Development of personalized tumor biomarkers using massively parallel sequencing - PubMed Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Feb 24;2(20):20ra14.
doi: 10.1126/scitranslmed.3000702.

Development of personalized tumor biomarkers using massively parallel sequencing

Affiliations

Development of personalized tumor biomarkers using massively parallel sequencing

Rebecca J Leary et al. Sci Transl Med. .

Abstract

Clinical management of human cancer is dependent on the accurate monitoring of residual and recurrent tumors. The evaluation of patient-specific translocations in leukemias and lymphomas has revolutionized diagnostics for these diseases. We have developed a method, called personalized analysis of rearranged ends (PARE), which can identify translocations in solid tumors. Analysis of four colorectal and two breast cancers with massively parallel sequencing revealed an average of nine rearranged sequences (range, 4 to 15) per tumor. Polymerase chain reaction with primers spanning the breakpoints was able to detect mutant DNA molecules present at levels lower than 0.001% and readily identified mutated circulating DNA in patient plasma samples. This approach provides an exquisitely sensitive and broadly applicable approach for the development of personalized biomarkers to enhance the clinical management of cancer patients.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Schematic of PARE approach. The method is based on next-generation mate-paired analysis of resected tumor DNA to identify individualized tumor-specific rearrangements. Such alterations are used to develop PCR-based quantitative analyses for personalized tumor monitoring of plasma samples or other bodily fluids.
Fig. 2
Fig. 2
Detection of tumor-specific rearrangements in breast and colorectal cancers. Two representative rearrangements are shown for each tumor sample. (A) PCR amplification across breakpoint regions. MW, molecular weight; T, tumor; N, normal. (B) Genomic coordinates for a representative mate pair of each rearrangement.
Fig. 3
Fig. 3
Detection of tumor-specific rearrangements in mixtures of tumor and normal DNA. Decreasing amounts of tumor DNA were mixed with increasing amounts of normal tissue DNA (300 ng total) and were used as template molecules for PCR using chromosome 4:8 translocation-specific primers or chromosome 3 control primers (see Materials and Methods for additional information).
Fig. 4
Fig. 4
Detection of tumor-specific rearrangements in plasma of cancer patients. (A) The identified chromosome 4:8 and 16 rearrangements were used to design PCR primers spanning breakpoints and to amplify rearranged DNA from tumor tissue and plasma from patients H×402 and H×403, respectively. A plasma sample from an unrelated healthy individual was used as a control for both rearrangements. (B) Plasma samples from patient H×402 were analyzed at different time points using digital PCR to determine the fraction of genomic equivalents of plasma DNA containing the chromosome 4:8 rearrangement. The fraction of rearranged DNA at day 137 was 0.3%, consistent with residual metastatic lesions present in the remaining lobe of the liver.

Comment in

Similar articles

Cited by

References

    1. Lengauer C, Kinzler KW, Vogelstein B. Genetic instabilities in human cancers. Nature. 1998;396:643–649. - PubMed
    1. Mitelman F, Johansson B, Mertens F. The impact of translocations and gene fusions on cancer causation. Nat. Rev. Cancer. 2007;7:233–245. - PubMed
    1. Pinkel D, Segraves R, Sudar D, Clark S, Poole I, Kowbel D, Collins C, Kuo WL, Chen C, Zhai Y, Dairkee SH, Ljung BM, Gray JW, Albertson DG. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet. 1998;20:207–211. - PubMed
    1. Lucito R, Healy J, Alexander J, Reiner A, Esposito D, Chi M, Rodgers L, Brady A, Sebat J, Troge J, West JA, Rostan S, Nguyen KC, Powers S, Ye KQ, Olshen A, Venkatraman E, Norton L, Wigler M. Representational oligonucleotide microarray analysis: A high-resolution method to detect genome copy number variation. Genome Res. 2003;13:2291–2305. - PMC - PubMed
    1. Peiffer DA, Le JM, Steemers FJ, Chang W, Jenniges T, Garcia F, Haden K, Li J, Shaw CA, Belmont J, Cheung SW, Shen RM, Barker DL, Gunderson KL. High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome Res. 2006;16:1136–1148. - PMC - PubMed

Publication types

LinkOut - more resources