Journal of Proteome Research ARTICLE Figure 4. Validation of proteomic diﬀerences by LC MRM-MS. Shotgun proteomics data are plotted as spectral counts for triplicate analyses (red bars), whereas MRM data are plotted as summed signal intensity for measured transitions normalized to summed intensity for transitions measured for a reference peptide (blue bars). (n = 3). A list of peptides and corresponding precursor and product m/z values is provided in Supplementary Table S2. of cancer-related mutations have not been well characterized. Here we examined the proteomic consequences of a single gene diﬀerence in a CRC cell line model in which APC expression has been restored. Label free LC MS/MS shotgun proteomics provided a robust and reproducible means to inventory over 5000 proteins in SW480APC and SW480Null. Diﬀerentially expressed proteins included cell adhesion and actin binding proteins and cell cycle regulators all known to be impacted by restoration of wildtype APC expression.11 Additionally, several protein classes not previously thought to be related to Wnt signaling were diﬀerentially expressed, for example, cholesterol biosynthesis, ZEB1 transcription targets. Although most canonical Wnt signaling proteins did not show altered expression (e.g., GSK3B, CTNNB1, DVL1), DKK4, a known negative regulator of Wnt signaling, was signiﬁcantly up- regulated in SW480APC.45 DKK4, in conjunction with Kremen2 (KRM2), inhibits the interaction between Wnt and its core- ceptor low-density lipoprotein receptor-related protein 5/6 (LRP5/6).46 Interestingly, DKK4 is down-regulated in primary colorectal tumors and several colorectal cancer cell lines, and re-expression of DKK4 resulted in attenuation of cell cycle progression.47 Our data agree with these earlier ﬁndings that DKK4 plays an important role in APC-dependent tumor forma- tion. In SW480Null cells we observed increased expression of CACYBP which plays a role in degradation of CTNNB1.48 CACYBP is up-regulated in pancreatic cancer and suppression by siRNA results in decreased cellular proliferation rates.49 In mutant APC expressing cells, enhanced CACYBP expression may be an adaptive response to increased levels of unbound CTNNB1. A distinct group of proteins involved in RNA processing is up- regulated in SW480Null cells (e.g., DDX23, SART1 and HNR- NPL). Several genes are known to undergo abnormal splicing in cancer, including KLF6, DNMT3B and BRCA1.50 52 Changes in the levels or the activities of regulatory splice proteins may contribute to tumor formation.53 For instance serine/arginine rich (SR) proteins play a key role in the speciﬁcation of splice sites in eukaryotic mRNA and are regulated in part by their phosphoryla- tion status. SFRS2 is an SR protein involved in the formation of an early ATP-dependent splicing complex.54 Here we see an increase in its interacting protein SFRSIP in SW480Null. SR proteins may also interact with heterogeneous nuclear ribonucleoproteins (hnRNPs).53 In the current data set HNRNPL is up-regulated in mutant APC cells. Changes to the stoichiometric ratios of SR proteins and hnRNPs may inﬂuence the expression proﬁles of splice variants in APCNull cells. Further experiments will be required to establish if increases to RNA processing proteins are merely a byproduct of the faster growth rate in SW480Null cells or the result of another aspect of APC deﬁciency. Altered expression was observed in proteins associated with isoprenoid biosynthetic pathways (ACAT2, MVD, FDPS, HMGCS2). Prenylation and farnesylation of key signal transduc- tion proteins may modify pathways activities in cancer. Modula- tions to PTP4A3 and CDC42 have been shown to contribute to colon cancer and breast cancer, respectively.55,56 Given the important role of prenylation in tumor formation, anticancer agents have been developed which suppress key enzymes in this pathway, including RCE1 and IMCT.57,58 Isoprenoid biosyn- thetic proteins identiﬁed here may represent alternative ther- apeutic targets in mutant APC-dependent colorectal cancer. Interestingly, many of these proteins showed discordant expres- sion patterns between transcriptomic and proteomic data sets. The isoprenoid pathway provides metabolic precursors to steroid biosynthesis, a process subject to feedback regulation. For example, elevated sterol levels result in decreased HMGCR, the rate-limiting enzyme of sterol biosynthesis, via ER-associated degradation and proteolysis.59 It is unclear if such a feedback mechanism may explain discordant expression of isoprenoid synthesis proteins in this study. In general, our results illustrate how proteomic analysis may provide biological insights that would otherwise not be predicted by transcriptomic analysis alone or by previous descriptions of 1192 dx.doi.org/10.1021/pr2009109 |J. Proteome Res. 2012, 11, 1184–1195