38 research outputs found
Somatic point mutation calling in low cellularity tumors
No full textSomatic mutation calling from next-generation sequencing data remains a challenge due to the difficulties of distinguishing true somatic events from artifacts arising from PCR, sequencing errors or mis-mapping. Tumor cellularity or purity, sub-clonality and copy number changes also confound the identification of true somatic events against a background of germline variants. We have developed a heuristic strategy and software (http://www.qcmg.org/bioinformatics/qsnp/) for somatic mutation calling in samples with low tumor content and we show the superior sensitivity and precision of our approach using a previously sequenced cell line, a series of tumor/normal admixtures, and 3,253 putative somatic SNVs verified on an orthogonal platform.Karin S. Kassahn, Oliver Holmes, Katia Nones, Ann-Marie Patch, David K. Miller, Angelika N. Christ, Ivon Harliwong, Timothy J. Bruxner, Qinying Xu, Matthew Anderson, Scott Wood, Conrad Leonard, Darrin Taylor, Felicity Newell, Sarah Song, Senel Idrisoglu, Craig Nourse, Ehsan Nourbakhsh, Suzanne Manning, Shivangi Wani, Anita Steptoe, Marina Pajic, Mark J. Cowley, Mark Pinese, David K. Chang, Anthony J. Gill, Amber L. Johns, Jianmin Wu, Peter J. Wilson, Lynn Fink, Andrew V. Biankin, Nicola Waddell, Sean M. Grimmond, John V. Pearso
Genomic analyses identify molecular subtypes of pancreatic cancer
No full textIntegrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.Peter Bailey, David K. Chang, Katia Nones, Amber L. Johns, Ann-Marie Patch, Marie-Claude Gingras, David K. Miller, Angelika N. Christ, Tim J. C. Bruxner, Michael C. Quinn, Craig Nourse, L. Charles Murtaugh, Ivon Harliwong, Senel Idrisoglu, Suzanne Manning, Ehsan Nourbakhsh, Shivangi Wani, Lynn Fink, Oliver Holmes, Venessa Chin, Matthew J. Anderson, Stephen Kazakoff, Conrad Leonard, Felicity Newell, Nick Waddell, Scott Wood, Qinying Xu, Peter J. Wilson, Nicole Cloonan, Karin S. Kassahn, Darrin Taylor, Kelly Quek, Alan Robertson, Lorena Pantano, Laura Mincarelli, Luis N. Sanchez, Lisa Evers, Jianmin Wu, Mark Pinese, Mark J. Cowley, Marc D. Jones, Emily K. Colvin, Adnan M. Nagrial, Emily S. Humphrey, Lorraine A. Chantrill, Amanda Mawson, Jeremy Humphris, Angela Chou, Marina Pajic, Christopher J. Scarlett, Andreia V. Pinho, Marc Giry-Laterriere, Ilse Rooman, Jaswinder S. Samra, James G. Kench, Jessica A. Lovell, Neil D. Merrett, Christopher W. Toon, Krishna Epari, Nam Q. Nguyen, Andrew Barbour, Nikolajs Zeps, Kim Moran-Jones, Nigel B. Jamieson, Janet S. Graham, Fraser Duthie, Karin Oien, Jane Hair, Robert Grützmann, Anirban Maitra, Christine A. Iacobuzio-Donahue, Christopher L. Wolfgang, Richard A. Morgan, Rita T. Lawlor, Vincenzo Corbo, Claudio Bassi, Borislav Rusev, Paola Capelli, Roberto Salvia, Giampaolo Tortora, Debabrata Mukhopadhyay, Gloria M. Petersen, Australian Pancreatic Cancer Genome Initiative, Donna M. Munzy, William E. Fisher, Saadia A. Karim, James R. Eshleman, Ralph H. Hruban, Christian Pilarsky, Jennifer P. Morton, Owen J. Sansom, Aldo Scarpa, Elizabeth A. Musgrove, Ulla-Maja Hagbo Bailey, Oliver Hofmann, Robert L. Sutherland, David A. Wheeler, Anthony J. Gill, Richard A. Gibbs, John V. Pearson, Nicola Waddell, Andrew V. Biankin, Sean M. Grimmon
Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders : Systematic Literature Review
No full textBackground: Normal voice production depends on the synchronized cooperation of multiple physiological systems, which makes the voice sensitive to changes. Any systematic, neurological, and aerodigestive distortion is prone to affect voice production through reduced cognitive, pulmonary, and muscular functionality. This sensitivity inspired using voice as a biomarker to examine disorders that affect the voice. Technological improvements and emerging machine learning (ML) technologies have enabled possibilities of extracting digital vocal features from the voice for automated diagnosis and monitoring systems. Objective: This study aims to summarize a comprehensive view of research on voice-affecting disorders that uses ML techniques for diagnosis and monitoring through voice samples where systematic conditions, nonlaryngeal aerodigestive disorders, and neurological disorders are specifically of interest. Methods: This systematic literature review (SLR) investigated the state of the art of voice-based diagnostic and monitoring systems with ML technologies, targeting voice-affecting disorders without direct relation to the voice box from the point of view of applied health technology. Through a comprehensive search string, studies published from 2012 to 2022 from the databases Scopus, PubMed, and Web of Science were scanned and collected for assessment. To minimize bias, retrieval of the relevant references in other studies in the field was ensured, and 2 authors assessed the collected studies. Low-quality studies were removed through a quality assessment and relevant data were extracted through summary tables for analysis. The articles were checked for similarities between author groups to prevent cumulative redundancy bias during the screening process, where only 1 article was included from the same author group. Results: In the analysis of the 145 included studies, support vector machines were the most utilized ML technique (51/145, 35.2%), with the most studied disease being Parkinson disease (PD; reported in 87/145, 60%, studies). After 2017, 16 additional voice-affecting disorders were examined, in contrast to the 3 investigated previously. Furthermore, an upsurge in the use of artificial neural network-based architectures was observed after 2017. Almost half of the included studies were published in last 2 years (2021 and 2022). A broad interest from many countries was observed. Notably, nearly one-half (n=75) of the studies relied on 10 distinct data sets, and 11/145 (7.6%) used demographic data as an input for ML models. Conclusions: This SLR revealed considerable interest across multiple countries in using ML techniques for diagnosing and monitoring voice-affecting disorders, with PD being the most studied disorder. However, the review identified several gaps, including limited and unbalanced data set usage in studies, and a focus on diagnostic test rather than disorder-specific monitoring. Despite the limitations of being constrained by only peer-reviewed publications written in English, the SLR provides valuable insights into the current state of research on ML-based voice-affecting disorder diagnosis and monitoring and highlighting areas to address in future research. © 2023 Journal of Medical Internet Research. All rights reserved
Parameters derived from compound muscle action potential scan for discriminating amyotrophic lateral sclerosis-related denervation
No full textWOS: 000479282600001PubMed ID: 31330055Artuğ, Tuğrul (Arel Author)Introduction The objective of this study was to determine compound muscle action potential (CMAP) scan parameters and MScanFit motor unit number estimation (MUNE) in patients with amyotrophic lateral sclerosis (ALS) and to compare the results in the abductor pollicis brevis (APB) to those in the abductor digiti minimi (ADM). Methods CMAP scans were recorded from the APB and ADM in 35 patients with ALS and 21 controls. MScanFit MUNE, neurophysiological index (NI), step%, returner%, and D50 were calculated. Results CMAP scan parameters including the returner%, MScanFit MUNE, and NI can distinguish ALS with high sensitivity and specificity. The electrophysiological parameters, with the exception of D50 (the number of largest consecutive differences of recorded responses generating 50% of maximum CMAP), showed more pronounced changes in the APB than in the ADM, even though most of the patients had normal APB/ADM amplitude ratios. Discussion CMAP scan parameters and MScanFit MUNE can be used in the evaluation of denervation and reinnervation and may herald the "split hand" in ALS
mRNA vaccine quality analysis using RNA sequencing
No full textAbstract The success of mRNA vaccines has been realised, in part, by advances in manufacturing that enabled billions of doses to be produced at sufficient quality and safety. However, mRNA vaccines must be rigorously analysed to measure their integrity and detect contaminants that reduce their effectiveness and induce side-effects. Currently, mRNA vaccines and therapies are analysed using a range of time-consuming and costly methods. Here we describe a streamlined method to analyse mRNA vaccines and therapies using long-read nanopore sequencing. Compared to other industry-standard techniques, VAX-seq can comprehensively measure key mRNA vaccine quality attributes, including sequence, length, integrity, and purity. We also show how direct RNA sequencing can analyse mRNA chemistry, including the detection of nucleoside modifications. To support this approach, we provide supporting software to automatically report on mRNA and plasmid template quality and integrity. Given these advantages, we anticipate that RNA sequencing methods, such as VAX-seq, will become central to the development and manufacture of mRNA drugs
Whole-genome landscape of pancreatic neuroendocrine tumours
No full textThe diagnosis of pancreatic neuroendocrine tumours (PanNETs) is increasing owing to more sensitive detection methods, and this increase is creating challenges for clinical management. We performed whole-genome sequencing of 102 primary PanNETs and defined the genomic events that characterize their pathogenesis. Here we describe the mutational signatures they harbour, including a deficiency in G:C > T:A base excision repair due to inactivation of MUTYH, which encodes a DNA glycosylase. Clinically sporadic PanNETs contain a larger-than-expected proportion of germline mutations, including previously unreported mutations in the DNA repair genes MUTYH, CHEK2 and BRCA2. Together with mutations in MEN1 and VHL, these mutations occur in 17% of patients. Somatic mutations, including point mutations and gene fusions, were commonly found in genes involved in four main pathways: chromatin remodelling, DNA damage repair, activation of mTOR signalling (including previously undescribed EWSR1 gene fusions), and telomere maintenance. In addition, our gene expression analyses identified a subgroup of tumours associated with hypoxia and HIF signalling
A workflow to increase verification rate of chromosomal structural rearrangements using high-throughput next-generation sequencing
No full textSomatic rearrangements, which are commonly found in human cancer genomes, contribute to the progres¬sion and maintenance of cancers. Conventionally, the verification of somatic rearrangements comprises many manual steps and Sanger sequencing. This is labor intensive when verifying a large number of rearrangements in a large cohort. To increase the verification throughput, we devised a high-throughput workflow that utilizes benchtop next-generation sequencing and in-house bioinformatics tools to link the laboratory processes. In the proposed workflow, primers are automatically designed. PCR and an optional gel electrophoresis step to confirm the somatic nature of the rearrangements are performed. PCR products of somatic events are pooled for Ion Torrent PGM and/or Illumina MiSeq sequencing, the resulting sequence reads are assembled into consensus contigs by a consensus assembler, and an automated BLAT is used to resolve the breakpoints to base level. We compared sequences and breakpoints of verified somatic rearrangements between the conventional and high-throughput workflow. The results showed that next-generation sequencing methods are comparable to conventional Sanger sequencing. The identified breakpoints obtained from next-gener-ation sequencing methods were highly accurate and reproducible. Furthermore, the proposed workflow al¬lows hundreds of events to be processed in a shorter time frame compared with the conventional workflow
Pancreatic cancer genomes reveal aberrations in axon guidance pathways genes
No full textPancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n5142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis
Whole–genome characterization of chemoresistant ovarian cancer
No full textPatients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1
Whole-genome landscape of pancreatic neuroendocrine tumours
No full textThe diagnosis of pancreatic neuroendocrine tumours (PanNETs) is increasing owing to more sensitive detection methods, and this increase is creating challenges for clinical management. We performed whole-genome sequencing of 102 primary PanNETs and defined the genomic events that characterize their pathogenesis. Here we describe the mutational signatures they harbour, including a deficiency in G:C > T:A base excision repair due to inactivation of MUTYH, which encodes a DNA glycosylase. Clinically sporadic PanNETs contain a larger-than-expected proportion of germline mutations, including previously unreported mutations in the DNA repair genes MUTYH, CHEK2 and BRCA2. Together with mutations in MEN1 and VHL, these mutations occur in 17% of patients. Somatic mutations, including point mutations and gene fusions, were commonly found in genes involved in four main pathways: chromatin remodelling, DNA damage repair, activation of mTOR signalling (including previously undescribed EWSR1 gene fusions), and telomere maintenance. In addition, our gene expression analyses identified a subgroup of tumours associated with hypoxia and HIF signalling
