RESUMO
Deficiency in DNA MMR activity results in tumors with a hypermutator phenotype, termed microsatellite instability (MSI). Beyond its utility in Lynch syndrome screening algorithms, today MSI has gained importance as predictive biomarker for various anti-PD-1 therapies across many different tumor types. Over the past years, many computational methods have emerged to infer MSI using either DNA- or RNA-based approaches. Considering this together with the fact that MSI-high tumors frequently exhibit a hypermethylated phenotype, herein we developed and validated MSIMEP, a computational tool for predicting MSI status from microarray DNA methylation tumor profiles of colorectal cancer samples. We demonstrated that MSIMEP optimized and reduced models have high performance in predicting MSI in different colorectal cancer cohorts. Moreover, we tested its consistency in other tumor types with high prevalence of MSI such as gastric and endometrial cancers. Finally, we demonstrated better performance of both MSIMEP models vis-à-vis a MLH1 promoter methylation-based one in colorectal cancer.
RESUMO
Germline and tumor BRCA testing constitutes a valuable tool for clinical decision-making in the management of epithelial ovarian cancer (EOC) patients. Tissue testing is able to identify both germline (g) and somatic (s) BRCA variants, but tissue preservation methods and the widespread implementation of NGS represent pre-analytical and analytical challenges that need to be managed. This study was carried out on a multicenter prospective GEICO cohort of EOC patients with known gBRCA status in order to determine the inter-laboratory reproducibility of tissue sBRCA testing. The study consisted of two independent experimental approaches, a bilateral comparison between two reference laboratories (RLs) testing 82 formalin-paraffin-embedded (FFPE) EOC samples each, and a Ring Test Trial (RTT) with five participating clinical laboratories (CLs) evaluating the performance of tissue BRCA testing in a total of nine samples. Importantly, labs employed their own locally adopted next-generation sequencing (NGS) analytical approach. BRCA mutation frequency in the RL sub-study cohort was 23.17%: 12 (63.1%) germline and 6 (31.6%) somatic. Concordance between the two RLs with respect to BRCA status was 84.2% (gBRCA 100%). The RTT study distributed a total of nine samples (three commercial synthetic human FFPE references, three FFPE, and three OC DNA) among five CLs. The median concordance detection rate among them was 64.7% (range: 35.3-70.6%). Analytical discrepancies were mainly due to the minimum variant allele frequency thresholds, bioinformatic pipeline filters, and downstream variant interpretation, some of them with consequences of clinical relevance. Our study demonstrates a wide range of concordance in the identification and interpretation of BRCA sequencing data, highlighting the relevance of establishing standard criteria for detecting, interpreting, and reporting BRCA variants.
RESUMO
Cancer stem cells play an important role in carcinogenesis and resistance to treatment and may lead to metastasis. The isolation of circulating stem cells involves cell sorting based on the presence of cell surface markers. Many surface markers such as CD133, c-Kit, SOX, OCT4 and TWIST have been reported. In the present study, we determined the expression of different stem cell markers and their variation in expression at different stages of the treatment process. Samples of EDTA blood were collected from metastatic colorectal cancer patients, and circulating cancer stem cells were isolated for the analysis of the expression of stem cell markers using RT-PCR. These findings were correlated with the response to therapy. All statistical analyses were performed using the GraphPad Prism 5.03 software. Significant differences were found in the expression levels of the markers CD133, SOX2, OCT4 and TWIST1. No differences were found in c-Kit expression. Correlation in the expression levels of most of the markers was observed. Expression of CD133, OCT4, SOX2 and TWIST1 had a predictive value for colon cancer behavior. Evaluation of this stem cell gene expression panel may be useful for predicting the response during the process of treatment, and the relative easy access to samples facilitates this method. Moreover the correlation between CD133 and TWIST1 expression may be associated with tumor regrowth and metastatic relapse.