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Bachelor Thesis, 2009, 54 Pages
1.1 Breast Cancer
1.2 RNA Expression Profiling and Prediction
1.3 Conceptional Formulation and Objectives
2 Materials and Methods
2.1.1 Instruments and Consumables
2.1.2 Buffers and Chemicals for Nucleic Acid Purification
2.1.3 Nucleic Acids, Cell Lines and Tissue Samples
2.1.4 Synthetic Oligonucleotides
2.1.5 Chemicals and Kits for PCR
2.2.1 General Approach
2.2.2 Purification of Nucleic Acids
2.2.3 Creation of a Standard Reference RNA Pool
2.2.4 Real-Time Kinetic RT-PCR
2.2.5 Designing Dually Labeled Primer-Probe Sets
2.2.6 Dilution of Primer-Probe Sets
2.2.7 Setup of Singleplex kPCR Assays
2.2.8 Evaluation of Different Reporter Dyes
2.2.9 Controlling of Primer-Probe-Set Performance
2.2.10 Testing Combinations of Two Sets (Duplexing)
2.2.11 Testing Combinations of Three Sets (Triplexing)
3.1 Identification of Suitable Reporter Dyes
3.2 Evaluation of Primer-Probe-Performance
3.3 Identification of Suitable Duplex Combinations
3.4 Identification of Suitable Triplex Combinations
4.1 Statistical Evaluation of Primer Performances
4.2 Suitable Reporter Dyes and Quencher
4.3 Optimization of Assays and kinetic RT-PCR Parameter
7.4 Oligonucleotide Sequences
7.5 Origins of Breast Cancer Samples for MAVPOOL080623a
“Cancer” describes a group of various diseases, where cells start changing their molecular structure and begin to grow and to supersede normal cells. Cancer is induced by numerous different elicitors, which finally all lead to an interference of the genetically regulated balance between cell cycle and apoptosis. Although every organ in the human body can be afflicted with cancer, there are significant differences in frequency relating amongst others to age, sex, geographic region and personal habits.
In the industrialized countries, breast cancer is the leading cause of death for women at the age between 30 and 60 years. With estimated 636.000 incident cases in the developed countries and 514.000 in the developing countries, breast cancer is the most prevalent cancer type among woman worldwide [World Cancer Report 2008].
Once detected, the cancer is classified based upon pathological characterizations of the tumor or a biopsy and the lymph nodes. A clinical way of characterizing the tumor is the TNM-classification, which describes the size of the tumor (T), the number of affected lymph nodes (N) and the existence of distant metastases (M). The histological classification characterizes the carcinoma according to its structural and cellular appearance and the amitosis rate leading to a grading from 1 to 3. An immuno-histological examination provides information about the estrogen- and the progesterone-receptor- and about the Her-2/neu-status [Wolff A et al 2007].
Breast cancer is a very heterogeneous disease. There are basic classifications that are unquestioned, even today. Recent studies confirmed the need to determine well known markers (i.e. estrogen (ER) and progesterone (PR) receptor status [Garcia-Closas M, 2008] or HER2 status [Science Daily, 2007]), but the large variety of subtypes and the corresponding different molecular pattern impede a uniform treatment.
Although already today other factors than anatomical classifications are being taken into consideration, there exists a need for further biological markers to assist the physician in charge with his evaluation. Beside the diagnostic recognition, the choice of appropriate therapy and the prediction of prognosis are goals that should be reached in order to prevent early stage cancer patients from therapies that provide minimal benefit but reduce their quality of life by intense adverse reactions [Ganz PA et al 2004].
Already today there are numerous genes associated with breast cancer occurrence, therapy selection and prognosis [van ‘t Veer LJ et al 2002]. These profiles can be generated by different techniques, like DNA-microarrays or kinetic polymerase chain reaction (kPCR). The kPCR displays the handier platform for research laboratories in terms of choices of genes. It was the method of choice during this work.
Besides choosing the appropriate genes for analysis, there are several other elementary requirements that may lead to solid results like a statistical relevant number of tissue samples and a dependable and accurate follow-up documentation of the patient’s disease history. Within this follow-up, clinical parameters and important events like the recurrence of tumors, discovery of metastasis or demise must be documented. These parameters can then be correlated to gene expression profiles by extensive statistical analysis [Buyse M et al 2007].
Targeting patients with lymph-node-negative breast cancer, Siemens Healthcare Diagnostics designed a diagnostic assay to predict the probability of developing distant metastasis after surgery within 5 to 10 years. This kPCR-based quantification method draws upon several previously determined and selected genes, and uses formalin-fixed, paraffin-embedded (FFPE) tissue samples of 310 patients from the Department of Obstetrics and Gynecology, Johannes-Gutenberg-University Mainz, Germany [Stropp U et al 2008]. After quantifying these genes of interest (GOI) and normalizing on housekeeping genes (HKG), the determined amounts were correlated with comprehensive statistical data of the patients. Finally an algorithm was developed to predict the forecast of patients and to determine their need for chemotherapy.
This diagnostic assay consists of 9 GOIs, 2 HKGs and 1 DNA control and is performed within a 96-well polypropylene plate.
To verify suitable algorithms, they have to be confirmed within control groups. 7 different algorithms were developed by in-house statisticians, who applied different mathematical approaches. These 7 algorithms were then applied to control groups to determine the most reliable and reproducible method.
The goal of this work was to reduce the amounts of wells per patient and assay by transforming the existing 12 singleplex assays into duplex- and triplex-formats, in order to increase the number of samples per plate or to allow more reference-control genes within a multiplex assay.
The primary goals of this project are:
- Reduction of cost of approximately 50% for mastermixes per patient
- Higher throughput due to larger sample number per plate
- Larger number and higher variety of GOIs per patient and plate
- Retrenchment of very valuable RNA material
- Generation of resources to run additional quality assurance (housekeeping-genes)
The platform the kPCRs were performed on was Stratagene’s MX3005p – a multichannel kPCR machine which possesses a tungsten halogen lamp and 5 different filter sets for parallel analysis of the corresponding amount of reporter dyes. It is able to excite and detect fluorophores with an excitation and emission wavelength between 400 and 700nm [Marras 2005]. The identification of suitable reporter dyes for the filter sets by performance-analysis was the initial requirement during this work, following the evaluation of compatibility of dyes among each other within multiplex assays. Finally the most promising and reliable multiplex assays had to be identified amongst the numerous different possible combinations.
In the context of this evaluation process great attention was put on consistent parameter during kPCR (i.e. buffer conditions, reaction volume, usage of identical lots, cycle conditions, etc.) and to strictly exclude any crosstalk between the individual channel.
The results emerging from this work will deliver a substantiated basis upon which further comparative studies with more comprehensive numbers of patients can be measured. Then, in-house bioinformaticians will test the existing algorithm on data gained from multiplex assays of a statistical larger universe of patients.
EPPENDORF, Hamburg, Germany
Centrifuge 5804, Cat. No.: 5804 000.013 with
Centrifuge Rotor A-2-DWP, Cat. 5804 740.009
Pipet Reference variable 0,1 – 2,5µl, Cat. No.: 4910 000.085
Pipet Reference variable 0,5 – 10µl, Cat. No.: 4910 000.018
Pipet Reference variable 10 – 100µl, Cat. No.: 4910 000.042
Pipet Reference variable 100 – 1000µl, Cat. No.: 4910 000.069
GILSON. Middleton, WI, USA
Repititive Pipet Distriman. Cat. No.: F164001
HEIDOLPH, Schwabach, Germany
Vortexer Reax Control, Cat. No.: 541-11000
LABNET, Woodbridge, NJ, USA
Centrifuge Quick Spin Minifuge, Cat. No.: C1201
SARSTEDT, Siegburg, Germany
Micro tube with screw cap 1.5ml, Cat. No.: 72.692.005
STRATAGENE, La Jolla, CA, USA
Mx3005P QPCR System, Cat. No.: 401458 with Alexa405-, ROX-, HEX-, FAM- and Cy5-Filter
Mx3000P®/Mx3005P® Optical Strip Caps, Cat. No.: 401425
Mx3000P® 96-well-plates skirted, Cat. No.: 401334
TECAN, Crailsheim, Germany
Robot Genesis Workstation 150
QIAGEN, Hilden, Germany
Proteinase K, Cat. No.: 19133
SIEMENS MEDICAL SOLUTIONS DIAGNOSTICS GMBH, Eschborn, Germany
Lysis Buffer, Cat. No.: 03745099
Washing Buffer I, Cat. No.: 03745226
Washing Buffer II, Cat. No.: 03746737
Washing Buffer III, Cat. No.: 03742146
Elution Buffer, Cat. No.: 03742677
Magnetic Beads, Cat. No.: 03749787
DSMZ, Braunschweig, Germany
German Collection of Microorganisms and Cell Cultures, Braunschweig
MCF-7 cell line, Cat.No.: DSMZ ACC 115
(RNA isolated using QIAGEN, RNeasy Mini Kit, Cat.No. 74104 according to manufacturers instructions)
STRATAGENE, La Jolla, CA, USA
Stratagene QPCR Reference Total RNA, Human, Cat. No.: 750500
BREAST CANCER SAMPLES
Prof. Dr. med Stephan Störkel, Helios Klinikum Wuppertal, Departement for Pathology
Prof. Dr. Med Carsten Denkert, Charite Berlin, Departement for Pathology
Samples from women with invasive breast cancer, surgery 2003
5-10µm Slides of FFPE Samples with tumor cell content >30%
Informed Consent of Patients at hand.
MICROSYNTH, Balgach, Switzerland
HPLC-purified oligonucleotides and MALDI/TOF-controlled probes
(See appendix for complete listing of oligonucleotide sequences)
AMBION, Austin, TX, USA
Nuklease-free water (not DEPC-treated), Cat. No.: AM9932
RNaseZap, Cat. No.: AM9782
DNAzap, Cat. No.: AM9890
INVITROGEN, Carlsbad, CA, USA
SuperScript III Platinum One-Step qRT-PCR kit, Cat. No.: 11732-088
MICROSOFT, Redmont, WA, USA
Microsoft Office Professional Edition 2003
APPLIED BIOSYSTEMS, Foster City, CA, USA
Primer Express Version 2.0.0
STRATAGENE, La Jolla, CA, USA
MxPro – Mx3005p v4.01 Build 369, Scheme 80
All working steps concerning the handling of RNA were performed at a reserved working place and with instruments, which were kept RNAse free.
Unless otherwise noted, when water is mentioned in the text, nuclease-free water is referred to.
Nucleic acids (NA) used in the context of this work were derived from formalin-fixed, paraffin embedded (FFPE) tissues of women with breast cancer surgery and from MCF-7 cell lines (see appendix 6.2). The tissue samples were available as paraffin sections of 5-10µm thickness and were stored at 8°C in 1,5ml Sarstedt reaction tubes. MCF-7 cell line is commercially available from the German Collection of Microorganisms and Cell Cultures, Braunschweig.
All nucleic acids extracted from patients breast-cancer samples were purified by an automated in-house sample preparation method using magnetic beads [Hennig G and Hildenbrand K 2006], specific solutions and a pipetting-robot (Figure 1).
Within this method, RNA was extracted from FFPE-samples. For this, samples were treated with a lysis buffer and Proteinase K and incubated for 2h at 65°C.
Together with a special binding buffer, the magnetic beads were added and incubated for another 10min at room temperature (RT).
While magnetizing the bead-bounded NAs, three wash-steps with washing buffer I - III removed waste compounds.
Finally an elution buffer was used to separate the NAs from the magnetic beads at 70°C and a DNAse I digestions removed the DNA to obtain the desired, pure RNA.
illustration not visible in this excerpt
Figure 1: Schematic Workflow of Nucleic Acid Extraction from FFPE Samples
A standard reference RNA pool was needed for further testings. Previous experiments had shown, that commercially available reference RNAs (i.e. Universal Human Reference RNA, Stratagene, Cat. No.: 740000) did not represent a realistic gene profile, since some genes of interest (GOI) are only amplified in patients RNA but not in commercial reference RNAs. (Mojica WD, Stein L, Hawthorn L 2008).
Therefore, RNA from 83 breast cancer samples and MCF-7 cells (see appendix for details of origin) was isolated and the extracted RNA was combined into a common pool. A dilution series was made by diluting the RNA with nuclease free water according to the following scheme:
Table 1: Dilution Series of Human Breast Cancer Samples for Setting up a Standard Reference RNA Pool
illustration not visible in this excerpt
5000µl of each dilution was then aliquoted in 50 x 100µl and stored as “MAVPOOL080623a” at -80°C.
The real-time quantitative RT-PCR method used to quantify RNA in breast cancer tissue combines two successive steps.
First, RNA is transcribed into cDNA by the enzyme reverse transcriptase, an RNA-dependent DNA-polymerase, which was first discovered in retroviruses (Gilboa E et al 1979) and which is able to synthesize a RNA-DNA-hybrid-strand from a single-stranded RNA, degrade the residual RNA and complete the molecule into a double-stranded cDNA.
In the second step, the cDNA serves as a template for the following quantitative polymerase chain reaction (PCR). The PCR uses two sequence-specific oligonucleotides and a DNA-dependent polymerase to amplify a definite DNA segment (Mullis KB, Faloona FA 1987).
An improvement of the PCR is the real-time quantitative PCR, where a third oligonucleotide, a hybridization probe labeled with two different fluorescent dyes and located between the forward- and the reverse-primer, is used. Since one dye works as the reporter dye (i.e. FAM, Cy5, Yakima Yellow, etc.) and the other one as the corresponding quencher (like TAMRA, BHQ1, BHQ2, etc.), the quencher absorbs the emission of the reporter dye by fluorescent resonance energy transfer (FRET).
When this dual-labeled probe hybridizes with the template DNA, the 5’-3’ nucleolytic activity of the polymerase degrades this probe resulting in a loss of quenching activity. Thus, a continuous increase of occurs during PCR. The amount of fluorescence at a given time point during PCR corresponds to the amount of PCR product. Since fluorescence is measured following each PCR cycle, it is possible to observe the amplification process “real-time” and to count back to the initial amount of cDNA (Heid CA, Stevens J, Livak K J et al.1996).
Primer design was accomplished with the help of the software tool Primer Express v2.0.0 from Applied Biosystems. Although this software was built for designing TaqMan® primer and probe sets, it delivers excellent results for other real-time applications such as the MX3005p. When choosing TaqMan® Primer and Probe Design, the software operates with predefined parameters using empirical rules to calculate optimal sequences based upon the input sequence. The most important parameters for the probe were:
- Amplicon size should range from 50 – 150 base pairs (bp)
- G/C content should be kept between 30% and 80%
- Avoiding repeats of identical bases – especially of Guanine
- The melting temperature should be between 68°C and 70°C
- No 5’-terminal Guanine
- Primers should be designed a close to the probe as possible
(Source: Primer Express Software Version 3.0 Getting Started Guide)
The corresponding forward- and reverse-primer were also automatically designed by that software and their melting temperature should have been about 10°C below the probe-temperature.
Although all samples were treated with DNAse, this digestion is very often imperfect [Wink, 2004]. The use of RNA-specific primer probe sets copes with that specific problem. In order to avoid amplification of genomic DNA, RNA-specific, intron-spanning [Freeman, 1999] primer-probe sets were designed if possible, based upon the cDNA sequence.
All primer-probe sets were ordered from Microsynth, Switzerland in 0.2µmol scale and HPLC purified.
Each set consisted of two standard oligonucleotides and one dual-labeled probe. Both, the unmodified and the modified oligonucleotides were first diluted to a final concentration of 100µM according to the documents provided by Microsynth. The working solution consisted of 50µl (each) forward and reverse primer and 25µl probe filled up with nuclease free water to a total volume of 1000µl. Thus, the working solution consisted of two unmodified oligonucleotides (5µM each) and one dual-labeled probe (2,5µM).
The standard setup for a singleplex QPCR was based upon a total volume of 20µl. The following quantities of the constituents were used:
Table 2: Setup of a Standard kPCR Assay
illustration not visible in this excerpt
After combining mastermix, water, primer-probe mix and MgSO4, the RT/Taq mix and the RNA was added, whereas both, the RT/Taq mix and the RNA must be handled on wet ice and all pipetting steps were performed on wet ice, too.
MgSO4 might affect the performance of the PCR, since its concentration affects primer annealing, denaturation of the strands and product specifity. In addition, MgSO4 is needed for the activity of enzymes. Since primer and nucleotides capture available MgSO4 [Mülhardt, C., 2000] the concentration was elevated by adding 1µl of 50mM MgSO4 to the mix. Since the 2x mastermix already contains 6mM MgSO4 the final concentration is increased by 2.5mM to 5.5mM MgSO4 [Henegariu O et al 1997].
After diluting the primer-probe mix, the final concentrations per assay are 250nM for each of the two unmodified oligonucleotides and 125nM for the dual-labeled probe.
Reactions were performed in 96-well polypropylene plates. After pipetting all required components, the plate is sealed with lids and centrifuged at 1500rpm for 5min before transferring it to the Stratagene MX3005p QPCR machine. This step is useful to remove possibly existing bubbles on the ground of each well, resulting in better duplicates.
The thermal profile was set based upon Invitrogens recommendations regarding their SuperScript III Platinum One-Step Quantitative RT-PCR System protocol. An adjustment of 50 cycles instead of 40 was the only change that was carried out.
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