Imperial College London
Dr Emrys Jones

DrEmrysJones

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Honorary Research Associate
 
 
 
//

Contact

 

emrys.jones

 
 
//

Location

 

Sir Alexander Fleming BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Guenther:2015:10.1158/0008-5472.CAN-14-2258,
author = {Guenther, S and Muirhead, LJ and Speller, AVM and Golf, O and Strittmatter, N and Ramakrishnan, R and Goldin, RD and Jones, E and Veselkov, K and Nicholson, J and Darzi, A and Takats, Z},
doi = {10.1158/0008-5472.CAN-14-2258},
journal = {Cancer Research},
pages = {1828--1837},
title = {Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry},
url = {http://dx.doi.org/10.1158/0008-5472.CAN-14-2258},
volume = {75},
year = {2015}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Breast cancer is a heterogeneous disease characterized by varying responses to therapeutic agents and significant differences in long-term survival. Thus, there remains an unmet need for early diagnostic and prognostic tools and improved histologic characterization for more accurate disease stratification and personalized therapeutic intervention. This study evaluated a comprehensive metabolic phenotyping method in breast cancer tissue that uses desorption electrospray ionization mass spectrometry imaging (DESI MSI), both as a novel diagnostic tool and as a method to further characterize metabolic changes in breast cancer tissue and the tumor microenvironment. In this prospective single-center study, 126 intraoperative tissue biopsies from tumor and tumor bed from 50 patients undergoing surgical resections were subject to DESI MSI. Global DESI MSI models were able to distinguish adipose, stromal, and glandular tissue based on their metabolomic fingerprint. Tumor tissue and tumor-associated stroma showed evident changes in their fatty acid and phospholipid composition compared with normal glandular and stromal tissue. Diagnosis of breast cancer was achieved with an accuracy of 98.2% based on DESI MSI data (PPV 0.96, NVP 1, specificity 0.96, sensitivity 1). In the tumor group, correlation between metabolomic profile and tumor grade/hormone receptor status was found. Overall classification accuracy was 87.7% (PPV 0.92, NPV 0.9, specificity 0.9, sensitivity 0.92). These results demonstrate that DESI MSI may be a valuable tool in the improved diagnosis of breast cancer in the future. The identified tumor-associated metabolic changes support theories of de novo lipogenesis in tumor tissue and the role of stroma tissue in tumor growth and development and overall disease prognosis. Cancer Res; 75(9); 1828–37. ©2015 AACR.
AU  - Guenther,S
AU  - Muirhead,LJ
AU  - Speller,AVM
AU  - Golf,O
AU  - Strittmatter,N
AU  - Ramakrishnan,R
AU  - Goldin,RD
AU  - Jones,E
AU  - Veselkov,K
AU  - Nicholson,J
AU  - Darzi,A
AU  - Takats,Z
DO  - 10.1158/0008-5472.CAN-14-2258
EP  - 1837
PY  - 2015///
SN  - 0008-5472
SP  - 1828
TI  - Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry
T2  - Cancer Research
UR  - http://dx.doi.org/10.1158/0008-5472.CAN-14-2258
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000353706600006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://cancerres.aacrjournals.org/content/75/9/1828
UR  - http://hdl.handle.net/10044/1/78229
VL  - 75
ER  -
Download