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Research Paper|Volume 15, Issue 22|pp 12907—12926

The necroptosis signature and molecular mechanism of lung squamous cell carcinoma

Guo-Qiang Song1, Hua-Man Wu2, Ke-Jie Ji1, Tian-Li He3, Yi-Meng Duan1, Jia-Wen Zhang1, Guo-Qiang Hu1,4
  • 1Department of Pulmonary, Changxing County Hospital of Traditional Chinese Medicine, Huzhou, China
  • 2Department of Pulmonary and Critical Care Medicine, Zigong First People’s Hospital, Zigong, China
  • 3Department of Radiotherapy, Changxing People’s Hospital, Huzhou, China
  • 4Department of Cancer Center, Changxing County Hospital of Traditional Chinese Medicine, Huzhou, China
Received: April 27, 2023Accepted: October 15, 2023Published: November 15, 2023
https://doi.org/10.18632/aging.205210

Copyright: © 2023 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Given the poor prognosis of lung squamous cell carcinoma (LUSC), the aim of this study was to screen for new prognostic biomarkers.

Methods: The TGCA_LUSC dataset was used as the training set, and GSE73403 was used as the validation set. The genes involved in necroptosis-related pathways were acquired from the KEGG database, and the differential genes between the LUSC and normal samples were identified using the GSEA. A necroptosis signature was constructed by survival analysis, and its correlation with patient prognosis and clinical features was evaluated. The molecular characteristics and drug response associated with the necroptosis signature were also identified. The drug candidates were then validated at the cellular level.

Results: The TCGA_LUSC dataset included 51 normal samples and 502 LUSC samples. The GSE73403 dataset included 69 samples. 159 genes involved in necroptosis pathways were acquired from the KEGG database, of which most showed significant differences between two groups in terms of genomic, transcriptional and methylation alterations. In particular, CHMP4C, IL1B, JAK1, PYGB and TNFRSF10B were significantly associated with the survival (p < 0.05) and were used to construct the necroptosis signature, which showed significant correlation with patient prognosis and clinical features in univariate and multivariate analyses (p < 0.05). Furthermore, CHMP4C, IL1B, JAK1 and PYGB were identified as potential targets of trametinib, selumetinib, SCH772984, PD 325901 and dasatinib. Finally, knockdown of these genes in LUSC cells increased chemosensitivity to those drugs.

Conclusion: We identified a necroptosis signature in LUSC that can predict prognosis and identify patients who can benefit from targeted therapies.