| | Biological correlates of FDG uptake in non-small cell lung cancerReceived 24 March 2006; received in revised form 25 August 2006; accepted 29 August 2006. Summary PurposeEach pathological stage of non-small cell lung cancer (NSCLC) consists of a heterogeneous population containing patients at much higher risk than others. Noninvasive functional imaging modalities, such as 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), could play a role in further characterization of NSCLCs. As many factors can influence the extent of FDG uptake, the underlying mechanisms for FDG accumulation in tumors, are still a matter of debate. The aim of the present study was to investigate these possible mechanisms in the primary site of early stage preoperatively untreated NSCLC. Methods19 patients with early stage NSCLC, who had undergone both preoperative FDG-PET imaging and curative surgery, were enrolled in this study. Standardized uptake values (SUVs) were used for evaluation of primary tumor FDG uptake. Final diagnosis, tumor type, tumor cell differentiation and size of the primary tumors were confirmed histopathologically in resected specimens. Histologic sections were analyzed for amount of inflammation and necrosis. Expression of the glucose membrane transporters (GLUT-1 and GLUT-3); the isoforms of the glycolytic enzyme hexokinase (HK-I, HK-II and HK-III); and the cysteine protease caspase-3, was evaluated immunohistochemically. ConclusionThe present study supports the hypothesis that tumor cell differentiation in combination with overexpression of GLUT-1 and GLUT-3 determine the extent of FDG accumulation and that squamous cell carcinomas accumulate more FDG than adenocarcinomas or large cell carcinomas. 1. Introduction  Lung cancer is the leading cause of cancer related death in both men and women. About 3 million new cases a year are estimated to arise worldwide, of which more than 200 000 are in the European Union. An increase in incidence is to be expected until the first decades of the 21st century [1]. For the average patient with a diagnosis of lung cancer the overall 5-year survival rates have increased from 12% in the early 70s to 15% in 2001 [2]. Survival ranges from 75% for patients with pT1N0 disease to virtually nil for patients with stage IV non-small cell lung cancer (NSCLC) [3]. Surgery with curative intent represents the best chance for cure, but is only an option in patients with stages I, II, and selected cases of stage IIIA (T3N1M0) NSCLC. However, only 30% of NSCLC cases present at these early stages. Even if a complete curative resection can be performed, the majority of patients will relapse. The majority of these relapses occur at distant sites, indicating micrometastatic disease at presentation [4]. Progress is being made due to the introduction of novel treatment programs, like induction chemotherapy [5], concurrent chemo-radiation for stage III disease [6], [7], and more recently, adjuvant chemotherapy for earlier stages [8], [9]. It is of major importance to be able to predict the relapses and to prevent them with these active intensified treatment regimens. The tumor-node-metastasis (TNM) staging system, to date considered the most important tool in estimation of prognosis and guidance of treatment decisions [10], however, provides an incomplete biologic profile of NSCLC, does not always provide a satisfactory explanation for differences in relapse and survival and is thus far from perfect as a prognostic indicator [11], [12]. Each pathological stage consists of a heterogeneous population containing individuals at much higher risk of recurrence and death than others [11], [12], [13]. Therefore, there is a need for noninvasive quantitative measures of biological aggressiveness that could play a role in further characterization of NSCLCs. A better understanding of biological mechanisms in lung tumor cells could be helpful and finally might lead to a better selection of patients who may benefit from (neo)adjuvant therapy. Such noninvasive quantitative measures of biological aggressiveness may be of particular value in stratifying patients for clinical trials. The introduction of the combined use of fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) has had a great impact on the diagnosis and staging of lung cancer. FDG-PET provides noninvasive mediastinal staging and reduces the number of futile thoracotomies and mediastinoscopies [14], [15], [16]. Furthermore, FDG-PET detects unsuspected extrathoracic metastases in 14–16.9% of patients otherwise deemed potentially resectable [17]. The number of clinical applications for FDG-PET in NSCLC continues to increase. Recently, FDG-PET has also demonstrated its value in radiation treatment planning, detection of recurrent disease, in identifying tumor response to chemotherapy at an early phase of treatment and in identifying subsets of patients with poor outcome [18]. One of the great advantages of this technique is that it cannot only visualize but can also quantify FDG uptake to distinguish metabolically highly active from less active tumor tissues and therefore offers an opportunity for noninvasive, in vivo tissue characterization. The biological basis of FDG-PET is the increased glucose metabolism of malignant cells as compared to noncancerous tissues. After administration of the glucose analog FDG, it will be transported into the tumor cell and will be phosphorylated by hexokinase. The intracellular FDG-6-phosphate is trapped in the malignant cells, as it will not be processed in the glycolytic pathway and can thus be visualized using PET. A variety of mechanisms have been proposed for accelerated glucose use in growing tumors and in transformed and malignant cells: passive diffusion, Na+-dependent glucose transport and via facilitative glucose transporters (GLUT). The latter is considered to be the most important mechanism for enhancing glucose influx into cells [19]. The glucose transporters GLUT-1 and GLUT-3, subtypes with a relatively high affinity for glucose, belong to the sugar transporter family, which currently includes 133 individual members [20]. Increased concentrations of the glucose phosphorylation enzyme, hexokinase, with decreased rates of glucose-6-phophatase are considered to accelerate glucose phosphorylation, which results in enhanced FDG intracellular trapping. Upregulation of hexokinase and glucose transporters, especially GLUT-1, and downregulation of glucose-6-phosphatase are frequently associated with malignant transformation. Glucose transport activity can be regulated by alterations in the expression of GLUT transporters and by post-translational mechanisms, including transporter translocation to plasma membranes [21]. Akhurst et al. recently reported that the use of chemotherapy could alter FDG uptake in tumors by altering the activity of hexokinase [22]. Moreover, the rate of FDG uptake in the primary site of NSCLC has been correlated with tumor doubling time [23] and proliferation rates [24] which, in turn, are known to correlate with tumor aggressiveness [25], [26], [27]. Furthermore, apoptosis plays a central role in the elimination of (the precursors of) tumor cells. Therapy resistance can be attributed, at least in part, to a disabled apoptotic program [28]. Sasaki et al. demonstrated that primary tumors showing high FDG uptake have the potential to be resistant to therapy and to metastasize [29]. It was recently reported that strong expression of the cysteine protease caspase-3, which is a key enzyme in apoptotic cell death, was a significant factor to predict poor prognosis [30]. Better understanding of a possible relationship between FDG uptake and apoptosis may provide insights into sensitivity or resistance of tumor cells. Furthermore, tumors that grow too rapidly or have a deficient vascular system are characterized by the formation of necrosis. Necrosis reflects cell death caused by hypoxia. Hypoxia results in enhanced anaerobic glycolysis and hence in increased FDG uptake [31]. Finally, the presence of inflammatory cells, might be confounding, since inflammatory cells may have a major impact on FDG uptake [32]. At present it is still not fully elucidated which of these factors contribute to the variable levels of FDG uptake in NSCLC. Results from studies on other tumor types cannot be extrapolated to NSCLC, as different tumors have different glucose-regulating mechanisms and enzyme expression patterns in association with various oncogenic alterations [33]. The aim of the present study was to investigate the mechanisms that drive FDG in the primary site of early stage untreated NSCLC. The relationship among FDG uptake and the immunohistochemical expressions of the key glucose membrane transporters, GLUT-1 and GLUT-3; the isoforms of the glycolytic enzyme hexokinase, HK-I, HK-II and HK-III; the cysteine protease, caspase-3, and several histological parameters was evaluated. 2. Methods 2.1. Patient eligibility criteria FDG uptake in early stage NSCLC was measured using PET in 19 patients (18 males, 1 female, mean age 62.4 years, range 38–76 years) who were subsequently treated with curative surgery. Patient characteristics are summarized in Table 1. Exclusion criteria were poorly regulated diabetes mellitus, preoperative chemotherapy or radiotherapy and metachronous lung cancers treated for at least 2 years before the study period. All patients underwent whole body FDG-PET as part of their routine preoperative staging procedure. All scans were performed within 6 weeks prior to surgery. Paraffin-embedded material of the surgical specimens of all patients was available. 2.2. FDG-PET A dedicated, rotating half-ring PET-scanner (ECAT-ART, Siemens/CTI, Knoxville, TN, USA) was used for data acquisition. Prior to FDG-injection, patients were fasted for at least 6 h, inducing a low insulin-state. Immediately prior to the procedure, the patients were hydrated with 500ml of water. One hour after intravenous injection of 200–220MBq FDG (Mallinckrodt Medical, Petten, The Netherlands), and 10–15mg furosemide, emission and transmission images of the area between the proximal femora and the base of the skull were acquired (10min per bed position). The images were corrected for attenuation and reconstructed using the ordered-subsets expectation maximization (OSEM) algorithm. 2.3. FDG-PET analysis Two experienced nuclear medicine physicians, who had access to all clinical data, primarily interpreted the FDG-PET images to determine eligibility for surgery. For this study, all FDG-PET studies were reanalyzed in order to acquire semiquantitative data. For that purpose volumes of interest (VOI) were drawn around the primary site of the NSCLC using an automatic 50% isocontour (ECAT software tool), which enclosed pixels with 50% or more of the maximum radioactivity within the VOI. Standardized uptake values (SUVs) were calculated using the concentration of FDG in the VOI as measured by PET, divided by the injected FDG dose and multiplied by body weight as a normalization factor. The maximum SUV (SUVmax, hereafter mentioned SUV) within the VOI was used for further analysis. Because no lesion was less than 1cm in size, partial volume correction was not applied. 2.5. Immunohistochemical staining procedure The expression of GLUT-1, GLUT-3, HK-I, HK-II, HK-III and caspase-3 was studied in the paraffin-embedded tissue arrays. The slides were dewaxed and rehydrated using xylene and ethanol, respectively. After immersion in 10mmol/l citrate, pH 6.0 the slides for caspase-3, HK-I, HK-II and HK-III were subjected to microwave irradiation for 10min for antigen retrieval. The slides for GLUT-1 and GLUT-3 were pretreated with pronase. Endogenous peroxidase activity was quenched with 40% methanol containing 0.6% H2O2 for 30min. After preincubation with 5% normal human serum for 30min, the slides were incubated with rabbit polyclonal antibody directed to GLUT-1 (1:200, DAKO, Glostrup, Denmark), rabbit polyclonal antibody directed to GLUT-3 (1:200, Lab Vision, CA, USA), rabbit polyclonal antibody directed to caspase-3 (1:200, BD Pharmingen, NJ, USA), goat polyclonal antibody directed to HK-I (1:20, Santa Cruz Biotechnology, Inc., CA, USA), goat polyclonal antibody against HK-II (1:70, Santa Cruz Biotechnology, Inc., CA, USA) goat polyclonal antibody directed to HK-III (1:20, Santa Cruz Biotechnology, Inc., CA, USA), for 60min. The slides were washed with phosphate buffered saline (PBS) followed by incubation with rabbit-anti-goat-biotine (1:200, DAKO, Glostrup, Denmark) for 30min in case of HK-isoforms and in case of GLUT-1, GLUT-3 and caspase-3 slides were incubated with polyclonal goat-anti-mouse-peroxidase conjugate (GAM-HRP, undiluted, Immunologic, Duiven, Nederland). After washing with PBS, the slides stained with the hexokinase antibodies were incubated with Vectastain Elite ABC kit (Vector Laboratories, CA, USA) for 30min. After washing with PBS, the bound antibodies were visualized using diaminobenzidine (Powervision DAB, Immunologic, Duiven, Nederland) as a chromogen. All slides were counterstained with hematoxylin. All antibodies were diluted in PBS containing 1% bovine serum albumin (BSA) and incubations were performed in the dark at room temperature. 2.6. Histopathologic evaluation Two experienced pathologists in lung cancer, who were unaware of the patient's clinical data, the FDG-PET results and results of the patient's other biomarkers, evaluated all of the pathologic material on a multiheaded light microscope. Disagreements were resolved by consensus. In the hematoxylin-eosin-stained sections tumor histology was determined, tumor cell differentiation was semiquantitatively scored as poor (0), moderate (I) or well (II), the percentage of tumor necrosis was estimated, and the amount of inflammation was scored as none (0), slight (I), moderate (II), or severe (III). The tumor size as measured in the resection specimen was recorded. All cases were classified according to the WHO-classification. The presence of membrane-bound GLUT-1, GLUT-3, caspase-3 and intracytoplasmic HK-I, -II and -III was examined for all tumor tissues. Red blood cells present in the tissues served as positive controls for GLUT-1. The presence of GLUT-1 and GLUT-3 tumor cell membrane staining and tumor cell cytoplasmic staining for HK isoforms I, II and III was graded by the percentage of tumor cells with positive staining: 0–25% (I), 26–50% (II), 51–75% (III), and 76–100% (IV). The intensity of staining was categorized as none (0), weak staining (I), medium staining (II), and intense staining (III), ignoring nonspecific nuclear staining, which was frequently noted for all HKs. The immunoreactive level was calculated by multiplication of the scores (intensity×% positive). The number of nuclear caspase-3 positive cells was semiquantitatively scored as none (I), occasional (II), or frequent (III). 2.7. Statistical analysis Spearman's rho correlations were used to estimate associations between the different continuous parameters (SUV, tumor size) and ordinal parameters (GLUT-1, GLUT-3, Hexokinase isoforms I-III, Caspase-3, amount of necrosis, inflammation and tumor cell differentiation) and between the SUV and a combination of parameters. Non-parametric statistics (Mann–Whitney) were used to test whether FDG uptake was different based on the categorical parameter histological tumor type (squamous cell carcinoma, adenocarcinoma and large cell carcinoma). To investigate which combination of parameters best explained FDG uptake, regression analysis was not suitable due to the small number of patients and a not jet generally accepted conceptual theory about the relationship between the various parameters. Alternatively, to arrive at a more reliable overall measure and to estimate its association with FDG uptake, all parameters that showed a moderate association (r>0.30) with SUV and that contributed to the reliability (internal consistency; Cronbach's alpha) of the overall measure were pooled. Because the various measures have different ranges, pooling was performed by summing standardized z-scores. The level of significance was set at 0.05. Statistical evaluations were performed using SPSS 12.0.1 statistical software (SPSS Inc, Chicago, IL). 3. Results All tumors accumulated FDG and were well-visualized by PET. The mean SUV of all tumors was 9.6±5.0 (range 3.3–22.8). The diameter of the primary tumors as determined from the resected specimens, ranged from 1.0 to 7.5cm, with a mean tumor size of 3.3cm. FDG uptake was significantly higher in squamous cell carcinomas (mean SUV 13.4±4.9, n=8) compared to adenocarcinomas (7.1±3.3, n=8, p=0.007) or large cell carcinomas (5.9±1.9, n=3, p=0.02). There was no significant difference in FDG uptake between adenocarcinomas and large cell carcinomas (p=0.92). Immunohistochemical analysis indicated that GLUT-1 and GLUT-3 were mainly expressed in the membrane of cancer cells. A typical example of GLUT-1 and GLUT-3 immunostaining of a tumor with a SUV lower (Fig. 1) and higher (Fig. 2) than the mean value (SUV 9.6) of the whole population. However, GLUT-1 and GLUT-3 positive granules were also observed in the cell cytoplasm and GLUT-3 positivity was often observed around necrotic areas or granulocytes (Fig. 2). A very fine uniform granular pattern was observed in the cytoplasm of most HK-I, -II or -III-positive cancer cells (Fig. 3). Caspase-3 was expressed in both the nucleus and the cytoplasm of the cancer cells. The distribution of staining was homogenous in both the nucleus and the cytoplasm. No significant relationship was found between SUV and each of the individual parameters. In Table 2, correlation coefficients between all parameters and corresponding p-values are shown. There was a statistically significant positive relationship between the GLUT-1 and GLUT-3 immunoreactive level (r=0.47, p=0.04), the HK-II and HK-III immunoreactive level (r=0.56, p=0.01), GLUT-1, GLUT-3 and tumor cell differentiation (r=0.50, p=0.03 for both glucose transporters) and between the percentage of necrotic tumor compounds and the immunoreactive level of each of the three HK isoforms and tumor cell differentiation (r=0.49, p=0.04 for HK-I; r=0.55, p=0.02 for HK-II; r=0.55, p=0.02 for HK-III, r=0.49, p=0.04 for tumor cell differentiation). Poorly differentiated tumors showed higher GLUT-1 expression than moderately differentiated tumors. More interestingly, the degree of FDG accumulation seemed to depend on GLUT-1 and GLUT-3 expression, the size of the tumor and the degree of tumor cell differentiation, as they showed a moderate association with the SUV (r=0.37, 0.35, 0.30 and 0.40, respectively, Table 2). The summed standardized values of the immunoreactive level of GLUT-1 and GLUT-3 and the differentiation grade correlated significantly with the SUV (r=0.47, p=0.05), which implies that these three parameters together form the strongest combination of variables to determine the extent of FDG accumulation. 4. Discussion The present study shows that the degree of FDG accumulation in the primary site of early stage NSCLC is mainly determined by tumor histology and the combination of the expression level of the glucose membrane transporters, GLUT-1 and GLUT-3 and tumor cell differentiation. This indicates that sufficient FDG uptake capability (reflected by GLUT-1 and GLUT-3) is relevant for detection of NSCLC by FDG-PET. Mamede et al. [32] and Higashi et al. [35] found a statistically significant correlation between SUV and GLUT-1 overexpression. Marom et al. [36], however, only observed a borderline associations between SUV and GLUT-1 and GLUT-3 expression. They concluded that the expression of these transporters alone did not affect FDG uptake in early stage NSCLC. Chung et al. [37] and Brown et al. [38] did not find any statistically significant correlation. Differences in results between above-mentioned studies can be explained by differences in antibodies and detection methods used or differences in study population. More importantly, special attention should be paid on the method of quantification of biomarkers. In the present study, only membranous GLUT expression was scored because this is the location of biologically active GLUT-1 and -3, while some other studies also included intracellular GLUT-expression. Furthermore, the present study showed a relationship between FDG uptake and histopathology of the tumor, as the SUV was significantly higher in squamous cell carcinomas compared to adenocarcinomas or large cell carcinomas. This observation is in line with results of several other studies [32], [35], [38], [39], [40]. These studies also found a significant association between GLUT-1 expression and histological tumor type and between SUV and tumor differentiation. Poorly differentiated tumors showed higher FDG uptake than well-differentiated tumors [32], [35]. The only study that could not confirm these results is the study of Marom et al. [36]. Combining these results with studies on the prognostic value of FDG-PET in NSCLC [29], [40], [41], [42], [43], [44], [45], [46] it appears that more aggressive neoplasms or neoplasms with poorer prognosis, show higher levels of GLUT-1 expression on the cell membrane of tumor cells and thus demonstrate a higher level of FDG accumulation. This could explain why NSCLCs with high FDG accumulation in the primary tumor had a poorer prognosis than NSCLCs with low FDG uptake. The GLUT-1 membrane transporter appears to be a very important rate-limiting step of FDG uptake in primary lung cancer cells. Thus, overexpression of GLUT-1 may have an important role in the survival of cancer cells by promoting adequate energy supply to support their high metabolism and faster growth in an often less-than-ideal physiological environment, a hypothesis that is also supported by the study of Younes et al. [19]. The results of the present study (Table 2 and Fig. 3), also suggested that the expression level of all three HK isoforms might be related to the extent of necrosis in the tumor. This positive correlation, might be explained by the findings of Yasuda et al., who reported that HK protein expression is localized in cancer cells near hypovascular or necrotic areas and that HIF-1 alpha protein expression, induced by chronic hypoxia due to poor vascularization, is positively correlated with HK-II expression [47]. Upregulation of HK may allow cancer cells to maintain glucose metabolism in the hypoxic environment. Mamede et al. [32] found a significant correlation between SUVs and the expression level of HK-II. Besides, they found that poorly differentiated adenocarcinomas showed higher HK-II expression and higher FDG uptake than well-differentiated adenocarcinomas. In the present study such relationship was not observed, possibly due to the limited number of patients in our study. Altogether it appears that the expression of GLUT-transporters at the cell membrane and not expression in cytoplasmic granules may be responsible for active glucose transport, that FDG uptake as well as GLUT-1 expression may be higher in squamous cell carcinomas compared with adenocarcinomas and large cell carcinomas. GLUT-1 expression, as well as FDG uptake, appears to be higher in poorly differentiated tumors. The present study, tried to unravel the complex molecular mechanisms and factors that regulate FDG uptake. A better understanding of the biological mechanisms that are involved in glucose transport, glucose metabolism and FDG accumulation could not only lead to better interpretation of FDG-PET as a promising noninvasive prognostic marker, but could also be helpful in the development of future targets for novel therapeutic interventions [48], [49]. 5. Conclusion The present study supports the hypothesis that overexpression of GLUT-1 in combination with overexpression of GLUT-3 and tumor cell differentiation determine the extent of FDG accumulation and that squamous cell carcinomas accumulate more FDG than adenocarcinomas or large cell carcinomas. Acknowledgments This study was funded with internal resources. The funding source had no involvement in study design and conduct, in the collection, management, analysis, and interpretation of data, in the writing of the report or in the decision to submit the paper for publication. The authors declare that none of them have a conflict of interest. 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[49]. [49]Ishikawa N, Oguri T, Isobe T, Fujitaka K, Kohno N. SGLT gene expression in primary lung cancers and their metastatic lesions. Jpn J Cancer Res. 2001;92:874–879. MEDLINE a Department of Nuclear Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands b Department of Pathology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands c Department of Medical Technology Assessment, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands d Department of Cardio-Thoracic Surgery, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands  Corresponding author at: Department of Nuclear Medicine (internal postal code 444), Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. Tel.: +31 24 3614048; fax: +31 24 3618942.
PII: S0169-5002(06)00465-X doi:10.1016/j.lungcan.2006.08.018 © 2006 Elsevier Ireland Ltd. All rights reserved. | |
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