The diffuse-type gastric cancer (DGC) is a subtype of gastric cancer with the worst prognosis and few treatment options. Here we present a dataset from 84 DGC patients, composed of a proteome of 11,340 gene products and mutation information of 274 cancer driver genes covering paired tumor and nearby tissue. DGC can be classified into three subtypes (PX1–3) based on the altered proteome alone. PX1 and PX2 exhibit dysregulation in the cell cycle and PX2 features an additional EMT process; PX3 is enriched in immune response proteins, has the worst survival, and is insensitive to chemotherapy. Data analysis revealed four major vulnerabilities in DGC that may be targeted for treatment, and allowed the nomination of potential immunotherapy targets for DGC patients, particularly for those in PX3. This dataset provides a rich resource for information and knowledge mining toward altered signaling pathways in DGC and demonstrates the benefit of proteomic analysis in cancer molecular subtyping.

Altered re-wiring of cell metabolism and transcriptional programs are both hallmarks of cancer that sustain rapid proliferation and metastasis1. However mechanisms controlling the interplay between metabolic reprogramming and transcriptional regulation remain elusive. Here we show that metabolic enzyme 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 4 (PFKFB4) regulates transcriptional reprogramming by activating the oncogenic steroid receptor coactivator-3 (SRC-3). We employed a method for identifying potential kinases that modulate coactivator functions by integrating kinome-wide RNA interference (RNAi)-based screening coupled to intrinsic SRC-3-transcriptional response. PFKFB4, a regulatory enzyme that synthesizes an allosteric stimulator of glycolysis2, was found to be a robust stimulator of SRC-3 that co-activates estrogen receptor (ER). PFKFB4 phosphorylates SRC-3 at serine 857 (S857) enhancing its transcriptional activity, whereas either suppression of PFKFB4 or ectopic expression of a phosphorylation-deficient SRC-3 mutant S857A (SRC-3S857A) significantly abolishes SRC-3-mediated transcriptional output. Functionally, PFKFB4-driven SRC-3 activation drives glucose flux towards the pentose phosphate pathway enabling purine synthesis by transcriptionally upregulating the expression of enzyme transketolase (TKT). In addition, two enzymes adenosine monophosphate deaminase-1 (AMPD1) and xanthine dehydrogenase (XDH) involved in purine metabolism were identified as SRC-3 targets which may or may not be directly involved in purine synthesis. Mechanistically, phosphorylation at S857 increases coactivator interaction with the transcription factor ATF4 stabilizing SRC-3/ATF4 recruitment to target gene promoters. Ablation of SRC-3 or PFKFB4 suppresses in vivo breast tumor growth and prevents metastasis to the lung from an orthotopic setting as does an SRC-3S857A mutant. PFKFB4 and pSRC-3-S857 levels are elevated and significantly correlate in ER positive tumors whereas, in patients with basal subtype, PFKFB4-SRC-3 drives a common protein signature that positively correlates with the poor survival of breast cancer patients. These findings suggest that the Warburg-pathway enzyme PFKFB4 acts as a molecular fulcrum coupling sugar metabolism to transcriptional activation by stimulating SRC-3 critical to promote aggressive metastatic tumors.

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In addition to its role as a tumour suppressor tenance of a fine balance of p53 protein levels within and cell-cycle checkpoint control protein, p53 has been embryonic cells is important for optimal development.Inappropriate overexpression or underexpression of p53 implicated as an important protein in embryonic development. Despite the viability of most p53 null mice, can lead to embryonic lethality or increased risk of evidence has accumulated that p53 may regulate differ-malformations. The p53 protein may utilize multiple entiation and the response of embryonic cells to diverse functional activities in its regulation of developmental environmental stresses. Moreover, it appears that main-processes.

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In quantitative mass spectrometry, the method by which peptides are grouped into proteins can have dramatic effects on downstream analyses. Here we describe gpGrouper, an inference and quantitation algorithm that offers an alternative method for assignment of protein groups by gene locus and improves pseudo-absolute iBAQ quantitation by weighted distribution of shared peptide areas. We experimentally show that distributing shared peptide quantities based on unique peptide peak ratios improves quantitation accuracy compared with conventional winner-take-all scenarios. Furthermore, gpGrouper seamlessly handles two-species samples such as patient-derived xenografts (PDXs) without ignoring the host species or species-shared peptides. This is a critical capability for proper evaluation of proteomics data from PDX samples, where stromal infiltration varies across individual tumors. Finally, gpGrouper calculates peptide peak area (MS1) based expression estimates from multiplexed isobaric data, producing iBAQ results that are directly comparable across label-free, isotopic, and isobaric proteomics approaches.

BackgroundChronic kidney disease (CKD) is commonly associated with cachexia, a condition that causes skeletal muscle wasting and an unfavourable prognosis. Although mechanisms leading to cachexia have been intensively studied, the advance of biological knowledges and technologies encourages us to make progress in understanding the pathogenesis of this disorder. Long noncoding RNAs (lncRNAs) are defined as >200 nucleotides RNAs but lack the protein‐coding potential. LncRNAs are involved in the pathogenesis of many diseases, but whether they functionally involve in muscle protein loss has not been investigated.MethodsWe performed lncRNA array and identified an lncRNA, which we named Atrolnc‐1, remarkably elevated in atrophying muscles from mice with cachexia. We examined how overexpression or knockdown of Atrolnc‐1 could influence muscle protein synthesis and degradation. We also examined whether inhibition of Atrolnc‐1 ameliorates muscle wasting in mice with CKD.ResultsWe documented that Atrolnc‐1 expression is continuously increased in muscles of mice with fasting (5.4 fold), cancer (2.0 fold), or CKD (5.1 fold). We found that depressed insulin signalling stimulates the transcription factor C/EBP‐α binding to the promoter of Atrolnc‐1 and promotes the expression of Atrolnc‐1. In cultured C2C12 myotubes, overexpression of Atrolnc‐1 increases protein degradation (0.45±0.03 vs. 0.64±0.02, *p<0.05); Atrolnc‐1 knockdown significantly reduces the rate of protein degradation stimulated by serum depletion (0.61±0.03 vs. 0.47±0.02, *p<0.05). Using mass spectrometry and a lncRNA pull‐down assay, we identified that Atrolnc‐1 interacts with A20 binding inhibitor of NF‐κB‐1 (ABIN‐1). The interaction impairs function, resulting in enhanced NF‐κB activity plus MuRF‐1 transcription. This response is counteracted by CRISPR/dCas9 mediated overexpression. In muscles from normal mice, overexpression of Atrolnc‐1 stimulates a 2.7‐fold increase in MuRF‐1 expression leading to myofibers atrophy. In contrast, Atrolnc‐1 knockdown attenuates muscle wasting by 42% in mice with CKD via suppression of NF‐κB activity and MuRF‐1 expression.ConclusionsOur findings provide evidence that lncRNAs initiates the pathophysiological process of muscle wasting. The interaction between Atrolnc‐1 and NF‐κB signalling modulates muscle mass and proteolysis in CKD and perhaps other catabolic conditions.

Although various in vitro assays have been developed to evaluate the cytochrome P450 (CYP)-inducing potential of drug candidates, there is a continuing need for the development of a reliable model in drug discovery. The objective of the present study was to compare CYP induction by chemicals in HepG2 cells with Huh7, NKNT-3, and reverted NKNT-3 cells. HepG2 cells showed more similarity to human liver than the other cell lines in comparisons of the expression of cellular proteins. In evaluation of basal CYP activity, Huh7 cells exhibited the highest CYP1A2 and CYP3A4 activity, and HepG2 cells showed the highest CYP2B6 activity. The inducibility of CYP1A2, CYP2B6, and CYP3A4 by prototypical inducers was determined using enzyme assay, immunoblot analysis, and real-time PCR. Among the cells tested, HepG2 cells were highly responsive to CYP inducers, such as 3-methylcholanthrene for CYP1A2 and phenobarbital for CYP2B6 and CYP3A4. Moreover, HepG2 cells were responsive to various CYP1A2, CYP2B6, and CYP3A4 inducers as determined using fluorogenic and LC-MS/MS substrates. Thus, HepG2 cells may be comparable to human hepatocytes for the evaluation of CYP induction or slightly less sensitive. These results suggest HepG2 cells as a cell-based model in screening for CYP inducers in drug discovery.