Abstract SY44-01: Proteogenomic analysis of human colon and rectal cancer
Authors: Daniel C. Liebler
Journal: Cancer Research (2015)

Abstract The growing body of genomics data for human cancers presents the challenge of inference between genomic abnormalities and cancer phenotypes. Proteomics yields proteotypes, which are analogous to genotypes, but provide a critical layer of information that is more directly related to phenotypic expression than either DNA- or RNA-based analyses. To explore this concept, we have conducted a series of proteogenomic studies of colon and rectal cancer (CRC) through the National Cancer Institute (NCI) Clinical Proteomics Tumor Analysis Consortium (CPTAC). We analyzed proteomes of 95 colon and rectal tumors previously characterized by the NCI Cancer Genome Atlas (TCGA) and performed integrated proteogenomic analyses. Analysis of proteomic data with custom databases generated from individual tumor RNAseq data enabled identification of 796 single amino acid variants. Somatic variants were enriched in hypermutated tumors and displayed reduced protein abundance compared to germline variants. Although mRNA and protein abundances were significantly correlated within individual tumors, only 32% of mRNAs were significantly correlated with abundances of the corresponding proteins across the tumor collection. To test whether the concordance between protein and mRNA variation is related to the biological function of the gene product, we performed KEGG enrichment analysis. Genes involved in several metabolic processes showed concordant mRNA and protein variation, whereas other gene classes, including genes involved in ribosome and spliceosome pathways and in oxidative phosphosphorylation showed low or even negative concordance in mRNA and protein variation. Genes with stable mRNA and stable protein tend to have higher mRNA-protein correlation than those with unstable mRNA and unstable protein. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA “MSI/CIMP” transcriptomic subtype, but had distinct mutation, methylation, and protein expression patterns associated with different clinical outcomes. A CRC proteomic subtype associated with poor outcome displayed protein co-expression network signatures consistent with an epithelial to mesenchymal transition (EMT). Analyses of a set of 60 normal colon biopsies provided reference data for comparison to CRC proteomic subtypes and enabled identification of a panel of 80 marker proteins for CRC subtypes. The TCGA study identified 17 regions of significant focal amplification and 28 regions of significant focal deletion in CRC. We examined the impact of copy number alterations (CNAs) on mRNA and protein abundance, including both cis-effects on the abundance of genes in the same loci and trans-effects on the abundance of genes at other loci in the genome. Although CNAs showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Proteomics data indicated that the chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates including HNF4A, TOMM34 and SRC. Our proteomic characterization of this collection of genomically-annotated TCGA CRC tissues illustrates the power of global proteogenomic analysis. We next asked whether proteogenomic analysis could inform the evaluation of specific cellular systems related to cancer phenotypes. Metabolic reprogramming is a hallmark of many cancers and proteogenomic analyses revealed distinct adaptations of metabolic pathways in CRC. Metabolic global protein expression profiles were highly conserved across normal colon specimens (average correlation = 0.93), but were less consistent across CRC (average correlation = 0.78) and distinctly different between CRC and normal tissue (average correlation = 0.52). Proteomic features displayed less variability than mRNA and better discriminated CRC from normal tissues. Of 601 metabolic proteins with shotgun proteomic data, 507 (84%) were differentially expressed between CRC and normal, with twice as many proteins downregulated in tumors versus normal tissues. Differential protein expression was only partially predicted by mRNA abundance differences (correlation = 0.33). Nucleotide metabolism pathways were predominantly upregulated at the protein level in tumors, whereas proteins in carbohydrate and amino acid metabolism pathways were both upregulated and downregulated. Proteins in energy metabolism were predominantly downregulated in tumors. Global proteomic profiles provided data on 85 of 107 proteins in central carbon metabolism pathways (glycolysis, pentose phosphate pathway and the tricarboxylic acid cycle). Comparable numbers of proteins in these three pathways were up- and down-regulated in CRC compared to normal tissues. A targeted, multiplexed parallel reaction monitoring (PRM) analysis of the normal colon and TCGA CRC specimens was used to more precisely quantify 51 proteins involved in central carbon metabolism. PRM analyses revealed heterogeneity in the regulation of enzymes of central carbon metabolism between proteomic CRC subtypes. Although many of the tumors displayed elevated expression of approximately two thirds of carbon metabolism enzymes, a significant subset instead displayed reduced abundance of the same proteins. This subset was enriched for tumors displaying the EMT-associated protein expression subtype, thus suggesting that distinct metabolic reprogramming signatures may encode different tumor phenotypes. Proteotypes derived from integrated proteogenomic analysis provide functional context to interpret genomic abnormalities and afford a new paradigm for understanding cancer biology. Integrated proteogenomic analysis, as demonstrated in this study, will enable new advances in cancer biology, diagnostics and therapeutics. (Supported by NIH Grant U24CA159988.) Citation Format: Daniel C. Liebler. Proteogenomic analysis of human colon and rectal cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr SY44-01. doi:10.1158/1538-7445.AM2015-SY44-01