ArticleHuman pathology2009
Diagnostic biomarkers for renal cell carcinoma: selection using novel bioinformatics systems for microarray data analysis.
Article in Human pathology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 26 citations in OpenAlex.
- Epigenetic and transcriptomic characterization reveals progression markers and essential pathways in clear cell renal cell carcinoma.Nature communications · 2023Article
- Gene expression and oxidative stress markers profile associated with toxic metals in patients with renal cell carcinoma.Molecular biology reports · 2022Article
- Characteristics of Clear Cell Papillary Renal Cell Carcinoma (ccpRCC).International journal of molecular sciences · 2021Review
- Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis.BioMed research international · 2020Article
- Mitochondrial proteomics with siRNA knockdown to reveal ACAT1 and MDH2 in the development of doxorubicin-resistant uterine cancer.Journal of cellular and molecular medicine · 2015Article
- Regulation of mitochondrial oxidative metabolism by tumor suppressor FLCN.Journal of the National Cancer Institute · 2012Article
- Linkage of microRNA and proteome-based profiling data sets: a perspective for the priorization of candidate biomarkers in renal cell carcinoma?Journal of proteome research · 2011Article
- Determination of angptl4 mRNA as a diagnostic marker of primary and metastatic clear cell renal-cell carcinoma.PloS one · 2010Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
The differential diagnosis of clear cell, papillary, and chromophobe renal cell carcinoma is clinically important, because these tumor subtypes are associated with different pathobiology and clinical behavior. For cases in which histopathology is equivocal, immunohistochemistry and quantitative reverse transcriptase-polymerase chain reaction can assist in the differential diagnosis by measuring expression of subtype-specific biomarkers. Several renal tumor biomarkers have been discovered in expression microarray studies. However, due to heterogeneity of gene and protein expression, additional biomarkers are needed for reliable diagnostic classification. We developed novel bioinformatics systems to identify candidate renal tumor biomarkers from the microarray profiles of 45 clear cell, 16 papillary, and 10 chromophobe renal cell carcinomas; the microarray data was derived from 2 independent published studies. The ArrayWiki biocomputing system merged the microarray data sets into a single file, so gene expression could be analyzed from a larger number of tumors. The caCORRECT system removed non-random sources of error from the microarray data, and the omniBioMarker system analyzed data with several gene-ranking algorithms to identify algorithms effective at recognizing previously described renal tumor biomarkers. We predicted these algorithms would also be effective at identifying unknown biomarkers that could be verified by independent methods. We selected 6 novel candidate biomarkers from the omniBioMarker analysis and verified their differential expression in formalin-fixed paraffin-embedded tissues by quantitative reverse transcriptase-polymerase chain reaction and immunohistochemistry. The candidate biomarkers were carbonic anhydrase IX, ceruloplasmin, schwannomin-interacting protein 1, E74-like factor 3, cytochrome c oxidase subunit 5a, and acetyl-CoA acetyltransferase 1. Quantitative reverse transcriptase-polymerase chain reaction was performed on 17 clear cell, 13 papillary and 7 chromophobe renal cell carcinoma. Carbonic anhydrase IX and ceruloplasmin were overexpressed in clear cell renal cell carcinoma; schwannomin-interacting protein 1 and E74-like factor 3 were overexpressed in papillary renal cell carcinoma; and cytochrome c oxidase subunit 5a and acetyl-CoA acetyltransferase 1 were overexpressed in chromophobe renal cell carcinoma. Immunohistochemistry was performed on tissue microarrays containing 66 clear cell, 16 papillary, and 12 chromophobe renal cell carcinomas. Cytoplasmic carbonic anhydrase IX staining was significantly associated with clear cell renal cell carcinoma. Strong cytoplasmic schwannomin-interacting protein 1 and cytochrome c oxidase subunit 5a staining were significantly more frequent in papillary and chromophobe renal cell carcinoma, respectively. In summary, we developed a novel process for identifying candidate renal tumor biomarkers from microarray data, and verifying differential expression in independent assays. The tumor biomarkers have potential utility as a multiplex expression panel for classifying renal cell carcinoma with equivocal histology. Biomarker expression assays are increasingly important for renal cell carcinoma diagnosis, as needle core biopsies become more common and different therapies for tumor subtypes continue to be developed.
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