Breast cancer diagnosis and prognosis through quantitative measurements of serum glycan profiles.

BACKGROUND Glycosylated proteins play important roles in cell-to-cell interactions, immunosurveillance, and a variety of receptor-mediated and specific protein functions through a highly complex repertoire of glycan structures. Aberrant glycosylation has been implicated in cancer for many years. METHODS We performed specific MALDI mass spectrometry (MS)-based glycomic profile analyses of permethylated glycans in sera from breast cancer patients (12, stage I; 11, stage II; 9, stage III; and 50, stage IV) along with sera from 27 disease-free women. The serum glycoproteins were enzymatically deglycosylated, and the released glycans were purified and quantitatively permethylated before their MALDI-MS analyses. We applied various statistical analysis tools, including ANOVA and principal component analysis, to evaluate the MS profiles. RESULTS Two statistical procedures implicated several sialylated and fucosylated N-glycan structures as highly probable biomarkers. Quantitative changes according to a cancer stage resulted when we categorized the glycans according to molecular size, number of oligomer branches, and abundance of sugar residues. Increases in sialylation and fucosylation of glycan structures appeared to be indicative of cancer progression. Different statistical evaluations confirmed independently that changes in the relative intensities of 8 N-glycans are characteristic of breast cancer (P < 0.001), whereas other glycan structures might contribute additionally to distinctions in the statistically recognizable patterns (different stages). CONCLUSIONS MS-based N-glycomic profiling of serum-derived constituents appears promising as a highly sensitive and informative approach for staging the progression of cancer.

[1]  J. Dennis,et al.  Sialylation and malignant potential in tumour cell glycosylation mutants. , 1994, Glycobiology.

[2]  A. Amoresano,et al.  Glycosylation profile of integrin alpha 3 beta 1 changes with melanoma progression. , 2003, Biochimica et biophysica acta.

[3]  Ping Zhu,et al.  Antibody Domain Exchange Is an Immunological Solution to Carbohydrate Cluster Recognition , 2003, Science.

[4]  J. Dennis,et al.  CMP-N-acetylneuraminic acid hydroxylase activity determines the wheat germ agglutinin-binding phenotype in two mutants of the lymphoma cell line MDAY-D2 , 1991, Glycoconjugate Journal.

[5]  K. Cheung,et al.  Tumour marker measurements in the diagnosis and monitoring of breast cancer. , 2000, Cancer treatment reviews.

[6]  T. Nishi,et al.  Expression of sialyl 6-sulfo Lewis X is inversely correlated with conventional sialyl Lewis X expression in human colorectal cancer. , 2000, Cancer research.

[7]  D. Lombardo,et al.  Fucosyltransferase activities in human pancreatic tissue: comparative study between cancer tissues and established tumoral cell lines. , 1998, Glycobiology.

[8]  A. Dell,et al.  Viewing AIDS from a glycobiological perspective: potential linkages to the human fetoembryonic defence system hypothesis. , 1997, Molecular human reproduction.

[9]  T. Cai,et al.  Combining Predictors for Classification Using the Area under the Receiver Operating Characteristic Curve , 2006, Biometrics.

[10]  Hiroaki Nakagawa,et al.  High Throughput Quantitative Glycomics and Glycoform-focused Proteomics of Murine Dermis and Epidermis* , 2005, Molecular & Cellular Proteomics.

[11]  J. Alper.  Turning Sweet on Cancer , 2003, Science.

[12]  S. Thompson,et al.  Quantifying heterogeneity in a meta‐analysis , 2002, Statistics in medicine.

[13]  S. Baldus,et al.  Expression of MUC1, MUC2 and oligosaccharide epitopes in breast cancer: prognostic significance of a sialylated MUC1 epitope. , 2005, International journal of oncology.

[14]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[15]  R. Dwek,et al.  Glycosylation and the immune system. , 2001, Science.

[16]  M. Kattan,et al.  Beyond prostate-specific antigen: new serologic biomarkers for improved diagnosis and management of prostate cancer. , 2004, Reviews in urology.

[17]  I. Ellis,et al.  Pathological prognostic factors in breast cancer. , 1999, Critical reviews in oncology/hematology.

[18]  Naoyuki Taniguchi,et al.  Comparison of the methods for profiling glycoprotein glycans--HUPO Human Disease Glycomics/Proteome Initiative multi-institutional study. , 2007, Glycobiology.

[19]  G. Hart,et al.  The emerging significance of O-GlcNAc in cellular regulation. , 2002, Chemical reviews.

[20]  Kit S Lam,et al.  Profiling of glycans in serum for the discovery of potential biomarkers for ovarian cancer. , 2006, Journal of proteome research.

[21]  Robert Camp,et al.  β1,6-Branched Oligosaccharides Are Increased in Lymph Node Metastases and Predict Poor Outcome in Breast Carcinoma , 2005, Clinical Cancer Research.

[22]  R. Walker,et al.  Analysis of glycoproteins released from benign and malignant human breast: changes in size and fucosylation with malignancy. , 1989, European journal of cancer & clinical oncology.

[23]  A. Amoresano,et al.  Glycosylation profile of integrin α3β1 changes with melanoma progression , 2003 .

[24]  S. Hakomori.  Tumor malignancy defined by aberrant glycosylation and sphingo(glyco)lipid metabolism. , 1996, Cancer research.

[25]  Giuseppe Musumarra,et al.  A Bioinformatic Approach to the Identification of Candidate Genes for the Development of New Cancer Diagnostics , 2003, Biological chemistry.

[26]  J A Swets,et al.  Measuring the accuracy of diagnostic systems. , 1988, Science.

[27]  C. Isaacs,et al.  New prognostic factors for breast cancer recurrence. , 2001, Seminars in oncology.

[28]  Y. Mechref,et al.  Differentiating structural isomers of sialylated glycans by matrix-assisted laser desorption/ionization time-of-flight/time-of-flight tandem mass spectrometry. , 2006, Rapid communications in mass spectrometry : RCM.

[29]  A. Kobata.  A retrospective and prospective view of glycopathology , 1998, Glycoconjugate Journal.

[30]  Y. Mechref,et al.  Mass spectrometric mapping and sequencing of N-linked oligosaccharides derived from submicrogram amounts of glycoproteins. , 1998, Analytical chemistry.

[31]  H.-L. Chen,et al.  Transfection of the nm23-H1 gene into human hepatocarcinoma cell line inhibits the expression of sialyl Lewis X, α1,3 fucosyltransferase VII, and metastatic potential , 2002, Journal of Cancer Research and Clinical Oncology.

[32]  Daan Brandenbarg.  The National. , 1892 .

[33]  M. Duffy,et al.  Serum tumor markers in breast cancer: are they of clinical value? , 2006, Clinical chemistry.

[34]  I. Fleming,et al.  The national cancer data base report on recent hospital cancer program progress toward complete American joint committee on cancer/TNM staging , 1997, Cancer.

[35]  J. Alper.  Glycobiology. Turning sweet on cancer. , 2003, Science.

[36]  Mark Sutton-Smith,et al.  Characterization of the Oligosaccharides Associated with the Human Ovarian Tumor Marker CA125* , 2003, Journal of Biological Chemistry.

[37]  M. Dwek,et al.  Breast cancer progression is associated with a reduction in the diversity of sialylated and neutral oligosaccharides. , 1998, Clinica chimica acta; international journal of clinical chemistry.

[38]  J. Paulson,et al.  Clinical significance of ST3Gal IV expression in human renal cell carcinoma. , 2002, Oncology reports.

[39]  Yehia Mechref,et al.  Structural Investigations of Glycoconjugates at High Sensitivity , 2002 .

[40]  Yehia Mechref,et al.  Solid-phase permethylation of glycans for mass spectrometric analysis. , 2005, Rapid communications in mass spectrometry : RCM.

[41]  W. Hancock,et al.  Multilectin affinity chromatography for characterization of multiple glycoprotein biomarker candidates in serum from breast cancer patients. , 2006, Clinical chemistry.