Based on gene expression patterns, we classified gastric cancers into 3 subtypes, and validated these in an independent set of tumors. The subgroups have differences in molecular and genetic features and response to therapy; this information might be used to select specific treatment approaches for patients with gastric cancer.

Epigenetic alterations are fundamental hallmarks of cancer genomes. We surveyed the landscape of DNA methylation alterations in gastric cancer by analyzing genome-wide CG dinucleotide (CpG) methylation profiles of 240 gastric cancers (203 tumors and 37 cell lines) and 94 matched normal gastric tissues. Cancer-specific epigenetic alterations were observed in 44% of CpGs, comprising both tumor hyper- and hypomethylation. Twenty-five percent of the methylation alterations were significantly associated with changes in tumor gene expression. Whereas most methylation-expression correlations were negative, several positively correlated methylation-expression interactions were also observed, associated with CpG sites exhibiting atypical transcription start site distances and gene body localization. Methylation clustering of the tumors revealed a CpG island methylator phenotype (CIMP) subgroup associated with widespread hypermethylation, young patient age, and adverse patient outcome in a disease stage-independent manner. CIMP cell lines displayed sensitivity to 5-aza-2'-deoxycytidine, a clinically approved demethylating drug. We also identified long-range regions of epigenetic silencing (LRESs) in CIMP tumors. Combined analysis of the methylation, gene expression, and drug treatment data suggests that certain LRESs may silence specific genes within the region, rather than all genes. Finally, we discovered regions of long-range tumor hypomethylation, associated with increased chromosomal instability. Our results provide insights into the epigenetic impact of environmental and biological agents on gastric epithelial cells, which may contribute to cancer.

The genetic information in DNA is transcribed to mRNA and then translated to proteins, which form the building blocks of life. Translation, or protein synthesis, is hence a central cellular process. We have developed a gene-sequence-specific mechanistic model for the translation machinery, which accounts for all the elementary steps of the translation mechanism. We performed a sensitivity analysis to determine the effects of kinetic parameters and concentrations of the translational components on protein synthesis rate. Utilizing our mathematical framework and sensitivity analysis, we investigated the translational kinetic properties of a single mRNA species in Escherichia coli. We propose that translation rate at a given polysome size depends on the complex interplay between ribosomal occupancy of elongation phase intermediate states and ribosome distributions with respect to codon position along the length of the mRNA, and this interplay leads to polysome self-organization that drives translation rate to maximum levels.

BMP4 epigenetic and expression status may represent promising biomarkers for GC cisplatin resistance. Targeting BMP4 may sensitise GC cells to cisplatin. Oxaliplatin, a clinically acceptable cisplatin alternative, may represent a potential therapeutic option for BMP4-positive GCs.

Translation is a central cellular process and the complexity of its mechanism necessitates mathematical frameworks to better understand system properties and make quantitative predictions. We have developed a gene sequence-specific mechanistic model for translation which accounts for all the elementary steps of translation elongation. Included in our model is the nonspecific binding of tRNAs to the ribosomal A site, and we find that the competitive, nonspecific binding of the tRNAs is the rate-limiting step in the elongation cycle for every codon. By introducing our model in terms of the Michaelis-Menten kinetic framework, we determine that these results are due to the tRNAs that do not recognize the ribosomal A site codon acting as competitive inhibitors to the tRNAs that do recognize the ribosomal A site codon. We present the results of a sensitivity analysis to determine the contribution of elongation cycle kinetic parameters of each codon on the overall translation rate, and observe that the translation rates of mRNAs are controlled by segments of rate-limiting codons that are sequence-specific. Along these lines, we find that the relative position of codons along the mRNA determines the optimal protein synthesis rate.