Prognosis Of Esophageal Squamous Cell Carcinoma Research Articles

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.

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.

Innovative prognostic modeling in ESCC: leveraging scRNA-seq and bulk-RNA for dendritic cell heterogeneity analysis.

Globally, esophageal squamous cell carcinoma (ESCC) stands out as a common cancer type, characterized by its notably high rates of occurrence and mortality. Recent advancements in treatment methods, including immunotherapy, have shown promise, yet the prognosis remains poor. In the context of tumor development and treatment outcomes, the tumor microenvironment (TME), especially the function of dendritic cells (DCs), is significantly influential. Our study aims to delve deeper into the heterogeneity of DCs in ESCC using single-cell RNA sequencing (scRNA-seq) and bulk RNA analysis. In the scRNA-seq analysis, we utilized the SCP package for result visualization and functional enrichment analysis of cell subpopulations. CellChat was employed to identify potential oncogenic mechanisms in DCs, while Monocle 2 traced the evolutionary trajectory of the three DC subtypes. CopyKAT assessed the benign or malignant nature of cells, and SCENIC conducted transcription factor regulatory network analysis, offering a preliminary exploration of DC heterogeneity. In Bulk-RNA analysis, we constructed a prognostic model for ESCC prognosis and immunotherapy response, based on DC marker genes. This model was validated through quantitative PCR (qPCR) and immunohistochemistry (IHC), confirming the gene expression levels. In this study, through intercellular communication analysis, we identified GALECTIN and MHC-I signaling pathways as potential oncogenic mechanisms within dendritic cells. We categorized DCs into three subtypes: plasmacytoid (pDC), conventional (cDC), and tolerogenic (tDC). Our findings revealed that pDCs exhibited an increased proportion of cells in the G2/M and S phases, indicating enhanced cellular activity. Pseudotime trajectory analysis demonstrated that cDCs were in early stages of differentiation, whereas tDCs were in more advanced stages, with pDCs distributed across both early and late differentiation phases. Prognostic analysis highlighted a significant correlation between pDCs and tDCs with the prognosis of ESCC (P< 0.05), while no significant correlation was observed between cDCs and ESCC prognosis (P = 0.31). The analysis of cell malignancy showed the lowest proportion of malignant cells in cDCs (17%), followed by pDCs (29%), and the highest in tDCs (48%), with these results being statistically significant (P< 0.05). We developed a robust ESCC prognostic model based on marker genes of pDCs and tDCs in the GSE53624 cohort (n = 119), which was validated in the TCGA-ESCC cohort (n = 139) and the IMvigor210 immunotherapy cohort (n = 298) (P< 0.05). Additionally, we supplemented the study with a novel nomogram that integrates clinical features and risk assessments. Finally, the expression levels of genes involved in the model were validated using qPCR (n = 8) and IHC (n = 16), thereby confirming the accuracy of our analysis. This study enhances the understanding of dendritic cell heterogeneity in ESCC and its impact on patient prognosis. The insights gained from scRNA-seq and Bulk-RNA analysis contribute to the development of novel biomarkers and therapeutic targets. Our prognostic models based on DC-related gene signatures hold promise for improving ESCC patient stratification and guiding treatment decisions.

Prognostic Risk Models Using Epithelial Cells Identify β-Sitosterol as a Potential Therapeutic Target Against Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) is an aggressive and fatal malignancy that leads to epithelial cancer. The association between epithelial cell heterogeneity, prognosis, and immune response in this cancer remains uncertain. This study aimed to investigate epithelial cell heterogeneity in ESCC and develop a predictive risk model using the identified cell types. Single-cell RNA sequencing (scRNA-seq) and differential ESCC gene data were accessed from the Gene Expression Omnibus. Functional enrichment analysis, inferCNV, cell development trajectories, and intercellular communication were analyzed following epithelial cell characterization. Differentially expressed ESCC (n = 773) and epithelial cell marker genes (n = 3407) were intersected to obtain core genes, and epithelial cell-related prognostic genes were identified. LASSO regression analysis was used to construct a prognostic model. The external dataset GSE53624 was used to further validate the stability of the model. Drug sensitivity predictions, and immune cell infiltration were analyzed. Molecular docking clarified the possible therapeutic role of β-sitosterol in ESCC. Finally, wound healing assay, cell colony, and transwell assay were constructed to detect the effects of the core gene PDLIM2 on ESCC cell proliferation, invasion, and migration. Eight cell clusters were identified, and epithelial cells were categorized into tumor and paratumor groups. The tumor group possessed more chromosomal variants than the paratumor group. Epithelial cells were associated with multiple cell types and significantly correlated with the Wnt, transforming growth factor, and epidermal growth factor signaling pathways. From 231 intersected genes, five core genes were screened for use in the risk model: CTSL, LAPTM4B, MYO10, NCF2, and PDLIM2. These genes may contribute to the cancerous transformation of normal esophageal epithelial cells and thereby act as biomarkers and potential therapeutic targets in patients with ESCC. β-Sitosterol furthermore displayed excellent docking potential with these genes. Meanwhile, further experiments demonstrated that the gene PDLIM2 plays a major role in the progression of oesophageal squamous carcinoma. We successfully developed a risk model for the prognosis of ESCC based on epithelial cells that addresses the response of ESCC to immunotherapy and offers novel cancer treatment options.

Comprehensive landscape and future perspectives of non-coding RNAs in esophageal squamous cell carcinoma, a bibliometric analysis from 2008 to 2023.

Objectives: Summarize the progress and hot topic evolution of non-coding RNAs (ncRNAs) research in esophageal squamous cell carcinoma (ESCC) in recent years and predict future research directions. Methods: Relevant articles from the Web of Science until 31 October 2023 were obtained. Bibliometric analysis of included articles was performed using software (VOSviewer, CiteSpace, and Bibliometrix). The volume and citation of publications, as well as the country, institution, author, journal, keywords of the articles were used as variables to analyze the research trends and hot spot evolution. Results: 1,118 literature from 2008 to 2023 were retrieved from database, with 25 countries/regions, 793 institutions, 5,426 authors, 261 journals involved. Global cooperation was centered on China, Japan, and the United States. Zhengzhou University, an institution from China, had the highest publication. The most prolific author was Guo Wei, and the most prolific journal was Oncology Letters. Analysis of keywords revealed that the research in this field revolved around the role of ncRNAs in the occurrence, development, diagnosis, treatment, and prognosis of ESCC, mainly including micro RNAs, long non-coding RNAs, and then circular RNAs. Conclusion: Overall, research on ncRNAs in ESCC remains strong. Previous research has mainly focused on the basic research, with a focus on the mechanism of ncRNAs in the occurrence, development, diagnosis, treatment, and prognosis of ESCC. Combining current research with emerging disciplines to further explore its mechanisms of action or shifting the focus of research from preclinical research to clinical research based on diagnosis, treatment, and prognosis, will be the main breakthrough in this field in the future.

Systematical identification of key genes and regulatory genetic variants associated with prognosis of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) stands as a highly lethal malignancy characterized by pronounced recurrence and metastasis, resulting in a bleak 5-year survival rate. Despite extensive investigations, encompassing genome-wide association studies, the identification of robust prognostic markers has remained elusive. In this study, leveraging four independent data sets comprising 404 ESCC patients, we conducted a systematic analysis to unveil pivotal genes influencing overall survival. our meta-analysis identified 278 genes significantly associated with ESCC prognosis. Further exploration of the prognostic landscape involved an examination of expression quantitative trait loci for these genes, leading to the identification of six tag single nucleotide polymorphisms predictive of overall survival in a cohort of 904 ESCC patients. Notably, functional annotation spotlighted rs11227223, residing in the enhancer region of nuclear paraspeckle assembly transcript 1 (NEAT1), as a crucial variant likely exerting a substantive biological role. Through a series of biochemistry experiments, we conclusively demonstrated that the rs11227223-T allele, indicative of a poorer prognosis, augmented NEAT1 expression. Our results underscore the substantive role of NEAT1 and its regulatory variant in prognostic predictions for ESCC. This comprehensive analysis not only advances our comprehension of ESCC prognosis but also unveils a potential avenue for targeted interventions, offering promise for enhanced clinical outcomes.

DUSP4 maintains the survival and LSD1 protein stability in esophageal squamous cell carcinoma cells by inhibiting JNK signaling-dependent autophagy.

DUSP4 is a biomarker of esophageal squamous cell carcinoma (ESCC), which is responsible for the prognosis in ESCC. However, the underlying mechanism of DUSP4-regulated ESCC carcinogenesis is unknown. As a negative regulator of JNK, DUSP4 can inhibit autophagy, which contributes to tumorigenesis. This study aimed to explore the role of autophagy in DUSP4-regulated ESCC carcinogenesis. Our results showed that DUSP4 overexpression inhibited autophagy and promoted LSD1 protein expression in ESCC cells, while DUSP4 silencing showed the opposite effects. However, DUSP4 overexpression and silencing did not affect LSD1 mRNA expression. But the regulatory ability of DUSP4 overexpression on autophagy, death level, and LSD1 protein was reversed by rapamycin. In addition, DUSP4 overexpression inhibited JNK and Bcl2 phosphorylation and the dissociation of Bcl2-Beclin1 complex, while DUSP4 silencing promoted JNK and Bcl2 phosphorylation. Moreover, the regulatory ability of DUSP4 overexpression on autophagy, death, and LSD1 protein was reversed by JNK activator anisomycin. The xenograft assays also showed that DUSP4 overexpression-promoted ESCC tumor growth in vivo and LC3II and LSD1 protein expression in tumor tissues were reversed by rapamycin or anisomycin. Overall, DUSP4 inhibits Bcl2-Beclin1-autophagy signal transduction through the negative regulation of JNK, thus suppressing autophagic death and the autophagic degradation of LSD1 in ESCC, by which DUSP4 promotes ESCC carcinogenesis.