BackgroundAs a common malignant tumor, esophageal carcinoma (ESCA) has a low early
diagnosis rate and poor prognosis. This study aimed to construct the prognostic features
composed of ZNF family genes to effectively predict the prognosis of ESCA patients.MethodsThe
mRNA expression matrix and clinical data were downloaded from TCGA and GEO database.
Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we
screened six prognosis-related ZNF family genes to construct the prognostic model.
We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC),
multivariable Cox regression analysis of clinical information, and nomogram to evaluate
the prognostic value within and across sets, separately and combined. We also validated
the prognostic value of the six-gene signature using GSE53624 dataset. The different
immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA).
Finally, real-time quantitative PCR was used to detect the expression of six prognostic
ZNF genes in twelve pairs of ESCA and adjacent normal tissues.ResultsA six prognosis-related
ZNF family genes model consisted of ZNF91, ZNF586, ZNF502, ZNF865, ZNF106 and ZNF225
was identified. Multivariable Cox regression analysis revealed that six prognosis-related
ZNF family genes were independent prognostic factors for overall survival of ESCA
patients in TCGA and GSE53624. Further, a prognostic nomogram including the riskScore,
age, gender, T, stage was constructed, and TCGA/GSE53624-based calibration plots indicated
its excellent predictive performance. Drug Sensitivity and ssGSEA analysis showed
that the six genes model was closely related to immune cells infiltration and could
be used as a potential predictor of chemotherapy sensitivity.ConclusionWe identified
six prognosis-related ZNF family genes model of ESCA, which provide evidence for individualized
prevention and treatment.
