Impact of Thawing on Reference Gene Expression Stability in Renal Cell Carcinoma Samples

BackgroundCD73–adenosine signaling in the tumor microenvironment is immunosuppressive and may be associated with aggressive renal cell carcinoma (RCC). We investigated the prognostic significance of CD73 protein expression in RCC leveraging nephrectomy samples. We also performed a complementary analysis using The Cancer Genome Atlas (TCGA) dataset to evaluate the correlation of CD73 (ecto-5′-nucleotidase (NT5E), CD39 (ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1)) and A2 adenosine receptor (A2AR; ADORA2A) transcript levels with markers of angiogenesis and antitumor immune response.MethodsPatients with RCC with available archived nephrectomy samples were eligible for inclusion. Tumor CD73 protein expression was assessed by immunohistochemistry and quantified using a combined score (CS: % positive cells×intensity). Samples were categorized as CD73negative (CS=0), CD73low or CD73high (< and ≥median CS, respectively). Multivariable Cox regression analysis compared disease-free survival (DFS) and overall survival (OS) between CD73 expression groups. In the TCGA dataset, samples were categorized as low, intermediate and high NT5E, ENTPD1 and ADORA2A gene expression groups. Gene expression signatures for infiltrating immune cells, angiogenesis, myeloid inflammation, and effector T-cell response were compared between NT5E, ENTPD1 and ADORA2A expression groups.ResultsAmong the 138 patients eligible for inclusion, ‘any’ CD73 expression was observed in 30% of primary tumor samples. High CD73 expression was more frequent in patients with M1 RCC (29% vs 12% M0), grade 4 tumors (27% vs 13% grade 3 vs 15% grades 1 and 2), advanced T-stage (≥T3: 22% vs T2: 19% vs T1: 12%) and tumors with sarcomatoid histology (50% vs 12%). In the M0 cohort (n=107), patients with CD73high tumor expression had significantly worse 5-year DFS (42%) and 10-year OS (22%) compared with those in the CD73negative group (DFS: 75%, adjusted HR: 2.7, 95% CI 1.3 to 5.9, p=0.01; OS: 64%, adjusted HR: 2.6, 95% CI 1.2 to 5.8, p=0.02) independent of tumor stage and grade. In the TCGA analysis, high NT5E expression was associated with significantly worse 5-year OS (p=0.008). NT5E and ENTPD1 expression correlated with higher regulatory T cell (Treg) signature, while ADORA2A expression was associated with increased Treg and angiogenesis signatures.ConclusionsHigh CD73 expression portends significantly worse survival outcomes independent of stage and grade. Our findings provide compelling support for targeting the immunosuppressive and proangiogenic CD73–adenosine pathway in RCC.

Download Full-text

Combining differential expression, chromosomal and pathway analyses for the molecular characterization of renal cell carcinoma

Canadian Urological Association Journal ◽

10.5489/cuaj.64 ◽

2012 ◽

Vol 1 (2S) ◽

Cited By ~ 1

Author(s):

Kyle A. Furge ◽

Karl Dykema ◽

David Petillo ◽

Michael Westphal ◽

Zhongfa Zhang ◽

...

Keyword(s):

Gene Expression ◽

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Gene Expression Profiling ◽

Cancer Cells ◽

Expression Profiling ◽

Renal Cell ◽

Molecular Signatures ◽

Genetic Makeup ◽

Papillary Rcc

Using high-throughput gene-expression profiling technology, we can now gaina better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup ofthe cancer cells. This abnormal genetic makeup can have profound effectson cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeuticagents and radiation. These approaches will lead to better molecularsubclassification of tumours, the basis of personalized medicine. We have, todate, done whole-genome microarray gene-expression profiling on several hundredsof kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used toidentify both cytogenetic abnormalities and molecular pathways that are deregulatedin renal cell carcinoma (RCC). For example, we have identified the deregulationof the VHL-hypoxia pathway in clear-cell RCC, as previously known,and the c-Myc pathway in aggressive papillary RCC. Besides the more commonclear-cell, papillary and chromophobe RCCs, we are currently characterizingthe molecular signatures of rarer forms of renal neoplasia such ascarcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosomeXp11 translocations associated with papillary RCC, renal medullarycarcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response.

Download Full-text