM

Variant in STAT4 was reported to correlate with response of IFN-α in a retrospective study in HBeAg-positive chronic hepatitis B (CHB) patients. Here we conducted a prospective study to analyze the effect of STAT4 genetic polymorphism on response of PegIFN-α-2a in HBeAg-positive patients.

METHOD

A prospective, multi-center, open-label, paralleled cohort study was performed. 150 treat-naïve and 156 nucleos(t)ide analogues (NAs)-experienced HBeAg-positive CHB patients were enrolled respectively. All patients received PegIFN-α-2a treatment for 48 weeks and 24-week follow-up post PegIFN-α-2a treatment. Before treatment, STAT4 genetic polymorphism were determined by PCR and DNA sequencing. Serological markers, serum HBV DNA level and adverse events were collected at each visit point.

RESULT

We observed a larger reduction of HBV DNA load and significant higher HBeAg seroconversion rate in GT/TT than in GG group at week 72 (P = 0.002 and P = 0.023) in treat-naïve patients. In NAs-experienced patients, the HBeAg seroconversion rate in GT/TT group was higher than in GG group at week 72 (P = 0.005). STAT4 rs7574865 gene polymorphism was the strongest independent predictor for HBeAg seroconversion in both two paralleled cohorts. Also, patients in GT/TT group had higher HBsAg loss rate than in GG group in the study. There was no significant difference in adverse events between GG and GT/TT groups.

CONCLUSION

This prospective cohort study confirmed that STAT4 rs7574865 polymorphism is associated with HBeAg seroconversion and HBsAg loss irrespective of naïve and NAs-experienced HBeAg-positive CHB patients treated with PegIFN-α-2a. This article is protected by copyright. All rights reserved.

Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

A new discovery of STAT4 single nucleotide polymorphisms associated with hepatocellular carcinoma risk in Chinese Han population: a case-control study

BACKGROUND

Hepatocellular carcinoma (HCC) is a common fatal malignant tumor worldwide. STAT4 is HCC susceptibility gene identified by genome-wide association study. The purpose of this study was to determine the association between four candidate single nucleotide polymorphisms (SNPs) in STAT4 genes and HCC risk in Chinese Han population.

METHODS

A case-control study was conducted to assess the association between STAT4 SNPs and HCC risk in 1011 Chinese Han population. Agena MassARRAY was used to genotype SNPs. The association between SNPs and HCC susceptibility under different genetic models was evaluated by logistic regression analysis. Multifactorial dimension reduction (MDR) analyzed the interaction of 'SNP-SNP' in HCC risk. The difference of clinical characteristics between different genotypes was completed by ANOVA.

RESULTS

The results showed that STAT4 rs11889341 was significantly associated with HCC risk under multiple genetic models (homozygote: OR = 0.60, p = 0.033; recessive: OR = 0.63, p = 0.028; log-additive: OR = 0.83, p = 0.032). The results of subgroup analysis showed that STAT4 rs11889341 is significantly associated with HCC risk with participants who were > 55 years, male or smoking. Both STAT4 rs7574865 and rs10174238 were significantly associated with HCC risk among participants who were > 55 years old, smoking or drinking. STAT4 haplotype (Trs11889341Trs7574865) could reduce the risk of HCC. In addition, rs11889341 and rs7574865 were significantly associated with the level of serum ferritin.

CONCLUSION

STAT4 rs11889341, rs7574865 or rs10174238 is potentially associated with HCC risk in Chinese Han population. In particular, rs11889341 showed outstanding association with HCC risk.

MicroRNA-200a and microRNA-141 have a synergetic effect on the suppression of epithelial-mesenchymal transition in liver cancer by targeting STAT4

MicroRNAs (miRNAs or miRs) are non-coding small RNAs that target specific messenger RNAs to inhibit protein translation. miR-200a and miR-141 function as tumor suppressors by targeting STAT4. These two miRNAs belong to the same family, and their expression is often decreased in various cancer types, but are located on different chromosomes of the human genome. The present study showed that the expression levels of miR-141 and miR-200a in serum and cells of liver cancer are significantly downregulated. The expression levels of miR-141 and miR-200a are closely associated with clinicopathological features of liver cancer, especially metastasis and invasion. It is first reported that STAT4 is the new common target gene of miR-141 and miR-200a. In the present study, miR-141 and miR-200a were confirmed to inhibit the expression of E-cadherin and vimentin synergistically during epithelial-mesenchymal transition to regulate the proliferation, migration and invasion of liver cancer cells by targeting STAT4. Simultaneous overexpression of miR-200a and miR-141 resulted in stronger effects compared with each miRNA alone. In addition, overexpression of STAT4 significantly reversed the tumor suppressive roles of miR-200a and miR-141 in liver cancer cells. These findings enrich the tumor suppressor mechanisms of the miR-200 family, and may also provide new experimental and theoretical basis for the use of miRNAs for early diagnosis, prognosis and thorough treatment of liver cancer.

Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk

Prediction of hepatocellular carcinoma (HCC) risk becomes increasingly important with recently emerging HCC-predisposing conditions, namely non-alcoholic fatty liver disease and cured hepatitis C virus infection. These etiologies are accompanied with a relatively low HCC incidence rate (~1% per year or less), while affecting a large patient population. Hepatitis B virus infection remains a major HCC risk factor, but a majority of the patients are now on antiviral therapy, which substantially lowers, but does not eliminate, HCC risk. Thus, it is critically important to identify a small subset of patients who have elevated likelihood of developing HCC, to optimize the allocation of limited HCC screening resources to those who need it most and enable cost-effective early HCC diagnosis to prolong patient survival. To date, numerous clinical-variable-based HCC risk scores have been developed for specific clinical contexts defined by liver disease etiology, severity, and other factors. In parallel, various molecular features have been reported as potential HCC risk biomarkers, utilizing both tissue and body-fluid specimens. Deep-learning-based risk modeling is an emerging strategy. Although none of them has been widely incorporated in clinical care of liver disease patients yet, some have been undergoing the process of validation and clinical development. In this review, these risk scores and biomarker candidates are overviewed, and strategic issues in their validation and clinical translation are discussed.

Omics-derived hepatocellular carcinoma risk biomarkers for precision care of chronic liver diseases

Precise hepatocellular carcinoma (HCC) risk prediction will play increasingly important roles with the contemporary HCC etiologies, that is, non-alcoholic fatty liver disease and resolved hepatitis C virus infection. Because the HCC incidence rate in this emerging patient population is relatively low (~1% per year), identification of a subset of patients at the highest risk is critical to concentrate the effort and resources of regular HCC screening to those who most need it. Omics profiling has been derived using several candidate HCC risk biomarkers, which could refine HCC screening by enabling individual risk-based personalized or risk-stratified patient management. Various types of biomolecules have been explored as sources of information to predict HCC risk at various time horizons. Germline DNA polymorphisms likely reflect race/ethnicity- and/or etiology-specific susceptibility to HCC development or chronic liver disease progression toward carcinogenesis. Transcriptomic dysregulations in the diseased liver capture functional molecular status supporting oncogenesis such as inflammatory pathway and myofibroblast activation. Circulating nucleic acids, proteins, and metabolites could serve as less-invasive measures of molecular HCC risk. Characterization of gut microbiota could also inform HCC risk estimation. Each biomarker could have its niche of clinical application depending on logistics of use, performance, and costs with a goal to eventually improve patient prognosis as a part of the whole algorithm of chronic liver disease management.

Analysis of clinical significance and prospective molecular mechanism of main elements of the JAK/STAT pathway in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one the most common malignancies and has poor prognosis in patients. The aim of the present study is to explore the clinical significance of the main genes involved in the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway in HCC. GSE14520, a training cohort containing 212 hepatitis B virus-infected HCC patients from the Gene Expression Omnibus database, and data from The Cancer Genome Atlas as a validation cohort containing 370 HCC patients, were used to analyze the diagnostic and prognostic significance for HCC. Joint-effect analyses were performed to determine diagnostic and prognostic significance. Nomograms and risk score models were constructed to predict HCC prognosis using the two cohorts. Additionally, molecular mechanism analysis was performed for the two cohorts. Prognosis-associated genes in the two cohorts were further validated for differential expression using reverse transcription-quantitative polymerase chain reaction of 21 pairs of hepatitis B virus-infected HCC samples. JAK2, TYK2, STAT3, STAT4 and STAT5B had diagnostic significance in the two cohorts (all area under curves >0.5; P≤0.05). In addition, JAK2, STAT5A, STAT6 exhibited prognostic significance in both cohorts (all adjusted P≤0.05). Furthermore, joint-effect analysis had advantages over using one gene alone. Molecular mechanism analyses confirmed that STAT6 was enriched in pathways and terms associated with the cell cycle, cell division and lipid metabolism. Nomograms and risk score models had advantages for HCC prognosis prediction. When validated in 21 pairs of HCC and non-tumor tissue, STAT6 was differentially expressed, whereas JAK2 was not differentially expressed. In conclusion, JAK2, STAT5A and STAT6 may be potential prognostic biomarkers for HCC. JAK2, TYK2, STAT3, STAT4 and STAT5B may be potential diagnostic biomarkers for HCC. STAT6 has a role in HCC that may be mediated via effects on the cell cycle, cell division and lipid metabolism.

Association of STAT3 and STAT4 polymorphisms with susceptibility to chronic hepatitis B virus infection and risk of hepatocellular carcinoma: a meta-analysis

Background: It has been reported that polymorphisms of signal transducer and activator of transcription (STAT) 3 and STAT4 might be associated with susceptibility to hepatitis B virus (HBV) infection and risk of chronic hepatocellular carcinoma (HCC). Owing to limitation of sample size and inconclusive results, we conducted a meta-analysis to clarify the association. Methods: We identified relevant studies by a systematic search of Medline/PubMed, Embase, Web of Science and the Cochrane Library up to 20 February 2019. The strength of the association measured by odds ratios (OR) with 95% confidence intervals (CIs) was studied. All the statistical analyses were conducted based on Review Manager 5.3 software. Results: A total of 5242 cases and 2717 controls from five studies were included for the STAT3 polymorphism, 5902 cases and 7867 controls from nine studies for the STAT4 polymorphism. Our results suggested that STAT3 rs1053004 polymorphism was a significant risk factor of chronic HBV infection (C vs. T: OR = 1.17, 95% CI: 1.07–1.29, P_A=0.0007; CC + CT vs. TT: OR = 1.38, 95% CI: 1.09–1.76, P_A=0.008). Validation with all the genetic models revealed that rs7574865 polymorphism of STAT4 gene was closely associated with chronic HBV infection (P_A<0.01) and chronic hepatitis B (CHB)-related HCC (P_A<0.05). Meanwhile, the authenticity of the above meta-analysis results was confirmed by trial sequential analysis (TSA). Conclusions: The meta-analysis showed that STAT3 rs1053004 polymorphism may be the risk for developing chronic HBV infection but not associated with HCC. The present study also indicates that STAT4 rs7574865 polymorphism increased the risk of chronic HBV infection and HCC.

Circulating predictive and diagnostic biomarkers for hepatitis B virus-associated hepatocellular carcinoma

Chronic hepatitis B virus (HBV) infected patients have an almost 100-fold increased risk to develop hepatocellular carcinoma (HCC). HCC is the fifth most common and third most deadly cancer worldwide. Up to 50% of newly diagnosed HCC cases are attributed to HBV infection. Early detection improves survival and can be achieved through regular screening. Six-monthly abdominal ultrasound, either alone or in combination with alpha-fetoprotein serum levels, has been widely endorsed for this purpose. Both techniques however yield limited diagnostic accuracy, which is not improved when they are combined. Alternative circulating or histological markers to predict or diagnose HCC are therefore urgently needed. Recent advances in systems biology technologies have enabled the identification of several new putative circulating biomarkers. Although results from studies assessing combinations of these biomarkers are promising, evidence for their clinical utility remains low. In addition, most of the studies conducted so far show limitations in design. Attention must be paid for instance to different ethnicities and different etiologies when studying biomarkers for hepatocellular carcinoma. This review provides an overview on the current understandings and recent progress in the field of diagnostic and predictive circulating biomarkers for hepatocellular carcinoma in chronically infected HBV patients and discusses the future prospects.