Investigation on the Potential Correlation Between TP53 and Esophageal Cancer

ZCCHC4 regulates esophageal cancer progression and cisplatin resistance through ROS/c-myc axis

Zinc finger CCHC-type containing 4 (ZCCHC4) is a newly discovered N6-methyladenosine (m6A) RNA methyltransferase (MTase), which possesses an m6A MTase domain and an RNA-binding protein (RBP) Znf domain. Aberrantly expressed ZCCHC4 has been found to be correlated with poor prognosis and chemoresistance in various tumors, such as hepatocellular carcinoma, lung cancer and colorectal cancer. However, the expression and functional analysis of the role of ZCCHC4 in esophageal cancer (ESCA) is still elusive. The expression of ZCCHC4 in esophageal cancer tissues was evaluated by qPT-PCR and western blot. Serum esophageal tumor markers are detected by electrochemiluminescence immunoassay. Relationship between ZCCHC4 expression and pathway enrichment analysis were analyzed by R. The reactive oxygen species (ROS), cell proliferation, cell cycle and apoptosis of ZCCHC4 in esophageal squamous cell carcinoma (ESCC) cells tested by CCK8 assay and flow cytometry assay. Aberrant expression of ZCCHC4 is associated with cancer stages, lymph node metastasis (LNM), and tumor histology, and poorer Overall Survival (OS) in esophageal cancer. The mRNA level of ZCCHC4 in esophageal cancer patients correlates with serum carcinoembryonic antigen (CEA) levels, Squamous Cell Carcinoma (SCC) markers, and tissue polypeptide antigen (TPA) levels. Knockdown of ZCCHC4 induces DNA damage, leading to an elevation of reactive oxygen species (ROS), which in turn triggers S-phase arrest, enhances apoptosis, augments sensitivity to cisplatin treatment, and inhibits proliferation in esophageal cancer cells. Conversely, overexpression of ZCCHC4 promotes proliferation, inhibits apoptosis, and increases resistance to cisplatin in esophageal cancer cells. Furthermore, scavenging ROS reverses the effects of ZCCHC4 downregulation on both proliferation and apoptosis in esophageal cancer cells. Additionally, downregulation of ZCCHC4 inhibits the progression of esophageal cancer and reduces cisplatin resistance in vivo. In summary, downregulation of ZCCHC4 leads to increased sensitivity of ESCC cells to cisplatin, inhibits proliferation, and promotes apoptosis in esophageal cancer cells, potentially via the ROS/c-myc axis. The study suggests a potential adjunctive role for ZCCHC4 in the diagnosis and treatment of esophageal cancer and aids in further understanding the underlying mechanisms in ESCA progression.

Biomarker Testing and Role of Tyrosine Kinase Inhibitors and Immunotherapy for Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) constitutes an aggressive subset of esophageal cancers that portends a poor prognosis. Management of ESCC has been historically challenging due to the limited effective therapeutic options. Broadening our understanding of the molecular landscape and identifying reliable biomarkers are essential in early detection, monitoring disease response and advancing treatment strategies. Recently, immunotherapy and tyrosine kinase inhibitors have changed the treatment algorithm of ESCC. In this review, we explore the molecular landscape and biomarkers that can aid in the management of ESCC and discuss the role of immunotherapy and tyrosine kinase inhibitors in the treatment of ESCC.

Expression and functional analyses of TERF2 in esophageal carcinoma

Background

Esophageal cancer (ESCA) is a prevalent malignancy with a high incidence of morbidity and mortality, particularly in Asia. Telomeric Repeat-binding Factor 2 (TERF2) is a crucial component of the telomere-binding protein complex that maintains telomere stability. Aberrant TERF2 expression has been implicated in tumorigenesis, however, its specific role in ESCA remains largely unexplored.

Methods

The expression levels of TERF2 were assessed in esophageal squamous cell carcinoma (ESCC) samples using RT-PCR, IHC, and Western blotting (WB). Serum tumor marker concentrations were determined via electrochemiluminescence immunoassay (ECLIA) and chemiluminescent microparticle immunoassay (CMIA). Bioinformatics analyses were employed to elucidate TERF2's function in EC. The impact of TERF2 on ESCC cell proliferation was evaluated through cell counting kit-8 (CCK8) assays and flow cytometry.

Results

TERF2 protein and mRNA expression were elevated in ESCC tissues and correlated with age, sex, cancer stage, tumor grade, lymph node metastasis (LNM), and tumor histology. Univariate Cox regression analysis indicated TERF2 was an independent prognostic factor for overall survival (OS). TERF2 mRNA levels were associated with serum levels of carcinoembryonic antigen (CEA), cytokeratin 19 fragment (CYFRA21-1), and tissue polypeptide antigen (TPA) in patients with ESCC. Immune infiltration and chemokine profiles were linked to TERF2 expression in ESCA. TERF2 is involved in regulating ESCC cell proliferation may through the DDR/P53 signaling way.

Conclusions

TERF2 is overexpressed in ESCA and contributes to ESCC cell proliferation may via DDR/TP53 signaling pathway. These results suggest that TERF2 may serve as a potential target for developing treatments and diagnostic biomarker for ESCA.

Exploring the hub genes and mechanisms of Daphne altaica treating esophageal squamous cell carcinoma based on network pharmacology and bioinformatics analysis

PURPOSE

Esophageal squamous cell carcinoma (ESCC), is a frequent digestive tract malignant carcinoma with a high fatality rate. Daphne altaica (D. altaica), a medicinal plant that is frequently employed in Kazakh traditional medicine, and which has traditionally been used to cure cancer and respiratory conditions, but research on the mechanism is lacking. Therefore, we examined and verified the hub genes and mechanism of D. altaica treating ESCC.

METHODS

Active compounds and targets of D. altaica were screened by databases such as TCMSP, and ESCC targets were screened by databases such as GeneCards and constructed the compound-target network and PPI network. Meantime, data sets between tissues and adjacent non-cancerous tissues from GEO database (GSE100942, GPL570) were analyzed to obtain DEGs using the limma package in R. Hub genes were validated using data from the Kaplan-Meier plotter database, TIMER2.0 and GEPIA2 databases. Finally, AutoDock software was used to predict the binding sites through molecular docking.

RESULTS

In total, 830 compound targets were obtained from TCMSP and other databases. In addition, 17,710 disease targets were acquired based on GeneCards and other databases. In addition, we constructed the compound-target network and PPI network. Then, 127 DEGs were observed (82 up-regulated and 45 down-regulated genes). Hub genes were screened including TOP2A, NUF2, CDKN2A, BCHE, and NEK2, and had been validated with the help of several publicly available databases. Finally, molecular docking results showed more stable binding between five hub genes and active compounds.

CONCLUSIONS

In the present study, five hub genes were screened and validated, and potential mechanisms of action were predicted, which could provide a theoretical understanding of the treatment of ESCC with D. altaica.

Construction and Evaluation of a Risk Score Model for Lymph Node Metastasis-Associated Circadian Clock Genes in Esophageal Squamous Carcinoma

Background: Studies suggested that circadian clock genes (CCGs) in human esophageal squamous carcinoma (ESCC) samples are dysregulated. However, the relevance of CCGs to lymph node metastasis (LNM) and prognosis of ESCC remains unclear. Methods: The differentially expressed genes (DEGs) between normal and ESCC samples in The Cancer Genome Atlas database (TCGA) database were intersected with the genes associated with LNM (LNMGs) in ESCC samples and 300 CCGs to obtain the differentially expressed LNM-associated CCGs (DE-LNM-CCGs). The risk model was constructed by Cox regression analysis in the TCGA-ESCC training set, and the accuracy of the risk model was verified by risk profile and overall survival profile. Furthermore, differences of 23 immune cells, 13 immune functions, and immune checkpoint molecules between the high- and low-risk groups were assessed using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Gene set enrichment analysis (GSEA) was conducted to investigate the functional differences between low- and high-risk groups. Finally, we validated the mRNA expression levels of prognostic model genes by quantitative real-time polymerase chain reaction (qRT-PCR). Results: A total of six DE-LNM-CCGs were identified in TCGA-ESCC. TP53 and NAGLU were selected by Cox regression analysis to construct the risk model. Risk profile plots, overall survival plots, and validation results of the risk model in the validation set indicated that the constructed risk model was reliable. The result of ssGSEA showed that the percentages of activated B cells, activated dendritic cells, effector memory CD8 T cells, immune function in neutrophils, plasmacytoid dendritic cells, T cell co-inhibition, and Type 17 T helper cells were different between the high- and low-risk groups. In addition, the expression of CD274, PDCD1, TNFRSF18, and TNFRSF9 was dysregulated between the high- and low-risk groups. GSEA revealed that the high-risk group was associated with cell differentiation, oxidative phosphorylation, and steroid biosynthesis pathways, while the low-risk group was associated with chromosome, ECM–receptor interaction, and other pathways. Finally, qRT-PCR results showed that the mRNA expression levels of two prognostic genes were consistent with TCGA. Conclusion: In conclusion, the risk model constructed based on TP53 and NAGLU could accurately predict the prognosis.