Impact of Increasing PD-L1 Levels on Outcomes to PD-1/PD-L1 Inhibition in Patients With NSCLC: A Pooled Analysis of 11 Prospective Clinical Trials.

BACKGROUND: Programmed death ligand 1 (PD-L1) expression is recognized as a key biomarker in the treatment of non-small cell lung cancer (NSCLC) with anti-PD(L)1 inhibitors. Previous work has highlighted that outcomes in patients with NSCLC treated with anti-PD(L)1 inhibitors generally improve with increasing PD-L1 expression. The objectives of these analyses are to quantitate the effect of PD-L1 expression on outcomes, to characterize the potentially nonlinear relationship between PD-L1 expression and outcomes, and to assess potential differences in these relationships across subgroups. PATIENTS AND METHODS: We performed a retrospective, pooled analysis of 11 clinical trials submitted to the US FDA between 2015 and 2022 that included patients with advanced NSCLC treated with anti-programmed death 1 or anti-PD-L1 immune checkpoint inhibitor (ICI) monotherapy in the first-line (1L) or second-line (2L) treatment setting. The clinical outcomes explored were overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). RESULTS: The primary analysis population included 3806 patients with advanced NSCLC, of which 2040 were treated in 1L and 1766 in 2L. For patients with a PD-L1 score of 100% in the 1L setting, the hazard ratio versus a patient with 1% PD-L1 was 0.55 (95% CI, 0.43 to 0.70) for OS and 0.50 (95% CI, 0.41 to 0.61) for PFS. For patients with a PD-L1 score of 100% in the 2L setting, the hazard ratio versus a patient with 0% PD-L1 was 0.55 (95% CI, 0.43 to 0.71) for OS and 0.51 (95% CI, 0.41 to 0.63) for PFS. Subgroup analyses suggested that this relationship may vary by subgroup, particularly by region. CONCLUSIONS: These analyses suggest PD-L1 expression has an appreciable impact on clinical outcomes for patients with NSCLC treated with ICI. As the impact of PD-L1 expression on outcomes may vary across regions, it is critical that future trials are multiregional and enroll a diverse patient population.

FDA approval summary: fam-trastuzumab deruxtecan-nxki for unresectable or metastatic non-small cell lung cancer with activating HER2 mutations.

On August 11, 2022, FDA granted accelerated approval to fam-trastuzumab deruxtecan-nxki (DS-8201a, T-DXd, ENHERTU, Daiichi Sankyo) for adult patients with unresectable or metastatic non-small cell lung cancer (NSCLC) whose tumors have activating human epidermal growth factor receptor 2 (HER2) mutations, as detected by an FDA-approved test, and who have received a prior systemic therapy. The approval was based on a prespecified interim analysis of DESTINY-Lung02 (Study U206), a multi-center, randomized, dose-optimization trial in patients with NSCLC harboring activating HER2-mutations. At the approved dose of 5.4 mg/kg given intravenously every 3 weeks, the overall response rate (ORR) was 58% (95% confidence interval [CI]: 43, 71). The median duration of response was 8.7 months (95% CI: 7.1, not estimable). These results were consistent with response rates observed at the 6.4 mg/kg dose level. The most common (≥ 20%) adverse reactions were nausea, constipation, decreased appetite, vomiting, fatigue, and alopecia. The rate of interstitial lung disease (ILD) or pneumonitis was 6% at the 5.4 mg/kg dose level and 14% at the 6.4 mg/kg dose level. In the setting of similar efficacy and reduced toxicity, approval was granted for the 5.4 mg/kg dose level. The applicant conducted a randomized, dose-optimization study with guidance from the FDA Oncology Center of Excellence's Project Optimus. This is the first approval of a targeted therapy for HER2-mutated NSCLC.

Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome.

BACKGROUND: Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome. RESULTS: While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395). CONCLUSIONS: NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.