Multi-omics analysis unveils a four-gene prognostic signature in esophageal squamous carcinoma and the therapeutic potential of PKP1

Apr 25, 2025BMC cancer

Four-gene signature predicts outcomes in esophageal squamous cancer and the treatment potential of PKP1

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Abstract

Four distinct subtypes of esophageal squamous cell carcinoma () were identified, each with unique cell type features and prognoses.

Dysregulated distributions of epithelial cells and fibroblasts were characteristic of ESCC.
A four-gene prognostic signature (CCND1-PKP1-JUP-ANKRD12) was constructed to discriminate the survival status of ESCC patients.
The risk score derived from the four-gene model correlated with the expression levels of immunoregulatory genes.
The expression levels of CCND1, PKP1, and JUP were confirmed at the protein level as dysregulated in ESCC tumors.
PKP1 expression was significantly correlated with EGFR expression and gene effect scores across multiple cancers.

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BACKGROUND: Esophageal squamous cell carcinoma () is one of the most common malignancies, characterized by high heterogeneity and poor outcomes. Effective classification for patient stratification and identifying reliable markers for prognosis prediction and treatment choice are crucial.

METHODS: Integration of single-cell RNA-sequencing (RNA-seq) and bulk RNA-seq analyses were used to characterize ESCC. Non-negative matrix factorization (NMF) clustering was performed to stratify the ESCC patients into different subtypes and the clinical and pathological features of the ESCC subtypes were compared. Cox regression analysis and LASSO regression analysis were used to select key genes and construct a risk model for ESCC. The associations of the key genes with anti-cancer drug sensitivities in ESCC cell lines were investigated. RT-qRCR experiments, proteomics analysis, and multiplex immunohistochemistry (mIHC) experiments were used to validate the results. Furthermore, one identified gene was selected to investigate its correlation with EGFR expression and the gene effect scores of various potential gene targets across pan-cancer.

RESULTS: The study identified the dysregulated distributions of epithelial cells and fibroblasts as characteristic of ESCC. ESCC patients could be classified into four distinct subtypes with unique cell type features and prognoses. With the gene makers of the cell type features, a four-gene prognostic signature for ESCC was constructed. The CCND1-PKP1-JUP-ANKRD12 model could effectively discriminate the survival status of ESCC patients, independent of various pathological and clinical features. The risk score for the samples was correlated with the expression levels of immunoregulatory genes. The prognostic effects of CCND1, PKP1, and JUP were confirmed at the protein level. The phosphorylation levels of PKP1, JUP, and ANKRD12 were found to be dysregulated in ESCC tumors. Their expression dysregulation and heterogeneity were demonstrated in ESCC cell lines. All four genes were significantly correlated with at least one of the anti-cancer drug sensitivities in ESCC cell lines. PKP1 expression was significantly correlated with EGFR expression and gene effect scores in multiple cancers.

CONCLUSIONS: We conclude that the CCND1-PKP1-JUP-ANKRD12 signature may serve as a novel indicator for ESCC prognosis and diagnosis. PKP1 expression might provide new clues for gene therapy efficacy in multiple cancers.

Key numbers

0.714

AUC of four-gene model

Area under the curve (AUC) for the four-gene prognostic model.

C1 patients had the shortest OS

Survival rate comparison

C1 cluster patients showed the worst overall survival (OS) outcomes.

0.38

Correlation of PKP1 with EGFR

Spearman correlation coefficient between PKP1 and EGFR expression levels.

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Multi-omics analysis unveils a four-gene prognostic signature in esophageal squamous carcinoma and the therapeutic potential of PKP1

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