Straightforward and sensitive RT-qPCR based gene expression analysis of FFPE samples

Fragmented RNA from formalin-fixed paraffin-embedded (FFPE) tissue is a known obstacle to gene expression analysis. In this study, the impact of RNA integrity, gene-specific reverse transcription and targeted cDNA preamplification was quantified in terms of reverse transcription polymerase chain reaction (RT-qPCR) sensitivity by measuring 48 protein coding genes on eight duplicate cultured cancer cell pellet FFPE samples and twenty cancer tissue FFPE samples. More intact RNA modestly increased gene detection sensitivity by 1.6 fold (earlier detection by 0.7 PCR cycles, 95% CI = 0.593-0.850). Application of gene-specific priming instead of whole transcriptome priming during reverse transcription further improved RT-qPCR sensitivity by a considerable 4.0 fold increase (earlier detection by 2.0 PCR cycles, 95% CI = 1.73-2.32). Targeted cDNA preamplification resulted in the strongest increase of RT-qPCR sensitivity and enabled earlier detection by an average of 172.4 fold (7.43 PCR cycles, 95% CI = 6.83-7.05). We conclude that gene-specific reverse transcription and targeted cDNA preamplification are adequate methods for accurate and sensitive RT-qPCR based gene expression analysis of FFPE material. The presented methods do not involve expensive or complex procedures and can be easily implemented in any routine RT-qPCR practice

A strategy to build and validate a prognostic biomarker model based on RT-qPCR gene expression and clinical covariates

Background: Construction and validation of a prognostic model for survival data in the clinical domain is still an active field of research. Nevertheless there is no consensus on how to develop routine prognostic tests based on a combination of RT-qPCR biomarkers and clinical or demographic variables. In particular, the estimation of the model performance requires to properly account for the RT-qPCR experimental design. Results: We present a strategy to build, select, and validate a prognostic model for survival data based on a combination of RT-qPCR biomarkers and clinical or demographic data and we provide an illustration on a real clinical dataset. First, we compare two cross-validation schemes: a classical outcome-stratified cross-validation scheme and an alternative one that accounts for the RT-qPCR plate design, especially when samples are processed by batches. The latter is intended to limit the performance discrepancies, also called the validation surprise, between the training and the test sets. Second, strategies for model building (covariate selection, functional relationship modeling, and statistical model) as well as performance indicators estimation are presented. Since in practice several prognostic models can exhibit similar performances, complementary criteria for model selection are discussed: the stability of the selected variables, the model optimism, and the impact of the omitted variables on the model performance. Conclusion: On the training dataset, appropriate resampling methods are expected to prevent from any upward biases due to unaccounted technical and biological variability that may arise from the experimental and intrinsic design of the RT-qPCR assay. Moreover, the stability of the selected variables, the model optimism, and the impact of the omitted variables on the model performances are pivotal indicators to select the optimal model to be validated on the test dataset

Aplicabilidad de la RT-PCR a tiempo real a partir de tejido fijado en formol e incluido en parafina a la búsqueda de perfiles de expresión génica con valor pronóstico en cáncer de endometrio

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Anatomía Patológica. Fecha de lectura: 12-09-2017El cáncer de endometrio es el tumor maligno del tracto genital más frecuente en países desarrollados, y el segundo en mortalidad. En la mayoría de los casos se diagnostica en estadios iniciales y debuta como una neoplasia bien diferenciada, con una alta tasa de curación quirúrgica. Sin embargo, en aproximadamente el 20 % de los casos, se trata de un tumor de alto grado de comportamiento agresivo, que se presenta es estadios avanzados, con mayor tasa de recaída en el curso de la enfermedad. El avance de las técnicas empleadas en la caracterización molecular en este tipo de neoplasias ha permitido una mayor comprensión del papel que juegan las distintas anomalías genéticas para poder aplicar estos conocimientos en la práctica clínica, con el objetivo de desarrollar un sistema de clasificación que integre las características histológicas y moleculares con un perfil pronóstico. El desarrollo de perfiles de expresión de genes relacionados con la transición epiteliomesénquima (TEM), la angiogénesis y el ciclo celular contribuiría a esclarecer el papel que desempeñan estos genes e identificar un conjunto de los mismos que permita diferenciar un grupo de pacientes que difieran en la tasa de supervivencia para realizar un adecuado manejo, así como identificar potenciales dianas terapéuticas. El presente estudio se ha realizado en 46 carcinomas de endometrio de tipo endometrioide mediante análisis de RT-qPCR con tarjetas microfluídicas. Se ha analizado el efecto de las variables clínico-patológicas sobre la supervivencia de las pacientes, así como la expresión de genes relacionados con la TEM, la angiogénesis y el ciclo celular. Nuestro análisis ha identificado el carácter pronóstico de los genes EGFR, PLK1 y PLK2, así como dos perfiles, uno para supervivencia libre de enfermedad (SLE), compuesto por 3 genes, y otro para supervivencia global (SG), compuesto por 10. Ambos modelos servirían para diferenciar a las pacientes de nuestra muestra en dos grupos de riesgo de manera significativa. No obstante, y debido al limitado tamaño muestral, los datos clínico-patológicos y genéticos incluidos para generar estos modelos predictivos podrían no ser representativos, por lo que sería imprescindible realizar una validación externa de los resultados mediante estudios prospectivos o validación in silico

Role of activation-induced cytidine deaminase (AID) in follicular lymphoma biology

Follicular lymphoma is the second most common non-Hodgkin’s lymphoma (NHL). The clinical course of disease is heterogeneous, typically with multiple relapses. Most patients live 10 years or more. However, another group of patients deteriorate rapidly and may progress to death within two years. Activation induced cytidine deaminase (AID) is an enzyme that plays an important role in somatic hypermutation (SHM) and class switch recombination (CSR) of immunoglobulin genes (IG). It induces mutations in IG and non-IG genes leading to genomic instability and chromosomal breaks that are important in the pathogenesis of B-cell malignancies. In this study, we wanted to first measure AID mRNA and protein levels and its biological function in follicular lymphoma (FL) and then correlate each of these variables with clinical features. Our cohort consisted of 87 patients recruited into the Purine-Alkylator Combination In Follicular lymphoma Immuno-Chemotherapy for Older patients (PACIFICO) trial which is comparing alternative frontline chemoimmunotherapy regimens in older patients with FL. The patient samples were in the form of formalin fixed, paraffin embedded (FFPE) biopsies, which are notorious for nucleic acid degradation. We first chose the best kits for extracting RNA and DNA from FFPE biopsies then optimized the procedure to obtain higher quantity of RNA and DNA from the minimum amount of tissue. We then degraded RNA from an AID positive cell line by heating and compared the degraded material with intact material obtained from the same cells to identify a cut-off point for RNA degradation to be applied in a quantitative polymerase chain reaction (qPCR) experiments. This was followed by a qPCR experiment to identify AID mRNA expression in 59 patients. AID protein was then quantified by Immunohistochemistry (IHC) in all samples. We also aimed to measure the functional readout of AID, first by exploring the nuclear/cytoplasmic (N/C) ratio of AID 2 (AID is stored in the cytoplasm and translocates to the nucleus to function), which was calculated for 20 patients using confocal microscopy. A second AID functional measurement was applied using cloning and PCR to detect ongoing mutation and AID-induced mutation in the immunoglobulin heavy variable gene (IGHV) in 18 cases. Finally, we correlated AID expression and functional readouts with available baseline and longitudinal clinical data obtained from the Clinical Trials Unit. In summary, a significant positive correlation was found between AID mRNA and protein expression (P= 0.001). We also found a significantly higher AID N/C ratio in the patient group with higher total AID mRNA and protein expression (P= 0.025 and 0.023 respectively). No correlation was identified between AID mRNA or protein levels and baseline or longitudinal clinical data. However, AID functionality measured as N/C ratio of AID and AID-related or ongoing IGHV mutation was positively correlated with disease status, treatment response and patient survival times. In conclusion, we found that functional readouts of AID are more strongly associated with adverse clinical features in FL compared to AID mRNA or protein expression