ArticleAmerican journal of translational research2009
Microarray gene expression profiling using core biopsies of renal neoplasia.
Article in American journal of translational research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Diagnostic accuracy of image-guided biopsies in small (<4 cm) renal masses with implications for active surveillance: a systematic review of the evidence.The British journal of radiology · 2018Pooled it
- The kidney cancer research priority-setting partnership: Identifying the top 10 research priorities as defined by patients, caregivers, and expert clinicians.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2017Article
- Heterogeneity and renal mass biopsy: a review of its role and reliability.Cancer biology & medicine · 2014Review
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We investigate the feasibility of using microarray gene expression profiling technology to analyze core biopsies of renal tumors for classification of tumor histology. Core biopsies were obtained ex-vivo from 7 renal tumors-comprised of four histological subtypes-following radical nephrectomy using 18-gauge biopsy needles. RNA was isolated from these samples and, in the case of biopsy samples, amplified by in vitro transcription. Microarray analysis was then used to quantify the mRNA expression patterns in these samples relative to non-diseased renal tissue mRNA. Genes with significant variation across all non-biopsy tumor samples were identified, and the relationship between tumor and biopsy samples in terms of expression levels of these genes was then quantified in terms of Euclidean distance, and visualized by complete linkage clustering. Final pathologic assessment of kidney tumors demonstrated clear cell renal cell carcinoma (4), oncocytoma (1), angiomyolipoma (1) and adrenalcortical carcinoma (1). Five of the seven biopsy samples were most similar in terms of gene expression to the resected tumors from which they were derived in terms of Euclidean distance. All seven biopsies were assigned to the correct histological class by hierarchical clustering. We demonstrate the feasibility of gene expression profiling of core biopsies of renal tumors to classify tumor histology.
Indexed as
Identifiers
19966938PMC2776289W128623453What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.