TarPan: an easily adaptable targeted sequencing panel viewer for research and clinical use

Ashby, Cody; Rutherford, Michael; Bauer, Michael; Peterson, Erich A.; Wang, Yan; Boyle, Eileen M.; Wardell, Christopher P.; Walker, Brian A

doi:10.1186/s12859-020-3477-y

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…In brief, we performed targeted sequencing on 125 genes and chromosomal regions that had previously been shown to be relevant to the biology, prognosis, and treatment of MM. This included the tiling of the Ig regions and MYC to identify Ig translocations, the V, D, and J rearrangements 27,31,32 , and MYC abnormalities.…”

Section: Methodsmentioning

confidence: 99%

The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

et al. 2021

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Smoldering myeloma (SMM) is associated with a high-risk of progression to myeloma (MM). We report the results of a study of 82 patients with both targeted sequencing that included a capture of the immunoglobulin and MYC regions. By comparing these results to newly diagnosed myeloma (MM) we show fewer NRAS and FAM46C mutations together with fewer adverse translocations, del(1p), del(14q), del(16q), and del(17p) in SMM consistent with their role as drivers of the transition to MM. KRAS mutations are associated with a shorter time to progression (HR 3.5 (1.5–8.1), p = 0.001). In an analysis of change in clonal structure over time we studied 53 samples from nine patients at multiple time points. Branching evolutionary patterns, novel mutations, biallelic hits in crucial tumour suppressor genes, and segmental copy number changes are key mechanisms underlying the transition to MM, which can precede progression and be used to guide early intervention strategies.

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Section: Methodsmentioning

confidence: 99%

The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

et al. 2021

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“…An SQLite database was generated using somatic variants by Strelka2, structural variants by Manta, copy number depth metrics by CNVKit, and QC metrics by Picard. Data were visualized using a custom built "RShiny" application, TarPan (42) showing the mutations, translocations, copy number, QC metrics, and cross-sample contamination estimations. In TarPan, copy number can be manually normalized based on the ratio and SNP allele calls using the best fitting chromosomes with the least variance (usually chromosome 2 or 10).…”

Section: Translational Relevancementioning

confidence: 99%

Myeloma Genome Project Panel is a Comprehensive Targeted Genomics Panel for Molecular Profiling of Patients with Multiple Myeloma

Sudha

Ahsan

Ashby

et al. 2022

Clinical Cancer Research

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Purpose: We designed a comprehensive multiple myeloma (MM) targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. Experimental Design: The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNAs). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical fluorescence in situ hybridization (FISH) (translocations), multiplex ligation probe analysis (MLPA) (CNAs), whole genome sequencing (WGS) (CNAs, mutations, translocations) or droplet digital PCR (ddPCR) of known standards (mutations). Results: Canonical IgH translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for one patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2=0.969. VAFs for 74 mutations were compared between sequencing and ddPCR with concordance of R2=0.9849. Conclusions: In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost effective, comprehensive, clinically actionable and can be routinely deployed to assist risk stratification at diagnosis or post-treatment to guide sequencing of therapies.

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Data Visualization Support for Tumor Boards and Clinical Oncology: Scoping Review (Preprint)

Boehm,

Strantz,

Ustjanzew

et al. 2024

Preprint

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BACKGROUND Complex and expanding data sets in clinical oncology applications require flexible and interactive visualization of patient data to provide physicians and other medical professionals with a maximum amount of information. In particular, interdisciplinary tumor conferences profit from customized tools to integrate, link, and visualize relevant data from all professions involved. OBJECTIVE Our objective was to identify and present currently available data visualization tools for tumor boards and related areas. We not only want to provide an overview of the digital tools currently used in tumor board settings but also of the data they include, the respective visualization solutions, and their integration into hospital processes. METHODS The scoping review is based on the Arksey and O'Malley scoping study framework. The following electronic databases were searched for articles: PubMed, Web of Knowledge, and SCOPUS. Articles were deemed eligible if published in English in the last ten years. Eligible articles were first deduplicated, followed by the screening of titles and abstracts. Second, a full-text screening was conducted to decide on article selection. A scoping review protocol was set up and published to prepare for the study, which can be accessed via the IRRID. The manuscript was written following the checklist “Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews” (PRISMA-ScR). RESULTS The review process started with 2049 articles, of which 1014 were included in the title-abstract screening. (112/2049, 5%) Publications were eligible for full-text screening, leading to (60/2049, 3%) Publications eligible for final inclusion. They covered 49 distinct visualization tools and applications. We discovered a variety of innovative visualization solutions, often driven by the complexity of *omics data. However, many projects remain unused and are mostly abandoned once the publications have been written and published. CONCLUSIONS There is a wide range of projects providing visualization solutions for tumor boards and clinical oncology applications. Under the few tools that find their way into clinical routine settings, there are both commercial and academic solutions alike. While tables for a variety of data types remain the dominant visualization strategy, the complexity of omics data appears to be the driving force behind many visualization innovations in the area of tumor boards. INTERNATIONAL REGISTERED REPORT RR2-10.2196/53627

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TarPan: an easily adaptable targeted sequencing panel viewer for research and clinical use

Cited by 3 publications

References 20 publications

The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

Myeloma Genome Project Panel is a Comprehensive Targeted Genomics Panel for Molecular Profiling of Patients with Multiple Myeloma

Data Visualization Support for Tumor Boards and Clinical Oncology: Scoping Review (Preprint)

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