Real-World Impact of Comprehensive Genomic Profiling on Biomarker Detection, Receipt of Therapy, and Clinical Outcomes in Advanced Non-Small Cell Lung Cancer.

PURPOSE: Therapeutic decision making for patients with advanced non-small cell lung cancer (aNSCLC) includes a growing number of options for genomic, biomarker-guided, targeted therapies. We compared actionable biomarker detection, targeted therapy receipt, and real-world overall survival (rwOS) in patients with aNSCLC tested with comprehensive genomic profiling (CGP) versus small panel testing (SP) in real-world community health systems. METHODS: Patients older than 18 years diagnosed with aNSCLC between January 1, 2015, and December 31, 2020, who received biomarker testing were followed until death or study end (September 30, 2021), and categorized by most comprehensive testing during follow-up: SP (≤52 genes) or CGP (>52 genes). RESULTS: Among 3,884 patients (median age, 68 years; 50% female; 73% non-Hispanic White), 20% received CGP and 80% SP. The proportion of patients with ≥one actionable biomarker (actionability) was significantly higher in CGP than in SP (32% v 14%; P < .001). Of patients with actionability, 43% (CGP) and 38% (SP) received matched therapies (P = .20). Among treated patients, CGP before first-line treatment was associated with higher likelihood of matched therapy in any line (odds ratio, 3.2 [95% CI, 1.84 to 5.53]). CGP testing (hazard ratio [HR], 0.80 [95% CI, 0.72 to 0.89]) and actionability (HR, 0.84 [95% CI, 0.77 to 0.91]) were associated with reduced risk of mortality. Among treated patients with actionability, matched therapy receipt showed improved median rwOS in months in CGP (34 [95% CI, 21 to 49] matched v 14 [95% CI, 10 to 18] unmatched) and SP (27 [95% CI, 21 to 43] matched v 10 [95% CI, 8 to 14] unmatched). CONCLUSION: Patients who received CGP had improved detection of actionable biomarkers and greater use of matched therapies, both of which were associated with significant increases in survival.

Inferring Negative Molecular Biomarker Data at Scale.

PURPOSE: Patients who represent the negative biomarker population, those tested for a biomarker but found to be negative, are a critical component of the growing molecular data repository. Many next-generation sequencing (NGS)-based tumor sequencing panels test hundreds of genes, but most laboratories do not provide explicit negative results on test reports nor in their structured data. However, the need for a complete picture of the testing landscape is significant. Syapse has created an internal ingestion and data transformation pipeline that uses the power of natural language processing (NLP), terminology management, and internal rulesets to semantically align data and infer negative results not explicitly stated. PATIENTS AND METHODS: Patients within the learning health network with a cancer diagnosis and at least one NGS-based molecular report were included. To obtain this critical negative result data, laboratory gene panel information was extracted and transformed using NLP techniques into a semistructured format for analysis. A normalization ontology was created in tandem. With this approach, we were able to successfully leverage positive biomarker data to derive negative data and create a comprehensive data set for molecular testing paradigms. RESULTS: The application of this process resulted in a drastic improvement in data completeness and clarity, especially when compared with other similar data sets. CONCLUSION: The ability to accurately determine positivity and testing rates among patient populations is imperative. With only positive results, it is impossible to draw conclusions about the entire tested population or the characteristics of the subgroup who are negative for the biomarker in question. We leverage these values to perform quality checks on ingested data, and end users can easily monitor their adherence to testing recommendations.

Longitudinal and multi-tissue molecular diagnostics track somatic BRCA2 reversion mutations that correct the open reading frame of germline alteration upon clinical relapse.

BRCA-mutant cancers often develop therapeutic resistance through several mechanisms. Here, we report a case of pathogenic germline BRCA2-driven breast cancer monitored for disease progression and acquired resistance using longitudinal multi-tissue genomic testing. Briefly, genomic testing was performed throughout the course of disease on tumor tissue from multiple sites, circulating tumor DNA from blood plasma, and matched normal tissue. Genomic analyses identified actionable variants for targeted therapies, as well as emerging resistance mutations over time. Two unique BRCA2 somatic alterations (p.N255fs and p.D252fs) were identified upon resistance to PARP inhibitor and platinum treatment, respectively. Both alterations restored the open reading frame of the original germline alteration, likely accounting for acquired resistance. This case exemplifies the evolution of multiple subclonal BRCA reversion alterations over time and demonstrates the value of longitudinal multi-tissue genomic testing for monitoring disease progression, predicting measures of response, and evaluating treatment outcomes in oncology patients.