Study on the Association Between the Timeliness of Comprehensive Genomic Profiling in Precision Oncology and Treatment Choices and Outcomes for Patients with Advanced Non-Small Cell Lung Cancer

Introduction

Advanced non-small-cell lung cancer (ANSCLC) is a highly lethal malignancy, and treatment choices directly affect the overall survival rate of patients. Therefore, the role of molecular biomarkers in treatment selection has become increasingly significant. Genomics has now become an integral part of first-line (1L) and second-line (2L) treatment options. For patients harboring oncogenic drivers such as EGFR (common deletions/mutations in exons ¹⁹⁄₂₁), BRAF V600E, MET exon 14 skipping, and fusions in ALK, ROS1, RET, and NTRK, targeted therapies against these drivers have been approved for 1L treatment. Further, discoveries such as KRAS G12C, EGFR exon 20 insertions, and HER2 mutations have also led to the approval of 2L treatments. However, timely and comprehensive biomarker testing is crucial in determining the opportunity for matched targeted therapies.

Currently, many patients with advanced non-small-cell lung cancer fail to receive the results of comprehensive genomic profiling (CGP) in a timely manner. Although patients lacking genomic testing other than PD-L1 immunohistochemistry might be guided to their 1L treatment choices by CGP, fewer patients receive CGP results promptly. This study explores the impact of timely CGP results on treatment choices and outcomes for patients with advanced non-small-cell lung cancer.

Study Source

This study was authored by Jeff Yorio, MD, Katherine T. Lofgren, PhD, Jessica K. Lee, MS, Khaled Tolba, MD, Geoffrey R. Oxnard, MD, Alexa B. Schrock, PhD, Richard S.P. Huang, MD, and Lorraine Brisbin, MS, and published in Journal of Clinical Oncology Precision Oncology. The DOI of the paper is https://doi.org/10.1200/po.23.00292.

Research Methods

Study Design and Process

The study utilized real-world data from the clinical genomic databases (CGDB) of Flatiron Health (FH) and Foundation Medicine (FMI), analyzing patient data from approximately 280 cancer clinics (around 800 treatment sites) in the United States. A total of 2694 patients with advanced non-small-cell lung cancer undergoing 1L treatment between May 2017 and September 2022 were analyzed. These patients received FMI tissue CGP testing and were treated within the FH network.

This research conducted a retrospective analysis of the patients’ electronic health record (EHR) data, linking them with genomic data from FMI comprehensive CGP tests through de-identified, deterministic matching. Samples used in the study were taken from appropriate tissue samples, with DNA extracted and analyzed to cover base substitutions, short insertions/deletions, copy number changes, and rearrangements, covering 315 or 324 cancer-related genes and selected introns of 28 or 36 genes, with an average coverage depth of >550x.

Data Collection and Experimental Steps

The study consisted of two primary steps: genomic analysis via FMI CGP testing and the classification and statistics of 1L treatment choices. During CGP testing, DNA was extracted from 40-micron formalin-fixed paraffin-embedded (FFPE) tissue sections, followed by analysis for base substitutions, short insertions/deletions, copy number alterations, and rearrangements. Tumor mutation burden (TMB) was also calculated, and PD-L1 expression was measured via immunohistochemistry (IHC).

1L treatments were classified into precision therapy or empiric therapy. Precision therapy included targeted therapies and precision immunotherapy checkpoint inhibitors (ICPI) guided by gene mutation results such as EGFR, BRAF, KRAS, etc. Empiric therapy did not consider molecular or genomic results and primarily included chemotherapy or chemotherapy combined with ICPI.

Statistical Analysis

Survival analysis was performed using the Kaplan-Meier method and Cox proportional hazards model. The study defined real-world overall survival (RWOS) and real-world time to treatment discontinuation (RWTTD).

Study Results

Key Findings

The study showed that patients who received timely CGP test results had significantly higher rates of matched targeted therapy and precision ICPI treatment than those who did not receive timely CGP results at the start of 1L treatment (increased by 14 percentage points). Additionally, ALK/EGFR/RET/ROS1-positive patients saw a 31 percentage point reduction in ineffective ICPI therapies. Patients with timely CGP results also exhibited significant advantages in real-world time to treatment discontinuation (median 10 months versus 3.9 months) and treatment cost (reduction of $13,659.37 per ALK/EGFR/RET/ROS1-positive patient).

However, there was no statistically significant difference in real-world overall survival (median 32 months vs 29 months) between the two groups.

Detailed Data Interpretation

Results were illustrated using multiple charts and tables to clarify the association between treatment choices and the timing of CGP result acquisition. For example, among patients who acquired CGP results before 1L treatment (n = 1666), 35% received precision therapy; whereas among those who received CGP results post treatment start (n = 1028), only 6.7% received precision therapy, with 90% receiving empiric therapy.

Of the patients who began 1L treatment without exact results, 11% had gene mutations amenable to targeted therapies, including KRAS G12C (11%) and EGFR mutations (5.4%).

Conclusion

Timely comprehensive genomic profiling (CGP) significantly enhances the quality and cost-effectiveness of treatment for patients with advanced non-small-cell lung cancer. The study emphasizes the importance of obtaining comprehensive genomic information in 1L treatment choices, demonstrating that timely CGP is associated with longer treatment discontinuation times and reduced ineffective ICPI costs. While no significant difference was observed in RWOS, the clinical value of CGP in guiding 1L treatment choices should not be overlooked.

Significance of the Study

This study illustrates the indispensable role of genomic analysis in the treatment of advanced non-small-cell lung cancer, emphasizing the importance of timely CGP in treatment decision-making and patient prognosis. The study’s conclusions provide valuable insights for future cancer treatment strategies and policy development, advocating for the integration of comprehensive genomic analysis into standard treatment protocols to achieve more precise cancer therapy.