4 research outputs found
Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens
Background: MammaTyper is a novel CE-marked in vitro diagnostic RT-qPCR assay which assigns routinely processed breast cancer specimens into the molecular subtypes Luminal A-like, Luminal B-like (HER2 positive or negative), HER2 positive (non-luminal) and Triple negative (ductal) according to the mRNA expression of ERBB2, ESR1, PGR and MKI67 and the St Gallen consensus surrogate clinical definition. Until now and regarding formalin-fixed, paraffin-embedded material (FFPE), this has been a task mostly accomplished by immunohistochemistry (IHC). However the discrepancy rates of IHC for the four breast cancer biomarkers are frequently under debate, especially for Ki-67 which carries the highest degree of inter-and even intra-observer variability. Herein we describe a series of studies in FFPE specimens which aim to fully validate the analytical performance of the MammaTyper assay, including the site to site reproducibility of the individual marker measurements. Methods: Tumor RNA was extracted with the novel RNXtract RNA extraction kit. Synthetic RNA was used to assess the sensitivity of the RNXtract kit. DNA and RNA specific qPCR assays were used so as to determine analyte specificity of RNXtract. For the assessment of limit of blank, limit of detection, analytical measurement range and PCR efficiency of the MammaTyper kit serial dilutions of samples were used. Analytical precision studies of MammaTyper were built around two different real time PCR platforms and involved breast tumor samples belonging to different subtypes analyzed across multiple sites and under various stipulated conditions. The MammaTyper assay robustness was tested against RNA input variations, alternative extraction methods and tumor cell content. Results: Individual assays were linear up to at least 32.33 and 33.56 Cqs (quantification cycles) for the two qPCR platforms tested. PCR efficiency ranged from 99 to 109 %. In qPCR platform 1, estimates for assay specific inter-site standard deviations (SD) were between 0.14 and 0.20 Cqs accompanied by >94 % concordant single marker assignments for all four markers. In platform 2, the inter-site SD estimates were between 0.40 and 0.66 Cqs while the concordance for single marker assignments was >94 % for all four markers. The agreement reached between the two qPCR systems located in one site was 100 % for ERBB2, 96.9 % for ESR1, 97.2 % for PGR and 98.6 % for MKI67. RT-qPCR for individual markers was stable up to a 64-fold dilution for a typical clinical sample. There was no change in assay performance detected at the level of individual markers or subtypes after using different RNA isolation methods. The presence of up to 80 % of surrounding non-tumor tissue including in situ carcinoma did not affect the assay output. Sixteen out of 20 RNXtract eluates yielded more than 50 ng/mu l of RNA (average RNA output: 233 ng/mu l), whereas DNA contamination per sample was restricted to less than 15 ng/mu l. Median recovery rate of RNA extraction was 91.0 %. Conclusions: In this study the performance characteristics of MammaTyper were successfully validated. The various sources of analytical perturbations resulted in negligible variations in individual marker assessments. Therefore, MammaTyper may serve as a technical improvement to current standards for decentralized FFPE-based routine assessment of the commonly used breast cancer biomarkers and for molecular subtyping of breast cancer specimens
Comparison of PD-L1 mRNA Expression Measured with the CheckPoint Typer (R) Assay with PD-L1 Protein Expression Assessed with Immunohistochemistry in Non-small Cell Lung Cancer
Background: Immunohistochemical (IHC) assessment of programmed death-ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC) has become important since the development of anti-PD-1/-PD-L1 directed drugs. Various PD-L1 antibodies and cut-offs have been used in different trials to predict response to these drugs, thus comparison of those studies is difficult. We compared PD-L1 mRNA expression measured by RT-qPCR with PD-L1 protein expression evaluated by IHC. Moreover, we investigated the impact of different tumour tissue acquisition methods on the reliability of PD-L1 measurement techniques. Materials and Methods: NSCLC cases (N=22), including n=9 mediastinal lymph node biopsies acquired by endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and n=5 metastases, were evaluated prospectively for PD-L1 protein on tumor cells (TC) and immune cells (IC) using E1L3N and 28-8 antibodies and PD-L1 mRNA using the CheckPoint TYPER (R) assay. Results: In primary NSCLC tissues, agreement between PD-L1 mRNA and TC staining using the 28-8 antibody was excellent (kappa=0.85, p=0.0002). Comparing both PD-L1 antibodies against each other showed a kappa value of 0.58 (p=0.0106). In EBUS-TBNA, PD-L1 mRNA correlated perfectly with the 28-8 antibody (kappa=1.0, p=0.0023). PD-L1 mRNA levels significantly differed when comparing 28-8 TC staining of tumours >49% with 1-49% and 0% (p=0.0040; p=0.0081, respectively). In metastatic lesions, differences between PD-L1 mRNA and IHC became apparent (kappa=0.2, p=0.2525). Conclusion: Testing of PD-L1 mRNA and 28-8 IHC showed an excellent agreement in NSCLC samples including mediastinal lymph node biopsies. Since PD-L1 expression in >50% TC detected by 28-8 IHC can be reliably detected by RT-qPCR, quantitative PD-L1 mRNA determination should be considered as an alternative to IHC as there is no interobserver variability in RNA results
Additional file 2: of Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens
A: RNA and DNA concentrations in RNXtract eluates, B: Analyte specificity data, C: Graphical representation of variance components. (DOCX 125 kb