Published online Nov 26, 2022. doi: 10.12998/wjcc.v10.i33.12077
Peer-review started: May 7, 2022
First decision: July 13, 2022
Revised: August 15, 2022
Accepted: October 11, 2022
Article in press: October 11, 2022
Published online: November 26, 2022
The prognosis for esophageal cancer, one of the malignancies that responds least to cancer therapy, has not improved despite several breakthroughs in treatment. Improving patient outcomes depends on finding biomarkers and comprehending the molecular causes of esophageal cancer.
We wanted to create a risk score based on platelet-related gene signatures for prognosis prediction since the expression of platelet-related genes is strongly linked to patient prognosis.
To predict esophageal cancer prognosis, a risk model and nomogram constructed based on platelet-related gene signatures and clinical factors associated with prognosis could be utilized.
We constructed a trustworthy platelet-related gene signature to predict the prognosis of esophageal cancer using 151 samples of the disease. Then, an integrated nomogram for clinical practice was created utilizing a combined risk score, risk score, and TNM stage. The prognostic accuracy of the model was also supported by the receiver operating characteristic curve, concordance index, and related calibration curve.
The survival curve was created after constructing a prognostic risk model based on four platelet genes associated with prognosis. Patients in the high-risk group had a considerably lower life expectancy than those in the low-risk group, according to the Kaplan-Meier survival analysis. The risk score was an independent factor in predicting survival, according to results from both univariate and multivariate Cox regression analyses.
We identified a four-gene signature, constructed a risk score, and developed a prediction nomogram for patients with esophageal cancer based on the risk score, TNM staging, and histopathological type.
Identification and prediction of prognostic indicators are essential for esophageal cancer patients.