Orbi‐SIMS Mediated Metabolomics Analysis of Pathogenic Tissue up to Cellular Resolution

Author:

Kern Christine1ORCID,Scherer Astrid1,Gambs Laura1ORCID,Yuneva Mariia2ORCID,Walczak Henning34ORCID,Liccardi Gianmaria5,Saggau Julia45ORCID,Kreuzaler Peter6ORCID,Rohnke Marcus17ORCID

Affiliation:

1. Institute of Physical Chemistry Justus Liebig University Giessen 35392 Giessen Germany

2. Oncogenes and Tumour Metabolism Laboratory The Francis Crick Institute London NW1 1 AT UK

3. Centre for Cell Death Cancer and Inflammation (CCCI) UCL Cancer Institute London WC1E 6DD UK

4. Institute of Biochemistry I & CECAD Cluster of Excellence Medical Faculty University of Cologne 50931 Cologne Germany

5. Genome instability inflammation and cell death laboratory Institute of Biochemistry I Centre of Biochemistry Medical Faculty University of Cologne 50931 Cologne Germany

6. University Hospital Cologne I & CECAD Cluster of Excellence Medical Faculty University of Cologne 50931 Cologne Germany

7. Center for Materials Research Justus Liebig University Giessen 35392 Giessen Germany

Abstract

AbstractTumors have a complex metabolism that differs from most metabolic processes in healthy tissues. It is highly dynamic and driven by the tumor cells themselves, as well as by the non‐transformed stromal infiltrates and immune components. Each of these cell populations has a distinct metabolism that depends on both their cellular state and the availability of nutrients. Consequently, to fully understand the individual metabolic states of all tumor‐forming cells, correlative mass spectrometric imaging (MSI) up to cellular resolution with minimal metabolite shift needs to be achieved. By using a secondary ion mass spectrometer (SIMS) equipped with an Orbitrap mass analyzer, we present a workflow to image primary murine tumor tissues up to cellular resolution and correlate these ion images with post acquisition immunofluorescence or histological staining. In a murine breast cancer model, we could identify metabolic profiles that clearly distinguish tumor tissue from stromal cells and immune infiltrates. We demonstrate the robustness of the classification by applying the same profiles to an independent murine model of lung cancer, which is accurately segmented by histological traits. Our pipeline allows metabolic segmentation with simultaneous cell identification, which in the future will enable the design of subpopulation‐targeted metabolic interventions for therapeutic purposes.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3