Clinical application of whole-genome sequencing of solid tumors for precision oncology

Abstract

Genomic alterations in tumors play a pivotal role in determining their clinical trajectory and responsiveness to treatment. Targeted panel sequencing (TPS) has served as a key clinical tool over the past decade, but advancements in sequencing costs and bioinformatics have now made whole-genome sequencing (WGS) a feasible single-assay approach for almost all cancer genomes in clinical settings. This paper reports on the findings of a prospective, single-center study exploring the real-world clinical utility of WGS (tumor and matched normal tissues) and has two primary objectives: (1) assessing actionability for therapeutic options and (2) providing clarity for clinical questions. Of the 120 patients with various solid cancers who were enrolled, 95 (79%) successfully received genomic reports within a median of 11 working days from sampling to reporting. Analysis of these 95 WGS reports revealed that 72% (68/95) yielded clinically relevant insights, with 69% (55/79) pertaining to therapeutic actionability and 81% (13/16) pertaining to clinical clarity. These benefits include the selection of informed therapeutics and/or active clinical trials based on the identification of driver mutations, tumor mutational burden (TMB) and mutational signatures, pathogenic germline variants that warrant genetic counseling, and information helpful for inferring cancer origin. Our findings highlight the potential of WGS as a comprehensive tool in precision oncology and suggests that it should be integrated into routine clinical practice to provide a complete image of the genomic landscape to enable tailored cancer management.

Fig. 1. Study design and metrics of the sequencing cohort.

a Flow diagram of the study protocol. b Technical success rate of the CancerVision^TM application in the clinical setting. c Tumor types enrolled in this study. d The distribution of the tumor cell fraction of cancer tissues estimated using WGS according to specimen type.

Fig. 2. Turnaround time of WGS-based cancer genome profiling in the clinical setting.

TAT was measured as working days from sample collection to the acquisition of the WGS report. The processes of the WGS assay were subdivided into six components: (1) library preparation, (2) presequencing quality assessment and library pooling, (3) sequence production, (4) postsequencing process, (5) bioinformatics analysis, and (6) final curation/report generation.

Fig. 3. Landscapes of somatically acquired mutations in cancer genomes.

a Comparison of tumor mutational burden (TMB) between Pan-Cancer Analysis of Whole-Genomes (PCAWG) and this study. Two studies showed similar TMBs in two cancer types. Every dot represents a sample, and the red horizontal lines are the median TMBs in the respective cancer type. b Landscape of somatically acquired mutations in 95 solid tumors in this study. Top to bottom: tumor mutational burden (TMB), cancer type, microsatellite instability (MSI) score, homologous recombination deficiency (HRD) score, tumor cell fraction estimated from WGS, genome ploidy, sample type (fresh-frozen or FFPE), sample acquisition method (biopsy or surgery), point mutations in frequently mutated cancer genes, mutational signatures (SBS, ID, and SV), and copy number alterations. c Cancer genes frequently altered by SVs (arcs inside the circle) and copy number changes (dots outside the circle). d A representative Circos plot summarizing all the somatic mutations (from outer to inner circles; chromosomes, point mutations with variant allele fraction (VAF), point mutations with intermutational distance, genome-wide loss-of-heterozygosity (LOH) pattern, genome-wide copy number changes, and SVs).

Fig. 4. Clinical utility of WGS in the assessment of therapeutic options.

a Overall, WGS was supportive for therapeutic options in ~70% of the patients. WGS provided information for therapeutics (I-1), clinical trials (I-2), or the exclusion of options (I-3). b Clinical utility for assessing therapeutic options across cancer types. c Two lung adenocarcinoma patients harboring an oncogenic EML4-ALK fusion gene via balanced chromothripsis mechanisms. d A lung adenocarcinoma patient harboring a rare HIP1-ALK fusion gene. e Seven patients with GI tract cancers showing MSI-H features, a mutational pattern-based target for pembrolizumab treatment. Two independent variables, i.e., the MSI score and MSI-associated mutational signatures, clearly distinguish MSI-H cancer samples. f A prostate cancer patient with HRD, a mutational pattern-based target for PARP inhibitors. A Circos plot showing HRD features, proportions of HRD-associated signatures for SBSs, indels, and SVs, and mutations that induced HRD in cancer (somatically acquired BRCA1 frameshift insertion and loss-of-heterozygosity events).

Fig. 5. Clinical utility of WGS in the assessment of therapeutic options: available clinical trials (Category I-2).

a Three cancer cases showing oncogene amplification (CCND1, EGFR) or NRG1 rearrangement, representing genomic targets for clinical trials. b A patient with cholangiocarcinoma harboring ecDNA-mediated FGFR2 hyperamplification, a genomic target for a clinical trial. c The clinical course of a triple-negative breast cancer patient who was identified as a possible candidate for a clinical trial using WGS. Surgically removed tissue from the right axillary lymph node (LN) was subjected to WGS. WGS identified the strong HRD feature and its underlying genetic cause (complete inactivation of somatically acquired BRIP1), which are targets for clinical trials. d Circos plot demonstrating the characteristic HRD features of the patient. Outer to inner: ideogram, point mutations (single base substitutions [SBSs] and short indels) and their variant allele frequencies, distances between adjacent point mutations, major (red line) and minor (blue line) allelic copy number (CN), total segmented CN (black dot) and structural variations (SVs). SBS and SV mutational signatures associated with HRD are shown in pie graphs. e Integrative genome viewer (IGV) snapshot of a somatic SV disrupting the BRCA1 interacting helicase 1 (BRIP1) gene, namely a 21.1-Kbp deletion between BRIP1 intron 14 and BRIP1 intron 6. f A patient with stomach cancer who was identified as a possible candidate for a clinical trial using WGS. WGS identified the strong HRD feature and its underlying genetic cause (a germline BRCA1 pathogenic variant combined with loss of heterozygosity of the locus in the cancer), which are targets for a clinical trial. A Circos plot showing the HRD features mentioned above and two pie graphs showing HRD-associated mutational signatures. g Pathogenic mutations underlying HRD in the patient: we identified germline BRCA1 mutations with loss of heterozygosity in the tumor sample. h Pedigree of the patients. WGS revealed a strong cancer predisposition in the patient’s family. The pathogenic BRCA1 p.L1780P variant was also identified in the younger brother.

Fig. 6. Clinical utility of WGS for providing clarity to clinical questions (Category II).

a WGS was supportive in ~81% of the cases conducted for clinical clarity. WGS provided information on the resistance/sensitivity mechanism (II-1), tumor origin (II-2), and evaluation of familial cancer patients (II-3). b A lung adenocarcinoma patient evaluated by WGS to determine the mechanism of resistance to erlotinib treatment. Hyperamplification of the EGFR wild-type allele was found. c In cancer, the MAPK pathway is activated by two mechanisms: (1) EGFR L858R and (2) EGFR-wt amplification. The latter cannot be inhibited by erlotinib. d 2-Deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG) positron-emission tomography-computed tomography (PET-CT) image at the initial presentation of a patient with cancer at an unknown primary site showing a 6.4-cm jejunal mass. A hypermetabolic mass was located in the right adrenal gland and identified as a potential peritoneal carcinomatosis. Additionally, we noted multiple small nodules in both lungs. A computed tomography scan and hematoxylin and eosin image of the right adrenal gland mass are also shown. e Circos plot showing genomic findings from WGS. f Mutational signature analysis of SBSs and IDs. High proportions of SBS4 and ID3 mutational signatures (attributed to tobacco smoking) were noted. g Treatment response to non-small cell lung cancer (NSCLC)-directed chemotherapy: nivolumab plus ipilimumab in combination with paclitaxel plus carboplatin. h A patient with colorectal cancer with a germline APC truncating mutation, suggesting that the cancer was a familial case (familial adenomatous polyposis). i A patient with bilateral breast cancer suspected to have familial cancer given her clinical features and familial history. j, k According to the cancer genome profiling, HRD-associated features were absent, suggesting that bilateral breast cancer was likely sporadic. In line with these observations, no pathogenic germline mutations were found.