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ABSTRACT
Objectives
To screen programmed cell death (PCD)-related genes in esophageal squamous cell carcinoma (ESCC) based on transcriptomic data and to explore its clinical value.
Methods
Differentially expressed PCD genes (DEPCDGs) were screened from ESCC transcriptome and clinical data in TCGA database. Univariate COX and LASSO COX were performed to on prognostically DEPCDGs in ESCC to develop prognostic model. Differences in immune cell infiltration in different RiskScore groups were determined by ssGSEA and CIBERSORT. The role of RiskScore in immunotherapy response was explored by Tumor Immune Dysfunction and Exclusion (TIDE) and IMvigor210 cohorts.
Results
14 DEPCDGs associated with prognosis were tapped in ESCC. These DEPCDGs form a RiskScore with good predictive performance for prognosis. RiskScore demonstrated excellent prediction accuracy in three data sets. The abundance of M2 macrophages and Tregs was higher in the high RiskScore group, and the abundance of M1 macrophages was higher in the low RiskScore group. The RiskScore also showed good immunotherapy sensitivity. RT-qPCR analysis showed that AUP1, BCAP31, DYRK2, TAF9 and UBQLN2 were higher expression in KYSE-150 cells. Knockdown BCAP31 inhibited migration and invasion.
Conclusion
A prognostic risk model can predict prognosis of ESCC and may be a useful biomarker for risk stratification and immunotherapy assessment.
Disclaimer
As a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also.Author contributions
All authors contributed to this present work: M Chen, YJ Qi, and HD Chen concepted and designed the research, SH Zhang, YB Du and SG Gao acquired the data, SG Gao, HD Chen analyzed and interpreted data. SG Gao, SH Zhang and M Chen drafted the manuscript, M Chen, HD Chen, YB Du and YJ Qi revised manuscript for important intellectual content. All authors read and approved the manuscript, and to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Abbreviations
| ESCC | = | Esophageal squamous cancer |
| PCD | = | programmed cell death |
| UCSC-Xena | = | University Of Cingifornia Sisha Cruz-Xena |
| TCGA | = | The cancer genome atlas |
| SNV | = | single nucleotide variants |
| DEGs | = | Differential expression genes |
| DEPCDGs | = | Differential expression programmed cell death genes |
| LASSO | = | least absolute shrinkage and selection operator |
| ROC | = | receiver operating characteristic |
| AUC | = | area under the curve |
| ssGSEA | = | single-sample gene set enrichment analysis |
| TIDE | = | Tumor Immune Dysfunction and Exclusion |
| CR | = | complete response |
| PR | = | partial response |
| SD | = | stable disease |
| PD | = | progressive disease |
Declarations statement
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Data availability
All analysis raw data is available in the Github (https://github.com/1MinChen/Raw-data-for-article.git).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/14737140.2024.2377184