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The Importance of Epitope Density in Selecting a Sensitive Positive IHC Control.

ABSTRACT: Clinical Immunohistochemistry (IHC) laboratories face unique challenges in performing accurate and reproducible immunostains. Among these challenges is the use of homemade controls derived from pathological discard samples. Such positive controls have an unknown number of analyte molecules per cell (epitope density). It is unclear how the lack of defined analyte concentrations affects performance of the control. To address this question, we prepared positive IHC controls ( IHControls) for human epidermal growth factor receptor type II (HER-2), estrogen receptor (ER), or progesterone receptor (PR) with well-defined, homogeneous, and reproducible analyte concentrations. Using the IHControls, we examined the effect of analyte concentration on IHC control sensitivity. IHControls and conventional tissue controls were evaluated in a series of simulated primary antibody reagent degradation experiments. The data demonstrate that the ability of a positive IHC control to reveal reagent degradation depends on (1) the analyte concentration in the control and (2) where that concentration falls on the immunostain's analytic response curve. The most sensitive positive IHC controls have analyte concentrations within or close to the immunostain's concentration-dependent response range. Strongly staining positive controls having analyte concentrations on the analytic response curve plateau are less sensitive. These findings emphasize the importance of selecting positive IHC controls that are of intermediate (rather than strong) stain intensity.

SUBMITTER: Vani K

PROVIDER: S-EPMC5533270 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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The Importance of Epitope Density in Selecting a Sensitive Positive IHC Control.

Vani Kodela K Sompuram Seshi R SR Schaedle Anika K AK Balasubramanian Anuradha A Pilichowska Monika M Naber Stephen S Goldsmith Jeffrey D JD Chang Kueikwun G KG Noubary Farzad F Bogen Steven A SA

The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society 20170630 8

Clinical Immunohistochemistry (IHC) laboratories face unique challenges in performing accurate and reproducible immunostains. Among these challenges is the use of homemade controls derived from pathological discard samples. Such positive controls have an unknown number of analyte molecules per cell (epitope density). It is unclear how the lack of defined analyte concentrations affects performance of the control. To address this question, we prepared positive IHC controls ( IHControls) for human ...[more]

PMID: 28665229

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Project description:BackgroundThe key to understanding changes in gene expression levels using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) relies on the ability to rationalize the technique using internal control genes (ICGs). However, the use of ICGs has become increasingly problematic given that any genes, including housekeeping genes, thought to be stable across different tissue types, ages and treatment protocols, can be regulated at transcriptomic level. Our interest in prenatal glucocorticoid (GC) effects on fetal growth has resulted in our investigation of suitable ICGs relevant in this model. The usefulness of RNA18S, ACTB, HPRT1, RPLP0, PPIA and TUBB as ICGs was analyzed according to effects of early dexamethasone (DEX) treatment, gender, and gestational age by two approaches: (1) the classical approach where raw (i.e., not normalized) RT-qPCR data of tested ICGs were statistically analyzed and the best ICG selected based on absence of any significant effect; (2) used of published algorithms. For the latter the geNorm Visual Basic application was mainly used, but data were also analyzed by Normfinder and Bestkeeper. In order to account for confounding effects on the geNorm analysis due to co-regulation among ICGs tested, network analysis was performed using Ingenuity Pathway Analysis software. The expression of RNA18S, the most abundant transcript, and correlation of ICGs with RNA18S, total RNA, and liver-specific genes were also performed to assess potential dilution effect of raw RT-qPCR data. The effect of the two approaches used to select the best ICG(s) was compared by normalization of NR3C1 (glucocorticoid receptor) mRNA expression, as an example for a target gene.ResultsRaw RT-qPCR data of all the tested ICGs was significantly reduced across gestation. TUBB was the only ICG that was affected by DEX treatment. Using approach (1) all tested ICGs would have been rejected because they would initially appear as not reliable for normalization. However, geNorm analysis (approach 2) of the ICGs indicated that the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can be considered a reliable approach for normalization of target genes in both control and DEX treated groups. Different subset of ICGs were tested for normalization of NR3C1 expression and, despite the overall pattern of the mean was not extremely different, the statistical analysis uncovered a significant influence of the use of different normalization approaches on the expression of the target gene. We observed a decrease of total RNA through gestation, a lower decrease in raw RT-qPCR data of the two rRNA measured compared to ICGs, and a positive correlation between raw RT-qPCR data of ICGs and total RNA. Based on the same amount of total RNA to performed RT-qPCR analysis, those data indicated that other mRNA might have had a large increase in expression and, as consequence, had artificially diluted the stably expressed genes, such as ICGs. This point was demonstrated by a significant negative correlation of raw RT-qPCR data between ICGs and liver-specific genes.ConclusionThe study confirmed the necessity of assessing multiple ICGs using algorithms in order to obtain a reliable normalization of RT-qPCR data. Our data indicated that the use of the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can provide a reliable normalization for the proposed study. Furthermore, the dilution effect observed support the unreliability of the classical approach to test ICGs. Finally, the observed change in the composition of RNA species through time reveals the limitation of the use of ICGs to normalize RT-qPCR data, especially if absolute quantification is required.

Project description:IntroductionExtracurricular research programmes (ERPs) may contribute to reducing the current shortage in physician-scientists, but usually select students based on grades only. The question arises if students should be selected based on their motivation, regardless of their previous academic performance. Focusing on grades and lacking to take motivation into account when selecting students for ERPs might exclude an important target group when aiming to cultivate future physician-scientists. Therefore, this study compared ERP students with lower and higher previous academic performance on subsequent academic performance, ERP performance, and motivational factors.MethodsProspective cohort study with undergraduate medical students who filled in a yearly questionnaire on motivational factors. Two student groups participating in an ERP were compared: students with first-year grade point average (GPA) ≥7 versus <7 on a 10-point grading scale. Linear and logistic regressions analyses were used to compare groups on subsequent academic performance (i.e. third-year GPA, in-time bachelor completion), ERP performance (i.e. drop-out, number of credits), and motivational factors (i.e. intrinsic motivation for research, research self-efficacy beliefs, perceptions of research, curiosity), while adjusting for gender and motivational factors at baseline.ResultsThe <7 group had significantly lower third-year GPA, and significantly higher odds for ERP drop-out than the ≥7 group. However, there was no significant between-group difference on in-time bachelor completion and the <7 group was not inferior to the ≥7 group in terms of intrinsic motivation for research, perceptions of research, and curiosity.ConclusionsSince intrinsic motivation for research, perceptions of research, and curiosity are prerequisites of future research involvement, it seems beneficial to focus on motivation when selecting students for ERPS, allowing students with lower current academic performance to participate in ERPs as well.

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The Importance of Epitope Density in Selecting a Sensitive Positive IHC Control.

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The Importance of Epitope Density in Selecting a Sensitive Positive IHC Control.

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