Implications of cancer-associated systemic inflammation for biomarker studies

Biochimica et Biophysica Acta 1806 (2010) 163–171

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Biochimica et Biophysica Acta j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / b b a c a n

Review

Implications of cancer-associated systemic inflammation for biomarker studies Magdalena Kowalewska a, Radoslawa Nowak a, Magdalena Chechlinska b,⁎ a b

Department of Molecular Biology, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, Roentgena 5, 02-781 Warsaw, Poland Department of Immunology, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, Roentgena 5, 02-781 Warsaw, Poland

a r t i c l e

i n f o

Article history: Received 31 March 2010 Received in revised form 16 June 2010 Accepted 17 June 2010 Available online 25 June 2010 Keywords: Cancer biomarker Marker specificity Marker validation Inflammation CTC

a b s t r a c t Highly sensitive molecular technologies provide new capacities for cancer biomarker research, but with sensitivity improvements marker specificity is significantly decreased, and too many false-positive results should disqualify the measurement from clinical use. Hence, of the thousands of potential cancer biomarkers only a few have found their way to clinical application. Differentiating false-positive results from truepositive (cancer-specific) results can indeed be difficult, if validation of a marker is performed against inadequate controls. We present examples of accumulating evidence that not only local but also systemic inflammatory reactions are implicated in cancer development and progression and interfere with the molecular image of cancer disease. We analyze several modern strategies of tumor marker discovery, namely, proteomics, metabonomics, studies on circulating tumor cells and circulating free nucleic acids, or their methylation degree, and provide examples of scarce, methodologically correct biomarker studies as opposed to numerous methodologically flawed biomarker studies, that examine cancer patients' samples against those of healthy, inflammation-free persons and present many inflammation-related biomarker alterations in cancer patients as cancer-specific. Inflammation as a cancer-associated condition should always be considered in cancer biomarker studies, and biomarkers should be validated against their expression in inflammatory conditions. © 2010 Elsevier B.V. All rights reserved.

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evidence of the systemic inflammatory response (SIR) in cancer patients . . . . . . . 2.1. Standard blood tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Cell phenotype changes . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Serum markers of inflammation in cancer patients . . . . . . . . . . . . . . 2.4. Inflammatory markers and prognosis in cancer patients . . . . . . . . . . . . 3. Systemic inflammation as a confounding factor in molecular biomarker measurements. 3.1. High throughput methods, the “Omics” . . . . . . . . . . . . . . . . . . . . 3.2. Free nucleic acid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Circulating tumor cell detection . . . . . . . . . . . . . . . . . . . . . . . 4. Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict Conflictofofinterest intereststatement statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Cancer biomarkers hold out some promise for helping to improve the clinical outcomes of cancer patients. With advances in our

⁎ Corresponding author. Tel.: +48 22 5462256; fax: +48 22 5463174. E-mail address: [email protected] (M. Chechlinska). 0304-419X/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.bbcan.2010.06.002

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understanding of the molecular pathogenesis of cancer and the rapid development of new technologies, thousands of potential cancer biomarkers have emerged and still only a few have found their way to clinical application. Here, we outline some of the most frequently exploited modern strategies for the discovery of new cancer biomarkers. We address an issue of systemic inflammation in cancer patients as a commonly neglected factor in interpreting the biomarker profiles of cancer patients that is non-specific and often undistinguishable from

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the inflammatory symptoms accompanying many other diseases (Fig. 1). We will discuss examples of what are potentially the least invasive markers—those identified in body fluids. Among several classes of molecular biomarkers, proteins have attracted renewed interest with the development of proteomics technologies that enable thousands of proteins to be identified, characterized and quantified from complex mixtures such as biological samples. The difficulty here lies in determining which proteins are specifically linked to the disease in question, and do not just reflect unspecific secondary changes. Blood sera contain other potential molecular markers, notably cell-free RNA and DNA, the levels of which are known to be elevated in cancer patients. However, finding a cancer-specific cell-free nucleic acid is also a challenge. Identifying cancer-derived extracellular DNA by typical genomic changes, such as oncogene and suppressor gene mutations and microsatelite alterations, presents high specificity, and this removes any ambiguities as to conclusions. But many other methodological approaches to the study of either the levels of circulating nucleic acids or their methylation degree do not employ reliable controls to differentiate cancer-specific changes. The relevant controls are also of special importance in a search for other cancer biomarker classes, such as excreted, urinary modified nucleosides (being biological indicators of whole-body RNA turnover), and molecular markers used for the assessment of circulating or disseminated tumor cells (CTC and DTC, respectively). To detect CTC/DTC, nucleic acid-based techniques such as RT-PCR are usually employed. The greatest challenge in CTC/DTC detection is again to address the appropriate, tumor-specific markers. Any factor affecting marker expression should be carefully analyzed. It is generally accepted that cancer is accompanied by inflammation and, as we show in this paper, systemic inflammatory response in cancer patients is a common phenomenon. On the other hand, numerous pieces of evidence described here demonstrate that inflammation strongly affects the biomarker profile. Unfortunately, most biomarker research does not refer to inflammation as an inherent component of cancer disease and thus many inflammation-related biomarker changes in cancer patients are interpreted as cancer-specific.

accompanies all stages of cancer [1]. Recent findings summarized by Mantovani et al. [2] have revealed that some genetic events that cause neoplasia are also responsible for generating an inflammatory microenvironment, with the same molecular pathways induced as in inflammatory or infectious conditions that increase the risk of developing cancer. Irrespective of the initial mechanism of cancer development, local as well as systemic cancer-related inflammation occurs [3].

2. Evidence of the systemic inflammatory response (SIR) in cancer patients

2.2. Cell phenotype changes

Inflammation, apart from playing a causal role in cancer development, is also generated as a host response to tumor development and

Fig. 1. An overlap of sets of markers of inflammatory disease and cancer. An intersection of sets contains non-specific markers. In cancer biomarker studies, if the results are referred to normal samples, instead of discovering cancer-specific markers we arrive at biomarkers that are most likely unspecific.

2.1. Standard blood tests It has been well documented that in patients with cancer routine blood tests often reveal changes similar to those observed in patients with infectious or inflammatory diseases. Numerous studies have shown that changed erythrocyte sedimentation rate (ESR), along with counts of neutrophiles, monocytes, platelets and total white blood cells (WBC), relates to clinical parameters, including the disease progress and outcomes of patients. Here are some examples. In a population-based study of over 3000 individuals, a higher WBC count was shown to be associated with all cancer mortality [4]. In the studies by Rasouli et al. [5], ESR in patients with different cancers was one of the best parameters for discriminating between malignant and healthy conditions. In renal cancer patients, a preoperative ESR was independently associated with cancer-specific survival after nephrectomy [6]. Elevated platelet count (thrombocytosis) is common in many cancers [7]. In early lung cancer, thrombocytosis combined with ESR and serum lactate dehydrogenase, presented high sensitivity and specificity in predicting malignancy in patients with lung lesions [8]. The neutrophil to lymphocyte ratio increased with the stage of NSCLC, and was an independent predictor of survival after the complete resection of primary lung cancer [9]. In a recent study on cervical cancer, a pre-treatment neutrophil and monocyte counts product was a predictor of poor prognosis, independent of stage and tumor size [10]. In patients with colorectal cancer, high neutrophil [11] and monocyte [12] counts were shown to be independent predictors of poor cancer-specific survival.

The Th1 to Th2 shift has been widely recognized in cancer patients [13]. Also, increased percentages of activated T lymphocytes were demonstrated in the peripheral blood of cancer patients [14–17]. Already in 1986, Tsuyuguchi et al. [15] showed a significantly increased mean percentage of circulating IL-2R+ T lymphocytes in untreated primary lung cancer patients, regardless of histopathological type and clinical stage. In patients with stages Ia and Ib ovarian cancer, the percentages of CD4+HLADR+ cells were significantly higher than in healthy controls and patients with benign and borderline ovarian tumors, but decreased in later stages [14]. In the peripheral blood of untreated patients with breast cancer, significantly elevated relative and absolute numbers of CD3+HLADR+, CD3+CD69+ and CD14+CD16+cells were described [17]. Sharma et al. [18], who studied breast cancer patients, were the first to show that gene-expression patterns in the peripheral blood cells were affected already in the early stages of the disease. It was suggested that the gene-expression changes may indicate systemic activation of some blood cell subsets. The systemic activation and phenotype changes of lymphocytes may relate to the elevated concentrations of serum cytokines, typical for both cancer and inflammatory diseases. This will be discussed below. 2.3. Serum markers of inflammation in cancer patients The inflammatory micro-environment of solid tumors is characterized by an excess of cytokines produced and released by cancer

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cells, infiltrating cells and the reactive stroma. This local overexpression, as shown in ovarian, cervical, prostate, lung, gastric, breast, colorectal, renal and other tumors, is accompanied by increased systemic concentrations of cytokines, including pro-inflammatory cytokines, such as IL-6, IL-8, TNFα, MIF, IL-1β, often related to the clinico-pathological features of cancer and to patients' survival. These issues have been described and discussed in detail elsewhere [19–22]. Systemic inflammatory disease in cancer patients is often evidenced by elevated circulating C-reactive protein (CRP) and serum amyloid A protein (SAA), the unspecific acute-phase proteins produced by hepatocytes upon stimulation by pro-inflammatory cytokines, such as IL-6, TNFα and IL-1β and by lowered albumin concentrations [23,24]. 2.4. Inflammatory markers and prognosis in cancer patients In patients with solid tumors, the prognostic significance of the systemic inflammatory response, as evidenced by the elevated serum acute phase proteins and hypoalbuminemia, has been well documented. Elevated preoperative CRP was shown to be an independent predictor of poor outcome in patients following potentially curative resection of renal clear cell cancer [25], colorectal cancer (CRC) [26] and colorectal liver metastases [27], as also in patients with oral SCC [28], inoperable gastro-esophageal cancer [29], transitional cell carcinoma of the urinary bladder [30] and advanced pancreatic cancer [31]. In patients with invasive, primary, operable breast cancer, it was the level of preoperative albumin, not that of CRP, that independently influenced prognosis [32]. However (in an extended study by Pierce et al. [33]), in patients with non-metastatic (stages 0 to IIIa) breast cancer, CRP as well as SAA levels, measured 31 months after diagnosis, were shown to be independently associated with long-term survival. Preoperative SAA concentrations have been associated with prognosis in patients with operable renal cell and gastric carcinomas [34,35]. SAA levels have also been shown to be significantly elevated in patients with head and neck SCC [36]. A combination of an elevated C-reactive protein and hypoalbuminemia has been proposed as an effective “inflammation-based prognostic score” (the Glasgow prognostic score—GPS) [37]. 3. Systemic inflammation as a confounding factor in molecular biomarker measurements We have recently raised an issue of systemic inflammation, a condition that is evidently accompanying cancer disease, as a prevalent confounding factor in cancer biomarker studies [3]. It should be considered in the cancer biomarker research, no matter which method of biomarker study is employed. 3.1. High throughput methods, the “Omics” Proteins, the main constituents of cells and body fluids, have received a great deal of attention as cancer biomarkers. The contemporary proteomic techniques have a potential to identify, characterize and quantify all proteins and peptides contained in a sample. Now, a real challenge is to identify proteins and peptides specific for a given condition. For example, by employing a proteomic modification called “cancer immunomics,” tumor-associated antibodies were identified in the sera of patients with early NSCLC and prostate cancer [38,39]. However, none of the global proteomic studies identified such proteins, not just because of the low abundance of these proteins, but very likely because the serum protein profiles are usually compared between cancer patients and healthy persons, or–at best–between cancer patients and patients with benign tumors of the relevant tissue. As a result, proteins involved in inflammatory reactions, but not cancer-specific proteins, are identified as differentially expressed. Comparative analysis of serum proteins and peptides

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in pancreatic cancer patients and healthy volunteers clearly pointed to the inflammation-related molecules as the dominant differences [40]. Similarly, sera of lung adenocarcinoma patients were discriminated from the sera of healthy donors by non-specific, inflammatory proteins [41]. It is right to conclude that inflammatory mechanisms are involved in these cancers, but this conclusion is hardly adequate to the sophisticated and expensive methods applied. Chen et al. [42] clearly demonstrated that a chronic inflammatory condition (pancreatitis) shares many protein signatures with the malignant disease involving the same organ (pancreatic cancer). Such comprehensive methodological approaches further emphasize the importance and difficulty of finding well-matched controls. Over the past decade, we have witnessed a rapid advancement in another category of the “omic” series, metabonomics, which measures the end products of metabolic response to pathophysiological stimuli or genetic modifications, and thus opens up worlds of potential cancer biomarkers. One of the groups of metabolites comprises modified nucleosides, which are degradation products of cellular RNAs, found in urine. Altered nucleoside excretion patterns may reflect metabolic imbalance or accelerated RNA turnover. Significant increase and an altered pattern of modified nucleosides have been described in urine from patients with different malignancies, such as breast, colon, sarcoma, melanoma, and lymphoid cancer [43–45]. However, to identify a reliable biochemical indicator of cancer appropriate controls are of primary importance. Unfortunately, researchers usually compare the metabolite profiles of the urine between cancer patients and healthy persons. Inevitably, such comparisons are misleading, as changed RNA turnover accompanies any disease, inflammatory conditions in particular, and consequently results in an altered nucleoside excretion pattern. Over a decade ago, Tebib et al. [46] demonstrated that the levels of urinary excreted modified nucleosides reach the same orders of magnitude in patients with cancer and in patients with rheumatoid arthritis, homeopathies or spondyloarthropathies. Yang et al. [47] studied a collection of 15 urinary nucleosides, promising candidates for markers of hepatocellular carcinoma. Mean concentrations of all nucleosides have significantly differed in cancer patients and in healthy persons. However, being aware that nucleoside levels need to differentiate cancer from other conditions in a specific way, the researchers also analyzed the urinary nucleoside concentrations in patients with acute and chronic hepatitis, as well as in patients with hepatocirrhosis. The results clearly demonstrated that the analysis of the 15 nucleosides would not differentiate patients with cancer from those with other liver diseases. By employing HPLC-based metabonomics the researchers identified a group of metabolites, most of an unknown function, which differentiated patients with hepatocellular cancer from those with hepatitis or hepatocirrhosis, with a positive predictive value of 100% and 93%, respectively. This study provides an example of finding and using an appropriate methodology that results in reliable evidence for conclusions on cancer-specific markers. In the light of these model biomarker studies, a recently published paper of Issaq et al. [48] is surprising. The researchers applied a similar metabonomic approach and were enthusiastic about being able to differentiate urine samples of patients with bladder cancer from those of healthy persons with 98% sensitivity and 96% specificity. However, the lack of comparisons with samples from patients with inflammatory conditions makes this enthusiasm premature. 3.2. Free nucleic acid analysis Free nucleic acids are widely researched as potential cancer biomarkers. According to Chan et al. [49], the increased levels of circulating cell-free nucleic acids may either reflect cancer cell disintegration or the response to the disease, or both. Here are examples of some recent studies. Banki et al. [50] examined plasma levels of cell-free DNA along with CEA in patients with esophageal

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cancer and in asymptomatic volunteers, and concluded that “elevated plasma DNA is an extremely reliable indicator of the presence of recurrent disease, contrary to CEA.” Paci et al. [51] employed a similarly flawed methodology to identify cancer-specific biomarkers and compared circulating plasma DNA levels in patients with nonsmall cell lung cancer to those of healthy controls. The differences obtained convinced the authors that “this could have practical implications such as the use in screening programs and a possible prognostic significance in the follow-up.” Unfortunately, these studies did not consider the well-known phenomenon of elevated levels of circulating free DNA accompanying different non-cancerous pathological conditions, such as systemic arterial inflammation [52], pulmonary embolism [53], acute pancreatitis [54], obstructive sleep apnea [55], and even overtraining-induced inflammation [56]. Moreover, van der Drift et al. [57], who examined free DNA in the sputum of lung cancer patients, demonstrated that „the amount of free DNA is related to the amount of inflammation, but not to the presence of lung cancer.” Numerous other studies have attempted to identify cancer cellspecific circulating RNA. A good example is the human telomerase reverse transcriptase (hTERT) mRNA, a tempting candidate for cancer biomarker. The levels of hTERT have been examined in patients with gynecologic malignancies, primary and recurrent gastric cancer, prostate, and lung cancer [58–61]. In all these studies, the hTERT mRNA levels of normal sera were set as a reference cut-off value. As a result, it has been concluded that free hTERT mRNA is a novel and excellent biomarker for the diagnosis and staging of cancer disease. This concept was based on an assumption that since hTERT is expressed in most cancer cells, but not in most normal cells, it may be regarded as cancer-specific. Unfortunately, this does not take account of the fact that activated lymphocytes are a rich source of hTERT [62]. Therefore, until the analyses against control patients with inflammatory diseases are performed, hTERT is unwarranted as a cancer marker. Epigenetic changes in the DNA methylation profiles are common in human cancers. Thus, hypermethylated cell-free serum DNA have been considered as a potential tumor marker. The results of recent studies in patients with testicular [63], prostate [64], gastric [65], and breast cancers [66] seem promising, but again, most analyses were performed against normal controls. Yet global DNA methylation in the peripheral blood leukocytes is altered in inflammation, for example in patients with coronary artery disease [67] or with chronic kidney disease [68]. Additionally, as emphasized by Duffy and colleagues [69], the process of aging as well as the presence of benign diseases, affects gene methylation patterns, and this constitutes one of the problems in the application of methylated genes as cancer markers. More genetic studies are necessary to determine which hypermethylated events are truly relevant for carcinogenesis. 3.3. Circulating tumor cell detection The potential of CTC or DTC detection in cancer prognosis and follow-up has been extensively studied. Still, the clinical relevance of CTC or DTC detection is controversial, and the current methods employed for CTC characterization and detection lack sensitivity, specificity or reproducibility. Morphological, immunological, molecular or combined approaches and different separation techniques have been employed to distinguish CTC/DTC from normal cells. The advantages and limitations of these methods have been recently discussed elsewhere [70,71]. However, it has to be underlined that even by using the most advanced, FDA-approved, and commercially available CellSearch system, 10% of healthy volunteers are found positive, and the percentage of false-positive results may increase during inflammatory conditions and following surgical interventions [72]. We will concentrate on the reasons why the molecular strategies fail to distinguish between CTC/DTC and normal cells.

For over a decade high sensitivity reverse transcriptase-polymerase chain reaction (RT-PCR) has been the most widely employed technique for CTC/DCT detection, as a molecular method of choice. One of the most frequently used RT-PCR markers of epithelial cells is cytokeratin (CK)19. The detection of CK19 transcripts has been used to confirm the tumor spread. Many recently published papers suggest that CK19 is an accurate marker for cancer cell detection in the lymph nodes [73] and bone marrow [74] of cancer patients. Another cytokeratin, CK20, is employed for cancer cell detection in the lymph nodes [75], and in peritoneal lavages [76] and it was recently proposed as a marker for urine analysis [77]. CEA is also an extensively studied gene that is predominantly expressed in cells of epithelial origin, and it is therefore considered to be an indicator of disseminated tumor cells in peritoneal lavages [76], the lymph nodes [78] and in the peripheral blood [79]. Many papers describe hMAM (human mammaglobin) as an accurate marker for cancer cell detection in the lymph nodes [80], peripheral blood [81], pleural effusions [82], cerebrospinal fluid [83], bone marrow and in the leukapheresis products [84]. However, the RT-PCR-based CTC/DCT detection assays are plagued by a high percentage of false positive results. For example, it has been demonstrated that CK19 and CK20 are expressed in the blood [85–93] and bone marrow [92,93] of non-cancer subjects, and CK19 also in the lymph nodes [90,94,95]. Similarly, positive results of CEA were obtained in the samples of peripheral blood [87,90,96], lymph nodes [90], bone marrow [97] and peritoneal lavages [98] from carcinomafree patients. These results were only the “warning signals” questioning the specificity of these markers. Additional arguments against cancer specificity arose when bone marrow samples obtained from patients suffering from chronic inflammatory diseases were found to be highly positive for CK19 [99], CEA [99] and CK20 [92]. One of the reasons behind these significant limitations of the RTPCR methodology was clarified by Jung and colleagues [99], who have shown that the expression of CK19 and CEA is inducible in lymphatic cells upon cytokine stimulation. Carried out in 1998, this was the first study to place an emphasis on the necessity to enroll patients suffering from nonmalignant diseases to evaluate RT-PCR assays, rather than simply standardizing them against the samples obtained from healthy volunteers. Also Pittini et al. [100] consistently indicated that CK19 expression was inducible in PBMC under inflammatory conditions, and this may result in frequent false-positives in RT-PCR. We have shown that the expression of hMAM, EGFR (epidermal growth factor receptor), SCCA (squamous-cell carcinoma antigen) and SBEM (small breast epithelial mucin), is inducible in normal peripheral blood mononuclear cells (PBMC) [101]. Similarly, Goeminne et al. [102] showed that CEA transcription was inducible in PBMC from healthy individuals upon GCSF. hMAM expression was found to be inducible by cytokines in bone marrow and peripheral stem cells from patients without epithelial cancer [103] and in normal peripheral blood leukocytes following apheretic procedures [104]. Although the prognostic value of various markers in cancer patients is often shown and regarded as an indirect proof of their cancer specificity, mere measurements of the inflammatory factors also present prognostic value (as noted above), and in patients with advanced cancer, the systemic inflammatory response is a strong independent prognostic factor. Moreover, when monitoring chemotherapy using RT-PCR, the disappearance of the given marker-positive cells in patients after chemotherapy (as observed for CK19 [105]) or radiotherapy may also result from the cytotoxic effect on the inflammatory cells. We have suggested that to reduce the falsepositive results associated with disseminated tumor cell testing, new molecular markers should be validated not against normal peripheral blood cells, but against activated lymphoid cells [101]. The ultra sensitive method, quantitative RT-PCR, has promised to have the potential to avoid the previous failures of the RT-PCR-based assays used to detect tumor cells. To improve the specificity of RT-PCR, numerous qRT-PCR approaches have been developed with different

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Table 1 Examples of studies in which inflammation might confound the findings on markers regarded as cancer-derived (light grey background); the inherent limitations of the methodologies applied in these studies are demonstrated by the published data (dark grey background).

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Table 1 (continued)

markers, including CK19 [106,107], hMAM [107,108] and CEA [109]. However, the clinical relevance of CTC/DTC detection using this technique still remains unproven. For example, Dimmler et al. [110] demonstrated that the variable background expression of the different CKs in bone marrow specimens from noncancer patients was a limiting factor for the use of CK RT-PCR assays for DTC detection. Koga et al. [111], while analyzing colonocytes isolated from feces by a real-time approach, were not able to reliably differentiate colorectal cancer patients from healthy volunteers based on the levels of CEA expression. Suchy et al. [112] could not observe the prognostic significance of the hMAM expression level in the blood of breast cancer patients. The analysis of CK19 and CK20 gene expression levels in the blood cells of patients with esophageal cancer was shown to be of limited clinical value [113]. Reports of other investigators on the incidence of CTC in breast cancer patients by quantitative analysis of the CK19 gene expression [114,115] were also disappointing, and showed a low specificity of the established assays. The low specificity of CTC detection by quantitative RT-PCR assays, as in the qualitative RT-PCR, may result from the presence of activated lymphoid cells. Even if the number of control samples is substantially increased, setting the appropriate cut-off thresholds based on healthy controls is not possible. For example, the CK19-positivity examined by the qualitative RT-PCR was almost two-fold higher in the “inflammatory” group than in healthy blood donors [116]. In accordance with these observations, the levels of the tumor markers’ mRNA expression, including CEA and CK20, measured by the real-time RT-PCR, have not differentiated the peripheral blood samples of patients with colorectal cancer from the reference blood samples (healthy donors and persons suffering from inflammatory bowel or infectious diseases) [117]. Moreover, the levels of CEA and CK19 transcripts were not different in pleural fluids from non-small cell lung cancer (NSCLC) patients and patients with tuberculo pleurisy [118]. In effect, numerous attempts to apply either RT-PCR or real time RT-PCR for micrometastasis/CTC detection have so far failed to produce a commonly accepted, routinely applied diagnostic method. Another example is provided by a recently developed method of detection of viable CTC using a GFP-expressing attenuated adenovirus, the replication of which is regulated by the telomerase promoter [119]. In principle, this fluorescence imaging should identify only viable, non-hematopoietic cells. However, a low level of fluorescence in the blood cells of healthy volunteers (0–4 cells in 5 ml of blood) has been detected. This raises the question of what is the level of falsepositive CTC detection in patients with inflammatory conditions. Kojima et al. [119], who wrote that replication of their adenovirus construct “is unlikely in normal hematopoietic cells, because of their low telomerase activity,” have not taken account of high telomerase expression levels in activated lymphocytes [62]. 4. Conclusion To summarize, we presented here examples of modern, sophisticated technologies which are promising tools for cancer detection.

Molecular profiling of cancer provides thousands of new potential tumor markers but only few biomarkers find clinical utility. There are several biological and technical reasons for this failure. We discussed the unsatisfactory specificity of the different assays developed to detect cancer by identifying disseminated cancer cells or different classes of molecular biomarkers discovered in body fluids (Table 1). We are convinced that special emphasis should be placed on systemic inflammation as a significant confounding biological factor in all these approaches, influencing poor specificity of the molecular cancer markers. There is no doubt that cancer-related inflammation is a common phenomenon. There are numerous examples of different tumor markers being overexpressed in activated cells and found elevated in the body fluids of patients with non-cancerous inflammatory conditions. Many researchers do not take account of the fact that cancer is a systemic disease, in which chronic inflammation plays an important role, not only accompanying, but also driving tumor development. As a result, most cancer biomarker studies have a considerable error factor because the results obtained in cancer patients are validated against those obtained in healthy persons. A series of studies, mostly by McMillan [37], clearly shows that unspecific parameters of systemic inflammatory response are independent predictors of prognosis in cancer patients. Yet numerous papers are published with inappropriate reference groups applied. To make real progress in discovering cancer biomarkers of high specificity, it is time to put different lines of research together and consider systemic inflammation as a cancer-associated condition and a prerequisite in the cancer biomarker studies. We are aware that it is generally not easy to acquire the appropriate inflammatory controls for the biomarker studies, especially within a single medical centre. Development of the relevant tissue and body fluid banks might overcome this difficulty in the biomarker research. To assess the independent predictive value of a biomarker, it should be validated against its expression in inflammatory conditions, and examined in the context of unspecific parameters of systemic inflammation. Conflict of interest statement No potential conflicts of interest were disclosed. Acknowledgments The authors are grateful to Professor Michael J. Duffy, PhD, FRCPath, FACB, for his critical reading of the manuscript. References [1] F. Balkwill, K.A. Charles, A. Mantovani, Smoldering and polarized inflammation in the initiation and promotion of malignant disease, Cancer Cell 7 (2005) 211–217. [2] A. Mantovani, P. Allavena, A. Sica, F. Balkwill, Cancer-related inflammation, Nature 454 (2008) 436–444. [3] M. Chechlinska, M. Kowalewska, R. Nowak, Systemic inflammation as a confounding factor in cancer biomarker discovery and validation, Nat. Rev. Cancer 10 (2010) 2–3.

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