Diagnosis Of Esophageal Squamous Cell Carcinoma Research Articles

The impact of Artificial Intelligence in detecting esophageal squamous cell carcinoma: advances and challenges

This review explores the transformative role of artificial intelligence (AI), especially through deep learning (DL) and convolutional neural networks (CNNs), in the early detection of esophageal squamous cell carcinoma (ESCC). ESCC presents significant diagnostic challenges due to its aggressive nature and high mortality, often diagnosed at advanced stages. Traditional endoscopic methods, while essential, suffer from limitations like interobserver variability, especially for subtle early lesions. AI-based systems have demonstrated high sensitivity in identifying these early neoplasms, reducing diagnostic discrepancies and enhancing precision. Through a bibliographic review, the article highlights recent AI advancements, particularly in utilizing CNNs to identify early-stage ESCC. These tools have shown the potential to improve diagnostic accuracy even among less experienced endoscopists and provide critical support in clinical decision-making, including biopsy guidance and lesion mapping in chromoendoscopy and narrow-band imaging (NBI). Despite promising results, challenges persist in AI’s practical application, such as the need for extensive data for training, clinical validation, and standardization across different endoscopic equipment. The study underscores the need for large-scale multicenter studies and standardization to solidify AI’s role in ESCC diagnosis. It envisions a future where AI not only serves as a diagnostic support tool but becomes integral to endoscopic practices, requiring continued technological development, ethical considerations, and regulatory frameworks to maximize clinical benefit.

Cancer-associated fibroblasts derived-exosomal circ_0076535 promotes esophageal squamous cell carcinoma progression

Background Esophageal cancer (EC) is a common malignant tumor of the digestive tract and an important health-related problem in many developing countries. Esophageal squamous cell carcinoma (ESCC) is the most common subtype of EC. The cancer-associated fibroblasts (CAFs) are the major stromal cells in ESCC microenvironment. They play important role in ESCC proliferation, metastasis, angiogenesis and chemotherapy resistance through paracrine processes. However, the roles of circRNAs enriched in CAF-derived exosmes have not been reported. Objective To explore the mechanisms of how CAF affects ESCC proliferation and metastasis through paracrine processes and to investigate the role of circRNAs enriched in CAF-derived exosomes. Methods Exosomes were isolated from the conditional medium of CAF using differential ultracentrifugation, and then validated by Nanosight analysis. Exosome secretion inhibitor-GW4869 validates the pro-carcinogenic role of exosomes. The qRT-PCR showed the highest expression of circ_0076535 in the exosomal CircRNA, and knockdown of it confirmed its function. Online bioinformatics tool was utilized to predict the potential target gene of circ_0076535, and captured miR-145-5p as the target gene with high predictive value. The targeting association between miR-145-5p and circ_0076535 is further confirmed by the dual luciferase reporter experiment. The stimulation of tumour development and EMT by the CAF-derived exosome circ_0076535 is further validated in vivo. Results In our research, we found that CAF-derived exosomes increased proliferation, migration, invasion and EMT in ESCC cells. Circ_0076535 was highly enriched in CAF-exosomes and transferred into ESCC cells directly depend on internalization of exosomes. CAF-exosomal circ_0076535 increased the level of circ_0076535 in ESCC cells and induced EMT. Mechanistic experiments revealed circ_0076535 acted as a sponge to absorb miR-145-5p and activated NF-κB signaling pathway. Conclusions Conclusively, CAF-exosomal circ_0076535 promoted the ESCC progression via miR-145-5p/NF-κB axis and expected to be a potential biomarker for early diagnosis and treatment of ESCC.

LncRNAs SOX2-OT and NEAT1 act as a potential biomarker for esophageal squamous cell carcinoma

Despite strides in diagnostic and therapeutic approaches for ESCC, patient survival rates remain relatively low. Recent studies highlight the pivotal role of long non-coding RNAs (lncRNAs) in regulating diverse cellular activities in humans. Dysregulated lncRNAs have emerged as potential diagnostic indicators across various cancers, including ESCC. However, further research is necessary to effectively leverage ESCC-associated lncRNAs in clinical settings. Understanding their clinical significance for ESCC diagnosis and their mechanisms can pave the way for more effective therapeutic strategies. Our qRT-PCR analysis revealed significant downregulation of SOX2-OT (~ 2.02-fold) and NEAT1 (~ 1.53-fold) in ESCC blood samples. These lncRNAs show potential as biomarkers for distinguishing ESCC patients from healthy individuals, with ROC curves and AUC values of 0.736 for SOX2-OT and 0.621 for NEAT1. Further analysis examined the correlation between SOX2-OT and NEAT1 expression and various clinicopathological factors, including age, gender, smoking, alcohol use, hot beverage intake, tumor grade, and TNM stages. In-silico studies highlighted their roles in miRNA sponging via mTOR and MAPK pathways, while co-expression network analysis identified associated genes. This research paves the way for future studies on ESCC prognosis using SOX2-OT and NEAT1 as predictive markers. By thoroughly investigating the functions of these lncRNAs, we aim to deepen our understanding of their potential as diagnostic markers and their role in facilitating effective therapeutic interventions for esophageal squamous cell carcinoma (ESCC) within clinical contexts.

Novel miRNA markers and their mechanism of esophageal squamous cell carcinoma (ESCC) based on TCGA

MicroRNAs(miRNAs) are promising biomarkers for early esophageal squamous cell carcinoma (ESCC) detection and prognostic prediction. This study aimed to explore the potential biomarkers and molecular pathogenesis in the early diagnosis of ESCC. Firstly, 48 differentially expressed miRNAs (DEMs) and 1319 differentially expressed genes (DEGs) were identified between 94 ESCC tissues and 13 normal esophageal tissues in TCGA. From miRNA–mRNA regulatory network, there are 6558 target genes of the 48 DEMs, where 400 target genes are also among 1319 DEGs. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment indicate that the 400 DEGs significantly enriched in cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and oocyte meiosis. And there are 66 DEGs among these six biological pathways, which we called GO-DEGs. From miRNA–mRNA regulatory network, 32 DEMs regulated the 66 GO-DEGs, where 22 DEMs were verified by different types of experiments in ESCC tissues, cells, or serum from the literature. For the other novel 10 DEMs, single-factor Cox regression analysis show that only hsa-miR-34b-3p showed no significant correlation with the overall survival of ESCC patients. Finally, we obtained the novel 9 ESCC-related DEMs, where three are down-regulated, and six are up-regulated. We analyzed the expression trends of target genes for five miRNAs and identified three significantly different miRNAs (hsa-miR-205-3p, hsa-miR-452-3p, and hsa-miR-6499-3p) confirmed by qPCR. Moreover, the stage-specific miRNAs were also suggested. These three qPCR validated miRNAs are also specific to the early stages of ESCC: hsa-miR-452-3p is specific to Stage I, II and III; hsa-miR-205-3p is specific in Stage II and III; and hsa-miR-6499-3p is Stage II specific. They might be the potential biomarkers for ESCC stage diagnosis. This study identified three novel miRNA markers potentially related to the diagnosis of ESCC and participated in the occurrence and development of ESCC through cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and signaling pathway for oocyte meiosis.

Exploring the clinicopathological characteristics of submucosal tumor-like esophageal squamous cell carcinoma and the diagnostic significance of endoscopic ultrasound: a comprehensive analysis.

Completely intramural growth submucosal squamous cell carcinoma of the esophagus, also known as SMT-like esophageal squamous cell carcinoma (ESCC), represents a rare and distinct form of esophageal cancer. Its white light endoscopic manifestations resemble those of esophageal subepithelial lesions, and biopsy pathology is often negative, leading to potential oversight or misdiagnosis. This study aimed to comprehensively summarize the clinicopathological and endoscopic ultrasound (EUS) characteristics of patients with SMT-like ESCC while also evaluating the immunohistochemical expression of these patient. This study collected clinical data, including demographic and clinicopathological data, as well as EUS findings, from six patients with SMT-like ESCC. Immunohistochemical analysis was also conducted on tumor tissues to assess the expression of CK7, CK19, CK20, TTF-1, SMA, S-100, Melan-A, CD117, Mucin (MUC) 2, and MUC5. In EUS, SMT-like ESCC is characterized by nonuniform hypoechoic lesions with indistinct borders, often exhibiting a burr or serrated appearance. Most of these lesions involved multiple levels. Cytological specimens obtained through EUS-guided fine needle aspiration (EUS-FNA) revealed suspected squamous cell carcinoma with positive expression of CK5/6, P40, and P63, further confirming the diagnosis of ESCC. Additionally, four patients exhibited CK7+/CK20- immune-expression profiles, and all patients had positive CK19 expression. TTF-1, SMA, S-100, Melan-A, CD117, MUC2, and MUC5 were negative. Combining EUS with EUS-FNA is a valuable approach for diagnosing and differentiating SMT-like ESCC. Furthermore, the characteristic CK7+/CK20- immune profile suggested a potential origin from the esophageal submucosa glands.

Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era

Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer with a poor prognosis. Early diagnosis and prognosis assessment are crucial for improving the survival rate of ESCC patients. With the advancement of artificial intelligence (AI) technology and the proliferation of medical digital information, AI has demonstrated promising sensitivity and accuracy in assisting precise detection, treatment decision-making, and prognosis assessment of ESCC. It has become a unique opportunity to enhance comprehensive clinical management of ESCC in the era of precision oncology. This review examines how AI is applied to the diagnosis, treatment, and prognosis assessment of ESCC in the era of precision oncology, and analyzes the challenges and potential opportunities that AI faces in clinical translation. Through insights into future prospects, it is hoped that this review will contribute to the real-world application of AI in future clinical settings, ultimately alleviating the disease burden caused by ESCC.

TRIM33 promotes glycolysis through regulating P53 K48-linked ubiquitination to promote esophageal squamous cell carcinoma growth

Esophageal squamous cell carcinoma (ESCC) is a common fatal malignant tumor of the digestive tract; however, its pathogenic mechanism is unknown and lacks specific molecular diagnosis and treatment. Therefore, it is particularly important to identify new tumor biomarkers to enhance the early diagnosis and molecular-targeted therapy of ESCC. Here, we found that the E3 ubiquitin ligase Tripartitemotif-containing33 (TRIM33) is highly expressed in ESCC tissues and cell lines, and is associated with adverse clinical outcomes. We determined that TRIM33 drives aerobic glycolysis to promote tumor growth in vivo and in vitro. In terms of mechanism, TRIM33 binds to p53 to inhibit its stability and promote the expression of downstream glycolysis target genes GLUT1, HK2, PKM2, and LDHA. In addition, TRIM33 promotes the polyubiquitination of P53 K48-linked and proteasome degradation. Further studies have shown that the K351 site of P53 is the key site mediating the ubiquitination of P53 K48-linked to promote aerobic glycolysis in ESCC and tumor cell growth. Our results reveal that the TRIM33-P53 signal axis regulates glycolysis during ESCC and may provide a new perspective for the diagnosis and treatment of ESCC.

Evaluating the discrepancies between evidence-based and community standard practices in the endoscopic diagnosis of esophageal squamous cell carcinoma: a survey study.

The practice of endoscopic diagnosis of esophageal squamous cell carcinoma (ESCC) often diverges from evidence-based standards due to various factors, including inadequate dissemination of evidence or a mismatch between evidence and real-world contexts. This survey aimed to identify discrepancies between evidence-based standard practices and community standard practices for ESCC among endoscopists. An online survey targeting endoscopists who perform upper gastrointestinal endoscopy at least weekly was conducted to collect data on clinical practices related to ESCC diagnosis. The survey, comprising 20 questions, was disseminated through multiple professional networks. Descriptive statistical analysis and logistic regression were performed to analyze the data. Data from 819 endoscopists were included in the analyses. Notably, a significant proportion employed narrow-band imaging/blue-laser imaging over iodine staining, and preferences varied based on risk assessment for ESCC. In total, 64.0% of endoscopists primarily used iodine solution at a concentration of 1% or less, while 96.5% of endoscopists performed an observation of the oral cavity and the pharynx when conducting upper gastrointestinal endoscopies on individuals at high risk of ESCC. The surveillance interval for metachronous multiple ESCCs was most commonly every 6months, followed by every 12months. In addition, most physicians conducted surveillance of metastatic recurrence at 6-month intervals. This survey highlights significant gaps between evidence-based and community standard practices in the endoscopic diagnosis of ESCC. These findings underscore the need for enhanced dissemination of evidence-based guidelines and consideration of real-world clinical contexts to bridge these gaps and optimize patient care.

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.

Expression of Interleukin-8, Interleukin-12 and Interleukin-13 in Esophageal Squamous Cell Carcinoma: Biomarker Potentiality and Prognostic Significance.

Interleukin-8 (IL8), Interleukin-12 (IL12) and Interleukin-13 (IL13) are cytokines that play regulatory role in cancer pathogenesis. We analysed their expression profile to evaluate as molecular biomarkers of esophageal squamous cell carcinoma (ESCC) and their association with different parameters and patient survival. Expression analysis was performed by Real time quantitative polymerase chain reaction and receiver operating characteristic (ROC) curve analysis was done. The expression profiles were associated with different clinicopathological and dietary factors. Survival and hazard analysis were also performed. IL8 expression showed upregulation in tissue (p = 0.000) and blood samples (p = 0.481), IL12 expression showed downregulation in tissue samples (p = 0.064) and upregulation in blood samples (p = 0.689) and IL13 expression showed upregulation in tissue (p = 0.000) and blood samples (p = 0.006). IL13 expression in tissue showed the highest area under the curve (AUC) value (0.773) for ESCC diagnosis, followed by IL8 expression in tissue (0.704) and IL13 expression in blood (0.643). This study also reveals the correlation of studied cytokines in tissue and blood level. Different clinicopathological and dietary factors showed significant association (p < 0.05) with IL8, IL12 and IL13 expression and with survival of ESCC patients. IL8 expression in blood and IL12 expression in tissue and blood showed significant association (p < 0.05) with patient survival. Altered expression of IL8, IL12 and IL13 may be associated with ESCC progression. Overexpression of IL8 and IL13 in tissue samples may be potential biomarkers for ESCC screening. Additionally, both survival and hazard analysis data indicate the effects of different parameters on the prognosis of ESCC patients.

Leveraging cfDNA fragmentomic features in a stacked ensemble model for early detection of esophageal squamous cell carcinoma

In this study, we develop a stacked ensemble model that utilizes cell-free DNA (cfDNA) fragmentomics for the early detection of esophageal squamous cell carcinoma (ESCC). This model incorporates four distinct fragmentomics features derived from whole-genome sequencing (WGS) and advanced machine learning algorithms for robust analysis. It is validated across both an independent validation cohort and an external cohort to ensure its generalizability and effectiveness. Notably, the model maintains its robustness in low-coverage sequencing environments, demonstrating its potentials in clinical settings with limited sequencing resources. With its remarkable sensitivity and specificity, this approach promises to significantly improve the early diagnosis and management of ESCC. This study represents a substantial step forward in the application of cfDNA fragmentomics in cancer diagnostics, emphasizing the need for further research to fully establish its clinical efficacy.

Prognostic factors for esophageal respiratory fistula in unresectable esophageal squamous cell carcinoma treated with radiotherapy

Limited studies have focused on the prognostic factors of esophageal respiratory fistula (ERF) associated with radiotherapy in patients with unresectable esophageal squamous cell carcinoma (ESCC). Between January 1st, 2014 and January 1st, 2021, we included patients who were initially diagnosed with unresectable ESCC and underwent radiotherapy. All patients were followed up for a period of 2 years after completing their radiotherapy treatment. The primary outcomes of the study were defined as death or severe adverse events. The survival curves of ERF were calculated using the Kaplan–Meier method. Cox proportional hazards model was employed to calculated the prognostic factors. A cohort of 232 patients underwent radiotherapy, of whom 32 patients experienced ERF. The median period from initial diagnosis of ESCC to ERF was 5.75 months, and the median period from ERF to the primary outcome was 4.6 weeks. Neck + upper chest location (odds ratio [OR] 3.305), high T stage (OR 1.765), esophageal stenosis (OR 1.073), high neutrophil to lymphocyte ratio (NLR) (OR 1.384) and platelet to lymphocyte ratio (PLR) (OR 1.765) were risk factors for the occurrence of ERF. Cox regression analysis suggested that tumor location (hazards ratio [HR] 3.572, 95% confidence interval [CI] 2.467–5.1), high T stage (HR 4.050, 95% CI 2.812–5.831), esophageal stenosis (HR 2.643, 95% CI 1.753–3.983), high PLR (HR 2.541, 95% CI 1.868–3.177) were independent prognostic factors for poor survival. Esophageal stenosis, neck + upper chest tumor location, high T stage and PLR predicted the prognosis of ERF in ESCC patients undergoing radiotherapy.

Molecular insights into programmed cell death in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a deadly type of esophageal cancer. Programmed cell death (PCD) is an important pathway of cellular self-extermination and is closely involved in cancer progression. A detailed study of its mechanism may contribute to ESCC treatment. We obtained expression profiling data of ESCC patients from public databases and genes related to 12 types of PCD from previous studies. Hub genes in ESCC were screened from PCD-related genes applying differential expression analysis, machine learning analysis, linear support vector machine (SVM), random forest and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. In addition, based on the HTFtarget and TargetScan databases, transcription factors (TFs) and miRNAs interacting with the hub genes were selected. The relationship between hub genes and immune cells were analyzed using the CIBERSORT algorithm. Finally, to verify the potential impact of the screened hub genes on ESCC occurrence and development, a series of in vitro cell experiments were conducted. We screened 149 PCD-related DEGs, of which five DEGs (INHBA, LRRK2, HSP90AA1, HSPB8, and EIF2AK2) were identified as the hub genes of ESCC. The area under the curve (AUC) of receiver operating characteristic (ROC) curve of the integrated model developed using the hub genes reached 0.997, showing a noticeably high diagnostic accuracy. The number of TFs and miRNAs regulating hub genes was 105 and 22, respectively. INHBA, HSP90AA1 and EIF2AK2 were overexpressed in cancer tissues and cells of ESCC. Notably, INHBA knockdown suppressed ECSS cell migration and invasion and altered the expression of important apoptotic and survival proteins. This study identified significant molecules with promising accuracy for the diagnosis of ESCC, which may provide a new perspective and experimental basis for ESCC research.

MiR-493-5p Silenced by DNA Methylation Promotes Angiogenesis via Exosomes and VEGF-A-Mediated Intracellular Cross-Talk Between ESCC Cells and HUVECs.

Exosomal microRNAs (miRNAs) in the tumor microenvironment play crucial roles in tumorigenesis and tumor progression by participating in intercellular cross-talk. However, the functions of exosomal miRNAs and the mechanisms by which they regulate esophageal squamous cell carcinoma (ESCC) progression are unclear. RNA sequencing and GEO analysis were conducted to identify candidate exosomal miRNAs involved in ESCC development. Receiver operating characteristic curve analysis was performed to assess the diagnostic value of plasma exosomal miR-493-5p. EdU, tube formation and Transwell assays were used to investigate the effects of exosomal miR-493-5p on human umbilical vein endothelial cells (HUVECs). A subcutaneous xenograft model was used to evaluate the antitumor effects of miR-493-5p and decitabine (a DNA methyltransferase inhibitor). The relationship between miR-493-5p and SP1/SP3 was revealed via a dual-luciferase reporter assay. A series of rescue assays were subsequently performed to investigate whether SP1/SP3 participate in exosomal miR-493-5p-mediated ESCC angiogenesis. We found that miR-493-5p expression was notably reduced in the plasma exosomes of ESCC patients, which showed the high potential value in early ESCC diagnosis. Additionally, miR-493-5p, as a candidate tumor suppressor, inhibited the proliferation, migration and tube formation of HUVECs by suppressing the expression of VEGFA and exerted its angiostatic effect via exosomes. Moreover, we found that SP1/SP3 are direct targets of miR-493-5p and that re-expression of SP1/SP3 could reverse the inhibitory effects of miR-493-5p. Further investigation revealed that miR-493-5p expression could be regulated by DNA methyltransferase 3A (DNMT3A) and DNMT3B, and either miR-493-5p overexpression or restoration of miR-493-5p expression with decitabine increased the antitumor effects of bevacizumab. Exosomal miR-493-5p is a highly valuable ESCC diagnosis marker and inhibits ESCC-associated angiogenesis. miR-493-5p can be silenced via DNA methylation, and restoration of miR-493-5p expression with decitabine increases the antitumor effects of bevacizumab, suggesting its potential as a therapeutic target for ESCC treatment.

Keratin 17 and Collagen type 1 genes: Esophageal cancer molecular marker discovery and evaluation.

One hundred eighty pairs of tissues of esophageal squamous cell carcinoma (ESCC) were tested by the transcriptome sequencing in order to explore etiology factors. The chi-square test and correlation analysis demonstrated that the relative expression levels of keratin 17 (KRT17) and collagen type I α1 chain (COL1A1) were significantly higher in EC with diabetes. Expression of KRT17 was correlated with blood glucose (r = 0.204, p = 0.001) and tumor size (r = -0.177, p = 0.038) in patients. COL1A1 correlated with age (r = -0.170, p = 0.029) and blood glucose levels (r = 0.190, p = 0.015). Experimental results of qRT-PCR: KRT17 and COL1A1 genes were highly expressed in ESCC (p < 0.05). When the two genes were used as a combination test, the positive detection rate of EC was 90.6%, and the ROC curve had greater power. The KRT17 and COL1A1 genes had the potential to be biomarkers for the diagnosis of ESCC.

Discovery and validation of combined biomarkers for the diagnosis of esophageal intraepithelial neoplasia and esophageal squamous cell carcinoma

Early diagnosis and intervention of esophageal squamous cell carcinoma (ESCC) can improve the prognosis. The purpose of this study was to identify biomarkers for ESCC and esophageal precancerous lesions (intraepithelial neoplasia, IEN). Based on the proteomic and genomic data of esophageal tissue including previously reported data, up-regulated proteins with copy number amplification in esophageal cancer were screened as candidate biomarkers. Five proteins, including KDM2A, RAD9A, ECT2, CYHR1 and TONSL, were confirmed by immunohistochemistry on ESCC and normal esophagus (NE). Then, we investigated the expression of 5 proteins in 236 participants (60 NEs, 93 IENs and 83 ESCCs) which were randomly divided into training set and test set. When distinguishing ESCC from NE, the area under curve (AUC) of the multiprotein model was 0.940 in the training set, while the lowest AUC of a protein was 0.735. In the test set, the results were similar. When distinguishing ESCC from IEN or distinguishing IEN from NE, the diagnostic efficiency of the multi-protein models were also improved compared with that of single protein. Our findings suggest that combined detection of KDM2A, RAD9A, ECT2, CYHR1 and TONSL can be used as potential biomarkers for the early diagnosis of ESCC and precancerous lesion development prediction. SignificanceCandidate biomarkers including KDM2A, RAD9A, ECT2, CYHR1 and TONSL screened by integrating genomic and proteomic data from the esophagus can be used as potential biomarkers for the early diagnosis of esophageal squamous cell carcinoma and precancerous lesion development prediction.

Leveraging cfDNA fragmentomic features in a stacked ensemble model for early detection of esophageal squamous cell carcinoma.

4054 Background: In this study, we developed a stacked ensemble model that leverages cell-free DNA (cfDNA) fragmentation for the early detection of esophageal squamous cell carcinoma (ESCC). The model combined four fragmentomics features obtained from whole genome sequencing (WGS) and employed four machine learning algorithms. We evaluated the model’s generalizability in an independent validation cohort and an external cohort collected at different center. Additionally, the model’s robustness and repeatability were assessed across low coverage and repeated measured samples. The results underscore the promising potential of our model as an effective strategy for early diagnosis and management of ESCC in clinical settings. Methods: 256 healthy individuals and 243 patients diagnosed with esophageal cancer were enrolled in this study, including 47 healthy participants and 44 patients in the external cohort. Plasma samples from all participants were profiled by whole-genome sequencing (WGS). Fragmentomic features encompassed copy number variation (CNV), fragmentation size coverage (FSC), fragmentation size distribution (FSD), and nucleosome positioning (NP) were incorporated alongside machine learning models to develop an optimized classification model. The model generated a cancer score ranging from 0 to 1 for each cancer and noncancer sample, with a score closer to 1 indicating a higher probability of cancer. The performance of this model was assessed using an independent validation cohort and an external cohort, and model’s robustness and reproducibility were examined. Results: A stacked ensemble model was developed by integrating four cfDNA features and four machine learning algorithms. This integrated model exhibiting remarkable sensitivity of 91.8% (89/97) and specificity of 98.1% (102/104), and AUC of 0.986 in the independent validation cohorts using the cut-off of 0.69 selected at a specificity level of 98% (105) in the training cohort. The external cohort demonstrated a sensitivity of 86.4% (38/44) and a specificity of 95.7% (45/47) with the same cut-off. The model's performance remained consistent even at low sequencing coverage depths of 0.5× (AUC 0.978), providing valuable insights into the resilience and stability of our methodology and ascertained its practical applicability in scenarios with limited sequencing resources or constraints. Furthermore, our model demonstrated sensitivity in identifying early pathological features, with a sensitivity of 94.1% (16/17) for stage I and 91.4% (53/58) for tumors smaller than 3 cm. Conclusions: A stacked ensemble model was implemented in this study, utilizing cfDNA fragmentomics features with exceptional sensitivity for early detection of esophageal squamous cell carcinoma. The anticipated impact of this model is the enhancement of early detection strategies for esophageal cancer in clinical setting.

IL-1β promotes esophageal squamous cell carcinoma growth and metastasis through FOXO3A by activating the PI3K/AKT pathway

Esophageal cancer is a common type of cancer that poses a significant threat to human health. While the pro-inflammatory cytokine IL-1β has been known to contribute to the development of various types of tumors, its role in regulating esophageal cancer progression has not been extensively studied. Our studies found that the expression of IL-1β and FOXO3A was increased in esophageal squamous cell carcinoma (ESCC). IL-1β not only increased the proliferation, migration, and invasion of two ESCC cell lines but also promoted tumor growth and metastasis in nude mice. We also observed that IL-1β and FOXO3A regulated the process of epithelial-mesenchymal transition (EMT) and autophagy. The PI3K/AKT pathway was found to be involved in the changes of FOXO3A with the expression level of IL-1β. The AKT agonist (SC79) reversed the reduction of FOXO3A expression caused by the knockdown of IL-1β, indicating that IL-1β plays a role through the PI3K/AKT/FOXO3A pathway. Furthermore, the knockdown of FOXO3A inhibited ESCC development and attenuated the pro-cancer effect of overexpressed IL-1β. Targeting IL-1β and FOXO3A may be potentially valuable for the diagnosis and treatment of ESCC.

The m6A reader IGF2BP2 promotes esophageal cell carcinoma progression by enhancing EIF4A1 translation

Esophageal squamous cell carcinoma (ESCC) is one of most prevalent cancers worldwide, especially in China. Lacking in depth mechanism study, effective targets and therapeutics are desperately needed in the clinic. RNA-binding proteins (RBPs) mediate the localization, stability, and translation of the target transcripts and fine-tune the physiological functions of the proteins encoded. Bioinformatics analysis revealed that IGF2BPs were highly expressed in ESCC tissues and at least participated in the regulation of cell proliferation of ESCC cells. Biological researches demonstrated that IGF2BP2 promoted the cell proliferation, migration and invasion of ESCC KYSE30 and KYSE450 cells. IGF2BP2 could bind to EIF4A1 mRNA by recognition of m6A sites and enhanced translation of EIF4A1. IGF2BPs, as m6A reader, IGF2BPs were oncogenic genes in ESCC by regulating the expression of EIF4A1 through m6A sites. IGF2BP2, EIF4A1 and their targets could serve as potential biomarkers and therapeutic targets for ESCC, offering promising novel approaches for the diagnosis and treatment of ESCC.

PPP1r18 promotes tumor progression in esophageal squamous cell carcinoma by regulating the calcineurin-mediated ERK pathway.

Esophageal cancer is one of the most common malignant tumors, and the 5-year overall survival rate is only 20%. Esophageal squamous cell carcinoma (ESCC) is the primary histological type of esophageal carcinoma in China. Protein phosphatase 1 regulatory subunit 18 (PPP1r18) is one of the actin-regulatory proteins and is able to bind to protein phosphatase 1 catalytic subunit alpha (PPP1CA). Yet, little is known about the role of PPP1r18 in ESCC. This study aimed to elucidate the biological functions of PPP1r18 in the ESCC progression. Clinical samples first confirmed that PPP1r18 expression was upregulated in ESCC, and PPP1r18 was correlated with tumor invasion depth, lymph node metastasis, distant metastasis and reduced overall survival. We then observed that PPP1r18 overexpression enhanced cell proliferation in vitro and in vivo. Mechanistically, PPP1r18 regulated tumor progression of ESCC through activating the calcineurin-mediated ERK pathway, rather than binding to PPP1CA. Collectively, our results suggest that PPP1r18 promotes ESCC progression by regulating the calcineurin-mediated ERK pathway. PPP1r18 might be a potential target for the diagnosis and treatment of ESCC.