Data collection and processing

Transcriptomic data (bulk RNA-seq), single-nucleotide variants and corresponding patient clinical information (race, ethnicity, clinical stage) were acquired for 64 pure seminoma cases (TCGA-TCGT project) available at The Cancer Genome Atlas (TCGA) data portal (https://portal.gdc.cancer.gov). Two cases (TCGA-2G-AAFG and TCGA-2G-AAHP) include primary and secondary tumors that were considered as different cases with additional number after case ID, ‘1’ for primary and ‘2’ for secondary (new primary) tumor respectively (for example TCGA-2G-AAFG1 and TCGA-2G-AAFG2) (Supplementary Table S1). Each sample was assigned to seminoma subtype 1 or 2 according to our previous study (Medvedev et al. 2022).

One of the major components of seminoma microenvironment is infiltrating lymphocytes (Hadrup et al. 2006). To assess differences in transcriptomic status of lymphocytes associated with different seminoma subtypes, we focus on highly abundant immune cell transcripts. Abundant immune cell transcripts were defined using the Database of Immune Cell Expression data (Schmiedel et al. 2018). Seminoma gene expression data was median centered and log2 transformed. The R function hclust was used for unsupervised hierarchical clustering of pure seminoma samples with Ward’s method, and the resulting heatmap was cut with the R function cutree. Boxplots were generated using R function ggplot. Statistical significance (p values) for boxplots were calculated using Wilcoxon test.