Identification of Potential Biomarkers Associated With Immune Infiltration in Papillary Renal Cell Carcinoma

Deng, Ran; Li, Jianpeng; Zhao, Hong; Zou, Zhirui; Man, Jiangwei; Cao, Jinlong; Li, Yang

doi:10.21203/rs.3.rs-769170/v1

Cited by 1 publication

(1 citation statement)

References 26 publications

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“…Thus, identifying robust gene signatures that correspond to cancer patients' immune status is essential in identifying reliable prognostic biomarkers and stratifying patients into high-or low-risk groups to optimize their responsiveness to immunotherapy. To date, IRG signatures have been explored for several cancers, including lung cancer (28), ovarian cancer (29), papillary thyroid cancer (30), and renal papillary cell carcinoma (31). Recently, Wang et al examined the IRG signature for ESCA (32); however, metastatic ESCA was not excluded from that study.…”

Section: Discussionmentioning

confidence: 99%

The prognostic value of an immune-related gene signature and infiltrating tumor immune cells based on bioinformatics analysis in primary esophageal cancer

Du¹,

Pang²,

Li³

et al. 2022

J Gastrointest Oncol

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Background: Immunotherapy is a promising novel treatment for esophageal cancer (ESCA). However, previous studies provide limited direct information about the prognostic significance of immune-related genes (IRGs) in primary ESCA development. This study explored the prognostic value of IRGs and infiltrating tumor immune cells in primary ESCA. Methods: The ribonucleic acid (RNA)-sequencing data and clinical information of primary ESCA were downloaded from The Cancer Genome Atlas (TCGA) database. Which included the clinical factors and prognosis outcomes of the ESCA patients. The IRGs were downloaded from the ImmPORT database. Results: We established the robust IRG prognostic signature of 4 IRGs (i.e., heat shock protein family A member 6, Oncostatin M, androgen receptor, and nuclear receptor subfamily 2 group F member 2) in primary ESCA, and divided the ESCA patients into high-and low-risk groups based on overall survival (OS). The Kaplan-Meier curves showed the high predictive ability of the prognostic signature in the training, testing, and full data sets (P=2.407e-03, P=1.044e-02, and P=2.535e-04, respectively). Multivariate Cox regression analyses were performed with age, grade, tumor stage, tumor type and the risk score as covariables. The risk score supports the use of a prognostic signature as an independent prognostic factor [training data set: hazard ratio (HR) =1.185, 95% confidence interval (95% CI): 1.013-1.388, P=0.034; testing data set: HR =2.056, 95% CI: 1.015-4.166, P=0.045; full data set: HR =1.197, 95% CI: 1.059-1.354, P=0.004]. The area under the curve (AUC) of the receiver operating characteristic curve validated the high predictive accuracy of the IRG signature in the training, testing, and full data set (AUCs =0.808, 0.657, and 0.751, respectively). The infiltration level of the activated mast cells was significantly higher in the high-risk group than the low-risk group; thus, infiltrating mast cells are associated with worse OS in ESCA patients. Conclusions: Our IRG prognostic signature provides a new direction to predict the survival of primaryESCA patients and has the potential ability to establish, promote, and improve personalized treatment procedures based on each patient's risk.

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