L Renee Ruhaak1, Uyen Thao Nguyen2, Carol Stroble3,4, Sandra L Taylor2, Ayumu Taguchi5, Samir M Hanash5,6, Carlito B Lebrilla3, Kyoungmi Kim2, Suzanne Miyamoto4. 1. Department of Chemistry, University of California Davis, Davis, CA 95616, USA. lruhaak@ucdavis.edu 2. Division of Biostatistics, Department of Public Health Sciences, University of California Davis, Davis, CA, USA. 3. Department of Chemistry, University of California Davis, Davis, CA, USA. 4. Division of Hematology and Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA, USA. 5. Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, WA, USA. 6. Department of Clinical Cancer Prevention - Research, Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abstract
PURPOSE: There is a need to identify better glycan biomarkers for diagnosis, early detection, and treatment monitoring in lung cancer using biofluids such as blood. Biofluids are complex mixtures of proteins dominated by a few high abundance proteins that may not have specificity for lung cancer. Therefore, two methods for protein enrichment were evaluated; affinity capturing of IgG and enrichment of medium abundance proteins, thus allowing us to determine which method yields the best candidate glycan biomarkers for lung cancer. EXPERIMENTAL DESIGN: N-glycans isolated from plasma samples from 20 cases of lung adenocarcinoma and 20 matched controls were analyzed using nLC-PGC-chip-TOF-MS (where PGC is porous-graphitized carbon). N-glycan profiles were obtained for five different fractions: total plasma, isolated IgG, IgG-depleted plasma, and the bound and flow-through fractions of protein enrichment. RESULTS: Four glycans differed significantly (false discovery rate, FDR < 0.05) between cases and controls in whole unfractionated plasma, while four other glycans differed significantly by cancer status in the IgG fraction. No significant glycan differences were observed in the other fractions. CONCLUSIONS AND CLINICAL RELEVANCE: These results confirm that the N-glycan profile in plasma of lung cancer patients is different from healthy controls and appears to be dominated by alterations in relatively abundant proteins.
PURPOSE: There is a need to identify better glycan biomarkers for diagnosis, early detection, and treatment monitoring in lung cancer using biofluids such as blood. Biofluids are complex mixtures of proteins dominated by a few high abundance proteins that may not have specificity for lung cancer. Therefore, two methods for protein enrichment were evaluated; affinity capturing of IgG and enrichment of medium abundance proteins, thus allowing us to determine which method yields the best candidate glycan biomarkers for lung cancer. EXPERIMENTAL DESIGN:N-glycans isolated from plasma samples from 20 cases of lung adenocarcinoma and 20 matched controls were analyzed using nLC-PGC-chip-TOF-MS (where PGC is porous-graphitized carbon). N-glycan profiles were obtained for five different fractions: total plasma, isolated IgG, IgG-depleted plasma, and the bound and flow-through fractions of protein enrichment. RESULTS: Four glycans differed significantly (false discovery rate, FDR < 0.05) between cases and controls in whole unfractionated plasma, while four other glycans differed significantly by cancer status in the IgG fraction. No significant glycan differences were observed in the other fractions. CONCLUSIONS AND CLINICAL RELEVANCE: These results confirm that the N-glycan profile in plasma of lung cancerpatients is different from healthy controls and appears to be dominated by alterations in relatively abundant proteins.
Authors: Larry Zeitlin; James Pettitt; Corinne Scully; Natasha Bohorova; Do Kim; Michael Pauly; Andrew Hiatt; Long Ngo; Herta Steinkellner; Kevin J Whaley; Gene G Olinger Journal: Proc Natl Acad Sci U S A Date: 2011-12-05 Impact factor: 11.205
Authors: William R Alley; Jacqueline A Vasseur; John A Goetz; Martin Svoboda; Benjamin F Mann; Daniela E Matei; Nancy Menning; Ahmed Hussein; Yehia Mechref; Milos V Novotny Journal: J Proteome Res Date: 2012-03-07 Impact factor: 4.466
Authors: Bram Blomme; Sven Francque; Eric Trépo; Louis Libbrecht; Dieter Vanderschaeghe; An Verrijken; Piet Pattyn; Yves Van Nieuwenhove; Dirk Van De Putte; Anja Geerts; Isabelle Colle; Joris Delanghe; Christophe Moreno; Luc Van Gaal; Nico Callewaert; Hans Van Vlierberghe Journal: Dig Liver Dis Date: 2011-11-25 Impact factor: 4.088
Authors: Mohamed Hassanein; J Clay Callison; Carol Callaway-Lane; Melinda C Aldrich; Eric L Grogan; Pierre P Massion Journal: Cancer Prev Res (Phila) Date: 2012-06-11
Authors: Sureyya Ozcan; Donald A Barkauskas; L Renee Ruhaak; Javier Torres; Cara L Cooke; Hyun Joo An; Serenus Hua; Cynthia C Williams; Lauren M Dimapasoc; Jae Han Kim; Margarita Camorlinga-Ponce; David Rocke; Carlito B Lebrilla; Jay V Solnick Journal: Cancer Prev Res (Phila) Date: 2013-12-10
Authors: L Renee Ruhaak; Sandra L Taylor; Carol Stroble; Uyen Thao Nguyen; Evan A Parker; Ting Song; Carlito B Lebrilla; William N Rom; Harvey Pass; Kyoungmi Kim; Karen Kelly; Suzanne Miyamoto Journal: J Proteome Res Date: 2015-09-30 Impact factor: 4.466
Authors: L Renee Ruhaak; Carol Stroble; Jianliang Dai; Matt Barnett; Ayumu Taguchi; Gary E Goodman; Suzanne Miyamoto; David Gandara; Ziding Feng; Carlito B Lebrilla; Samir Hanash Journal: Cancer Prev Res (Phila) Date: 2016-01-26
Authors: L Renee Ruhaak; Kyoungmi Kim; Carol Stroble; Sandra L Taylor; Qiuting Hong; Suzanne Miyamoto; Carlito B Lebrilla; Gary Leiserowitz Journal: J Proteome Res Date: 2016-02-24 Impact factor: 4.466