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Keywords:

  • GIST;
  • CD133 (prominin-1);
  • KIT;
  • expression profiling;
  • biomarker

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

In gastrointestinal stromal tumors (GISTs), KIT exon 11 deletions are associated with poor prognosis. The aim of this study was to determine the gene expression profiles of GISTs carrying KIT exon 11 deletions and to identify genes associated with poor prognosis. Expression profiling was performed on nine tumors with KIT exon 11 deletions and 7 without KIT exon 11 mutations using oligonucleotide microarrays. In addition, gene expression profiles for 35 GISTs were analyzed by meta-analysis. Expression of CD133 (prominin-1) protein was examined by tissue microarray (TMA) analysis of 204 GISTs from a population-based study in western Sweden. Survival analysis was performed on patients subjected to R0 resection (n = 180) using the Cox proportional hazards model. Gene expression profiling, meta-analysis, and qPCR showed up regulation of CD133 in GISTs carrying KIT exon 11 deletions. Immunohistochemical analysis on TMA confirmed CD133 expression in 28% of all tumors. CD133 positivity was more frequent in gastric GISTs (48%) than in small intestinal GISTs (4%). CD133 positivity was also more frequent in GISTs with KIT exon 11 mutations (41%) than in tumors with mutations in KIT exon 9, platelet-derived growth factor receptor α (PDGFRA), or wild-type tumors (0–17%). Univariate survival analysis showed a significant correlation between the presence of CD133 protein and shorter overall survival (hazard ratio = 2.23, p = 0.027). Multivariate analysis showed that CD133 provided additional information on patient survival compared to age, sex, National Institutes of Health (NIH) risk group and mutational status. CD133 is expressed in a subset of predominantly gastric GISTs with KIT exon 11 mutations and poor prognosis.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract, arising from the interstitial cells of Cajal (ICC).1 The morphological and clinical spectrum of GIST is wide, ranging from small, incidentally detected, entirely benign lesions to large, highly aggressive tumors. The majority of GISTs are sporadic, but some are hereditary and associated with neurofibromatosis type 1 (NF1), the Carney triad, or familiar GIST syndromes. Sporadic GISTs frequently harbor gain-of-function mutations involving KIT2 or platelet-derived growth factor receptor α (PDGFRA),3 which cause constitutive activation of the tyrosine kinase in the absence of ligand. KIT and PDGFRA are homologous tyrosine kinase receptors originating from a common ancestral gene. KIT and PDGFRA mutations in GISTs are mutually exclusive and are important oncogenetic events. Approximately 80% of all GISTs carry KIT mutations located in exons 9, 11, 13 or 17, while 5–8% of GISTs carry mutations in PDGFRA located in exons 12, 14 or 18.4 In approximately 12–15% of the tumors, no mutations in KIT or PDGFRA can be detected.

Three major oncogenic pathways are activated by mutated KIT/PDGFRA, including the STAT pathway, the MAPKinase pathway, and the PI3K/AKT cascade.4 Inhibition of activated KIT or PDGFRA by targeted therapy with the tyrosine kinase inhibitor (TKI) imatinib has dramatically improved the survival of patients with high-risk GIST.5 The median overall survival (OAS) of patients with metastatic GIST in the pre-imatinib era has been reported to be 19 months,6 while the median OAS for this group of patients has increased to more than 50 months after introduction of imatinib treatment.7 About 80% of all GISTs respond to imatinib treatment, which relates to mutational status. Tumors with KIT exon 11 mutations are most responsive (70–85% response rate), while tumors with KIT exon 9 mutations demonstrate an intermediate responsiveness (25–48% response rate). Tumors with KIT exon 13 or 17 mutations or no mutations, respond poorly to imatinib, whereas tumors with PDGFRA exon 18 (D842V) mutations are resistant.4, 8, 9 Although activating mutations in KIT and PDGFRA are identified as primary oncogenetic events, less is known about the genetic and epigenetic alterations during tumor progression. Secondary mutations in KIT or PDGFRA have been identified in patients who have developed imatinib resistance during treatment with the drug.9 Cytogenetic analysis has demonstrated a number of recurrent aberrations in GIST, including −14q, −1p, −22q, −15q, −13q and +5p.10 Loss of 14q occurs in benign and malignant tumors and it is therefore regarded as an early event in tumor formation.11 Using an oncogenetic tree model, three cytogenetic pathways were detected in GIST, initiated by −14q, −1p or −22q.10 The −14q pathway characterized gastric tumors with stable karyotypes and favorable clinical course, while loss of 1p characterized small intestinal GISTs with increased cytogenetic complexity and more aggressive course. The −22q pathway, frequently combined with +8q, −9p and −9q, was associated with shorter disease-free survival. Gene expression profiling is a powerful tool to monitor the molecular changes involved in carcinogenesis and tumor progression. Such profiling may provide new prognostic markers and therapeutic targets. Expression studies on GISTs have identified specific profiles related to tumor site, malignant behavior, and mutational status.12–15 We, and others have previously shown an association between mutational status and prognosis.16–18KIT exon 11 deletions, which are detected with similar frequency in GIST from stomach, small intestine, and large bowel, were associated with short survival. The aim of the present study was to characterize the gene expression profiles of GISTs carrying KIT exon 11 deletions, and to compare them to those of GISTs lacking KIT exon 11 mutations, in order to identify genes involved in tumor progression and genes that might be used to predict outcome. We therefore analyzed the two groups of GISTs with expression microarray and performed a meta-analysis of gene expression data from previously published studies.12, 13 A large number of genes were shown to be differentially expressed in the two tumor groups. We found that CD133 (prominin-1) is highly expressed in GISTs with KIT exon 11 deletions, and we further explored the expression of this protein in a large series of GISTs using tissue microarray (TMA) to confirm the usefulness of CD133 as a biomarker for patient survival.

Material and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Patients and tumor material

For gene expression profiling and quantitative real-time PCR (qPCR), fresh tumor material was obtained from 16 GIST patients who underwent surgery at the Department of Surgery, Sahlgrenska University Hospital, Göteborg, Sweden, 2001–2005. The diagnosis was based on typical histopathology of resected tumors including positive immunohistochemical staining for KIT. Clinico-pathological and genetic data are presented in Table 1. Nine tumors had deletions in KIT exon 11 and 7 tumors had no mutations in KIT exon 11. In the group of tumors lacking KIT exon 11 mutations, two had duplication mutations in KIT exon 9, two had mutations in PDGFRA exon 18, and three had no detectable mutations in KIT exons 9, 11, 13, or 17, or PDGFRA exons 12, 14 or 18 (wild-type (wt) tumors). Tumors with deletions in KIT exon 11 were from stomach (n = 4), small intestine (n = 3), and rectum (n = 2). Tumors with no mutation in KIT exon 11 were from stomach (n = 3) and small intestine (n = 4). Patients with complete tumor resection (R0) had 12 months of adjuvant treatment with imatinib (Gleevec®; Novartis Pharma, Basel, Switzerland) (400 mg/day). Patients with residual tumor after surgery underwent continuous palliative treatment with imatinib (400 mg/day). None of the patients received imatinib treatment at the time of surgery or harvest of tumor material.

Table 1. Clinico-pathological and genetic characterization of patients with GIST analyzed by expression microarray and real time qPCR
  1. M: male, F: female, R: rectum, SI: small intestine, S: stomach, inter.: intermediate risk, s: spindle cell type, e: epithelioid cell type, del: deletion mutation, miss: missense mutation, dupl: duplication mutation, wt: wild-type, Loc: local recurrence of tumor, Prim: primary tumor, L: liver metastasis, DOD: dead of disease, NED: no evidence of disease, AWD: alive with disease, RFS: recurrence-free survival, OAS: overall survival, P: palliative treatment, A: adjuvant treatment.

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For TMA, tumor material from our population-based study of GIST (1983–2001) was retrieved;19 the mutational and survival data have already been published.18 All patients in this series from the pre-imatinib era were only treated surgically for their tumor disease. All tumors had typical histopathology and stained positive for KIT. Cases with mutational data and sufficient paraffin-embedded tumor material were used to construct a TMA block. The TMA block contained material from 204 patients (106 males and 98 females; mean age 68 years, range 25–92 years). In total, 224 paraffin blocks from resected tumors were collected: 202 primary tumors, 17 metastases, and 5 local recurrences. Primary tumors were from stomach (n = 114, 56%), small intestine (n = 75, 37%), colon (n = 7, 4%), rectum (n = 6, 3%), or unknown location (n = 2, 1%). The tumors were classified as very low risk (n = 23, 11%), low risk (n = 63, 31%), intermediate risk (n = 47, 23%) and high risk (n = 71, 35%) according to the National Institutes of Health (NIH) risk consensus.20 The mutational analyses revealed that 66 tumors had KIT exon 11 deletions (32%), 27 had KIT exon 11 missense mutations (13%), 19 had KIT exon 11 duplications (9%), one had a KIT exon 17 missense mutation (0.5%), six had KIT exon 9 duplications (3%), six had PDGFRA mutations (3%), and that 79 tumors were wt (39%). This population based series of GIST contained a higher proportion of wt tumors than reported for other series. For clinico-pathological and mutational data on patients whose material was included in the TMA block, see Supporting Information Table S1. Representative regions of tumor tissue were identified in hematoxylin and eosin stained sections. Tissue cylinders (0.6 mm diameter) were punched from paraffin blocks and brought into recipient paraffin block. Each recipient block contained one punched biopsy from each tumor and was made in duplicate. The validity of the constructed TMA block was confirmed from typical histopathology and positive KIT immunohistochemistry.

Ethics

For the use of clinical materials for research purposes, prior patient's consents and approval from the Regional Ethical Review Board in Göteborg, Sweden, were obtained.

Expression microarray analysis

Fresh tumor material from GISTs with KIT exon 11 deletions (n = 9) and GISTs without mutations in KIT exon 11 (n = 7) were used; the latter group included mutations in KIT exon 9, PDGFRA exon 18, or wt tumors. Total RNA was isolated from biopsies by homogenization with Trizol® Reagent (Invitrogen Life Technologies, CA) followed by RNA purification (RNeasy Mini Kit; Qiagen, CA). Fluorescence-labeled cDNA was synthesized from extracted RNA by reverse transcription using the ChipShot™ Direct Labeling System (Pronto Plus Systems; Corning B.V, Schiphol, Netherlands). Tumor cDNA was labeled with Cy3-dCTP (Amersham BioSciences, Buckinghamshire, UK) and reference cDNA (synthesized from universal human reference RNA (UHRR); Stratagene, CA) was labeled with Cy5-dCTP (Amersham BioSciences).

Labeled cDNA from tumors and reference sample were hybridized to 55K oligonucleotide microarrays. The microarray glass slides, containing more than 26,000 unique probes in duplicate covering the entire human genome, were provided by Swegene DNA Microarray Resource Center, Lund, Sweden. Hybridization was performed in a Corning Hybridization Chamber for 17 hr in a 42°C water bath, followed by post-hybridization washes (Corning). Microarrays were quantified in an Agilent microarray scanner (G2505B; Agilent Technologies, CA) and image processing was carried out using Feature Extraction Software version 7.5 (Agilent Technologies).

Statistical analysis of expression data

Pre-processing and statistical analysis of microarray data were performed in the statistical language R 2.7.2 using the Bioconductor package LIMMA.21 Values from probes printed in duplicate within each array were averaged and the data were then log2-transformed and finally normalized using Lowess normalization.22 The probes were ranked both according to the average log-fold change and the moderated t-statistic. Expression data are available according to the MIAME standard at the Gene Express Omnibus database (http://www.ncbi.nlm.nih.gov/geo/) with accession number GSE14755.

To include more patients in the analysis, we searched the literature and found two other gene expression studies using microarray for tumor samples and with results that include KIT and PDGFRA mutational status.12, 13 From Subramanian et al. (2004),12 we used 7 GISTs with KIT exon 11 deletions and 15 tumors without KIT exon 11 mutations, and from Kang et al. (2005),13 we used 7 GISTs with KIT exon 11 deletions and 6 tumors without KIT exon 11 mutations. Thus, including our present study, a total of 23 GISTs with KIT exon deletions and 28 tumors without KIT exon 11 mutations were included in a meta-analysis. The raw data from Subramanian et al. were analyzed in a way that was analogous to the present study (Lowess normalization, gene-ranking by average log fold-change). For Kang et al., pre-processed log fold-change values were downloaded from http://www.molpathol.org/. To compare the three datasets, we first re-annotated all probes by mapping them to available coding sequences (CDS) at Ensembl (http://www.ensembl.org) using basic local alignment search tool.23 In total, 83% of the probes from the present study, 67% of the probes from the study by Subramanian et al. and 88% of the probes from the study by Kang et al. could be identified (E-value cut-off: 10−100). Once all experiments shared a common annotation, we compared the top 1,000 transcripts according to the average fold change. A list of all genes found in at least two of the three datasets is available in Supporting Information Table S2.

Quantitative real-time PCR (qPCR)

qPCR was performed on the same biopsies as those that were analyzed by expression microarray. RNA was extracted as previously described, but with DNase treatment in addition using DNA-Free™ (Ambion Inc., TX). cDNA was synthesized from extracted RNA using TaqMan® Reverse Transcription Reagents (Applied Biosystems, CA). The PCR assay was performed in 96-well optical plates, using an ABI Prism® 7500 Fast System SDS. The samples were analyzed in triplicate. The cycle threshold (Ct) for target genes and β-actin was determined for each sample. Values were expressed as -ΔCt (Cttarget gene – Ctβ-actin). One-sided non-parametric Wilcoxon-Mann-Whitney tests were used to test for differential expression.

Primers and probes were purchased from Applied Biosystems: Hs01009260_m1 (CD133), Hs00216121_m1 (DOG1), Hs00174029_m1 (KIT), Hs00156373_m1 (CD34), Hs00234422_m1 (MMP2), Hs00171584_m1 (DLK1), Hs00163869_m1 (CA2), Hs00165908_m1 (TGFBI), Hs00181213_m1 (IGFBP5), Hs00171467_m1 (SERPINF1), and TaqMan® β-actin Control Reagent.

Immunohistochemistry

Sections (4-μm thick) from TMA blocks and normal stomach/small intestine were placed on positively charged glass slides, deparaffinized, rehydrated, and subjected to heat-induced antigen retrieval using microwave treatment (Tris-EDTA, pH 9). A mouse monoclonal anti-human CD133/1 antibody (clone AC133; Miltenyi Biotec) directed against the extracellular part of CD133 was used at a dilution of 1:25. This antibody recognizes a glycosylated epitope on CD133 that is preferentially expressed in undifferentiated cells.24 After blocking, bound antibodies were visualized using Dako REAL EnVision + Detection System (DakoCytomation). For further characterization of GIST, sections were stained with antibodies to KIT (CD117, rabbit polyclonal; DAKO), DOG1 (clone K9, mouse monoclonal; Novocastra), CD34 (clone QBEND/10, mouse monoclonal; DAKO), α-SMA (clone 1A4, mouse monoclonal; DAKO), S-100 (rabbit polyclonal; DAKO) and desmin (clone D33, mouse monoclonal; DAKO). The degree of labeling was assessed and scored by two independent observers. Tumor biopsies were categorized as positive when > 10% of the tumor cells were clearly labeled. Immunohistochemical and clinic-pathological data were analyzed by Fisher's exact test and logistic regression.

Survival analysis

OAS and recurrence-free survival (RFS) were documented for all patients included in the TMA analysis and subjected to R0 resection (n = 180). A regression-based survival analysis was performed using the Cox proportional hazards model25 implemented in the survival package in the statistical language R 2.7.2. Patients who died causes other than GIST, or who were alive when the study was ended (2001), were right-censored.26 The model assumptions were tested and found valid for all patients.27 All analyses were adjusted for sex and age. Significant differences in deviance between nested regression models were tested using χ2 tests.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

KIT mutational status in GIST is associated with specific gene expression profiles

Global gene expression profiling was performed on GISTs arranged into two separate groups according to mutational status: tumors with KIT exon 11 deletions and tumors without KIT exon 11 mutations. The analysis showed differentially expressed genes between the two tumor groups, representing a diversity of biological processes including genes related to cell adhesion (CD34, HMCN1, TGFBI), cell motility (CALD1, IGFBP5, CXCL12), cell proliferation (IGFBP5, TGFBI, SERPINF1), and genes involved in the cell cycle (NBL1). Among the differentially regulated genes were previously known markers for GIST, including KIT, DOG1 and CD34, which were up regulated in GISTs carrying KIT exon 11 deletions. Moreover, one highly up regulated gene in tumors with KIT exon 11 deletions was CD133, which has not been described previously in GIST. The 15 most up regulated and 15 most down regulated genes, sorted by fold change, are given in Table 2. A list of the 1,000 most differentially expressed genes is available in Supporting Information Table S3.

Table 2. Differentially expressed genes in GISTs with KIT exon 11 deletions relative to expression in GISTs without mutations in KIT exon 11. The expression microarray data presented relate to the 15 most up regulated genes and 15 most down regulated genes sorted by log2 fold change
  1. Note: Genes with * analyzed by qPCR, see Fig. 1b.

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Meta-analysis confirmed specific gene expression profile in GIST s with KIT exon 11 deletions

Expression data from our GIST material was compared with data from two previously published studies on gene expression profiles of GIST.12, 13 Meta-analysis confirmed that CD133 expression was up regulated in GISTs with KIT exon 11 deletions relative to that in GISTs with no mutations in KIT exon 11. Up regulation of e.g., CD34, KIT, DOG1 and MMP2 and down regulation of e.g., TGFBI, IGFBP5, CA2 and DLK1 in tumors with KIT exon 11 deletions was also confirmed. Trends of expression levels for these genes in meta-analysis are shown in Figure 1a. The complete list of differentially regulated genes from meta-analysis is presented in Supporting Information Table S2.

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Figure 1. Gene expression analysis of GIST. (a) Meta-analysis reveals consistent up and down regulation of the ten selected genes in three independent microarray datasets (Arne et al. (2010) (present study), Kang et al. (2005) and Subramanian et al. (2004)). The combined data comprises whole-genome gene expression measurements from more than 51 patients. Arrow up indicates higher expression and arrow down lower expression in GISTs with KIT exon 11 deletions relative to expression in GISTs without KIT exon 11 mutations. “—” indicates missing genes from the microarrays. A full list of regulated genes from meta-analysis is available in Supporting Information Table S2. (b) Verification of the ten selected genes using qPCR comparing GISTs with KIT exon 11 deletions to GISTs without KIT exon 11 mutations. Dark and light bars shows the differentially expression measured by the microarray and qPCR respectively. The directions of regulation were consistent for all the ten genes, while large differentially expressions were, as expected, underestimated by the microarray. The y-axis represents log2 fold change.

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CD133 is significantly up regulated in GISTs carrying KIT exon 11 deletions

To verify the gene expression profile obtained from the microarray analysis, we performed qPCR analysis of 10 genes shown to be differentially expressed (Table 2 and Fig. 1a). qPCR analysis confirmed up regulation of five genes (CD133, DOG1, CD34, KIT and MMP2) in GISTs with KIT exon 11 deletions relative to GISTs with no mutations in KIT exon 11, and down regulation of five genes (TGFBI, IGFBP5, SERPINF1, CA2 and DLK1) (Figure 1b). Among the verified genes, CD133 showed the highest degree of up regulation (more than four times) in tumors with KIT exon 11 deletions (p = 0.021).

CD133 protein expression in GIST is associated with gastric location and KIT exon 11 mutations, but not to tumor size or risk group

To expand our analysis of CD133 in GIST, we analyzed a separate group of tumors (n = 204) using immunohistochemistry and monoclonal antibodies against a glycosylated epitope on CD133. Positive labeling for CD133 was detected in 55/195 GISTs (28%) included in the TMA block. Labeling was confined to the cell membrane and cytoplasm of tumor cells, with no labeling of the surrounding stroma (Fig. 2). In cases where both primaries and recurrences or metastases were available, all the lesions from the same patient showed a similar CD133-staining pattern. In terms of tumor site, the highest proportion of CD133-positive tumors was found in gastric GIST (correlation p = 3.1×10−11), while CD133-positive tumors were rare in GIST of the small intestine, colon, and rectum. Comparing CD133-labeling and mutational status, we found the highest proportion of CD133-positive tumors in GISTs with KIT exon 11 mutations (41%). Tumors with mutations in KIT exon 9 or 17, PDGFRA exon 12 or 18, or wt tumors had lower proportion of CD133-positive tumors (0–17%). The correlation between positive CD133 staining and presence of KIT exon 11 mutations was significant (p = 1.1 × 10−4), and so was the correlation between positive CD133 staining and KIT exon 11 deletions (p = 1.6 × 10−5). There was no significant association between CD133-labeling in tumors and NIH risk score, tumor size, mitotic count, Ki67-labeling, or histopathological growth patterns (p-values > 0.1). However, there was a positive correlation between CD133-labeling and CD34-labeling (p = 6.2×10−5), and a negative correlation between CD133-labeling and the presence of α-SMA (p = 1.1×10−4). Immunohistochemical analysis of tumor-free stomach and small intestine did not reveal any CD133-staining of normal ICC. Labeling results from our immunohistochemical study are given in Table 3 and Figure 2.

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Figure 2. Immunohistochemical demonstration of CD133 protein in GIST. A TMA including core biopsies of GISTs from 204 patients was analyzed by immunohistochemistry. (a) Overview of TMA-section stained for CD133 by monoclonal antibody AC133. Boxed biopsies are shown in detail in (b). (b) Four biopsies from three patients. Upper biopsies were from a primary gastric GIST (left) and its peritoneal metastasis (right) (case 86, Supporting Information Table S1). This tumor was of high risk type and with a KIT exon 11 deletion. All tumor cells are strongly positive for CD133. Lower left biopsy was from a small intestinal GIST of low risk type, and wild-type for KIT/PDGFRA (case 141, Supporting Information Table S1). This tumor was negative for CD133. Lower right biopsy was from a gastric GIST of low risk type and wild-type for KIT/PDGFRA (case 38, Supporting Information Table S1). This tumor was positive for CD133. (cf) High power micrographs of high risk gastric GIST with KIT exon 11 deletion (case 86) demonstrates strong staining for CD133 (c), CD34 (d), DOG1 (e) and KIT (f).

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Table 3. Expression of CD133, CD34, DOG1 and KIT in GISTs analyzed by immunohistochemistry on tissue microarray (TMA). The data are presented as number of positive tumors in relation to total number of tumors analyzed; the percentage is given in parentheses
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Survival analysis revealed poor outcome in patients with CD133-positive GIST

Survival analysis was performed on patients with R0-resected tumors included in the TMA analysis (n = 180). In the first step, univariate Cox regression analysis adjusted for sex and age was performed for each of the variables CD133, risk group, and mutational status individually. The analysis showed that patients with GIST positive for CD133 had significantly shorter OAS (hazard ratio = 2.27, p = 0.024) and RFS (hazard ratio = 2.23, p = 0.027) than patients with CD133-negative tumors. The Cox regression curve showing survival of GIST patients in relation to CD133 immunostaining is presented in Figure 3. Furthermore, patients in the high-risk group have a significantly shorter survival time (OAS p-value = 3.7 × 10−5, RFS p-value = 2.6 × 10−5). The analysis also showed a significant correlation between short survival and KIT exon 11 deletions (see Fig. 3, OAS p-value = 0.0036, RFS p-value = 0.0033).

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Figure 3. CD133 expression in GIST is associated with short survival. (a) Survival analysis shows that CD133 expression is associated with short survival time (p = 0.024). (b) Survival analysis of mutational status shows differences in survival time. The patients with KIT exon 11 deletion has a significantly shorter survival (p-value = 3.7×10−5). Patients with KIT exon 9 duplications were excluded from the analysis due to low number of observations (n = 5). Curves in both figures were calculated from overall survival of GIST patients operated with R0 resection and estimated by Cox regression adjusted for age and sex. Analogous curves for recurrence-free survival (RFS) are available in Supporting Information Table 4.

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To control for possible confounding effects a multivariate Cox regression analysis was performed including the variables for age, sex, risk group, mutational status, CD34, α-SMA, S-100 and CD133. This analysis demonstrated that age, sex, risk group, and CD133 expression were significantly associated with shorter OAS and RFS (p < 0.05). When CD133 expression was excluded from the regression the error increased significantly (for OAS p = 0.037, and for RFS p = 0.023). This implies that CD133 expression provides additional information regarding patient survival not available in the variables age, sex, risk group, mutational status, CD34, α-SMA and S-100.

Tumors showing CD133 expression has a high prevalence of being located in the stomach and the survival analysis was therefore reiterated for the subgroup of gastric GISTs. In total, there were 106 patients with gastric GISTs and of these were 51 (48%) CD133 positive (Table 3). Univariate analysis performed on these patients showed that CD133 was significantly correlated with short survival time (OAS: hazard ratio = 4.19, p = 0.013, RFS: hazard ratio = 3.93, p = 0.017). In addition, multivariate analysis demonstrated that CD133 and risk score as the only significant variables. When CD133 were removed from the multivariate model, the error increased significantly (OAS p = 0.017, RFS p = 0.022). Hence, there is a significant association between shorter survival and CD133 expression in patients with gastric GISTs. Full details of the survival analysis are available in Supporting Information Table S4.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Besides morphological features, e.g. tumor size, mitotic rate, pleomorphism, high micro-vessel density and tumor necrosis, several molecular events provide prognostic information in GIST, e.g. oncogene amplification, expression of CD26, Pfetin, VEGF, SKP2, and loss of p16 and down regulation of cell cycle inhibitors such as p16INK4A and p27KIP1.4, 15, 28–31 Expression profiling of GIST has identified molecular signatures associated with survival or genotype.32 In this study, we performed expression analysis comparing GISTs carrying KIT exon 11 deletions and GISTs without mutations in KIT exon 11. The rationale for comparing these two tumor groups was the observation that KIT exon 11 deletions are associated with poor survival.16–18 Expression profiling demonstrated a number of differentially expressed genes in the two tumor groups. Due to the limited access to tumor material, we expanded the number of tumors by performing meta-analysis with two additional expression datasets.12, 13 Based on all three studies, we identified a specific gene expression profile in GISTs carrying KIT exon 11 deletions, including up regulation of KIT, DOG1, CD34, CD133 and MMP2. Expression of KIT and DOG1 is well documented in GISTs and both genes are used as sensitive diagnostic markers for this tumor entity. Regulation of DOG1 gene expression in GIST has not been studied, but the regulation of KIT expression by PKC-theta has been demonstrated.33 The activity of PKC-theta in relation to KIT mutational status remains to be determined. CD34, another marker for GIST, is expressed in about 70% of GISTs and is associated with gastric location. CD34 is expressed in a subset of ICC and the differential expression in GIST has been attributed to differences in cellular origin.34 The mechanisms for CD34 regulation in GIST remain unknown. Expression of MMP2 in GIST has not been described previously; however up regulation of MMP2 in GISTs carrying KIT exon 11 deletions is of potential interest since MMP2 has been associated with invasive growth, metastasis formation and poor survival in a number of tumor types.

Identification of CD133 as a differentially up regulated gene in GISTs with KIT exon 11 deletions is a novel finding with potential implications for tumor biology, patient survival and response to therapy. We therefore decided to further explore the importance of CD133 as a biomarker for GIST. TMA analysis of CD133 expression was performed on a separate group of tumors obtained from a population-based series collected during the pre-imatinib era. CD133, detected by the monoclonal antibody AC133, was expressed in a subgroup of tumors – notably gastric GISTs carrying mutations in KIT exon 11. Thus, CD133 expression in GIST is a reflection of tumor site and oncogenesis. Cox regression analysis showed that patients with GIST positive for CD133 had significantly shorter survival than patients with GIST negative for CD133. The significant correlation was still present when the parameters age, sex, risk group, and mutational status was added to the model. Hence, in relation to these parameters, CD133 provides additional information and can therefore not be dismissed as a confounding factor. Furthermore, the correlation between CD133 expression was particularly strong in the group of gastric GIST.

The gene product of human CD133 (prominin-1) was first identified as a cell surface antigen present on CD34+ hematopoietic stem cells.35 CD133 was later shown to be expressed by stem cells in other tissues, e.g. crypt stem cells in the gastrointestinal tract and neural progenitor cells.36 In neoplasia, CD133 is a marker for tumor-initiating cells or cancer stem cells, as shown in glioblastoma, prostate cancer, pancreatic cancer, and colorectal cancer. The expression of CD133 in tumors depends on CD133 promoter methylation37 as well as Notch, TGFβ, mTOR and HIF1α signaling.38, 39 However, the functions of CD133 in normal physiology or neoplasia are not well understood. In normal cells, CD133 may function as an organizer of plasma membrane topology.24 In tumor disease, CD133 is expressed by cancer stem cells and correlates to invasive growth, patient survival, and drug resistance.40, 41 In experimental studies, down regulation of CD133 reduces the capacity of tumor cells to metastasize and targeting CD133 (and putative cancer stem cells) has therefore been suggested as a novel treatment strategy.42 Demonstration of CD133 in a subgroup of gastric GISTs with KIT exon 11 mutations suggests CD133 as a treatment target for this group of tumors in case of imatinib resistance. However, further studies are needed to delineate the relationship between CD133 and putative cancer stem cells in GIST. It is noteworthy that GISTs express several markers normally present in cancer stem cells, e.g. CD133, CD34 and nestin.43 These observations suggest the presence of cancer stem cells in GIST, and if proven may have important clinical implications. Cancer stem cells usually represent a minor proportion of solid tumors, yet these cells have a crucial role in tumor initiation, recurrence, and resistance to chemotherapy/radiotherapy.44 Identification and characterization of cancer stem cells in GIST may provide new information on the biology of these tumors and the need for stem cell-targeted therapy.

Targeting of KIT in GIST by TKI has been a considerable success, however, approximately 10% of tumors demonstrate primary resistance to imatinib (progression within 6 months) and an additional 40–50% of tumors develop secondary drug resistance (progression within 2 years).45, 46 Secondary imatinib resistance is usually caused by additional mutations in KIT (exon 13, 14, 17, 18) or PDGFRA. In case of imatinib resistance, sunitinib is the natural first choice. Sunitinib was the first drug in the second generation of TKIs inhibiting several tyrosine kinases other than KIT and PDGFRA, e.g., VEGFR 1-2, RET, CSF1R and FLT3.47 The best tumor responses to sunitinib are seen in patients with primary KIT exon 9 mutations or wt tumors, but also patients with secondary KIT exon 13 and 14, or PDGFRA mutations may respond.48 It must be born in mind that the adverse effects of sunitinib can be high in individual patients leading to early termination of therapy. For these patients there is a need to target alternative molecular pathways. Drugs aimed at targeting novel pathways in GIST should have the same efficacy and safety as imatinib or sunitinib. A new generation of TKIs has been developed with broader target profiles including inhibition of protein kinase C and MAPK signaling.49 Inhibition of IGFR1 signaling has been suggested as a novel treatment strategy in wt GISTs and pediatric GISTs, which carry IGF1R amplification.50 The results from the present study suggest the CD133 may represent an alternative molecular target in gastric GIST with KIT exon 11 mutations, developing secondary imatinib resistance.

In summary we have identified a specific gene expression profile of GIST carrying KIT exon 11 mutations, including up regulation of CD133. Expression of CD133 is associated with gastric tumor site and poor patient survival after R0-resection in series from the pre-imatinib era. CD133 may be used as a biomarker to select patients for further treatment. Targeting CD133 in GIST may provide a novel treatment strategy.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The expert technical assistance of Anna-Carin Ericsson, Carina Karlsson, Ann-Christine Illerskog, Malin Berntsson, Gülay Altiparmak, and Johanna Andersson is greatly appreciated. This study was supported by the Swedish Cancer Society (to O. Nilsson), the Swedish Research Council (to H. Ahlman), the Swedish Research Council through Gothenburg Stochastic Centre (O. Nerman), Sahlgrenska Academy (the government ALF agreement) (to O. Nilsson and H.Ahlman), the Johan Jansson Foundation for Cancer Research (to G. Arne), the Assar Gabrielsson Research Foundation (to G. Arne), the Nordic Cancer Union (to L-G. Kindblom), and the Sahlgrenska University Hospital Research Foundation (to G. Arne). Lars-Gunnar Kindblom received a grant from Novartis Oncology, Stockholm, Sweden.

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  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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IJC_25755_sm_supptable1.xls140KSupporting Table 1
IJC_25755_sm_supptable2.xls180KSupporting Table 2
IJC_25755_sm_supptable3.xls192KSupporting Table 3
IJC_25755_sm_supptable4.pdf242KSupporting Table 4

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