Diagnosis Of Esophageal Squamous Cell Carcinoma Research Articles

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.

Novel milestones for early esophageal carcinoma: From bench to bed.

Esophageal cancer (EC) is the seventh most common cancer worldwide, and esophageal squamous cell carcinoma (ESCC) accounts for the majority of cases of EC. To effectively diagnose and treat ESCC and improve patient prognosis, timely diagnosis in the initial phase of the illness is necessary. This article offers a detailed summary of the latest advancements and emerging technologies in the timely identification of ECs. Molecular biology and epigenetics approaches involve the use of molecular mechanisms combined with fluorescence quantitative polymerase chain reaction (qPCR), high-throughput sequencing technology (next-generation sequencing), and digital PCR technology to study endogenous or exogenous biomolecular changes in the human body and provide a decision-making basis for the diagnosis, treatment, and prognosis of diseases. The investigation of the microbiome is a swiftly progressing area in human cancer research, and microorganisms with complex functions are potential components of the tumor microenvironment. The intratumoral microbiota was also found to be connected to tumor progression. The application of endoscopy as a crucial technique for the early identification of ESCC has been essential, and with ongoing advancements in technology, endoscopy has continuously improved. With the advancement of artificial intelligence (AI) technology, the utilization of AI in the detection of gastrointestinal tumors has become increasingly prevalent. The implementation of AI can effectively resolve the discrepancies among observers, improve the detection rate, assist in predicting the depth of invasion and differentiation status, guide the pericancerous margins, and aid in a more accurate diagnosis of ESCC.

The CXCR4 might be a potential biomarker for esophageal squamous cell carcinoma: A meta-analysis.

To evaluate the relationship between CXCL12/CXCR4 and the progress, prognosis of esophageal squamous cell carcinoma (ESCC), providing evidence for potential early diagnosis, clinical treatment, prognosis evaluation, and therapeutic target of ESCC. Databases of PubMed, the Cochrane Library, Embase, and Web of Science were searched for the relationship between CXCL12/CXCR4 and clinicopathological characteristics and survival time of ESCC. Stata16.0 software was used to conduct meta-analysis. A total of 10 studies involving 1216 cases of patients with ESCC were included in our study. The results indicated that high-level expression of CXCR4 was significantly correlated with tumor differentiation [OR = 0.69, 95% confidence interval (CI): (0.50, 0.97)], tumor infiltration [OR = 0.39, 95% CI: (0.25, 0.61)], lymph node metastasis [OR = 0.36, 95% CI: (0.21, 0.61)], clinical stage [OR = 0.33, 95% CI: (0.24, 0.45)] of ESCC. The expression of CXCR4 was also significantly correlated with OS [HR = 2.00, 95% CI: (1.63, 2.45)] and disease-free survival [HR = 1.76, 95% CI: (1.44, 2.15)] in patients of ESCC after surgical resection. No significant relationship was observed between the expression of CXCL12 and the clinicopathological characteristics of ESCC. CXCR4 might be a potential biomarker for the progress and prognosis evaluation, and therapeutic target for ESCC.

VEGF, HIF-1α, and Metabolic Indicators in Esophageal Squamous Cell Carcinoma

Objective: To explore and analyze the expression and clinical significance of vascular endothelial growth factor (VEGF), hypoxia-inducible factor 1α (HIF-1α), and metabolic indicators in esophageal squamous cell carcinoma (ESCC). Methods: Sixty ESCC patients admitted to the hospital from October 2021 to October 2023 were selected as the ESCC group. Sixty normal healthy patients from the same period were chosen as the control group. Their serum samples and tissue samples were collected. Metabolic indicators of all study subjects were obtained based on the basic biochemical results upon admission. RT-PCR was utilized to detect the expression of VEGF and HIF-1α in ESCC tissues. Results: The expression of VEGF and HIF-1α in the ESCC T3+T4 group was significantly higher than that of the carcinoma in situ (Tis) group, T1+T2 group, and control group. Furthermore, the expression of HIF-1α was found to be related to the expression of VEGF, showing a significant correlation between the quantities. Significant differences in the levels of metabolic indicators were observed between the ESCC group and the control group (P &lt; 0.05). Conclusion: Metabolic indicators are associated with the onset of ESCC in patients. Abnormal lipid metabolism plays a crucial role in the occurrence and development of tumors. The expression of VEGF and HIF-1α in ESCC tissues significantly correlates with the tumor stage, providing a new reference for the diagnosis and treatment of ESCC.

Combining fecal microbiome and metabolomics reveals diagnostic biomarkers for esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the most predominant subtypes of esophageal cancer. The characteristics of the gut microbiome and its metabolites from patients with ESCC have not been adequately studied and discussed. In this study, 40 fecal samples (20 from ESCC patients and 20 from healthy controls) were analyzed by 16S rRNA gene sequencing and untargeted metabolomics. The data sets were analyzed individually and synthesized using various bioinformatics methods. Alpha and beta diversity indicated significant differences in microbial diversity and abundance between ESCC and healthy control feces. At the genus level, the abundance of Phascolarctobacterium, Sutterella, and Streptococcus was significantly increased in ESCC. At the genus level, linear discriminant analysis effect size identified two biomarkers: Bacteroides_stercoris and Prevotella_copri. Untargeted metabolomics analysis revealed 307 differential metabolites between ESCC and healthy control feces, with indoles and derivatives, tropane alkaloids, lipids, and lipid-like molecules in higher relative abundance in ESCC feces than in healthy control feces. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that unsaturated fatty acids (FAs), ascorbate and aldarate metabolism, and hypoxia-inducible factor 1 signaling pathway were significantly associated with differential metabolite. Phenylethanolamine and despropionyl p-fluoro fentanyl could be used as reliable biomarkers to differentiate ESCC from healthy control. The correlation analysis showed that Prevotella may be involved in the synthesis of fatty acyl, carboxylic acids and derivatives, benzenes and substituted derivatives, organic oxygenates, and indoles and derivatives as metabolites. Fusicatenibacter and Lachnospira may be involved in the degradation of indoles and derivatives. Alistipes, Agathobacter, and Parabacteroides may be involved in the synthesis of indoles and derivatives with strong contributions. There is an intricate relationship between the gut microbiome and the levels of several metabolites (e.g., fatty acyls, carboxylic acids and derivatives, indoles, and derivatives). Microbial-associated metabolites can be used as diagnostic biomarkers in therapeutic exploration. Further analysis revealed that Prevotella, Alistipes, Agathobacter, and Parabacteroides might promote ESCC by regulating the synthesis of indoles and their derivatives. The results of this study provide favorable evidence for the early diagnosis of ESCC and subsequent individualized treatment and targeted interventions.IMPORTANCEWe describe for the first time the differences in fecal microbiome composition and metabolites between patients with esophageal squamous cell carcinoma (ESCC) and healthy controls by 16S rRNA gene sequencing and untargeted metabolomics. The results of this study provide a favorable basis for the early diagnosis of ESCC and subsequent targeted interventional therapy.

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.

Exosomal MALAT1 promotes the proliferation of esophageal squamous cell carcinoma through glyoxalase 1-dependent methylglyoxal removal

In previous study we characterized the oncogenic role of long non-coding RNA MALAT1 in esophageal squamous cell carcinoma (ESCC), but the detailed mechanism remains obscure. Here we identified glyoxalase 1 (GLO1) as the most possible executor of MALAT1 by microarray screening. GLO1 is responsible for degradation of cytotoxic methylglyoxal (MGO), which is by-product of tumor glycolysis. Accumulated MGO may lead to glycation of DNA and protein, resulting in elevated advanced glycation end products (AGEs), while glyoxalase 1 detoxify MGO to alleviate its cytotoxic effect to tumor cells. GLO1 interfering led to accumulation of AGEs and following activation of DNA injury biomarkers, which lead to cell cycle arrest and growth inhibition. In silico analysis based on online database revealed abundant enrichment of histone acetylation marker H3K27ac in GLO1 promotor, and acetyltransferase inhibitor C646 declined GLO1 expression. Acetyltransferase KAT2B, which was also identified as a target of MALAT, mediated histone lysine acetylation of GLO1 promotor, which was confirmed by ChIP-qPCR experiment. Shared binding sites of miR-206 were found on MALAT1 and KAT2B mRNA. Dual-luciferase reporter assays confirmed interaction within MALAT1-miR-206-GLO1. Finally, we identified MALAT1 encapsuled by exosome from donor cells, and transferred malignant behaviors to recipient cells. The secreted exosomes may enter circulation, and serum MALAT1 level combined with traditional tumor markers showed potential power for ESCC diagnosis.

Nuclear-cytoplasmic translocation of SQSTM1/p62 protein enhances ESCC cell migration and invasion by stabilizing EPLIN expression

Esophageal squamous cell carcinoma (ESCC) is an aggressive malignant disease with a poor prognosis. We previously found that p62 presented a marked nuclear-cytoplasmic translocation in ESCC cells as compared that in normal esophageal epithelial cells, but its effects on ESCC cells remain unclear. This study aims to clarify the impacts of different cellular localization of p62 on the function of ESCC cells and the underlying molecular mechanisms. We here demonstrated that cytoplasmic p62 enhances the migration and invasion abilities of esophageal cancer cells, whereas nuclear p62 has no effect. We further explored the interaction protein of p62 by using GST pull-down experiment and identified EPLIN as a potential protein interacting with p62. In addition, reducing EPLIN expression significantly inhibited the migration and invasion of ESCC cells, which were rescued when EPLIN expression was restored after the p62 knockdown. At a molecular level, p62 in cytoplasm positively regulated the expression of EPLIN via enhancing its protein stability. Data from the TCGA and GEO database displayed a significant up-regulation of EPLIN mRNA expression in ESCC tissues compared with corresponding paired esophageal epithelial samples. Our findings present evidence that the nuclear-cytoplasmic translocation of p62 protein contributes to an aggressive malignancy phenotype, providing candidate molecular biomarkers and potential molecular targets for the diagnosis and treatment of ESCC.

Image Enhanced Endoscopy in Esophageal Squamous Cell Carcinoma

Esophageal Squamous Cell Carcinoma (ESCC) accounts for a significant portion of esophageal cancer cases worldwide, particularly in high-risk regions like China, Iran, and eastern Africa. It is often diagnosed at advanced stages, leading to poor prognosis and limited treatment options. Image-enhanced endoscopy enables precise visualization of abnormal mucosa, aiding in targeted biopsies for early detection of ESCC and reducing unnecessary sampling. Various techniques have emerged including lugol’s chromoendoscopy, narrow-band imaging, confocal laser endomicroscopy, and high-resolution microendoscopy. This article also discusses advancements in post-processing imaging technology and the novel role of Artificial Intelligence (AI) in improving diagnostic accuracy. While image enhanced endoscopy is promising, challenges such as training, standardization, and long-term validation remain. Implementing image enhanced endoscopy, combined with advancements in AI, has the potential to transform ESCC diagnosis and significantly improve patient outcomes, especially in high-risk populations.

AKAP12 inhibits esophageal squamous carcinoma cell proliferation, migration, and cell cycle via the PI3K/AKT signaling pathway

Esophageal squamous cell carcinoma (ESCC) consistently ranks as one of the most challenging variants of squamous cell carcinomas, primarily due to the lack of effective early detection strategies. We herein aimed to elucidate the underlying mechanisms and biological role associated with A-kinase anchoring protein 12 (AKAP12) in the context of ESCC. Bioinformatic analysis had revealed significantly lower expression level of AKAP12 in ESCC tissue samples than in their non-cancerous counterparts. To gain deeper insights into the potential role of AKAP12 in the progression of ESCC, we conducted a single-gene set enrichment analysis of AKAP12 on ESCC datasets. Our findings suggested that AKAP12 exhibits functions inhibiting cell cycle progression, tumor proliferation, and epithelial-mesenchymal transition. To further validate our findings, we subjected ESCC cell lines to AKAP12 overexpression using CRISPR/Cas9-SAM. In vitro analyses demonstrated that increased expression of AKAP12 significantly reduced cell proliferation, migration, and cell cycle progression. Simultaneously, genes associated with this biological role undergo corresponding regulatory shifts. These observations provided valuable insights into the biological role played by AKAP12 in ESCC progression. In summary, AKAP12 shows promise as a new potential biomarker for early ESCC diagnosis, offering potential advantages for subsequent therapeutic intervention and disease management.