Variation in pre-PCR processing of FFPE samples leads to discrepancies in BRAF and EGFR mutation detection: a diagnostic RING trial.

AIMS: Mutation detection accuracy has been described extensively; however, it is surprising that pre-PCR processing of formalin-fixed paraffin-embedded (FFPE) samples has not been systematically assessed in clinical context. We designed a RING trial to (i) investigate pre-PCR variability, (ii) correlate pre-PCR variation with EGFR/BRAF mutation testing accuracy and (iii) investigate causes for observed variation. METHODS: 13 molecular pathology laboratories were recruited. 104 blinded FFPE curls including engineered FFPE curls, cell-negative FFPE curls and control FFPE tissue samples were distributed to participants for pre-PCR processing and mutation detection. Follow-up analysis was performed to assess sample purity, DNA integrity and DNA quantitation. RESULTS: Rate of mutation detection failure was 11.9%. Of these failures, 80% were attributed to pre-PCR error. Significant differences in DNA yields across all samples were seen using analysis of variance (p

A new generation of companion diagnostics: cobas BRAF, KRAS and EGFR mutation detection tests

The cobas® (Roche) portfolio of companion diagnostics in oncology currently has three assays CE-marked for in vitro diagnostics. Two of these (EGFR and BRAF) are also US FDA-approved. These assays detect clinically relevant mutations that are correlated with response (BRAF, EGFR) or lack of response (KRAS) to targeted therapies such as selective mutant BRAF inhibitors in malignant melanoma, tyrosine kinases inhibitor in non-small cell lung cancer and anti-EGFR monoclonal antibodies in colorectal cancer, respectively. All these assays are run on a single platform using DNA extracted from a single 5 µm section of a formalin-fixed paraffin-embedded tissue block. The assays provide an ‘end-to-end’ solution from extraction of DNA to automated analysis and report on the cobas z 480. The cobas tests have shown robust and reproducible performance, with high sensitivity and specificity and low limit of detection, making them suitable as companion diagnostics for clinical use.

External quality assessment of BRAF molecular analysis in melanoma

The availability of BRAF inhibitors has given metastatic melanoma patients an effective new treatment choice and molecular testing to determine the presence or absence of a BRAF codon 600 mutation is pivotal in the clinical management of these patients. This molecular test must be performed accurately and appropriately to ensure that the patient receives the most suitable treatment in a timely manner. Laboratories have introduced such testing; however, some experience low sample throughput making it critical that an external quality assurance programme is available to help promote a high standard of testing, reporting and provide an educational aspect for BRAF molecular testing. Laboratories took part in three rounds of external quality assessment (EQA) during a 12-month period giving participants a measure of the accuracy of genotyping, clinical interpretation of the result and experience in testing a range of different samples. Formalin fixed paraffin embedded tissue sections from malignant melanoma patients were distributed to participants for BRAF molecular testing. The standard of testing was generally high but distribution of a mutation other than the most common, p.(Val600Glu), highlighted concerns with detection or reporting of the presence of rarer mutations. The main issues raised in the interpretation of the results were the importance of clear unambiguous interpretation of the result tailored to the patient and the understanding that the treatment is different from that given to other stratified medicine programmes. The variability in reporting and wide range of methodologies used indicate a continuing need for EQA in this field.

Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules

Background
It is generally acknowledged that a functional understanding of a biological system can only be obtained by an understanding of the collective of molecular interactions in form of biological networks. Protein networks are one particular network type of special importance, because proteins form the functional base units of every biological cell. On a mesoscopic level of protein networks, modules are of significant importance because these building blocks may be the next elementary functional level above individual proteins allowing to gain insight into fundamental organizational principles of biological cells.
Results
In this paper, we provide a comparative analysis of five popular and four novel module detection algorithms. We study these module prediction methods for simulated benchmark networks as well as 10 biological protein interaction networks (PINs). A particular focus of our analysis is placed on the biological meaning of the predicted modules by utilizing the Gene Ontology (GO) database as gold standard for the definition of biological processes. Furthermore, we investigate the robustness of the results by perturbing the PINs simulating in this way our incomplete knowledge of protein networks.
Conclusions
Overall, our study reveals that there is a large heterogeneity among the different module prediction algorithms if one zooms-in the biological level of biological processes in the form of GO terms and all methods are severely affected by a slight perturbation of the networks. However, we also find pathways that are enriched in multiple modules, which could provide important information about the hierarchical organization of the system