Abstract A066: Expanding insights into the colorectal cancer tumor proteome; unbiased protein profiling reveals multiple proteomic-based tumor subtypes
Authors: Dupuis Nicholas , Muntel Jan , Bruderer Roland , Reiter Lukas 
Published: February 2019

Introduction: Recent approvals of microsatellite instability (MSI) or mismatch repair (MMR) testing, in addition to PD-L1 expression, expand the tools available to identify tumor characteristics that may help predict the likelihood of patient response to immunotherapy treatment. However, even in MSI positive subgroups, not all subjects achieve a durable response and research continues to identify tumor characteristics that further predict the likelihood of patient response. To support and advance this area of research, new tools are being developed that provide deeper and unbiased views of the tumor proteome. Here, we characterize the protein expression profiles of 95 colorectal cancer tumors (CRC) using SWATH acquisition mass spectrometry (SWATH MS) to further probe tumor phenotypic characteristics. Experimental Methods: FFPE colon tissue samples (10 healthy, 95 cancer) were obtained from commercial biobanks. Proteins were extracted from the tissue, processed to peptides with trypsin, and prepared for LC-MS analysis. Peptides for each sample were injected on a Triart C18 column (YMC) coupled to a NanoLC 425 system (SCIEX) using a 43min gradient at a flow rate of 5µl/min. The eluted peptides were then analyzed with a TripleTOF® 6600 system (SCIEX) operated in SWATH mode. Total run time per sample was 1 hour. Data were analyzed in Spectronaut Pulsar X (Biognosys) with a project specific library. All data were filtered with a 1% FDR on peptide and protein level. Results: Across all samples, &gt;4,500 protein groups were quantified (approximately 3,600 per sample). Data analysis revealed a large number of proteins (~1,000) were differentially expressed in the cancer cohort. Consistent with increased tumor cell proliferation, proteins involved in protein translation were upregulated in the tumor samples. Unsupervised clustering of the data separated the healthy and the cancer cohort. Clustering also revealed three main proteomic subtypes within in the cancer cohort (A, B and C), which were largely distinguished by expression of cell adhesion proteins, including neuronal growth regulator 1 (NEGR1), a potential tumor suppressor. Interestingly, hepatocyte nuclear factor 4-alpha (HNF4A), a transcription factor which is known to be elevated in CRC, was only overexpressed in subtype B. Further analysis of key protein networks related to CRC treatment and immunotherapy development will be presented. Conclusions: High-throughput proteomic profiling of FFPE tissues using SWATH-MS enables the deepest phenotypic characterization of tumor tissue. Ultimately, analyses of this type will enable a functional understanding of interplay between the tumor microenvironment, expression of protein networks and response to immune-directed therapies.

Citation Format: Nicholas Dupuis, Jan Muntel, Roland Bruderer, Lukas Reiter. Expanding insights into the colorectal cancer tumor proteome; unbiased protein profiling reveals multiple proteomic-based tumor subtypes [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr A066.