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90 active trials for Esophageal Squamous Cell Carcinoma

Multimodal Functional Imaging Combined With Metabolomics in Predicting the Efficacy of nCRT for Locally Advanced ESCC

Esophageal cancer (EC) is the seventh most frequently diagnosed cancers and the sixth leading causes of cancer death worldwide . It is one of the most common malignancy in China, with the third highest morbidity and mortality rate. More than 90% of patients with EC in China have esophageal squamous cell carcinoma (ESCC). Neoadjuvant chemoradiotherapy (nCRT) followed by surgery is currently widely used strategy for locally advanced surgical EC. At present, conventional imaging methods have certain defects (focus only on the volume change) in the evaluation of the efficacy of nCRT. Whereas functional imaging can more comprehensively reflect the biological and microstructural characterization of tumors. The changes of these aspects of tumors can be observed earlier than volumetric changes of tumors. The normal metabolism of the body is the basis for ensuring life activities. Due to the increased energy demand and proliferation of tumor tissue in patients with cancer, the metabolism of patients is different from that of normal person. Thus, the metabolic alterations seen in cancer cells have emerged as one of the hallmarks of cancer. Previous metabolomic studies have demonstrated various metabolic alterations in patients with ESCC. Many metabolites have been found to be promising diagnostic, staging or prognostic biomarkers for ESCC. However, there are few studies on metabolic markers on the chemoradiation sensitivity of esophageal cancer. Therefore, the aim of the present study is to evaluate the value of functional imaging parameters and metabolic markers in assessing and predicting pathological response in patients who underwent nCRT for ESCC.

Start: January 2020
Carrelizumab, Chemotherapy and Apatinib in the Neoadjuvant Treatment of Resectable Esophageal Squamous Cell Carcinoma

China with high incidence of esophageal cancer, the number of new cases and deaths account for about 50% of the world every year. In the past few decades, surgery, radiotherapy, chemotherapy and other treatments were continuously improved, however, the mortality of esophageal squamous cell carcinoma patients was not significantly decreased. For patients with locally advanced esophageal cancer, direct surgery is not effective. It is difficult to achieve radical resection by surgery merely, and even if many patients receive surgery, they may eventually have tumor recurrence and poor survival rate. Therefore, it is necessary to explore effective perioperative neoadjuvant treatment to reduce the risk of postoperative recurrence and improve the postoperative survival rate of patients. According to the reports, the expression of PD-L1 in esophageal cancer was about 41.4%. Therefore, PD-1/ PD-L1 immunocheckpoint inhibitor may become a new method for the treatment of esophageal cancer. Preliminary clinical results showed that immunotherapy combined with chemoradiotherapy provided a synergies antitumor effect. Multiple clinical results showed that Carrillizumab provided higher overall response rate for advanced esophageal cancer. However, in patients with locally advanced esophageal cancer, the efficacy of Carrillizumab combined with chemotherapy and apatinib for sequential radical surgery is still unclear. The purpose of this study is to observe and evaluate the efficacy and safety of Carrillizumab combined with chemotherapy and antiangiogenic drugs in the neoadjuvant therapy of resectable esophageal squamous cell carcinoma.

Start: November 2020
Preoperative Image-guided Identification of Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

Rationale: For locally advanced esophageal cancer the standard treatment consists of 5 weeks of neoadjuvant chemoradiotherapy (nCRT) followed by surgery. Surgery is currently performed independent of the response to nCRT and is associated with substantial morbidity. Prior knowledge of the eventual response to nCRT would greatly impact on the optimal care for many esophageal cancer patients for two imperative reasons: Firstly, it is argued that patients who achieved a pathologic complete response (pCR, 29%) may not have benefitted from surgery. Consequently, proper identification of pathological complete responders prior to surgery could yield an organ-preserving regimen avoiding unnecessary toxicity. Secondly, non-responders are exposed to the side effects of nCRT without showing any tumor regression. Early identification of the non-responders during nCRT would be beneficial for this group as ineffective therapy could be stopped, and for who altered treatment strategies could be explored. Objective: To develop a multimodal model that predicts the probability of pathologic complete response to nCRT in esophageal cancer, by integrating diffusion weighted magnetic resonance imaging (DW-MRI) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in conjunction with combined 18F-fluorodeoxyglucose positron emission tomography and computed tomography (18F-FDG PET-CT) scans acquired prior to, during and after administration of nCRT. Study design: Multi-center observational study Study population: Patients (>18 years) with potentially resectable locally advanced squamous cell- or adenocarcinoma of the esophagus or gastroesophageal junction, receiving nCRT prior to surgery. Intervention: In addition to the standard diagnostic work-up for esophageal cancer that includes a 18F-FDG PET-CT scan at diagnosis and after nCRT, one 18F-FDG PET-CT scans will be performed during nCRT, as well as three MRI scans (before, during and after nCRT) within fixed time intervals. Furthermore, after response imaging after nCRT has been performed, but prior to surgery, patients will undergo (on an opt-out basis) an endoscopy and/or endoscopic ultrasonography (EUS) with biopsies of the primary tumor site, other suspected lesions and suspected lymph nodes. Furthermore, blood samples will be collected at three time points. Main study parameters/endpoints: An accurate multimodal prediction model for the patients' individual probability of pathologic complete response after nCRT, based on the quantitative parameters derived from a longitudinal series of DW-MRI, DCE-MRI and 18F-FDG PET-CT datasets.

Start: April 2018