Abstract B18: Molecular classification of NMIBC based on protein abundance
Authors: Rafael S. Stroggilos, Marika Mokou, Agnieszka Latosinska, Manousos Makridakis, Vasiliki Lygirou, Emmanouil Mavrogeorgis, Dimitris Drekolias, Maria Frantzi, William Mullen, Charalampos Fragkoulis, Konstantinos Stasinopoulos, Georgios Papadopoulos, Georgios Stathouros, Konstantinos Ntoumas, Harald Mischak, Jerome Zoidakis, Antonia Vlahou
Journal: Clinical Cancer Research (2020)

Abstract Recent investigations, mainly at the DNA/RNA levels, of muscle-invasive (MIBC) and non-muscle invasive bladder cancer (NMIBC) highlighted the existence of molecular subtypes exhibiting diverse levels of aggressiveness. Studies at the protein level are scarce but are needed to enhance present findings and fill existing gaps. The objective of our work is to subtype NMIBC at the proteomic level and place it in the context of the existing NMIBC classification schemes, targeting to ultimately define optimal patient management. One hundred seventeen fresh-frozen tissue specimens from primary untreated BC cases (98 NMIBC and 19 MIBC samples) were processed for high-resolution LC-MS/MS analysis. By utilizing only the high-confidence spectrometric data (FDR &amp;lt; 0.01), as well as the mean abundance of the top 3 most abundant peptides per protein for protein quantification, more than 5,000 protein IDs in total were identified. The proteomics output was subjected to unsupervised consensus clustering, principal component analysis (PCA), and investigation of subtype-specific features, pathways, and genesets. Based on protein abundance, NMIBC patients were optimally stratified to 3 subtypes (classes), differing at size, clinicopathologic, and molecular backgrounds: Class 1 (mostly high stage/grade/risk samples) was the smallest in size (17/98) and expressed predominantly an immune/inflammatory phenotype, features involved in cell proliferation, unfolded protein response, and DNA damage response; class 2 (mixed stage/grade/risk composition) presented with an infiltrated/mesenchymal profile; and class 3 tumors were rich in luminal/differentiation markers, in line with their pathologic classification (mostly low stage/grade/risk samples). PCA revealed proximity of class 1 and conversely, remoteness of class 3 to the proteome of MIBC. Using GSEA and a Random Forest-based classifier on UROMOL's data (Hedegaard J et al., Cell 2016), we identified strong associations between our proteomics class 1 and the progressed UROMOL subtype and likewise between our proteomics class 3 and the two nonprogressed UROMOL subtypes. Several proteins distinguishing these two extreme proteomic subtypes (class 1 vs. 3) were found to also consistently differ at the mRNA levels between NMIBC “progressor” and “nonprogressor” groups of the UROMOL and LUND cohorts. Collectively, protein-based classification of NMIBC resulted in the definition of 3 classes with distinct pathologic and molecular profiles, sharing analogies to the existing transcriptomic NMIBC subtypes. The presented results facilitate shortlisting potential NMIBC prognosticators for further validation in clinical trials. Citation Format: Rafael S. Stroggilos, Marika Mokou, Agnieszka Latosinska, Manousos Makridakis, Vasiliki Lygirou, Emmanouil Mavrogeorgis, Dimitris Drekolias, Maria Frantzi, William Mullen, Charalampos Fragkoulis, Konstantinos Stasinopoulos, Georgios Papadopoulos, Georgios Stathouros, Konstantinos Ntoumas, Harald Mischak, Jerome Zoidakis, Antonia Vlahou. Molecular classification of NMIBC based on protein abundance [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr B18.