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Research Paper|Volume 15, Issue 19|pp 10305—10329

The integrated single-cell analysis developed an immunogenic cell death signature to predict lung adenocarcinoma prognosis and immunotherapy

Pengpeng Zhang1,2, Haotian Zhang1, Junjie Tang1, Qianhe Ren1, Jieying Zhang3, Hao Chi4, Jingwen Xiong5, Xiangjin Gong5, Wei Wang1, Haoran Lin1, Jun Li1, Chenjun Huang1
  • 1Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
  • 2Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
  • 3First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
  • 4Clinical Medical College, Southwest Medical University, Luzhou, China
  • 5Department of Sports Rehabilitation, Southwest Medical University, Luzhou, China
* Equal contribution and share the first authorship
Received: May 30, 2023Accepted: September 6, 2023Published: October 4, 2023
https://doi.org/10.18632/aging.205077

Copyright: © 2023 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Research on immunogenic cell death (ICD) in lung adenocarcinoma (LUAD) has been relatively limited. This study aims to create ICD-related signatures for accurate survival prognosis prediction in LUAD patients, addressing the challenge of lacking reliable early prognostic indicators for this type of cancer.

Methods: Using single-cell RNA sequencing (scRNA-seq) analysis, ICD activity in cells was calculated by AUCell algorithm, divided into high- and low-ICD groups according to median values, and key ICD regulatory genes were identified through differential analysis, and these genes were integrated into TCGA data to construct prognostic signatures using LASSO and COX regression analysis, and multi-dimensional analysis of ICD-related signatures in terms of prognosis, immunotherapy, tumor microenvironment (TME), and mutational landscape.

Results: The constructed signature reveals a pronounced disparity in prognosis between the high- and low-risk groups of LUAD patients. The statistical discrepancies in survival times among LUAD patients from both the TCGA and GEO databases further corroborate this observation. Additionally, heightened levels of immune cell infiltration expression are evidenced in the low-risk group, suggesting a potential benefit from immunotherapeutic interventions for these patients. The expression levels of pivotal risk-associated genes in tissue samples were assessed utilizing qRT-PCR, thereby unveiling PITX3 as a plausible therapeutic target in the context of LUAD.

Conclusions: Our constructed ICD-related signatures provide help in predicting the prognosis and immunotherapy of LUAD patients, and to some extent guide the clinical treatment of LUAD patients.