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Validation of whole genome amplification for analysis of the p53 tumor suppressor gene in limited amounts of tumor samples
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
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2012 (English)In: Biochemical and Biophysical Research Communications - BBRC, ISSN 0006-291X, E-ISSN 1090-2104, Vol. 425, no 2, 379-383 p.Article in journal (Refereed) Published
Abstract [en]

Personalized cancer treatment requires molecular characterization of individual tumor biopsies. These samples are frequently only available in limited quantities hampering genomic analysis. Several whole genome amplification (WGA) protocols have been developed with reported varying representation of genomic regions post amplification. In this study we investigate region dropout using a 929 polymerase based WGA approach. DNA from 123 lung cancers specimens and corresponding normal tissue were used and evaluated by Sanger sequencing of the p53 exons 5-8. To enable comparative analysis of this scarce material, WGA samples were compared with unamplified material using a pooling strategy of the 123 samples. In addition, a more detailed analysis of exon 7 amplicons were performed followed by extensive cloning and Sanger sequencing. Interestingly, by comparing data from the pooled samples to the individually sequenced exon 7, we demonstrate that mutations are more easily recovered from WGA pools and this was also supported by simulations of different sequencing coverage. Overall this data indicate a limited random loss of genomic regions supporting the use of whole genome amplification for genomic analysis.

Place, publisher, year, edition, pages
2012. Vol. 425, no 2, 379-383 p.
Keyword [en]
Whole genome amplification, TP53, Mutations, Validation
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:kth:diva-102911DOI: 10.1016/j.bbrc.2012.07.101ISI: 000308384400044Scopus ID: 2-s2.0-84865372505OAI: oai:DiVA.org:kth-102911DiVA: diva2:557647
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20120928

Available from: 2012-09-28 Created: 2012-09-28 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Analysis of genetic variations in cancer
Open this publication in new window or tab >>Analysis of genetic variations in cancer
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of this thesis is to apply recently developed technologies for genomic variation analyses, and to ensure quality of the generated information for use in preclinical cancer research.

Faster access to a patients’ full genomic sequence for a lower cost makes it possible for end users such as clinicians and physicians to gain a more complete understanding of the disease status of a patient and adjust treatment accordingly. Correct biological interpretation is important in this context, and can only be provided through fast and simple access to relevant high quality data.

Therefore, we here propose and validate new bioinformatic strategies for biomarker selection for prediction of response to cancer therapy. We initially explored the use of bioinformatic tools to select interesting targets for toxicity in carboplatin and paclitaxel on a smaller scale. From our findings we then further extended the analysis to the entire exome to look for biomarkers as targets for adverse effects from carboplatin and gemcitabine. To investigate any bias introduced by the methods used for targeting the exome, we analyzed the mutation profiles in cancer patients by comparing whole genome amplified DNA to unamplified DNA. In addition, we applied RNA-seq to the same patients to further validate the variations obtained by sequencing of DNA. The understanding of the human cancer genome is growing rapidly, thanks to methodological development of analysis tools. The next step is to implement these tools as a part of a chain from diagnosis of patients to genomic research to personalized treatment.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. iii, 62 p.
Series
TRITA-BIO-Report, ISSN 1654-2312 ; 2012:18
Keyword
Cancer, Mutations, Variations, Single Nucleotide Polymorphism, DNA, RNA, Genome, Massively Parallel Sequencing, Exome Sequencing, Toxicity
National Category
Other Medical Biotechnology
Identifiers
urn:nbn:se:kth:diva-104438 (URN)978-91-7501-450-0 (ISBN)
Public defence
2012-11-22, Hillarpsalen, Retzius väg 8, Karolinska Institutet, Solna, 09:00 (English)
Opponent
Supervisors
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20121105

Available from: 2012-11-05 Created: 2012-11-02 Last updated: 2014-02-11Bibliographically approved

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