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Identification and validation of prognostic and immunotherapeutic responses in esophageal squamous carcinoma based on hypoxia phenotype-related genes.

ABSTRACT: The study aimed to investigate the clinical significance of the interaction between hypoxia and the immune system in esophageal squamous cell carcinoma (ESCC) microenvironment. A comprehensive evaluation of 13 hypoxia phenotype-related genes (HPRs) was conducted using data from TCGA-ESCC and two GEO cohorts. Three distinct HPRclusters were identified, and the HPRscore was established as an independent prognostic factor (p = 0.001), with higher scores indicating poorer prognosis. The HPRscore was validated in various immunotherapy cohorts, demonstrating its efficacy in evaluating immunotherapy and chemotherapy outcomes. Additionally, phenome-wide association study (PheWAS) analysis showed that PKP1 had no significant correlation with other traits at the gene level. PKP1 was identified as a potential prognostic marker for ESCC, with upregulated expression observed in ESCC patients. In vitro experiments showed that the knockdown of PKP1 inhibited ESCC cell proliferation and migration. These findings suggest that the novel HPRscore and PKP1 may serve as prognostic tools and therapeutic targets for ESCC patients.

SUBMITTER: Xie K

PROVIDER: S-EPMC10955338 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Identification and validation of prognostic and immunotherapeutic responses in esophageal squamous carcinoma based on hypoxia phenotype-related genes.

Xie Kai K Chen Zhe Z Feng Jian J Pan Liangbin L Wang Nan N Luo Jing J Yao Yu Y Ma Haitao H Feng Yu Y Jiang Wei W

Frontiers in pharmacology 20240307

The study aimed to investigate the clinical significance of the interaction between hypoxia and the immune system in esophageal squamous cell carcinoma (ESCC) microenvironment. A comprehensive evaluation of 13 hypoxia phenotype-related genes (HPRs) was conducted using data from TCGA-ESCC and two GEO cohorts. Three distinct HPRclusters were identified, and the HPRscore was established as an independent prognostic factor (<i>p</i> = 0.001), with higher scores indicating poorer prognosis. The HPRsc ...[more]

PMID: 38515846

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Project description:Background: Esophageal squamous cell carcinoma (ESCC) is a prevalent and aggressive form of cancer that poses significant challenges in terms of prognosis and treatment. Regulatory T cells (Treg cells) have gained attention due to their influential role in immune modulation within the tumor microenvironment (TME). Understanding the intricate interactions between Treg cells and the tumor microenvironment is essential for unraveling the mechanisms underlying ESCC progression and for developing effective prognostic models and immunotherapeutic strategies. Methods: A combination of single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq analysis was utilized to explore the role of Treg cells within the TME of ESCC. The accuracy and applicability of the prognostic model were assessed through multi-dimensional evaluations, encompassing an examination of the model's performance across various dimensions, such as the mutation landscape, clinical relevance, enrichment analysis, and potential implications for immunotherapy strategies. Results: The pivotal role of the macrophage migration inhibitory factor (MIF) signaling pathway within the ESCC TME was investigated, with a focus on its impact on Treg cells and other subpopulations. Through comprehensive integration of bulk sequencing data, a Treg-associated signature (TAS) was constructed, revealing that ESCC patients with elevated TAS (referred to as high-TAS individuals) experienced significantly improved prognoses. Heightened immune infiltration and increased expression of immune checkpoint markers were observed in high-TAS specimens. The model's validity was established through the IMvigor210 dataset, demonstrating its robustness in predicting prognosis and responsiveness to immunotherapy. Heightened therapeutic benefits were observed in immune-based interventions for high-TAS ESCC patients. Noteworthy differences in pathway enrichment patterns emerged between high and low-TAS cohorts, highlighting potential avenues for therapeutic exploration. Furthermore, the clinical relevance of key model genes was substantiated by analyzing clinical samples from ten paired tumor and adjacent tissues, revealing differential expression levels. Conclusion: The study established a TAS that enables accurate prediction of patient prognosis and responsiveness to immunotherapy. This achievement holds significant implications for the clinical management of ESCC, offering valuable insights for informed therapeutic interventions.

Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is one of the most lethal malignant tumors worldwide, and a larger number of ESCC patients have unsatisfactory overall survival (OS) rates. While pyroptosis participates in the development of a variety of malignancies, the function of pyroptosis-related genes (PRGs) in ESCC is still obscure. The aim of this study was to construct the pyroptosis-related prognostic model for ESCC, which will be developed to stratify the risk hazards of ESCC patients and to provide theoretical evidence for individualized treatment.MethodsRNA-seq data of ESCC were download from the NCBI Gene Expression Omnibus (GEO) database. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to explore the potential biological functions or pathways. OS was considered as the primary prognosis outcome in this study. The riskscore was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis. The pyroptosis-related prognostic model was constructed based on all independent prognostic factors and verified by C-index, Receiver operating characteristic (ROC) curves, and Calibration curves, and the role of the riskscore in ESCC immunotherapy was evaluated by the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm.ResultsThe current study found 31 differentially expressed PRGs (P<0.001), and functional enrichment analysis showed these PRGs were enriched in positive regulation of cytokine production, interleukin-1 beta production. Univariate and multivariate Cox regression analysis were applied to validate that the riskscore based on four prognostic PRGs (HMGB1, IL-18, NLRP7, and PLCG1) was an independent prognostic factor for ESCC, and the C-index of prognostic model related to the riskscore (C-index =0.705) was higher than that of tumor node metastasis (TNM) stage (0.620). The low-risk group showed a better efficacy of immune checkpoint inhibitors.ConclusionsThe riskscore related to PRGs was one of the independent prognostic factors for ESCC. Moreover, the prognostic model related to the riskscore could be used to predict the OS of ESCC patients effectively. However, there still were several limitations in this study, such as no external validation sample. In summary, our data provides a novel perspective in exploring the potential prognostic biomarkers of ESCC.

Project description:Esophageal carcinoma (EC) is a common malignant cancer worldwide. Esophageal squamous cell carcinoma (ESCC), the main type of EC, is difficult to treat because of the widespread morbidity, high fatality rates, and low quality of life caused by postoperative complications and no specific molecular target. In this study, we screened genes to establish a prognostic model for ESCC. The transcriptome expression profiles of 81 ESCC tissues and 340 normal esophageal mucosal epithelium tissues were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cohorts. The transcriptome expression datasets of 19 esophageal squamous carcinoma cell lines were downloaded from Cancer Cell Line Encyclopedia (CCLE). The R software Limma package was used to identify 6,231 differentially expressed genes and 647 differentially expressed immune-related genes between normal and ESCC tissues. Gene functional analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Weighted gene co-expression network analysis (WGCNA) was used to screen out 18 immune-related prognostic genes. We then established the prognostic and risk signature using these genes, and the patients were divided into low-risk and high-risk groups. Compared with high-risk group patients, the low-risk group patients had longer overall survival. M1 macrophages and resting dendritic cells were differentially distributed between the low-risk and high-risk groups and were related to patient survival. We also examined the functional immune cell and immune molecule levels in low-risk and high-risk group patients, with significant differences in the tumor microenvironment between the two groups. To further verify the accuracy of the prognostic risk model, we performed area under the ROC curve (AUC) analysis. The AUC value was 0.931 for the prognostic risk, which was better than the microsatellite instability (MSI) and Tumor Immune Dysfunction and Exclusion (TIDE) scores. In conclusion, we found 18 immune-related prognostic genes related to the occurrence of ESCC and established a prognostic model for predicting disease severity.

Dataset Information

Identification and validation of prognostic and immunotherapeutic responses in esophageal squamous carcinoma based on hypoxia phenotype-related genes.

Publications

Identification and validation of prognostic and immunotherapeutic responses in esophageal squamous carcinoma based on hypoxia phenotype-related genes.

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