CALR mutations screening in wild type JAK2(V617F) and MPL(W515K/L) Brazilian myeloproliferative neoplasm patients.

Some myeloproliferative neoplasm (MPN) patients harbor JAK2(V617F) mutation, and CALR mutations were recently discovered in wild type (WT) JAK2(V617F). We evaluated the frequency and type of CALR mutations, and clinical and hematological characteristics in WT JAK2(V617F) and MPL(W515K/L) MPN patients. Sixty-five patients were included: 21 with primary myelofibrosis (PMF), 21 with myelofibrosis post-essential thrombocythemia (MPET) and 23 with essential thrombocythemia (ET). Screening for JAK2(V617F) and MPL(W515K/L) were performed using real-time PCR, while CALR mutations were analyzed by fragment analysis and Sanger sequencing. JAK2(V617F) was the most frequent mutation (54.5%) and one patient (1.5%) harbored MPL(W515L). CALR mutations were present in 38.1% of PMF, 12.5% of ET and 33.3% of MPET patients. Five types of CALR mutations were detected, among which type 1 (32.1%) and type 2 (21.4%) were found to be the most common. A novel CALR mutation in a PMF patient was found. Patients carrying CALR mutations had higher platelet count and less presence of splenomegaly than JAK2(V617F), while triple negatives had higher C-reactive protein levels than CALR mutant carriers. Screening for CALR mutations and its correlation with clinical features could be useful for the characterization of MPN patients and result in its incorporation into a new prognostic score.

An integrated tool for determining the primary origin site of metastatic tumours.

AIMS: Cancers of unknown primary sites account for 3%-5% of all malignant neoplasms. Current diagnostic workflows based on immunohistochemistry and imaging tests have low accuracy and are highly subjective. We aim to develop and validate a gene-expression classifier to identify potential primary sites for metastatic cancers more accurately. METHODS: We built the largest Reference Database (RefDB) reported to date, composed of microarray data from 4429 known tumour samples obtained from 100 different sources and divided into 25 cancer superclasses formed by 58 cancer subclass. Based on specific profiles generated by 95 genes, we developed a gene-expression classifier which was first trained and tested by a cross-validation. Then, we performed a double-blinded retrospective validation study using a real-time PCR-based assay on a set of 105 metastatic formalin-fixed, paraffin-embedded (FFPE) samples. A histopathological review performed by two independent pathologists served as a reference diagnosis. RESULTS: The gene-expression classifier correctly identified, by a cross-validation, 86.6% of the expected cancer superclasses of 4429 samples from the RefDB, with a specificity of 99.43%. Next, the performance of the algorithm for classifying the validation set of metastatic FFPE samples was 83.81%, with 99.04% specificity. The overall reproducibility of our gene-expression-classifier system was 97.22% of precision, with a coefficient of variation for inter-assays and intra-assays and intra-lots <4.1%. CONCLUSION: We developed a complete integrated workflow for the classification of metastatic tumour samples which may help on tumour primary site definition.

Molecular Classification of Thyroid Nodules with Indeterminate Cytology: Development and Validation of a Highly Sensitive and Specific New miRNA-Based Classifier Test Using Fine-Needle Aspiration Smear Slides.

Background: Thyroid nodules can be identified in up to 68% of the population. Fine-needle aspiration (FNA) cytopathology classifies 20%-30% of nodules as indeterminate, and these are often referred for surgery due to the risk of malignancy. However, histological postsurgical reports indicate that up to 84% of cases are benign, highlighting a high rate of unnecessary surgeries. We sought to develop and validate a microRNA (miRNA)-based thyroid molecular classifier for precision endocrinology (mir-THYpe) with both high sensitivity and high specificity, to be performed on the FNA cytology smear slide with no additional FNA. Methods: The expression of 96 miRNA candidates from 39 benign/39 malignant thyroid samples, (indeterminate on FNA) was analyzed to develop and train the mir-THYpe algorithm. For validation, an independent set of 58 benign/37 malignant FNA smear slides (also classified as indeterminate) was used. Results: In the training set, with a 10-fold cross-validation using only 11 miRNAs, the mir-THYpe test reached 89.7% sensitivity, 92.3% specificity, 90.0% negative predictive value and 92.1% positive predictive value. In the FNA smear slide validation set, the mir-THYpe test reached 94.6% sensitivity, 81.0% specificity, 95.9% negative predictive value, and 76.1% positive predictive value. Bayes' theorem shows that the mir-THYpe test performs satisfactorily in a wide range of cancer prevalences. Conclusions: The presented data and comparison with other commercially available tests suggest that the mir-THYpe test can be considered for use in clinical practice to support a more informed clinical decision for patients with indeterminate thyroid nodules and potentially reduce the rates of unnecessary thyroid surgeries.