The Cancer Gene Census (CGC) catalogues genes with mutations causally implicated in cancer and explains how dysfunction of these genes drives cancer.
With COSMIC v99, new high-quality genes have been added to the CGC ─ three to Tier 1 and three to Tier 2. The genes are HGF, RAD50, RRAS2, GSK3B, MUC6 and RAP1B.
More, cancer hallmark annotations have been added to each of the 8 existing CGC Tier 1 genes (SRC, SRSF2, STAT3, STAT5B, STK11, SUFU, TBX3, TNFRSF14). Cancer hallmark annotations summarize the effect of Tier 1 genes on the phenotypic traits shared by cancers.
The CGC has been compiled over 19 years and is periodically reviewed. This ensures that gene assignment to the Census reflects the latest evidence indicative of the strength of a causal association between a gene and one, or more, cancer types, and consistency in the application of the COSMIC inclusion criteria for CGC Tier 1 and Tier 2 assignment. Based on this, and following a recent review, TSHR has been re-assigned from Tier 1 of the Census to Tier 2, and its previous designation as an oncogene rescinded.
→ Want more details? Read the full COSMIC v99 release notes here.
v99 is the second release available through COSMIC's new, improved download files. These new files contain the same gold standard COSMIC data found in its current files, but presented in a more accessible and interoperable manner.
The COSMIC team wants to lead by example in encouraging data to be FAIR (Findable, Accessible, Interoperable and Reusable) compliant, and as part of this goal, they will be phasing out their current files for COSMIC v100 in May 2024. This means that the current download files will be retired and only the new style files will be available to download.
→ Learn more about COSMIC's new files and transition support here.
In cancer research, the focus has shifted to precision medicine and much progress has been made developing therapies that have improved and prolonged the lives of patients with advanced cancer. While we have made great strides, there is still an infinite amount of information to learn. In this article, experts shed light on 3 trends in cancer research that will have major implications this year and beyond.
In 2022, the annual report from the American Cancer Society (ACS) estimates that 1,918,030 Americans will be diagnosed with cancer, equivalent to 5,250 new cases being detected every day. This is up from approximately 1.8 million new cases that likely occurred in 2021.
Both figures—for cases and deaths—are the highest estimates made by the ACS since 2007.
Health experts suggest that people missing cancer screenings and doctor's appointments due to the COVID-19 pandemic may cause cancer rates to rise in the coming years. In fact, 44% of countries around the world reported an increase in service backlogs for cancer screening in the second half 2021.
What does this mean for cancer researchers? First and foremost, there will be more patients undergoing genetic testing for cancer risk and diagnosis this year than ever before. To keep up with demand, labs analyzing and interpreting these tests will need to develop new workflows to efficiently handle a higher-throughput of samples.
Second, as more patients undergo genetic testing, the number of detected variants will continue to grow, challenging researchers to confidently identify meaningful mutations that could influence or improve decisions in experimental design, at point-of-care, or in drug development.
In a recent paper published in Trends in Genetics, researchers at the University of Liverpool found that of the 17,371 human genes studied and documented in PubMed, approximately 90% have some connection to cancer.
The results may indicate a trend that is complicating science’s ability to tease out which genes are underpinning true drivers of cancer and which are just passengers. For researchers, the main challenge is that if you’re trying to interpret results or identify new drug targets in the context of cancer, you may have too many genes associated with it.
If every gene can be associated with cancer, then figuring out which cancer-related genes are driving different types of cancer and identifying the best biomarkers becomes challenging. This trend underscores the need for high-quality somatic databases that can provide gene-level, alteration-level, and disease-level information including clinically observed gene and variant frequencies across diseases.
The combination of human expertise and artificial intelligence, Augmented Molecular Intelligence is an approach to variant curation that uses machines to rapidly index millions of articles and human curators to review and certify the accuracy, relevancy, and consistency of the information pulled.
The “gold standard” of variant curation, platforms, software and databases that offer AMI can gather all types of data (both structured and unstructured) from many sources, across disparate and siloed systems. Then a team of certified human curators examine the data to ensure there are no errors or inconsistencies in the data collected.
The result? Research and clinical labs that use platforms, software, and databases powered by AMI are better informed with deeper insight that can be trusted.
Across oncology applications, from research to molecular testing and pharmaceutical development, the ability to identify potentially actionable genetic alterations and exploit the molecular vulnerabilities of cancer is becoming increasingly difficult.
The Human Somatic Mutation Database (HSMD) is a new somatic database developed by QIAGEN that contains extensive genomic content relevant to solid tumors and hematological malignancies. The resource contains over 3.7 million curated alteration findings and focuses on providing deep insight into small variants, such as SNVs, indels, and frameshifts, that have been clinically observed or curated from scientific literature to help users better understand and define precise function and actionability.
Powered by Augmented Molecular Intelligence, HSMD contains content from two sources: expert-curated content from the QIAGEN Knowledge Base (QKB) and data from over 300,000 real-world clinical oncology cases sourced from our professional clinical interpretation services. Users can easily search and explore mutational characteristics across genes, synthesize key findings from drug labels, clinical trials, and professional guidelines, and receive detailed annotations for each observed variant.
Explore, search, and test HSMD for free. To demonstrate the quality, flexibility, and simplicity of HSMD, QIAGEN Digital Insights offers complimentary, 5-day trials of the new somatic database.
You will gain access to:
Learn more about HSMD and request your trial here.
