Journal of Thoracic Oncology:
Putative Stem Cell Markers in Non–Small-Cell Lung Cancer: A Clinicopathologic Characterization
Sterlacci, Willam MD*; Savic, Spasenija MD†; Fiegl, Michael MD‡; Obermann, Ellen MD†; Tzankov, Alexandar MD†
*Institute of Pathology, Klinikum Bayreuth, Bayreuth, Germany; †Institute of Pathology, University Hospital Basel, Basel, Switzerland; and ‡Department of Internal Medicine, Division of Hematology and Oncology, Medical University Innsbruck, Austria.
Drs. Obermann and Tzankov share senior authorship of this article.
Disclosure: The authors declare no conflict of interest.
Address for correspondence: Willam Sterlacci, MD, Institute of Pathology, Klinikum Bayreuth, Preuschwitzerstrasse 101, 95444 Bayreuth, Germany. E-mail: email@example.com
Introduction: The cancer stem cell (CSC) theory postulates the existence of a distinct population of undifferentiated cells responsible for tumor initiation and maintenance. CSCs may be naturally resistant to the cytotoxic effect of radio-chemotherapy because of slow cell cycling, lower proliferation, and increased expression of DNA repair and antiapoptosis genes. To date, a universal marker for CSCs has not been identified. Proposed CSC markers are expressed both by cancer cells as well as by benign stem cells. Although many putative CSC markers exist, a precise characterization for non–small-cell lung cancer (NSCLC) is lacking.
Methods: We explored the expression of multiple alleged stemness associated markers in 371 surgically resected NSCLCs. Extensive clinical data and a postoperative follow-up period of up to 15 years enabled detailed clinicopathological correlations. ABCG5, ALDH1, CD24, CD44, CD133, CD166, epithelial cell adhesion molecule epitopes (ESA, MOC-31, Ber-EP4), nestin, OCT4, and sex-determining region Y-box 2 were analyzed immunohistochemically by using a standardized tissue microarray platform.
Results: Sex-determining region Y-box 2, CD44, ABCG5, ALDH1, and nestin were associated with poorer tumor differentiation and/or an increased proliferation index. ALDH1, CD44, and SOX2 were frequently found in squamous cell carcinoma, whereas CD24, CD166, and epithelial cell adhesion molecule markers were encountered in adenocarcinomas. CD44 expression was an independent marker associated with better overall survival in squamous cell carcinoma and Ber-EP4 was associated with tumor recurrences.
Conclusion: The expression and prognostic significance of CSC markers obviously varies depending on histologic NSCLC subtype. Importantly, our findings suggest that CD44 and Ber-EP4 may be promising for ongoing targeted therapies in specific NSCLC subgroups.
The cancer stem cell (CSC) theory postulates the existence of a distinct population of undifferentiated cells responsible for tumor initiation and maintenance.1 The existence of CSCs was first proven in acute myeloid leukemia, and more recently in various other neoplasms including glioblastoma, melanoma, and epithelial cancers.2–4 CSCs have the capacity for self-renewal, multipotency, and unlimited proliferation. CSCs may be naturally resistant to the cytotoxic effect of radio-chemotherapy because of slow cell cycling, lower proliferation, and increased expression of DNA repair and antiapoptosis genes.5 These traits also characterize embryonic stem cells, thus suggesting probable overlap in the molecular signature between embryonic stem cells and CSCs.6 Various alleged stem cell markers have been used for CSC identification and isolation, although detailed studies with phenotypic correlation are lacking. CD133 (prominin-1), a five-transmembrane glycoprotein, was initially described as a marker specific for human stem cells and their tumoral counterparts.7 However, it is a matter of debate whether CD133 positive cells truly represent the ultimate tumorigenic population, apart from objective difficulties of staining specificity and interpretation.8–10 The aldehyde dehydrogenase (ALDH) family represents cytosolic isoenzymes responsible for oxidizing intracellular aldehydes, contributing to the oxidation of retinol to retinoic acid in early stem cell differentiation.11 CSCs express metabolic enzymes such as ALDH1, which confer resistance to cyclophosphamide in normal stem cells.5 Octamer binding transcription factor 4 (OCT4) belongs to the family of pituitary-specific positive transcription factor 1, Octamer transcription factor proteins 1 and 2, neural Unc (uncoordinated protein)-86 transcription factor from Caenorhabditis elegans (POU)-domain transcription factors involved in regulation of cell growth and differentiation. Its expression is normally confined to pluripotent cells of the developing embryo but OCT4 also plays a crucial role in maintaining CSC characteristics and resistive properties.12 Another transcriptional factor, sex-determining region Y-box 2 (SOX2), also provides key signals for achieving characteristics of stem cells.13 CD44, a cell-surface extracellular matrix receptor is commonly used as a CSC marker as well. CD44 can have multiple signaling functions (proliferation, apoptosis, survival, migration, differentiation), which depend on the cell type it is expressed on (embryonic, progenitor, cancer).5 CD24 is a cell surface protein molecule functioning in cell–cell and cell–matrix interactions, thus playing a role in cell adhesion and metastasis.14 Its role as a cancer stem cell marker remains ambiguous, although CD24−/CD44+ tumor cells are often considered as CSCs, especially in breast cancer.15 Nestin is known as a stem cell marker as well as a novel angiogenesis marker of neovascularization and epithelial cell adhesion molecule (EpCAM) has also been reported as part of the signature of cancer-propagating cells in numerous solid tumors and of normal progenitor and stem cells.16,17 CD166, also known as activated leukocyte cell adhesion molecule, has been identified as a cell surface marker of certain hematopoietic progenitor cells as well as of pluripotent mesenchymal stem cells and is frequently considered a colorectal CSC marker.18–20 The ABCG5 protein is a member of the ATP-binding cassette (ABC) subfamily G, which plays a role in the efflux transport of sterols and is thus involved in the development of resistance because of reduction of anticancer agents in cancer cells.21,22 In colorectal cancer overexpression of EpCAM with ABCG5 has been observed and was associated with poor prognosis.23 Furthermore, recent findings demonstrate that the two novel concepts, epithelial mesenchymal transition (EMT) and CSCs, have merged in cancer biology.24 Studies show that EMT cells (e.g., epithelial cells with loss of E-cadherin expression) acquire stem cell characteristics, that maintenance of the stem cell state depends on continuous EMT-inducing signals, and that signaling pathways involved in stemness also act as potent EMT inducers.24
Proposed CSC markers show overlapping expression on other cancer cells and normal stem cells.25 Although CSCs are typically present at very low levels, eradicating them could have high potential to more effectively treat tumors or remove residual tumor cells left after standard therapies, which bear a high risk for disease recurrence and metastasis. The identification and validation of CSC antigens for the generation of therapeutic antibodies may be a crucial factor, but is still in its infancy. Especially in lung cancer, one of the worldwide leading causes of cancer morbidity and mortality, CSCs have not been studied as intensively as in other cancers. Therefore, we aimed to explore the expression of multiple stemness associated factors in a well-documented cohort of surgically resected non–small-cell lung cancer (NSCLC) patients and to perform a correlative analysis with clincopathological parameters.,26
MATERIALS AND METHODS
Patients and Tissue Sampling
The archival samples were derived from 371 NSCLC patients with radical surgical resection in curative intent between 1992 and 2004 and diagnosed at the Institute of Pathology, Medical University of Innsbruck.27 Carcinoids were excluded from this analysis. Cases were selected only based on tissue preservation. Hematoxylin and eosin stained slides from all available specimens were initially reclassified by two pathologists (WS and AT) without knowledge of patient data, according to the current (2004) World Health Organization classification of tumors of the lung as described previously.40 For the classification of adenocarcinomas (ACA) and distinguishing ACA from squamous cell carcinomas (SCC) and large cell carcinomas (LCC), the recently published multidisciplinary guidelines of the International Association for the Study of Lung Cancer, American Thoracic Society and European Respiratory Society were applied.28 Tumor differentiation was graded as well, moderate, or poor. The clinical information was documented within the Twelve Years Retrospective of Lung Cancer survey, a project aiming to analyze various features of a large number of lung cancer patients.29,30 Approval for data acquisition and analysis was obtained from the local Institutional Review Board, that is, the Ethics Committee of the Medical University of Innsbruck.
Tissue Microarray Construction
Tumor material consisted of paraffin-embedded tissue after fixation in 10% neutral buffered formalin. The tissue microarray (TMA) was constructed as previously described.27 The first sections were stained by hematoxylin and eosin to confirm validity, the remaining sections were used for immunohistochemistry.
The primary antibodies and their applications are shown in Table 1. Staining protocols were followed according to the recommendation of the respective manufacturer. Immunohistochemistry was performed using the automated staining system Benchmark XT (Roche/Ventana Medical Systems, Tucson, AZ), except for ABCG5, CD133, CD166, and SOX2, which were incubated using the automated staining system Bond-maX (Leica Biosystems, Newcastle, United Kingdom). Positive control tissue for E-cadherin, Ber-EP4, epithelial-specific antigen (ESA), and MOC-31: skin and skin appendages; for SOX2 and OCT4: embryonal carcinoma; for CD24: Merkel cell carcinoma and an adenocarcinoma of the papilla Vateri; for nestin: gastrointestinal stromal tumor; for CD166: invasive ductal carcinoma of the breast; for CD44: diffuse large B-cell lymphoma; for ALDH1: ductal carcinoma of the pancreas; and for ABCG5: colon carcinoma.
Only spots containing at least 20 vital tumor cells were evaluated. If all four spots of a case did not meet this criterion it was excluded. Tumor cells were scored independently by two pathologists (WS, SS, EO, or AT) to study agreement between observers. The percentage of positively stained cells with clearly visible strong or moderate staining intensities, including staining localization was noted for each spot, followed by the calculation of the arithmetic mean value. The median percentage of positively staining tumor cells for each marker was chosen as the cutoff value for determining positive and negative cases, because the determination of cutoff values by receiver operating characteristic (ROC) analysis is less relevant in this setting.31
The degree of agreement between observers was evaluated by interclass correlation coefficients, using reliability Cronbach’s alpha analysis. Correlation analysis of clinicopathological and immunohistochemical parameters was performed using the Spearman test corrected for multiple testing, considering p values of 0.016 or lesser as significant. In addition, for the three major histology types (ACA, SCC, LCC), the mean percentage of positively stained cells was compared, and markers with significant distribution differences corrected for multiple testing (p valueANOVA ≤0.016) were further analyzed using the Kruskall–Wallis H test. Kaplan–Meier curves were calculated for survival estimates and a log rank statistic used to determine differences between groups; multivariable analysis was performed using the Cox regression model; p values less than 0.05 were considered significant. Two-sided tests were used throughout. Statistical calculations were performed using SPSS 19.0 software (SPSS, Chicago, IL).
Histopathology and Patient Characteristics
Histological subtypes consisted of 215 ACA, 123 SCC, 22 LCC (including 8 neuroendocrine LCC), eight adenosquamous carcinomas, two sarcomatoid carcinomas, and one mucoepidermoid carcinoma. Patient characteristics are presented in detail in Table 2.
Cronbach’s alpha for interobserver reproducibility of the immunohistochemical markers was excellent (highest α=1 for OCT4, lowest α=0.78 for ALDH1). Intratumoral staining heterogeneity was noted for some markers, however, only in a few tumors for each stain and this observation was not statistically significant. Quantitative and qualitative immunohistochemical data are shown in Table 3 and Figure 1.
The observed staining patterns in detail were: aldehyde dehydrogenase (ALDH1), ABCG5, and nestin: cytoplasmic; OCT4: nuclear and cytoplasmic (unspecific and not taken into account); SOX2: nuclear; cluster of differentiation (CD)133: cytoplasmic; CD24, CD166, CD44, E-cadherin, ESA, MOC-31, and Ber-EP4: membranous, some also cytoplasmic. The mean percentage of stained cells according to main histologic subtype is shown in Table 3. SOX2, CD44, and ALDH1 were more frequently found among SCC and CD24; CD166 and the EpCAM markers (Ber-EP4, MOC-31, ESA) were more often positive in ACA.
Correlations between Variables
All significant results of the correlation analysis are demonstrated in detail in Table 4. SOX2, CD44, ABCG5, ALDH1, and nestin were associated with poorer tumor differentiation and/or an increased proliferation index, whereas CD24 was associated with better tumor differentiation. E-cadherin expression correlated with the presence of the ACA-associated markers Ber-EP4, MOC-31, ESA, CD24 (as well as thyroid transcription factor 1 (TTF1) and cytokeratin (CK) 7; data not shown) and with better tumor differentiation and showed a negative correlation with the SCC-associated markers SOX2 and CD44 (as well as p63 and CK5/6; data not shown). Patients with recurrent disease more abundantly expressed Ber-EP4 (p=0.003); which in subgroup analysis was apparent for SCC (p=0.004) but not for ACA (p=0.585). Disease stage (pUICC) showed no correlation with any of the analyzed CSC markers. This was also the case for the individual T, N, and M parameters (data not shown). As described above, ACA were classified according to the multidisciplinary guidelines of the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society.28 The different ACA subtypes (lepidic, acinary, papillary, micropapillary, and solid) did not correlate with the analyzed markers of stemness. Staining results also remained unaffected when the ACA were grouped according to tumor grade, which is based on architecture and provides higher case numbers per group (lepidic: grade 1, acinary and papillary: grade 2, micropapillary and solid: grade 3; data not shown).
Regarding oncogenic driver mutations in NSCLC, we correlated our findings with the expression of mesenchymal epithelial transition factor (MET), considering MET expression in 50% or more of tumor cells as MET positive. Of 324 evaluable cases, 57 (17.6%) were MET positive and three cases showed additional MET gene amplification. Expression of MET correlated with expression of ABCG5 (correlation coefficient: 0.191; p=0.001) and showed a negative correlation with SOX2 (correlation coefficient: −0.165; p=0.003). Analysis of EGFR or KRAS mutation was not performed here because the tumor specimens consisted of TMA material. However, results concerning epidermal growth factor receptor (EGFR) protein expression and gene status were obtained. EGFR expression correlated with the expression of CD44 (correlation coefficient: 0.190; p≤0.001) and showed a negative correlation with CD166 (correlation coefficient: −0.161; p=0.003). Amplification of EGFR showed a negative correlation with ABCG5 (correlation coefficient: −0.201; p=0.004).
Among the multitude of variables analyzed in this study, none were associated with clinical outcome for the entire cohort. When analyzed among the histological subgroups, CD44 positivity was a favorable prognostic marker for SCC and nestin positivity was an unfavorable prognostic marker for ACA (Fig. 2A and B). Stratified according to pUICC stage, the only significant finding was shorter overall survival for patients with CD166 positive tumors in pUICC stage I (p=0.042). When all significant parameters by univariable analysis (pUICC stage, age, sex, Ki-67 index, CD44 for SCC, and nestin for ACA) were tested by multivariable analysis (for the entire cohort, as well as separately for the major histological subtypes), the only independent CSC marker was CD44 positivity indicating a better overall survival for SCC (p=0.01; hazard ratio: 1.870; 95% confidence interval: 1.162–3.008).
The phenotype CD24−/CD44+ did not show a significant difference in overall survival for the entire cohort when compared with the CD24+/CD44− population. However, when stratified according to histology, ACA displaying the putative CSC signature CD24−/CD44+ had a significantly shorter overall survival than CD24+/CD44− ACA (p=0.018; Fig. 2C), but this constellation was not an independent factor, when calculated by multivariable analysis as described above. The groups of cases either CD24+/CD44− or CD24−/CD44+ were further stratified according to positive or negative Ber-EP4 expression. Ber-EP4 expression did not have a significant effect on overall survival (OS) among these groups, which was also the case when only ACA were analyzed, respectively, (results not shown).
We analyzed in situ expression of various proteins commonly considered as CSC markers in a large cohort of NSCLC specimens and found correlations among each other, as well as associations between CSC markers and clinical and pathological features.
The well-known association of antibodies recognizing different EpCAM epitopes (e.g., Ber-EP4, MOC-31, and ESA) with ACA histology was also apparent in our study. Among these, Ber-EP4 seems to be the most relevant. In addition to information on possible stemness properties of tumors, according to our data, Ber-EP4 also delivers prognostic information because patients with recurrent SCC more abundantly expressed the epitope recognized by this antibody. CD24 and CD166 were more frequently expressed in ACA than in SCC. CD166 is often reported as a CSC marker for colorectal cancer, however, data concerning NSCLC are lacking. Only few studies exist regarding CD24 and NSCLC, which also describe a correlation between CD24 expression and ACA histology.14,32 Interestingly, these authors found CD24 to be a marker of poor prognosis, which could not be confirmed in our comparably large group of patients over a follow-up period of up to 15 years. However, the probable stem cell phenotype CD24−/CD44+ was indeed associated with adverse outcome for ACA, which has been shown for other tumors, especially breast cancer.33 Expression of CD44, SOX2, and ALDH1 was more common in SCC. This has been described for SOX2, but comparable data regarding ALDH1 are lacking.34,35 One group showed an increased expression of ALDH1 in NSCLC compared with small-cell lung cancer and also postulated an association with malignant transformation in ACA.36 Others have found that expression of ALDH1 is associated with inferior prognosis, which was not the case in our cohort.37 ALDH1 is emerging as a possible target to eliminate cancer-initiating cells and there are promising efforts in vitro and in vivo showing that ALDH1-directed immunotherapy can inhibit tumor growth and metastasis and prolong survival.38 CD44 has repeatedly been associated with SCC, which is also confirmed by our results.39,40 CD44 expression has also been reported as a marker for prognosis in ACA, although with conflicting results, suggesting better as well as worse prognosis.39,40 CD44 as a sole marker was not associated with overall survival in our group of ACA, but was of significant prognostic relevance (poor survival) in the context of CD24 negativity, indicating the importance of multiple-marker profiling; however, increased CD44 expression was an indicator of better prognosis for SCC, even in multivariate analysis. Importantly, CD44 is a potential target for stem cell–directed cancer therapy. Various microRNA forms have been shown to target CD44, thus inhibiting clonogenic expansion, tumor regeneration, and metastasis as well as suppressing tumorigenicity and multidrug resistance in solid cancers.41,42 Our data indicate its potential role in NSCLC as a target for CD24−/CD44+ ACA to improve survival. The only single CSC marker associated with prognosis for ACA was nestin, which correlated with decreased survival, but was not an independent prognostic factor. For the entire cohort, CSC markers showed no association with prognosis. CSC markers were also not associated with tumor stage (entire cohort as well to the major histologic subtypes). Ber-EP4 was found to correlate with recurrent disease in SCC, which has not been reported to date and may represent a marker for biological tumor aggressiveness at diagnosis. At the moment comparative studies are lacking, but we hope our work will prompt further research to clarify the role of Ber-EP4 for tumor aggressiveness. Antibodies directed against EpCAM are already being used for immunotherapeutic anticancer approaches and a clinical benefit in the treatment of malignant ascites associated with EpCAM-positive carcinomas is well known.43 CD166, which has been linked to prognosis in colorectal cancer, was associated with decreased overall survival in our group only for patients with stage I disease, independent of histology.44 The frequently postulated stem cell signature for breast cancer, CD24−/CD44+, was analyzed here and was found, as already mentioned, to be a negative prognostic constellation for ACA, when compared with CD24+/CD44− tumors. This is in accordance with various reports of CD24−/CD44+ tumors with poor prognosis for breast cancer.45,46
CD133 has been used extensively to identify stem cells in various cancers, although CD133 negative tumor cells are also capable of tumor initiation and CD133 can be present in normal epithelial tissue as well.8,47 For NSCLC some authors have therefore suggested that CD133 should be evaluated in combination with other markers of stemness.48,49 Overall, the results for CD133 and NSCLC are very diverse and often conflicting, possibly because of poorly performing antibodies or poor preservation of antigens after formalin fixation. Inconsistent CD133 detection when using different primary CD133 antibody clones has also been observed.9 Our analyzed cases all expressed CD133, although showing a cytoplasmic staining pattern and therefore probably not specific for a membranously located protein. Others have reported CD133 negativity in all their analyzed NSCLC cases.39,50 These findings together with its uncertain biological role render CD133 a doubtful marker of stemness and acquired data should be interpreted critically.
Decreased expression of E-cadherin, which is implicated in the process of EMT and has been associated with stem cell characteristics, correlated with the expression of CD44, SOX2, and higher tumor grade, as well as loss of CD24 and EpCAM markers. Less-differentiated tumors more frequently expressed CD44, SOX2, and nestin, whereas CD24 was associated with better tumor differentiation. Results for Ki-67 levels were similar, showing a higher proliferation index for tumors with increased expression of CD44 and SOX2, which was also noticed for ALDH1 and ABCG5. Thus, various parameters postulated as CSC markers are also linked to tumor differentiation and proliferation, characterizing biological aggressiveness.
Although TMA data may be regarded as possibly not representative for the whole tumor sample, TMA technique offers an ideal method to evaluate a large number of cases. Compared with standard viewing of slides, this approach reduces staining variations and minimizes observer differences because (1) all samples are processed and evaluated in 1 day, which minimizes biases resulting from staining variability and daily variations in the gaging of the observer, and (2) interpretation of immunostains is based on the findings within a well-defined small area of well-preserved tissue (and not immunohistochemical hot spots) in which absolute cell counts can be easily assessed to determine the percentage of positively stained cells.51 Quadruplicate cores, as analyzed here, improve accuracy compared with the usual duplicate core method and reduce microheterogeneity biases to a negligible minimum.52
Acknowledged oncogenic driver mutations (e.g., EGFR, KRAS, anaplastic lymphoma kinase 1 [ALK1], MET) play an important role in the biology and treatment strategies of NSCLC, especially for ACA. The present study focuses on a clinicopathological characterization of alleged CSC markers in NSCLC, which is currently lacking and may provide a basis for further studies. Particularly the evaluation of oncogenic driver mutations in NSCLC in regard to CSC signatures is of interest and should be examined in greater detail in future studies.
In conclusion, the issue of identifying CSC seems promising, especially for future targeted therapies; however, the importance of the various implicated markers obviously differs depending on tumor entity, and even within a single tumor type reported findings are often contradictory. To date, a universal marker or combination of markers to reliably define CSC is lacking. Our findings provide further evidence that in NSCLC, SCC and ACA have distinct expression profiles regarding commonly considered CSC markers, the former more commonly expressing CD44 and the latter nestin as well as showing the putative CSC phenotype CD24−/CD44+. In addition, CSC markers are frequently associated with tumor differentiation and proliferation index. Importantly, CD44 may play a special role for prognosis especially in the context of CD24. Our results show that increased expression of CD44 is an independent indicator of increased overall survival for patients with SCC. CD24−/CD44+ ACA were associated with an adverse outcome.
This study was partially supported by the “Verein für Tumorforschung.”
1. Pardal R, Clarke MF, Morrison SJ. Applying the principles of stem-cell biology to cancer. Nat Rev Cancer. 2003;3:895–902
2. Bonnet D, Dick JE. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med. 1997;3:730–737
3. Schatton T, Murphy GF, Frank NY, et al. Identification of cells initiating human melanomas. Nature. 2008;451:345–349
4. Dalerba P, Dylla SJ, Park IK, et al. Phenotypic characterization of human colorectal cancer stem cells. Proc Natl Acad Sci U S A. 2007;104:10158–10163
5. Deonarain MP, Kousparou CA, Epenetos AA. Antibodies targeting cancer stem cells: a new paradigm in immunotherapy? MAbs. 2009;1:12–25
6. Hassan KA, Chen G, Kalemkerian GP, Wicha MS, Beer DG. An embryonic stem cell-like signature identifies poorly differentiated lung adenocarcinoma but not squamous cell carcinoma. Clin Cancer Res. 2009;15:6386–6390
7. Ricci-Vitiani L, Lombardi DG, Pilozzi E, et al. Identification and expansion of human colon-cancer-initiating cells. Nature. 2007;445:111–115
8. Shmelkov SV, Butler JM, Hooper AT, et al. CD133 expression is not restricted to stem cells, and both CD133+ and CD133- metastatic colon cancer cells initiate tumors. J Clin Invest. 2008;118:2111–2120
9. Hermansen SK, Christensen KG, Jensen SS, Kristensen BW. Inconsistent immunohistochemical expression patterns of four different CD133 antibody clones in glioblastoma. J Histochem Cytochem. 2011;59:391–407
10. Bidlingmaier S, Zhu X, Liu B. The utility and limitations of glycosylated human CD133 epitopes in defining cancer stem cells. J Mol Med (Berl). 2008;86:1025–1032
11. Yoshida A, Hsu LC, Davé V. Retinal oxidation activity and biological role of human cytosolic aldehyde dehydrogenase. Enzyme. 1992;46:239–244
12. Karoubi G, Gugger M, Schmid R, Dutly A. OCT4 expression in human non-small cell lung cancer: implications for therapeutic intervention. Interact Cardiovasc Thorac Surg. 2009;8:393–397
13. Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567–582
14. Lee HJ, Choe G, Jheon S, Sung SW, Lee CT, Chung JH. CD24, a novel cancer biomarker, predicting disease-free survival of non-small cell lung carcinomas: a retrospective study of prognostic factor analysis from the viewpoint of forthcoming (seventh) new TNM classification. J Thorac Oncol. 2010;5:649–657
15. Jaggupilli A, Elkord E. Significance of CD44 and CD24 as cancer stem cell markers: an enduring ambiguity. Clin Dev Immunol. 2012;2012:708036
16. Mokrý J, Cízková D, Filip S, et al. Nestin expression by newly formed human blood vessels. Stem Cells Dev. 2004;13:658–664
17. Gires O, Klein CA, Baeuerle PA. On the abundance of EpCAM on cancer stem cells. Nat Rev Cancer. 2009;9:143; author reply 143
18. Uchida N, Yang Z, Combs J, et al. The characterization, molecular cloning, and expression of a novel hematopoietic cell antigen from CD34+ human bone marrow cells. Blood. 1997;89:2706–2716
19. Arai F, Ohneda O, Miyamoto T, Zhang XQ, Suda T. Mesenchymal stem cells in perichondrium express activated leukocyte cell adhesion molecule and participate in bone marrow formation. J Exp Med. 2002;195:1549–1563
20. Levin TG, Powell AE, Davies PS, et al. Characterization of the intestinal cancer stem cell marker CD166 in the human and mouse gastrointestinal tract. Gastroenterology. 2010;139:2072–2082.e5
21. Hirata T, Okabe M, Kobayashi A, Ueda K, Matsuo M. Molecular mechanisms of subcellular localization of ABCG5 and ABCG8. Biosci Biotechnol Biochem. 2009;73:619–626
22. Cole SP, Bhardwaj G, Gerlach JH, et al. Overexpression of a transporter gene in a multidrug-resistant human lung cancer cell line. Science. 1992;258:1650–1654
23. Hostettler L, Zlobec I, Terracciano L, Lugli A. ABCG5-positivity in tumor buds is an indicator of poor prognosis in node-negative colorectal cancer patients. World J Gastroenterol. 2010;16:732–739
24. Liu J, Brown RE. Immunohistochemical detection of epithelialmesenchymal transition associated with stemness phenotype in anaplastic thyroid carcinoma. Int J Clin Exp Pathol. 2010;3:755–762
25. Yang YM, Chang JW. Current status and issues in cancer stem cell study. Cancer Invest. 2008;26:741–755
26. Sterlacci W, Fiegl M, Hilbe W, et al. Deregulation of p27 and cyclin D1/D3 control over mitosis is associated with unfavorable prognosis in non-small cell lung cancer, as determined in 405 operated patients. J Thorac Oncol. 2010;5:1325–1336
27. Sterlacci W, Fiegl M, Hilbe W, Auberger J, Mikuz G, Tzankov A. Clinical relevance of neuroendocrine differentiation in non-small cell lung cancer assessed by immunohistochemistry: a retrospective study on 405 surgically resected cases. Virchows Arch. 2009;455:125–132
28. Travis WD, Brambilla E, Noguchi M, et al. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol. 2011;6:244–285
29. Fiegl M, Hilbe W, Auberger J, et al. Twelve-year retrospective analysis of lung cancer: the TYROL Study: daily routine in 1,424 patients (1995–2006). J Clin Oncol. 2008;26:abstract 19063
30. Hilbe W, Aigner K, Dittrich C, et al. [Expert recommendations 2006 on the rationale for second-line therapy for non-small cell bronchial neoplasms]. Wien Klin Wochenschr. 2007;119:259–266
31. Tzankov A, Zlobec I, Went P, et al. Prognostic immunophenotypic biomarker studies in diffuse large B cell lymphoma with special emphasis on rational determination of cut-off scores. Leuk Lymphoma. 2010;51:199–212
32. Kristiansen G, Schlüns K, Yongwei Y, Denkert C, Dietel M, Petersen I. CD24 is an independent prognostic marker of survival in nonsmall cell lung cancer patients. Br J Cancer. 2003;88:231–236
33. Perrone G, Gaeta LM, Zagami M, et al. In situ identification of CD44+/CD24- cancer cells in primary human breast carcinomas. PLoS One. 2012;7:e43110
34. Sholl LM, Long KB, Hornick JL. Sox2 expression in pulmonary non-small cell and neuroendocrine carcinomas. Appl Immunohistochem Mol Morphol. 2010;18:55–61
35. Yuan P, Kadara H, Behrens C, et al. Sex determining region Y-Box 2 (SOX2) is a potential cell-lineage gene highly expressed in the pathogenesis of squamous cell carcinomas of the lung. PLoS One. 2010;5:e9112
36. Patel M, Lu L, Zander DS, et al. ALDH1A1 and ALDH3A1 expression in lung cancers: correlation with histologic type and potential precursors. Lung Cancer. 2008;59:340–349
37. Jiang F, Qiu Q, Khanna A, et al. Aldehyde dehydrogenase 1 is a tumor stem cell-associated marker in lung cancer. Mol Cancer Res. 2009;7:330–338
38. Visus C, Wang Y, Lozano-Leon A, et al. Targeting ALDH(bright) human carcinoma-initiating cells with ALDH1A1-specific CD8+
T cells. Clin Cancer Res. 2011;17:6174–6184
39. Leung EL, Fiscus RR, Tung JW, et al. Non-small cell lung cancer cells expressing CD44 are enriched for stem cell-like properties. PLoS One. 2010;5:e14062
40. Ko YH, Won HS, Jeon EK, et al. Prognostic significance of CD44s expression in resected non-small cell lung cancer. BMC Cancer. 2011;11:340
41. Liu C, Kelnar K, Liu B, et al. The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44. Nat Med. 2011;17:211–215
42. Cheng W, Liu T, Wan X, Gao Y, Wang H. MicroRNA-199a targets CD44 to suppress the tumorigenicity and multidrug resistance of ovarian cancer-initiating cells. FEBS J. 2012;279:2047–2059
43. Simon M, Stefan N, Plückthun A, Zangemeister-Wittke U. Epithelial cell adhesion molecule-targeted drug delivery for cancer therapy. Expert Opin Drug Deliv. 2013;10:451–468
44. Lugli A, Iezzi G, Hostettler I, et al. Prognostic impact of the expression of putative cancer stem cell markers CD133, CD166, CD44s, EpCAM, and ALDH1 in colorectal cancer. Br J Cancer. 2010;103:382–390
45. Idowu MO, Kmieciak M, Dumur C, et al. CD44(+)/CD24(-/low) cancer stem/progenitor cells are more abundant in triple-negative invasive breast carcinoma phenotype and are associated with poor outcome. Hum Pathol. 2012;43:364–373
46. Giatromanolaki A, Sivridis E, Fiska A, Koukourakis MI. The CD44+/CD24- phenotype relates to ‘triple-negative’ state and unfavorable prognosis in breast cancer patients. Med Oncol. 2011;28:745–752
47. Wu Y, Wu PY. CD133 as a marker for cancer stem cells: progresses and concerns. Stem Cells Dev. 2009;18:1127–1134
48. Chen YC, Hsu HS, Chen YW, et al. Oct-4 expression maintained cancer stem-like properties in lung cancer-derived CD133-positive cells. PLoS One. 2008;3:e2637
49. Janikova M, Skarda J, Dziechciarkova M, et al. Identification of CD133+/nestin+ putative cancer stem cells in non-small cell lung cancer. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2010;154:321–326
50. Cui F, Wang J, Chen D, Chen YJ. CD133 is a temporary marker of cancer stem cells in small cell lung cancer, but not in non-small cell lung cancer. Oncol Rep. 2011;25:701–708
51. Tzankov A, Went P, Zimpfer A, et al. Tissue microarray technology: principles, pitfalls and perspectives—lessons learned from hematological malignancies. Exp Gerontol. 2005;40:737–744
52. Camp RL, Charette LA, Rimm DL. Validation of tissue microarray technology in breast carcinoma. Lab Invest. 2000;80:1943–1949
Stem cells; Markers; Immunohistochemistry; Non–small-cell lung cancer
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