Amino acids availability and subsequent metabolic reprogramming sustain endocrine resistance in breast cancer (mRNA)
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PROVIDER: PRJNA495051 | ENA |
REPOSITORIES: ENA
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Project description:Amino acids availability and subsequent metabolic reprogramming sustain endocrine resistance in breast cancer
| PRJNA495047 | ENA
Project description:Amino acids availability and subsequent metabolic reprogramming sustain endocrine resistance in breast cancer (microRNA)
| PRJNA495052 | ENA
Project description:The majority of breast tumours express oestrogen receptor (ER) and receive endocrine therapy (ET) as standard care. Despite its efficacy, ~40% of women relapse with endocrine therapy-resistant (ETR) disease. A global transcription analysis and subsequent integrative approaches of ETR cells showed a deregulated node between miR-23b-3p and the amino acids transporter SLC6A14. Mechanistic analysis supports a model in which such deregulation impairs amino acids metabolism in the ETR cells with subsequent activation of autophagy and enhanced aspartate and glutamate import mediated by the SLC1A2 transporter. The clinical significance of these findings was validated by multiple orthogonal approaches in a large cohort of ET-treated patients, in patient-derived xenografts and in in vivo experiments. Targeting such reprogramming impairs the aggressive features of ETR cells and offers predictive biomarkers and potential targetable pathways to be exploited to combat or delay ETR in ER positive breast cancers.
2019-07-28 | GSE120930 | GEO
Project description:The majority of breast tumours express oestrogen receptor (ER) and receive endocrine therapy (ET) as standard care. Despite its efficacy, ~40% of women relapse with endocrine therapy-resistant (ETR) disease. A global transcription analysis and subsequent integrative approaches of ETR cells showed a deregulated node between miR-23b-3p and the amino acids transporter SLC6A14. Mechanistic analysis supports a model in which such deregulation impairs amino acids metabolism in the ETR cells with subsequent activation of autophagy and enhanced aspartate and glutamate import mediated by the SLC1A2 transporter. The clinical significance of these findings was validated by multiple orthogonal approaches in a large cohort of ET-treated patients, in patient-derived xenografts and in in vivo experiments. Targeting such reprogramming impairs the aggressive features of ETR cells and offers predictive biomarkers and potential targetable pathways to be exploited to combat or delay ETR in ER positive breast cancers.
2019-07-28 | GSE120929 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2019-07-28 | GSE120931 | GEO
Project description:Dysregulation of extracellular matrix (ECM) deposition and cellular metabolism promotes tumor aggressiveness by sustaining the activity of key growth, invasion, and survival pathways. Yet mechanisms by which biophysical properties of ECM relate to metabolic processes and tumor progression remain undefined. In both cancer cells and carcinoma-associated fibroblasts (CAFs), we found that ECM stiffening mechanoactivates glycolysis and glutamine metabolism and thus coordinates non-essential amino acid flux within the tumor niche. Specifically, we demonstrate a metabolic crosstalk between CAF and cancer cells in which CAF-derived aspartate sustains cancer cell proliferation, while cancer cell-derived glutamate balances the redox state of CAFs to promote ECM remodeling. Collectively, our findings link mechanical stimuli to dysregulated tumor metabolism and thereby highlight a new metabolic network within tumors in which diverse fuel sources are used to promote growth and aggressiveness. Furthermore, this study identifies potential metabolic drug targets for therapeutic development in cancer.
| S-EPMC6432652 | biostudies-literature
Project description:Branched-chain amino acid (BCAA) catabolism and high levels of enzymes in the BCAA metabolic pathway have recently been shown to be associated with cancer growth and survival. However, the precise roles of BCAA metabolism in cancer growth and survival remain largely unclear. Here, we found that BCAA metabolism has an important role in human pancreatic ductal adenocarcinoma (PDAC) growth by regulating lipogenesis. Compared with nontransformed human pancreatic ductal (HPDE) cells, PDAC cells exhibited significantly elevated BCAA uptake through solute carrier transporters, which were highly upregulated in pancreatic tumor tissues compared with normal tissues. Branched-chain amino-acid transaminase 2 (BCAT2) knockdown markedly impaired PDAC cell proliferation, but not HPDE cell proliferation, without significant alterations in glutamate or reactive oxygen species levels. Furthermore, PDAC cell proliferation, but not HPDE cell proliferation, was substantially inhibited upon knockdown of branched-chain α-keto acid dehydrogenase a (BCKDHA). Interestingly, BCKDHA knockdown had no significant effect on mitochondrial metabolism; that is, neither the level of tricarboxylic acid cycle intermediates nor the oxygen consumption rate was affected. However, BCKDHA knockdown significantly inhibited fatty-acid synthesis, indicating that PDAC cells may utilize BCAAs as a carbon source for fatty-acid biosynthesis. Overall, our findings show that the BCAA metabolic pathway may provide a novel therapeutic target for pancreatic cancer.
| S-EPMC6884453 | biostudies-literature
Project description:Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissociation might alter gene expressions. In this work, we cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from human pancreata. We innovated fluorescence-activated nuclei sorting (FANS) based on the positive signal of NKX2-2 antibody to enrich for nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. We observed comparable endocrine cellular composition and cell type signature gene expression between our snRNA-seq libraries and conventional scRNA-seq libraries generated with live cells from freshly isolated human islets. Our work fills a technological gap and helps to unleash archival pancreatic tissue for molecular profiling targeting the endocrine population. We expect that our protocol can be used to enrich nuclei for transcriptomics study from various populations in the pancreas and in different organs/tissues.
2024-04-01 | GSE252614 | GEO
Project description:Aquatic microorganisms are typically identified as either oligotrophic or copiotrophic, representing trophic strategies adapted to low or high nutrient concentrations, respectively. Here, we sought to take steps towards identifying these and additional adaptations to nutrient availability with a quantitative analysis of microbial resource use in mixed communities. We incubated an estuarine microbial community with stable isotope labeled amino acids (AAs) at concentrations spanning three orders of magnitude, followed by taxon-specific quantitation of isotopic incorporation using NanoSIMS analysis of high-density microarrays. The resulting data revealed that trophic response to AA availability falls along a continuum between copiotrophy and oligotrophy, and high and low activity. To illustrate strategies along this continuum more simply, we statistically categorized microbial taxa among three trophic types, based on their incorporation responses to increasing resource concentration. The data indicated that taxa with copiotrophic-like resource use were not necessarily the most active, and taxa with oligotrophic-like resource use were not always the least active. Two of the trophic strategies were not randomly distributed throughout a 16S rDNA phylogeny, suggesting they are under selective pressure in this ecosystem and that a link exists between evolutionary relatedness and substrate affinity. The diversity of strategies to adapt to differences in resource availability highlights the need to expand our understanding of microbial interactions with organic matter in order to better predict microbial responses to a changing environment. manuscript accepted by PLoS ONE 4 datasets: 1) fluorescence data for 3 treatments combined, 2) isotopic data for treatment = LOW, 3) isotopic data for treatment = MEDIUM, 4) isotopic data for treatment = HIGH
2014-03-26 | E-GEOD-56119 | biostudies-arrayexpress
Project description:Isolating the properties of proteins that allow them to convert sequence into the structure is a long-lasting biophysical problem. In particular, studies focused extensively on the effect of a reduced alphabet size on the folding properties. However, the natural alphabet is a compromise between versatility and optimisation of the available resources. Here, for the first time, we include the impact of the relative availability of the amino acids to extract from the 20 letters the core necessary for protein stability. We present a computational protein design scheme that involves the competition for resources between a protein and a potential interaction partner that, additionally, gives us the chance to investigate the effect of the reduced alphabet on protein-protein interactions. We devise a scheme that automatically identifies the optimal reduced set of letters for the design of the protein, and we observe that even alphabets reduced down to 4 letters allow for single protein folding. However, it is only with 6 letters that we achieve optimal folding, thus recovering experimental observations. Additionally, we notice that the binding between the protein and a potential interaction partner could not be avoided with the investigated reduced alphabets. Therefore, we suggest that aggregation could have been a driving force in the evolution of the large protein alphabet.
| S-EPMC7021711 | biostudies-literature