Prognosis Of Esophageal Squamous Cell Carcinoma Research Articles

Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms.

As a treatment for esophageal squamous cell carcinoma (ESCC), which is common and fatal, mitophagy is a conserved cellular mechanism that selectively removes damaged mitochondria and is crucial for cellular homeostasis. While tumor development and resistance to anticancer therapies are related to ESCC, their role in ESCC remains unclear. Here, we investigated the relationship between mitophagy-related genes (MRGs) and ESCC to provide novel insights into the role of mitophagy in ESCC prognosis and diagnosis prediction. First, we identified MRGs from the GeneCards database and examined them at both the single-cell and transcriptome levels. Key genes were selected and a prognostic model was constructed using least absolute shrinkage and selection operator analysis. External validation was performed using the GSE53624 dataset and Kaplan-Meier survival analysis was performed to identify PYCARD as a gene significantly associated with survival in ESCC. We then examined the effect of PYCARD on ESCC cell proliferation and migration and identified 169 MRGs at the single-cell and transcriptome levels, as well as the high-risk groups associated with cancer-related pathways. Thirteen key genes were selected for model construction via multiple machine learning algorithms. PYCARD, which is upregulated in patients with ESCC, was negatively correlated with prognosis and its knockdown inhibited ESCC cell proliferation and migration. Our ESCC prediction model based on mitophagy-related genes demonstrated promising results and provides more options for the management and clinical treatment of ESCC patients. Moreover, targeting or regulating PYCARD levels might offer new therapeutic strategies for ESCC patients in clinical settings.

Identifying Survival Subtypes of Esophageal Squamous Cell Carcinoma Patients: An Application of Deep Learning in Gene Expression Data Analysis

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most lethal types of cancer. Late diagnosis significantly decreases patient survival rates. Objectives: The study aimed to identify survival groups for patients with ESCC and find predictive biomarkers of time-to-death from ESCC using state-of-the-art deep learning (DL) and machine learning algorithms. Methods: Expression profiles of 60 ESCC patients, along with their demographic and clinical variables, were downloaded from the GEO dataset. A DL autoencoder model was employed to extract lncRNA features. The univariate Cox proportional hazard (Cox-PH) model was used to select significant extracted features related to patient survival. Hierarchical clustering (HC) identified risk groups, followed by a decision trees algorithm which was used to identify lncRNA profiles. We used Python.3.7 and R.4.0.1 software. Results: Inputs of the autoencoder were 8,900 long noncoding RNAs (lncRNAs), of which 1000 features were extracted. Out of the features, 42 lncRNAs were significantly related to time-to-death using the Cox-PH model and used as input for clustering of patients into high and low-risk groups (P-value of log-rank test = 0.022). These groups were then labeled for supervised HC. The C5.0 algorithm achieved an overall accuracy of 0.929 on the test set and identified four hub lncRNAs associated with time-to-death. Conclusions: Novel discovered lncRNAs lnc-FAM84A-1, LINC01866, lnc-KCNE4-2 and lnc-NUDT12-4 implicated in the pathogenesis of death from ESCC. Our findings represent a significant advancement in understanding the role of lncRNAs on ESCC prognosis. Further research is necessary to confirm the potential and clinical application of these lncRNAs.

Extracellular glypican-1 affects tumor progression and prognosis in esophageal cancer.

Cells are covered with a glycan surface layer that is referred to as the glycocalyx (GCX). It has been reported that the formation of the GCX is promoted on cancer cells and is associated with tumor growth and metastasis. Heparan sulfate proteoglycan glypican-1 (GPC1) is a core protein of the GCX that is overexpressed in esophageal squamous cell carcinoma (ESCC) and is involved in the development and progression of cancer cells. The purpose of the present study is to analyze the utility of GPC1 as a new biomarker ralated to glycocalyx that reflects therapeutic effect and prognosis of ESCC. We measured the concentration of GPC1 protein in preoperative plasma from advanced esophageal cancer patients and examined its relationships with clinicopathological factors and therapeutic efficacy, and the effects of extracellular GPC1 were investigated. The following clinical factors were significantly correlated with the preoperative high GPC1 concentration: male, tumor size ≥30 mm, venous invasion, pT factor ≥2, pStage ≥3, residual tumor, and distant metastatic recurrence. Both overall and recurrence-free survival were significantly worse in the high GPC1 group. Extracellular GPC1 protein concentration reflected intracellular GPC1 expression. Furthermore, we examined the effects of extracellular recombinant human (rh)GPC1 on ESCC cells, and found that extracellular rhGPC1 affects cell motility, including migration and invasion. These results demonstrated the utility of extracellular GPC1 as a biomarker, which can be assayed from a less invasive blood sample-based liquid biopsy. Extracellular GPC1 protein plays a role in both tumor cell motility and cancer progression. Thus, plasma GPC1 is a useful biomarker for esophageal cancer progression and may be a potential candidate of therapeutic target.

401. CLINICAL SIGNIFICANCE OF SIGNAL REGULATORY PROTEIN ALPHA AND CLUSTER OF DIFFERENTIATION 47 EXPRESSION IN ESOPHAGEAL SQUAMOUS CELL CARCINOMA

Abstract Background This study focuses on assessing the expression of Signal Regulatory Protein Alpha (SIRPα) and Cluster of Differentiation 47 (CD47) in Esophageal Squamous Cell Carcinoma (ESCC) and their impact on prognosis. Given the prominence of the CD47-SIRPα axis in cancer for inhibiting macrophage-mediated phagocytosis, this research aims to explore their role and significance in the development and treatment of ESCC. Methods In this study, 100 ESCC patients who underwent esophagectomy were included. Resected specimens were stained immunohistochemical staining for SIRPα and CD47. SIRPα expression was classified as high or low with cut-off value of 3%. CD47 expression was evaluated by Combined Positive Score (CPS) and Tumor Proportion Score (TPS) methods with setting a 10% threshold for high and low expression. The five-year survival rates were compared across groups over a median observation period of 61 months. This study reveals the correlation between these biomarkers and postoperative prognosis. Results Total 79 males and 21 females were included in this study and mean age was 68.7-year-old. The high SIRPα expression group (48 patients) revealed significantly worse 5-year overall survival rate than the low expression group (52 patients) (56.4 vs 82.8%, P=0.0098). For CD47, both evaluated by using CPS and TPS, the high expression group also showed significantly worse 5-year overall survival rate than its low group (48.8 vs 89.5%, P<0.0001, and 48.4 vs 87.5%, P<0.0001 respectively). Relapse free survival also showed significantly worse survival rate in high expression group of SIRPα and CD47. Conclusion The expression levels of SIRPα and CD47 serve as important biomarkers for predicting the prognosis of ESCC. They may influence prognosis by inhibiting macrophage-mediated tumor cell phagocytosis and modulating anti-tumor immune responses, offering new targets for ESCC treatment.

240. CACHEXIA INDEX AS A POTENTIAL BIOMARKER FOR SENSITIVITY OF NEOADJUVANT THERAPY AND PROGNOSIS IN ESOPHAGEAL SQUAMOUS CELL CARCINOMA

Abstract Background Cancer cachexia has a negative impact on the clinical outcome of patients with esophageal squamous cell carcinoma (ESCC). The cachexia index (CXI) is a potential biomarker for cancer cachexia, whereas its implications for ESCC prognosis and treatment outcomes have not been investigated. Methods In our study, 454 ESCC patients who had neoadjuvant therapy followed by surgery were included. Based on the exclusion criteria, a total of 224 patients were finally enrolled in this study. The CXI was determined as the serum albumin/neutrophil-lymphocyte ratio × the skeletal muscle index (based on CT image), which was classified as L3-CXI or pectoralis muscles-CXI depending upon the type of muscle involved. The patients were divided into high- and low-CXI groups using sex-specific medians as cutoff values for CXI. Results Tumor regression grade = 0,1 (sensitive to treatment) to neoadjuvant therapy was obtained in 61.6% and 46.4% of patients in the high-pretreatment L3-CXI and low-pretreatment L3-CXI groups, respectively (P = 0.023). ESCC patients with △L3-CXI <0 (L3-CXI decreased during treatment) had significantly shorter overall survival (P = 0.006) and disease-free survival (P = 0.002) than those with △L3-CXI ≥0. Multivariable analysis showed that △L3-CXI <0 was an independent negative prognostic factor for overall survival and disease-free survival. Conclusions In patients with ESCC, pretreatment CXI is a biomarker for treatment response, and △CXI can predict postoperative complications and survival outcomes. Patients could be clearly stratified by pretreatment CXI and △CXI categories, which provides a new nutritional assessment tool for clinical decision-making for patients with ESCC.

569. PROGNOSTIC VALUE OF T CELL PHENOTYPES AND PD-L1 EXPRESSION IN ESOPHAGEAL SQUAMOUS CELL CARCINOMA

Abstract Backgrounds The tumor microenvironment (TME) is a complex niche for tumor cells and immune cells to survive. Tumor-infiltrating lymphocytes (CD8+ T cells, FoxP3+ Tregs…etc), one of the main components of TME, are key factors in the host-tumor immune response, and the exact immune response in esophageal squamous cell carcinoma (ESCC) is still unclear. The purpose of this study was to investigate the expression of PD-L1 and TILs phenotypes in ESCC, their interactions and clinical significance. Methods Surgical specimens from 126 ESCC patients who underwent curative surgery between January 2001 and April 2017. We performed immunophenotyping of CD4, CD8, CD25, FOXP3 and PD-L1 within the tumor using immunohistochemistry and multiple immunofluorescence immunolabeling. PD-L1 was detected to expressed on tumor cells (PD-L1 TC) and tumor-infiltrating immune cells (PD-L1 TIIC), and PD-L1 TC affect biologic behavior. The calculation of overall survival (OS) and recurrence-free survival (RFS) were made using Kaplan-Meier analysis, and Cox regression model was used to analyze the correlation between survival and prognosis. Results CD8, FoxP3 and PD-L1 expression were positive in 40 (31.7%), 55 (43.7%) and 35 (27.8%) ESCC patient, respectively. CD8 and FoxP3 positive were associated with prolonged OS (p=0.0028, p=0.0324, respectively) and RFS (p=0.0019, p=0.0628, respectively). The overall survival rate in the PD-L1 positive group was statistically lower than that in the negative group (p=0.0402). Furthermore, the combination of CD8/PD-L1 and CD8/Foxp3 was able to more clearly classify and predict prognostic groups of ESCC. Considering the Treg phenotype, the presence of triple positive cell infiltration with Foxp3, CD4, and CD25 was strongly associated with poor prognosis of ESCC (p=0.0349). Cox proportional hazard model suggested that tumor depth, CD8+ infiltration and PD-L1 expression were significantly correlated with overall survival. CD8+ infiltration and PD-L1 expression were revealed to be independent prognostic factors. Conclusion CD8 and PD-L1 expression are independent prognostic and predictive factors for ESCC. And it is necessary to elucidate the immune mechanism comprehensively and thoroughly in the insight of multidimensional, multi-molecular and to provide therapeutic strategies for immunotherapy of ESCC.

T cell-related circRNA pairs to predict prognosis of patients with esophageal squamous cell carcinoma

The prognosis for esophageal squamous cell carcinoma (ESCC), a prevalent and aggressive form of cancer, remains poor despite advancements in treatment options. Addressing the gap in comprehensive prognostic information derived from circRNA expression profiles for ESCC, our study aimed to establish a linkage between circRNA expressions and ESCC prognosis. To achieve this, we first developed an optimized prognostic model named T cell-related risk score (TRRS), which integrates T cell-associated features with machine learning algorithms. In parallel, we re-analyzed existing RNA-seq datasets to redefine the expression profiles of circRNAs and mRNAs. Utilizing the TRRS as a foundational “bridge,” we identified circRNAs correlated with TRRS, leading to the development of a novel circRNA pair-based prognostic model, the TCRS, which is independent of specific expression levels. Further investigations uncovered two circRNAs, circNLK(5,6,7).1 and circRC3H1(2).1, with potential functional significance. These findings underscore the utility of these risk scores as tools for predicting overall survival and identifying potential therapeutic targets for ESCC patients.

Screening of genes related to programmed cell death in esophageal squamous cell carcinoma and construction of prognostic model based on transcriptome analysis

ABSTRACT Objectives To screen programmed cell death (PCD)-related genes in esophageal squamous cell carcinoma (ESCC) based on transcriptomic data and to explore its clinical value. Methods Differentially expressed PCD genes (DEPCDGs) were screened from ESCC transcriptome and clinical data in TCGA database. Univariate COX and LASSO COX were performed on prognostically DEPCDGs in ESCC to develop prognostic model. Differences in immune cell infiltration in different RiskScore groups were determined by ssGSEA and CIBERSORT. The role of RiskScore in immunotherapy response was explored using Tumor Immune Dysfunction and Exclusion (TIDE) and IMvigor210 cohorts. Results Fourteen DEPCDGs associated with prognosis were tapped in ESCC. These DEPCDGs form a RiskScore with good predictive performance for prognosis. RiskScore demonstrated excellent prediction accuracy in three data sets. The abundance of M2 macrophages and Tregs was higher in the high RiskScore group, and the abundance of M1 macrophages was higher in the low RiskScore group. The RiskScore also showed good immunotherapy sensitivity. RT-qPCR analysis showed that AUP1, BCAP31, DYRK2, TAF9 and UBQLN2 were higher expression in KYSE-150 cells. Knockdown BCAP31 inhibited migration and invasion. Conclusion A prognostic risk model can predict prognosis of ESCC and may be a useful biomarker for risk stratification and immunotherapy assessment.

Comparative evaluation of imaging methods for prognosis assessment in esophageal squamous cell carcinoma: focus on diffusion-weighted magnetic resonance imaging, computed tomography and esophagography.

To identify the most sensitive imaging examination method to evaluate the prognosis of esophageal squamous cell carcinoma (ESCC). Thirty patients with esophageal squamous cell carcinoma (ESCC) participated in the study and underwent chemoradiotherapy (CRT). They were divided into two groups based on their survival status: the survival group and non-survival group. The diagnostic tests were utilized to determine the most effective imaging examination method for assessing the prognosis. 1. There were no significant differences in tumor length shown on esophagography or computed tomography (CT) or the maximal esophageal wall thickness shown on CT at the specified time points between the two groups. 2. The tumor length on diffusion-weighted imaging (DWI) in the survival group was significantly lower than in the non-survival group at the end of the sixth week of treatment (P=0.001). The area under the ROC curve was 0.840 (P=0.002), and the diagnostic efficiency was moderately accurate. 3. The apparent diffusion coefficient (ADC) values of the survival group were significantly higher than those in the non-survival group at the end of the fourth week and sixth week of treatment (both P<0.001). Areas under the curve were 0.866 and 0.970, with P values of 0.001 and <0.001 and good diagnostic accuracy. Cox regression analyses indicated the ADC at the end of the sixth week of treatment was an independent risk factor. Compared with esophagography and CT, DW-MRI has certain advantages in predicting the prognosis of ESCC.

Roles of long non‑coding RNAs in esophageal cell squamous carcinoma (Review).

Esophageal squamous cell carcinoma (ESCC) is a prevalent and deadly malignancy of the digestive tract. Recent research has identified long non‑coding RNAs (lncRNAs) as crucial regulators in the pathogenesis of ESCC. These lncRNAs, typically exceeding 200 nucleotides, modulate gene expression through various mechanisms, including the competing endogenous RNA (ceRNA) pathway and RNA‑protein interactions. The current study reviews the multifaceted roles of lncRNAs in ESCC, highlighting their involvement in processes such as proliferation, migration, invasion, epithelial‑mesenchymal transition, cell cycle progression, resistance to radiotherapy and chemotherapy, glycolysis, apoptosis, angiogenesis, autophagy, tumor growth, metastasis and the maintenance of cancer stem cells. Specific lncRNAs like HLA complex P5, LINC00963 and non‑coding repressor of NFAT have been shown to enhance resistance to radio‑ and chemotherapy by modulating pathways such as AKT signaling and microRNA interaction, which promote cell survival and proliferation under therapeutic stress. Furthermore, lncRNAs like family with sequence similarity 83, member A antisense RNA 1, zinc finger NFX1‑type containing 1 antisense RNA 1 and taurine upregulated gene 1 are implicated in enhancing invasive and proliferative capabilities of ESCC cells through the ceRNA mechanism, while interactions with RNA‑binding proteins further influence cancer cell behavior. The comprehensive analysis underscores the potential of lncRNAs as biomarkers for prognosis and therapeutic targets in ESCC, suggesting avenues for future research focused on elucidating the detailed molecular mechanisms and clinical applications of lncRNAs in ESCC management.

Correlation of PD-L1 expression with CD8+ T cells and oxidative stress-related molecules NRF2 and NQO1 in esophageal squamous cell carcinoma.

Oxidative stress and the immune microenvironment both contribute to the pathogenesis of esophageal squamous cell carcinoma (ESCC). However, their interrelationships remain poorly understood. We aimed to examine the status of key molecules involved in oxidative stress and the immune microenvironment, as well as their relationships with each other and with clinicopathological features and prognosis in ESCC. The expression of programmed death-ligand 1 (PD-L1), CD8, nuclear factor erythroid-2 related factor-2 (NRF2), and NAD(P)H quinone oxidoreductase 1 (NQO1) was detected using immunohistochemistry in tissue samples from 176 patients with ESCC. We employed both combined positive score (CPS) and tumor proportion score (TPS) to evaluate PD-L1 expression and found a positive correlation between CPS and TPS. Notably, PD-L1 expression, as assessed by either CPS or TPS, was positively correlated with both NRF2 nuclear score and NQO1 score in stage II-IV ESCC. We also observed a positive correlation between the density of CD8+ T cells and PD-L1 expression. Furthermore, high levels of PD-L1 CPS, but not TPS, were associated with advanced TNM stage and lymph node metastases. Moreover, both PD-L1 CPS and the nuclear expression of NRF2 were found to be predictive of shorter overall survival in stage II-IV ESCC. By using the Mandard-tumor regression grading (TRG) system to evaluate the pathological response of tumors to neoadjuvant chemotherapy (NACT), we found that the TRG-5 group had higher NRF2 nuclear score, PD-L1 CPS, and TPS in pre-NACT biopsy samples compared with the TRG-3 + 4 group. The NQO1 scores of post-NACT surgical specimens were significantly higher in the TRG-5 group than in the TRG 3 + 4 group. In conclusion, the expression of PD-L1 is associated with aberrant NRF2 signaling pathway, advanced TNM stage, lymph node metastases, and unfavorable prognosis. The dysregulation of PD-L1 and aberrant activation of the NRF2 signaling pathway are implicated in resistance to NACT. Our findings shed light on the complex interrelationships between oxidative stress and the immune microenvironment in ESCC, which may have implications for personalized therapies and improved patient outcomes.

A novel amino acid metabolism-related gene signature to predict the overall survival of esophageal squamous cell carcinoma patients.

Esophageal squamous cell carcinoma (ESCC) has a poor early detection rate, prognosis, and survival rate. Effective prognostic markers are urgently needed to assist in the prediction of ESCC treatment outcomes. There is accumulating evidence of a strong relationship between cancer cell growth and amino acid metabolism. This study aims to determine the relationship between amino acid metabolism and ESCC prognosis. This study comprehensively evaluates the association between amino acid metabolism-related gene (AAMRG) expression profiles and the prognosis of ESCC patients based on data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to verify the expression of prognosis-related genes. A univariate Cox regression analysis of TCGA data identified 18 prognosis-related AAMRGs. The gene expression profiles of 90 ESCC tumor and normal tissues were obtained from the GSE20347 and GSE67269 datasets. Two differently expressed genes (DEGs) were considered as ESCC prognosis-related genes; and they were branched-chain amino acid transaminase 1 (BCAT1) and methylmalonic aciduria and homocystinuria type C protein (MMACHC). These two AAMRGs were used to develop a novel AAMRG-related gene signature to predict 1- and 2-year prognostic risk in ESCC patients. Both BCAT1 and MMACHC expression were verified by RT-qPCR. A prognostic nomogram that incorporated clinical factors and BCAT1 and MMACHC gene expression was constructed, and the calibration plots showed that it had good prognostic performance. The AAMRG signature established in our study is efficient and could be used in clinical settings to predict the early prognosis of ESCC patients.

PET/CT deep learning prognosis for treatment decision support in esophageal squamous cell carcinoma

ObjectivesThe clinical decision-making regarding choosing surgery alone (SA) or surgery followed by postoperative adjuvant chemotherapy (SPOCT) in esophageal squamous cell carcinoma (ESCC) remains controversial. We aim to propose a pre-therapy PET/CT image-based deep learning approach to improve the survival benefit and clinical management of ESCC patients.MethodsThis retrospective multicenter study included 837 ESCC patients from three institutions. Prognostic biomarkers integrating six networks were developed to build an ESCC prognosis (ESCCPro) model and predict the survival probability of ESCC patients treated with SA and SPOCT. Patients who did not undergo surgical resection were in a control group. Overall survival (OS) was the primary end-point event. The expected improvement in survival prognosis with the application of ESCCPro to assign treatment protocols was estimated by comparing the survival of patients in each subgroup. Seven clinicians with varying experience evaluated how ESCCPro performed in assisting clinical decision-making.ResultsIn this retrospective multicenter study, patients receiving SA had a median OS 9.2 months longer than controls. No significant differences in survival were found between SA patients with predicted poor outcomes and the controls (p > 0.05). It was estimated that if ESCCPro was used to determine SA and SPOCT eligibility, the median OS in the ESCCPro-recommended SA group and SPOCT group would have been 15.3 months and 24.9 months longer, respectively. In addition, ESCCPro also significantly improved prognosis accuracy, certainty, and the efficiency of clinical experts.ConclusionESCCPro assistance improved the survival benefit of ESCC patients and the clinical decision-making among the two treatment approaches.Critical relevance statementThe ESCCPro model for treatment decision-making is promising to improve overall survival in ESCC patients undergoing surgical resection and patients undergoing surgery followed by postoperative adjuvant chemotherapy.Key PointsESCC is associated with a poor prognosis and unclear ideal treatments.ESCCPro predicts the survival of patients with ESCC and the expected benefit from SA.ESCCPro improves clinicians’ stratification of patients’ prognoses.Graphical

High expression of the stemness-associated molecule Nanog in esophageal squamous cell carcinoma tissues promotes tumor invasion and metastasis by activating the TGF-β signaling pathway

To investigate the expression of Nanog and its regulatory relationship with MMP-2/MMP-9 proteins in esophageal squamous cell carcinoma (ESCC). We detected Nanog and MMP-2/MMP-9 protein expressions in 127 ESCC tissues and 82 adjacent normal tissues using immunohistochemistry and explored their correlations with the clinicopathological parameters and prognosis of the patients. GEO database was utilized to analyze the pathways enriched with the stemness-related molecules including Nanog, and TIMER online tool was used to analyze the correlations among TβR1, MMP-2, and MMP-9 in esophageal cancer. Nanog and MMP-2/MMP-9 proteins were significantly upregulated in ESCC tissues and positively intercorrelated. Their expression levels were closely correlated with infiltration depth and lymph node metastasis of ESCC but not with age, gender, or tumor differentiation. The patients with high expressions of Nanog and MMP-2/MMP-9 had significantly shorter survival time. Bioinformatics analysis showed enrichment of stemness-associated molecules in the TGF-β signaling pathway, and the expressions of MMP-2/MMP-9 and TβR1 were positively correlated. In cultured ESCC cells, Nanog knockdown significantly decreased the expression of TβR1, p-Smad2/3, MMP-2, and MMP-9 and strongly inhibited cell migration. The high expressions of Nanog, MMP-2, and MMP-9, which are positively correlated, are closely related with invasion depth, lymph node metastasis, and prognosis of ESCC. Nanog regulates the expressions of MMP-2/MMP-9 proteins through the TGF-β signaling pathway, and its high expression promotes migration of ESCC cells.

IQGAP1 overexpression attenuates chemosensitivity through YAP-mediated ferroptosis inhibition in esophageal squamous cell cancer cells

Chemoresistance is one of the major hindrances to many cancer therapies, including esophageal squamous cell carcinoma (ESCC). Ferroptosis, a new programmed cell death, plays an essential role in chemoresistance. IQ-domain GTPase activating protein 1 (IQGAP1) is a scaffold protein and functions as an oncogene in various human malignancies. However, the underlying effect and molecular mechanisms of IQGAP1 on paclitaxel (PTX) resistance and ferroptosis in ESCC remain to be elucidated. In this study, we found that IQGAP1 was highly expressed in ESCC tissues and could as a potential biomarker for diagnosis and predicting the prognosis of ESCC. Functional studies revealed that IQGAP1 overexpression reduced the sensitivity of ESCC cells to PTX by enhancing ESCC cell viability and proliferation and inhibiting cell death, and protected ESCC cells from ferroptosis, whereas IQGAP1 knockdown exhibited contrary effects. Importantly, reductions of chemosensitivity and ferroptosis caused by IQGAP1 overexpression were reversed with ferroptosis inducer RSL3, while the increases of chemosensitivity and ferroptosis caused by IQGAP1 knockdown were reversed with ferroptosis inhibitor ferrostatin-1 (Fer-1) in ESCC cells, indicating that IQGAP1 played a key role in resistance to PTX through regulating ferroptosis. Mechanistically, we demonstrated that IQGAP1 overexpression upregulated the expression of Yes-associated protein (YAP), the central mediator of the Hippo pathway. YAP inhibitor Verteporfin (VP) could reverse the effects of IQGAP1 overexpression on ESCC chemoresistance and ferroptosis. Taken together, our findings suggest that IQGAP1 promotes chemoresistance by blocking ferroptosis through targeting YAP. IQGAP1 may be a novel therapeutic target for overcoming chemoresistance in ESCC.

Tumor-Derived Exosomal miR-143-3p Induces Macrophage M2 Polarization to Cause Radiation Resistance in Locally Advanced Esophageal Squamous Cell Carcinoma.

We aimed to determine whether monitoring tumor-derived exosomal microRNAs (miRNAs) could be used to assess radiotherapeutic sensitivity in patients with locally advanced esophageal squamous cell carcinoma (ESCC). RNA sequencing was employed to conduct a comparative analysis of miRNA expression levels during radiotherapy, focusing on identifying miRNAs associated with progression. Electron microscopy confirmed the existence of exosomes, and co-cultivation assays and immunofluorescence validated their capacity to infiltrate macrophages. To determine the mechanism by which exosomal miR-143-3p regulates the interplay between ESCC cells and M2 macrophages, ESCC cell-derived exosomes were co-cultured with macrophages. Serum miR-143-3p and miR-223-3p were elevated during radiotherapy, suggesting resistance to radiation and an unfavorable prognosis for ESCC. Increased levels of both miRNAs independently predicted shorter progression-free survival (p = 0.015). We developed a diagnostic model for ESCC using serum microRNAs, resulting in an area under the curve of 0.751. Radiotherapy enhanced the release of miR-143-3p from ESCC cell-derived exosomes. Immune cell infiltration analysis at the Cancer Genome Atlas (TCGA) database revealed that ESCC cell-derived miR-143-3p triggered M2 macrophage polarization. Mechanistically, miR-143-3p upregulation affected chemokine activity and cytokine signaling pathways. Furthermore, ESCC cell exosomal miR-143-3p could be transferred to macrophages, thereby promoting their polarization. Serum miR-143-3p and miR-223-3p could represent diagnostic and prognostic markers for patients with ESCC undergoing radiotherapy. Unfavorable prognosis could be linked to the increased levels of ESCC cell-derived exosomal miR-143-3p, which might promote tumor progression by interacting with macrophages.

Latest insights into the global epidemiological features, screening, early diagnosis and prognosis prediction of esophageal squamous cell carcinoma

As a highly invasive carcinoma, esophageal cancer (EC) was the eighth most prevalent malignancy and the sixth leading cause of cancer-related death worldwide in 2020. Esophageal squamous cell carcinoma (ESCC) is the major histological subtype of EC, and its incidence and mortality rates are decreasing globally. Due to the lack of specific early symptoms, ESCC patients are usually diagnosed with advanced-stage disease with a poor prognosis, and the incidence and mortality rates are still high in many countries, especially in China. Therefore, enormous challenges still exist in the management of ESCC, and novel strategies are urgently needed to further decrease the incidence and mortality rates of ESCC. Although the key molecular mechanisms underlying ESCC pathogenesis have not been fully elucidated, certain promising biomarkers are being investigated to facilitate clinical decision-making. With the advent and advancement of high-throughput technologies, such as genomics, proteomics and metabolomics, valuable biomarkers with high sensitivity, specificity and stability could be identified for ESCC. Herein, we aimed to determine the epidemiological features of ESCC in different regions of the world, especially in China, and focused on novel molecular biomarkers associated with ESCC screening, early diagnosis and prognosis prediction.

VBP1 promotes tumor proliferation as a part of the hypoxia-related signature in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor in East Asia. Hypoxia, a hallmark of solid tumors, significantly alters redox homeostasis inside tumor microenvironment. This alteration drives tumor proliferation, invasion, and metastasis, leading to poor prognostic outcomes. However, the role of hypoxia-related genes in ESCC remains poorly understood. We employed RNA sequencing to identify differentially expressed genes in ESCC. Clinical data, transcriptome profiles, and a hypoxia-related gene set were extracted from open-source databases. A prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression, which was then validated through Cox regression analysis. Within this prognostic model, we pinpointed and investigated a key hypoxia-related gene affecting prognosis. The gene's expression was validated using real-time PCR and immunohistochemistry in both esophageal carcinoma and normal tissues. Tumor proliferation was examined through in vitro and in vivo assays, including the Cell Counting Kit-8, EdU, colony formation, and subcutaneous tumor models. A robust four-gene prognostic model (VBP1, BGN, CDKN1A, and PPFIA1) was successfully constructed and validated. Among these, VBP1 emerged as a key gene, exhibiting high expression levels that correlated with poor prognosis in ESCC. Functional experiments confirmed that VBP1 significantly accelerated tumor proliferation both in vitro and in vivo. VBP1 is identified as a pivotal gene within the hypoxia-related prognostic signature, and it significantly promotes tumor proliferation in ESCC.

Integrating bulk and single-cell sequencing data to construct a Scissor+ dendritic cells prognostic model for predicting prognosis and immune responses in ESCC

Esophageal squamous cell carcinoma (ESCC) is characterized by molecular heterogeneity with various immune cell infiltration patterns, which have been associated with therapeutic sensitivity and resistance. In particular, dendritic cells (DCs) are recently discovered to be associated with prognosis and survival in cancer. However, how DCs differ among ESCC patients has not been fully comprehended. Recently, the advance of single-cell RNA sequencing (scRNA-seq) enables us to profile the cell types, states, and lineages in the heterogeneous ESCC tissues. Here, we dissect the ESCC tumor microenvironment at high resolution by integrating 192,078 single cells from 60 patients, including 4379 DCs. We then used Scissor, a method that identifies cell subpopulations from single-cell data that are associated bulk samples with genomic and clinical information, to stratify DCs into Scissorhi and Scissorlow subtypes. We applied the Scissorhi gene signature to stratify ESCC scRNAseq patient, and we found that PD-L1, TIGIT, PVR and IL6 ligand-receptor-mediated cell interactions existed mainly in Scissorhi patients. Finally, based on the Scissor results, we successfully developed a validated prognostic risk model for ESCC and further validated the reliability of the risk prediction model by recruiting 40 ESCC clinical patients. This information highlights the importance of these genes in assessing patient prognosis and may help in the development of targeted or personalized therapies for ESCC.

Non‑coding RNA: A promising diagnostic biomarker and therapeutic target for esophageal squamous cell carcinoma (Review).

Esophageal cancer (EC) is a common form of malignant tumor in the digestive system that is classified into two types: Esophageal squamous cell carcinomas (ESCC) and esophageal adenocarcinoma. ESCC is known for its early onset of symptoms, which can be difficult to identify, as well as its rapid progression and tendency to develop drug resistance to chemotherapy and radiotherapy. These factors contribute to the high incidence of disease and low cure rate. Therefore, a diagnostic biomarker and therapeutic target need to be identified for ESCC. Non-coding RNAs (ncRNAs) are a class of molecules that are transcribed from DNA but do not encode proteins. Initially, ncRNAs were considered to be non-functional segments generated during transcription. However, with advancements in high-throughput sequencing technologies in recent years, ncRNAs have been associated with poor prognosis, drug resistance and progression of ESCC. The present study provides a comprehensive overview of the biogenesis, characteristics and functions of ncRNAs, particularly focusing on microRNA, long ncRNAs and circular RNAs. Furthermore, the ncRNAs that could potentially be used as diagnostic biomarkers and therapeutic targets for ESCC are summarized to highlight their application value and prospects in ESCC.