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microRNA Signatures in Cancer

1st International Congress on Controversies in Personalized Oncology (CONPO)

BARCELONA,   SPAIN

MARCH 9, 2013

E. ROBERT WASSMAN, MD, FAAP, FACMG

CHIEF MEDICAL OFFICER, ROSETTA GENOMICS

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Safe Harbor Statement

Except 

for 

historical 

information, 

the 

statements 

made 

in 

the 

following 

presentation, 

including 

without 

limitation, 

statements 

relating 

to 

projected 

cash 

burn 

rate 

and 

the 

expected 

timing 

of 

development 

of 

our 

pipeline 

products, 

and 

the 

future 

potential 

of 

microRNA 

products

in 

diagnostic 

and 

therapeutic 

markets 

are 

forward‐looking statements.

Such forward‐looking statements 

involve 

significant 

risks 

and 

uncertainties 

that 

may 

cause 

actual 

results 

and 

events 

to 

differ 

materially 

and 

adversely 

from 

those 

implied 

by 

the 

forward‐

looking statements.

Risks and uncertainties include: that the timing

and successful development of diagnostic 

and 

therapeutic 

products 

is 

highly 

uncertain; 

as 

well 

as 

the 

risks 

and 

uncertainties 

set 

forth 

under 

“Risk 

Factors”

in 

Rosetta’s 

Annual 

Report 

on 

Form 

20‐F 

for 

the 

year 

ended 

December 

31, 

2011, 

filed 

with 

the 

Securities and Exchange Commission.

Rosetta is presenting this information as of the date of the presentation 

and 

expressly 

disclaims 

any 

duty 

to 

update 

the 

information 

contained 

in 

this 

presentation. 

This 

presentation 

contains 

information 

from 

third‐party 

sources, 

including 

data 

from 

studies 

conducted 

by 

others 

and 

market 

data 

and 

industry 

forecasts 

obtained 

from 

industry 

publications.

Although 

Rosetta 

Genomics 

believes 

that 

such 

information 

is 

reliable, 

we 

have 

not 

independently 

verified

any 

of 

this 

information 

and 

we 

do 

not 

guarantee the accuracy or completeness of this information.

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microRNAs: The Basics

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4

Discovered in 1993: central to cell 

differentiation & development in 

C.elegans

microRNAs are ~22nt long single 

stranded RNAs

Post‐transcriptional regulation 

“Master control”

at translation of  

protein coding genes

Identified in humans in 2001 with 

~2000 found since

Linked to diseases, notably cancer, 

immune mediated disorders, viral 

infections, cardiovascular disesase, 

neurological and metabolic disorders Winter et al., Nature Cell Biology 2009

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Biologic role makes microRNAs ideal cancer biomarkers & potential therapeutic candidates

• MicroRNAs are aberrantly expressed in all cancers studied

• MicroRNAs are oncogenes and tumor suppressors

• microRNAs target self sufficiency in growth signals, apoptosis evasion, limitless proliferation, sustained angiogenesis and tissue invasion and metastasis

• MicroRNA genomic deletions correlate with specific cancers (B- cell lymphoma)

Iorio and Croce, EMBO Molecular Medicine 2011

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MicroRNAs are ideal biomarkers for 

cancer diagnostics

Short RNAs embedded in protein complex: robust to degradationStable markers in a variety of tissue samples and body fluidsStable at room temperature for years under FFPE conditions MicroRNAs identify tissues by source regardless of sample preparationExpression profiles classify most tumors with high accuracy and may predict clinical outcomes

00.10.20.30.40.50.60.70.80.9

1

2 3 3 5 7 7 8 8 8 9 9 10 11

age (years)

corr

elat

ion

2 years 11 years Equal quality

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MicroRNAs identify tissues by source regardless 

of sample preparation

microRNA expression profiles cluster according to the patient/source whether 

sourced as fresh‐frozen or formalin‐fixed paraffin‐embedded (FFPE) tissues;

However, mRNA expression profiles most closely reflect the sample type1

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1. Liu A, et al. (2009) Int J Clin Exp Pathol. 2:519-527.

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MicroRNAs demonstrate high tissue specificity 

Epithelial origin separateted 

from non‐epithelial origin using 

only 2 microRNAs

–

miR‐200c and miR‐205

Published by Rosetta in March 

20081

Subsequent independent 

papers suggested same 

microRNAs control epithelial 

mesenchymal transition (EMT)1 Rosenfeld, N., R. Aharonov, et al. (2008). "MicroRNAs accurately

identify cancer tissue origin." Nat Biotechnol 26(4): 462-9.

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Historically, in ~20%‐30% of cases, 

specimen quantity & quality, and 

available methodology limits 

correct classification of lung 

tumors 

qRT‐PCR microRNA analysis of 8 

miRs clearly distinguishes between 

the 4 main subtypes of lung 

tumors

Highly suitable for sub‐optimal 

Fine Needle Aspirates (FNA), 

brushings, and other small 

specimens 

High tissue specificity translates into an accurate 

lung cancer assay using only small tumor samples

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Lung cancer discrimination validated 

performance higher than histopathology

Results of assay on 45 validation set samples

•

Overall Sensitivity:  = 93.7%•

Overall Specificity:  = 97.9%•

Sensitivity for  pathology specimen: = 92.1%•

Sensitivity for cytology specimen:      = 95%•

Overall success rate (samples with answer):  = 91%•

Overall correct samples:  384/410Reference: Classification of the four main types of Lung cancer using a microRNA‐based 

diagnostic assay. Gilad.S, Lithwick‐Yanai G, Barshack I. et all. J Mol Diagn. 2012 Sep;14(5):510‐7.

Results of assay on 451 validation set samplesTotalFailedSmall CellCarcinoidNon‐SquamousSquamous

384N/A6533153133Correctly 

classified

26N/A52136In‐correctly 

classified

451417035166139Total

101010

Similarly, high tissue specificity translates into 

an accurate renal cancer subtyping assay

10Fridman, E, et al: Accurate Molecular Classification of Renal Tumors Using MicroRNA Expression. J Mol 

Diag, 12(5):687‐96, 2010.

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Renal tumors assessed by KNN (5)   

algorithm using 24 microRNAs 

Onco‐cytoma 

Chromo‐phobe 

PapillaryClear Cell

153Clear Cell

150Papillary

339Chromo‐phobe

3241Onco‐cytoma

Overall 174/184 classified correctly 95% accuracy1 sample failed sample QA due to insufficient RNA; 16 samples: no results were generated (8%)

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Non Ep

ithelia

l origin

Epith

elial

GI orig

in

SQ or

iginAden

o orig

inNeuroen

docrin

e

Sarcom

a

microRNA based decision tree also 

sorts multiple cancer types effectively

Germ Cell

RCC

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Microarray analysis of 64 miRNAs can 

identify 42 distinct tumor origins

Trained with ~1300 FFPE tumor samples Independent validation test set of 509 samples

–

146 (30%) were metastatic tumors–

Result of 1 or 2 tumor types generated from two algorithms –

Only 20 samples (4%) failed to produce result Overall, the correct tissue of origin was predicted by at least one of 

the reported answers in 418 (85%) (“sensitivity of prediction”)–

403 samples (82%) received a single answer, of which 361 (90%) 

were classified correctly–

Overall specificity up to 99% –

54 samples (11%) resulted in a “unified categorical”

answer, e.g. 

Sarcoma, RCC, Thyroid type not specified, etc. (7‐categories)Meiri E, Mueller WC, Rosenwald S, et al. A Second-Generation MicroRNA-Based Assay for Diagnosing Tumor Tissue Origin.

Oncologist 2012 May 22

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Most robust discrimination achieved via

two discrete complementary classifiers

Array resultsSignal 

Processing

Signal 

Processing

KNN

DecisionMaker

DecisionMaker

Decision

 Tree

Two classifiers are employed to 

interpret the expression of 64 

microRNAs as a combined 

classifier  

-15 -10 -5 0

-15

-10

-5

0

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Studies in actual CUP patients at leading 

international centers show 80‐92% concordance

• Prospective study on 75 CUP patients at M.D. Anderson done on first generation assay (narrower range of miRNAs & tumor types) and results corroborated with second generation assay

• 84% concordance with final diagnosis1

• Two studies (first* & second** generation) on 52 real CUP patients as well as on metastases of known origin at Heidelberg University

• 80%* & 88%** concordance with final diagnosis2,3

• Study on 84 real CUP patients at University of Ioannina & Hellenic Cooperative Oncology Group

• 92% concordance with final diagnosis4

1. Prospective Gene Signature Study Using microRNA to Identify the Tissue of Origin in Patients with Carcinoma of Unknown Primary (CUP). Varadhachary, Spector et al. Clinical Cancer Research 17 2011

2. Meiri, E, Mueller, WC, Rosenwald, S, et al. A Second-Generation MicroRNA-Based Assay for Diagnosing Tumor Tissue Origin. The Oncologist, 2012; 17(6): 801-812.

3. Accurate classification of metastatic brain tumors using a novel microRNA-based test. Muller, Spector et al. The Oncologist 16:165-74, 20114. G Pentheroudakis, N Pavlidis et al. A Novel microRNA-based Assay demonstrates 92% accuracy in classification of metastatic tumors from

patients diagnosed with carcinoma of unknown primary. Poster presentation at ASCO meeting in Chicago, June 2012

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Ioannina University Hospital, Greece

study of use in real CUP cases1

Tested Patients84 (100%)

Tested Patients84 (100%)

Clinical DxClinical Dx

Assay ResultsAssay ResultsPresentation Clinical Dx

Presentation Clinical Dx

Final Clinical DxFinal Clinical Dx

Initial Dxprocess

Additional Dxand follow up

Additional IHC for 4 patients

miRview®mets2

59 (70%)

Agreement

Agreement

Agreement

75 (89%)

77 (92%)

1. G Pentheroudakis, N Pavlidis et al. A Novel microRNA-based Assay demonstrates 92% accuracy in classification of metastatic tumors from patients diagnosed with carcinoma of unknown primary. Poster presentation at ASCO meeting in Chicago, June 2012

Retrospective cohort of resected metastatic lesions from 84 CUP patient1

Each prediction was assessed for agreement with:

Pathological information

Clinical information

Follow‐up and outcome data

92% concordance overall

1717

In 77 patients (92%) test results were fully concordant with final 

diagnosisFor 18 patients (21%), following test results would have resulted 

in administration of different chemotherapeutic regimens–

In 9 patients, different combination chemotherapies likely to be

more active 

possibly with superior survival

–

In 16 patients, the change in diagnosis could have been coupled to a change 

in targeted therapy employed

In the remaining patients, results in agreement with the 

presenting diagnosis were still deemed useful objective 

information to narrow the differential diagnosis and increase the 

confidence level for treatment strategy

Potential impact of microRNA test results in 

Ioannina University Hospital CUP cases1

1. G Pentheroudakis, N Pavlidis et al. A Novel microRNA-based Assay demonstrates 92% accuracy in classification of metastatic tumors from patients diagnosed with carcinoma of unknown primary. Poster presentation at ASCO meeting in Chicago, June 2012

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Case report–brain metastases in a woman 

with triple negative breast cancer (TNBC)

H&E

HMB45

S100

x100 x200

A B

Clinical presentation:Female presented with breast mass 

several months earlier Pathology:  Dx TNBC•Poorly‐differentiated adenocarcinoma 

with tumor giant cells, adenoid formations •IHC: negative for Estrogen‐Receptor, 

Progesterone‐Receptor and Her2/neu 

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microRNA microarray test result: MelanomaIHC after molecular profiling consistent with microRNA:

–

HMB45 ‐

positive–

S‐100 ‐

focally positive–

MELAN A – negative 

Breast lesion was then molecularly profiled on microRNA 

array and resulted in the same diagnosis of melanomaIHC for breast lesion same as metastasis

Published in: The Oncologist 16:165‐74, 2011‐”Accurate classification of metastatic brain tumors using a novel

microRNA‐based test”

Muller, Spector et al. 

Case report–triple negative breast cancer in actuality CUP from “lost” melanoma

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The challenge of triple negative breast cancer 

(TNBC): can microRNA open new paths?

In TNBC cells, 13 microRNAs recently 

reported as dysregulated versus normal1

Metastatic signature of TNBC: 6 

microRNAs differentially expressed in 

tumor vs. metastasis and in normal vs. 

metastasis, but not in normal vs. tumormiR‐424 is down regulated in mets vs. 

primary

Aberrant miR‐424 has been observed 

in progression of other cancer types, 

and may indicate a role in the 

development of metastases2

1. Cascione L, Gasparini P, Lovat F et al. Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer. PLoS One. 2013;8(2):e55910

2. Xu J, Li Y, Wang F, Wang X et al. Suppressed miR-424 expression via upregulation of target gene Chk1 contributes to the progression of cervical cancer. Oncogene. 2013 Feb 21;32(8):976-87

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microRNA expression signatures may be able 

to stratify survival in TNBC

4 microRNAs significantly 

associated with overall 

survival of TNBC patientsCombined 4‐miR signature 

stratified median overall 

survival of 69 vs. 83 month 

between the high and low 

microRNA‐based risk groups

Cascione L, Gasparini P, Lovat F et al. Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer. PLoS One. 2013;8(2):e55910

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Ovarian Cancer Response To 

First Line Platinum Based Treatment

microRNAs from FFPE tumor samples of 57 ovarian cancer patients receiving 

platinum‐based therapy as first line hybridized to Rosetta’s microarrays

7 microRNAs were found to be significantly differentially expressed in tumors 

from platinum sensitive vs. platinum resistant patients  

5 microRNAs were associated with significant difference in survival or 

recurrence‐free survival

High expression of hsa‐mir‐27a identified a sub‐group with very  poor prognosis

hsa‐mir‐27 expression correlates with survival

surv

ival

Eitan R, Kushnir M, Lithwick-Yanai G, et al., Tumor microRNA expression patterns associated with resistance to platinum based chemotherapy and survival in ovarian cancer patients. Gynecol Oncol. 2009 Aug;114(2):253-9

2323

Mesothelioma diagnosis: orphan clinical unmet 

need of increasing importance

G Pentheroudakis, N Pavlidis et al. A Novel microRNA-based Assay demonstrates 92% accuracy in classification of metastatic tumors from patients diagnosed with carcinoma of unknown primary. Poster presentation at ASCO meeting in Chicago, June 2012

Results of further IHC performed 

following microRNA test results:A

H&E

B

CK5/6 C

Calretinin 

D

Mesothelin

61‐year‐old female presented with 

peritoneal carcinomatosis and ascitesPresumptive diagnosis: primary 

peritoneal/ovarian carcinoma. Failed response to taxane‐platinum 

therapy, but had indolent course, with 

overall survival of 30 monthsLater microRNA profile gave a single 

answer: mesotheliomaAdditional IHC tests confirmed 

diagnosisThis guided diagnosis might suggest 

alternative therapy of 

pemetrexed/platinum

2424

Despite indolent course in previous patient, mesothelioma remains 

highly lethal  with Median TTP and survival after surgery 8‐12m and 12‐

20mCurrently, inability to forecast outcomes limits clinicians from

directing 

aggressive therapy to the individuals who may actually benefit from such 

an approachElevated miR‐29c* Associated With Better Prognosis

Mesothelioma prognosis: orphan clinical 

unmet need of increasing importance

2525

Functional Consequences of miR‐29c* 

Overexpression in Mesothelioma Cell Lines

Mir29c* is higher in 

normal mesothelial 

cell lines compared 

with MPM Associated with a 

more differentiated 

phenotypeFunctional analyses 

data is compatible 

with the clinical 

findings

Pass HI, Goparaju C, Ivanov S et al. hsa-miR-29c* is linked to the prognosis of malignant pleural mesothelioma. Cancer Res. 2010 Mar 1;70(5):1916-24

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Elevated miR‐29c* Associated With Better 

Mesothelioma Prognosis

miR‐29c* had significantly different 

expression (p = 0.00036, FC 1.8) 

between long and short TTPElevated miR‐29c* was associated 

with longer survival time in both 

training and test sets

B ad p rog no sis Goo d prog no sis6

7

8

9

10

11

h sa-m iR -29c*p -value 0 .000355fo ld ch ang e 1 .8

Pass HI, Goparaju C, Ivanov S et al. hsa-miR-29c* is linked to the prognosis of malignant pleural mesothelioma. Cancer Res. 2010 Mar 1;70(5):1916-24

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miRNA biomarkers for stratification of response to novel immunotherapy

• Experimental immunotherapy trial in metastatic solid tumor• 12 miRNAs identified differentiating 10 responders from 10 non-

responders at Day30 (all passed FDR P<0.05) • A classifier using two miRNA’s from day 30 markers also shows

good signal at outset of therapy

22 22.5 23 23.5 24 24.521

21.5

22

22.5

23

23.5

24

hsa‐miR‐A hsa‐miR‐A

hsa‐miR‐B

hsa‐miR‐B

PCR

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Looking Forward with microRNAs

Blood‐based diagnosticsAdditional Response/Predictive Biomarkers for New Drugs

–

Identify patient sub‐cohorts that respond well to drugs stalled in 

development

–

Response prediction suggested in several cancer types to date

Therapeutics–

Up or down regulating a microRNAs can regulate entire pathway

–

Liver cancer (HCC):  animal POC successfully completed & published

–

Ovarian cancer: initial, pre‐clinical phase

–

Recent studies in triple negative breast cancers suggest opportunity

Non‐oncology applications