Mass Spectrometry as a Diagnostic and a Cancer Biomarker Discovery Tool
2004; Elsevier BV; Volume: 3; Issue: 4 Linguagem: Inglês
10.1074/mcp.r400007-mcp200
ISSN1535-9484
Autores Tópico(s)Metabolomics and Mass Spectrometry Studies
ResumoSerum proteomic profiling, by using surfaced-enhanced laser desorption/ionization-time-of-flight mass spectrometry, is one of the most promising new approaches for cancer diagnostics. Exceptional sensitivities and specificities have been reported for some cancer types such as prostate, ovarian, breast, and bladder cancers. These sensitivities/specificities are far superior to those obtained by using classical cancer biomarkers. In this review, I concentrate more on questions that cast doubt on the results reported and propose experiments to investigate these questions in detail, before the technique is used at the clinic. It is clear that the method needs to be externally and thoroughly validated before clinical implementation is warranted. Serum proteomic profiling, by using surfaced-enhanced laser desorption/ionization-time-of-flight mass spectrometry, is one of the most promising new approaches for cancer diagnostics. Exceptional sensitivities and specificities have been reported for some cancer types such as prostate, ovarian, breast, and bladder cancers. These sensitivities/specificities are far superior to those obtained by using classical cancer biomarkers. In this review, I concentrate more on questions that cast doubt on the results reported and propose experiments to investigate these questions in detail, before the technique is used at the clinic. It is clear that the method needs to be externally and thoroughly validated before clinical implementation is warranted. Our current efforts to combat cancer are not very successful. Despite the recent spectacular advances in molecular medicine, genomics, proteomics, and translational research, mortality rates for the most prevalent cancers have not been significantly reduced. Some of the best available options to combat cancer include primary prevention, earlier diagnosis, and improved therapeutic interventions. We are now witnessing the development of new drugs against cancer that are based on rational instead of empirical designs. There is hope that some of these drugs will prove to be more effective at the clinic than older generations of medicines. In terms of primary prevention, we do not as yet have at hand any robust strategies, because the mechanisms of cancer initiation and progression are still largely unknown.One of the best strategies to combat cancer now is by early diagnosis and administration of effective treatment (1Etzioni R. Urban N. Ramsey S. McIntosh M. Schwartz S. Ried B. Radich J. Anderson G. Hartwell L. The case for early detection..Nature Rev. Cancer. 2003; 3: 243-252Google Scholar). Another approach includes close monitoring of the cancer patient after initial treatment (usually surgery) to detect early relapse and then prescribe additional therapy. A third valuable approach would be the stratification of patients into subgroups that respond better to different types of treatment (individualized therapy). Medical imaging and serum or tissue biomarkers are valuable tools for monitoring these patients in order to optimize clinical outcomes.In this review, I will concentrate on mass spectrometry as a diagnostic and cancer biomarker discovery tool. Much has been published on this technology, and excellent reviews have already been prepared (2Petricoin E.F. Zoon K.C. Kohn E.C. Barrett J.C. Liotta L.A. Clinical proteomics: Translating benchside promise into bedside reality..Nature Rev. 2002; 1: 683-695Google Scholar, 3Srinivas P.R. Srivastava S. Hannah S. Wright Jr., G.L. Proteomics in early detection of cancer..Clin. Chem. 2001; 47: 1901-1911Google Scholar, 4Marvin L.F. Roberts M.A. Laurent B.F. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in clinical chemistry..Clin. Chim. Acta. 2003; 337: 11-21Google Scholar, 5Merchant M. Weinberger S.R. Recent advancements in surface-enhanced laser desorption/ionization time-of-flight-mass spectrometry..Electrophoresis. 2000; 21: 1164-1167Google Scholar, 6Fung E.T. Enderwick C. ProteinChip clinical proteomics: Computational challenges and solutions..BioTechniques. 2002; 81 (Suppl. 34)40-(Suppl. 34)41Google Scholar, 7Isaaq H.J. Veenstra T.D. Conrads T.P. Felschow D. The SELDI-TOF MS approach to proteomics: protein profiling and biomarker identification..Biochem. Biophys. Res. Commun. 2002; 292: 587-592Google Scholar, 8Isaaq H.J. Conrads T.P. Prieto D.A. Tirumalai R. Veenstra T.D. SELDI-TOF MS for diagnostic proteomics..Anal. Chem. 2003; 75: 149A-155AGoogle Scholar, 9Wulfkuhle J.D. Liotta L.A. Petricoin E.F. Proteomic applications for the early detection of cancer..Nature Rev. 2003; 3: 267-276Google Scholar, 10Petricoin E.F. Zoon K.C. Kohn E.C. Barrett J.C. Liotta L.A. Clinical proteomics: Translating benchside promise into bedside reality..Nature Rev. Drug Discovery. 2002; 1: 683-695Google Scholar, 11Pusch W. Flocco M.T. Leung S.-M. Thiele H. Kostrzewa M. Mass spectrometry-based clinical proteomics..Pharmacogenomics. 2003; 4: 1-14Google Scholar, 12Raj A.J. Zhang Z. Rosenzweig J. Shih L-M. Pham T-P. Fung E.T. Sokoll L.J. Chan D.W. Proteomic approaches to tumor marker discovery..Arch. Pathol. Lab. Med. 2002; 126: 1518-1526Google Scholar). My presentation will be biased toward underlining potential limitations that have not been adequately addressed in the already existing extensive literature.MASS SPECTROMETRYMass spectrometry has been used as a diagnostic tool in clinical laboratories for many decades. This technology has been coupled with gas chromatography (GC/MS) 1The abbreviations used are: GC/MS, gas chromatography/mass spectrometry; MALDI, matrix-assisted laser desorption/ionization; ESI, electrospray ionization; MS/MS, tandem mass spectrometry; LC/MS, liquid chromatography/mass spectrometry; SELDI-TOF, surface-enhanced laser desorption/ionization time-of-flight; PSA, prostate-specific antigen; ELISA, enzyme-linked immunosorbent assay; PSMA, prostate-specific membrane antigen. and has been used with success for the identification and quantification of relatively small molecules (with molecular mass 99%) for the test to be considered viable (18Menon U. Jacobs I. Screening for ovarian cancer..Best Pract. Res. Clin. Obstet. Gynaecol. 2002; 16: 469-482Google Scholar). It can be concluded that none of the individual biomarkers currently at hand can fulfill the requirements of population screening for cancer. Biomarkers are clinically recommended mainly for monitoring the effectiveness of therapeutic interventions. Some biomarkers are also invaluable tools for early diagnosis of cancer relapse, which may trigger additional treatments before the appearance of clinical symptoms.Table ISome established cancer biomarkersBiomarkeraAll of these markers are used as aids in diagnosis, prognosis, and monitoring of therapy; steroid hormone receptors are used for predicting therapeutic response to antiestrogens.Cancer typebAll markers measured in serum except steroid hormone receptors, which are measured in cancer tissues.α-Fetoprotein (AFP)Hepatoma; testicular cancerCarcinoembryonic antigen (CEA)Colon; breast; lung; pancreaticPSAProstateCA125OvarianCA15.3BreastCA19.9GastrointestinalImmunoglobulinsB cell dyscrasiasChroriogonadotropin (hCG)Testicular cancer; trophoblastic tumorsSteroid hormone receptorsBreasta All of these markers are used as aids in diagnosis, prognosis, and monitoring of therapy; steroid hormone receptors are used for predicting therapeutic response to antiestrogens.b All markers measured in serum except steroid hormone receptors, which are measured in cancer tissues. Open table in a new tab With current cancer biomarkers, much is left to be desired in terms of clinical applicability. We need new cancer biomarkers that will further enhance our ability to diagnose, prognose, and predict therapeutic response in many types of cancer. Because biomarkers can be analyzed relatively noninvasively and economically, it is worth investing in discovering more biomarkers in the future. The completion of the Human Genome Project has raised expectations that the knowledge of all genes and proteins will lead to the identification of many candidate biomarkers for cancer and other diseases. This prediction still needs to be realized. Among specialists in the field, the prevailing view is that the most powerful single cancer biomarkers may have already been discovered (e.g. those shown in Table I). Likely, we are now bound to discover biomarkers that are less sensitive or specific but that could be used in panels, in combination with powerful bioinformatic tools (such as artificial neural networks, logistic regression, etc.), to devise diagnostic algorithms with improved sensitivity and specificity (19Finne P. Finne R. Stenman U.H. Neural network analysis of clinicopathological factors in urological disease: A critical evaluation of available techniques..Brit. J. U. Intl. 2001; 88: 825-831Google Scholar, 20Stephan C. Vogel B. Cammann H. Lein M. Klevecka V. Sinha P. Kristiansen G. Schnorr D. Jung K. Leoning S.A. An artificial neural network as a tool in risk evaluation of prostate cancer. Indication for biopsy with the PSA range of 2–20 microg/l..Urologe A. 2003; 42: 1221-1229Google Scholar). These efforts are currently ongoing.GENERAL STRATEGIES FOR DISCOVERING NEW CANCER BIOMARKERSMost of the currently used cancer biomarkers were discovered following development of novel analytical techniques, such as immunological assays and the monoclonal antibody technology. It was then found that these molecules were elevated in biological fluids from cancer patients in comparison to normal subjects. Many cancer biomarkers were discovered by immunizing animals with extracts from tumors or cancer cell lines, and then screening for monoclonal antibodies that recognize “cancer-associated” antigens. More recently, and with the completion of the Human Genome Project, many researchers hypothesized that the best cancer biomarkers will likely be secreted proteins (21Welsh J.B. Sapinoso L.M. Kern S.G. Brown D.A. Liu T. Bauskin A.R. Ward R.N. Hawkins N.J. Quinn D.I. Russell P.J. Sutherland R.L. Breit S.N. Moskaluk CA. Frierson Jr., H.F. Hampton G.M. Large-scale delineation of secreted protein biomarkers overexpressed in cancer tissue and serum..Proc. Natl. Acad. Sci. U. S. A. 2003; 100: 3410-3415Google Scholar); about 20–25% of all cell proteins are secreted. However, this is not an absolute requirement because a number of classical cancer biomarkers (e.g. CEA, Her2-neu) are cell membrane-bound, but their extracellular domains are shed into the circulation. Other groups, including our own, are using bioinformatics, such as digital differential display and in silico Northern blotting, to compare gene expression between normal and cancerous tissues to identify overexpressed genes (22Yousef G.M. Polymeris M.E. Yacoub G.M. Scorilas A. Soosaipillai A. Popalis C. Fracchioli S. Katsaros D. Diamandis E.P. Parallel overexpression of seven kallikrein genes in ovarian cancer..Cancer Res. 2003; 63: 2223-2227Google Scholar). Although one of the prevailing hypotheses in new biomarker discovery is that the most promising biomarkers should be overexpressed proteins, this is not generally true for some of the best known cancer biomarkers such as PSA (23Makglara A. Scorilas A. Stephan C. Kristiansen G.O. Hauptmann S. Jung K. Diamandis E.P. Decreased concentrations of prostate-specific antigen and human glandular kallikrein 2 in malignant versus nonmalignant prostatic tissue..Urology. 2000; 56: 527-532Google Scholar). Overexpressed genes are now identified experimentally by using microarrays. Some of these genes have been proposed as candidate cancer biomarkers (24Welsh J.B. Sapinoso L.M. Si A.I. Kern S.G. Wang-Rodriguez J. Moskaluk C.A. Frierson Jr., H.F. Hampton G.M. Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer..Cancer Res. 2001; 61: 5974-5978Google Scholar, 25Welsh J.B. Zarrinkar P.P. Sapinoso L.M. Kern S.G. Behling C.A. Monk B.J. Lockhart D.J. Burger R.A. Hampton G.M. Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer..Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 1176-1181Google Scholar, 26Hellstrom I. Raycraft J. Hayden-Ledbetter M. Ledbetter J.A. Schummer M. McIntosh M. Drescher C. Urban N. Hellstrom K.E. The HE4 (WFDC2) protein is a biomarker for ovarian carcinoma..Cancer Res. 2003; 63: 3695-3700Google Scholar). Despite this reasonable hypothesis, very few cancer biomarkers have been discovered by using this approach (26Hellstrom I. Raycraft J. Hayden-Ledbetter M. Ledbetter J.A. Schummer M. McIntosh M. Drescher C. Urban N. Hellstrom K.E. The HE4 (WFDC2) protein is a biomarker for ovarian carcinoma..Cancer Res. 2003; 63: 3695-3700Google Scholar, 27Kim J.H. Skates S.J. Uede T. Wong K.k.K.K. Schorge J.O. Feltmate C.M. Berkowitz R.S. Cramer D.W. Mok S.C. Osteopontin as a potential diagnostic biomarker for ovarian cancer..J. Am. Med. Assoc. 2002; 287: 1671-1679Google Scholar). We followed another approach, in which we postulated that if a molecule is already a known-cancer biomarker, members of the same family of genes/proteins may also constitute novel biomarkers. We have since shown that kallikreins, a group of serine proteases with high homology at both the DNA and protein levels (this family includes PSA), are candidate biomarkers for ovarian, prostate, and breast cancers (28Diamandis E.P. Yousef G.M. Human tissue kallikreins: A family of new cancer biomarkers..Clin. Chem. 2002; 48: 1198-1205Google Scholar, 29Yousef G.M. Diamandis E.P. The new human tissue kallikrein gene family: Structure, function and association to disease..Endocr. Rev. 2001; 22: 184-204Google Scholar).Over many years of developing cancer biomarkers, we came to understand that a molecule may become a practical serological biomarker if it has certain characteristics, i.e. it is a secreted or shed protein and has the ability to diffuse into the circulation during tumor development and progression, through either angiogenesis or invasion of surrounding tissues and vasculature by cancer cells. Preferably, such proteins should be stable (not degraded) and not bound to inhibitors that could interfere with their measurement. The experience with the classical biomarkers has taught us many lessons on the dynamic relationships between the patient and biological phenomena related to biomarkers such as appearance in the circulation, cleavage, binding to serum proteins, degradation, modification, elimination half-life, etc. In this review, I will use PSA as an example to compare what we know from such molecules with mass spectrometric approaches for diagnostics.MASS SPECTROMETRY AS A CANCER BIOMARKER DISCOVERY AND DIAGNOSTIC TOOLPetricoin et al. have pioneered the use of mass spectrometry as a diagnostic tool (30Petricoin III E.F. Ardekani A.M. Hitt B.A. Levine P. Fusaro V.A. Steinberg S. Mills G.B. Simcoe C. Fishman D.A. Kohn D.C. Liotta L.A. Use of proteomic patterns in serum to identify ovarian cancer..Lancet. 2002; 359: 572-575Google Scholar). They suggested that this approach represents a paradigm shift in cancer diagnostics, based on complex mass spectrometric differences between proteomic patterns in serum between patients with or without cancer identified by bioinformatics. Their premise is that no matter what the nature of these molecules are, their potential to discriminate between these two conditions should be further exploited. The central hypothesis of this approach is as follows: protein or protein fragments produced by cancer cells or their microenvironment may eventually enter the general circulation. Then, the concentration (abundance) of these proteins/fragments could be analyzed by mass spectrometry and used for diagnostic purposes, in combination with a mathematical algorithm (30Petricoin III E.F. Ardekani A.M. Hitt B.A. Levine P. Fusaro V.A. Steinberg S. Mills G.B. Simcoe C. Fishman D.A. Kohn D.C. Liotta L.A. Use of proteomic patterns in serum to identify ovarian cancer..Lancet. 2002; 359: 572-575Google Scholar).The vast majority of the currently available data have been produced by using the SELDI-TOF technology, marketed by Ciphergen Biosystems (Fremont, CA). Ciphergen claims that over 200 papers have already been published with this technology. The types of cancers that have been examined include ovarian, prostate, breast, bladder, renal, and others, and the biological fluids analyzed include serum, urine, cerebrospinal fluid, nipple aspirate fluid, etc. The apparent successes with this technology have been recently reviewed by many investigators (2Petricoin E.F. Zoon K.C. Kohn E.C. Barrett J.C. Liotta L.A. Clinical proteomics: Translating benchside promise into bedside reality..Nature Rev. 2002; 1: 683-695Google Scholar, 3Srinivas P.R. Srivastava S. Hannah S. Wright Jr., G.L. Proteomics in early detection of cancer..Clin. Chem. 2001; 47: 1901-1911Google Scholar, 4Marvin L.F. Roberts M.A. Laurent B.F. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in clinical chemistry..Clin. Chim. Acta. 2003; 337: 11-21Google Scholar, 5Merchant M. Weinberger S.R. Recent advancements in surface-enhanced laser desorption/ionization time-of-flight-mass spectrometry..Electrophoresis. 2000; 21: 1164-1167Google Scholar, 6Fung E.T. Enderwick C. ProteinChip clinical proteomics: Computational challenges and solutions..BioTechniques. 2002; 81 (Suppl. 34)40-(Suppl. 34)41Google Scholar, 7Isaaq H.J. Veenstra T.D. Conrads T.P. Felschow D. The SELDI-TOF MS approach to proteomics: protein profiling and biomarker identification..Biochem. Biophys. Res. Commun. 2002; 292: 587-592Google Scholar, 8Isaaq H.J. Conrads T.P. Prieto D.A. Tirumalai R. Veenstra T.D. SELDI-TOF MS for diagnostic proteomics..Anal. Chem. 2003; 75: 149A-155AGoogle Scholar, 9Wulfkuhle J.D. Liotta L.A. Petricoin E.F. Proteomic applications for the early detection of cancer..Nature Rev. 2003; 3: 267-276Google Scholar, 10Petricoin E.F. Zoon K.C. Kohn E.C. Barrett J.C. Liotta L.A. Clinical proteomics: Translating benchside promise into bedside reality..Nature Rev. Drug Discovery. 2002; 1: 683-695Google Scholar, 11Pusch W. Flocco M.T. Leung S.-M. Thiele H. Kostrzewa M. Mass spectrometry-based clinical proteomics..Pharmacogenomics. 2003; 4: 1-14Google Scholar, 12Raj A.J. Zhang Z. Rosenzweig J. Shih L-M. Pham T-P. Fung E.T. Sokoll L.J. Chan D.W. Proteomic approaches to tumor marker discovery..Arch. Pathol. Lab. Med. 2002; 126: 1518-1526Google Scholar). In general, it has been suggested that this technology can achieve much higher diagnostic sensitivity and specificity (approaching 100%) in comparison to the classical cancer biomarkers (31Powell K. Proteomics delivers on promise of cancer biomarkers..Nat. Med. 2003; 9: 980Google Scholar). The technology’s potential has been expanded to other diseases such as Alzheimer’s disease, Creutzfeldt-Jakob disease, renal allograft rejection, etc. (32Carrette O. Demalte I. Scherl A. Yalkinoglu O. Corthais G. Burkhard P. Hochstrasser D.F. Sanchez J.C. A panel of cerebrospinal fluid potential biomarkers for the diagnosis of Alzheimer’s disease..Proteomics. 2003; 3: 1486-1494Google Scholar, 33Guillaume E. Zimmerman C. Burkhard P.R. Hochstrasser D.F. Sanchez J-C. A poteintial cerebrospinal fluid and plasmatic marker for the diagnosis of Creutzfeldt-Jacob disease..Proteomics. 2003; 3: 1495-1499Google Scholar, 34Clarke W. Silverman B.C. Zhang Z. Chan D.W. Klein A.S. Molmenti E.P. Characterization of renal allograft rejection by urinary proteomic analysis..Ann. Surg. 2003; 237: 660-664Google Scholar).The analytical procedure with this technology involves a few common steps. The biological fluid of interest is first interacted with a protein chip that incorporates some kind of an affinity separation between “noninformative” and “informative” proteins. After washing, the immobilized (and fortunately mostly informative) proteins can be studied by using SELDI-TOF mass spectrometry. Two types of data have been reported in the literature: 1) discriminating peaks of unknown identity that are different in amplitude (increased or decreased) between normal individuals and patients with cancer; and 2) data in which at least some of these peaks have been positively identified (see below). Computer algorithms have been used to analyze these multidimensional data to demonstrate that a pattern consisting of several peaks (from tens to thousands) is sufficiently different between the two groups of subjects. In this review, I will not comment much on peaks that have not been positively identified, because nothing is known about them, except that their heights go up or down in the disease state. I will use the few positively identified molecules to draw comparisons between them and the classical cancer biomarkers.The extraordinary data presented in the literature with this new approach were welcomed by scientists, the press, the public, and even by politicians (31Powell K. Proteomics delivers on promise of cancer biomarkers..Nat. Med. 2003; 9: 980Google Scholar, 35Service R.F. Recruiting genes, proteins for a revolution in diagnostics..Science. 2003; 300: 235-239Google Scholar). This technology is now seen as the most promising way of diagnosing early cancer (35Service R.F. Recruiting genes, proteins for a revolution in diagnostics..Science. 2003; 300: 235-239Google Scholar). Clinical trials are now underway and will reveal, in a blinded fashion, if these data can be reproduced and if they are robust enough for clinical use. In the following paragraphs, I will concentrate on issues that have not been adequately addressed and raise concerns that at least some of this data may not be accurate or expected on theoretical grounds.The use of SELDI-TOF technology as a cancer biomarker discovery tool (as opposed to a cancer diagnostic tool) is straightforward. The discriminatory peaks, if positively identified, may represent molecules that could be measured with simpler and cheaper techniques for the purpose of diagnosing cancer. For example, some investigators postulate that such molecules may be routinely quantified by using enzyme-linked immunosorbent assay (ELISA) technologies. In practice, very few, if any, of the SELDI-TOF identified novel candidate biomarkers have been validated by using alternative technologies.POTENTIAL LIMITATIONSLiotta et al. hypothesized that the relative cellular abundance of tens of thousands of different proteins, along with their cleaved or modified forms, is a reflection of ongoing physiological and pathological events. They further postulate that as tissues are perfused by blood and lymph, proteins and protein fragments, passively or actively, enter the circulation. Thus, the complex chemistry of the tumor-host microenvironment should generate unique signatures in the blood microenvironment. I agree with this statement. The major question here is if these putative
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