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Simple Summary: Esophageal squamous cell carcinoma (ESCC) is a malignancy characterized by high mortality and dismal quality of life. Circulating tumor cells (CTCs), considered precursors of distant metastasis, can be analyzed using a non-invasive liquid biopsy approach to identify patients at risk of cancer progression or recurrence. The current study employed an unbiased size-based CTC enrichment strategy in combination with quantitative reverse transcription polymerase chain reaction (RT-qPCR) to investigate gene transcripts as potential biomarkers in the bloodstream. We categorized 83.6% (46/55) of ESCC patients as CTC-positive, each displaying at least two detected markers. Furthermore, 50.9% (28/55) of ESCC patients were identified as CTC-high, showing at least five detected markers using a 10-gene CTC panel. The presence of specific markers, namely TWIST1, VEGFC, CCND1, and TFRC, was significantly associated with shorter survival of the patients, suggesting their prognostic values as liquid biopsy markers to guide clinical ESCC treatment decisions and enhance treatment efficacy. We investigated the clinical significance of CTCs in cancer progression by detecting multiple cancer driver genes associated with epithelial-to-mesenchymal transition (EMT) at the transcript level. The 10-gene panel, comprising CCND1, ECT2, EpCAM, FSCN1, KRT5, KRT18, MET, TFRC, TWIST1, and VEGFC, was established for characterizing CTCs from mouse ESCC xenograft models and clinical ESCC peripheral blood (PB) samples. Correlations between gene expression in CTCs from PB samples (n = 77) and clinicopathological features in ESCC patients (n = 55) were examined. The presence of CTCs at baseline was significantly correlated with tumor size (p = 0.031). The CTC-high patients were significantly correlated with advanced cancer stages (p = 0.013) and distant metastasis (p = 0.029). High mRNA levels of TWIST1 (Hazard Ratio (HR) = 5.44, p = 0.007), VEGFC (HR = 6.67, p < 0.001), TFRC (HR = 2.63, p = 0.034), and EpCAM (HR = 2.53, p = 0.041) at baseline were significantly associated with a shorter overall survival (OS) in ESCC patients. This study also revealed that TWIST1 facilitates EMT and enhances malignant potential by promoting tumor migration, invasion, and cisplatin chemoresistance through the TWIST1-TGFBI-ZEB1 axis in ESCC, highlighting the prognostic and therapeutic potential of TWIST1 in clinical ESCC treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Prognosis for patients with locally advanced esophageal squamous cell carcinoma (ESCC) remains poor mainly due to late diagnosis and limited curative treatment options. Neoadjuvant chemoradiotherapy (nCRT) plus surgery is considered the standard of care for patients with locally advanced ESCC. Currently, predicting prognosis remains a challenging task. Quantitative imaging radiomics analysis has shown promising results, but these methods are traditionally data-intensive, requiring a large sample size, and are not necessarily based on the underlying biology. Feature selection based on genomics is proposed in this work, leveraging differentially expressed genes to reduce the number of radiomic features allowing for the creation of a CT-based radiomic model using the genomics-based feature selection method. The established radiomic signature was prognostic for patients' long-term survival. The radiomic nomogram could provide a valuable prediction for individualized long-term survival. Purpose: To evaluate the prognostic value of baseline and restaging CT-based radiomics with features associated with gene expression in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant chemoradiation (nCRT) plus surgery. Methods: We enrolled 106 ESCC patients receiving nCRT from two institutions. Gene expression profiles of 28 patients in the training set were used to detect differentially expressed (DE) genes between patients with and without relapse. Radiomic features that were correlated to DE genes were selected, followed by additional machine learning selection. A radiomic nomogram for disease-free survival (DFS) prediction incorporating the radiomic signature and prognostic clinical characteristics was established for DFS estimation and validated. Results: The radiomic signature with DE genes feature selection achieved better performance for DFS prediction than without. The nomogram incorporating the radiomic signature and lymph nodal status significantly stratified patients into high and low-risk groups for DFS (p < 0.001). The areas under the curve (AUCs) for predicting 5-year DFS were 0.912 in the training set, 0.852 in the internal test set, 0.769 in the external test set. Conclusions: Genomics association was useful for radiomic feature selection. The established radiomic signature was prognostic for DFS. The radiomic nomogram could provide a valuable prediction for individualized long-term survival. [ABSTRACT FROM AUTHOR]

We investigated the clinical significance of CTCs in cancer progression by detecting multiple cancer driver genes associated with epithelial-to-mesenchymal transition (EMT) at the transcript level. The 10-gene panel, comprising CCND1, ECT2, EpCAM, FSCN1, KRT5, KRT18, MET, TFRC, TWIST1, and VEGFC, was established for characterizing CTCs from mouse ESCC xenograft models and clinical ESCC peripheral blood (PB) samples. Correlations between gene expression in CTCs from PB samples (n = 77) and clinicopathological features in ESCC patients (n = 55) were examined. The presence of CTCs at baseline was significantly correlated with tumor size (p = 0.031). The CTC-high patients were significantly correlated with advanced cancer stages (p = 0.013) and distant metastasis (p = 0.029). High mRNA levels of TWIST1 (Hazard Ratio (HR) = 5.44, p = 0.007), VEGFC (HR = 6.67, p < 0.001), TFRC (HR = 2.63, p = 0.034), and EpCAM (HR = 2.53, p = 0.041) at baseline were significantly associated with a shorter overall survival (OS) in ESCC patients. This study also revealed that TWIST1 facilitates EMT and enhances malignant potential by promoting tumor migration, invasion, and cisplatin chemoresistance through the TWIST1-TGFBI-ZEB1 axis in ESCC, highlighting the prognostic and therapeutic potential of TWIST1 in clinical ESCC treatment.