Cianflone Francesco, Lazarevic Dejan, Palmisano Anna, Fallara Giuseppe, Larcher Alessandro, Freschi Massimo, Dell'Antonio Giacomo, Scotti Giulia Maria, Morelli Marco J, Ferrara Anna Maria, Trevisani Francesco, Cinque Alessandra, Esposito Antonio, Briganti Alberto, Tacchetti Carlo, Doglioni Claudio, Del Maschio Alessandro, de Cobelli Francesco, Bertini Roberto, Salonia Andrea, Montorsi Francesco, Tonon Giovanni, Capitanio Umberto
Unit of Urology, Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Center for Omics Scences, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Transl Androl Urol. 2022 Feb;11(2):149-158. doi: 10.21037/tau-21-713.
The combination of radiomic and transcriptomic approaches for patients diagnosed with small clear-cell renal cell carcinoma (ccRCC) might improve decision making. In this pilot and methodological study, we investigate whether imaging features obtained from computed tomography (CT) may correlate with gene expression patterns in ccRCC patients.
Samples from 6 patients who underwent partial nephrectomy for unilateral non-metastatic ccRCC were included in this pilot cohort. Transcriptomic analysis was conducted through RNA-sequencing on tumor samples, while radiologic features were obtained from pre-operative 4-phase contrast-enhanced CT. To evaluate the heterogeneity of the transcriptome, after a 1,000 re-sampling via bootstrapping, a first Principal Component Analyses (PCA) were fitted with all transcripts and a second ones with transcripts deriving from a list of 369 genes known to be associated with ccRCC from The Cancer Genome Atlas (TCGA). Significant pathways in each Principal Components for the 50 genes with the highest loadings absolute values were assessed with pathways enrichment analysis. In addition, Pearson's correlation coefficients among radiomic features themselves and between radiomic features and transcripts expression values were computed.
The transcriptomes of the analysed samples showed a high grade of heterogeneity. However, we found four radiogenomic patterns, in which the correlation between radiomic features and transcripts were statistically significant.
We showed that radiogenomic approach is feasible, however its clinical meaning should be further investigated.
对于诊断为小细胞透明肾细胞癌(ccRCC)的患者,将放射组学和转录组学方法相结合可能会改善决策制定。在这项试点和方法学研究中,我们调查了从计算机断层扫描(CT)获得的影像特征是否可能与ccRCC患者的基因表达模式相关。
本试点队列纳入了6例因单侧非转移性ccRCC接受部分肾切除术的患者样本。通过对肿瘤样本进行RNA测序进行转录组分析,同时从术前四期增强CT中获取放射学特征。为了评估转录组的异质性,在通过自举法进行1000次重采样后,对所有转录本进行了首次主成分分析(PCA),并对来自癌症基因组图谱(TCGA)中已知与ccRCC相关的369个基因列表中的转录本进行了第二次主成分分析。使用通路富集分析评估每个主成分中50个绝对值负荷最高的基因的显著通路。此外,计算了放射组学特征之间以及放射组学特征与转录本表达值之间的Pearson相关系数。
分析样本的转录组显示出高度的异质性。然而,我们发现了四种放射基因组模式,其中放射组学特征与转录本之间的相关性具有统计学意义。
我们表明放射基因组方法是可行的,但其临床意义应进一步研究。