Microarray Technologies. Julie Støve Bødker cand scient, PhD

Transcription

1 Microarray Technologies Julie Støve Bødker cand scient, PhD

2 2 Microarray Technologies - Outline I. Lecture, ~30 minutes II. Presentation of articles, ~30 minutes 1. Alizadeh et al., 2000: Maria Rodrigo 2. Thorsen et al., 2011: Lea Sollfrank and Ditte Løhmann III. Group work, ~20 minutes IV. Discussion of answers and perspectives of the method and articles, ~10 minutes

3 3 Evolution of gene-analysis Hypothesis driven experiments: One gene pr experiment RT-PCR, northern blots, RNase assays Macroarrays Nylon membranes and 32 P labelled samples Microarrays One labelled samples per microarray Sequencing/Next generation sequencing A huge amount of data

4 4 The principle The underlying principle of the microarray technology is the ability of DNA to bind specific to itself and to RNA

5 5 Microarrays What material do we need? Purified DNA or RNA In our laboratory: - Blood, bone marrow, thymus, lymphnodes, tonsils, spleen, heart, skin, saliva and more (from humans, pigs and mice) - Cell lines from tissue culture Materials are: - Fresh or frozen, healthy or malignant, before or after treatment/drug exposure Depending on array type: - RNA: ng (mrna or total RNA) - DNA: 100/500 ng - Linear amplification is possible if you have very limited material will introduce bias!!

6 6 Microarrays - Affymetrix Wash station (FS 450) Hybridization owen GeneChip Scanner (GS 3000)

7 7 Microarrays - Affymetrix I

8 8 Microarrays - Affymetrix Probes on array are generated through Photolithography

9 9 Microarrays - Affymetrix DNA eller RNA: fragmented, labelled hybridize data (.CEL files) scan wash

10 10 Setup of microarray experiments What to consider? What is my hypothesis/scientific question? - How many samples do I need? (Power calculations, include age, sex, smoking history, medications and so forth ) - What is published by others? Microarrays online? - Paired samples IS VERY IMPORTANT!! (e.g. tumor vs. normal from the same tissue of each patient possible?) - Ensure a homogeneous mass of cells (laser micro dissection, FACS, purify cell of interest Ideally more than 80 % pure) - Which platform to use? Identical processing of samples (a great meta sheet!) - At the clinic (technician/time to storage/buffer/total freezing time ) - At the laboratory (identical lot no/technician/student ) Perform array hybridization/scan by an intelligent strategy - mix/randomiza states/treatments/conditions of samples

11 11 Quality parameters Quality assessment of arrays Can I include all my.cel files in my analysis? Is the scan ok? (DAT file) Asses.CEL file quality identify outliers. - Sample histogram - Principal Component Analysis 3 nd Principal Komponent (1.5 %) 2 nd Principal Komponent (1.8 %)

12 12 RNA as input Expression arrays: Measures the expression of genes/mirna at the time of RNA purification Exon: Expression level of the individual exon s of genes Exon level expression Gene level expression U133plus2.0: Gene expression from the 3 -end of genes Gene level expression mirna: Expression level of the individual mirnas on the array Gene 1a Gene 1b Gene 1c 5 3 * Genomic DNA Exon Array 3 Array (U133plus2.0) mirna

13 13 Organizing and viewing expression profiling Identify differentially expressed genes/mirna s Genes samples PCA plots heatmap

14 14 Analysis of expression data Supervised Directed by known sample information. Tumor vs normal Samples stratified by clinical outcome, response to treatment Student t-test, correlation, survival analysis Classification, outcome-prediction Unsupervised Expression patterns agnostic to sample information Hierarchical clustering, self-organizing maps, principal component analysis Discovery of tumor subtypes - Verify genes/mirnas by qpcr - Test involvement of gene/mirna in a specific process using e.g. cell line experiments

15 15 Microarray data analysis Supervised analysis Training data set Discovery Validation data set

16 16 Microarray data analysis unsupervised analysis Hierarchiel clustering Different groups of patients is defined based on gene expression profiles

17 17 Microarrays Expression Exon arrays From Thorsen et al.

18 18 DNA as input SNP/cytogenetic-array (DNA): Detection of variations in single nucleotide polymorphisms (SNPs) in individuals and identifies LOH, and copy number variations (CNVs) SNP6.0 ( probes) Cytogenetic Whole-genome 2.7M array or Cyto HD scan ( probes) Probes Copy number probes (to detect CNV) SNP probes: A pair of 3 probes matching either allele A or B (for SNP and LOH)

19 SNP6/Cyto arrays: CNVs in primary vs relapse DLBCL patient - Prospective study: Clinical paired samples from the biobank Amp, del, LOH, SNPs (no normal DNA) Do the relapse tumor have a different genetic profile? 19 p Relaps Primær Amp Del

20 20 SNP6/Cyto arrays Zoom to chromosome 2 Relaps Primær Normal AA, AB, BB LOH AA, BB Regions with Tumor suppressor genes

21 21 SNP6/Cyto arrays Identify minimal commen regions between subsets of samples - Is a region with CN change/loh predominantly in one subset of samples (clinical parameters) What genes are present in CNV regions - Involvement in disease pathogenesis/relapse/resistance Regions with CNV can be verified by qpcr

22 22 Microarrays online Microarray data repositories Gene Expression Omnibus (GEO)(NIH) For most pulications you will have to publish your raw data at GEO. Other databases ArrayExpress ChipDB Stanford/Yale Microarray Database Many organism-specific databases

23 23 Microarrays online Why use outside microarray data? It s free and plentiful!!! - A vast amount of data is available Series, Samples (GEO, 11/ ) - Preliminary data can be used on grant applications - As validation sets for your own discoveries Compare/contrast similar conditions/phenotypes - Use other data sets to expand or narrow your genes/mirnas/cnvs of interest Observe genes of interest in different diseases, species, tissue type, etc Ability to account for other variables outside your study

24 24 Microarrays online Questions to ask when using outside microarray data What is the quality of the data? Is the same platform/labelling method used? Is the study adequately powered? Normalization of data? YES, against controls of the individual study Is sufficient accompanying sample data available?

25 25 Other microarray applications DNA methylation Methylation-sensitive endonucleases, bisulfite modification DNA-protein interactions Chromatin immunoprecipitation ( ChIP-chip ) Gene function Reverse transfection arrays Protein levels, interactions Antibody arrays Tissue expression Tissue microarrays

26 26 Cell lines A cell culture is a complex process, where cells grow under controlled conditions ie. Appropriate culture media, CO2 and O2 i a humidified atmosphere A cell culture can be a cell line or cultivation of primary cells (suspension or adherent cells)

27 27 Cell lines how to make them Cell lines originate from tumor tissue from cancer patient or stem cells Homogenous population of immortal cells with the ability to continous cell divisions normal cells cannot Many cancer cell lines vare produced in the 1950 s or 1960 s International cell depositories store and sell the cell line Cancer cell lines are most commen, but cancer stem cell lines also exists

28 28 Cell lines in cancer research Just a few Drug screens on cell lines (instead of humans!) Validation of microarray discoveries Perform migration or invasion arrays Induction or reduction of gene/mirna expression Pathway inhibitors Drug inhibitors Modified cell lines in mouse-cancer models

29 29 Conclusions Microarrays and cell lines have multiple applications and are very usefull tools in cancer research

30 30 Questions?

31 31 Questions to lecture and to articles 1. Explain the allelic background and CN of the chr regions A-D using A and B 2. How can you induce or reduce the level of a particular protein/gene/mirna in cell lines? And how can you measure it? Alizadeh et al: 3. How is the Lymphochip different from the expression arrays I presented? 4. Their control mrna is a pool of 9 cell lines? Why is that not optimal? What is a much better reference/control? 5. The paper is from Is it implemented in clinical practice in DK? 6. How would you setup an experiment tomorrow to look for subgroups in a heterogenous disease? Thorsen et al: 7. What is alternatice transcription start site usage? (TSS) What is alternative splicing? 8. Why do they analyse the isoforms of the 3 genes in laser capture microdissected samples? A B C D