Genomic profiling of NSCLC tumors with the TruSight oncology 500 assay provides broad coverage of clinically actionable genomic alterations and detection of known and novel associations between genomic alterations, TMB, and PD-L1.

Introduction: Matching patients to an effective targeted therapy or immunotherapy is a challenge for advanced and metastatic non-small cell lung cancer (NSCLC), especially when relying on assays that test one marker at a time. Unlike traditional single marker tests, comprehensive genomic profiling (CGP) can simultaneously assess NSCLC tumors for hundreds of genomic biomarkers and markers for immunotherapy response, leading to quicker and more precise matches to therapeutics.

Methods: In this study, we performed CGP on 7,606 patients with advanced or metastatic NSCLC using the Illumina TruSight Oncology 500 (TSO 500) CGP assay to show its coverage and utility in detecting known and novel features of NSCLC.

Case report: Single gene testing and comprehensive genomic profiling in non-small cell lung cancer-a case series of divergent results from a large reference laboratory.

Clinical management of non-small cell lung cancer (NSCLC) requires accurate identification of tumor-specific genetic alterations to inform treatment options. Historically, providers have relied on single-gene testing (SGT) for actionable variants due to a perception of cost-effectiveness and/or efficient turnaround time compared to next-generation sequencing (NGS). However, not all actionable variants may be evaluated through SGT modalities, and an SGT approach can exhaust valuable tissue needed for more comprehensive analyses.

A consensus-based classification workflow to determine genetically inferred ancestry from comprehensive genomic profiling of patients with solid tumors.

Disparities in cancer diagnosis, treatment, and outcomes based on self-identified race and ethnicity (SIRE) are well documented, yet these variables have historically been excluded from clinical research. Without SIRE, genetic ancestry can be inferred using single-nucleotide polymorphisms (SNPs) detected from tumor DNA using comprehensive genomic profiling (CGP). However, factors inherent to CGP of tumor DNA increase the difficulty of identifying ancestry-informative SNPs, and current workflows for inferring genetic ancestry from CGP need improvements in key areas of the ancestry inference process.