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IL6 and BCL3 Expression Are Potential Biomarkers in Esophageal Squamous Cell Carcinoma.

ABSTRACT: Esophageal squamous cell carcinoma (ESCC) ranks among the most lethal tumors worldwide, as a consequence of late detection and poor treatment response, evidencing the need for diagnosis anticipation and new therapeutic targets. First, we investigated the IL6 gene and protein expression in the esophagus of individuals without esophageal disorders (healthy), ESCC, and non-tumoral surrounding tissue (NTST). Our results showed that IL6 mRNA and protein expression is upregulated in tumor cells relative to NTST. In the TCGA dataset, we identified a set of genes whose expression was correlated with IL6 mRNA levels, including the antiapoptotic gene BCL3. By using an immortalized esophageal cell line, we confirmed that IL6 was capable of inducing BCL3 expression in esophageal cells. BCL3 mRNA and protein are overexpressed in ESCC and NTST compared to healthy esophagus, and BCL3 mRNA could distinguish the morphologically normal samples (healthy and NTST) with 100% sensitivity and 95.12% specificity. The spatial intratumoral heterogeneity of both IL6 and BCL3 expression was evaluated, corroborating IL6 upregulation throughout the tumor, while tumor and NTST showed a consistent increase of BCL3 expression relative to the healthy esophagus. Our study shows that IL6 overexpression seems to be a key event in ESCC carcinogenesis, contributing to ESCC through a homogeneous antiapoptotic signalling via BCL3 overexpression, thus suggesting anti-IL6 therapies to be further considered for ESCC treatment. Finally, our data support the use of BCL3 mRNA expression as a potential biomarker for ESCC detection.

SUBMITTER: Soares-Lima SC

PROVIDER: S-EPMC8371528 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Diagnostic and therapeutic biomarkers useful for esophageal squamous cell carcinoma (ESCC) have the ability to increase the long term survival of cancer patients. A metabolomics study, using plasma from four groups including ESCC patients before, during, and after chemoradiotherapy (CRT) and healthy controls, was originally carried out by LC-MS to determine global alterations in the metabolic profiles and find biomarkers potentially applicable to diagnosis and monitoring treatment effects. It is worth pointing out that a clear clustering and separation of metabolic data from the four groups was observed, which indicated that disease status and treatment intervention resulted in specific metabolic perturbations in the patients. A series of metabolites were found to be significantly altered in ESCC patients versus healthy controls and in pre- versus post-treatment patients based on multivariate statistical data analysis (MVDA). To further validate the reliability of these potential biomarkers, an independent validation was performed by using the selected reaction monitoring (SRM) based targeted approach. Finally, 18 most significantly altered plasma metabolites in ESCC patients, relative to healthy controls, were tentatively identified as lysophosphatidylcholines (lysoPCs), fatty acids, l-carnitine, acylcarnitines, organic acids, and a sterol metabolite. The classification performance of these metabolites were analyzed by receiver operating characteristic (ROC)(1) analysis and a biomarker panel was generated. Together, biological significance of these metabolites was discussed. Comparison between pre- and post-treatment patients generated 11 metabolites as potential therapeutic biomarkers that were tentatively identified as amino acids, acylcarnitines, and lysoPCs. Levels of three of these (octanoylcarnitine, lysoPC(16:1), and decanoylcarnitine) were closely correlated with treatment effect. Moreover, variation of these three potential biomarkers was investigated over the treatment course. The results suggest that these biomarkers may be useful in diagnosis, as well as in monitoring therapeutic responses and predicting outcomes of the ESCC.

Project description:Background: Esophageal squamous cell carcinoma (ESCC) is one of the most fatal diseases worldwide. Because early diagnosis is difficult, ESCC is mostly diagnosed at an advanced stage, leading to a poor overall prognosis. The purpose of this study was to explore the differences between plasma metabolic profiles in ESCC patients and healthy controls and to establish a diagnostic model of ESCC. Methods: In this study, a cohort of 310 subjects, containing 140 ESCC patients and 170 healthy controls (HC), was recruited. Participants were randomly separated into a training set (80 ESCCs, 80 HCs) and a validation set (60 ESCCs, 90 HCs) and their plasma metabolomics profiles were analyzed by ultra-performance liquid chromatography-tandem quadruple time-of-flight mass spectrometry (UPLC-QTOF/MS) technique. Univariate statistical analysis and multivariate analysis (MVA) methods were used to identify differential metabolites. Finally, the dysregulated pathways associated with ESCC were further explored and the diagnostic performance of the biomarker panel was evaluated. Results: Metabolic analyses identified 34 significant metabolites involved in the metabolism of amino acids, phospholipids, fatty acids, purine, and choline. Farthermore, an effective diagnostic model for ESCC was constructed based on eight metabolites. This panel of biomarkers consisted of hypoxanthine, proline betaine, indoleacrylic acid, inosine, 9-decenoylcarnitine, tetracosahexaenoic acid, LPE (20:4), and LPC (20:5). The model was verified and evaluated in the validation set. The AUC value of the ROC curve was 0.991(95% CI: 0.981-1.000, CI, Confidence interval), with a sensitivity (SE) of 98.8% and a specificity (SP) of 94.9% for the training set and 0.965(95% CI: 0.936-0.993), with a SE of 88.3% and a SP of 88.9% for the validation set. Among them, three biomarkers, indoleacrylic acid, LPC (20:5), and LPE (20:4), exhibited a trend associated with the ESCC progression. Conclusions: Our study identified a novel plasma biomarker panel, which clearly distinguishes ESCC patients and provides insight into the mechanisms of ESCC. This finding may form the basis for the development of a minimally invasive method for ESCC detection.

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IL6 and BCL3 Expression Are Potential Biomarkers in Esophageal Squamous Cell Carcinoma.

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