Cytokine gene polymorphisms in gastric cancer patients from two Italian areas at high and low cancer prevalence

Polymorphisms of interleukin-1beta (IL-1beta), IL-1 receptor antagonist (IL1-RN), and tumor necrosis factor-alpha (TNF-alpha) genes are supposed to be key determinants of gastric cancer risk. Our aim was to study the association between these polymorphisms and gastric cancer in two areas characterized by high (Pavia/Bologna, North Italy) and low (San Giovanni Rotondo, South Italy) gastric cancer prevalence. Genomic DNA was obtained from 216 healthy donors and 98 gastric cancer patients from Pavia and Bologna, and 146 healthy donors and 86 gastric cancer patients from San Giovanni Rotondo. Two SNP in IL-1beta (-511 C/T) and TNF-alpha (-308 G/A) as well as the VNTR polymorphism of IL-1RN locus were studied. A significant linkage disequilibrium was found between IL-1beta -511 and IL-1RN. Genotype and allele frequencies at the IL-1beta, IL-1RN, and TNF-alpha loci in gastric cancer cases were not significantly different from controls. An epistatic effect between IL-1beta -511 and IL-1RN was found with the IL-1beta -511C/IL-1RN*2 haplotype conferring a significant protection against the intestinal-type of gastric cancer in the Southern population. In conclusion, IL-1beta, IL1-RN, and TNF-alpha genotypes are not associated with gastric cancer in Italian patients. An epistatic interrelationship between IL-1beta -511 and IL-1RN confers protection against gastric cancer in low-risk Italian population.     

Genotyping of the lactase-phlorizin hydrolase c/t-13910 polymorphism by means of a new rapid denaturing high-performance liquid chromatography-based assay in healthy subjects and colorectal cancer patients

Adult-type hypolactasia results from the progressive decline of lactase-phlorizin hydrolase activity in enterocytes after weaning. Lactase nonpersistence may determine a primary lactose intolerance with reduced diary product consumption, which is possibly related to an increased risk of colon cancer. Recently, a genetic variant C/T(-13910) upstream of the lactase-phlorizin hydrolase (LCT) gene has been strongly correlated with the lactase persistence/nonpersistence trait in both family and case-control studies. The authors validate a denaturing high-performance liquid chromatography (dHPLC)-based assay versus conventional genotype sequencing in detecting the C/T(-13910) polymorphism of LCT and evaluate its prevalence in 2 different Italian geographical areas and in colorectal cancer patients. DNA samples of 157 healthy subjects and 124 colon cancer patients from Apulia and of 97 healthy subjects from Sardinia were evaluated for the C/T(-13910) polymorphism by dHPLC, sequencing, and restriction fragment length polymorphism (RFLP). Under optimized conditions, dHPLC was as sensitive as DNA sequencing and detected a new genetic variant (T/C(-13913)) in 2 individuals that was not identified by RFLP assay. Frequency of lactase nonpersistence genotype (C/C(-13910)) was similar in healthy subjects from 2 different Italian geographical areas and not increased in patients with colorectal cancer. The results indicate that the dHPLC method may be used as a rapid, noninvasive, and labor-saving screening tool for genotyping C/T(-13910) polymorphism, with high success, low cost, and reproducibility.     

A deep auto-encoder model for gene expression prediction

Background

Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance.

Results

To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns.

Conclusion

We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes’ contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

     

Amoxicillin/tetracycline combinations are inadequate as alternative therapies for Helicobacter pylori infection

Background. Triple therapy with proton pump inhibitors or ranitidine bismuth citrate, clarithromycin and either amoxicillin or nitroimidazole derivatives are the present gold standards for cure of Helicobacter pylori infection. However, primary resistance to either clarithromycin or nitroimidazole derivatives is increasing and alternative therapies are needed. Aim. To determine the efficacy and safety of three regimens consisting of amoxicillin and tetracycline or doxycycline combined with either lansoprazole or ranitidine bismuth citrate. Methods. Two hundred and seventy H. pylori infected patients were randomly given one of the following treatments: amoxicillin 1 g twice a day (b.i.d.) plus tetracycline 500 mg four times a day (q.i.d.) with either lansoprazole 30 mg b.i.d. (group LAT) or ranitidine bismuth citrate 400 mg b.i.d. (group RBCAT) for 7 days and amoxicillin 1 g b.i.d. plus doxycycline 100 mg b.i.d. and lansoprazole 30 mg b.i.d. for 14 days (group LAD). Eradication rate was assessed by UBT at 4–6 weeks after therapy. Results. The three groups (LAT, RBCAT, and LAD) of patients achieved eradication rates of 35% (25–45), 20% (12–29) and 36% (25–46), respectively, on intention‐to‐treat analysis. Patient compliance was optimal and side‐effects minimal in all three groups. Conclusions. Although the amoxicillin/tetracycline combination is attractive (inexpensive, safe, and with low primary resistance rate), it can not be recommended for H. pylori eradication.     

IPLEX Administration Improves Motor Neuron Survival and Ameliorates Motor Functions in a Severe Mouse Model of Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is an inherited neurodegenerative disorder and the first genetic cause of death in childhood. SMA is caused by low levels of survival motor neuron (SMN) protein that induce selective loss of α-motor neurons (MNs) in the spinal cord, resulting in progressive muscle atrophy and consequent respiratory failure. To date, no effective treatment is available to counteract the course of the disease. Among the different therapeutic strategies with potential clinical applications, the evaluation of trophic and/or protective agents able to antagonize MNs degeneration represents an attractive opportunity to develop valid therapies. Here we investigated the effects of IPLEX (recombinant human insulinlike growth factor 1 [rhIGF-1] complexed with recombinant human IGF-1 binding protein 3 [rhIGFBP-3]) on a severe mouse model of SMA. Interestingly, molecular and biochemical analyses of IGF-1 carried out in SMA mice before drug administration revealed marked reductions of IGF-1 circulating levels and hepatic mRNA expression. In this study, we found that perinatal administration of IPLEX, even if does not influence survival and body weight of mice, results in reduced degeneration of MNs, increased muscle fiber size and in amelioration of motor functions in SMA mice. Additionally, we show that phenotypic changes observed are not SMN-dependent, since no significant SMN modification was addressed in treated mice. Collectively, our data indicate IPLEX as a good therapeutic candidate to hinder the progression of the neurodegenerative process in SMA.