= Emerging. More than 5 years before clinical availability. (29.54%)
= Expected to be clinically available in 1 to 4 years. (38.82%)
= Clinically available now. (31.65%)
MSACL 2020 US : Kazanc

MSACL 2020 US Abstract

Topic: Imaging

Podium Presentation in Room 4 on Thursday at 13:35 (Chair: Christopher Anderton / Wojciech Michno)

A Multi-modal Analysis on Cancer Research Using DESI-MSI, LC-MS, and RNA-seq with Laser Capture Microdissection

Emine Kazanc (Presenter)
Imperial College of London

Presenter Bio(s): I have completed my bachelor's in Molecular Biology and Genetics at Istanbul University, Turkey, 2012. I did internships in institutes such as in Emory Winship Cancer Institute, USA, 2015, and the Institute of Neuroscience in Newcastle, UK, 2011. I also took part in a project as a research student in Yeditepe University, Turkey, 2012-2014. During this project, I decided to continue in the cancer field. I then got a scholarship to conduct my master in The Cancer Cell and Molecular Biology at the University of Leicester, UK, 2015-2016. In 2017, I have started my Ph.D. in the Surgery and Cancer department in the Imperial College of London. I have focused on developing a multi-modal analysis protocol for clinical specimens. This analysis approach using DESI-MSI, LC-MS, and RNA seq with the great help of Laser capture microdissection allows us to analyze the clinical samples comprehensively.

Authors: Emine Kazanc(1),Evdoxia Karali(2),Vincen Wu(1), Paolo Inglese(1), James McKenzie(1),Erika Dorado Montezuma (1), Sadaf Ghaem-Maghami(3), George Poulogiannis(2),Zoltan Takats(1)
1)Imperial College London, Computational and Systems Medicine, Faculty of Medicine, UK 2)Institute of Cancer Research, UK 3)Imperial College London, Hammersmith Hospital, UK



A multi-modal analysis approach using desorption electrospray ionization (DESI-MSI), Liquid chromatography-mass spectrometry(LC-MS), and RNA-Seq can envision a complete metabolic and genetic information from clinical specimens. The combination of a multi-modal analysis approach with laser capture microdissection(LCM) provides a compelling opportunity for molecular sub-characterizing of diseases in particularly in cancer. The envisioned combination analysis raises special requirements, including short LCM time, to prevent RNA degradation during microdissection at room temperature. The isolated RNA must have sufficient quality and quantity to carry out qPCR, RNA seq for transcriptomics. Also, the extracted samples from microdissected sections must have an adequate amount for LC-MS.


The aim of this study was developing a multi-modal analysis protocol for clinical specimens. This analysis approach using DESI-MSI, LC-MS, and RNA seq with the great help of Laser capture microdissection allows us to analyze the clinical samples comprehensively, particularly precious tumor biopsies.


Multiple fresh-frozen human tissue samples were obtained from Imperial College Healthcare Tissue Bank (ICHTB). Tissue samples from a patient with ovarian cancer were cryosectioned at 10 ┬Ám and mounted on PEN membrane glass slides, which are unique slides for LASER Capture Microdissection (LDM). The DESI imaging analysis area was obtained line-by-line using the DEFFI sprayer. The analyzed tissue sections were stained with H&E in RNase free conditions and annotated by a histopathologist to allow the alignment of optical and MSI images. Next, the areas of interest in the same slide were microdissected by Laser Capture Microdissection for LC-MS and RNA-seq (Leica LDM 7000). RNA was isolated with a commercial kit (Qiagen RNeasy Micro Kit). Finally, standardization of RNA quality control was done by the Agilent 2100 Bioanalyzer System and followed by qPCR and RNA Sequencing.


Preliminary results showed that the extracted samples from microdissected sections using Laser Capture Microdissected for LC-MS could be used to validate the metabolites and lipids, which already had been imaged by DESI-MSI. These DESI-MSI and LC-MS results, which obtained from specific areas on the tissue sections can be attributed to identifying sub-clones in the same tumor sections. The next identification method for sub-cloning is a transcriptomic approach. For the transcriptomic study, the results of Agilent showed that the RNA quality of samples was sufficiently competent to carry out downstream analysis, including qPCR and RNA seq. RNA seq can identify specific gene expression of the pathways, which are related to the identified metabolic profiling by DESI-MSI and LC-MS.


We found that developing a multi-modal analysis protocol using Laser capture microdissection is a promising approach for identification sub-clones in the cancerous specimens.

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