Modern Diagnosis of Early Esophageal Cancer: From Blood Biomarkers to Advanced Endoscopy and Artificial Intelligence

Liquid biopsy of oesophageal squamous cell carcinoma: implications in diagnosis, prognosis, and treatment monitoring

Oesophageal squamous cell carcinoma (ESCC) is a common malignant tumour of the gastrointestinal tract. Early detection and access to appropriate treatment are crucial for the long-term survival of patients. However, limited diagnostic and monitoring methods are available for identifying early stage ESCC. Endoscopic screening and surgical resection are commonly used to diagnose and treat early ESCC. However, these methods have disadvantages, such as high recurrence, lethality, and mortality rates. Therefore, methods to improve early diagnosis of ESCC and reduce its mortality rate are urgently required. In 1961, Gary et al. proposed a novel liquid biopsy approach for clinical diagnosis. This involved examining exosomes, circulating tumour cells, circulating free DNA, and circulating free RNA in body fluids. The ability of liquid biopsy to obtain samples repeatedly, wide detection range, and fast detection speed make it a feasible option for non-invasive tumour detection. In clinical practice, liquid biopsy technology has gained popularity for early screening, diagnosis, treatment efficacy monitoring, and prognosis assessment. Thus, this is a highly promising examination method. However, there have been no comprehensive reviews on the four factors of liquid biopsy in the context of ESCC. This review aimed to analyse the progress of liquid biopsy research for ESCC, including its classification, components, and potential future applications.

The 1st EoETALY Consensus on the Diagnosis and Management of Eosinophilic Esophagitis - Definition, Clinical Presentation and Diagnosis

Eosinophilic esophagitis (EoE) is a chronic type 2-mediated inflammatory disease of the esophagus that represents the most common eosinophilic gastrointestinal disease. Experts in the field of EoE across Italy (i.e., EoETALY Consensus Group) including gastroenterologists, endoscopists, allergologists/immunologists, and paediatricians conducted a Delphi process to develop updated consensus statements for the management of patients with EoE and update the previous position paper of the Italian Society of Gastroenterology (SIGE) in light of recent evidence. Grading of the strength and quality of the evidence of the recommendations was performed using accepted GRADE criteria. The guideline is divided in two documents: Part 1 includes three chapters, namely 1) definition, epidemiology, and pathogenesis; 2) clinical presentation and natural history, and 3) diagnosis, while Part 2 includes two chapters: 4) treatment and 5) monitoring and follow-up. This document has received the endorsement of three Italian national societies including the SIGE, the Italian Society of Neurogastroenterology and Motility (SINGEM), and the Italian Society of Allergology, Asthma, and Clinical Immunology (SIAAIC). With regards to patients' involvement, these guidelines involved the contribution of members of ESEO Italia, the Italian Association of Families Against EoE.

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.

Artificial Intelligence Tools for the Diagnosis of Eosinophilic Esophagitis in Adults Reporting Dysphagia: Development, External Validation, and Software Creation for Point-of-Care Use

BACKGROUND

Despite increased awareness of eosinophilic esophagitis (EoE), the diagnostic delay has remained stable over the past 3 decades. There is a need to improve the diagnostic performance and optimize resources allocation in the setting of EoE.

OBJECTIVE

We developed and validated 2 point-of-care machine learning (ML) tools to predict a diagnosis of EoE before histology results during office visits.

METHODS

We conducted a multicenter study in 3 European tertiary referral centers for EoE. We built predictive ML models using retrospectively extracted clinical and esophagogastroduodenoscopy (EGDS) data collected from 273 EoE and 55 non-EoE dysphagia patients. We validated the models on an independent cohort of 93 consecutive patients with dysphagia undergoing EGDS with biopsies at 2 different centers. Models' performance was assessed by area under the curve (AUC), sensitivity, specificity, and positive and negative predictive values (PPV and NPV). The models were integrated into a point-of-care software package.

RESULTS

The model trained on clinical data alone showed an AUC of 0.90 and a sensitivity, specificity, PPV, and NPV of 0.90, 0.75, 0.80, and 0.87, respectively, for the diagnosis of EoE in the external validation cohort. The model trained on a combination of clinical and endoscopic data showed an AUC of 0.94, and a sensitivity, specificity, PPV, and NPV of 0.94, 0.68, 0.77, and 0.91, respectively, in the external validation cohort.

CONCLUSION

Our software-integrated models (https://webapplicationing.shinyapps.io/PointOfCare-EoE/) can be used at point-of-care to improve the diagnostic workup of EoE and optimize resources allocation.

Patient journey in gastroesophageal reflux disease: real-world perspectives from Italian gastroenterologists, primary care physicians, and ENT specialists

Background

Gastroesophageal reflux disease (GERD) is a challenging condition that involves different physicians, such as general practitioners (GPs), gastroenterologists, and ears, nose and throat (ENT) specialists. A common approach consists of proton-pump inhibitors (PPIs) administration. Adjunctive pharmacological treatment may have a role in the management of non-responders to PPIs.

Objectives

We aimed to survey GPs and different medical specialists to investigate the medical approaches to patients reporting GERD symptoms. In addition, we examined the use of adjunctive pharmacological treatments in patients with GERD symptoms who do not respond to PPIs.

Design

Retrospective observational study.

Methods

A survey was conducted among a large sample of gastroenterologists, GPs, and ENT specialists. Symptoms were divided into typical and extraesophageal, and their severity and impact on quality of life were explored with the GERD Impact Scale and with Reflux Symptom Index (RSI). All therapies administered usually for GERD were investigated.

Results

A total of 6211 patients were analyzed in this survey. Patients with typical symptoms were 53.5%, while those with extraesophageal symptoms were 46.5%. The latter were more frequently reported by ENT patients (53.6%, p < 0.0001). The GSI was higher in patients followed by gastroenterologists (9 points) and GPs (9 points) than ENT specialists (8 points), but the RSI was higher in the ENT group (14.3 ± 6.93) than in GPs and gastroenterologist groups (10.36 ± 6.36 and 10.81 ± 7.30, p < 0.0001). Chest pain had the highest negative impact on quality of life (p < 0.0001). Of the 3025 patients who used PPIs, non-responders showed a lower GSI when treated with a combination of adjunctive pharmacological treatments and bioadhesive compounds, than with single-component drugs.

Conclusion

Patients with GERD referred to a gastroenterologist had more severe disease and poorer quality of life. The combination of adjunctive pharmacological treatments and bioadhesive compounds seems to be effective in the management of PPI refractory patients.

Biomarker discovery and validation for gastrointestinal tumors: A comprehensive review of colorectal, gastric, and liver cancers

Gastrointestinal (GI) malignancies, encompassing gastric, hepatic, colonic, and rectal cancers, are prevalent forms of cancer globally and contribute substantially to cancer-related mortality. Although there have been improvements in methods for diagnosing and treating GI cancers, the chances of survival for these types of cancers are still extremely low. According to the World Cancer Research International Fund's most recent figures, stomach cancer was responsible for roughly one million deaths worldwide in 2020. This emphasizes the importance of developing more effective tools for detecting, diagnosing, and predicting the outcome of these cancers at an early stage. Biomarkers, quantitative indications of biological processes or disease states, have emerged as promising techniques for enhancing the diagnosis and prognosis of GI malignancies. Recently, there has been a considerable endeavor to discover and authenticate biomarkers for various GI cancers by the utilization of diverse methodologies, including genomics, proteomics, and metabolomics. This review provides a thorough examination of the current state of biomarker research in the field of gastrointestinal malignancies, with a specific emphasis on colorectal, stomach, and liver cancers. A thorough literature search was performed on prominent databases such as PubMed, Scopus, and Web of Science to find pertinent papers published until November, 2023 for the purpose of compiling this review. The diverse categories of biomarkers, encompassing genetic, epigenetic, and protein-based biomarkers, and their potential utility in the fields of diagnosis, prognosis, and treatment selection, are explored. Recent progress in identifying and confirming biomarkers, as well as the obstacles that persist in employing biomarkers in clinical settings are emphasized. The utilization of biomarkers in GI cancers has significant potential in enhancing patient outcomes. Ongoing research is expected to uncover more efficient biomarkers for the diagnosis and prognosis of these cancers.

Cysteine protease inhibitor 1 promotes metastasis by mediating an oxidative phosphorylation/MEK/ERK axis in esophageal squamous carcinoma cancer

Cysteine protease inhibitor 1 (CST1) is a cystatin superfamily protein that inhibits cysteine protease activity and is reported to be involved in the development of many malignancies. Mitochondrial oxidative phosphorylation (OXPHOS) also plays an important role in cancer cell growth regulation. However, the relationship and roles of CST1 and OXPHOS in esophageal squamous cell carcinoma (ESCC) remains unclear. In our pilot study, CST1 was shown the potential of promoting ESCC migration and invasion by the activation of MEK/ERK pathway. Transcriptome sequencing analysis revealed that CST1 is closely associated with OXPHOS. Based on a real-time ATP rate assay, mitochondrial complex I enzyme activity assay, immunofluorescence, co-immunoprecipitation, and addition of the OXPHOS inhibitor Rotenone and MEK/ERK inhibitor PD98059, we determined that CST1 affects mitochondrial complex I enzyme activity by interacting with the GRIM19 protein to elevate OXPHOS levels, and a reciprocal regulatory relationship exists between OXPHOS and the MEK/ERK pathway in ESCC cells. Finally, an in vivo study demonstrated the potential of CST1 in ESCC metastasis through regulation of the OXPHOS and MEK/ERK pathways. This study is the first to reveal the oncogenic role of CST1 in ESCC development by enhancing mitochondrial respiratory chain complex I activity to activate the OXPHOS/MEK/ERK axis, and then promote ESCC metastasis, suggesting that CST1/OXPHOS is a promising target for ESCC treatment.

Prediction of Response to Chemoradiotherapy by Dynamic Changes of Circulating Exosome Levels in Patients with Esophageal Squamous Cell Carcinoma

Background

The exosomes-based liquid biopsy represents a prospective biomarker for tumor screening, prognosis prediction, and tumor regression. This study aimed to isolate circulating exosomes (CEs) from plasma of the esophageal squamous cell carcinoma (ESCC) patients who received chemoradiotherapy through exosome detection method via the ultrafast-isolation system (EXODUS) and investigated the association between the dynamic changes of CE levels and therapeutic effect.

Methods

We isolated and quantitatively analyzed CEs from plasma of locally advanced ESCC patients received chemoradiotherapy at 2 time points: baseline (pre-chemoradiotherapy) and 2 months after the chemoradiotherapy (post-chemoradiotherapy). We isolated exosomes from plasma by EXODUS platform and confirmed them through nanoparticle tracking analysis (NTA), transmission electron microscope (TEM), and Western blot. The associations of CE level with clinicopathological characteristics, tumor regression, and progression-free survival (PFS) were analyzed.

Results

The average diameter of CEs was 107.4±14.3 nm at baseline and 101.7±17.1 nm at post-chemoradiotherapy. The mean exosome concentration significantly decreased after chemoradiotherapy (7.3×1011 particles/mL vs 5.4×1011 particles/mL, P < 0.001). The patients with stage III-IVA and tumor length ≥5cm had obviously higher baseline CE levels. Dynamic changes in CE levels were successfully applied for evaluation of chemoradiotherapy response and PFS. Furthermore, through multivariate Cox regression analysis, it was revealed that dynamic changes of CE levels were an independent predictor of PFS in locally advanced ESCC patients who received chemoradiotherapy.

Conclusion

Here, we demonstrated EXODUS platform isolated and enriched CEs from plasma of ESCC patients with high-purity and high-yield. The EXODUS platform can facilitate liquid biopsy based on exosomes translation to the clinic. Baseline CE levels can reflect ESCC tumor burden. The dynamic changes of CE levels during chemoradiotherapy allow the prediction of treatment effect and PFS of ESCC patients, requiring further investigations in larger patient cohorts.

An integrated analysis of dysregulated SCD1 in human cancers and functional verification of miR-181a-5p/SCD1 axis in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC), one of the most lethal cancers, has become a global health issue. Stearoyl-coA desaturase 1 (SCD1) has been demonstrated to play a crucial role in human cancers. However, pan-cancer analysis has revealed little evidence to date. In the current study, we systematically inspected the expression patterns and potential clinical outcomes of SCD1 in multiple human cancers. SCD1 was dysregulated in several types of cancers, and its aberrant expression acted as a diagnostic biomarker, indicating that SCD1 may play a role in tumorigenesis. We used ESCC as an example to demonstrate that SCD1 was dramatically upregulated in tumor tissues of ESCC and was associated with clinicopathological characteristics in ESCC patients. Furthermore, Kaplan-Meier analysis showed that high SCD1 expression was correlated with poor progression-free survival (PFS) and disease-free survival (DFS) in ESCC patients. The protein-protein interaction (PPI) network and module analysis by PINA database and Gephi were performed to identify the hub targets. Meanwhile, the functional annotation analysis of these hubs was constructed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Functionally, the gain-of-function of SCD1 in ESCC cells promoted cell proliferation, migration, and invasion; in contrast, loss-of-function of SCD1 in ESCC cells had opposite effects. Bioinformatic, QPCR, Western blotting and luciferase assays indicated that SCD1 was a direct target of miR-181a-5p in ESCC cells. In addition, gain-of-function of miR-181a-5p in ESCC cells reduced the cell growth, migratory, and invasive abilities. Conversely, inhibition of miR-181a-5p expression by its inhibitor in ESCC cells had opposite biological effects. Importantly, reinforced SCD1 in miR-181a-5p mimic ESCC transfectants reversed miR-181a-5p mimic-prevented malignant phenotypes of ESCC cells. Taken together, these results indicate that SCD1 expression influences tumor progression in a variety of cancers, and the miR-181a-5p/SCD1 axis may be a potential therapeutic target for ESCC treatment.

Robotic Colonoscopy and Beyond: Insights into Modern Lower Gastrointestinal Endoscopy

Lower gastrointestinal endoscopy is considered the gold standard for the diagnosis and removal of colonic polyps. Delays in colonoscopy following a positive fecal immunochemical test increase the likelihood of advanced adenomas and colorectal cancer (CRC) occurrence. However, patients may refuse to undergo conventional colonoscopy (CC) due to fear of possible risks and pain or discomfort. In this regard, patients undergoing CC frequently require sedation to better tolerate the procedure, increasing the risk of deep sedation or other complications related to sedation. Accordingly, the use of CC as a first-line screening strategy for CRC is hampered by patients' reluctance due to its invasiveness and anxiety about possible discomfort. To overcome the limitations of CC and improve patients' compliance, several studies have investigated the use of robotic colonoscopy (RC) both in experimental models and in vivo. Self-propelling robotic colonoscopes have proven to be promising thanks to their peculiar dexterity and adaptability to the shape of the lower gastrointestinal tract, allowing a virtually painless examination of the colon. In some instances, when alternatives to CC and RC are required, barium enema (BE), computed tomographic colonography (CTC), and colon capsule endoscopy (CCE) may be options. However, BE and CTC are limited by the need for subsequent investigations whenever suspicious lesions are found. In this narrative review, we discussed the current clinical applications of RC, CTC, and CCE, as well as the advantages and disadvantages of different endoscopic procedures, with a particular focus on RC.

The current state of artificial intelligence in endoscopic diagnosis of early esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive tract. The most effective method of reducing the disease burden in areas with a high incidence of esophageal cancer is to prevent the disease from developing into invasive cancer through screening. Endoscopic screening is key for the early diagnosis and treatment of ESCC. However, due to the uneven professional level of endoscopists, there are still many missed cases because of failure to recognize lesions. In recent years, along with remarkable progress in medical imaging and video evaluation technology based on deep machine learning, the development of artificial intelligence (AI) is expected to provide new auxiliary methods of endoscopic diagnosis and the treatment of early ESCC. The convolution neural network (CNN) in the deep learning model extracts the key features of the input image data using continuous convolution layers and then classifies images through full-layer connections. The CNN is widely used in medical image classification, and greatly improves the accuracy of endoscopic image classification. This review focuses on the AI-assisted diagnosis of early ESCC and prediction of early ESCC invasion depth under multiple imaging modalities. The excellent image recognition ability of AI is suitable for the detection and diagnosis of ESCC and can reduce missed diagnoses and help endoscopists better complete endoscopic examinations. However, the selective bias used in the training dataset of the AI system affects its general utility.

Biomarkers for Early Detection, Prognosis, and Therapeutics of Esophageal Cancers

Esophageal cancer (EC) is the deadliest cancer worldwide, with a 92% annual mortality rate per incidence. Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two major types of ECs, with EAC having one of the worst prognoses in oncology. Limited screening techniques and a lack of molecular analysis of diseased tissues have led to late-stage presentation and very low survival durations. The five-year survival rate of EC is less than 20%. Thus, early diagnosis of EC may prolong survival and improve clinical outcomes. Cellular and molecular biomarkers are used for diagnosis. At present, esophageal biopsy during upper endoscopy and histopathological analysis is the standard screening modality for both ESCC and EAC. However, this is an invasive method that fails to yield a molecular profile of the diseased compartment. To decrease the invasiveness of the procedures for diagnosis, researchers are proposing non-invasive biomarkers for early diagnosis and point-of-care screening options. Liquid biopsy involves the collection of body fluids (blood, urine, and saliva) non-invasively or with minimal invasiveness. In this review, we have critically discussed various biomarkers and specimen retrieval techniques for ESCC and EAC.

Using deep learning and explainable artificial intelligence to assess the severity of gastroesophageal reflux disease according to the Los Angeles Classification System

OBJECTIVES

Gastroesophageal reflux disease (GERD) is a complex disease with a high worldwide prevalence. The Los Angeles classification (LA-grade) system is meaningful for assessing the endoscopic severity of GERD. Deep learning (DL) methods have been widely used in the field of endoscopy. However, few DL-assisted researches have concentrated on the diagnosis of GERD. This study is the first to develop a five-category classification DL model based on the LA-grade using explainable artificial intelligence (XAI).

MATERIALS AND METHODS

A total of 2081 endoscopic images were used for the development of a DL model, and the classification accuracy of the models and endoscopists with different levels of experience was compared.

RESULTS

Some mainstream DL models were utilized, of which DenseNet-121 outperformed. The area under the curve (AUC) of the DenseNet-121 was 0.968, and its classification accuracy (86.7%) was significantly higher than that of junior (71.5%) and experienced (77.4%) endoscopists. An XAI evaluation was also performed to explore the perception consistency between the DL model and endoscopists, which showed meaningful results for real-world applications.

CONCLUSIONS

The DL model showed a potential in improving the accuracy of endoscopists in LA-grading of GERD, and it has noticeable clinical application prospects and is worthy of further promotion.

Exosomal microRNAs: A Diagnostic and Therapeutic Small Bio-molecule in Esophageal Cancer

Esophageal cancer (EC) is one of the major causes of cancer-related death worldwide. EC is usually diagnosed at a late stage, and despite aggressive therapy, the five-year survival rate of patients remains poor. Exosomes play important roles in cancer biology. Indeed, exosomes are implicated in tumor proliferation, angiogenesis, and invasion. They contain bioactive molecules such as lipids, proteins, and non-coding RNAs. Exosome research has recently concentrated on microRNAs, which are tiny noncoding endogenous RNAs that can alter gene expression and are linked to nearly all physiological and pathological processes, including cancer. It is suggested that deregulation of miRNAs results in cancer progression and directly induces tumor initiation. In esophageal cancer, miRNA dysregulation plays an important role in cancer prognosis and patients' responsiveness to therapy, indicating that miRNAs are important in tumorigenesis. In this review, we summarize the impact of exosomal miRNAs on esophageal cancer pathogenesis and their potential applications for EC diagnosis and therapy.

Expression and Prognostic Value of Chromobox Family Proteins in Esophageal Cancer

Background: Esophageal cancer (EC) is one of the most common human malignant tumors worldwide. Chromobox (CBX) family proteins are significant components of epigenetic regulatory complexes. It is reported that CBXs play critical roles in the oncogenesis and development of various tumors. Nonetheless, their functions and specific roles in EC remain vague and obscure. Methods and Materials: We used multiple bioinformatics tools, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), UALCAN, Kaplan–Meier plotter, cBioPortal, Metascape, TIMER2 and TISIDB, to investigate the expression profile, gene alterations and prognostic roles of CBX family proteins, as well as their association with clinicopathologic parameters, immune cells and immune regulators. In addition, RT-qPCR, Western blot, CCK8, colony formation, wound healing and transwell assays were performed to investigate the biological functions of CBX3 in EC cells. Results: CBX3 and CBX5 were overexpressed in EC compared to normal tissues. Survival analysis revealed that high expression of CBX1 predicted worse disease-free survival (DFS) in EC patients. Functionally, CBXs might participate in mismatch repair, spliceosome, cell cycle, the Fanconi anemia pathway, tight junction, the mRNA surveillance pathway and the Hippo signaling pathway in EC development. Furthermore, CBXs were related to distinct immune cells infiltration and immune regulators. Additionally, depletion of CBX3 inhibited the proliferation, migration and invasion abilities of EC cells. Conclusions: Our study comprehensively investigated the expression pattern, prognostic value, and gene alterations of CBXs in EC, as well as their relationships with clinicopathologic variables, immune cells infiltration and immune regulators. These results suggested that CBX family proteins, especially CBX3, might be potential biomarkers in the progression of EC.

Nomogram based on circulating lymphocyte subsets for predicting radiation pneumonia in esophageal squamous cell carcinoma

Purpose

Currently, the relationship between radiation pneumonia (RP) and circulating immune cell in patients with esophageal squamous cell carcinoma (ESCC) remains unclear. This study aimed to explore the relationship between RP and circulating lymphocyte subsets in patients with ESCC receiving chemoradiotherapy (CRT), and develop a nomogram model to predict RP. Since we should implement clinical intervention to ≥ grade 2 RP, a nomogram model for ≥ grade 2 RP was also established to provide an early warning.

Patients and methods

This study retrospectively included 121 patients with ESCC receiving CRT from Guangxi Medical University Cancer Hospital from 2013 to 2021. Independent factors associated with occurrence of RP and ≥ grade 2 RP were identified by univariate and multivariate logistic regression analysis in the training cohort, and incorporated into nomograms. The predictive accuracy and discrimination of the model was assessed using Concordance Index (C-index), calibration curve and decision curve analysis (DCA). And each model was internally validated. Additionally, to verify the optimized predictive performance of the nomograms, the area under the ROC curve (AUC) of each nomogram was compared to that of single independent risk factors, lung V10 and lung V20, respectively. Moreover, each model was further evaluated for risk stratification to identify populations at high risk of RP and ≥ grade 2 RP.

Results

Multivariate analysis suggested that TNM stage, post-RT percentage of CD8+ T cell, and lung V15 were independent predictive factors of RP. Besides, pre- and post-RT percentage of CD8+ T cell, and V15 were independent factors of ≥ grade 2 RP. The C-indexes of RP and ≥ grade 2 RP nomograms were 0.809 (95% CI: 0.715-0.903) and 0.787 (95% CI: 0.685-0.889) in the training cohort, respectively. And the C-indexes of RP and ≥ grade 2 RP nomograms were 0.718 (95% CI: 0.544-0.892) and 0.621 (95% CI: 0.404-0.837) in the validation cohort, respectively. The calibration curves showed that the predicted values of model agreed well with actual observations. Moreover, DCA results indicated the applicability and accuracy of the models to predict RP and ≥ grade 2 RP. After stratification, the incidence of the high-risk group was significantly higher than that of the low-risk group with respect to either RP or ≥ grade 2 RP.

Conclusion

TNM stage, post-RT percentage of CD8+ T cell, and lung V15 were the independent predictors of RP toxicity. Pre- and post-RT percentage of CD8+ T cell, and lung V15 were the independent factors of ≥ grade 2 RP toxicity. The nomograms based on circulating lymphocyte subsets can robustly predict RP and ≥ grade 2 RP, guiding clinicians in risk stratification and early intervention.

A computational method for large-scale identification of esophageal cancer-related genes

The incidence of esophageal cancer has obvious genetic susceptibility. Identifying esophageal cancer-related genes plays a huge role in the prevention and treatment of esophageal cancer. Through various sequencing methods, researchers have found only a small number of genes associated with esophageal cancer. In order to improve the efficiency of esophageal cancer genetic susceptibility research, this paper proposes a method for large-scale identification of esophageal cancer-related genes by computational methods. In order to improve the efficiency of esophageal cancer genetic susceptibility research, this paper proposes a method for large-scale identification of esophageal cancer-related genes by computational methods. This method fuses graph convolutional network and logical matrix factorization to effectively identify esophageal cancer-related genes through the association between genes. We call this method GCNLMF which achieved AUC as 0.927 and AUPR as 0.86. Compared with other five methods, GCNLMF performed best. We conducted a case study of the top three predicted genes. Although the association of these three genes with esophageal cancer has not been reported in the database, studies by other reseachers have shown that these three genes are significantly associated with esophageal cancer, which illustrates the accuracy of the prediction results of GCNLMF.

The circRNA circADAMTS6 promotes progression of ESCC and correlates with prognosis

Circular RNAs (circRNAs) are a type of noncoding RNA, which play a vital role in the occurrence and development of esophageal squamous cell carcinoma (ESCC). While the role of novel circADAMTS6 in ESCC remains unknown. We assessed circADAMTS6 expression in ESCC tissues and cells, and the relationship between circADAMTS6 expression and overall survival of ESCC patients. Functional experiments in vitro and xenograft in vivo assay were applied to explore the functions and mechanisms of circADAMTS6 in ESCC. Results found that up-regulation of circADAMTS6 was associated with poor overall survival and may acted as an independent risk factor for ESCC prognosis. Knockdown of circADAMTS6 significantly inhibited the proliferation, migration and invasion of ESCC cells and growth of xenograft tumors in vivo. Induced AGR2 expression was able to rescue the loss of function induced by si-circADAMTS6 in KYSE150 cell. CircADAMTS6 may acts as oncogene by activating AGR2 and the Hippo signaling pathway coactivator YAP in ESCC.

The Use of Confocal Laser Endomicroscopy in Diagnosing Barrett’s Esophagus and Esophageal Adenocarcinoma

Confocal laser endomicroscopy (CLE) is a diagnostic technique that enables real-time microscopic imaging during microscopic examination and evaluation of epithelial structures with 1000-fold magnification. CLE can be used in the diagnosis of various pathologies, in pneumology, and in urology, and it is very widely utilized in gastroenterology, most importantly in the diagnosis of Barrett’s esophagus (BE), esophageal adenocarcinoma (EAC), biliary strictures, and cystic pancreatic lesions. A literature search was made in MEDLINE/PubMed and Google Scholar databases while focusing on diagnostics using CLE of BE and EAC. We then examined randomized and observational studies, systematic reviews, and meta-analyses relating to the utilization of CLE in BE and EAC diagnostics. Here, we discuss whether CLE can be a suitable diagnostic method for surveillance of BE. Even though many studies have proven that CLE increases diagnostic accuracy in detecting neoplastic transformation of BE, CLE is still not used as a standard diagnostic tool in BE surveillance due to a deficiency of scientific evidence. More studies and data are needed if CLE is to find a place as a new technique in BE surveillance.

Esophageal squamous cell carcinoma: Integrated bioinformatics analysis for differential gene expression with identification of hub genes and lncRNA

Background

Esophageal squamous cell carcinoma (ESCC) is a typical Gastro-Intestinal (GI) tract neoplasm. This study was conducted to know the Differential Expressed Genes (DEGs) profile of ESCC along with hub gene screening, lncRNA identification, and drug-genes interactions.

Methods

GSE161533, GSE20347, GSE45670 microarray datasets were retrieved from the NCBI Gene Expression Omnibus (GEO) database. GEO2R was used for the DEGs identification, whereas GO (Gene Ontology) and KEGG enrichment analysis were performed in DAVID. PPI network constructed using STRING and visualized with Cytoscape app with the help of MCODE. The top ten connectivity genes were selected as hub genes—further survival analysis was performed in the Kaplan-Meier plotter. Moreover, Boxplot, pathological stage plots were constructed using GEPIA (Gene Expression Profiling Interactive Analysis). The methylation heatmap assembled in the DiseaseMeth version 2.0. lncRNA (Long non-coding RNA) was identified comparing the list of genes in HUGO, and Gene-drug interactions were accumulated from the DgiDB platform.

Results

This experiment showed 16 upregulated, and 59 downregulated DEGs shared among the three datasets. Biological process analysis showed significant terms such as extracellular matrix disassembly and collagen catabolism. The extracellular region was detected as the most crucial cellular compartment. Notably, metalloen dopeptidease and serine-type endopeptidase activity showed significant molecular functions term. In contrast, transcriptional misregulation was a highly substantial KEGG pathway. Kaplan-Meier plotter showed higher expression of CXCL8, SPP1, MMP13, CXCL1, and TOP2A have a significant impact on the overall survival of the patients. Nine out of ten hub genes have significantly different expression levels than normal and cancer tissues. HYMAI was the only lncRNA commonly expressed upregulated among the three datasets. Drug-gene interaction showed multiple genes have no drug options exist till now.

•

GSE161533, GSE20347, and GSE45670 microarray datasets were analyzed.

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16 upregulated and 59 downregulated DEGs shared among the three datasets.

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CXCL8, SPP1, MMP13, CXCL1, and TOP2A have a significant impact on survival.

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HYMAI was the only lncRNA commonly expressed.

•

Multiple genes have no drug options that exist.

Upregulation of hsa_circ_0000977 participates in esophageal squamous cancer progression by sponging miR-874-3p

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common clinical malignancies of the digestive system, characterized by high mortality but not evident early symptoms. Molecular markers for diagnostic and outcome prediction are urgently needed. Circular RNAs might play essential roles in the progression of ESCC.

METHODS

Hsa_circ_0000977 was identified using circRNA microarrays and qRT-PCR. The diagnostic value of hsa_circ_0000977 was calculated. We also examined in vitro cell functions in ECA109 and TE12 ESCC cells to determine the effect of hsa_circ_0000977. A dual-luciferase reporter vector validated the binding of hsa_circ_0000977 to miR-874-3p.

RESULTS

The top 10 significantly upregulated circRNAs from microarray assays were hsa_circ_0000977, hsa_circ_0006220, hsa_circ_0043278, hsa_circ_0000691, hsa_circ_0000288, hsa_circ_0000367, hsa_circ_0021647, hsa_circ_0006440, hsa_circRNA_405571 and hsa_circRNA_100790, while the top 10 significantly downregulated circRNAs were hsa_circ_0008389, hsa_circ_0089763, hsa_circ_0089762, hsa_circ_0000102, hsa_circ_0001714, hsa_circ_0089761, hsa_circ_0007326, hsa_circ_0001549, hsa_circ_0005133 and hsa_circRNA_405965. Hsa_circ_0000977 was significantly upregulated in ESCC (p < 0.01) and had diagnostic value in ESCC. The hsa_circ_0000977 expression level was related to the pT stage and numbers of lymph nodes in ESCC patients. Elevated hsa_circ_0000977 promoted cell proliferation, migration and inhibited apoptosis in ESCC cells. Hsa_circ_0000977 might function as a micro-RNA sponge to competitively bind miR-874-3p.

CONCLUSION

Disordered hsa_circ_0000977 expression can promote carcinogenesis in ESCC and might serve as a diagnostic biomarker to evaluate the occurrence and development of esophageal cancer.

360º optoacoustic capsule endoscopy at 50 Hz for esophageal imaging

Gastrointestinal (GI) endoscopy is a common medical diagnostic procedure used for esophageal cancer detection. Current emerging capsule optoacoustic endoscopes, however, suffer from low pulse repetition rates and slow scanning units limit attainable imaging frame rates. Consequently, motion artifacts result in inaccurate spatial mapping and misinterpretation of data. To overcome these limitations, we report a 360^º, 50 Hz frame rate, distal scanning capsule optoacoustic endoscope. The translational capability of the instrument for human GI tract imaging was characterized with an Archimedean spiral phantom consisting of twelve 100 µm sutures, a stainless steel mesh with a pitch of 3 mm and an ex vivo pig esophagus sample. We estimated an imaging penetration depth of ~0.84 mm in vivo by immersing the mesh phantom in intralipid solution to simulate light scattering in human esophageal tissue and validated our findings ex vivo using pig esophagus. This proof-of-concept study demonstrates the translational potential of the proposed video-rate endoscope for human GI tract imaging.

Pan-immune-inflammation Value and Prognosis in Patients With Esophageal Cancer

Mini-abstract

The pan-immune-inflammation value was associated with clinical outcomes and tumor-infiltrating lymphocytes in 866 esophageal cancers. Systemic immune competence may influence patient prognosis through local immune response.

Objective

To examine the relationship between the pan-immune-inflammation value (PIV), tumor immunity, and clinical outcomes in 866 patients with esophageal cancer.

Background

The PIV, calculated from all immune-inflammatory cells in the peripheral blood count, is a recently proposed marker for clinical outcomes in some types of cancers. Nonetheless, the prognostic significance of PIV in esophageal cancer remains unclear.

Methods

In the derivation cohort (n = 433), we set the optimal cutoff value using a time-dependent receiver operating characteristic (ROC) curve. In the validation cohort (n = 433), the relationships between the PIV, tumor-infiltrating lymphocytes (TILs), CD8 expression by immunohistochemical staining, and patient prognosis were examined.

Results

The area under the ROC curve for the PIV at 5 years was 0.631 in the derivation cohort. The validation cohort, divided into PIV-low cases (n = 223) and PIV-high cases (n = 210), showed significantly worse overall survival (log-rank P = 0.0065; hazard ratio [HR]: 1.48; 95% confidence interval [CI]: 1.12-1.98; P < 0.001; multivariate HR: 1.41; 95% CI: 1.05-1.90; P = 0.023). The prognostic effect of the PIV was not significantly modified by any clinical characteristics (P for interaction > 0.05). The PIV-high cases were significantly associated with a low TIL status (P < 0.001) and low CD8-positive cell counts (P = 0.011).

Conclusions

The PIV was associated with clinical outcomes in esophageal cancer, supporting its role as a prognostic biomarker. Considering the relationship between the PIV and TILs, systemic immune competence may influence patient prognosis through a local immune response.

Correlation Analysis of circRNA Circ_0071662 in Diagnosis and Prognosis of Esophageal Squamous Cell Carcinoma

Background

The role of circRNA circ_0071662 has been studied in bladder cancer. The present study aimed to analyze its involvement in esophageal squamous cell carcinoma (ESCC).

Methods

Patients with ESCC (n = 66), esophageal ulcer (EU, n = 66), or gastroesophageal reflux disease (GERD, n = 66) and healthy controls (n = 66) were enrolled in this study. Plasma samples were collected from all patients and controls. ESCC and paired non-tumor tissue samples were collected from ESCC patients. Circ_0071662 levels in these samples were determined by RT-qPCRs. Diagnostic and prognostic values of circ_0071662 for ESCC were analyzed with ROC curve and survival curve analyses.

Results

Circ_0071662 level was decreased in ESCC, but not in GERN and EU compared to the controls and in ESCC tissues compared to the non-tumor tissues. Plasma circ_0071662 was closely correlated with patients’ tumor size but not with other clinical features. Decreased plasma circ_0071662 levels separated ESCC patients from GERN patients, EU patients, and healthy controls. Low plasma circ_0071662 levels were closely correlated with worse survival outcomes of ESCC patients.

Conclusion

Circ_0071662 is lowly expressed in ESCC and may serve as a potential diagnostic and prognostic biomarker for ESCC.

Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases

Artificial intelligence (AI) has enormous potential to support clinical routine workflows and therefore is gaining increasing popularity among medical professionals. In the field of gastroenterology, investigations on AI and computer-aided diagnosis (CAD) systems have mainly focused on the lower gastrointestinal (GI) tract. However, numerous CAD tools have been tested also in upper GI disorders showing encouraging results. The main application of AI in the upper GI tract is endoscopy; however, the need to analyze increasing loads of numerical and categorical data in short times has pushed researchers to investigate applications of AI systems in other upper GI settings, including gastroesophageal reflux disease, eosinophilic esophagitis, and motility disorders. AI and CAD systems will be increasingly incorporated into daily clinical practice in the coming years, thus at least basic notions will be soon required among physicians. For noninsiders, the working principles and potential of AI may be as fascinating as obscure. Accordingly, we reviewed systematic reviews, meta-analyses, randomized controlled trials, and original research articles regarding the performance of AI in the diagnosis of both malignant and benign esophageal and gastric diseases, also discussing essential characteristics of AI.

Clinical use of mean nocturnal baseline impedance and post-reflux swallow-induced peristaltic wave index for the diagnosis of gastro-esophageal reflux disease

The clinical diagnosis of gastro-esophageal reflux disease (GERD) is based on the presence of typical esophageal troublesome symptoms. In clinical practice, heartburn relief following a proton pump inhibitor (PPI) trial or endoscopy can confirm a diagnosis of GERD. In cases of diagnostic uncertainty or before anti-reflux interventions, combined impedance-pH monitoring (MII-pH) provides a comprehensive assessment of both physical and chemical properties of the refluxate, allowing to achieve a conclusive diagnosis of GERD. Recently, the Lyon Consensus proposed the use of mean nocturnal baseline impedance (MNBI) and post-reflux swallow-induced peristaltic wave index (PSPW-I) as novel MII-pH metrics to support the diagnosis of GERD. The calculation of MNBI and PSPW-I currently needs to be performed manually, but artificial intelligence systems for the automated analysis of MII-pH tracings are being developed. Several studies demonstrated the increased diagnostic yield MNBI and PSPW-I for the categorization of patients with GERD at both on- and off-PPI MII-pH monitoring. Accordingly, we performed a narrative review on the clinical use and diagnostic yield of MNBI and PSPW-I when the diagnosis of GERD is uncertain. Based on currently available evidence, we strongly support the evaluation of PSPW-I and MNBI as part of the standard assessment of MII-pH tracings for the evaluation of GERD, especially in patients with endoscopy-negative heartburn.

Easily-injectable shear-thinning hydrogel provides long-lasting submucosal barrier for gastrointestinal endoscopic surgery

Submucosal injection material has shown protective effect against gastrointestinal injury during endoscopic surgery in clinic. However, the protective ability of existing submucosal injection material is strictly limited by their difficult injectability and short barrier time. Herein, we report a shear-thinning gellan gum hydrogel that simultaneously has easy injectability and long-lasting barrier function, together with good hemostatic property and biocompatibility. Shear-thinning property endows our gellan gum hydrogel with excellent endoscopic injection performance, and the injection pressure of our gellan gum hydrogel is much lower than that of the small molecule solution (50 wt% dextrose) when injected through the endoscopic needle. More importantly, our gellan gum hydrogel shows much stronger barrier retention ability than normal saline and sodium hyaluronate solution in the ex vivo and in vivo models. Furthermore, our epinephrine-containing gellan gum hydrogel has a satisfactory hemostatic effect in the mucosal lesion resection model of pig. These results indicate an appealing application prospect for gellan gum hydrogel utilizing as a submucosal injection material in endoscopic surgery.

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Submucosal injection materials are widely used in endoscopic surgery to protect against gastrointestinal injury.

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Gellan gum hydrogel with shear-thinning character is a novel submucosal injection material.

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Gellan gum hydrogel simultaneously has easy injectability and long-lasting barrier performance in vivo.

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Epinephrine-containing gellan gum hydrogel has a satisfactory hemostatic effect.

Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas

Tumor progression involves an intricate interplay between malignant cells and their surrounding tumor microenvironment (TME) at specific sites. The TME is dynamic and is composed of stromal, parenchymal, and immune cells, which mediate cancer progression and therapy resistance. Evidence from preclinical and clinical studies revealed that TME targeting and reprogramming can be a promising approach to achieve anti-tumor effects in several cancers, including in GEA. Thus, it is of great interest to use modern technology to understand the relevant components of programming the TME. Here, we discuss the approach of machine learning, which recently gained increasing interest recently because of its ability to measure tumor parameters at the cellular level, reveal global features of relevance, and generate prognostic models. In this review, we discuss the relevant stromal composition of the TME in GEAs and discuss how they could be integrated. We also review the current progress in the application of machine learning in different medical disciplines that are relevant for the management and study of GEA.