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Background: Radical concurrent chemoradiotherapy (CCRT) is frequently used as the first-line treatment for patients with locally advanced esophageal cancer. Unfortunately, some patients respond poorly. To predict response to radical concurrent chemoradiotherapy in pre-treatment patients with esophageal squamous carcinoma (ESCC), and compare the predicting efficacies of radiomics features of primary tumor with or without regional lymph nodes, we developed a radiomics-clinical model based on the positioning CT images. Finally, SHapley Additive exPlanation (SHAP) was used to explain the models. Methods: This retrospective study enrolled 105 patients with medically inoperable and/or unresectable ESCC who underwent radical concurrent chemoradiotherapy (CCRT) between October 2018 and May 2023. Patients were classified into responder and non-responder groups with RECIST standards. The 11 recently admitted patients were chosen as the validation set, previously admitted patients were randomly split into the training set (n = 70) and the testing set (n = 24). Primary tumor site (GTV), the primary tumor and the uninvolved lymph nodes at risk of microscopic disease (CTV) were identified as Regions of Interests (ROIs). 1762 radiomics features from GTV and CTV were respectively extracted and then filtered by statistical differential analysis and Least Absolute Shrinkage and Selection Operator (LASSO). The filtered radiomics features combined with 13 clinical features were further filtered with Mutual Information (MI) algorithm. Based on the filtered features, we developed five models (Clinical Model, GTV Model, GTV-Clinical Model, CTV Model, and CTV-Clinical Model) using the random forest algorithm and evaluated for their accuracy, precision, recall, F1-Score and AUC. Finally, SHAP algorithm was adopted for model interpretation to achieve transparency and utilizability. Results: The GTV-Clinical model achieves an AUC of 0.82 with a 95% confidence interval (CI) of 0.76–0.99 on testing set and an AUC of 0.97 with a 95% confidence interval (CI) of 0.84–1.0 on validation set, which are significantly higher than those of other models in predicting ESCC response to CCRT. The SHAP force map provides an integrated view of the impact of each feature on individual patients, while the SHAP summary plots indicate that radiomics features have a greater influence on model prediction than clinical factors in our model. Conclusion: GTV-Clinical model based on texture features and the maximum diameter of lesion (MDL) may assist clinicians in pre-treatment predicting ESCC response to CCRT. [ABSTRACT FROM AUTHOR]

Background: To evaluate and compare the potential performance of various diffusion parameters obtained from mono-exponential model (MEM)-, bi-exponential model (BEM)-, and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in grading of esophageal squamous carcinoma (ESC). Methods: Eighty-two patients with pathologically confirmed ESC without treatment underwent multi-b-value DWI scan with 13 b values (0~12,00 s/mm2). The apparent diffusion coefficient (ADC) deriving from the MEM; the pure molecular diffusion (ADCslow), pseudo-diffusion coefficient (ADCfast), perfusion, and fraction (f) deriving from the BEM; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (a) deriving from the SEM were calculated and compared between poorly differentiated and well/moderately differentiated ESC, respectively. The prediction parameters and diagnostic efficiency were compared by drawing receiver operating characteristic (ROC) curves. Results: The ADC, ADCslow, ADCfast, and DDC in poorly ESC were significantly lower than those in well/moderately differentiated ones. By using only one parameter, ADCslow, DDC had the moderate diagnostic efficiency and the areas under the curve (AUC) were 0.758 and 0.813 in differentiating ESC. The DDC had the maximum AUC with sensitivity (88.00%) and specificity (68.42%). Combining ADC with ADCfast, ADCslow, and DDC and combining ADCslow with ADCfast can provide a higher diagnostic accuracy with AUC ranging from 0.756, 0.771, 0.816, and 0.793, respectively. Conclusion: Various parameters derived from different DWI models including MEM, BEM, and SEM were potentially helpful in grading ESC. DDC obtained from SEM was the most promising diffusion parameter for predicting the grade of ESC. [ABSTRACT FROM AUTHOR]

Background and Purpose: This study aimed to evaluate the geometrical differences in and metabolic parameters of 18F-fluorodeoxyglucose positron emission tomography–computed tomography (18F-FDG PET-CT) and diffusion-weighted magnetic resonance imaging (DW-MRI) performed before and during radiotherapy (RT) for patients with esophageal cancer based on the three-dimensional CT (3DCT) medium and explore whether the high signal area derived from DW-MRI can be used as a tool for an individualized definition of the volume in need of dose escalation for esophageal squamous cancer. Materials and Methods: Thirty-two patients with esophageal squamous cancer sequentially underwent repeated 3DCT, 18F-FDG PET-CT, and enhanced MRI before the initiation of RT and after the 15th fraction. All images were fused with 3DCT images through deformable registration. The gross tumor volume (GTV) was delineated based on PET Edge on the first and second PET-CT images and defined as GTVPETpre and GTVPETdur, respectively. GTVDWIpre and GTVDWIdur were delineated on the first and second DWI and corresponding T2-weighted MRI (T2W-MRI)-fused images. The maximum, mean, and peak standardized uptake values (SUVs; SUVmax, SUVmean, and SUVpeak, respectively); metabolic tumor volume (MTV); and total lesion glycolysis(TLG) and its relative changes were calculated automatically on PET. Similarly, the minimum and mean apparent diffusion coefficient (ADC; ADCmin and ADCmean) and its relative changes were measured manually using ADC maps. Results: The volume of GTVCT exhibited a significant positive correlation with that of GTVPET and GTVDWI (both p < 0.001). Significant differences were observed in both ADCs and 18F-FDG PET metabolic parameters before and during RT (both p < 0.001). No significant correlation was observed between SUVs and ADCs before and during RT (p = 0.072–0.944) and between ∆ADCs and ∆SUVs (p = 0.238–0.854). The conformity index and degree of inclusion of GTVPETpre to GTVDWIpre were significantly higher than those of GTVPETdur to GTVDWIdur (both p < 0.001). The maximum diameter shrinkage rate (∆LDDWI) (24%) and the tumor volume shrinkage rate (VRRDWI) (60%) based on DW-MRI during RT were significantly greater than the corresponding PET-based ∆LDPET (14%) and VRRPET (41%) rates (p = 0.017 and 0.000, respectively). Conclusion: Based on the medium of CT images, there are significant differences in spatial position, biometabolic characteristics, and the tumor shrinkage rate for GTVs derived from 18F-FDG PET-CT and DW-MRI before and during RT for esophageal squamous cancer. Further studies are needed to determine if DW-MRI will be used as tool for an individualized definition of the volume in need of dose escalation. [ABSTRACT FROM AUTHOR]

Background and Objective: The intercourse between Esophageal squamous cell carcinoma etc. (ESC) and Celiac disease (CD) is still a complicated subject. The purpose of this research was to define the relationship between CD and ESC, and the factors associated with CD in patients with ESC. Methods: This research was conducted by Van University Medical Center in Turkey from 2012 to 2016. CD was identified by analyzing duodenal biopsy materials from 63 ESC patients via histopathologic examinations. Serum samples from the patients were also serologically tested to identify CD. A control group was selected from among subjects who underwent gastroduodenoscopy due to dyspepsia. Distinctions between case characteristics were evaluated with chi-square tests and t-tests for categorical and continuous factors, respectively. Results: Of the 63 study cases, 6 (9.5%) were both histological and serological positive for CD. Of the 290 control group, 8 (2.8%) had histopathological CD and tested positive for celiac antibodies. The patients with ESC had a significantly higher prevalence of CD compared to the dyspeptic patients (p<0.001). In addition, the mean creatinine levels of ESC patients with histopathological-proven CD were higher than those without CD (p=0.026). Furthermore, ESC patients who tested positive for tTg IgA had significantly higher levels of glucose and AST than those who were negative for tTg IgA (p=0.032) and (p=0.008), respectively. Conclusion: The present study demonstrated a statistically significant positive correlation between ESC and CD. Most remarkably, higher creatinine, glucose, and AST levels may predict CD in patients with ESC. These evidences may lead novel approaches for preventing ESC in patients with CD. [ABSTRACT FROM AUTHOR]

Background: There is increased interest in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting the outcomes of patients with advanced esophageal cancer.Purpose: To explore whether DCE-MRI histogram parameters can predict 12-month progression-free survival (PFS) in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiation therapy (CRT).Material and Methods: This retrospective study enrolled 134 patients with advanced esophageal squamous carcinoma who were receiving CRT. The pre-CRT DCE-MRI histogram parameters (median, mean, SD, skewness, kurtosis, and 10th and 90th percentiles) of Ktrans, Kep, and Ve were collected. PFS analyses were performed using the Kaplan-Meier method and log-rank tests to compute the survival curves. The significant prognostic predictors among the data characteristics and DCE-MRI parameters were determined using multivariate Cox proportional hazards regression analyses.Results: There were 65 good responders (PFS ≥ 12 months) and 69 poor responders (PFS < 12 months). The median and mean values of Ktrans were higher, and the kurtosis value of Ktrans was lower in good responders. The median, mean, and 10th and 90th percentile values of Ktrans were higher, and the kurtosis values of Ktrans and Ve were lower in good responders. The PFS of patients aged ≥60 years, a CR effect, or a 10th percentile value of Ktrans ≥0.13 was increased (P < 0.001, <0.001, and 0.014, respectively).Conclusion: DCE-MRI histogram parameters can be used to evaluate the response to CRT in patients with advanced esophageal squamous carcinoma. The 10th percentile value of Ktrans has significant prognostic value for 12-month PFS. [ABSTRACT FROM AUTHOR]

Abundant evidence indicates that long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) serve important roles in tumorigenesis and tumour progression. However, their diagnostic and treatment value for esophageal squamous carcinoma (ESCC) remains unknown. A microarray (SBC human ceRNA array V1.0) was performed to assess the expression profiles and biological functions of lncRNAs, circRNAs and mRNAs in ESCC and para-cancerous tissues from three patients. Microarray data were validated by reverse transcription-quantitative polymerase chain reaction for a group of genes. A number of lncRNA-microRNAs (miRNA) and circRNA-miRNA-mRNA networks were constructed. Bioinformatics tools, including gene ontology and Kyoto Encyclopedia of Genes and Genomes biological pathway analyses, were used to predict the functions of differentially expressed lncRNAs, circRNAs and potentially co-expressed target genes. The results revealed that compared with the expression levels of para-cancerous tissues, 1,384 lncRNAs, 2,046 circRNAs and 936 mRNAs were frequently altered in ESCC tissues. Co-expression networks of lncRNAs-miRNAs-circRNAs-mRNAs were constructed based on the correlation analyses among the differentially expressed RNAs. Furthermore, using bioinformatics methods, correlation expression networks were constructed that included cis- and trans-regulatory elements. Therefore, these results suggest that lncRNAs and circRNAs may be involved in the pathogenesis and development of ESCC. These findings provide a novel and systematic perspective on the potential function of noncoding RNAs in ESCC. [ABSTRACT FROM AUTHOR]

Esophageal squamous carcinoma (ESCC) is a prevalent and highly lethal malignant tumor, with a five-year survival rate of approximately 20 %. Tumor-associated macrophages (TAMs) are the most prominent immune cells in the tumor microenvironment (TME), comprising over 50 % of the tumor volume. TAMs can be polarized into two distinct phenotypes, M1-type and M2-type, through interactions with cancer cells. M2-type TAMs are more abundant than M1-type TAMs in the TME, contributing to tumor progression, such as tumor cell survival and the construction of an immunosuppressive environment. This review focuses on the role of TAMs in ESCC, including their polarization, impact on tumor proliferation, angiogenesis, invasion, migration, therapy resistance, and immunosuppression. In addition, we discuss the potential of targeting TAMs for clinical therapy in ESCC. A thorough comprehension of the molecular biology about TAMs is essential for the development of innovative therapeutic strategies to treat ESCC. [Display omitted] • Summary of TAMs polarization in the tumor microenvironment. • A review on the role of TAMs in the progression and metastasis in ESCC. • Contribution of TAMs to treatment resistance and immunosuppressive microenvironment formation in ESCC. • Proposal of the possibility of targeting TAMs for the ESCC therapy. [ABSTRACT FROM AUTHOR]

• Apply machine learning methods and multi-omics profiling. • Describe a comprehensive landscape of ESCC immune infiltration patterns. • Reveal the mechanism of esophageal squamous carcinoma (ESCC) and immune microenvironment. To explore the molecular mechanism in the esophageal squamous carcinoma (ESCC) environment, we selected datasets of ESCC patients from The Cancer Genome Atlas (TCGA) (n = 78) and explored the infiltration condition of 24 immune cells in each sample. We assorted the microenvironment of ESCC into two Infiltration groups (I and II) and built a random forest classifier model. We showed traits of gene and clinicopathology in the tumor microenvironment (TME) phenotypes systematically. Infiltration I had low infiltration of immune cells and immunomodulators but relatively higher mutation load, while Infiltration II was enriched with cytotoxic T cells and immunosuppressive cells. The upregulation of several immune cytokines like IFN-γ, TNF-β, and PD-L1 was seen in Infiltration II. The infiltration group was an independent predictor of prognosis showed by Multivariable Cox analysis (Infiltration II vs. I, hazard ratio = 2.73, 95% confidence interval = 1.08–6.91, p = 0.03). All the results can be verified in datasets from the Gene Expression Omnibus database (GEO) and our institution (n = 98). Our results demonstrate a synthesis of the infiltration pattern of the immune in ESCC. We reveal the mechanism of TME, which may contribute to the progress of immunotherapy for patients with ESCC. [ABSTRACT FROM AUTHOR]