Cancer Res Treat.  2025 Apr;57(2):350-361. 10.4143/crt.2024.114.

Target-Enhanced Whole-Genome Sequencing Shows Clinical Validity Equivalent to Commercially Available Targeted Oncology Panel

• Lee S
• Roh J
• Park JS
• Tuncay IO
• Lee W
• Kim JA
• Oh BBL
• Shin JY
• Lee JS
• Ju YS
• Kim R
• Park S
• Koo J
• Park H
• Lim J
• Connolly-Strong E
• Kim TH
• Choi YW
• Ahn MS
• Lee HW
• Kim S
• Kim JH
• Kwon M

• KMID: 2566854
• DOI: http://doi.org/10.4143/crt.2024.114

Abstract

Purpose
Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS.
Materials and Methods
This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches.
Results
TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making.
Conclusion
TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Keyword

Neoplasms; Biomarkers; Mutation; Precision medicine; Whole genome sequencing

Figure

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  Fig. 1. Overview of target-enhanced whole-genome sequencing (TE-WGS). This cartoon depicts TE-WGS, which combines a 40× coverage WGS backbone with a focused exploration of over 500 key biomarker genes. This is achieved through the enrichment of pooled WGS libraries. The illustration highlights TE-WGS’s ability to detect low-level biomarker expressions, enhancing diagnostic precision in personalized oncology.

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  Fig. 2. CONSORT diagram depicting patient enrollment and selection. Of the 56 patients enrolled in the study, only 49 met both the eligibility criteria and sample requirements, and thus, 49 patients were included in the analysis. FFPE, formalin-fixed paraffin-embedded; TE-WGS, target-enhanced whole genome sequencing; TSO500, TruSight Oncology 500.

• 

  Fig. 3. Variant comparison between TruSight Oncology 500 (TSO500) and target-enhanced whole genome sequencing (TE-WGS). (A) Representative sequencing depth on TP53 locus for TE-WGS. In general, TE-WGS achieved a 50× sequence depth in 93.12% of targeted regions. (B) A complete correlation in variant allele fractions was detected between TSO500 and TE-WGS methodologies (r=0.978). Of the shared variants, TE-WGS determined 44.8% of the variants to be of germline origin (red color), while 55.2% are identified as somatic variants. (C) Concordance in gene amplification copy number between TSO500 and TE-WGS, after adjusting for tumor purity by TE-WGS (r=0.842, p=7.24e-11). All tier I and II copy number variations from TSO500 were confirmed by TE-WGS. (D) CD74::ROS1 fusion in lung adenocarcinoma was identified by TE-WGS. TPS, targeted-panel sequencing.

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  Fig. 4. Tumor cell fraction estimation. (A) TruSight Oncology 500 (TSO500)’s reliance on pathologists’ inputs and target-enhanced whole-genome sequencing (TE-WGS)’s computational algorithm, leading to evidence discrepancies and a weak correlation (r=0.44). (B) Concordance in gene amplification copy number between TSO500 and TE-WGS, before adjusting for tumor purity by TE-WGS.

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  Fig. 5. Comparison of genomic instability biomarkers. (A) Comparison of tumor mutation burden (TMB) assessment between TruSight Oncology 500 (TSO500) and target-enhanced whole-genome sequencing (TE-WGS) reveals a good correlation (r=0.89), though some discrepancies were observed in TMB-high classification. (B) 12.2% of tumors classified as TMB-high by TSO500 were deemed TMB-low by TE-WGS. (C) Evaluation of microsatellite instability (MSI) showed strong concordance between TSO500 and TE-WGS (r=0.96); most tumors were MSI-stable, with one notable exception. (D) TE-WGS’ method for assessing homologous recombination deficiency (HRD) effectively distinguished homologous recombination (HR)–proficient from HR-deficient tumors, revealing germline variants in HRD-related genes not identified by TSO500.

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  Fig. 6. Mutational signature analysis highlighting tumor samples exhibiting homologous recombination deficiency (HRD), as evidenced by the enrichment of single base substitution (SBS) signature 3 and small insertions and deletions (ID) signature 6, and tumors bearing APOBEC (apolipoprotein B mRNA-editing enzyme, catalytic polypeptides) mutations, characterized by the enrichment of SBS2 and SBS13 signatures. The presence of the HRD mutational signature suggests an underlying HRD mutational process, even in the absence of related gene mutations like BRCA1/2.

Reference

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