Literature DB >> 28110648

In Situ Metabolomics in Cancer by Mass Spectrometry Imaging.

A Buck1, M Aichler1, K Huber1, A Walch2.   

Abstract

Metabolomics is a rapidly evolving and a promising research field with the expectation to improve diagnosis, therapeutic treatment prediction, and prognosis of particular diseases. Among all techniques used to assess the metabolome in biological systems, mass spectrometry imaging is the method of choice to qualitatively and quantitatively analyze metabolite distribution in tissues with a high spatial resolution, thus providing molecular data in relation to cancer histopathology. The technique is ideally suited to study tissues molecular content and is able to provide molecular biomarkers or specific mass signatures which can be used in classification or the prognostic evaluation of tumors. Recently, it was shown that FFPE tissue samples are also suitable for metabolic analyses. This progress in methodology allows access to a highly valuable resource of tissues believed to widen and strengthen metabolic discovery-driven studies.
© 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Diagnostic; FFPE tissue; MALDI; Mass spectrometry imaging; Metabolomics; Predictive; Prognostic pathology

Mesh:

Substances:

Year:  2016        PMID: 28110648     DOI: 10.1016/bs.acr.2016.11.004

Source DB:  PubMed          Journal:  Adv Cancer Res        ISSN: 0065-230X            Impact factor:   6.242


  8 in total

Review 1.  Metabolic Regulation of Tissue Stem Cells.

Authors:  Suzanne N Shapira; Heather R Christofk
Journal:  Trends Cell Biol       Date:  2020-04-28       Impact factor: 20.808

2.  Simultaneous metabolite MALDI-MSI, whole exome and transcriptome analysis from formalin-fixed paraffin-embedded tissue sections.

Authors:  Julia Hess; Kristian Unger; Lisa Kreutzer; Peter Weber; Theresa Heider; Mathias Heikenwälder; Tobias Riedl; Philipp Baumeister; Frederick Klauschen; Claus Belka; Axel Walch; Horst Zitzelsberger
Journal:  Lab Invest       Date:  2022-08-31       Impact factor: 5.502

3.  High-dimensionality reduction clustering of complex carbohydrates to study lung cancer metabolic heterogeneity.

Authors:  Lindsey R Conroy; Josephine E Chang; Qi Sun; Harrison A Clarke; Michael D Buoncristiani; Lyndsay E A Young; Robert J McDonald; Jinze Liu; Matthew S Gentry; Derek B Allison; Ramon C Sun
Journal:  Adv Cancer Res       Date:  2022-03-18       Impact factor: 5.767

4.  A transcriptional metabolic gene-set based prognostic signature is associated with clinical and mutational features in head and neck squamous cell carcinoma.

Authors:  Lu Xing; Mingzhu Guo; Xiaoqi Zhang; Xiaoqian Zhang; Feng Liu
Journal:  J Cancer Res Clin Oncol       Date:  2020-02-17       Impact factor: 4.553

Review 5.  Novel methods in adrenal research: a metabolomics approach.

Authors:  Thomas G Papathomas; Na Sun; Vasileios Chortis; Angela E Taylor; Wiebke Arlt; Susan Richter; Graeme Eisenhofer; Gerard Ruiz-Babot; Leonardo Guasti; Axel Karl Walch
Journal:  Histochem Cell Biol       Date:  2019-02-06       Impact factor: 4.304

6.  Molecular Imaging of Immunity and Inflammation and Its Impact on Precision Medicine.

Authors:  Moritz Wildgruber; Michel Eisenblätter
Journal:  Biomedicines       Date:  2021-01-11

Review 7.  Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies.

Authors:  Michelle Junyi He; Wenjun Pu; Xi Wang; Wei Zhang; Donge Tang; Yong Dai
Journal:  Front Oncol       Date:  2022-07-18       Impact factor: 5.738

8.  Molecular subtype identification and prognosis stratification by a metabolism-related gene expression signature in colorectal cancer.

Authors:  Dagui Lin; Wenhua Fan; Rongxin Zhang; Enen Zhao; Pansong Li; Wenhao Zhou; Jianhong Peng; Liren Li
Journal:  J Transl Med       Date:  2021-06-30       Impact factor: 5.531

  8 in total

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