Advances, Challenges, and Limitations in Serum-Proteome-Based Cancer Diagnosis Matthias P. A. Ebert,†,* Murray Korc,| Peter Malfertheiner,§ and Christoph Ro1 cken‡ Medical Department II, Klinikum rechts der Isar, Technical University of Munich, D-81675 Munich, Germany, Institute of Pathology and Department of Gastroenterology and Hepatology, Otto-von-Guericke University, D-39120 Magdeburg, Germany, and Departments of Medicine, and Pharmacology and Toxicology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire 03756 Received August 17, 2005
Recent advances in medicine have dramatically reduced the incidence and mortality of many cardiovascular, infectious, and certain neoplastic diseases; the overall mortality for most malignant solid tumors remains high. The poor prognosis in these cancers is due, in part, to the absence of adequate early screening tests, leading to delays in diagnosis. Three strategies have been applied to fight cancer: analysis of the molecular mechanisms involved in its pathogenesis and progression, improvement of early diagnosis, and the development of novel treatment strategies. There have been major advances in our understanding of cancer biology and pathogenesis and in the development of new (targeted) treatment modalities. However, insufficient progress has been made with respect to improving the methods for the early diagnosis and screening of many cancers. Therefore, cancer is often diagnosed at advanced stages, delaying timely treatment and leading to poor prognosis. Proteome analysis has recently been used for the identification of biomarkers or biomarker patterns that may allow for the early diagnosis of cancer. This tool is of special interest, since it allows for the identification of tumor-derived secretory products in serum or other body fluids. In addition, it may be used to detect reduced levels or loss of proteins in the serum of cancer patients that are present in noncancer individuals. These changes in the serum proteome may result from cancer-specific metabolic or immunological alterations, which are, at least partly, independent of tumor size or mass, thereby fascilitating early discovery. Keywords: tumor • serum • screening • diagnosis • proteome
Introduction Recent epidemiological data from Europe indicate that more than 2 million Europeans will develop a malignant tumor, in which gastrointestinal tumors in general and colorectal cancers in particular are by far the most frequent cancers.1 While there are both increasing and decreasing incidences for various cancers of the gastrointestinal tract, the overall mortality is high and prognosis remains poor.1,2 Most patients are diagnosed at advanced stages with the presence of either a locally advanced tumor and/or evidence of lymph node or distant metastases that often do not allow for curative tumor resection. Cancer is also often a disease of the elderly and serious co-morbidities may further limit aggressive therapeutic options.3 In these cases, systemic therapy, such as chemotherapy or combined * Address correspondence to Matthias P. A. Ebert, MD, II. Medical Department, Klinikum rechts der Isar, Technical University of Mu ¨ nchen, Ismaningerstr. 22, D-81675 Mu ¨ nchen, Germany. Tel: +49-89-4140-2250. Fax: +49-89-4140-4871. E-mail:
[email protected]. † Technical University of Munich. | Dartmouth-Hitchcock Medical Center. § Department of Gastroenterology and Hepatology, Otto-von-Guericke University. ‡ Institute of Pathology, Otto-von-Guericke University. 10.1021/pr050271e CCC: $33.50
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chemoradiation, is necessary. Both may have serious side effects, and the overall impact on patient survival and prognosis is poor. Thus, to improve cancer prognosis, it has to be diagnosed in its early stages.4 This can be achieved by identifying high-risk populations, enrolling them in screening and surveillance programs, and using highly sensitive, specific, and cost-effective disease markers, with the ultimate goal of either treating cancer curatively or preventing its formation.5 Thus, the identification of markers of cancer development is of great importance and would form the basis for efficient screening programs. The requirements for these markers are the following: 1. high sensitivity and specificity for the detection of cancer at an early stage or detection of precursor lesions; 2. easy and noninvasive access to the site of biomarker assessment, such as plasma or serum and other body fluids; 3. cheap, rapid, reproducible, and cost-effective determination of the biomarker or biomarker pattern; and 4. the capability to tail the treatment strategy. If these requirements were met, the diagnosis of human cancers would be greatly facilitated, and cancer prognosis would improve. Unfortunately, most common tumor markers, Journal of Proteome Research 2006, 5, 19-25
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reviews that are mainly determined in the serum of cancer patients, do not meet these requirements.6 While the role of R-fetoprotein (AFP) for hepatocellular cancer and of prostate specific antigen (PSA) for prostate cancer in clinical management of these particular cancers is well-established, other cancers cannot be identified by a tumor-specific serum marker.7,8 For example, gastric cancers are frequently diagnosed at an advanced stage, restricting the number of curatively treatable patients.9 By the time of diagnosis, most gastric cancers have spread to the lymph nodes, which is the most significant independent prognostic factor for this disease: the five-yearsurvival rate of patients with lymph node metastases is 9.8 ( 4% as compared with 58 ( 11% for patients without lymph node metastases.10 As in the case of many other cancers, the early diagnosis of gastric cancer with currently available serum tumor markers, such as CEA, Ca 72-4, or Ca 19-9, is impossible, as they have a low sensitivity and specificity.11-13 Stage I gastric cancer is identified in less than 25% of the cases using any of these serum markers. Thus, these serum markers are insufficient for early diagnosis or for the screening of gastric cancer.14 Alternatively, gastroscopic examination has been proposed as a screening method for the early detection of gastric cancer. However, no randomized trials evaluating a positive impact of screening on mortality from gastric cancer have been reported.15 Gastroscopy is an expensive procedure with risks, reaching beyond blood sampling. There may be some justification for gastroscopic screening of some populations that are at high risk for this malignancy. However, there is considerable debate with respect to incidence rates that would justify such screening, especially since gastroscopy does not meet requirements for a screening test, such as high convenience and efficiency.15 Molecular Diagnosis of Cancers. A multitude of studies have addressed the molecular biology and pathogenesis of cancer. Overall there seems to be a common background of genetic and molecular alterations which underly cancer pathogenesis, especially with respect to gastrointestinal cancers, where there is an abundance of genomic mutations and a high frequency of chromosomal instability.16 Genetic and epigenetic changes on the basis of microsatellite instability associated with impaired function of DNA repair genes provide another distinct and different pathway for the development of cancers.17 On the basis of these findings, several groups have tried to use specific molecular changes to identify patients with cancer or precursor lesions. Analyses were performed using stool, serum, blood, pancreatic juice, urine, and other biological samples.18-20 Generally, both RNA and DNA were employed for the analysis of tumor-specific changes in biological fluids. These include the analysis of tyrosinase mRNA in patients with suspected malignant melanoma, thyroglobulin mRNA in patients with suspected thyroid cancer, as well as other tumor-specific changes.21,22 Other studies addressed the utility of genomic DNA alterations in the diagnosis of cancer patients, in which free circulating DNA in serum or DNA from circulating cancer cells in blood samples of patients with cancers was determined.23-25 Interestingly, the amount of free DNA in serum samples from cancer patients is increased compared to individuals without cancer.26 K-ras mutations can be found in the blood of pancreatic cancer patients and p16 and/or APC mutations in peripheral blood or stool of colorectal cancer patients.23-25 Apart from the analysis of genetic alterations of the circulating DNA in cancer patients, the presence of circulating viral DNA or RNA has also been used for the identification of cancer 20
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patients. Thus, circulating EBV DNA has been considered a potential tumor marker for nasopharyngeal and gastric cancers.27,28 Nonetheless, the analysis of genetic and molecular alterations of genomic DNA in serum or blood of cancer patients has been largely disappointing. Most of these studies were performed with a small number of patients. The sensitivities and specificities achieved are, as yet, unsatisfactory. In addition, not all cancers, even of the same origin, exhibit the same molecular changes, increasing the risk for false-negative results. Considerable interest was raised by the analysis of epigenetic changes in biological samples from cancer patients, since these changes are present frequently and occur early in the pathogenesis of almost all cancers.29 First results from the analysis of gene methylation in epithelial cells present in either the sputum of lung cancer patients, the stool, or peripheral blood of colorectal cancer patients, have been published recently.30,31 However, again these studies need to be confirmed by large studies with more patients and adequate controls before a final interpretation of their efficacy can be established. Apart from the detection of cancer-specific alterations of tumor-derived RNA and DNA, serum levels of certain proteins involved in tumor biology have also been assessed in cancer patients. Serum levels of cathepsin B, E-cadherin, hepatocyte growth factor, interleukins, and other cytokines and hormones have been measured in the serum of cancer patients.32-36 However, while some markers are useful to assess patient prognosis after a diagnosis was reached, sensitivity and specificity are too low in order to fascilitate the detection of cancer in its early stages. Serum Protein Profiling. Recent developments in the field of proteome analysis have led to considerable advances in our understanding of the changes and functional expression of proteins in the process of cancer biology. 2D-PAGE analysis has been the standard procedure for more than 30 years, which has been combined with mass spectrometry (MALDI) for the detection of aberrantly expressed proteins in tissue and serum of cancer patients.37 With the help of 2D-PAGE analysis, nanomolar amounts of proteins are separated and identified by mass spectrometry, especially in the molecular weight ranging from 10 to 150 kDa. Approximately 1000-3000 proteins can be separated on a pH range from 3 to 10, whereas using a more narrow pH range, for example, 4-7, the resolution and number of proteins can be increased. However, this method exhibits some major limitations regarding its role in the identification of potential biomarkers for cancer diagnosis: this method is less well-suited for small, and either very basic or acidic proteins, or hydrophobic proteins.38,39 Furthermore, the protein amounts required for reproducible identification of serum proteins are rather high, and standardization of the technique is difficult. In contrast, SELDI-TOF MS is a rather new method which is especially valuable for the identification of serum-derived biomarkers.40 This method is based on ProteinChip Arrays which carry various chromatographic properties, such as anion exchange, cation exchange, and hydrophilic or hydrophobic surfaces.41 For the analysis of serum, only 5-10 µL of serum sample is applied to these surfaces; after washing off unbound material, the protein fingerprint can be determined and visualized by time-of-flight mass spectrometry. The advantages of this method are the low amount of sample necessary for analysis, its speed, and high throughput capability.40,41 Many different groups have used this method and related methods based on prefractionation of serum proteins by beads and subsequent MALDI analysis for the identification
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Figure 1. Overlay of representative spectra of healthy individuals (red) and patients with gastric cancer (blue). Note reduced peak height of several masses, indicating reduced serum levels or even loss of certain masses in cancer patients (arrows).
of biomarkers in serum, urine, pancreatic juice, and other biological fluids.42-46 In these studies, the identification of cancers based on these biomarkers or biomarker patterns was possible and beyond the sensitivity and specificity of conventional serum markers. Interestingly, many of the peptides and proteins that were identified in the course of SELDI analysis have not previously been linked to the biology of human cancers, and thus, this method also provides further insight into the changes leading to or underlying cancer development and progression. Various groups have confirmed the high sensitivity and specificity of this method for the detection of various cancers, including bladder, prostate, ovarian, pancreatic, and breast cancer.42-45 We also used SELDI analysis based on ProteinChip Arrays to screen for biomarkers or biomarker patterns for the identification of gastric cancer patients.46 Interestingly, we found profound changes in the serum protein profile in gastric cancer patients versus patients with dyspepsia in which cancer was ruled out by endoscopy (Figure 1). However, none of the single masses proved to be able to separate all cancer patients from noncancer individuals. Using the decision tree analysis, we generated a classifier ensemble with 28 out of 71 masses to generate 50 decision trees. This classifier ensemble was highly effective in the differentiation of cancer patients from noncancer individuals. Thus, while all cancers in the training set were correctly classified (sensitivity 100%), even 8 of 9 stage I cancers of an independent test set were correctly classified as cancer patients.46 Specificity was high as well, in that all but one individual without cancer of a further independent test set were correctly classified as noncancer individuals. Interestingly, the decision trees were generated from masses that were identified both in the serum of cancer individuals and noncancer individuals. Thus, the high performance of the classifier ensemble was based not only on the identification of tumor-derived or tumor-specific masses in cancer patients but also on the decreased levels or loss of certain proteins in the serum of cancer patients which were present in noncancer individuals. Several other groups have also reported the down-regulation of certain proteins in different kinds of cancer both in the tumor itself using MALDI MS imaging or in the serum using SELDI-TOF MS.47-50 Recently, magnet bead-assisted prefractionation of serum proteins combined with proteome analysis by MALDI has also been developed and used for the identification of biomarkers and biomarker patterns in various diseases, such as lymphatic leukaemia, brain tumors, and inflammatory diseases.51-53 While reproducibility has been demonstrated to be good in a study conducted by Zhang et al.,53 further studies are required to define the role of this approach in clinical proteomics. The Tumor-Host Interface and Cancer Diagnosis. Conventional serum tumor markers are based on the measurement
of tumor-derived or tumor-specific secretory peptides or proteins in the serum of cancer patients. Thus, the detection of circulating levels of AFP has proven to be of adequate efficacy for the identification of most patients with hepatocellular cancer, at least in advanced stages.7 In addition, other conventional serum markers such as carcinoembryonic antigen (CEA) or PSA are regarded to be tumor-specific proteins that are produced and secreted by the tumor and reach the circulation in which elevated levels are regarded as diagnostic criteria for cancer detection.8 In this respect, these proteins can be regarded as part of the serum profile of cancer patients in that the presence of these proteins in the serum of cancer patients contributes to the tumor-specific protein profile of cancer patients. However, PSA may also help to illustrate one major problem of positive serum protein profiling. PSA is only synthesized by prostatic columnar epithelium and is secreted into the seminal plasma.54 Even in healthy individuals, a very small proportion (1 in 100-1000 molecules) of PSA reaches the circulation through cell and tissue leakage, where it is rapidly diluted in 5 L blood volume. In healthy males, serum PSA averages 1 µg/L, while, in seminal plasma, it is in the range of g/L.54 Under disease conditions, cell and tissue leakage increases, as does the serum level of PSA. The sensitivity and specificity of serum PSA levels depend on the amount of protein synthesized by the individual tumor cell, the tumor cell mass, and co-variables, such as inflammation and tissue manipulation. Thus, a putative, tumor-specific biomarker might indeed reach the serum by cell and tissue leakage. However, several, not necessarily tumor-specific variables, influence sensitivity and specificity of this biomarker. Therefore, to be informative, the serum level has to exceed a certain cutoff value.54 Sensitivity can be increased by adding up several biomarkers to a biomarker pattern (Figure 2). When SELDI analysis was used, a wide range of further proteins were identified which ultimately may result in a more complex “positive serum profile”. Recent studies published by Rosty et al. and other groups have identified biomarkers such as the pancreatitisassociated protein (HIP/PAP-I) or defensins which are present in cancer patients.43 Overall, the combined analysis of these serum markers and the generation of biomarker patterns based on tumor-specific or tumor-derived serum proteins have increased the diagnostic yield substantially (Figure 2). Apart from tumor- and tissue-specific gene products, such as AFP, CEA, PSA, or HIP/PAP-I, entering the circulation through cell leakage, tissue leakage, and necrosis, serum protein profiling may also detect signatures in the serum of posttranslational protein- or peptide-modifications taking place at the tumor-host interface (Figure 3). These might be due to the development of a desmoplastic stroma, neoangiogenesis, and the inflammatory response to tumor invasion. Many Journal of Proteome Research • Vol. 5, No. 1, 2006 21
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Figure 2. Comparison of the diagnostic accuracy of various approaches to serum-based cancer diagnosis. The diagnostic accuracy of conventional tumor markers (A) is low, and even the sensitivity of the combined analysis of several tumor markers is often below 60-70%. Various molecular markers (B) as well as single biomarkers (C) identified by proteome analysis only detect a small subset of cancer patients, since not all cancers express these proteins or exhibit these alterations in the cancer cells. The generation of biomarker patterns, e.g., through decision tree analysis, markedly increases sensitivity (D). Apart from the detection of proteins or peptides that are secreted by the tumor (red boxes), the integration of serum proteins that are decreased in cancer individuals but are present in noncancer individuals (blue boxes) in a more complex decision tree may improve the identification of cancers (E).
enzymes are differentially expressed in malignant tumors, some of which have unique functions in extracellular matrix and cell homeostasis, are proteolytically active in the tumor-host interface, and promote tumor growth and spread.55 Among many other enzymes, cathepsins were found to be upregulated in tumor cells of various malignancies, and increased serum levels were found in cancer patients, probably as a result of cell and tissue leakage, cell death, and aberrant secretion.32 These enzymes modify proteins and peptides generating putative biomarkers of the disease. The tumor-host interface is unique for a malignant tumor. Thus, it is very reasonable to assume that serum-proteomic profiling can separate invasive cancer from inflammation as shown by several studies.42,56 Enzymatic activity at the tumor-host interface, as well as metabolic and immunological changes in cancer patients, may lead to substantial changes of the serum proteome, including various diagnostically relevant post-translational modifica22
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tions.57 These changes may not only generate diagnostically relevant tumor-specific or tumor-derived proteins in the serum of cancer patients but also lead to the reduction or loss of certain peptide or protein species naturally present in healthy, noncancer individuals (Figure 2). This “loss” of certain peptides or proteins in the serum of cancer patients may result from a change in protein synthesis, an altered protein metabolism, or a tumor-specific post-translational modification and may further increase the diagnostic efficacy of biomarker patterns for the diagnosis of cancer patients (Figure 2). In our study, in which we analyzed serum of gastric cancer patients, the single best mass for the differentiation of gastric cancer from noncancer individuals was thrombin light chain a, a proteolytic fragment of prothrombin, which was reduced or undetectable in cancer patients.58 This indicates not only that the loss of certain proteins may have substantial diagnostic impact but also that the coagulation system undergoes profound changes
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Figure 3. The role of serum tumor profiling for the diagnosis of cancer. Adenocarcinomas often synthesize and secrete mucous substances as well as many other peptides and proteins, which may eventually reach the serum, where they can be detected by serum profiling (Tumor marker). The hallmark of cancer, i.e., invasive growth, is characterized by the development of a desmoplastic stroma and a local inflammatory response (Tumor metabolism). High local proteolytic activity and the specific metabolic and immunologic changes due to invasive growth change the serum proteome in a complex manner often with reduction of specific peptides and proteins in the serum. A combination of serum profiling and detection of tumor metabolic changes bear the capability to significantly improve early detection of cancer, reaching beyond conventional serum profiling.
in cancer patients. These observations support our hypothesis that metabolic and immunological changes can be found in every patient with a malignant tumor and, therefore, could be used as a diagnostic tool.48-50,58 SELDI-TOF MS and related MALDI technologies have the capacity to detect and visualize both the positive and negative serum profile of cancer patients and noncancer individuals and thereby allow the identification of cancer patients with a sensitivity and specificity that cannot be reached by conventional or single tumor markers (Figure 2). The importance of the negative serum profile is underscored by the fact that these changes are independent of the size of the primary tumor, the presence of lymph node or distant metastasis, or the overall tumor stage. In our analysis, even 8 of 9 stage I cancers were correctly classified, indicating that this approach may not only improve cancer detection but also have a special impact on the identification of early cancers which could be treated with a curative intent. If the detection of early gastric cancers by SELDI is confirmed in larger studies, endoscopic screening may be tailored to high-risk individuals with serum protein profiles indicating early cancers, which could then be treated curatively. While large endoscopic screening programs are not cost-effective, the tailored approach to individuals with pathological serum protein profiles may well improve diagnostic accuarcy and overall sensitivity.15 In prostate cancers, several studies have also confirmed the high specificity and sensitivity for the discrimination of prostate cancer patients from noncancer patients.59 In a recent study,
Ornstein et al. also demonstrated that these serum-proteome patterns allow the discrimination of men with elevated PSA due to benign processes from men with prostate cancer.60 In the conclusion of their study, they postulate that these serum profiles may allow the reduction of unnecessary prostate biopsies without compromising the detection of curable prostate cancers, an approach which would also tailor biopsies to high-risk individuals identified by SELDI analysis. Limitations of Serum-Proteome-Based Cancer Diagnosis. Although SELDI analysis has identified a number of potential biomarkers and biomarker patterns that allow the identification of cancer patients with a very high sensitivity and specificity, a number of questions have been raised regarding the reproducibility and specifity of this approach.61,62 Thus, this method has been regarded not to be sensitive enough to detect lowabundance proteins which would be important for early cancer diagnosis. Furthermore, the proteins which are detected in the serum using this method are often not regarded as tumorspecific, such as transthyretin, haptoglobin, or amyloid A protein.63 The greatest concern, however, is reproducibility within each group and among various groups using this method. Thus, often, biomarkers have not been (re)-identified in experiments using the same study population and applying different bioinformatic approaches.45 However, recently, two independent studies using sera from patients with hepatocellular cancers identified a 8900 kDa mass in the cancer sera in both studies, which was finally identified as the C-terminal part Journal of Proteome Research • Vol. 5, No. 1, 2006 23
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vitronectin.64,65
of the V10 fragment of Furthermore, Zhang et al. identified biomarkers specific for early ovarian cancer using sera which were drawn and analyzed by SELDI at two centers independently, and data were cross-validated to identify potential biomarkers.66 Furthermore, in a recent multiinstitutional approach, interlaboratory calibration and standardization of the SELDI assay platform was confirmed.67 Nonetheless, despite these recent reports, reproducibility of biomarker identification has been an issue of debate and further approaches are necessary to solve this problem.45 Regarding the issue of tumor specificity, Fung et al. recently reevaluated the role of previously identified biomarkers, that is, transthyretin and inter-alpha trypsin inhibitor heavy chain 4 (ITIH4), in sera of patients with ovarian, breast, prostate, and colon cancer.57 Most of these proteins, including albumin, transthyretin, lipoproteins, c-reactive proteins, and others, are synthesized in the liver and have been regarded as noncancer specific alterations or epiphenomena of tumors which result from a cascade of inflammatory signals.68 However, in their study, they found a high degree of post-translational modifications, including proteolytic truncation, cysteinylation, and glutathionylation in these cancer sera. These post-translational modifications were identified by SELDI-TOF MS and allowed the differentiation of cancer sera from noncancer sera and also the differential diagnosis of tumor type.57 Thus, these posttranslational modifications of serum proteins in cancer patients allowed cancer-specific diagnosis which would not have been identified by the use of a conventional ELISA technique. Although these serum proteins are synthesized mainly by the liver and not by the tumor itself and, thus, are regarded as nonspecific systemic reactions, the modifications of these proteins may seem suitable for cancer detection and, thus, should also be considered as biomarkers for cancers. Inasmuch as this host response, which has been termed host response protein amplification cascade by Fung et al.,57 includes both the induction and down-regulation of circulating proteins as a consequence of tumor development early in the process of cancer pathogenesis, the combined detection of their tumorspecific post-translational modifications in conjunction with other tumor-secreted biomarkers may still allow early diagnosis of cancer. Their data also support our hypothesis that the metabolic activity in cancer patients and at the tumor-host interface may be associated with cancer and cancer-subtypespecific, diagnostically relevant post-translational modifications of proteins. To further solve the remaining other problems of reproducibility, sensitivity, and specificity, a number of other actions should be taken as recommended by Diamandis and our group in recent publications.61,62,69 This includes the importance of identifying the biomarker, the inclusion of internal controls in the SELDI analysis, and the careful control of the study population with regard to disease state, sampling conditions, sampling storage, and other clinical features.61,62,69
Conclusions and Outlook Most cancers are diagnosed in advanced stages when curative treatment is impossible and prognosis poor. Conventional serum markers are largely unsatisfactory for the early detection of cancer or the screening of high-risk individuals. Even molecular markers, based on the detection of mRNA levels of certain factors that have been implicated in tumor biology or genetic or epigenetic changes of DNA in serum or peripheral blood of cancer patients, have not led to improvements in the 24
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early diagnosis of human cancers. Mostly, the available studies were performed only with few patients, and sensitivity and specificity were limited in these studies. The analysis of the serum proteome has led to the identification of a number of proteins, peptides, and disease-specific post-translational modifications that may be used as biomarkers or biomarker patterns for cancer detection. Serious questions of reproducibility, sensitivity, and specificity need, however, be addressed before this technique may be introduced in the clinical management of cancer patients. Nonetheless, since classical serum tumor markers have generally failed to identify cancers in their early stages, the detection of metabolic and immunologic changes in the serum proteome of cancer patients by SELDI and MALDI analyses may be useful to improve our understanding of cancer biology and may provide a very useful tool for the early diagnosis of human cancers (Figure 3). As soon as these serum protein profiles or biomarker patterns have been confirmed in large studies involving various centers throughout the world, it is conceivable that serum protein profiling may allow the easy, cheap, noninvasive, reproducible, and rapid identification of cancer patients with a high sensitivity and specificity. While most current screening strategies are not cost-effective and often include invasive procedures to obtain histology, serumproteome-based cancer diagnosis may allow the identification of high-risk individuals that should undergo more invasive procedures to diagnose and even curatively treat neoplastic or preneoplastic conditions.
Acknowledgment. M. Ebert is supported by the Heisenberg-Programme of the DFG (Eb 187/5-1) and by a grant from the Land Sachsen-Anhalt. References (1) Boyle, P.; Autier, P.; Bartelink, H.; Baselga, J.; Boffetta, P.; Burn, J.; Burns, H. J.; Christensen, L.; Denis, L.; Dicato, M.; Diehl, V.; Doll, R.; Franceschi, S.; Gillis, C. R.; Gray, N.; Griciute, L.; Hackshaw, A.; Kasler, M.; Kogevinas, M.; Kvinnsland, S.; La Vecchia, C.; Levi, F.; McVie, J. G.; Maisonneuve, P.; MartinMoreno, J. M.; Bishop, J. N.; Oleari, F.; Perrin, P.; Quinn, M.; Richards, M.; Ringborg, U.; Scully, C.; Siracka, E.; Storm, H.; Tubiana, M.; Tursz, T.; Veronesi, U.; Wald, N.; Weber, W.; Zaridze, D. G.; Zatonski, W.; zur Hausen, H. Ann. Oncol. 2003, 14, 9731005. (2) Boyle, P.; d’Onofrio, A.; Maisonneuve, P.; Severi, G.; Robertson, C.; Tubiana, M.; Veronesi, U. Ann. Oncol. 2003, 14, 1312-1325. (3) Gridelli, C.; Aapro, M.; Ardizzoni, A.; Balducci, L.; De Marinis, F.; Kelly, K.; Le Chevalier, T.; Manegold, C.; Perrone, F.; Rosell, R.; Shepherd, F.; De Petris, L.; Di Mario, M.; Langer, C. J. Clin. Oncol. 2005, 23, 3125-3137. (4) Bonelli, L. Tech. Coloproctol. 2004, 8, s267-272. (5) Crawford, E. D. Lancet 2005, 365, 1447-1449. (6) Bast, R. C., Jr.; Ravdin, P.; Hayes, D. F.; Bates, S.; Fritsche, H., Jr.; Jessup, J. M.; Kemeny, N.; Locker, G. Y.;, Bennel, R. G.; Somerfield, M. R. J. Clin. Oncol. 2001, 19, 1865-1878. (7) Di Bisceglie, A. Gastroenterology 2004, 127, S104-107. (8) Hernandez, J.; Thompson, I. Cancer 2004, 101, 894-904. (9) Ebert, M. P. A.; Malfertheiner, P. Aliment. Pharmacol. Ther. 2002, 16, 1059-1066. (10) Yokota, T.; Ishiyama, S.; Saito, T.; Teshima, S.; Narushima, Y.; Murata, K.; Iwamoto, K.; Yashima, R.; Yamauchi, H.; Kikuchi, S. Scand. J. Gastroenterol. 2004, 39, 380-384. (11) Marrelli, D.; Roviello, F.; de Stefano, A.; Farnetani, M.; Garosi, L.; Messano, A.; Pinto, E. Oncology 1999, 57, 55-62. (12) Nakajiima, K.; Ochiai, T.; Suzuki, T.; Shimada, H.; Hayashi, H.; Yasumoto, A.; Takeda, A.; Hishikawa, E.; Isono, K. Tumor Biol. 1998, 19, 464-469. (13) Istigami, S.; Natsugoe, S.; Hokita, S.; Che, X.; Tokuda, K.; Nakajo, A.; Iwashige, H.; Tokushige, M.; Watanabe, T.; Takao, S.; Aikou, T. J. Clin. Gastroenterol. 2001, 32, 41-44. (14) Lieberman, D.; Fennerty, M.. B.; Morris, C. D.; Holub, J.; Eisen, G.; Sonnenberg, A. Gastroenterology 2004, 127, 1067-1075.
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Serum-Proteome-Based Cancer Diagnosis (15) Riecken, B.; Pfeiffer, R.; Ma, J. L.; Jin, M. L.; Li, J. Y.; Liu, W. D.; Zhang, L.; Chang, Y. S.; Gail, M. H.; You, W. C. Prev. Med. 2002, 34, 22-28. (16) Draviam, V. M.; Xie, S.; Sorger, P. K. Curr. Opin. Genet. Dev. 2004, 14, 120-125. (17) Feinberg, A. P. Semin. Cancer Biol. 2004, 14, 427-432. (18) von Knobloch, R.; Brandt, H.; Schrader, A. J.; Heidenreich, A.; Hofmann, R. Clin. Cancer Res. 2004, 10, 988-993. (19) Kanaoka, S.; Yoshida, K.; Miura, N.; Sugimura, H.; Kajimura, M. Gastroenterology 2004, 127, 422-427. (20) Melissourgos, N.; Kastrinakis, N. G.; Davilas, I.; Foukas, P.; Farmakis, A.; Lykourinas, M. Urology 2003, 62, 362-367. (21) Stoitchkov, K.; Letellier, S.; Garnier, J. P.; Toneva, M.; Naumova, E.; Peytcheva, E.; Tzankov, N.; Bousquet, B.; Morel, P.; Le Bricon, T. Clin. Chim. Acta 2001, 306, 133-138. (22) Kaufmann, S.; Schmutzler, C.; Schomburg, L.; Korber, C.; Luster, M.; Rendl, J.; Reiners, C.; Kohrle, J. Endocr. Regul. 2004, 38, 4149. (23) Kanyama, Y.; Hibi, K.; Nakayama, H.; Kodera, Y.; Ito, K.; Akiyama, S. Cancer Sci. 2003, 94, 418-420. (24) Wang, J. Y.; Hsieh, J. S.; Chang, M. Y.; Huang, T. J.; Chen, F. M.; Cheng, T. L.; Alexandersen, K.; Huang, Y. S.; Tzou, W. S.; Lin, S. R. World J. Surg. 2004, 28, 721-726. (25) Lauschke, H.; Caspari, R.; Friedl, W.; Schwarz, B.; Mathiak, M.; Propping, P.; Hirner, A. Cancer Detect. Prev. 2001, 25, 55-61. (26) Gautschi, O.; Bigosch, C.; Huegli, B.; Jermann, M.; Marx, A.; Chasse, E.; Ratschiller, D.; Weder, W.; Joerger, M.; Betticher, D. C.; Stahel, R. A.; Ziegler, A. J. Clin. Oncol. 2004, 22, 4157-4164. (27) Chan, K. C.; Lo, Y. M. Semin. Cancer Biol. 2002, 12, 489-496. (28) Lo, Y. M.; Chan, W. Y.; Ng, E. K.; Chan, L. Y.; Lai, P. B.; Tam, J. S.; Chung, S. C. Clin. Cancer Res. 2001, 7, 1856-1859. (29) Lofton-Day, C.; Lesche, R. Dig. Dis. 2003, 21, 299-308. (30) Wang, Y. C.; Lu, Y. P.; Tseng, R. C.; Lin, R. K.; Chang, J. W.; Chen, J. T.; Shih, C. M.; Chen, C. Y. J. Clin. Invest. 2003, 111, 887-895. (31) Leung, W. K.; To, K. F.; Man, E. P.; Chan, M. W.; Bai, A. H.; Hui, A. J.; Chan, F. K.; Lee, J. F.; Sung, J. J. Clin. Chem. 2004, 50, 21792182. (32) Ebert, M. P.; Kruger, S.; Fogeron, M. L.; Lamer, S.; Chen, J.; Pross, M.; Schulz, H. U.; Lage, H.; Heim, S.; Roessner, A.; Malfertheiner, P.; Rocken, C. Proteomics 2005, 5, 1693-1704. (33) Juhasz, M.; Ebert, M. P.; Schulz, H. U.; Rocken, C.; Molnar, B.; Tulassay, Z.; Malfertheiner, P. Scand. J. Gastroenterol. 2003, 38, 850-855. (34) Maruo, Y.; Gochi, A.; Kaihara, A.; Shimamura, H.; Yamada, T.; Tanaka, N. Int. J. Cancer 2002, 100, 486-490. (35) Karayiannakis, A. J.; Syrigos, K. N.; Polychronidis, A.; Zbar, A.; Kouraklis, G.; Simopoulos, C. Ann. Surg. 2002, 236, 37-42. (36) Ohta, M.; Konno, H.; Tanaka, T.; Baba, M.; Kamiya, K.; Syouji, T. Cancer Lett. 2003, 192, 215-225. (37) Gorg, A.; Weiss, W.; Dunn, M. J. Proteomics 2004, 4, 3665-3685. (38) Aldred, S.; Grant, M. M.; Griffiths, H. R. Clin. Biochem. 2004, 37, 943-952. (39) Wright, M. E.; Han, D. K.; Aebersold, R. Mol. Cell. Proteomics 2005, 4, 545-554. (40) Wulfkuhle, J. D.; Liotta, L. A.; Petricoin, E. F. Nat. Rev. Cancer 2003, 3, 267-275. (41) Issaq, H. J.; Veenstra, T. D.; Conrads, T. P.; Felschow, D. Biochem. Biophys. Res. Commun. 2002, 292, 587-592. (42) Vlahou, A.; Schellhammer, P. F.; Mandrinos, S.; Patel, K.; Kondylis, F. I.; Gong, L.; Nasim, S.; Wright, G. L. Am. J. Pathol. 2001, 158, 1491-1502. (43) Rosty, C.; Christa, L.; Kuzdzal, S.; Baldwin, W. M.; Zahurak, M. L.; Carnot, F.; Chan, D. W.; Canto, M.; Lillemoe, K. D.; Cameron, J. L.; Yeo, C. J.; Hruban, R. H.; Goggings, M. Cancer Res. 2002, 62, 1868-1875. (44) Petricoin, E. F.; Ardekani, A. M.; Hitt, B. A.; Levine, P. J.; Fusaro, V. A.; Steinberg, S. M.; Mills, G. B.; Simone, C.; Fishman, D. A.; Kohn, E. C.; Liotta, L. A. Lancet 2002, 359, 572-577. (45) Adam, B. L.; Qu, Y.; Davis, J. W.; Ward, M. D.; Clements, M. A.; Cazares, L. H.; Semmes, O. J.; Schellhammer, P. F.; Yasui, Y.; Feng, Z.; Wright, GL. Cancer Res. 2002, 62, 3609-3614.
(46) Ebert, M. P.; Meuer, J.; Wiemer, J. C.; Schulz, H. U.; Reymond, M. A.; Traugott, U.; Malfertheiner, P.; Rocken, C. J. Proteome Res. 2004, 3, 1261-1266. (47) Mobley, J. A.; Lam, Y. W.; Lau, K. M.; Pais, V. M.; L’Esperance, J. O.; Steadman, B.; Fuster, L. M.; Blute, R. D.; Taplin, M. E.; Ho, S. M. J. Urol. 2004, 172, 331-337. (48) Lam, Y. W.; Mobley, J. A.; Evans, J. E.; Carmody, J. F.; Ho, S. M. Proteomics 2005, 5, 2927-2938. (49) Yanagisawa, K.; Shyr, Y.; Xu, B. J.; Massion, P. P.; Larsen, P. H.; White, B. C.; Roberts, J. R.; Edgerton, M.; Gonzalez, A.; Nadaf, S.; Moore, J. H.; Caprioli, R. M.; Carbone, D. P. Lancet 2003, 362, 433-439. (50) Schwartz, S. A.; Weil, R. J.; Johnson, M. D.; Toms, S. A.; Caprioli, R. M. Clin. Cancer Res. 2004, 10, 981-987. (51) Pusch, W.; Flocco, M. T.; Leung, S. M.; Thiele, H.; Kostrzewa, M. Pharmacogenomics 2003, 4, 463-476. (52) Villanueva, J.; Philip, J.; Entenberg, D.; Chaparro, C. A.; Tanwar, M. K.; Holland, E. C.; Tempst, P. Anal. Chem. 2004, 76, 15601570. (53) Zhang, X.; Leung, S. M.; Morris, C. R.; Shigenaga, M. K. J. Biomol. Tech. 2004, 15, 167-175. (54) Schmid, H. P.; Riesen, W.; Prikler, L. Crit. Rev. Oncol. Hematol. 2004, 50, 71-78. (55) Koblinski, J. E.; Ahram, M.; Sloane, B. F. Clin. Chim. Acta 2000, 291, 113-135. (56) Koopmann, J.; Zhang, Z.; White, N.; Rosenzweig, J.; Fedarko, N.; Jagannath, S.; Canto, M. I.; Yeo, C. J.; Chan, DW.; Goggins, M. Clin. Cancer Res. 2004, 10, 860-868. (57) Fung, E. T.; Yip, T. T.; Lomas, L.; Wang, Z.; Yip, C.; Mang, X. Y.; Lin, S.; Zhang, F.; Zhang, Z.; Chan, D. W.; Weinberger, S. R. Int. J. Cancer 2005, 115, 783-789. (58) Ebert, M. P.; Lamer, S.; Meuer, J.; Malfertheiner, P.; Reymond, M.; Buschmann, T.; Rocken, C.; Seibert, V. J. Proteome Res. 2005, 4, 586-590. (59) Qu, Y.; Adam, B. L.; Yasui, Y.; Ward, M. D.; Cazares, L. H.; Schellhammer, P. F.; Feng, Z.; Semmes, O. J.; Wright, G. L. Clin. Chem. 2002, 48, 1835-1843. (60) Ornstein, D. K.; Rayford, W.; Fusaro, V. A.; Conrads, T. P.; Ross, S. J.; Hitt, B. A.; Wiggins, W. W.; Veenstra, T. D.; Liotta, L. A.; Petricoin, E. F. J. Urol. 2004, 172, 1302-1305. (61) Jacobs, I. J.; Menon, U. Mol. Cell. Proteomics 2004, 3, 355-366. (62) Diamandis, E. P. Mol. Cell. Proteomics 2004, 3, 367-378. (63) Zhang, Z.; Bast, R. C.; Yu, Y.; Li, J.; Sokoll, L. J.; Rai, A. J.; Rosenzweig, J. M.; Cameron, B.; Wang, Y. Y.; Mang, X. Y.; Berchuk, A.; Van Haaften-Day, C. Cancer Res. 2004, 64, 5882-5890. (64) Poon, T. C. W.; Yip, T. T.; Chan, A. T. C.; Yip, C.; Yip, V.; Mok, T. S. K.; Lee, C. C. Y.; Leung, T. W. T.; Ho, S. K. W.; Johnson, P. J. Clin. Chem. 2003, 49, 752-760. (65) Paradis, V.; Degos, F.; Dargere, D.; Pham, N.; Belghiti, J.; Degott, C.; Janeau, J. L.; Bezeaud, a.; Delforge, D.; Cubizolles, M.; Laurendeau, I.; Bedossa, P. Hepatology 2005, 41, 40-47. (66) Zhang, Z.; Bast, R. C.; Yu, Y.; Li, J.; Sokoll, L. J.; Rai, A. J.; Rosenzweig, J. M.; Cameron, B.; Wang, Y. Y.; Meng, X. Y.; Berchuk, A.; van Haaften-Day, C.; Hacker, N. F.; de Bruijn, H. W. A.; van der Zee, A. G. J.; Jacobs, I. J.; Fung, E. T.; Chan, D. W. Cancer Res. 2004, 64, 5882-5890. (67) Semmes, O. J.; Feng, Z.; Adam, B. L.; Banez, L. L.; Bigbee, W. L.; Campos, D.; Cazares, L. H.; Chan, D. W.; Grizzle, W. E.; Izbicka, E.; Kagan, J.; Malik, G.; McLerran, D.; Moul, J. W.; Partin, A.; Prasanna, P.; Rosenzweig, J.; Sokoll, L. J.; Srivastava, S.; Srivastava, S.; Thompson, I.; Welsh, M. J.; White, N.; Winget, M.; Yasui, Y.; Zhang, Z.; Zhu, L. Clin. Chem. 2005, 1, 102-112. (68) Sheth, K.; Bankey, P. Curr. Opin. Crit. Care 2001, 7, 99-104. (69) Seibert, V.; Ebert, M. P. A.; Buschmann, T. Briefings Funct. Genomics Proteomics 2005, 4, 1-11.
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