High expression of GEM and EDNRA is associated with metastasis and poor outcome in patients with advanced bladder cancer
© Laurberg et al.; licensee BioMed Central Ltd. 2014
Received: 1 April 2014
Accepted: 27 August 2014
Published: 30 August 2014
The standard treatment for non-metastatic muscle-invasive bladder cancer (stages T2–T4a) is radical cystectomy with lymphadenectomy. However, patients undergoing cystectomy show metastatic spread in 25% of cases and these patients will have limited benefit from surgery. Identification of patients with high risk of lymph node metastasis will help select patients that may benefit from neoadjuvant and/or adjuvant chemotherapy.
RNA was procured by laser micro dissection of primary bladder tumors and corresponding lymph node metastases for Affymetrix U133 Plus 2.0 Gene Chip expression profiling. A publically available dataset was used for identification of the best candidate markers, and these were validated using immunohistochemistry in an independent patient cohort of 368 patients.
Gene Set Enrichment Analysis showed significant enrichment for e.g. metastatic signatures in the metastasizing tumors, and a set of 12 genes significantly associated with lymph node metastasis was identified. Tumors did not cluster according to their metastatic ability when analyzing gene expression profiles using hierarchical cluster analysis. However, half (6/12) of the primary tumor clustered together with matching lymph node metastases, indicating a large degree of intra-patient similarity in these patients. Immunohistochemical analysis of 368 tumors from cystectomized patients showed high expression of GEM (P = 0.033; HR = 1.46) and EDNRA (P = 0.046; HR = 1.60) was significantly associated with decreased cancer-specific survival.
GEM and EDNRA were identified as promising prognostic markers for patients with advanced bladder cancer. The clinical relevance of GEM and EDNRA should be evaluated in independent prospective studies.
KeywordsBladder cancer Metastasis Outcome GEM EDNRA
Bladder cancer is the 4th most common cancer in men and the 11th most common cancer in women . Patients with non-muscle-invasive bladder cancer (NMIBC) are predominantly treated with transurethral resection of the bladder in combination with Bacillus Calmette-Guerin (BCG) or Mitomycin C. Cystectomy is offered if local control cannot be maintained. Recently, treatment of NMIBC has shifted towards a more aggressive approach based on EORTC risk scores, resulting in more patients receiving cystectomy [2, 3]. The standard treatment for non-metastatic muscle-invasive bladder cancer (MIBC) (stages T2–T4a) is radical cystectomy with lymphadenectomy . Patients with immobile tumors (T4b) receive chemotherapy– sometimes followed by salvage cystectomy or radiotherapy . Five-year cancer-specific survival for patients with MIBC is 65% following cystectomy and neoadjuvant chemotherapy increases the 5-year survival with 6–8% but is, for now, not standard treatment in all clinical settings [6, 7].
Patients undergoing cystectomy show metastatic spread in 25% of cases , and these patients will have limited benefit of surgery. Identification of patients with high risk of lymph node metastasis could help identify patients that would benefit from neoadjuvant chemotherapy. Therefore, identification of metastatic disease (to lymph nodes or distant organs) prior to cystectomy is of high importance. Previously, several studies have focused on studying molecular markers to identify metastatic risk or ability based on analysis of the patient’s primary tumor. Key players in the DNA-damage-response and cell-cycle machinery (e.g. p53, Rb, p21, p16, Tip60) have been investigated by immunohistochemistry, but none of the markers have shown significant power in validation studies to reach the clinic [9–12]. More recently, gene-expression signatures have revealed promising results but have not yet been validated in prospective patient cohorts [13, 14]. Smith et al. reported a 20 gene signature in the primary tumor for predicting lymph node metastasis based on three different cohorts, making it the first study in MIBC where the gene signature was validated in an independent patient cohort . Patients with high relative risk (1.74) and low relative risk (0.70) of node positive disease could be identified. In other disease like e.g. breast cancer, metastatic capacity of the primary tumors has been studied intensely, and several gene expression signatures for predicting metastatic outcome have been develop and successfully validated [16–19].
Here we laser micro dissected primary bladder tumors and corresponding lymph node metastases and performed microarray gene expression profiling of the procured cells. We compared gene expression patterns in primary bladder tumors with and without metastatic disease and by including previously published data from Riester et al. we identified a panel of 12 transcripts significantly associated with disease outcome. The prognostic value of GEM (GTP binding protein overexpressed in skeletal muscle) and EDNRA (endothelin receptor type A) were successfully validated in an independent patient cohort using tissue microarrays (TMAs).
Patients and follow-up
Written informed consent was obtained from all patients and the study was approved by the Central Denmark Region Committees on Biomedical Research Ethics (1994/2920). All patients were cystectomized at Department of Urology at Aarhus University Hospital between 1998 and 2008, and surviving patients had at least 36 months of follow-up, and were censored after a maximum of 96 months. Tumor stage was determined using the American Joint Committee on Cancer recommendations from 2002 and WHO 2004 classification was used to determine tumor grade. All patients were clinically free of metastasis before surgery and no patients received neoadjuvant or adjuvant treatment in terms of chemotherapy or radiotherapy.
Laser micro dissection, RNA extraction and microarray analysis
All patient specimens collected at the time of surgery were split into tissue for pathology and tissue for the biobank. Tissue for the biobank was embedded in Tissue-Tek® O.C.T™ Compound and snap frozen in liquid nitrogen before storage at -80°C. Sections were examined by a genitourinary pathologist to identify carcinoma cell content. Following, cresyl violet stained tissue was microdissected using the PALM laser microbeam system. RNA extraction was performed using RNeasy Micro Kits (Qiagen) according to manufacturer protocols. RNA quality was assessed using an Agilent Bioanalyzer 2100 (RIN: 2.4-8.8; median 5.9). Total RNA was amplified and converted to cDNA using Nugen Pico-RNA system. The two-round amplification kit is optimized to amplify low volumes and poor quality RNA for Affymetrix array analysis. After amplification, the cDNA was fragmented and labeled using NuGen FL-Ovation kit, loaded onto the Affymetrix U133 Plus 2.0 Gene Chip according to the manufacturer’s protocol, and scanned using the Affymetrix 3000 7G Scanner.
Microarray data analysis
Raw microarray data was normalized and intensity measures generated by RMA  using GeneSpring version 11 software. Unsupervised hierarchical cluster analysis of all transcripts with a variance above 1.5 was performed using Cluster 3.0 and Java tree-view software . Gene Set Enrichment Analysis (GSEA) v2.07 software was used to test if previously published gene signatures and curated pathways were enriched in the data. We used the inbuilt KEGG, BIOCARTA, REACTOME, gene ontology, and oncogenic signatures in MsigDB database and supplemented with curated signatures containing “cancer”, “metastasis”, “cell cycle”, “repair”, “DNA damage”, and “hypoxia”. We used the default significance levels to test if significant enrichment was reached with normalized p-values below 0.05 and with false discovery rates below 0.25. A previously published dataset (GEO ID: GSE31684; U133 Plus 2.0 GeneChip) from laser microdissected tumors from 93 cystectomized patients was retrieved. A total of 69 patients were included in the analysis, after exclusion of all patients without reported lymph node status, and all node negative patients without 24 months of follow-up.
Tissue microarray (TMA) analysis
Biopsies from a total of 368 tumors from cystectomy specimens and from 41 lymph node metastases were incorporated into a TMA. All tumors were reevaluated regarding T-stage and grade by the same uro-pathologist prior to placement on the TMA. The patients included and the TMA construction is described earlier .
Immunohistochemistry and Western blotting
The immunohistochemichal staining procedure was carried out based on the EnVision + TM System HRP (Dako) as previously described . Antibodies against GEM (Novus Biologicals # NBP1-58906) diluted 1:150 and against EDNRA (Abcam #ab76259) diluted 1:800 were used. The specificity of the antibodies against GEM and EDNRA was validated by Western blotting using T24 cell line essentially as described earlier .
Scoring of IHC staining
A Hamamatsu Nanozoomer scanner (Hamamatsu Corporation, Hamamatsu City, Japan) was used to scan the TMA slides, and VIS visualization software (Visiopharm A/S, Hørsholm, Denmark) was used for visualization of IHC staining during scoring of the protein expression intensities. Percentage of positive carcinoma cells was scored on a continuous scale for each core, and optimal cut-off values were afterwards defined by ROC curves. Scoring was performed by two observers blinded to outcome. The first observer scored on a continuous scale, and the second scored according to the dichotomized cutoff value generated. Differences in the dichotomized scorings were reviewed and consensus was reached.
Comparisons between the metastatic and non-metastatic groups were performed using two-sided t-test statistics. Categorical data was compared in univariate analysis using the χ2 test and censored data was compared using log-rank test. Hazard ratios (HR) were estimated using Cox proportional hazard models. Multivariate analysis was performed separately for each biomarker including only significant clinical parameter from the univariate analysis. All analyses were performed using STATA (version 11).
Clinical and histopathological information for each patient used for gene expression profiling
Dead of Bladder cancer
Time to relapse (months)
Follow up (months)
Molecular subgroup analysis
Gene set enrichment analysis (GSEA)
GSEA of published signatures in MsigDB
Enriched in metastatic tumors
Enriched in non-metastatic tumors
Proliferation and survival
Identification of markers associated with outcome
Transcripts significantly up-regulated in metastasizing tumors in both cohorts
Non-metastatic vs metastatic tumors
Lymph node metastasis vs non-metastatic tumors
Non-metastatic vs metastatic tumors
(Riester et al.)
Univariate and multivariate Cox regression analysis of disease specific survival as function of molecular markers
Multivariate analysis including EDNRA
Multivariate analysis including GEM
Nr. of patients
Median Follow-up months (range)
Age median (range)
HR = 1.01 (P=0.47)
HR = 1.56 (P=0.007)
HR = 1.62 (P=0.015)
HR = 1.45 (P=0.048)
HR = 1.59 (P<0.001)
HR = 1.28 (P=0.049)
HR = 1.22 (P=0.070)
Lymph node metastases
HR = 3.98 (P<0.001)
HR = 3.82 (P<0.001)
HR = 3.55 (P<0.001)
HR = 1.18 (P=0.78)
HR = 1.60 (P=0.046)
HR = 1.63 (P=0.042)
HR = 1.46 (P=0.032)
HR = 1.33 (P=0.11)
The risk of recurrence and later metastasis following cystectomy is as high as 50%  and most patients will ultimately succumb to the disease following recurrence . Therefore, early detection of metastasis and prediction of recurrence risk following cystectomy could ultimately improve survival as better treatment regimens could be applied. The aim of this study was to identify markers of lymph node metastasis at (before) cystectomy. We compared gene-expression profiles from 10 primary bladder tumors with 12 matched lymph node metastases and eight primary tumors without metastasis to identify markers associated with metastatic disease, and to test similarity between lymph node metastases and matched primary tumors. Overall, we found no large difference in gene expression between the two patient groups. Furthermore, we found that primary tumors and corresponding lymph node metastases showed comparable gene expression profiles in half of the cases. The reason for this lack of overall difference between the groups may be caused by tumor heterogeneity, minor sub clones responsible for metastatic ability, and also by inclusion of tumors of different stages (T1-T4). Gene set enrichment analysis (GSEA) was used to investigate biological differences between metastasizing and non-metastasizing tumors. Interestingly, signatures associated with “metastasis”, “extracellular function”, “proliferation and survival”, and “cell signaling” were significantly enriched in the metastasizing tumors while signatures associated with “metabolism”, “cell cycle” and “DNA repair” were associated with non-metastatic tumors – indicating that the overall biological process may be different in the two tumor groups. However, due to the large heterogeneity we were not able to identify general molecular differences between lymph node metastases and primary tumors.
The tumor heterogeneity (intra and inter) may make marker identification difficult, and consequently we included additional patient samples from a previously published dataset  for delineating significant markers of outcome. The panel of 12 genes that were significant in both datasets contained GEM and EDNRA. These genes were selected for further validation based on significance, difference in expression, expression level, and based on antibody availability. We found no overlap between our 12 genes and the 21-gene metastasis signature reported by Smith et al. previously , which may reflects multiple factors like cohort heterogeneity and size, and differences in sampling (laser micro dissection vs bulk tumor analysis). We found high expression of GEM and EDNRA to be significantly associated with a decrease in cancer-specific survival, when analyzing the protein expression on a cohort of 368 patients. Furthermore, high EDNRA was significantly associated with decreased cancer-specific survival in multivariate analysis.
The possible functional roles of EDNRA (endothelin receptor type A) and GEM (GTP binding protein overexpressed in skeletal muscle) in cancer progression and metastasis are currently unclear. EDNRA and GEM have not been associated with disease outcome and cancer outcome. GEM is a small GTP-binding protein that plays a role in regulating Ca2+ channel expression at the cell surface . Furthermore, it is involved in cytoskeletal remodeling in interphase cells and is a spindle-associated protein required for prober mitotic progression . EDNRA is a G-protein coupled receptor for endothelins and it is expressed on vascular smooth-muscle cells and on heart, kidney, and neuronal cells .
This study included a limited number of tumors in the initial characterization of tumor subgroups, and although we isolated carcinoma cells in primary tumors and lymph node metastases using laser-micro dissection, the patient cohort may still be too small to draw firm conclusion regarding molecular subgroups and differences between primary tumors and metastatic lesions. The strength of our approach is the inclusion of matched lymph node metastasis in the selection of candidate markers for metastasis, and this is to our knowledge the first study of bladder cancer that compare the lymph nodes to the primary tumors.
Recently, large intra-tumor heterogeneity of several cancer types has been reported [33–35]. A recent study of clear cell renal cell carcinomas showed significant molecular heterogeneity using whole-exome sequencing of multiple tumor areas . As small cellular sub-clones may be responsible for the disease progression and metastasis it may be difficult to identify any good molecular markers of outcome by analyzing the bulk tumors. Other studies of tumor metastasis in mice have shown limited overlap in genomic alterations (about 9%) between primary tumors and metastases , indicating that metastatic lesions probably propagate from small sub-populations in the primary tumors. Intra-tumor heterogeneity has so far not been addressed in detail in bladder cancer. However, Li et al. performed whole-exome sequencing of 66 individual cells from a single muscle invasive tumor, and identified large variation in mutant genes between the cells. Other groups [39, 40] have recently shown that muscle invasive bladder cancers belong to 4–5 distinct molecular subgroups. Consequently, future studies of prognostic markers for patients with advanced bladder cancer should include large patient cohorts, stratification according to overall tumor subgroup and sub-clonal analysis to compensate for the large inter and intra tumor heterogeneity for these patients.
We observed a high degree of heterogeneity between primary tumors with and without metastases, and between paired samples of primary tumors and associated lymph-node metastases. GEM and EDNRA were identified to be promising prognostic markers for patients with advanced bladder cancer. The clinical relevance of GEM and EDNRA should be evaluated in independent prospective studies.
The work was also supported The John and Birthe Meyer Foundation; the Danish Cancer Society; the Ministry of Technology and Science; The Danish Cancer Biobank (DCB) and the Lundbeck Foundation. Furthermore, our research has received funding from the European Community’s Seventh Framework program FP7/2007-2011 under grant agreement n° 201663. We thank Ms. Pamela Celis, Ms. Margaret Gellett, and Ms. Hanne Steen for excellent technical assistance.
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