Powerpoint

A review of the cancer gene cloning strategies

You must be logged in to download this document
Reviews
Shared by: sammyc2007
Stats
views:
84
downloads:
5
rating:
not rated
reviews:
0
posted:
4/11/2008
language:
English
pages:
0
A review of the cancer gene cloning strategies: pre-genomic era STONE AGE post-genomic eras MODERN AGE www.interlog.com/~lenore/ art/pix/stone.jpg fmwww.bc.edu/JSPMA/ Pre-genomic era startegy are basic Knowledge about human genome is a landmark that gave us a chance to get closer to goal, but not solve all problems in goal attaining itself (in cancer gene cloning) Typical strategy to find a cancer-related gene contain many steps that take time There are many variations in the strategy, and many different approaches to prove that gene is cancer-related can be chosen HUMAN GENOME SEQUENCE CAN HELP US TO CHOOSE CANDIDATE GENES but have nothing to do with answers “YES”/”NO” In a modern time a search for a cancer related gene IS NOT A TASK OF CLASSICAL GENETICS You ask why? 1. Most changes in cancer-related genes occurs in somatic cells, not in germ-line 2. Almost all Mendelian germ-line affected genes that are underlie cancer syndromes are already described 3. All “associations” and “influences” of polymorhic allele to cancer are true weak to moderate; Up to now most attempts to locate cancer polymorphism with methods of classical genetics are inconclusive. In this course of lecture we will review cancer syndromes itself BUT We will omit “classical genetics” strategies to clone cancer genes Linkage disequilibrium, log of odds of linkage (LOD) scores…. “Classical genetics” strategies to clone genes involved in inherited cancer syndromes are similar to “classical genetics” strategies to clone any non-cancer syndrome involved gene, and subject of Human Genetics Cancer genetics = SOMATIC CELL GENETICS HOW TO FIND A GENE Positional cloning – based strategies Strategies not connected to certain position in genome Goal of approach: Goal of approach: choose a list of candidates In a whole genome-based search located in place of interest, make list of candidates located in different places in genome; Remove false-positives; Prove that a particular candidate is a true cancer related gene HOW TO FIND A GENE Locate a chromosomal area deleted in particular tumor type Screen hundreds of patients to find a “lucky” small deletion Make a cosmid (PAC) contig Retrieve a genomic sequence You Can Believe In The Strategy Map all genes-candidates (experimentally or in silico) Check all candidates (try mutations, expression in cell lines, or knockout in mice) The Pure Science Starts HERE Honestly study gene functions in the tissues and tumors Locate a chromosomal area deleted in particular tumor type (Deletion mapping) (Study a sites of translocations) often accompanied by deletion Chromosome-based screenings Gross chromosomal abnormalities Polymorhism-based screenings LOH (loss of heterozygozity) of polymorphic makers with known locations FISH Analysis CGH analysis Gross chromosomal abnormalities (Conventional cytogenetics testing) t(9:22) CML Microscopically visible Trained eye can recognize chromosomes After conventional Band-revealing staining LOCUSES revealed by Gross chromosomal abnormality staining are include hundreds of genes…. Problem… www.cmlsupport.com/cyto.jpg FISH analysis (Fluorescent in situ hybridization) -- translocation DNA probes are hybridized to fixed cells on microscope slides. metaphase The hybridization to target loci is visualized by the detection of fluorescent signals on metaphase chromosomes or interphase nuclei. Pre-metaphase FITC or Fluorescein (green), Texas-red (red), Rhodamine (red), DAPI (blue) COMMON FLUORO DYES Green + RED = YELLOW mti-n.mti.uni-jena.de/~huwww/ MOL_ZYTO/imageAU9.J FISH analysis (Fluorescent in situ hybridization) -- DELETION Interphase FISH, relaxed chromatin Two green, two reds on different chromosomes – no deletion Two green, one red – One red is deleted. Size of deletion can not be estimated. Deletion size is smaller than distance to green signal (probe) GREEN SIGNAL SERVE AS A CONTROL PROBE ON A SAME CHROMOSOME. http://lambertlab.uams.edu/images/cell.jpg Aneuploidy revealed by FISH 8 copies of chromosome 13 in pancreatic carcinoma Chromosome13-specific probe painting http://68.33.28.8/geneticsweb/fish.htm RESOLUTION of FISH methods Classical Cytogenetics can see aberrations approximately one chromosomal band in size A. High resolution FISH mapping on interphase chromatin. The resolution (distance between probes) of such mapping is approximately 20 Kb while the coverage is 20Kb -- 5,000Kb. Coverage is a size of the probe itself. B. High resolution FISH mapping on released DNA fiber. The resolution of DNA fiber mapping is 1-2 Kb. The figure illustrates three probes ( a, b and c) simultaneously located within 50 kb region www.seedna.com/gif/fiber1.jpg FIBER FISH – down to exon level! Fiber-FISH of HER-2/neu (GREEN) and topoisomerase II-alpha (RED) in DNA from UACC-812 cell line You can see exons! To be honest, not always…. It is a difficult method. Most researchers stop on interphase FISH stage www.uta.fi/laitokset/imt/ sgy/jorma/uaccfiber.jpg Comparative Genomics Hybridizations (CGH) CGH is a genome-wide scanning of differences in DNA sequence copy number CGH is based on a modified in situ hybridisation, where differentially labelled test DNA (cancer, green) and reference DNA (normal, red) are co-hybridised to normal metaphase spreads Both test (tumor) and reference (normal) are whole genome DNA preparations Digital imaging system DNA gains and in test DNA are seen as chromosomal regions with an increased fluorescence ratio (> 1.25), while losses result in a reduced ratio (<0.75). Typical pictures of CGH Of course, CGH data should coincide with FISH and LOH data Pitfalls of CGH 1. A technically demanding technique, requiring expensive hardware and software. 2. Cannot detect balanced translocations or rearrangements. (Only net gain or loss of material). 3. There is a room for standardization, more objective and uniform interpretation and statistical evaluation of the CGH profiles. Common database has just been set. 4. The technique is limited by the resolution of the hybridisation target, e.g. the metaphase chromosomes. The current resolution is 5-10Mb. Changes affecting smaller regions are only detectable in the case of high level amplifications (e.g. 5-10 fold amplification of 1Mb). 5. Sensitivity can also be hampered by contamination of tumor cells with normal cells, Mosaicism is difficult for detection. LOH (loss of heterozygosity) Reminder: Informative microsatellite ( = polymorphic in this particular normal sample) TWO alleles in normal tissue versus ONE allele in tumor tissue RESOLUTION of LOH deletion mapping depends on a density of polymorphic markers on the map. Average density on good whole genome LOH scan is 10 Mb. The total genetic map length of the human genome is about 3,000 Mb. We have to run 300 polymorphic markers (500 to be sure) A hell of work to 10 Mb resolution! Typical result of LOH mapping Allelotyping of ductal carcinoma in situ of the breast: deletion of loci on 8p, 13q, 16q,17p, and 17q. [clear box], p arm; [black-filled box], q arm www.genlink.wustl.edu/.../figures/ figure1_radford1.html How to avoid huge amount of work and poor resolution of LOH? 1. Start from particular chromosome. If previous analysis suggests that chromosome 16 is involved in breast cancer, work only with chromosome 16 – derived marker panel. You can achieve a good resolution by choosing 300 markers form the same chromosome. 2. Use polymorphic markers residing in the introns of candidate genes. In such case you can be sure that candidate gene is deleted without extensive checking of neighbouring genes. Typical result of LOH mapping Smallest regions of overlap of LOH patterns on 16q in breast cancer PISSLRE, copine VII, CTCF, SIAH1 are excluded (1999-2002) Those smallest regions are ready to go in screening for genes residing in them (1994)! WWOX, a gene that maps to the common fragile site FRA16D region in chromosome 16q23.3-24.1 So, resolution is still poor….. CBFA2T3, 2002 Screen hundreds of patients to find a “lucky” small deletion (Small-scale deletion mapping) FiberFish (as was described before) Genomic Southern with densely scattered probes Electrophoresis of digested genomicDNA (band sizes 1-10 kb, EcoRI, HindIII or both A serie of consequent hybridizations with short, non-repetitive genomic probes with known locations Band that is absent on autograph is homozygously deleted Band that is twice weaker than control is hemizygously deleted How genomic Southern looks Housekeeping gene Serve as a control Potential Pitfall: presence of normal cells makes 2-allele deleted probe looks like 1-allele deleted; 1-allele deletion can be undistinguishable from normal Screen hundreds of patients to find a “lucky” small deletion (Small-scale deletion mapping) FiberFish (as was described before) Genomic Southern with densely scattered probes Why not detect by simple PCR? Why not detect by simple PCR? Speaking theoretically, we can design primers for every probe (the same probe as for genomic Southern) And check it easily without any time-consuming hybridization In reality, It will be very difficult to do Because of cross-contamination due to the extreme sensitivity of PCR We will have a mess of PCR-amplified traces of air-born DNA contamination + sample to sample difference of normal DNA contamination, That is why PCR detection of deletions method is not very practical Screen hundreds of patients to find a “lucky” small deletion (Small-scale deletion mapping) FiberFish (as was described before) Genomic Southern with densely scattered probes Why not detect by simple PCR? Representation Difference Analysis (RDA) {“very special” PCR} Representation Difference Analysis (RDA) Introduced by Nikolay Lisitsyn (Science 259: 946, 1993) It is a PCR procedure that analyzes the difference between two complex sets of genomes RDA detects deletions, rearrangements, or exogenous viral DNA sequences RDA enriches for unique DNA sequences from one of the genomes by removing shared sequences. It takes advantage of PCR to selectively amplify the regions of difference DRIVER NORMAL TESTER CANCER 1. FRAGMENTED TESTER DNA IS LIGATED WITH ADAPTER PRIMERS FOR PCR 2. TESTER WITH PRIMERS ATTACHED is melted and re-anneled with DRIVER (IN EXCESS) CANCER 3. FILL IN ENDS OF FRAGMENTS to create double-stranded PCR priming sequences, then PCR AMPLIFY 4. Only sequences unique to tester WILL AMPLIFY EXPONENTIALLY CANCER 5. ADD MORE DRIVER to PCR products and SUBTRACT DRIVER AGAIN. X X www.ich.ucl.ac.uk/.../academicunits/ HOW RDA LOOKS 1. 2. 3. 4. 5. Lane 1 Molecular weight markers Lane 2 TESTER (digested tumor genomic DNA) Lanes 3 to 5 progressive enrichment for sequences amplified in tumor DNA following three successive rounds of subtractive hybridisation. www.tv.slu.se/birch/ image1.htm PITFALLS OF RDA 1. Amplifications are more easily detected by RDA than deletions, (as we always should add an excess of driver). Normal driver DNA is usually more available than cancer driver DNA 2. If studied tester sample have more than one region of deletion/amplification, found genomic probes will belong to all rearranged regions (will be scattered across the genome) 3. All disadvantages of PCR (all contaminations will be found as false-positives!) + Make a cosmid or PAC contig That overlap an area of interest As we have now complete sequences of human and mouse genomes, in many cases we no need to fulfill this goal anymore However This step still can not be skipped for mapping of cancer-related genes in model animals and in livestock ACTUALLY, MOUSE IS NOT THAT GOOD MODEL FOR MANY HUMAN CANCERS….. Typical representation of contig assembly Polmorphic markers or mapped probes used as anchors Contig can be made from cosmids, PACs or YACs Most reliable contigs are 4 to 7x coverage http://www.mrc-lmb.cam.ac.uk/happy/gifs/contig.gif HOW TO BUILD A CONTIG Every cosmid presumably belonging to the region of interest is hybridized to all cosmids from chromosome-specific library with 5-7x coverage Results of all hybridisations are subject to analysis by contig-building software Weak (less covered) points need re-hybridization to libraries made by different method http://www.roche-applied-science.com/dig/images/dot_blot.jpg Pitfalls of contig construction in the areas deleted in tumors 1. Areas rearranged in tumors often contain a lot of repeats (that is why they are prone to rearrangements). Repetitive areas are difficult to clone (therefore they are under-represented in libraries). We can overcome it by extensive hybridizations (enhancing the coverage) or by using special cloning systems durable to loss of repetitive inserts 2. Contig branching (because of region specific low copy repeats) Retrieve a genomic sequence than computationally search for candidates Currently we able to retrieve free of charge: 1. Human Genomic Sequence located between two known markers 3. BLAST Human Genomic Sequence to mouse genome and draft genome and retrieve corresponding genomic sequences 2. BLAST Human Genomic Sequence to human, mouse and other subdivisions of dbEST database and retrieve corresponding expressed sequences Comparative genomics Direct comparizon of two synthenic genome areas (often human vs mouse) Helps to find all conservative ( important) region. 1. genes that absent in dbEST because of restricted pattern of expression or low-level expression 2. Exons that absent in common mRNA, but important for certain (ideally, cancer-related) gene function 3. Regulatory regions (promoters, enchancers, silencers, SAR/MAR =scaffold-associated /matrix-associated regions VISTA is a best tool for comparative genomic study Lawrence Berkeley National Laboratory, 2002 It was designed to visualize long sequence alignments of DNA from two or more species with annotation information mVISTA (main VISTA) A program for visualizing alignments of an arbitrary number of genomic sequences from different species rVISTA (regulatory VISTA) combines transcription factor binding sites database search with a comparative sequence analysis. www.lbl.gov HOW VISTA OUTPUT LOOKS www.lbl.gov/ EST-based reconstruction of mRNA isoforms ESTs also can be aligned in contigs. Automatically built EST contigs are stored in UNIGENE and in TIGR database Manual alignment of ESTs in contig is time-consuming, but gave to researcher a deeper understanding of gene structure, (…presumably…) error-free and allows to make a multi-species ESTs contigs. Some area of the gene of interest can be overlapped by Mouse-derived clones, and reconstructed by conservative human genome sequence EST-based semi-automatic scheme of gene http://www.mad-cow.org/contig.gif Experimental search for cancer-related genes in defined chromosomal regions Hybridization screening of cDNA libraries with probes made from whole cosmids (PACs, YACs). 1. Before hybridization, the complexity of the probes should be reduced via pre-hybridization with repetitive fraction of DNA 2. Choice of library is dictated by tissue of tumor origin. So, to find a leukemia-involved gene it will be clever to screen lymphocyte-derived library. Not muscle, brain… (By the way, testis is a clever choice for any screening) Strategies of cancer gene search not connected to certain locus in the genome Differential display Tumor markers and phage display Microarrays SAGE (Serial Analysis of Gene Expression) Kinetics of paper publishing RDA and Subtr Hybr is almost the same technic http://www.genhunter.com/support/comparison.graphic.jpg Differential Displaying (DD) - PCR A set of different primers for DDRT-PCR are complimentary to poly (A), and contain two additional 3’ nucleotides like GG, GG, GA…. All separately 5’ xxxxxxxxxxxxxCTAAAAAAAAAA 3’ GATTTTTTTTTTT 5’ 12 primers = 12 aliquotes First strand reverse transcription to cDNAs in 12 aliquotes 2nd PCR with the same anchor primers (separately) and a randomly designed decamer in the presence of labeled dATP for visualization 2nd PCR A Arbitrary primers can be gene-specific by chance Gene-specific primer B oligo dT primer C D Possible primer combinations (we can not control them) ALL 12 PCR reaction ARE MADE with mRNA from tumor and normal sample, then separated in parallel lanes on gel Differentially expressed products are seen after comparison http://biology.uark.edu/drhoads/ddrt_pcr.gif Verification is extremely important www.jenapharm.de/eng/research/endo/bilder/genomics.jpg Most common issues with the DDRT method A. High Frequency of false positives 1. Fail to re-amplify with the same primers 2. Fail to be differentially expressed on Northern B. Low Sensitivity for transcripts that are expressed at (very) low copy numbers more than 70 technical articles have been published on improvements and powerful derivatives of the differential display method (mostly on specificity improvement) SAGE (Serial Analysis of Gene Expression) Invented in 1995 Velculescu V.E, Zhang L., Vogelstein B. and Kinzler K. W. (Science 270:484-487, 1995) Includes tons of sequencing SAGE Scheme 1. The restriction enzyme Nla III, = "anchoring enzyme" (AE), cleaves at the sequence 5'-GTAC, leaving a four nucleotide 3' overhang. BIOTIN overhangs Biotinylated fragments are isolated using streptavidin beads. 2. Beads with DNA divide in two tubes and DNA is ligated to linkers A or B. The linkers contain unique primer binding sites, the recognition sequence (5'-GGGAC) for a tagging enzyme (TE), in this case BsmFI, and an Nla III compatible sticky end. Cleave with BsmFI tagging enzyme (TE) and blunt-end-fill in. The enzyme BsmFI cuts 10 and 14 bases in the 3' direction from its recognition site, thus leaving the 9-11 nt "Tag” connected to linkers. BsmFI rec site BsmFI rec site 9-11 nt in size 9-11 nt in size mRNA-specific TAGs All pieces with beads ligated all together and amplified using primers A and B. Restriction with anchoring enzyme The we isolate ditags, concatenate them and clone. X and O represent nucleotides from different transcripts. SEQUENCING OF concatemers SAGE software searches GenBank for matches to each tag Count their relative abundance in tumor and control sample SAGE analysis of genes that change their expression during p53-induced apoptosis www.sagenet.org/ p53sage/ MAINSAGE.HTM Colon carcinoma SAGE project 290,394 tags were analyzed from normal, adenomatous, and cancerous colonic epithelium 21,343 different transcripts observed 957 were found to be differentially expressed 45 transcripts were elevated 20-fold in adenomas, 40 transcripts were elevated 20-fold in cancers, 9 transcripts were elevated 20-fold in both. Cancer Res 2001 Oct 1;61(19):6996-7001 Diagram of genes overexepressed and underexpressed in Colon Cancer UNDEREXPRESSED OVEREXPRESSED Major conclusion: primary tumors and tumor cell lines are very different object to study Experimental proof of SAGE data H769020 (TGF-beta induced gene beta-IGH3, M77349) , increased H516402 (CL 100protein tyrosine phosphotase, X68277) , decreased EXPRESSION MICROARRAY High-density arranged gene- representing spots on surface suitable for hybridization Nylon Surface Probe labeling Radioactive Glass or plastic Fluorescent PCR fragments Genes can be represented by Oligonucleotides www.dkfz-heidelberg.de/funct_genome/ fig-cancer-chip.jpg Working cycle of fluorescently labelling microarray Healthy lung Lung tumor Excitation Emission Green Red Fluorescent scanning Normal in red Tumor in green Hybridization to microarray Comparizon of gene profiles www.omrf.org/OMRF/Images/PRPics/ 2001SprSchematic.jpg Representation of genes differentially expressed in normal mucosa and colon tumors (upper and lower boundaries represent a 4-fold difference). 2% of 4000 genes changed expression significantly microarray.princeton.edu/oncology/ images/figure1big.jpg Adenoma vs. Carcinoma (differential diagnosis of this states by small subset of genes) microarray.princeton.edu/oncology/ images/figure1big.jpg Golub et al., Molecular Classification of Cancer: Class Discovery and Class Prediction by gene expression monitoring. Science 1999 286: 531-537 For the most effective treatment in a specific cancer type. Acute Lymphoblastic Leukemia vs Actue Myeloid Leukemia RNA from 38 Bone Marrow Samples (27 ALL, 11 AML) hybridized to high-density oligonucleotide microarrays of 6817 human genes 50 Genes identified as best predictors of cancer class; so real diagnostic array can be cut to 50 spots TUMOR MARKERS AND PHAGE DISPLAY Tumor markers are proteins that can often be detected in higher-than-normal amounts in the blood, urine or body tissues of some patients with certain types of cancer. Tumor markers are produced either by the tumor itself or by the body in response to the presence of cancer or certain benign conditions. Examples of tumor markers: PSA and PAP Prostate Specific Antigen (PSA) and Prostatic Acid Phosphatase (PAP) are elevated in benign prostate conditions, such as prostatitis and benign prostatic hyperplasia (BPH), or in a prostatic carcimomas. CA125 Many women with ovarian cancer have elevated CA 125 levels. A falling CA 125 level generally indicates that the cancer is responding to treatment. It is also used for monitoring of recurrence. Carcinoembryonic Antigen (CEA) Used for monitoring of colorectal and lung cancer Alpha-fetoprotein (AFP) AFP is normally produced by a developing fetus. An elevated level of AFP strongly suggests the presence of either primary liver cancer or germ cell cancer Changes in tumor marker concentration during the course of disease No response to treatment No treatemnt Relapse Good response Second remission Remission : www.dpcweb.com/medical/cancer/ cancer_tm_overview_lg.html Phage display Is a method of a search for a new tumor markers Antibody fragments can nowadays be isolated from naive phage display libraries without immunisation, by-passing hybridoma technology human recombinant antibodies can be presented in phage libraries in scFv format. They consist of a single polypeptide chain: -- antibody heavy chain variable domain (VH) -- a flexible polypeptide linker -- a light chain variable domain (VL) How scFv antibodies looks : Ig G Bispecific IgG Fab Fv scFv Phage display usually utilize only 3 of 50 antibody germline gene segments. Large repertoire produced by appending short variable complementarity-determining regions 3 (CDR3) onto them. (random loops of 4, 5 or 6 amino acids. ) ....... C92 A R (X)4-6 F D Y ...... Scheme of phagemid library cloning scFv antibodies are presented on coat of phages We can generate a millions of random scFv plaques representing a variety of potential Abs on bacterial lawn www.pharma.ethz.ch/bmm /protocols/schema.jpg Selection of antibodies from phage display libraries: the enrichment of an antigen-specific phage-antibody (circle) on a background of non specific phage-antibodies (square). www.pharma.ethz.ch/bmm/ protocols/schema.jpg Antigen comes from serum of cancer patients HOW to prove that our candidate is real cancer-related gene Detection of mutations in tumor samples Experiments on cells in culture Promoter methylation in tumor samples Knockout/ transgenic mice Detection of mutations in tumor samples DGGE (Denaturing Gradeint Gel Electrophoresis) Both discovery and diagnostics SSCP (Single Strand Conformation Polymorphism) SEQUENCING – a king of methods. It is already cheap enough Mutation detection chips (more diagnostics than discovery) Allele-specific oligonucleotides (ASO) and modifications… (Diagnostics only) SSCP (Single Strand Conformation Polymorphism) PCR product is denatured, chilled quickly and run on non-denaturing gels. Any sequence change causes formation a different conformer resulting in variation in strand mobility. Needs sequencing to prove a significance of the change www.uct.ac.za/depts/liver/ images/sscp.jpg A differences in conformation depends on conditions of gel running (% of buffer and acrilamide, glycine in buffer, temperature etc….) Often it is important to check 3-5 different conditions before undoubtful resolution can be achieved www.hci.utah.edu/groups/genomics/ images/APC%20SSCP.gif DGGE (Denaturing Gradeint Gel Electrophoresis) The small (200-700 bp) genomic fragments are run on a low to high denaturant GRADIENT acrylamide gel Each fragments move according to molecular weight, but as they progress into more denaturing conditions, each (depending on its sequence composition) reaches A POINT where the DNA BEGINS TO MELT They retard, and we will see shift in mobility We will see different shifts in mobility for differing products Here is just one sample ! hwww.enbiogen.com/product/ image/tgge1.gif “mirroring” of two curves indicative of mutation Separated homoand heterodimeres Urea/formamide gradient 0%100% Many samples in one gel – we will not see any curves 1- normal 3- Homozygous mutations will yield one band on a different position 2, 4, 5, 6 – heterozygous mutations will yield 4 bands (2 homozygous and 2 heterozygous) NOT ALL BANDS ARE SEEN !!!!! www.leveninc.com/cftr_ex.gif Sequencing is direct method of mutation detection Mutations Deletion www.infobiogen.fr/doc/STADENdoc/ manual/ Mutation detection chips photolithography or piezoelectric printing of Prefabricated Oligonucleotides OR directed oligonucleotide synthesis on chip Example: Chip to detect all possible heterozygous mutations in the 3.4 kb BRCA1 exon 11 (~60% of coding region). > 96,600 oligonucleotides designed to detect all possible single-base substitutions, single-base insertions and 1-5 bp deletions on both strands. 28 separate oligonucleotides (sense and antisense strands) for each nt position Allele-specific probes (tons of modifications of principle) Just one variant (fluorescent) Principle: specific annealing of probes to one but not to another alelle that differ by one nt Suitable only for detection of known mutations www.idahotech.com/.../RAPID/ images/ hybridizationprobes.jpg Promoter methylation in tumor samples c Best methods are based on bisulfite modification of genomic DNA CU C m unmodified www.bmskorea.co.kr/ Note the disappearance of bands in the "C" lane of the unmethylated DNA demonstrating that the unmethylated cytosine nucleotides were converted to uracil by the bisulfite treatment. G www.intergenco.com/pictures/ cpgenome_seq.jpg Classical representation of promoter methylation in papers otir.cancer.gov/tech/slides-brock/ 19-01_sequence.gif Experiments on cells in culture Transfection a TSG to cancer cells makes changes of cell phenotype Apoptosis Growth became slow Transfection an oncogene to normal cells makes them transformed STOP make tumors in nude mice Rapidly divide grow in soft agar; Start growing in multilayer Stop grow in soft agar; grow only in monolayer Morphology changes (more ECM and attachment) Make tumors in nude mice Morphology changes (less ECM and attachment) Morphology changes after TSG transfection (MAD = Myc antagonist) Less cells; shape not “round” Morphology comparison of parent cells (A), control BEL-7404M0 cells (B) and mad overexpressed BEL-7404-M1 cells (C). http://www.cell-research.com/991/991-xyh.htm Mad inhibit growth of cells in culture Mock–transfected and control cells Mad –transfected cells http://www.cell-research.com/991/991-xyh.htm Influence of MAD transfection on growth in soft agar Cells BEL-7404 cell BEL-7404-M0 cell BEL-7404-M1 cell Mad -transfected Number of colonies in soft agar 1104 1031 151 http://www.cell-research.com/991/991-xyh.htm Cell cycle analysis of Mad-overexpressing BEL-7404-M1 cells Cells Percentage in cell cycle G0/G1 BEL-7404 cells BEL-7404-M1 cells 48.50% 63.37% S 26.95% 18.40% G2/M 24.45% 18.23% BEL-7404-M0 cells 50.15% 24.45% 25.40% Conclusion: MAD-overexpressing cells are in quiescence more often than control cells NUDE MICE with tumors grown from transfected cell Tumor cells transfected with MAD (suppressor gene) produce tumor of smaller size research.dfci.harvard.edu/ coe/project_03/ KNOCKOUT MICE Normal (+) gene X Genome Isolate gene X and insert it into vector. Defective (-) Gene X VECTOR MARKER GENE Inactivate the gene by inserting a marker gene that make cell resistont to antibiotic (e.g. puromycin) Transfer vector with (-) gene X into ES cells (embryonic stem) Vector and genome will recombine via homologous sequences Grow ES cells in antibiotic containing media; Only cell with marker gene ( without target gene) will survive Inject ES cells with (-) gene X into early mouse embryo Transfer embryos to surrogate mothers Resulting chimaras have some cells with (+) gene X and (-) gene X. Mate them with normal mice Lucky you, if germline contain (-) gene X Screen pups to find -/+ and mate them Next generation will split as 3:1 (Mendelian) Evaluation of KO mice features Cancer-involved genes often produce organismal changes. 1. (-/-) embryos can die on early gestational stages (like it happens with BRCA 1 and 2 embryos) In this case we will see only +/+ and +/- pups (changes in Mendelian frequency) 2. 3. (-/-) pups can have profound defects in different systems, often problems with immunity or behavior (-/-) mice can develop more spontaneous tumors than normal ones, or are more susceptible to chemical induction of tumorigenesis
Related docs
A review of the cancer gene cloning strategies
Views: 84  |  Downloads: 5
Gene Upshaw
Views: 187  |  Downloads: 0
Lung cancer and gene therapy
Views: 115  |  Downloads: 6
Gene environmental interactions in cancer
Views: 46  |  Downloads: 1
Gene selection
Views: 72  |  Downloads: 4
Gene Sequencing for Research on Aging
Views: 147  |  Downloads: 1
cloning lesson
Views: 57  |  Downloads: 2
Other docs by sammyc2007