PCR-array gene expression profiling of hepatocellular carcinoma

Many trials using DNA microarrays have been reported for various human malignancies, but an efficient molecular diagnostic system has yet to be established. Here, we adopted a high throughput quantitative PCR-array system based on adaptor-tagged competitive PCR (ATAC-PCR), as a novel technique for gene expression profiling of hepatocellular carcinoma (HCC). This PCR-array contained 3,072 genes derived from three different cDNA libraries, including 298 additional known genes suspected to be involved in hepatocarcinogenesis. Using this PCR-array with 20 pairs of liver tissues (20 HCC, 20 surrounding nontumor liver), we identified a total of 117 genes differing in expression levels in the two liver tissues. Hierarchical clustering analysis and principal component analysis with these genes revealed distinct gene expression patterns in the HBV-positive group and the HCV-positive groups. Among 117 genes, only 7 (GPAA1, TMEM9, FACL4, ADFP, MAWBP, PACE4, FOS) were common to both groups. In conclusion, this PCR-array analysis with an appropriate set of genes is considered useful for gene expression profiling of HCC, and we identified some genes which may play a common key role in hepatocarcinogenesis.     

肾透明细胞癌与癌旁组织差异蛋白表达谱分析

目的:通过比较肾透明细胞癌和癌旁组织的蛋白表达谱差异,筛选新的肾癌肿瘤标志,为提高肾癌诊断的敏感性和特异性提供基础。方法:分别提取10例肾透明细胞癌及其癌旁肾组织蛋白,蛋白定量后,采用双向凝胶电泳(2-DE)对组织蛋白表达谱进行分离,采用飞行时间质谱对差异位点进行蛋白鉴定。结果:鉴定出20个肾癌上调蛋白,10个下调蛋白,上调蛋白集中于缺氧反应和抗凋亡,以及Glycolysis、Regulation of actin cytoskeleton和PPAR信号通路。结论:本研究筛选出一组在肾癌组织中高表达的蛋白,是肾透明细胞癌的候选肿瘤标志,为进一步的验证和功能研究提供了基础。     

Future of molecular profiling of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a fatal disease occurring worldwide and developing mainly in chronic liver diseased patients. Despite routine screening of individuals at high risk, most of the patients are diagnosed at late stages of HCC. In addition, the recurrence rate after surgical resection of small tumors is high. Molecular profiling, including expression analysis, comparative genomics and proteomics, provides powerful tools to gain insight into the molecular mechanisms underlying carcinogenesis. Advances in bioinformatics have also allowed for the evaluation of large data sets. Therefore, molecular profiling of HCC using a Biological Expression Network Discovery (BLEND) strategy that integrates global molecular profiling data, including mRNA, miRNA, DNA methylation and DNA copy numbers from both the tumor and the surrounding microenvironment, along with mechanistic studies, may improve the diagnosis, treatment and prognosis of HCC patients. Such an approach will provide mechanistic insight into the pathogenesis of HCC, potentially leading to personalized medicine and the identification of new therapeutic targets.     

蛋白质芯片SELDI-TOF-MS技术及其在大肠癌中的应用

蛋白质芯片SELDI—TOF—MS技术是蛋白质组学研究中的一种全新的技术平台，现阐述在消化道常见恶性肿瘤大肠癌中应用该技术筛检肿瘤标志物的最新进展。     

应用MALDI-TOF-MS检测原发性肝癌骨转移患者血清的多肽差异谱

目的:应用基质辅助激光解析电离飞行时间质谱(matrix-assisted laser desorption ionization-time of flight mass spectrometry,MALDI-TOF-MS)系统分析原发性肝细胞癌(hepatocellular carcinoma,HCC)骨转移患者血清多肽差异谱,寻找具有潜在诊断意义的血清分子标志物.方法:收集50例HCC骨转移患者和50例HCC未骨转移患者的血清,分成训练组(76例)和验证组(24例).所有样本分别经ClinProt磁珠纯化、MALDI-TOF-MS检测及ClinProTools软件进行血清多肽差异谱分析.应用液相色谱质谱联用的方法对差异多肽进行序列鉴定.应用径向基神经网络(radial basis function neural network,RBFNN)算法建立诊断模型,并对诊断模型进行单盲法实验验证.结果:HCC骨转移患者中,共获得10条差异有统计学意义[P (Wilcoxon-test)＜0.001]的多肽峰,并成功鉴定了其中7条肽段(质荷比分别为1 780.7、1 866.5、2 131.6、2 880.4、1 532.4、2 489.8和2 234.3)的氨基酸序列,这些肽段的来源蛋白分别为甲胎蛋白(alpha-fetoprotein)、凝血酶原(prothrombin)、丝甘蛋白聚糖(serglycin)、交联-α-胰蛋白酶抑制物H4重链异构体2(isoform 2 of inter-alpha-trypsin inhibitor heavy chain H4)、自噬相关蛋白16-2异构体1(isoform 1 of autophagy-related protein 16-2)、转甲状腺素蛋白(transthyretin)和纤维蛋白β链(fibrinogen beta chain).选取2组间统计学差异最显著的6条多肽峰(质荷比分别为1 535.4、1 780.7、1 866.5、2 131.6、2 880.4和2 901.9)建立的诊断模型的识别率为89.47％,预测率为82.89％;单盲法验证模型的灵敏度为83％,特异度为92％.结论:筛选获得的差异血清多肽可能成为潜在的诊断HCC骨转移的分子标志物.     

肝细胞癌周围微小转移分布的研究

目的研究肝癌微转移的分布规律,为手术切除范围提供参考.方法选择无临床转移灶的肝细胞癌病例,取切缘较充分的手术切除标本36例,将其瘤周组织划分为近端区域和远端区域,制成病理大切片.在距原发灶边缘0.5,1.0,2.0 cm分别做3条分界线(L0.5、L1.0、L2.0),把近端和远端区域的瘤周组织由内向外划分出6组条带(Zp0.5、Zp1.0、Zp2.0和Zd0.5、Zd1.0、Zd2.0).分析微转移的扩散距离和各组条带的微转移密度(Dp0.5、Dp1.0、Dp2.0和Dd0.5、Dd1.0、Dd2.0).结果检出的微转移72.5%(111/153)是门静脉微癌栓.在66.7%(24/36)的标本中检出了微转移,其中91.7%(22/24)的标本远端最大扩散距离<3 cm.在近端区域的特定分析中,92.3%(12/13)的标本近端最大扩散距离<1.5 cm.微转移密度比较Dp0.5>Dp1.0>Dp2.0,Dd0.5>Dd1.0>Dd2.0,Dd1.0>Dp1.0,Dd2.0>Dp2.0,差异有显著性.结论 (1)肝癌微转移主要以门静脉微癌栓的形式存在;(2)距原发灶越远,微转移发生率越低;(3)在距原发灶0.5 cm以外的范围,微转移在近端区域的发生率比在远端区域的低;(4)对于无临床转移灶的患者,在远端切除瘤周组织范围达到3 cm,在近端切除范围达到1.5 cm,可能有助于降低术后复发率.     

Proteomic analysis of differentially expressed proteins in hepatitis B virus-related hepatocellular carcinoma tissues

Background

Hepatocellular carcinoma (HCC), a major cause of cancer death in China, is preceded by chronic hepatitis and liver cirrhosis (LC). Although hepatitis B virus (HBV) has been regarded as a clear etiology of human hepatocarcinogenesis, the mechanism is still needs to be further clarified. In this study, we used a proteomic approach to identify the differential expression protein profiles between HCC and the adjacent non-tumorous liver tissues.

Methods

Eighteen cases of HBV-related HCC including 12 cases of LC-developed HCC and 6 cases of chronic hepatitis B (CHB)-developed HCC were analyzed by two-dimensional electrophoresis (2-DE) combined with matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS), and the results were compared to those of paired adjacent non-tumorous liver tissues.

Results

A total of 17 differentially expressed proteins with diverse biological functions were identified. Among these, 10 proteins were up-regulated, whereas the other 7 proteins were down-regulated in cancerous tissues. Two proteins, c-Jun N-terminal kinase 2 and ADP/ATP carrier protein were found to be up-regulated only in CHB-developed HCC tissues. Insulin-like growth factor binding protein 2 and Rho-GTPase-activating protein 4 were down-regulated in LC-developed and CHB-developed HCC tissues, respectively. Although 11 out of these 17 proteins have been already described by previous studies, or are already known to be involved in hepatocarcinogenesis, this study revealed 6 new proteins differentially expressed in HBV-related HCC.

Conclusion

These findings elucidate that there are common features between CHB-developed HCC and LC-developed HCC. The identified proteins are valuable for studying the hepatocarcinogenesis, and may be potential diagnostic markers or therapeutic targets for HBV-related HCC.     

DETECTION OF ALPHA-1 ANTICHYMOTRYPSIN IN HEPATOCELLULAR CARCINOMA TISSUE

One hundred and fifty-three consecutive cases of HCC and 25 controls from autopsy material were studied by immunohistochemical method in this paper. A review of the histopathology and demonstration of AFP, alpha- 1-antichymotrypsin (AACT), alpha 1-antitrypsin (AAT) and CEA were made.Among the tumor markers. AACT yielded the highest positive rate, 109 cases (71%) out of 153 HCC. CEA was the next, 95 cases (62%) .AFP and AAT gave the same result, 72 cases (47%) . AACT, AAT and CEA were not found in the controls. AFP was present in a few hepatocytes in 1 of 25 controls. The results were in keeping with serum tests so far as the highest positive rate being AACT was concerned. Therefore, combined determination of AACT and AFP would seem a better screening method than by that of AFP alone for survey of HCC.     

Glucocorticoid receptors in hepatocellular carcinoma and adjacent liver tissue

Glucocorticoid and progesterone receptors, tyrosine aminotransferase, gamma-glutamyltransferase and alpha-fetoprotein levels were determined in human hepatocellular carcinoma (HCC) and adjacent liver tissues. Glucocorticoid receptor was present in seven of ten HCC samples, values ranged from 1.9 to 66.8 fmol/mg protein. Progesterone receptor was present in two of ten HCC samples with values of 1.7 and 7.2 fmol/mg protein, respectively. In the adjacent liver tissues, no measurable progesterone receptor was found and only one sample had glucocorticoid receptor with a value of 3.0 fmol/mg protein. The increase of glucocorticoid receptor in HCC samples was coincident with a decreased level of tyrosine aminotransferase and an increased level of gamma-glutamyltransferase. No correlation was found among glucocorticoid receptor level, serum or tissue alpha-fetoprotein levels. The presence of glucocorticoid receptors in HCC suggest that hormones may play an important role in the formation of hepatoma, and hormonal therapy may be useful for patients with HCC.     

Gene expression profiling of human HBV- and/or HCV-associated hepatocellular carcinoma cells using expressed sequence tags

Liver cancer is one of the leading causes of cancer death worldwide. To identify novel target genes that are related to liver carcinogenesis, we examined new genes that are differentially expressed in human hepatocellular carcinoma (HCC) cell lines and tissues based on the expressed sequence tag (EST) frequency. Eleven libraries were constructed from seven HCC cell lines and three normal liver tissue samples obtained from Korean patients. An analysis of gene expression profiles for HCC was performed using the frequency of ESTs obtained from these cDNA libraries. Genes were identified (n=120) as being either up- or down-regulated in human liver cancer cells. Among these, 14 genes (FTL, K-ALPHA1, LDHA, RPL4, ENO1, ANXA2, RPL9, RPL10, RPL13A, GNB2L1, AMBP, GC, A1BG, and SERPINC1), in addition to previously well-known liver cancer related genes, were confirmed to be differentially expressed in seven liver cancer cell lines and 17 HCC tissues by semi-quantitative RT-PCR. In addition, 73 genes, in which there was a significant difference (P>0.99) between HBV- and HCV-associated HCC cells, were selected. Of these, expression patterns of 14 (RPLP0, AKR1C, KRT8, GPX4, RPS15, ID1, RPS21, VIM, EEF1G, EIF4A1, HLA-C, FN1, CD44, and RPS10) were confirmed by semi-quantitative RT-PCR in four of HBV- and three of HCV-associated HCC cell lines. Among those genes, an immunohistochemical analysis for ANXA2 showed that it is expressed at high levels in HCC. Using an analysis of EST frequency, the newly identified genes, especially ANXA2, represent potential biomarkers for HCC and useful targets for elucidating the molecular mechanisms associated with HCC involving virological etiology.     

Gene expression profiling reveals potential biomarkers of human hepatocellular carcinoma.

PURPOSE: Hepatocellular carcinoma (HCC), a common cancer worldwide, has a dismal outcome partly due to the poor identification of early-stage HCC. Currently, one third of HCC patients present with low serum alpha-fetoprotein (AFP) levels, the only clinically available diagnostic marker for HCC. The aim of this study was to identify new diagnostic molecular markers for HCC, especially for individuals with low serum AFP. EXPERIMENTAL DESIGN: We used the microarray technique to determine the expression profiles of 218 HCC specimens from patients with either high or low serum AFP. From the microarray study, we selected five candidate genes (i.e., GPC3, PEG10, MDK, SERPINI1, and QP-C), which were overexpressed in HCCs. Using quantitative real-time PCR analyses, we validated the expression of these five genes in 50 AFP-normal and 8 AFP-positive HCC specimens and 36 cirrhotic noncancerous hepatic specimens, which include 52 independent specimens not used in microarray analysis. RESULTS: A significant increase in the expression of the five candidate genes could be detected in most of the HCC samples, including those with normal serum AFP and small tumors. GPC3, MDK, and SERPINI1 encode known serum proteins. Consistently, a significant increase in serum midkine, encoded by MDK, was associated with HCC patients, including those with normal serum AFP. Using prediction analysis of microarray, we showed that a combined score of these five genes can accurately classify noncancerous hepatic tissues (100%) and HCC (71%). CONCLUSIONS: We suggest that a diagnostic signature approach using a combined score of these five biomarkers rather than a single marker may improve the prediction accuracy of HCC patients, including those with normal serum AFP and smaller-sized tumors.     

Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling

There has been limited analysis of the effects of hepatocellular carcinoma (HCC) on liver metabolism and circulating endogenous metabolites. Here, we report the findings of a plasma metabolomic investigation of HCC patients by ultraperformance liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS), random forests machine learning algorithm, and multivariate data analysis. Control subjects included healthy individuals as well as patients with liver cirrhosis or acute myeloid leukemia. We found that HCC was associated with increased plasma levels of glycodeoxycholate, deoxycholate 3-sulfate, and bilirubin. Accurate mass measurement also indicated upregulation of biliverdin and the fetal bile acids 7α-hydroxy-3-oxochol-4-en-24-oic acid and 3-oxochol-4,6-dien-24-oic acid in HCC patients. A quantitative lipid profiling of patient plasma was also conducted by ultraperformance liquid chromatography-electrospray ionization-triple quadrupole mass spectrometry (UPLC-ESI-TQMS). By this method, we found that HCC was also associated with reduced levels of lysophosphocholines and in 4 of 20 patients with increased levels of lysophosphatidic acid [LPA(16:0)], where it correlated with plasma α-fetoprotein levels. Interestingly, when fatty acids were quantitatively profiled by gas chromatography-mass spectrometry (GC-MS), we found that lignoceric acid (24:0) and nervonic acid (24:1) were virtually absent from HCC plasma. Overall, this investigation illustrates the power of the new discovery technologies represented in the UPLC-ESI-QTOFMS platform combined with the targeted, quantitative platforms of UPLC-ESI-TQMS and GC-MS for conducting metabolomic investigations that can engender new insights into cancer pathobiology.     

Gene expression profiling in polycythemia vera using cDNA microarray technology

Polycythemia vera (PV) is a myeloproliferative disorder characterized by an increased proliferation of all three myeloid lineages. The molecular pathogenesis of PV is unknown. Using cDNA microarrays comprising 6000 human genes, we studied the gene expression profile of granulocytes obtained from 11 PV patients compared with granulocytes obtained from healthy individuals. We found that 147 genes were up-regulated by >/==" BORDER="0">2.5 fold in the majority of PV patients. Eleven of these 147 genes were up-regulated in all PV patients studied and may represent a molecular signature for this disorder. An increase in the expression of several protease inhibitors with affinity for proteases that promote apoptosis in neutrophils (e.g., cystatin F, secretory leukocyte protease inhibitor), as well as the up-regulation of a number of antiapoptotic and survival factors was found (e.g., adrenomedullin, p38 mitogen-activated protein kinase). We speculate that the deregulation of these factors may inhibit normal apoptosis and promote cell survival in the granulocytes of patients with PV. These PV-specific expression changes are likely to be biologically important in the pathophysiology of this disorder.     

A prognostic fingerprint in liver transplantation for hepatocellular carcinoma based on plasma metabolomics profiling

IntroductionTumor recurrence is a major cause of post-transplant mortality in liver transplantation for hepatocellular carcinoma (HCC). This study aimed to explore an effective noninvasive approach to accurately predict post-transplant tumor recurrence.Materials and methodsMetabolomics profiling was performed on pre-operative plasma from 122 HCC patients undergoing liver transplantation, 52 healthy controls (HC) and 25 liver cirrhosis (LC) patients.ResultsFive prognostic metabolites were identified by univariate analysis (P < 0.01), including phosphatidylcholine (PC) (16:0/P-18:1), PC(18:2/OH-16:0), PC(o-16:0/20:4), nutriacholic acid and 2-oxo-4-methylthiobutanoic acid. In the HCC group, PC(o-16:0/20:4), nutriacholic acid and 2-oxo-4-methylthiobutanoic acid were decreased, while PC(18:2/OH-16:0) was elevated compared with the LC group (e < 0.05). PC(16:0/P-18:1) was associated with tumor size, vascular invasion, and neutrophil-lymphocyte ratio (NLR; P < 0.05). Moreover, PC(18:2/OH-16:0) was also related to tumor number and NLR (P < 0.05). Multivariate cox regression showed that PC(16:0/P-18:1), PC(18:2/OH-16:0), nutriacholic acid and alpha-fetoprotein (AFP) were independent risk factors for tumor recurrence (P < 0.01). A prognostic fingerprint was established as a nomogram, which divided the patients into low risk (n = 45), moderate risk (n = 48) and highrisk groups (n = 29) with discriminated prognosis (P < 0.001). In patients fulfilling the Hangzhou criteria, the fingerprint/nomogram could also successfully stratify the patients into two groups with different recurrence risk (P < 0.05).ConclusionsThe established pre-operative plasma fingerprint/nomogram is efficient in the prediction of recurrence risk, which could facilitate candidate selection in liver transplantation for HCC.     

From tissue phenotype to proteotype: sensitive protein identification in microdissected tumor tissue

Correlation of disease phenotype with protein profile (proteotype) is a significant challenge for biomedical research. The main obstacles have been the need to insure sufficient quantities of pure protein sample, the reproducibility of protein display, and rapid and accurate protein identification. We present a modified approach that combines enhanced detection sensitivity with tissue microdissection from frozen primary renal cancer tissues of different histological subtypes, followed by 2D gel analysis and protein identification with MALDI mass spectrometry. We obtained reliable and highly consistent results in phenotypically similar tumors of each individual subtype by performing strict morphological control of the analyzed tumor cells without physical or chemical alteration of the frozen tissue samples. By application of non-oxidizing silver staining, proteins were resolved and identified with high levels of specificity and sensitivity. This new combination of techniques allows not only for sensitive identification of specific protein patterns that correspond to a histological tumor phenotype, but also for identification of specific disease-associated protein targets.