Targeted proteomics data interpretation with DeepMRM.

Targeted proteomics is widely utilized in clinical proteomics; however, researchers often devote substantial time to manual data interpretation, which hinders the transferability, reproducibility, and scalability of this approach. We introduce DeepMRM, a software package based on deep learning algorithms for object detection developed to minimize manual intervention in targeted proteomics data analysis. DeepMRM was evaluated on internal and public datasets, demonstrating superior accuracy compared with the community standard tool Skyline. To promote widespread adoption, we have incorporated a stand-alone graphical user interface for DeepMRM and integrated its algorithm into the Skyline software package as an external tool.

Proteogenomic landscape of human pancreatic ductal adenocarcinoma in an Asian population reveals tumor cell-enriched and immune-rich subtypes.

We report a proteogenomic analysis of pancreatic ductal adenocarcinoma (PDAC). Mutation-phosphorylation correlations identified signaling pathways associated with somatic mutations in significantly mutated genes. Messenger RNA-protein abundance correlations revealed potential prognostic biomarkers correlated with patient survival. Integrated clustering of mRNA, protein and phosphorylation data identified six PDAC subtypes. Cellular pathways represented by mRNA and protein signatures, defining the subtypes and compositions of cell types in the subtypes, characterized them as classical progenitor (TS1), squamous (TS2-4), immunogenic progenitor (IS1) and exocrine-like (IS2) subtypes. Compared with the mRNA data, protein and phosphorylation data further classified the squamous subtypes into activated stroma-enriched (TS2), invasive (TS3) and invasive-proliferative (TS4) squamous subtypes. Orthotopic mouse PDAC models revealed a higher number of pro-tumorigenic immune cells in TS4, inhibiting T cell proliferation. Our proteogenomic analysis provides significantly mutated genes/biomarkers, cellular pathways and cell types as potential therapeutic targets to improve stratification of patients with PDAC.

Blockers of Wnt3a, Wnt10a, or ß-Catenin Prevent Chemotherapy-Induced Neuropathic Pain In Vivo.

Although chemotherapy is a key cancer treatment, many chemotherapeutic drugs produce chronic neuropathic pain, called chemotherapy-induced neuropathic pain (CINP), which is a dose-limiting adverse effect. To date, there is no medicine that prevents CINP in cancer patients and survivors. We determined whether blockers of the canonical Wnt signaling pathway prevent CINP. Neuropathic pain was induced by intraperitoneal injection of paclitaxel (PAC) on four alternate days in male Sprague-Dawley rats or male Axin2-LacZ knock-in mice. XAV-939, LGK-974, and iCRT14, Wnt/ß-catenin blockers, were administered intraperitoneally as a single or multiple doses before or after injury. Mechanical allodynia, phosphoproteome profiling, Wnt ligands, and inflammatory mediators were measured by von Frey filament, phosphoproteomics, reverse transcription-polymerase chain reaction, and Western blot analysis. Localization of ß-catenin was determined by immunohistochemical analysis in the dorsal root ganglia (DRGs) in rats and human. Our phosphoproteome profiling of CINP rats revealed significant phosphorylation changes in Wnt signaling components. Importantly, repeated systemic injections of XAV-939 or LGK-974 prevented the development of CINP in rats. In addition, XAV-939, LGK-974, and iCRT14 ameliorated CINP. PAC increased Wnt3a and Wnt10a, activated ß-catenin in DRG, and increased monocyte chemoattractant protein-1 and interleukin-1ß in DRG. PAC also upregulated rAxin2 in mice. Furthermore, ß-catenin was expressed in neurons, including calcitonin gene-related protein-expressing neurons and satellite cells in rat and human DRG. In conclusion, chemotherapy increases Wnt3a, Wnt10a, and ß-catenin in DRG and their pharmacological blockers prevent and ameliorate CINP, suggesting a target for the prevention and treatment of CINP.

Proteogenomic Characterization of Human Early-Onset Gastric Cancer.

We report proteogenomic analysis of diffuse gastric cancers (GCs) in young populations. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival. Furthermore, integrated clustering of mRNA, protein, phosphorylation, and N-glycosylation data identified four subtypes of diffuse GCs. Distinguishing these subtypes was possible by proteomic data. Four subtypes were associated with proliferation, immune response, metabolism, and invasion, respectively; and associations of the subtypes with immune- and invasion-related pathways were identified mainly by phosphorylation and N-glycosylation data. Therefore, our proteogenomic analysis provides additional information beyond genomic analyses, which can improve understanding of cancer biology and patient stratification in diffuse GCs.

Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease-related protein networks.

Multi-dimensional proteomic analyses provide different layers of protein information, including protein abundance and post-translational modifications. Here, we report an integrated analysis of protein expression, phosphorylation, and N-glycosylation by serial enrichments of phosphorylation and N-glycosylation (SEPG) from the same tissue samples. On average, the SEPG identified 142,106 unmodified peptides of 8,625 protein groups, 18,846 phosphopeptides (15,647 phosphosites), and 4,019 N-glycopeptides (2,634 N-glycosites) in tumor and adjacent normal tissues from three gastric cancer patients. The combined analysis of these data showed that the integrated analysis additively improved the coverages of gastric cancer-related protein networks; phosphoproteome and N-glycoproteome captured predominantly low abundant signal proteins, and membranous or secreted proteins, respectively, while global proteome provided abundances for general population of the proteome. Therefore, our results demonstrate that the SEPG can serve as an effective approach for multi-dimensional proteome analyses, and the holistic profiles of protein expression and PTMs enabled improved interpretation of disease-related networks by providing complementary information.

A protein profile of visceral adipose tissues linked to early pathogenesis of type 2 diabetes mellitus.

Adipose tissue is increasingly recognized as an endocrine organ playing important pathophysiological roles in metabolic abnormalities, such as obesity, cardiovascular disease, and type 2 diabetes mellitus (T2DM). In particular, visceral adipose tissue (VAT), as opposed to subcutaneous adipose tissue, is closely linked to the pathogenesis of insulin resistance and T2DM. Despite the importance of VAT, its molecular signatures related to the pathogenesis of T2DM have not been systematically explored. Here, we present comprehensive proteomic analysis of VATs in drug-naïve early T2DM patients and subjects with normal glucose tolerance. A total of 4,707 proteins were identified in LC-MS/MS experiments. Among them, 444 increased in abundance in T2DM and 328 decreased. They are involved in T2DM-related processes including inflammatory responses, peroxisome proliferator-activated receptor signaling, oxidative phosphorylation, fatty acid oxidation, and glucose metabolism. Of these proteins, we selected 11 VAT proteins that can represent alteration in early T2DM patients. Among them, up-regulation of FABP4, C1QA, S100A8, and SORBS1 and down-regulation of ACADL and PLIN4 were confirmed in VAT samples of independent early T2DM patients using Western blot. In summary, our profiling provided a comprehensive basis for understanding the link of a protein profile of VAT to early pathogenesis of T2DM.

High yield synthesis of catalytically active five-fold twinned Pt nanorods from a surfactant-ligated precursor.

The CO-assisted thermal decomposition of a new, surfactant-ligated Pt precursor, [Pt(acac)(NHR)](n) (n = 2, 3; R = C(18)H(37)), gives structurally uniform five-fold twinned Pt nanorods. The Pt nanorods, mostly covered by {100} facets, exhibit much enhanced electrocatalytic activity over {100} faceted Pt nanocubes, indicating the superior catalytic performance due to the presence of the reactive twinning interface.