Fatty Acid Synthase (FASN), a key enzyme of de novo lipogenesis, is upregulated in many cancers including colorectal cancer (CRC); increased FASN expression is associated with poor prognosis. Potent FASN inhibitors (TVBs) developed by 3-V Biosciences demonstrate anti-tumor activity in vitro and in vivo and a favorable tolerability profile in a Phase I clinical trial.However, CRC characteristics associated with responsiveness to FASN inhibition are not fully understood. We evaluated the effect of TVB-3664 on tumor growth in nine CRC patient-derived xenografts (PDXs) and investigated molecular and metabolic changes associated with CRC responsiveness to FASN inhibition.CRC cells and PDXs showed a wide range of sensitivity to FASN inhibition. TVB-3664 treatment showed significant response (reduced tumor volume) in 30% of cases. Anti-tumor effect of TVB-3664 was associated with a significant decrease in a pool of adenine nucleotides and alterations in lipid composition including a significant reduction in fatty acids and phospholipids and an increase in lactosylceramide and sphingomyelin in PDXs sensitive to FASN inhibition. Moreover, Akt, Erk1/2 and AMPK were major oncogenic pathways altered by TVBs.In summary, we demonstrated that novel TVB inhibitors show anti-tumor activity in CRC and this activity is associated with a decrease in activation of Akt and Erk1/2 oncogenic pathways and significant alteration of lipid composition of tumors. Further understanding of genetic and metabolic characteristics of tumors susceptible to FASN inhibition may enable patient selection and personalized medicine approaches in CRC.

Background and Aims Resolution of pathways that converge to induce deleterious effects in hepatic diseases, such as in the later stages, have potential antifibrotic effects that may improve outcomes. We aimed to explore whether humans and rodents display similar fibrotic signaling networks. Approach and Results We assiduously mapped kinase pathways using 340 substrate targets, upstream bioinformatic analysis of kinase pathways, and over 2000 random sampling iterations using the PamGene PamStation kinome microarray chip technology. Using this technology, we characterized a large number of kinases with altered activity in liver fibrosis of both species. Gene expression and immunostaining analyses validated many of these kinases as bona fide signaling events. Surprisingly, the insulin receptor emerged as a considerable protein tyrosine kinase that is hyperactive in fibrotic liver disease in humans and rodents. Discoidin domain receptor tyrosine kinase, activated by collagen that increases during fibrosis, was another hyperactive protein tyrosine kinase in humans and rodents with fibrosis. The serine/threonine kinases found to be the most active in fibrosis were dystrophy type 1 protein kinase and members of the protein kinase family of kinases. We compared the fibrotic events over four models: humans with cirrhosis and three murine models with differing levels of fibrosis, including two models of fatty liver disease with emerging fibrosis. The data demonstrate a high concordance between human and rodent hepatic kinome signaling that focalizes, as shown by our network analysis of detrimental pathways. Conclusions Our findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents.

IntroductionDirect injection Fourier-transform mass spectrometry (FT-MS) allows for the high-throughput and high-resolution detection of thousands of metabolite-associated isotopologues. However, spectral artifacts can generate large numbers of spectral features (peaks) that do not correspond to known compounds. Misassignment of these artifactual features creates interpretive errors and limits our ability to discern the role of representative features within living systems.ObjectivesOur goal is to develop rigorous methods that identify and handle spectral artifacts within the context of high-throughput FT-MS-based metabolomics studies.ResultsWe observed three types of artifacts unique to FT-MS that we named high peak density (HPD) sites: fuzzy sites, ringing and partial ringing. While ringing artifacts are well-known, fuzzy sites and partial ringing have not been previously well-characterized in the literature. We developed new computational methods based on comparisons of peak density within a spectrum to identify regions of spectra with fuzzy sites. We used these methods to identify and eliminate fuzzy site artifacts in an example dataset of paired cancer and non-cancer lung tissue samples and evaluated the impact of these artifacts on classification accuracy and robustness.ConclusionOur methods robustly identified consistent fuzzy site artifacts in our FT-MS metabolomics spectral data. Without artifact identification and removal, 91.4% classification accuracy was achieved on an example lung cancer dataset; however, these classifiers rely heavily on artifactual features present in fuzzy sites. Proper removal of fuzzy site artifacts produces a more robust classifier based on non-artifactual features, with slightly improved accuracy of 92.4% in our example analysis.Electronic supplementary materialThe online version of this article (10.1007/s11306-018-1426-9) contains supplementary material, which is available to authorized users.

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Targeting the epidermal growth factor receptor (EGFR) with tyrosine kinase inhibitors (TKIs) is one of the major precision medicine treatment options for lung adenocarcinoma. Due to common development of drug resistance to first-and second-generation TKIs, third-generation inhibitors, including osimertinib and rociletinib, have been developed. A model of EGFR-driven lung cancer and a method to develop tumors of distinct epigenetic states through 3D organotypic cultures are described here. It is discovered that activation of the EGFR T790M/L858R mutation in lung epithelial cells can drive lung cancers with alveolar or bronchiolar features, which can originate from alveolar type 2 (AT2) cells or bronchioalveolar stem cells, but not basal cells or club cells of the trachea. It is also demonstrated that these clones are able to retain their epigenetic differences through passaging orthotopically in mice and crucially that they have distinct drug vulnerabilities. This work serves as a blueprint for exploring how epigenetics can be used to stratify patients for precision medicine decisions.

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Exposure to ionizing radiation associated with highly energetic and charged heavy particles is an inherent risk astronauts face in long duration space missions. We have previously considered the transcriptional effects that three levels of radiation (0.3 Gy, 1.5 Gy, and 3.0 Gy) have at an immediate time point (1 hr) post-exposure [1]. Our analysis of these results suggest effects on transcript levels that could be modulated at lower radiation doses [2]. In addition, a time dependent effect is likely to be present. Therefore, in order to develop a lab-on-a-chip approach for detection of radiation exposure in terms of both radiation level and time since exposure, we developed a time- and dose-course study to determine appropriate sensitive and specific transcript biomarkers that are detectable in blood samples. The data described herein was developed from a study measuring exposure to 0.15 Gy, 0.30 Gy, and 1.5 Gy of radiation at 1 hr, 2 hr, and 6 hr post-exposure using Affymetrix® GeneChip® PrimeView™ microarrays. This report includes raw gene expression data files from the resulting microarray experiments representing typical radiation exposure levels an astronaut may experience as part of a long duration space mission. The data described here is available in NCBI's Gene Expression Omnibus (GEO), accession GSE63952.

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