Dataset Information

Metabolomics in pancreatic cancer cells influenced by MTHFD2

ABSTRACT: Metabolomics of pancreatic cancer cell are modified by metabolic enzyme MTHFD2. SW1990 cells were transfected with MTHFD2 siRNA and control siRNA. Cells were collected for metabolomics analysis.

ORGANISM(S): Homo Sapiens

SUBMITTER: Ting Wang

PROVIDER: PXD024228 | iProX | Thu Feb 18 00:00:00 GMT 2021

REPOSITORIES: iProX

ACCESS DATA

Publications

The folate cycle enzyme MTHFD2 induces cancer immune evasion through PD-L1 up-regulation.

Shang Man M Yang Huijie H Yang Ran R Chen Tao T Fu Yuan Y Li Yeyi Y Fang Xianlong X Zhang Kangjian K Zhang Jianju J Li Hui H Cao Xueping X Gu Jinfa J Xiao Jianwen J Zhang Qi Q Liu Xinyuan X Yu Qiujing Q Wang Ting T

Nature communications 20210329 1

Metabolic enzymes and metabolites display non-metabolic functions in immune cell signalling that modulate immune attack ability. However, whether and how a tumour's metabolic remodelling contributes to its immune resistance remain to be clarified. Here we perform a functional screen of metabolic genes that rescue tumour cells from effector T cell cytotoxicity, and identify the embryo- and tumour-specific folate cycle enzyme methylenetetrahydrofolate dehydrogenase 2 (MTHFD2). Mechanistically, MTH ...[more]

PMID: 33782411

Similar Datasets

Project description:The paper describes a model on the size of pancreatic tumour. Created by COPASI 4.25 (Build 207) This model is described in the article: Modeling Pancreatic Cancer Dynamics with Immunotherapy Xiaochuan Hu, Guoyi Ke and Sophia R.-J. Jang Bulletin of Mathematical Biology (2019) 81:1885–1915 Abstract: We develop a mathematical model of pancreatic cancer that includes pancreatic cancer cells, pancreatic stellate cells, effector cells and tumor-promoting and tumor- suppressing cytokines to investigate the effects of immunotherapies on patient survival. The model is first validated using the survival data of two clinical trials. Local sen- sitivity analysis of the parameters indicates there exists a critical activation rate of pro-tumor cytokines beyond which the cancer can be eradicated if four adoptive trans- fers of immune cells are applied. Optimal control theory is explored as a potential tool for searching the best adoptive cellular immunotherapies. Combined immunother- apies between adoptive ex vivo expanded immune cells and TGF-β inhibition by siRNA treatments are investigated. This study concludes that mono-immunotherapy is unlikely to control the pancreatic cancer and combined immunotherapies between anti-TGF-β and adoptive transfers of immune cells can prolong patient survival. We show through numerical explorations that how these two types of immunotherapies are scheduled is important to survival. Applying TGF-β inhibition first followed by adoptive immune cell transfers can yield better survival outcomes. This model is hosted on BioModels Database and identified by: MODEL1907050003. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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.

Dataset Information

Metabolomics in pancreatic cancer cells influenced by MTHFD2

Publications

The folate cycle enzyme MTHFD2 induces cancer immune evasion through PD-L1 up-regulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets