While the world showed its support for affected people during Breast Cancer Awareness Month, COSMIC's expert curators were working hard behind the scenes to get information on rare breast cancers ready for the upcoming release later that month.
Breast cancer is still a big global problem
Breast cancer is the most prevalent cancer type worldwide. At the end of 2020, there were 7.8 million women alive who’d been diagnosed with breast cancer in the previous five years. And despite leaps and bounds in detection and treatment, there were still 685,000 deaths from breast cancer in 2020 alone.
Nevertheless, the numbers are still fairly optimistic. Breast cancer mortality in high-income countries has dropped 40% between the 1980s and 2020 - and it’s continuing to drop by around 2-4% in these countries each year. Innovations in treatment and targeted drug therapies, such as trastuzumab to treat HER-2 positive cancers, are showing outstanding results. And let’s be clear, early detection and effective treatment is really the only option. Unlike many common cancers, even if all the risk factors for breast cancer development were controlled, this would only reduce the risk by 30%. A multi-pronged approach is needed- optimize care pathways, facilitate early diagnosis, and provide the right treatment at the right time.
And for treatment-resistant breast cancers? We need to understand what’s driving these cancers at a genetic level and identify targets for the next generation of drugs.
Cue COSMIC as the navigational tool that hosts the data to springboard scientific innovation. COSMIC’s latest release v95 (November 2021) has a special focus on rare female cancers, including the rarer breast cancer subtype with notorious poor outcomes, metaplastic breast cancer (MpBC).
The lowdown on metaplastic breast cancer
Metaplastic breast cancer is a rare and aggressive malignancy. Although the incidence is low (it only accounts for 0.2–5% of all breast cancers), MpBC accounts for a significant proportion of breast-cancer deaths.
MpBCs are usually (but not always) triple-negative - meaning they lack expression of estrogen receptor (ER), progesterone receptor (PR), and HER2. So, some of the revolutions in current treatments are ineffective. Like other triple-negative breast cancers, they’re more likely to present with distant metastasis, but they generally have a worse prognosis than their grade-matched counterparts.
Compared to other cancers, relatively little is known about MpBC, but more studies are happening all the time. Speaking of, time to look at some of the new datasets being incorporated into V95 of COSMIC.
Classification: Phenotypic and molecular dissection of metaplastic breast cancer and the prognostic implications
When cancer is rare, it can be harder to create clear definitions, classifications, and guidance. This is especially true of MpBC, a cancer literally named for its heterogeneity in cell types. Metaplasia derives from Ancient Greek and means ‘change in form’. In this context, it’s the transformation of one differentiated cell type to another differentiated cell type. The World Health Organisation (WHO) guidelines currently rely on the structure, shape, and organization of the cells to create sub-categories - without any information on molecular causes or clinical guidance.
Caption: Table showing the various WHO classifications of metaplastic breast cancer [1]
But Lakhani et al. decided to look under the hood. Using strength in numbers, they formed the Asia-Pacific MpBC consortium to collect and study 347 MpBCs in depth.
What did the increased numbers provide? Let’s start with genetics. Exome sequencing was performed on 30 of the MpBC cases and found TP53, PTEN, and PIK3CA mutations co-occurring. This countered a long-held concept that TP53/PTEN and PI3CA/PTEN mutations were mutually exclusive.
Moving on to prognosis - the top question that patients have when diagnosed: ‘How bad is it’?’ This study shed a little light. The significant indicators of poor prognosis were large tumor size, loss of cytokeratin expression, EGFR overexpression, and the presence of more than three distinct morphological entities. On the flip side, favorable indicators included fewer morphological components and EGFR negativity.
With these findings, Lakhani et al. suggest minor changes to the WHO classification. The paper ends with the comment that, ‘thousands of samples would need to be reviewed centrally in order to tease out the subtleties required to make any bolder changes to the guidelines’. As more similar data is incorporated into COSMIC datasets, it will enable this scale of analysis.
New targets: Molecular Profiling of the Metaplastic Spindle Cell Carcinoma of the Breast Reveals Potentially Targetable Biomarkers
Having discussed the WHO guidelines more broadly, time to zone in on one of the even rarer subtypes of MbBC, WHO_5: Spindle Cell Carcinoma. This subtype displays the previously mentioned triple-negative characteristic, as well as having an association with resistance to conventional chemotherapy.
Evidently, new tactics are needed. Precision oncology and immuno-oncology could provide some strategies for targeted therapies, but first we need to know if the right mutations and immune markers are present. Gatalica et al. studied this with some promising results.
They used 23 MpBC spindle cell carcinomas and thoroughly analyzed them using immunohistochemistry and DNA/RNA sequencing. And some familiar faces emerge here - PIK3CA, TP53, HRAS, NF1, and PTEN pathogenic gene mutations were identified in the majority (21) of cases. As highlighted by the authors, PIK3CA mutations are particularly relevant because they’ve been classified as strong predictors of response to PIK3CA inhibitors, and several drugs have either been recently approved, or are in the pipeline, for targeting the PI3K pathway, including Piqray (alpelisib).
Finally, onto the immuno-oncology markers. PD1 is a molecular ‘gun’ found on the surface of immune cells - when they spot a threat they attach and fire. Unless the cell in question puts out a defence - PD-L1 - which puts the safety on and prevents firing. Tumors can use PD-L1 as a means of escaping destruction by the immune system, so new drugs have been developed to block PDL1 and PD1 from binding. But there’s an added layer of complexity, if another molecule - PTEN - is present, then it’s indicated that drugs designed to target PD-L1/PD1 will be less effective.
PDL1 and PD1 molecules interacting on surface of cells. PD1 is purple and PDL-1 is yellow.
Back to the research. The study found evidence of PD-L1 expression, but only above the threshold for treatments in two cases. And two cases also had concurrent PTEN expression. So, for biomarkers, there’s promise that targeted therapies could work in some cases, but a thorough analysis would need to be done on a case by case basis.
Power in numbers
It’s promising to see this volume of new studies and big data being gathered for the rarer cancers. And it’s evident that the route forward is in numbers, collaborations, and collating evidence from multiple sources. Seeing the mounting evidence for PIK3CA expression involvement in MpBC is just one example of this. But without a centralized database, curated from thousands of papers that have been read and analyzed by trusted experts (with a passion for their work) it would be easy to miss key cases.
Reach out to the QIAGEN team to get access to this exciting data. Test it out for yourself – the first 100 lines of COSMIC are made available for free download.
[1] McCart Reed AE, Kalaw E, Nones K, Bettington M, Lim M, Bennett J, Johnstone K, Kutasovic JR, Saunus JM, Kazakoff S, Xu Q, Wood S, Holmes O, Leonard C, Reid LE, Black D, Niland C, Ferguson K, Gresshoff I, Raghavendra A, Harvey K, Cooper C, Liu C, Kalinowski L, Reid AS, Davidson M, Pearson JV, Pathmanathan N, Tse G, Papadimos D, Pathmanathan R, Harris G, Yamaguchi R, Tan PH, Fox SB, O'Toole SA, Simpson PT, Waddell N, Lakhani SR. Phenotypic and molecular dissection of metaplastic breast cancer and the prognostic implications. J Pathol. 2019 Feb;247(2):214-227. doi: 10.1002/path.5184. Epub 2018 Dec 20. PMID: 30350370.
Read the full article here!
The contest was called to address a current industry challenge: standardizing variant interpretation and reporting. The increasing demand for next-generation sequencing (NGS)-based tests has led to a high degree of variability in how members of the global molecular genetics and pathology community classify variants and prepare final reports. To better understand the limitations of standardization and move forward in the same direction, Agilent Technologies, Thermo Fisher Scientific, and QIAGEN engaged in a friendly competition to determine which company had the most accurate and consistent NGS analysis and interpretation platform: the Alissa Interpret platform, Ion Torrent platform, and QIAGEN's Biomedical Genomics Workbench and QIAGEN Clinical Insight (QCI™) Interpret, respectively.
Erasmus University Medical Center (Erasmus MC) Rotterdam generated sequence data from five clinical samples using Thermo Fisher’s Ion Torrent platform. The three contestants were given this sequence data and instructed to identify clonal and subclonal mutations in the tumors down to an allele frequency level of at least five percent. Then, the contestants were asked to identify and annotate the variants, calculate allele frequency, and interpret the variants according to a five-tier classification system ranging from “benign” to “clinically significant.”
This was no easy task.
Initially, seven companies expressed interest in meeting the challenge. In the end, only three crossed the finish line. According to Professor Winand Dinjens, the organizer of this year’s competition, and head of molecular diagnostics in the Department of Pathology at Erasmus MC Rotterdam, most contenders dropped out after struggling to analyze the sequencing data, which was produced with the Ion S5 XL System, a version of the Ion Torrent platform. As the race unfolded, unfamiliarity with the provided sequencing data caused more than half of the competitors to exit the track.
So, was there a home advantage?
The sequencing data in question was produced by the Ion Torrent platform, which means the Thermo Fisher team analyzed the data using tools custom-built to work with this type of sequence data. For example, during the variant calling process, the Thermo Fisher team was able to apply “flow space” information for each base as it related to Ion Torrent chemistry.
Even so, QIAGEN didn’t back down.
While Thermo Fisher may have had greater familiarity with this particular “track,” QIAGEN’s bioinformatics solutions are open platforms and have experienced over 750,000 “races” on all types of “tracks” across the world. The QIAGEN Knowledge Base is the industry’s largest, most up-to-date clinical database with the direct experience of analyzing over 750,000 human samples. This cumulative experience, in addition to more than 16 million knowledge base findings across 23,000 genes, gives QCI Interpret greater scope and depth.
For each of the five cancer samples, Erasmus supplied FASTQ files plus aligned BAM files, from which the task was to perform variant calling and interpretation and to generate a list of clinically reportable findings. Tim Bonnert, QIAGEN’s Associate Director of Bioinformatics Field Application Scientists, EMEA first used QIAGEN’s Biomedical Genomics Workbench to process the FASTQ files and perform the variant calling. Then he assessed the variants with QCI Interpret, which has curated content that triggered built-in ACMG/AMP and AMP/ASCO/CAP guidelines.
When the results from all contenders were in, none were identical.
QIAGEN’s software solutions performed significantly better than the competition. The organizers stated that there were a total of 12 variants across the five samples. QIAGEN reported 11 of the 12 variants; the variant had been identified in a homopolymer region, and the QIAGEN team identified this variant as a potential false positive. However, this classification does not change the overall clinical actionability recommendation for the patient. By contrast, Agilent and Thermo Fisher missed multiple calls. In some cases, neither platform detected variants in a sample that did in fact have clinically actionable findings; for example, the Torrent Variant Caller pipeline generated no calls for three clinically meaningful variants.
Even though QIAGEN outperformed competitors and achieved almost 100% concordance, these kinds of “battles” illustrate the importance of having pre-defined and clear standards for bioinformatics workflows. Classification and reporting of variants to healthcare providers is critical for patient care. This process requires: accurate reporting of the tumor response to targeted therapy; establishment of professional guidelines for patient care; and collaborative institutional clinical trials, thereby supporting the need for standardization among laboratories performing these tests.
According to Bonnert, “While Erasmus MC no doubt had these standards nailed down in their routine testing pipelines, for this competition there was, for example, uncertainty about required depth of coverage, acceptable distance into the intron, and other confidence metrics and standards that we believe are essential to any routine clinical bioinformatics approach. The need for standards in routine testing also extends to employing clearly defined rules and assessment criteria supported by curated clinical evidence.”
Standards are important for ensuring consistency of secondary and tertiary analysis workflows and for generating actionable data. The faithful detection of variants from Ion Torrent data by the Biomedical Genomics Workbench and the standardized clinical decision support provided by QCI Interpret proved the winning combination.
We are honored to have participated in the Battle of the Bioinformatics Pipelines. Here at QIAGEN, we are committed to building the most reliable, robust and technologically-advanced bioinformatics tools that are sequencer-agnostic because we want to empower more labs, more clinicians, and more patients to do and know more. Just as our pipeline proved victorious with Ion Torrent data in this battle, our research and clinical solutions work successfully with QIAGEN’s own GeneReader platform, as well as with data from Illumina.
Get in touch with one of our experts today! CONTACT US
We are proud to share an article written by Ramon Felciano, Chief Technology Officer and Vice President, Strategy & Technology, QIAGEN Bioinformatics, that was featured in The Pathologist, a UK-based publication that considers the latest research and innovation in pathology and diagnostics. Titled “Deciding Factors,” the article shines a light on new trends in clinical labs that are improving the accuracy and efficiency of genetic test interpretation. It argues that these advances are made possible with clinical decision support (CDS) tools, which incorporate big data, sophisticated informatics, and augmented intelligence (as opposed to artificial intelligence), to better inform treatment decisions, manage liability risk, and ensure compliance with ever-changing data privacy regulations.
The adoption and implementation of CDS tools is no longer a luxury, but rather a necessity. Just a few years ago in the United States, only pre-eminent academic medical centers offered precision medicine. As stated in the article, “Today, an estimated 24 percent of hospitals will provide some form of precision medicine by the end of 2018.”(1) With the use of CDS tools and related technologies gaining traction, clinical teams need to ensure they select support tools that provide maximum interpretation transparency and detailed reporting. Dr. Felciano explains how CDS tools are personnel assets—not replacements—that enhance productivity, reliability and the practice of precision medicine.
(1)N. Versel, “Data requirements, money hold back growth of precision medicine among health systems” (2018). Available at: https://bit.ly/2qFSb60. Accessed April 18, 2018.
ASHG 2015 was everything we hoped it would be: interesting and inspiring scientific presentations and a place to reconnect with friends and customers. When we weren’t manning a busy booth, our team had a wonderful time soaking in the latest and greatest in human genetics.
Here is a recap of our scientific line up at the show:
Tuesday October 6, Dan Richards, PhD., VP of Biomedical Informatics, QIAGEN Bioinformatics, gave a presentation about “Genome-scale ACMG pathogenicity classification using comprehensive curated clinical evidence and data.”
Wednesday October 7, we hosted a workshop with two guest speakers: Yuval Itan from Rockefeller University and Ben Solomon from Inova.
Yuval Itan talked about “NGS Diagnostic Odyssey - From Bench to Beside: Join fellow investigators in an educational overview of how bioinformatic solutions transform NGS results into actionable hereditary disease insights”.
Ben Solomon gave a presentation on “Solving Diagnostic Odysseys in the Neonatal Intensive Care Unit Achieving Valuable Insight from a Single Cell Genome.”
And Thursday October 8 was the time for our three poster presentations:
How can our solutions help you?
The solutions featured in our speakers presentations may also further your NGS studies. Take a look here and get inspired:
Of course you're also more than welcome to contact us for any questions you might have. Hope to see you next year in Vancouver - we’re already looking forward to it!
