方法

血清样品制备

　　无已知恶性肿瘤的健康志愿者（男女均用，年龄23-56岁，见补充表1）和诊断为前列腺癌、乳腺癌或膀胱癌的患者的血清按照标准临床操作规程取自Sloan-Kettering纪念癌症中心[29]，有关患者的年龄、性别及病理诊断的详情参见补充表1。所有采血操作均获得MSKCC制度审查和隐私局的批准，并得到患者的书面同意书。血样收集在8.5-ml的BD红头玻璃采血管(BD; 366430)中，在室温下凝固1小时，1,400–2,000 g离心10分钟。上清液（血清）移至4个4ml冷冻管(Fischer Scientific International, 0566966)中，每管1ml，储存于–80°C备用^[29]。绿头的肝素抗凝管(BD, 366480)中血浆的制备方法相似，不过在收集血样后立即进行离心处理。送至MS实验室后，在冷冻管上贴条形码。每个样品取1管，冰上融解，分至9个更小的微量eppendorf管中、贴条形码、存放于贴条形码的盒中，置–80°C备用。本实验中，所有的血清标本均经过两次冻融，第二次冻融后立即进行多肽提取和MS分析。我们尽了最大努力，使护士、抽血人员、联络人员和临床医师严格按照标准规程操作。

分析化学

　　自动操作、固相多肽提取、MALDITOF MS、信号处理和质谱图匹配及常规质谱图观察均按照以往作者本实验室自行开发的过程进行^[18,29]。更多细节和串联MS鉴定选定的血清多肽的方法见补充方法。

统计学

　　表格程序中含有取自癌症患者和健康受试者的样品的质谱图资料（共106个样品，651 个m/z值，经过标准化换算的各样品强度值，> 70,000个数据点）以及前列腺癌试验组的资料（PR2；41个样；～27,000个数据点），这些资料均输入GeneSpring程序(version 7; Agilent Technologies)，采用不同的统计算法如单向ANOVA、主成分分析、分级聚类、k 个最近邻居分类法或SVM进行分析。GeneSpring编制了不同的试验代表这些质量值。在这些质量值经数据库标准化处理之前不对试验进行标准化处理。在试验的参数部分，设置了一个名为“癌症类型”的参数将样品标明为前列腺癌、膀胱癌、乳腺癌或正常组。未使用交叉基因错误模式。

ANOVA

　　创建试验后，采用非参数检验（曼-怀二氏检验即秩和检验（二元比较）和克(鲁斯卡尔)-瓦(利斯)二氏检验即Ｈ检验法（多元比较）过滤m/z值(峰) 。 Benjamini-Hochberg法用于校正多元比较的P值[79]。P<0.00001设为有显著性差异。这些检验的目的是发现在临床各组之间具有显著性差异的峰。

分级聚类

　　对651个m/z值（峰）进行平均-连锁分级聚类分析，以标准相互关系（即皮尔森相互关系）作为距离尺度（GeneSpring程序）。将峰绘成基因数和试验树形式，横轴代表样品，纵轴代表质量。

分级预测

　　采用GeneSpring的分级预测工具进行SVM 和 k-NN分析。训练组采用二元比较(PR1 和 对照组)或多级比较（PR1，乳腺癌、膀胱癌和对照组）。试验组为PR2。预测参数设置在癌症类型。基因选择设为选用经过选择的不同组的质量（如651、68、26)。k-NN分析中，邻居数量按照P值判断截止为1而设为5。SVM分析的训练组及参数同上，预测PR2组。计算方程为多项式点积（一级方程），斜率为0。

致谢

　　本工作为NIH基金项目（资助号：1-R21-CA1119425、5-P30-CA08748和5-P50-CA92629），并获得前列腺癌基金会、Vakil研究基金和Accelerate Brain Cancer Cure的奖励。感谢Larry Norton和Mark Kris的支持;感谢Richard Robbins、 Mark Robson和Chris Sander对讨论的帮助；感谢San San Yi 的多肽合成工作及Lynne Lacomis的文字工作；感谢无偿捐助血样的所有志愿者。

参考文献：

1. Lander, E.S., et al. 2001. Initial sequencing and analysis of the human genome. Nature. 409:860–921.
2. Hood, L. 2003. Leroy Hood expounds the principles, practice and future of systems biology. Drug Discov. Today. 8:436–438.
3. Etzioni, R., et al. 2003. The case for early detection.Nat. Rev. Cancer. 3:243–252.
4. Chung, C.H., Bernard, P.S., and Perou, C.M. 2002. Molecular portraits and the family tree of cancer. Nat. Genet. 32(Suppl.):533–540.
5. Staudt, L.M. 2002. Gene expression profiling of lymphoid malignancies. Annu. Rev. Med. 53:303–318.
6. Anderson, N.L., and Anderson, N.G. 2002. The human plasma proteome: history, character, and diagnostic prospects. Mol. Cell. Proteomics. 1:845–867.
7. Adkins, J.N., et al. 2002. Toward a human blood serum proteome: analysis by multidimensional separation coupled with mass spectrometry. Mol.Cell. Proteomics. 1:947–955.
8. Sidransky, D. 2002. Emerging molecular markers of cancer. Nat. Rev. Cancer. 2:210–219.
9. Bidart, J.M., et al. 1999. Kinetics of serum tumor marker concentrations and usefulness in clinical monitoring. Clin. Chem. 45:1695–1707.
10. Jortani, S.A., Prabhu, S.D., and Valdes, R., Jr. 2004. Strategies for developing biomarkers of heart failure. Clin. Chem. 50:265–278.
11. Watts, N.B. 1999. Clinical utility of biochemical markers of bone remodeling. Clin. Chem. 45:1359–1368.
12. Gillette, M.A., Mani, D.R., and Carr, S.A. 2005. Place of pattern in proteomic biomarker discovery. J. Proteome Res. 4:1143–1154.
13. Hugosson, J., et al. 2003. Prostate specific antigen based biennial screening is sufficient to detect almost all prostate cancers while still curable. J. Urol. 169:1720–1723.
14. Ghosh, A., Wang, X., Klein, E., and Heston, W.D. 2005. Novel role of prostate-specific membrane antigen in suppressing prostate cancer invasiveness. Cancer Res. 65:727–731.
15. Richter, R., et al. 1999. Composition of the peptide fraction in human blood plasma: database of circulating human peptides. J. Chromatogr. B Biomed. Sci. Appl. 726:25–35.
16. Tirumalai, R.S., et al. 2003. Characterization of the low molecular weight human serum proteome. Mol. Cell. Proteomics. 1:1096–1103.
17. Koomen, J.M., et al. 2005. Direct tandem mass spectrometry reveals limitations in protein profiling experiments for plasma biomarker discovery. J. Proteome Res. 4:972–981.
18. Villanueva, J., et al. 2004. Serum peptide profiling by magnetic particle-assisted, automated sample processing and MALDI-TOF mass spectrometry. Anal. Chem. 76:1560–1570.
19. Petricoin, E.F., et al. 2002. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 359:572–577.
20. Adam, B.L., et al. 2002. Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men. Cancer Res. 62:3609–3614.
21. Li, J., Zhang, Z., Rosenzweig, J., Wang, Y.Y., and Chan, D.W. 2002. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin. Chem. 48:1296–1304.
22. Ebert, M.P., et al. 2004. Identification of gastric cancer patients by serum protein profiling. J. Proteome Res. 3:1261–1266.
23. Ornstein, D.K., et al. 2004. Serum proteomic profiling can discriminate prostate cancer from benign prostates in men with total prostate specific antigen levels between 2.5 and 15.0 ng/ml. J. Urol. 172:1302–1305.
24. Conrads, T.P., et al. 2004. High-resolution serum proteomic features for ovarian cancer detection. Endocr. Relat. Cancer. 11:163–178.
25. Coombes, K.R., Morris, J.S., Hu, J., Edmonson, S.R., and Baggerly, K.A. 2005. Serum proteomics profiling-a young technology begins to mature. Nat. Biotechnol. 23:291–292.
26. Diamandis, E.P. 2004. Mass spectrometry as adiagnostic and a cancer biomarker discovery tool:opportunities and potential limitations. Mol. Cell. Proteomics. 3:367–378.
27. Check, E. 2004. Proteomics and cancer: running before we can walk? Nature. 429:496–497.
28. Ransohoff, D.F. 2005. Opinion: bias as a threat to the validity of cancer molecular-marker research.Nat. Rev. Cancer. 5:142–149.
29. Villanueva, J., et al. 2005. Correcting common errors in identifying cancer-specific serum peptide signatures. J. Proteome Res. 4:1060–1072.
30. Marshall, J., et al. 2003. Processing of serum proteins underlies the mass spectral fingerprinting of myocardial infarction. J. Proteome Res. 2:361–372.
31. Bergen, H.R., 3rd, et al. 2003. Discovery of ovarian cancer biomarkers in serum using NanoLC electrospray ionization TOF and FT-ICR mass spectrometry. Dis. Markers. 19:239–249.
32. Zhang, Z., et al. 2004. Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res. 64:5882–5890.
33. Weinberger, S.R., Dalmasso, E.A., and Fung, E.T. 2002. Current achievements using ProteinChip Array technology. Curr. Opin. Chem. Biol. 6:86–91.
34. Kapp, E.A., et al. 2003. Mining a tandem mass spectrometry database to determine the trends and global factors influencing peptide fragmentation. Anal. Chem. 75:6251–6264.
35. Gao, J., Opiteck, G.J., Friedrichs, M.S., Dongre, A.R., and Hefta, S.A. 2003. Changes in the protein expression of yeast as a function of carbon source. J. Proteome Res. 2:643–649.
36. Fach, E.M., et al. 2004. In vitro biomarker discovery for atherosclerosis by proteomics. Mol. Cell. Proteomics. 3:1200–1210.
37. Jandl, J.H. 1996. Blood: textbook of hematology. Little, Brown and Co. New York, New York, USA. 1510 pp.
38. Sahu, A., and Lambris, J.D. 2001. Structure and biology of complement protein C3, a connecting link between innate and acquired immunity. Immunol. Rev. 180:35–48.
39. Abbasciano, V., Levato, F., and Zavagli, G. 1987. Specificity of fibrinopeptide A (FpA) as a marker for gastrointestinal cancers before and after surgery. Med. Oncol. Tumor Pharmacother. 4:75–79.
40. Auger, M.J., Galloway, M.J., Leinster, S.J., McVerry, B.A., and Mackie, M.J. 1987. Elevated fibrinopeptide A levels in patients with clinically localized breast carcinoma. Haemostasis. 17:336–339.
41. Stewart, J.M. 2003. Bradykinin antagonists as anticancer agents. Curr. Pharm. Des. 9:2036–2042.
42. Kato, H., Matsumura, Y., and Maeda, H. 1988. Isolation and identification of hydroxyproline analogues of bradykinin in human urine. FEBS Lett. 232:252–254.
43. Salier, J.P., Rouet, P., Raguenez, G., and Daveau, M. 1996. The inter-alpha-inhibitor family: from structure to regulation. Biochem. J. 315:1–9.
44. Nishimura, H., et al. 1995. cDNA and deduced amino acid sequence of human PK-120, a plasma kallikrein-sensitive glycoprotein. FEBS Lett. 357:207–211.
45. Belt, K.T., Carroll, M.C., and Porter, R.R. 1984. The structural basis of the multiple forms of human complement component C4. Cell. 36:907–914.
46. July, L.V., et al. 2002. Clusterin expression is significantly enhanced in prostate cancer cells following androgen withdrawal therapy. Prostate. 50:179–188.
47. Scaltriti, M., et al. 2004. Clusterin (SGP-2, ApoJ) expression is downregulated in low- and high-grade human prostate cancer. Int. J. Cancer. 108:23–30.
48. Miyake, H., Gleave, M., Kamidono, S., and Hara, I. 2002. Overexpression of clusterin in transitional cell carcinoma of the bladder is related to disease progression and recurrence. Urology. 59:150–154.
49. Jiang, W.G., Ablin, R., Douglas-Jones, A., and Mansel, R.E. 2003. Expression of transglutaminases in human breast cancer and their possible clinical significance. Oncol. Rep. 10:2039–2044.
50. Tietz, N.W. 1995. Clinical guide to laboratory tests. Philadelphia, Pennsylvania, USA. W.B. Saunders Co. 1096 pp.
51. Sanderink, G.J., Artur, Y., and Siest, G. 1988. Human aminopeptidases: a review of the literature. J. Clin. Chem. Clin. Biochem. 26:795–807.
52. Silveira, P.F., Gil, J., Casis, L., and Irazusta, J. 2004. Peptide metabolism and the control of body fluid homeostasis. Curr. Med. Chem. Cardiovasc. Hematol. Agents. 2:219–238.
53. Mitsui, T., Nomura, S., Itakura, A., and Mizutani, S. 2004. Role of aminopeptidases in the blood pressure regulation. Biol. Pharm. Bull. 27:768–771.
54. Nesheim, M., et al. 1997. Thrombin, thrombomodulin and TAFI in the molecular link between coagulation and fibrinolysis. Thromb. Haemost. 78:386–391.
55. Ito, N., et al. 2004. ADAMs, a disintegrin and metalloproteinases, mediate shedding of oxytocinase. Biochem. Biophys. Res. Commun. 314:1008–1013.
56. van Hensbergen, Y., et al. 2002. Soluble aminopeptidase aminopeptidase N/CD13 in malignant and nonmalignant effusions and intratumoral fluid. Clin. Cancer Res. 8:3747–3754.
57. Martinez, J.M., et al. 1999. Aminopeptidase activities in breast cancer tissue. Clin. Chem. 45:1797–1802.
58. Matrisian, L.M., Sledge, G.W., Jr., and Mohla, S. 2003. Extracellular proteolysis and cancer: meeting summary and future directions. Cancer Res. 63:6105–6109.
59. Egeblad, M., and Werb, Z. 2002. New functions for the matrix metalloproteinases in cancer progression. Nat. Rev. Cancer. 2:161–174.
60. Rao, J.S. 2003. Molecular mechanisms of glioma invasiveness: the role of proteases. Nat. Rev. Cancer. 3:489–501.
61. Moffatt, S., Wiehle, S., and Cristiano, R.J. 2005. Tumor-specific gene delivery mediated by a novel peptide-polyethylenimine-DNA polyplex targeting aminopeptidase N/CD13. Hum. Gene Ther. 16:57–67.
62. Kehlen, A., Lendeckel, U., Dralle, H., Langner, J., and Hoang-Vu, C. 2003. Biological significance of aminopeptidase N/CD13 in thyroid carcinomas. Cancer Res. 63:8500–8506.
63. Rocken, C., et al. 2004. Ectopeptidases are differentially expressed in hepatocellular carcinomas. Int. J. Oncol. 24:487–495.
64. Carl-McGrath, S., et al. 2004. The ectopeptidases CD10, CD13, CD26, and CD143 are upregulated in gastric cancer. Int. J. Oncol. 25:1223–1232.
65. Kojima, K., et al. 1987. Serum activities of dipeptidyl-aminopeptidase II and dipeptidyl-aminopeptidase IV in tumor-bearing animals and in cancer patients. Biochem. Med. Metab. Biol. 37:35–41.
66. Essler, M., and Ruoslahti, E. 2002. Molecular specialization of breast vasculature: a breast-homing phage-displayed peptide binds to aminopeptidase P in breast vasculature. Proc. Natl. Acad. Sci. U. S. A. 99:2252–2257.
67. Carrera, M.P., et al. 2005. Serum enkephalindegrading aminopeptidase activity in N-methyl nitrosourea-induced rat breast cancer. Anticancer Res. 25:193–196.
68. Pulido-Cejudo, G., et al. 2004. A monoclonal antibody driven biodiagnostic system for the quantitative quantitative screening of breast cancer. Biotechnol. Lett. 26:1335–1339.
69. Suganuma, T., et al. 2004. Regulation of aminopeptidase A expression in cervical carcinoma: role of tumor-stromal interaction and vascular endothelial growth factor. Lab. Invest. 84:639–648.
70. Selvakumar, P., et al. 2004. High expression of methionine aminopeptidase 2 in human colorectal adenocarcinomas. Clin. Cancer Res. 10:2771–2775.
71. Ni, R.Z., Huang, J.F., Xiao, M.B., Li, M., and Meng, X.Y. 2003. Glycylproline dipeptidyl aminopeptidase isoenzyme in diagnosis of primary hepatocellular carcinoma. World J. Gastroenterol. 9:710–713.
72. Sheppard, G.S., et al. 2004. 3-Amino-2-hydroxyamides and related compounds as inhibitors of methionine aminopeptidase-2. Bioorg. Med. Chem. Lett. 14:865–868.
73. Griffith, E.C., et al. 1998. Molecular recognition of angiogenesis inhibitors fumagillin and ovalicin by methionine aminopeptidase 2. Proc. Natl. Acad. Sci. U. S. A. 95:15183–15188.
74. Pasqualini, R., et al. 2000. Aminopeptidase N is a receptor for tumor-homing peptides and a target for inhibiting angiogenesis. Cancer Res. 60:722–727.
75. Petrovic, N., Bhagwat, S.V., Ratzan, W.J., Ostrowski, M.C., and Shapiro, L.H. 2003. CD13/APN transcription is induced by RAS/MAPK-mediated phosphorylation of Ets-2 in activated endothelial cells. J. Biol. Chem. 278:49358–49368.
76. O’Malley, P.G., Sangster, S.M., Abdelmagid, S.A., Bearne, S.L., and Too, C.K. 2005. Characterization of a novel, cytokine-inducible carboxypeptidase-D isoform in hematopoietic tumor cells. Biochem. J.390:665–673.
77. Fair, W.R., Israeli, R.S., and Heston, W.D. 1997. Prostate-specific membrane antigen. Prostate. 32:140–148.
78. Marker, P.C., Donjacour, A.A., Dahiya, R., and Cunha, G.R. 2003. Hormonal, cellular, and molecular control of prostatic development. Dev. Biol. 253:165–174.
79. Benjamini, Y., and Hochberg, Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. (Ser. B.) 57:289–300.