Research Report on Efferocytosis Features and Their Prognostic and Immunotherapy Associations in Lung Adenocarcinoma

Background and Research Motivation

Lung cancer is a leading cause of cancer-related mortality worldwide, with lung adenocarcinoma (LUAD) being the most common histological subtype. Due to the insidious nature of the disease and lack of specific symptoms, most lung cancer patients are diagnosed at advanced stages, with limited effectiveness of traditional treatments like surgery, radiotherapy, and chemotherapy. Despite the advent of immune checkpoint inhibitors (ICIs), which offer hope for non-small cell lung cancer (NSCLC) treatment, their effectiveness remains constrained by the immune-suppressive tumor microenvironment (TME).

Efferocytosis (ER), the process by which phagocytes clear apoptotic cells, plays a critical role in tumor progression. Research suggests that ER promotes immune evasion in tumors while influencing tumor growth, migration, and metastasis. However, the mechanisms of ER in LUAD remain underexplored. This study aims to leverage transcriptomics and single-cell RNA sequencing data integrated with deep learning techniques to explore the prognostic potential of ER in LUAD and its immunotherapy response characteristics.

Research Source

This study was conducted by Yiluo Xie, Huili Chen, and colleagues from Bengbu Medical University and its affiliated hospital. The paper was published in Cancer Cell International (Volume 24, 2024), DOI: 10.1186/s12935-024-03571-3.

Methods and Workflow

Data Collection and Processing

Data were sourced from TCGA, GEO, and CTRP databases, including clinical information, transcriptomics, single-cell RNA sequencing, and drug sensitivity data. Additionally, 167 efferocytosis-related genes (ERGs) were identified from the literature and screened using univariate Cox regression, LASSO regression, and multivariate Cox regression for prognostic relevance.

Classification and Features of Efferocytosis in LUAD

LUAD patients were stratified into two subtypes (C1 and C2) using consensus clustering of ERGs. Subtype C2 exhibited better survival outcomes and higher immune infiltration scores, whereas subtype C1 was associated with active tumor proliferation and immune evasion. Single-cell RNA sequencing analysis revealed elevated ER activity in macrophages and endothelial cells, highlighting their role in clearing apoptotic cells within the tumor microenvironment.

Development and Validation of an ER-Related Prognostic Scoring System

A prognostic scoring system, ERGRS (Efferocytosis-Related Gene Risk Score), comprising seven genes (e.g., HAVCR1, IL1A, MERTK), was constructed using LASSO and multivariate Cox regression. ERGRS demonstrated robust prognostic performance across multiple datasets, with AUC values of 0.71, 0.69, and 0.70 for predicting 1-year, 3-year, and 5-year survival rates, respectively.

Deep Learning Model

A deep neural network (DNN) model was developed using TCGA-LUAD data, employing ERGRS as the classification label. The model achieved an AUC of 0.845 on the test set, indicating high accuracy in predicting LUAD prognosis.

Immunotherapy and Drug Sensitivity Analysis

The low ERGRS group showed higher immune cell infiltration and better responses to immunotherapy, such as anti-PD-L1 treatment. Potential therapeutic agents, including BRD-K92856060 and Monensin, were identified for high ERGRS patients via CTRP and PRISM databases.

Functional Validation of HAVCR1

HAVCR1 was highly expressed in LUAD tissues compared to normal tissues. Knockdown experiments demonstrated that HAVCR1 significantly inhibited LUAD cell proliferation, migration, and invasion, supporting its role as a prognostic marker.

Results

Key Findings

1. ER’s Role in LUAD Prognosis and Immunotherapy: The C2 subtype was associated with enhanced immune infiltration, better prognosis, and superior immunotherapy responses.
2. ERGRS as a Prognostic Tool: ERGRS accurately predicted survival and treatment responses in LUAD patients.
3. HAVCR1 Functional Studies: HAVCR1 influenced malignant behaviors of LUAD cells and was associated with poor patient prognosis.

Clinical Implications

ERGRS offers a novel approach for personalized treatment in LUAD, effectively identifying patients likely to benefit from immunotherapy. HAVCR1 presents a promising target for future therapeutic interventions.

Highlights and Future Directions

This study introduces a novel prognostic scoring system, ERGRS, linked to efferocytosis, shedding light on its critical role in cancer progression and treatment response. Despite its promising findings, further research is needed, including prospective clinical trials and additional in vivo experiments, to validate the clinical utility of ERGRS and elucidate the mechanisms underlying poor prognosis in high-risk patients.

Integration of ERGRS into Clinical Practice

To enhance the application of ERGRS in clinical workflows: - Integration with Clinical Decision Support Systems (CDSS): Embedding ERGRS within existing systems for real-time recommendations. - Workflow Optimization: Incorporating ERGRS scoring into electronic health records. - Quality Improvement Programs: Regularly assessing and refining ERGRS-based decision-making.

These strategies aim to improve treatment precision and survival outcomes for LUAD patients.