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.

Cachexia is a devastating muscle-wasting syndrome that occurs in patients who have chronic diseases. It is most commonly observed in individuals with advanced cancer, presenting in 80% of these patients, and it is one of the primary causes of morbidity and mortality associated with cancer. Additionally, although many people with cachexia show hypermetabolism, the causative role of metabolism in muscle atrophy has been unclear. To understand the molecular basis of cachexia-associated muscle atrophy, it is necessary to develop accurate models of the condition. By using transcriptomics and cytokine profiling of human muscle stem cell-based models and human cancer-induced cachexia models in mice, we found that cachectic cancer cells secreted many inflammatory factors that rapidly led to high levels of fatty acid metabolism and to the activation of a p38 stress-response signature in skeletal muscles, before manifestation of cachectic muscle atrophy occurred. Metabolomics profiling revealed that factors secreted by cachectic cancer cells rapidly induce excessive fatty acid oxidation in human myotubes, which leads to oxidative stress, p38 activation and impaired muscle growth. Pharmacological blockade of fatty acid oxidation not only rescued human myotubes, but also improved muscle mass and body weight in cancer cachexia models in vivo. Therefore, fatty acid-induced oxidative stress could be targeted to prevent cancer-induced cachexia.

CitationTumor-derived circulating endothelial cell clusters in colorectal cancer. 2016, 8 (345) * Clusters of tumor cells are often observed in the blood of cancer patients. These structures have been described as malignant entities for more than 50 years, although their comprehensive characterization is lacking. Contrary to current consensus, we demonstrate that a discrete population of circulating cell clusters isolated from the blood of colorectal cancer patients are not cancerous but consist of tumor-derived endothelial cells. These clusters express both epithelial and mesenchymal markers, consistent with previous reports on circulating tumor cell (CTC) phenotyping. However, unlike CTCs, they do not mirror the genetic variations of matched tumors. Transcriptomic analysis of single clusters revealed that these structures exhibit an endothelial phenotype and can be traced back to the tumor endothelium. Further results show that tumor-derived endothelial clusters do not form by coagulation or by outgrowth of single circulating endothelial cells, supporting a direct release of clusters from the tumor vasculature. The isolation and enumeration of these benign clusters distinguished healthy volunteers from treatment-naïve as well as pathological early-stage (≤IIA) colorectal cancer patients with high accuracy, suggesting that tumor-derived circulating endothelial cell clusters could be used as a means of noninvasive screening for colorectal cancer. In contrast to CTCs, tumorderived endothelial cell clusters may also provide important information about the underlying tumor vasculature at the time of diagnosis, during treatment, and throughout the course of the disease.

Intratumor heterogeneity (ITH) contributes to cancer progression and chemoresistance. We sought to comprehensively describe ITH of somatic mutations, copy number, and transcriptomic alterations involving clinically and biologically relevant gene pathways in colorectal cancer (CRC). We performed multiregion, high‐depth (384× on average) sequencing of 799 cancer‐associated genes in 24 spatially separated primary tumor and nonmalignant tissues from four treatment‐naïve CRC patients. We then used ultra‐deep sequencing (17 075× on average) to accurately verify the presence or absence of identified somatic mutations in each sector. We also digitally measured gene expression and copy number alterations using NanoString assays. We identified the subclonal point mutations and determined the mutational timing and phylogenetic relationships among spatially separated sectors of each tumor. Truncal mutations, those shared by all sectors in the tumor, affected the well‐described driver genes such as APC, TP53, and KRAS. With sequencing at 17 075×, we found that mutations first detected at a sequencing depth of 384× were in fact more widely shared among sectors than originally assessed. Interestingly, ultra‐deep sequencing also revealed some mutations that were present in all spatially dispersed sectors, but at subclonal levels. Ultra‐high‐depth validation sequencing, copy number analysis, and gene expression profiling provided a comprehensive and accurate genomic landscape of spatial heterogeneity in CRC. Ultra‐deep sequencing allowed more sensitive detection of somatic mutations and a more accurate assessment of ITH. By detecting the subclonal mutations with ultra‐deep sequencing, we traced the genomic histories of each tumor and the relative timing of mutational events. We found evidence of early mixing, in which the subclonal ancestral mutations intermixed across the sectors before the acquisition of subsequent nontruncal mutations. Our findings also indicate that different CRC patients display markedly variable ITH, suggesting that each patient's tumor possesses a unique genomic history and spatial organization.