Unlocking Precision Cancer Care through Whole Genome Sequencing

Cancer is a leading cause of death worldwide, responsible for nearly 10 million deaths in 2020 according to the World Health Organization. While significant progress has been made in developing new treatments, cancer remains difficult to diagnose and treat due to its complex nature. Tumors can vary greatly between patients and even within the same patient over time as the disease progresses. To improve patient outcomes, oncologists need a more comprehensive understanding of the molecular changes driving each individual’s cancer.

A new large-scale study published in Nature Medicine provides important insights towards this goal. Researchers from Genomics England and the National Health Service (NHS) in the UK analyzed whole genome sequencing (WGS) data from over 13,800 solid tumors across 33 different cancer types. Paired with longitudinal clinical records, their findings underscore the value of systematically linking genomic and real-world treatment data on a massive scale. According to the authors, their results support the clinical implementation of WGS and hold implications for optimizing cancer care through more personalized treatment strategies.

The study analyzed genome sequencing data generated through the Cancer Programme of the 100,000 Genomes Project, an NHS initiative led by Genomics England. WGS provides a complete molecular profile of a tumor by detecting various genomic alterations, including gene mutations, copy number changes, and structural variants, from a single test. Analysis of these multi-omics data revealed clinically actionable abnormalities in many of the analyzed cancers.

Overview of the 100,000 Genomes Cancer Programme. a, Journey of the patient’s genome. Patients provided written informed consent for paired tumor and normal (germline) WGS analysis. DNA was extracted from tumor and normal (blood) samples using standardized protocols and samples were submitted for WGS, which was performed on an Illumina sequencer. An automated pipeline was constructed for sequence quality control, alignment, variant calling and interpretation, with results returned to the 13 NHS Genomic Medicine Centers for review in regional GTABs. b, Linked genomic and real-world clinical datasets. In the 100,000 Genomes Project, participants are followed over their life course using electronic health records (all hospital episodes, cancer registration entries, systemic anticancer therapies and cause of death). c, Infinity loop representing the link between healthcare and research in genomics. Adapted from Reference

For example, small gene mutations recommended for standard testing by clinical guidelines were present in over half of cases for several tumor types including glioblastoma, skin melanoma, and colorectal cancer. Certain cancers like sarcoma showed a particularly high prevalence of structural variants affecting clinically important genes. Additionally, abnormalities in genes involved in DNA repair like BRCA1/2 were found in 40% of ovarian cancers, underscoring the value of integrating germline and somatic genomic analyses.

Perhaps most notably, the study linked genomic findings to real-world treatment outcomes through England’s National Health Service clinical databases. Stratifying over 1,700 cancer patients according to molecular markers revealed their prognostic potential. Presence of homologous recombination deficiency (HRD), for instance, strongly predicted improved survival among platinum-treated breast and ovarian cancer patients. Conversely, higher tumor mutation burden associated with worse prognosis in melanoma.

These results highlight the clinical utility of WGS for surveillance, guiding therapy decisions, and predicting response. By uncovering actionable abnormalities across multiple testing platforms from a single assay, WGS could serve as a first-line molecular profiling approach. While targeted panels detect important alterations, their limited gene coverage may miss opportunities for matching patients to emerging precision treatments.

Looking ahead, the promise of WGS will depend on health systems adapting to this new level of genomic data. Cancer centers will need expert multidisciplinary teams, known as genomic tumor boards, to reliably interpret WGS results and translate findings into personalized care decisions. Developing standardized reporting formats and clinical decision support tools can help ensure this complex information reaches treating clinicians. As the cost of WGS declines, determining fair reimbursement models will also be crucial to ensure equitable access.

Perhaps most significantly, health systems must find ways to systematically feed real-world outcome data back into clinical practice. By continually analyzing large genomic cohorts linked to electronic health records, researchers can refine biomarkers and uncover new therapeutic targets over time. Clinicians too will benefit from routinely querying outcome databases according to patients’ molecular profiles. This learning health system approach is key to advancing precision oncology and maximizing the impact of initiatives like the 100,000 Genomes Project.

If successfully implemented, WGS holds promise to revolutionize cancer care. By comprehending the complete molecular portrait of each tumor, oncologists can match individual patients to optimal therapies, clinical trials, or investigational options. Genomic profiling may one day become a standard part of cancer screening, diagnostics, and longitudinal surveillance. Most importantly, as health systems evolve to systematically integrate genomic and outcomes data, we move closer to the vision of precision cancer treatment tailored for each unique patient. Realizing this potential will require continued collaboration between researchers, healthcare leaders, and policymakers, but studies like this provide encouraging proof that the fruits of genomics can translate into real-world clinical benefits at a massive scale.

Reference(s)

1. https://doi.org/10.1038/s41591-023-02682-0

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GENETICS | MEDICINE | ONCOLOGY | PUBLIC HEALTH