代谢组学在结直肠癌诊断中的应用

结直肠癌是严重威胁人类健康的常见恶性肿瘤之一,代谢组学能有效地补充传统检查手段的不足。代谢组学通过检测肿瘤患者组织、血液及尿液中的代谢物,寻找差异代谢物从而发现新的特异性的肿瘤标志物。与正常细胞相比,肿瘤细胞存在着多个异常代谢通路。找出其代谢变化,为深入探讨结直肠癌生物标志物及其相关机制奠定了基础,对诊断和个体化治疗有着深远的意义。     

血清C反应蛋白神经元特异性烯醇化酶糖类抗原199及胃泌素释放肽前体联合检测在肺癌诊断中的应用价值

目的探讨C反应蛋白(CRP)、神经元特异性烯醇化酶(NSE)、癌胚抗原(CEA)、糖类抗原199(CA199)和胃泌素释放肽前体(Pro GRP)联合检测在肺癌诊断中的应用价值。方法选取2013年8月至2015年3月间确诊的67例肺癌患者作为肺癌组,选取同期收治的42例肺部良性疾病患者作为肺部良性疾病组,选取同期收治的41例健康体检者作为健康组。分别测定3组研究对象的血清CRP及肿瘤标志物水平。结果肺癌组患者NSE、CEA、CA199、和Pro GRP血清肿瘤标志物水平均高于肺部良性疾病组及健康组,差异均有统计学意义(均P<0.05)。肺癌组患者CRP水平显著高于健康组,差异有统计学意义(P<0.05)。CRP与血清肿瘤标志物联合检测可提高肺癌诊断的敏感性。结论 CRP与NSE等血清肿瘤标志物联合检测可提高对肺癌诊断的敏感性,具有临床应用价值。     

代谢组学在胃肠肿瘤诊断中的应用

代谢组学是继基因组学、转录组学和蛋白质组学之后发展起来的一门新的组学方法,因其独特的优势,已广泛应用到肿瘤诊断生物标志物的筛选之中.目前利用代谢组学方法在胃肠肿瘤患者组织、血液、尿液、粪便中已发现了一些诊断相关生物标志物,有助于胃肠恶性肿瘤的早期诊断及个体化治疗.     

基于UPLC-TOF/MS的小细胞肺癌患者血清代谢组学研究

目的 探索小细胞肺癌患者与健康人血清代谢组学差异,为小细胞肺癌的鉴定与分期寻找血清潜在生物标志物。方法 利用超高效液相色谱-飞行时间质谱联用仪(UPLC-TOF/MS)建立小细胞肺癌血清代谢图谱,采用EZinfo2.0软件进行主成分分析(Principal component analysis,PCA)、正交隐变量投影判别分析(Orthogonal partial least squares discriminant analysis,OPLS-DA)分析病例组和正常对照组之间的代谢差异。通过聚类分析并利用HMDB和METLIN数据库搜索差异物的精确质荷比,对一些具有显著性差异的物质进行初步的成分鉴别。结果 通过质谱分析和数据库检索筛选并鉴定出溶血性磷脂酰胆碱等10种差异性代谢产物,不同分期的小细胞肺癌患者轮廓分析存在甘氨胆酸等10种差异性物质。结论 小细胞肺癌患者与健康对照人群在血清代谢水平上具有明显差异,差异代谢物的发现为小细胞肺癌的鉴定以及分期寻找潜在标志物提供实验依据。     

血清肿瘤标志物在肺癌辅助诊断中的应用

背景与目的近年来,肺癌肿瘤标志物的研究不断取得进展,并逐步应用到临床上,本研究探讨6种血清肿瘤标志物在肺癌辅助诊断中的应用价值,并选择最理想的血清肿瘤标志物组合。方法应用酶联免疫吸附实验(ELISA)检测170例肺癌患者、80例健康人和80例肺部良性疾病患者血清中神经元特异性烯醇化酶(NSE)、胃泌素释放肽前体(pro-GRP)、细胞角蛋白19(CYFRA21-1)、鳞癌抗原(SCC)、p53抗体和癌抗原199(CA199)的含量。结果肺癌患者的6种血清肿瘤标志物水平均明显高于健康人组和肺部良性疾病组,差异均有统计学意义(P<0.01)。NSE、pro-GRP在小细胞肺癌中的水平明显高于其他类型的肺癌(P<0.01);CYFRA21-1、鳞癌抗原(SCC)在鳞癌中的水平明显高于其他类型的肺癌(P<0.01)。NSE、pro-GRP对小细胞肺癌检测的敏感性明显高于其他类型的肺癌(P<0.01);CYFRA21-1、鳞癌抗原(SCC)对鳞癌检测的敏感性明显高于其他类型的肺癌(P<0.01)。6种血清肿瘤标志物经组合后,敏感性明显高于任一单项肿瘤标志物(P<0.01)。结论6种血清肿瘤标志物对于肺癌的辅助诊断有一定的临床意义。NSE、pro-GRP二者可作为联合检测小细胞肺癌的标志物组合;CYFRA21-1、SCC可作为联合检测肺鳞癌的标志物组合。     

食管癌诊断中代谢组学应用进展

目的 食管癌在我国具有高发病率和高死亡率,找到早期筛查和诊断的方法是提高生存率的关键.代谢组学在肿瘤标志物的早期筛查中具有较为显著的优势.本研究总结代谢组学在食管癌早期诊断中的应用,探讨其发展方向和最新动态.方法 以"代谢组学、肿瘤、食管癌和诊断"为关键词,检索PubMed以及CNKI期刊全文数据库截至2016-10发表的相关文献,共检索到英文文献108篇,中文文献46篇.纳入标准:(1)代谢组学相关研究;(2)食管癌的诊断.根据纳入标准分析文献23篇.结果食管癌患者和健康个体之间确实存在代谢轮廓差异.目前研究人员已经证明了血清代谢组学和尿液代谢组学应用于食管癌的诊断和分期的可行性,并筛选出一部分异常的小分子代谢物,包括胆碱磷酸、谷氨酸盐、肌醇、腺苷、缬氨酸和γ氨基丁酸等.结论食管癌代谢组学研究已取得可喜的进展,但因为代谢组学技术和检测仪器的局限,得到的食管癌发病相关代谢物还不全面,还需进一步提高检测手段,改进研究方法,使代谢组学发挥更大的作用.     

代谢综合征与肺癌恶性程度的相关性探讨

目的:分析代谢综合征及其组分与肺癌恶性程度的相关性。方法:收集2017年01月至2019年04月我院收治的285例肺癌患者,根据是否合并代谢综合征,分为单纯肺癌组195例和肺癌合并代谢综合征组90例;根据是否合并心脑血管疾病,将90例代谢综合征合并肺癌患者分为肺癌并代谢综合征伴心脑血管疾病组65例及不合并心脑血管疾病组25例。采用独立样本ｔ检验分析两组患者间的年龄差异;卡方检验分析两组患者性别、吸烟史、病理类型、肿瘤分期的差异;Logistic回归分析代谢综合征各组分与肺癌肿瘤分期的相关性。结果:肺癌合并代谢综合征组患者的肿瘤分期明显高于单纯肺癌组,且存在显著性差异(P<0.05);血压异常（P=0.000）和血脂异常（P=0.042）对于肿瘤分期有显著影响,血糖异常（P=0.429）和体质量指数（P＝0.518）对肿瘤分期无显著影响;合并心脑血管疾病者其肿瘤分期较未合并基础疾病者无明显差异（P＝0.234）。结论:肺癌伴有代谢综合征者肿瘤恶性程度高,高血压和高血脂是肿瘤分期的危险因素,合并心脑血管疾病者肿瘤分期与未合并者无统计学差异。     

血清CEA、CA153和CA125联合检测对肺癌的诊断价值

目的:探讨血清肿瘤标志物CEA、CA153和CA125单项和联合检测对肺癌的诊断价值.方法:采用化学发光方法分别检测75例肺癌患者、60例良性肺部疾病患者和70例健康对照者血清中CEA、CA153和CA125水平,并分析上述3项指标在肺癌诊断中的敏感度和特异性.结果:肺癌患者3项肿瘤标志物血清水平均高于良性肺部疾病患者和健康对照者,差异具有统计学意义(P＜0.Ol).3项标志物的联合检测诊断肺癌的敏感度高于单项标志物检测,其敏感度高达88％,特异性为76.2％.结论:3项肿瘤标志物联合检测可提高诊断肺癌的敏感度.     

肿瘤代谢标志物在肺癌液体活检中的研究进展

液体活检被逐渐应用于肺癌临床诊疗中。目前,随着代谢组学的发展,越来越多代谢标志物被认为是潜在的反映肿瘤发生发展的敏感标志物。本文概括了肺癌主要代谢途径的改变,包括葡萄糖代谢、氨基酸代谢、脂质代谢、鞘脂代谢、甘油磷脂代谢和嘌呤代谢。同时,本文综述了代谢标志物在肺癌早期诊断、预测疾病进展、评估化疗与免疫治疗疗效的作用,旨在为肿瘤诊疗提供有效的标志物。     

血清肿瘤标志物在肺癌辅助诊断中的应用

目的探讨5种血清肿瘤标志物在肺癌辅助诊断中的应用价值,并选择最理想的血清肿瘤标志物组合。方法应用酶联免疫吸附实验(ELISA)检测170例肺癌患者、50例健康人和60例肺部良性疾病患者血清中神经元特异性烯醇化酶(NSE)、胃泌素释放肽前体(pro GRP)、细胞角蛋白19(CYFRA211)、p53抗体和癌胚抗原(CEA)的水平含量。结果肺癌患者的5种血清肿瘤标志物水平均明显高于健康人组和肺部良性疾病组,差异有统计学意义(P<0.01)。NSE、pro GRP在小细胞肺癌中的水平明显高于其他类型的肺癌(P<0.01),CYFRA211在鳞癌中的水平明显高于其他类型的肺癌(P<0.01)。p53抗体的特异性为100%,NSE、pro GRP对小细胞肺癌检测的敏感性明显高于其他类型的肺癌(P<0.01),CYFRA211对鳞癌检测的敏感性明显高于其他类型的肺癌(P<0.01)。5种血清肿瘤标志物经组合后,敏感性明显高于任一单项肿瘤标志物(P<0.01)。结论5种血清肿瘤标志物对于肺癌的辅助诊断有一定的临床意义。NSE、pro GRP二者可作为联合检测小细胞肺癌的首选标志物,CYFRA211、CEA和p53抗体三者可作为联合检测非小细胞肺癌的首选标志物。p53抗体对肺癌的辅助诊断有很高的特异性,CYFRA211对鳞癌的辅助诊断有一定的作用。     

A metabolomic approach to lung cancer

Lung cancer is one of the most common cancers in the world, but no good clinical markers that can be used to diagnose the disease at an early stage and predict its prognosis have been found. Therefore, the discovery of novel clinical markers is required. In this study, metabolomic analysis of lung cancer patients was performed using gas chromatography mass spectrometry. Serum samples from 29 healthy volunteers and 33 lung cancer patients with adenocarcinoma (n = 12), squamous cell carcinoma (n = 11), or small cell carcinoma (n = 10) ranging from stage I to stage IV disease and lung tissue samples from 7 lung cancer patients including the tumor tissue and its surrounding normal tissue were used. A total of 58 metabolites (57 individual metabolites) were detected in serum, and 71 metabolites were detected in the lung tissue. The levels of 23 of the 58 serum metabolites were significantly changed in all lung cancer patients compared with healthy volunteers, and the levels of 48 of the 71 metabolites were significantly changed in the tumor tissue compared with the non-tumor tissue. Partial least squares discriminant analysis, which is a form of multiple classification analysis, was performed using the serum sample data, and metabolites that had characteristic alterations in each histological subtype and disease stage were determined. Our results demonstrate that changes in metabolite pattern are useful for assessing the clinical characteristics of lung cancer. Our results will hopefully lead to the establishment of novel diagnostic tools.     

Diagnosis of Lung Cancer Based on Plasma Metabolomics Combined with Serum Markers

Predicting the onset and metastasis of early tumor is the primary means of improving lung cancer prognosis. The purpose of this study was to identify the ability of plasma metabolomics combined with blood markers to establish benign lung disease versus lung cancer regression models. Blood samples were collected from 174 lung cancer patients, 350 benign lung disease patients and 100 healthy volunteers and the metabolites were analyzed by mass spectrometry. The target metabolites consisted of 23 amino acids, 26 acylcarnitines and 45 conventional blood markers. A regression analysis model was established based on 12 metabolites and five blood markers selected by elastic network analysis. Two-thirds of the data were used in a training set for modeling and signature construction, and the remaining one-third were used in a validation set to test the model. This model was identified to have good specificity and sensitivity in distinguishing between lung cancer and lung disease. The performance of the model was evaluated using the area under the receiver operating curve, which was 0.915 in training set and 0.875 in validation set. In conclusion, this study demonstrates that regression model established by plasma metabolomics in combination with conventional serum markers has potential for the diagnosis of lung cancer.     

Diagnosis of renal cancer by molecular urinalysis

BACKGROUND: Organ-confined renal malignancies can be cured in the majority of patients, whereas more extensive lesions have a poor prognosis. We sought to develop a noninvasive test for renal cancer detection based on a novel molecular approach. METHODS: Matched urine and serum DNA samples were obtained before surgery from 30 patients with clinically organ-confined solid renal masses (25 with malignant tumors and five with tumors of low malignant potential) and were subjected to microsatellite analysis. Serum samples and urine samples obtained from 16 individuals without clinical evidence of genitourinary malignancy served as controls. RESULTS: Nineteen (76%) of the 25 patients with malignant tumors were found to have one or more microsatellite DNA alterations in their urine specimen, and 15 (60%) were found to have alterations in their serum DNA by microsatellite analysis. In every case, the microsatellite changes in urine or serum were identical to those found in the primary tumor. Three of five patients with tumors of low malignant potential were found to have DNA alterations in their urine, but none displayed alterations in their serum. Moreover, microsatellite alterations were not identified in either the urine or the serum samples from normal control subjects and patients with hematuria due to nephrolithiasis (renal stones). CONCLUSION: These data suggest that microsatellite DNA analysis of urine specimens provides a potentially valuable tool for the early detection of resectable kidney cancer. Furthermore, microsatellite analysis of serum samples reveals evidence of circulating tumor-specific DNA in approximately half of these patients and may reflect the propensity of these tumors to spread to distant sites at an early stage.     

Cancer-specific proteins and their application in the diagnosis of lung cancer

Thin slab PAGE was used to analyze 588 normal serum samples, 134 lung cancer samples and 68 noncancer lung diseases samples to determine whether distinct protein bands could be classified as tumor markers. Three distinct bands were noted. The band most frequently seen in the sera of lung cancer patients was of the molecular weight of 175, 000 Doltons while a band of 115,000 Doltons appeared with the sera of normal and noncancerous lung disease patients. These bands were termed “tumor positive” and “tumor negative” markers respectively. The tumor negative marker protein reacted readily with anti-C3, and it was called complement-related protein or Rc3. The tumor positive marker corresponded to lung cancer in 78.4% of cases; the false positive rates for normal and non-cancer lung diseases were 6% and 11%, respectively. The sensitivity of this method was 78.4% (S=78%); specificity was 86% (F=86%.)     

不同标本肿瘤标志物联合检测对肺癌的诊断价值

目的：检测血液、痰液、支气管肺泡灌洗液（BALF）、胸腔积液四种标本中癌胚抗原（CEA）、癌抗原125（CA125）、癌抗原199（CA199）和细胞角蛋白21—1片段（CYFRA21—1）的浓度,探讨不同标本肿瘤标志物（TM）联合检测在肺癌诊断中的意义。方法：采用化学发光免疫分析法检测52例肺癌和46例肺部良性病变患者血液、痰液、BALF、胸腔积液中CEA、CA125、CA199和CYFRA21—1的浓度。结果：52例肺癌患者血液、痰液、BALF、胸腔积液中四种TM联合检测的阳性率分别为69．2％、90．4％、88．5％和82．1％;而46例肺部良性病变患者的阳性率分别为19．6％、26．1％、23．9％、21．7％。经统计学检验两组问四种标本TM联合检测阳性率差异有统计学意义（P〈0．05）。肺癌组不同标本之间TM联合检测的阳性率差异有统计学意义（P=0．02）;痰液和BALF标本TM联合检测较血液临床意义更大（P=0．01;P=0．02）。联合两个或三个标本检测与单个血液标本检测相比,其差异有统计学意义（P〈0．05）。结论：不同标本肿瘤标志物CEA、CA125、CA199和CYFRA21—1联合检测对肺癌的诊断具有一定的意义。联合不同标本检测四种TM能提高肺癌诊断的敏感性。     

肿瘤标志物联合检测对肺癌的诊断价值

目的探讨血清肿瘤标志物细胞角蛋白19片段(CYFRA21-1)、神经元特异性烯醇化酶(NSE)、癌胚抗原(CEA)、糖蛋白抗原125(CA125)、恶性肿瘤特异性生长因子(TSGF)联合检测对肺癌的诊断价值。方法采用电化学发光法检测76例肺癌患者、90例肺部良性病变患者和86例健康体检者血清中的5种肿瘤标志物,并用统计学方法对比分析。结果肺癌患者组5种肿瘤标志物水平明显高于肺良性病变组和健康体检组,差异有高度统计学意义(P<0.01)。结论 CYFRA21-1、NSE、CEA、CA125和TSGF5种肿瘤标志物联合检测可有效提高肺癌诊断的敏感性,对肺癌早期诊断有重要的临床意义。     

Distinct glycosylation of serum proteins in patients with cancer: brief communication.

Concanavalin A and wheat germ agglutinin, lectins that interact with serum glycoprotein in a manner similar to the antigen--antibody reaction, were used as "antibodies" in a single radial immunodiffusion technique to test a coded serum panel (from the National Cancer Institute, Bethesda, Md., and the Mayo Clinic, Rochester, Minn.) containing a) 99 serum samples from patients with different types of malignant neoplasms of the gastrointestinal tract, prostate gland, and lung, b) 50 samples from patients with benign diseases of the same organs as those affected in the cancer patients, and c) 50 samples from apparently healthy smokers. The resulting precipitation rings were not correlated to serum protein concentration, and the differences (demonstrated by Student's t-test and with a generalization of the one-sided two-sample Kolmogorov-Smirnov statistic for evaluating diagnostic tests) established that serum glycoproteins are glycosylated differently in cancer patients than in people without cancer.     

Determination of various tumor markers, with special reference to sialyl SSEA-1 antigen in lung cancer

Tumor markers including sialyl SSEA-1 antigen (SLX) were measured in 77 patients with lung cancer and 116 patients with benign respiratory diseases. Increased levels of serum SLX were observed in 57.6% (19/33) of adenocarcinoma of the lung, and an overall positive rate was 42.9% (33/77) in lung cancer cases. The false positive incidence of SLX in the sera from the patients with non-malignant diseases was as low as 8.6%. Among other tumor markers determined, serum CA 19-9, CEA had a relatively high positive rate, but the false positive incidence were not low. In cases of poor prognostic cases of with adenocarcinoma of the lung, SLX levels became levels higher than the previous ones, but not in cases of other cell types were not. Not only in the patients with lung cancer but also in those with benign respiratory diseases such as bronchiectasis and lung fibrosis, high levels of SLX seemed to suggest poor prognosis. These results indicate that SLX may contribute for monitoring and prognosis of the cases of lung cancer and other respiratory diseases.     

Kidney tumor biomarkers revealed by simultaneous multiple matrix metabolomics analysis

Metabolomics is increasingly being used in cancer biology for biomarker discovery and identification of potential novel therapeutic targets. However, a systematic metabolomics study of multiple biofluids to determine their interrelationships and to describe their use as tumor proxies is lacking. Using a mouse xenograft model of kidney cancer, characterized by subcapsular implantation of Caki-1 clear cell human kidney cancer cells, we examined tissue, serum, and urine all obtained simultaneously at baseline (urine) and at, or close to, animal sacrifice (urine, tissue, and plasma). Uniform metabolomics analysis of all three "matrices" was accomplished using gas chromatography- and liquid chromatography-mass spectrometry. Of all the metabolites identified (267 in tissue, 246 in serum, and 267 in urine), 89 were detected in all 3 matrices, and the majority was altered in the same direction. Heat maps of individual metabolites showed that alterations in serum were more closely related to tissue than was urine. Two metabolites, cinnamoylglycine and nicotinamide, were concordantly and significantly (when corrected for multiple testing) altered in tissue and serum, and cysteine-glutathione disulfide showed the highest change (232.4-fold in tissue) of any metabolite. On the basis of these and other considerations, three pathways were chosen for biologic validation of the metabolomic data, resulting in potential therapeutic target identification. These data show that serum metabolomics analysis is a more accurate proxy for tissue changes than urine and that tryptophan degradation (yielding anti-inflammatory metabolites) is highly represented in renal cell carcinoma, and support the concept that PPAR-α antagonism may be a potential therapeutic approach for this disease.