MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR (qPCR)
May 16th, 2012
Quantitative Real Time polymerase chain reaction (qPCR) is a rapid and sensitive method to investigate the expression levels of various microRNA (miRNA) molecules in tumor samples. Using this method expression of hundreds of different miRNA molecules can be amplified, quantified, and analyzed from the same cDNA template.
The overall goal of the following experiment is to quantify the expression levels of micro RNA molecules in prostate cancer and normal prostate tissue using quantitative real-time PCR. This is achieved by first extracting total RNA from prostate tissues. That includes Mr NA micro RNA, and other small RNAs.
Next, the RNA is reversed transcribed to generate CDNA. Then cyber green based real-time PCR is carried out using the CD NA as a template to amplify and quantitate micro RNA expression in real time. Results are obtained that show relative expression of microRNAs in various prostate samples based on quantitative realtime PCR.
The main advantage of this technique over other methods is that it offers great sensitivity, accuracy, reproducibility, and it is fast and cost effective. This method can be used to answer key questions in the field of cancer biology as microRNA expression is often correlated with genes that are heavily involved in the cancer process. We can therefore use QPCR to assess the expression of microRNAs and see how this correlates with clinical variables.
These biomarkers may potentially be used as both diagnostic and prognostic tools. They may help us diagnose prostate cancer as well as help us determine which prostate cancers are aggressive. In addition, there is potential for these biomarkers to be therapeutic agents.
Not only can this method provide insight into prostate tumor genesis, it may also be applied to other cancers and diseases. Collect prostate samples at the time of ectomy and orient the specimen using anatomic landmarks. Paint the prostate and the seminal vesicles as follows, right side green, left side blue.
Take a random transverse midsection of the tissue perpendicular to the rectal surface, freeze the sample and store it negative 80 degrees Celsius. Take a photocopy and orient the slices of specimens and divide them into four equal parts. Consult a pathologist to determine the tumor versus normal areas on the corresponding image.
Use the marked areas as a guide to identify tumor tissue for extracting RNA To isolate RNA. Begin by placing frozen prostate samples on dry ice and referring to the delineated photocopy. Cut out a small portion of the prostate tumor.
Homogenize the prostate tumor tissue in one milliliter of triol reagent. Incubate the homogenized samples for five minutes. At room temperature, add 0.2 milliliters of chloroform to the samples and shake vigorously for 15 seconds.
Incubate the samples for three minutes at room temperature, then centrifuge at 12, 000 times G for 15 minutes at four degrees Celsius. Transfer the colorless upper aqueous phase to fresh tubes and add 0.5 milliliters of isopropyl alcohol. Incubate samples for 10 minutes at room temperature, then centrifuge 12, 000 times G for 10 minutes at four degrees Celsius.
Carefully aspirate the supernatant without disturbing the pellet containing the RNA. Add one milliliter of 75%ethanol to the RNA pellet vortex, the sample and sediment by centrifugation for five minutes at 7, 500 times G at four degrees Celsius. Again, aspirate the SNAT and dry the RNA pellet for five to 10 minutes, making sure it is not completely dry.
Red, dissolve the pellet in nuclease free water and use a spectrophotometer to measure the concentration of the RNA. Use a bioanalyzer to check the quality and integrity of the RNA samples. Reverse transcribe the RNA into CDNA using a reverse transcription kit according to the manufacturer's instructions.
To generate a standard curve, prepare a series of dilution of the original CD NA from a sample that is known to have a substantial expression of the gene of interest. Perform real-time PCR by preparing a master mix based on a 20 microliter reaction volume of two x quant. Detect cyber green PCR master mix 10 x microscript universal primer, 10 x microscript primer assay and RN a's free water.
Include two sets of primers, one for the target gene and another for the reference gene in this case, RNU six B.Pipette two microliters of each CDNA dilution into individual light cycler capillary tubes, and add 18 microliters of the master mix. Use a capillary adapter to centrifuge. Place the capillaries into a capillary based realtime cycler and run the PCR program as follows, 95 degrees Celsius for 15 minutes, followed by 50 cycles of 94 degrees Celsius for 15 seconds.
55 degrees Celsius for 30 seconds and 70 degrees Celsius. For 30 seconds, select a sample to be the calibrator and set its normalized target amount to one. Compare the relative expression of the micro RNA in all the other samples to the calibrator to generate amplification curves.
For the PCR reactions, use the molecular biochemicals light cycler software version 3.5 in the quantification tab. Quantify the reactions and export the data to a text file. Import the data to the REL quant analysis software to generate quantification results.
Import separate files for target gene, reference gene and standard curve data. Specify the position of the calibrator for both target and reference gene, as well as the positions of the samples. Data is expressed as the target to reference ratio of different samples divided by the target to reference ratio of the calibrator.
Use the standard curve previously generated for a particular micro RNA and housekeeping gene as a reference standard for extrapolating quantitative data for micro RNA. Targets of unknown concentrations. Analyze three samples as a group and calculate the mean concentrations and standard deviations of the triplicate.
If one of the triplicates is inconsistent with the rest of the set, the program will exclude it. Shown here is an example of A-Q-P-C-R analysis of prostate samples. The graphs showing the expression levels of the reference gene U six begin exponential amplification at about cycle 20 while expression of the target gene, MIR 98 showed delayed amplification around cycle 25.
The data from this experiment were exported as a text file and analyzed by requ analysis software positions of the capillaries containing the calibrator and samples are specified. Once mastered, this technique can be done in one day when performed properly. Reliability of this technique depends on the quality of RNA.
Therefore, it's important to take extra care in handling RNA because it can degrade very easily.
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Overview
This study utilizes quantitative real-time polymerase chain reaction (qPCR) to measure microRNA expression levels in prostate cancer and normal prostate tissue. The method allows for the amplification and quantification of various miRNA molecules from the same cDNA template.
Key Study Components
Area of Science
- Neuroscience
- Oncology
- Molecular Biology
Background
- MicroRNAs play a crucial role in gene regulation.
- Prostate cancer is a significant health concern.
- Understanding miRNA expression can provide insights into cancer biology.
- qPCR is a widely used technique for analyzing gene expression.
Purpose of Study
- To quantify microRNA expression levels in prostate cancer tissues.
- To compare miRNA levels between cancerous and normal prostate tissues.
- To utilize qPCR for sensitive and rapid analysis of miRNA.
Methods Used
- Total RNA extraction from prostate tissues.
- Reverse transcription to generate cDNA.
- Cyber Green-based real-time PCR for amplification.
- Quantification of microRNA expression in real time.
Main Results
- Relative expression levels of various microRNAs were determined.
- Differences in miRNA expression between cancerous and normal tissues were observed.
- Results highlight the potential of miRNAs as biomarkers for prostate cancer.
- qPCR proved effective for analyzing multiple miRNAs simultaneously.
Conclusions
- qPCR is a valuable tool for studying microRNA expression in cancer research.
- Findings may contribute to the understanding of prostate cancer biology.
- Further research is needed to explore the functional roles of identified miRNAs.
Frequently Asked Questions
Executive Industry Relevance
Quantitative real-time PCR (qPCR) for microRNA detection in prostate tumors enables sensitive, reproducible quantification of miRNA expression, supporting early biomarker discovery and target validation. This workflow addresses the need for robust, quantitative molecular readouts in oncology R&D, facilitating risk-adjusted decisions at the discovery and translational interface. Reliable miRNA quantification underpins portfolio triage and informs mechanistic de-risking in cancer research pipelines.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables quantitative interrogation of miRNA involvement in oncogenic pathways.
- Supports functional target validation by correlating miRNA expression with clinical variables.
- Facilitates mechanistic de-risking through precise measurement of regulatory RNA species.
- Provides data for prioritizing candidate biomarkers in early-stage oncology programs.
Screening & Assay Development
- Delivers validated, quantitative assays for miRNA detection in clinical and preclinical samples.
- Standardizes normalization using reference genes to ensure reproducibility across experiments.
- Enables scalable, high-throughput screening of miRNA expression profiles.
- Supports assay transferability to other tissue types and disease models.
Translational & Preclinical Research
- Aligns miRNA quantification with clinical sample analysis for translational biomarker development.
- Ensures continuity from discovery through preclinical validation by using archived and fresh samples.
- Provides quantitative endpoints for evaluating disease relevance of candidate miRNAs.
- Reduces translational risk by enabling robust cross-sample comparisons.
Pipeline & Workflow Integration
This qPCR-based miRNA quantification method integrates from early discovery through translational research, supporting lead identification and preclinical validation in oncology pipelines.
- Discovery Biology: Quantitative miRNA profiling clarifies regulatory mechanisms and supports hypothesis-driven target selection.
- Screening: Standardized qPCR assays enable reproducible, quantitative readouts for compound or biomarker screening.
- Analytics: Relative quantification and normalization provide actionable data for comparing tumor and normal samples.
- Translational Research: Method accommodates both fresh and archived clinical samples, supporting biomarker continuity.
- Enterprise Reuse: Assay design and normalization strategies are adaptable across tissue types and disease areas.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence in miRNA-based target validation and biomarker discovery.
- Operational Value: Delivers standardized, reproducible, and scalable workflows for molecular quantification.
- Strategic Value: Improves go/no-go decisions and reduces late-stage biological risk in oncology portfolios.
- Portfolio Impact: Enables risk-adjusted prioritization of candidate biomarkers and therapeutic targets.
Implementation Considerations
- Requires expertise in RNA handling and qPCR assay design.
- Demands high-quality instrumentation for RNA extraction, cDNA synthesis, and real-time PCR.
- Necessitates rigorous normalization and reference gene selection for cross-sample comparability.
- Adaptable to various tissue types and archived clinical specimens with appropriate validation.
- RNA integrity and sample handling are critical to data reliability and reproducibility.
