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1
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Ghimire H, Viennois E, Hu X, Qin G, Merlin D, Perera AGU. Infrared spectrometric biomarkers for ulcerative colitis screening using human serum samples. JOURNAL OF BIOPHOTONICS 2022; 15:e202100307. [PMID: 35133076 DOI: 10.1002/jbio.202100307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 12/29/2021] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
This study uses infrared spectrometry coupled with data analysis techniques to understand colitis-induced alterations in the molecular components of serum samples. Using samples from 18 ulcerative colitis patients and 28 healthy volunteers, we assessed features such as absorbance values at wavenumbers of 1033 and 1076 cm-1 , and the ratios at 1121 versus 1020 cm-1 and 1629 versus 1737 cm-1 . Through the deconvolution of the amide I band, protein secondary structure analysis was performed. Colitis-induced alterations are reflected as fluctuations in the vibrational modes, and are used to identify associated spectral signatures. The results of the study show statistically significant differences in five identifying spectral signatures. Among them, the sensitivity and specificity of the spectral signature, I1121 /I1020 , were 100% and 86%, respectively. These findings resemble our earlier proof-of-concept investigations in mouse models and provide preliminary evidence that this could be a reliable diagnostic test for human patients.
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Affiliation(s)
- Hemendra Ghimire
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA, USA
| | - Emilie Viennois
- Institute for Biomedical Sciences, Digestive Disease Research Group, Georgia State University, Atlanta, GA, USA
| | - Xinjie Hu
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA
| | - Gengsheng Qin
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA
| | - Didier Merlin
- Institute for Biomedical Sciences, Digestive Disease Research Group, Georgia State University, Atlanta, GA, USA
- Atlanta Veterans Affairs Medical Center, Decatur, GA, USA
| | - A G Unil Perera
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA, USA
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Mitchell BL, Yasui Y, Li CI, Fitzpatrick AL, Lampe PD. Impact of Freeze-thaw Cycles and Storage Time on Plasma Samples Used in Mass Spectrometry Based Biomarker Discovery Projects. Cancer Inform 2017. [DOI: 10.1177/117693510500100110] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Mass spectrometry approaches to biomarker discovery in human fluids have received a great deal of attention in recent years. While mass spectrometry instrumentation and analysis approaches have been widely investigated, little attention has been paid to how sample handling can impact the plasma proteome and therefore influence biomarker discovery. We have investigated the effects of two main aspects of sample handling on MALDI-TOF data: repeated freeze-thaw cycles and the effects of long-term storage of plasma at –70°C. Repeated freeze-thaw cycles resulted in a trend towards increasing changes in peak intensity, particularly after two thaws. However, a 4-year difference in long-term storage appears to have minimal effect on protein in plasma as no differences in peak number, mass distribution, or coefficient of variation were found between samples. Therefore, limiting freeze/thaw cycles seems more important to maintaining the integrity of the plasma proteome than degradation caused by long-term storage at –70°C.
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Affiliation(s)
- Breeana L Mitchell
- Public Health Sciences, University of Alberta
- Fred Hutchinson Cancer Research Center, Molecular and Cellular Biology Program, University of Alberta
| | - Yutaka Yasui
- University of Washington, Department of Public Health Sciences, University of Alberta
| | - Christopher I Li
- Public Health Sciences, University of Alberta
- Departments of Epidemiology, University of Alberta
| | | | - Paul D Lampe
- Public Health Sciences, University of Alberta
- Fred Hutchinson Cancer Research Center, Molecular and Cellular Biology Program, University of Alberta
- Departments of Pathobiology, University of Alberta
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Grizzle WE, Semmes OJ, Bigbee W, Zhu L, Malik G, Oelschlager DK, Manne B, Manne U. The Need for Review and Understanding of SELDI/MALDI Mass Spectroscopy Data Prior to Analysis. Cancer Inform 2017. [DOI: 10.1177/117693510500100106] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Multiple studies have reported that surface enhanced laser desorption/ionization time of flight mass spectroscopy (SELDI-TOF-MS) is useful in the early detection of disease based on the analysis of bodily fluids. Use of any multiplex mass spectroscopy based approach as in the analysis of bodily fluids to detect disease must be analyzed with great care due to the susceptibility of multiplex and mass spectroscopy methods to biases introduced via experimental design, patient samples, and/or methodology. Specific biases include those related to experimental design, patients, samples, protein chips, chip reader and spectral analysis. Contributions to biases based on patients include demographics (e.g., age, race, ethnicity, sex), homeostasis (e.g., fasting, medications, stress, time of sampling), and site of analysis (hospital, clinic, other). Biases in samples include conditions of sampling (type of sample container, time of processing, time to storage), conditions of storage, (time and temperature of storage), and prior sample manipulation (freeze thaw cycles). Also, there are many potential biases in methodology which can be avoided by careful experimental design including ensuring that cases and controls are analyzed randomly. All the above forms of biases affect any system based on analyzing multiple analytes and especially all mass spectroscopy based methods, not just SELDI-TOF-MS. Also, all current mass spectroscopy systems have relatively low sensitivity compared with immunoassays (e.g., ELISA). There are several problems which may be unique to the SELDI-TOF-MS system marketed by Ciphergen®. Of these, the most important is a relatively low resolution (±0.2%) of the bundled mass spectrometer which may cause problems with analysis of data. Foremost, this low resolution results in difficulties in determining what constitutes a “peak” if a peak matching approach is used in analysis. Also, once peaks are selected, the peaks may represent multiple proteins. In addition, because peaks may vary slightly in location due to instrumental drift, long term identification of the same peaks may prove to be a challenge. Finally, the Ciphergen® system has some “noise” of the baseline which results from the accumulation of charge in the detector system. Thus, we must be very aware of the factors that may affect the use of proteomics in the early detection of disease, in determining aggressive subsets of cancers, in risk assessment and in monitoring the effectiveness of novel therapies.
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Affiliation(s)
| | | | - William Bigbee
- University of Pittsburgh Cancer Institute, Pittsburgh, PA, USA
| | - Liu Zhu
- University of Alabama at Birmingham, Birmingham, AL
| | | | | | - Barkha Manne
- University of Alabama at Birmingham, Birmingham, AL
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4
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Li Y, Sun X, Zhang X, Liu Y, Yang Y, Li R, Liu X, Jia R, Li Z. Establishment of a decision tree model for diagnosis of early rheumatoid arthritis by proteomic fingerprinting. Int J Rheum Dis 2015; 18:835-41. [PMID: 26249836 DOI: 10.1111/1756-185x.12595] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
AIM The objective of this study was to identify proteomic biomarkers specific for rheumatoid arthritis (RA) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in combination with weak cationic exchange (WCX) magnetic beads. METHODS Serum samples from 50 patients with RA and 110 disease controls (50 SLE and 60 SS) and 51 healthy individuals were analyzed. The samples were randomly divided into a training set or test set to develop a diagnostic model for RA. RESULTS A total of 83 protein peaks were identified to be related with RA, in which four of the peaks with mass-charge ratio (m/z) at 8133.85, 5844.60, 13 541.3 and 14 029.0 were selected to establish a model for diagnosis of RA. This classification model could separate patients with RA from diseased and healthy controls with sensitivity of 84.0% and specificity of 92.5%, and its accuracy was confirmed in the blind testing set with high sensitivity and specificity of 80.0% and 93.3%, respectively. CONCLUSIONS This study suggested that potential serum biomarkers for RA diagnosis could be discovered by MALDI-TOF-MS. The classification tree model set up in this study might be used as a novel diagnostic tool for RA.
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Affiliation(s)
- Yuhui Li
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Xiaolin Sun
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Xuewu Zhang
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Yanying Liu
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Yuqin Yang
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Ru Li
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Xu Liu
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Rulin Jia
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
| | - Zhanguo Li
- Department of Rheumatology & Immunology, Peking University People's Hospital, Beijing, China
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5
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Li Y, Sun X, Zhang X, Yang Y, Jia R, Liu X, Li R, Liu Y, Li Z. Establishment of a novel diagnostic model for Sjögren's syndrome by proteomic fingerprinting. Clin Rheumatol 2014; 33:1745-50. [PMID: 25178777 DOI: 10.1007/s10067-014-2762-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2014] [Revised: 08/06/2014] [Accepted: 08/18/2014] [Indexed: 01/17/2023]
Abstract
Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease that lacks sensitive and specific diagnostic methods. The aim of this study was to identify potential biomarkers specific for pSS and to establish a diagnostic model. Serum samples from patients with pSS, disease controls (DC, patients with systemic lupus erythematosus (SLE), rheumatoid arthritis (RA)), and healthy controls (HC)) were randomly divided into a training set (35 pSS, 50 DC, and 26 HC) and a testing set (25 pSS, 50 DC, and 25 HC). Weak cationic exchange (WCX) magnetic beads were used to differentially capture serum proteins prior to proteomic analysis. Proteomic mass spectra were generated by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). One hundred differential M/Z peaks associated with pSS were identified, and the m/z peaks at 8,133.85, 11,972.8, 2,220.81, and 4,837.66 were used to establish a diagnostic model for pSS. This diagnostic model was able to distinguish pSS from non-pSS controls with a sensitivity of 77.1 % and a specificity of 85.5 %, and its efficacy was confirmed in our blinded testing set with good sensitivity and specificity of 95.5 and 88 %, respectively. The results indicated that the proteomic fingerprinting model was effective in the diagnosis of pSS.
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Affiliation(s)
- Yuhui Li
- Department of Rheumatology and Immunology, Clinical Immunology Center, Peking University People's Hospital, 11 Xizhimen South Street, 100044, Beijing, China
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Lukkahatai N, Patel S, Gucek M, Hsiao CP, Saligan LN. Proteomic serum profile of fatigued men receiving localized external beam radiation therapy for non-metastatic prostate cancer. J Pain Symptom Manage 2014; 47:748-756.e4. [PMID: 23916682 PMCID: PMC3743082 DOI: 10.1016/j.jpainsymman.2013.05.016] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2013] [Revised: 05/07/2013] [Accepted: 05/15/2013] [Indexed: 10/26/2022]
Abstract
CONTEXT Fatigue is the most distressing side effect of radiation therapy, and its progression etiology is unknown. OBJECTIVES This study describes proteome changes from sera of fatigued men with non-metastatic prostate cancer receiving external beam radiation therapy (EBRT). METHODS Fatigue scores, measured by the Functional Assessment of Chronic Illness Therapy-Fatigue, and serum were collected from 12 subjects at baseline (before EBRT) and at midpoint (Day 21) of EBRT. Depleted sera from both time points were analyzed using two-dimensional difference gel electrophoresis, and up/down regulated proteins were identified using liquid chromatography-tandem mass spectrometry. Western blot analyses confirmed the protein changes observed. RESULTS Results showed that apolipoprotein (Apo)A1, ApoE, and transthyretin (TTR) consistently changed from baseline (Day 0) to midpoint (Day 21). The mean ApoE level of subjects with high change in fatigue (HF: n = 9) increased significantly from baseline to midpoint and were higher than in subjects with no change in fatigue. The mean ApoA1 level was higher in HF subjects at baseline and at midpoint than in no fatigue subjects at both time points. The mean TTR level of no fatigue subjects was higher at baseline and midpoint than in HF subjects. CONCLUSION These ApoE, ApoA1, and TTR results may assist in understanding pathways that can explain fatigue progression etiology in this clinical population.
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Affiliation(s)
- Nada Lukkahatai
- National Institute of Nursing Research, National Institutes of Health, Bethesda, Maryland, USA.
| | - Sajni Patel
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Marjan Gucek
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Chao-Pin Hsiao
- National Institute of Nursing Research, National Institutes of Health, Bethesda, Maryland, USA
| | - Leorey N Saligan
- National Institute of Nursing Research, National Institutes of Health, Bethesda, Maryland, USA
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Kowdley G, Srikantan S, Abdelmohsen K, Gorospe M, Khan J. Molecular biology techniques for the surgeon. World J Surg Proced 2012; 2:5-15. [DOI: 10.5412/wjsp.v2.i2.5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
New technologies are constantly being introduced into the medical and surgical fields. These technologies come in the form of newer medicines, imaging methods and prognostic tools, among others, and allow clinicians to make more rational and informed decisions on the care of their patients. Many of these technologies utilize advanced techniques which are at the forefront of many research fields and represent a transition of bench advances into the clinical realm. This review will highlight four technologies that are at the forefront in the treatment of oncology patients treated by surgeons on a daily basis. Circulating tumor cells, microarray analysis, proteomic studies and rapid sequencing technologies will be highlighted. These technologies will be reviewed and their potential use in the care of surgical patients will be discussed.
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Brauer HA, Lampe PD, Yasui YY, Hamajima N, Stolowitz ML. Biochips that sequentially capture and focus antigens for immunoaffinity MALDI-TOF MS: a new tool for biomarker verification. Proteomics 2011; 10:3922-7. [PMID: 20957758 DOI: 10.1002/pmic.201000219] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
A novel approach to immunoaffinity MS is described wherein antibodies are appended to a patterned gold Biochip surface. The Biochip surface is patterned with an array of concentric immunocapture zones composed of highly hydrophilic central zones surrounded by moderately hydrophilic zones that reside on a non-wetting background, with protein attachment via electrochemically cleavable linkers. After linker cleavage, matrix application forms a discrete spot suitable for MALDI-TOF-MS. Use of the Biochip to purify transthyretin from human serum allowed a distinct resolution of four disulfide conjugates and one truncated form isoforms with good mass resolution and sensitivity.
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Affiliation(s)
- Heather Ann Brauer
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
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Ning QY, Wu JZ, Li GJ, Zang N, Hu DF, Wu JL, Chen MW, Wan PQ. Screening of differentially expressed low-abundance proteins among serum samples from patients with different HBV-related hepatic diseases by SELDI-TOF-MS. Shijie Huaren Xiaohua Zazhi 2011; 19:143-150. [DOI: 10.11569/wcjd.v19.i2.143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
AIM: To screen differentially expressed low-abundance proteins among serum samples from patients with different HBV-related hepatic diseases and to evaluate their possible value in the diagnosis of these diseases.
METHODS: The surface-enhanced laser desorption or ionization time-of-flight mass spectroscopy (SELDI-TOF-MS) was used to screen differentially expressed proteins among serum samples, in which high-abundance proteins had been removed with acetonitrile, collected from patients with asymptomatic chronic hepatitis B (ASC), chronic hepatitis B (CHB), liver cirrhosis (LC), hepatocellular carcinoma (HCC), and normal controls. Diagnostic models for each disease were then established with differentially expressed proteins. Protein databases were searched to predict the possible structure and function of differentially expressed proteins.
RESULTS: Compared with the normal control group, 63 differentially expressed protein peaks were detected in the ASC group, of which 29 were up-regulated and 34 down-regulated (P < 0.05); 57 in the CHB group, of which 29 up-regulated and 34 down-regulated; 68 in the LC group, of which 33 up-regulated and 35 down-regulated; and 74 in the HCC group, of which 28 up-regulated and 46 down-regulated. A peak with a m/z of 15 889.8 corresponded to a protein whose expression was up-regulated gradually in an order of healthy controls, ASC, CHB and LC patients, and its expression level in the HCC group was lower than those in the CHB group and LC group. The expression of a protein with a m/z of 11 742.2 was higher in the LC group and HCC group than in other groups, and its expression was gradually increased in an order of healthy controls, CHB, and LC patients, or in another order of healthy controls, CHB, and HCC patients. The sensitivity and specificity using the protein peak at 11 742.2 for diagnosis of LC were 90% and 86.67% and for HCC were 93.33% and 83.33%, respectively.
CONCLUSION: Ten protein peaks with m/z values of 8 709.7, 13 759.8, 14 004.0, 15 361.89, 16 072.3, 2 746.8, 3 449.1, 3 941.06, 4 098.3, and 9 445.5 correspond to proteins that might be involved in HBV infection. The protein peak with a m/z of 15 889.8 might be used as a biomarker for early diagnosis of HBV-related liver cirrhosis, while that with a m/z of 11 742.2 might be an important biomarker for the development of HBV-related liver cirrhosis or HCC.
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10
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Sun L, Chen H, Hu C, Wang P, Li Y, Xie J, Tang F, Ba D, Zhang X, He W. Identify biomarkers of neuropsychiatric systemic lupus erythematosus by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with weak cation magnetic beads. J Rheumatol 2011; 38:454-61. [PMID: 21239757 DOI: 10.3899/jrheum.100550] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
OBJECTIVE To identify proteomic biomarkers in cerebrospinal fluid (CSF) and develop a diagnostic proteomic model for neuropsychiatric systemic lupus erythematosus (NPSLE). METHODS CSF proteomic spectra were generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cation exchange (WCX) magnetic beads. The spectra were taken from 27 patients with NPSLE before and after treatment, and 27 controls including 17 patients with scoliosis and 10 patients with SLE but without neuropsychiatric manifestation. Discriminating peaks were processed by Biomarker Patterns Software to build a decision tree model for NPSLE classification. In addition, CSF samples of 12 patients with NPSLE, 12 patients with lumbar disc herniation, and 9 patients with other neurological conditions were used as a blind test group to verify the accuracy of the model. RESULTS Twelve discriminating mass-to-charge (m/z) peaks were identified between NPSLE and controls: m/z peaks 7740, 11962, 8065, 7661, 6637, 5978, 11384, 11744, 8595, 10848, 7170, and 5806. The diagnostic decision tree model, built with a panel of m/z peaks 8595, 7170, 7661, 7740, and 5806, recognized NPSLE with both sensitivity and specificity of 92.6%, based on training group samples, and sensitivity and specificity of 91.7% and 85.7%, respectively, based on the blind test group. In addition, the root node m/z peak 8595 protein, which was downregulated in the CSF of patients with NPSLE after treatment, was identified and confirmed as ubiquitin by immunoprecipitation and ELISA. CONCLUSION Potential CSF biomarkers for NPSLE are identified by MALDI-TOF-MS combined with WCX magnetic beads. The novel diagnostic proteomic model with m/z peaks 8595, 7170, 7661, 7740, and 5806 is highly sensitive and relatively specific for NPSLE diagnosis. The level of ubiquitin in CSF is a promising biomarker for active NPSLE.
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Affiliation(s)
- Ling Sun
- Department of Rheumatology, Chinese Academy of Medical Science, Beijing 100005, China
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Niu Q, Huang Z, Shi Y, Wang L, Pan X, Hu C. Specific serum protein biomarkers of rheumatoid arthritis detected by MALDI-TOF-MS combined with magnetic beads. Int Immunol 2010; 22:611-8. [PMID: 20497952 DOI: 10.1093/intimm/dxq043] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVES To identify novel serum protein biomarkers and establish diagnostic pattern for rheumatoid arthritis (RA) by using proteomic technology. METHODS Serum proteomic spectra were generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. A training set of spectra, derived from analyzing sera from 22 patients with RA, 26 patients with other autoimmune diseases and 25 age- and sex-matched healthy volunteers, was used to train and develop a decision tree model with a machine learning algorithm called decision boosting. A blinded testing set, including 21 patients with RA, 24 patients with other autoimmune diseases and 25 healthy people, was used to examine the accuracy of the model. RESULTS A decision tree model was established, consisting of four potential protein biomarkers whose m/z values were 4966.88, 5065.3, 5636.97 and 7766.87, respectively. In validation test, the decision tree model could differentiate RA from other autoimmune diseases and healthy people with the sensitivity of 85.71% and specificity of 87.76%, respectively. CONCLUSIONS The present data suggested that MALDI-TOF-MS combined with magnetic beads could screen and identify some novel serum protein biomarkers related to RA. The proteomic pattern based on the four candidate biomarkers is of value for laboratory diagnosis of RA.
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Affiliation(s)
- Qian Niu
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, No. 37, Guo Xue Xiang, Chengdu 610041, The People's Republic of China
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Shevchenko VE, Arnotskaya NE, Zaridze DG. Detection of lung cancer using plasma protein profiling by matrix-assisted laser desorption/ionization mass spectrometry. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2010; 16:539-549. [PMID: 20625202 DOI: 10.1255/ejms.1080] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
There are no satisfactory plasma biomarkers which are available for the early detection and monitoring of lung cancer, one of the most frequent cancers worldwide. The aim of this study is to explore the application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS) to plasma proteomic patterns to distinguish lung cancer patients from healthy individuals. The EDTA plasma samples have been pre-fractionated using magnetic bead kits functionalized with weak cation exchange coatings. We compiled MS protein profiles for 90 patients with squamous cell carcinomas (SCC) and compared them with profiles from 187 healthy controls. The MALDI-ToF spectra were analyzed statistically using ClinProTools bioinformatics software. Depending on the sample used, up to 441 peaks/spectrum could be detected in a mass range of 1000-20,000 Da; 33 of these proteins had statistically differential expression levels between SCC and control plasma (P < 0.001). The series of the peaks were automatically chosen as potential biomarker patterns in the training set. They allowed the discrimination of plasma samples from healthy control and samples from SCC patients (sensitivity and specificity >90%) in external validation test. These results suggest that plasma MALDI-ToF MS protein profiling can distinguish patients with SCC and also from healthy individuals with relatively high sensitivity and specificity and that MALDI- ToF MS is a potential tool for the screening of lung cancer.
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Affiliation(s)
- Valeriy E Shevchenko
- N.N. Blokhin Russian Cancer Research Center, 24 Kashirskoye sh., Moscow 115478, Russia.
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13
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Guo J, Wang W, Liao P, Lou W, Ji Y, Zhang C, Wu J, Zhang S. Identification of serum biomarkers for pancreatic adenocarcinoma by proteomic analysis. Cancer Sci 2009; 100:2292-301. [PMID: 19775290 PMCID: PMC11159697 DOI: 10.1111/j.1349-7006.2009.01324.x] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Diagnosis of pancreatic adenocarcinoma (PaCa) at an early stage is important for successful treatment and improving the prognosis of patients. Serum samples were applied to strong anionic exchange chromatography (SAX) protein chips for protein profiling by surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to distinguish PaCa from noncancer. The Wilcoxon rank-sum test, decision tree algorithm, and logistic regression were used to statistically analyze the multiple protein peaks. Sixty-one protein peaks between 2000 and 30,000 m/z ratios were detected to establish multiple decision classification trees for differentiating the known disease states. A sensitivity of 0.833 and a specificity of 1.000 were obtained in distinguishing PaCa from healthy controls and benign pancreatic diseases. Six protein biomarkers related to different PaCa TNM stages were detected (P < 0.01). One protein biomarker (m/z 4016) rich in PaCa had a down-regulated trend when preoperative and postoperative samples (P < 0.05) were compared. Three protein biomarkers (m/z 4155, 4791, and 28,068) were detected in the differential diagnosis of the three test groups (P < 0.05). A peak m/z 28 068 was identified as C14orf16 using ProteinChip immunoassay. C14orf166 levels were significantly higher in the serum of patients with PaCa compared with the control group using a sandwich immunoenzymatic system. Immunolabeling of tissue sections revealed that the C14orf166 protein was strongly expressed in tumor cells. The results suggest that SELDI-TOF-MS serum profiling is helpful for the diagnostic, prognostic or therapeutic effects of PaCa, which is superior to CA 19-9. The identified protein biomarker C14orf166 is a potential biomarker of PaCa.
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Affiliation(s)
- Jinghui Guo
- Department of Gastroenterology, Affiliated Zhongshan Hospital of Fudan University, Fudan University Medical College, Shanghai, China
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Findeisen P, Neumaier M. Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective. Clin Chem Lab Med 2009; 47:666-84. [PMID: 19445650 DOI: 10.1515/cclm.2009.159] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.
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Affiliation(s)
- Peter Findeisen
- Institute for Clinical Chemistry, Medical Faculty Mannheim of the University of Heidelberg, Heidelberg, Germany.
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Oh JH, Lotan Y, Gurnani P, Rosenblatt KP, Gao J. Prostate cancer biomarker discovery using high performance mass spectral serum profiling. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2009; 96:33-41. [PMID: 19423179 DOI: 10.1016/j.cmpb.2009.04.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2008] [Revised: 04/04/2009] [Accepted: 04/04/2009] [Indexed: 05/27/2023]
Abstract
Prostate-specific antigen (PSA) is the most widely used serum biomarker for early detection of prostate cancer (PCA). Nevertheless, PSA level can be falsely elevated due to prostatic enlargement, inflammation or infection, which limits the PSA test specificity. The objective of this study is to use a machine learning approach for the analysis of mass spectrometry data to discover more reliable biomarkers that distinguish PCA from benign specimens. Serum samples from 179 prostate cancer patients and 74 benign patients were analyzed. These samples were processed using ProXPRESSION Biomarker Enrichment Kits (PerkinElmer). Mass spectra were acquired using a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time-of-flight (MALDI-O-TOF) mass spectrometer. In this study, we search for potential biomarkers using our feature selection method, the Extended Markov Blanket (EMB). From the new marker selection algorithm, a panel of 26 peaks achieved an accuracy of 80.7%, a sensitivity of 83.5%, a specificity of 74.4%, a positive predictive value (PPV) of 87.9%, and a negative predictive value (NPV) of 68.2%. On the other hand, when PSA alone was used (with a cutoff of 4.0ng/ml), a sensitivity of 66.7%, a specificity of 53.6%, a PPV of 73.5%, and a NPV of 45.4% were obtained.
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Affiliation(s)
- Jung Hun Oh
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA
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16
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Wang Q, Shen J, Li ZF, Jie JZ, Wang WY, Wang J, Zhang ZT, Li ZX, Yan L, Gu J. Limitations in SELDI-TOF MS whole serum proteomic profiling with IMAC surface to specifically detect colorectal cancer. BMC Cancer 2009; 9:287. [PMID: 19689818 PMCID: PMC2743709 DOI: 10.1186/1471-2407-9-287] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2009] [Accepted: 08/19/2009] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Surface enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF-MS) analysis on serum samples was reported to be able to detect colorectal cancer (CRC) from normal or control patients. We carried out a validation study of a SELDI-TOF MS approach with IMAC surface sample processing to identify CRC. METHODS A retrospective cohort of 338 serum samples including 154 CRCs, 67 control cancers and 117 non-cancerous conditions was profiled using SELDI-TOF-MS. RESULTS No CRC "specific" classifier was found. However, a classifier consisting of two protein peaks separates cancer from non-cancerous conditions with high accuracy. CONCLUSION In this study, the SELDI-TOF-MS-based protein expression profiling approach did not perform to identify CRC. However, this technique is promising in distinguishing patients with cancer from a non-cancerous population; it may be useful for monitoring recurrence of CRC after treatment.
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Affiliation(s)
- Qi Wang
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Colorectal Surgery, Peking University School of Oncology, Beijing Cancer Hospital & Institute, Beijing, PR China.
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17
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Abstract
Diagnostic oncoproteomics is the application of proteomic techniques for the diagnosis of malignancies. A new mass spectrometric technology involves surface enhanced laser desorption ionization combined with time-of flight mass analysis (SELDI-TOF-MS), using special protein chips. After the description of the relevant principles of the technique, including approaches to proteomic pattern diagnostics, applications are reviewed for the diagnosis of ovarian, breast, prostate, bladder, pancreatic, and head and neck cancers, and also several other malignancies. Finally, problems and prospects of the approach are discussed.
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Affiliation(s)
- John Roboz
- Division of Hematology-Oncology, Department of Medicine, Mount Sinai School of Medicine, New York, New York, USA
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18
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Pakharukova NA, Pastushkova LK, Trifonova OP, Pyatnitsky MA, Vlasova MA, Nikitin IP, Moshkovsky SA, Nikolayev EN, Larina IM. Optimization of serum proteome profiling of healthy humans. ACTA ACUST UNITED AC 2009. [DOI: 10.1134/s0362119709030116] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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19
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Huang Z, Shi Y, Cai B, Wang L, Wu Y, Ying B, Qin L, Hu C, Li Y. MALDI-TOF MS combined with magnetic beads for detecting serum protein biomarkers and establishment of boosting decision tree model for diagnosis of systemic lupus erythematosus. Rheumatology (Oxford) 2009; 48:626-31. [PMID: 19389822 DOI: 10.1093/rheumatology/kep058] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVES To discover novel potential biomarkers and establish a diagnostic pattern for SLE by using proteomic technology. METHODS Serum proteomic spectra were generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with weak cationic exchange magnetic beads. A training set of spectra, derived from analysing sera from 32 patients with SLE, 43 patients with other autoimmune diseases and 43 age- and sex-matched healthy volunteers, was used to train and develop a decision tree model with a machine learning algorithm called decision boosting. A blinded testing set, including 32 patients with SLE, 42 patients with other autoimmune diseases and 40 healthy people, was used to determine the accuracy of the model. RESULTS The diagnostic pattern with a panel of four potential protein biomarkers of mass-to-charge (m/z) ratio 4070.09, 7770.45, 28 045.1 and 3376.02 could accurately recognize 25 of 32 patients with SLE, 36 of 42 patients with other autoimmune diseases and 36 of 40 healthy people. CONCLUSIONS The preliminary data suggested a potential application of MALDI-TOF MS combined with magnetic beads as an effective technology to profile serum proteome, and with pattern analysis, a diagnostic model comprising four potential biomarkers was indicated to differentiate individuals with SLE from RA, SS, SSc and healthy controls rapidly and precisely.
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Affiliation(s)
- Zhuochun Huang
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China
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20
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Ocak S, Chaurand P, Massion PP. Mass spectrometry-based proteomic profiling of lung cancer. PROCEEDINGS OF THE AMERICAN THORACIC SOCIETY 2009; 6:159-70. [PMID: 19349484 PMCID: PMC2674226 DOI: 10.1513/pats.200809-108lc] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/22/2008] [Accepted: 12/05/2008] [Indexed: 01/02/2023]
Abstract
In an effort to further our understanding of lung cancer biology and to identify new candidate biomarkers to be used in the management of lung cancer, we need to probe these tissues and biological fluids with tools that address the biology of lung cancer directly at the protein level. Proteins are responsible of the function and phenotype of cells. Cancer cells express proteins that distinguish them from normal cells. Proteomics is defined as the study of the proteome, the complete set of proteins produced by a species, using the technologies of large-scale protein separation and identification. As a result, new technologies are being developed to allow the rapid and systematic analysis of thousands of proteins. The analytical advantages of mass spectrometry (MS), including sensitivity and high-throughput, promise to make it a mainstay of novel biomarker discovery to differentiate cancer from normal cells and to predict individuals likely to develop or recur with lung cancer. In this review, we summarize the progress made in clinical proteomics as it applies to the management of lung cancer. We will focus our discussion on how MS approaches may advance the areas of early detection, response to therapy, and prognostic evaluation.
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Affiliation(s)
- Sebahat Ocak
- Division of Allergy, Pulmonary and Critical Care Medicine, Thoracic Oncology Center, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee; Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University Medical Center, Nashville, Tennessee; and Veterans Affairs Medical Center, Nashville, Tennessee
| | - Pierre Chaurand
- Division of Allergy, Pulmonary and Critical Care Medicine, Thoracic Oncology Center, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee; Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University Medical Center, Nashville, Tennessee; and Veterans Affairs Medical Center, Nashville, Tennessee
| | - Pierre P. Massion
- Division of Allergy, Pulmonary and Critical Care Medicine, Thoracic Oncology Center, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee; Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University Medical Center, Nashville, Tennessee; and Veterans Affairs Medical Center, Nashville, Tennessee
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21
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Qiu F, Liu HY, Dong ZN, Feng YJ, Zhang XJ, Tian YP. Searching for Potential Ovarian Cancer Biomarkers with Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry. AMERICAN JOURNAL OF BIOMEDICAL SCIENCES 2009; 1:80-90. [PMID: 20664751 PMCID: PMC2907187 DOI: 10.5099/aj090100080] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Ovarian cancer is a common gynecological malignant disease, causing more deaths among women .The key objective in the treatment of ovarian cancer is early diagnosis. The objective of our study was to seek new ovarian cancer biomarkers based on a serum protein profile with the aim of discriminating ovarian cancer patients from healthy controls. An MB-WCX kit was used to analyze serum samples obtained from 20 ovarian cancer patients and 20 healthy controls and then we generated MALDI-TOF protein profiles from the analysis. After pre-processing of the spectra, linear analysis with ClinProTools bioinformatics software was used to classify protein profiles and search for prominent peaks that could be used as potential ovarian cancer biomarkers. Using ClinproTools bioinformatics and statistical software, we found 5 prominent expressed proteins in the ovarian cancer and healthy control groups. The mass to charge ratio were 4648.21(m/z), 9294.03(m/z), 3886.1(m/z), 9066.38(m/z) and 4254.71(m/z), respectively, and the former four proteins were expressed higher in the ovarian cancer patients, but the later one was expressed at lower levels in the cancer patients. The sensitivity and specificity were both more than 90%. From our study, we found that MALDI-TOF MS is a high-throughput sample preparation method and is a new potential tool for the diagnosis of human disease, not only to search for new early detection biomarkers in the ovarian cancer patients' serum samples, but also with a potential use for routine clinical work.
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Affiliation(s)
- Feng Qiu
- Department of Clinical Biochemistry, Chinese PLA General Hospital, 28 Fu-Xing Road, Beijing 100853, China
| | - Hong-Ying Liu
- Department of Clinical Biochemistry, Chinese PLA General Hospital, 28 Fu-Xing Road, Beijing 100853, China
| | - Zhen-Nan Dong
- Department of Clinical Biochemistry, Chinese PLA General Hospital, 28 Fu-Xing Road, Beijing 100853, China
| | - Ying-Ji Feng
- Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - X-J Zhang
- Department of Clinical Biochemistry, Chinese PLA General Hospital, 28 Fu-Xing Road, Beijing 100853, China
- Department of Chemistry, University of South Florida, 4202 E. Fowler Ave., CHE 205A, Tampa, Fl 33620-5250, USA
| | - Ya-Ping Tian
- Department of Clinical Biochemistry, Chinese PLA General Hospital, 28 Fu-Xing Road, Beijing 100853, China
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22
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Ma N, Ge CL, Luan FM, Yao DB, Hu CJ, Li N, Liu YF. Serum protein fingerprint of patients with pancreatic cancer by SELDI technology. Chin J Cancer Res 2008; 20:171-176. [DOI: 10.1007/s11670-008-0171-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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23
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Ummanni R, Junker H, Zimmermann U, Venz S, Teller S, Giebel J, Scharf C, Woenckhaus C, Dombrowski F, Walther R. Prohibitin identified by proteomic analysis of prostate biopsies distinguishes hyperplasia and cancer. Cancer Lett 2008; 266:171-85. [DOI: 10.1016/j.canlet.2008.02.047] [Citation(s) in RCA: 70] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2007] [Revised: 02/18/2008] [Accepted: 02/19/2008] [Indexed: 10/22/2022]
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24
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A serum Biomarker model to diagnose pancreatic cancer using proteomic fingerprint technology. ACTA ACUST UNITED AC 2008. [DOI: 10.1007/s11805-008-0200-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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25
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Whelan LC, Power KAR, McDowell DT, Kennedy J, Gallagher WM. Applications of SELDI-MS technology in oncology. J Cell Mol Med 2008; 12:1535-47. [PMID: 18266982 PMCID: PMC3918069 DOI: 10.1111/j.1582-4934.2008.00250.x] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Considerable interest, speculation and controversy have been generated utilising surface-enhanced laser desorption/ionization in conjunction with mass spectrometry (SELDI-MS) for the diagnosis, prognosis and therapeutic monitoring of cancer and offers an attractive approach to cancer biomarker discovery from tissues and biological fluids. This technology utilises a combination of mass spectrometry and chromatography to facilitate protein profiling of complex biological mixtures. Compared to some other more traditional proteomic platforms, such as 2D polyacrylamide gel electrophoresis, it has a high-throughput capability and can resolve low-mass proteins. However, a considerable number of challenging issues related to the design of studies, including reproducibility, sensitivity, specificity, variation in sample collection, processing and storage, have been reported as problematic with this technology; albeit some of these concerns could perhaps also be lauded against other proteomic approaches that have attempted to address complex protein mixtures, such as plasma. Applications, successes and limitations of SELDI-MS in both clinical and basic science arenas will be reviewed in this article.
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Affiliation(s)
- L C Whelan
- UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Ireland
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26
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27
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Zhang X, Wang B, Zhang XS, Li ZM, Guan ZZ, Jiang WQ. Serum diagnosis of diffuse large B-cell lymphomas and further identification of response to therapy using SELDI-TOF-MS and tree analysis patterning. BMC Cancer 2007; 7:235. [PMID: 18163913 PMCID: PMC2242801 DOI: 10.1186/1471-2407-7-235] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2007] [Accepted: 12/29/2007] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Currently, there are no satisfactory biomarkers available to screen for diffuse large B cell lymphoma (DLBCL) or to identify patients who do not benefit from standard anti-cancer therapies. In this study, we used serum proteomic mass spectra to identify potential serum biomarkers and biomarker patterns for detecting DLBCL and patient responses to therapy. METHODS The proteomic spectra of crude sera from 132 patients with DLBCL and 75 controls were performed by SELDI-TOF-MS and analyzed by Biomarker Patterns Software. RESULTS Nine peaks were considered as potential DLBCL discriminatory biomarkers. Four peaks were considered as biomarkers for predicting the patient response to standard therapy. The proteomic patterns achieved a sensitivity of 94% and a specificity of 94% for detecting DLBCL samples in the test set of 85 samples, and achieved a sensitivity of 94% and a specificity of 92% for detecting poor prognosis patients in the test set of 66 samples. CONCLUSION These proteomic patterns and potential biomarkers are hoped to be useful in clinical applications for detecting DLBCL patients and predicting the response to therapy.
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Affiliation(s)
- Xing Zhang
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China.
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28
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Christensen GB, Cannon-Albright LA, Thomas A, Camp NJ. Extracting disease risk profiles from expression data for linkage analysis: application to prostate cancer. BMC Proc 2007; 1 Suppl 1:S82. [PMID: 18466585 PMCID: PMC2367601 DOI: 10.1186/1753-6561-1-s1-s82] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
The genetic factors underlying many complex traits are not well understood. The Genetic Analysis Workshop 15 Problem 1 data present the opportunity to explore whether gene expression data from microarrays can be utilized to define useful phenotypes for linkage analysis in complex diseases. We utilize expression profiles for multiple genes that have been associated with a disease to develop a composite 'risk profile' that can be used to map other loci involved in the same disease process. Using prostate cancer as our disease of interest, we identified 26 genes whose expression levels had previously been associated with prostate cancer and defined three phenotypes: high, neutral, or low risk profiles, based on individual expression levels. Linkage analyses using MCLINK, a Markov-chain Monte Carlo method, and MERLIN were performed for all three phenotypes. Both methods were in very close agreement. Genome-wide suggestive linkage evidence was observed on chromosomes 6 and 4. It was interesting to note that the linkage signals did not appear to be strongly influenced by the location of the original 26 genes used in the phenotype definition, indicating that composite measures may have potential to locate additional genes in the same process. In this example, however, extreme caution is necessary in any extrapolation of the identified loci to prostate cancer due to the lack of data regarding the behavior of these genes' expression level in lymphoblastoid cells. Our results do indicate there exists potential to augment our current knowledge about the relationships among genes associated with complex diseases using expression data.
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Affiliation(s)
- G Bryce Christensen
- Department of Biomedical Informatics, University of Utah, 391 Chipeta Way Suite D, Salt Lake City, Utah 84108-1266, USA.
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29
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Yang YH, Zhang S, Cui JF, Lu B, Dong XH, Song XY, Liu YK, Zhu XX, Hu RM. Diagnostic potential of serum protein pattern in Type 2 diabetic nephropathy. Diabet Med 2007; 24:1386-92. [PMID: 18042080 DOI: 10.1111/j.1464-5491.2007.02312.x] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
AIMS Microalbuminuria is the earliest clinical sign of diabetic nephropathy (DN). However, the multifactorial nature of DN supports the application of combined markers as a diagnostic tool. Thus, another screening approach, such as protein profiling, is required for accurate diagnosis. Surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a novel method for biomarker discovery. We aimed to use SELDI and bioinformatics to define and validate a DN-specific protein pattern in serum. METHODS SELDI was used to obtain protein or polypeptide patterns from serum samples of 65 patients with DN and 65 non-DN subjects. From signatures of protein/polypeptide mass, a decision tree model was established for diagnosing the presence of DN. We estimated the proportion of correct classifications from the model by applying it to a masked group of 22 patients with DN and 28 non-DN subjects. The weak cationic exchange (CM10) ProteinChip arrays were performed on a ProteinChip PBS IIC reader. RESULTS The intensities of 22 detected peaks appeared up-regulated, whereas 24 peaks were down-regulated more than twofold (P < 0.01) in the DN group compared with the non-DN groups. The algorithm identified a diagnostic DN pattern of six protein/polypeptide masses. On masked assessment, prediction models based on these protein/polypeptides achieved a sensitivity of 90.9% and specificity of 89.3%. CONCLUSION These observations suggest that DN patients have a unique cluster of molecular components in serum, which are present in their SELDI profile. Identification and characterization of these molecular components will help in the understanding of the pathogenesis of DN. The serum protein signature, combined with a tree analysis pattern, may provide a novel clinical diagnostic approach for DN.
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Affiliation(s)
- Y-H Yang
- Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China
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Bitarte N, Bandrés E, Zárate R, Ramirez N, Garcia-Foncillas J. Moving forward in colorectal cancer research, what proteomics has to tell. World J Gastroenterol 2007; 13:5813-21. [PMID: 17990347 PMCID: PMC4205428 DOI: 10.3748/wjg.v13.i44.5813] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer is the third most common cancer and is highly fatal. During the last several years, research has been primarily based on the study of expression profiles using microarray technology. But now, investigators are putting into practice proteomic analyses of cancer tissues and cells to identify new diagnostic or therapeutic biomarkers for this cancer. Because the proteome reflects the state of a cell, tissue or organism more accurately, much is expected from proteomics to yield better tumor markers for disease diagnosis and therapy monitoring. This review summarizes the most relevant applications of proteomics the biomarker discovery for colorectal cancer.
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31
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Yildiz PB, Shyr Y, Rahman JSM, Wardwell NR, Zimmerman LJ, Shakhtour B, Gray WH, Chen S, Li M, Roder H, Liebler DC, Bigbee WL, Siegfried JM, Weissfeld JL, Gonzalez AL, Ninan M, Johnson DH, Carbone DP, Caprioli RM, Massion PP. Diagnostic accuracy of MALDI mass spectrometric analysis of unfractionated serum in lung cancer. J Thorac Oncol 2007; 2:893-901. [PMID: 17909350 PMCID: PMC4220686 DOI: 10.1097/jto.0b013e31814b8be7] [Citation(s) in RCA: 94] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
PURPOSE There is a critical need for improvements in the noninvasive diagnosis of lung cancer. We hypothesized that matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) analysis of the most abundant peptides in the serum may distinguish lung cancer cases from matched controls. PATIENTS AND METHODS We used MALDI MS to analyze unfractionated serum from a total of 288 cases and matched controls split into training (n = 182) and test sets (n = 106). We used a training-testing paradigm with application of the model profile defined in a training set to a blinded test cohort. RESULTS Reproducibility and lack of analytical bias was confirmed in quality-control studies. A serum proteomic signature of seven features in the training set reached an overall accuracy of 78%, a sensitivity of 67.4%, and a specificity of 88.9%. In the blinded test set, this signature reached an overall accuracy of 72.6 %, a sensitivity of 58%, and a specificity of 85.7%. The serum signature was associated with the diagnosis of lung cancer independently of gender, smoking status, smoking pack-years, and C-reactive protein levels. From this signature, we identified three discriminatory features as members of a cluster of truncated forms of serum amyloid A. CONCLUSIONS We found a serum proteomic profile that discriminates lung cancer from matched controls. Proteomic analysis of unfractionated serum may have a role in the noninvasive diagnosis of lung cancer and will require methodological refinements and prospective validation to achieve clinical utility.
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MESH Headings
- Adenocarcinoma/blood
- Adenocarcinoma/pathology
- Biomarkers, Tumor/blood
- Blood Proteins/metabolism
- Carcinoma, Large Cell/blood
- Carcinoma, Large Cell/pathology
- Carcinoma, Non-Small-Cell Lung/blood
- Carcinoma, Non-Small-Cell Lung/pathology
- Carcinoma, Small Cell/blood
- Carcinoma, Small Cell/pathology
- Case-Control Studies
- Chromatography, Liquid
- Cohort Studies
- Female
- Humans
- Lung Neoplasms/blood
- Lung Neoplasms/pathology
- Male
- Middle Aged
- Neoplasm Proteins/metabolism
- Neoplasm Staging
- Neoplasms, Squamous Cell/blood
- Neoplasms, Squamous Cell/pathology
- Prognosis
- Proteomics
- Sensitivity and Specificity
- Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
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Affiliation(s)
- Pinar B. Yildiz
- Division of Allergy, Pulmonary and Critical Care Medicine, Nashville, Tennessee
- Specialized Program of Research Excellence in Lung Cancer, , Nashville, Tennessee
| | - Yu Shyr
- Specialized Program of Research Excellence in Lung Cancer, , Nashville, Tennessee
- Department of Biostatistics, Nashville, Tennessee
| | | | - Noel R. Wardwell
- Division of Allergy, Pulmonary and Critical Care Medicine, Nashville, Tennessee
| | | | | | | | - Shuo Chen
- Department of Biostatistics, Nashville, Tennessee
| | - Ming Li
- Department of Biostatistics, Nashville, Tennessee
| | | | | | - William L. Bigbee
- Specialized Program of Research Excellence in Lung Cancer University of Pittsburgh Cancer Institute, Hillman Cancer Center, Pittsburgh, Pennsylvania
| | - Jill M. Siegfried
- Specialized Program of Research Excellence in Lung Cancer University of Pittsburgh Cancer Institute, Hillman Cancer Center, Pittsburgh, Pennsylvania
| | - Joel L. Weissfeld
- Specialized Program of Research Excellence in Lung Cancer University of Pittsburgh Cancer Institute, Hillman Cancer Center, Pittsburgh, Pennsylvania
| | | | - Mathew Ninan
- Department of Thoracic Surgery, Vanderbilt University, Nashville, Tennessee
| | - David H. Johnson
- Division of Hematology–Oncology, Department of Medicine, Nashville, Tennessee
- Specialized Program of Research Excellence in Lung Cancer, , Nashville, Tennessee
| | - David P. Carbone
- Division of Hematology–Oncology, Department of Medicine, Nashville, Tennessee
- Specialized Program of Research Excellence in Lung Cancer, , Nashville, Tennessee
| | - Richard M. Caprioli
- Specialized Program of Research Excellence in Lung Cancer, , Nashville, Tennessee
- Department of Biochemistry, Nashville, Tennessee
| | - Pierre P. Massion
- Division of Allergy, Pulmonary and Critical Care Medicine, Nashville, Tennessee
- Specialized Program of Research Excellence in Lung Cancer, , Nashville, Tennessee
- Veterans Affairs Medical Center, Nashville, Tennessee
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Bermúdez-Crespo J, López JL. A better understanding of molecular mechanisms underlying human disease. Proteomics Clin Appl 2007; 1:983-1003. [PMID: 21136752 DOI: 10.1002/prca.200700086] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2007] [Indexed: 01/06/2023]
Abstract
This review summarises and discusses the degree to which proteomics is contributing to medical care, providing examples and signspots for future directions. Why do genomic approaches provide a limited view of gene expression? Because of the multifactorial nature of many diseases, proteomics enables us to understand the molecular basis of disease, not only at the organism, whole-cell or tissue levels, but also in subcellular structures, protein complexes and biological fluids. The application of proteomics in medicine is expected to have a major impact by providing an integrated view of individual disease processes. This review describes several proteomic platforms and examines the role of proteomics as a tool for clinical biomarker discovery, the identification of prognostic and earlier diagnostic markers, their use in monitoring the effects of drug treatments and eventually find more efficient and safer therapeutics for a wide range of pathologies.
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Affiliation(s)
- José Bermúdez-Crespo
- Department of Genetics, Faculty of Biology, University of Santiago de Compostela, Santiago de Compostela, Spain
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Hellström M, Jonmarker S, Lehtiö J, Auer G, Egevad L. Proteomics in clinical prostate research. Proteomics Clin Appl 2007; 1:1058-65. [PMID: 21136757 DOI: 10.1002/prca.200700082] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2007] [Indexed: 11/08/2022]
Abstract
The incidence of early prostate cancer (PCa) has increased rapidly in recent years. The majority of newly diagnosed PCa are in early tumor phase. Presently, we do not have adequate biomarkers to assess tumor aggressiveness in individual cases. Consequently, too many patients are given curatively intended treatment. An exploration of the human proteome may provide clinically useful markers. 2-DE has been successfully used for analysis of the protein phenotype using clinical samples. Proteins are separated according to size and charge, gels are compared by image analysis, protein spots of interest are excised, and proteins identified by MS. This method is exploratory and allows protein identification. However, low-abundance proteins are difficult to detect and 2-DE is currently too labor-intensive for routine use. In recent years, nongel based techniques, such as LC-MS, SELDI-MS, and protein arrays have emerged. They require smaller sample sizes and can be more automated than 2-DE. In this review, we describe studies of the protein expression of benign prostatic tissue and PCa, which is likely to serve as the first step in prognostic biomarker discovery. The prostate proteome is still far from a complete mapping which would enhance our understanding of PCa biology.
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Affiliation(s)
- Magnus Hellström
- Department of Urology, Karolinska University Hospital, Stockholm, Sweden
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Affiliation(s)
- Haleem J Issaq
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., NCI-Frederick, P.O. Box B, Frederick, Maryland 21702, USA
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Luque-Garcia JL, Neubert TA. Sample preparation for serum/plasma profiling and biomarker identification by mass spectrometry. J Chromatogr A 2007; 1153:259-76. [PMID: 17166507 PMCID: PMC7094463 DOI: 10.1016/j.chroma.2006.11.054] [Citation(s) in RCA: 143] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2006] [Revised: 11/06/2006] [Accepted: 11/16/2006] [Indexed: 01/14/2023]
Abstract
In this article, we present an overview of the different strategies for sample preparation for identification by mass spectrometry (MS) of biomarkers from serum and/or plasma. We consider the effects of the variables involved in sample collection, handling and storage, and describe different approaches for removal of high abundance proteins and serum/plasma fractionation. We review the advantages and disadvantages of such techniques as centrifugal ultrafiltration, different formats for solid phase extraction, organic solvent extraction, gel and capillary electrophoresis, and liquid chromatography. We also discuss a variety of current proteomic methods and their main applications for biomarker-related studies.
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Affiliation(s)
| | - Thomas A. Neubert
- Skirball Institute of Biomolecular Medicine and Department of Pharmacology, New York University School of Medicine, New York, NY 10016, USA
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Zhang X, Wei D, Yap Y, Li L, Guo S, Chen F. Mass spectrometry-based "omics" technologies in cancer diagnostics. MASS SPECTROMETRY REVIEWS 2007; 26:403-31. [PMID: 17405143 DOI: 10.1002/mas.20132] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Many "omics" techniques have been developed for one goal: biomarker discovery and early diagnosis of human cancers. A comprehensive review of mass spectrometry-based "omics" approaches performed on various biological samples for molecular diagnosis of human cancers is presented in this article. Furthermore, the existing and potential problems/solutions (both de facto experimental and bioinformatic challenges), and future prospects have been extensively discussed. Although the use of present omic methods as diagnostic tools are still in their infant stage and consequently not ready for immediate clinical use, it can be envisaged that the "omics"-based cancer diagnostics will gradually enter into the clinic in next 10 years as an important supplement to current clinical diagnostics.
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Affiliation(s)
- Xuewu Zhang
- College of Light Industry and Food Sciences, South China University of Technology, Guangzhou, China.
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Bons JA, Drent M, Bouwman FG, Mariman EC, van Dieijen-Visser MP, Wodzig WK. Potential biomarkers for diagnosis of sarcoidosis using proteomics in serum. Respir Med 2007; 101:1687-95. [PMID: 17446058 DOI: 10.1016/j.rmed.2007.03.002] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2006] [Revised: 02/16/2007] [Accepted: 03/05/2007] [Indexed: 10/23/2022]
Abstract
BACKGROUND Sarcoidosis is a multi-systemic inflammatory disorder, which affects the lungs in 90% of the cases. The main pathologic feature is chronic inflammation resulting in non-caseating granuloma formation. Until now there is no satisfying biomarker for diagnosis or prognosis of sarcoidosis. This study is focused on the detection of potential biomarkers in serum for the diagnosis of sarcoidosis using surface-enhanced laser desorption ionization-time of flight-mass spectrometry (SELDI-TOF-MS). METHODS For detection of potential biomarkers, protein profiles of anion exchange fractionated serum of 35 sarcoidosis patients and 35 healthy controls were compared using SELDI-TOF-MS. Sensitivities and specificities of the potential biomarkers obtained with SELDI-TOF-MS, generated with decision tree algorithm, were compared to the conventional markers angiotensin converting enzyme (ACE) and soluble interleukin-2 receptor (sIL-2R). RESULTS Optimal classification was achieved with metal affinity binding arrays. A single marker with a mass-to-charge (m/z) value of 11,955 resulted in a sensitivity and specificity of 86% and 63%, respectively. A multimarker approach of two peaks, m/z values of 11,734 and 17,377, resulted in a sensitivity and specificity of 74% and 71%, respectively. These sensitivities and specificities were higher compared to measurements of ACE and sIL-2R. Identification of the peak at m/z 17,377 resulted in the alpha-2chain of haptoglobin. CONCLUSIONS This study acts as a proof-of-principle for the use of SELDI-TOF-MS in the detection of new biomarkers for sarcoidosis. The peak of the multimarker at m/z 17,377 was identified as the alpha-2chain of haptoglobin.
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Affiliation(s)
- Judith A Bons
- Department of Clinical Chemistry, University Hospital Maastricht, P. Debyelaan 25, 6202 AZ Maastricht, The Netherlands
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Fung ET, Weinberger SR, Gavin E, Zhang F. Bioinformatics approaches in clinical proteomics. Expert Rev Proteomics 2007; 2:847-62. [PMID: 16307515 DOI: 10.1586/14789450.2.6.847] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Protein expression profiling is increasingly being used to discover, validate and characterize biomarkers that can potentially be used for diagnostic purposes and to aid in pharmaceutical development. Correct analysis of data obtained from these experiments requires an understanding of the underlying analytic procedures used to obtain the data, statistical principles underlying high-dimensional data and clinical statistical tools used to determine the utility of the interpreted data. This review summarizes each of these steps, with the goal of providing the nonstatistician proteomics researcher with a working understanding of the various approaches that may be used by statisticians. Emphasis is placed on the process of mining high-dimensional data to identify a specific set of biomarkers that may be used in a diagnostic or other assay setting.
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Affiliation(s)
- Eric T Fung
- Ciphergen Biosystems, Inc., 6611 Dumbarton Circle, Fremont, CA 94555, USA.
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Ehmann M, Felix K, Hartmann D, Schnölzer M, Nees M, Vorderwülbecke S, Bogumil R, Büchler MW, Friess H. Identification of potential markers for the detection of pancreatic cancer through comparative serum protein expression profiling. Pancreas 2007; 34:205-14. [PMID: 17312459 DOI: 10.1097/01.mpa.0000250128.57026.b2] [Citation(s) in RCA: 112] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Early detection is the only promising approach to significantly improve the survival of patients with pancreatic cancer (PCa). Noninvasive tools for the diagnosis, prognosis, and monitoring of this disease are of urgent need. The purpose of this study was to identify and validate new biomarkers in PCa patient serum samples. METHODS Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry has been applied to analyze serum protein alterations associated with PCa and to identify sets of potential biomarkers indicative for this disease. A cohort of 96 serum samples from patients undergoing PCa surgery was compared with sera from 96 healthy volunteers as controls. The sera were fractionated by anion exchange chromatography, and 3 of 6 fractions were analyzed onto 2 different chromatographic arrays. RESULTS Data analysis revealed 24 differentially expressed protein peaks (P < 0.001), of which 21 were downregulated in the PCa samples. The best single marker can predict 92% of the controls and 89% of the cancer samples correctly. In addition, multivariate pattern analysis was performed. The best pattern model using a set of 3 markers was obtained using fraction 6 on immobilized metal affinity capture, loaded with Cu-Cu arrays. With this pattern model, a sensitivity of 100% and a specificity of 98% for the training data set and a sensitivity of 83% and specificity of 77% for the test data set were achieved with the PCa group set as true positive. Several of protein peaks, including the best single marker at 17.27 kd and other proteins from the pattern models, were purified and identified by peptide mapping and postsource decay-matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. Apolipoprotein A-II, transthyretin, and apolipoprotein A-I were identified as markers, and these identified proteins were decreased at least 2-fold in PCa serum when compared with the control group. CONCLUSIONS PCa is associated with a specific decrease of distinct serum proteins, which allows a reliable differentiation between pancreatic cancer and healthy controls.
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Affiliation(s)
- Michael Ehmann
- Department of General Surgery, University of Heidelberg, INF 110, D-69120 Heidelberg, Germany
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Engwegen JYMN, Mehra N, Haanen JBAG, Bonfrer JMG, Schellens JHM, Voest EE, Beijnen JH. Validation of SELDI-TOF MS serum protein profiles for renal cell carcinoma in new populations. J Transl Med 2007; 87:161-72. [PMID: 17318195 DOI: 10.1038/labinvest.3700503] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Currently, no suitable biomarker for the early detection or follow-up of renal cell carcinoma (RCC) is available. We aimed to validate previously reported potential serum biomarkers for RCC obtained with Surface Enhanced Laser Desorption Ionisation-Time of Flight Mass Spectrometry (SELDI-TOF MS) in our laboratory using distinct patient populations. Two sets of sera from RCC patients and healthy controls (HC) were gathered from different institutes and analysed according to published procedures. The first set (40 RCC, 32 HC) consisted of mainly presurgery samples from patients with disease stages I-IV. The second set (26 RCC, 27 HC) were mostly sera from patients with stage-IV disease, drawn after nephrectomy. Only the increased expression of the previously found serum amyloid-alpha (SAA) peak cluster could be validated in a similar RCC patient subset in both our populations in two independent analyses. It was seen both in early- and late-stage disease and in pre- and postsurgery samples. These results were also confirmed by ELISA. Other previously identified biomarker candidates (mass-to-charge ratio's (m/z) 3900, 4107, 4153, 5352 and 5987) proved difficult to reproduce upon duplicate analysis. Modification of the analytical protocol for these markers resulted in their detection, but we did not achieve satisfactory classification of patients and controls with these alleged biomarkers in any of our two sample sets. Instead, two new peaks (m/z 4289 and 8151) were identified with better performance (sensitivity and specificity approximately 65-90%) for separating patients from controls in the first sample set. Concluding, only the SAA peak cluster was validated as a robust RCC biomarker candidate, which is present in a specific subset of these patients, regardless of disease stage or nephrectomy status. In addition, two new peaks were seen which might prove useful as biomarkers, provided these are validated in new populations.
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Affiliation(s)
- Judith Y M N Engwegen
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute/Slotervaart Hospital, Amsterdam, The Netherlands.
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Göbel T, Vorderwülbecke S, Hauck K, Fey H, Häussinger D, Erhardt A. New multi protein patterns differentiate liver fibrosis stages and hepatocellular carcinoma in chronic hepatitis C serum samples. World J Gastroenterol 2006; 12:7604-12. [PMID: 17171788 PMCID: PMC4088041 DOI: 10.3748/wjg.v12.i47.7604] [Citation(s) in RCA: 37] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
AIM: To identify a multi serum protein pattern as well as single protein markers using surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS) for detection and differentiation of liver fibrosis (F1-F2), liver cirrhosis (F4) and hepatocellular carcinoma (HCC) in patients with chronic hepatitis C virus (HCV).
METHODS: Serum samples of 39 patients with F1/F2 fibrosis, 44 patients with F4 fibrosis, 34 patients with HCC were applied to CM10 arrays and analyzed using the SELDI-TOF ProteinChip System (PBS-IIc; Ciphergen Biosystems) after anion-exchange fractionation. All patients had chronic hepatitis C and histologically confirmed fibrosis stage/HCC. Data were analyzed for protein patterns by multivariate statistical techniques and artificial neural networks.
RESULTS: A 4 peptide/protein multimarker panel (7486, 12 843, 44 293 and 53 598 Da) correctly identified HCCs with a sensitivity of 100% and specificity of 85% in a two way-comparison of HCV-cirrhosis versus HCV-HCC training samples (AUROC 0.943). Sensitivity and specificity for identification of HCC were 68% and 80% for random test samples. Cirrhotic patients could be discriminated against patients with F1 or F2 fibrosis using a 5 peptide/protein multimarker pattern (2873, 6646, 7775, 10 525 and 67 867 Da) with a specificity of 100% and a sensitivity of 85% in training samples (AUROC 0.976) and a sensitivity and specificity of 80% and 67% for random test samples. Combination of the biomarker classifiers with APRI score and alfa-fetopotein (AFP) improved the diagnostic performance. The 6646 Da marker protein for liver fibrosis was identified as apolipoprotein C-I.
CONCLUSION: SELDI-TOF-MS technology combined with protein pattern analysis seems a valuable approach for the identification of liver cirrhosis and hepatocellular carcinoma in patients with chronic hepatitis C. Most probably a combination of different serum markers will help to identify liver cirrhosis and early-stage hepatocellular carcinomas in the future.
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Affiliation(s)
- Thomas Göbel
- Klinik für Gastroenterologie, Hepatologie und Infektiologie, Heinrich-Heine-Universität Düsseldorf, Moorenstr. 5, D-40225 Düsseldorf, Germany
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Abstract
The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.
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Affiliation(s)
- Shen Hu
- School of Dentistry, Division of Oral Biology and Medicine, Dental Research Institute, University of California, Los Angeles, CA 90095, USA.
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Zhou M, Prieto DA, Lucas DA, Chan KC, Issaq HJ, Veenstra TD, Conrads TP. Identification of the SELDI ProteinChip human serum retentate by microcapillary liquid chromatography-tandem mass spectrometry. J Proteome Res 2006; 5:2207-16. [PMID: 16944932 DOI: 10.1021/pr060061h] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Surface-enhanced laser desorption/ionization (SELDI) time-of-flight (TOF) mass spectrometry (MS) has been widely applied for conducting biomarker research with the goal of discovering patterns of proteins and/or peptides from biological samples that reflect disease status. Many diseases, ranging from cancers of the colon, breast, and prostate to Alzheimer's disease, have been studied through serum protein profiling using SELDI-based methods. Although the results from SELDI-based diagnostic studies have generated a great deal of excitement and skepticism alike, the basis of the molecular identities of the features that underpin the diagnostic potential of the mass spectra is still largely unexplored. A detailed investigation has been undertaken to identify the compliment of serum proteins that bind to the commonly used weak cation exchange (WCX-2) SELDI protein chip. Following incubation and washing of a standard serum sample on the WCX-2 sorbent, proteins were harvested, digested with trypsin, fractionated by strong cation exchange liquid chromatography (LC), and subsequently analyzed by microcapillary reversed-phase LC coupled online with an ion-trap mass spectrometer. This analysis resulted in the identification of 383 unique proteins in the WCX-2 serum retentate. Among the proteins identified, 50 (13%) are documented clinical biomarkers with 36 of these (72%) identified from multiple peptides.
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Affiliation(s)
- Ming Zhou
- Laboratory of Proteomics and Analytical Technologies, SAIC-Frederick, Inc., National Cancer Institute at Frederick, P.O. Box B, Frederick, Maryland 21702, USA
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Massion PP, Caprioli RM. Proteomic Strategies for the Characterization and the Early Detection of Lung Cancer. J Thorac Oncol 2006. [DOI: 10.1016/s1556-0864(15)31639-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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Abstract
Although prostate-specific antigen (PSA) has evolved as a very useful tool for detection of prostate cancer, there remains an urgent need for more accurate biomarkers to diagnose prostate cancer and predict cancer-related outcomes. Recent advances in the study of proteomics and high throughput techniques have led to the discovery of many potential biomarkers for prostate cancer. This article briefly reviews the current status of PSA testing and discusses several candidate protein biomarkers for prostate cancer, as well as highlighting some recent proteomic discoveries with the potential to supplement or even replace PSA for the diagnosis and prognosis of prostate cancer.
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Affiliation(s)
- Timothy J Bradford
- Department of Urology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
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Abstract
Molecular profiling studies of human prostate cancer provide great opportunities to identify new prostate cancer biomarkers to improve prostate cancer detection and treatment. Proteomics has distinct advantages over genomic and ribonucleic acid expression studies because it is the proteins that are ultimately responsible for the malignant phenotype. The goal of traditional proteomic studies is to identify disease-specific biomarkers. Two-dimensional (2-D) gel electrophoresis (polyacrylamide gel electrophoresis; PAGE) coupled with mass spectrometry is the most widely used experimental strategy and, to date, has yielded several potentially relevant prostate cancer biomarkers. A promising prostate cancer biomarker identified by 2-D PAGE and mass spectrometry is annexin I. Studies have already confirmed that annexin I is underexpressed in a majority of early stage prostate cancers. Other non-gel-based proteomic technologies that may have improved sensitivity as compared to 2-D PAGE have recently been developed. An example of this is the ProteomeLab PF 2-D (Beckman Coulter, Inc., Fullerton, CA). The goal of most proteomic studies is to identify biomarkers that can be measured by enzyme-linked immunosorbent assay or immunohistochemistry. Improvements in proteomic technology may be changing this paradigm because there are now efforts to develop proteomic technologies directly into clinical diagnostic tests. An example of this technology is surface-enhanced laser desorption ionization time-of-flight mass spectrometry. Using this technology combined with a pattern recognition based bioinformatics tool, discriminatory spectrum proteomic profiles were generated that could help discriminate men with prostate cancer from those with benign prostates. If several technologic hurdles can be overcome, it is possible that methodology will improve the specificity and sensitivity of prostate cancer detection.
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Affiliation(s)
- David K Ornstein
- Department of Urology, The University of California-Irvine, Orange, CA 92868, USA.
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Liang Y, Fang M, Li J, Liu CB, Rudd JA, Kung HF, Yew DTW. Serum proteomic patterns for gastric lesions as revealed by SELDI mass spectrometry. Exp Mol Pathol 2006; 81:176-180. [PMID: 16828742 DOI: 10.1016/j.yexmp.2006.04.008] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2006] [Revised: 03/27/2006] [Accepted: 04/13/2006] [Indexed: 01/04/2023]
Abstract
SELDI mass spectrometry was used to investigate protein expression in sera of patients with gastric cancer and gastritis compared to normal volunteers. Differences in peak morphology and intensity were observed in regions of 5910 Da, 5084 Da, 6640 Da and 8691 Da. Patients with gastric cancer exhibited an up-regulation of the 5910 Da peak and a down-regulation of the 8691 Da peak compared to the healthy volunteers; there was also some bi-partitioning and tri-partitioning at the 5084 Da peak. When comparing the sera of these cancer patients with those of gastritis, the former had an up-regulation of the 5910 Da peak and a down-regulation of the 6640 Da peak. This is the first report showing that SELDI sera analysis may be useful in the screening of gastric lesions.
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Affiliation(s)
- Yong Liang
- Institute of Cell Biology, Medical College of Zhejiang University, Hangzhou, Zhejiang, China
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García-Foncillas J, Bandrés E, Zárate R, Remírez N. Proteomic analysis in cancer research: potential application in clinical use. Clin Transl Oncol 2006; 8:250-61. [PMID: 16648100 DOI: 10.1007/bf02664935] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The ultimate goal of cancer proteomics is to adapt proteomic technologies for routine use in clinical laboratories for the purpose of diagnostic and prognostic classification of disease states, as well as in evaluating drug toxicity and efficacy. The novel technologies allows researchers to facilitate the comprehensive analyses of genomes, transcriptomes, and proteomes in health and disease. The information that is expected from such technologies may soon exert a dramatic change in cancer research and impact dramatically on the care of cancer patients. Analysis of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. The localization of gene products, which is often difficult to deduce from the sequence, can be determined experimentally. Mechanisms, such as regulation of protein function by proteolysis, recycling, and isolation in cell compartments, affect gene products, not genes. Finally, protein-protein interactions and the molecular composition of cellular structures can be determined only at the protein level. The biological variability among patient samples as well as the great dynamic range of biomarker concentrations are currently the main challenges facing efforts to deduce diagnostic patterns that are unique to specific disease states. While several strategies exist to address this problem, we have tried to offer a wide perspective about the current possibilities.
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Affiliation(s)
- Jesús García-Foncillas
- Laboratory of Pharmacogenomics, Center for Medical Applied Research, Department of Oncology and Radiotherapy, University Clinic, University of Navarra, Pamplona, Spain.
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Miles AK, Matharoo-Ball B, Li G, Ahmad M, Rees RC. The identification of human tumour antigens: Current status and future developments. Cancer Immunol Immunother 2006; 55:996-1003. [PMID: 16408215 PMCID: PMC11029826 DOI: 10.1007/s00262-005-0115-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2005] [Accepted: 12/10/2005] [Indexed: 11/25/2022]
Abstract
The biggest challenge facing us today in cancer control and prevention is the identification of novel biomarkers for detection and improved therapeutic interventions to reduce mortality and morbidity rates. Biomarkers are important indicators to inform us of the physiological state of the cell at a specific time. It is now clear that malignant transformation occurs by changes in cellular DNA and protein expression with subsequent clonal proliferation of the altered cells. The affected genes and their expressed protein products or biomarkers are those involved in the normal growth and maintenance of the cancerous cells. These biomarkers could prove pivotal for the identification of early cancer and people at risk of developing cancer. Altered proteins or changes in gene expression in malignant cells may lead to the expression of tumour antigens recognised by host immune system. In this review we discuss current research into the molecular technologies making possible the global genomic-wide analysis of changes in DNA (genotyping), RNA expression (transcriptomics) and protein expression (proteomics) that have accelerated the rate of new biomarker/tumour antigen discovery. To gain a comprehensive understanding of the physiology and pathophysiology of cancer an approach that harmoniously integrates the various 'omic' platforms are key to unraveling the complexity 'needle-in-a-haystack' quality of biomarker/tumour antigen discovery.
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Affiliation(s)
- Amanda K. Miles
- School of Biomedical and Natural Sciences, Nottingham Trent University, Clifton Lane, Clifton, NG11 8NS Nottingham, UK
| | - Balwir Matharoo-Ball
- School of Biomedical and Natural Sciences, Nottingham Trent University, Clifton Lane, Clifton, NG11 8NS Nottingham, UK
| | - Geng Li
- School of Biomedical and Natural Sciences, Nottingham Trent University, Clifton Lane, Clifton, NG11 8NS Nottingham, UK
| | - Murrium Ahmad
- School of Biomedical and Natural Sciences, Nottingham Trent University, Clifton Lane, Clifton, NG11 8NS Nottingham, UK
| | - Robert C. Rees
- School of Biomedical and Natural Sciences, Nottingham Trent University, Clifton Lane, Clifton, NG11 8NS Nottingham, UK
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