Correcting common errors in identifying cancer-specific serum peptide signatures

被引:168
作者
Villanueva, J
Philip, J
Chaparro, CA
Li, YB
Toledo-Crow, R
DeNoyer, L
Fleisher, M
Robbins, RJ
Tempst, P
机构
[1] Mem Sloan Kettering Canc Ctr, Dept Med, Dept Clin Labs, Engn Resource Lab,Prot Ctr,Mol Biol Program, New York, NY 10021 USA
[2] Spectrum Sq Associates, Ithaca, NY 14850 USA
关键词
serum; biomarkers; peptides; patterns; bias; mass spectrometry; peak alignment; specimen collection; sample processing;
D O I
10.1021/pr050034b
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
' Molecular signatures ' are the qualitative and quantitative patterns of groups of biomolecules (e.g., mRNA, proteins, pepticles, or metabolites) in a cell, tissue, biological fluid, or an entire organism. To apply this concept to biomarker discovery, the measurements should ideally be noninvasive and performed in a single read-out. We have therefore developed a pepticlomics platform that couples magnetics-based, automated solid-phase extraction of small peptides with a high-resolution MALDITOF mass spectrometric readout (Villanueva, J.; Philip, J.; Entenberg, D.; Chaparro, C. A.; Tanwar, M. K.; Holland, E. C.; Tempst, P. Anal. Chem. 2004, 76, 1560-1570). Since hundreds of peptides can be detected in microliter volumes of serum, it allows to search for disease signatures, for instance in the presence of cancer. We have now evaluated, optimized, and standardized a number of clinical and analytical chemistry variables that are major sources of bias; ranging from blood collection and clotting, to serum storage and handling, automated pepticle extraction, crystallization, spectral acquisition, and signal processing. In addition, proper alignment of spectra and user-friendly visualization tools are essential for meaningful, certifiable data mining. We introduce a minimal entropy algorithm, ' Entropycal ', that simplifies alignment and subsequent statistical analysis and increases the percentage of the highly distinguishing spectral information being retained after feature selection of the datasets. Using the improved analytical platform and tools, and a commercial statistics program, we found that sera from thyroid cancer patients can be distinguished from healthy controls based on an array of 98 discriminant peptides. With adequate technological and computational methods in place, and using rigorously standardized conditions, potential sources of patient related bias (e.g., gender, age, genetics, environmental, dietary, and other factors) may now be addressed.
引用
收藏
页码:1060 / 1072
页数:13
相关论文
共 20 条
[1]  
Adam BL, 2002, CANCER RES, V62, P3609
[2]   Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments [J].
Baggerly, KA ;
Morris, JS ;
Coombes, KR .
BIOINFORMATICS, 2004, 20 (05) :777-U710
[3]   Use of proteomics to discover novel markers of cardiac allograft rejection [J].
Borozdenkova, S ;
Westbrook, JA ;
Patel, V ;
Wait, R ;
Bolad, I ;
Burke, MM ;
Bell, AD ;
Banner, NR ;
Dunn, MJ ;
Rose, ML .
JOURNAL OF PROTEOME RESEARCH, 2004, 3 (02) :282-288
[4]   Proteomics and cancer - Running before we can walk? [J].
Check, E .
NATURE, 2004, 429 (6991) :496-497
[5]   Influence of matrix solution conditions on the MALDI-MS analysis of peptides and proteins [J].
Cohen, SL ;
Chait, BT .
ANALYTICAL CHEMISTRY, 1996, 68 (01) :31-37
[6]   Mass Spectrometry as a diagnostic and a cancer biomarker discovery tool - Opportunities and potential limitations [J].
Diamandis, EP .
MOLECULAR & CELLULAR PROTEOMICS, 2004, 3 (04) :367-378
[7]   Identification of gastric cancer patients by serum protein profiling [J].
Ebert, MPA ;
Meuer, J ;
Wiemer, JC ;
Schulz, HU ;
Reymond, MA ;
Traugott, U ;
Malfertheiner, P ;
Röcken, C .
JOURNAL OF PROTEOME RESEARCH, 2004, 3 (06) :1261-1266
[8]   Support vector machine classification and validation of cancer tissue samples using microarray expression data [J].
Furey, TS ;
Cristianini, N ;
Duffy, N ;
Bednarski, DW ;
Schummer, M ;
Haussler, D .
BIOINFORMATICS, 2000, 16 (10) :906-914
[9]  
Li JN, 2002, CLIN CHEM, V48, P1296
[10]   Use of proteomic patterns in serum to identify ovarian cancer [J].
Petricoin, EF ;
Ardekani, AM ;
Hitt, BA ;
Levine, PJ ;
Fusaro, VA ;
Steinberg, SM ;
Mills, GB ;
Simone, C ;
Fishman, DA ;
Kohn, EC ;
Liotta, LA .
LANCET, 2002, 359 (9306) :572-577