High CHAF1A Expression Levels Are Positively-Correlated with PD-L1 Expression and Indicate Poor Prognosis in Gastric Cancer.

Abstract

Objective:

The aim of this study was to analyze the association between the expression of chromatin assembly factor 1 subunit A (CHAF1A) in gastric cancer (GC) and clinicopathological features, disease prognosis, and expression of programmed cell death-ligand 1 (PD-L1). Material and Methods. A total of 140 GC tissue specimens were collected between January 2013 and December 2017. CHAF1A expression in GC and paracancerous tissues was determined. Then, the associations between CHAF1A expression level in the collected tissues and clinicopathological features as well as PD-L1 expression level were investigated. Cox regression analyses were carried out to determine whether CHAF1A is an independent prognostic factor for GC. Finally, the association between CHAF1A expression levels and survival of the GC patients was investigated.

Results:

A significantly higher level of CHAF1A expression in GC tissues was found compared to that in paracancerous tissues (p=0.042). CHAF1A expression level in GC tissues was found to be strongly associated with family history (p=0.005), smoking history (p=0.016), T stage (p=0.001), tumor marker AFP (p=0.017), tumor marker CEA (p=0.027), and PD-L1 expression (p=0.029). CHAF1A expression was also found to be positively correlated to PD-L1 expression (p=0.012). Moreover, high CHAF1A expression levels were found to lead to poor prognosis (p=0.019). Univariate and multivariate analyses all showed that CHAF1A was an independent poorer prognostic factor for gastric cancer (p=0.021, HR = 1.175, 95% CI: 1.090-2.890 for univariate analyses; p=0.014, HR = 2.191, 95% CI:1.170-4.105 for multivariate analyses). A high level of CHAF1A expression was thus found to be an independent risk factor for GC prognosis.

Conclusion:

High CHAF1A expression is associated with poor GC prognosis and positively correlated to PD-L1 expression. Thus, CHAF1A expression level may be used as a novel biomarker for GC diagnosis.

• Authors: Zhehan Bao, Yanqiang Zhang, Pengcheng Yu, Yi Wang, Can Hu, Yuhang Xia, Li Yuan, Zhiyuan Xu, Xiangdong Cheng
• Journal: Evidence-based complementary and alternative medicine : eCAM (Evid Based Complement Alternat Med) Vol. 2022 Pg. 1323321 ( 2022) ISSN: 1741-427X [Print] United States
• PMID: 35911136 (Publication Type: Journal Article, Retracted Publication)
• Copyright: Copyright © 2022 Zhehan Bao et al.