早期肝癌诊断标志物的筛选与初步鉴定
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摘要
我国属肝癌高发国家,肝癌病死率占恶性肿瘤病死率第二位,占全球肝癌死亡人数的53%。尽管肝癌的治疗学近些年有了很大的进步,但在过去的三十多年,肝癌生存率并无明显改善。临床实践证明,肝癌的成功切除与预后,取决于早期诊断。在高危人群中,早期筛查和发现肝癌,可赢得手术治疗的时间,提高术后生存率。腹部超声、CT、MRI的检查,虽能发现部分小肝脏肿瘤,但其鉴别良、恶性病变较难,因此肿瘤标志物的研究开发和临床应用对肿瘤的诊断治疗预后具有十分重要的意义。
目前,AFP为肝癌较可靠的血清标志物,其灵敏度为60%～70%,特异性为90%左右,但近40%的肝癌AFP不升高,其原因可能是AFP含量与肿瘤体积大小有关。有文献报道,早期肝癌AFP的假阴性率可达40%以上,进展期肝癌AFP的假阴性率也可达15%～20%,因此,单凭AFP诊断肝癌易造成漏诊与误诊。寻找更加敏感、特异的早期诊断标记物显得十分迫切。
有学者认为,将一些敏感性和特异性较差的标志物联合检测,结合生物信息技术,可明显改善诊断的敏感性和特异性。人类基因组计划的完成及相关检测技术的进步,给大规模筛查并发现肿瘤和其他疾病的生物标记带来期望。作为标志物,肿瘤分泌蛋白无疑最具研究价值。
基于此,我们在前期研究中建立了大鼠早期肝癌模型,应用Affymetrix公司的Rat Genome 230.2.0基因芯片检测早期肝癌组织(T)和正常肝组织(N)中mRNA,构建差异表达谱,得到T与N Log R≥2和Log R≤-2差异表达基因共677个,其中表达上调409个,表达下调268个。经后续分析,上调和下调共涉及178种分子功能和204种生物学过程,并根据Gene ontology(GO)分类和应用EMBOSS程序TMAP和SIGLEAVE分别预测氨基酸序列的跨膜结构域和信号肽剪切位点以及Excel交集补集分析,按照其参与的生物学过程和具有分子功能进行聚类并筛选出可能的诊断标志物14个。经同源分析14个候选诊断标志物均与人具有同源性,随后采用RT-PCR及免疫组化对其在大鼠试验组与对照组及人正常肝脏组织、癌旁组织、小肝癌及大肝癌中mRNA水平和蛋白水平的表达进行鉴定,初步预测其在小肝癌诊断中的价值。
研究方法:
1.应用二乙基亚硝胺(diethylnitrosamine DEN)构建大鼠肝癌模型,并经常规病理学检测;
2.提取对照组大鼠正常肝脏组织与实验组早期肝癌组织总mRNA,逆转录cDNA,应用Rneasy Mini kit合成cRNA。cRNA与Affymetrix Rat Genenome 230.2.0基因芯片杂交,扫描芯片,筛选差异表达基因,并行数据归一化与和目标性去冗余处理;
3.应用GO注释结合序列分析筛选上调基因中编码分泌蛋白的基因后行Blast比对、HPRD数据库与文献查询,选择人同源基因作为候选诊断标志物;
4.应用RT-PCR、定量PCR及免疫组化对部分候选标志物在大鼠早期肝癌和人小肝癌中转录和蛋白表达水平进行验证。
结果
1.在DEN灌胃14-16周时,成功构建大鼠早期肝癌模型;
2.Affymetrix Rat Genenome 230.2.0基因芯片杂交后,扫描芯片原始数据经规一化处理筛选出差异表达基因677个,其中上调表达基因409个,下调表达基因268个,其中全长已知基因368个;
3.对上调基因中已知211个基因应用GO注释结合序列分析的二次筛选得到22个编码分泌蛋白的基因,再次经“PubMed”“Homogene”与“HPRD”检索,将同时具备人同源性、表达位点(Expression sits)中包括血清或血浆、文献显示与肿瘤发生有相关性的14个人同源的编码分泌蛋白基因作为候选标志物;
4.14个候选标志物经文献检索,其中AFP(alpha-fetoprotein),TGFBP1(transforming growth factor,beta1),GGT1(gamma-glutamyltransferase 1)已作为肝癌的诊断标志物在临床上应用,另4个:LOX(Lysyl oxidase),IGFBP3(insulin-like growth factor binding protein3),ENTPD 5(ectonudeoside triphosphate dipho sphohu drolase 5),PLAT(plasminogen activator,tissue)已有与肝癌相关的报道,本研究予以剔出。剩余的7个应用RT-PCR和免疫组化在大鼠正常组织和早期肝癌中行初步验证显示其中4个:CTGF(connective tissuegrowth factor),GDF15(growth differentiated factor 15),TXNRD 1(Thioredoxin reductase 1),SPP1(secreted phosphoperotein 1)在大鼠早期肝癌组织中高表达;
5.进一步在人正常肝脏组织、癌旁组织、小肝癌与大肝癌组织中对前述4个基因半定量RT-PCR显示小肝癌、大肝癌组织中mRNA表达明显上调;免疫组化显示,小肝癌和大肝癌组织中CTGF,GDF15,TXNRD1,SPP1的阳性表达面积比、积分灰度值与面积灰度整合值均明显高于正常肝组织与癌旁肝硬化组织。表达阳性部位均主要在胞浆和胞外基质。
结论:
1.商业化基因芯片结合合理的生物信息学数据处理是筛选肿瘤疾病基因差异表达的高效方法;
2.以动物模型为线索,利用基因芯片技术结合GO注释与针对性的序列分析是筛选分泌性蛋白作为人疾病早期诊断标志物的有效策略;
3.CTGF,GDF15,TXNRD1,SPP1初步鉴定显示其对人小肝癌筛选有潜在应用价值。
Hepatocellular carcinoma (HCC) has one of the worst prognoses among malignancies as the majority of this type of cancer at the early-stage is asymptomatic, and over three-quarter of the diagnoses are made at a time when the disease has already established regional or distant metastases. The 5-year survival is favorable for cases with an early diagnosis (80% approx), while survival with distant metastases over the same time period is less than 5%. The only validated serology tumor-marker in current use for diagnosis of HCC is AFP, which can be detected in the serum of more than 56.1% of cases with HCC. However, AFP is thought to be robust only in following the progression of the disease, but is not sensitive enough as an early stage diagnostic marker. Thus, there is an important need for additional diagnostic markers for this disease. Microarray technology allows researchers to simultaneously monitor the expression of thousands of genes, which provides molecular biomarkers to differentiate normal cells from malignant ones. For its capability to illustrate the cellular behavior on the genomic level, microarray technology has been applied in cancer research as one of the major topics in this field. Furthermore, effective application of this technique relies on well-organized data; because most existing microarray databases in cancer research are raw data sets and are hard-coded as columns in a table. It is difficult to draw directly supportive information for clinical cancer research from these. Gene expression profiling in the animal model holds great promise for our understanding of human pathogenesis. Here, we have generated and analyzed gene expression from Rat's liver cancer that was induced by DEN.
We used oligonucleotide microarrays that including over 30,000 well-substantiated rat genes to monitor the levels of expression within normal and early stage malignant liver tissues. Furthermore, we extended this analysis to investigate secreted protein by web resource that allows users to easily perform common queries on the data and to discover candidate diagnostic markers of early-stage HCC that can be detected in the blood. The overexpression of several genes that encode secreted protein were confirmed at transcript and protein expression level in the microtumors of rat models, as well as in the early-stage HCC patients. Our results show several of the genes as up-regulated in cancer and diagnostically useful. Other genes presented here, some of which we have validated, may find similar utility and suggest that many of these molecules may be relevant to tumorigenesis and may combination to form a simultaneous determination of early-stage HCC.
Methods
1. HCC model of rats were developed by feeding DEN (diethylnitrosamine) and early-stage HCC tissues were gathered at 14th -16th week.
2. Affymetrix Rat Genenome 230.2.0 GeneChip was used to detect the gene expression profile. Web-based bio-information and sequence analysis were used to screen target genes which significantly elevated expressed in tumor tissues and encode secreted proteins.
3. Transcription and protein expression levels of four target markers in both of animal model and human different stage HCC have subsequently been confirmed by RT-PCR and Immunohistochemistry. RT-PCR, Real-time quantitative PCR and immunohistochemistry were performed to identify the expression of candidate molecul in human HCC tissues.
Results
1. DEN successfully induced rat early-stage liver cancer
2. When compared with normal liver tissues, 677 genes(EST/Full length) in early-stage HCC were found to have different expression levels of more than two folds. Among those, 409 genes were up-regulated (log ratio>2), and 268 genes were down-regulated (log Ratio<-2).
3. According to the GO consortium annotations and the EMBOSS programs TMAP and SIGCLEAVE overlapping analysis, 22 genes were predicted to encode the secreted proteins in 211 highly expression known genes. After defining the query and gaining access to web-based resource , 14 retrieved genes were found to have the common features of H.sapiens orthologous gene, correlation with oncogenesis and expression sites including blood, serum, plasma. Of the 14 genes, Several have been applied to clinical diagnosis or reported to have relevant with tumorigenesis of HCC, such as AFP (α-fetoprotein), TGFβ1 (transforming growth factor, beta 1) and GGT1 (gamma-glutamyltransferase 1).
4. Primary validations were employed in four potential markers, CTGF, GDF15, SPP1 and TXNRD1. The results show a significant higher expression of the four markers in tumors than in normal tissues at both transcript and protein expression level.
Conclusions
Four candidate diagnostic markers were successfully screened and theidentification results show it can be a potential serology diagnosis markerof early-stage HCC.
目前,AFP为肝癌较可靠的血清标志物,其灵敏度为60%～70%,特异性为90%左右,但近40%的肝癌AFP不升高,其原因可能是AFP含量与肿瘤体积大小有关。有文献报道,早期肝癌AFP的假阴性率可达40%以上,进展期肝癌AFP的假阴性率也可达15%～20%,因此,单凭AFP诊断肝癌易造成漏诊与误诊。寻找更加敏感、特异的早期诊断标记物显得十分迫切。
有学者认为,将一些敏感性和特异性较差的标志物联合检测,结合生物信息技术,可明显改善诊断的敏感性和特异性。人类基因组计划的完成及相关检测技术的进步,给大规模筛查并发现肿瘤和其他疾病的生物标记带来期望。作为标志物,肿瘤分泌蛋白无疑最具研究价值。
基于此,我们在前期研究中建立了大鼠早期肝癌模型,应用Affymetrix公司的Rat Genome 230.2.0基因芯片检测早期肝癌组织(T)和正常肝组织(N)中mRNA,构建差异表达谱,得到T与N Log R≥2和Log R≤-2差异表达基因共677个,其中表达上调409个,表达下调268个。经后续分析,上调和下调共涉及178种分子功能和204种生物学过程,并根据Gene ontology(GO)分类和应用EMBOSS程序TMAP和SIGLEAVE分别预测氨基酸序列的跨膜结构域和信号肽剪切位点以及Excel交集补集分析,按照其参与的生物学过程和具有分子功能进行聚类并筛选出可能的诊断标志物14个。经同源分析14个候选诊断标志物均与人具有同源性,随后采用RT-PCR及免疫组化对其在大鼠试验组与对照组及人正常肝脏组织、癌旁组织、小肝癌及大肝癌中mRNA水平和蛋白水平的表达进行鉴定,初步预测其在小肝癌诊断中的价值。
研究方法:
1.应用二乙基亚硝胺(diethylnitrosamine DEN)构建大鼠肝癌模型,并经常规病理学检测;
2.提取对照组大鼠正常肝脏组织与实验组早期肝癌组织总mRNA,逆转录cDNA,应用Rneasy Mini kit合成cRNA。cRNA与Affymetrix Rat Genenome 230.2.0基因芯片杂交,扫描芯片,筛选差异表达基因,并行数据归一化与和目标性去冗余处理;
3.应用GO注释结合序列分析筛选上调基因中编码分泌蛋白的基因后行Blast比对、HPRD数据库与文献查询,选择人同源基因作为候选诊断标志物;
4.应用RT-PCR、定量PCR及免疫组化对部分候选标志物在大鼠早期肝癌和人小肝癌中转录和蛋白表达水平进行验证。
结果
1.在DEN灌胃14-16周时,成功构建大鼠早期肝癌模型;
2.Affymetrix Rat Genenome 230.2.0基因芯片杂交后,扫描芯片原始数据经规一化处理筛选出差异表达基因677个,其中上调表达基因409个,下调表达基因268个,其中全长已知基因368个;
3.对上调基因中已知211个基因应用GO注释结合序列分析的二次筛选得到22个编码分泌蛋白的基因,再次经“PubMed”“Homogene”与“HPRD”检索,将同时具备人同源性、表达位点(Expression sits)中包括血清或血浆、文献显示与肿瘤发生有相关性的14个人同源的编码分泌蛋白基因作为候选标志物;
4.14个候选标志物经文献检索,其中AFP(alpha-fetoprotein),TGFBP1(transforming growth factor,beta1),GGT1(gamma-glutamyltransferase 1)已作为肝癌的诊断标志物在临床上应用,另4个:LOX(Lysyl oxidase),IGFBP3(insulin-like growth factor binding protein3),ENTPD 5(ectonudeoside triphosphate dipho sphohu drolase 5),PLAT(plasminogen activator,tissue)已有与肝癌相关的报道,本研究予以剔出。剩余的7个应用RT-PCR和免疫组化在大鼠正常组织和早期肝癌中行初步验证显示其中4个:CTGF(connective tissuegrowth factor),GDF15(growth differentiated factor 15),TXNRD 1(Thioredoxin reductase 1),SPP1(secreted phosphoperotein 1)在大鼠早期肝癌组织中高表达;
5.进一步在人正常肝脏组织、癌旁组织、小肝癌与大肝癌组织中对前述4个基因半定量RT-PCR显示小肝癌、大肝癌组织中mRNA表达明显上调;免疫组化显示,小肝癌和大肝癌组织中CTGF,GDF15,TXNRD1,SPP1的阳性表达面积比、积分灰度值与面积灰度整合值均明显高于正常肝组织与癌旁肝硬化组织。表达阳性部位均主要在胞浆和胞外基质。
结论:
1.商业化基因芯片结合合理的生物信息学数据处理是筛选肿瘤疾病基因差异表达的高效方法;
2.以动物模型为线索,利用基因芯片技术结合GO注释与针对性的序列分析是筛选分泌性蛋白作为人疾病早期诊断标志物的有效策略;
3.CTGF,GDF15,TXNRD1,SPP1初步鉴定显示其对人小肝癌筛选有潜在应用价值。
Hepatocellular carcinoma (HCC) has one of the worst prognoses among malignancies as the majority of this type of cancer at the early-stage is asymptomatic, and over three-quarter of the diagnoses are made at a time when the disease has already established regional or distant metastases. The 5-year survival is favorable for cases with an early diagnosis (80% approx), while survival with distant metastases over the same time period is less than 5%. The only validated serology tumor-marker in current use for diagnosis of HCC is AFP, which can be detected in the serum of more than 56.1% of cases with HCC. However, AFP is thought to be robust only in following the progression of the disease, but is not sensitive enough as an early stage diagnostic marker. Thus, there is an important need for additional diagnostic markers for this disease. Microarray technology allows researchers to simultaneously monitor the expression of thousands of genes, which provides molecular biomarkers to differentiate normal cells from malignant ones. For its capability to illustrate the cellular behavior on the genomic level, microarray technology has been applied in cancer research as one of the major topics in this field. Furthermore, effective application of this technique relies on well-organized data; because most existing microarray databases in cancer research are raw data sets and are hard-coded as columns in a table. It is difficult to draw directly supportive information for clinical cancer research from these. Gene expression profiling in the animal model holds great promise for our understanding of human pathogenesis. Here, we have generated and analyzed gene expression from Rat's liver cancer that was induced by DEN.
We used oligonucleotide microarrays that including over 30,000 well-substantiated rat genes to monitor the levels of expression within normal and early stage malignant liver tissues. Furthermore, we extended this analysis to investigate secreted protein by web resource that allows users to easily perform common queries on the data and to discover candidate diagnostic markers of early-stage HCC that can be detected in the blood. The overexpression of several genes that encode secreted protein were confirmed at transcript and protein expression level in the microtumors of rat models, as well as in the early-stage HCC patients. Our results show several of the genes as up-regulated in cancer and diagnostically useful. Other genes presented here, some of which we have validated, may find similar utility and suggest that many of these molecules may be relevant to tumorigenesis and may combination to form a simultaneous determination of early-stage HCC.
Methods
1. HCC model of rats were developed by feeding DEN (diethylnitrosamine) and early-stage HCC tissues were gathered at 14th -16th week.
2. Affymetrix Rat Genenome 230.2.0 GeneChip was used to detect the gene expression profile. Web-based bio-information and sequence analysis were used to screen target genes which significantly elevated expressed in tumor tissues and encode secreted proteins.
3. Transcription and protein expression levels of four target markers in both of animal model and human different stage HCC have subsequently been confirmed by RT-PCR and Immunohistochemistry. RT-PCR, Real-time quantitative PCR and immunohistochemistry were performed to identify the expression of candidate molecul in human HCC tissues.
Results
1. DEN successfully induced rat early-stage liver cancer
2. When compared with normal liver tissues, 677 genes(EST/Full length) in early-stage HCC were found to have different expression levels of more than two folds. Among those, 409 genes were up-regulated (log ratio>2), and 268 genes were down-regulated (log Ratio<-2).
3. According to the GO consortium annotations and the EMBOSS programs TMAP and SIGCLEAVE overlapping analysis, 22 genes were predicted to encode the secreted proteins in 211 highly expression known genes. After defining the query and gaining access to web-based resource , 14 retrieved genes were found to have the common features of H.sapiens orthologous gene, correlation with oncogenesis and expression sites including blood, serum, plasma. Of the 14 genes, Several have been applied to clinical diagnosis or reported to have relevant with tumorigenesis of HCC, such as AFP (α-fetoprotein), TGFβ1 (transforming growth factor, beta 1) and GGT1 (gamma-glutamyltransferase 1).
4. Primary validations were employed in four potential markers, CTGF, GDF15, SPP1 and TXNRD1. The results show a significant higher expression of the four markers in tumors than in normal tissues at both transcript and protein expression level.
Conclusions
Four candidate diagnostic markers were successfully screened and theidentification results show it can be a potential serology diagnosis markerof early-stage HCC.
引文
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8. Daid A Brown, Carsten Stephan, Robyn L Ward, et al. Measurement of Serum Levels of MIC1 Combinded with Prostate-Specific Antigen Improves Prostate Cancer Diagnosis, C Cancer Res, 2006,12 (1):89-96
9. Cervello M, Giannitrapani L, Labbozzetta M, et al. Expression of WISPs and of their novel alternative variants in human hepatocellular carcinoma cells. Ann N Y Acad Sci. 2004 Dec; 1028:432-439
10.Dornhofer N, Spong S, Bennewith K, et al.Connective tissue growth factor-specific monoclonal antibody therapy inhibits pancreatic tumor growth and metastasis. Cancer Res. 2006 Jun 1; 66(11):5816-5827
11. Aikawa T, Gunn J, Spong SM, et al. Connective tissue growth factor-specific antibody attenuates tumor growth, metastasis, and angiogenesis in an orthotopic mouse model of pancreatic cancer, Mol Cancer Ther. 2006, 5(5): 1108-1116
12. Dirk Vordermark~* 1, Harun M Saidl, Astrid Katzerl,et al. Plasma osteopontin levels in patients with head and neck cancer and cervix cancer are critically dependent on the choice of ELISA System [J]. BMC Cancer 2006, 6:207 doi:10.1186/1471-2407-6-207
13. A Celetti, D Testa, S Staibano,et al. Overexpression of the Cytokine Osteopontin Identifies Aggressive Laryngeal Squamous Cell Carcinomas and Enhances Carcinoma Cell Proliferation and Invasiveness [J]Clin. Cancer Res, 2005; 11(22): 8019 - 8027
14．曹慧芳、满晓波、蒋虹等．spp1基因在肺癌组织中表达的定量检测
15. Thalmann GN, Sikes RA, Devoll RE, et al. Osteopontin: possible role in prostate cancer progression. Clin Cancer Res 1999, 5:2271-7
16. Agrawal D, Chen T, Irby R, et al. Osteopontin identified as lead marker of colon cancer progression, using pooled sample expression profiling. J Natl Cancer Inst, 2002, 94:513-21
17. Rittling SR, Chambers AF. Role of osteopontin in tumour progression. Br J Cancer 2004, 90:1877-81
18. Ani C Khodavirdi, Zhigang Song, Shangxin Yang, et al. Increased expression of osteopontin contributes to the progression of prostate cancer [J], Cancer Res 2006, 66: (2) 883-888
19. Arner, E. S, A. Holmgren. Physiological functions of thioredoxin and thioredoxin reductase, Eur. J. Biochem, 2000,267:6102-6109
20. Han H, D J Bearss, L W Browne, et al. Identification of differentially expressed genes in pancreatic cancer cells using cDNA microarray. Cancer Res, 2002, 62:2890-2896
21. Lincoln DT, EM Ali Emadi, KF Tonissen, et al. The thioredoxin-thioredoxin reductase system: over-expression in human cancer[J]. Anticancer Res, 2003, 23:2425-2433.
22. Powis G, D Mustacich, A Coon. The role of the redox protein thioredoxin in cell growth and cancer. Free Radic. Biol Med. 2000. 29:312-322
23. Rundlof A K, E S Arner. Regulation of the mammalian selenoprotein thioredoxin reductase 1 in relation to cellular phenotype, growth, and signaling events [J]. Antioxid Redox Signal. 2004.6:41-52
24. Schuhmacher M, F Kohlhuber, M Holzel, et al. The transcriptional program of a human B cell line in response to Myc [J]. Nucleic Acids Res. 2001, 29:397-406
25. Hirota K, H Nakamura, H Masutani, et al. Thioredoxinsuperfamily and thioredoxin-inducing agents [J]. Acad. Sci. 2002. 957:189-199
1.Thomas MB,Abbruzzese JL et al.Opportunities for targeted therapies in hepatocellular carcinoma[J].Clin Oncol,2005,23(31):8093-108
2.Blum HE.Hepatocellular carcinoma:therapy and prevention[J].World J Gastroenterol.2005 Dec2005,21;11(47):7391-400.
3.Kreczko S,Lipska A,Wysocka J,et al.Alfa-fetoprotein:diagnostic value in hepatic disorders [J]. Pol Merkuriusz Lek, 2000, 8(48):420-423
4. Yoshida S, Kurokohchi K, Arima K, et al. Clinical significance of lens culinaris agglutinin reactive fraction of serum alpha-fetoprotein in patients with hepatocellular carcinoma [J]. Int J Oncol, 2002, 20(2): 305-309
5. Hayashi K, Kumada T, Nakano S,et al. Usefulness of measurement of Lensculinaris agglutinin reactive fraction of alpha-fetoprotein as a marker of prognosis and recurrence of small hepatocellular carcinoma[J]. AmJ Gastroenterol, 1999, 94 (10):2028-3033
6. Hsu HC, ChengW, Lai PL, et al. Cloning and exp ression of a developmentally regulated transcrip tMXR7 in hepatocellular carcinoma: biological significance and temporospatial distribution [J]. Cancer Res, 1997, 57(22): 5179-5184
7. CapurroM, Wanless IR, ShermanM, et al. Glyp ican23: a novel serum and histochemicalmarker for hepatocellular carcinoma [J]. Gastroenterology, 2003,125(1): 89-97
8. I Jichi M, Takayama T, Matsumura M, et al. Alpha-fetoprotein mRNA in the circulation as a predictor of postsurgical recurrence of hepatocellular carcinoma; a prospective study [J]. Hepatology, 2002, 35(4):835-860
9. Schmilovitz-Weiss H, Stemmer SM, Liberzon E, et al. Quantitation of alpha-fetoprotein messenger RNA for early detection of recurrent hepatocellular carcinoma: A prospective pilot study [J].Cancer Detect Prev, 2006 Apr 22;
10. Nakao A. Genetic detection and clinical application in patients with hepatocellular carcinoma.Nippon Geka Gakkai Zasshi, 2002, 103(6):472-475.
11. Miura N, Maeda Y, Kanbe T, et al. Serumhuman telomerase reverse transcriptase messenger RNA as a novel tumor marker for hepatocellular carcinoma[J]. Clin Cancer Res 2005, 11: 3205-3209
12. Miura N, Shiota G, Nakagawa T, et al. Sensitive detection of human telomerase reverse transcriptase mRNA in the serum of patients with hepatocellular carcinoma [J]. Oncology, 2003, 64: 430-434
13. Crawford LV, Pim DC, Bulbrook R, et al. Detection of antibodies against t he cellular protein p53 in sera from patients with breast cancer [J ]. Int J Cancer, 1982, 30 (2):403-408.
14. Charuruks N, Tangkijvanich P, Voravud N, et al. Clinical signifi cance of p53 antigen and anti-p53 antibodies in the sera of hepatocellular carcinoma patients [J]. Gastroenterol, 2001, 36: 830-836
15. Hu TH, Huang CC, Lin PR, et al. Expression and prognostic role of tumor suppressor gene PTEN/MMAC1/TEP1 in hepatocellular carcinoma [J]. Cancer, 2003, 97: 1929-1940
16. Wu F, Wu L, Zheng S, et al. The clinical value of hepatocyte growth factor and its receptor c-met for liver cancer patients with hepatectomy [J]. Dig Liver Dis, 2006 Apr 14
17. Sugimachi K, Tanaka S, Terashi T, et al. The mechanisms of angiogenesis in hepatocellular carcinoma: angiogenic switch during tumor progression [J]. Surgery, 2002, 131: S135-S141
18.Liu Z, Yan L, Xiang T, et al. Expression of vascular endothelial growth factor and matrix metalloproteinase-2 correlates with the invasion and metastasis of hepatocellular carcinoma [J]. Shengwu Yixue Gongcheng Xue Zazhi, 2003,20: 249-250,254
19. Huang GW, Yang LY, Lu WQ. Expression of hypoxia-inducible factor 1alpha and vascular endothelial growth factor in hepatocellular carcinoma: Impact on neovascularization and survival [J]. World J Gastroenterol, 2005, 11: 1705-1708
20. Kim SJ, Choi IK, Park KH, et al. Serum vascular endothelial growth factor per platelet count in hepatocellular carcinoma: correlations with clinical parameters and survival [J]. Jpn Clin Oncol, 2004, 34: 184-190
21. Akiba J, Yano H, Ogasawara S, et al. Expression and function of interleukin-8 in human hepatocellular carcinoma[J]. Int J Oncol, 2001,18:257-264
22. Ren Y, Poon RT, Tsui HT, et al. Interleukin-8 serum levels in patients with hepatocellular carcinoma: correlations with clinicopathological features and prognosis [J]. Clin Cancer Res, 2003,9: 5996-6001
23. Song BC, Chung YH, Kim JA, et al. Transforming growth factor betal as a useful serologic marker of small hepatocellular carcinoma[J]. Cancer, 2002, 94: 175-180
24. Sacco R, Leuci D, Tortorella C, et al. Transforming growth factor betal and soluble Fas serum levels in hepatocellular carcinoma [J]. Cytokine 2000, (12): 811-814
25. Yuen MF, Norris S, Evans LW, et al. Transforming growth factor betal, activin and follistatin in patients with hepatocellular carcinoma and patients with alcoholic cirrhosis [J]. Scand J Gastroenterol, 2002, 37 (2): 233-238.
26. ZhuJH, QiuDW, XiaJR, et al. Diagnostic value of TSGF and combined tumor marker determination in patients with malignant tumors [J]. Chongqing Yike Daxue Xuebao, 2004(29): 219-220, 244
27. Pan L, Lei JI, Pan BI, et al. Significance of detection of serum tumor markers in the diagnosis of primary hepatocellular carcinoma [J]. Zhongguo Zhongliu Linchuang Yu Kangfu, 2004(11): 401-402
28. Tsai JF, Jeng JE, Chuang LY, et al. Serum insulin 2like growth factor2 II as a serologic marker of small hepatocellular carcinoma [ J ]. Scand J Gastroenterol, 2005, 40 (1): 68-75.
29. Cui R, He J, Zhang F, et al. Diagnostic value of protein induced by vitamin K absence (PIVKAII) and hepatoma-specific band of serum gammaglutamyl transferase (GGTII) as hepatocellular carcinoma markers complementary to alpha-fetoprotein [J]. Br J Cancer, 2003, (88): 1878-1882
30. Tangkijvanich P, Tosukhowong P, Bunyongyod P, et al. Alpha-L-fucosidase as a serum marker of hepatocellular carcinoma in Thailand [J]. Southeast Asian J Trop Med Public Health, 1999, (30): 110-114
31. Ishizuka H, Nakayama T, Matsuoka S, et al. Prediction of the development of hepato-cellular-carcinoma in patients with liver cirrhosis by the serial determinations of serum alpha-L-fucosidase activity [J]. Intern Med, 1999, (38): 927-931
32. Shimizu A, Shiraki K, et al. Sequential fluctuation pattern of serum desgammacarboxy prothrombin levels detected by high sensitive electrochemiluminescence system as an eystem as an early predictive marker for hepatocellular carcinoma in patients with cirrhosis [J]. Int Mol Med, 2002, 9(3):245-250
33. Yao DF, Jiang DR, Huang ZW, et al. Abnormal expression of hepatoma specific γ-glutamyl transferase and alteration of γ-glutamyl gene methylation status in patients with hepatocellular carcinoma[J]. Cancer, 2000, 88 (4):761-769.
34. Quaglia A, McStay M, Stoeber K, et al. Novel markers of cell kinetics to evaluate progression from cirrhosis to hepatocellular carcinoma [J]. Liver Int, 2006, 26(4):424-32.
35. Chuma M, Sakamoto M, Yamazaki K, et al. Expression profiling in multi-stage hepatocarcinogenesis: identification of HSP70 as a molecular marker of early hepatocellular carcinoma [J]. Hepatology, 2003,37(1):198-207
36. Graveel CR, Harkins Perry SR, Acevedo LG, et al. Identificaiton of characterization of CRG2L2, a new marker for liver tumor development [J] . Oncogene, 2003, 22 (11): 1730-1736
37. Editorials. How are we going to discover new cancer biomarkers? a proteomic approach for bladder cancer. Clin Chem 2004,50(50): 793-795
38. Conrads TP, Zhou M, Petricoin EF, et al. Cancer diagnosis using proteomics patterns [J]. Expert Rev Mol Diagn,2003,3(4):411-420)
39. Adam B L, Qu Y, Davis JW, et al. Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men [J]. Cancer Res, 2002, 62(13):3609-3614
40. Vlahou A, Schellbammer PF, Mendrino S, et al. Development of a novel proteomic approach for the detection of transitional cell carcinoma of the bladder in urine [J]. Am J Pathol,2001, 158(4):1491-1502
41. Pepe MS, Etzioni R, Feng Z, et al. Phases of biomarker development for early detection of cancer [J]. Natl Cancer Inst, 2001, 93(14): 1054-1061.
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1.Fairlie WD,Moore AG,Bauskin AR,et al.MIC-1 is a novel TGF-h superfamily cytokine associated with macrophage activation.J Leukocyte Biol,1999,65:2-5.
2.Welsh JB,Sapinoso LM,Kern SG,et al.Large-scale delineation of secreted protein biomarkers overexpressed in cancer tissue and serum.Proc Natl Acad Sci USA,2003,100:3410-3415
3.Schober A,Bottner M,Strelau J,et al.Expression of growth differentiation factor- 15/macrophage inhibitory cytokine- 1(GDF-15/MIC-1)in the perinatal,adult,and injured rat brain.J Comp Neurol 2001,439:32-45
4.Samina Noorali,Takeshi Kurita,Bruce Woolcock,et al Dynamics of expression of growth differentiation factor 15 in normal and PIN development in the mouse Differentiation,2007,75:325-336
5.Koopmann J,Rosenzweig CN,Zhang Z,et al.Goggins M.Serum markers in patients with resectable pancreatic adenocarcinoma: macrophage inhibitory cytokine 1 versus CA19-9 Clin Cancer Res.2006 Jan 15;12(2):442-6
6. Brown DA, Ward RL, Buckhaults P, et al. MIC-1 serum level and genotype: associations with progress and prognosis of colorectal carcinoma [J]. Clinical Cancer Res, 2003, (9):2642-2650
7. Koopmann J, Rosenzweig CN, Zhang Z, et al. Serum markers in patients with resectable pancreatic adenocarcinoma: macrophage inhibitory cytokine 1 versus CA19-9[J]. Clin Cancer Res, 2006,12 (2):442-446
8. Daid A Brown, Carsten Stephan, Robyn L Ward, et al. Measurement of Serum Levels of MIC1 Combinded with Prostate-Specific Antigen Improves Prostate Cancer Diagnosis, C Cancer Res, 2006,12 (1):89-96
9. Cervello M, Giannitrapani L, Labbozzetta M, et al. Expression of WISPs and of their novel alternative variants in human hepatocellular carcinoma cells. Ann N Y Acad Sci. 2004 Dec; 1028:432-439
10.Dornhofer N, Spong S, Bennewith K, et al.Connective tissue growth factor-specific monoclonal antibody therapy inhibits pancreatic tumor growth and metastasis. Cancer Res. 2006 Jun 1; 66(11):5816-5827
11. Aikawa T, Gunn J, Spong SM, et al. Connective tissue growth factor-specific antibody attenuates tumor growth, metastasis, and angiogenesis in an orthotopic mouse model of pancreatic cancer, Mol Cancer Ther. 2006, 5(5): 1108-1116
12. Dirk Vordermark~* 1, Harun M Saidl, Astrid Katzerl,et al. Plasma osteopontin levels in patients with head and neck cancer and cervix cancer are critically dependent on the choice of ELISA System [J]. BMC Cancer 2006, 6:207 doi:10.1186/1471-2407-6-207
13. A Celetti, D Testa, S Staibano,et al. Overexpression of the Cytokine Osteopontin Identifies Aggressive Laryngeal Squamous Cell Carcinomas and Enhances Carcinoma Cell Proliferation and Invasiveness [J]Clin. Cancer Res, 2005; 11(22): 8019 - 8027
14．曹慧芳、满晓波、蒋虹等．spp1基因在肺癌组织中表达的定量检测
15. Thalmann GN, Sikes RA, Devoll RE, et al. Osteopontin: possible role in prostate cancer progression. Clin Cancer Res 1999, 5:2271-7
16. Agrawal D, Chen T, Irby R, et al. Osteopontin identified as lead marker of colon cancer progression, using pooled sample expression profiling. J Natl Cancer Inst, 2002, 94:513-21
17. Rittling SR, Chambers AF. Role of osteopontin in tumour progression. Br J Cancer 2004, 90:1877-81
18. Ani C Khodavirdi, Zhigang Song, Shangxin Yang, et al. Increased expression of osteopontin contributes to the progression of prostate cancer [J], Cancer Res 2006, 66: (2) 883-888
19. Arner, E. S, A. Holmgren. Physiological functions of thioredoxin and thioredoxin reductase, Eur. J. Biochem, 2000,267:6102-6109
20. Han H, D J Bearss, L W Browne, et al. Identification of differentially expressed genes in pancreatic cancer cells using cDNA microarray. Cancer Res, 2002, 62:2890-2896
21. Lincoln DT, EM Ali Emadi, KF Tonissen, et al. The thioredoxin-thioredoxin reductase system: over-expression in human cancer[J]. Anticancer Res, 2003, 23:2425-2433.
22. Powis G, D Mustacich, A Coon. The role of the redox protein thioredoxin in cell growth and cancer. Free Radic. Biol Med. 2000. 29:312-322
23. Rundlof A K, E S Arner. Regulation of the mammalian selenoprotein thioredoxin reductase 1 in relation to cellular phenotype, growth, and signaling events [J]. Antioxid Redox Signal. 2004.6:41-52
24. Schuhmacher M, F Kohlhuber, M Holzel, et al. The transcriptional program of a human B cell line in response to Myc [J]. Nucleic Acids Res. 2001, 29:397-406
25. Hirota K, H Nakamura, H Masutani, et al. Thioredoxinsuperfamily and thioredoxin-inducing agents [J]. Acad. Sci. 2002. 957:189-199
1.Thomas MB,Abbruzzese JL et al.Opportunities for targeted therapies in hepatocellular carcinoma[J].Clin Oncol,2005,23(31):8093-108
2.Blum HE.Hepatocellular carcinoma:therapy and prevention[J].World J Gastroenterol.2005 Dec2005,21;11(47):7391-400.
3.Kreczko S,Lipska A,Wysocka J,et al.Alfa-fetoprotein:diagnostic value in hepatic disorders [J]. Pol Merkuriusz Lek, 2000, 8(48):420-423
4. Yoshida S, Kurokohchi K, Arima K, et al. Clinical significance of lens culinaris agglutinin reactive fraction of serum alpha-fetoprotein in patients with hepatocellular carcinoma [J]. Int J Oncol, 2002, 20(2): 305-309
5. Hayashi K, Kumada T, Nakano S,et al. Usefulness of measurement of Lensculinaris agglutinin reactive fraction of alpha-fetoprotein as a marker of prognosis and recurrence of small hepatocellular carcinoma[J]. AmJ Gastroenterol, 1999, 94 (10):2028-3033
6. Hsu HC, ChengW, Lai PL, et al. Cloning and exp ression of a developmentally regulated transcrip tMXR7 in hepatocellular carcinoma: biological significance and temporospatial distribution [J]. Cancer Res, 1997, 57(22): 5179-5184
7. CapurroM, Wanless IR, ShermanM, et al. Glyp ican23: a novel serum and histochemicalmarker for hepatocellular carcinoma [J]. Gastroenterology, 2003,125(1): 89-97
8. I Jichi M, Takayama T, Matsumura M, et al. Alpha-fetoprotein mRNA in the circulation as a predictor of postsurgical recurrence of hepatocellular carcinoma; a prospective study [J]. Hepatology, 2002, 35(4):835-860
9. Schmilovitz-Weiss H, Stemmer SM, Liberzon E, et al. Quantitation of alpha-fetoprotein messenger RNA for early detection of recurrent hepatocellular carcinoma: A prospective pilot study [J].Cancer Detect Prev, 2006 Apr 22;
10. Nakao A. Genetic detection and clinical application in patients with hepatocellular carcinoma.Nippon Geka Gakkai Zasshi, 2002, 103(6):472-475.
11. Miura N, Maeda Y, Kanbe T, et al. Serumhuman telomerase reverse transcriptase messenger RNA as a novel tumor marker for hepatocellular carcinoma[J]. Clin Cancer Res 2005, 11: 3205-3209
12. Miura N, Shiota G, Nakagawa T, et al. Sensitive detection of human telomerase reverse transcriptase mRNA in the serum of patients with hepatocellular carcinoma [J]. Oncology, 2003, 64: 430-434
13. Crawford LV, Pim DC, Bulbrook R, et al. Detection of antibodies against t he cellular protein p53 in sera from patients with breast cancer [J ]. Int J Cancer, 1982, 30 (2):403-408.
14. Charuruks N, Tangkijvanich P, Voravud N, et al. Clinical signifi cance of p53 antigen and anti-p53 antibodies in the sera of hepatocellular carcinoma patients [J]. Gastroenterol, 2001, 36: 830-836
15. Hu TH, Huang CC, Lin PR, et al. Expression and prognostic role of tumor suppressor gene PTEN/MMAC1/TEP1 in hepatocellular carcinoma [J]. Cancer, 2003, 97: 1929-1940
16. Wu F, Wu L, Zheng S, et al. The clinical value of hepatocyte growth factor and its receptor c-met for liver cancer patients with hepatectomy [J]. Dig Liver Dis, 2006 Apr 14
17. Sugimachi K, Tanaka S, Terashi T, et al. The mechanisms of angiogenesis in hepatocellular carcinoma: angiogenic switch during tumor progression [J]. Surgery, 2002, 131: S135-S141
18.Liu Z, Yan L, Xiang T, et al. Expression of vascular endothelial growth factor and matrix metalloproteinase-2 correlates with the invasion and metastasis of hepatocellular carcinoma [J]. Shengwu Yixue Gongcheng Xue Zazhi, 2003,20: 249-250,254
19. Huang GW, Yang LY, Lu WQ. Expression of hypoxia-inducible factor 1alpha and vascular endothelial growth factor in hepatocellular carcinoma: Impact on neovascularization and survival [J]. World J Gastroenterol, 2005, 11: 1705-1708
20. Kim SJ, Choi IK, Park KH, et al. Serum vascular endothelial growth factor per platelet count in hepatocellular carcinoma: correlations with clinical parameters and survival [J]. Jpn Clin Oncol, 2004, 34: 184-190
21. Akiba J, Yano H, Ogasawara S, et al. Expression and function of interleukin-8 in human hepatocellular carcinoma[J]. Int J Oncol, 2001,18:257-264
22. Ren Y, Poon RT, Tsui HT, et al. Interleukin-8 serum levels in patients with hepatocellular carcinoma: correlations with clinicopathological features and prognosis [J]. Clin Cancer Res, 2003,9: 5996-6001
23. Song BC, Chung YH, Kim JA, et al. Transforming growth factor betal as a useful serologic marker of small hepatocellular carcinoma[J]. Cancer, 2002, 94: 175-180
24. Sacco R, Leuci D, Tortorella C, et al. Transforming growth factor betal and soluble Fas serum levels in hepatocellular carcinoma [J]. Cytokine 2000, (12): 811-814
25. Yuen MF, Norris S, Evans LW, et al. Transforming growth factor betal, activin and follistatin in patients with hepatocellular carcinoma and patients with alcoholic cirrhosis [J]. Scand J Gastroenterol, 2002, 37 (2): 233-238.
26. ZhuJH, QiuDW, XiaJR, et al. Diagnostic value of TSGF and combined tumor marker determination in patients with malignant tumors [J]. Chongqing Yike Daxue Xuebao, 2004(29): 219-220, 244
27. Pan L, Lei JI, Pan BI, et al. Significance of detection of serum tumor markers in the diagnosis of primary hepatocellular carcinoma [J]. Zhongguo Zhongliu Linchuang Yu Kangfu, 2004(11): 401-402
28. Tsai JF, Jeng JE, Chuang LY, et al. Serum insulin 2like growth factor2 II as a serologic marker of small hepatocellular carcinoma [ J ]. Scand J Gastroenterol, 2005, 40 (1): 68-75.
29. Cui R, He J, Zhang F, et al. Diagnostic value of protein induced by vitamin K absence (PIVKAII) and hepatoma-specific band of serum gammaglutamyl transferase (GGTII) as hepatocellular carcinoma markers complementary to alpha-fetoprotein [J]. Br J Cancer, 2003, (88): 1878-1882
30. Tangkijvanich P, Tosukhowong P, Bunyongyod P, et al. Alpha-L-fucosidase as a serum marker of hepatocellular carcinoma in Thailand [J]. Southeast Asian J Trop Med Public Health, 1999, (30): 110-114
31. Ishizuka H, Nakayama T, Matsuoka S, et al. Prediction of the development of hepato-cellular-carcinoma in patients with liver cirrhosis by the serial determinations of serum alpha-L-fucosidase activity [J]. Intern Med, 1999, (38): 927-931
32. Shimizu A, Shiraki K, et al. Sequential fluctuation pattern of serum desgammacarboxy prothrombin levels detected by high sensitive electrochemiluminescence system as an eystem as an early predictive marker for hepatocellular carcinoma in patients with cirrhosis [J]. Int Mol Med, 2002, 9(3):245-250
33. Yao DF, Jiang DR, Huang ZW, et al. Abnormal expression of hepatoma specific γ-glutamyl transferase and alteration of γ-glutamyl gene methylation status in patients with hepatocellular carcinoma[J]. Cancer, 2000, 88 (4):761-769.
34. Quaglia A, McStay M, Stoeber K, et al. Novel markers of cell kinetics to evaluate progression from cirrhosis to hepatocellular carcinoma [J]. Liver Int, 2006, 26(4):424-32.
35. Chuma M, Sakamoto M, Yamazaki K, et al. Expression profiling in multi-stage hepatocarcinogenesis: identification of HSP70 as a molecular marker of early hepatocellular carcinoma [J]. Hepatology, 2003,37(1):198-207
36. Graveel CR, Harkins Perry SR, Acevedo LG, et al. Identificaiton of characterization of CRG2L2, a new marker for liver tumor development [J] . Oncogene, 2003, 22 (11): 1730-1736
37. Editorials. How are we going to discover new cancer biomarkers? a proteomic approach for bladder cancer. Clin Chem 2004,50(50): 793-795
38. Conrads TP, Zhou M, Petricoin EF, et al. Cancer diagnosis using proteomics patterns [J]. Expert Rev Mol Diagn,2003,3(4):411-420)
39. Adam B L, Qu Y, Davis JW, et al. Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men [J]. Cancer Res, 2002, 62(13):3609-3614
40. Vlahou A, Schellbammer PF, Mendrino S, et al. Development of a novel proteomic approach for the detection of transitional cell carcinoma of the bladder in urine [J]. Am J Pathol,2001, 158(4):1491-1502
41. Pepe MS, Etzioni R, Feng Z, et al. Phases of biomarker development for early detection of cancer [J]. Natl Cancer Inst, 2001, 93(14): 1054-1061.