Spatially resolved proteomic profiling identifies tumor cell CD44 as a biomarker associated with sensitivity to PD-1 axis blockade in advanced non-small- cell lung cancer

Most patients with advanced non-small-cell lung cancer (NSCLC) fail to derive significant benefit from programmed cell death protein-1 (PD-1) axis blockade, and new biomarkers of response are needed. In this study, we aimed to discover and validate spatially resolved protein markers associated with sensitivity to PD-1 axis inhibition in NSCLC

HER2 Aberrations in Non-Small Cell Lung Cancer: From Pathophysiology to Targeted Therapy

While human epidermal growth factor receptor 2 (HER2) aberrations have long been described in patients with non-small cell lung cancer (NSCLC), they have only recently been effectively targeted. Unlike patients with breast cancer, NSCLC patients can harbor either HER2-activating mutations or HER2 amplification coupled with protein overexpression. The latter has also been the case for patients with acquired resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). As preclinical data continue to accumulate, clinical trials evaluating novel agents that target HER2 have produced promising preliminary results. Here, we review existing data on HER2 aberrations in NSCLC. Starting from HER2 biology in normal and disease processes, we summarize discrepancies in HER2 diagnostic assays between breast cancer and NSCLC. Finally, to dissect the therapeutic implications of HER2-activating mutations versus gene amplification and/or protein overexpression, we present data from prospective clinical trials that have employed distinct classes of agents to target HER2 in patients with NSCLC

Baseline gene expression profiling determines long-term benefit to programmed cell death protein 1 axis blockade

Abstract Treatment with immune checkpoint inhibitors has altered the course of malignant melanoma, with approximately half of the patients with advanced disease surviving for more than 5 years after diagnosis. Currently, there are no biomarker methods for predicting outcome from immunotherapy. Here, we obtained transcriptomic information from a total of 105 baseline tumor samples comprising two cohorts of patients with advanced melanoma treated with programmed cell death protein 1 (PD-1)-based immunotherapies. Gene expression profiles were correlated with progression-free survival (PFS) within consecutive clinical benefit intervals (i.e., 6, 12, 18, and 24 months). Elastic net binomial regression models with cross validation were utilized to compare the predictive value of distinct genes across time. Lasso regression was used to generate a signature predicting long-term benefit (LTB), defined as patients who remain alive and free of disease progression at 24 months post treatment initiation. We show that baseline gene expression profiles were consistently able to predict long-term immunotherapy outcomes with high accuracy. The predictive value of different genes fluctuated across consecutive clinical benefit intervals, with a distinct set of genes defining benefit at 24 months compared to earlier outcomes. A 12-gene signature was able to predict LTB following anti-PD-1 therapy with an area under the curve (AUC) equal to 0.92 and 0.74 in the training and validation set, respectively. Evaluation of LTB, via a unique signature may complement objective response classification and characterize the logistics of sustained antitumor immune responses

Spatially resolved proteomic profiling identifies tumor cell CD44 as a biomarker associated with sensitivity to PD-1 axis blockade in advanced non-small- cell lung cancer

Most patients with advanced non-small-cell lung cancer (NSCLC) fail to derive significant benefit from programmed cell death protein-1 (PD-1) axis blockade, and new biomarkers of response are needed. In this study, we aimed to discover and validate spatially resolved protein markers associated with sensitivity to PD-1 axis inhibition in NSCLC