Proteomic biomarker discovery for the monogenic disease cystic fibrosis

Review

10.1586/14789450.4.2.199 © 2007 Future Drugs Ltd ISSN 1478-9450 199www.future-drugs.com

Proteomic biomarker discovery for the monogenic disease cystic fibrosisDeborah Penque

Instituto Nacional de Saúde Dr Ricardo Jorge, Laboratório de Proteómica, Centro de Genética Humana, 1649-016-Lisboa, PortugalTel.: + 351 217 508 137Fax: + 351 217 526 [email protected]

KEYWORDS: 2DE, CF-modifier gene, CFTR, CFTR-binding partner, chronic lung disease biomarker, cystic fibrosis, mass spectrometry, proteomics

Proteomics was initially viewed as a promising new scientific discipline to study complex disorders such as polygenic, infectious and environment-related diseases. However, the first attempts to understand a monogenic disease such as cystic fibrosis (CF) by proteomics-based approaches have proved quite rewarding. In CF, the impairment of a unique protein, the CF transmembrane conductance regulator, does not completely explain the complex and variable CF clinical phenotype. The great advances in our knowledge about the molecular and cellular consequences of such impairment have not been sufficient to be translated into effective treatments, and CF patients are still dying due to chronic progressive lung dysfunction. The progression of proteomics application in CF will certainly unravel new proteins that could be useful as biomarkers either to elucidate CF basic mechanisms and to better monitor the disease progression, or to promote the development of novel therapeutic strategies against CF. This review will summarize the recent technological advances in proteomics and the first results of its application to address the most important issues in the CF field.

Expert Rev. Proteomics 4(2), 199–209 (2007)

The great challenge for modern medicine afterthe genome sequencing programme is the inte-grated examination of gene expression of theentire genome under physiological or patho-logical conditions, and how this expressionpattern defines and predicts the different statesof disease progression [1].

Proteomics, the large-scale study of proteinprofiles under given times/conditions, is revo-lutionizing the way in which disease mecha-nisms are understood and how novel bio-markers and therapeutic interventions arediscovered in the postgenomic era [2].

Initially viewed as a promising new scien-tific discipline for unraveling the complexorchestration of gene products in polygenicdiseases and the basic mechanisms in infec-tious and environmental disorders, proteomicsnow appears to be a determinant for the studyof monogenic diseases, in which the know-ledge of the functional defect of a unique geneand its product is far from being adequate forits management.

This is the case for cystic fibrosis (CF), themost common recessive monogenic disorder inCaucasians, which is caused by mutations in agene coding for a cyclic AMP (cAMP)-regu-lated chloride channel, the CF transmembraneconductance regulator (CFTR) [3]. CFTR iscritically involved in the regulation of epithelialsurface fluid composition of several organs,such as sweat glands and ducts, airways, pan-creas, intestine and the reproductive system.Absence of CFTR function leads to a multisys-temic disorder, which includes elevated sweatCl- concentrations, abnormal viscous mucusresponsible for progressive respiratory infectionand dysfunction, gastrointestinal disease, andinfertility [4–6].

Since the cloning of the CFTR gene, a greatdeal of knowledge about the mutational basis ofthe disease, CFTR expression and function, andthe functional consequences of the most com-mon mutations in CFTR have been derived[4–6]. Despite these rapid advances in our under-standing of the molecular determinants of CF,

CONTENTS

Biological purposes

Proteomics tools

Cystic fibrosis

Proteomics-based approaches in cystic fibrosis lung disease research

Expert commentary & five-year view

Key issues

References

Affiliation

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200 Expert Rev. Proteomics 4(2), (2007)

none of the approved treatments can currently correct the bio-chemical defect, and the majority of CF patients die from achronic, progressive, lung dysfunction.

Proteomics-based approaches have the potential to provideadditional information on CF pathogenesis that could be cru-cial to the identification of new CF diagnostic/prognosticbiomarkers, as well as for the development of novel therapeuticstrategies for CF.

This review summarizes recent technological advances inproteomics and the first steps of its application to address themost important issues in the CF pulmonary field.

Biological purposesProteomics employs a variety of technologies based on highlyefficient methods of separation and analysis of proteins in orderto characterize, study and understand the proteome (set of pro-teins) of a living system at as large a scale as possible (FIGURE 1).

Proteomics has three main biological purposes:

• Spatial and temporal characterization of protein expression ina cell or tissue for the identification of an entire protein setand their post-translational modifications. This approach canprovide key information about the entire protein profile (as aprotein expression map or catalog) of cells/tissues. Proteinsassociated directly or indirectly with a disease can be mappedspatially/temporally to the potential cell/tissue targets [7].

• Quantitative/qualitative comparative study of global changesin protein expression between treated and nontreated and/ornormal and diseased cells to look for toxic effects/responses ordisease diagnostic and prognostic biomarkers, respectively [8].

• Functional proteome study. One example is the characteriza-tion of protein complexes to provide functional identificationof protein–protein, DNA/RNA–protein or drug–proteininteractions. Identification of such complexes and moleculesthat can regulate these interactions is of great interest sincethey may subsequently be used as targets for therapeutic drugscreening [9]. Another example is to detect functional changesin the entire proteome by using chemical probes directedtoward the active sites of specific classes of enzymes: a methodknown as activity-based protein profiling (ABPP) [10].From any of these proteomics-based biological applications,

a consolidated list of proteins, also referred to as biomarkercandidates, can be generated using any of the proteomics-based approaches described below (discovery phase; FIGURE 1).The subsequent phase is the validation of these biomarkersbefore they can be implemented as validated biomarkers forthe purposes for which they were generated (FIGURE 1).

Proteomics tools2D gel electrophoresis & mass spectrometry-based proteomicsProteomics was traditionally associated with 2D gel electro-phoresis (2DE) for the separation and visualization of proteins,which was followed by protein characterization using mass spec-trometry (MS) and bioinformatics [11]. The first dimension of2DE consists of isoelectric focusing, during which the proteinsare separated on the basis of their isoelectric point in an immo-bilized pH gradient gel (IPG). This IPG is then applied on theedge of a second gel, a slab sodium dodecyl sulfate polyacryl-amide gel electrophoresis, in which the proteins undergo anadditional separation according to their molecular weight under

Figure 1. Workflow paradigm illustrating different proteomics-based approaches and major steps required for proteomic biomarker discovery, validation and implementation. ABPP: Activity-based protein profiling; ESI: Electrospray ionization; FFPE: Formalin-fixed, paraffin-embedded; ICAT: Isotope-coded affinity tag; IMAC: Immobilized metal affinity chromatography ; iTRAQ™: Isobaric tags for relative and absolute quantitation; LC: Liquid chromatography; MALDI: Matrix-assisted laser desorption/ionization; MS/MS: Tandem mass spectrometry; MudPIT: Multidimensional protein identification technology; PTM: Post-translational modification; SELDI: Surface-enhanced laser desorption/ionization; SILAC: Stable isotope labeling by amino acids in cell culture; TOF: Time-of-flight.

Biologicalpurpose

Spatial and temporalcharacterization of proteinexpression (including PTMof proteins

Quantitative/qualitativecomparative study of globalchanges in protein expression(i.e., healthy × disease;nontreated × treated)

Functional proteome study(e.g., protein–protein interaction and enzyme activity profiling)

Discovery phase Validation/implementation phase

Proteomics technical platform

Imaging MALDI-TOF

SELDI-TOF

Protein microarrays

2D gel2D map computer analysis

Spots

MudPIT-LC Integrated to

MALDI-TOF/TOFESI-MS/MS

Bioinformatics

Biomarker validation(immunocytochemistry, western blotting, northern blotting etc.)

Biomarker implementation

Biospecimens andsample preparation(Fresh/FFPE cells/tissues/fluids)

Total protein extracts; isolated cells from tissue by laser microdissection microscopy; prefractionated organelles; isolated protein complexes; proteins purified by depletion/fractionation/enrichment techniques (e.g., phosphorylated proteins isolated by IMAC); stable isotope-labeled proteins for proteome quantification (e.g., ICAT, iTRAQ™ and SILAC); labeled proteins by chemical probes for activity determination (ABPP)

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Proteomic biomarker discovery for cystic fibrosis

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denaturing conditions. Typically, a 1000 protein spots can besimultaneously visualized on a 2DE by using standard proce-dures of protein staining, such as Coomassie blue, colloidal blueand MS-compatible silver stain [11]. Other choices include pre-gel (fluorescence 2D differential in-gel electrophoresis) or post-run labeling with fluorescent dyes (SYPRO® Ruby) or pre-runlabeling of proteins with radioisotopes (e.g., 35S-methionine or32P-phosphorous) [12]. Subsequent analysis of the spot patternon a gel by specialized software (a variety of software packagesare commercially available) enables multiple-gel comparison,whereby quantitative and qualitative changes are detected. Adatabase of 2D maps can be created and made available on awebsite. In addition to 2D images, most 2D maps containinformation about the isoelectric point and molecular weight ofthe protein spots, comparison of gels, immunoblotting resultsand MS data [13].

The new generation of MS instrumentation has played a cru-cial role in proteomics due to its high automation and sensitiv-ity, which require femto- (10-15M) to attomolar (10-18M) con-centrations of peptide or protein material [14]. The mostpopular systems are matrix-assisted laser desorption/ionization(MALDI) time-of-flight (TOF) MS and electrospray ioniza-tion (ESI) MS [14]. The protein spot excised from the gel isdigested, usually with trypsin, and the resulting mixture of pep-tides is introduced into the MS and analyzed. Two specifictypes of protein data can be obtained:

• Peptide-mass fingerprinting, which involves the determinationof the masses of all peptides in the digest;

• Amino acid sequence of peptides, also called peptide-sequence tags, which are obtained by ESI tandem MS(MS/MS) or by MALDI equipped with a post-source decayapparatus or additional MS/MS (MALDI-TOF/TOF) forisolation of peptide ions and their subsequent fragmentationand microsequencing.

Peptide-mass fingerprints and peptide-sequence tags are usedto search a predicted mass map or protein sequence within adatabase to identify the protein of interest. The candidate pro-teins are ranked from a list of the most closely matched candi-dates using various scoring algorithms. If there is no match withany known sequence, new proteins and genes can be identifiedif enough sequence information is obtained.

The major limitation of current proteomics-based approachesthat combine 2DE and MS is the limited ability of 2DE toresolve low-abundance proteins and hydrophobic basic proteins[15]. A low capability to quantify proteins and peptides in complexmixtures has also been attributed to 2DE [15]. Sample prefrac-tionation or affinity-based protein purification that reduce thecomplexity of protein mixtures have increased the visualizationcapability of less abundant proteins by the 2DE system [11].

Gel-free mass spectrometry-based proteomics In recent years, strategies to entirely circumvent the need for 2DEhave been developed [16]. One of these utilizes liquid chromato-graphy (LC) coupled directly to MS/MS. Complex mixtures of

proteins can be digested and the resulting peptides selectivelyseparated by affinity high-performance LC (according to theirhydrophobicity, charge, polarity, size or binding characteristics)and then directly analyzed by MS/MS [17]. The possibility ofeluting multiple subsets of peptides (multidimensional proteinidentification technology) allows for a dramatic increase in thetotal number of peptides that can be resolved and for whichMS/MS data can be collected [17]. Although a more comprehen-sive cataloging of proteome composition is provided, this tech-nique, per se, is not able to give reliable quantitative informationthat is crucial in disease biomarker discovery.

To overcome this limitation, new methods based on selectiveisotope peptide labeling have emerged to improve the quantita-tive comparison of control and experimental samples [16]. Stableisotope labeling by amino acids in cell culture (SILAC) isachieved in vivo via biosynthetic incorporation of stable iso-tope-containing amino acids during protein synthesis [18]. Iso-tope-coded affinity tags (ICAT), chemicals that derivatizecysteine residues, are preceded by cell lysis and protein isolation[19]. Isobaric tags for relative and absolute quantitation(iTRAQ™) and O16/O18 exchange are used during or after pro-teolytic digestion, respectively [20,21]. In general, these methodsare based on reacting proteins with chemically identical formsof the above reagents that contain a linker of a light or heavytag [16]. After labeling, the samples are combined and the mix-ture analyzed by LC/MS. During the analysis, the peptidescommon to both control and experimental samples retain thesame chemical properties, and thus are detected as peak pairs,differing in mass spectral peak height or peak area, which areused to determine the relative quantification. A limitation ofthis approach is that it does not provide information aboutpost-translational modifications. For that, similar chemicalstrategies have been introduced to evaluate the post-transla-tional modification state of proteins, such as phosphorylationand glycosylation [22]. For the functional analysis of proteins, achemical approach called ABPP has been developed with amenu of chemical probes that can be used either separately orin combination to discover enzyme activities associated withdiscrete physiological and/or pathological states [23].

Array-based proteomics Protein expression profiling by using surface-enhanced laser des-orption/ionization (SELDI) TOF is another methodology thatexpands the spectrum of tools available for proteomics research[24]. These protein-chip arrays utilize a variety of different affin-ity chromatographic surfaces and washing conditions to isolate asubset of proteins at various positions on the chip. A smallamount of protein mixture on the chip well is analyzed directlyby MALDI, which allows quantitative MS evaluation of thepeak of ionized peptides rather than the qualitative evaluationthat is traditionally used in all MS methods. Several new cancermarkers have been discovered using SELDI technology [25].

Protein microarrays or chips have been proposed as a sensi-tive screening system for high-throughput protein expres-sion, protein–protein interactions and protein–nucleic acid

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interactions [26,27]. The chips are constructed by spotting manyhundreds of capture molecules (proteins, peptides or antibodies)onto a matrix (e.g., membranes, glass slides, polyacrylamidematrixes and nanostructure surfaces) in a way that should retaintheir ability to recognize and capture their targets [26,27]. Proteinchip analysis can be performed by enhanced chemilumines-cence, fluorescent or radioactive labels, electric/magnetic detec-tion systems and, more recently, directly by MS [28]. Despitethese advances, the great variability and complexity of proteinmolecules renders the development of protein microchips withhigh specificity and accuracy a particularly challenging task inthe coming years.

Imaging mass spectrometry-based proteomics The more recent innovative proteomics approach utilizes imag-ing MALDI technology to directly map and locate peptides andproteins in biological specimens [29]. Fresh frozen sections, indi-vidual cells or clusters of cells isolated by laser-capture micro-dissection, or contact blotting of a tissue on a membrane targetare incubated with a solution matrix, dried and introduced intothe vacuum inlet of the MALDI-TOF equipped with a specificMS imaging software. Imaging MS can be a valuable tool forthe comparison of molecular weight-based protein patterns indisease versus normal tissues, and in helping identify biomark-ers in lesions and at various stages of disease progression [29].The recent possibility of performing LC/MS/MS on cells iso-lated either from fresh frozen sections or formalin-fixed paraf-fin-embedded tissues by laser-capture microdissection has alsoincreased our ability to explore the whole proteome or specificbiomarkers present in different cell types of a (archive) tissuethat could be correlated with a specific disorder profile [30–32].

Bioinformatics & validationThe high dimensionality of data generated from proteomicsstudies has required the development of bioinformatics toolsfor efficient and accurate data analysis, interpretation and cor-relation in order to translate data mining into knowledge dis-covery. The most recent bioinformatics initiatives or solutionsfor proteomics are extensively discussed and reviewed in [33,34].

In a biomarker discovery program, the validation processes(usually more challenging than the discovery phase for severalreasons [35]), cannot be performed without the assistance of bio-informatics for the management and integration of data fromdifferent sources (e.g., enzyme-linked immunosorbent assay,western blots, DNA/RNA microarrays and clinical data) toprovide valid biomarkers to the medical community.

Cystic fibrosis Monogenic chronic lung diseaseAlthough several organs are affected in CF, the lung diseasemanifestation represents the most life-threatening clinical fea-ture responsible for 95% of CF morbidity and mortality [4–6].CF lung disease is initiated by the failure of innate airwaydefense against inhaled bacteria and propagated by the inabilityto effectively clear the infection [36].

It is not completely clear how precisely the impaired iontransport by the CFTR protein affects the activity of innate air-way defenses and gives rise to persistent airway infection andinflammation, although several mechanisms have been pro-posed. Altered electrolyte transport leading to the depletion ofairway surface liquid (ASL) volume has been observed to causethickened and dehydrated mucus, which impairs mucociliaryclearance, the primary innate defense against inhaled pathogens[36]. Failure to kill bacteria properly may result from an altera-tion in the nonspecific airway defenses, such as defensins, lacto-ferrin, lysozyme or NO, which are produced and secreted intothe ASL by airway epithelial cells. The levels of defensins, lacto-ferrin and lysozyme appear to be normal in CF as well as theirpotential salt-sensitive function, since ASL, albeit reduced,seems to remain isotonic [36,37]. By contrast, exhaled NO, ele-vated in most inflammatory lung diseases, is decreased in CF,suggesting deregulation in the metabolism or maintenance ofNO. The expression of inducible NO synthase and the NOsynthase-2, enzymes involved in NO metabolism, are down-regulated in CF patients [38,39]. Unfortunately, relatively little isknown about the complete information contained in the ASL interms of antibacterial peptides, metabolites and signaling mole-cules that regulate ASL volume/composition and, consequently,protection against infections. Therefore, the full characteriza-tion of ASL composition would provide important advances forthe elucidation of pathogenesis of CF airway disease.

The pH alteration in CF cell organelles caused by a defectiveCFTR reduces sialysation of glycoconjugates in CF epithelialcells [40,41]. The abnormal bacterial retention in the CF airwaymay be explained by the increasing number of asialoGM1 mole-cules, a ligand for many bacterial respiratory pathogens that havebeen found in CF patients [42]. CFTR may constitute itself as aspecific receptor for Pseudomonas aeruginosa that, once bound toCFTR, is internalized and killed by the epithelial cell that under-goes apoptosis [43]. This hypothesis claims that the absent ordefective CFTR receptor at the airway epithelial surface leavesthe pathogens free to multiply in the airway of CF patients [43].

The inflammation response to pathogens is exaggerated andpersistent in CF, and is characterized by a high number of sus-tained neutrophils in the airway lumen. This feature isobserved even in clinically stable patients with mild lung dis-ease and in neonates with positive screening for CF [44,45]. Theexcess production of granulocyte macrophage colony-stimulat-ing factor and the low concentration of anti-inflammatorycytokine interleukin (IL)-10, in contrast to high concentrationsof proinflammatory cytokines IL-8 and -6 and tumor necrosisfactor-α, lead to a severe lung inflammatory response in CF[4–6]. Neutrophils also release large amounts of neutrophilelastase and oxygen radicals, which saturate the ASL anti-protease activity and causes oxidative stress in the airways of CFpatients, respectively [46,47].

Deregulated inflammation associated with an increased suscep-tibility to bacterial infections, a vicious cycle of infection, inflam-mation and progressive airway damage is established in CF. Futuretherapeutic approaches for CF lung disease should focus on



molecular targets that disrupt and/or normalize pathways of thispathogenic cycle. Albeit the main target of this cycle, a dysfunc-tional CFTR could be hit by gene therapy in future, it appearsthat this approach could be insufficient in patients at an advancedpathophysiological cycle of the disease. Therefore, the greatchallenge to overcome this situation is the continued search foralternative or complementary candidate targets for CF therapy.

Phenotype variability & modifier genes Patients are not all equal with regard to CF disease manifesta-tion and progression. In fact, there is no gold standard for CFdiagnosis and; since the clinical phenotype may be indistinct,the usual genotype or sweat test investigation may not com-pletely confirm the diagnosis. There are patients with all of theCF classical manifestations from infancy with a relatively poorprognosis, while others with milder or even atypical diseasesymptoms with very little deterioration over time. The CFphenotype heterogeneity is partially explained by the largespectrum of CF mutations, which includes over 1300 CFTRmutations and 200 polymorphisms that have been defined todate [101]. Depending on their effect on protein function, muta-tions in the CFTR gene are divided into at least five classes and,according to the pancreatic status, classified as severe (i.e., pan-creatic insufficient) or mild (i.e., pancreatic sufficient). Severemutations result in no synthesis, defective processing or defec-tive function (classes I, II and III, respectively), whereas mildmutations cause partial loss of the protein conductance orreduced synthesis (classes IV and V, respectively) [4–6]. Most CFpatients (∼70%) have at least one F508del allele, a severeclass II mutation that results in a misfolded CFTR that,although active as a Cl- channel, is largely degraded in theendoplasmic reticulum (ER), and thus never reaches the cellsurface [4–6]. The CFTR genotype and CF phenotype correla-tion is highest for the pancreatic status, but very low for othermanifestations, particularly for the pulmonary disease [48]. Themajority of patients who are homozygous for F508del haveinadequate pancreatic function, but great variation in the age ofonset and severity of lung disease [49]. Patients with the sameCFTR mutations, even siblings, can differ greatly as far as thelung disease is concerned [50]. Although patients with pancre-atic sufficiency tend to have milder pulmonary disease, theinfluence of environmental factors (e.g., exposure to infectiousagents, therapeutic regimens, nutrition and inhaled pollutants),socioeconomic status and modifier genes have been describedon the progression and severity of CF lung disease.

CF-modifier genes might include ion channels other thanCFTR and genes involved in the regulation of ASL volume/com-position, host defense, airway inflammation/repair, mucins andimmunodefense factors. In recent years, polymorphisms in sev-eral genes have been described to affect the rate of bacterial infec-tion, the outcome of lung dysfunction and immunity in CFpatients [51]. In brief, the candidates proposed to date are:

• α1-antitrypsin, an antiprotease;

• Mannose binding lectin-2, a protein involved in innate defense;

• Glutathione-S-transferase M1, an antioxidant gene family;

• β-adrenergic receptor, a cAMP regulator in the airway; tissuegrowth factor-β, a profibrotic cytokine;

• NO synthases NOS-1 and 3, responsible for NO synthesis, ahost defense and inflammation regulator in airway;

• Major histocompatibility complexes, critical molecules inantigen presentation and the ensuing inflammatory response.

Although evidence suggests that genetic modifiers of CFlung disease exist, significantly more research is required tofully establish specific genes as modifiers [51].

Multifunctional & interactive proteinActivities other than Cl- transport have been proposed forCFTR [52]. One that has a direct impact on ASL volume regula-tion is the negative regulation of epithelial Na+ channel (ENaC)activity [53,54]. Impairment of CFTR function in airway epithe-lial cells leads to Na+ and fluid hyperabsorption, and conse-quently ASL depletion [53,54]. Recently, it was demonstrated thata transgenic mouse overexpressing ENaC has a lung disease verysimilar to human CF lung pathology, supporting the idea thatthe CF lung disease correlates mainly with upregulation of Na+

absorption [55]. At present, it is not completely clear whetherthis observation is airway specific (since there is no ENaC up-regulation in CF sweat glands [56]) and how exactly CFTRchannel dysfunction alters CFTR interaction and Na+ channelactivity in the apical membrane of airway epithelial cells.

CFTR also seems to complement and regulate the calcium-activated Cl- channel (CaCC) in transepithelial Cl- and fluidtransport [57]. CFTR activation or increased expression is asso-ciated with a reduction in CaCC function. While CFTR regu-lates ASL homeostasis, CaCC appears to regulate Cl- secretionand ASL height acutely in response to extracellular stimuli [57].Additionally, CFTR has also been described as a regulator ofintracellular energy (ATP), vesicular trafficking, glycosylation,extracellular purinergic receptor function (uridine 5´-triphos-phate and other breakdown products), transmembrane pH gra-dients (HCO3-), antioxidant transport (GSH) and cellularendocytosis [52]. For example, it is believed that abnormal Cl-,HCO3- and glutathione secretion mediated by CFTR leads toreduced volume and increased acidification and oxidation ofASL, which will eventually be responsible for high concentra-tion of proinflammatory mediators and reduced mucociliaryclearance in CF [58].

The idea that CFTR is more than a Cl- channel is continuingto develop. However, the question that remains to be answeredis how far downstream such pleotropic functions of CFTRaffect the disease phenotype.

CFTR-binding partnersCFTR-binding partners that modify the synthesis and process-ing of CFTR might contribute to the CF variability. CFTR isan ATP-binding cassette-transporter that is synthesized andprocessed in the ER, and its delivery to the cell membranerequires an ATP-dependent conformational change [5]. The

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CFTR trafficking competent conformation is mediated by inter-actions with cytosolic and ER chaperones (heat-shock cognateprotein [Hsc]70, heat-shock protein [Hsp]90 and calnexin) andco-chaperones (Hsp40 homologs and chromatin immunoprecip-itation [CHIP]) [59,60]. Class II mutants of CFTR, like F508del-CFTR, have an unstable conformation that is recognized by theER-associated degradation (ERAD) components for ER extrac-tion, ubiquitylation and recruitment to the proteosome for deg-radation. Proteins such as Hsc70, calnexin, co-chaperones/E3ligase CHIP [59,60], derlin1 [61], p97/valosin-containing andgp78/autocrine motility factor receptor [62] have been involved inthe ERAD of F508del-CFTR. However, the complete picture ofproteins involved in the ERAD that distinguish a normal proteinconformation from an abnormal one has been largely unclarified.As F508del-CFTR and probably many other class II CFTRmutants are potentially functional if they can reach the cell sur-face, interfering with the interactions of ERAD components maybe an interesting therapeutic strategy in CF [5].

CFTR at the apical cell membrane can exist as a dimer, clus-tered into distinct microdomains by post-synaptic zona occlu-dens (PDZ)-based interactions that form multimeric complexeswith PDZ proteins [59]. Several PDZ domain interacting part-ners, such as ROMK, a potassium channel, β2-AR receptor,Na+/H+ exchanger regulatory factor (NHERF)1, NHERF2,enhancer binding protein 50 and cytoskeleton proteins, such asazerin, as well as other non-PDZ intermediary interactors, havebeen described to participate in this complex [59]. It has been

hypothesized that F508del cannot form a functional dimerduring biogenesis; therefore, it aggregates and is recognized byERAD [59].

CFTR-binding partners that downregulate CFTR function,such as syntaxin1, SNAP-23 and components of the SNAREmachinery, have also been demonstrated [63]. In general, thegrowing number of proteins that, through a protein–proteininteraction mechanism, influence or collaborate with CFTR forits processing and (multiple) activities has been an importantarea for the elucidation of CF pathophysiology.

Proteomics-based approaches in cystic fibrosis lung disease research The complex interactions and pathways described earlier,which link the dysfunction of the CFTR with CFTR-bindingpartners, CFTR-regulators, modifier genes and the environ-mental factors leading to CF lung disease phenomena as wellas the CF phenotype itself, are very interesting subjects forproteomic research.

The applications of proteomics in the CF field are at an earlystage. The putative strategies using different proteomics-basedapproaches are summarized in FIGURE 2.

According to the type of question, any of the aformentionedproteomics-based approaches can be applied to different bio-logical materials derived from CF patients (e.g., with/withoutexacerbation and/or according to disease stage/severity orpatient age/gender) in addition to animal models, such as CF

Figure 2. Schematic representation of putative proteomic strategies for the development of specific biomarkers in CF lung disease. CF: Cystic fibrosis; CFTR: CF transmembrane conductance regulator; COPD: Chronic obstructive pulmonary disease; LC: Liquid chromatography; MS: Mass spectrometry; MS/MS: Tandem MS; SELDI: Surface-enhanced laser desorption/ionization; TOF: Time-of-flight; wt: Wild type.

Controls

CF patients

Transgenic CF mice

2D gel MS LC/MS/MS SELDI-TOF

Airway system

Blood system

Nasal or bronchial brushing cellsNasal or bronchoalveolar lavage fluidSputum, lung biopsy or autopsy

Serum, plasma, platelets, red blood cells and lymphocytes

Healthy subjects and patientswith other chronic lung diseases,such as asthma and COPD

Cell linesProteomicstechnology platforms

Human CF and non-CF airway cell lines, or cells expressing wt or F508del CFTR cDNA

Bioinformatics

Systems biology

Specific biomarkers for CF lung diseaseExpert Review of Proteomics



transgenic mice [64], cell lines established from healthy controlsor CF patients, or heterologous cell systems expressing thehuman wild-type (wt) or mutated CFTR cDNA [65].

One of the problems associated with patient-derived materialis that CF lung tissue is usually limited. Samples from lungtransplants present a high degree of differentiation and degra-dation, and are thus poor representatives of a patient’s nativelung tissue. One approach to circumvent this limitation andallow for the evaluation of cell and protein components in theupper/lower respiratory tracts of patients is the use of nasal epi-thelial cells, sputum, bronchoalveolar lavage fluid (BALF) orbronchial brushing cells.

Epithelial cells recovered from the superficial nasal mucosa bybrushing have been a useful native biological material in theassessment of chronic respiratory diseases, including CF [66,67].The nasal brushing technique is a noninvasive method thatallows for the easy sampling of numerous representative, well-preserved and dissociated cells from the superficial respiratorymucosa [66,67]. Moreover, as we reported previously, usually80–90% of nasal cells recovered by brushing are epithelial cells,which are the main targets for CFTR expression [66,68]. Recently,through the comparison of 2DE protein profiles of these cellsfrom F508del-homozygous CF patients and non-CF controls,we revealed a set of 18 proteins that are differentially expressedin CF [69]. These included proteins related to chronic inflamma-tion, oxidative stress injury, molecular chaperones and cyto-skeleton organization. Lower levels were found for some mito-chondrial proteins (ATP synthase D chain, NADH-ubiquinoneoxidoreductase and prohibitin), thereby confirming the oldnotion that mitochondrial metabolism is not fully functional inCF tissues. However, further studies will be necessary to clarifythe involvement of such proteins in CF pathophysiology andwhether they might be CF therapeutic targets.

Another amenable sample that is easily collected by non-invasive means is sputum. Searching 2DE sputum profiles fromCF children and CF adult patients with exacerbation, Sloane andcolleagues proposed a set of proteins as inflammation biomarkercandidates that could be used as a standard assessment in CFexacerbation [70]. One of these candidates is myeloperoxidase, aprotein involved in the inflammatory response that was shown tobe associated with exacerbation since decreasing levels afterhospitalization are suggestive of improving pulmonary status [70].

Although BALF is obtained via a more invasive method, itsproteomic analysis may also reveal valuable information on theinflammatory status of the cells lining the lung lumen and theinflux of inflammatory cells [71–73]. Using 2DE and westernblotting, Bredow and Griese demonstrated that the majority ofCF patients analyzed presented, even in the absence of bacte-rial or fungal infection, higher degradation of surfactant pro-tein A, a lung host defense component, as well as a higher abun-dance of BALF low-molecular-weight proteome in comparisonwith controls [74]. The exact identities of these low-molecular-weight proteins are still to be determined and would certainlyprovide important information regarding the inflammation sta-tus in CF in the absence of infection. Using 1DE or 2DE and

high-resolution analysis of MS, Bai and colleagues identifiedmodifications (hydroxyl-prolin) and degradation products ofSP-A and SP-D in BALF of CF patients, but also in patientswith chronic bronchitis or pulmonary alveolar proteinosis [75].This suggests that the inflammation response could share manycommon aspects among different chronic lung diseases. There-fore, comparative studies involving CF patients and patientswith other chronic diseases such as asthma and chronic obstruc-tive pulmonary disease could help provide specific biomarkersfor CF lung inflammation, as suggested in FIGURE 2.

Due to its ready availability, the use of peripheral blood inproteomics has generated considerable excitement among sci-entists in recent years, since this may hold promise for theestablishment of rapid disease blood tests through MS-basedprofiling of patient proteomes/peptidomes [76,77]. The bloodsystem, which includes cells (red blood cells, leukocytes andplatelets) and fluid (serum/plasma) that constantly perfusestissues, can indeed be an interesting source of informationabout the status of CF lung disease.

By screening CF patient blood serum for circulating anti-bodies using a combination of 2DE of sputum, western blot-ting and MS (immunoproteomics), Pedersen and colleagueswere able to identify inflammation-associated autoantigens,including enolase 1B, myeloperoxidase and calgranulin B fromthe sputum of CF patients with acute exacerbation [78]. Thepatients screened were also found to be immunoreactive toP. aeruginosa proteins, such as stress, immunosuppressive andalginate synthetase pathway proteins, implicating their clinicalrelevance as biomarkers of infection [78].

A number of proteomics studies have been performed onmice as a model for lung inflammations other than CF [79–81].The first preliminary results reported by us, using a 2DE gel-free proteomic approach on laser-dissected cells from proximalbronchial epithelium of a transgenic CF mouse that washomozygous for F508del, proved promising and confirmed ouridea that proteomics of a CF model mice will certainly giveimportant hints to CF lung pathology [82].

Due to the limitations of human tissue, immortalized humancell lines as well as heterologous systems expressing human geneshave been of a significant benefit in the study of human disease[65]. The proteomic profiling of an immortalized CF bronchialepithelial cell line, IB3-1, revealed a unique set of 194 high-abundance proteins [83]. The expression of a small group of theseproteins was significantly changed in this cell line when repairedby CFTR gene transfer [84]. Proteomics experiments performedon HeLa cells stably expressing wt-CFTR or F508del-CFTRrevealed the involvement of keratins-8 and -18 in the cellulartrafficking of CFTR. Decreasing the expression of keratin-18 byRNA interference was sufficient to rescue transport of functionalF508del-CFTR to the plasma membrane [85].

Expert commentary & five-year viewThe status of a monogenic disease, in which the unique geneand its corresponding protein are well documented, does notnecessary imply indubitable diagnosis, optimum assessment of

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disease progression, full success in gene-repair therapy or evenreadiness in finding novel (conventional) treatments. As pre-sented here, CF is a perfect example of such a disease. Despitethe remarkable insights gained so far about the CFTR gene andprotein, the complex pathways that link Cl- channel dysfunctionand CF phenotypes are not straightforward. The reality is thatCF remains a lethal disease without effective therapy, especiallyregarding lung pathology.

The spectrum of proteomics-based approaches discussed herecan contribute to the unraveling of the underlying mechanisms ofCF lung pathology, providing biomarkers for different steps. Thiscould simultaneously be useful to promote the development ofnovel therapeutic strategies against CF. As reviewed here, the firstattempts to apply proteomics to the study of CF have proved verypromising, and the progression of these studies together with thedevelopment of the proteomics technology itself will certainlyattract much interest in coming years. The completion of thenormal lung and airway protein inventory should also help inelucidating the pathogenesis of CF lung disease. Implementationof multiple collaborative strategies and proteomic technological

platforms (interacting with genomics) could be necessary, per-haps as a lung project initiative involving Human ProteomeOrganisation (HUPO) [102] and European Proteomics Associa-tion (EuPA) [103]. Concerns have also been voiced regarding sam-ple collection, processing and storage, patient demographics (e.g.,gender and age), analytical chemistry, and data analysis meth-ods. Validation is also an important stage in the biomarker andtherapeutic target discovery process that should be considered ina systems biology approach as much as possible [86].

Acknowledgements Projects running in Deborah Penque’s laboratory are partiallysupported by FEDER/FCT project grants, FCT/Poly-AnnualFunding Program and FEDER/Saúde XXI Program (Portugal).Deborah Penque would like to acknowledge J Lavinha (INSARicardo Jorge-Lisboa) and C Boyd (University Edinburgh, UK)for manuscript discussion and English review, and J Banha forsupporting the compilation of literature references. DeborahPenque apologizes to those authors whose work could not beincluded here due to the space constraints.

Key issues

• The impairment of a unique protein, the cystic fibrosis (CF) transmembrane conductance regulator (CFTR), in CF does not completely explain the complex and variable CF clinical phenotype, and the extensive knowledge gained about CFTR protein/gene to date has not been sufficient to be translated into effective treatments. Therefore, CF patients are still dying, mainly from a chronic progressive lung dysfunction.

• The recent advances in proteomics-based approaches, as those summarized here, have been very promising and, by using some of them, putative biomarker candidates have been unraveled for CF lung disease.

• Progression of these proteomics studies involving CF patients and patients with other chronic diseases (asthma, chronic obstructive pulmonary disease and others) in addition to CF animal/cell models will certainly provide validated biomarkers to elucidate CF basic mechanisms and to better monitor the disease progression or promote the development of novel therapeutic strategies against CF.

ReferencesPapers of special note have been highlighted as:• of interest•• of considerable interest

1 Hanash S. Disease proteomics. Nature 422(6928), 226–232 (2003).

2 Wilkins MR, Sanchez JC, Gooley AA et al. Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it. Biotechnol. Genet. Eng. Rev. 13, 19–50 (1996).

3 Riordan JR, Rommens JM, Kerem B et al. Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA. Science 245(4922), 1066–1073 (1989).

4 Davis PB. Cystic fibrosis since 1938. Am. J. Respir. Crit. Care Med. 173(5), 475–482 (2006).

•• Provides an informative broad overview about cystic fibrosis (CF).

5 Riordan JR. Assembly of functional CFTR chloride channels. Annu. Rev. Physiol. 67, 701–718 (2005).

•• Overview focused on CF transmembrane conductance regulator protein function and dysfunction.

6 Mickle JE, Cutting GR. Genotype–phenotype relationships in cystic fibrosis. Med. Clin. North Am. 84(3), 597–607 (2000).

• Overview of the complex genotype–phenotype correlation in CF.

7 Bernhardt J. Defining the proteome. Genome Biol. 6(12), 360 (2005).

8 Conrads TP, Hood BL, Petricoin EF III, Liotta LA, Veenstra TD. Cancer proteomics: many technologies, one goal. Expert Rev. Proteomics 2(5), 693–703 (2005).

9 Miklos GL, Maleszka R. Integrating molecular medicine with functional proteomics: realities and expectations. Proteomics 1(1), 30–41 (2001).

10 Speers AE, Cravatt BF. Profiling enzyme activities in vivo using click chemistry methods. Chem. Biol. 11(4), 535–546 (2004).

11 Gorg A, Weiss W, Dunn MJ. Current two-dimensional electrophoresis technology for proteomics. Proteomics 4(12), 3665–3685 (2004).

12 Roxo-Rosa M, Davezac N, Bensalem N et al. Proteomics techniques for cystic fibrosis research. J. Cyst. Fibros 3(Suppl. 2), 85–89 (2004).

13 Drews O, Gorg A. DynaProt 2D: an advanced proteomic database for dynamic online access to proteomes and two-dimensional electrophoresis gels. Nucleic Acids Res. 33(Database issue), D583–D587 (2005).

14 Aebersold R, Mann M. Mass spectrometry-based proteomics. Nature 422(6928), 198–207 (2003).

•• Describes the development and application of different mass spectrometers.



15 Gygi SP, Corthals GL, Zhang Y, Rochon Y, Aebersold R. Evaluation of two-dimensional gel electrophoresis-based proteome analysis technology. Proc. Natl Acad. Sci. USA 97(17), 9390–9395 (2000).

16 Roe MR, Griffin TJ. Gel-free mass spectrometry-based high throughput proteomics: tools for studying biological response of proteins and proteomes. Proteomics 6(17), 4678–4687 (2006).

17 Qian WJ, Jacobs JM, Liu T, Camp DG, Smith RD. Advances and challenges in liquid chromatography-mass spectrometry-based proteomics profiling for clinical applications. Mol. Cell. Proteomics 5(10), 1727–1744 (2006).

18 Ong SE, Blagoev B, Kratchmarova I et al. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 1(5), 376–386 (2002).

19 Gygi SP, Rist B, Griffin TJ, Eng J, Aebersold R. Proteome analysis of low-abundance proteins using multidimensional chromatography and isotope-coded affinity tags. J. Proteome Res. 1(1), 47–54 (2002).

20 Shadforth IP, Dunkley TP, Lilley KS, Bessant C. i-Tracker: for quantitative proteomics using iTRAQ™. BMC Genomics 6, 145 (2005).

21 Staes A, Demol H, Van Damme J, Martens L, Vandekerckhove J, Gevaert K. Global differential non-gel proteomics by quantitative and stable labeling of tryptic peptides with oxygen-18. J. Proteome Res. 3(4), 786–791 (2004).

22 Adam GC, Sorensen EJ, Cravatt BF. Chemical strategies for functional proteomics. Mol. Cell. Proteomics 1(10), 781–790 (2002).

23 Saghatelian A, Cravatt BF. Assignment of protein function in the postgenomic era. Nat. Chem. Biol. 1(3), 130–142 (2005).

24 Seibert V, Wiesner A, Buschmann T, Meuer J. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI TOF-MS) and ProteinChip technology in proteomics research. Pathol. Res. Pract. 200(2), 83–94 (2004).

25 Engwegen JY, Gast MC, Schellens JH, Beijnen JH. Clinical proteomics: searching for better tumour markers with SELDI-TOF mass spectrometry. Trends Pharmacol. Sci. 27(5), 251–259 (2006).

26 Becker KF, Metzger V, Hipp S, Hofler H. Clinical proteomics: new trends for protein microarrays. Curr. Med. Chem. 13(15), 1831–1837 (2006).

27 Sobek J, Bartscherer K, Jacob A, Hoheisel JD, Angenendt P. Microarray technology as a universal tool for high-throughput analysis of biological systems. Comb. Chem. High Throughput Screen. 9(5), 365–380 (2006).

28 Koopmann JO, Blackburn J. High affinity capture surface for matrix-assisted laser desorption/ionisation compatible protein microarrays. Rapid Commun. Mass Spectrom. 17(5), 455–462 (2003).

29 Chaurand P, Cornett DS, Caprioli RM. Molecular imaging of thin mammalian tissue sections by mass spectrometry. Curr. Opin. Biotechnol. 17(4), 431–436 (2006).

30 Crockett DK, Lin Z, Vaughn CP, Lim MS, Elenitoba-Johnson KS. Identification of proteins from formalin-fixed paraffin-embedded cells by LC-MS/MS. Lab. Invest. 85(11), 1405–1415 (2005).

31 Hood BL, Darfler MM, Guiel TG et al. Proteomic analysis of formalin-fixed prostate cancer tissue. Mol. Cell. Proteomics 4(11), 1741–1753 (2005).

32 Palmer-Toy DE, Krastins B, Sarracino DA, Nadol JB Jr, Merchant SN. Efficient method for the proteomic analysis of fixed and embedded tissues. J. Proteome Res. 4(6), 2404–2411 (2005).

33 Palagi PM, Hernandez P, Walther D, Appel RD. Proteome informatics I: Bioinformatics tools for processing experimental data. Proteomics 6(20), 5435–5444 (2006).

34 Lisacek F, Cohen-Boulakia S, Appel RD. Proteome informatics II: bioinformatics for comparative proteomics. Proteomics 6(23), 6380 (2006).

•• Attempts to cover the most recent bioinformatics initiatives directed towards representing, storing, displaying and processing protein-related data suited to undertake comparative proteomics studies.

35 Zolg W. The proteomic search for diagnostic biomarkers: lost in translation? Mol. Cell. Proteomics 5(10), 1720–1726 (2006).

• Highlights important considerations in biomarker discovery phase, such as making selections, setting priorities, facing the complexity of samples and validation strategies, among others.

36 Boucher RC. New concepts of the pathogenesis of cystic fibrosis lung disease. Eur. Respir. J. 23(1), 146–158 (2004).

37 Tarran R. Regulation of airway surface liquid volume and mucus transport by active ion transport. Proc. Am. Thorac. Soc. 1(1), 42–46 (2004).

38 Moeller A, Horak F Jr, Lane C et al. Inducible NO synthase expression is low in airway epithelium from young children with cystic fibrosis. Thorax 61(6), 514–520 (2006).

39 Kelley TJ, Drumm ML. Inducible nitric oxide synthase expression is reduced in cystic fibrosis murine and human airway epithelial cells. J. Clin. Invest. 102(6), 1200–1207 (1998).

40 Poschet JF, Boucher JC, Tatterson L, Skidmore J, Van Dyke RW, Deretic V. Molecular basis for defective glycosylation and Pseudomonas pathogenesis in cystic fibrosis lung. Proc. Natl Acad. Sci. USA 98(24), 13972–13977 (2001).

41 Imundo L, Barasch J, Prince A, Al-Awqati Q. Cystic fibrosis epithelial cells have a receptor for pathogenic bacteria on their apical surface. Proc. Natl Acad. Sci. USA 92(7), 3019–3023 (1995).

42 Bryan R, Kube D, Perez A, Davis P, Prince A. Overproduction of the CFTR R domain leads to increased levels of asialoGM1 and increased Pseudomonas aeruginosa binding by epithelial cells. Am. J. Respir. Cell Mol. Biol. 19(2), 269–277 (1998).

43 Pier GB, Grout M, Zaidi TS et al. Role of mutant CFTR in hypersusceptibility of cystic fibrosis patients to lung infections. Science 271(5245), 64–67 (1996).

44 Khan TZ, Wagener JS, Bost T, Martinez J, Accurso FJ, Riches DW. Early pulmonary inflammation in infants with cystic fibrosis. Am. J. Respir. Crit. Care Med. 151(4), 1075–1082 (1995).

45 Zahm JM, Gaillard D, Dupuit F et al. Early alterations in airway mucociliary clearance and inflammation of the lamina propria in CF mice. Am. J. Physiol. 272(3 Pt 1), C853–C859 (1997).

46 Venaille TJ, Ryan G, Robinson BW. Epithelial cell damage is induced by neutrophil-derived, not Pseudomonas-derived, proteases in cystic fibrosis sputum. Respir. Med. 92(2), 233–240 (1998).

47 Hull J, Vervaart P, Grimwood K, Phelan P. Pulmonary oxidative stress response in young children with cystic fibrosis. Thorax 52(6), 557–560 (1997).

48 Zielenski J. Genotype and phenotype in cystic fibrosis. Respiration 67(2), 117–133 (2000).

49 Kristidis P, Bozon D, Corey M et al. Genetic determination of exocrine pancreatic function in cystic fibrosis. Am. J. Hum. Genet. 50(6), 1178–1184 (1992).

Penque


50 Bronsveld I, Mekus F, Bijman J et al. Chloride conductance and genetic background modulate the cystic fibrosis phenotype of Delta F508 homozygous twins and siblings. J. Clin. Invest. 108(11), 1705–1715 (2001).

51 Cutting GR. Modifier genetics: cystic fibrosis. Annu. Rev. Genomics Hum. Genet. 6, 237–260 (2005).

•• Details the current state-of-the-art in CF and CF-modifier genes

52 Vankeerberghen A, Cuppens H, Cassiman JJ. The cystic fibrosis transmembrane conductance regulator: an intriguing protein with pleiotropic functions. J. Cyst. Fibros 1(1), 13–29 (2002).

53 Matsui H, Grubb BR, Tarran R et al. Evidence for periciliary liquid layer depletion, not abnormal ion composition, in the pathogenesis of cystic fibrosis airways disease. Cell 95(7), 1005–1015 (1998).

54 Mall M, Bleich M, Greger R, Schreiber R, Kunzelmann K. The amiloride-inhibitable Na+ conductance is reduced by the cystic fibrosis transmembrane conductance regulator in normal but not in cystic fibrosis airways. J. Clin. Invest. 102(1), 15–21 (1998).

55 Mall M, Grubb BR, Harkema JR, O’Neal WK, Boucher RC. Increased airway epithelial Na+ absorption produces cystic fibrosis-like lung disease in mice. Nat. Med. 10(5), 487–493 (2004).

56 Beck S, Kuhr J, Schutz VV et al. Lack of correlation between CFTR expression, CFTR Cl- currents, amiloride-sensitive Na+ conductance, and cystic fibrosis phenotype. Pediatr. Pulmonol. 27(4), 251–259 (1999).

57 Eggermont J. Calcium-activated chloride channels: (un)known, (un)loved? Proc. Am. Thorac. Soc. 1(1), 22–27 (2004).

58 Machen TE. Innate immune response in CF airway epithelia: hyperinflammatory? Am. J. Physiol. Cell Physiol. 291(2), C218–C230 (2006).

59 Li C, Naren AP. Macromolecular complexes of cystic fibrosis transmembrane conductance regulator and its interacting partners. Pharmacol. Ther. 108(2), 208–223 (2005).

60 Mehta A. CFTR: More than just a chloride channel. Pediatr. Pulmonol. 39(4), 292–298 (2005).

61 Sun F, Zhang R, Gong X, Geng X, Drain PF, Frizzell RA. Derlin-1 promotes the efficient degradation of CFTR and CFTR folding mutants. J. Biol. Chem. 281(48), 36856–36863 (2006).

62 Vij N, Fang S, Zeitlin PL. Selective inhibition of endoplasmic reticulum-associated degradation rescues ΔF508-cystic fibrosis transmembrane regulator and suppresses interleukin-8 levels: therapeutic implications. J. Biol. Chem. 281(25), 17369–17378 (2006).

63 Naren AP, Kirk KL. CFTR chloride channels: binding partners and regulatory networks. News Physiol. Sci. 15, 57–61 (2000).

64 Scholte BJ, Davidson DJ, Wilke M, De Jonge HR. Animal models of cystic fibrosis. J. Cyst. Fibros 3(Suppl. 2), 183–190 (2004).

65 Gruenert DC, Willems M, Cassiman JJ, Frizzell RA. Established cell lines used in cystic fibrosis research. J. Cyst. Fibros 3(Suppl. 2), 191–196 (2004).

66 Penque D, Mendes F, Beck S et al. Cystic fibrosis F508del patients have apically localized CFTR in a reduced number of airway cells. Lab. Invest. 80(6), 857–868 (2000).

67 Danel C, Erzurum SC, McElvaney NG, Crystal RG. Quantitative assessment of epithelial and inflammatory cell populations in large airways of normals and individuals with cystic fibrosis. Am. J. Respir. Crit. Care Med. 153(1), 362–368 (1996).

68 Carvalho-Oliveira I, Efthymiadou A, Malho R et al. CFTR localization in native airway cells and cell lines expressing wild-type or F508del-CFTR by a panel of different antibodies. J. Histochem. Cytochem. 52(2), 193–203 (2004).

69 Roxo-Rosa M, da Costa G, Luider TM et al. Proteomic analysis of nasal cells from cystic fibrosis patients and non-cystic fibrosis control individuals: search for novel biomarkers of cystic fibrosis lung disease. Proteomics 6(7), 2314–2325 (2006).

70 Sloane AJ, Lindner RA, Prasad SS et al. Proteomic analysis of sputum from adults and children with cystic fibrosis and from control subjects. Am. J. Respir. Crit. Care Med. 172(11), 1416–1426 (2005).

71 Noel-Georis I, Bernard A, Falmagne P, Wattiez R. Proteomics as the tool to search for lung disease markers in bronchoalveolar lavage. Dis. Markers 17(4), 271–284 (2001).

72 Neumann M, von Bredow C, Ratjen F, Griese M. Bronchoalveolar lavage protein patterns in children with malignancies, immunosuppression, fever and pulmonary infiltrates. Proteomics 2(6), 683–689 (2002).

73 Plymoth A, Lofdahl CG, Ekberg-Jansson A et al. Human bronchoalveolar lavage: biofluid analysis with special emphasis on sample preparation. Proteomics 3(6), 962–972 (2003).

74 von Bredow C, Birrer P, Griese M. Surfactant protein A and other bronchoalveolar lavage fluid proteins are altered in cystic fibrosis. Eur. Respir. J. 17(4), 716–722 (2001).

75 Bai Y, Galetskiy D, Damoc E et al. High-resolution mass spectrometric alveolar proteomics: identification of surfactant protein SP-A and SP-D modifications in proteinosis and cystic fibrosis patients. Proteomics 4(8), 2300–2309 (2004).

76 Veenstra TD, Conrads TP. Serum protein fingerprinting. Curr. Opin. Mol. Ther. 5(6), 584–593 (2003).

77 Villar-Garea A, Griese M, Imhof A. Biomarker discovery from body fluids using mass spectrometry. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. (2006) (Epub ahead of print).

78 Pedersen SK, Sloane AJ, Prasad SS et al. An immunoproteomic approach for identification of clinical biomarkers for monitoring disease: application to cystic fibrosis. Mol. Cell. Proteomics 4(8), 1052–1060 (2005).

79 Fehniger TE, Sato-Folatre JG, Malmstrom J et al. Exploring the context of the lung proteome within the airway mucosa following allergen challenge. J. Proteome Res. 3(2), 307–320 (2004).

80 Roh GS, Shin Y, Seo SW et al. Proteome analysis of differential protein expression in allergen-induced asthmatic mice lung after dexamethasone treatment. Proteomics 4(11), 3318–3327 (2004).

81 Houtman R, Krijgsveld J, Kool M et al. Lung proteome alterations in a mouse model for nonallergic asthma. Proteomics 3(10), 2008–2018 (2003).

82 Carvalho-Oliveira I, Luider TM, Demmers J, Penque D, Scholte BJ. Identification of proteins by mass spectrometry on laser-dissected cells from mouse proximal bronchial epithelium. Mol. Cell. Proteomics 4(8 Suppl. 1), S142 (2005).

83 Pollard HB, Ji XD, Jozwik C, Jacobowitz DM. High abundance protein profiling of cystic fibrosis lung epithelial cells. Proteomics 5(8), 2210–2226 (2005).

84 Pollard HB, Eidelman O, Jozwik C et al. De novo biosynthetic profiling of high abundance proteins in cystic fibrosis lung epithelial cells. Mol. Cell Proteomics 5(9), 1628–1637 (2006).



85 Davezac N, Tondelier D, Lipecka J et al. Global proteomic approach unmasks involvement of keratins 8 and 18 in the delivery of cystic fibrosis transmembrane conductance regulator (CFTR)/ΔF508-CFTR to the plasma membrane. Proteomics 4(12), 3833–3844 (2004).

86 Kitano H. Systems biology: a brief overview. Science 295(5560), 1662–1664 (2002).

• Highlights the importance of systems biology for the structure and dynamics examination of cellular and organismal function.

Websites

101 Cystic Fibrosis Mutation Database www.genet.sickkids.on.ca/cftr/app

102 Human Proteome Organisation www.hupo.org

103 European Proteomics Association www.eupa.org

Affiliation

• Deborah Penque, PhD

Instituto Nacional de Saúde Dr Ricardo Jorge, Laboratório de Proteómica, Centro de Genética Humana, 1649-016 Lisboa, PortugalTel.: + 351 217 508 137Fax: + 351 217 526 [email protected]

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Proteomic biomarker discovery for the monogenic disease cystic fibrosis