Quantitative analysis of proteins of metabolism by reverse phase protein microarrays identifies potential biomarkers of rare neuromuscular diseases

Journal of Translational Medicine

María Sánchez-Aragó³  José M Cuezva³  Miguel A Martín¹  Carmen Navarro²  Cristina Núñez de Arenas³  Margarita Chamorro³  Fulvio Santacatterina³ 

[1] Laboratorio de Enfermedades Mitocondriales y Neuromusculares, Hospital Universitario 12 de Octubre, Madrid, 28041, Spain;Instituto de Investigación Biomédico de Vigo (IBIV), Hospital Universitario de Vigo, Meixoeiro, Vigo, 36200, Spain;Instituto de Investigación Hospital 12 de Octubre, ISCIII, Madrid, Spain

关键词: Rare diseases;    Neuromuscular diseases;    Biomarkers;    Mitochondria;    Energy metabolism;   

Others  :  1133043
DOI  :  10.1186/s12967-015-0424-1

 received in 2014-10-30, accepted in 2015-01-30,  发布年份 2015

【 摘 要 】

Background

Muscle diseases have been associated with changes in the expression of proteins involved in energy metabolism. To this aim we have developed a number of monoclonal antibodies against proteins of energy metabolism.

Methods

Herein, we have used Reverse Phase Protein Microarrays (RPMA), a high throughput technique, to investigate quantitative changes in protein expression with the aim of identifying potential biomarkers in rare neuromuscular diseases. A cohort of 73 muscle biopsies that included samples from patients diagnosed of Duchenne (DMD), Becker (BMD), symptomatic forms of DMD and BMD in female carriers (Xp21 Carriers), Limb Girdle Muscular Dystrophy Type 2C (LGMD2C), neuronal ceroid lipofuscinosis (NCL), glycogenosis type V (Mc Ardle disease), isolated mitochondrial complex I deficiency, intensive care unit myopathy and control donors were investigated. The nineteen proteins of energy metabolism studied included members of the mitochondrial oxidation of pyruvate, the tricarboxylic acid cycle, β-oxidation of fatty acids, electron transport and oxidative phosphorylation, glycogen metabolism, glycolysis and oxidative stress using highly specific antibodies.

Results

The results indicate that the phenotype of energy metabolism offers potential biomarkers that could be implemented to refine the understanding of the biological principles of rare diseases and, eventually, the management of these patients.

Conclusions

We suggest that some biomarkers of energy metabolism could be translated into the clinics to contribute to the improvement of the clinical handling of patients affected by rare diseases.

【 授权许可】

   
2015 Santacatterina et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

【 参考文献 】

• [1]Vander Heiden MG, Cantley LC, Thompson CB: Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 2009, 324:1029-33.
• [2]Willers IM, Cuezva JM: Post-transcriptional regulation of the mitochondrial H(+)-ATP synthase: A key regulator of the metabolic phenotype in cancer. Biochim Biophys Acta 1807, 2011:543-51.
• [3]Cuezva JM, Krajewska M, de Heredia ML, Krajewski S, Santamaria G, Kim H, et al.: The bioenergetic signature of cancer: a marker of tumor progression. Cancer Res 2002, 62:6674-81.
• [4]Aldea M, Clofent J, Nunez De Arenas C, Chamorro M, Velasco M, Berrendero JR, et al.: Reverse phase protein microarrays quantify and validate the bioenergetic signature as biomarker in colorectal cancer. Cancer Lett 2011, 311:210-8.
• [5]Sanchez-Arago M, Cuezva JM: The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil. J Transl Med 2011, 9:19. BioMed Central Full Text
• [6]Sanchez-Arago M, Formentini L, Cuezva JM: Mitochondria-mediated energy adaption in cancer: the H(+)-ATP synthase-geared switch of metabolism in human tumors. Antioxid Redox Signal 2013, 19:285-98.
• [7]Mueller C, Liotta LA, Espina V: Reverse phase protein microarrays advance to use in clinical trials. Mol Oncol 2010, 4:461-81.
• [8]Tibes R, Qiu Y, Lu Y, Hennessy B, Andreeff M, Mills GB, et al.: Reverse phase protein array: validation of a novel proteomic technology and utility for analysis of primary leukemia specimens and hematopoietic stem cells. Mol Cancer Ther 2006, 5:2512-21.
• [9]Michaud GA, Salcius M, Zhou F, Bangham R, Bonin J, Guo H, et al.: Analyzing antibody specificity with whole proteome microarrays. Nat Biotechnol 2003, 21:1509-12.
• [10]Strausberg RL, Simpson AJ, Old LJ, Riggins GJ: Oncogenomics and the development of new cancer therapies. Nature 2004, 429:469-74.
• [11]Acebo P, Giner D, Calvo P, Blanco-Rivero A, Ortega AD, Fernandez PL, et al.: Cancer abolishes the tissue type-specific differences in the phenotype of energetic metabolism. Transl Oncol 2009, 2:138-45.
• [12]Sanchez-Cenizo L, Formentini L, Aldea M, Ortega AD, Garcia-Huerta P, Sanchez-Arago M, et al.: Up-regulation of the ATPase inhibitory factor 1 (IF1) of the mitochondrial H + −ATP synthase in human tumors mediates the metabolic shift of cancer cells to a Warburg phenotype. J Biol Chem 2010, 285:25308-13.
• [13]Willers IM, Martínez-Reyes I, Martínez-Diez M, Cuezva JM: miR-127-5p targets the 3'UTR of human β-F1-ATPase mRNA and inhibits its translation. Biochim Biophys Acta-Bioenergetics 1817, 2012:838-48.
• [14]Liotta L, Petricoin E: Molecular profiling of human cancer. Nat Rev Genet 2000, 1:48-56.
• [15]Chen WW, Birsoy K, Mihaylova MM, Snitkin H, Stasinski I, Yucel B, et al.: Inhibition of ATPIF1 ameliorates severe mitochondrial respiratory chain dysfunction in mammalian cells. Cell Rep 2014, 7:27-34.
• [16]Lucia A, Ruiz JR, Santalla A, Nogales-Gadea G, Rubio JC, Garcia-Consuegra I, et al.: Genotypic and phenotypic features of McArdle disease: insights from the Spanish national registry. J Neurol Neurosurg Psychiatry 2012, 83:322-8.
• [17]Nogales-Gadea G, Consuegra-Garcia I, Rubio JC, Arenas J, Cuadros M, Camara Y, et al.: A transcriptomic approach to search for novel phenotypic regulators in McArdle disease. PLoS One 2012, 7:e31718.
• [18]Cuezva JM, Sanchez-Arago M, Sala S, Blanco-Rivero A, Ortega AD: A message emerging from development: the repression of mitochondrial beta-F1-ATPase expression in cancer. J Bioenerg Biomembr 2007, 39:259-65.
• [19]Cuezva JM, Ortega AD, Willers I, Sanchez-Cenizo L, Aldea M, Sanchez-Arago M: The tumor suppressor function of mitochondria: translation into the clinics. Biochim Biophys Acta 2009, 1792:1145-58.
• [20]Balzano W, Del Sorbo MR: Genomic comparison using data mining techniques based on a possibilistic fuzzy sets model. Biosystems 2007, 88:343-9.
• [21]Rahimov F, Kunkel LM: The cell biology of disease: cellular and molecular mechanisms underlying muscular dystrophy. J Cell Biol 2013, 201:499-510.
• [22]Lemmers RJ, Tawil R, Petek LM, Balog J, Block GJ, Santen GW, et al.: Digenic inheritance of an SMCHD1 mutation and an FSHD-permissive D4Z4 allele causes facioscapulohumeral muscular dystrophy type 2. Nat Genet 2012, 44:1370-4.
• [23]Manzini MC, Tambunan DE, Hill RS, Yu TW, Maynard TM, Heinzen EL, et al.: Exome sequencing and functional validation in zebrafish identify GTDC2 mutations as a cause of Walker-Warburg syndrome. Am J Hum Genet 2012, 91:541-7.
• [24]Ledford H: Metabolic quirks yield tumour hope. Nature 2014, 508:158-9.
• [25]Hathout Y, Marathi RL, Rayavarapu S, Zhang A, Brown KJ, Seol H, et al.: Discovery of serum protein biomarkers in the mdx mouse model and cross-species comparison to Duchenne muscular dystrophy patients. Hum Mol Genet 2014, 23(24):6458-69.
• [26]Brancaccio P, Lippi G, Maffulli N: Biochemical markers of muscular damage. Clin Chem Lab Med 2010, 48:757-67.
• [27]Shima K, Tashiro K, Hibi N, Tsukada Y, Hirai H: Carbonic anhydrase-III immunohistochemical localization in human skeletal muscle. Acta Neuropathol 1983, 59:237-9.
• [28]Emery AE: The muscular dystrophies. BMJ 1998, 317:991-5.
• [29]Ramadasan-Nair R, Gayathri N, Mishra S, Sunitha B, Mythri RB, Nalini A, et al.: Mitochondrial alterations and oxidative stress in an acute transient mouse model of muscle degeneration: implications for muscular dystrophy and related muscle pathologies. J Biol Chem 2014, 289:485-509.
• [30]Guevel L, Lavoie JR, Perez-Iratxeta C, Rouger K, Dubreil L, Feron M, et al.: Quantitative proteomic analysis of dystrophic dog muscle. J Proteome Res 2011, 10:2465-78.
• [31]Burghes AH, Logan C, Hu X, Belfall B, Worton RG, Ray PN: A cDNA clone from the Duchenne/Becker muscular dystrophy gene. Nature 1987, 328:434-7.
• [32]Yoshida M, Suzuki A, Yamamoto H, Noguchi S, Mizuno Y, Ozawa E: Dissociation of the complex of dystrophin and its associated proteins into several unique groups by n-octyl beta-D-glucoside. Eur J Biochem 1994, 222:1055-61.
• [33]Rahimov F, King OD, Leung DG, Bibat GM, Emerson CP Jr, Kunkel LM, et al.: Transcriptional profiling in facioscapulohumeral muscular dystrophy to identify candidate biomarkers. Proc Natl Acad Sci U S A 2012, 109:16234-9.
• [34]Doran P, Donoghue P, O'Connell K, Gannon J, Ohlendieck K: Proteomic profiling of pathological and aged skeletal muscle fibres by peptide mass fingerprinting (Review). Int J Mol Med 2007, 19:547-64.
• [35]Nadarajah VD, van Putten M, Chaouch A, Garrood P, Straub V, Lochmuller H, et al.: Serum matrix metalloproteinase-9 (MMP-9) as a biomarker for monitoring disease progression in Duchenne muscular dystrophy (DMD). Neuromuscul Disord 2011, 21:569-78.