Identification of genes for normalization of real-time RT-PCR data in breast carcinomas

<p>Abstract</p> <p>Background</p> <p>Quantitative real-time RT-PCR (RT-qPCR) has become a valuable molecular technique in basic and translational biomedical research, and is emerging as an equally valuable clinical tool. Correlation of inter-sample values requires data normalization, which can be accomplished by various means, the most common of which is normalization to internal, stably expressed, reference genes. Recently, such traditionally utilized reference genes as GAPDH and B2M have been found to be regulated in various circumstances in different tissues, emphasizing the need to identify genes independent of factors influencing the tissue, and that are stably expressed within the experimental milieu. In this study, we identified genes for normalization of RT-qPCR data for invasive breast cancer (IBC), with special emphasis on estrogen receptor positive (ER+) IBC, but also examined their applicability to ER- IBC, normal breast tissue and breast cancer cell lines.</p> <p>Methods</p> <p>The reference genes investigated by qRT-PCR were RPLP0, TBP, PUM1, ACTB, GUS-B, ABL1, GAPDH and B2M. Biopsies of 18 surgically-excised tissue specimens (11 ER+ IBCs, 4 ER- IBCs, 3 normal breast tissues) and 3 ER+ cell lines were examined and the data analyzed by descriptive statistics, geNorm and NormFinder. In addition, the expression of selected reference genes in laser capture microdissected ER+ IBC cells were compared with that of whole-tissue.</p> <p>Results</p> <p>A group of 3 genes, TBP, RPLP0 and PUM1, were identified for both the combined group of human tissue samples (ER+ and ER- IBC and normal breast tissue) and for the invasive cancer samples (ER+ and ER- IBC) by GeNorm, where NormFinder consistently identified PUM1 at the single best gene for all sample combinations.</p> <p>Conclusion</p> <p>The reference genes of choice when performing RT-qPCR on normal and malignant breast specimens should be either the collected group of 3 genes (TBP, RPLP0 and PUM1) employed as an average, or PUM1 as a single gene.</p

Selection of reference genes for normalization of quantitative real-time PCR in organ culture of the rat and rabbit intervertebral disc

<p>Abstract</p> <p>Background</p> <p>The accuracy of quantitative real-time RT-PCR (qRT-PCR) is often influenced by experimental artifacts, resulting in erroneous expression profiles of target genes. The practice of employing normalization using a reference gene significantly improves reliability and its applicability to molecular biology. However, selection of an ideal reference gene(s) is of critical importance to discern meaningful results. The aim of this study was to evaluate the stability of seven potential reference genes (Actb, GAPDH, 18S rRNA, CycA, Hprt1, Ywhaz, and Pgk1) and identify most stable gene(s) for application in tissue culture research using the rat and rabbit intervertebral disc (IVD).</p> <p>Findings</p> <p><it>In vitro</it>, four genes (Hprt1, CycA, GAPDH, and 18S rRNA) in rat IVD tissue and five genes (CycA, Hprt1, Actb, Pgk1, and Ywhaz) in rabbit IVD tissue were determined as most stable for up to 14 days in culture. Pair-wise variation analysis indicated that combination of Hprt1 and CycA in rat and the combination of Hprt1, CycA, and Actb in rabbit may most stable reference gene candidates for IVD tissue culture.</p> <p>Conclusions</p> <p>Our results indicate that Hprt1 and CycA are the most stable reference gene candidates for rat and rabbit IVD culture studies. In rabbit IVD, Actb could be an additional gene employed in conjunction with Hprt1 and CycA. Selection of optimal reference gene candidate(s) should be a pertinent exercise before employment of PCR outcome measures for biomedical research.</p

Impact of Reference Gene Selection for Target Gene Normalization on Experimental Outcome Using Real-Time qRT-PCR in Adipocytes

Background: With the current rise in obesity-related morbidities, real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) has become a widely used method for assessment of genes expressed and regulated by adipocytes. In order to measure accurate changes in relative gene expression and monitor intersample variability, normalization to endogenous control genes that do not change in relative expression is commonly used with qRT-PCR determinations. However, historical evidence has clearly demonstrated that the expression profiles of traditional control genes (e.g., b-actin, GAPDH, a-tubulin) are differentially regulated across multiple tissue types and experimental conditions. Methodology/Principal Findings: Therefore, we validated six commonly used endogenous control genes under diverse experimental conditions of inflammatory stress, oxidative stress, synchronous cell cycle progression and cellular differentiation in 3T3-L1 adipocytes using TaqMan qRT-PCR. Under each study condition, we further evaluated the impact of reference gene selection on experimental outcome using examples of target genes relevant to adipocyte function and differentiation. We demonstrate that multiple reference genes are regulated in a condition-specific manner that is not suitable for use in target gene normalization. Conclusion/Significance: Data are presented demonstrating that inappropriate reference gene selection can have profound influence on study conclusions ranging from divergent statistical outcome to inaccurate data interpretation of significan

Scaling relationships based on partition coefficients and body sizes have similarities and interactions

The LC50 of compounds with a similar biological effect, at a given exposure period, is frequently plotted log-log against the octanol-water partition coefficient and a straight line is fitted for interpolation purposes. This is also frequently done for physiological properties, such as the weight-specific respiration rate, as function of the body weight of individuals. This paper focuses on the remarkable observation that theoretical explanations for these relationships also have strong similarities. Both can be understood as result of the covariation of the values of parameters of models of a particular type for the underlying processes, while this covariation follows logically from the model structure. The one-compartment model for the uptake and elimination of compounds by organisms is basic to the BioConcentration Factor (BCF), or the partition coefficient; the standard Dynamic Energy Budget model is basic to the (ultimate) body size. The BCF is the ratio of the uptake and the elimination rates; the maximum body length is the ratio of the assimilation (i.e. uptake of resources) and the maintenance (i.e. use of resources) rates. This paper discusses some shortcomings of descriptive approaches and conceptual aspects of theoretical explanations. The strength of the theory is in the combination of why metabolic transformation depends both on the BCF and the body size. We illustrate the application of the theory with several data sets from the literature

Analysis of ecological thresholds in a temperate forest undergoing dieback.

Positive feedbacks in drivers of degradation can cause threshold responses in natural ecosystems. Though threshold responses have received much attention in studies of aquatic ecosystems, they have been neglected in terrestrial systems, such as forests, where the long time-scales required for monitoring have impeded research. In this study we explored the role of positive feedbacks in a temperate forest that has been monitored for 50 years and is undergoing dieback, largely as a result of death of the canopy dominant species (Fagus sylvatica, beech). Statistical analyses showed strong non-linear losses in basal area for some plots, while others showed relatively gradual change. Beech seedling density was positively related to canopy openness, but a similar relationship was not observed for saplings, suggesting a feedback whereby mortality in areas with high canopy openness was elevated. We combined this observation with empirical data on size- and growth-mediated mortality of trees to produce an individual-based model of forest dynamics. We used this model to simulate changes in the structure of the forest over 100 years under scenarios with different juvenile and mature mortality probabilities, as well as a positive feedback between seedling and mature tree mortality. This model produced declines in forest basal area when critical juvenile and mature mortality probabilities were exceeded. Feedbacks in juvenile mortality caused a greater reduction in basal area relative to scenarios with no feedback. Non-linear, concave declines of basal area occurred only when mature tree mortality was 3-5 times higher than rates observed in the field. Our results indicate that the longevity of trees may help to buffer forests against environmental change and that the maintenance of old, large trees may aid the resilience of forest stands. In addition, our work suggests that dieback of forests may be avoidable providing pressures on mature and juvenile trees do not pass critical thresholds