高尔基体蛋白73单独及联合甲胎蛋白检测在肝细胞癌诊断中的价值

目的探讨血清高尔基体蛋白(Golgi protein,GP)73单独及联合甲胎蛋白(AFP)检测在肝细胞癌(hepatocellular carcinoma,HCC)诊断中的价值。方法选择HCC、肝炎、非HCC的其他肿瘤患者和健康人群,分别以酶联免疫吸附试验检测GP73水平,电化学发光法检测AFP水平。结果 HCC组GP73水平为(231.2±92.3)ng/ml,明显高于肝炎组、其他肿瘤组和健康对照组,差异有统计学意义(P0.005)。GP73在81.08 ng/ml处获得最大约登指数,此时诊断HCC的灵敏度和特异度分别为86.2%和87.8%,高于AFP诊断的价值。GP73联合AFP诊断HCC,可使诊断灵敏度进一步提高至92.3%。结论 GP73作为一种新型HCC血清标记物在HCC诊断中有较高的灵敏度和特异度,且优于AFP。GP73联合AFP检测可进一步提高HCC诊断的灵敏度。     

乙型肝炎病毒剪接特异性蛋白在乙肝病毒感染相关肝细胞癌中的表达及意义

目的 观察乙型肝炎病毒剪接特异性蛋白(HBSP)在乙肝病毒(HBV)感染相关肝细胞癌(HCC)中的表达及意义.方法 选取HBV感染肝脏疾病患者152例,其中慢性HBV携带者(CHBC)40例、慢性乙型肝炎(CHB)患者42例、肝硬化(LC)患者38例、HCC患者32例,采用实时定量PCR法检测HBSP水平,荧光定量法检...     

高尔基体蛋白73定量测定对肝细胞癌的诊断价值

目的：探讨血清高尔基体蛋白（GP73）检测用于肝细胞癌（HCC）辅助诊断的可行性。方法选择HCC患者145例（ HCC组）、肝炎与肝硬化患者128例（良性肝病组）、其他消化系统恶性肿瘤患者87例（肿瘤对照组）及健康体检者99例（健康对照组）,应用ELISA方法测定血清GP73,化学发光法测定甲胎蛋白（AFP）,计算二者单独检测与联合检测诊断HCC的敏感度和特异度。对HCC患者进行手术切除治疗,比较治疗前后血清GP73的变化情况。结果 HCC组血清GP73水平明显高于良性肝病组、肿瘤对照组和健康对照组（ P均＜0．01）。单项检测GP73的敏感度和特异度分别为71．0％、85．4％,AFP分别为46．2％、80．3％;联合检测GP73和AFP的敏感度和特异度分别为82．8％、78．3％。 HCC治疗后GP73水平较治疗前显著降低（P＜0．01）。结论 GP73对HCC有较好的诊断性能,可作为恶性肝病的独立指标与AFP互补应用于临床。     

用飞行质谱技术筛选肝棘球蚴病患者血清蛋白质组学标记物

目的 筛选肝棘球蚴病患者血清蛋白质组学标记物,建立血清蛋白质指纹图诊断模型,评价其应用价值.方法 肝棘球蚴病患者68例,对照组73例(其他肝病患者33例,健康人40例),将全部样品分为训练组(37例)和测试组(67例).用弱阳离子交换蛋白芯片结合表面增强激光解析电离飞行时间质谱(SELDI-TOF-MS)技术检测肝棘球蚴病患者和对照者的血清蛋白质谱.分别比较训练组中37例肝棘球蚴患者和37例对照者、5例肝囊型棘球蚴病(HCE)患者和5例肝泡球蚴病(HAE)患者、8例肝棘球蚴病患者手术前后两组血清蛋白质峰的差异.利用ZJU-PDAS软件进行数据处理,通过支持向量机(SVM)运算建立蛋白质指纹图诊断模型,并用测试组标本采用盲法对模型的灵敏度和特异度进行验证.结果 肝棘球蚴病组和对照组共筛选出9个差异蛋白峰,其中相对分子质量为1044、1047、1073、1075、1338、6453、6649、8714 m/z的8个蛋白质峰在病例组中下调,相对分子质量为5651 m/z的蛋白峰在病例组中上调(P<0.05),盲法验证表明所建模型对肝棘球蚴病诊断的灵敏度为77.4%(24/31),特异度为66.7%(24/36);阳性预测值为66.7%(24/36),阴性预测值为77.4%(24/31).HCE和HAE患者之间筛选出2个差异表达蛋白峰,质荷比分别为8716和2751 m/z(P<0.05);8例肝棘球蚴病患者手术前后两组共筛选出6个差异表达蛋白质峰,相对分子质量分别为1297、1505、1525、1534、5921,5941 m/z(P<0.05).结论 SELDI-TOF-MS技术结合生物信息学方法能筛选出肝棘球蚴病患者血清蛋白质组学标记物,对肝棘球蚴病诊断及预后判断具有潜在的应用价值.     

SELDI-TOF-MS技术在肝癌诊断和介入治疗评价中的价值

目的:建立肝癌血清学诊断模型,探讨评估SELDI-TOF-MS技术在肝癌诊断和介入治疗评价中的价值.方法:用弱阳离子交换芯片(CM10芯片)和表面增强激光解吸电离飞行时间质谱仪(surface-enhanced laser desorption ionization time-of-flight mass spectrometry,SELDI-TOF-MS)技术,测定60例肝癌患者和60例正常对照者的血清蛋白质指纹图谱,应用BiomarkerWizard统计软件比较肝癌组和正常对照组血清蛋白质表达的差异性,采用Biomarker Pattern软件分析数据建立肝癌诊断模型,比较介入治疗前后血清蛋白质指纹图谱的差异性.结果:在质荷比(M/Z)为2000-10000范围内,和正常血清比较,肝癌的差异峰有3个(M/Z为4182Da、5710Da、6992Da;P<0.01),4182Da和5710Da下调,6992Da上调.用这3个差异蛋白峰建立肝癌诊断模型,诊断肝癌的灵敏度为93.3%(28/30),特异度为90.0%(27/30),正确率为91.7%(55/60),约登指数为0.833.差异蛋白峰(M/Z4182Da)在介入术后1mo明显上调(P<0.05).结论:应用SELDI-TOF-MS技术进行肝癌血清蛋白质指纹图谱分析,建立肝癌诊断树模型,对肝癌的诊断有一定的价值;筛选出的差异蛋白峰对肝癌的介入治疗评估有一定的应用价值.     

蛋白芯片联合SELDI-TOF-MS在卵巢癌诊断中的应用

目的用蛋白芯片联合表面增强激光解析离子化/飞行时间质谱（SELDI-TOF-MS）分析卵巢癌与对照血清中的差异表达蛋白来筛选与卵巢癌早期诊断和预后相关的肿瘤标志物。方法采用联合SELDI-TOF-MS及WXC2蛋白质芯片,对21例卵巢癌患者（实验组）及24例健康妇女（对照组）血清标本进行检测。结果在相对分子质量0~50 000 Da范围内,检测出69个差异蛋白峰。卵巢癌差异表达明显（P〈0.01）的蛋白峰8个,其中高表达的波峰3个,质荷比分别为5 927.6,8 719.3和11 729.8 Da,低表达的波峰5个,质荷比分别为4 073.8,4 158.4,4 186.7,4 290.2和8 162.5 Da。其中11 729.8 Da蛋白峰已经鉴定为血清淀粉样蛋白A1（SAA1）。结论SELDI-TOF-MS联合蛋白质芯片能够直接检测出卵巢癌患者血清中相对特异的蛋白峰,对于卵巢癌的诊断具有一定的临床意义。     

原发性肝癌血清蛋白质谱图人工神经网络诊断模型研究

目的建立早期有效检测原发性肝癌的实验指标。方法利用表面增强激光解析电离飞行时间质谱（SELDI—TOF—MS）技术及其配套的金芯片（GoldChip）检测435份血清蛋白质谱数据,并将其分为训练集和验证集两组。训练集用于筛选原发性肝癌的差异蛋白标志物并建立ANN诊断模型,验证集用于模型诊断效度的盲法验证。结果共发现7个有明显表达差异的标志蛋白。用其建立ANN诊断模型对原发性肝癌进行盲法验证,诊断的灵敏度和特异度分别为84．00％和81．25％,受试者工作特征曲线（ROC曲线）下面积（AUC）为0．847,阴性预测值94．20％,阳性预测值58．33％,准确度为81．90％。结论原发性肝癌患者血清具有明显表达差异的特征蛋白,据其建立的人工神经网络模型可为原发性肝癌的诊断提供新方法,有重要的参考价值。     

胰腺癌相关糖尿病的血清蛋白质组学分析

目的 检测胰腺癌相关糖尿病的血清蛋白标志物,并建立诊断模型.方法 应用表面增强激光解析电离飞行时间质谱( SELDI-TOF-MS)技术检测17例胰腺癌相关糖尿病与17例新发2型糖尿病、17例健康对照者血清的差异表达蛋白,用Biomarker Patterns Software 5.0软件建立胰腺癌相关糖尿病诊断模型并验证.结果 在胰腺癌相关糖尿病、新发2型糖尿病,健康者各10例的蛋白指纹图谱中筛选出12个差异表达蛋白峰,其中质荷比为6116、6695、8936 Da的蛋白峰被选为建立胰腺癌相关糖尿病诊断模型的蛋白峰.该诊断模型的诊断正确率为90％.盲法验证各组另7例样本,正确诊断胰腺癌相关糖尿病患者达100％,新发2型糖尿病患者为71％,健康人群为86％.经检索蛋白质数据库,与以上3种差异表达蛋白分子质量最为接近的蛋白分别为金属硫蛋白、胰腺干细胞增殖分化因子和成纤维细胞生长因子 1.结论 通过SELDI方法筛选出3种胰腺癌相关糖尿病的血清蛋白标志物,建立了可靠的胰腺癌相关糖尿病的诊断模型.     

血清生长分化因子15和甲胎蛋白联合检测对HBV相关肝细胞癌的诊断价值

目的探讨血清生长分化因子15(GDF15)和AFP联合检测对诊断HBV感染相关肝细胞癌(HCC)的临床价值。方法选取2019年3月1日-2019年9月1日在武汉大学人民医院诊治的患者和健康体检者共225例,其中HBV感染导致的HCC患者(HCC组)97例,慢性乙型肝炎患者(CHB组)41例,健康体检者(NC组)87例,分别测定三组人群的GDF15和AFP水平。计量资料采用单样本Kolmogorov-Smirnov法检验各组数据是否符合正态性,正态分布资料多组间比较采用方差分析,进一步两两比较采用LSD-t检验;非正态分布资料多组间比较采用Kruskal-Wallis H检验,两两比较采用Mann-Whitney U检验。计数资料采用χ2检验。采用二元logistic回归分析得到GDF15和AFP联合的回归模型,并绘制GDF15和AFP单独或联合检测的ROC曲线,计算曲线下面积及灵敏度、特异度和约登指数。结果HCC组、CHB组和NC组的GDF15和AFP水平差异均有统计学意义(χ2值分别为53.77、119.12,P值均<0.01);HCC组GDF15水平明显高于CHB组和NC组(P值均<0.01);HCC组和CHB组AFP水平均显著高于NC组,且HCC组AFP水平显著高于CHB组,差异均有统计学意义(P值均<0.01)。ROC曲线分析显示,GDF15、AFP及二者联合诊断HCC的曲线下面积、灵敏度和特异度分别为0.752、74.0%和68.3%,0.660、45.8%和85.4%,0.816、88.4%和68.5%。结论GDF15和AFP联合检测可以提高HBV相关HCC的诊断性能,具有较高的临床价值。     

DNA损伤修复基因hOGG1的遗传多态与乙肝相关性HCC的风险

目的:探讨DNA损伤修复基因hOGGI的遗传多态Ser326Cys与肝细胞癌(HCC)易感性的关系．方法:应用基因测序分型方法,分析96例HCC患者和96例健康对照hOGG1的遗传多态及与HBV感染的交互作用．结果:HCC病例组的Cys／Cys,Cys／Ser和Ser／Ser基因型分别为20．9％,44．2％和34．9％．Ser／Cys杂合子个体的OR值为1．5,Cys／Cys纯合子个体的OR值为1．9,明显高于Ser/Ser个体,表现出剂量效应．HBV感染者发生HCC的相对风险度是非HBV感染者的9倍(OR=9．2;95％CI 0．99-5．9)．对于HCC,hOGG1-Ser326Cys变异或HBV感染单一因素的OR值分别为5．5 (95％CI 0．7-240．1)和10．9(95％CI1．6-453．3),但携带变异基因者如果感染HB V,OR值则高达27．8(95％CI4．7-970．2)．结论:DNA修复基因hOGG1的Cys等位基因可能增加HCC的遗传易感性,他与HBV协同在乙肝相关性HCC的发生中起着重要作用．     

应用SELDI-TOF-MS技术建立肝癌筛选血清蛋白质指纹图谱模型

目的:建立肝癌筛选血清蛋白质指纹图谱模型．方法:用表面加强激光解析电离飞行时间质谱技术(SELDI-TOF-MS)及WCX2蛋白芯片获得新发肝癌、肝硬化患者和正常人血清的蛋白质指纹图谱,用计算机软件进行比较分析,建立肝癌的筛选模型．结果:肝癌患者与健康对照组血清蛋白质指纹图谱之间有5个标志蛋白(4477,8943,5181, 8617,13 761 Da)在肝癌患者血清中高表达,肝癌患者与肝硬化患者血清蛋白质指纹图谱之间2个标志蛋白(4477,13 761 Da)在肝癌患者血清中高表达,1个标志蛋白(4097 Da)在肝癌患者血清中低表达．SELDI-TOF-MS技术的特异性(60／60,100％);敏感度(18／20,90％)．分析系统筛选出4477,8943,13 761,4097 Da标志蛋白建立的肝癌诊断模型．结论:建立的血清蛋白质指纹图谱模型能够区分肝癌与非肝癌患者,SELDI-TOF-MS在肝癌的诊断及肿瘤特异性蛋白质生物标志分子的筛选等方面具有一定价值．     

Prediction of chronic hepatitis B, liver cirrhosis and hepatocellular carcinoma by SELDI-based serum decision tree classification

PURPOSE: To screen potential serological biomarkers and develop decision tree classifications of chronic hepatitis B, liver cirrhosis (LC) and hepatocellular carcinoma (HCC), respectively, with high prediction score for improving diagnosis of liver diseases. METHODS: The total serum samples were randomly divided into three training sets (41 HBV and 35 health; 36 LC and 35 health; 39 HCC and 35 health) and three testing groups (34 HBV and 38 health; 18 LC and 52 health; 42 HCC and 47 health). Selected WCX2 protein chip capture followed by SELDI-TOF-MS analysis was applied to generate the serum protein profiles. Subsequently serum protein spectra were normalized and aligned by Ciphergen SELDI Software 3.1.1 with Biomarker Wizard including baseline subtraction, mass accuracy calibration, automatic peak detection. Once the intensities of selected significant peaks from the training data set were transferred to further BPS analysis, an optimized classification tree with sequence-decision was established to divide training data set into disease group and control group successfully. A double blind test was employed to determine the clinical sensitivity and clinical specificity of three models. RESULTS: After comparative analysis of SELDI based serum protein profile between the cases of disease and healthy, a HCC decision tree classification with sensitivity of 94.872% and specificity of 94.286%; a LC decision tree classification with sensitivity of 91.667% and specificity of 94.286% and a HBV decision tree classification with sensitivity of 95.122% and specificity of 94.286% were produced by BPS respectively. When three decision tree models were challenged by the double-blind test samples, clinical sensitivity and clinical specificity of these models were predicted in diagnosis of three liver diseases (HCC: 90.48 and 89.36%; cirrhosis: 100 and 86.5%; HBV: 85.29 and 84.21%). CONCLUSION: SELDI-based decision tree classifications showed great advantages over conventional serological biomarkers in the diagnosis of chronic hepatitis B, LC as well as HCC.     

Surface enhanced laser desorption/ionization profiling: New diagnostic method of HBV-related hepatocellular carcinoma

Background and Aim:  To screen for serum biomarkers of HBV-related hepatocellular carcinoma (HCC) and HBV-related liver cirrhosis (LC) in an attempt to seek a new method for differential diagnosis of HCC and LC using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) techniques.
Methods:  Using SELDI-TOF-MS, serum proteins/peptide profiles on the immobilized metal ion affinity capture (IMAC) protein chips were obtained from 29 HCC patients and 30 LC patients. Discriminant analysis was carried out to establish new diagnostic methods using protein/peptide peaks with or without α-fetoprotein (AFP).
Results:  Forty-five protein/peptide peaks changed much more in the HCC group than they did in the LC group. Discriminant analysis using the Wilcoxon rank-sum test showed high sensitivity and specificity in distinguishing HCC from LC. The most significantly differentiating peak, 3892, offered 69.0% sensitivity, 83.3% specificity and 80% positive predictive value in distinguishing HCC and LC. Interestingly, six HCC patients with negative serum AFP were confirmed by peak 3892. The combination of multi-protein peaks (m/z = 9297, 29 941) with AFP offered an 82.8% sensitivity, 93.3% specificity and 92.3% positive predictive value, which was much better than AFP alone ( P  = 0.013).
Conclusions:  Special proteins/peptides of serum may differentiate HBV-related HCC and HBV-related LC, indicating that SELDI-TOF-MS may be useful to distinguish HCC from LC with the proper discriminant analytical method. SELDI peak 3892 may be a complementary diagnostic marker to positive AFP for HCC and a potential marker for the diagnosis of AFP-negative HCC as well.     

New serum biomarkers for detection of HBV-induced liver cirrhosis using SELDT protein chip technology

AIM: To find new serum biomarkers for liver cirrhosis (LC)in chronic carriers of hepatitis B virus (HBV).METHODS: Surface enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry was used to discover biomarkers for differentiating HBV induced LC from non-cirrhotic cohorts. A training population of 25 patients with HBV-induced LC, 20 patients with HCC, and 25 closely age-matched healthy men, was studied.RESULTS: Two biomarkers with Mr 7 772 and 3 933 were detected in sera of non-cirrhotic cohorts, but not in patients with HBV-induced LC. A sensitivity of 80% for all LC patients,a specificity of 81.8% for all non-cirrhotic cohorts and a positive predictive value of 75% for the study population were obtained.CONCLUSION: These two serum biomarkers for HBVinduced LC might be used for diagnosis and assessment of disease progression.     

New serum biomarkers for detection of HBV-induced liver cirrhosis using SELDI protein chip technology

AIM: To find new serum biomarkers for liver cirrhosis (LC) in chronic carriers of hepatitis B virus (HBV). METHODS: Surface enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry was used to discover biomarkers for differentiating HBV induced LC from non-cirrhotic cohorts. A training population of 25 patients with HBV-induced LC, 20 patients with HCC, and 25 closely age-matched healthy men, was studied. RESULTS: Two biomarkers with M(r) 7 772 and 3 933 were detected in sera of non-cirrhotic cohorts, but not in patients with HBV-induced LC. A sensitivity of 80% for all LC patients, a specificity of 81.8% for all non-cirrhotic cohorts and a positive predictive value of 75% for the study population were obtained. CONCLUSION: These two serum biomarkers for HBV-induced LC might be used for diagnosis and assessment of disease progression.     

Evaluation of serum clusterin as a surveillance tool for human hepatocellular carcinoma with hepatitis B virus related cirrhosis

Background and Aim: Hepatocellular carcinoma (HCC) is a common human cancer worldwide. The levels of serum clusterin in HCC patients and its potential diagnostic significance is not clear. We aimed to evaluate the clinical use of serum clusterin levels as a surveillance tool for HCC with hepatitis B virus (HBV) related cirrhosis. Methods: Twenty‐two cases of healthy subjects, 31 cases of HBV carriers, 26 patients with chronic hepatitis B, 29 patients with cirrhosis, and 76 patients with HCC were enrolled in this study. Serum levels of clusterin were measured by a sandwich enzyme‐linked immunosorbent assay. Results: The serum clusterin levels in HCC patients were significantly lower than that in healthy, HBV carriers and chronic hepatitis B, but statistically higher than in cirrhosis patients. Receiver operator characteristic (ROC) curve indicated that a serum clusterin value of 50 µg/mL yielded the best sensitivity (91%) and specificity (83%) for differentiating HCC patients with HBV‐related cirrhosis from those with HBV‐related cirrhosis. The optimal alpha fetoprotein (AFP) cutoff value was 15 ng/mL and was inferior to the clusterin value of 50 µg/mL, the area under the ROC curves being 0.937 versus 0.781, respectively (P < 0.05). Conclusions: Serum clusterin was more sensitive and specific than serum AFP for differentiating HCC patients with HBV‐related cirrhosis from those with HBV‐related liver cirrhosis, and may be a useful surveillance tool of HCC based on HBV‐related cirrhosis.     

Screening serum hepatocellular carcinoma-associated proteins by SELDI-based protein spectrum analysis

AIM： To find out potential serum hepatocellular carcinoma （HCC）-associated proteins with low molecular weight and low abundance 13y SELDI-based serum protein spectra analysis, that will have much application in the diagnosis or differentiated diagnosis of HCC, as well as giving a better understanding of the mechanism of hepato-card nogenesis.
METHODS： Total serum samples were collected with informed consent from 81 HCC patients with HBV（＋）/ cirrhosis（＋）, 36 cirrhosis patients and 43 chronic hepatitis B patients. Serum protein fingerprint profiles were first generated by selected WCX2 protein chip capture integrating with SELDI-TOF-MS, then normalized and aligned by Ciphergen SELDI Software 3.1.1 with Biomarker Wizard..Comparative analysis of the intensity of corresponding protein fingerprint peaks in normalized protein spectra, some protein peaks with significant difference between H.CC and cirrhosis or chronic hepatitis B were found.
RESULTS： One hundred and twenty-eight serum protein peaks betweeri.2000 and 30000Da were identified under the condition of signal-to-noise 〉 5 and minimum threshold for cluster 〉 20%. Eighty-seven of these proteins were showed significant differences in intensity between HCC and cirrhosis （P 〈 0.05）. Of the above differential proteins, 45 proteins had changes greater than two-fold, including 15 upregulated proteins and 30 downregulated proteins i.n HCC serum. Between HCC and chronic hepatitis B, 9 of 52 differential proteins （P 〈 0.05） had intensities of more than two-fold, including 2 upregulated proteins and 7 downregulated proteins in HCC serum. Between cirrhosis and chronic hepatitis B, 28 of 79 significant differential proteins （P 〈 0.05） changes greater than two-fold in intensity, including 17 upregulated proteins and 11 downregulated proteins in cirrhosis serum. For the analysis of these leading differential proteins in subtraction difference mode among three diseases, the five common downregulated proteins in HCC serum （M/Z 287     

表面增强激光解析电离飞行时间质谱法筛选肺癌患者血清和肺泡灌洗液中标志蛋白的研究

目的 应用表面增强激光解析电离飞行时间质谱(SELDI-TOF-MS)技术筛选肺癌患者血清和BALF中的差异性表达蛋白,探讨是否可作为诊断肺癌的肿瘤标志物.方法 应用SELDI-TOF-MS技术通过弱阳离子交换蛋白芯片(WCX-2芯片)分别检测35例肺癌和18例肺部良性病变患者血清和BALF中的蛋白质质谱图,用Biomarker Pattern软件分析肺癌的差异蛋白并初步建立诊断模型,通过盲筛进一步验证诊断模型.结果 在肺癌患者血清中发现5个高表达的蛋白质波峰,选用其中质荷比为5639的差异蛋白波峰建立分类树模型,其诊断的敏感度为80%(28/35),特异度为78%(14/18).盲法验证的敏感度为85%(17/20),特异度为90%(9/10),粗符合率为87%(26/30),Youden指数为0.7.在肺癌患者BALF中发现8个高表达蛋白质波峰,选用其中质荷比为7976和11 809的差异蛋白波峰建立分类树模型,其诊断的敏感度为86%(30/35),特异度为72%(13/18).盲法验证的敏感度为90%(18/20),特异度为90%(9/1O),粗符合率为90%(27/30),Youden指数为0.8.平行试验结果显示两者联合应用时诊断肺癌的敏感度、准确率及特异度均为100%,具有互补作用.结论SELDI-TOF-MS技术可筛选出肺癌患者血清和BALF中差异性表达蛋白,作为一种肿瘤标志物,其诊断敏感度高,特异度好,尤其是BALF中差异性表达蛋白的测定可能具有较好的临床应用前景.

Abstract：

Objective To detect the protein markers in serum and bronchoalveolar lavage fluid (BALF) of the patients with lung cancer by surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) technology, and to explore if they can be used as markers for the diagnosis of lung cancer.Methods SELDI-TOF-MS technology and protein chips weak cation exchange (WCX-2 chip) were used to detect the protein mass spectrum in serum and BALF of 35 patients with lung cancer and 18 cases of benign pulmonary diseases.The different protein markers were analyzed by Biomarker Pattern Software and the initial diagnosis models were set up.The diagnosis models were verified further by blind screen to confirm the efficacy of diagnosis.Results Five protein peaks in the sera of the patients with lung cancer were significantly higher (P ＜ 0.05 ).The protein peak with a mass/charge ratio (M/Z)of 5639 was selected to establish the classification tree model.The sensitivity of diagnosis was 80% (28/35) and the specificity was 78% (14/18).The results verified by blind screen showed a sensitivity of 85% (17/20),a specificity of 90% (9/10), a crude accuracy (CA) of 87% ( 26/30 ) and Youden' s index (γ) of 0.7.Eight protein peaks in the BALF of the patients with lung cancer were significantly higher ( P ＜ 0.05).The different protein peaks with M/Z of 7976 and 11 809 respectively were selected to establish the classification tree model.The sensitivity of diagnosis was 86% (30/35) and the specificity was 72% (13/18).The results verified by blind screen showed a sensitivity of 90% (18/20), a specificity of 90% (9/10), a CA of 90% (27/30) and γof 0.8.There was a complementary role in combination of differential proteins in serum and BALF and the sensitivity, specificity and accuracy of diagnosis for lung cancer were 100% by parallel test.Conclusions The SELDI-TOF-MS technology can screen out the differential protein markers in serum and BALF of the patients with lung cancer, which show high sensitivity and specificity as tumor markers.The differential proteins in the BALF may be more promising for clinical application.     

Application of Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry Coupled With an Artificial Neural Network Model for the Diagnosis of Hepatocellular Carcinoma

Background/Aims: There are no satisfactory biomarkers for hepatocellular carcinoma (HCC). The surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technique has been used to identify biomarkers for cancer. Methodology: Four hundred thirty five serum samples were tested by SELDI-TOF-MS matching on a gold chip. Samples were assigned to a training set and a testing set according to collection order. The training set was used to identify statistically significant peaks and to develop the artificial neural network (ANN) model for diagnosing HCC. The testing set was used in a blind test to validate the diagnostic efficiency of the ANN model. Results: A total of 75 proteins that differed between patients and controls were identified (p<0.05). Seven of these proteins (p<0.01; m/z at 4207Da, 6604Da, 7734Da, 8106Da, 8545Da, 8599Da, 8894Da) were chosen to develop the ANN model. The model was subjected to a blind test using the testing set for HCC diagnosis. Sensitivity and specificity were 84.00% and 81.25%, respectively, and the accuracy was 81.90%. Conclusions: These results suggest that patients with HCC may have serum proteins that differ from healthy controls. The ANN is a new method for diagnosing and identifying HCC.