» Articles » PMID: 36483802

Integrative Analysis of Platelet-related Genes for the Prognosis of Esophageal Cancer

Overview
Specialty General Medicine
Date 2022 Dec 9
PMID 36483802
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Every year, esophageal cancer is responsible for 509000 deaths and around 572000 new cases worldwide. Although esophageal cancer treatment options have advanced, patients still have a dismal 5-year survival rate.

Aim: To investigate the relationship between genes associated to platelets and the prognosis of esophageal cancer.

Methods: We searched differentially expressed genes for changes between 151 tumor tissues and 653 normal, healthy tissues using the "limma" package. To develop a prediction model of platelet-related genes, a univariate Cox regression analysis and least absolute shrinkage and selection operator Cox regression analysis were carried out. Based on a median risk score, patients were divided into high-risk and low-risk categories. A nomogram was created to predict the 1-, 2-, and 3-year overall survival (OS) of esophageal cancer patients using four platelet-related gene signatures, TNM stages, and pathological type. Additionally, the concordance index, receiver operating characteristic curve, and calibration curve were used to validate the nomogram.

Results: The prognosis of esophageal cancer was associated to , , , and according to univariate Cox regression analysis and least absolute shrinkage and selection operator regression analysis. Patients with esophageal cancer at high risk had substantially shorter OS than those with cancer at low risk, according to a Kaplan-Meier analysis ( < 0.05). TNM stage (hazard ratio: 2.187, 95% confidence interval: 1.242-3.852, = 0.007) in both univariate and multivariate Cox regression and risk score were independently correlated with OS (hazard ratio: 2.451, 95% confidence interval: 1.599-3.756, 0.001).

Conclusion: A survival risk score model and independent prognostic variables for esophageal cancer have been developed using , , , and . OS for esophageal cancer might be predicted using the nomogram based on TNM stage, pathological type, and risk score. The nomogram demonstrated strong predictive ability, as shown by the concordance index, receiver operating characteristic curve, and calibration curve.

Citing Articles

A novel risk model consisting of nine platelet-related gene signatures for predicting prognosis, immune features and drug sensitivity in glioma.

Wei S, Zhou J, Dong B Hereditas. 2024; 161(1):52.

PMID: 39707577 PMC: 11662788. DOI: 10.1186/s41065-024-00355-7.


Characterization of platelet-related genes and constructing signature combined with immune-related genes for predicting outcomes and immunotherapy response in lung squamous cell carcinoma.

Zhao S, Gong H, Liang W Aging (Albany NY). 2023; 15(14):6969-6992.

PMID: 37477536 PMC: 10415560. DOI: 10.18632/aging.204886.

References
1.
Baba Y, Nomoto D, Okadome K, Ishimoto T, Iwatsuki M, Miyamoto Y . Tumor immune microenvironment and immune checkpoint inhibitors in esophageal squamous cell carcinoma. Cancer Sci. 2020; 111(9):3132-3141. PMC: 7469863. DOI: 10.1111/cas.14541. View

2.
Lindhiem O, Petersen I, Mentch L, Youngstrom E . The Importance of Calibration in Clinical Psychology. Assessment. 2018; 27(4):840-854. PMC: 6778000. DOI: 10.1177/1073191117752055. View

3.
Li J, Huang C, Xiong T, Zhuang C, Zhuang C, Li Y . A CRISPR Interference of CBP and p300 Selectively Induced Synthetic Lethality in Bladder Cancer Cells . Int J Biol Sci. 2019; 15(6):1276-1286. PMC: 6567804. DOI: 10.7150/ijbs.32332. View

4.
Okuda Y, Shimura T, Iwasaki H, Fukusada S, Nishigaki R, Kitagawa M . Urinary microRNA biomarkers for detecting the presence of esophageal cancer. Sci Rep. 2021; 11(1):8508. PMC: 8058072. DOI: 10.1038/s41598-021-87925-1. View

5.
Bang K, Na Y, Wook Huh H, Hwang S, Kim M, Kim M . The Delivery Strategy of Paclitaxel Nanostructured Lipid Carrier Coated with Platelet Membrane. Cancers (Basel). 2019; 11(6). PMC: 6627627. DOI: 10.3390/cancers11060807. View