MicroRNA Rosetta Genomics
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Transcript of MicroRNA Rosetta Genomics
Applications of MicroRNA-Based Diagnostics in Oncology Practice
E. Robert Wassman, MD, FAAP, FACMG Chief Medical Officer, Rosetta Genomics
With Introduction by: Kenneth Berlin President & CEO, Rosetta Genomics
Safe Harbor and Confidentiality Statement
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Except for historical information, the statements made in the following presentation, including without limitation, statements relating to the future potential of microRNA products in diagnostic and therapeutic markets, as well as statements relating to results of future experiments, 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; 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, 2012, 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.
No unauthorized duplication, dissemination or any other use of any information contained herein is allowed and all rights to any and all information contained herein remains the sole property of Rosetta Genomics.
Cancer of Unknown Primary
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Clinician: Non-Hodgkin Lymphoma Pathologist: Carcinoid? Histology and IHC: excluded lymphoma &
melanoma o Cytokeratins – and Synaptophysin weakly +
Rosetta Cancer Origin Test: Sarcoma Mesenchymal antigens IHC + SMA & Vimentin +
Findings now consistent with Sarcoma
Case Report: 67 yo Female Presented with Brain Metastases – Unknown primary
Meiri, E, Mueller, WC, Rosenwald, S, et al. A Second-Generation MicroRNA-Based Assay for Diagnosing Tumor Tissue Origin. Oncologist, 2012; 17(6): 801-812.
When to Consider Molecular Profiling
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Diagnosis is cancer of unknown/uncertain primary Basic 8-10 slide IHC panel doesn’t yield definitive Dx
Central Biologic Role make microRNAs Ideal Cancer Biomarkers
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“Master” control of gene expression at level of translation Aberrantly expressed in all cancers Map to regions of known genomic instability in cancers Some are oncogenes and tumor suppressors Target steps in oncogenesis: Proliferation signals Metastasis and tissue invasion Sustained angiogenesis Apoptosis inhibition
Iorio and Croce, EMBO Molecular Medicine 2011
Well preserved in FFPE at room temperature for years Direct measure of
functional elements mRNA is not: i.e., indirect
measure for proteins
Robust to degradation Short 22nt RNAs Embedded in proteins
Stable in body fluids and tissue samples
microRNA Stability Results in Highest Test Success Rates
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microRNA Identifies Tissues by Source NOT Sample Type
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Liu A, et al. (2009) Int J Clin Exp Pathol. 2:519-527.
miR-200c and miR-205 alone distinguish epithelial cancers1
Actually control EMT too2,3
64 such microRNAs stacked together yields a decision tree to identify ~95% of CUP origins 42 distinct tumor types
microRNAs Demonstrate High Tissue Specificity
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1) Rosenfeld, N., R. Aharonov, et al. (2008). "MicroRNAs accurately identify cancer tissue origin." Nat Biotechnol 26(4): 462-9. 2) Gregory PA, Bert AG, et al. The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1. Nat Cell
Biol. 2008 May;10(5):593-601. 3) Korpal M, Lee ES, et al. The miR-200 family inhibits epithelial-mesenchymal transition and cancer cell migration by direct targeting of E-cadherin
transcriptional repressors ZEB1 and ZEB2. J Biol Chem. 2008 May 30;283(22):14910-4.
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Decision Tree Structure
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① Quantitative binary tree classification algorithm reduces complex multi-tissue classification problem Simple binary decisions with ~1-3 microRNA each
② “Most similar tumor” KNN algorithm versus training set patterns
③ Decision-maker algorithm to resolve discrepancies
Powerful 3-algorithm Combo uses 1300 Sample Training Set
Rosenfeld, N., R. Aharonov, et al. (2008). "MicroRNAs accurately identify cancer tissue origin." Nat Biotechnol 26(4): 462-9.
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Highly Sensitive & Reproducible Custom Microarray
900 DNA probes Printed in triplicate with
relevant controls
Verified against RT-PCR and across labs Dynamic range >3 orders of magnitude
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Test set of 509 FFPE tumor samples o 146 (30%) were metastases of known primaries
Very low 4% QA failure rate 82% yielded single answer with 90% sensitivity Overall sensitivity of 85% for at least one answer
correctly predicting source 54 samples (11%) resulted in a reported answer
which is one of the 7 “unified answers”
Clinical Validity Proven in Known Primary Cancers1,2
1. Chajut A, Rosenwald S, Edmondson T, et alDevelopment and validation of a second generation microRNA-based assay for diagnosing tumor tissue origin. AACR. 2011
2. Chajut A, Aharonov R, Rosenwald S, et al. A second generation microRNA-based assay for diagnosing tumor tissue origin. ASCO 2011.
Cancer of Unknown Primary Maps Closely to Cancer of Known Primary
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Pentheroudakis et al., Clin Exper Metastasis, Epub ahead of print 11/4/2012 DOI 10.1007/s10585-012-9548-3
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Clinical: ascites, no large hepatic lesions Pathology: poorly differentiated adenocarcinoma IHC: CK20/7 -, focal HepPar +,
morphology “not” suggestive of HCC
Rosetta Cancer Origin Test: Hepatocellular carcinoma Further workup: AFP = 186,000 Treatment for HCC resulted in AFP with 6 month response
Case Report: 63 yo Male Presented with Peritoneal Carcinomatosis
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Compared result with the final work-up and outcome data at leading CUP Centers Baseline complete initial clinical, pathological, and imaging work-up Plus unique IHC markers, clinical course & response to therapy, latent primary discovery, & post mortem Define best answer “Gold Standard” “Agreement Score” reflecting four levels of concordance
Establishing “Gold Standard” for Clinical Truth: Study Design for CUP
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Prospective study on 75 CUP patients at M.D. Anderson 84% concordance with final diagnosis1
Study of 52 real CUP patients, plus metastases from known primaries at Heidelberg University 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
Concordance with “Gold Standard” Final Diagnosis Consistently High
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, 2011 4. 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 Cases
Retrospective cohort of 84 CUP patients Testing resected metastases Followed for additional work-up and outcomes Each step of incremental information increased the credibility of profiling prediction 92% concordance after 4 extra IHCs
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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Clinicians: profiling would alter chemotherapy regimens in 21% of cases 9 patients: more active combination chemotherapy 16 patients: new diagnosis could have lead to targeted Rx
Corroboration of presenting diagnosis alone deemed useful objective information: Narrow the differential diagnosis Increase treatment confidence Decrease additional work-up
Test Results Would Impact Patient Care Significantly for Many
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
258 consecutive specimens referred for clinical testing Sufficient tumor material in 217 (85%) cases, and 192 (88%) successfully
reported with mean TAT of 7 days The most common diagnoses consistent with prior series Colorectal 12% Breast 10.4% (~3% of total are Male) Upper body SCC 7.3% Ovarian 6.8% Biliary/pancreatic 6.8% 30 Other tumors 57%
Referring MD follow-up of correlation of test prediction & impact Overall 86% concordance with clinical and/or pathological best final
diagnosis Utility cited in ~70% based on
o Changed or re-considering therapy; o Increased decisional certainty for current regimen
CLIA-Lab “Real World” Experience Corresponds Closely
Observational study of real world clinical performance of microRNA molecular profiling for cancer of unknown primary (CUP) Mats Sanden, Karin Ashkenazi, Hila Benjamin, Eran Goren, Yael Spector, E. Robert Wassman, Rosetta Genomics Inc.,
Philadelphia, PA.
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Case Report: 61-yo Female Presented with Peritoneal Carcinomatosis/Ascites
Clinical diagnosis: primary peritoneal/ovarian carcinoma No response to taxane-platinum therapy Subsequent indolent course, with OS 30 months Rosetta Cancer Origin Test: Mesothelioma IHC confirmed this diagnosis Might have suggested
pemetrexed combo Rx
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
When to Consider Molecular Profiling
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Diagnosis is cancer of unknown/uncertain primary Basic IHC panel doesn’t yield definitive diagnosis Atypical presentation or discordant findings Failure to respond as expected to treatment
A Diagnosis Dramatically Changes a Patient’s Experience with Their Disease
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Cancer is hard to accept, BUT CUP patients find it significantly harder to accept an “unknown” cancer diagnosis Extensive series of tests are disheartening “they looked everywhere” to no avail Find clinicians seem uncomfortable and evasive with them, then suddenly tell the final bad news with “enormous urgency”
Boyland et al. (2008) Patients’ experience of carcinoma of unknown primary site. J Palliative Med 22:177-183
Value for Patients: End Diagnostic Odyssey and Indicate Therapy
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Treated as “CUP”
Primary “FOLFOX” (OS)
Breast 6 mo
Colorectal 16 mo
NSCLC 9 mo
Ovary 18 mo
Adapted with permission from: J. Bridgewater, CUP-02 Grant Proposal (Pending) with regimen survival data from NICE (specifc references available)
Treated as Primary
Specific Regimen Specifc Rx (OS)
Anthracycline, taxane, capecetabine 24 mo
Oxaliplatin/irinotecan; 5FU/capecetabine; Bevacizumab/Cetuximab
24 mo
Platinum regimens 13 mo
Carboplatin/paclitaxel; pegylated doxorubicin 50 mo
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Diagnosis: poorly differentiated primary “triple negative” ductal breast carcinoma IHC: ER, PR, Her2/Neu negative; A1/3 weak +
Treatment: R mastectomy + local radiotherapy Recurrence in 8 months: 3x4 cm R parieto-occipital brain lesion Histology & IHC profile diagnosed as breast cancer metastasis 1 month later, L axillary mass: undifferentiated, large-cell
carcinoma c/w breast metastasis Rosetta Cancer Origin Test:
Melanoma
Case Report: 70 yo Female Presented with R Breast Mass on Mammogram
The Oncologist 16:165-74, 2011-”Accurate classification of metastatic brain tumors using a novel microRNA-based test” Muller, Spector et al.
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After profiling result of Melanoma: Brain IHC:
o HMB45+, S-100+ and MELAN A- Breast & Axilla IHC:
o HMB45+, S-100+ and MELAN A+
Final diagnosis consistent with Rosetta Cancer Origin Test
Case Report: Not What it Seems
H&E
HMB45
S100
x100 x200
The Oncologist 16:165-74, 2011-”Accurate classification of metastatic brain tumors using a novel microRNA-based test” Muller, Spector et al.
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When to Consider Molecular Profiling
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Diagnosis is cancer of unknown/uncertain primary
Basic IHC panel doesn’t yield definitive diagnosis
Atypical presentation or discordant findings
Failure to respond as expected to treatment
Need to accelerate path to clear primary diagnosis
Value of definitive diagnosis of CUP cases to family
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High sensitivity answers Answers instead of ambiguity An end to leaving patients in limbo But, we don’t get all the answers The real question is “not whether but when” to use microRNA profiling
So Why Use microRNA Profiling?
Uncertainty is not Acceptable! Know First…Treat second
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