Genomika klinikai alkalmazásai 2.

1. Genomika klinikai alkalmazásai2. TUMOR microRNS Falus András

2. Ígéretes eredmények microarray génexpresszió mérés klinikai alkalmazásában • Hisztológiailag hasonló tumorok elkülönítése • Leukémia • Melanoma • Emlőrák • Jobb prognózis • Betegek szubtipizálása • Metasztázis kialakulásának jóslása • Gyógyszerérzékenység jóslása • Áttétes tumorok eredetének kiderítése

3. Melanoma progression

4. Autocrine and paracrine regulations in melanoma Lazar et al, 2000

5. Pos, et al

9. Diffúz nagysejtes B sejt lymphoma Eddig nem volt diff. diagnózisa: • Szövettani • Immunológiai • PCR (egyes gének) • módszerrel

11. Rheum.arthritis specifikus “signature” (202 RA beteg limfocitái) lymphochip Immungenom: az emberi genom 6%-a

12. A melanoma máj metastasisprediktor génkészlete Bittner et al, Nature, August, 2000 Saghatelian et al, PNAS, 2004

15. The most frequent chromosomal alterations in prostate cancer are deletions of parts of chromosome arms 6q, 8p, 10q, 13q, 16q and 17p, and amplification of 8q (Trapman et al. 1994; Van Alewijk et al. 1999 for chromosome arm 8p). Some chromosomal alterations can already be recognized in pre-cancerous lesions. However, chromosomal alterations are most frequent in tumor metastases. In a subset of endocrine-therapy resistant prostate cancers, amplification of the androgen receptor gene, which is located on the X chromosome, has been found (Koivisto et al. 1997). Out of the many known traditional oncogenes and tumor suppressor genes, inactivation of P53 at 17p and PTEN at 10q contribute most frequently to prostate cancer growth (Vlietstra et al., 1998).

20. J Clin Invest. 2004 March 15; 113 (6): 913–923DOI: 10.1172/JCI200420032 Gene expression profiling predicts clinical outcome of prostate cancer Gennadi V. Glinsky,1 Anna B. Glinskii,1 Andrew J. Stephenson, 2 Robert M. Hoffman,3 and William L. Gerald2 1Sidney Kimmel Cancer Center, San Diego, California, USA. 2Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. 3AntiCancer Inc., San Diego, California, USA. 12,625 transcripts in prostate tumors from patients with distinct clinical outcomes after therapy as well as metastatic human prostate cancer xenografts in nude mice

23. Orvosi Nobel-dij, 2001 Hunt Nurse Hartwell

25. After the genome sequencing projects • non-protein-coding RNAs can represent up to 97%–98% of all transcriptional output from the human genome. • much less than 1% (0.1-0.5%) of the sequence differences between individual humans and primates occurs in protein-coding sequences (versus appr 4% in non-coding when humans and apes compared) (Venter et al. 2001) • the majority of phenotypic variation between individuals (and species) results from differences in the control architecture, not the proteins themselves. • phenotypic variation in complex organisms results from the differential use of a set of core components is becoming common (Gerhart and Kirschner 1997; Duboule and Wilkins 1998)

26. The revolution of non-coding RNA • Housekeeping • transfer RNA • ribosomal RNA • small nuclear RNA • small nucleolar RNA Piwi-interacting RNA (Drosophila, mouse, rat) histone és DNA-methylation→ Silencing selfish genetic elements in male germ cells epigenetics Repeat-associated siRNA (plants, Drosophila, yeast) histone és DNA-methylation→ Silencing selfish genetic elements Non-coding RNA =ncRNA, make transcripts that function directly as RNA, rather than encoding proteins • Regulator • piRNA • rasiRNA • microRNA • ? microRNA (plants és animals) RNA-degradation and/or inhibition of translation→ wide spectrum of regulated processes, a new layer of gene expression regulation

27. Biogenesis and mechanism of action The stem-loop structure is cleaved by the nuclear RNase III Drosha to release the precursor of miRNA (pre-miRNA) Dicer, is responsible for generating an approximately 21-nt, short, single stranded RNA that is the mature microRNA. Dicer was first recognized for its role in generating siRNAs that mediate RNA interference (RNAi) (Bernstein et al. 2001). Mature miRNAs are incorporated into the effector complexes, which are known as ‘miRNP’, ‘mirgonaute’ or, more generally, ‘miRISC’ (miRNA-containing RNA induced silencing complex). The effector complex containing siRNA, in distinction, is referred to as ‘RISC’,‘sirgonaute’ or siRISC’.

28. Structure of the hairpin MicroRNAs are named using the “miR” prefix and a unique identifying number (e.g., miR-1, miR-2, . . . miR-89, etc.). The identifying numbers are assigned sequentially, with identical miRNAs having the same number, regardless of organism. Nearly identical orthologs can also be given the same number, at the discretion of the researcher. Identical or very similar miRNA sequences within a species can also be given the same number, with their genes distinguished by letter and/or numeral suffixes, according to the convention of the organism (e.g., the ∼22-nt transcripts of Drosophila mir-13a and mir-13b are slightly different in sequence, whereas those of mir-6-1 and mir-6-2 are identical; Lagos-Quintana et al. 2001). Ambros et al.: A uniform system for microRNA annotation, RNA 2003. mature sequence stem-loop flanking sequence Bartel DP. Cell 116:281, 2004

29. microRNA: new members of the RNA-world • The first miRNA was discovered in 1993 by Lee, Feinbaum, and Ambros in C. elegans. • Hundreds of miRNAs have been identified in plants and animals, either through computational searches, RT-PCR-mediated cloning, or both. • They were found in organisms ranging from nematodes to plants to humans. Many individual miRNAs are conserved across widely diverse phyla, indicating their physiological importance. • 474 human miRNAs were tabulated in MicroRNA Registry until recently • It was estimated that there could be from 200 to 1000 microRNA genes in the mammalian genome (1%-3% of known genes are represented by microRNAs). Today the number of microRNAs, including those electronically cloned, is over 1000 and still growing.

30. in silico cloning: miRNA gene finding Sequence of non-repetitive genomic regions Conservation filtering using genome sequences of phylogenetically closely related species. AGCTTCGGGTTGATC RNA-folding program Training set: experimentally validated miRNA genes Machine learning algorythms stable extended stem-loop structures, with continuous helical pairing and a few internal bulges. Northern blot, PCR, microarray

31. The function: fine-tuning of gene expression Probing microRNAs with microarrays: Tissue specificity and functional inference BABAK T et al., RNA (2004), 10:1813–1819. • The ability to simultaneously regulate large sets of genes by a single microRNA appears to be at the heart of control of multiple pathways that include morphogenesis and cell fate decisions, response to infectious organisms, and centromeric heterochromatin structure. • It was found that different tissues have distinct miRNA expression profiles and that related tissues/organs (e.g., heart and muscle) have more similar profiles than more functionally distant tissues/organs.

32. Tissue specificity • miRNA expression profile reflects on the developmental origin Shingara et al.: An optimized isolation and labeling platform for accurate microRNA expression profiling, RNA 2005

33. Cell-type or differentiation stage specific expression? • In haemopoietic differentiation: the most pronounced similarities were observed among fully differentiated effector cells (Th1 and Th2 lymphocytes and mast cells) and • precursors at comparable stages of differentiation (double negative thymocytes and pro-B cells), • commitment to particular cellular lineages, miRNAs might have an important general role in the mechanism of cell differentiation and maintenance of cell identity. • (Silvia Monticelli: MicroRNA profiling of the murine hematopoietic system, Genome Biology 2005) Seminars in Cancer Biology, 2007/8 In press (guest edited by A.Falus)

34. Distribution of putative function using computational approaches Gaidatzis et al: Inference of miRNA targets using evolutionary conservation and pathway analysis BMC Bioinformatics 2007, 8:69

35. microRNAs in the “exosomal shuttled RNA” It is now clear that miRNAs not only contribute in developmental processes related funtions, but also play an important role in the response of cells to outer signals, moreover miRNAs can be tools in the communication between different cell types. In a recent paper revealed that miRNAs are present in the by mast cells secreted microvesicles as part of the delivered “exosomal shuttled RNA”. Through this newly discovered form of cell-cell communication the donor cell may modulate the posttranscriptional system of target cells directly. Valadi H et al.: Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007 Jun;9(6):654-9.

36. miRNAs as tumor suppressors and oncogenes In oncogenesis, some miRNAs expression is decreased in cancerous cells. These types of miRNAs are considered tumorsuppressor genes nucleus cytoplasm Those miRNAs whose expression is increased in tumors may be considered as oncogenes. These oncogene miRNAs, called “oncomirs”, usually promote tumor development by negatively inhibiting tumor suppressor genes and/or genes that control cell differentiation or apoptosis. One of the strands incorporated to RISC RISC mRNA degradation Translational repression „haploidomics”

37. Other examples

38. Example: mir-17-92 polycistron • mir-17–92 cluster is a miRNA polycistron located at chromosome 13q31, a genomic locus that is amplified in lung cancer and several kinds of lymphoma, including diffuse large B-cell lymphoma • Overexpression of miR-17–92 using transgenic mice (hematopoietic stem cells)significantly accelerated the formation of lymphoid malignancies (He et al., 2005b). • The expression of miR-17–92 is related to the expression of c-Myc gene; both miR-17–92 and c-Myc regulate the expression of cell cycle transcription factor gene E2F1(O'Donnell et al., 2005) These findings suggest that c-Myc regulated miR-17–92 modulates E2F1 expression (O'Donnell et al., 2005), that affects apoptosis-mediated cell death through the ARE-p53 pathway in which miR-17–92 inhibits Myc induced apoptosis (Hammond, 2006; O'Donnell et al., 2005).

40. miRNA in tumor classification • Hierarchical clustering of the samples using miRNA profiles paralleled the developmental origins of the tissues. • miRNAs could be used to distinguish tumours from normal tissues • Tumours of histologically uncertain cellular origin High diagnostic relevance Lu et al.:Nature, 2005

41. miRNA in tumor classification • MicroRNA expression changes have been described to correlate with the clinico-pathological features of the tumor in human cancers. e.g.: • Calin, G. A et al: (2005) A microRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. N. Engl. J. Med. 353:1793–1801. • Iorio, M. V et al: (2005) MicroRNA gene expression deregulation in human breast cancer. Cancer Res. 65:7065–7070. • Yanaihara et al: (2006) Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9:189–198. major diferences in survival rate based on miRNA patterns

42. miRNAs in fragile sites miR-coding locuses • more than half of miRNA genes were located in CAGRs (=cancer-associated genomic regions) • miRNA genes were located in regions that exhibited DNA copy number abnormalities (CNV): • ovarian cancer (37.1%) • breast cancer (72.8%) • melanoma (85.9%) • Dicer1 and Argonaute 2 exhibited gains in DNA copy number by 24.8% and 51.5%, respectively, in ovarian tumors aCGH Comparative genome hybridisation Zhang et al.: microRNAs exhibit high frequency genomic alterations in human cancer PNAS 2006.

43. miRNAs play critical role in all in p53 pathways!!! http://www.diana.pcbi.upenn.edu/cgi-bin/search.cgi?mode=Trans

44. What would be the next step? Target-mRNA/network-identification! miRBase::Sequences MIRANDA TargetScan PicTar Nucleic Acids Research, 2007, Vol. 35, Database issue Prediction of target mRNAs Close to 100 in July, 2007

45. Target prediction • Prediction miRNAs recognize their targets at least partly on the basis of simple sequence complementarity=> pure knowledge of the sequence of a miRNA is sufficient to predict many targets. (not yet possible for transcription factors, for which large training data sets or other experimental information are needed to accurately identify targets computationally) In plants, miRNA binding sites are usually contained in coding regions and have extensive complementarity to the mature miRNA Animal miRNA binding sites usually lie in 3' UTRs of target mRNAs and exhibit imperfect complementarity to the mature miRNA (estimated accuracy for targets is 50–85%) • Validation of predicted targets microarrays to identify the genes that show expression changes and to correlate these changes with 3' UTR sequence motifs, for example, by a linear regression model. miRNA knock-down or overexpression

46. Validating targets http://www.diana.pcbi.upenn.edu/tarbase.html • Expression data: miRNAs with different expression in experimental context The amount of miRNA change artificially miRNA miRNA inhibitors - + cDNA-microarray

47. Principles of gene regulation by miRNA AAA 3’UTR 3’UTR A Target-mRNA B Target-mRNA • coordinate principle • co-regulatory principle • differential regulation • competitive action More independent binding site AAA Target-mRNA 3’UTR A and B take part in the same process AAA Distincts programs AAA Target-mRNA 3’UTR AAA Target-mRNA 3’UTR miR-21 MIRANDA Hua Z, Lv Q, Ye W, Wong C-K, Cai G et al.: MiRNA-directed regulation of VEGF and other angiogenic factors under hypoxia (2006) PLoS ONE

48. Intervention to miRNA-pathway miRNA gene (vector) mature miRNA mimicking siRNA (pre-mir és anti-mir) miRNA-precursor mimicking shRNA-vector

49. In vitro melanoma-model Pos et al, Cancer Res, 2005, 2007 in press HT168 SCID Primer melanocyta culture human melanoma human melanocytes HT168 SCID liver- metastasis HT168-M1

50. miRNAs shows significant difference between melanocyte and melanoma cell lines miRNAs shows significant difference between melanocyte and all of melanoma samples (included both of cell lines and clinical samples)