It has been postulated that non-steroidal anti-inflammatory drugs (NSAIDs) use leads to decreased prostate cancer (PCa) risk. In recent years, NSAIDs’ role in PCa development has been extensively studied; however, there is not yet a definitive answer. Moreover, the epidemiological results for NSAIDs’ effect on PCa-specific mortality have been inconsistent. Therefore, we performed a meta-analysis to examine the controversy. We performed a literature database search and included all published studies conducted in the general population exposed to any NSAID, extracting an odds ratio (OR) or a hazard ratio (HR) with 95% confidence intervals (95% CIs) that compared the incidence of PCa or PCa-specific mortality with non-exposure. We derived a pooled OR or HR using random or fixed effects models, as appropriate. Subgroup analyses were also performed. Thirty-nine studies (20 case–control and 19 cohort studies) were included in this analysis. Thirty-one studies were available concerning NSAID use and PCa incidence and eight studies on PCa-specific mortality. Compared to non-use, aspirin use was statistically significantly associated with PCa incidence risk, and the association was slightly stronger for advanced PCa than for total PCa (OR = 0.92, 95% CI = 0.87 to 0.97 for total PCa; OR = 0.81, 95% CI = 0.73 to 0.89 for advanced PCa). Aspirin use seems also to be associated with a modest reduction in PCa-specific mortality (HR = 0.86, 95% CI = 0.78 to 0.96 for total PCa; OR = 0.81, 95% CI = 0.71 to 0.92 for advanced PCa). Generally, the pooled effects for any NSAIDs, NA-NSAIDs and cyclooxygenase-2 inhibitors demonstrated no adverse or beneficial effects on PCa development or PCa-specific mortality, but the results were not consistent. The effect estimates did not vary markedly when stratified by study design and study quality but varied by geographic region. Furthermore, long-term aspirin use (≥4 years) was also significantly associated with reduced PCa incidence (OR = 0.88, 95% CI 0.79 to 0.99). The present meta-analysis provides support for the hypothesis that aspirin use is inversely related to PCa incidence and PCa-specific mortality. The effect estimates, varying by geographic region, deserve further investigation.

Aims: In the cancer-related research field, there is currently a major need for a greater number of valuable biomarkers to predict the prognosis of hepatocellular carcinoma (HCC). In this study, we aimed to screen hub genes related to immune cell infiltration and explore their prognostic value for HCC.Methods: We analyzed five datasets (GSE46408, GSE57957, GSE74656, GSE76427, and GSE87630) from the Gene Expression Omnibus database to screen the differentially expressed genes (DEGs). A protein–protein interaction network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes; then, the hub genes were identified. Functional enrichment of the genes was performed on the Metascape website. Next, the expression of these hub genes was validated in several databases, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Human Protein Atlas. We explored the correlations between the hub genes and infiltrated immune cells in the TIMER2.0 database. The survival curves were generated in GEPIA2, and the univariate and multivariate Cox regression analyses were performed using TIMER2.0.Results: The top ten hub genes [DNA topoisomerase II alpha (TOP2A), cyclin B2 (CCNB2), protein regulator of cytokinesis 1 (PRC1), Rac GTPase-activating protein 1 (RACGAP1), aurora kinase A (AURKA), cyclin-dependent kinase inhibitor 3 (CDKN3), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle-associated 5 (CDCA5), abnormal spindle microtubule assembly (ASPM), and non-SMC condensin I complex subunit G (NCAPG)] were identified in subsequent analysis. These genes are most markedly enriched in cell division, suggesting their close association with tumorigenesis. Multi-database analyses validated that the hub genes were upregulated in HCC tissues. All hub genes positively correlated with several types of immune infiltration, including B cells, CD4⁺ T cells, macrophages, and dendritic cells. Furthermore, these hub genes served as independent prognostic factors, and the expression of these hub genes combing with the macrophage levels could help predict an unfavorable prognosis of HCC.Conclusion: In sum, these hub genes (TOP2A, CCNB2, PRC1, RACGAP1, AURKA, CDKN3, NUSAP1, CDCA5, ASPM, and NCAPG) may be pivotal markers for prognostic prediction as well as potentially work as targets for immune-based intervention strategies in HCC.

Accumulated evidence has indicated a correlation between S100A4 expression and colorectal cancer (CRC) progression. However, its prognostic significance for patients with CRC remains inconclusive. To clarify their relationship, a meta-analysis of the relevant published studies was performed. PubMed, Cochrane Library, and Web of Science databases were electronically searched. All studies evaluating the prognostic value of S100A4 expression in CRC patients regarding survival and a series of clinicopathological parameters were included. The effect of S100A4 expression on the overall survival (OS) and disease-free survival (DFS) were measured by pooled hazard ratios (HRs) and 95% confidence intervals (CIs), while the effect of S100A4 expression on the clinicopathological parameters were measured by the pooled odds ratios (ORs) and their 95% CIs. Eleven studies (2,824 patients in total) were included in the meta-analysis. Overall, S100A4 overexpression was significantly associated with worse OS (HR = 1.90, 95% CI: 1.58–2.29, P <0.001), and worse DFS (HR = 2.16, 95% CI: 1.53–3.05, P <0.001) in patients with CRC. Subgroup analyses showed that S100A4 overexpression was significantly correlated with poor OS in Asian, European, and Australian patients and patients treated with surgery or chemotherapy. Additionally, there were significant associations between S100A4 expression and several clinicopathological parameters (tumour location, lymph node metastasis, nodal status, TNM stage, and tumour depth). This meta-analysis indicates that S100A4 overexpression seems to correlate with tumour progression and poor prognosis of CRC patients. It may be a useful marker to predict progression and prognosis of CRC. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/8643820431072915

Tumor necrosis factor-alpha (TNF-α) is an important inflammatory cytokine that may play a role in controlling the progression of prostate cancer. Two common polymorphisms in the TNF-α gene, −308G/A and −238C/T, have been suggested to alter the risk for prostate cancer, but the results have been inconclusive so far. In order to obtain a better understanding of the effects of these two polymorphisms on prostate cancer risk, all available studies were considered in a meta-analysis. We conducted a comprehensive literature search in the Cochrane Library, PubMed, EMBASE, Chinese Biomedical Literature database (CBM), and the China National Knowledge Infrastructure (CNKI). The associations were evaluated by calculating the pooled odds ratio (OR) with 95% confidence interval (95% CI). In this meta-analysis, we included 14 studies with 5,757 patients and 6,137 control subjects for the TNF-α-308G/A polymorphism and 1,967 patients and 2,004 control subjects for the TNF-α-238C/T polymorphism. A significantly increased prostate cancer risk was found to be associated with the TNF-α-308C/T polymorphism in studies with healthy volunteers (AA + AG vs. GG: OR = 1.531, 95% CI = 1.093–2.145; P = 0.013; AG vs. GG: OR = 1.477, 95% CI = 1.047–2.085; P = 0.026). No significant association was found between the TNF-α-238G/A polymorphism and prostate cancer risk in the overall or subgroup analyses. There was no risk of publication bias in this meta-analysis. Our results suggest that while the TNF-α-238G/A polymorphism may not be associated with prostate cancer the TNF-α-308C/T polymorphism may significantly contribute to prostate cancer susceptibility in healthy volunteers. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1629288120116301

Background: Catechol-O-methyltransferase (COMT) is one of the most important enzymes involved in estrogen metabolism and its functional genetic polymorphisms may be associated with breast cancer (BC) risk. Many epidemiological studies have been conducted to explore the association between theCOMTVal158Met polymorphism and breast cancer risk. However, the results remain inconclusive. In order to derive a more precise estimation of this relationship, a large meta-analysis was performed in this study.Methods: Systematic searches of the PubMed, Embase and Cochrane Library were performed. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to estimate the strength of the association.Results: A total of 56 studies including 34,358 breast cancer cases and 45,429 controls were included. Overall, no significant associations between theCOMTVal158Met polymorphism and breast cancer risk were found for LL versus HH, HL versus HH, LL versus HL, recessive model LL versus HL+HH, and dominant model LL+HL versus HH. In subgroup analysis by ethnicity, source of controls, and menopausal status, there was still no significant association detected in any of the genetic models.Conclusion: Our meta-analysis results suggest that theCOMTVal158Met polymorphism may not contribute to breast cancer susceptibility.Virtual slides: The virtual slides(s) for this article can be found here:http://www.diagnosticpathology.diagnomx.eu/vs4806123577708417

Previous studies proved that interferon gamma (IFN-γ) gene polymorphisms were associated with the risk of hepatitis B virus (HBV) infection. However, the association between IFN-γ polymorphisms and HBV-related liver cirrhosis (HBV-LC) risk is still unclear. IFN-γ +874 T/A and +2109G/A genotypes were determined in 126 HBV-LC patients, 129 chronic hepatitis B(CHB) patients, and 173 early HBV infection controls using a sequence-specific primer-polymerase chain reaction and a polymerase chain reaction-restriction fragment length polymorphism, respectively. Significant associations were observed between +2109A/G polymorphisms and HBV-LC risk in the co-dominant model (GG vs. AA: OR = 0.321, 95% CI = 0.130-0.793, P = 0.014), the allelic model (OR = 0.565, 95% CI = 0.388-0.825, P = 0.003), the dominant model (OR = 0.551, 95% CI = 0.344-0.883, P = 0.013), and the recessive model (OR = 0.385, 95% CI = 0.159-0.930, P = 0.034). In addition, haplotype analysis indicated that the T+874G+2109 haplotype significantly decreased the HBV-LC risk (OR = 0.106, 95% CI = 0.022-0.502, P = 0.000), and A+874A+2109 haplotype significantly increased the LC risk (OR = 1.485, 95% CI = 1.065-2.070, P = 0.019). No significant associations were observed between IFN-γ +874 T/A polymorphisms and HBV-LC risk, as well as the two single-nucleotide polymorphisms (SNPs) and CHB risk (P > 0.05). Our observations suggested a significant association of IFN-γ polymorphisms with HBV-LC risk in the Chinese population.