Screening For Esophageal Squamous Cell Carcinoma Research Articles

Revealing key proteins in comparison of tumor and para-tumor tissues in stage I esophageal squamous cell carcinoma: A combined gene expression clustering and protein interaction network analysis

Esophageal Squamous Cell Carcinoma (ESCC) which is diagnosed in advanced stages and metastasis to the vital organs, remained the sixth fatal malignancy among other types of cancer-related death. Considering the lack of specific clinical symptoms in the early development of the disease, finding suitable biomarkers and tissue-specific alterations for effective screening of ESCC is targeted in this project. Gene expression profiles of tumor tissue and para-tumors of stage I ESCC patients were retrieved from the Gene Expression Omnibus (GEO) database. The significant tissue-specific differentially expressed genes (DEGs) were identified and studied based on fold change distribution and the functional role of genes in the action map. A total number of 11,483 significant DEGs discriminated the tumor tissue from para-tumor tissue. Clustering analysis of significant DEGs led to identifying 220 DEGs as the final significant genes. Protein interaction network and action map analysis of the final gene list showed matrix metallopeptidase-9 (MMP9) as the critical gene related to the development of ESCC diseases in stage I. Significant expression change of MMP9 in esophageal carcinoma was validated in UALCAN (The University of Alabama at Birmingham Cancer Data Analysis Portal). This study highlighted the pivotal role of MMP9 in combination with SPP1, MMP13, and IL18 as a possible biomarkers panel in studies of tumor invasion and prognosis for stage I ESCC disease.

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.

Early Diagnostic Markers for Esophageal Squamous Cell Carcinoma: Copy Number Alteration Gene Identification and cfDNA Detection

The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis revealed widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer data sets. Subsequent validation of 5 candidate markers via ddPCR underscored the efficacy of combined predictive models encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1 in early ESCC screening, as evidenced by the area-under-the-curve values exceeding 0.92 (P < .0001) across various detection contexts. The findings highlighted the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.

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

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

EsophaCap Sponge Cytology Screening for Esophageal Squamous Cell Dysplasia and Carcinoma is Feasible in a High-Risk Area in Western India

Objective: Conventional endoscopy remains the gold standard for detecting esophageal squamous cell carcinoma (ESCC) despite its high cost and need for expertise. In resource-poor regions, a less labor-intensive yet accurate screening tool is needed. The purpose of this study is to assess feasibility of establishing a non-endoscopic screening program in rural India and to test the diagnostic accuracy of the EsophaCap swallowable sponge in detecting ESCC in a high-risk patient population. Methods: A prospective cohort study was conducted between 2017 and 2019, in which subjects with risk factors for ESCC (tobacco smoking or chewing, betel nut/leaf, alcohol and hot beverage consumption) were approached during upper endoscopy visits at a clinic in Western India. After obtaining EsophaCap sponge cytology samples, random endoscopic biopsies were obtained at 20 and 30 cm from the incisors. Histologic diagnoses were confirmed and select biopsy samples were sequenced for genomic aberrations. Visual Analog Scale (VAS) scores were used to assess patient experience of sponge swallowing (range 1-5, “very comfortable” to “very uncomfortable”). Results: In our cohort of 178 patients, 157 (88%) were males. Mean age was 52 ± 12 years. Sixty-eight (38%) patients were current cigarette or bidi smokers; 132 (74%) patients were daily tobacco chewers, and 83 (47%) patients chewed betel nuts/leaves on a daily basis. Forty-six (26%) patients were daily alcohol users and 151 (85%) patients drank ≥3 hot beverages per day. The median number of risk factors per patient was 3. The first-time swallow rate of the encapsulated sponge was successful in 190/200 (95%) patients. Median VAS score was 2 (“comfortable”). EsophaCap cytology revealed 6 (3%) patients with atypical squamous cells of unknown significance (ASCUS) and 3 (1%) patients with dysplasia. Based on the endoscopic biopsies, 6 (3%) patients had ESCC, 4 (2%) patients had lesions with squamous dysplasia, and 63 (35%) patients had esophageal leukoplakia. Four patients classified as ASCUS pathology via EsophaCap were normal, benign, or leukoplakia via endoscopy. EsophaCap’s sensitivity and specificity for detecting dysplasia or ESCC by histology was 30% and 97%, respectively. Conclusions: Establishing a non-endoscopic screening program in a high-risk area with language barriers and low medical literacy is very safe and feasible. EsophaCap may help identify ASCUS patients in need of serial endoscopic monitoring. Further studies of combined sponge cytology with immunohistochemistry studies are necessary to improve accuracy of ESCC screening.

Untargeted serum metabolomics reveals potential biomarkers and metabolic pathways associated with the progression of gastroesophageal cancer

BackgroundPrevious metabolic studies in upper digestive cancer have mostly been limited to cross-sectional study designs, which hinders the ability to effectively predict outcomes in the early stage of cancer. This study aims to identify key metabolites and metabolic pathways associated with the multistage progression of epithelial cancer and to explore their predictive value for gastroesophageal cancer (GEC) formation and for the early screening of esophageal squamous cell carcinoma (ESCC).MethodsA case-cohort study within the 7-year prospective Esophageal Cancer Screening Cohort of Shandong Province included 77 GEC cases and 77 sub-cohort individuals. Untargeted metabolic analysis was performed in serum samples. Metabolites, with FDR q value < 0.05 and variable importance in projection (VIP) > 1, were selected as differential metabolites to predict GEC formation using Random Forest (RF) models. Subsequently, we evaluated the predictive performance of these differential metabolites for the early screening of ESCC.ResultsWe found a distinct metabolic profile alteration in GEC cases compared to the sub-cohort, and identified eight differential metabolites. Pathway analyses showed dysregulation in D-glutamine and D-glutamate metabolism, nitrogen metabolism, primary bile acid biosynthesis, and steroid hormone biosynthesis in GEC patients. A panel of eight differential metabolites showed good predictive performance for GEC formation, with an area under the receiver operating characteristic curve (AUC) of 0.893 (95% CI = 0.816–0.951). Furthermore, four of the GEC pathological progression-related metabolites were validated in the early screening of ESCC, with an AUC of 0.761 (95% CI = 0.716–0.805).ConclusionsThese findings indicated a panel of metabolites might be an alternative approach to predict GEC formation, and therefore have the potential to mitigate the risk of cancer progression at the early stage of GEC.

Performance of Prediction Models for Esophageal Squamous Cell Carcinoma in General Population: A Systematic Review and External Validation Study.

Prediction models for esophageal squamous cell carcinoma (ESCC) need to be proven effective in the target population before they can be applied to population-based endoscopic screening to improve cost-effectiveness. We have systematically reviewed ESCC prediction models applicable to the general population and performed external validation and head-to-head comparisons in a large multicenter prospective cohort including 5 high-risk areas of China (Fei Cheng, Lin Zhou, Ci Xian, Yang Zhong, and Yan Ting). Models were identified through a systematic review and validated in a large population-based multicenter prospective cohort that included 89,753 participants aged 40-69 years who underwent their first endoscopic examination between April 2017 and March 2021 and were followed up until December 31, 2022. Model performance in external validation was estimated based on discrimination and calibration. Discrimination was assessed by C-statistic (concordance statistic), and calibration was assessed by calibration plot and Hosmer-Lemeshow test. The systematic review identified 15 prediction models that predicted severe dysplasia and above lesion (SDA) or ESCC in the general population, of which 11 models (4 SDA and 7 ESCC) were externally validated. The C-statistics ranged from 0.67 (95% confidence interval 0.66-0.69) to 0.70 (0.68-0.71) of the SDA models, and the highest was achieved by Liu et al (2020) and Liu et al (2022). The C-statistics ranged from 0.51 (0.48-0.54) to 0.74 (0.71-0.77), and Han et al (2023) had the best discrimination of the ESCC models. Most models were well calibrated after recalibration because the calibration plots coincided with the x = y line. Several prediction models showed moderate performance in external validation, and the prediction models may be useful in screening for ESCC. Further research is needed on model optimization, generalization, implementation, and health economic evaluation.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study.

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

Encoding LC-MS-Based Untargeted Metabolomics Data into Images toward AI-Based Clinical Diagnosis.

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics provides comprehensive and quantitative profiling of metabolites in clinical investigations. The use of whole metabolome profiles is a promising strategy for disease diagnosis but technically challenging. Here, we developed an approach, namely MetImage, to encode LC-MS-based untargeted metabolomics data into multi-channel digital images. Then, the images that represent the comprehensive metabolome profiles can be employed for developing deep learning-based AI models toward clinical diagnosis. In this work, we demonstrated the application of MetImage for clinical screening of esophageal squamous cell carcinoma (ESCC) in a clinical cohort with 1104 participants. A convolutional neuronal network-based AI model was trained to distinguish ESCC screening positive and negative subjects using their serum metabolomics data. Superior performances such as sensitivity (85%), specificity (92%), and area under curve (0.95) were validated in an independent testing cohort (N = 442). Importantly, we demonstrated that our AI-based ESCC screening model is not a "black box". The encoded images reserved the characteristics of mass spectra from the raw LC-MS data; therefore, metabolite identifications in key image features were readily achieved. Altogether, MetImage is a unique approach that encodes raw LC-MS-based untargeted metabolomics data into images and facilitates the utilization of whole metabolome profiles for AI-based clinical applications with improved interpretability.

Microbial and epidemiological factors in early detection of esophageal squamous cell carcinoma and precancerous lesions.

Microbial and epidemiological factors in early detection of esophageal squamous cell carcinoma and precancerous lesions.

A RASSF8-AS1 based exosomal lncRNAs panel used for diagnostic and prognostic biomarkers for esophageal squamous cell carcinoma.

Exosomal long non-coding RNA (lncRNA) has been shown to be potential biomarker for cancer diagnosis and follow up. However, little is known about its application in esophageal squamous cell carcinoma (ESCC) detection. Here, we sought to develop a novel diagnostic model based on serum exosomal lncRNAs to improve ESCC screening efficiency. A multiphase, case-control study was conducted among 140 ESCC patients and 140 healthy controls. Microarray screening was performed to acquire differentially expressed exosomal lncRNAs in the discovery phase. The diagnostic model Index I was constructed based on a panel of three lncRNAs using logistic regression in the training phase, and were confirmed in a subsequent validation phase. A receiver operating characteristic (ROC) curve was generated to calculate the diagnostic value. The effects of the selected lncRNAs level on ESCC mortality were evaluated using a Cox hazard regression model and Kaplan-Meier curve analysis, and the expression level with clinicopathological features was also calculated. Finally, we explored the oncogenic potential of candidate lncRNA RASSF8-AS1 in vitro and by target mRNA sequencing. Index I was able to discriminate ESCC patients from healthy controls, and showed superiority to classic tumor biomarkers. Moreover, serum levels of the exosomal lncRNAs correlated with clinicopathological features and prognosis. The in vitro assays showed that RASSF8-AS1 played an oncogenic role in ESCC. Target mRNA scanning results suggested involvement of RASSF8-AS1 in tumor immunity and metabolism. The newly identified serum exosomal lncRNAs could be used as new biomarkers for ESCC, and showed oncogenic potential in ESCC.

Squamous Cell Carcinoma of the Esophagus.

Esophageal squamous cell carcinoma (ESCC) is common in the developing world with decreasing incidence in developed countries and carries significant morbidity and mortality. Major risk factors for ESCC development include significant use of alcohol and tobacco. Screening for ESCC can be recommended in high-risk populations living in highly endemic regions. The treatment of ESCC ranges from endoscopic resection therapy or surgery in localized disease to chemoradiotherapy in metastatic disease, and prognosis is directly related to the stage at diagnosis. New immunotherapies and molecular targeted therapies may improve the dismal survival outcomes in patients with metastatic ESCC.

Absence of NOTCH1 mutation and presence of CDKN2A deletion predict progression of esophageal lesions.

Currently, surveillance for esophageal squamous cell carcinoma (ESCC) runs a risk of underestimation of early lesions which show absence of iodine staining, with no or only mild histologic changes. The development of molecular markers that indicate risk of progression is thus warranted. We performed whole-exome sequencing on biopsies from two sequential endoscopies of a single esophageal lesion and matching blood samples. There were 27 pairs of age-, gender-, pathologic stage-, and sampling interval-matched progressors and non-progressors identified in a prospective community-based ESCC screening trial. Putative molecular progression markers for ESCC were first evaluated by comparing somatic mutation, copy number alteration (CNA), and mutational signature information among progressors and non-progressors. These markers were then validated with another 24 pairs of matched progressors and non-progressors from the same population using gene alteration status identified by target sequencing and quantitative PCR. Progressors had more somatic mutation and CNA burden, as well as apolipoprotein B mRNA editing catalytic polypeptide-like and age-related signature weights compared with non-progressors. A gene score consisting of somatic NOTCH1 mutation and CDKN2A deletion is predictive of risk of progression in lesions which show absence of iodine staining under endoscopy but have no or only mild dysplasia. This gene score was also validated in an external cohort of matched progressors and non-progressors. Absence of NOTCH1 mutation and presence of CDKN2A deletion are markers of progression in squamous lesions of the esophagus. This gene score would be an ideal indicator for assisting the pathologist in the identification of high-risk individuals who could be potentially 'missed' or subject to a risk underestimation by histologic analysis, and might improve the performance of ESCC surveillance. © 2022 The Pathological Society of Great Britain and Ireland.

Endoscopic Surveillance for Premalignant Esophageal Lesions: A Community-Based Multicenter, Prospective Cohort Study

Mild and moderate dysplasia are major premalignant lesions of esophageal squamous cell carcinoma (ESCC); however, evidence of the progression risk in patients with these conditions is extremely limited. We aimed to assess the incidence and risk factors for advanced neoplasia in patients with mild-moderate dysplasia. This prospective cohort study included patients with mild-moderate dysplasia from 9 regions in rural China. These patients were identified from a community-based ESCC screening program conducted between 2010 and 2016 and were offered endoscopic surveillance until December 2021. We estimated the incidence of advanced esophageal neoplasia, including severe dysplasia, carcinoma in situ, or ESCC, and identified potential risk factors using the Cox regression model. The 1183 patients with mild-moderate dysplasia were followed up over a period of 6.95 years. During follow-up evaluation, 88 patients progressed to advanced neoplasia (7.44%), with an incidence rate of 10.44 per 1000 person-years. The median interval from the progression of mild-moderate dysplasia to advanced neoplasia was 2.39 years (interquartile range, 1.58-4.32y). A total of 74.47% of patients with mild-moderate dysplasia experienced regression tonondysplasia, and 18.09% showed no lesion progression. Patients with mild-moderate dysplasia who had a family history of esophageal cancer and were age 55 years and oldershowed 97% higher advanced neoplasia yields than all patients with mild-moderate dysplasia. In a country with a high incidence of ESCC, patients with mild-moderate dysplasia showed an overall risk of advanced neoplasia progression of 1.04% per year. Patients with mild-moderate dysplasia would be recommended for endoscopic surveillance during the first 2 to 3 years.

Feasibility of using P16 methylation as a cytologic marker for esophageal squamous cell carcinoma screening: A pilot study.

Early diagnosis and treatment of esophageal squamous cell dysplasia (ESCdys) and esophageal squamous cell carcinoma (ESCC) could significantly reduce the incidence and mortality of ESCC. This pilot study aimed to investigate whether P16/CDKN2A methylation could serve as a cytologic biomarker for early detection of ESCdys and ESCC. Paired esophageal biopsy and cytology specimens (exfoliated cells) were obtained from subjects at different stages of ESCC development. The methylation status of P16 gene in these two specimen types was determined using a 115-bp MethyLight assay. Categorical data were compared by the Chi-square test. Logistic regression was performed to assess adjusted odds ratios of P16 methylation associated with ESCC and ESCdys. Prediction models for identifying individuals at risk of ESCC and high-grade ESCdys (high-grade intraepithelial neoplasia, HGIN) were developed by multivariable logistic regression. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. Internal validation of the prediction models was performed using the 1000-bootstrap resample. A total of 105 subjects with diagnoses ranging from normal mucosa through ESCC were included in this study. An increase in P16 methylation frequency was observed with increasing severity of esophageal lesions (p for trend <0.001). In the adjusted logistic regression models, P16 methylation in cytology specimens was positively associated with ESCC and ESCdys risk, whereas P16 methylation in biopsy specimens was only associated with a higher risk of developing ESCC. The predictive capacity of base model I (AUC, 0.816) for ESCC and HGIN was significantly increased by adding P16 methylation in cytology specimens (model III; AUC, 0.882; p=0.043), but not P16 methylation in biopsy specimens (model II; AUC, 0.850; p=0.225). Bootstrap validation showed optimism-corrected AUC of 0.789 for model I, 0.822 for model II, and 0.854 for model III. P16 methylation as a cytologic marker was associated with the ESCC development and has the potential for application in minimally invasive ESCC screening.

Tumor-associated autoantibodies in ESCC screening: Detecting prevalent early-stage malignancy or predicting future cancer risk?

Background: To assess potential roles for tumor-associated autoantibodies (TAAs) in esophageal squamous cell carcinoma (ESCC) screening: detecting early-stage malignancy, and predicting future cancer risk.Methods: Thirteen candidate autoantibodies identified in previous literatures were measured using multiplex serological assays in sera from cases and matched controls nested in two population-level screening cohorts in China. To evaluate the role of TAAs in detecting prevalent esophageal malignant lesions, an identification set (150 cases vs. 560 controls) and an external validation set (34 cases vs. 121 controls) were established with pre-screening sera collected ≤ 12 months prior to screening-related diagnosis. To explore the role of TAAs in predicting future ESCC risk, an exploration set (105 cases vs. 416 controls) with pre-diagnostic sera collected > 12 months before clinical diagnosis was established. Two models, the questionnaire-based model and full model additionally incorporating TAA markers, were constructed. Area under the receiver operating characteristic curve (AUC) and net reclassification improvement (NRI) were calculated to compare the performance of the two models.Findings: In the identification set, NY-ESO-1 (OR=2·12, 95% CI=1·02-4·40) and STIP1 (OR=1·83, 95% CI=1·10-3·05) were positively associated with higher risk of esophageal malignancy. Elevated MMP-7 was associated with higher risk of malignancy in females (ORfemale=5·07, 95% CI=1·30-19·71). The estimates in validation set were consistent with these results, but were close to null in exploration set. Integration of selected TAAs improved the performance of questionnaire-based models in detecting prevalent esophageal malignancy (female: AUCfull model=0·745, 95% CI=0·675-0·814, AUCquestionnaire-based model=0·658, 95% CI=0·585-0·732, NRI=0·604, P<0·0001; male: AUCfull model=0·662, 95% CI=0·596-0·728, AUCquestionnaire-based model=0·619, 95% CI=0·548-0·690, NRI=0·357, P=0·0028). This improvement was also seen in validation set, but was not similarly effective in distinguishing long-term incident cases from healthy controls.Interpretation: Serological autoantibodies against NY-ESO-1, STIP1, and MMP-7 perform well in detecting early-stage esophageal malignancy, but are less effective in predicting future ESCC risks.Funding: This work was supported by the National Science & Technology Fundamental Resources Investigation Program of China (2019FY101102), the National Natural Science Foundation of China (82073626), the National Key R&D Program of China (2016YFC0901404), the Beijing-Tianjin-Hebei Basic Research Cooperation Project (J200016), the Digestive Medical Coordinated Development Center of Beijing Hospitals Authority (XXZ0204), and the Natural Science Foundation of Beijing Municipality (7182033).

Feasibility and Accuracy of Artificial Intelligence–Assisted Sponge Cytology for Community-Based Esophageal Squamous Cell Carcinoma Screening in China

Screening is the pivotal strategy to relieve the burden of esophageal squamous cell carcinoma (ESCC) in high-risk areas. The cost, invasiveness, and accessibility of esophagogastroduodenoscopy (EGD) necessitate the development of preliminary screening methods. Residents aged 40-85 years were recruited in a high-risk area of ESCC. Esophageal cells were collected using an approved novel capsule sponge, and cytology slides were scanned by a trained artificial intelligence (AI) system before cytologists provided confirmation. Atypical squamous cell or more severe diagnosis was defined as positive cytology. AI-based abnormal cell counts were also reported. EGD was performed subsequently with biopsy as needed. Diagnostic accuracy, adverse events, and acceptability of cytology testing were assessed. Esophageal high-grade lesions (ESCC and high-grade intraepithelial neoplasia) were the primary target lesions. In total, 1,844 participants were enrolled, and 20 (1.1%) high-grade lesions were confirmed by endoscopic biopsy. The AI-assisted cytologist-confirmed cytology showed good diagnostic accuracy, with a sensitivity of 90.0% (95% confidence interval [CI], 76.9%-100.0%), specificity of 93.7% (95% CI, 92.6%-94.8%), and positive predictive value of 13.5% (95% CI, 7.70%-19.3%) for detecting high-grade lesions. The area under the receiver operation characteristics curve was 0.926 (95% CI, 0.850-1.000) and 0.949 (95% CI, 0.890-1.000) for AI-assisted cytologist-confirmed cytology and AI-based abnormal cell count, respectively. The numbers of EGD could be reduced by 92.5% (from 99.2 to 7.4 to detect 1 high-grade lesion) if only cytology-positive participants were referred to endoscopy. No serious adverse events were documented during the cell collection process, and 96.1% participants reported this process as acceptable. The AI-assisted sponge cytology is feasible, safe, and acceptable for ESCC screening in community, with high accuracy for detecting esophageal squamous high-grade lesions.

Analyzing the Expression Level and Associated Clinical Characteristics of miRNA-138 in Esophageal Squamous Cell Carcinoma in Iranian Patients

Background: Esophageal Squamous Cell Carcinoma (ESCC) is the seventh most common and lethal malignancy worldwide with a high incidence in Iran. Esophageal cancer has a poor prognosis and low 5-years survival rate. Despite several studies on esophageal cancer, its underlying mechanism remains unclear. Therefore, it is significant to analyze the molecular factors involved in disease for introducing effective diagnosis and therapeutic approaches. Accordingly, the aberrant expression of miRNA was demonstrated in the etiology of esophageal cancer, and applying them as detecting biomarkers was further considered by researchers. This study aimed to evaluate the expression level of miRNA-138 in the tumor tissues of ESCC and normal adjacent tissues. Objective: In total, 35 samples of tumor and normal tissues of the esophagus were collected from ESCC patients. Methods: Then, RNA extraction was conducted and the expression level of miRNA-138 was assessed in the collected tissue samples, applying real-time RT-PCR. Moreover, the relationship between the miRNA-138 expression level and the patient’s clinical characteristics was assessed. Results: According to the obtained results, the expression of miR-138 was significantly downregulated in the tumor tissues of ESCC, compared to normal adjacent tissues (P&lt;0.05). Additionally, the level of miRNA-138 downregulation was significantly correlated with tumor differentiation degree and metastasis status (P&lt;0.05). Conclusion: The significant downregulation of miRNA-138 in the tumor samples of ESCC indicated the role of this epigenetic alteration in esophageal carcinogenesis. Therefore, applying the miRNA-138 could be considered as a potential molecular biomarker for ESCC diagnosis and screening.

Improved esophageal squamous cell carcinoma screening effectiveness by risk-stratified endoscopic screening: evidence from high-risk areas in China.

BackgroundRisk‐stratified endoscopic screening (RSES), which offers endoscopy to those with a high risk of esophageal cancer, has the potential to increase effectiveness and reduce endoscopic demands compared with the universal screening strategy (i.e., endoscopic screening for all targets without risk prediction). Evidence of RSES in high‐risk areas of China is limited. This study aimed to estimate whether RSES based on a 22‐score esophageal squamous cell carcinoma (ESCC) risk prediction model could optimize the universal endoscopic screening strategy for ESCC screening in high‐risk areas of China.MethodsEight epidemiological variables in the ESCC risk prediction model were collected retrospectively from 26,618 individuals aged 40‐69 from three high‐risk areas of China who underwent endoscopic screening between May 2015 and July 2017. The model's performance was estimated using the area under the curve (AUC). Participants were categorized into a high‐risk group and a low‐risk group with a cutoff score having sensitivities of both ESCC and severe dysplasia and above (SDA) at more than 90.0%.ResultsThe ESCC risk prediction model had an AUC of 0.80 (95% confidence interval: 0.75–0.84) in this external population. We found that a score of 8 (ranging from 0 to 22) had a sensitivity of 94.2% for ESCC and 92.5% for SDA. The RSES strategy using this threshold score would allow 50.6% of endoscopies to be avoided and save approximately US$ 0.59 million compared to universal endoscopic screening among 26,618 participants. In addition, a higher prevalence of SDA (1.7% vs. 0.9%), a lower number need to screen (60 vs. 111), and a lower average cost per detected SDA (US$ 3.22 thousand vs. US$ 5.45 thousand) could have been obtained by the RSES strategy.ConclusionsThe RSES strategy based on individual risk has the potential to optimize the universal endoscopic screening strategy in ESCC high‐risk areas of China.

Targeted proteomics-derived biomarker profile develops a multi-protein classifier in liquid biopsies for early detection of esophageal squamous cell carcinoma from a population-based case-control study

BackgroundEarly diagnosis of esophageal squamous cell carcinoma (ESCC) remains a challenge due to the lack of specific blood biomarkers. We aimed to develop a serum multi-protein signature for the early detection of ESCC.MethodsWe selected 70 healthy controls, 30 precancerous patients, 60 stage I patients, 70 stage II patients and 70 stage III/IV ESCC patients from a completed ESCC case-control study in a high-risk area of China. Olink Multiplex Oncology II targeted proteomics panel was used to simultaneously detect the levels of 92 cancer-related proteins in serum using proximity extension assay.ResultsWe found that 10 upregulated and 13 downregulated protein biomarkers in serum could distinguish the early-stage ESCC from healthy controls, which were validated by the significant dose-response relationships with ESCC pathological progression. Applying least absolute shrinkage and selection operator (LASSO) regression and backward elimination algorithm, ANXA1 (annexin A1), hK8 (kallikrein-8), hK14 (kallikrein-14), VIM (vimentin), and RSPO3 (R-spondin-3) were kept in the final model to discriminate early ESCC cases from healthy controls with an area under curve (AUC) of 0.936 (95% confidence interval: 0.899 ~ 0.973). The average accuracy rates of the five-protein classifier were 0.861 and 0.825 in training and test data by five-fold cross-validation.ConclusionsOur study suggested that a combination of ANXA1, hK8, hK14, VIM and RSPO3 serum proteins could be considered as a potential tool for screening and early diagnosis of ESCC, especially with the establishment of a three-level hierarchical screening strategy for ESCC control.