The methods for gene expression profiling and integrated DEG analysis have been described previously [1 (link)2 (link)]. Briefly, the 20 matched pairs of pre- and post-TKI treatment tumor samples from the 10 patients were used for expression profiling of the acquired resistance cohort. Their differential gene expression between paired pre- and post-TKI tumor samples was analyzed with the empirical Bayes moderated paired t-test using R package limma.
To overcome the limitation of the small number (10) of cases in our acquired resistance cohort, we used a public dataset (GSE76068) generated from a ccRCC patient-derived xenograft (PDX) model [15 (link)]. We also used GEPIA, which provides gene expression analysis based on tumor and normal samples from the TCGA and the GTEx databases. Functional transcriptome analyses were performed using Ingenuity Pathway Analysis (IPA) and MetaCore (Clarivate Analytics) software with default settings.
To overcome the limitation of the small number (10) of cases in our acquired resistance cohort, we used a public dataset (GSE76068) generated from a ccRCC patient-derived xenograft (PDX) model [15 (link)]. We also used GEPIA, which provides gene expression analysis based on tumor and normal samples from the TCGA and the GTEx databases. Functional transcriptome analyses were performed using Ingenuity Pathway Analysis (IPA) and MetaCore (Clarivate Analytics) software with default settings.
