Abstract PO-042: A multimodal analysis in breast cancer: Revealing metabolic heterogeneity using DESI-MS imaging with Laser-microdissection coupled transcriptome approach
Authors: Emine Kazanc, Evi Karali, Vincen Wu, Paolo Inglese, James McKenzie, Aurelien Tripp, Nikos Koundouros, Thanasis Tsalikis, Hiromi Kudo, George Poulogiannis, Zoltan Takats
Journal: Cancer Research (2020)

Abstract Introduction A multi-modal analysis approach using desorption electrospray ionization (DESI-MSI) and RNA-Seq can envision a complete metabolic and genetic information from clinical specimens revealing tumour heterogeneity. Coupled with laser capture microdissection (LCM) provides a compelling opportunity for molecular sub-characterizing of the tumour tissues. 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 RNA seq for transcriptomics. Objectives The aim of this study was developing a multi-modal analysis protocol obtaining metabolic clusters to get a more in-depth knowledge for tumour-heterogeneity from Patient-derived Xenografts (PDXs) and clinical specimens. Methods PDXs and primary tissue biopsies from patients with Breast cancer were cryosectioned at ten μm 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&amp;E 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 RNA Sequencing. Results 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 metabolically different sub-clones in the adjacent tumour 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 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. Conclusion: We found that developing a multi-modal analysis protocol coupled to Laser capture microdissection is a promising approach for the identification of metabolic heterogeneity in the cancerous specimens. Citation Format: Emine Kazanc, Evi Karali, Vincen Wu, Paolo Inglese, James McKenzie, Aurelien Tripp, Nikos Koundouros, Thanasis Tsalikis, Hiromi Kudo, George Poulogiannis, Zoltan Takats. A multimodal analysis in breast cancer: Revealing metabolic heterogeneity using DESI-MS imaging with Laser-microdissection coupled transcriptome approach [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-042.