0. microRNAS as biomarkers
Δήμητρα Ντάφου
Επ. Καθηγήτρια
Σχολή Βιολογίας, Τμήμα Γενετικής, Ανάπτυξης και Μοριακής Βιολογίας
Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης

1. William Cho 1

2. 3% coding and rest of it junk (repetitive DNA).
How is the human genome organised?
3% coding and rest of it junk (repetitive DNA).
Nuclear and mitochondrial
You are 99.99% similar to your neighbor

3. Non-coding RNA: the formerly known as “junk” ncRNA: non-coding RNAs
NC-RNAs compose majority of transcription in complex genomes
RNA
mRNA
Protein-coding RNA
ncRNA: non-coding RNAs
Transcribed RNA with a structural,
functional or catalytic role
rRNA
Ribosomal RNA
Participate in
protein synthesis
tRNA
Transfer RNA
Interface between
mRNA &
amino acids
snRNA
Small nuclear
RNA
RNA that form
part of the
spliceosome
snoRNA
Small nucleolar
RNA
Found in nucleolus,
involved in
modification
of rRNA
RNAi
RNA interference
Small non-coding
RNA involved
in regulation
of gene expression
Other
Including large RNA
with roles in
chromotin structure
and imprinting
siRNA
Small interfering RNA
Active molecules in
RNA interference
miRNA
MicroRNA
Small RNA involved
in regulation
of protein-coding gene

4. Non- coding rna: a key to eukaryotic complexity ?4

5. NOBEL PRIZE IN PHYSIOLOGY 2006
William Cho
Cho WC. MicroRNAs in cancer - from research to therapy.
Biochim Biophys Acta - Rev Cancer 2010;1805(2):
C. elegans

6. microRNAs: A new class of regulatory molecules
Small non-coding RNAs (21 to 23 nucleotides long)
First discovered in Caenorhabditis elegans
Found in nearly all eukaryotes
Act “negatively” in gene expression and control cellular timing
Recent estimation support that more than 60% of the human coding genome is directly regulated by microRNAs

7. How microRNAs are produced?
Mainly produced by RNA polymerase II
1st maturation in the nucleus
2nd maturation in the cytoplasm
Active complex: miRISC
Nature Reviews MCB, 2008

8. biogenesis
-Primary-miRNA is transcribed in the nucleus, and is usually several kilobases long; posses 5’ cap and a poly-A tail.
-Cleaved in the nucleus by Drocha enzyme to 70nt hairpin transcript (pre-miRNA).
-Transported to the cytoplasm by Exportin 5 through nuclear pores.
-Cleaved by Dicer enzyme (RNase III enzyme) into 19-22nt ds-transcripts.
Esquela-Kerscher, A., and Slack, F.J. (2006). Nature Reviews 6, p. 263 8

9. How microRNAs work?
Partial complementarity with 3’UTR regions (position 2 to 8 critical)
Cooperative effect
Abrogate protein synthesis
Nature Reviews MCB, 2008
One microRNA may regulate up to 100 different genes!

10. Genomic organization 10

11. Precise expression profile
miR-1-1
Srivatvas, miR-1 controls Hand2.
miR-1 genes are direct transcriptional targets of muscle differentiation regulators including serum response
factor, MyoD and Mef2.
miR-1-2
Zhao et al, Nature 2005
Pena et al, Nature Methods 2009

12. Precise expression profile: haematopoiesis
Gangaraju and Lin, Nature Reviews MCB 2009

13. Implication in cell differentiation
Stefani and Slack, Nature Reviews MCB 2008

14. The loss of microRNAs leads to fatality
Loss of miR-1-2 leads to overproduction of muscle cells
Zhao et al, Cell 2007
Jacks, Sharp, Jaenisch. Regulate proapoptotic gene Bim
Loss of miR cluster is embryonic lethal
Ventura et al, Cell 2008

15. POTENTIAL MECHANISMS THAT LINK microRNAs TO DISEASES
Genomic alterations of microRNAs
Chromosome deletion, amplification, and translocation
Single nucleotide polymorphism of miRNA or miRNA targets
Alterations on the expression of levels of miRNAs
Transcriptional control: transcription factor, enhancer, repressor
Epigenetic modification: DNA methylation, histone acetylation
Alteration on the processes of microRNA biogenesis

16. Mechanisms that link micrornas to diseases
Change in miRNA expression levels
Change in miRNA target spectrum

17. Cardiac, immune, neurological and metabolic disorders
microRNAs are associated to various diseases
Viral infections
Viruses encodes microRNAs that target viral mRNAs to regulate various stages of the viral life cycle
Viral microRNAs suppress expression of specific host genes
Viral infections induce expression of host microRNAs that inhibits expression of cellular genes
Upon viral infections, host cells express specific microRNA that suppress viral mRNA expression
Cardiac, immune, neurological and metabolic disorders

18. ARE microRNAs RARELY OR OFTEN AFFECTED IN CANCER DEVELOPMENT?
Correlation between Fragile chromosome sites and location of miRNA genes
microRNAs are frequently located in altered genomic regions associated to various cancers
Correlation between FRAs and miRs. A karyotype showing the position of 113 FRAs and 186 miRs is presented. The 61 miRs located in the same chromosomal band as the FRA are red. We were able to precisely locate 35 miRs inside 12 cloned FRAs. The red arrow shows frequently observed FRAs.
Copyright © 2004, The National Academy of Sciences
Calin G. A. et.al. PNAS 2004;101:

19. microRNAs and Cancer
Different expression profile between healthy and cancer tissue samples
Golub, Horvitz and Jacks. Monitor 217 human microRNAs in 334 samples.
Lu et al, Nature 2005

20. microRNAs and Cancer
Oncogenes
Tumour suppressors

21. Why microRNAs are functionally important in primary cancers?
There are tumour-specific microRNA signatures which accurately distinguish different sub-types of cancers
Modulation of microRNAs in cancer cell lines can directly regulates fundamental behaviors of cancer cells such as proliferation and apoptosis
Many microRNAs deregulated in cancers have been shown to control oncogenes, tumour suppressors and signaling pathway components as direct targets
1) suggest that specific microRNAs provide a clonal growth advantage in different tumour types likely depending on the context of other gene mutations present in the cancer 2)

22. microRNAs and Cancer: more and more examples
Mutation or epigenetic changes can lead to:
Deletion of microRNA
Epigenetic silencing of microRNA locus
Point mutation affecting a microRNA or microRNA precursor
Genomic amplification or translocation of microRNA locus
Loss of epigenetic silencing of microRNA locus
Point mutations in the microRNA targets
Rearrangement of 3’UTR
miR-15a,-miR-16-1
miR-29, miR-203
miR-15a,-miR-16-1
miR-17~92, miR-21
miR : deleted region in Chronic lymphocityc lymphomas
miR cluster in lymphomas
miR-21: overexpressed in many tumours
HMGA2 (12q15): Chromosomal translocation in different tumours (Lipomas, myomas, adenomas, hamartomas, sarcomas, carcinomas, leukemias) that leads to the lost of let-7 microRNA binding within the 3’UTR
Derepression of oncogene
increased repression of tumour suppressor
alteration of microRNA/mRNA binding
One target of miR cluster is the pro-apoptotic gene BIM (a potent tumour suppressor in the Eu-Myc model of B cell lymphoma).
List of target of miR-15a and miR-16-1 include BCL2, Cyclin D1 and WNT3a
HMGA-2

23. microRNA as a Cancer therapy: miR-26a
Induced liver tumour in mouse model using tet-o-MYC: LAP-tTa mice
Decrease in tumour mass
Kota et al. Cell, 2009

24. Micro rna profiling applications

25. New therapies: Controlling microRNA expression
Science, 2008

26. Controlling microRNA expression: different methods
Garzon et al, Nature Reviews Drug Discovery, 2010

27. Why microRNA are excellent biomarkers?
Extremely stable in fluids as well as on formalin-fixed paraffin-embedded tissue
Expression profile correlates well between fresh and formalin-fixed paraffin-embedded samples
Resistant to degradation

28. Predictive modelling
Permit risk stratification.
Customize treatment
Less extensive surgery
Rational drug selection
Monitoring response to therapy

29. Predictive or diagnostic modelling
Use of one or more biomarkers to determine prognosis
or response to treatment beyond usual clinical criteria
Tissue based
Serum or urinary based
Cellular based

30. Why microRNA are excellent biomarkers?
Weber et al, Clinical chemistry, 2010

31. Unique MicroRNA Profile in Lung Cancer Diagnosis and Prognosis
Genetic and epigenetic alteration may
affect miRNA expression, thereby
leading to aberrant target gene(s)
expression in cancers
Yanaihara et al, Cancer Cell, 2006:
- miRNA profiles of 104 pairs of primary
lung cancers and corresponding non-
cancerous lung tissues were analyzed by
miRNA microarrays
- 43 miRNAs showed statistical differences
William Cho

32. Unique MicroRNA Profile in Lung Cancer Diagnosis and Prognosis
A univariate Cox proportional hazard
regression model with a global permutation test indicated that expression of the miRNAs hsa-mir-155 and hsa-let-7a-2 were related to adenocarcinoma patient outcome
Lung adenocarcinoma patients with
either high hsa-mir-155 or reduced
hsa-let-7a-2 expression had poor survival
William Cho
Yanaihara N, et al. Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 2006, 9:

33. microRNAs and Cancer: new biomarkers
A subset of miRNA can be misregulated in various tumours (21 according to Volinia et al PNAS 2006; Croce lab). miR-21 in all six. Support that the same pathway may be affected.
Very important to develop such diagnostic biomarkers because 3-5% of all metastatic cancers, we are unable to establish primary tumours.
Nature Biotechnology 2008

34. The ROLE of microRNAs IN CANCER DIAGNOSIS
With the application of in situ RT-PCR, it was shown that the aberrantly expressed miR-221, miR-301 and miR-376a were localized to pancreatic cancer cells but not to stroma or normal acini or ducts.
Aberrant miRNA expression offered new clues to pancreatic tumorigenesis and might provide diagnostic biomarkers for pancreatic cancer.
Lee EJ, et al. Expression profiling identifies microRNA signature in pancreatic cancer.
Int J Cancer 2007, 120:
Cho WC. MicroRNAs: potential biomarkers for cancer diagnosis, prognosis and targets for therapy. Int J Biochem Cell Biol 2010.
Cho WC. MicroRNAs in cancer - from research to therapy. Biochim Biophys Acta - Rev Cancer 2010;1805(2):
William Cho

35. The ROLE of microRNAs IN CANCER PROGNOSIS
The expression pattern of miRNAs in pancreatic cancer were compared with those of normal pancreas and chronic pancreatitis using miRNA microarrays.
Differentially expressed miRNAs were identified which could differentiate pancreatic cancer from normal pancreas, chronic pancreatitis, or both.
High expression of miR-196a-2 was found to predict poor survival of more than 24 months.
Bloomston M, et al. MicroRNA expression patterns to differentiate pancreatic adenocarcinoma from normal pancreas and chronic pancreatitis. JAMA 2007, 297:
William Cho

36. The ROLE of microRNAs IN CANCER PROGNOSIS
Expression of let-7 miRNA was frequently reduced in human lung cancers, and that reduced let-7 miRNA expression was significantly associated with shorter postoperative survival.
Overexpression of let-7 miRNA in A549 lung adenocarcinoma cell line inhibited lung cancer cell growth in vitro.
Takamizawa J, et al. Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival. Cancer Res 2004, 64:
William Cho

37. microRNAs and Cancer: new biomarkers to predict drug resistance
Clinical Cancer Research, 2009
High level of miR-200 leads to a better sensitivity to EGFR inhibitor
Stable expression of miR-200 in mesenchymal UMUC3 cells increased E-cadherin levels, decreased expression of ZEB1, ZEB2, ERRFI-1, and cell migration, and increased sensitivity to EGFR-blocking agents.

38. microRNAs Tumorigenesis Diagnosis Prognosis miR-9 Neuroblastoma
miR-10b
Breast cancer
miR-15, miR-15a
Leukemia, pituitary adenoma
miR-16, miR-16-1
miR-17-5p, miR-17-92
Lung cancer, lymphoma
miR-20a
Lymphoma, lung cancer
miR-21
Breast cancer, cholangiocarcinoma, head & neck cancer, leukemia
Pancreatic cancer
miR-29, miR-29b
Leukemia, cholangiocarcinoma
miR-31
Colorectal cancer
miR-34a
miR-96
miR-98
Head & neck cancer
miR-103
miR-107
Leukemia, pancreatic cancer
miR-125a, miR-125b
Neuroblastoma, breast cancer
miR-128
Glioblastoma
miR-133b
miR-135b
miR-143
Colon cancer
miR-145
Breast cancer, colorectal cancer
miR-146
Thyroid carcinoma
William Cho

39. microRNAs Tumorigenesis Diagnosis Prognosis miR-155, has-miR-155
Breast cancer, leukemia, pancreatic cancer
Lung cancer
miR-181, imR-181a, imR-181b, imR-181c
Leukemia, glioblastoma, thyroid carcinoma
miR-183
Colorectal cancer
miR-184
Neuroblastoma
miR-193
Gastric cancer
miR-196a-2
Pancreatic cancer
miR-221
Glioblastoma, thyroid carcinoma
miR-222
Thyroid carcinoma
miR-223
Leukemia
miR-301
miR-376
let-7, let-7a, let-7a-1, has-let-7a-2, let-7a-3
Lung cancer, colon cancer
William Cho
Cho WC. MicroRNAs: potential biomarkers for cancer diagnosis, prognosis and targets for therapy.
Int J Biochem Cell Biol 2010.
Cho WC. OncomiRs: the discovery and progress of microRNAs in cancers. Mol Cancer. 2007;6:60.

40. Independent Validation by Immunoassay
STUDY DESIGN FOR BIOMARKER DISCOVERY
Site 1
Benign
Control
Stage III/IV
Stage I/II Ca
Other Ca 2
Other Ca 1
Other Ca 3
Independent
Validation
Cross
Comparison
Candidate
Markers
Site 2
Site 3
Site 4
Site 5
Multivariate
Models
target ID
Independent Validation by Immunoassay
Results:
Descriptive statistics
Two-group t-tests
Performance
ROC curve analysis
Model Derivation
Discovery 1
Discovery 2
William Cho 40

41. William Cho 41

42. Pathway and network analysis tools
assign phenotypic signatures (referred to as phenoprints) to every Drosophila gene. Phenoprints can then be used to cluster genes that are functionally related, guiding functional genomics efforts to assign a biological function to uncharacterized or unknown genes based on where they cluster in RNAi screens. The RNAi signatures/phenoprints panel illustrates how 12 genes (1–12) can be functionally clustered based on the comparison of distinct phenotypes (an–dn) scored in hypothetical screens (1–6).
Furthermore, global correlations between phenoprints, transcriptional profiling (RNAi profiling), interactome data sets (proteome and genetic interactomes), and published literature (literature-mining tools) can be used to derive network graphs critical to data mining.
Cold Spring Harb Symp Quant Biol. 2006;71:141-8.

43. Pathway and network analysis tools
William Cho 43

44. microRNA profiling platform
Real-Time quantitative PCR based platform
Access 377 different microRNA (A) 290 (B)
1- Seven logs VS three-four logs for microarray
3- Different melting temperature lead to false positives and negatives

45. microRNA profiling platform45

46. microRNA profiling platform
Extremely sensitive (from 10 cells)
Great specificity
No hybridization required
Easily go from profiling to validation
1- Seven logs VS three-four logs for microarray
3- Different melting temperature lead to false positives and negatives

47. Conventional cancer treatment:
microRNA profiling platforms
Conventional cancer treatment:
Personalized cancer treatment:
Treatment:
Pathway targeted therapy →
William Cho
Diagnosis
Stage, Grade, IHC
Treatment
Chemotherapy

48. What are the targets of microRNAs?
Fundamental research:
Questions to be answered
What are the targets of microRNAs?
How microRNA expression is regulated?
How microRNAs regulate gene expression?
Which are the cellular factors implicated in the microRNA pathway?

49. Translational research: WHAT CAN WE DO?
Implication of HNF4A-miR-24 network in Hepatocellular carcinoma _Hatziapostolou et al, Cell 2011
Mir24 antagmir24
Identification of microRNA targets
Functional test in in vitro and in vivo models
microRNA profiling

50. Putative target genes can be identified by expression profiling of cells in which the miRNA is overexpressed or antagonized, by biochemical isolation of the miRISC or by target prediction algorithms. These methods generally identify hundreds of candidate genes or more. Bioinformatic analysis of these large candidate gene lists for over-represented Gene Ontology (GO) terms, enriched biological pathways or gene interaction networks can then help researchers to select candidate genes to evaluate experimentally.

51. William Cho

52. RNA Quality Assessment