National Key R&D Program of China, PUMC Youth Fund and the Fundamental Research Funds for the Central Universities, and Major State Basic Innovation Program of the Chinese Academy of Medical Sciences.

Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression. Diagnostic applications have been proposed for inflammatory bowel disease diagnosis and prognosis, colorectal cancer prescreening and therapeutic choices in melanoma. Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic and cardiovascular diseases. To understand the generalizability of microbiota-based diagnostic models of metabolic disease, we characterized the gut microbiota of 7,009 individuals from 14 districts within 1 province in China. Among phenotypes, host location showed the strongest associations with microbiota variations. Microbiota-based metabolic disease models developed in one location failed when used elsewhere, suggesting that such models cannot be extrapolated. Interpolated models performed much better, especially in diseases with obvious microbiota-related characteristics. Interpolation efficiency decreased as geographic scale increased, indicating a need to build localized baseline and disease models to predict metabolic risks.

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A B S T R A C TPurpose BRAF mutations promote melanoma cell proliferation and survival primarily through activation of MEK. The purpose of this study was to determine the response rate (RR) for the selective, allosteric MEK1/MEK2 inhibitor trametinib (GSK1120212), in patients with metastatic BRAFmutant melanoma. Patients and MethodsThis was an open-label, two-stage, phase II study with two cohorts. Patients with metastatic BRAF-mutant melanoma previously treated with a BRAF inhibitor (cohort A) or treated with chemotherapy and/or immunotherapy (BRAF-inhibitor naive; cohort B) were enrolled. Patients received 2 mg of trametinib orally once daily. ResultsIn cohort A (n ϭ 40), there were no confirmed objective responses and 11 patients (28%) with stable disease (SD); the median progression-free survival (PFS) was 1.8 months. In cohort B (n ϭ 57), there was one (2%) complete response, 13 (23%) partial responses (PRs), and 29 patients (51%) with SD (confirmed RR, 25%); the median PFS was 4.0 months. One patient each with BRAF K601E and BRAF V600R had prolonged PR. The most frequent treatment-related adverse events for all patients were skin-related toxicity, nausea, peripheral edema, diarrhea, pruritis, and fatigue. No cutaneous squamous cell carcinoma was observed. ConclusionTrametinib was well tolerated. Significant clinical activity was observed in BRAF-inhibitor-naive patients previously treated with chemotherapy and/or immunotherapy. Minimal clinical activity was observed as sequential therapy in patients previously treated with a BRAF inhibitor. Together, these data suggest that BRAF-inhibitor resistance mechanisms likely confer resistance to MEK-inhibitor monotherapy. These data support further evaluation of trametinib in BRAF-inhibitornaive BRAF-mutant melanoma, including rarer forms of BRAF-mutant melanoma.

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Aberrant expression of miR-335 has been frequently reported in cancer studies, suggesting that there is a close correlation between miR-335 and cancer during its development, progression, metastasis and prognosis. The expression of miR-335 in gastric cancer and its effects are not known. Relative expression of miR-335 in 4 gastric cancer cell lines and in 70 gastric cancer tissues was confirmed by real-time quantitative reverse transcriptase-PCR compared with controls. Transwell cell migration and Matrigel invasion assay in vitro and metastasis formation assay in vivo were used to examine the effects of miR-335 expression on gastric cancer cell invasion and metastasis. The effect of miR-335 expression on gastric cancer cell proliferation was estimated by the 3-(4,5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide assay. Luciferase reporter assay and western blot were used to examine the potential target genes and related pathways. Gene silencing with small-interfering RNA was used to examine the effects of target genes on gastric cancer cell invasion. miR-335 was dramatically downregulated in gastric cancer cell lines than in the normal gastric cell line GES-1. Low expression of miR-335 was significantly associated with lymph-node metastasis, poor pT stage, poor pN stage and invasion of lymphatic vessels. Overexpression of miR-335 suppressed gastric cancer cell invasion and metastasis in vitro and in vivo, but has no significant effects on cell proliferation. Furthermore, miR-335 might suppress gastric cancer invasion and metastasis by targeting Bcl-w and specificity protein 1 (SP1). Taken together, our results provide evidence that miR-335 might function as a metastasis suppressor in gastric cancer by targeting SP1 directly and indirectly through the Bcl-w-induced phosphoinositide 3-kinase-Akt-Sp1 pathway. miR-335 showing altered expression at different stages of gastric cancer could be a target for gastric cancer therapies and could be further developed as a potential prognostic factor.

Various ‘omics’ technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.