Biochimica et Biophysica Acta 1806 (2010) 163–171

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Biochimica et Biophysica Acta

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Review

Implications of cancer-associated systemic inflammation for biomarker studies

Magdalena Kowalewska a, Radoslawa Nowak a, Magdalena Chechlinska b,⁎a Department of Molecular Biology, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, Roentgena 5, 02-781 Warsaw, Polandb Department of Immunology, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, Roentgena 5, 02-781 Warsaw, Poland

⁎ Corresponding author. Tel.: +48 22 5462256; fax: +E-mail address: chech@coi.waw.pl (M. Chechlinska)

0304-419X/$ – see front matter © 2010 Elsevier B.V. Adoi:10.1016/j.bbcan.2010.06.002

a b s t r a c t

a r t i c l e i n f o

Article history:Received 31 March 2010Received in revised form 16 June 2010Accepted 17 June 2010Available online 25 June 2010

Keywords:Cancer biomarkerMarker specificityMarker validationInflammationCTC

Highly sensitive molecular technologies provide new capacities for cancer biomarker research, but withsensitivity improvements marker specificity is significantly decreased, and too many false-positive resultsshould disqualify the measurement from clinical use. Hence, of the thousands of potential cancer biomarkersonly a few have found their way to clinical application. Differentiating false-positive results from true-positive (cancer-specific) results can indeed be difficult, if validation of a marker is performed againstinadequate controls.We present examples of accumulating evidence that not only local but also systemic inflammatory reactionsare implicated in cancer development and progression and interfere with the molecular image of cancerdisease. We analyze several modern strategies of tumor marker discovery, namely, proteomics,metabonomics, studies on circulating tumor cells and circulating free nucleic acids, or their methylationdegree, and provide examples of scarce, methodologically correct biomarker studies as opposed to numerousmethodologically flawed biomarker studies, that examine cancer patients' samples against those of healthy,inflammation-free persons and present many inflammation-related biomarker alterations in cancer patientsas cancer-specific. Inflammation as a cancer-associated condition should always be considered in cancerbiomarker studies, and biomarkers should be validated against their expression in inflammatory conditions.

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Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1632. Evidence of the systemic inflammatory response (SIR) in cancer patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

2.1. Standard blood tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1642.2. Cell phenotype changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1642.3. Serum markers of inflammation in cancer patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1642.4. Inflammatory markers and prognosis in cancer patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165

3. Systemic inflammation as a confounding factor in molecular biomarker measurements. . . . . . . . . . . . . . . . . . . . . . . . . . . 1653.1. High throughput methods, the “Omics” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1653.2. Free nucleic acid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1653.3. Circulating tumor cell detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166

4. Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168Conflict of interest statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

Conflict of interest statement

1. Introduction

Cancer biomarkers hold out some promise for helping to improvethe clinical outcomes of cancer patients. With advances in our

understanding of the molecular pathogenesis of cancer and the rapiddevelopment of new technologies, thousands of potential cancerbiomarkers have emerged and still only a few have found their way toclinical application. Here, we outline some of the most frequentlyexploitedmodern strategies for thediscoveryof newcancerbiomarkers.We address an issue of systemic inflammation in cancer patients as acommonly neglected factor in interpreting the biomarker profiles ofcancer 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 leastinvasive markers—those identified in body fluids.

Among several classes of molecular biomarkers, proteins haveattracted renewed interest with the development of proteomicstechnologies that enable thousands of proteins to be identified,characterized andquantified from complexmixtures such as biologicalsamples. The difficulty here lies in determining which proteins arespecifically linked to the disease in question, and do not just reflectunspecific secondary changes. Blood sera contain other potentialmolecularmarkers, notably cell-free RNA and DNA, the levels of whichare known to be elevated in cancer patients. However, finding acancer-specific cell-free nucleic acid is also a challenge. Identifyingcancer-derived extracellular DNA by typical genomic changes, such asoncogene and suppressor gene mutations and microsatelite altera-tions, presents high specificity, and this removes any ambiguities as toconclusions. But many other methodological approaches to the studyof either the levels of circulating nucleic acids or their methylationdegree do not employ reliable controls to differentiate cancer-specificchanges. The relevant controls are also of special importance in asearch for other cancer biomarker classes, such as excreted, urinarymodified nucleosides (being biological indicators of whole-body RNAturnover), and molecular markers used for the assessment ofcirculating or disseminated tumor cells (CTC and DTC, respectively).To detect CTC/DTC, nucleic acid-based techniques such as RT-PCR areusually employed. The greatest challenge in CTC/DTC detection isagain to address the appropriate, tumor-specific markers.

Any factor affectingmarker 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 cancerpatients is a common phenomenon. On the other hand, numerouspieces of evidence described here demonstrate that inflammationstrongly affects the biomarker profile. Unfortunately, most biomarkerresearch does not refer to inflammation as an inherent component ofcancer disease and thusmany inflammation-related biomarker changesin cancer patients are interpreted as cancer-specific.

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

Inflammation, apart from playing a causal role in cancer develop-ment, 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 intersectionof sets contains non-specific markers. In cancer biomarker studies, if the results arereferred to normal samples, instead of discovering cancer-specific markers we arrive atbiomarkers that are most likely unspecific.

accompanies all stages of cancer [1]. Recent findings summarized byMantovani et al. [2] have revealed that some genetic events that causeneoplasia are also responsible for generating an inflammatory micro-environment, with the same molecular pathways induced as ininflammatory or infectious conditions that increase the risk ofdeveloping cancer. Irrespective of the initial mechanism of cancerdevelopment, local as well as systemic cancer-related inflammationoccurs [3].

2.1. Standard blood tests

It has been well documented that in patients with cancer routineblood tests often reveal changes similar to those observed in patientswith infectious or inflammatory diseases.

Numerous studies have shown that changed erythrocyte sedimen-tation rate (ESR), along with counts of neutrophiles, monocytes,platelets and total white blood cells (WBC), relates to clinicalparameters, including the disease progress and outcomes of patients.Here are some examples. In a population-based study of over 3000individuals, a higher WBC count was shown to be associated with allcancer mortality [4]. In the studies by Rasouli et al. [5], ESR in patientswith different cancerswas one of the best parameters for discriminatingbetween malignant and healthy conditions. In renal cancer patients, apreoperative ESR was independently associated with cancer-specificsurvival after nephrectomy [6]. Elevated platelet count (thrombocyto-sis) is common inmany cancers [7]. In early lung cancer, thrombocytosiscombined with ESR and serum lactate dehydrogenase, presented highsensitivity and specificity in predictingmalignancy in patientswith lunglesions [8]. The neutrophil to lymphocyte ratio increased with the stageof NSCLC, and was an independent predictor of survival after thecomplete resection of primary lung cancer [9]. In a recent study oncervical cancer, a pre-treatment neutrophil and monocyte countsproduct was a predictor of poor prognosis, independent of stage andtumor size [10]. In patients with colorectal cancer, high neutrophil [11]and monocyte [12] counts were shown to be independent predictors ofpoor cancer-specific survival.

2.2. Cell phenotype changes

The Th1 to Th2 shift has been widely recognized in cancer patients[13]. Also, increased percentages of activated T lymphocytes weredemonstrated in the peripheral blood of cancer patients [14–17].Already in 1986, Tsuyuguchi et al. [15] showed a significantly in-creased mean percentage of circulating IL-2R+ T lymphocytes inuntreated primary lung cancer patients, regardless of histopatholog-ical type and clinical stage. In patients with stages Ia and Ib ovariancancer, the percentages of CD4+HLADR+ cells were significantlyhigher than in healthy controls and patients with benign andborderline ovarian tumors, but decreased in later stages [14]. Inthe 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 thefirst to show that gene-expression patterns in the peripheral bloodcells were affected already in the early stages of the disease. It wassuggested that the gene-expression changes may indicate systemicactivation of some blood cell subsets.

The systemic activation and phenotype changes of lymphocytesmay relate to the elevated concentrations of serum cytokines, typicalfor both cancer and inflammatory diseases. This will be discussedbelow.

2.3. Serum markers of inflammation in cancer patients

The inflammatory micro-environment of solid tumors is charac-terized by an excess of cytokines produced and released by cancer

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cells, infiltrating cells and the reactive stroma. This local overexpres-sion, as shown in ovarian, cervical, prostate, lung, gastric, breast,colorectal, renal and other tumors, is accompanied by increasedsystemic concentrations of cytokines, including pro-inflammatorycytokines, such as IL-6, IL-8, TNFα, MIF, IL-1β, often related to theclinico-pathological features of cancer and to patients' survival. Theseissues have been described and discussed in detail elsewhere [19–22].Systemic inflammatorydisease in cancer patients is often evidencedbyelevated circulating C-reactive protein (CRP) and serum amyloid Aprotein (SAA), the unspecific acute-phase proteins produced byhepatocytes upon stimulation by pro-inflammatory cytokines, suchas 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 thesystemic inflammatory response, as evidenced by the elevated serumacute phase proteins and hypoalbuminemia, has been well documen-ted. Elevated preoperative CRP was shown to be an independentpredictor of poor outcome in patients following potentially curativeresection 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 cellcarcinoma of the urinary bladder [30] and advanced pancreatic cancer[31]. In patients with invasive, primary, operable breast cancer, it wasthe level of preoperative albumin, not that of CRP, that independentlyinfluenced prognosis [32]. However (in an extended study by Pierceet al. [33]), in patients with non-metastatic (stages 0 to IIIa) breastcancer, 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 prognosisin patients with operable renal cell and gastric carcinomas [34,35].SAA levels have also been shown to be significantly elevated inpatients with head and neck SCC [36]. A combination of an elevatedC-reactive protein and hypoalbuminemia has been proposed as aneffective “inflammation-based prognostic score” (the Glasgow prog-nostic score—GPS) [37].

3. Systemic inflammation as a confounding factor in molecularbiomarker measurements

We have recently raised an issue of systemic inflammation, acondition that is evidently accompanying cancer disease, as aprevalent confounding factor in cancer biomarker studies [3]. Itshould be considered in the cancer biomarker research, no matterwhich method of biomarker study is employed.

3.1. High throughput methods, the “Omics”

Proteins, the main constituents of cells and body fluids, havereceived a great deal of attention as cancer biomarkers. Thecontemporary proteomic techniques have a potential to identify,characterize and quantify all proteins and peptides contained in asample. Now, a real challenge is to identify proteins and peptidesspecific for a given condition. For example, by employing a proteomicmodification called “cancer immunomics,” tumor-associated antibo-dies were identified in the sera of patients with early NSCLC andprostate cancer [38,39]. However, none of the global proteomic studiesidentified such proteins, not just because of the low abundance ofthese proteins, but very likely because the serum protein profiles areusually compared between cancer patients and healthy persons, or–atbest–between cancer patients and patients with benign tumors of therelevant tissue. As a result, proteins involved in inflammatoryreactions, but not cancer-specific proteins, are identified as differen-tially expressed. Comparative analysis of serum proteins and peptides

in pancreatic cancer patients and healthy volunteers clearly pointed tothe inflammation-related molecules as the dominant differences [40].Similarly, sera of lung adenocarcinoma patients were discriminatedfrom the sera of healthy donors by non-specific, inflammatory proteins[41]. It is right to conclude that inflammatory mechanisms areinvolved in these cancers, but this conclusion is hardly adequate tothe sophisticated and expensive methods applied. Chen et al. [42]clearly demonstrated that a chronic inflammatory condition (pancre-atitis) shares many protein signatures with the malignant diseaseinvolving the same organ (pancreatic cancer). Such comprehensivemethodological approaches further emphasize the importance anddifficulty of finding well-matched controls.

Over the past decade, we have witnessed a rapid advancement inanother category of the “omic” series, metabonomics, whichmeasuresthe end products of metabolic response to pathophysiological stimulior genetic modifications, and thus opens upworlds of potential cancerbiomarkers. One of the groups of metabolites comprises modifiednucleosides, which are degradation products of cellular RNAs, found inurine. Altered nucleoside excretion patterns may reflect metabolicimbalance or accelerated RNA turnover. Significant increase and analtered pattern of modified nucleosides have been described in urinefrom patients with different malignancies, such as breast, colon,sarcoma, melanoma, and lymphoid cancer [43–45]. However, toidentify a reliable biochemical indicator of cancer appropriate controlsare of primary importance. Unfortunately, researchers usually com-pare the metabolite profiles of the urine between cancer patients andhealthy persons. Inevitably, such comparisons are misleading, aschanged RNA turnover accompanies any disease, inflammatoryconditions in particular, and consequently results in an alterednucleoside excretion pattern. Over a decade ago, Tebib et al. [46]demonstrated that the levels of urinary excretedmodified nucleosidesreach the same orders of magnitude in patients with cancer and inpatients with rheumatoid arthritis, homeopathies or spondyloarthro-pathies. Yang et al. [47] studied a collection of 15 urinary nucleosides,promising candidates for markers of hepatocellular carcinoma. Meanconcentrations of all nucleosides have significantly differed in cancerpatients and in healthy persons. However, being aware that nucleosidelevels need to differentiate cancer from other conditions in a specificway, the researchers also analyzed the urinary nucleoside concentra-tions in patientswith acute and chronic hepatitis, as well as in patientswith hepatocirrhosis. The results clearly demonstrated that theanalysis of the 15 nucleosides would not differentiate patients withcancer from thosewith other liver diseases. By employing HPLC-basedmetabonomics the researchers identified a group of metabolites, mostof an unknown function, which differentiated patients with hepato-cellular cancer from those with hepatitis or hepatocirrhosis, with apositive predictive value of 100% and 93%, respectively. This studyprovides an example of finding and using an appropriatemethodologythat results in reliable evidence for conclusions on cancer-specificmarkers.

In the light of these model biomarker studies, a recently publishedpaper of Issaq et al. [48] is surprising. The researchers applied a similarmetabonomic approach and were enthusiastic about being able todifferentiate urine samples of patients with bladder cancer from thoseof healthy persons with 98% sensitivity and 96% specificity. However,the lack of comparisons with samples from patients with inflamma-tory conditions makes this enthusiasm premature.

3.2. Free nucleic acid analysis

Free nucleic acids are widely researched as potential cancerbiomarkers. According to Chan et al. [49], the increased levels ofcirculating cell-free nucleic acids may either reflect cancer celldisintegration or the response to the disease, or both. Here areexamples of some recent studies. Banki et al. [50] examined plasmalevels of cell-free DNA along with CEA in patients with esophageal

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cancer and in asymptomatic volunteers, and concluded that “elevatedplasma DNA is an extremely reliable indicator of the presence ofrecurrent disease, contrary to CEA.” Paci et al. [51] employed asimilarly flawed methodology to identify cancer-specific biomarkersand compared circulating plasma DNA levels in patients with non-small cell lung cancer to those of healthy controls. The differencesobtained convinced the authors that “this could have practicalimplications such as the use in screening programs and a possibleprognostic significance in the follow-up.” Unfortunately, these studiesdid not consider the well-known phenomenon of elevated levels ofcirculating free DNA accompanying different non-cancerous patho-logical conditions, such as systemic arterial inflammation [52],pulmonary embolism [53], acute pancreatitis [54], obstructive sleepapnea [55], and even overtraining-induced inflammation [56].Moreover, van der Drift et al. [57], who examined free DNA in thesputumof lung cancer patients, demonstrated that „the amount of freeDNA is related to the amount of inflammation, but not to the presenceof lung cancer.”

Numerous other studies have attempted to identify cancer cell-specific circulating RNA. A good example is the human telomerasereverse transcriptase (hTERT) mRNA, a tempting candidate for cancerbiomarker. The levels of hTERT have been examined in patients withgynecologic malignancies, primary and recurrent gastric cancer,prostate, and lung cancer [58–61]. In all these studies, the hTERTmRNA levels of normal sera were set as a reference cut-off value. As aresult, it has been concluded that free hTERT mRNA is a novel andexcellent biomarker for the diagnosis and staging of cancer disease.This concept was based on an assumption that since hTERT isexpressed in most cancer cells, but not in most normal cells, it maybe regarded as cancer-specific. Unfortunately, this does not takeaccount of the fact that activated lymphocytes are a rich source ofhTERT [62]. Therefore, until the analyses against control patients withinflammatory diseases are performed, hTERT is unwarranted as acancer marker.

Epigenetic changes in the DNA methylation profiles are commonin human cancers. Thus, hypermethylated cell-free serum DNA havebeen considered as a potential tumor marker. The results of recentstudies in patients with testicular [63], prostate [64], gastric [65], andbreast cancers [66] seem promising, but again, most analyses wereperformed against normal controls. Yet global DNAmethylation in theperipheral blood leukocytes is altered in inflammation, for example inpatients with coronary artery disease [67] or with chronic kidneydisease [68]. Additionally, as emphasized by Duffy and colleagues [69],the process of aging as well as the presence of benign diseases, affectsgenemethylation patterns, and this constitutes one of the problems inthe application of methylated genes as cancer markers. More geneticstudies are necessary to determinewhich hypermethylated events aretruly relevant for carcinogenesis.

3.3. Circulating tumor cell detection

The potential of CTC or DTC detection in cancer prognosis andfollow-up has been extensively studied. Still, the clinical relevance ofCTC or DTC detection is controversial, and the current methodsemployed for CTC characterization and detection lack sensitivity,specificity or reproducibility. Morphological, immunological, molec-ular or combined approaches and different separation techniqueshave been employed to distinguish CTC/DTC from normal cells. Theadvantages and limitations of these methods have been recentlydiscussed elsewhere [70,71]. However, it has to be underlined thateven by using the most advanced, FDA-approved, and commerciallyavailable CellSearch system, 10% of healthy volunteers are foundpositive, and the percentage of false-positive results may increaseduring inflammatory conditions and following surgical interventions[72]. We will concentrate on the reasons why the molecular strategiesfail to distinguish between CTC/DTC and normal cells.

For over a decade high sensitivity reverse transcriptase-polymer-ase chain reaction (RT-PCR) has been the most widely employedtechnique for CTC/DCTdetection, as amolecularmethod of choice. Oneof the most frequently used RT-PCR markers of epithelial cells iscytokeratin (CK)19. The detection of CK19 transcripts has been used toconfirm the tumor spread. Many recently published papers suggestthat CK19 is an accurate marker for cancer cell detection in the lymphnodes [73] and bone marrow [74] of cancer patients. Anothercytokeratin, CK20, is employed for cancer cell detection in the lymphnodes [75], and in peritoneal lavages [76] and it was recently proposedas a marker for urine analysis [77]. CEA is also an extensively studiedgene that is predominantly expressed in cells of epithelial origin, and itis therefore considered to be an indicator of disseminated tumor cellsin peritoneal lavages [76], the lymph nodes [78] and in the peripheralblood [79].Manypapers describe hMAM(humanmammaglobin) as anaccurate 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 plaguedby a high percentage of false positive results. For example, it has beendemonstrated that CK19 and CK20 are expressed in the blood [85–93]and bone marrow [92,93] of non-cancer subjects, and CK19 also in thelymph nodes [90,94,95]. Similarly, positive results of CEA wereobtained in the samples of peripheral blood [87,90,96], lymph nodes[90], bone marrow [97] and peritoneal lavages [98] from carcinoma-free patients. These results were only the “warning signals”questioning the specificity of these markers. Additional argumentsagainst cancer specificity arose when bone marrow samples obtainedfrom patients suffering from chronic inflammatory diseases werefound to be highly positive for CK19 [99], CEA [99] and CK20 [92].

One of the reasons behind these significant limitations of the RT-PCR methodology was clarified by Jung and colleagues [99], who haveshown that the expression of CK19 and CEA is inducible in lymphaticcells upon cytokine stimulation. Carried out in 1998, this was the firststudy to place an emphasis on the necessity to enroll patients sufferingfrom nonmalignant diseases to evaluate RT-PCR assays, rather thansimply standardizing them against the samples obtained from healthyvolunteers. Also Pittini et al. [100] consistently indicated that CK19expressionwas inducible in PBMCunder inflammatory conditions, andthis may result in frequent false-positives in RT-PCR. We have shownthat the expression of hMAM, EGFR (epidermal growth factorreceptor), SCCA (squamous-cell carcinoma antigen) and SBEM(small breast epithelial mucin), is inducible in normal peripheralblood mononuclear cells (PBMC) [101]. Similarly, Goeminne et al.[102] showed that CEA transcription was inducible in PBMC fromhealthy individuals upon GCSF. hMAM expression was found to beinducible by cytokines in bonemarrow and peripheral stem cells frompatients without epithelial cancer [103] and in normal peripheralblood leukocytes following apheretic procedures [104].

Although the prognostic value of variousmarkers in cancer patientsis often shown and regarded as an indirect proof of their cancerspecificity, mere measurements of the inflammatory factors alsopresent prognostic value (as noted above), and in patients withadvanced cancer, the systemic inflammatory response is a strongindependent prognostic factor. Moreover, when monitoring chemo-therapy using RT-PCR, the disappearance of the given marker-positivecells in patients after chemotherapy (as observed for CK19 [105]) orradiotherapy may also result from the cytotoxic effect on theinflammatory cells. We have suggested that to reduce the false-positive results associated with disseminated tumor cell testing, newmolecular markers should be validated not against normal peripheralblood cells, but against activated lymphoid cells [101].

The ultra sensitive method, quantitative RT-PCR, has promised tohave the potential to avoid the previous failures of the RT-PCR-basedassays used to detect tumor cells. To improve the specificity of RT-PCR,numerous qRT-PCR approaches have been developed with different

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

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Table 1 (continued)

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markers, including CK19 [106,107], hMAM [107,108] and CEA [109].However, the clinical relevance of CTC/DTC detection using thistechnique still remains unproven. For example, Dimmler et al. [110]demonstrated that the variable background expression of thedifferent CKs in bone marrow specimens from noncancer patientswas 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 areal-time approach, were not able to reliably differentiate colorectalcancer patients from healthy volunteers based on the levels of CEAexpression. Suchy et al. [112] could not observe the prognosticsignificance of the hMAM expression level in the blood of breastcancer patients. The analysis of CK19 and CK20 gene expression levelsin the blood cells of patients with esophageal cancer was shown to beof limited clinical value [113]. Reports of other investigators on theincidence of CTC in breast cancer patients by quantitative analysis ofthe CK19 gene expression [114,115] were also disappointing, andshowed 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 activatedlymphoid cells. Even if the number of control samples is substantiallyincreased, setting the appropriate cut-off thresholds based on healthycontrols is not possible. For example, the CK19-positivity examined bythe qualitative RT-PCR was almost two-fold higher in the “inflamma-tory” group than in healthy blood donors [116]. In accordance withthese observations, the levels of the tumor markers’ mRNA expres-sion, including CEA and CK20, measured by the real-time RT-PCR,have not differentiated the peripheral blood samples of patients withcolorectal cancer from the reference blood samples (healthy donorsand persons suffering from inflammatory bowel or infectiousdiseases) [117]. Moreover, the levels of CEA and CK19 transcriptswere 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 formicrometastasis/CTC detection have so far failed to produce acommonly accepted, routinely applied diagnostic method.

Another example is provided by a recently developed method ofdetection 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 onlyviable, non-hematopoietic cells. However, a low level of fluorescencein the blood cells of healthy volunteers (0–4 cells in 5 ml of blood) hasbeen detected. This raises the question of what is the level of false-positive CTC detection in patients with inflammatory conditions.Kojima et al. [119], who wrote that replication of their adenovirusconstruct “is unlikely in normal hematopoietic cells, because of theirlow telomerase activity,” have not taken account of high telomeraseexpression levels in activated lymphocytes [62].

4. Conclusion

To summarize, we presented here examples of modern, sophisti-cated technologies which are promising tools for cancer detection.

Molecular profiling of cancer provides thousands of new potentialtumor markers but only few biomarkers find clinical utility. There areseveral biological and technical reasons for this failure. We discussedthe unsatisfactory specificity of the different assays developed todetect cancer by identifying disseminated cancer cells or differentclasses of molecular biomarkers discovered in body fluids (Table 1).We are convinced that special emphasis should be placed on systemicinflammation as a significant confounding biological factor in all theseapproaches, influencing poor specificity of the molecular cancermarkers. There is no doubt that cancer-related inflammation is acommon phenomenon. There are numerous examples of differenttumor markers being overexpressed in activated cells and foundelevated in the body fluids of patients with non-cancerous inflam-matory conditions. Many researchers do not take account of the factthat cancer is a systemic disease, in which chronic inflammation playsan important role, not only accompanying, but also driving tumordevelopment. As a result, most cancer biomarker studies have aconsiderable error factor because the results obtained in cancerpatients are validated against those obtained in healthy persons.

A series of studies, mostly by McMillan [37], clearly shows thatunspecific parameters of systemic inflammatory response are inde-pendent predictors of prognosis in cancer patients. Yet numerouspapers are published with inappropriate reference groups applied. Tomake real progress in discovering cancer biomarkers of highspecificity, it is time to put different lines of research together andconsider systemic inflammation as a cancer-associated condition anda prerequisite in the cancer biomarker studies. We are aware that it isgenerally not easy to acquire the appropriate inflammatory controlsfor the biomarker studies, especially within a single medical centre.Development of the relevant tissue and body fluid banks mightovercome this difficulty in the biomarker research. To assess theindependent predictive value of a biomarker, it should be validatedagainst its expression in inflammatory conditions, and examined inthe 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.

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