Carrie Cibulskis

PURPOSE: Many children with very early-onset solid tumors remain without an identified germline risk factor after negative panel testing. Whole-genome sequencing (WGS) enables detection of large structural variants (SVs) and rare loss-of-function variants in highly constrained genes that are not routinely captured by standard clinical assays. The additional yield and spectrum of germline findings identified by WGS in this population remain incompletely defined. METHODS: We conducted a retrospective cohort study of children with very early-onset solid or brain tumors evaluated at a tertiary cancer genetic risk clinic with clinically guided germline panel testing. Germline WGS was performed on blood-derived DNA. Analyses focused on pathogenic or likely pathogenic variants in established cancer predisposition genes (CPGs), large SVs (>1,000,000 bp), aneuploidies, and loss-of-function variants in highly constrained genes. RESULTS: One hundred thirty-two patients were included, with median (IQR) age at diagnosis of 1.7 (0.8-3.2) years. Panel testing identified pathogenic CPG variants in 27 of 132 patients (20%). WGS recapitulated panel findings and identified nine additional putative pathogenic variants, increasing yield to 27%. Eight patients (6%) harbored large germline SVs or aneuploidies, including five events not previously recognized. Rare loss-of-function variants in highly constrained genes were identified in 46 patients (35%), many involving pathways relevant to cancer development. Overall, 66 of 132 patients (50%) carried at least one rare germline variant of potential pathogenic relevance. CONCLUSION: In children with very early-onset solid tumors, germline WGS increased detection of potentially pathogenic variants, including novel structural and constrained-gene alterations. These findings support broader consideration of germline WGS in early-onset solid tumors to refine genetic risk assessment and enable discovery of novel susceptibility mechanisms.

Detecting somatic mutations in normal tissues is challenging due to sequencing errors and the low allele fractions of post-zygotic variants. Duplex sequencing greatly reduces errors and can detect mutations at any allele fraction, but systematic, cross-platform comparisons are lacking. We present a comprehensive benchmarking of six duplex sequencing technologies used by the SMaHT Network: CODEC, CompDuplex-seq, HiDEF-seq, NanoSeq, ppmSeq, and VISTA-seq. We evaluated their performance using cord blood DNA, a tumor-normal cell line mixture, and homogenates from six human tissues. Each method shows distinct profiles in genomic footprint, sensitivity, and cost. Despite differences in library construction and sequencing platforms, estimates of mutation rates and mutational signatures are highly concordant. Integration with ultra-deep whole-genome sequencing shows that duplex approaches sensitively capture mutations and signatures beyond embryonic or clonally expanded variants. These results provide a foundation for selecting duplex methods and interpreting their data, enabling scalable single-molecule analyses of somatic mutation landscapes.

Supplementary tables 1-4 and supplementary figure legend

Supplemental Figure 6: Evolutionary analysis of longitudinal plasma ctDNA samples

Supplemental Figure 1: Consort diagram

Supplemental Figure 5: SSNVs detected in the cancer-related genes across 68 ctDNA WES samples

Supplemental Figure 2: Plasma circulating tumor DNA (ctDNA) collection and analysis

Supplemental Figure 3: Plasma circulating tumor DNA (ctDNA) tumor fraction (TF) dynamics determined with ULP-WGS

Supplemental Figure 4: Overview of SSNVs in 68 ctDNA WES samples