STAT3 genetic variant, alone and in combination with STAT5b polymorphism, contributes to breast cancer risk and clinical outcomes

STAT3 polymorphisms in North Africa and its implication in breast cancer

BACKGROUND

Only a few studies have investigated the association of single nucleotide polymorphisms in STAT3 gene with the susceptibility to cancer and response to chemotherapy. Our aim was to determine the allele frequencies of rs3869550, rs957971, and rs7211777 at the STAT3 gene in North African populations and compare them to 1000 genomes populations, and to investigate their relation with cancer.

METHODS

The targeted SNPs have been analyzed in six Tunisian populations and a sample of Libyans using TaqMan® Assay. The results were compared to 1000 Genomes Project population samples. Targeting of the regions encompassing the three SNPs by micro-ARN was assessed using miR databases.

RESULTS

The analysis of the 3 SNPs showed that North African populations were close to South Asians. As expected, African populations presented a significant frequency of the ancestral CCG haplotype in contrast to other populations where the fully derived TGA haplotype was more frequent. The presence and diversity of rare haplotypes at STAT3 in North African populations could have been generated by recombination between the two major haplotypes. A screening of the micro-RNA databases showed that the STAT3 region with the mutated allele of rs7211777 (G>A) could be targeted by miR hsa-miR-3606-5p, which also targets genes involved in breast cancer.

Toll-like receptors as a therapeutic target in cancer, infections and inflammatory diseases

Toll-like receptors (TLRs) are widely expressed pattern recognition receptors that bind to conserved molecular patterns expressed by pathogens and damaged cells. After recognition, activated TLRs induce the expression of various proinflammatory and antiviral molecules. Thus, TLRs are potential targets for treatment strategies aimed at boosting the adaptive immune response to vaccines, controlling infections, enhancing immune responses during tumor treatment and attenuating immune responses in inflammatory disorders. This Special Report examines the potential of TLRs as targets for the treatment of cancer, infections and inflammatory diseases. Here, we make a particular emphasis on molecules capable of modulating TLRs and their therapeutic applications.

STAT3 rs4796793 contributes to lung cancer risk and clinical outcomes of platinum-based chemotherapy

BACKGROUND

Signal transducer and activator of transcription (STAT) 3 plays a vital role in carcinogenesis and drug response. Platinum-based chemotherapy is the first-line treatment for lung cancer patients, especially those in advanced stages. In the present study, we investigated the association of STAT3 polymorphism rs4796793 with lung cancer susceptibility, platinum-based chemotherapy response, and toxicity.

METHODS

A total of 498 lung cancer patients and 213 healthy controls were enrolled in the study. 467 of them received at least 2-cycle platinum-based chemotherapy. Unconditional logistical regression analysis was used to assess the associations.

RESULTS

STAT3 rs4769793 G allele carriers had an increased susceptibility of lung cancer [additive model: adjusted OR (95% CI) 1.376 (1.058-1.789), P = 0.017; recessive model: adjusted OR (95% CI) 1.734 (1.007-2.985), P = 0.047]. Rs4769793 was not significantly associated with platinum-based chemotherapy response in lung cancer patients. STAT3 rs4796793 was associated with an increased risk of severe overall toxicity [additive model: adjusted OR (95% CI) 1.410 (1.076-1.850), P = 0.013; dominant model: adjusted OR (95% CI) 1.638 (1.091-2.459), P = 0.017], especially hematological toxicity [additive model: adjusted OR (95% CI) 1.352 (1.001-1.826), P = 0.049].

CONCLUSIONS

STAT3 rs4796793 may be considered as a potential candidate biomarker for the prediction of susceptibility and prognosis in Chinese lung cancer patients. However, well-designed studies with larger sample sizes are required to verify the results.

Height, selected genetic markers and prostate cancer risk: results from the PRACTICAL consortium

BACKGROUND

Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer.

METHODS

We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions.

RESULTS

The results suggest that height is associated with high-grade prostate cancer risk. Men with height >180 cm are at a 22% increased risk as compared to men with height <173 cm (OR 1.22, 95% CI 1.01-1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group.

CONCLUSIONS

There was no evidence of gene-environment interaction between height and the selected candidate SNPs.Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.

Association between STAT3 polymorphisms and cancer risk: a meta-analysis

Five polymorphisms, rs2293152, rs4796793, rs12949918, rs6503695, rs744166, in the STAT3 gene have been implicated in susceptibility to cancer, but the results were inconclusive. The aim of this meta-analysis is to investigate the association between the five polymorphisms and cancer risk. All eligible case-control studies published up to March 2015 were identified by searching PubMed, Web of Science, Wanfang, VIP, and CNKI. Effect sizes of odds ratio (OR) and 95 % confidence interval (95 % CI) were calculated by using a fixed- or random-effect model. A total of 15 articles were included. Overall, a significantly decreased risk was found for rs12949918 polymorphism (dominant model: OR = 0.83, 95 % CI: 0.75-0.91, recessive model: OR = 0.77, 95 % CI: 0.68-0.87, TC vs. TT: OR = 0.87, 95 % CI: 0.79-0.96, CC vs. TT: OR = 0.71, 95 % CI: 0.62-0.81), and for rs744166 polymorphism (recessive model: OR = 0.75, 95 % CI: 0.58-0.98; GG vs. AA: OR = 0.68, 95 % CI: 0.51-0.90), while there was no significant association for other three polymorphisms under all genetic models. In subgroup analysis by ethnicity, for rs12949918 polymorphism, similar results were detected among Caucasians, similarly, a significant decreased risk was observed in Asians under dominant and CC vs. TT model; for rs2293152 polymorphism, significant association was detected among Asians under recessive model. This meta-analysis suggests that the STAT3 rs12949918 and rs744166 polymorphisms, but not other three polymorphisms, may be an important protective factor for cancer.