A single-cell characterised signature integrating heterogeneity and microenvironment of lung adenocarcinoma for prognostic stratification

Jiachen Xu ¹, Yundi Zhang ¹, Man Li ¹

⁰State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Ebiomedicine +

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March 28, 2024

View abstract on PubMed

Summary

This study developed an 11-gene signature using single-cell sequencing to predict lung adenocarcinoma (LUAD) patient prognosis by analyzing tumor heterogeneity and the tumor microenvironment (TME). The signature accurately stratifies patients and may guide immunotherapy treatment selection.

Area Of Science

Oncology
Genomics
Immunotherapy

Background

Tumor heterogeneity and microenvironment complexity significantly impact cancer development and immunotherapy response.
Lung adenocarcinoma (LUAD) prognosis is challenging due to these intricate factors.

Purpose Of The Study

To characterize the single-cell landscape of LUAD.
To develop a prognostic signature integrating tumor heterogeneity and the tumor microenvironment (TME).

Main Methods

Single-cell tagged reverse transcription sequencing (STRT-seq) on LUAD tissues and matched normal tissues.
Identification of 11 key genes related to tumor development and immune cell distribution.
Validation in 11 independent cohorts and in-vitro experiments.

Main Results

An 11-gene signature was established, stratifying LUAD patients into high- and low-score groups with distinct prognoses.
The signature demonstrated prognostic and predictive power for immunotherapy response across multiple cohorts.
In-vitro experiments and drug sensitivity predictions validated the signature's generalizability.

Conclusions

The single-cell-characterized 11-gene signature provides valuable insights for LUAD prognosis stratification.
This signature may guide personalized treatment selection for LUAD patients.

Keywords:

Immune microenvironment Lung adenocarcinoma Prognostic stratification Single cell sequencing Tumour heterogeneity