Genomic landscape of adult testicular germ cell tumours in the 100,000 Genomes Project

Abstract

Testicular germ cell tumours (TGCT), which comprise seminoma and non-seminoma subtypes, are the most common cancers in young men. In this study, we present a comprehensive whole genome sequencing analysis of adult TGCTs. Leveraging samples from participants recruited via the UK National Health Service and data from the Genomics England 100,000 Genomes Project, our results provide an extended description of genomic elements underlying TGCT pathogenesis. This catalogue offers a comprehensive, high-resolution map of copy number alterations, structural variation, and key global genome features, including mutational signatures and analysis of extrachromosomal DNA amplification. This study establishes correlations between genomic alterations and histological diversification, revealing divergent evolutionary trajectories among TGCT subtypes. By reconstructing the chronological order of driver events, we identify a subgroup of adult TGCTs undergoing relatively late whole genome duplication. Additionally, we present evidence that human leukocyte antigen loss is a more prevalent mechanism of immune disruption in seminomas. Collectively, our findings provide valuable insights into the developmental and immune modulatory processes implicated in TGCT pathogenesis and progression.

Fig. 1. Mutational landscape of adult testicular germ cell tumours (TGCT).

a Genomic profiling of primary and metastatic TGCT samples with matched germline DNA from peripheral blood. Samples were collected from 60 participants recruited from seven NHS Genomic Medicine Centres (GMCs) across England as indicated on the map. The human silhouette drawing was modified from a template from V<underline>ecteezy.com</underline> (https://www.vecteezy.com/vector-art/299365-medical-infographic-of-human-body). b From top to bottom: number of coding mutations identified in each sample; number of insertions and deletions (indels) in each sample; total number of structural variants in each sample, separated into tandem duplications (TD), deletions (DEL), head-to-head (H2HINV) and tail-to-tail (T2TINV) inversions, transversions (TRANS); proportion of mutations assigned to single base substitution (SBS), insertion/deletion (ID), and doublet base substitution (DBS) mutational signatures; TGCT subtype; tumour type (primary or metastasis); clinical stage; age-group of participant; mutation status of KIT driver gene; mutation status of RAS (KRAS or NRAS) driver genes; presence or absence of 12p amplification according to GISTIC2. Exposures or processes linked with mutational signatures are listed. Two samples that were not sequenced via a PCR-free workflow are excluded from this figure. HRD homologous recombination deficiency, amp amplification, mut driver mutation, NHEJ non-homologous end joining, NSGCT non-seminomatous germ cell tumours, ROS reactive oxygen species, y years of age.

Fig. 2. Heatmap of molecular mutations in testicular germ cell tumours (TGCT).

In total, 57 individual adult participant samples were analysed. Point mutation and indel drivers independently identified in The Cancer Genome Atlas (TCGA) and Genomics England (GEL) TGCT cohorts are shown alongside annotated GISTIC2 focal segments. Driver presence/absence in the Memorial Sloan Kettering—Metastatic Events and Tropisms (MSK-MET) TGCT cohort is also shown. Seventeen recurrently mutated genes were found in the cohort, respectively, with KIT being the most frequently altered gene (Supplementary Data 2). The colour code indicates mutation type(s) or TGCT subtype (see legends). Samples with more than one type of mutation (missense, nonsense or in-frame insertion) in the same gene correspond to ‘Multi Hit’ events. Samples with driver mutations and amplifications/deletions in the same gene are indicated with an overlay of two colours. Amp amplification, Del deletion, CNA copy number alteration, NSGCT non-seminomatous germ cell tumours.

Fig. 3. Timing of whole genome duplication (WGD) events across Pan-Cancer Analysis of Whole Genomes (PCAWG) and Genomics England (GEL) testicular germ cell tumour (TGCT) cohorts.

a Bar plot showing estimated pre-duplication mutation burden (yellow) and total clonal mutation burden (dark grey) per TGCT. The dashed line indicates the median pre-duplication burden across all samples. Samples where WGD occurred relatively late are shaded in light grey. b Number of samples with a WGD event in each cancer type is shown alongside the corresponding violinplot. Data points from PCAWG appear in grey. Data points from GEL appear in red. PCAWG cancer types with less than four WGD samples not shown. Tumour abbreviations reported as per PCAWG study (ref. ). c Distribution of synchronous (sync) and asynchronous (async) gain patterns across GEL TGCT genomes, split by ploidy status (WGD whole genome duplication, ND near diploid). Uninformative samples had too few mutations or gained segments to allow accurate timing.

Fig. 4. Probabilistic ordering reveals most likely timing of copy number and driver events in TGCT.

a Genome-wide landscape of clonal and subclonal loss of heterozygosity (LOH), gain, and homozygous deletion (HD) events in Genomics England (GEL) testicular germ cell tumour (TGCT) cohort. The y-axis corresponds to the fraction of tumours with a particular event. Events identified as enriched by our model and genes of interest within these regions are labelled. b Probabilistic ordering (left panel) of significantly enriched copy number events, whole genome duplication (WGD), and IntOGen-identified mutational drivers. A Plackett-Luce model was used to order events by sampling from all possible tumour phylogenies across the entire dataset (1000 iterations). Events are ordered along a timing scale (x-axis) from early to late by the mean value of the relative timing estimates. Horizontal lines show the range of time scale values inferred across the cohort for each event. The vertical lines and points for each event represent the mean and standard deviation for each distribution. The grey dashed vertical line represents the mean timing estimate of WGD across all samples. The proportion of these events present in different subtypes and clinical stages is shown in two central panels. Horizontal lines (right panel) indicate the minimum and maximum age of diagnosis in individuals harbouring a mutational event. The shaded grey circle indicates the median age of diagnosis corresponding to each mutational event. The dashed red line shows the median age of the cohort. c. Plackett-Luce-based probabilistic ordering of enriched events and mutational drivers only in seminomas. Seminomas were split into two groups (young-onset, late-onset; Supplementary Methods). The grey dashed vertical line represents the mean timing estimate of WGD across all samples. LOH loss of heterozygosity, NSGCT non-seminomatous germ cell tumours excluding tumours with seminomatous components, NSGCT (Sem) NSGCT with seminomatous components.