1 / 51

Sequencing Cancer Genomes

Sequencing Cancer Genomes. John A Pack. Overview. Introduction DNA Sequencing Circos Plot IDH1 Sequencing Genomes Examples of Sequenced Cancer Genomes Sequencing Disagreements Sequencing Proponents Small Scale Projects Impact Conclusions Future Research.

mercia
Download Presentation

Sequencing Cancer Genomes

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Sequencing Cancer Genomes John A Pack

  2. Overview • Introduction • DNA Sequencing • Circos Plot • IDH1 • Sequencing Genomes • Examples of Sequenced Cancer Genomes • Sequencing Disagreements • Sequencing Proponents • Small Scale Projects • Impact • Conclusions • Future Research

  3. Leading Causes of Death in US • Heart Disease: 631,636 • Cancer: 559,888 • Stroke (cerebrovascular diseases): 137,119 • Chronic lower respiratory disease: 124,583 • Accidents (unintentional injuries): 121,599 • Diabetes: 72,449 Data for 2006 obtained from Centers for Disease Control and Prevention (CDC) (http://www.cdc.gov/nchs/fastats/lcod.htm)

  4. Genetics and Genomics Timeline http://www.nature.com/nature/journal/v422/n6934/full/nature01626.html

  5. What is DNA Sequencing • DNA • Made up of 3 billion chemical building blocks (A, T, C, and G) • DNA Sequencing • Process of determining the exact order of the building blocks that make up the DNA of the 24 different human chromosomes • Revealed the estimated 20,000-25,000 human genes within our DNA as well as the regions controlling them http://www.scq.ubc.ca/a-monks-flourishing-garden-the-basics-of-molecular-biology-explained/

  6. DNA Sequencing Process http://www.ornl.gov/sci/techresources/Human_Genome/graphics/DNASeq.Process.pdf

  7. Circos Plot • Circos is a software package for visualizing data and information • Used for identification and analysis of similarities and differences arising from comparisons of genomes Ledford, Heidi. “The Cancer Genome Challenge”.

  8. http://mkweb.bcgsc.ca/circos/

  9. http://mkweb.bcgsc.ca/circos/

  10. http://mkweb.bcgsc.ca/circos/

  11. Previous Discovery • Mutation in the gene IDH1 found in 2006 study of 35 colorectal cancers • Not expected to be of importance • Changed only a lowly housekeeping enzyme involved in metabolism • 13,000 other genes sequenced from each of 300 more samples http://waynesword.palomar.edu/molecu1.htm

  12. IDH1 Mutation Surfaced Again • 12% of samples of glioblastomamultiforme (type of brain cancer) • 8% of actue myeloid leukaemia samples http://www.mir.wustl.edu/neurorad/internal.asp?NavID=92 http://www.cancerhelp.org.uk/type/aml/about/the-blood-and-acute-myeloid-leukaemia

  13. Studying IDH1 Mutation • Studies showed the mutation changed the activity of isocirtratedehydrogenase • Caused a cancer-promoting metabolite to accumulate in cells • Pharmaceutical companies hunting for a drug to stop the process • IDH1 mutation is the inconspicuous needle found in a veritable haystack of cancer-associated mutations thanks to high powered genome sequencing. http://unitedcaremedical.com/services.shtml

  14. Sequencing Genomes • Labs around the world are teaming up to sequence DNA from thousands of tumors as well as healthy cells from the same person • Nearly 75 cancer genomes have at least begun to be to sequenced and published • By the end of 2010 researchers expect to have over 100 cancer genomes fully sequenced http://www.fhcrc.org/science/pacr/internships/index.html

  15. Difficulties in Researching • Further the research goes the larger the “haystack” • Comparison of tumor cell to healthy cell reveals dozens of single-letter changes, or point mutations • Comparison also reveals repeated, deleted, swapped, or inverted sequences http://activerain.com/blogs/davidhitt http://nl.ijs.si/et/talks/esslli02/metadata.html

  16. Difficulties • “The Difficulty is going to be figuring out hot to use the information to help people rather than to just catalogue lots and lots of mutations.” – Bert Voglestein, John Hopkins University • Clinically tumors can look the same but most differ genetically http://archive.sciencewatch.com/sept-oct2003/sw_sept-oct2003_page1.htm

  17. Distinguishing Mutation Data • Drivers – mutations that cause and accelerate cancers • Passengers – Accidental by-products and thwarted DNA-repair mechanisms • Distinguishing between the drivers and passengers is not always trivial http://www.modified.com/motorsports/0203scc_subaru_us_rally_team_petter_solberg/photo_02.html

  18. Finding Mutations • Mutations that pop up again and again • Identify key pathways that are mutated at different points • Finding more questions than answers • How do researchers decide which mutations are worthy of follow up and functional analysis? http://www.answersingenesis.org/home/area/cfol/ch2-mutations.asp

  19. World Collaboration • The International Cancer Genome Consortium Pilot Project • 11 Countries to sequence DNA • 20 cancer types • 500 tumor samples for each • Cost to sequence each cancer type = US$20 Million http://www.jonessoda.com/wordpress/?m=200904

  20. Ledford, Heidi. “The Cancer Genome Challenge”.

  21. Contributing Countries United States of America Britain • More than 6 types of cancer being sequenced • Ovarian Cancer • Brain Cancer • GlioblastomaMultiforme (IDH1 Mutation found in 12%) • Lung Cancer • Adenocarcinoma • Acute Myeloid Leukaemia (IDH1 Mutation found in 8%) • Colon Cancer • Adenocarcinoma • Others • Breast Cancer • ER-, PR-, HER- • Breast Cancer • Lobular • Breast Cancer • ER+, HER- • European Union Sponsored http://www.medicstravel.co.uk/countryhospitals/usacanada/usa_and_canada.htm http://www.state.gov/p/eur/ci/uk/

  22. Contributing Countries France Australia • Breast Cancer • HER2 overepxpressing • Liver Cancer • Alcohol-associated • Renal-cell carcinoma • European Union Sponsored • Pancreatic Cancer • Ductaladenocarcinoma • Ovarian Cancer http://www.state.gov/p/eap/ci/as/ http://www.state.gov/p/eur/ci/fr/

  23. http://www.thecommonwealth.org/YearbookHomeInternal/138389/ Contributing Countries Canada China • Pancreatic Cancer • Ductaladenocarcinoma • Gastric Cancer http://www.oiep.umd.edu/Training/chinaMap.html India Germany • Pediatric Brain Cancer • Medulloblastoma • PilocyticAstrocytoma • Oral Cancer • Gingivobuccal http://geology.com/world/germany-satellite-image.shtml http://www.state.gov/p/sca/ci/in/

  24. Contributing Countries Italy Japan • Rare Pancreatic Cancers • Enteropancreatic endocrine • Pancreatic exocrine • Liver Cancer • Virus- Associated http://www.state.gov/p/eur/ci/it/ http://www.state.gov/p/eap/ci/ja/ Spain • Chronic lymphocytic leukaemia http://www.state.gov/p/eur/ci/sp/

  25. ICGC • The International Cancer Genome Consortium (ICGC), est. 2008, combined two older, large scale projects • The Cancer Genome Project • Over 100 partial genomes and roughly 15 whole genomes. Tends to tackle over 2,000 more in the next 5-7 years • The US National Institutes of Health’s Cancer Genome Atlas (TCGA) • Sequence up to 500 tumors for each of 20 cancers over next 5 years http://www.icgc.org/ http://www.bfeedme.com/cancer-fighting-foods-spices/

  26. TCGA Pilot Project • The two groups in the TCGA are collaborating to sequence a subset of tumor samples (about 100) from each cancer type • The most promising areas of the genome will then be sequenced in the remaining 400 samples

  27. TCGA Network http://cancergenome.nih.gov/wwd/pilot_program/process.asp?processStyle=image

  28. From the Study • Larger sample numbers could provide driver mutations like the one in IDH1 • Knowledge and study of these mutations could lead to developing new cancer therapies according to researchers http://www.cancercompass.com/cancer-guide/complementary-therapies/complementary-therapies.html

  29. “If there are lots of abnormalities of a particular gene, the most likely explanation is often that those mutations have been selected for by the cancers and therefore are cancer-causing.” Michael Stratton (Co-Director of the Cancer Genome Project) http://www.icr.ac.uk/research/research_profiles/2750.shtml

  30. Challenging • IDH1 was first overlooked on the basis of the colorectal cancer data alone • Search expanded to other cancers before importance was revealed • Some drivers are mutated at very low frequency (less than 1% of the cancers) • heavy sampling is needed to find these low frequency drivers • Sequencing 500 samples per cancer reveal mutations present in as few as 3% of the tumors, but may still have important biological lessons • Need to know in order to understand the overall genomic landscape of cancer

  31. Another Popular Approach • Look for mutations that cluster in a pathway • In an analysis of 24 pancreatic cancers • 12 identified signaling pathways had been altered • Very difficult approach • Pathways overlap and boundaries not clear • Many pathways that are obtained using data from different animals or cell types do not always match up with what’s found in human tissue http://mkweb.bcgsc.ca/circos/

  32. There is A Lot More to Do • Distinguishing between drivers and passengers gets increasingly harder as researchers are beginning to sequence entire tumor genomes • Only a fraction of the existing cancer genomes have been completely sequenced http://www.lbl.gov/Science-Articles/Archive/sabl/2007/Jan/breast-cancer-genome.html

  33. Protein and Non-Protein Coding Regions • Most cancer genome sequences are only covering the exome • Keep costs low • Directly codes for protein (easiest to interpret) • Importance of mutations found in the non-protein coding depths • More challenging • Scientists don’t know what function these regions usually serve • Majority of mutations http://pandasthumb.org/archives/2005/12/another-example.html

  34. Cancer Genomes Coming Fast http://www.asa3.org/ASA/topics/Youth%20page/index.html • Some Full Genome have been Sequenced • Small-cell lung carcinoma (Type of Lung Cancer) • Metastatic melanoma (Type of Skin Cancer) • Basal-like breast cancer (Type of Breast Cancer) • Only exome has been sequenced • Glioblastomamultiforme (Type of Brain Cancer) http://www.mydochub.com/skin-cancer.php http://www.mir.wustl.edu/neurorad/internal.asp?NavID=92

  35. Lung CancerCancer: Small-Cell Lung Carcinoma • Sequenced: full genome • Source: NCI-H209 cell line • Point mutations: 22,910 • Point mutations in gene regions: 134 • Genomic rearrangements: 58 • Copy-number changes: 334 • Highlights: Duplication of the CHD7 gene confirmed in two other small-cell lung carcinoma cell lines http://scienceblog.cancerresearchuk.org/2009/12/16/skin-and-lung-cancer-genomes-are-truly-groundbreaking/

  36. Skin CancerCancer: Metastatic Melanoma • Sequenced: full genome • Source: COLO-829 cell line • Point mutations: 33,345 • Point mutations in gene regions: 292 • Genomic rearrangements: 51 • Copy-number changes: 41 • Highlights: Patterns of mutation reflect damage by ultraviolet light Ledford, Heidi. “The Cancer Genome Challenge”.

  37. Breast CancerCancer: Basal-Like Breast Cancer • Sequenced: full genome • Source: • primary tumor • brain metastasis • tumors transplanted into mice • Point mutations: • 27,173 in primary • 51,710 in metastasis • 109,078 in transplant • Point mutations in gene regions: • 200 • 225 • 328 • Genomic rearrangements: 34 • Copy-number changes: • 155 • 101 • 97 Ledford, Heidi. “The Cancer Genome Challenge”. • Highlights: Patterns of mutation reflect damage by ultraviolet light

  38. Brain CancerCancer: GlioblastomaMultiforme • Sequenced: exome (no complete Circos plot) • Source: • 7 patient tumors • 15 tumors transplanted into mice • Genes containing at least one protein altering mutation: 685 • Genes containing at least one protein altering point mutation: 644 • Copy-number changes: 281 • Highlights: Mutations in the active site of IDH1 have been found in 12% of patients http://www.mir.wustl.edu/neurorad/internal.asp?NavID=92

  39. Finding all mutations • Very important to find all, even in non-protein, regions • Maybe none of these mutations could pertain to the causation of cancer • Some could • Only way to find out is to systematically investigate them

  40. Researcher Disagreements • Some researchers Argue against fully sequencing genomes • Cost of projects outweighs the benefits • Prices will drop due to technology advances in next few years, why not wait? • In the mean time • Mutations that affect how many copies of a gene are found in a genome • Cheaper to assess • Provide more intuitive insight into biological processes http://www.shutterstock.com/pic-2585059/stock-photo-costs-outweigh-benefits.html

  41. Sequencing Proponents • Changes in genome copy number detection • Array-based technology • Fast and relatively inexpensive • Sequencing • Higher-resolution snapshot of regions • The higher resolution can provide • More precision in mapping boundaries • Ability to catch tiny duplications or deletions that an array may not detect

  42. Array-Based Process http://www.nature.com/scitable/content/diagram-of-the-microarray-based-comparative-genomic-41020

  43. Don’t Wait to Sequence • A lot of small scale hospitals are investing millions of dollars into cancer sequencing projects • (e.g.) St. Jude Children’s Research Hospital • Proponents don’t want to wait • The real work starts after the sequencing is over • Determining what these mutations are doing • Old-fashioned biology and experimental analysis http://www.stjude.org/stjude/v/index.jsp?vgnextoid=f2bfab46cb118010VgnVCM1000000e2015acRCRD http://www.the-aps.org/education/k-12misc/careers.htm

  44. US National Cancer Institute • Two 2-year projects • Develop high-throughput methods • Test how the mutations identified by the TCGA pilot project affect cell function • Aim to pull needles from the haystack and make since of them (like the IDH1 mutation) http://www.bfeedme.com/cancer-fighting-foods-spices/

  45. US National Cancer Institute Projects • Dana-Farber Cancer Center (Boston) • Systematically amplify and reduce the expression of genes of interest in cell cultures • Cold Spring Harbor Laboratory (New York) • Study cancer-associated mutations using tumors transplanted into mice http://www.gbaohn.org/files_for_update/Dana%20Farber-job.htm http://www.scivee.tv/user/7054

  46. Other Large Scale Projects • Asses effects of deleting each gene in the mouse genome • Learn more about the normal function of genes that are mutated in cancer http://thecoloringspot.com/animals/animals-set-7.html

  47. Impact • Global • Cancer is a world-wide disease • Cancer Patients • New Technology • New Treatment Processes • Researchers • More grants to make new advances

  48. Conclusions • Sequencing tumor DNA genomes can lead to finding cancer-causing gene mutations • Very challenging to pinpoint gene mutations that are cancer-causing • Very high sample numbers • Sampling and sequencing full cancer genomes is extremely expensive • Some opponents think the cost outweighs the benefits right now • A lot of people think the cost is worth it, because there is a lot more work to do after sequencing, so we should not wait for prices to come down

  49. Future Research • Better technology for making the sequencing equipment to bring costs down • New technology to detect mutations • Complete Full genome sequences for all cancers • Developing ways to stop or kill these mutations but leave the healthy cells unharmed • Nanotechnology (nanopharmaceuticals could have an impact here)

  50. References • Ledford, Heidi. “The Cancer Genome Challenge”. Nature Journal. Vol 464. 15 April 2010. p. 972-974. Macmillan Publishers Limited. 2010 • Human Genome Project Information. Facts About Genome Sequencing. Accessed: April 29, 2010. Last modified: September 19, 2008. http://www.ornl.gov/sci/techresources/Human_Genome/faq/seqfacts.shtml. • Krzywinski, M. et al. Circos: an Information Aesthetic for Comparative Genomics.Genome Res (2009) 19:1639-1645 • Francis S. Collins1, et al. “A vision for the future of genomics research”. Nature Publishing Group. 2010. Accessed April 30, 2010. http://www.nature.com/nature/journal/v422/n6934/full/nature01626.html • Circos Website. Acessed April 30, 2010. http://mkweb.bcgsc.ca/circos/

More Related