{"id":9377,"date":"2016-11-15T18:50:46","date_gmt":"2016-11-15T18:50:46","guid":{"rendered":"http:\/\/admin.acceleratingscience.com\/behindthebench\/?p=9377"},"modified":"2020-05-28T19:18:07","modified_gmt":"2020-05-28T19:18:07","slug":"amp-2016-poster-wrap-up","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/behindthebench\/amp-2016-poster-wrap-up\/","title":{"rendered":"AMP 2016 Poster Wrap Up!"},"content":{"rendered":"

Now that we are all back from Charlotte, North Carolina, where the Association for Molecular Pathology (AMP) 2016 annual meeting<\/a> was held from Nov 10th – 12th this year.\u00a0In case you missed going to AMP this year or\u00a0missed\u00a0our posters don\u2019t worry we\u2019ve got you covered. Here is the wrap-up\u00a0of all the posters we presented at AMP 2016.<\/p>\n

\"poster-1\"<\/a>

Click to download poster<\/p><\/div>\n

Computational Methods for detection of somatic mutations at 0.1% frequency from cfDNA<\/b><\/h4>\n

Blood screening to track tumor recurrence and resistance may improve treatment selection and monitoring. Virtually all tumors carry somatic DNA mutations, serving as biomarker in blood. Circulating cell-free DNA (cfDNA) is one source of tumor DNA in blood. Tumor DNA comes from different tumor clones, and its abundance in plasma can be very low at critical stages such as early recurrence or development of resistance. This enables interest in detecting mutation biomarkers at very low frequency from cfDNA.<\/p>\n

The Oncomine\u00ae Liquid Biopsy Workflow with the Ion Torrent\u2122 platform<\/a> is a comprehensive 2 days sample-to-variant solution that facilitates researchers to study relevant biomarkers at 0.1% frequency in cfDNA\/FF\/FFPE DNA. Analysis is compatible with lower frequency variant detection, but will require higher input DNA amount and higher sequencing coverage.<\/p>\n

We present a research use only <\/i>analysis workflow for detection of low frequency DNA variants. Our variant calling method enables sensitive and specific detection of somatic mutations to 0.1% frequency.<\/p>\n

\"poster-2\"<\/a>

Click to download poster<\/p><\/div>\n

Comparison of Type and Time of Fixation on Tissue DNA Sequencing Results<\/b><\/h4>\n

Tissue fixatives in clinical practice are classified as denaturing fixatives, cross-linking fixatives, or a combination. Fixatives have different rates of penetration and fixation mechanisms, and combination with fixation time will lead to variability in the protein cross-linking or denaturation. This pre-analytical variability could lead to differences in analysis of morphology, IHC, and NGS. In order to understand tissue fixation effects on anatomical and molecular assays, five different fixatives were used to fix LCa tissues for 3 different time points.\u00a0The effects of type and duration of tissue fixation were studied using three different lung (LCa) cancer research samples. Each tissue sample was fixed in five different fixatives, for three different time points in each fixative. Next generation sequencing (NGS), tissue morphology analysis (H+E), and antigenicity (IHC) were performed for each of the resulting samples. The analysis indicates that both time and type of fixation impact NGS results.<\/p>\n

\"poster-3\"<\/a>

Click to download poster<\/p><\/div>\n

High Sensitivity Sanger Sequencing for Minor Variant Detection<\/h5>\n

Detecting minor genetic variants has become essential to cancer and infectious disease management. Many have turned to next generation sequencing to fill this need given the common perception that the limit of detection (LOD) for Sanger sequencing is somewhere between 15% to 25%. We have discovered a software algorithmic solution<\/a> to reduce this detection limit to 5% and have demonstrated detection at even lower allele frequencies. Standard Sanger sequencing protocols can be used and the method can generate the familiar electropherogram data display with noise substantially reduced. This opens up an alternative for detecting low level somatic variants.<\/p>\n

The key observation that enabled this development is that the noise underlying Sanger sequencing fluorescence data (traces) appears to be highly correlated to the primary sequence in the data.\u00a0A two-part algorithm has been developed to exploit this observation. The first part minimizes the noise that underlies the traces. The second part detects variants, if any, in the noise minimized traces. This communication describes the algorithmic details and shows test results.<\/p>\n

\"poster-4\"<\/a>

Click to download poster<\/p><\/div>\n

TT01: Speeding up sequencing: Sequencing in an hour enables sample to answer in a workday<\/b><\/h5>\n

At this time next generation sequencing (NGS)<\/a> is hindered by slow and often manual workflow procedures. Decreasing overall workflow times is critical for the widespread adoption of targeted and whole genome sequencing<\/a> (WGS) for many time-sensitive applications, in particular for infectious disease analysis. To this end, we describe improvements to the four main steps of the NGS workflow: i) library preparation; ii) template preparation, iii) sequencing; iv) and data analysis. Together, these advances dramatically decrease the overall turnaround times.\u00a0Ion Torrent\u2122 semiconductor-based sequencing instruments utilities flow sequencing with speed largely dependent on and the number of nucleotide flows (one flow produces ~0.5 base) and the speed of the flows.<\/p>\n

\"Click<\/a>

Click to download poster<\/p><\/div>\n

A Next Generation Sequencing Approach to Detect Large Rearrangements in BRCA1\/2 Simultaneous to Small Mutation Detection from FFPE Research Samples<\/h5>\n

Germline and somatic mutations in the BRCA1 and BRCA2 genes are highly involved in hereditary and non-hereditary breast and ovarian cancers. A test that detects these mutations from relevant FFPE samples is tremendously. Large rearrangements (LRs) represent a small, yet important portion of BRCA1\/2 mutations, in addition to single nucleotide mutations and small insertion\/deletions. The sizes of LRs make them difficult to detect using traditional sequencing approaches thereby requiring additional tests such as multiplex ligation dependent probe amplification (MLPA). Recently, several reports have shown feasibility using amplicon-based massively parallel sequencing methods to detect LRs simultaneous to small mutations. However, these tests were either not designed for use with FFPE samples, or lack data analysis methods optimized for such an application and therefore fail to achieve the necessary sensitivity.<\/p>\n

We have developed an amplicon-based NGS approach for FFPE samples that can detect SNVs, small mutations and LRs simultaneously. We have implemented a comprehensive bioinformatics algorithm that detects LRs at high sensitivity, even in the absence of control sample(s). This significantly reduces the cost and labor for BRCA1\/2 genetic analyses.<\/p>\n

\"Click<\/a>

Click to download poster<\/p><\/div>\n

Information Genetic Content (IGC): a comprehensive discovery platform for disease-gene research association<\/b><\/h5>\n

We developed Information Genetic Content (IGC), a comprehensive knowledgebase and discovery tool for human genes and genetic disorders research use. IGC comprises three components: the Disease-Association Database (DAD), the Gene Scoring Algorithm (GSA), and the Virtual Panel Library (VPL). The DAD module contains over 400,000 associations between over 17,000 genes and 15,000 Mendelian and complex diseases from both expert-curated and text-mined data. The DAD module also features a hierarchical organization of human diseases using a UMLS-controlled vocabulary, permitting queries at any level of the disease ontology hierarchy. The GSA module aims to prioritize genes for a specific disease of interest. This gene scoring algorithm is distinctive in the way it combines the strength of association and the number of associated diseases to provide an unbiased score for each gene. In conjunction with the DAD module, the GSA module is able to produce a list of ranked genes for one or more diseases at any level of the disease hierarchy. The VPL module generates optimal gene grouping by disease classification using hierarchical-clustering-based network analysis. Genes that are involved in the same pathological pathways are grouped into the same cluster.<\/p>\n

\"Click<\/a>

Click to download poster<\/p><\/div>\n

Ion Torrent<\/b>\u2122 <\/b><\/span>Next Generation Sequencing-Oncomine<\/b>\u2122 <\/b><\/span>Lung cfDNA assay detected 0.1% low frequency somatic variants in Cell-Free DNA<\/b><\/h5>\n

Study of genetic Information from cell-free (cf) DNA provide valuable opportunities in cancer research and potentially impact future oncology. As an example, liquid biopsy provide a non-invasive and cost effective solution for future compared to traditional biopsy tests. Here we report the application of research based Ion Torrent\u2122 <\/span>next-generation sequencing (NGS) Oncomine\u2122 <\/span>cfDNA assays<\/a> and associated workflow, which is developed to detect somatic variants at low frequency of 0.1% in cfDNA from plasma. We conclude that:<\/span><\/p>\n