二维电泳和质谱技术鉴定肝癌血清差异表达的N-连接糖蛋白

缺乏有效的早期诊断方法是导致肝细胞癌(hepatocellular carcinoma, HCC)预后极差的主要原因之一.蛋白质异常糖基化与恶性肿瘤细胞侵袭、转移等生物学过程关系密切,人体内至少有50%的蛋白质发生了糖基化修饰.本实验采用IgY12去除血清高丰度蛋白、多植物凝集素亲和层析技术分别从20例肝癌和年龄、性别匹配的20例非癌慢性肝病患者血清中纯化N 连接糖蛋白、二维电泳分析差异表达的蛋白质斑点,质谱检测、生物信息学等技术鉴定了18个差异表达的糖蛋白和/或其异质体（12种高表达和6种低表达）.ExPASy数据库比对结果表明,本实验鉴定的糖蛋白质分子含有至少1个已报道的N 糖基化位点.这些差异表达的糖蛋白属于急性期反应蛋白,分别具有蛋白酶抑制、生物转运、凝血和纤溶等功能,表明肝癌的发生发展过程中机体产生的急性期反应物可能是潜在的肝癌血清标志物.     

18O标记法在定量蛋白质组学中的应用

基于质谱技术去识别和检测蛋白质表达差异是一个热点,有助于生物过程和体系的分子机制的研究。近年来各种基于质谱技术的定量蛋白质组学研究方法发展较快,相对其他方法而言,18O标记法是一种较为理想、相对容易实现并且在不断完善的体外标记方法,最近在定量蛋白质组学研究中应用较多。现对18O标记法原理、特点以及技术方法的优化和应用进展进行综述。     

激光捕获显微切割技术结合^18O标记定量蛋白质组技术在胃癌标志物筛查中的应用研究

建立一种更加精确地分离鉴定胃癌特异肿瘤标志物的定量蛋白质组学技术.首先采用激光捕获显微切割技术(LCM)纯化胃腺癌细胞及胃黏膜良性上皮细胞,将裂解的样本总蛋白经过1D SDS-PAGE预分离,然后采用17O/16O分别标记两种样本酶切后的多肽混合物.结合纳升级液相色谱(Nano-HPLC-MS/MS)定量地鉴定胃癌细胞和胃黏膜良性上皮细胞的差异表达蛋白.共筛选出78个差异表达蛋白,其中42个蛋白质在胃癌组织中表达上调,36个蛋白质下调.Western blot技术验证了其中几个差异蛋白(moesin,periostin,annexin A2,annexin A4)的表达,与蛋白质组学研究的结果一致.LOM技术结合18O稳定同位素标记的定量蛋白质组学技术,为研究胃癌发生机制、筛选胃癌的分子标志物提供了新的思路,亦为诸如胃癌等复杂体系蛋白质的分离鉴定提供了新的技术选择.     

Quantitative Proteomic Analysis of Formalin-fixed and Paraffin-embedded Nasopharyngeal Carcinoma Using iTRAQ Labeling,Two-dimensional Liquid Chromatography,and Tandem Mass Spectrometry

Formalin-fixed, paraffin-embedded (FFPE) tissue specimens represent a potentially valuable resource for protein biomarker investigations. In this study, proteins were extracted by a heat-induced antigen retrieval technique combined with a retrieval solution containing 2% SDS from FFPE tissues of normal nasopharyngeal epithelial tissues (NNET) and three histological types of nasopharyngeal carcinoma (NPC) with diverse differentiation degrees. Then two-dimensional liquid chromatography-tandem mass spectrometry coupled with isobaric tags for relative and absolute quantification (iTRAQ) labeling was employed to quantitatively identify the differentially expressed proteins among the types of NPC FFPE tissues. Our study resulted in the identification of 730 unique proteins, the distributions of subcellular localizations and molecular functions of which were similar to those of the proteomic database of human NPC and NNET that we had set up based on the frozen tissues. Additionally, the relative expression levels of cathepsin D, keratin8, SFN, and stathmin1 identified and quantified in this report were consistent with the immunohistochemistry results acquired in our previous study. In conclusion, we have developed an effective approach to identifying protein changes in FFPE NPC tissues utilizing iTRAQ technology in conjunction with an economical and easily accessible sample preparation method. (J Histochem Cytochem 58:517–527, 2010)     

Proteomic Differences Between Hepatocellular Carcinoma and Nontumorous Liver Tissue Investigated by a Combined Gel-based and Label-free Quantitative Proteomics Study

Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 × HCC versus 7 × nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n = 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies.Hepatocellular carcinoma (HCC)¹ currently is the fifth most common malignancy worldwide with an annual incidence up to 500 per 100,000 individuals depending on the geographic region investigated. Whereas 80% of new cases occur in developing countries, the incidence increases in industrialized nations including Western Europe, Japan, and the United States (1). To manage patients with HCC, tumor markers are very important tools for diagnosis, indicators of disease progression, outcome prediction, and evaluation of treatment efficacy. Several tumor markers have been reported for HCC, including α-fetoprotein (AFP) (2), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) (3), and des-γ-carboxyl prothrombin (DCP) (4). However, none of these tumor markers show 100% sensitivity or specificity, which calls for new and better biomarkers.To identify novel biomarkers of HCC, many clinical studies using “omics”-based methods have been reported over the past decade (5–6). In particular, the proteomics-based approach has turned out to be a promising one, offering several quantification techniques to reveal differences in protein expression that are caused by a particular disease. In most studies, the well-established 2D-DIGE technique has been applied for protein quantification followed by identification via mass spectrometry (7–15). Even if the quantification is very accurate and sensitive in this gel-based approach, the relatively high amount of protein sample necessary for protein identification is the major disadvantage of this technique. Several mass-spectrometry-based quantitative studies using labeling-techniques like SILAC (stable isotope labeling by amino acids in cell culture) or iTRAQ (isobaric tags for relative and absolute quantification) have also been carried out for biomarker discovery of HCC (16–18). Here, the concomitant protein quantification and identification in a mass spectrometer allows high-throughput analyses. However, such experiments imply additional labeling reactions (in case of iTRAQ) or are limited to tissue culture systems (in case of SILAC). In the latter case, one can overcome the limitation by using the isotope-labeled proteins obtained from tissue culture as an internal standard added to a corresponding tissue sample. This approach is known as CDIT (culture-derived isotope tags) and was applied in a HCC study, very recently (19). Label-free proteomics approaches based on quantification by ion-intensities or spectral counting offer another possibility for biomarker discovery. These approaches are relatively cheap compared with the labeling approaches, because they do not require any labeling reagents and furthermore they allow for high-throughput and sensitive analyses in a mass spectrometer. A quantitative study of HCC using spectral counting has been reported (20), whereas to our knowledge an ion-intensity-based study has not been performed yet. Apart from these quantification strategies, protein alterations in HCC have been studied by MALDI imaging, as well. Here, the authors could show that based on its proteomic signature, hepatocellular carcinoma can be discriminated with high accuracy from liver metastasis samples or other cancer types (21) as well as liver cirrhosis (22). Based on these results, it could be assumed that MALDI imaging might be a promising alternative to standard histological methods in the future.Here, we report a quantitative proteomic study that combines two different techniques, namely the well-established 2D-DIGE approach and a label-free ion-intensity-based quantification via mass spectrometry and liquid chromatography. To our knowledge this is the first time such a combined study was performed with regard to hepatocellular carcinoma. By comparing the results of both studies, we aim to identify high-confident biomarker candidates of HCC, as gel- and LC-MS-based techniques are complementary. To verify the differential protein expressions detected in our proteomic studies we performed additional immunological verifications for selected proteins within two different sample sets (Fig. 1).Open in a separate windowFig. 1.Schematic representation of the applied workflow.     

Labeling of Bifidobacterium longum Cells with 13C-Substituted Leucine for Quantitative Proteomic Analyses

Stable isotope labeling of amino acids in cell culture was used for Bifidobacterium longum. A comprehensive proteomic strategy was developed and validated by designing an appropriate semidefined medium that allows stable replacement of natural leucine by [¹³C₆]leucine. Using this strategy, proteins having variations of at least 50% in their expression rates can be quantified with great confidence.     

定量蛋白质组学中的同位素标记技术

定量蛋白质组学的目的是对复杂的混合体系中所有的蛋白质进行鉴定,并对蛋白质的量及量的变化进行准确的测定,是当前系统生物科学研究的重要内容。近年来,由于质谱技术和生物信息学的进步,定量蛋白质组学在分析蛋白质组或亚蛋白质组方面已取得了令人瞩目的成就,但其最显著的成就应该归功于稳定同位素标记技术的应用。该技术使用针对某一类蛋白具有特异性的化学探针来标记目的蛋白质或肽段,同时化学探针要求含有用以精确定量的稳定同位素信号。在此基础上,实现了对表达的蛋白质差异和翻译后修饰的蛋白质差异进行精确定量分析。综述了在定量蛋白质组学中使用的各种同位素标记技术及其应用。     

Quantitative Proteomic Analysis in Metastatic Renal Cell Carcinoma Reveals a Unique Set of Proteins with Potential Prognostic Significance

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC. We identified 1256 non-redundant proteins, and 456 of these were quantified. Further analysis identified 29 proteins that were differentially expressed (12 overexpressed and 17 underexpressed) in metastatic and primary RCC. Dysregulated protein expressions of profilin-1 (Pfn1), 14–3-3 zeta/delta (14–3-3ζ), and galectin-1 (Gal-1) were verified on two independent sets of tissues by means of Western blot and immunohistochemical analysis. Hierarchical clustering analysis showed that the protein expression profile specific for metastatic RCC can distinguish between aggressive and non-aggressive RCC. Pathway analysis showed that dysregulated proteins are involved in cellular processes related to tumor progression and metastasis. Furthermore, preliminary analysis using a small set of tumors showed that increased expression of Pfn1 is associated with poor outcome and is a potential prognostic marker in RCC. In addition, 14–3-3ζ and Gal-1 also showed higher expression in tumors with poor prognosis than in those with good prognosis. Dysregulated proteins in metastatic RCC represent potential prognostic markers for kidney cancer patients, and a greater understanding of their involved biological pathways can serve as the foundation of the development of novel targeted therapies for metastatic RCC.Renal cell carcinoma (RCC)¹ is the most common neoplasm of the adult kidney. Worldwide incidence and mortality rates of RCC are rising each decade (1). Seventy-five percent of kidney tumors are of the clear cell (ccRCC) subtype (2). Although modern imaging techniques for abdominal screening have led to increased incidental detection of renal tumors (3), unfortunately ∼25% to 30% of patients still have metastases at presentation.The prognosis with RCC is quite variable. The greatest risk of recurrence following nephrectomy is within the first 3 to 5 years (4). The ability to predict which tumors will metastasize would have a significant effect on patient outcomes, because the likelihood of a favorable response to treatment is greater when the metastatic burden is limited, and surgical resection of a single or limited number of metastases can result in longer survival (5). Furthermore, ∼3% of patients will develop a second primary renal tumor, either synchronous or metachronous. Currently, patient prognosis is assessed based on histological parameters and a multivariate analysis developed at Memorial Sloan Kettering (6), but neither is sufficiently accurate. A more accurate assessment of prognosis is urgently needed to better guide patient management.Although surgery can be curative for localized disease, many patients eventually relapse. Metastatic RCC is one of the most treatment-resistant malignancies, with chemotherapy and radiotherapy having limited effect. The five-year survival rate for metastatic RCC is ≤10% (7). Although there has been much progress in RCC treatment with the new era of antiangiogenic therapy, the majority of patients ultimately suffer a relapse and die from progression of the cancer. A more in-depth understanding of the pathogenesis of metastasis will be a cornerstone in the development of new targeted therapies. A number of prognostic markers have previously been identified based on comparative analysis of primary and metastatic tumors, including C-reactive protein, tetraspanin 7, hypoxia-inducible factor 1 α, phos-S6, U3 small nucleolar ribonucleoprotein protein, carbonic anhydrase IX, and microvascular density (8–14). However, no biomarker has yet had an established clinical role independent of stage (15). Differential protein expression between primary RCC and normal tissues was previously studied (16–18). Also, differential expression between primary and metastatic kidney disease has been investigated at the microRNA level (19, 20). Molecular analyses hold the promise of providing a better understanding of the pathogenesis of kidney cancer (21).In this study, we aimed to elucidate the pathogenesis of RCC metastasis through proteomic analysis and to identify potential prognostic markers for kidney cancer. We performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS to identify proteins that were dysregulated in metastatic RCC relative to primary RCC. Differential expressions of selected biologically interesting proteins—profilin-1 (Pfn1), 14–3-3 zeta/delta (14–3-3ζ), and galectin-1 (Gal-1)—were validated on two independent sets of tumors by means of western blot (WB) analysis and immunohistochemistry (IHC). Hierarchical clustering analysis showed that differential protein expression can distinguish between aggressive and non-aggressive tumors. In order to explore the role of these dysregulated proteins in tumor progression, we performed Gene Ontology (GO) and pathway analyses. In addition, we carried out a preliminary analysis to assess the potential of Pfn1, 14–3-3ζ, and Gal-1 as prognostic markers in RCC.     

Enhanced Interferon Signaling Pathway in Oral Cancer Revealed by Quantitative Proteome Analysis of Microdissected Specimens Using 16O/18O Labeling and Integrated Two-dimensional LC-ESI-MALDI Tandem MS

Oral squamous cell carcinoma (OSCC) remains one of the most common cancers worldwide, and the mortality rate of this disease has increased in recent years. No molecular markers are available to assist with the early detection and therapeutic evaluation of OSCC; thus, identification of differentially expressed proteins may assist with the detection of potential disease markers and shed light on the molecular mechanisms of OSCC pathogenesis. We performed a multidimensional ¹⁶O/¹⁸O proteomics analysis using an integrated ESI-ion trap and MALDI-TOF/TOF MS system and a computational data analysis pipeline to identify proteins that are differentially expressed in microdissected OSCC tumor cells relative to adjacent non-tumor epithelia. We identified 1233 unique proteins in microdissected oral squamous epithelia obtained from three pairs of OSCC specimens with a false discovery rate of <3%. Among these, 977 proteins were quantified between tumor and non-tumor cells. Our data revealed 80 dysregulated proteins (53 up-regulated and 27 down-regulated) when a 2.5-fold change was used as the threshold. Immunohistochemical staining and Western blot analyses were performed to confirm the overexpression of 12 up-regulated proteins in OSCC tissues. When the biological roles of 80 differentially expressed proteins were assessed via MetaCore™ analysis, the interferon (IFN) signaling pathway emerged as one of the most significantly altered pathways in OSCC. As many as 20% (10 of 53) of the up-regulated proteins belonged to the IFN-stimulated gene (ISG) family, including ubiquitin cross-reactive protein (UCRP)/ISG15. Using head-and-neck cancer tissue microarrays, we determined that UCRP is overexpressed in the majority of cheek and tongue cancers and in several cases of larynx cancer. In addition, we found that IFN-β stimulates UCRP expression in oral cancer cells and enhances their motility in vitro. Our findings shed new light on OSCC pathogenesis and provide a basis for the future development of novel biomarkers.Oral cancer is one of the most common cancers worldwide. In Taiwan, it remains the sixth most prevalent cancer overall and the fourth most common cancer to afflict males. Over the past 2 decades, the overall incidence and morbidity rates of patients with oral cancer have increased continuously. Epidemiological studies show that ∼50–70% of patients who undergo surgery for oral cancer die within 5 years (1–6). This poor prognosis predominantly reflects late stage presentation, secondary cancer occurrence, local recurrence, and metastasis (7) as well as the lack of suitable markers for cancer detection. Therefore, there is an urgent need to identify proteins that are dysregulated in patients with oral cancer. Such proteins would serve as a valuable resource to find markers for the early diagnosis and disease monitoring of patients with oral cancer.Oral cancer, a subtype of head-and-neck squamous cell carcinoma (HNSCC),¹ can form at various locations within the oral cavity, including the lips, tongue, buccal surfaces, gingiva, palate, floor of mouth, and oropharynx. Tongue and buccal cancers are the most common and most serious types of oral squamous cell carcinoma (OSCC) especially in southeast Asia (2, 8). Alcohol abuse, smoking, and betel nut chewing are the main risk factors for OSCC. Genome-wide approaches have revealed many epigenetic and genetic alterations in patients with OSCC, including several biochemical pathways (9–11). However, these studies have provided little information regarding alterations in the protein profiles of patients with OSCC. Recently state-of-the-art proteomics technologies have revealed alterations in protein abundance, posttranslational modification and turnover, and spatial and temporal distribution within tumor specimens. Using proteomics approaches, aberrantly expressed proteins have been identified in body fluids (12–14), frozen or paraffin-embedded tissues (15–18), and cultured cell lines (19–22). The fold changes in protein expression in samples from healthy and cancerous states as well as the roles of each protein in disease progression must be determined to identify potential candidates for biomarkers and therapeutic targets.Blood samples are often used in clinical studies because they are less invasive and more convenient than other types of bodily samples and can be analyzed using automatic and high throughput techniques. Unfortunately the extremely dynamic range of protein concentrations in serum and plasma impedes the direct discovery of potential biomarkers (23, 24). Proteins can be released into the blood from diseased tissues during cell death or via secretory pathways. To counteract this problem, serum and plasma biomarkers are sometimes identified by analyzing differential protein expression in tumors and adjacent normal tissues (25).Like many other types of solid tumors, OSCCs often contain heterogeneous cell populations. Laser capture microdissection (LCM) is a common technique used to dissect a particular tumor cell type from heterogeneous cell populations, thereby reducing the tissue complexity and facilitating the discovery of tumor-associated molecules in small samples (9, 26–28). Several laboratories have studied differential protein expression in microdissected tissue specimens from patients with head-and-neck cancer in efforts to discover novel tumor markers (15, 17, 29–31). However, the semiquantitative approaches used in these studies may have limited the number of potential markers identified as well as the reliability of the protein quantification. To minimize technical variations and improve the reliability of protein quantification, a variety of sophisticated stable isotope labeling techniques have been developed for MS-based proteomics analysis, including chemical (32, 33), metabolic (34, 35), and enzymatic (36–38) labeling techniques. Improvements in the quality and accuracy of quantitative proteomics analysis via such stable isotope labeling strategies have facilitated the discovery of potential tumor markers in malignancies such as OSCC/HNSCC (16, 39, 40).Here we describe a strategy consisting of LCM, ¹⁸O labeling, two-dimensional (2D) LC separation and an integrated ESI-MS/MS and MALDI-TOF/TOF MS (ESI-MALDI tandem MS) system. This strategy was used to identify differentially expressed proteins in OSCC cells microdissected from oral cancer tissue biopsies. A computational data analysis pipeline was also developed to calculate the relative abundances of ¹⁶O- and ¹⁸O-labeled peptides (similar to that described in a previous report (26)) and to assist with multidimensional protein identification and quantification. Using three pairs of OSCC specimens, we identified 1233 unique proteins with a false discovery rate less than 3%. Of these, we quantified 977 non-redundant proteins in which 80 proteins displayed ≥2.5-fold changes in expression in microdissected tumor cells versus non-tumor cells. We validated these results in 12 selected targets via immunohistochemical staining and Western blot analysis of OSCC tissues. Our findings reveal that the interferon (IFN) signaling pathway is significantly altered in OSCC lesions.     

HBV相关肝癌组织中微生物宏蛋白质组特征分析

越来越多的证据表明微生物菌群和肝脏疾病有着密切联系,但是HBV相关肝细胞癌(hepatitis B virus(HBV)-related hepatocellular carcinoma,HCC)人群肝脏组织内的微生物菌群种类和数量仍不清楚.本研究对来自165个HCC人群的肝癌组织和对应癌旁组织的质谱数据进行宏蛋白质组...     

Predicting Early Intrahepatic Recurrence of Hepatocellular Carcinoma after Microwave Ablation Using SELDI-TOF Proteomic Signature

Background/Aims

Despite great progress in the treatment of hepatocellular carcinoma (HCC) over the last-decade, intrahepatic recurrence is still the most frequent serious adverse event after all the treatments including microwave ablation. This study aimed to predict early recurrence of HCC after microwave ablation using serum proteomic signature.

Methods

After curative microwave ablation of HCC, 86 patients were followed-up for 1 year. Serum samples were collected before microwave ablation. The mass spectra of proteins were generated using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Serum samples from 50 patients were randomly selected as a training set and for biomarkers discovery and model development. The remaining serum samples were categorized for validation of the algorithm.

Results

According to preablation serum protein profiling obtained from the 50 HCC samples in the training set, nine significant differentially-expressed proteins were detected in the serum samples between recurrent and non-recurrent patients. Decision classification tree combined with three candidate proteins with m/z values of 7787, 6858 and 6646 was produced using Biomarker Patterns Software with sensitivity of 85.7% and specificity of 88.9% in the training set. When the SELDI marker pattern was tested with the blinded testing set, it yielded a sensitivity of 80.0%, a specificity of 88.5% and a positive predictive value of 86.1%.

Conclusions

Differentially-expressed protein peaks in preablation serum screened by SELDI are associated with prognosis of HCC. The decision classification tree is a potential tool in predicting early intrahepatic recurrence in HCC patients after microwave ablation.     

Genome-Wide and Differential Proteomic Analysis of Hepatitis B Virus and Aflatoxin B1 Related Hepatocellular Carcinoma in Guangxi,China

Both hepatitis B virus (HBV) and aflatoxin B1 (AFB1) exposure can cause liver damage as well as increase the probability of hepatocellular carcinoma (HCC). To investigate the underlying genetic changes that may influence development of HCC associated with HBV infection and AFB1 exposure, HCC patients were subdivided into 4 groups depending upon HBV and AFB1 exposure status: (HBV(+)/AFB1(+), HBV(+)/AFB1(-), HBV(-)/AFB1(+), HBV(-)/AFB1(-)). Genetic abnormalities and protein expression profiles were analyzed by array-based comparative genomic hybridization and isobaric tagging for quantitation. A total of 573 chromosomal aberrations (CNAs) including 184 increased and 389 decreased were detected in our study population. Twenty-five recurrently altered regions (RARs; chromosomal alterations observed in ≥10 patients) in chromosomes were identified. Loss of 4q13.3-q35.2, 13q12.1-q21.2 and gain of 7q11.2-q35 were observed with a higher frequency in the HBV(+)/AFB1(+), HBV(+)/AFB1(-) and HBV(-)/AFB1(+) groups compared to the HBV(-)/AFB(-) group. Loss of 8p12-p23.2 was associated with high TNM stage tumors (P = 0.038) and was an unfavorable prognostic factor for tumor-free survival (P =0.045). A total of 133 differentially expressed proteins were identified in iTRAQ proteomics analysis, 69 (51.8%) of which mapped within identified RARs. The most common biological processes affected by HBV and AFB1 status in HCC tumorigenesis were detoxification and drug metabolism pathways, antigen processing and anti-apoptosis pathways. Expression of AKR1B10 was increased significantly in the HBV(+)/AFB1(+) and HBV(-)/AFB1(+) groups. A significant correlation between the expression of AKR1B10 mRNA and protein levels as well as AKR1B10 copy number was observered, which suggest that AKR1B10 may play a role in AFB1-related hepatocarcinogenesis. In summary, a number of genetic and gene expression alterations were found to be associated with HBV and AFB1- related HCC. The possible synergistic effects of HBV and AFB1 in hepatocarcinogenesis warrant further investigations.     

应用iTRAQ标记技术结合2DLC-MS/MS分析家蝇幼虫免疫诱导后血淋巴蛋白质组

目的分析家蝇幼虫免疫诱导前后血淋巴中的免疫防御相关靶标,探索其先天性免疫机制。方法采用同位素标记及相对定量技术(isobaric tags for relative and absolute quantification,iTRAQ)结合2D LC-MS/MS对家蝇幼虫诱导前后的血淋巴蛋白质组进行研究。结果与对照组比较研究后共获得237个不同肽段,鉴定到13个具有定量信息的差异蛋白。免疫刺激后显著上调的蛋白有9个,下调蛋白4个(P0.05),对鉴定到的差异蛋白进行理化性质分析和GO(gene ontology)注释分析,发现这些蛋白分别具有抗菌、抗氧化、催化结合等功能,并参与了免疫、代谢、应激、转运等生物学过程,表明对家蝇幼虫经诱导后血淋巴中多种功能蛋白的表达发生了变化。结论 iTRAQ标记技术结合2D LC-MS/MS可以有效地分离鉴定昆虫血淋巴蛋白质组,为深入研究差异蛋白的功能奠定了基础。     

肝癌预后miRNA风险评分模型的鉴定和分析

肝细胞癌(hepatocellular carcinoma,HCC)是世界上高发病率和高死亡率的恶性肿瘤之一.研究目的是寻找HCC相关的mi RNA预后生物学标志物,预测HCC患者的风险程度和生存时间,为他们提供有效的预后信息.使用4种方法从TCGA中识别差异表达的mi RNAs(DEMs).并用Kaplan-Meier生存曲线、单因素和多因素Cox回归分析从DEMs中筛选肝癌预后相关的mi RNA.最终4个HCC的预后mi RNA生物学标志物(hsa-mi R-132-3p、hsa-mi R-139-5p、hsa-mi R-3677-3p、hsa-mi R-500a-3p)被筛选出来组合成一个风险评分模型.目前还没有实验证据表明组合中的hsa-mir-3677-3p与HCC相关,是本研究新发现的mi RNA.生存曲线、ROC曲线、卡方检验等多种生物信息学方法的评价结果均表明,该模型计算出的风险分值能有效预测患者的风险程度(P<0.000,风险比=2.551,95%置信区间=1.751-3.717).低风险组HCC患者1-5年生存率比高风险组高20%-30%.通过与临床数据分析发现,组合的生物学标志物较其他临床指标相比具有更好的预后效果,也可以作为独立的预后因子.最后,预测了4种mi RNA的靶基因,包括AGO2、FOXO1、ROCK2、RAP1B、CYLD等,并在细胞增殖、迁移、凋亡、免疫应答等生物学过程中富集.     

人肝细胞癌及其配对非癌肝组织、正常肝组织中热休克蛋白Hsp90基因mRNA水平的分析

 为定量分析和比较 2 2对人肝细胞癌 (HCC)及其配对非癌肝组织 (PNL)和 2例正常肝 (NL)组织中热休克蛋白Hsp(heatshockprotein) 90基因mRNA的表达水平 ,用狭缝杂交法检测hsp90 βmRNA的表达 ;并进一步用以特异性复合cRNA为内参照的定量RT PCR法对hsp90α和hspβmRNA的表达进行分析比较 .狭缝杂交结果显示 ,hsp90 βmRNA在 1 3例 ( 59 1 % )PNL中的表达平均升高至NL的 1 87倍 ;在 2 1例 ( 95 5% )HCC中的表达平均升高至NL的 3 45倍 ;在 2 0例 ( 90 9% )HCC中的表达平均升高至PNL的 2 75倍 .以cRNA为内参照的mRNA定量RT PCR结果显示 ,hsp90αmRNA在1 8例 ( 81 8% )PNL中的表达平均升高至NL的 3 0 6倍 ;在全部 2 2例HCC中的表达平均升高至至PNL的 2 0 8倍和NL的 5 1 0倍 .hsp90 βmRNA仅在小部分 ( 8例 ,36 4% )PNL中的表达轻度升高至NL的 1 2 7倍 ,而在全部 2 2例HCC中的表达显著升高至PNL的 2 95倍和NL的 2 52倍 .hsp90α和hsp90 β可能分别在人HCC发生、发展的不同阶段发挥不同的作用 ;以cRNA为内参照的定量RT PCR法是较狭缝杂交法更为灵敏、准确和快捷的mRNA定量分析方法 .     

实时定量PCR检测miRNA-29a在肝癌中的变化

目的:探讨微小RNA(miRNA)-29a在正常人和原发性肝癌患者血清,以及原发性肝癌患者的正常肝脏组织和肝癌组织中的表达.方法:应用荧光实时定量PCR方法检测miRNA-29a,在正常人和原发性肝癌患者血清水平.同时收集并检测原发性肝癌患者术中取得的正常肝脏组织和癌症组织中miRNA-29a的含量.结果:1)与正常人血清相比,miRNA-29a在原发性肝癌患者血清中水平没有明显改变(P＞0.05).2)与正常肝脏组织相比,原发性肝癌患者肝癌组织中miRNA-125含量明显降低,有统计学差异(P＜0.01).结论:MiRNA-29a在原发性肝癌患者的肝癌组织中表达显著降低,但患者的血清水平并没有明显改变.     

Quantitative Proteomic Analysis of Serum from Pregnant Women Carrying a Fetus with Conotruncal Heart Defect Using Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) Labeling

Objective

To identify differentially expressed proteins from serum of pregnant women carrying a conotruncal heart defects (CTD) fetus, using proteomic analysis.

Methods

The study was conducted using a nested case-control design. The 5473 maternal serum samples were collected at 14–18 weeks of gestation. The serum from 9 pregnant women carrying a CTD fetus, 10 with another CHD (ACHD) fetus, and 11 with a normal fetus were selected from the above samples, and analyzed by using isobaric tags for relative and absolute quantitation (iTRAQ) coupled with two-dimensional liquid chromatography-tandem mass spectrometry(2D LC-MS/MS). The differentially expressed proteins identified by iTRAQ were further validated with Western blot.

Results

A total of 105 unique proteins present in the three groups were identified, and relative expression data were obtained for 92 of them with high confidence by employing the iTRAQ-based experiments. The downregulation of gelsolin in maternal serum of fetus with CTD was further verified by Western blot.

Conclusions

The identification of differentially expressed protein gelsolin in the serum of the pregnant women carrying a CTD fetus by using proteomic technology may be able to serve as a foundation to further explore the biomarker for detection of CTD fetus from the maternal serum.