Skin cancer is one of the most common forms of cancer, with nearly 3 million people globally affected each year.* Of every 3 diagnosed cancers, 1 is a skin cancer.** While basal cell carcinoma, squamous cell carcinoma, and melanoma are the most common types, there are several rare skin cancers that are often underrepresented in scientific literature.
The latest Catalogue of Somatic Mutations in Cancer (COSMIC) release, v98, focuses on rarer skin cancers like adnexal tumors, Merkel cell carcinoma, Kaposi sarcoma, dermatofibrosarcoma protuberans, and extramammary Paget's disease—providing deeper insight into the somatic mutations behind them and their clinical implications.
The inclusion of these rare skin tumors in COSMIC will allow clinicians to better understand the molecular mechanisms behind these cancers, which in turn aids in more accurate diagnosis and personalized treatment planning. Now, researchers and drug developers have more resources to help identify potential drug targets and develop new precision therapies for rare skin cancers.
In COSMIC v98, 776 new samples were curated from publications and 25,236 new variants were found in the rare skin tumors newly included. 17 new skin tumor types or subtypes were added to the histology classification system. Users can explore all of the variant data and sample metadata using the COSMIC Cancer Browser on the website. All the tumor types in COSMIC derive from samples that have been found to have somatic mutations in them.
The COSMIC v98 release marks a significant step forward in addressing the underrepresentation of rare skin cancers in scientific literature and databases.
→ Learn more about COSMIC here. (more…)
We are pleased to announce the release of the latest version of the Human Somatic Mutation Database, a new somatic database developed by QIAGEN that contains extensive genomic content relevant to solid tumors and hematological malignancies. HSMD 2.1.1 enhances the database with the latest cutting-edge cancer content, including new clinical trials, new drugs, and new variants that have been clinically observed or curated from scientific literature to help users better understand and define precise function and actionability.
HSMD 2.1.1 release highlights
View the full list of new content updates here.
About HSMD
Combining over 2 decades of expert curation and data from real-world clinical oncology cases, HSMD is a new somatic database from QIAGEN that serves as a single, trusted data source for clinical labs to validate, assess, and better understand the clinical significance of detected variants.
HSMD aggregates manually curated content from the QIAGEN Knowledge Base, the industry’s largest collection of biological and clinical findings, with data from over 500,000 real-world clinical oncology cases that have been analyzed and interpreted by QIAGEN’s professional clinical interpretation service, to eliminate the need to manually collect information across knowledge bases and provide deep genomic insight into the molecular characterizations of your patient’s tumor.
Easy to search with new content added weekly, HSMD enables users to explore key genes or mutations with driving properties or clinical relevance, and lets users search for associated treatment options, off-label therapies, resistance markers, and regional and/or disease-specific clinical trials.
Learn more about HSMD here.
[NEW!] HSMD Software Developer Now Available: Integrate HSMD into your in-house analytical tool for increased efficiency. You’ll be able to link out to the full HSMD online content via endpoints (API keys). HSMD Software Developer access provides integration keys for +1.5 million cancer-associated variants.
QCI Interpret Translational's latest software update comes with several new features, including a new workflow for comprehensive cancer panels and greater variant coverage for labs using the GRCh38 reference genome
We are pleased to announce that the Summer 2022 Release of QCI Interpret Translational, QIAGEN’s web-based software application for the annotation, classification, and research of variants from next generation sequencing (NGS) data in genomic laboratories, is now available. Expanding on the software’s current capabilities, the QCI Interpret Translational Summer 2022 Release brings new workflows, variant content and functionality improvements.
QCI Interpret Translational is a web-based software application for the annotation, classification, and research of variants from next generation sequencing (NGS) data in genomic laboratories. Using augmented molecular intelligence and expertly curated content from the QIAGEN Knowledge Base, QCI Interpret Translational uses evidence-based approaches to automatically compute pathogenicity classifications (Pathogenic to Benign) and actionability classifications (Tier 1 to 4) for each alteration according to the 2015 professional guidelines from the American College of Medical Genetics and Association for Molecular Pathology (ACMG/AMP) [1] and the 2017 guideline from the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists (AMP/ASCO/CAP) [2], respectively.
Pathogenicity and actionability classifications in QCI Interpret Translational are accompanied by clear visibility into the criteria and evidence supporting the classifications. This workflow starts with a variant call format (VCF) file, so it is compatible with the output from any NGS platform. The final analysis is sample-specific and includes candidate causal variants, their deep annotations, interpretations, and references specified throughout the assessment process. The assessment process also has customized automation allowing for even more streamlined variant research workflows.
QCI Interpret Translational helps research labs:
Learn more about QCI Interpret Translational here.
QCI Interpret's latest software update comes with several new features, including a new workflow for comprehensive cancer panels and greater variant coverage for labs using the GRCh38 reference genome
We are pleased to announce that the Summer 2022 Release of QCI Interpret, QIAGEN’s decision support software platform for the annotation, classification, and reporting of actionable alterations from next-generation sequencing (NGS) data in clinical genomic laboratories, is now available. Expanding on the software’s current capabilities, the QCI Interpret Summer 2022 Release brings new workflows, variant content and functionality improvements.
QCI Interpret is a clinical decision support software platform for the annotation, classification, and reporting of actionable alterations from NGS data for oncology and hereditary disease applications. Using augmented molecular intelligence and expertly curated content from the QIAGEN Knowledge Base, QCI Interpret applies a rules-based approach to automatically compute pathogenicity classifications (Pathogenic to Benign) and actionability classifications (Tier 1 to 4) for each alteration according to professional guidelines from ACMG/AMP and AMP/ASCO/CAP, respectively.
Pathogenicity and actionability classifications in QCI Interpret are accompanied by clear visibility into the criteria and evidence supporting the classifications. This workflow starts with a variant call format (VCF) file, so it is compatible with the output from any NGS platform. The final report includes the alterations, interpretations, and references specified throughout the assessment process, which has customizable automation capabilities allowing for streamlined clinical decision support workflows.
Learn more about QCI Interpret for Oncology here.
Learn more about QCI Interpret for Hereditary Diseases here.
Next-generation sequencing (NGS) has transformed the field of oncology. Early successes in identifying and targeting oncogenic drivers of solid tumors have set the foundation for genomics guided precision medicine; but, for hematological malignancies, the path to precision medicine is a lot more complex.
Within the hematologic oncology space, there is a spectrum of biologically related, but clinically heterogeneous diseases. In part, the differences between patients are driven by the particular combination of genetic mutations each disease acquires during its evolution. To effectively treat and manage myeloid malignancies, hematologist oncologists need highly parallel, highly sensitive assays that (1) enable the simultaneous analysis of multiple genes and (2) are coupled with indication-specific bioinformatic pipelines that provide information on disease classification, prognostication, treatment selection, and monitoring.
In this application note, we discuss the importance of streamlined clinical NGS workflows within the hematologic-oncology space. Learn how to develop a robust, automated, and streamlined NGS analysis pipeline for the interpretation and reporting of genomic alterations associated with hematological malignancies.
Read and download the application note >
In order to provide the best software and product support for our customers, QIAGEN must periodically retire older versions of our software. This enables us to dedicate all our resources in delivering the latest features, enhancements and support to our current versions and latest solutions.
At this time, we would like to announce the pending end of life of QIAGEN Ingenuity Variant Analysis (IVA). On December 31, 2020, Adobe will end support of Flash Player, the web-based technology that powers IVA.
“Adobe is planning to end-of-life Flash. Specifically, we will stop updating and distributing the Flash Player at the end of 2020 and encourage content creators to migrate any existing Flash content to these new open formats.”
QIAGEN Digital Insights has evolved from the collection of world-class bioinformatics and scientific and clinical content properties, such as Ingenuity, CLC bio, Biobase, OmicSoft, and N-of-One. As such, there has been an effort to streamline the QIAGEN Digital Insights portfolio.
We have taken the opportunity to deprecate the Flash version of IVA while merging its functionality into QIAGEN Clinical Insights (QCI). This way we can streamline the QIAGEN Digital Insights portfolio while preserving the IVA workflows in an HTML5 compliant platform.
During the 2020 transition period, IVA users will have full access to the classic, Flash-based IVA platform. By mid-2020, an updated version of QCI will contain elements supporting many of the existing IVA workflows. Once this version of QCI becomes available, all IVA users will automatically have access to QCI as part of their IVA subscription within 2020. With access to both IVA and QCI, users will be able to learn how to perform IVA workflows within QCI and provide feedback to the development team.
After December 31, 2020, all IVA users must use the QCI platform, as the classic IVA Flash platform will be terminated after that date.
If you have any questions, please contact us at bioinformaticssales@qiagen.com.
The Spring 2020 Release of the Human Gene Mutation Database (HGMD) Professional is available, expanding the world’s largest collection of human inherited disease mutations to 282,895 entries–that’s 7,179 more than the previous release.
For over 30 years, HGMD Professional has been used worldwide by researchers, clinicians, diagnostic laboratories and genetic counselors as an essential tool for the annotation of next-generation sequencing (NGS) data in routine clinical and translational research. Founded and maintained by the Institute of Medical Genetics at Cardiff University, HGMD Professional provides users with a unique resource containing expert-curated mutations all backed by peer-reviewed publications where there is evidence of clinical impact.
Whether searching for an overview of known mutations associated with a particular disease, interpreting clinical test results, looking for the likely causal mutation in a list of variants, or seeking to integrate mutation content into your custom NGS pipeline or data repository—HGMD is the defacto-standard repository for heritable mutations that can be adapted to a broad range of applications.
detailed mutation reports
new mutation entries in 2019 alone
summary reports listing all known
inherited disease mutations
HGMD is powered by a team of expert curators at Cardiff University. Data are collected weekly by a combination of manual and computerized search procedures. In excess of 250 journals are scanned for articles describing germline mutations causing human genetic disease. The required data are extracted from the original articles and augmented with the necessary supporting data.
The number of disease-associated germline mutations published per year has more than doubled in the past decade (Figure 1). As rare and novel genetic mutations continue to be uncovered, having access to the latest scientific evidence is critical for timely interpretations of next-generation sequencing (NGS) data.
View the complete HGMD Professional statistics here.
Read more about the importance of having access to the most up-to-date and comprehensive database for human disease mutations in our white paper.
HGMD Professional helps clinical testing labs analyze and annotate next-generation sequencing (NGS) data with current and trusted information. Unlike other mutation databases, HGMD mutations are all backed by peer-reviewed publications where there is evidence of clinical impact.
To get the most out of your HGMD Professional subscription, visit our Resources webpage for case studies, technical notes, and video tutorials. Or hear from Peter Stenson, manager of HGMD, in an on-demand webinar on how HGMD has empowered a generation of geneticists for precision medicine here.
Or hear from Peter Stenson, manager of HGMD, in an on-demand webinar on how HGMD has empowered a generation of geneticists for precision medicine here.
An updated version of ANNOVAR is also available.
Learn more about how ANNOVAR can be used with HGMD for variant annotation. Watch a recorded webinar featuring ANNOVAR here.
The Genome Trax™ 2020.1 is now available. Updated tracks have been released with HGMD 2020.1 content for all HGMD-related tracks. Additional major updates include TRANSFAC® release 2020.1, and PROTEOME™ release 2020.1.
For labs looking to generate clinician-grade reports for germline or somatic NGS testing, QIAGEN Clinical Insight (QCI) Interpret reproducibly translates highly complex NGS data into standardized reports using current clinical evidence from the QIAGEN Knowledge Base, which consists of over 40 public and proprietary databases, including HGMD Professional.
Click here for a free demonstration of QCI Interpret.
Wednesday, March 25, hear from Dr. Anthony M Magliocco, CEO and Founder of Protean BioDiagnostics, as he discusses the application of whole exome sequencing for guiding clinical trial enrollment for patients with cancer.
The remarkable advances in precision medicine are unfortunately not currently available to all patients, especially those being treated in community cancer settings. This growing “gap” is now challenging the health system to provide cost-effective, scalable, innovative solutions for underserved patients. Protean BioDiagnostics was founded to close this gap and accelerate access to precision oncology for all patients, regardless of where they live. To this end, Protean has created an adaptable and innovative framework for rapidly deploying the latest companion diagnostics. Protean’s simplification of universal access to complex diagnostics is poised to change the practice of precision oncology in the community and truly “close the gap.”
In this webinar, you will learn more about
Date: Wednesday, March 25, 2020
Time: 11 am EDT
A host of new features help you scale your research, and allow you to ramp up your productivity by taking your multi-sample analyses to the next level:
Figure 1. The ‘Iterate’ and ‘Collect and Distribute’ control elements allow batching over sections of the workflow. In this example, fastq files from a two-level factorial RNA-seq experiment performed in triplicate can be analyzed in a single workflow. The reads are trimmed, quality controlled (QC’ed) and the RNA-seq analysis reads are mapped, sample by sample. Then the RNA-seq expression levels are compared among groups, and comparisons are collected to create heat maps, Venn diagrams and PCA plots. Finally, trimming, QC and RNA-seq analysis read mapping reports are combined across samples. The workflow was used to analyze data from De Maio et al. (2016), comparing the transcriptional profile (RNA-seq) of Dengue virus 2 and mock infected human cells at 24 and 36 hours post-infection. The samples (accessions) are described in a CLC metadata table according to infection status and time point prior to workflow execution.
Figure 2. With the ‘Combined Reports’ tool you can gain a quick overview of the main results in your analysis. In this case, the GC-content has been summarized from the QC reports of 12 RNA-seq samples from De Maio et al. (2016).
Figure 3. Minimum Spanning Tree produced by QIAGEN CLC Microbial Genomics Module.
QIAGEN CLC Genomics Workbench now supports even more QIAseq UMI-based library preparation kits and panels, via a series of new ready-to-use workflows accessible through the Biomedical Genomics Analysis plugin, including:
View all supported QIAseq panels here.
Don't miss our on-demand webinar where we review these latest features of the QIAGEN CLC Genomics Workbench 20, and discuss:
References:
De Maio F.A. et al. (2016). The Dengue virus NS5 protein intrudes in the cellular spliceosome and modulates splicing. PLoS
Pathog. 12(8):e1005841.
Neurofibromatosis (NF) is a genetic disorder that causes tumors to form on nerve tissue. These tumors can develop anywhere in the nervous system, including the brain, spinal cord and nerves. NF is usually diagnosed in childhood or early adulthood.
Every year, scientists and clinicians who focus on advancing basic, translational and clinical research in NF gather at the Children's Tumor Foundation's NF conference to foster important discussion and collaboration within the NF community. As a prelude to the NF conference, this year the 2nd NF Hackathon took place from September 13–15, and experts from QIAGEN participated, helping to broaden NF awareness and introduce new perspectives to NF research.
During the three-day event, participants explored and analyzed data from the NF Data Portal, the leading open source collection of genomic and clinical data dedicated to this genetic disorder. This year, the NF Hackathon focused on analyzing diverse datasets including genomic, drug screening, drug-target association, imaging and other data for all the three types of NF (NF1, NF2, Schwannomatosis).
Team QIAGEN was among the winners of the hackathon, with their submission ‘Inferring regulators and pathways involved in NF1 and NF2 tumors originating from Schwann cells using gene expression data’. They used several QIAGEN bioinformatics tools in their analyses, including OmicSoft Array Studio, Ingenuity Pathway Analysis and the QIAGEN Knowledge Base. The team concluded that NF1 and NF2 are clearly differentiated, and that their approach is able to discriminate between tumor types by identifying drivers and signaling cascades. The team also identified potential therapeutic targets, including SMARCA4. As a result of their findings, Team QIAGEN was selected to present their work at the Children's Tumor Foundation's NF conference, held recently from Sept. 21–24 in San Francisco.
Congratulations to all the winners!
