The molecular mechanisms underlying the pathogenesis of diffuse-type gastric cancer (DGC) have not been adequately explored due to a scarcity of appropriate animal models. A recently developed tool well suited for this line of investigation is the Pdx-1-Cre;Cdh1 ;Trp53 ;Smad4 (pC PS) mouse model that spontaneously develops metastatic DGC showing nearly complete E-cadherin loss. Here, we performed a proteogenomic analysis to uncover the molecular changes induced by the concurrent targeting of E-cadherin, p53, and Smad4 loss. The gene expression profiles of mouse DGCs and in vivo gastric phenotypes from various combinations of gene knockout demonstrated that these mutations collaborate to activate cancer-associated pathways to generate aggressive DGC. Of note, WNT-mediated epithelial-to-mesenchymal transition (EMT) and extracellular matrix (ECM)-cytokine receptor interactions were prominently featured. In particular, the WNT target gene osteopontin (OPN) that functions as an ECM cytokine is highly upregulated. In validation experiments, OPN contributed to DGC stemness by promoting cancer stem cell (CSC) survival and chemoresistance. It was further found that Bcl-xL acts as a targetable downstream effector of OPN in DGC CSC survival. In addition, Zeb2 and thymosin-β4 (Tβ4) were identified as prime candidates as suppressors of E-cadherin expression from the remaining Cdh1 allele during DGC development. Specifically, Tβ4 suppressed E-cadherin expression and anoikis while promoting cancer cell growth and migration. Collectively, these proteogenomic analyses broaden and deepen our understanding of the contribution of key driver mutations in the stepwise carcinogenesis of DGC through novel effectors, namely OPN and Tβ4.

Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid mass spectrometers such as the quadrupole-orbitrap mass spectrometer, can yield tens of thousands of tandem mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor monoisotopic masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate monoisotopic masses to MS/MS spectra, including those subject to cofragmentation. The method, “multiplexed post-experiment monoisotopic mass refinement” (mPE-MMR), consists of the following: multiplexing of precursor masses to assign multiple monoisotopic masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states to assign correct charges to the precursor ions of MS/ MS spectra with no charge information, and mass correction for inaccurate monoisotopic peak picking. When combined with MS-GF+, a database search algorithm based on fragment mass difference, mPE-MMR effectively increases both sensitivity and accuracy in peptide identification from complex high-throughput proteomics data compared to conventional methods.

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