Integrating Functional Genomic Screens and Multi-Omics Data to Construct a Prognostic Model for Lung Adenocarcinoma...

Area of Science:

• Oncology
• Genomics
• Biomarker Discovery

Background:

• Lung adenocarcinoma (LUAD) is a heterogeneous cancer with limited treatment options.
• There is a critical need for prognostic biomarkers and therapeutic targets in LUAD.
• Integrating multi-omics data with functional genomic screens offers a promising strategy.

Purpose of the Study:

• To develop a prognostic risk-score model for LUAD using multi-omics data.
• To identify novel therapeutic targets for LUAD.
• To validate the role of SPC25 in LUAD progression and treatment response.

Main Methods:

• Genome-scale CRISPR-Cas9 screening data (DepMap) and TCGA-LUAD transcriptomic data were used.
• A 7-gene prognostic model was built using LASSO and Cox regression, validated in GEO datasets.
• In vitro, in vivo, and single-cell RNA-seq experiments validated the role of SPC25.

Main Results:

• A 7-gene risk-score model accurately stratified LUAD patient prognosis and served as an independent prognostic factor.
• High-risk scores correlated with advanced stage, immunosuppressive microenvironment, and poor immunotherapy response.
• SPC25 knockdown inhibited LUAD cell proliferation and tumor growth; high SPC25 expression was linked to immunosuppressive cells.

Conclusions:

• A robust prognostic model for LUAD was developed, aiding in patient stratification.
• SPC25 is validated as a crucial oncogene in LUAD.
• SPC25 represents a promising therapeutic target for lung adenocarcinoma.