Single-cell RNA-seq reveals gene expression heterogeneity in NSCLC and its link to the immune microenvironment

Our single-cell transcriptomic dissection of NSCLC highlights cellular heterogeneity as well as potential biomarkers associated with immune microenvironment. The findings provide a foundation for the rational development of biomarker-driven personalized treatment and therapy by extending the cell-type specificity of current designs of NSCLC therapeutics.

Authors

Institutions

Publication Details

Journal
Discover Oncology
Published
2025-09-24
DOI
https://doi.org/10.1007/s12672-025-03494-z
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Single-cell RNA-seq reveals gene expression heterogeneity in NSCLC and its link to the immune microenvironment

Hua Zhang, Juan Ren, Haiyong Wu
Discover Oncology
Single-cell and spatial transcriptomics
article

Single-cell RNA-seq reveals gene expression heterogeneity in NSCLC and its link to the immune microenvironment

Hua Zhang, Juan Ren, Haiyong Wu
article en

Abstract

Our single-cell transcriptomic dissection of NSCLC highlights cellular heterogeneity as well as potential biomarkers associated with immune microenvironment. The findings provide a foundation for the rational development of biomarker-driven personalized treatment and therapy by extending the cell-type specificity of current designs of NSCLC therapeutics.

Discover OncologyVol. 16(1)
Hebei North University (CN), Zhangjiakou Academy of Agricultural Sciences (CN)
Openalex Percentile: Top 77%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.