Profiling Solid Tumor Heterogeneity by LCM and Biological MS of Fresh-Frozen Tissue Sections
The heterogeneous nature of solid tumors represents a common problem in mass spectrometry (MS)-based analysis of fresh-frozen tissue specimens. Here, we describe a method that relies on synergy between laser capture microdissection (LCM) and MS for enhanced molecular profiling of solid tumors. This method involves dissection of homogeneous histologic cell types from thin fresh-frozen tissue sections via LCM, coupled with liquid chromatography (LC)-MS analysis. Such an approach enables an in-depth molecular profiling of captured cells. This is a bottom-up proteomic approach, where proteins are identified through peptide sequencing and matching against a specific proteomic database. Sample losses are minimized, since lysis, solubilization, and digestion are carried out directly on LCM caps in buffered methanol using a single tube, thus reducing sample loss between these steps. The rationale for the LCM-MS coupling is that once the optimal method parameters are established for a solid tumor of interest, homogeneous histologic tumor/tissue cells (i.e., tumor proper, stroma, etc.) can be effectively studied for potential biomarkers, drug targets, pathway analysis, as well as enhanced understanding of the pathological process under study.
Key wordsThin fresh-frozen tissue sections Laser capture microdissection Liquid chromatography-mass spectrometry Solid tumor heterogeneity Biomarker Cancer
This project was funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract HSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does the mention of trade names, commercial products, or organizations implies endorsement by the US Government.
- 1.Mbeunkui F, Johann DJ, Jr., (2009) Cancer and the tumor microenvironment: a review of an essential relationship. Cancer Chemother Pharmacol 63: 571–82.Google Scholar
- 2.Swanton C, Caldas C, (2009) Molecular classification of solid tumours: towards pathway-driven therapeutics. Br J Cancer100: 1517–22.Google Scholar
- 3.Johann DJ, Jr., Blonder J, (2007) Biomarker discovery: tissues versus fluids versus both. Expert Rev Mol Diagn 7: 473–5.Google Scholar
- 4.Johann DJ, Wei BR, Prieto DA, Chan KC, Ye X, Valera VA, Simpson RM, Rudnick PA, Xiao Z, Issaq HJ, Linehan WM, Stein SE, Veenstra TD, Blonder J. Combined Blood/Tissue Analysis for Cancer Biomarker Discovery: Application to Renal Cell Carcinoma. Anal Chem 2010.Google Scholar
- 5.Emmert-Buck MR, Bonner RF, Smith PD, Chuaqui RF, Zhuang Z, Goldstein SR, Weiss RA, Liotta LA. (1996) Laser capture microdissection. Science 274: 998–1001.Google Scholar
- 6.Aebersold R, Mann M, (2003) Mass spectrometry-based proteomics. Nature 422: 198–207.Google Scholar
- 7.Hwang SI, Thumar J, Lundgren DH, Rezaul K, Mayya V, Wu L, Eng J, Wright ME, Han DK. (2007) Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues. Oncogene 26: 65–76.Google Scholar
- 8.Blonder J, Chan KC, Issaq HJ, Veenstra TD, (2006) Identification of membrane proteins from mammalian cell/tissue using methanol-facilitated solubilization and tryptic digestion coupled with 2D-LC-MS/MS. Nat Protoc 1: 2784–90.Google Scholar
- 9.Johann DJ, Rodriguez-Canales J, Mukherjee S, Prieto DA, Hanson JC, Emmert-Buck M, Blonder J. (2009) Approaching solid tumor heterogeneity on a cellular basis by tissue proteomics using laser capture microdissection and biological mass spectrometry. J Proteome Res 8: 2310–8.Google Scholar
- 10.Wibke H, Pelargus C, Keffhalm K, Ros A, Anselmetti D. (2005) Single cell manipulation, analytics, and label-free protein detection in microfluidic devices for systems nanobiology. Electrophoresis 26: 3689–96.Google Scholar