GRAIL blood test for identifying multiple cancer types

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Earlier cancer detection offers the opportunity to identify tumors when cures are more achievable, outcomes are superior, and treatment can be less morbid

Effective screening paradigms exist only for a small subset of cancers, are focused on single cancer types, and have variable adoption and compliance

  • utilization of blood-based circulating tumor cell-free DNA (cfDNA) to simultaneously detect and localize multiple cancer types may address this large unmet need

The Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study was designed to determine whether genome-wide cfDNA sequencing in combination with machine learning could detect and localize a large number of cancer types at sufficiently high specificity to be considered for a general population-based cancer screening program

  • during discovery work in the first CCGA sub-study, wholegenome bisulfite sequencing (WGBS) interrogating genomewide methylation patterns outperformed whole-genome sequencing (WGS) and targeted sequencing approaches interrogating copy-number variants (CNVs) and singlenucleotide variants (SNVs)/small insertions and deletions, respectively (1,2)

  • additionally, targeted sequencing with SNV based classification was significantly confounded by clonal hematopoiesis of indeterminate potential (CHIP) (3); such a test would thus require concurrent sequencing of white blood cells (WBCs) to return accurate results

  • DNA methylation is a biological process by which methyl groups are added to the DNA molecule
    • methylation can change the activity of a DNA segment without changing the sequence. When located in a gene promoter, DNA methylation typically acts to repress gene transcription

  • Liu et al report results from the second case-control sub-study designed to develop, train, and validate a methylation-based assay for simultaneous multi-cancer detection across stages as well as tissue of origin (TOO) localization in preparation for clinical validation and utility studies (NCT03085888, NCT03934866) and for a study in which results will be returned to health care providers and patients (NCT04241796)

  • prospective case-control sub-study (from NCT02889978 and NCT03085888) assessed the performance of targeted methylation analysis of circulating cell-free DNA (cfDNA) to detect and localize multiple cancer types across all stages at high specificity
    • participants and methods: The 6689 participants [2482 cancer (>50 cancer types), 4207 non-cancer] were divided into training and validation sets

    • plasma cfDNA underwent bisulfite sequencing targeting a panel of >100 000 informative methylation regions. A classifier was developed and validated for cancer detection and tissue of origin (TOO) localization

    • Study Results
      • performance was consistent in training and validation sets
        • in validation, specificity was 99.3% [95% confidence interval (CI): 98.3% to 99.8%; 0.7% false-positive rate (FPR)]

        • stage I-III sensitivity was 67.3% (CI: 60.7% to 73.3%) in a pre-specified set of 12 cancer types (anus, bladder, colon/rectum, esophagus, head and neck, liver/bile-duct, lung, lymphoma, ovary, pancreas, plasma cell neoplasm, stomach), which account for approximately 63% of US cancer deaths annually, and was 43.9% (CI: 39.4% to 48.5%) in all cancer types

        • detection increased with increasing stage: in the pre-specified cancer types sensitivity was
          • 39% (CI: 27% to 52%) in stage I,
          • 69% (CI: 56% to 80%) in stage II,
          • 83% (CI: 75% to 90%) in stage III, and
          • 92% (CI: 86% to 96%) in stage IV

        • in all cancer types sensitivity
          • was 18% (CI: 13% to 25%) in stage I,
          • 43% (CI: 35% to 51%) in stage II,
          • 81% (CI: 73% to 87%) in stage III,
          • and 93% (CI: 87% to 96%) in stage IV
        • TOO was predicted in 96% of samples with cancer-like signal; of those, the tissue of origin (TOO) localization was accurate in 93%

      • study authors concluded:
        • cfDNA sequencing leveraging informative methylation patterns detected more than 50 cancer types across stages. Considering the potential value of early detection in deadly malignancies, further evaluation of this test is justified in prospective population-level studies

Notes:

  • Lui et al noted that the CCGA study was designed such that results may be generalizable as well as to minimize bias, a problem that has plagued the early detection field
    • accomplished by pre-specifying analyses, controlling for pre-analytic factors (e.g., age, sex, site location) and ensuring that demographics were comparable between the cancer and non-cancer groups, ensuring that stage distribution and method of diagnosis were consistent in independent training and validation sets, ensuring that multiple cancer types at all stages (including early stages) were represented such that resultant cancer classifiers would not be confounded by inappropriate comparison cohorts, and ensuring that there were no site-specific effects on classifier performance
    • the inclusion of a large non-cancer cohort enriched in potentially confounding conditions demonstrated with confidence a high specificity (i.e. safety) that may be appropriate for population-level screening, minimizing potential harm from false positives
  • methylation outperformed WGS and targeted mutation panels in cancer detection and TOO localization for a number of reasons
    • methylation is more pervasive compared with canonical mutation sites typically interrogated in traditional liquid biopsy approaches
      • this targeted methylation approach interrogated approximately 1 million informative CpG sites out of the roughly 30 million CpGs across the genome that can be methylated or unmethylated
      • allowed deeper sequencing of those informative regions compared with WGBS and may overcome expected cost and efficiency limitations of WGS or WGBS approaches
        • although WGS detected cancer at high tumor fractions, it had a worse limit of detection than a methylation-based approach
        • targeted mutation detection also suffered a worse limit of detection and was subject to highly prevalent mutations present in individuals due to biological processes such as CHIP. As such, unlike methylation, targeted sequencing required concurrent WBC sequencing to achieve strong performance
        • epigenetic signals inherently reflect tissue differentiation and malignant cancer states; this likely contributed to the strong cancer detection and TOO classification

  • " The ability to use a blood test to identify undiagnosed cancer; and then identify with a high degree of accuracy the tissue of origin (TOO) is a huge step forward in cancer screening. However the data from Lui et al reveals a sensitivity of 43.9% for all cancers, i.e. more than half of patients who had the blood test AND had a cancer were NOT identified by the blood test. The ability of the blood test to identify undiagnosed cancers increased with increasing cancer stage. The specificity of the blood test was very high (99.3%) i.e., if a blood test was positive then it was very likely that the patient had a cancer.
  • The technology underlying the test is based on machine learning and so the ability of the test to identify undetected cancers may indeed become higher than the current 43.9% based on the GRAIL study in England. So in conclusion, this is a very exciting innovation in cancer screening but, at present, the sensitivity of the blood test needs to be considered when a clinician discusses the result of the blood test with a patient." (5)

Reference:

  • Oxnard GR, Klein EA, Seiden MV, et al. Simultaneous multi-cancer detection and tissue of origin (TOO) localization using targeted bisulfite sequencing of plasma cell-free DNA (cfDNA). Ann Oncol. 2019;30(suppl 5):LBA77.
  • Liu MC, Klein E, Hubbell E, et al. Plasma cell-free DNA (cfDNA) assays for early multi-cancer detection: the circulating cell-free genome atlas (CCGA) study. Ann Oncol. 2018;29(suppl 8):500.
  • Swanton C,Venn O, Aravanis A, et al. Prevalence of clonal hematopoiesis of indeterminate potential (CHIP) measured by an ultra-sensitive sequencing assay: exploratory analysis of the Circulating Cancer Genome Atlas (CCGA) study. J Clin Oncol. 2018;36(suppl 15):12003
  • Lui MC et al. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. Jun;31(6):745-759. doi: 10.1016/j.annonc.2020.02.011. Epub 2020 Mar 30.
  • Commentary - Dr Jim McMorran (Editor in Chief, GPnotebook) April 27th 2021

Last edited 04/2021 and last reviewed 03/2022

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