RealTime ready Application Note No. 6

Abstract

One of the fundamental steps in characterizing tissues or cells using RT-qPCR based methods is the identification of valid endogenous reference genes that can be used for normalization. In this study, we probed and identified a set of reference genes for gene expression analysis in a set of different multipotent mesenchynmal stromal cells (MSCs). An envisioned outcome of the project is a concise panel of RealTime ready qPCR assays that are descriptive for biological states of the different cell types or stages and allow a fast and reliable characterization of human multipotent mesenchymal stromal cells.

Introduction

Every multicellular organism originates from a single cell. However, this totipotency is soon lost after the first cell divisions, resulting in increasingly specialized cellular offspring. Despite the terminal differentiation of most adult cells, it has long been known that some cellular progenitors in the adult organism maintain different degrees of pluri- or multipotency. Besides the ability to differentiate into various mesodermal cell lineages the MSCs, a subset of these cells, also show a striking capability to execute immune modulatory effects (for recent reviews on MSCs, see [1–3]).

In the current literature the abbreviation MSC is sometimes used ambiguously as either mesenchymal stromal or mesenchymal stem cell and it is still under debate whether MSCs really qualify as true stem cells. Here were refer to MSCs according to the International Society for Cellular Therapy definition as multipotent mesenchymal stromal cells [4].

Kornelius Wiechman*, Heiko Walch+, Alex Seiler+, Markus Neubauer*, Heike Wegmeyer*

* Roche Pharma, Penzberg+ Roche Applied Science, Penzberg

RealTime ready For life science research only. Not for use in diagnostic procedures.

December 2011

RealTime ready

Identification of Valid Endogenous References for Monitoring Gene Expression Changes in Human Multipotent Mesenchymal Stromal Cells using RealTime ready Assays

Identification of Valid Endogenous References for Monitoring Gene Expression Changes in Human Multipotent Mesenchymal Stromal Cells 22

Table 1: Genes contained in the RealTime ready Human Reference Gene Panel

The immune modulatory characteristic of MSCs, in conjunction with findings that they can be found in many different tissues throughout the body and that MSCs are “homing” towards inflamed regions, raised additional research interest. Stem cell research in general is one of the most active current research fields and receives increasing coverage in scientific literature as well as in public media. The plurality of possible applications described and discussed in the literature is not only reflected by the increase in scientific publications but also by the constant increase in clinical trials associated with stem cells (see Figure 1).

It is well known that sub-culturing or passaging of cells can lead to undesired and even dramatic changes in the cell characteristics [5-8]. In the case of MSCs, this could lead to partial differentiation into mesodermal cell linages, with accompanying loss of multipotency or (for example) the loss or alteration of immune modulatory abilities.

We aim to evaluate and monitor these changes on a gene expression level under controlled conditions and with standardized materials. Studying the potential use of MSCs in any therapeutic application demands strictest quality controls and standardizations. It is crucial not only to monitor and safeguard constant quality of all input materials but also to apply the highest possible quality control standards to the resulting cells. Our group is interested in determining,

whether the transcriptional regulation of a set of key marker genes can be used as a fast and reliable control system to assess certain characteristics of MSCs.

A first step in setting up a reasonable RT-qPCR experiment, as formulated by key opinion leaders in the MIQE guidelines [9, 10] is the identification of a set of reasonable reference genes for this particular application. Poor reference gene selection can render the whole experiment useless; because the reference genes are used for normalization, a potential marker can be only as powerful as the genes used for this normalization. Using multiple reference genes is considered a best practice guideline [9, 10]. The basic requirement to qualify as a normalizer is trivial to formulate (no regulation in the experimental circumstances), and several methods for identifying a good set of reference genes were recently published [11-13]. We decided to challenge and compare two of the methods that are also implemented in the GenEx qPCR analysis software package (MultiD) with our spreadsheet calculation approach and elucidate any possible differences. As a fast and pragmatic approach, we used the RealTime ready Human Reference Gene Panel, which contains a set of 19 RT-qPCR assays for reference genes well known from the literature (see Table 1). This selection offers a high chance to identify a suitable reference gene for a large number of applications.

AssayID Gene Symbol Gene Description

101125 ACTB actin, beta

101128 GAPDH glyceraldehyde-3-phosphate dehydrogenase

101144 RPLP0 ribosomal protein, large, P0

101145 TBP TATA box binding protein

102065 B2M beta-2-microglobulin

102074 GUSB glucuronidase, beta

102079 HPRT1 hypoxanthine phosphoribosyltransferase 1

102083 PGK1 phosphoglycerate kinase 1

102088 PPIA peptidylprolyl isomerase A (cyclophilin A)

102095 TFRC transferrin receptor (p90, CD71)

102098 G6PD glucose-6-phosphate dehydrogenase

102108 ALAS1 aminolevulinate, delta-, synthase 1

102110 HMBS hydroxymethylbilane synthase

102119 RPL13A small nucleolar RNA, C/D box 32A

102125 YWHAZ tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein

102132 IPO8 importin 8

102136 SDHA succinate dehydrogenase complex, subunit A

102141 HBB hemoglobin, beta

104092 RN18S1 RNA, 18S ribosomal 1

Figure 1: Growing interest in stem cells: The red line (right y-axis) shows the PubMed entries associated with the MESH search term “stem cells”, whereas the blue line (left y-axis) shows entries listed at www.ClinicalTrials.gov containing the term “stem cell” in the ‘Interventions’ search field.

Introduction continued

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Identification of Valid Endogenous References for Monitoring Gene Expression Changes in Human Multipotent Mesenchymal Stromal Cells 33

The purpose of the project is to identify possible marker genes indicating changes for MSCs in cell culture. The actual selection of marker genes was literature based and is partly described in more detail below. A reasonable pilot experiment to identify reference genes needs to be representative for the envisioned final experimental setup. We are interested in monitoring and characterizing gene expression changes of MSCs from different tissue sources, different cell culture passages and for different biological states. This included an experimental branch that monitors the MSCs’ expressional behavior after subjecting them to an inflamed environment mimicked by cytokine stimulation with TNF-alpha (TNF) and interferon gamma (IFNG) (see Table 2). A human dermal fibroblast and a cell line of endothelial origin served as additional controls. Our final sample set for the pilot experiment consisted of MSCs from four different human tissues, different donors and varying passages, the aforementioned fibroblast and endothelial cell lines. Three MSCs from different sources were also stimulated with cytokines (see Table 3).

From each cell culture, we isolated total RNA using the High Pure RNA Isolation Kit*. As a modification to the recommendations of the pack insert, we applied twice the amount of cells on each column (2 x 106). The RNAs were assessed using an Agilent biochip and showed RNA Integrity Numbers of 9.9 and 10, indicating perfect quality. Each RNA was reverse transcribed using the Transcriptor First Strand cDNA Synthesis Kit* with 2 µg of RNA input material. In order to have sufficient amounts of cDNA for further experiments, we scaled up to 5x the standard volume (see Table 4).

The cDNAs were purified and the final content was measured for each reaction using a NanoDrop (ThermoScientific). The same amount of cDNA was used for each PCR. For each cDNA, we performed qPCR experiments in triplicate with 2 ng cDNA in 20 µl volume (see Table 5).

* for ordering information pls. see page 7.

Cells and Experimental Setup

Compound Concentration Time

TNF-alpha 20 ng/ml 24 h

IFN-gamma 20 ng/ml 24 h

Table 2: MSC stimulation with cytokines

Source Tissue Donor Passage Stimulated

MSC 1 L1 P3

MSC 1 L2 P3

MSC 2 L1 P3

MSC 2 L1 P3 Yes

MSC 2 L1 P9

MSC 3 L3 P3

MSC 3 L3 P3 Yes

MSC 4 L3 P2

MSC 4 L3 P2 Yes

Endothelial cells

Fibroblasts

Component Volume (5x) Final Conc.

Total RNA variable 10 µg

Oligo (dT)18 Primer (Vial 5) 5 µl 2,5 µM

Random Hexamer Primer (Vial 6) 10 µl 60 µM

Water, PCR grade (Vial 7) variable add 65 µl

Total Volumeà Mix carefullyà 10 min, 65°C (denaturation)à Place tube on ice

65 µl

Adding Enzyme

Buffer (Vial 2) 20 µl 1x

Protector RNase Inhibitor (Vial 3) 2,5 µl 20 U

dNTPs (Vial 4) 10 µl 1 mM each

Transcriptor RT (Vial 1) 2,5 µl 10 U

Total Volume 35 µl

End Volumeà Mix carefullyà 10 min 25°Cà 30 min, 55°C (RT reaction, up to 4 kb)à 5 min, 85°C (RT inactivation)à Place tube on ice

100 µl

Table 3: Cell types and treatments used in the pilot experiment

Table 4: cDNA synthesis setup and protocol

Components 1x 28 x

LightCycler® 480 Probes Master, 2x conc. (Vial 1) 10 µl 280 µl

Water, PCR grade (Vial 2) 8 µl 224 µl

cDNA (1 ng/µl) 2 µl 56 µl

Final Volume 20 µl 560 µl

à 20 µl / reaction

Table 5: PCR setup

Identification of Valid Endogenous References for Monitoring Gene Expression Changes in Human Multipotent Mesenchymal Stromal Cells 4

The experimental setup is depicted in Fig. 2. MSCs from four tissue sources were sampled from different donors, passaged and stimulated. The applied experimental schema allows evaluation of gene expression levels of MSCs from early and late passages for the same tissues from different donors as well as the gene expression differences between stimulated and not-stimulated cells for an early passage (see Figure 2).

The RealTime ready Human Reference Gene Panel* is available in 96- and 384-well formats; we decided to use the 96-well format that contains gene set quadruplicates on each plate. With the mentioned experimental layout, we

Figure 2: Diagram of the experimental setup. MSCs from 4 tissue sources were sampled from different donors, passaged and stimulated (left). The applied experimental schema (right) allows evaluation of gene expression levels of MSCs from early and late passages for the same tissues from different donors as well as the gene expression differences between stimulated and not-stimulated cells for an early passage.

Cells and Experimental Setup continued

needed 24 replicates or 6 plates overall. The plates are shipped with the specific primers and probe dried in each well of a LightCycler® 480 Multiwell Plate. The plate is sealed with a gold foil that can be easily removed. The overall experimental setup was accordingly fast and convenient, requiring only addition of the cDNA and the master mix (LightCycler® 480 Probes Master*) to the wells. The plates were placed into the LightCycler® 480 Instrument* and the predefined PCR program was finished after ~1 hour. The final results were readily exported as a text file from the LightCycler® 480 Software*. Data comparison and evaluation between the plates was performed outside the LightCycler® 480 Software.

Bone marrowAmniotic membraneUmbilical cordAdipose TissueDental pulpLiverHeartSynoviumOther postnatal connective tissues …

Characterization

Identification of Valid Endogenous References for Monitoring Gene Expression Changes in Human Multipotent Mesenchymal Stromal Cells 5

Quality ControlsThe RealTime ready Focus Panels each contain 5 assays that can be used for internal quality control. Two wells containing the same assay serve as a generic RT- control. The contained assay is known to amplify both cDNA and genomic DNA. One well receives the cDNA and the other well receives the raw RNA from the preparation. Whereas the cDNA well must result in a signal (RT+), the RNA well (RT-) should either be completely void of signal or the Cq should be sufficiently higher compared to the RT+ well. All 24 RT- wells produced no signal, indicating that no interfering amount of residual genomic DNA was contained in the RNA preparations.

The second control partly assesses the RNA quality and consists of three assays targeting different regions of the

Figure 3: TBP shows a uniform expression level across the different cell types and treatments. ACTB also shows a uniform expression but slightly reduced expression in the fibroblast cell line. In comparison the expression of 18S RNA and GAPDH shows considerably more variability. B2M and GUSB both show clear responses to the stimulation with cytokines.

Data Analysis and Results

same transcript. Ideally, all three assays should result in the same Cq values and extensive degradation of RNA should result in major shifts in the individual Cq values. This concept is evident for oligo-dT primed cDNA but partly levered out by using a mixed oligo-dT and random hexamer reverse transcriptase priming approach. Nevertheless, on average, the three assays showed a delta of 1.2 for replicates and none exhibited a difference above 1.4. This is expected, in concordance with the Agilent chip readout and generally expected with the good RNA quality achieved using the High Pure RNA Isolation Kit* with cell culture samples. Looking at the reproducibility of the technical replicates, we see a good average standard deviation of 0.19 Cqs, increasing our confidence in the overall technical setup.

ResultsTo identify the most stable expressed genes, we first exported all the Cq values and normalized the results with the average of all Cq values of each replicate. In a second step, we calculated the average Cq for one gene over all cell types and used this for normalizing the Cq of the individual

cell types. The results were plotted in individual histogram charts for each gene, as shown in Figure 3. The most stable expressed genes are indicated by evenly sized columns and by small error bars indicating the standard deviation as shown for 6 out of 19 genes.

3.00

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MSC1

L1 P3

MSC1

L2 P3

MSC2

L1 P3

MSC2

L1 P3

(S)

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MSC3

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L1 P9

MSC3

L3 P3

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L3 P3

(S)

MSC4

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(S)

GAPDH

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MSC1

L1 P3

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MSC2

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(S)

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L1 P9

MSC3

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MSC3

L3 P3

(S)

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MSC1

L1 P3

MSC1

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MSC2

L1 P3

MSC2

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(S)

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MSC3

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L3 P3

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GUSB

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Identification of Valid Endogenous References for Monitoring Gene Expression Changes in Human Multipotent Mesenchymal Stromal Cells 6

Data Analysis and Results continued

The assays for two of the classical housekeepers often cited in literature, 18S RNA and GAPDH, showed a higher variation compared to other genes from the gene set and therefore are inappropriate reference genes in our experimental regime. The assays for beta-2 microglobulin (B2M) and for beta-glucuronidase (GUSB) responded considerably to the stimulation with cytokines. Whereas B2M was up-regulated, GUSB seems to be down regulated. B2M is part of the MHC class I complex, which is known to be up-regulated upon IFNG stimulation [14] [15]. Assessing only the non-stimulated cell lines, B2M seems like a potential reference gene; however, including the cells from the stimulated experimental branch clearly disqualifies B2M as a references gene. This strongly emphasizes the need of including all relevant conditions in the pilot experiment. Using the described data analysis approach, TBP, ACTB, and IPO8 (data not shown) were selected as good reference genes for evaluating gene expression changes due to consecutive passages and stimulation with TNF and IFNG.

Data comparison can be tedious and time consuming in standard spreadsheet applications; we decided to evaluate the data analysis capabilities of the GenEx qPCR software package in conjunction with the recently published

RealTime ready Import Wizard* (see Figure 4). A detailed description of the few steps required to transfer the data into the software is provided by MultiD [16, 17]. In principle, all that is required are the exported Cq values from the LightCycler® 480 Software. The import wizard already knows the correct layout for the RealTime ready Focus Panels, and the data import with the first data cleanup steps is a guided workflow requiring only a few mouse clicks.

Several publications elucidated suitable statistical methods for identifying the genes with the least variance in a set of experiments. Two algorithms, GeNorm and Normfinder are implemented in GenEx [11, 13]. Both algorithms independently identified TBP and IPO8 as most stable references and B2M as well as GUSB under the most variant ones (see Figure 4). Both methods are in concordance with our own Excel based approach and differences from rank 3 on are only marginal and create a consistent overall picture. The planned follow-up experiments consist of an initial extensive gene selection of more than 250 different potential marker genes. As a consequence, we decided not to limit the number of references to the suggested two, but to expand the list with the top five references from the two algorithms.

Figure 4: Graphical output from GenEx for the NormFinder (left) and GeNorm (right) algorithms. The genes recommended as reference genes are shown in red. Both algorithms agree on the top and the bottom scoring genes. The biological meaningful separation of B2M due to the stimulated cells is more pronounced by NormFinder.

Genes

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Identification of Valid Endogenous References for Monitoring Gene Expression Changes in Human Multipotent Mesenchymal Stromal Cells 7

Conclusion

Outlook

Following the MIQE guidelines for experimental planning and reference gene selection is strongly recommended, and including all relevant samples and experimental conditions in the pilot experiment is certainly mandatory. Using the RealTime ready Human Reference Gene Panel in

Identifying the reference genes is only the first step. The final aim is to create one or more concise lists of regulated genes that are predictive for the biological state and hence the quality of MSC cell lines.

There are two principal ways to come up with a list of target genes for characterizing biological states. Following a common knowledge paradigm of Data > Information > Knowledge > Wisdom, a first holistic-view driven approach starts with assessing the expression of all possible genes (e.g., by array analysis.). A second approach tries to avoid generating costly and mainly useless data and takes a shortcut into the knowledge chain using and building on public and proprietary know-how to come up with a smaller and more concise list to start with. We decided to go for the second approach and performed extensive literature searches to narrow down the list of potential meaningful genes for our purpose. While doing so, we used the RealTime ready

conjunction with the RealTime ready Data Import Wizard from GenEx software provides a very fast and pragmatic approach to identify suitable reference genes, resulting in sound scientific data.

Configurator (www.configurator.realtimeready.roche.com)[18] extensively to gather information on the genes we extracted from literature. The RealTime ready Configurator proved to be a well-stocked collection of public and proprietary data; nearly 95% of all genes we were interested in were already covered by RealTime ready assays and all targets could be easily identified using the keyword search capabilities. Starting with common synonyms for gene targets sometimes resulted in multiples results which were helpful to clarify any ambiguities present in the public data. The genes not covered by RealTime ready assays so far were developed and lab tested by Roche Applied Science [19, 20] in a short time frame, saving us tremendous time, effort, and money for assay development. Overall the RealTime ready Configurator was used rather intensively and interactively to bring in new data and play around with different options before deciding on a final dataset and layout.

Ordering Information

Product Cat. No. Pack size.

RealTime ready Human Reference Gene Panel, 96

05 339 545 001 2 LightCylcer® 480 Multiwell Plates 96

RealTime ready Human Reference Gene Panel, 384

05 467 675 001 2 LightCylcer® 480 Multiwell Plates 384

Transcriptor First Strand cDNA Synthesis Kit 04 379 012 001 Kit for 50 reactions

LightCycler® 480 Probes Master 04 707 494 001 5 x 1ml

LightCycler® 480 Software, Version 1.5 04 994 884 001 1 software package

High Pure RNA Isolation Kit 11 828 665 001 50 isolations

RealTime ready Import Wizard available as part of GenEx Software from Multi D

www.realtimeready.roche.com www.configurator.realtimeready.roche.comwww.lightcycler.com

Published byRoche Diagnostics GmbHSandhofer Straße 11668305 MannheimGermany

© 2011 Roche Diagnostics.All rights reserved.

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For life science research only. Not for use in diagnostic procedures.

HIGH PURE, LIGHTCYCLER and REALTIME READY are trademarks of Roche.All other product names and trademarks are the property of their respective owners.

NOTICE: This product may be subject to certain use restrictions. Before using this product please refer to the Online Technical Support page (HYPERLINK „http://technical-support.roche.com/“ \o „http://technical-support.roche.com/“ http://technical-support.roche.com) and search under the product number or the product name, whether this product is subject to a license disclaimer containing use restrictions.

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11. Andersen, C.L., J.L. Jensen, and T.F. Orntoft, Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer research, 2004. 64(15): p. 5245-50.12. Pfaffl, M.W., et al., Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper--Excel-based tool using pair-wise correlations. Biotechnology letters, 2004. 26(6): p. 509-15.13. Vandesompele, J., et al., Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome biology, 2002. 3(7): p. RESEARCH0034.14. Tsuda, H., et al., Possible mechanisms for the elevation of serum beta 2-microglobulin levels in adult T-cell leukemia. International journal of hematology, 1992. 55(2): p. 179-87.15. Hemeda, H., et al., Interferon-gamma and tumor necrosis factor-alpha differentially affect cytokine expression and migration properties of mesenchymal stem cells. Stem cells and development, 2010. 19(5): p. 693-706.16. MultiD. GenEx qPCR Analysis Software. 2011; Available from: http://multid.se/.17. MultiD. Roche RealTime ready import Wizard. 2011; Available from: http://multid.se/UserGuide.pdf.18. Configurator, R. RealTime ready Configurator. 2011; Available from: https://configurator.realtimeready.roche.com/.19. Dietrich, M., et al. RealTime ready RT-qPCR Assay Development and Qualification. RealTime ready Whitepaper 2011; Available from: https://www.roche-applied-science.com/sis/ realtimeready/RT_docs/RTR_Whitepaper_2_3AK.pdf.20. Dietrich, M. and H. Walch. RealTime ready qPCR Assay Design and Configuration Portal Content. RealTime ready Whitepaper 2011; Available from: https://www.roche-applied-science.com/sis/ realtimeready/RT_docs/Whitepaper_3ak_HR_el.pdf.

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