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Analysis of genetic variations in cancer
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
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 [en]
Cancer, Mutations, Variations, Single Nucleotide Polymorphism, DNA, RNA, Genome, Massively Parallel Sequencing, Exome Sequencing, Toxicity
National Category
Other Medical Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-104438ISBN: 978-91-7501-450-0 (print)OAI: oai:DiVA.org:kth-104438DiVA: diva2:564681
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
List of papers
1. Validation of whole genome amplification for analysis of the p53 tumor suppressor gene in limited amounts of tumor samples
Open this publication in new window or tab >>Validation of whole genome amplification for analysis of the p53 tumor suppressor gene in limited amounts of tumor samples
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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.

Keyword
Whole genome amplification, TP53, Mutations, Validation
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-102911 (URN)10.1016/j.bbrc.2012.07.101 (DOI)000308384400044 ()2-s2.0-84865372505 (Scopus ID)
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
2. Assessment of Whole Genome Amplification for Sequence Capture and Massively Parallel Sequencing
Open this publication in new window or tab >>Assessment of Whole Genome Amplification for Sequence Capture and Massively Parallel Sequencing
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2014 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 1, e84785- p.Article in journal (Refereed) Published
Abstract [en]

Exome sequence capture and massively parallel sequencing can be combined to achieve inexpensive and rapid global analyses of the functional sections of the genome. The difficulties of working with relatively small quantities of genetic material, as may be necessary when sharing tumor biopsies between collaborators for instance, can be overcome using whole genome amplification. However, the potential drawbacks of using a whole genome amplification technology based on random primers in combination with sequence capture followed by massively parallel sequencing have not yet been examined in detail, especially in the context of mutation discovery in tumor material. In this work, we compare mutations detected in sequence data for unamplified DNA, whole genome amplified DNA, and RNA originating from the same tumor tissue samples from 16 patients diagnosed with non-small cell lung cancer. The results obtained provide a comprehensive overview of the merits of these techniques for mutation analysis. We evaluated the identified genetic variants, and found that most (74%) of them were observed in both the amplified and the unamplified sequence data. Eighty-nine percent of the variations found by WGA were shared with unamplified DNA. We demonstrate a strategy for avoiding allelic bias by including RNA-sequencing information.

Keyword
Exome Capture, Amplified Dna, Mutation, Cancer, Metagenomes, Discovery, Viruses, Samples, Tumor
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-104473 (URN)10.1371/journal.pone.0084785 (DOI)000329463500033 ()2-s2.0-84896910544 (Scopus ID)
Funder
EU, European Research Council, CHEMORES LSHC-CT-2007-037665Swedish Cancer SocietySwedish Research CouncilScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20140211. Updated from submitted to published.

Available from: 2012-11-05 Created: 2012-11-05 Last updated: 2017-12-07Bibliographically approved
3. Identification of candidate SNPs for drug induced toxicity from differentially expressed genes in associated tissues
Open this publication in new window or tab >>Identification of candidate SNPs for drug induced toxicity from differentially expressed genes in associated tissues
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2012 (English)In: Gene, ISSN 0378-1119, E-ISSN 1879-0038, Vol. 506, no 1, 62-68 p.Article in journal (Refereed) Published
Abstract [en]

The growing collection of publicly available high-throughput data provides an invaluable resource for generating preliminary in silico data in support of novel hypotheses. In this study we used a cross-dataset meta-analysis strategy to identify novel candidate genes and genetic variations relevant to paclitaxel/carboplatin-induced myelosuppression and neuropathy. We identified genes affected by drug exposure and present in tissues associated with toxicity. From ten top-ranked genes 42 non-synonymous single nucleotide polymorphisms (SNPs) were identified in silico and genotyped in 94 cancer patients treated with carboplatin/paclitaxel. We observed variations in 11 SNPs, of which seven were present in a sufficient frequency for statistical evaluation. Of these seven SNPs. three were present in ABCA1 and ATM, and showed significant or borderline significant association with either myelosuppression or neuropathy. The strikingly high number of associations between genotype and clinically observed toxicity provides support for our data-driven computations strategy to identify biomarkers for drug toxicity.

Keyword
Paclitaxel, Carboplatin, Single nucleotide polymorphism, Toxicity, Gene expression microarrays, Meta-analysis
National Category
Genetics
Identifiers
urn:nbn:se:kth:diva-103126 (URN)10.1016/j.gene.2012.06.053 (DOI)000308260400010 ()2-s2.0-84864511649 (Scopus ID)
Funder
EU, European Research Council, CHEMORES LSHC-CT-2007-037665Swedish Research CouncilScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20121008

Available from: 2012-10-08 Created: 2012-10-04 Last updated: 2017-12-07Bibliographically approved
4. Using whole exome sequencing to identify genetic candidates for carboplatin and gemcitabine induced toxicities
Open this publication in new window or tab >>Using whole exome sequencing to identify genetic candidates for carboplatin and gemcitabine induced toxicities
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(English)Article in journal (Other academic) Submitted
Abstract [en]

Chemotherapies are associated with significant inter-individual variability in therapeutic effect and adverse drug reactions. In lung cancer the use of gemcitabine and carboplatin induces grade 3-4 myelosuppression in about ¼ of the patients while an equal fraction of patients are basically unaffected in terms of myelosuppressive side effects. We therefore set out to try to identify genetic markers for gemcitabine / carboplatin induced myelosuppression. We selected 32 patients that suffered extremely high neutropenia and thrombocytopenia (grade 3 or 4 after first chemotherapy cycle) or were virtually unaffected (grade 0-1 after the first chemotherapy cycle) by the chemotherapy out of 243 lung cancer patients treated with gemcitabine / carboplatin. These patients were exome sequenced and their genetic differences compared using six different bioinformatic strategies; whole exome non-synonymous SNV association analysis, deviation from Hardy-Weinberg equilibrium, analysis of genes selected by a priori biological knowledge, analysis of genes selected from gene expression meta-analysis of toxicity data sets, Ingenuity pathway analysis and FunCoup network enrichment analysis. All patients were successfully sequenced and 5000-7000 non-synonymous single nucleotide variants were identified in each patient. PI3 (elastase specific inhibitor in neutrophils) showed the strongest association in the single SNV analysis (nominal p=0.0005). Further, variants within IL37, an inhibitor of the innate immune system, and CSAG1, a tumor antigen, differed among the two patient groups and appeared among the top hits in several of the performed analysis, indicating that the approach identifies genetic variants associated with the immune system and tumor differentiation, which might be important for the sensitivity to chemotherapeutic agents. However, the associations reported here are in a need of replication before clinical interpretations can be made.

Keyword
Exome sequencing, Gemcitabine, Carboplatin, Thrombocytopenia, Neutropenia, Toxicity
National Category
Genetics
Identifiers
urn:nbn:se:kth:diva-104474 (URN)
Note

QS 2012

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

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Johanna Hasmats thesis(1139 kB)757 downloads
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