Department of Medical Oncology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi, PR China.
Diagn Pathol. 2013 Aug 5;8:130. doi: 10.1186/1746-1596-8-130.
Hepatocellular carcinoma (HCC) is one of the most common cancers in the world,and the identification of biomarkers for the early detection is a relevant target. The purpose of the study is to discover specific low molecular weight (LMW) serum peptidome biomarkers and establish a diagnostic pattern for HCC.
We undertook this pilot study using a combined application of magnetic beads with Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) technique and ClinPro Tools v2.2 to detect 32 patients with HCC, 16 patients with chronic hepatitis (CH), 16 patients with liver cirrhosis (LC) and 16 healthy volunteers.
The results showed 49, 33 and 37 differential peptide peaks respectively appeared in HCC, LC and CH groups. A Supervised Neural Network (SNN) algorithm was used to set up the classification model. Eleven of the identified peaks at m/z 5247.62, 7637.05, 1450.87, 4054.21, 1073.37, 3883.64, 5064.37, 4644.96, 5805.51, 1866.47 and 6579.6 were used to construct the peptides patterns. According to the model, we could clearly distinguish between HCC patients and healthy controls as well as between LC or CH patients and healthy controls.
The study demonstrated that a combined application of magnetic beads with MALDI-TOF MB technique was suitable for identification of potential serum biomarkers for HCC and it is a promising way to establish a diagnostic pattern.
The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1503629821958720.
肝细胞癌(HCC)是世界上最常见的癌症之一,因此识别早期检测的生物标志物是一个相关的目标。本研究的目的是发现特定的低分子量(LMW)血清肽组生物标志物,并建立 HCC 的诊断模式。
我们使用磁珠与基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF MS)技术的组合,以及 ClinPro Tools v2.2 检测了 32 名 HCC 患者、16 名慢性肝炎(CH)患者、16 名肝硬化(LC)患者和 16 名健康志愿者,以进行这项初步研究。
HCC、LC 和 CH 组分别显示出 49、33 和 37 个差异肽峰。使用监督神经网络(SNN)算法建立分类模型。在 m/z 5247.62、7637.05、1450.87、4054.21、1073.37、3883.64、5064.37、4644.96、5805.51、1866.47 和 6579.6 处鉴定出的 11 个峰用于构建肽图谱。根据该模型,我们可以清楚地区分 HCC 患者和健康对照组,以及 LC 或 CH 患者和健康对照组。
该研究表明,磁珠与 MALDI-TOF MB 技术的联合应用适用于鉴定 HCC 的潜在血清生物标志物,这是建立诊断模式的一种很有前途的方法。
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