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Forensic Genetic Genealogy using microarrays for the identification of human remains: the need for good quality samples – a pilot study. Forensic Sci Int 2022; 334:111242. [DOI: 10.1016/j.forsciint.2022.111242] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/31/2022] [Accepted: 02/23/2022] [Indexed: 11/20/2022]
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2
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Kurnit KC, Dumbrava EEI, Litzenburger B, Khotskaya YB, Johnson AM, Yap TA, Rodon J, Zeng J, Shufean MA, Bailey AM, Sánchez NS, Holla V, Mendelsohn J, Shaw KM, Bernstam EV, Mills GB, Meric-Bernstam F. Precision Oncology Decision Support: Current Approaches and Strategies for the Future. Clin Cancer Res 2018; 24:2719-2731. [PMID: 29420224 PMCID: PMC6004235 DOI: 10.1158/1078-0432.ccr-17-2494] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 11/02/2017] [Accepted: 01/30/2018] [Indexed: 12/11/2022]
Abstract
With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719-31. ©2018 AACR.
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Affiliation(s)
- Katherine C Kurnit
- Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | - Beate Litzenburger
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
- Bioinformatics, Qiagen Inc., Redwood City, California
| | - Yekaterina B Khotskaya
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Amber M Johnson
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Timothy A Yap
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jordi Rodon
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jia Zeng
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Md Abu Shufean
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ann M Bailey
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Nora S Sánchez
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Vijaykumar Holla
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - John Mendelsohn
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
- Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kenna Mills Shaw
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Elmer V Bernstam
- School of Biomedical Informatics and Medical School, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Gordon B Mills
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
- Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Funda Meric-Bernstam
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
- Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
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3
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Tuzov N. A framework for the estimation of the proportion of true discoveries in single nucleotide variant detection studies for human data. PLoS One 2018; 13:e0196058. [PMID: 29694377 PMCID: PMC5918994 DOI: 10.1371/journal.pone.0196058] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 04/05/2018] [Indexed: 12/30/2022] Open
Abstract
Any single nucleotide variant detection study could benefit from a fast and cheap method of measuring the quality of variant call list. It is advantageous to be able to see how the call list quality is affected by different variant filtering thresholds and other adjustments to the study parameters. Here we look into a possibility of estimating the proportion of true positives in a single nucleotide variant call list for human data. Using whole-exome and whole-genome gold standard data sets for training, we focus on building a generic model that only relies on information available from any variant caller. We assess and compare the performance of different candidate models based on their practical accuracy. We find that the generic model delivers decent accuracy most of the time. Further, we conclude that its performance could be improved substantially by leveraging the variant quality metrics that are specific to each variant calling tool.
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Affiliation(s)
- Nik Tuzov
- Partek Incorporated, Saint Louis, Missouri, United States of America
- * E-mail:
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Boone M, De Koker A, Callewaert N. Capturing the 'ome': the expanding molecular toolbox for RNA and DNA library construction. Nucleic Acids Res 2018; 46:2701-2721. [PMID: 29514322 PMCID: PMC5888575 DOI: 10.1093/nar/gky167] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2017] [Revised: 02/05/2018] [Accepted: 02/23/2018] [Indexed: 12/14/2022] Open
Abstract
All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application.
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Affiliation(s)
- Morgane Boone
- Center for Medical Biotechnology, VIB, Zwijnaarde 9052, Belgium
- Department of Biochemistry and Microbiology, Ghent University, Ghent 9000, Belgium
| | - Andries De Koker
- Center for Medical Biotechnology, VIB, Zwijnaarde 9052, Belgium
- Department of Biochemistry and Microbiology, Ghent University, Ghent 9000, Belgium
| | - Nico Callewaert
- Center for Medical Biotechnology, VIB, Zwijnaarde 9052, Belgium
- Department of Biochemistry and Microbiology, Ghent University, Ghent 9000, Belgium
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Kjällquist U, Erlandsson R, Tobin NP, Alkodsi A, Ullah I, Stålhammar G, Karlsson E, Hatschek T, Hartman J, Linnarsson S, Bergh J. Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs). BMC Cancer 2018; 18:174. [PMID: 29433456 PMCID: PMC5810006 DOI: 10.1186/s12885-018-4021-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2016] [Accepted: 01/22/2018] [Indexed: 11/10/2022] Open
Abstract
Background Tumor heterogeneity in breast cancer tumors is today widely recognized. Most of the available knowledge in genetic variation however, relates to the primary tumor while metastatic lesions are much less studied. Many studies have revealed marked alterations of standard prognostic and predictive factors during tumor progression. Characterization of paired primary- and metastatic tissues should therefore be fundamental in order to understand mechanisms of tumor progression, clonal relationship to tumor evolution as well as the therapeutic aspects of systemic disease. Methods We performed full exome sequencing of primary breast cancers and their metastases in a cohort of ten patients and further confirmed our findings in an additional cohort of 20 patients with paired primary and metastatic tumors. Furthermore, we used gene expression from the metastatic lesions and a primary breast cancer data set to study the gene expression of the AKAP gene family. Results We report that somatic mutations in A-kinase anchoring proteins are enriched in metastatic lesions. The frequency of mutation in the AKAP gene family was 10% in the primary tumors and 40% in metastatic lesions. Several copy number variations, including deletions in regions containing AKAP genes were detected and showed consistent patterns in both investigated cohorts. In a second cohort containing 20 patients with paired primary and metastatic lesions, AKAP mutations showed an increasing variant allele frequency after multiple relapses. Furthermore, gene expression profiles from the metastatic lesions (n = 120) revealed differential expression patterns of AKAPs relative to the tumor PAM50 intrinsic subtype, which were most apparent in the basal-like subtype. This pattern was confirmed in primary tumors from TCGA (n = 522) and in a third independent cohort (n = 182). Conclusion Several studies from primary cancers have reported individual AKAP genes to be associated with cancer risk and metastatic relapses as well as direct involvement in cellular invasion and migration processes. Our findings reveal an enrichment of mutations in AKAP genes in metastatic breast cancers and suggest the involvement of AKAPs in the metastatic process. In addition, we report an AKAP gene expression pattern that consistently follows the tumor intrinsic subtype, further suggesting AKAP family members as relevant players in breast cancer biology. Electronic supplementary material The online version of this article (10.1186/s12885-018-4021-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Una Kjällquist
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden. .,Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
| | - Rikard Erlandsson
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas P Tobin
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden
| | - Amjad Alkodsi
- Research Programs Unit, Genome-Scale Biology and Medicum, University of Helsinki, Helsinki, Finland
| | - Ikram Ullah
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden
| | - Gustav Stålhammar
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden
| | - Eva Karlsson
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden
| | - Thomas Hatschek
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden
| | - Johan Hartman
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden
| | - Sten Linnarsson
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Jonas Bergh
- Department of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institute and University Hospital, Stockholm, Sweden
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Abstract
Long-term studies enable the identification of eco-evolutionary processes that occur over extended time periods. In addition, they provide key empirical data that may be used in predictive modelling to forecast evolutionary responses of natural ecosystems to future environmental changes. However, excluding a few exceptional cases, long-term studies are scarce because of logistic difficulties associated with accessing temporal samples. Temporal dynamics are frequently studied in the laboratory or in controlled mesocosm experiments with exceptional studies that reconstruct the evolution of natural populations in the wild. Here, a standard operating procedure (SOP) is provided to revive or resurrect dormant Daphnia magna, a widespread zooplankton keystone species in aquatic ecosystems, to dramatically advance the state-of-the-art longitudinal data collection in natural systems. The field of Resurrection Ecology was defined in 1999 by Kerfoot and co-workers, even though the first attempts at hatching diapausing zooplankton eggs date back to the late 1980s. Since Kerfoot's seminal paper, the methodology of resurrecting zooplankton species has been increasingly frequently applied, though propagated among laboratories only via direct knowledge transfer. Here, an SOP is described that provides a step-by-step protocol on the practice of resurrecting dormant Daphnia magna eggs. Two key studies are provided in which the fitness response of resurrected Daphnia magna populations to warming is measured, capitalizing on the ability to study historical and modern populations in the same settings. Finally, the application of next generation sequencing technologies to revived or still dormant stages is discussed. These technologies provide unprecedented power in dissecting the processes and mechanisms of evolution if applied to populations that have experienced changes in selection pressure over time.
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Affiliation(s)
| | - Luisa Orsini
- Environmental Genomics Group, School of Biosciences, University of Birmingham;
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Comparison of whole genome amplification techniques for human single cell exome sequencing. PLoS One 2017; 12:e0171566. [PMID: 28207771 PMCID: PMC5313163 DOI: 10.1371/journal.pone.0171566] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 01/21/2017] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Whole genome amplification (WGA) is currently a prerequisite for single cell whole genome or exome sequencing. Depending on the method used the rate of artifact formation, allelic dropout and sequence coverage over the genome may differ significantly. RESULTS The largest difference between the evaluated protocols was observed when analyzing the target coverage and read depth distribution. These differences also had impact on the downstream variant calling. Conclusively, the products from the AMPLI1 and MALBAC kits were shown to be most similar to the bulk samples and are therefore recommended for WGA of single cells. DISCUSSION In this study four commercial kits for WGA (AMPLI1, MALBAC, Repli-G and PicoPlex) were used to amplify human single cells. The WGA products were exome sequenced together with non-amplified bulk samples from the same source. The resulting data was evaluated in terms of genomic coverage, allelic dropout and SNP calling.
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Chevrier S, Arnould L, Ghiringhelli F, Coudert B, Fumoleau P, Boidot R. Next-generation sequencing analysis of lung and colon carcinomas reveals a variety of genetic alterations. Int J Oncol 2014; 45:1167-74. [PMID: 24990411 DOI: 10.3892/ijo.2014.2528] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2014] [Accepted: 06/04/2014] [Indexed: 11/05/2022] Open
Abstract
The development of targeted therapies in cancer has accelerated the development of molecular diagnosis. This new cancer discipline is booming, with an increasing number of gene alterations to analyze in a growing number of patients. To deal with this fast-developing activity, current analysis techniques (Sanger sequencing, allelic discrimination and high resolution melting) take more and more time. In recent years, next generation sequencing (NGS) technologies have appeared and given new perspectives in oncology. In this study, we analyzed FFPE lung and colon carcinomas using the Truseq Cancer Panel, which analyzes the mutation hotspots of 48 genes. We also tested the use of whole-genome amplification before NGS analysis. NGS results were compared with the data obtained from routine diagnosis. All of the alterations routinely observed were identified by NGS. Moreover, NGS revealed mutations in the KRAS and EGFR genes in patients diagnosed as wild-type by routine techniques. NGS also identified concomitant mutations in EGFR and KRAS or BRAF mutations, and a 15-nt deletion in exon 19 of EGFR in colon carcinomas. The study of the other genes sequenced in the Panel revealed 14 genes altered by 27 different mutations and three SNP with a possible role in cancer susceptibility or in the response to treatment. In conclusion, this study showed that NGS analysis could be used for the analysis of gDNA extracted from FFPE tissues. However, given the high sensitivity of this technology, high-throughput clinical trials are needed to confirm its reliability for the molecular diagnosis of cancer.
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Affiliation(s)
- Sandy Chevrier
- Department of Biology and Pathology of Tumors, Centre Georges-François Leclerc, 21079 Dijon, France
| | - Laurent Arnould
- Department of Biology and Pathology of Tumors, Centre Georges-François Leclerc, 21079 Dijon, France
| | - François Ghiringhelli
- Department of Medical Oncology, Centre Georges-François Leclerc, 21079 Dijon, France
| | - Bruno Coudert
- Department of Medical Oncology, Centre Georges-François Leclerc, 21079 Dijon, France
| | - Pierre Fumoleau
- Department of Medical Oncology, Centre Georges-François Leclerc, 21079 Dijon, France
| | - Romain Boidot
- Department of Biology and Pathology of Tumors, Centre Georges-François Leclerc, 21079 Dijon, France
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