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Radiomic and gEnomic approaches for the enhanced DIagnosis of REnal Cancer (REDIRECt): A translational pilot study

ABSTRACT: Introduction: The aim of this pilot study is to establish a radiogenomic characterisation of a clear-cell renal cell carcinoma (ccRCC) subpopulation, focusing on the transcriptomic underpinnings of radiomic features. Materials & Methods: To establish the viability of conducting a combined analysis of both radiomic and genomic data, a pilot cohort of 6 patients with <5cm G2 unilateral non-metastatic T1a-b ccRCC, who underwent surgery, was evaluated. Transcriptomic analysis was conducted through RNA-seq on tumor samples, while radiomic data was extracted from pre-operative 4 phase contrast-enhanced multidetector CT scans. Genomic heterogeneity was assessed with principal component analysis run on unrestricted data, on a clear-cell renal cell carcinoma associated gene list with zero-centered Reads Per Kilobase of transcript, per million mapped reads values. The underlying pathways and gene ontologies were established with enrichment analysis. In addition, Pearson’s correlation between radiomic data and the transcription of significant genes was fitted, and dendrogram and heatmap plots were drawn. Results: Even in a clinically homogeneous population, the employed analyses have demonstrated that RCC should be regarded as an intrinsically heterogeneous disease. The analysis of the radiomic features and gene expression correlation using heatmap and dendrogram showed four distinct radiogenomic correlation patterns: with one including 5 radiomic features, and the other three including 2 features each. Conclusion: The current pilot study is the first investigation demonstrating an innovative radiogenomic characterisation of clear-cell RCC. Based on such observations, further investigation into the radiomic and genomic approaches for the enhanced diagnosis of RCC is warranted.

ORGANISM(S): Homo sapiens

PROVIDER: GSE133460 | GEO | 2019/06/28

REPOSITORIES: GEO

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Project description:Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney. Currently, there are no biomarkers for the diagnostic, prognostic, or predictive applications in RCC. MicroRNAs (miRNAs) are short non protein-coding RNAs that negatively regulate gene expression and have been shown to be involved in cancer. We analyzed a total of 70 matched pairs of clear cell RCC (ccRCC) and normal kidney tissues from the same patients by microarray analysis and validated our results by quantitative real time PCR. We identified 166 miRNAs significantly dysregulated in ccRCC. MiR-122, miR-155 and miR-210 had the highest fold changes of overexpression while miR-200c, miR-335, and miR-218 were the most downregulated. We performed extensive bioinformatics analysis including a combinatorial analysis of previously reported miRNAs dysregulated in RCC and extensive target prediction analysis. Many miRNAs were predicted to target a number of genes involved in RCC pathogenesis. Our results showed that miRNA dysregulation in RCC can be attributed in part, to chromosomal aberrations, the co-regulation of miRNA clusters, and co-expression with host genes. We also correlated miRNA expression with clinical characteristics and found miR-155 expression was correlated with ccRCC tumor size. In conclusion, our analysis showed that a number of miRNAs are dysregulated in ccRCC and may contribute to kidney cancer pathogenesis by targeting more than one key molecule. We identified mechanisms that may contribute to miRNA dysregulation in ccRCC. Dysregulated miRNAs represent potential biomarkers for kidney cancer. We preformed a miRNA microarray on 20 pairs of matched primary clear cell renal cell carcinoma (ccRCC) and normal kidney tissue from the same patient (St. Michael's Hospital, Toronto, Canada). One matched pair was used per array for a total of 20 arrays. Microarray results were validated by quantitative real time PCR using an independent set of 50 matched pairs of ccRCC and normal kidney tissue from the same patient.

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Radiomic and gEnomic approaches for the enhanced DIagnosis of REnal Cancer (REDIRECt): A translational pilot study

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