Biomarkers in Immunology: from Concepts to Applications
Pages 826 - 835
Abstract
In this paper, we summarized the challenges and promises of the study of immune biomarkers. We reviewed key concepts in biomarker discovery and discussed the framework for applying these concepts in the study of the immune system and its effects on the disease -- cancer, infection, allergy, immunodeficiencies, and autoimmunity. The immune system plays a special role in biomarker discovery since it interacts with all other systems in the human body and immune biomarkers are relevant for large number of diseases.
References
[1]
Adamczyk-Poplawska M et al. 2011. Proteomics for development of vaccine. J Proteomics. 74(12), 2596-616.
[2]
Adams, N. et al. 2011. PIDO, the primary immunodeficiency disease ontology. Bioinformatics. 27(22), 3193--9.
[3]
Anderson, K. S. and LaBaer, J. 2005. The sentinel within: exploiting the immune system for cancer biomarkers. J. Proteome Res. 4(4), 1123--33.
[4]
Armah, H. B. et al. 2007. Cerebrospinal fluid and serum biomarkers of cerebral malaria mortality in Ghanaian children. Malar J. 6, 147.
[5]
Arstila, T. P. et al. 1999. A direct estimate of the human alphabeta T cell receptor diversity. Science. 286(5441), 958--61.
[6]
Azuaje, F. 2010. Bioinformatics and biomarker discovery, omic data analysis for personalised medicine. Wiley-Blackwell.
[7]
Barrallo-Gimeno, A. and Nieto, M. A. 2005. The Snail genes as inducers of cell movement and survival, implications in development and cancer. Development. 132(14), 3151--61.
[8]
Bass, M. B. et al. 2010. Biomarkers as predictors of response to treatment with motesanib in patients with progressive advanced thyroid cancer. J Clin Endocrinol Metab. 95(11), 5018--27.
[9]
Bauer, J. W. et al. 2006. Elevated serum levels of interferon-regulated chemokines are biomarkers for active human systemic lupus erythematosus. PLoS Med. 3(12), e491.
[10]
Bay-Jensen, A. C. et al. 2013. Circulating protein fragments of cartilage and connective tissue degradation are diagnostic and prognostic markers of rheumatoid arthritis and ankylosing spondylitis. PLoS One. 8(1), e54504.
[11]
Bielekova, B. and Martin, R. 2004. Development of biomarkers in multiple sclerosis. Brain. 127(Pt 7), 1463--78.
[12]
Biomarkers Definitions Working Group. 2001. Biomarkers and surrogate endpoints, preferred definitions and conceptual framework. Clin Pharmacol Ther. 69(3), 89--95.
[13]
Blüggel, M. et al. 2011 Toward protein biomarkers for allergy: CD4+ T cell proteomics in allergic and nonallergic subjects sampled in and out of pollen season. J Proteome Res. 10(4), 1558--70.
[14]
Boles, J. W. et al. 2003. Generation of protective immunity by inactivated recombinant staphylococcal enterotoxin B vaccine in nonhuman primates and identification of correlates of immunity. Clin Immunol. 108, 51--9.
[15]
Brusic V and August JT. 2004. The changing field of vaccine development in the genomics era. Pharmacogenomics. 5(6), 597--600.
[16]
Brusic V et al. 1998. Data learning, understanding biological data. In Knowledge Sharing Across Biological and Medical Knowledge Based Systems, Merrill G., Pathak D.K. Ed. AAAI Press, 12--19.
[17]
Brusic V et al. 2005. Information technologies for vaccine research. Expert Rev Vaccines. 4(3), 407--17.
[18]
Chen, R et al. 2013. A bayesian diagnostic system to differentiate glioblastomas from solitary brain metastases. Neuroradiol J. 26(2), 175--83.
[19]
Chen, YD et al. 2004. Artificial neural networks analysis of surface-enhanced laser desorption/ionization mass spectra of serum protein pattern distinguishes colorectal cancer from healthy population. Clin Cancer Res. 10(24), 8380--5.
[20]
Chintamaneni, M. and Bhaskar, M. 2012. Biomarkers in Alzheimer's disease, a review. ISRN Pharmacol. 984786.
[21]
Cohen, I. R. 2007. Biomarkers, self-antigens and the immunological homunculus. J Autoimmun. 29:246--9.
[22]
Cromme, F. V. et al. 1994. Loss of transporter protein, encoded by the TAP-1 gene, is highly correlated with loss of HLA expression in cervical carcinomas. J Exp Med. 179(1), 335--40.
[23]
Davis, M. M. 2008. A prescription for human immunology. Immunity. 29(6), 835--8.
[24]
DelaRosa, O. et al. 2006. Immunological biomarkers of ageing in man: changes in both innate and adaptive immunity are associated with health and longevity. Biogerontology. 7(5-6), 471--81.
[25]
DeNardo, D. G. et al. 2010. Interactions between lymphocytes and myeloid cells regulate pro- versus antitumor immunity. Cancer Metastasis Rev. 29(2), 309--16.
[26]
Doecke, J. D. et al. 2012. Alzheimer's disease neuroimaging initiative. Blood-based protein biomarkers for diagnosis of Alzheimer disease. Arch Neurol. 69(10), 1318--25.
[27]
Draper N and Smith H. 1981. Applied Regression Analysis, 2d Edition, New York, John Wiley & Sons, Inc.
[28]
Eifan, A. O. et al. 2011. Long-term clinical and immunological effects of allergen immunotherapy. Curr Opin Allergy Clin Immunol. 11(6):586--93.
[29]
Enríquez-de-Salamanca, A., Bonini, S., and Calonge, M. 2012. Molecular and cellular biomarkers in dry eye disease and ocular allergy. Curr Opin Allergy Clin Immunol. 12, 523--33.
[30]
Feng, Z. et al. 2013. The early detection research network's specimen reference sets, paving the way for rapid evaluation of potential biomarkers. Clin Chem. 59(1), 68--74.
[31]
Franco, L. M. et al. 2013. Integrative genomic analysis of the human immune response to influenza vaccination. Elife. 2, e00299.
[32]
Frankenstein, Z. et al. 2006. The immune-body cytokine network defines a social architecture of cell interactions. Biol Direct. 1, 32.
[33]
Gibson, D. S. et al. 2010. Diagnostic and prognostic biomarker discovery strategies for autoimmune disorders. J Proteomics. 73(6), 1045--60.
[34]
Gnatenko, D. V. et al. 2010. Class prediction models of thrombocytosis using genetic biomarkers. Blood. 115(1), 7--14.
[35]
Graham WG. 2009. Missing data analysis, making it work in the real world. Annu. Rev. Psychol. 60, 549--76.
[36]
Grivennikov, S. I. et al. 2010. Immunity, inflammation, and cancer. Cell. 140(6), 883--99.
[37]
Habermann K et al. 2009. The gene expression signature of genomic instability in breast cancer is an independent predictor of clinical outcome. Int J Cancer. 124(7), 1552--64.
[38]
Haight T and Jagust J. 2012. Alzheimer's Disease Neuroimaging Initiative, relative contributions of biomarkers in Alzheimer's disease. Ann Epidemiol. 22, 868--75.
[39]
Hamilton, J. A. and Tak, P. P. 2009. The dynamics of macrophage lineage populations in inflammatory and autoimmune diseases. Arthritis Rheum. 60(5), 1210--21.
[40]
Hanahan, D and Weinberg, R. A. 2011. Hallmarks of cancer, the next generation. Cell. 144(5), 646--74.
[41]
Heo, C. K. et al. 2012. Tumor-associated autoantibodies as diagnostic and prognostic biomarkers. BMB Rep 45(12), 677--85.
[42]
Hicklin, D. J. et al. 1999. HLA class I antigen downregulation in human cancers: T-cell immunotherapy revives an old story. Mol Med Today. 5(4), 178--86.
[43]
Hocking, R. 1976. The Analysis and Selection of Variables in Linear Regression. Biometrics. 32(1), 1--49.
[44]
Hollevoet, K. et al. 2011. Serial measurements of mesothelioma serum biomarkers in asbestos-exposed individuals, a prospective longitudinal cohort study. J Thorac Oncol. 6(5), 889--95.
[45]
Hooks, J. J. et al. 1979. Immune interferon in the circulation of patients with autoimmune disease. N Engl J Med. 301(1), 5--8.
[46]
Huang, B. et al. 2005. Toll-like receptors on tumor cells facilitate evasion of immune surveillance. Cancer Res. 65(12), 5009--14.
[47]
Huang, H.C. 2009. Designing a knowledge-based system for strategic planning, a balanced scorecard perspective. Expert Systems Applicat. 36, 209--18.
[48]
Huang, Z. et al. 2009. 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). 48(6), 626--31.
[49]
Hulka, B. S. 1990. Overview of biological markers. In Biological markers in epidemiology, Hulka, B. S., Griffith, J. D., Wilcosky, T. C. Ed. New York, Oxford University Press, 3--15.
[50]
Ibelgaufts, H. 2013. COPE: Cytokines Online Pathfinder Encyclopedia. Version 31.4. DOI=http://www.copewithcytokines.de.
[51]
Jacobsen, M. et al. 2007. Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis. J Mol Med (Berl). 85(6), 613--21.
[52]
Janeway, C. A. and Jr Medzhitov, R. 2002. Innate immune recognition. Annu Rev Immunol. 20, 197--216.
[53]
Jerne, N. K. 1993. The generative grammar of the immune system. Scand J Immunol. 38, 1--9.
[54]
Joyce, A. R. and Palsson, B. Ø. 2006. The model organism as a system, integrating 'omics' data sets. Nat Rev Mol Cell Biol. 7(3), 198--210.
[55]
Kharitonov, S. A. and Barnes, P. J. 2006. Exhaled biomarkers. Chest. 130(5), 1541--6.
[56]
Kim, R. et al. 2006. Tumor-driven evolution of immunosuppressive networks during malignant progression. Cancer Res. 66(11), 5527--36.
[57]
Kirouac, D. C. et al. 2010. Dynamic interaction networks in a hierarchically organized tissue. Mol Syst Biol. 6, 417.
[58]
Klymkowsky, M. W. and Savagner, P. 2009. Epithelial-mesenchymal transition, a cancer researcher's conceptual friend and foe. Am J Pathol. 174(5), 1588--93.
[59]
Kuller, L. H. et al. 2008. INSIGHT SMART Study Group. Inflammatory and coagulation biomarkers and mortality in patients with HIV infection. PLoS Med. 5(10), e203.
[60]
Kwon D et al. 2008. A novel wavelet-based thresholding method for the pre-processing of mass spectrometry data that accounts for heterogeneous noise. Proteomics. 8, 3019--29.
[61]
Lai, D. et al. 2003. Sample size for biomarker studies, more subjects or more measurements per subject? Ann Epidemiol. 13(3), 204--8.
[62]
Lin, K. C. et al. 2007. Discriminant analysis of serum inflammatory biomarkers which differentiate pediatric appendicitis from other acute abdominal diseases. Acta Paediatr Taiwan. 48(3), 125--30.
[63]
Liu, C. et al. 2008. Genome-wide association scan identifies candidate polymorphisms associated with differential response to anti-TNF treatment in rheumatoid arthritis. Mol Med. 14(9-10), 575--81.
[64]
Liu, C. et al. 2011. MALDI-TOF MS combined with magnetic beads for detecting serum protein biomarkers and establishment of boosting decision tree model for diagnosis of colorectal cancer. Int J Med Sci. 8(1), 39--47.
[65]
Liu, Z., Jiang F., Tian, G., Wang, S., Sato, F., Meltzer, S. J., and Tan, M. 2007. Sparse logistic regression with Lp penalty for biomarker identification. Stat Appl Genet Mol Biol. 6(1), 6.
[66]
Luterman, J. D. et al. 2000. Cytokine gene expression as a function of the clinical progression of Alzheimer disease dementia. Arch Neurol. 57(8), 1153--60.
[67]
Macedo, P. et al. 2009. Inflammatory biomarkers in airways of patients with severe asthma compared with non-severe asthma. Clin Exp Allergy. 39(11), 1668--76.
[68]
Mattsson, N. and Zetterberg, H. 2009. Alzheimer's disease and CSF biomarkers, key challenges for broad clinical applications. Biomark Med. 3(6), 735--7.
[69]
Mayeux, R. 2004. Biomarkers: potential uses and limitations. NeuroRx. 1(2), 182--8.
[70]
Merbl, Y. et al. 2007. Newborn humans manifest autoantibodies to defined self molecules detected by antigen microarray informatics. J Clin Invest. 117(3):712--8.
[71]
Moffitt KL et al. 2013. Inflammatory and immunological biomarkers are not related to survival in adults with Cystic Fibrosis. J Cyst Fibros. S1569--1993(13).
[72]
Mrak. R. E. and Griffin, W. S. T. 2005. Potential Inflammatory biomarkers in Alzheimer's disease. J Alzheimers Dis. 8(4), 369--375.
[73]
Naylor, S. 2003. Biomarkers: current perspectives and future prospects. Expert Rev Mol Diagn. 3(5), 525--9.
[74]
Norris J et al. 2007. Processing MALDI mass spectra to improve mass spectral direct tissue analysis. Int J Mass Spectrom. 260, 212--21.
[75]
Novelli G, et al. 2008. Genetic tests and genomic biomarkers: regulation, qualification and validation. Clin Cases Miner Bone Metab. 5(2), 149--54.
[76]
Novellino, L., Castelli, C., and Parmiani, G. 2005. A listing of human tumor antigens recognized by T cells: March 2004 update. Cancer Immunol Immunother. 54(3), 187--207.
[77]
Olsen, L. R., Zhang, G. L., Olsen, L. R., Reinherz, E. L., and Brusic, V. 2011. FLAVIdB, a data mining system for knowledge discovery in flaviviruses with direct applications in immunology and vaccinology. Immunome Res. 7(3), 1--9.
[78]
Pappalardo, F. et al. 2009. ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization. Brief Bioinform. 10(3), 330--40.
[79]
Parida, S. K. and Kaufmann, S. H. 2010. The quest for biomarkers in tuberculosis. Drug Discov Today. 15(3-4), 148--57.
[80]
Pascual, V. et al. 2010. A genomic approach to human autoimmune diseases. Annu Rev Immunol. 28, 535--71.
[81]
Poland, G. A. et al. 2013. Vaccinomics, adversomics, and the immune response network theory: Individualized vaccinology in the 21st century. Semin Immunol. 13, 00023--7.
[82]
Polyak, K., Weinberg, R. A. 2009. Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nat Rev Cancer. 9(4), 265--73.
[83]
Prescott, S. L. et al, 2003. The value of perinatal immune responses in predicting allergic disease at 6 years of age. Allergy. 58(11):1187--94.
[84]
Price JV et al. 2013. Characterization of influenza vaccine immunogenicity using influenza antigen microarrays. PLoS One. 8(5), e64555.
[85]
Prince, H. E. 2005. Biomarkers for diagnosing and monitoring autoimmune diseases. Biomarkers. 10(Suppl 1), S44--9.
[86]
Puck, J. M. 2012. Laboratory technology for population-based screening for severe combined immunodeficiency in neonates, the winner is T-cell receptor excision circles. J Allergy Clin Immunol. 129(3), 607--16.
[87]
Robinson, J. et al. 2013. The IMGT/HLA database. Nucleic Acids Res. 41(Database issue), D1222--7.
[88]
Sadun, R. E. et al. 2007. Immune signatures of murine and human cancers reveal unique mechanisms of tumor escape and new targets for cancer immunotherapy. Clin Cancer Res. 13(13), 4016--25.
[89]
Saeys, Y., Inza, I., and Larrañaga, P. 2007. A review of feature selection techniques in bioinformatics. Bioinformatics. 23(19), 2507--17.
[90]
Sawyers, C. L. 2008. The cancer biomarker problem. Nature. 452(7187), 548--52.
[91]
Schetter, A. J. et al. Inflammation and cancer: interweaving microRNA, free radical, cytokine and p53 pathways. Carcinogenesis. 31, 37--49.
[92]
Seib KL et al. 2012. Developing vaccines in the era of genomics, a decade of reverse vaccinology. Clin Microbiol Infect. 18(Suppl 5), 109--16.
[93]
Shi, Y. et al. 2009. Sparse discriminant analysis for breast cancer biomarker identification and classification. Progress Natural Sci. 19(11), 1635--41.
[94]
Sicherer, S. H. and Sampson, H. A. 2009. Food allergy: recent advances in pathophysiology and treatment. Annu Rev Med. 60:261--77.
[95]
Smyth, G. K. 2004. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 3.
[96]
Snijders, C. C. P., Matzat, U., and Reips, U. D. 2012. Big data: big gaps of knowledge in the field of Internet Science. Int J Internet Sci. 7(1), 1--5.
[97]
Suarez-Alvarez B., Rodriguez, R. M., Fraga, M. F., López-Larrea, C. 2012. DNA methylation: a promising landscape for immune system-related diseases. Trends Genet. 28(10), 506--14.
[98]
Thomas, D. A. and Massagué, J. 2005. TGF-beta directly targets cytotoxic T cell functions during tumor evasion of immune surveillance. Cancer Cell. 8(5), 369--80.
[99]
Tusher, V. G. et al. 2001. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA. 98, 5116--5121.
[100]
Vaughn, H. A. et al. 2004. The humoral immune response to head and neck cancer antigens as defined by the serological analysis of tumor antigens by recombinant cDNA expression cloning. Cancer Immunity 4, 5.
[101]
Vigneron, N., Stroobant, V., Van den Eynde, B. J., and van der Bruggen, P. 2013. Database of T cell-defined human tumor antigens: the 2013 update. Cancer Immun. 13, 15
[102]
Wang, T. et al. 2004. Regulation of the innate and adaptive immune responses by Stat-3 signaling in tumor cells. Nat Med. 10(1), 48--54.
[103]
Wu, Z. 2009. A review of statistical methods for preprocessing oligonucleotide microarrays. Stat Methods Med Res. 18(6), 533--41.
[104]
Xu, Q. W. et al. 2012. An integrated genome-wide approach to discover tumor-specific antigens as potential immunologic and clinical targets in cancer. Cancer Res. 72(24), 6351--61.
[105]
Yan, S. D. et al. 1997. Amyloid-β peptide-receptor for advanced glycation endproduct interaction elicits neuronal expression of macrophage-colony stimulating factor, a proinflammatory pathway in Alzheimer disease. Proc Natl Acad Sci USA. 94, 5296--301.
[106]
Yang C, He Z, Yu W. 2009. Comparison of public peak detection algorithms for MALDI mass spectrometry data analysis. BMC Bioinformatics. 10, 4.
[107]
Yang, I. S. et al. 2008. IDBD, infectious disease biomarker database. Nucleic Acids Res. 36, D455--60.
[108]
Yilmaz, M. and Christofori, G. 2009. EMT, the cytoskeleton, and cancer cell invasion. Cancer Metastasis Rev. 28(1-2), 15--33.
[109]
Yousef M et al. 2009. Classification and biomarker identification using gene network modules and support vector machines. BMC Bioinformatics. 10, 337.
[110]
Yu W et al. 2006. Statistical methods in proteomics. In Springer Handbook of Engineering Statistics, Springer London, 623--38.
[111]
Yu, Y. et al. 2005. Prediction of pancreatic cancer by serum biomarkers using surface-enhanced laser desorption/ionization-based decision tree classification. Oncology. 68(1), 79--86.
[112]
Yuan, Z. and Ghosh, D. 2008. Combining multiple biomarker models in logistic regression. Biometrics. 64(2), 431--439.
[113]
Zabel, M. et al. 2012. Assessing candidate serum biomarkers for Alzheimer's disease, a longitudinal study. J Alzheimers Dis. 30(2), 311--21.
[114]
Zea, A. H. et al. 2005. Arginase-producing myeloid suppressor cells in renal cell carcinoma patients, a mechanism of tumor evasion. Cancer Res. 65(8), 3044--8.
[115]
Zeger SL and Liang KY. 1992. An overview of methods for the analysis of longitudinal data. Stat Med. 11(14-15), 1825--39.
[116]
Zhang J et al. 2008. CSF multianalyte profile distinguishes Alzheimer and Parkinson diseases. Am J Clin Pathol. 129(4), 526--9.
[117]
Zhang, G. L., Olsen, L. R., Kudahl, U. J., Chitkushev, L. T., and Brusic, V. 2013. Streamlining the development of immunological knowledge bases. Methods Mol Biol. (in press).
[118]
Zhang, Y. et al. 2012. Systematic analysis of the gene expression in the livers of nonalcoholic steatohepatitis, implications on potential biomarkers and molecular pathological mechanism. PLoS One. 7, e51131.
[119]
Zheng, G. and Joo, J. 2010. Statistical tests for biomarker development with applications to genetics data. Encyclopedia of Biopharmaceutical Statistic, 1294--9.
[120]
Zitvogel, L. et al. 2010. Immune parameters affecting the efficacy of chemotherapeutic regimens. Nat Rev Clin Oncol. 8(3):151--60.
[121]
Zou, W. 2006. Regulatory T cells, tumour immunity and immunotherapy. Nat Rev Immunol. 6(4), 295--307.
Index Terms
- Biomarkers in Immunology: from Concepts to Applications
Recommendations
Integrated Analysis of Autophagy-Related Genes Identifies Diagnostic Biomarkers and Immune Correlates in Preeclampsia
Bioinformatics Research and ApplicationsAbstractPreeclampsia (PE) presents a significant challenge in pregnancy due to its high incidence and clinical fatality rate. Previous studies have emphasized the involvement of autophagy and cellular immunity in PE pathogenesis; however, research on ...
Outlier analysis and top scoring pair for integrated data analysis and biomarker discovery
Pathway deregulation has been identified as a key driver of carcinogenesis, with proteins in signaling pathways serving as primary targets for drug development. Deregulation can be driven by a number of molecular events, including gene mutation, ...
Integration of mRNA and protein expression data for the identification of potential biomarkers associated with pancreatic ductal adenocarcinoma
AbstractPancreatic ductal adenocarcinoma (PDAC) is one of the most death-dealing tumors, with a tremendously poor prognosis. Here, we, through interrogation of mRNA and protein data combined with a system biology approach, identified several key genes, ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
September 2013
987 pages
ISBN:9781450324342
DOI:10.1145/2506583
Copyright © 2013 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 22 September 2013
Check for updates
Author Tags
Qualifiers
- Tutorial
- Research
- Refereed limited
Conference
BCB'13
Sponsor:
Acceptance Rates
BCB'13 Paper Acceptance Rate 43 of 148 submissions, 29%;
Overall Acceptance Rate 254 of 885 submissions, 29%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 195Total Downloads
- Downloads (Last 12 months)1
- Downloads (Last 6 weeks)0
Reflects downloads up to 09 Dec 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in