Network-based single-cell analysis identifies a proliferative GZMB+ plasma cell subset linked to Hedgehog signaling and prognostic risk in lung squamous cell carcinoma

BACKGROUND: Lung squamous cell carcinoma (LUSC) is a heterogeneous cancer characterized by complex cellular interactions. Plasma cells, a critical immune population, exhibit functional diversity in LUSC. The aim of this study was to characterize plasma cell heterogeneity and their interactions with tumor cells using an integrative single-cell framework. METHODS: We constructed a high-resolution single-cell atlas of LUSC using single-cell RNA-sequencing data to identify plasma cell subsets. Plasma cell heterogeneity was assessed through clustering and differential expression analysis, and differentiation trajectories were plotted. Cell-cell communication was analyzed using the "CellChat" package. A prognostic nine-gene signature was derived using LASSO-Cox regression and further validated across independent GEO cohorts. Upstream regulatory mechanisms of prognostic genes were investigated through integrative transcriptomic analysis. The role of ZBTB20 in tumor progression was validated through functional assays. RESULTS: plasma cells. Network-based communication analysis demonstrated that C2 plasma cells interact with LUSC tumor cells via the SHH-PTCH1 signaling axis. A nine-gene prognostic signature robustly stratified patients, and was associated with immune signaling, cytokine interactions, apoptosis regulation, and tumor microenvironment remodeling. Integrative regulatory analysis identified UBB as a central prognostic gene, with ZBTB20 and PPARG as potential upstream transcriptional regulators. The prognostic significance of the C2-related gene signature was validated in independent GEO cohorts. ZBTB20 was further identified as a key regulator of tumor-related signaling and cellular proliferation, and its oncogenic role was verified through functional experiments. CONCLUSIONS: The proliferative C2 plasma cell subset has prognostic and functional significance in LUSC. ZBTB20 regulates key tumor-related pathways in LUSC cells through UBB-centered transcriptional control. These findings provide a systems-level framework for understanding plasma cell dynamics and tumor-immune interactions in LUSC progression for future development of targeted therapies.

Authors

Institutions

Publication Details

Journal
Journal of Translational Medicine
Published
2026-05-30
DOI
https://doi.org/10.1186/s12967-026-08328-2
Primary Topic
Cancer Cells and Metastasis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Network-based single-cell analysis identifies a proliferative GZMB+ plasma cell subset linked to Hedgehog signaling and prognostic risk in lung squamous cell carcinoma

Xiaoye Hu, Wen Ma, Yan Yuan, ZHOU Jie et al.
Journal of Translational Medicine
Cancer Cells and Metastasis
article

Network-based single-cell analysis identifies a proliferative GZMB+ plasma cell subset linked to Hedgehog signaling and prognostic risk in lung squamous cell carcinoma

Xiaoye Hu, Wen Ma, Yan Yuan, ZHOU Jie, Junjie Kuang, Shaohui Huang, Zhiwei Liao
article en

Abstract

BACKGROUND: Lung squamous cell carcinoma (LUSC) is a heterogeneous cancer characterized by complex cellular interactions. Plasma cells, a critical immune population, exhibit functional diversity in LUSC. The aim of this study was to characterize plasma cell heterogeneity and their interactions with tumor cells using an integrative single-cell framework. METHODS: We constructed a high-resolution single-cell atlas of LUSC using single-cell RNA-sequencing data to identify plasma cell subsets. Plasma cell heterogeneity was assessed through clustering and differential expression analysis, and differentiation trajectories were plotted. Cell-cell communication was analyzed using the "CellChat" package. A prognostic nine-gene signature was derived using LASSO-Cox regression and further validated across independent GEO cohorts. Upstream regulatory mechanisms of prognostic genes were investigated through integrative transcriptomic analysis. The role of ZBTB20 in tumor progression was validated through functional assays. RESULTS: plasma cells. Network-based communication analysis demonstrated that C2 plasma cells interact with LUSC tumor cells via the SHH-PTCH1 signaling axis. A nine-gene prognostic signature robustly stratified patients, and was associated with immune signaling, cytokine interactions, apoptosis regulation, and tumor microenvironment remodeling. Integrative regulatory analysis identified UBB as a central prognostic gene, with ZBTB20 and PPARG as potential upstream transcriptional regulators. The prognostic significance of the C2-related gene signature was validated in independent GEO cohorts. ZBTB20 was further identified as a key regulator of tumor-related signaling and cellular proliferation, and its oncogenic role was verified through functional experiments. CONCLUSIONS: The proliferative C2 plasma cell subset has prognostic and functional significance in LUSC. ZBTB20 regulates key tumor-related pathways in LUSC cells through UBB-centered transcriptional control. These findings provide a systems-level framework for understanding plasma cell dynamics and tumor-immune interactions in LUSC progression for future development of targeted therapies.

Journal of Translational Medicine
Liuzhou General Hospital (CN), Fourth Affiliated Hospital of Guangxi Medical University (CN), Jiangmen Central Hospital (CN), Guangzhou Medical University Cancer Hospital (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 6%
Cancer Cells and Metastasis
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.