Identification of molecular subtypes of gastric cancer with different responses to PI3-kinase inhibitors and 5-fluorouracil.

BACKGROUND & AIMS: Almost all gastric cancers are adenocarcinomas, which have considerable heterogeneity among patients. We sought to identify subtypes of gastric adenocarcinomas with particular biological properties and responses to chemotherapy and targeted agents. METHODS: We compared gene expression patterns among 248 gastric tumors; using a robust method of unsupervised clustering, consensus hierarchical clustering with iterative feature selection, we identified 3 major subtypes. We developed a classifier for these subtypes and validated it in 70 tumors from a different population. We identified distinct genomic and epigenomic properties of the subtypes. We determined drug sensitivities of the subtypes in primary tumors using clinical survival data, and in cell lines through high-throughput drug screening. RESULTS: We identified 3 subtypes of gastric adenocarcinoma: proliferative, metabolic, and mesenchymal. Tumors of the proliferative subtype had high levels of genomic instability, TP53 mutations, and DNA hypomethylation. Cancer cells of the metabolic subtype were more sensitive to 5-fluorouracil than the other subtypes. Furthermore, in 2 independent groups of patients, those with tumors of the metabolic subtype appeared to have greater benefits with 5-fluorouracil treatment. Tumors of the mesenchymal subtype contain cells with features of cancer stem cells, and cell lines of this subtype are particularly sensitive to phosphatidylinositol 3-kinase-AKT-mTOR inhibitors in vitro. CONCLUSIONS: 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.

Integrated epigenomics identifies BMP4 as a modulator of cisplatin sensitivity in gastric cancer.

OBJECTIVE: Cisplatin is a widely used gastric cancer (GC) chemotherapy; however, genetic factors regulating GC responses to cisplatin remain obscure. Identifying genes regulating cisplatin resistance could aid clinicians in tailoring treatments, by distinguishing cisplatin sensitive patients from those who might benefit from alternative platinum therapies, and highlight novel targeted strategies for overcoming cisplatin resistance. Here integrated epigenomics is applied to identify genes associated with GC cisplatin resistance. DESIGN: 20 GC cell lines were subjected to gene expression profiling, DNA methylation profiling and drug response assays. The molecular data were integrated to identify genes highly expressed and unmethylated specifically in cisplatin-resistant lines. Candidate genes were functionally tested by several in vitro and in vivo assays. Clinical impact of candidate genes was also assessed in a cohort of 197 GC patients. RESULTS: Epigenomic analysis identified bone morphogenetic protein 4 (BMP4) as an epigenetically regulated gene highly expressed in cisplatin-resistant lines. Functional assays confirmed that BMP4 is necessary and sufficient for the expression of several prooncogenic traits, likely mediated through stimulation of the epithelial-mesenchymal transition. In primary tumours, BMP4 promoter methylation levels were inversely correlated with BMP4 expression, and patients with high BMP4-expressing tumours exhibited significantly worse prognosis. Therapeutically, targeted genetic inhibition of BMP4 caused significant sensitisation of GC cells to cisplatin. Notably, BMP4-expressing GCs also did not exhibit cross resistance to oxaliplatin. CONCLUSIONS: 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.

DNA epigenetic signature predictive of benefit from neoadjuvant chemotherapy in oesophageal adenocarcinoma: results from the MRC OE02 trial.

BACKGROUND: DNA methylation signatures describing distinct histological subtypes of oesophageal cancer have been reported. We studied DNA methylation in samples from the MRC OE02 phase III trial, which randomised patients with resectable oesophageal cancer to surgery alone (S) or neoadjuvant chemotherapy followed by surgery (CS). AIM: The aim of the study was to identify epigenetic signatures predictive of chemotherapy benefit in patients with oesophageal adenocarcinoma (OAC) from the OE02 trial and validate the findings in an independent cohort. METHODS: DNA methylation was analysed using the Illumina GoldenGate platform on surgically resected OAC specimens from patients in the OE02 trial. Cox proportional hazard analysis was performed to select probes predictive of survival in the CS arm. Non-negative matrix factorisation was used to perform clustering and delineate DNA methylation signatures. The findings were validated in an independent cohort of patients with gastroesophageal adenocarcinoma treated with neoadjuvant chemotherapy. RESULTS: A total of 229 patients with OAC were analysed from the OE02 trial (118 in the CS arm and 111 in the S arm). There was no difference in DNA methylation status between the CS and S arms. A metagene signature was created by dichotomising samples into two clusters. In cluster 1, patients in the CS arm had significant overall survival (OS) benefit (median OS CS: 931 days vs. S: 536 days [HR: 1.54, P = 0.031]). In cluster 2, patients in the CS arm had similar (or worse) OS compared with patients in the S arm (CS: 348 days vs. S: 472 days [HR: 0.70, P = 0.1], and test of interaction was significant (p = 0.005). In the validation cohort (n = 13), there was no difference in DNA methylation status in paired pre- and post-treatment samples. When the epigenetic signature was applied, cluster 1 samples had better OS (median OS, cluster 1: 1174 days vs. cluster 2: 392 days, HR: 3.47, p = 0.059) CONCLUSIONS: This is the first and largest study of DNA methylation in patients with OAC uniformly treated in a randomised phase III trial. We identified an epigenetic signature that may serve as a predictive biomarker for chemotherapy benefit in OAC.

Effects of codon distributions and tRNA competition on protein translation.

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.

Methylation subtypes and large-scale epigenetic alterations in 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.

A model for protein translation: polysome self-organization leads to maximum protein synthesis rates.

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.