SolidTumor Check+

Genomic solutions to improve how cancer will be identified and treated. Recommended treatment options based on patient genetic profile.

One sample, One Test, One Report can lead to improved patient outcomes

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• Analyze multiple variant types and key biomarkers in 500+ genes across DNA and RNA in a single assay

• Go from sample to results in 4-5 days using manual or automated workflows that integrate library prep, sequencing, and data analysis with the DRAGEN™ Bio-IT Platform.

• Generate accurate data and reliable results that meet demanding performance specifications.

• Keep samples in house and obtain data that is relevant to the local institution and community.

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Large-cohort studies show that comprehensive genomic profiling has the potential to identify relevant genetic alterations in up to 90% of samples.1-6 A single, comprehensive assay to assess a wide range of biomarkers uses less sample and returns results more quickly compared to multiple, iterative tests. To help researchers working with limited tissue supply and time, PreCheck offers SolidTumorCheck+. With proven technology, relevant biomarker content, and multiple established Pharma partnerships, these assays are well positioned to be the foundation for future tumor profiling diagnostic assays.

Analyze multiple tumor types and biomarkers with a single workflow.

SolidTumorCheck+ is next-generation sequencing (NGS) assays that simultaneously analyze both DNA and RNA in one integrated workflow. Panel content includes multiple variant types and key bio-markers across 523 cancer-relevant genes for DNA and RNA, eliminating the need to spend time and precious sample, such as formalin fixed, paraffin embedded (FFPE) tissue blocks, on iterative testing.

Benefit of NGS in Oncology

• As genomics-focused pharmacology begins to play a greater role in cancer treatment, next-generation sequencing (NGS) has emerged as a valuable method for obtaining a deeper and more accurate look into the molecular underpinnings of individual tumors. With targeted therapies becoming the new standard of care in oncology, NGS-driven companion diagnostics are widely seen as driving the selection of treatments to optimize patient outcomes in the future.
• Compared to traditional methods, NGS offers advantages in accuracy, sensitivity, and speed that has the potential to make a significant impact on the field of oncology. Because NGS can assess multiple genes in a single assay, it eliminates the need to order multiple tests to identify the causative mutation.
• This multigene approach decreases the time to answer, providing a more economical solution and reducing the risk of exhausting precious clinical samples. In addition, NGS can provide high sensitivity, enabling the detection of mutations present at as little as 5% of the DNA isolated from a tumor sample.
• NGS has the potential to change the future of oncology and advance the promise of personalized medicine.

References

1. Stransky N, Cerami E, Schalm S, Kim JL, Lengauer C. The landscape of kinase fusions in cancer. Nat Commun. 2014;5:4846. doi:10.1038/ncomms5846.

2. Boland GM, Piha-Paul SA, Subbiah V, et al. Clinical next generation sequencing to identify actionable aberrations in a phase I program. Oncotarget. 2015;6(24):20099-20110. doi:10.18632/oncotarget.4040

3. Massard C, Michiels S, Ferté C, et al. High-Throughput Genomics and Clinical Outcome in Hard-to-Treat Advanced Cancers: Results of the MOSCATO 01 Trial. Cancer Discov. 2017;7(6):586-595. doi:10.1158/2159-8290.CD-16-1396.

4. Harris MH, DuBois SG, Glade Bender JL, et al. Multicenter Feasibility Study of Tumor Molecular Profiling to Inform Therapeutic Decisions in Advanced Pediatric Solid Tumors: The Individualized Cancer Therapy (iCat) Study. JAMA Oncol. 2016;2(5):608-615. doi:10.1001/jamaoncol.2015.5689

5. Parsons DW, Roy A, Yang Y, et al. Diagnostic Yield of Clinical Tumor and Germline Whole-Exome Sequencing for Children With Solid Tumors. JAMA Oncol. 2016;2(5):616-624. doi:10.1001/

jamaoncol.2015.5699

6. Zehir A, Benayed R, Shah RH, et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med. 2017;23(6):703-713. doi:10.1038/nm.4333

7. Tray N, Weber JS, Adams S. Predictive Biomarkers for Check-point Immunotherapy: Current Status and Challenges for Clinical Application. Cancer Immunol Res. 2018;6(10):1122-1128. doi:10.1158/2326-6066.CIR-18-0214

8. Samstein RM, Lee CH, Shoushtari AN, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51(2):202-206. doi:10.1038/s41588-018-0312-8

9. U.S. Food & Drug Administration. FDA Approves First-Line Immunotherapy for Patients with MSI-H/dMMR Metastatic Col-orectal Cancer. fda.gov/news-events/press-announcements/fda-approves-first-line-immunotherapy-patients-msi-hdmmr-metastatic-colorectal-cancer. Published 2020. Accessed March 30, 2022.

10. U.S. Food & Drug Administration. FDA approves pembrolizumab for adults and children with TMB-H solid tumors. fda.gov/drugs/drug-approvals-and-databases/fda-approves-pembrolizum-ab-adults-and-children-tmb-h-solid-tumors. Published 2020. Accessed March 30, 2022.

11. Illumina. TruSight Oncology UMI Reagents technical note. illumina.com/content/dam/illumina-marketing/documents/products/ datasheets/trusight-oncology-umi-reagents-datasheet-1000000050425.pdf. Published 2018. Accessed March 30, 2022.

12. Pierian. Genomic Knowledgebase. pieriandx.com/genomic-knowledge base. Accessed March 30, 2022.

13. Illumina. Analysis of TMB and MSI Status with TruSight Oncology 500. illumina.com/content/dam/illumina-marketing/ documents/products/appnotes/trusight-oncology-500-tmb-analysis-1170-2018-009.pdf. Published 2018. Accessed March 30, 2022.

14. Beroukhim R, Mermel CH, Porter D, et al. The landscape of somatic copy-number alteration across human cancers. Nature. 2010;463(7283):899-905. doi:10.1038/nature08822

15. Green MR, Vicente-Dueñas C, Romero-Camarero I, et al. Transient expression of Bcl6 is sufficient for oncogenic function and induction of mature B-cell lymphoma. Nat Commun.2014;5:3904. doi:10.1038/ncomms4904

16. Piskol R, Ramaswami G, Li JB. Reliable identification of genomic variants from RNA-seq data. Am J Hum Genet. 2013;93(4):641-651. doi:10.1016/j.ajhg.2013.08.008

Turnaround time is 4-6 weeks