Intrapulmonic Cavity or Necrosis on Baseline CT Scan Serves as an Efficacy Predictor of Anti-PD-(L)1 Inhibitor in Advanced Lung Squamous Cell Carcinoma

Single-cell RNA sequencing of baseline PBMCs predicts ICI efficacy and irAE severity in patients with NSCLC

BACKGROUND

Immune checkpoint inhibitors (ICIs) have transformed treatment and have provided significant clinical benefits and durable responses for patients with advanced non-small cell lung cancer (NSCLC). However, only a small percentage of patients respond to ICI treatment, and immune-related adverse events (irAEs) leading to treatment discontinuation remain challenging. Despite the recognized need for biomarkers to predict both the efficacy of ICIs and the risk of irAEs, such biomarkers are yet to be clearly identified.

METHODS

In this study, we performed single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from 33 patients with NSCLC before ICIs treatment. To validate our findings, we reanalyzed public scRNA-seq data, conducted a cytometric bead array (CBA), and supported our findings with T-cell receptor sequencing.

RESULTS

While the immune response was more pronounced in patients with a favorable prognosis, the hypoxic pathway was more prominent in patients with primary resistance. Lymphocytes such as CD8 T cells, CD4 T cells, and natural killer cells were primarily involved in these pathways, with PRF1 and GZMB expression showing strong associations with favorable prognosis. In contrast, irAEs were mainly linked to myeloid cells, such as monocytes and macrophages. As irAE severity increased, inflammation and the TNF-NFKB1 pathway were more prominent. Specifically, increased expression of IL1B, CXCL8, and CXCL2 in monocytes and TNF in macrophages was closely associated with severe irAE through involvement in these pathways.Notably, the increase of PRF1 and GZMB expression showed a close association with both a favorable prognosis and a reduced severity of irAE, which was validated through CBA analysis. Moreover, the expression of these key markers varied according to prognosis and irAE severity regardless of patient background, such as programmed death-ligand 1 expression levels, tumor histology, or prior treatment regimens.

CONCLUSIONS

This study identified biological pathways and key biomarkers associated with ICI prognosis and irAE severity using PBMC samples before treatment. These findings provide a foundation for improved therapeutic strategies that enhance clinical outcomes while minimizing ICI treatment-associated risks.

Pretreatment pulmonary tumor necrosis is a promising prognostic imaging biomarker for first-line anti-PD-1/PD-L1 therapy in advanced lung squamous cell carcinoma: a multi-institutional, propensity score-matching cohort analysis

BACKGROUND

Tumor necrosis (TN) is a common feature in lung squamous cell carcinoma (LSCC), which could provide useful predictive and prognostic information.

OBJECTIVES

This study aimed to investigate the effect of pretreatment pulmonary TN (PTN) on the prognosis of first-line anti-programmed cell death 1 (PD-1)/PD ligand 1 (PD-L1) inhibitor in advanced LSCC.

DESIGN

We conducted a retrospective study to analyze the association between the presence of PTN and clinical outcomes in advanced LSCC patients treated with anti-PD-1/PD-L1 inhibitors.

METHODS

Data from 240 eligible patients were collected from 27 hospitals across China between 2016 and 2020. The presence of PTN was assessed using contrast-enhanced chest computed tomography (CT) imaging at baseline. We utilized the Cox proportional-hazards regression model to analyze the association between PTN and clinical outcomes. In addition, to account for potential confounding factors and ensure comparability between groups, we employed propensity score-matching (PSM) analysis.

RESULTS

In the overall patient cohort, the presence of PTN was 39.6%. The median follow-up duration was 20.3 months. The positive PTN group exhibited a notably inferior median progression-free survival (PFS; 6.5 months vs 8.6 months, p = 0.012) compared to the negative PTN group. Within the Cox proportional-hazards regression model, PTN emerged as an independent predictor of unfavorable PFS (hazard ratio (HR) = 1.354, 95% confidence interval (CI): 1.002-1.830, p = 0.049). After PSM, the median PFS for the positive PTN group (6.5 months vs 8.0 months, p = 0.027) remained worse than that of the negative PTN group. Multivariate analyses also further underscored that the presence of PTN independently posed a risk for shorter PFS (HR = 1.494, 95% CI: 1.056-2.112, p = 0.023). However, no statistically significant difference in overall survival was observed between the two groups.

CONCLUSION

Our study suggests that the presence of PTN on baseline contrast-enhanced chest CT is a potential negative prognostic imaging biomarker for the outcome of anti-PD-1/PD-L1 inhibitor therapy in advanced LSCC. Further studies are warranted to validate these findings and explore the underlying mechanisms.

Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy

Introduction

Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance.

Methods

Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes.

Results

The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage.

Conclusions

Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.