Freed Gary L, Cazares Lisa H, Fichandler Craig E, Fuller Thomas W, Sawyer Christopher A, Stack Brendan C, Schraff Scott, Semmes O John, Wadsworth J Trad, Drake Richard R
Department of Microbiology and Molecular Cell Biology, Center for Biomedical Proteomics, Eastern Virginia Medical School, 700 W. Olney Road, Norfolk, VA 23507, U.S.A.
Laryngoscope. 2008 Jan;118(1):61-8. doi: 10.1097/MLG.0b013e31814cf389.
A long-term goal of our group is to develop proteomic-based approaches to the detection and use of protein biomarkers for improvement in diagnosis, prognosis, and tailoring of treatment for head and neck squamous cell cancer (HNSCC). We have previously demonstrated that protein expression profiling of serum can identify multiple protein biomarker events that can serve as molecular fingerprints for the assessment of HNSCC disease state and prognosis.
An automated Bruker Daltonics (Billerica, MA) ClinProt matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer was used. Magnetic chemical affinity beads were used to differentially capture serum proteins prior to MALDI-TOF analysis. The resulting spectra were analyzed using postprocessing software and a pattern recognition genetic algorithm (ClinProt 2.0). An HNSCC cohort of 48 sera samples from 24 patients consisting of matched pretreatment and 6 to 12 month posttreatment samples was used for further analysis. Low-mass differentially expressed peptides were identified using MALDI-TOF/TOF.
In the working mass range of 1,000 to 10,000 m/z, approximately 200 peaks were resolved for ionic bead capture approaches. For spectra generated from weak cation bead capture, a k-nearest neighbor genetic algorithm was able to correctly classify 94% normal from pretreatment HNSCC samples, 80% of pretreatment from posttreatment samples, and 87% of normal from posttreatment samples. These peptides were then analyzed by MALDI-TOF/TOF mass spectometry for sequence identification directly from serum processed with the same magnetic bead chemistry or alternatively after gel electrophoresis separation of the captured proteins. We were able to compare this with similar studies using surface-enhanced laser desorption ionization (SELDI)-TOF to show this method as a valid tool for this process with some improvement in the identification of our groups.
This initial study using new high-resolution MALDI-TOF mass spectrometry coupled with bead fractionation is suitable for automated protein profiling and has the capability to simultaneously identify potential biomarker proteins for HNSCC. In addition, we were able to show improvement with the MALDI-TOF in identifying groups with HNSCC when compared with our prior data using SELDI-TOF. Using this MALDI-TOF technology as a discovery platform, we anticipate generating biomarker panels for use in more accurate prediction of prognosis and treatment efficacies for HNSCC.
我们团队的一个长期目标是开发基于蛋白质组学的方法，用于检测和利用蛋白质生物标志物，以改善头颈部鳞状细胞癌（HNSCC）的诊断、预后评估及治疗方案定制。我们之前已经证明，血清蛋白质表达谱分析能够识别多个蛋白质生物标志物事件，这些事件可作为评估HNSCC疾病状态和预后的分子指纹。
使用自动布鲁克道尔顿公司（马萨诸塞州比勒里卡）的ClinProt基质辅助激光解吸/电离飞行时间（MALDI-TOF）质谱仪。在进行MALDI-TOF分析之前，使用磁化学亲和珠对血清蛋白进行差异捕获。使用后处理软件和模式识别遗传算法（ClinProt 2.0）对所得光谱进行分析。使用来自24例患者的48份血清样本组成的HNSCC队列进行进一步分析，这些样本包括配对的治疗前样本以及治疗后6至12个月的样本。使用MALDI-TOF/TOF鉴定低质量差异表达肽。
在1000至10000 m/z的工作质量范围内，离子珠捕获方法分辨出约200个峰。对于弱阳离子珠捕获产生的光谱，k近邻遗传算法能够正确地将94%的正常样本与治疗前HNSCC样本区分开，80%的治疗前样本与治疗后样本区分开，87%的正常样本与治疗后样本区分开。然后通过MALDI-TOF/TOF质谱分析法对这些肽进行序列鉴定，可直接从使用相同磁珠化学方法处理的血清中鉴定，也可在对捕获的蛋白质进行凝胶电泳分离后鉴定。我们能够将此结果与使用表面增强激光解吸电离（SELDI）-TOF的类似研究进行比较，以表明该方法是此过程的有效工具，并且在我们团队的鉴定方面有一些改进。
这项使用新型高分辨率MALDI-TOF质谱联用珠分级分离的初步研究适用于自动化蛋白质谱分析，并且有能力同时鉴定HNSCC的潜在生物标志物蛋白。此外，与我们之前使用SELDI-TOF的数据相比，我们能够证明MALDI-TOF在鉴定HNSCC组方面有所改进。将这种MALDI-TOF技术用作发现平台，我们期望生成生物标志物组，用于更准确地预测HNSCC的预后和治疗效果。
