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Microarray technology fails in detecting point mutations present in a small fraction of cells from heterogeneous tissue samples or in plasma in a background of wild-type cell-free circulating tumor DNA (ctDNA). The aim of this study is to overcome the lack of sensitivity and specificity of current microarray approaches introducing a rapid and sensitive microarray-based assay for the multiplex detection of minority mutations of oncogenes (KRAS, NRAS and BRAF) with relevant diagnostics implications in tissue biopsies and plasma samples in metastatic colorectal cancer patients. In our approach, either wild-type or mutated PCR fragments are hybridized in solution, in a temperature gradient, with a set of reporters with a 5' domain, complementary to the target sequences and a 3' domain complementary to a surface immobilized probe. Upon specific hybridization in solution, which occurs specifically thanks to the temperature gradients, wild-type and mutated samples are captured at specific location on the surface by hybridization of the 3' reporter domain with its complementary immobilized probe sequence. The most common mutations in KRAS, NRAS and BRAF genes were detected in less than 90 minutes in tissue biopsies and plasma samples of metastatic colorectal cancer patients. Moreover, the method was able to reveal mutant alleles representing less than 0,3% of total DNA. We demonstrated detection limits superior to those provided by many current technologies in the detection of RAS and BRAF gene superfamily mutations, a level of sensitivity compatible with the analysis of cell free circulating tumor DNA in liquid biopsy.

It is widely accepted that assessing circular tumor DNA (ctDNA) in the plasma of cancer patients is a promising practice to evaluate somatic mutations from solid tumors noninvasively. Recently, it was reported that isolation of extracellular vesicles improves the detection of mutant DNA from plasma in metastatic patients; however, no consensus on the presence of dsDNA in exosomes has been reached yet. We analyzed small extracellular vesicle (sEV)-associated DNA of eleven metastatic colorectal cancer (mCRC) patients and compared the results obtained by microarray and droplet digital PCR (ddPCR) to those reported on the ctDNA fraction. We detected the same mutations found in tissue biopsies and ctDNA in all samples but, unexpectedly, in one sample, we found a KRAS mutation that was not identified either in ctDNA or tissue biopsy. Furthermore, to assess the exact location of sEV-associated DNA (outside or inside the vesicle), we treated with DNase I sEVs isolated with three different methodologies. We found that the DNA inside the vesicles is only a small fraction of that surrounding the vesicles. Its amount seems to correlate with the total amount of circulating tumor DNA. The results obtained in our experimental setting suggest that integrating ctDNA and sEV-associated DNA in mCRC patient management could provide a complete real-time assessment of the cancer mutation status.

It has now been established that in biological fluids such as blood, it is possible to detect cancer causing genomic alterations by analysing circulating tumour DNA (ctDNA). Information derived from ctDNA offers a unique opportunity to enrich our understanding of cancer biology, tumour evolution and therapeutic efficacy and resistance. Here, we propose a workflow to identify targeted mutations by a customized microarray-based assay for the simultaneous detection of single point mutations in different oncogenes (KRAS, NRAS and BRAF) followed by droplet digital PCR (ddPCR) to determine the fractional abundance of the mutated allele. Genetic variants were determined in the plasma of 20 metastatic colorectal cancer (mCRC) patients previously genotyped on tissue biopsy at the diagnosis for medication planning (T0) and following the tumour genetic evolution during treatment phase (T1 and T2) with the objective of allowing therapy response prediction and monitoring. Our preliminary results show that this combined approach is suitable for routine clinical practice. The microarray platform enables for a rapid, specific and sensitive detection of the most common mutations suitable for high-throughput analysis without costly instrumentation while, the ddPCR, consents an absolute quantification of the mutated allele in a longitudinal observational study on patients undergoing targeted therapy.

BackgroundUntil now, non-invasive prenatal diagnosis of genetic diseases found only limited routine applications. In autosomal recessive diseases, it can be used to determine the carrier status of the fetus through the detection of a paternally inherited disease allele in cases where maternal and paternal mutated alleles differ.MethodsConditions for non-invasive identification of fetal paternally inherited mutations in maternal plasma were developed by two independent approaches: coamplification at lower denaturation temperature-PCR (COLD-PCR) and highly sensitive microarrays. Assays were designed for identifying 14 mutations, 7 causing β-thalassaemia and 7 cystic fibrosis.ResultsIn total, 87 non-invasive prenatal diagnoses were performed by COLD-PCR in 75 couples at risk for β-thalassaemia and 12 for cystic fibrosis. First, to identify the more appropriate methodology for the analysis of minority mutated fetal alleles in maternal plasma, both fast and full COLD-PCR protocols were developed for the most common Italian β-thalassaemia Cd39 and IVSI.110 mutations. In 5 out of 31 samples, no enrichment was obtained with the fast protocol, while full COLD-PCR provided the correct fetal genotypes. Thus, full COLD-PCR protocols were developed for all the remaining mutations and all analyses confirmed the fetal genotypes obtained by invasive prenatal diagnosis. Microarray analysis was performed on 40 samples from 28 couples at risk for β-thalassaemia and 12 for cystic fibrosis. Results were in complete concordance with those obtained by both COLD-PCR and invasive procedures.ConclusionsCOLD-PCR and microarray approaches are not expensive, simple to handle, fast and can be easily set up in specialised clinical laboratories where prenatal diagnosis is routinely performed.

Background: Mutations in the retina-specific ABC transporter (ABCA4) gene have been associated with several forms of macular degenerations. Because the high complexity of the molecular genotype makes scanning of the ABCA4 gene cumbersome, we describe here the first use of denaturing HPLC (DHPLC) to screen for ABCA4 mutations. Methods: Temperature conditions were designed for all 50 exons based on effective separation of 83 samples carrying 86 sequence variations and 19 mutagenized controls. For validation, samples from 23 previously characterized Stargardt patients were subjected to DHPLC profiling. Subsequently, samples from a cohort of 30 patients affected by various forms of macular degeneration were subjected to DHPLC scanning under the same conditions. Results: DHPLC profiling not only identified all 132 sequence alterations previously detected by double-gradient denaturing gradient gel electrophoresis but also identified 5 sequence alterations that this approach had missed. Moreover, DHPLC scanning of an additional panel of 30 previously untested patients led to the identification of 26 different mutations and 29 polymorphisms, accounting for 203 sequence variations on 29 of the 30 patients screened. In total, the DHPLC approach allowed us to identify 16 mutations that had never been reported before. Conclusions: These results provide strong support for the use of DHPLC for molecular characterization of the ABCA4 gene.

Background Motor capacity is crucial in amyotrophic lateral sclerosis (ALS) clinical trial design and patient care. However, few studies have explored the potential of multimodal MRI to predict motor capacity in ALS. This study aims to evaluate the predictive value of cervical spinal cord MRI parameters for motor capacity in ALS compared to clinical prognostic factors. Methods Spinal multimodal MRI was performed shortly after diagnosis in 41 ALS patients and 12 healthy participants as part of a prospective multicenter cohort study, the PULSE study (NCT 2013-A00969-36). Motor capacity was assessed using ALSFRS-R scores. Multiple stepwise linear regression models were constructed to predict motor capacity at 3 and 6 months from diagnosis, based on clinical variables, structural MRI measurements, including spinal cord cross-sectional area (CSA), anterior–posterior, and left-to-right cross-section diameters at vertebral levels from C1 to T4, and diffusion parameters in the lateral corticospinal tracts (LCSTs) and dorsal columns. Results Structural MRI measurements were significantly correlated with the ALSFRS-R score and its sub-scores. And as early as 3 months from diagnosis, structural MRI measurements fit the best multiple linear regression model to predict the total ALSFRS-R ( R 2  = 0.70, p value = 0.0001) and arm sub-score ( R 2  = 0.69, p value = 0.0002), and combined with DTI metric in the LCST and clinical factors fit the best multiple linear regression model to predict leg sub-score ( R 2  = 0.73, p value = 0.0002). Conclusions Spinal multimodal MRI could be promising as a tool to enhance prognostic accuracy and serve as a motor function proxy in ALS.