Overexpression of YAP confers radioresistance to esophageal cancer by altering the tumor microenvironment.

This study aimed to investigate the role of yes-associated protein (YAP) in the radiotherapy sensitivity of esophageal squamous cell carcinoma (ESCC). The clonogenic ability of ESCC cells was reduced after YAP silencing and radiotherapy. Overexpression of YAP promoted cell survival and had a synergistic effect with the hypoxic microenvironment. YAP was found to directly regulate hypoxia-inducible factor 1α (HIF-1α). Bioinformatics analysis revealed the involvement of YAP in modulating the tumor immune microenvironment. Inhibition of YAP expression reduced myeloid-derived suppressor cells (MDSCs) and influenced the immunosuppressive state, leading to radio resistance. These findings provide insights into the YAP-HIF-1α interaction and support YAP as a potential target for enhancing radiotherapy sensitivity in esophageal cancer.

Single-cell transcriptome sequencing analysis reveals intra-tumor heterogeneity in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignant tumor of the digestive system that poses a significant threat to human life and health. It is crucial to thoroughly investigate the mechanisms of esophageal carcinogenesis and identify potential key molecular events in its carcinogenesis. Single-cell transcriptome sequencing is an emerging technology that has gained prominence in recent years for studying molecular mechanisms, which may help to further explore the underlying mechanisms of the ESCC tumor microenvironment in depth. The single-cell dataset was obtained from GSE160269 in the Gene Expression Omnibus database, including 60 tumor samples and four paracancer samples. The single-cell data underwent dimensional reduction clustering analysis to identify clusters and annotate expression profiles. Subcluster analysis was conducted for each cellular taxon. Copy number variation analysis of tumor cell subpopulations was performed to primarily identify malignant cells within them. A proposed chronological analysis was performed to obtain the process of cell differentiation. In addition, cell communication, transcription factor analysis, and tumor pathway analysis were also performed. Relevant risk models and key genes were established by univariate COX regression and LASSO analysis. The key genes obtained from the screen were subjected to appropriate silencing and cellular assays, including CCK-8, 5-ethynyl-2'-deoxyuridine, colony formation, and western blot. Single-cell analysis revealed that normal samples contained a large number of fibroblasts, T cells, and B cells, with fewer other cell types, whereas tumor samples exhibited a relatively balanced distribution of cell types. Subclassification analysis of immune cells, fibroblasts, endothelial cells, and epithelial cells revealed their specific spatial characteristics. The prognostic risk model, we constructed successfully, achieved accurate prognostic stratification for ESCC patients. The screened key gene, UPF3A, was found to be significantly associated with the development of ESCC by cellular assays. This process might be linked to the phosphorylation of ERK and P38. Single-cell transcriptome analysis successfully revealed the distribution of cell types and major expressed factors in ESCC patients, which could facilitate future in-depth studies on the therapeutic mechanisms of ESCC.

Single-cell mapping of N6-methyladenosine in esophageal squamous cell carcinoma and exploration of the risk model for immune infiltration.

Background: N6-methyladenosine (m6A) modification is the most common RNA modification, but its potential role in the development of esophageal cancer and its specific mechanisms still need to be further investigated. Methods: Bulk RNA-seq of 174 patients with esophageal squamous carcinoma from the TCGA-ESCC cohort, GSE53625, and single-cell sequencing data from patients with esophageal squamous carcinoma from GSE188900 were included in this study. Single-cell analysis of scRNA-seq data from GSE188900 of 4 esophageal squamous carcinoma samples and calculation of PROGENy scores. Demonstrate the scoring of tumor-associated pathways for different cell populations. Cell Chat was calculated for cell populations. thereafter, m6A-related differential genes were sought and risk models were constructed to analyze the relevant biological functions and impact pathways of potential m6A genes and their impact on immune infiltration and tumor treatment sensitivity in ESCC was investigated. Results: By umap downscaling analysis, ESCC single-cell data were labelled into clusters of seven immune cell classes. Cellchat analysis showed that the network interactions of four signaling pathways, MIF, AFF, FN1 and CD99, all showed different cell type interactions. The prognostic risk model constructed by screening for m6A-related differential genes was of significant value in the prognostic stratification of ESCC patients and had a significant impact on immune infiltration and chemotherapy sensitivity in ESCC patients. Conclusion: In our study, we explored a blueprint for the distribution of single cells in ESCC based on m6A methylation and constructed a risk model for immune infiltration analysis and tumor efficacy stratification in ESCC on this basis. This may provide important potential guidance for revealing the role of m6A in immune escape and treatment resistance in esophageal cancer.

Effects of Radiotherapy on Survival of Esophageal Cancer Patients Receiving Immunotherapy: Propensity Score Analysis and Nomogram Construction.

Purpose: The present study assessed the effects of radiotherapy on overall survival (OS) and progression-free survival time (PFS) in patients with stage II or higher esophageal cancer receiving immunotherapy; evaluated factors independently prognostic of OS and PFS in these patients; and utilized these factors to establish a prognostic nomogram. Patients and Methods: This study enrolled 134 patients with stage II or higher esophageal cancer treated with chemotherapy (platinum-based agents plus paclitaxel or fluorouracil) and immunotherapy. These patients were divided into two groups, a radiotherapy (RT) group (n = 55) and a non-radiotherapy (non-RT) group (n = 79). Following 1:1 propensity score matching, OS and PFS were compared by the Kaplan-Meier method, and factors associated with survival were determined by univariate and multifactorial Cox regression analyses. These factors were used to construct a prognostic nomogram. Results: After propensity matching, all covariates were well balanced in the two groups (all P > 0.05). After matching, both median PFS (15.70 months [95% confidence interval (CI) 8.68-22.72 months] vs 5.70 months [95% CI 3.38-8.02 months], P = 0.002) and median OS (15.72 months [95% CI 12.94-18.46 months] vs 12.06 months [95% CI 9.91-14.20 months], P = 0.036) were significantly longer in the RT than in the non-RT group. Univariate and multifactorial analyses showed that RT, neutrophil-lymphocyte ratios, and tumor differentiation were independently prognostic of OS, with all hazard ratios (HRs) <1 and all P-values <0.05. A nomogram based on these factors was constructed, and its accuracy was verified. Conclusion: Immunotherapy plus RT resulted in better survival outcomes than immunotherapy alone. A nomogram based on prognostic factors can guide personalized treatment and monitor prognosis.

The Monte Carlo Simulation of Three Antimicrobials for Empiric Treatment of Adult Bloodstream Infections With Carbapenem-Resistant Enterobacterales in China.

Introduction: The aim of this study was to predict and evaluate three antimicrobials for treatment of adult bloodstream infections (BSI) with carbapenem-resistant Enterobacterales (CRE) in China, so as to optimize the clinical dosing regimen further. Methods: Antimicrobial susceptibility data of blood isolates were obtained from the Blood Bacterial Resistance Investigation Collaborative Systems in China. Monte Carlo simulation was conducted to estimate the probability target attainment (PTA) and cumulative fraction of response (CFR) of tigecycline, polymyxin B, and ceftazidime/avibactam against CRE. Results: For the results of PTAs, tigecycline following administration of 50 mg every 12 h, 75 mg every 12 h, and 100 mg every 12 h achieved > 90% PTAs when minimum inhibitory concentration (MIC) was 0.25, 0.5, and 0.5 µg/mL, respectively; polymyxin B following administration of all tested regimens achieved > 90% PTAs when MIC was 1 µg/mL with CRE; ceftazidime/avibactam following administration of 1.25 g every 8 h, 2.5 g every 8 h achieved > 90% PTAs when MIC was 4 µg/mL, 8 µg/mL with CRE, respectively. As for CFR values of three antimicrobials, ceftazidime/avibactam achieved the lowest CFR values. The highest CFR value of ceftazidime/avibactam was 77.42%. For tigecycline and ceftazidime/avibactam, with simulated regimens daily dosing increase, the CFR values were both increased; the highest CFR of tigecycline values was 91.88%. For polymyxin B, the most aggressive dosage of 1.5 mg/kg every 12 h could provide the highest CFR values (82.69%) against CRE. Conclusion: This study suggested that measurement of MICs and individualized therapy should be considered together to achieve the optimal drug exposure. In particular, pharmacokinetic and pharmacodynamic modeling based on local antimicrobial resistance data can provide valuable guidance for clinicians for the administration of empirical antibiotic treatments for BSIs.