Pan-cancer neural regulation pattern with implications for patient stratification and immunotherapy

Area of Science:

• Oncology
• Neuroscience
• Genomics

Background:

• The nervous system's role in cancer (oncogenesis) is increasingly recognized.
• Understanding neuro-tumor interactions is crucial for developing new cancer therapies.

Purpose of the Study:

• To comprehensively map the pan-cancer landscape of neuro-tumor interactions.
• To identify neural signals as predictive biomarkers for cancer treatment response, especially immunotherapy.

Main Methods:

• Integrated analysis of The Cancer Genome Atlas (TCGA) bulk transcriptomics, pan-cancer spatial transcriptomics, and single-cell transcriptomes from checkpoint-inhibitor-treated patients.
• Spatiotemporal transcriptome analysis and ligand-receptor interaction network construction.
• Development of the Neuro_Cancer data resource.

Main Results:

• Characterized neural cancer subtypes and found significant correlations between neural signals and clinical features.
• High neural signals are linked to cancer-associated fibroblast infiltration and immune exclusion.
• Identified pivotal modulators of tumor growth in tumor core regions and demonstrated neural signals as predictive biomarkers for drug treatment responses, including immunotherapy.

Conclusions:

• Neural signals are critical regulators of tumorigenesis and influence cancer progression and immune evasion.
• The Neuro_Cancer resource provides a valuable platform for investigating neuro-tumor interactions.
• Targeting neuro-tumor interactions presents potential therapeutic opportunities in cancer treatment.