Use of cancer-specific genomic rearrangements to quantify disease burden in plasma from patients with solid tumors

Abstract

Detection of recurrent somatic rearrangements routinely allows monitoring of residual disease burden in leukemias, but is not used for most solid tumors. However, next-generation sequencing now allows rapid identification of patient-specific rearrangements in solid tumors. We mapped genomic rearrangements in three cancers and showed that PCR assays for rearrangements could detect a single copy of the tumor genome in plasma without false positives. Disease status, drug responsiveness, and incipient relapse could be serially assessed. In future, this strategy could be readily established in diagnostic laboratories, with major impact on monitoring of disease status and personalizing treatment of solid tumors.

© 2010 Wiley-Liss, Inc.

Figures

Figure 1

Protocol and rearrangement screens. (A) Outline of protocol and current time-frames for each step. (B) Example of a deletion mapped to base-pair resolution from the osteosarcoma sample (Patient 3). Using knowledge of the breakpoint, a nested PCR assay can be designed, with a fluorescent probe used for the second round real-time PCR reaction. (C) Genome-wide rearrangement screen for Patient 1, showing eight somatically acquired genomic rearrangements, including interchromosomal (purple arcs) and intrachromosomal (green arcs) variants. Copy number is shown in blue. (D) Genome-wide rearrangement screen for Patient 2. (E) Genome-wide rearrangement screen for Patient 3.

Figure 2

Analysis of plasma DNA from two patients with breast cancer (Patients 1 and 2). (A,B) Results of a nested, real-time PCR from a control region of the genome performed on undiluted (dark brown) and serial 10-fold dilutions of DNA extracted from plasma of the two patients (lighter shades of brown). Results for plasma DNA from a normal individual are also shown (green). (C,D) Results of a nested, real-time PCR from a tumor-specific rearrangement performed on serial 10-fold dilutions of DNA extracted from plasma of the two patients (brown) and a normal control (green). The horizontal black lines represent the fluorescence threshold at which a reaction is deemed to become positive. The x axis denotes the number of cycles of PCR, with more strongly positive reactions crossing the threshold at an earlier cycle number.

Figure 3

Analysis of serial samples from a patient with osteosarcoma (patient 3). (A) Analysis of two rearrangements in duplicate reactions across a dilution series of tumor DNA into normal DNA. When the number of cycles to reach positivity (Ct) is ≤27, the absolute amount of tumor DNA can be estimated from the line of best fit. For reactions in which the number of cycles to reach positivity (Ct) > 27, disease can only be classified as detectable or undetectable. (B) Estimated amount of tumor DNA per ml of serum from seven samples collected at milestone time points in the patient’s clinical course.