细胞应激和氧化还原活性蛋白参与硫氧还蛋白-1高表达幽门螺杆菌感染所致胃黏膜的癌变

Cellular stress and redox activity proteins are involved in gastric carcinogenesis associated with Helicobacter pylori infection expressing high levels of thioredoxin-1 # # 细胞应激和氧化还原活性蛋白参与硫氧还蛋白-1高表达幽门螺杆菌感染所致胃黏膜的癌变 1 first-author 2 3 4 2 2 2 corresp ‡Corresponding Author ‡Corresponding Author †E-mail:dingshigang222@163.com †E-mail:dingshigang222@163.com dingshigang222@163.com Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Department of Gastroenterology, Peking University Third Hospital, Beijing 100191, China Department of Gastroenterology, Peking University Third Hospital, Beijing 100191, China Department of Microbiology, Peking University Health Science Center, Beijing 100191, China Department of Microbiology, Peking University Health Science Center, Beijing 100191, China Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China Helicobacter pylori infection is related to the development of gastric diseases. Our previous studies showed that high thioredoxin-1 (Trx1) expression in H. pylori can promote gastric carcinogenesis. To explore the underlying molecular mechanisms, we performed an isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomic analysis of stomach tissues from Mongolian gerbil infected with H. pylori expressing high and low Trx1. Differences in the profiles of the expressed proteins were analyzed by bioinformatics and verified using Western blot analysis. We found three candidate proteins, 14-3-3α/β, glutathione- S -transferase (GST), and heat shock protein 70 (HSP70), in high Trx1 tissues compared with low Trx1 tissues and concluded that cellular stress and redox activity-related proteins were involved in the pathogenesis of gastric cancer associated with H. pylori Trx1. 目的 2 探索高表达硫氧还蛋白-1(Trx1)的幽门螺杆菌在致胃黏膜癌变过程中的作用机制. 创新点 2 首次分析临床分离菌株感染蒙古沙土鼠的胃黏膜疾病动物模型,首次对不同菌株感染所致的胃黏膜癌变相关分子机制进行探索. 方法 2 用同位素标记相对和绝对定量(iTRAQ)蛋白质组学及生物信息学分析方法进行分析,并用免疫印迹法(Western blot)对重要分子进行验证. 结论 2 高表达Trx1的幽门螺杆菌在致胃黏膜癌变过程中,三个重要的细胞应激和氧化还原活性蛋白包括14-3-3α/β、谷胱甘肽转移酶(GST)和热休克蛋白(HSP70)参与致病. Thioredoxin-1 (Trx1) Helicobacter pylori Gastric carcinogenesis Proteomics Isobaric tags for relative and absolute quantitation (iTRAQ) 硫氧还蛋白-1(Trx1) 幽门螺杆菌 胃黏膜癌变 蛋白质组学 同位素标记相对和绝对定量(iTRAQ) Introduction 1 Gastric cancer is one of the most common cancers in the world. In China, incidence and mortality are high (Yang, 2006 2006 ). Helicobacter pylori is thought to promote the pathogenesis of gastritis, peptic ulcer, and gastric cancer (Wroblewski et al., 2010 2010 ). The discovery of H. pylori by Marshall and Warren ( 1984 1984 ) was followed by many studies which indicated that H. pylori infection is associated with gastric carcinogenesis (Parsonnet et al., 1991 1991 ; Blaser et al., 1995 1995 ; Suerbaum and Michetti, 2002 2002 ; Suriani et al., 2005 2005 ). The International Agency for Research on Cancer classified H. pylori as a group I carcinogen (WHO, 1994 1994 ). Long-term H. pylori colonization has also been shown to induce the development of gastric cancer in animals (Honda et al., 1998 1998 ; Watanabe et al., 1998 1998 ; Tsukamoto et al., 2013 2013 ). However, the pathogenic mechanisms of H. pylori are still not clear. Thioredoxin-1 (Trx1), encoded by HP0824 in H. pylori 26695, is one of several antioxidants in H. pylori (Baker et al., 2001 2001 ). As an arginase chaperone, it mediates resistance to nitrosative and oxidative stresses, and is responsible for H. pylori ’s ability to colonize and persist for decades in hostile gastric environments (Windle et al., 2000 2000 ; Comtois et al., 2003 2003 ; McGee et al., 2006 2006 ; Wang et al., 2006 2006 ; Kuhns et al., 2015 2015 ). In previous studies, we found that Trx1 expression in H. pylori isolated from clinical gastric cancer tissues was significantly higher than that from gastritis tissues (Zhang et al., 2006 2006 ), indicating that H. pylori Trx1 may be involved in the occurrence of gastric cancer. Further studies, both in vitro and in vivo, confirmed this finding (Shi et al., 2013 2013 ; Liu et al., 2016 2016 ). However, the mechanism by which H. pylori Trx1 has its carcinogenic effect is unknown. We have explored the biological processes and molecular pathways through which H. pylori Trx1 exerts its pathogenic effects using proteomic technologies and Western blotting verification in Mongolian gerbils infected by H. pylori expressing either high or low Trx1, as described by Liu et al. ( 2016 2016 ). Materials and methods 1 Tissues of Mongolian gerbil models 2 All institutional and national guidelines for the care and use of laboratory animals were followed. After sacrifice, animal gastric tissues were taken for H. pylori culture and histological analysis and were snap-frozen in liquid nitrogen for protein extraction. Haematoxylin and eosin were used for histological analysis. Whilst establishing the gerbil model, we found that gastritis, dysplasia, and gastric cancer appeared gradually in the groups infected by H. pylori expressing high and low Trx1. We used tissues of varying degrees of gastric pathology for proteomic analysis, as follows: one control tissue (D23: 90 weeks without H. pylori infection), two chronic gastritis tissues (D4 and D22: 70 weeks after inoculation with H. pylori expressing high or low level of Trx1), two dysplasia tissues (C15 and C13: 90 weeks after H. pylori inoculation), and two gastric cancer tissues (C17 and C23: 90 weeks after H. pylori inoculation). Detailed information about the gerbils is provided in Table 1 1 . We used seven more animals treated in the same way as above for Western blot analysis. Animal number Histopathologic diagnosis Infection period (week) H. pylori Trx1 level  D4 Gastritis 70 High  D22 Gastritis 70 Low  C15 Dysplasia 90 High  C13 Dysplasia 90 Low  C17 Gastric cancer 90 High  C23 Gastric cancer 90 Low  D23 Negative control 90 Protein extraction 2 Gastric tissues were dissolved as described (Hsu et al., 2016 2016 ) in lysis buffer (20 mmol/L Tris-HCl, 1 mmol/L ethylene diamine tetraacetic acid (EDTA), 1 mmol/L ethylene glycol tetraacetic acid (EGTA), 1% (v/v) Triton X-100, 50 mmol/L NaF, 20 mmol/L Na 4 P 2 O 7 , 1 mmol/L Na 3 VO 4 , and protease inhibitors) and extracted with Precellys® homogenizer (Bertin Technologies, Saint Quentin en Yvelines Cedex, France). After homogenization, the tissue extracts were centrifuged at 14 000 r/min for 20 min at 4 °C, and the supernatants were collected. A Bradford protein assay (Bio-Rad Laboratories, Inc., Hercules, CA, USA) was used to determine the protein concentrations; the protein samples were stored at −80 °C before use. In-solution protein digestion, isobaric tags for relative and absolute quantitation (iTRAQ) labeling, and strong cationic-exchange (SCX) chromatography fractionation 2 Every protein sample (100 μg) was digested with Trypsin Gold (Promega, Madison, WI, USA) at 37 °C for 16 h. The peptides were then dried by vacuum centrifugation and reconstituted in 0.5 mol tetraethyl ammonium bromide (TEAB; Applied Biosystems, Milan, Italy). Groups of tissue extracts were labeled with different iTRAQ labeling reagents (C13: 114; C15: 115; C17: 116; C23: 117; D4: 118; D22: 119; D23: 121). The labeled samples were incubated for 2 h at room temperature, and then mixed and dried by vacuum centrifugation (Long et al., 2016 2016 ). High performance liquid chromatography (HPLC) Pump System (LC-20AB, Shimadzu, Kyoto, Japan) and Ultremex SCX column containing 5-μm particles (4.6 mm×250 mm, Phenomenex, USA) were coupled to SCX chromatography. The peptide mixtures were eluted for 15 min at a flow rate of 1 ml/min with 4 ml buffer A (10 mmol/L KH 2 PO 4 in 25% (v/v) acetonitrile (ACN), pH 3.0), and with a gradient of 0% (v/v) buffer B (10 mmol/L KH 2 PO 4 and 2 mol/L KCl in 25% ACN, pH 3.0) for 30 min, 0–5% buffer B for 1 min, 5%–30% buffer B for 15 min, 30%–50% buffer B for 5 min, 50% buffer B for 5 min, 50%–100% buffer B for 5 min, and 100% buffer B for 10 min. The elution was monitored by absorbance at 214 nm, and fractions were collected every 1 min. Finally, the elution fractions were desalted with a Strata X C18 column (50 mm×2.1 mm, Phenomenex, USA), and the resultant fractions were vacuum-dried and re-suspended in buffer C (0.1% (v/v) formic acid) for further desalting. Liquid chromatography-electrospray ionization-tandem mass spectrometry analysis 2 To analyze the iTRAQ-labeled peptide mixtures (Long et al., 2016 2016 ), each fraction was reconstituted in buffer C, and then loaded onto nano-HPLC (LC-20AD, Shimadzu, Kyoto, Japan) by the autosampler onto a 2-cm C18 trap column, and separated on a resolving 10-cm analytical C18 column (inner diameter 75 μm). The samples were loaded at 8 μl/min for 5 min, and then the gradient was run at 400 nl/min starting from 5% (v/v) buffer D (ACN containing 0.1% (v/v) formic acid) for 10 min, 5%–30% buffer D for 30 min, 30%–60% buffer D for 5 min, 60%–80% buffer D for 3 min, 80% buffer D for 7 min, then returning to 5% buffer D in 3 min, and maintenance at 5% buffer D for 7 min. A mass spectrometer (Q-Exactive, Thermo Fisher Scientific, San Jose, CA, USA) was coupled online to the HPLC. Peptides were detected by mass spectrometry (MS) analysis with a resolution of 70 000 and a mass range of 350–2000 m / z . The 15 most abundant precursor ions above a threshold ion count of 20 000 were selected for tandem MS (MS/MS) analysis. An electrospray voltage of 1.8 kV was applied. MS/MS analysis was recorded with a resolution of 17 500 and the mass range was automatically dependent on the range of MS analysis. Peptides were fractured with normalized collision energy of 27% and detected on the Q-Exactive. Database search and protein quantification analysis 2 The MS/MS spectra were searched using the Mascot search engine (Version 2.3.02, Matrix Science, London, UK) against the SwissProt database containing rodentia protein sequences. The analysis allowed one missed cleavage from the trypsin digestion, and oxidation (M), Gln→Pyro-Glu (N-term Q), iTRAQ8plex (K), iTRAQ8plex (Y), and iTRAQ8plex (N-term) were set as the potential variable modifications, while carbamidomethyl (C) was set as fixed modifications. An automatic target-decoy search strategy was used in combination with percolator in order to score peptide spectral matches and so estimate the false discovery rate (FDR). Only peptides identified with strict spectral FDR of < 1% ( q -value < 0.01) were considered. The peptide precursor mass tolerance was 15×10 −6 mg/L, MS/MS tolerance 20 mmu (millimass unit). Each confident protein identification was supported by at least one unique peptide. The quantitative protein ratios were weighted and normalized by the median ratio, the normalization method being median. Mascot software (Applied Biosystem, USA) was used to calculate the confidence of each quantitative protein based on the amount of spectrum. Modulated protein expression was defined as ≥1.2-fold change in expression level. Ratios with P -value of < 0.05 were considered significantly different. GO annotation, KEGG pathway enrichment, and network analysis 2 Proteins that had changed significantly were analyzed using the search tool DAVID ( http://david.abcc.ncifcrf.gov http://david.abcc.ncifcrf.gov ) for gene ontology (GO) annotation and enrichment analysis, which includes three main modules: biological process, cellular component, and molecular function. The web-based Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.p/kegg http://www.genome.p/kegg ) was used for pathway analysis (Kanehisa et al., 2012 2012 ). STRING ( http://string.embl.de http://string.embl.de ) was used as a database of predicted signaling networks and protein interactions (Deng et al., 2015 2015 ). Western blot analysis 2 Protein samples were analyzed by Western blot to validate the differentially expressed proteins. For protein extraction, tissues were ground and then suspended in lysis buffer containing a protease inhibitor mixture and shaken on ice for 30 min (Shi et al., 2013 2013 ). The lysate was centrifuged at 15 000 g at 4 °C for 10 min, and the supernatant was collected. The total protein concentration was measured by the Bradford method using a bicinchoninic acid (BCA) protein assay kit (Pierce, Rockford, IL, USA). Proteins (60 μg) were separated on 12% (0.12 g/ml) sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels and electrophoretically transferred onto polyvinylidene fluoride (PVDF) membranes. The membranes were blocked in 5% (w/v) fat-free milk in Tris-buffered saline–0.5% (v/v) Tween-20 at room temperature for 1 h and incubated overnight at 4 °C with antibodies against heat shock protein 70 (HSP70, 1:500; Flarebio, China), glutathione- S -transferase (GST, 1:1000; Abcam, UK), 14-3-3α/β (1:500; BlueGene, China), and β-actin (1:2000; MBL, Japan). After three washes in phosphate-buffered saline (PBS) supplemented with 0.1% (v/v) Tween-20 for 15 min, the membranes were incubated with a secondary antibody, goat anti-rabbit IRDye 680 or goat anti-mouse IRDye 800CW (1:5000; LI-COR Biosciences, Lincoln, USA), for 1 h at room temperature. Proteins were identified by scanning the membranes using the Odyssey Imager System (LI-250A, LI-COR Biosciences, Lincoln, USA). Results 1 Protein identification and quantification 2 We used an iTRAQ-based quantitative proteomic approach, as described above, to understand how the proteome changes in animal stomach tissues during the development of gastric cancer, and 792 differentially expressed proteins were identified from paired gastritis tissues infected with H. pylori expressing high or low Trx1, 677 proteins from paired dysplasia tissues, and 1116 proteins from paired gastric cancer tissues (Tables S1 S1 , S2 S2 , S3 S3 ). A total of 1506 different proteins were identified from the three groups, in which 242 proteins were common to all three groups. Fig. 1a 1a is a Venn diagram showing the commonly and uniquely expressed proteins in the gastritis, dysplasia, and gastric cancer tissues. (a) Venn diagram showing the commonly and uniquely expressed 242 proteins in gastritis, dysplasia, and gastric cancer tissues infected by H. pylori expressing high or low thioredoxin-1 (Trx1). (b) Heatmap of the expression levels shown as log 2 ratio of 1506 dysregulated proteins. The red-colored clusters represent up-regulated proteins and the blue-colored clusters represent down-regulated proteins (Note: for interpretation of the references to color in this figure legend, the reader is referred to the web version of this article) Cluster analysis of the identified proteins 2 A heatmap was constructed from the data obtained for the differentially expressed proteins. Clustering analysis showed that the genes encoding these proteins are regulated (Fig. 1b 1b , Table S4 S4 ). 14-3-3α/β, HSP70, and GST were differentially expressed in all paired tissues (Table 2 2 ). These three proteins were also differentially expressed in the development of gastric cancer infected with H. pylori expressing high or low level of Trx1 (Table 3 3 ). Ratio of the specific value of expression intensity of the protein in gastric tissues infected with H. pylori expressing high or low Trx1 Disease 14-3-3α/β HSP70 GST A2 GST A3 GST κ1 Gastritis 4.31 1.41 0.55 1.43 0.83 Dysplasia 1.79 0.71 1.47 0.43 0.82 Gastric cancer 2.82 0.66 0.34 0.64 1.25 Ratio of the specific value of expression intensity of the protein in the development of gastric cancer infected with H. pylori expressing high or low Trx1. “/” represents no significant change Level of H. pylori Trx1 Disease 14-3-3α/β HSP70 GST A2 GST A3 GST κ1  High Negative control vs. gastritis 0.29 0.81 2.26 / 1.25  High Gastritis vs. dysplasia 2.76 1.57 0.53 1.51 /  High Dysplasia vs. gastric cancer 0.27 0.81 2.27 / /  Low Negative control vs. gastritis 3.18 / 1.21 1.33 /  Low Gastritis vs. dysplasia / 0.79 1.67 0.46 /  Low Dysplasia vs. gastric cancer 0.51 0.77 0.51 1.33 1.60 Functional classification and enrichment of H. pylori Trx1-regulated proteins 2 We classified the proteins identified in paired tissues infected with H. pylori expressing high or low Trx1, while results showed the same histopathological changes. Functional categories of the differentially expressed proteins are shown in Figs. 2 2 , 3 3 , 4 4 . For paired gastritis tissues D4 and D22, the top ten enriched GO terms within each major functional category are shown in Fig. 2 2 . Figs. 2a–2c 2a–2c show the functional categories of proteins contributing the highest proportions. The top four most enriched GO terms under “biological process” included “protein localization”, “homeostatic process”, “cytoskeleton organization”, and “intracellular transport” (Fig. 2a 2a ). The top ten categories of the differentially expressed proteins under “cellular component” are shown in Fig. 2b 2b . “Intracellular non-membrane-bounded organelle” and “non-membrane-bounded organelle” had the most proteins, followed by “mitochondrion” and “cytoskeleton”. In the molecular function category, “nucleotide binding”, “purine nucleotide binding”, and “cytoskeleton protein binding” were the most prominent categories (Fig. 2c 2c ). Fig. 2d 2d shows the top ten functional categories of protein according to P- values of enriched GO terms. (a) Top ten enriched GO terms under “biological process”. (b) Top ten enriched GO terms under “cellular component”. (c) Top ten enriched GO terms under “molecular function”. (d) Top ten functional categories of proteins according to P -values of enriched GO terms (a) Top ten enriched GO terms under “biological process”. (b) Top ten enriched GO terms under “cellular component”. (c) Top ten enriched GO terms under “molecular function”. (d) Top ten functional categories of proteins according to P -values of enriched GO terms (a) Top ten enriched GO terms under “biological process”. (b) Top ten enriched GO terms under “cellular component”. (c) Top ten enriched GO terms under “molecular function”. (d) Top ten functional categories of proteins according to P -values of enriched GO terms For paired dysplasia tissues C15 and C13, the top four most enriched GO terms under “biological process” were “oxidation reduction”, “cytoskeleton organization”, “translation”, and “macromolecular complex assembly” (Fig. 3a 3a ). The top ten categories of the differentially expressed proteins under “cellular component” are shown in Fig. 3b 3b . For gastritis tissues, “intracellular non-membrane-bounded organelle” and “non-membrane-bounded organelle” had the most proteins, followed by “mitochondrion” and “cytoskeleton”. In the molecular function category, “nucleotide binding”, “calcium ion binding”, and “structural molecule activity” were the most prominent categories (Fig. 3c 3c ). Fig. 3d 3d shows the top ten functional categories of protein according to P -values of enriched GO terms. For paired gastric cancer tissues C17 and C23, the top four most enriched GO terms under “biological process” included “oxidation reduction”, “translation”, “generation of precursor metabolites and energy”, and “cytoskeleton organization” (Fig. 4a 4a ). The top ten categories of the differentially expressed proteins under “cellular component” are shown in Fig. 4b 4b . As with gastritis tissues, “mitochondrion” and “organelle membrane” had the most proteins followed by “mitochondrial part”. In the molecular function category, “nucleotide binding”, “structural molecule activity” and “cytoskeletal protein binding” were the most prominent categories (Fig. 4c 4c ). “Nucleotide binding” included 35% of identified proteins, which made it the most enriched GO term under the three major functional categories. Fig. 4d 4d shows the top ten functional categories of protein according to P -values of enriched GO terms. KEGG analysis of H. pylori Trx1-regulated proteins 2 The differentially expressed proteins were mapped to the KEGG database in order to identify the biological pathway operating during gastric carcinogenesis (Fig. 5 5 ). Among the 792 proteins identified in gastritis tissues D4 and D22, 410 proteins had KEGG orthology (KO) ID and were involved in 165 pathways. The top ten enriched pathways with P -values less than 0.05 are shown in Fig. 5a 5a , and the top two were “focal adhesion” and “ECM-receptor interaction”. Among the 677 proteins identified in dysplasia tissues C15 and C13, 350 proteins had KO ID and were involved in 170 pathways. The top ten enriched pathways with P -values less than 0.05 are shown in Fig. 5b 5b , and the top two were “vascular smooth muscle contraction” and “systemic lupus erythematosus”. Among the 1116 proteins identified in gastric cancer tissues C17 and C23, 624 proteins had KO ID and were involved in 188 pathways. The top ten enriched pathways with P -values less than 0.05 are shown in Fig. 5c 5c , and the top two were “oxidative phosphorylation” and “Parkinson’s disease”. Verification of three candidates 2 To support the results of proteomic analysis, we performed Western blot analysis to monitor changes in the three proteins implicated in gastric carcinogenesis, HSP70, GST, and 14-3-3α/β (Figs. 6a and 6b 6a and 6b ). The changes in HSP70 expression were found to be consistent with the proteome data. For GST, the changes in expression were found to be approximately consistent with the proteome data for gastritis and gastric cancer tissues. For 14-3-3α/β, the expression changes were consistent for all three kinds of tissue, while the fold change ratios in the high Trx1 group compared with low Trx1 group were less than one, indicating that these were not consistent with the proteome data (Fig. 6c 6c ). Gastric tissues infected by H. pylori expressing low (a) and high (b) levels of Trx1 (1, negative control; 2, normal; 3, gastritis; 4, dysplasia; 5, gastric cancer). (c) Compared with H. pylori expressing low Trx1, fold change ratios of HSP70, GST, and 14-3-3α/β proteins in gastric tissues infected by H. pylori expressing high levels of Trx1 using iTRAQ or Western blot Discussion 1 H. pylori is one of the pathogens involved in gastric carcinogenesis, which is a multifactorial and multistage process (Zheng et al., 2004 2004 ). Half of the world’s population is infected with H. pylori , but only a subpopulation develops severe digestive diseases (Suerbaum and Michetti, 2002 2002 ; Abadi and Kusters, 2016 2016 ). Studies of bacterial virulence factors will provide mechanistic evidence on gastric carcinogenesis and identify populations with a high risk of H. pylori infection. Many biomarkers have been considered to be critical to H. pylori virulence, such as cytotoxin-associated gene A ( cag A) and vacuolating cytotoxin A ( vac A) (Montecucco and Rappuoli, 2001 2001 ; González et al., 2011 2011 ). However, recently, it has been reported that other virulence factors may contribute significantly to the characteristics of H. pylori infection (Zhang et al., 2001 2001 ; Fock et al., 2008 2008 ): for example, the role of cag A has been reported to be mediated by other factors (Wang et al., 2016 2016 ). These other virulence factors require further research. Previous in vitro and in vivo studies found H. pylori Trx1 to be a potential virulence factor associated with gastric carcinogenesis with H. pylori expressing high levels of Trx1, which causes more serious tubular adenocarcinoma in a higher percentage of Mongolia gerbils compared with H. pylori expressing low Trx1 levels (Zhang et al., 2006 2006 ; Shi et al., 2013 2013 ; Liu et al., 2016 2016 ). However, the mechanisms by which Trx1 promotes carcinogenesis are not clear. In previous studies, we used H. pylori clinical isolates to infect gastric epithelial cells in vitro to determine that high Trx1 expression in H. pylori is associated with gastric carcinogenesis. The effects on cell lines were confirmed using the H. pylori Trx1-knockout mutant strain (Shi et al., 2013 2013 ). For animal models, in our present study, we used clinical isolates to simulate real situations in clinical populations. Limited by the numbers of Mongolian gerbils, we did not use the H. pylori Trx1-knockout mutant strain, which was a limitation of this study (Liu et al., 2016 2016 ). We used an iTRAQ-based proteomic analysis to quantitatively profile the proteins of animal models infected by H. pylori and so revealed the central metabolic proteins in gastric carcinogenesis tissues, as well as gastritis, dysplasia, and gastric cancer tissues. The iTRAQ coupled with two dimensions (2D)-liquid chromatography (LC)-MS/MS analysis identified 1506 differentially expressed proteins. Expression of HSP70, GST, and 14-3-3α/β changed frequently in the developing stages of gastric carcinogenesis. Combined with the literature search, we focused on the three proteins thought to be associated with oxidative stress, cancer, and H. pylori infection. GSTs are a family of detoxification enzymes which protect against the harmful effects of toxicants and carcinogens (Hayes et al., 2005 2005 ). GSTs regulate the mitogen-activated protein (MAP) kinase pathway participating in cellular survival and death signals via interactions with c-Jun N-terminal kinase 1 (JNK1) and apoptosis signal-regulating kinase 1 (ASK1), which are activated in response to cellular stress. Cell apoptosis is inhibited and GST is therefore considered to be associated with tumorigenesis (Townsend and Tew, 2003 2003 ). After H. pylori infection, GST can remove reactive oxygen species by the oxidation of the GST enzyme protein. Some studies have shown that GST expression is significantly up-regulated in H. pylori -infected gastric mucosa (Baek et al., 2004 2004 ). However, other studies reported that GST activity was significantly lower in H. pylori -positive gastric tissues than in H. pylori -negative tissues (Kim et al., 2005 2005 ), implying that H. pylori -infection could antagonize the expression of GST, weakening its toxicant protection role and making it easier to damage the gastric mucosa barrier. Therefore, reduced GST activity may increase the risk of gastric cancers. Compared with tissues infected with low Trx1 H. pylori , GST was down-regulated in tissues infected with high Trx1 H. pylori , especially in gastric cancer tissues. Research has shown that GST polymorphism and methylation may also be associated with H. pylori -infection or gastric carcinogenesis (García-González et al., 2012 2012 ). HSP70 which is abundant in all cellular compartments has a diverse array of cellular functions (Bellini et al., 2017 2017 ; Cesa et al., 2017 2017 ), including the refolding of misfolded or aggregated proteins (Cybulsky et al., 2016 2016 ) and the facilitation of nuclear proteome stability upon thermal stress (Niforou et al., 2014 2014 ). HSP70 expression can be induced by stresses such as oxidative stress and anticancer drugs and is at a very low level under normal conditions (Niforou et al., 2014 2014 ). It plays important roles in cancer development, through anti-apoptotic effects and by inhibiting oncogene-induced senescence (Wu et al., 2017 2017 ), and is often over-expressed in cancer cells. H. pylori -infection has been reported to inhibit the expression of HSP70 in gastric mucosa. Teprenone can restore HSP70 expression and inhibit inducible nitric oxide synthase (iNOS), implying that teprenone therapy can protect gastric mucosa cells from H. pylori infection (Yeo et al., 2004 2004 ; Targosz et al., 2012 2012 ). Other reports, however, show the opposite that HSP70 expression is progressively increased in gastric carcinogenesis (Carrasco et al., 2011 2011 ). In our study, the fold change ratio of HSP70 expression in gastric mucosa infected by high and low Trx1 H. pylori infection was greater than one in gastritis, and was less than one in dysplasia and gastric cancer. Compared with low Trx1 H. pylori , HSP70 expression in gastritis tissues was up-regulated after infection with high Trx1 H. pylori and was down-regulated in dysplasia and gastric cancer tissues. This indicates that with high Trx1 H. pylori infection, the lower HSP70 in dysplasia and gastric cancer tissues makes it easier for H. pylori to damage gastric mucosa. The 14-3-3 proteins are a family of conserved regulatory molecules, which are phospho-serine/threonine binding proteins that have important roles in the regulation of metabolism and signal transduction networks (Uhart and Bustos, 2014 2014 ). 14-3-3 protein could bind Bcl-2-associated death promoter (BAD) and ASK1, which are known to induce apoptosis. Therefore 14-3-3 proteins may suppress apoptotic signaling. The expression of 14-3-3α/β isoform can be induced by oxidative stress by H. pylori infection associated with nuclear factor κB (NF-κB) activation in gastric epithelial cells (Lim et al., 2004 2004 ; Zhou et al., 2017 2017 ). In this study, we found that 14-3-3α/β is up-regulated by high Trx1 H. pylori infection in gastritis tissues. Previously, we suggested that expression of Trx1 as one of the antioxidant enzymes in H. pylori was related to reactive oxygen species (Shi et al., 2014 2014 ). 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This article does not contain any studies with human or animal subjects performed by any one of the authors. 10.1631/jzus.B1700456 Project supported by the Key Laboratory for Helicobacter pylori Infection and Upper Gastrointestinal Diseases, Beijing Key Laboratory (No. BZ0371) and the National Natural Science Foundation of China (Nos. 81700496, 81270475, and 30770980) 2017-09-08 2018-02-07 2022-01-05 Copyright © Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2018 2018 Journal of Zhejiang University-SCIENCE B (Biomedicine and Biotechnology) 10 19