Comprehensive Single-Cell Characterization of LDL in the Ovarian Cancer Microenvironment and Its Prognostic...

Area of Science:

• Oncology
• Molecular Biology
• Immunology

Background:

• Low-density lipoprotein (LDL) impacts lipid metabolism and cancer development, but its role in the ovarian cancer tumor microenvironment (TME) is not fully understood.
• Investigating LDL's distribution and function within the ovarian cancer TME is crucial for understanding tumor progression and identifying therapeutic targets.

Purpose of the Study:

• To comprehensively analyze the distribution, functional pathways, and prognostic significance of LDL in ovarian cancer using single-cell transcriptomics.
• To develop and validate a prognostic signature for ovarian cancer based on LDL-related gene expression.

Main Methods:

• Single-cell RNA sequencing data from ovarian cancer patients were analyzed using AUCell for LDL gene expression scoring.
• Gene Set Variation Analysis (GSVA) and CellChat were employed to assess functional pathways and cell-cell communication.
• A machine learning approach combined differentially expressed genes with bulk RNA-seq data to create the LDL-related ovarian cancer prognostic signature (LDLOCPS).

Main Results:

• LDL was highly expressed in myeloid and stromal cells within the ovarian cancer TME, correlating with pathways like EMT, inflammation, coagulation, and angiogenesis.
• Enhanced cell-cell communication was observed in high LDL score groups, particularly involving macrophages and monocytes.
• The validated LDLOCPS model accurately stratified patients by risk, with high LDLOCPS associated with worse overall survival and an immunosuppressive microenvironment.

Conclusions:

• This study elucidates LDL's spatial distribution and regulatory roles in ovarian cancer progression via multiple signaling pathways.
• The LDLOCPS model serves as a valuable tool for risk stratification and prognosis prediction in ovarian cancer.
• LDL-mediated microenvironmental and immunosuppressive effects suggest potential for novel targeted and immunomodulatory therapies.