microRNAs as Biomarkers in Blood and Other ... - Asuragen
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SUMMARY POINTS microRNAs (miRNA) represent a possible new class of biomarkers for diagnostic applications based upon the following observations: The expression levels of miRNAs correlate with disease state (Calin 2002, Lu 2004) and patient prognosis (Takamizawa 2004, Yanaihara 2005), miRNAs can be readily recovered from archived FFPE samples and used to identify biomarkers associated with clinical outcome miRNAs are present and relatively stable in clinically accessible biofluids such as serum, plasma, urine, and saliva Donor-to-donor variation in miRNA expression is extremely low in plasma, suggesting that disease specific miRNAs will be relatively easy to identify Highly stable miRNAs have been identified that enable more confident measurements of miRNA expression • • • • • CONCLUSION We have used a collection of technologies to isolate and quantify miRNAs from frozen tissues, FFPE samples, serum, plasma, urine, and saliva. The observation that miRNAs are abundant, relatively stable, and easy to recover from patient samples that are readily available in clinical settings suggests that small RNAs might ultimately support diagnostic applications. Combined with the observation that the expression of miRNAs correlates with clinically important factors like prognosis, disease type, and genetic aberration, we believe that miRNAs will ultimately prove to be an ideal analyte for cancer diagnostic assays. microRNAs as Biomarkers in Blood and Other Biofluids Jon Kemppainen, Jeffrey Shelton, Kevin Kelnar, Stephanie Volz, Heidi Peltier, Anna Szafranska, Dmitriy Ovcharenko, Thomas Illmer, Manu Labourier, Gary Latham, David Brown Asuragen, Inc., 2150 Woodward Ave., Austin, Texas 78744 Figure 1. Highly sensitive and quantitative for miRNA Expression Analysis The mirVana miRNA Bioarray, featuring more than 600 known miRNA’s and 150 proprietary human miRNA’s, can be used in conjunction with the mirVana miRNA labeling kit (Ambion) to label and quantify miRNAs in RNA samples. To identify miRNAs that are differentially expressed in tumors relative to normal tissues, cancer patient tissue samples were recovered, macro-dissected to separate cancer and normal tissue, and used to recover total RNA. The miRNA in the sample was purified using flashPAGE ™ (Ambion) to eliminate precursor miRNAs and other RNAs that might generate false signals on the array. The labeled miRNA samples were hybridized to the array which was then washed and analyzed. Cancer and normal tissue samples were compared and differentially expressed microRNA candidates are identified. The differentially expressed miRNAs were verified by qRT-PCR assays (Asuragen patent pending). As few as 100 copies of a candidate miRNA (per RT reaction) can be accurately quantified using the qRT-PCR method. Multiple studies have revealed that the expression profiles of miRNAs in cancer samples correlate with prognosis, cancer type, and genetic abnormality (Calin 2002, Calin 2004, Takamizawa 2004, Lu 2005). Because of their small size and inherent stability in clinical samples, miRNAs could be ideal biomarkers for diagnostic assays. These small RNAs can provide patient information that can not be determined by standard pathology, including patient prognosis and response to therapy. Analyses are possible using available surgical samples, FFPE blocks, or readily accessible blood, urine, or saliva samples. INTRODUCTION RNA from frozen tissue samples was isolated using the mirVana ™ PARIS ™ RNA Isolation kit (Ambion). RNA from FFPE samples was isolated using the RecoverAll ™ Isolation kit (Ambion). RNA from biofluids was isolated using a novel glass fiber filter-based protocol for extracting small amounts of RNA from large sample volumes. The relative abundance of miRNAs in frozen and FFPE tissue samples was measured using mirVana BioArrays. Microarray data was verified by qRT-PCR using TaqMan ® assays (ABI) or Asuragen technology as noted. The abundance of miRNAs in biofluid RNA samples was measured by qRT-PCR in the same manner. MATERIALS AND METHODS RESULTS References Calin GA, Dumitru CD, Shimizu M, Bichi R, Zupo S, et al. (2002) Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Nat’l Acad Sci USA 99, 15524-15529. Calin GA, Sevignani C, Dumitru CD, Hyslop T, Noch E, et al. (2004a) Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc Nat’l Acad Sci USA 101, 2999-3004. Lu J, Getz G, Miska EA, Alvarez_Saavedra E, Lamb J, et al. (2005a) MicroRNA expression profiles classify human tumors. Nature 435: 834-838. Takamizawa J, Konishi H, Yanagisawa K, Tomida S, Osada H (2004) Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival. Cancer Res 64, 3753-3756. Yanaihara N, Caplen N, Bowman E, Seike M,et al (2005) Unique microRNA molecular profiles in lung cancer diagnosis and prognosis, CANCER CELL 9, 189–198. Verification of Assay Design N Ch Ca Second Principal Component First Principal Component (62.98%) Normal N, n=5 Chronic Ch, n=6 Cancer Ca, n=8 -8 -6 -4 -2 0 2 4 6 8 10 12 14 N Ca Ch -2 2 6 10 14 18 22 N Ca Ch -2 2 6 10 14 18 22 N Ca Ch - = miR-217 miR-196 Figure 3: Pancreatic Ductal Adenocarcinoma Study: miRNAs as Potential Diagnostic Analytes Asuragen’s qRT-PCR assays for hsa-miR 194 and hsa-miR 217 were used to compare normal, chronic pancreatitis, and carcinoma samples. These data demonstrate that a combination of two miRNA’s could be used to distinguish normal, pancreatitis, and carcinoma samples. Prostate carcinoma B cell lymphoma Myometrium 0 2 4 6 8 10 12 0 2 4 6 8 10 12 0 2 4 6 8 10 12 0 2 4 6 8 10 12 1 year vs 11 years: 85% correlation 0 2 4 6 8 10 12 0 2 4 6 8 10 12 1 year vs 7 years: 90% correlation Frozen vs 1 year: 96% correlation Frz FFPE Frz FFPE Frz FFPE Frz FFPE Frz FFPE Frz FFPE Frz FFPE Frz FFPE Frz FFPE Figure 2: Pancreatic Ductal Adenocarcinoma Study: Array Classification Total RNA was prepared from frozen pancreatic tumor, chronic pancreatitis, and normal adjacent tissue samples using the mirVana PARIS isolation kit. mirVana Bioarrays were used to profile the miRNA in 10 ug of total RNA that had been processed by flashPAGE. Principal component analysis showed that samples could be sorted by miRNA expression into cancer, chronic pancreatitis, or normal. Frozen vs FFPE tissues Archived Samples Fixed 4: miRNAs in Fixed Samples RNA expression for FFPE and frozen samples from three different tissue types as measured to assess miRNA accessibility and stability in archived samples. Tissue samples were stored frozen or as FFPE blocks for 1 to 11 years and processed using miRVana PARIS (frozen samples) or RecoverAll Total Nucleic Acid Isolation Kit (FFPE samples). In each case, the miRNA from 10 ug of total RNA was labeled and analyzed using mirVana Bioarrays. Unlike mRNAs, miRNAs appear to remain relatively intact and compatible with expression analysis even when stored for long periods in FFPE tissue blocks. miR-24 miR-27a miR-98 0 5 10 15 20 25 30 35 40 Saliva #1 Saliva #2 miR-24 miR-27a miR-98 0 5 10 15 20 25 30 35 40 Serum #1 Serum #2 miR-24 miR-27a miR-98 0 5 10 15 20 25 30 35 40 Urine #1 Urine #2 miR-24 miR-27a miR-98 0 5 10 15 20 25 30 35 40 Plasma #1 Plasma #2 Plasma RNA Serum RNA Urine RNA Saliva RNA Figure 5: Characterization of RNA in Biofluid Samples Expression analysis of hsa-miR 24, hsa-miR 27a, and hsa-miR 98 in different biofluid samples. Total RNA was purified from plasma, serum, urine, and saliva using Asuragen’s proprietary isolation procedures. miRNAs were analyzed by qRT-PCR using the Ambion mirVana ™ miRNA Detection Kit (urine and Serum) samples, Asuragen’s proprietary miRNA detection method (plasma samples), or TaqMan miRNA assays (ABI) (saliva samples). Total input RNAs vary from 250 pg/rxn for plasma to 14 ng/rxn for urine. miRNAs could be readily detected in all biofluid samples tested. 100 nt VS. Total miRNAs Cell-free Sample Plasma/Serum Yes Saliva 100 ng Yes Urine 3-20 ng Yes Present Yield/ml 5-50 ng Quality RNA Figure 6: miRNA Stability in Plasma Plasma from healthy donors was processed immediately or allowed to incubate for extended time periods at room temperature (25°C). miRNAs were analyzed by qRT-PCR using Asuragen’s proprietary miRNA detection method. Both hsa-miR 16 or hsa-miR 24 levels remained stable for at least 22 hours. R 2 = 0.6951 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 Avg NonPlasm a Ct 15.00 20.00 25.00 30.00 35.00 40.00 45.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 Normal #1 Figure 8: miRNAs in Blood Samples Whole blood from male and female donors was separated into plasma and cellular fractions. Total RNA was isolated from both fractions and qRT-PCR- based miRNA expression analysis was used to compare the miRNAs in the various samples. The relatively low correlation between the cellular and acellular fractions of blood suggests that the plasma is not simply a repository of miRNAs from blood cells, but that cells from organs in the body might also be contributing to the population of miRNAs in plasma. The levels of miRNAs in plasma from various individuals were surprisingly consistent, suggesting that there is a “normal” amount of cell-free miRNA in blood. This has important implications for diagnostics, since slight variations from normal induced by a disease will be relatively straight forward to identify. Figure 9: Method for miRNA Expression Analysis Total RNA was isolated from plasma of prostate and lung cancer patients and miRNA expression profiles were generated by qRT-PCR. Comparing two lung cancer patients or two prostate cancer patients reveals very few significantly differentially expressed miRNAs. While the levels of miRNAs in the plasma of prostate and lung cancer patient samples were also very similar, it is noteworthy that several miRNAs appeared to be present at significantly higher levels in the plasma of prostate cancer patients than in the lung cancer patients. 0.980 0.978 0.990 Female#2 1 0.985 0.978 Female #1 0.985 1 0.983 Male #2 1 0.980 0.978 0.990 0.978 0.983 1 Male #1 Female#2 Female#1 Male #2 Male #1 15 20 25 30 35 40 45 15 20 25 30 35 40 45 Lung Cancer #1 10 15 20 25 30 35 40 10 15 20 25 30 35 40 Prostate Patient #1 Microarray D1 D2 D3 D4 D5 D6 D7 D8 0 1 2 3 4 dCt Donor miR 24 D1 D2 D3 D4 D5 D6 D7 D8 19 20 21 22 23 Avg Ct Donor miR 24 D1 D2 D3 D4 D5 D6 D7 D8 1 2 3 4 5 6 7 8 dCt Donor miR 103 D1 D2 D3 D4 D5 D6 D7 D8 20 21 22 23 24 25 26 27 Avg Ct Donor miR 103 D1 D2 D3 D4 D5 D6 D7 D8 19 20 21 22 23 Avg Ct Donor miR 146 a D1 D2 D3 D4 D5 D6 D7 D8 0 1 2 3 4 dCt Donor miR 146a miR 24 miR 103 miR 146a Normalized to Total RNA Normalized to miRNA Control Figure 7: miRNA Normalization Plasma RNAs isolated from 8 healthy donors were compared in qRT-PCR. A total of 16 miRNAs (250 pg input/rxn) were analyzed using TaqMan miRNA assays (ABI) or Asuragen’s proprietary miRNA detection assays. Data was analyzed by geNorm and NormFinder algorithms, which both identified the same miRNA as the most suitable reference RNA for normalization. Representative data for 3 miRNA targets are shown.
Transcript of microRNAs as Biomarkers in Blood and Other ... - Asuragen
SUMMARY POINTSmicroRNAs (miRNA) represent a possible new class of biomarkers for diagnostic applications based upon the following observations:
The expression levels of miRNAs correlate with disease state (Calin 2002, Lu 2004) and patient prognosis (Takamizawa 2004, Yanaihara 2005),
miRNAs can be readily recovered from archived FFPE samples and used to identify biomarkers associated with clinical outcome
miRNAs are present and relatively stable in clinically accessible biofluids such as serum, plasma, urine, and saliva
Donor-to-donor variation in miRNA expression is extremely low in plasma, suggesting that disease specific miRNAs will be relatively easy to identify
Highly stable miRNAs have been identified that enable more confident measurements of miRNA expression
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CONCLUSIONWe have used a collection of technologies to isolate and quantify miRNAs from frozen tissues, FFPE samples, serum, plasma, urine, and saliva. The observation that miRNAs are abundant, relatively stable, and easy to recover from patient samples that are readily available in clinical settings suggests that small RNAs might ultimately support diagnostic applications. Combined with the observation that the expression of miRNAs correlates with clinically important factors like prognosis, disease type, and genetic aberration, we believe that miRNAs will ultimately prove to be an ideal analyte for cancer diagnostic assays.
microRNAs as Biomarkers in Blood and Other BiofluidsJon Kemppainen, Jeffrey Shelton, Kevin Kelnar, Stephanie Volz, Heidi Peltier, Anna Szafranska, Dmitriy Ovcharenko, Thomas Illmer, Manu Labourier, Gary Latham, David Brown
Asuragen, Inc., 2150 Woodward Ave., Austin, Texas 78744
Figure 1. Highly sensitive and quantitative for miRNA Expression AnalysisThe mirVana miRNA Bioarray, featuring more than 600 known miRNA’s and 150 proprietary human miRNA’s, can be used in conjunction with the mirVana miRNA labeling kit (Ambion) to label and quantify miRNAs in RNA samples. To identify miRNAs that are differentially expressed in tumors relative to normal tissues, cancer patient tissue samples were recovered, macro-dissected to separate cancer and normal tissue, and used to recover total RNA. The miRNA in the sample was purifi ed using fl ashPAGE™ (Ambion) to eliminate precursor miRNAs and other RNAs that might generate false signals on the array. The labeled miRNA samples were hybridized to the array which was then washed and analyzed. Cancer and normal tissue samples were compared and differentially expressed microRNA candidates are identifi ed. The differentially expressed miRNAs were verifi ed by qRT-PCR assays (Asuragen patent pending). As few as 100 copies of a candidate miRNA (per RT reaction) can be accurately quantifi ed using the qRT-PCR method.
Multiple studies have revealed that the expression profiles of miRNAs in cancer samples correlate with prognosis,
cancer type, and genetic abnormality (Calin 2002, Calin 2004, Takamizawa 2004, Lu 2005). Because of their
small size and inherent stability in clinical samples, miRNAs could be ideal biomarkers for diagnostic assays.
These small RNAs can provide patient information that can not be determined by standard pathology, including
patient prognosis and response to therapy. Analyses are possible using available surgical samples, FFPE blocks,
or readily accessible blood, urine, or saliva samples.
INTRODUCTION
RNA from frozen tissue samples was isolated using the mirVana™ PARIS™ RNA Isolation kit (Ambion). RNA from
FFPE samples was isolated using the RecoverAll™ Isolation kit (Ambion). RNA from biofluids was isolated using
a novel glass fiber filter-based protocol for extracting small amounts of RNA from large sample volumes.
The relative abundance of miRNAs in frozen and FFPE tissue samples was measured using mirVana BioArrays.
Microarray data was verified by qRT-PCR using TaqMan® assays (ABI) or Asuragen technology as noted. The
abundance of miRNAs in biofluid RNA samples was measured by qRT-PCR in the same manner.
MATERIALS AND METHODS
RESULTS
ReferencesCalin GA, Dumitru CD, Shimizu M, Bichi R, Zupo S, et al. (2002) Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Nat’l Acad Sci USA 99, 15524-15529.
Calin GA, Sevignani C, Dumitru CD, Hyslop T, Noch E, et al. (2004a) Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc Nat’l Acad Sci USA 101, 2999-3004.
Lu J, Getz G, Miska EA, Alvarez_Saavedra E, Lamb J, et al. (2005a) MicroRNA expression profi les classify human tumors. Nature 435: 834-838.
Takamizawa J, Konishi H, Yanagisawa K, Tomida S, Osada H (2004) Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival. Cancer Res 64, 3753-3756.
Yanaihara N, Caplen N, Bowman E, Seike M,et al (2005) Unique microRNA molecular profi les in lung cancer diagnosis and prognosis, CANCER CELL 9, 189–198.
Verifi cation of Assay Design
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Figure 3: Pancreatic Ductal Adenocarcinoma Study: miRNAs as Potential Diagnostic AnalytesAsuragen’s qRT-PCR assays for hsa-miR 194 and hsa-miR 217 were used to compare normal, chronic pancreatitis, and carcinoma samples. These data demonstrate that a combination of two miRNA’s could be used to distinguish normal, pancreatitis, and carcinoma samples.
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Figure 2: Pancreatic Ductal Adenocarcinoma Study: Array Classifi cationTotal RNA was prepared from frozen pancreatic tumor, chronic pancreatitis, and normal adjacent tissue samples using the mirVana PARIS isolation kit. mirVana Bioarrays were used to profi le the miRNA in 10 ug of total RNA that had been processed by fl ashPAGE. Principal component analysis showed that samples could be sorted by miRNA expression into cancer, chronic pancreatitis, or normal.
Frozen vs FFPE tissues Archived Samples
Fixed 4: miRNAs in Fixed SamplesRNA expression for FFPE and frozen samples from three different tissue types as measured to assess miRNA accessibility and stability in archived samples. Tissue samples were stored frozen or as FFPE blocks for 1 to 11 years and processed using miRVana PARIS (frozen samples) or RecoverAll Total Nucleic Acid Isolation Kit (FFPE samples). In each case, the miRNA from 10 ug of total RNA was labeled and analyzed using mirVana Bioarrays. Unlike mRNAs, miRNAs appear to remain relatively intact and compatible with expression analysis even when stored for long periods in FFPE tissue blocks.
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Figure 5: Characterization of RNA in Biofl uid Samples Expression analysis of hsa-miR 24, hsa-miR 27a, and hsa-miR 98 in different biofl uid samples. Total RNA was purifi ed from plasma, serum, urine, and saliva using Asuragen’s proprietary isolation procedures. miRNAs were analyzed by qRT-PCR using the Ambion mirVana™ miRNA Detection Kit (urine and Serum) samples, Asuragen’s proprietary miRNA detection method (plasma samples), or TaqMan miRNA assays (ABI) (saliva samples). Total input RNAs vary from 250 pg/rxn for plasma to 14 ng/rxn for urine. miRNAs could be readily detected in all biofl uid samples tested.
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Figure 6: miRNA Stability in PlasmaPlasma from healthy donors was processed immediately or allowed to incubate for extended time periods at room temperature (25°C). miRNAs were analyzed by qRT-PCR using Asuragen’s proprietary miRNA detection method. Both hsa-miR 16 or hsa-miR 24 levels remained stable for at least 22 hours.
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Figure 8: miRNAs in Blood SamplesWhole blood from male and female donors was separated into plasma and cellular fractions. Total RNA was isolated from both fractions and qRT-PCR-based miRNA expression analysis was used to compare the miRNAs in the various samples. The relatively low correlation between the cellular and acellular fractions of blood suggests that the plasma is not simply a repository of miRNAs from blood cells, but that cells from organs in the body might also be contributing to the population of miRNAs in plasma. The levels of miRNAs in plasma from various individuals were surprisingly consistent, suggesting that there is a “normal” amount of cell-free miRNA in blood. This has important implications for diagnostics, since slight variations from normal induced by a disease will be relatively straight forward to identify.
Figure 9: Method for miRNA Expression AnalysisTotal RNA was isolated from plasma of prostate and lung cancer patients and miRNA expression profi les were generated by qRT-PCR. Comparing two lung cancer patients or two prostate cancer patients reveals very few signifi cantly differentially expressed miRNAs. While the levels of miRNAs in the plasma of prostate and lung cancer patient samples were also very similar, it is noteworthy that several miRNAs appeared to be present at signifi cantly higher levels in the plasma of prostate cancer patients than in the lung cancer patients.
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Figure 7: miRNA Normalization Plasma RNAs isolated from 8 healthy donors were compared in qRT-PCR. A total of 16 miRNAs (250 pg input/rxn) were analyzed using TaqMan miRNA assays (ABI) or Asuragen’s proprietary miRNA detection assays. Data was analyzed by geNorm and NormFinder algorithms, which both identifi ed the same miRNA as the most suitable reference RNA for normalization. Representative data for 3 miRNA targets are shown.
