Project description:The detachment of epithelial cells, but not cancer cells, causes anoikis due to reduced energy production. Invasive tumor cells generate three splice variants of the metastasis gene osteopontin. The cancer-specific form osteopontin-c supports anchorage-independence through inducing oxidoreductases and upregulating intermediates/enzymes in the hexose monophosphate shunt, glutathione cycle, glycolysis, glycerol phosphate shuttle, and mitochondrial respiratory chain. Osteopontin-c signaling upregulates glutathione (consistent with the induction of the enzyme GPX-4), glutamine and glutamate (which can feed into the tricarboxylic acid cycle). Consecutively, the cellular ATP levels are elevated. The elevated creatine may be synthesized from serine via glycine and also supports the energy metabolism by increasing the formation of ATP. Metabolic probing with N-acetyl-L-cysteine, L-glutamate, or glycerol identified differentially regulated pathway components, with mitochondrial activity being redox dependent and the creatine pathway depending on glutamine. The effects are consistent with a stimulation of the energy metabolism that supports anti-anoikis. Our findings imply a synergism in cancer cells between osteopontin-a, which increases the cellular glucose levels, and osteopontin-c, which utilizes this glucose to generate energy. mRNA profiles of MCF-7 cells transfected with osteopontin-a, osteopontin-c and vector control were generated by RNA-Seq, in triplicate, by Illumina HiSeq.
Project description:BackgroundColonic polyps are common tumors occurring in ~50% of Western populations with ~10% risk of malignant progression. Dietary agents have been considered the primary environmental exposure to promote colorectal cancer (CRC) development. However, the colonic mucosa is permanently in contact with the microbiota and its metabolic products including toxins that also have the potential to trigger oncogenic transformation.AimTo analyze fecal DNA for microbiota composition and functional potential in African Americans with pre-neoplastic lesions.Materials & methodsWe analyzed the bacterial composition of stool samples from 6 healthy individuals and 6 patients with colon polyps using 16S ribosomal RNA-based phylogenetic microarray; the Human intestinal Tract Chip (HITChip) and 16S rRNA gene barcoded 454 pyrosequencing. The functional potential was determined by sequence-based metagenomics using 454 pyrosequencing.ResultsFecal microbiota profiling of samples from the healthy and polyp patients using both a phylogenetic microarraying (HITChip) and barcoded 454 pyrosequencing generated similar results. A distinction between both sets of samples was only obtained when the analysis was performed at the sub-genus level. Most of the species leading to the dissociation were from the Bacteroides group. The metagenomic analysis did not reveal major differences in bacterial gene prevalence/abundances between the two groups even when the analysis and comparisons were restricted to available Bacteroides genomes.ConclusionThis study reveals that at the pre-neoplastic stages, there is a trend showing microbiota changes between healthy and colon polyp patients at the sub-genus level. These differences were not reflected at the genome/functions levels. Bacteria and associated functions within the Bacteroides group need to be further analyzed and dissected to pinpoint potential actors in the early colon oncogenic transformation in a large sample size.
Project description:Although substantial evidence supports aspirin's efficacy in colorectal cancer chemoprevention, key molecular mechanisms are uncertain. An untargeted metabolomics approach with high-resolution mass spectrometry was used to elucidate metabolic effects of aspirin treatment in human colon tissue. We measured 10,269 metabolic features in normal mucosal biopsies collected at colonoscopy after approximately 3 years of randomized treatment with placebo, 81 or 325 mg/day aspirin from 325 participants in the Aspirin/Folate Polyp Prevention Study. Linear regression was used to identify aspirin-associated metabolic features and network analysis was used to identify pathways and predict metabolite identities. Poisson regression was used to examine metabolic features associations with colorectal adenoma risk. We detected 471 aspirin-associated metabolic features. Aside from the carnitine shuttle, aspirin-associated metabolic pathways were largely distinct for 81 mg aspirin (e.g., pyrimidine metabolism) and 325 mg (e.g., arachidonic acid metabolism). Among aspirin-associated metabolic features, we discovered three that were associated with adenoma risk and could contribute to the chemopreventive effect of aspirin treatment, and which have also previously been associated with colorectal cancer: creatinine, glycerol 3-phosphate, and linoleate. The last two of these are in the glycerophospholipid metabolism pathway, which was associated with 81 mg aspirin treatment and provides precursors for the synthesis of eicosanoids from arachidonic acid upstream of cyclooxygenase inhibition by aspirin. Conversely, carnitine shuttle metabolites were increased with aspirin treatment and associated with increased adenoma risk. Thus, our untargeted metabolomics approach has identified novel metabolites and pathways that may underlie the effects of aspirin during early colorectal carcinogenesis.
Project description:Mammals display wide range of variation in their lifespan. Investigating the molecular networks that distinguish long- from short-lived species has proven useful to identify determinants of longevity. Here, we compared the liver of long-lived naked mole-rats (NMRs) and the phylogenetically closely related, shorter-lived, guinea pigs using an integrated omic approach. We found that NMRs livers display a unique expression pattern of mitochondrial proteins that result in distinct metabolic features of their mitochondria. For instance, we observed a generally reduced respiration rate associated with lower protein levels of respiratory chain components, particularly complex I, and increased capacity to utilize fatty acids. Interestingly, we show that the same molecular networks are affected during aging in both NMR and humans, supporting a direct link to the extraordinary longevity of both species. Finally, we identified a novel longevity pathway and validated it experimentally in the nematode C. elegans.
Project description:The naked mole-rat (NMR), Heterocephalus glaber, is a mouse-sized subterranean rodent native to East Africa. Research on NMRs is intensifying in an effort to gain leverage from their unusual physiology, long-life span and cancer resistance for the development of new theraputics. Few studies have attempted to explain the reasons behind the NMR’s cancer resistance, but most prominently Tian et al. reported that NMR cells produce high-molecular weight hyaluronan as a potential cause for the NMR’s cancer resistance. Tian et al. have shown that NMR cells are resistant to transformation by SV40 Large T Antigen (SV40LT) and oncogenic HRAS (HRASG12V), a combination of oncogenes sufficient to transform mouse and rat fibroblasts. We have developed a number of lentiviral vectors to deliver both these oncogenes and generated 106 different cell lines from five different tissues and eleven different NMRs, and report here that contrary to Tian et al.’s observation, NMR cells are susceptible to oncogenic transformation by SV40LT and HRASG12V. Our data thus point to a non-cell autonomous mechanism underlying the remarkable cancer resistance of NMRs. Identifying these non-cell autonomous mechanisms could have significant implications on our understanding of human cancer development.
Project description:We used whole-exome and targeted sequencing to characterize somatic mutations in 103 colorectal cancers (CRC) from African Americans, identifying 20 new genes as significantly mutated in CRC. Resequencing 129 Caucasian derived CRCs confirmed a 15-gene set as a preferential target for mutations in African American CRCs. Two predominant genes, ephrin type A receptor 6 (EPHA6) and folliculin (FLCN), with mutations exclusive to African American CRCs, are by genetic and biological criteria highly likely African American CRC driver genes. These previously unsuspected differences in the mutational landscapes of CRCs arising among individuals of different ethnicities have potential to impact on broader disparities in cancer behaviors.
Project description:The interplay between pathogens and hosts has been studied for decades using targeted approaches such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods such as transcriptomics and proteomics have been used to study host-pathogen interactions. Recently, metabolomics was established as a new method to study changes in the biochemical composition of host tissues. We report a metabolomics study of Salmonella enterica serovar Typhimurium infection. We used Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Direct Infusion to reveal that dozens of host metabolic pathways are affected by Salmonella in a murine infection model. In particular, multiple host hormone pathways are disrupted. Our results identify unappreciated effects of infection on host metabolism and shed light on mechanisms used by Salmonella to cause disease, and by the host to counter infection. Female C57BL/6 mice were infected with Salmonella enterica serovar Typhimurium SL1344 cells by oral gavage. Feces and livers were collected and metabolites extracted using acetonitrile. For experiments with feces, samples were collected from 4 mice before and after infection. For liver experiments, 11 uninfected and 11 infected mice were used. Samples were combined into 3 groups of 3-4 mice each, resulting in the analysis of 3 group samples of uninfected and 3 of infected mice. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140 [PMID 19081807]). To identify differences in metabolite composition between uninfected and infected samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from uninfected and infected mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.