| According to the3rd statistical survey of2004-2005, malignant tumor mortality rate in9sampling region of guangxi is up to112.02/10myriad. Malignant tumors have already become the1st cause of death in guangxi. Malignant tumor mortality rate of guangxi has risen by38.29/10myriad from1990s to the nearly three years and HCC has become the1st cancer killer. Early primary hepatocellular carcinoma(HCC) usually does not have any symptoms in the early phase. Once appearing clinical manifestations, most of cases have entered the terminal phase with fast and aggressive cancer progress. The early diagnosion of HCC mainly relies on serum detection of AFP combining with imaging examination. But the39%-64%sensitivity,76%-91%specificity and9%-32%positive predictive value of AFP testing is unsatisfactory for its omission, false positives and false negatives in HCC detection. Thus screening effective biomarker for early warning and diagnosis has become the urgent task for the HCC medical research in guangxi.iTRAQ (isobaric tags for relative and absolute quantitation) is the advanced technology for screening disease biomarkers with proteomics strategy, through which our team analyzed and identified biomarker for HBV related HCC in30cases of HCC, HBV related liver cirrhosis, chronic hepatitis and normal serum respectively. The results suggested there were98diffentially expressed proteins(DEPs) between HCC and normal group, including52DEPs(36up-regulated and16down-regulated) in AFP>400ng/ml group,34DEPs(20up-regulated and14down-regulated) in400ng/ml>AFP>25ng/ml group, and32DEPs(21up-regulated and11down-regulated) in AFP<25ng/ml group. Notably, GSN decreased in all the above group which caught our eyes with the question of Whether GSN could be the significant biomarker for HCC?The discovery of biomarker should go through three important steps as the discription of discovery, verification, and validation, then could walk into the deeper phase for clinical validation and molecular epidemiology application, which means the persistent investment of time, samples, and funds. Recently, most of the studies were terminated at validation phase, rare of which could be applied in the practical clinic. The complexity and heterogeneity of most solid tumors present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. So discerning critical molecular of HCC and determining its biological effects have become the considerable challenge for establishing biomarkers in the field of HCC molecular epidemiology.For GSN was considered as the potential HCC biomarker in our early study, we utilized this assay to answer the questions of Whether GSN could be the significant biomarker for HCC and what’s the role of GSN playing in HCC. We performed the study with two strategy:(1) transcriptomics strategy, through establishing GSN overexpressed/inhibited SMMC7721cells, we used RNA-seq to analyze the regulation of HCC transcription, and the expression and function of the differentially expressed genes, to explore the important clues of GSN impacted HCC biological effects,and to study the potential mechanism.(2) clinical analytic strategy, through the relationship between the change of GSN expression and the clinical pathology, we gained the clues of GSN impacted HCC biological effects, and then performed the functional validation so as to illuminate the possible mechanism.Part1Establishment of GSN overexpressed/inhibited SMMC7721cellsObjective:To establish GSN overexpressed/inhibited SMMC7721cells as the cell model for functional study and to validate the expressed level of GSN in the transfectants.Method:1. Establishing GSN overexpressed SMMC7721cells by the use of the Lentiviral vector:Firstly,mixing the PCDH-CMV-MCS-EFl-Puro GSN/PCDH-CMV-MCS-EFl-Puro, psPAX2, pMD2.G plasmids with the proportion of4:3:1. Then dropping the mixture with transfected reagent into the293T cells and collecting the virus after48h’s incubation. Finally, infecting SMMC7721and screening transfectants by the lug/ml puromycin.2. Establishing GSN inhibited SMMC7721cells by the use of the shRNA vector:Dropping the pGFP-V-RS GSN shRNA/pGFP-V-RS shRNA with transfected reagent into the SMMC7721, and observing the GFP signal after 24’s incubation. Adding lug/ml puromycin for transfectant screening while the GFP signals were stable.3. Validation the GSN expression in the transfected SMMC7721cells by the use of RT-PCR and In-cell WB.4. Validation the stability of GSN overexpressed/inhibited transfected cells in the5th,10th and20th generation by the use of In-cell WB.Result:1. The results of RT-PCR showed that the mRNA level of GSN increased6.982±1.614(P=0.000) times in the overexpressed SMMC7721and decreased to0.364±0.025(P=0.001) in the inhibited SMMC7721while comparing with the respecrtive control. In-cell WB showed that the expression of GSN increased2.022±0.179(P=0.000) times in the overexpressed SMMC7721and decreased to0.233±0.052(P=0.000) in the inhibited SMMC7721while comparing with the respecrtive control.2. The results of stable cell line detection showed that the expression GSN stable in the5th,10th and20th generation.Conclusion:The stable GSN overexpressed/inhibited transfected cells were successfully established as the functional research model for exploring the effects of GSN in HCC. Part2Transcriptomics study in GSN overexpressed hepatoma cellsObjective:To illuminate the GSN regulated transcription of hepatoma cells by analyzing DEGs, GO, COG and KEGG pathway, to explore the function of GSN in HCC, and to discuss the possible mechanism.Method:1. Isolating and purifying cell mRNA, performing RNA-seq and DEGs analysis in the GSN-SMMC7721and the parent SMMC7721.Collecting the raw data from Ion proton system, matching them with the genomic sequence, and searching the information of gene annotation.2. Establishing Junction database, calculating and adjusting the number of sequence in every genetic interval base on the refGene.txt file in the UCSC Utilizing FPKM (fragments per kilobase of exon per million fragments mapped) value to replace the totality of gene sequence, uploading data to the GEO (Gene Expression Omnibus) and calculating the gene expression abundance.3. Comparing the function of genes expressed in the GSN-SMMC7721and the parent SMMC7721, according to the statistics of GO (Gene Ontology) Screening differentially expressed gene (DEGs) through Audic and Claverie test, Fisher exact test, chi-suqared test by the use of IDEG6software. For the genes with the characters of RPKM＞2and fold change＞50, analyzing the function cluster using WEGO on line tools. Searching the biological pathway of enriched genes through KEGG (Kyoto Encyclopedia of Genes and Genomes) servicer.4. Screening the GSN impacted transcriptional regulation in HCC according to the enrichment analysis of function cluster and KEGG pathway, exploring the possible mechanism.Result:1. Ion proton gained the7.5G raw data, including78,119,422fragments with the average length of about100bp.2. Statistics through FPKM gained the gene expression abundance information, which included53853known genes and580un known genes.3.RNA-seq gained495DEGs(277up-regulated and218down-regulated) while comparing the transcription of GSN-SMMC7721and the parent SMMC7721.Cluster analysis showed the significant differences while GSN was up-regulated in the hepatoma cells.4.GO analysis showed the significant DEGs expression in the GO terms for "apoptotic process" were mainly inhibited, the same status could also be found in the "DNA damage response, signal transduction by p53class mediator resulting in induction of apoptosis","JNK cascade","cellular response to interleukin-3", and "cysteine-type endopeptidase activator activity involved in apoptotic process", which indicated that GSN might affect apoptosis of cancer cells.Those above GO terms included13apoptosis-related genes(12up-regulated and1down-regulated),those inhibited DEGS such as PSME2,PTK2B, RRM2B, FOS, JUN, ITGB1, MAP2K7, MAP3K4, MAP3K12and Racl participated in the apoptosis-related pathway such as antigen processing and presentation, natural killer cell mediated cytotoxicity, p53signaling pathway, pathways in cancer, Jak-STAT signaling pathway and MAPK signaling pathway.5.In all of the6KEGG pathways, excepting antigen processing and presentation pathway,the the rests including natural killer cell mediated cytotoxicity, p53signaling pathway, pathways in cancer, Jak-STAT signaling pathway,and MAPK-JNK pathway owned the cross links with each other.The terminal function factors of above pathways were Bcl-2、cytochrome C and caspase3.Conclusion:1. RNA-seq technology is a powerful tool with the advantage of large flux and high resolution for gene expression regulation.2. GSN might be the HCC apoptosis inhibitor and affected apoptosis through natural killer cell mediated cytotoxicity, p53signaling pathway, pathways in cancer, Jak-STAT signaling pathway,and MAPK-JNK pathway.3. Caspase3、cytochrome C and bcl-2might play improtant roles in the inhibition of HCC apoptosis.4. Transcriptome analysis provided valuable clues for the further study of GSN function. Part3Inhibition of Overexpressed GSN in HCC apoptosisObjective:To discuss the relationship between GSN and HCC apoptosis by the use of apoptosis related technologies.Method:1. Detecting cell total,early and late apoptosis rates in GSN-SMMC7721, NC1-SMMC7721, GSN shRNA-SMMC7721and NC2-SMMC7721cell lines through flow cytometry.2. Detecting the expression of caspase3, bcl-2and cytochrome C in GSN-SMMC7721, NC1-SMMC7721, GSN shRNA-SMMC7721and NC2-SMMC7721cell lines through In-cell WB.3. Observing the apoptosis morphology in the GSN-SMMC7721, NC1-SMMC7721, GSN shRNA-SMMC7721and NC2-SMMC7721cell lines through transmission electron microscope.Result:1.The results of flow cytometry showed the early,late and total apoptosis rates were0.72±0.11,3.48±0.25,4.20±0.18respectively in GSN overexpressed SMMC7721cell lines. The early,late and total apoptosis rates were9.97±1.01,5.44±0.98,15.41±1.26respectively in GSN shRNA-SMMC7721cell lines.The late and total apoptosis rates in GSN overexpressed SMMC7721cells were lower than those of the NC1-SMMC7721(P≤0.05). The early and total apoptosis rates in GSN shRNA-SMMC7721cells were higher than those of the NC2-SMMC7721(P≤0.05).2. The results of In-cell WB showed the expression of caspase3was down-regulated0.625±0.133(P=0.023),and the expression of Bcl-2was up-regulated4.138±0.857(P=0.004) in GSN-SMMC7721while comparing to NC1-SMMC7721. The expression of caspase3was up-regulated1.908±0.257(P=0.041),and the expression of Bcl-2was down-regulated0.411±0.122(P=0.018) in GSN shRNA-SMMC7721while comparing to NC2-SMMC7721.But the expression of cytochrome C was invariable while GSN was overexpressed/inhibited.3. The results of transmission electron microscope showed the apoptosis cells with the typical apoptosis characteristics.In GSN shRNA-SMMC7721cell line,the observed apoptosis morphology could be described as "apoptotic body","autophagy","early apoptosis","late apoptosis", and "oncosis".Conclusion:1. Flow cytometry technique and electron microscope confirmed GSN inhibited apoptosis of hepatoma cells.2. In-cell western identified that the molecular mechanism for GSN inhibited apoptosis through up-regulated bcl-2and down-regulated caspase3.Bcl-2and caspase3are the key for the process of GSN regulated apoptosis. Part4Promotion of Up-regulated GSN in the HCC migration and invasionObjective:GSN plays important roles in the migration and invasion of kinds of malignancy, But the regulation between GSN and HCC migration was rare published.This section discussed the aspect.Method:1. Analyzing the expression of GSN in69HCC and adjacent tissues, evaluating the clinical significance of GSN in HCC2.Discussing the relationship between GSN and HCC migration and metastasis by the use of wound healing,MMPs detection, migration and metastasis analysis in the GSN-SMMC7721、NC1-SMMC7721、GSN shRNA-SMMC7721and NC2-SMMC772.3. Seeking GSN interacted metastasis factors through two tag TAP-IP technology. Extracting cell lysis protein which contains FLAG/HA-GSN, joining into the Flag and HA column successively, and eluting products with3x Flag/HA peptide, after ultrafiltration, degeneration, reduction,and alkylation, eluting products were analyzed by MALDI-TOF-MS/MS mass spectrometer.The parameters of mass spectrometer were as follows:the optimization of molecular mass range was800～4000,the reflection and MS/MS laser shots were1250and2500times respectively.Confirming Mass spectrometry data with ProteinPilot2.0(P＜0.05, confidence＞95%).4.Pull down technology was used to validate the GSN interacted metastasis factor MMP14.We firstly used bioinformatics to predict the interacted region,which indicated catalytic domain (Tyr89-Gly261) and hemopexin-like domain (Pro293-Cys485) with the most possible binding sites.Repairing the His bind packing column, extracting cell lysis protein and joining into the column then eluting the binding products. After ultrafiltration, degeneration, reduction, and alkylation, eluting products were analyzed by MALDI-TOF MS/MS mass spectrometer. The parameters of mass spectrometer were the same as above3.5.RT-PCR and In-cell WB were used to analyzed and explored the GSN interacted metastasis factor and the possible mechanism for GSN promoted HCC metastasis.Results:1. Analyzing the clinical significance of GSN through69cases of HCC and the paired adjacent samples.The results showed that the100%(69/69) positive rate of GSN in the adjacent samples was higher than that of the HCC(72.5%(50/69),P≤0.05).The expression of GSN increased in the portal vein and extrahepatic invasion cases with the positive rate of80%(8/10) and88.9%(16/18) respectively which were significantly higher than the negative portal vein and extrahepatic invasion cases with the positive rate of50.8%(30/59) and43.1%(22/51)(P≤0.05).But the expression of GSN was invariable in the disparate age,gender,tumor size,tumer number,etc,cases.2. Wound healing assay indicated the86.0±6.0healing rate(%)of GSN-SMMC7721was higher than that of the NC1-SMMC7721(51.7±3.0)(P=0.011).Transwell migration and invasion experiment found that the migrated cells of GSN-SMMC7721were up to278, which was more than the GSN shRNA-SMMC7721(72), NC1-SMMC7721(143) and NC2-SMMC7721(138)(P=0.000). MMPs activity detection showed that the activity of MMP2was35.7±1.3in the GSN-SMMC7721,which was higher than that of the NC1-SMMC7721(13.8±1.7)(P=0.023)3. TAP-IP identified13GSN interacted protein, including MMTM and MMP14as well-knowed metastasis related factors.4.Pull down showed GSN interacted with MMP14hemopexin-like domain (Pro293-Cys485).5. RT-PCR, In-cell WB and cell immune chemistry experiment identified the upregulated MMP14and MMP2in the GSN-SMMC7721.The mRNA levels of MMP2and MMP14in GSN-SMMC7721were up-regulated5.257±0.618and3.485±0.533times while comparing with NC1-SMMC7721(P≤0.05). The protein levels of MMP2and MMP14in GSN-SMMC7721were up-regulated3.625±0.422and2.933±0.312times while comparing with NC1-SMMC7721(P≤0.05)Conclusion:1. GSN increased in the transferred HCC cases.2. The metastasis ability of GSN-SMMC7721was up-regulated, the activity of MMP2was also increased.3. The mechanism for GSN promoted HCC metastasis was through the interaction with MMP14and the following activity of MMP2. |
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