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High-throughput sequencing for noninvasive disease detection in hematologic malignancies

Florian Scherer, David M. Kurtz, Maximilian Diehn and Ash A. Alizadeh

Article Figures & Data

Figures

  • Figure 1.

    DNA sources for MRD detection in hematologic malignancies. Graphic overview of distinct DNA sources for molecular disease profiling in hematologic neoplasms, which include circulating tumor DNA as part of the circulating cell-free DNA pool and circulating tumor cells in the bloodstream as well as malignant cells in the BM compartment. Their main characteristics and role in hematologic cancers are displayed in the table next to the graphic.

  • Figure 2.

    Detection limits of methods used for DNA identification in PB and BM. Diagrams depicting the range of detection of methods used for identification of cellular DNA in PB and BM (A) and cell-free DNA in plasma (B). PB input material for each assay was considered from a normal 10 mL EDTA vacutainer. aAnalytical sensitivity highly depends on panel width, sequencing depth, and technical conditions (eg, barcoding, duplex sequencing). bAnalytical sensitivity substantially varies depending on the target/targets interrogated and number of input genomes. cAnalytical sensitivity depends on the method used and number of markers tested. WES, whole exome sequencing; WGS, whole genome sequencing.

Tables

  • Table 1.

    Clinical impact of noninvasive disease detection at distinct disease milestones in lymphoid malignancies

    DiagnosisPrecancerous conditionDiagnosis/pretreatmentDuring therapyPosttreatment/surveillanceRelapse/progression
    ALLCTC or malignant BM cell: levels predict outcome before allo-SCT38,41,43,55CTC or malignant BM cell: positivity predicts clinical outcome29-35,38-43,54,55; positivity predicts relapse39,56; positivity might guide treatment decisions33,35Malignant BM cell: positivity identifies relapse39
    HLctDNA: positivity tends to predict clinical outcome66,68
    MMCTC or malignant BM cell: genotyping defines clinical risk (eg, t(4:14))71Autograft: positivity predicts clinical outcome82Malignant BM cell: positivity predicts clinical outcome72,73,77-79; positivity pre-lenalidomide maintenance predicts clinical outcome78
    MCLCTC or malignant BM cell: positivity before auto-SCT predicts survival87CTC or malignant BM cell: positivity predicts clinical outcome85,86,88; detection might guide treatment decisions84
    CLLCTC: genotyping defines clinical risk (eg, del(17p13), TP53)92,93; assessment might identify therapeutic targets (eg, del(17p13))92,93CTC or malignant BM cell: levels predict clinical outcome68,94-99,103,104; dynamics predict relapse97
    FLHealthy PBMC: BCL2-IGH rearrangement levels >0.01% are associated with a 23-fold higher risk for malignant transformation112ctDNA or malignant BM cells: levels correlate with clinical outcome122,132CTC or malignant BM cells: positivity predicts clinical outcome116-120,125,127,129,131CTC: positivity identifies relapse116
    DLBCLctDNA: levels correlate with tumor burden and PFS22,134,135; genotyping identifies COO subtypes22; profiling identifies DH and TH lymphomas22ctDNA: profiling identifies resistant clones22,137; negativity after 2 cycles predicts PFS134CTC or ctDNA: predicts relapse with 3-6 month lead time22,134,135; positivity predicts clinical outcome22,134CTC or ctDNA: positivity identifies relapse22,134,135,137; profiling detects histological transformation22
    • Role of PBMC, CTC, ctDNA, and BM cell profiling for detection of premalignant states in healthy individuals, identification of clinically relevant biomarkers, and prediction of outcome in lymphoid malignancies at distinct disease milestones.

    • COO, cell of origin; DH, double hit; DLBCL, diffuse large B-cell lymphoma; TH, triple hit.

  • Table 2.

    Clinical impact of noninvasive disease detection at distinct disease milestones in myeloid malignancies

    DiagnosisPrecancerous conditionDiagnosis/pretreatmentDuring therapyPosttreatment/surveillanceRelapse/progression
    AMLHealthy PBMC: harbor age-dependent aberrations associated with overt AML/MDS138-142CTC or malignant BM cell: genotyping defines molecular prognostic factors150,151; genotyping might identify therapeutic targets (eg, FLT3)151,152CTC or malignant BM cell: positivity and kinetics during therapy predict risk of relapse155,157CTC or malignant BM cell: positivity postinduction and postconsolidation predicts clinical outcome156,157,161,164CTC or malignant BM cell: profiling identifies emergent clones at relapse163; profiling identifies relapse161
    CMLCTC or malignant BM cell: BCR-ABL1 levels predict clinical outcome168-170; profiling identifies resistance mutations176,177,180,181CTC or malignant BM cell: rising BCR-ABL1 levels indicate progression178
    MPNCTC or malignant BM cell: genotyping is part of diagnostic criteria189CTC or malignant BM cell: levels predict clinical outcome190,191
    • Role of PBMC, CTC, ctDNA, and BM cell profiling for detection of premalignant states in healthy individuals, identification of clinically relevant biomarkers, and prediction of outcome in myeloid malignancies at distinct disease milestones.

  • Table 3.

    Key characteristics of methods used for noninvasive disease detection in hematologic malignancies

    Embedded Image
    • Colors in column 1 refer to the colors in Figure 2.

    • CNVs, copy number variations; WES, whole exome sequencing; WGS, whole genome sequencing.