Integrative Multi-Omics Data on Spatial Niches and CYP27A1+ TAMs in NSCLC Immunotherapy

A 5.1 MB PDF dataset from figshare, authored by Qingsheng Liu and last updated in March 2026, integrates single-cell and spatial transcriptomic data from non-small cell lung cancer patients. The data was used to construct nine spatial niches and identify CYP27A1+ tumor-associated macrophages as a key component linked to immune checkpoint blockade response. This resource supports the development of prognostic models for personalized cancer management.

Use Cases

• Predicting immunotherapy response in NSCLC based on spatial niche composition.
• Modeling the role of CYP27A1+ TAMs in recruiting CD8+ T cells via antigen presentation and chemokine secretion.
• Investigating the LXR pathway activation in macrophages following immune checkpoint blockade treatment.
• Developing prognostic models for patient outcomes using multi-omics and spatial transcriptomic features.

Strengths

• Data integrates single-cell and spatial transcriptomic data from the same patients, providing a multi-modal view.
• Analysis defined nine distinct spatial niches, offering a structured framework for microenvironment study.
• Findings were validated through external cohorts, immunohistochemistry, immunofluorescence, and in vivo experiments.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• The primary file format is a 5.1 MB PDF, which may require extraction or parsing to access underlying data tables.

Provenance

Source

figshare, author Qingsheng Liu.

Collection Method

Integrated single-cell and spatial transcriptomic data analyzed using ISCHIA to construct spatial niches.

Time Range

Temporal coverage of the underlying patient data is not specified.

Freshness

Last updated 2026-03-18 07:41:31; freshness should be verified.

Geography

Spatial coverage of the patient cohort is not specified.