Identification of biomarkers related to prostatic hyperplasia based on bioinformatics and machine learning.

In older adults, benign prostatic hyperplasia (BPH) is the most common cause of lower urinary tract symptoms (LUTS). This study aimed to explore the genes with diagnostic value in patients with BPH, reveal the relationship between the expression of diagnosis-related genes and the immune microenvironment, and provide a reference for molecular diagnosis and immunotherapy of BPH. The combined gene expression data of GSE6099, GSE7307 and GSE119195 in the GEO database were used. The differential expression of autophagy-related genes between BPH patients and healthy controls was obtained by differential analysis. Then the genes related to BPH diagnosis were screened by a machine learning algorithm and verified. Finally, five important genes (IGF1, PSIP1, SLC1A3, SLC2A1 and T1A1) were obtained by random forest (RF) algorithm, and their relationships with the immune microenvironment were discussed. Five genes play an essential role in the occurrence and development of BPH and may become new diagnostic markers of BPH. Among them, immune cells have significant correlation with some genes. The signal transduction of IL-4 mediated by M2 macrophages is closely related to the progress of BPH. There are abundant active mast cells in BPH. The adoption and metastasis of regulatory T cells may be an important method to treat BPH.

Predictive role of the overexpression for CXCR4, C-Met, and VEGF-C among breast cancer patients: A meta-analysis.

BACKGROUND: The overexpression of CXCR4, C-Met and VEGF-C present widely in breast tumors, they may be markers of resistance to treatment. However, the studies are still controversial. Thus, this meta-analysis aims to research the relationship between the overexpression of CXCR4, C-Met, VEGF-C and clinical prognosis among breast cancer patients. METHODS: PubMed and EMBASE databases were searched for eligible literature. The outcomes of interest were progression-free survival (PFS), relapse-free survival (RFS) and overall survival (OS). All tests of statistical significance were two sided. RESULTS: A total of 7830 patients from 28 eligible studies were assessed. The overexpression of the CXCR4 and C-Met both implied significantly worse PFS compared with normal expression [HR = 2.56, 95% CI = 1.34-4.91, P = 0.005; and HR = 1.63 95% CI = 1.20-2.22, P = 0.002]. Meanwhile, if patients had high expression of CXCR4, they would have worse OS [HR = 2.56 95% CI = 1.52-4.31, P = 0.000]. However, the overexpression of C-Met did not relate to OS for breast cancer patients [HR = 1.16, 95% CI = 0.69-1.95, P = 0.570]. Meanwhile, no statistically significant different was observed with respect to PFS and OS between VEGF-C overexpression and normal expression [HR = 0.99, 95% CI = 0.64-1.52, P = 0.968; and HR = 0.76, 95% CI = 0.43-1.33, P = 0.333]. CONCLUSIONS: Our meta-analysis showed that CXCR4 and C-Met were efficient prognostic factors for breast cancer. Nevertheless, highly expressing VEGF-C was not related to progression-free survival and overall survival. Due to the small samples and insufficient date, further studies should be conducted to clarify the association between the overexpression of CXCR4 or C-Met or VEGF-C and the prognosis about breast cancer patients.

Targeted drugs for unselected patients with advanced non-small-cell lung cancer: a network meta-analysis.

BACKGROUND: Currently, targeted therapy has shown encouraging treatment benefits in selected patients with advanced non-small cell lung cancer (NSCLC). However, the comparative benefits of targeted drugs and chemotherapy (CT) treatments in unselected patients are not clear. We therefore conduct a network meta-analysis to assess the relative efficacy and safety of these regimens. METHODS: PubMed, EMBASE, Cochrane Library and abstracts from major scientific meetings were searched for eligible literatures. The odds ratio (OR) for objective response rate (ORR) and safety was used for pooling effect sizes. Bayesian network meta-analysis was conducted to calculate the efficacy and safety of all included treatments. All tests of statistical significance were two sided. RESULTS: A total of 13,060 patients from 24 randomized controlled trials (RCT) were assessed. The targeted agents included bevacizumab (Bev), gefitinib (Gef), erlotinib (Erl) and cetuximab (Cet). Network meta-analysis showed that Bev + CT had a statistically significantly higher incidence of ORR relative to the other six different treatments, including placebo (OR =6.47; 95% CI, 3.85-10.29), Erl (OR =2.81; 95% CI, 2.08-3.70), CT (OR =1.92; 95% CI, 1.61-2.28), Gef (OR =1.40; 95% CI, 1.10-1.75), Erl + CT (OR =1.46; 95% CI, 1.17-1.80) and Gef + CT (OR =1.75; 95% CI, 1.36-2.22), whereas placebo and Erl were associated with statistically significantly lower incidence of ORR. Trend analyses of rank probability revealed that Bev + CT had the highest probability of being the best treatment arm in term of ORR, followed by Cet + CT. Meanwhile, Cet + CT showed significant severer rash and thrombocytopenia compared with Bev + CT. Gef was probable to be the rank 3 for ORR but was associated with relatively low risk for grade ≥3 toxicities. CONCLUSIONS: Our study suggested that Bev + CT may offer better ORR in the treatment of unselected patients with advanced NSCLC. Future studies will be needed to investigate whether the increase of ORR with targeted drugs would be translated into survival benefits.

Association of longevity with TNF-α G308A and IL-6 G174C polymorphic inflammatory biomarkers in Caucasians: a meta-analysis.

BACKGROUND: Mutations in genes encoding tumor necrosis factor (TNF)-α and interleukin (IL)-6 were previously shown to affect mortality. Single nucleotide polymorphisms (SNPs) in the functional promoter regions of TNF-α (G308A) and IL-6 (G174C) are among the most widely studied. OBJECTIVES: To determine whether TNF-α G308A and IL-6 G174C SNPs confer susceptibility to longevity, we performed a meta-analysis to comprehensively estimate the association between these SNPs and longevity in long-lived individuals (LLI, aged ≥ 80 years). MATERIALS AND METHODS: Studies addressing the role of TNF-α and IL-6 SNPs in longevity were identified from the PubMed database. Pooled ORs with 95 % confidence intervals (CIs) were used to assess the association between SNPs and longevity. RESULTS: The meta-analysis was based on four studies of TNF-α G308A and nine of IL-6 G174C, covering a total of 2945 LLI individuals and 2992 controls. Overall, no significantly increased risks were observed for G308A [A vs. G (additive model): OR = 0.98, 95 % CI = 0.79-1.22, p = 0.852; AA + AG vs. GG (dominant model): OR = 0.97, 95 % CI = 0.75-1.24, p = 0.791] or for G174C [C vs. G (additive model): OR = 1.07, 95 % CI = 0.94-1.22, p = 0.293; CC + CG vs. GG (dominant model): OR = 1.09, 95 % CI = 0.93-1.28, p = 0.299]. There was no change in the significance when a cutoff age of ≥ 90 years was introduced. CONCLUSIONS: We found no evidence that the TNF-α G308A and IL-6 G174C SNPs affected the probability of reaching an advanced age in Caucasians, and that they have little effect on delaying the onset and progression of age-related diseases, but this does not rule out the possibility of population-specific effects caused by different genes and/or environmental factors and their interactions.

Comparison of clinical outcomes of patients with non-small-cell lung cancer harbouring epidermal growth factor receptor exon 19 or exon 21 mutations after tyrosine kinase inhibitors treatment: a meta-analysis.

PURPOSE: Exon 19 deletion and exon 21 L858R mutation were the most common epidermal growth factor receptor (EGFR) mutations. We examined the clinical impact of these two mutations in patients with non-small-cell lung cancer (NSCLC) after EGFR tyrosine kinase inhibitor (TKI) treatment. METHODS: The outcomes of interest were progression-free survival (PFS), overall survival (OS) and objective response rates (ORR), network meta-analysis and direct meta-analysis were conducted to calculate the efficacy of EGFR-TKIs between these two mutations. We also investigated the association between EGFR mutation types and clinical characteristics. RESULTS: A total of 4835 patients from 26 trials were assessed. EGFR-TKIs, compared with chemotherapy, significantly prolonged PFS and OS in both exon 19 deletion and exon 21 L858R mutation based on 8 trials. Network meta-analysis revealed that treatment with EGFR-TKIs had greater benefit in exon 19 deletion than in exon 21 L858R mutation. Furthermore, direct meta-analysis from 12 studies showed the similar result; patients with exon 19 deletion had a significantly longer PFS compared with exon 21 L858R mutation (HR, 0.69; 95 % CI, 0.57­0.82; P < 0.001). There were also greater benefit on OS (HR, 0.61; 95 % CI, 0.43­0.86; P = 0.005) and higher ORR (OR, 2.14; 95 % CI, 1.63­2.81; P < 0.001). Additionally, we found that a significant association between the type of mutation and age (P < 0.001) or smoking status (P = 0.022), but no other significant differences were detected in sex, histologic subtype and performance status between these two mutations. CONCLUSIONS: Patients with NSCLC and EGFR exon 19 deletion had a longer PFS, OS and higher response rates after EGFR-TKI therapy compared with exon 21 L858R mutation.

Paraoxonase (PON1) polymorphisms Q192R and L55M are not associated with human longevity: A meta-analysis.

BACKGROUND: Genetic mutations in the paraoxonase 1 (PON1) encoding gene have been considered to affect mortality and of these the functional promoter region polymorphisms Q192R and L55M are among the most widely studied. OBJECTIVE: The aim of this study was to determine whether the Q192R and L55M polymorphisms of PON1 can increase susceptibility to longevity. A meta-analysis was performed to obtain a comprehensive estimation of the association between Q192R and L55M and longevity in long-lived individuals (LLIs) aged 80 years or more. MATERIAL AND METHODS: A search was carried out in the PubMed database (from January 2001 to May 2014) to obtain data on the role of PON1 polymorphisms in longevity and a pooled odds ratio (OR) with a 95% confidence interval (CI) was used to assess the associations. RESULTS: The meta-analysis was based on 9 studies of PON1 Q192R and 5 studies of PON1 L55M that covered a total of 5086 LLIs and 4494 controls. Overall, significantly increased risks were not observed for either Q192R or L55M. The results of the statistical calculations were as follows: R vs. Q (additive model): OR = 1.080, 95% CI = 0.989-1.179, p = 0.088 and RR + RQ vs. QQ (dominant model): OR = 1.099, 95% CI = 0.975-1.240, p = 0.124; M vs. L (additive model): OR = 0.946, 95% CI = 0.862-1.039, p = 0.245 and MM + ML vs. LL (dominant model): OR = 0.951, 95% CI = 0.836-1.081, p = 0.442 for Q192R and L55M, respectively. The results did not change with an age cut-off among the LLIs of ≥ 93 years. CONCLUSION: No evidence that the Q192R and L55M polymorphisms of PON1 impacted on the probability of reaching extreme ages was found although this cannot be completely ruled out; however, the possibility of population-specific effects due to the influence of and interaction between different genes or environmental factors could not be ruled out.