ABSTRACT
The score and prognostic value of necroptosis were analyzed in the TCGA and GSE120622 datasets. Necroptosis has the highest correlation with the immune microenvironment, and the high score in NSCLC correlates with poor prognosis. Differentially expressed genes between non-small cell lung cancer (NSCLC) and controls in both datasets were identified and subjected to construct co-expression networks, respectively. Black and blue modules were selected because of high correction with necroptosis. The intersected two module genes were mainly involved in immune and inflammatory response, cell cycle process and DNA replication. Nine marker genes of necroptosis were identified in these modules and considered as candidate genes. Based on candidate genes, we identified two clusters utilizing concordance clustering, additionally dividing NSCLC samples into high- and low-risk groups. There were significant differences in overall survival between two clusters and between high- and low-risk groups. Furthermore, PARP1 was found among the candidate genes to be the target gene of dexmedetomidine acting on necroptosis. Molecular experimental results found that PARP1 was highly expressed in the dexmedetomidine treated NSCLC compared with the NSCLC. Candidate genes associated with necroptosis may provide a powerful prognostic tool for precision oncology. Dexmedetomidine may target PARP1 to promote necroptosis and then affect NSCLC.
Acknowledgements
All authors would like to thank all subjects who contributed to this study.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data available statement
Data analyzed in this study are available from TCGA and GEO databases (GSE120622).
Supplemental data
Supplemental data for this article can be accessed online at https://doi.org/10.1080/02648725.2023.2193469.
Ethics approval and consent to participate
This study was approved by the Ethics Committee of Harbin Medical University Cancer Hospital (KY2018–20). Oral informed consents were obtained from all patients.
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Funding
Notes on contributors
Yang Liu
Yang Liu designed the research and wrote the manuscript.
Xiaodan Teng
Xiaodan Teng collected and analyzed data.
Yubo Yan
Yubo Yan drew figures.
Su Zhao
Su Zhao performed the experiments.
Guonian Wang
Guonian Wang participated in the revision of the manuscript. All authors have read and approved the article.