Clinical Research Directory

Validation of a Model for Predicting Duodenal Stump Leakage After Gastrectomy

This study aims to validate a machine learning model for predicting duodenal stump leakage after laparoscopic radical gastrectomy for gastric cancer.

A Phase I/II Study of MEDI4736 in Combination With Olaparib in Patients With Advanced Solid Tumors.

The purpose of this study is to look at the effectiveness, safety, and antitumor activity of study drugs MEDI4736 in combination with olaparib (modules 1, 2, 3, 4, 5 and 7) and MEDI4736 in combination with olaparib and bevacizumab (module 6). It will also examine what happens to the study drugs in the body and investigate how well the combination between MEDI4736, olaparib and bevacizumab is tolerated.

BOLD-100 in Combination With FOLFOX for the Treatment of Advanced Solid Tumours

BOLD-100 is an intravenously administered sterile solution containing the ruthenium-based small molecule. BOLD-100 has been shown to preferentially decrease the expression of GRP78 in tumour cells and ER stressed cells when compared to normal cells. BOLD-100 will be combined with cytotoxic FOLFOX chemotherapy in this study, with a dose escalation cohort to ensure tolerability and safety, followed by a cohort expansion phase.

Study to Evaluate the Diagnostic Performance of GEH300079 (68Ga) Injection PET/CT for Detection of PC in Patients With Colorectal, Gastric, Ovarian, or Pancreatic Cancers (PERISCOPE)

This study is a Phase 2/3, prospective, multicenter, open-label, non-randomized clinical trial, in which GEH300079 (68Ga) PET/CT images will be acquired in patients with primary colorectal, gastric, ovarian, or Pancreatic Ductal Adenocarcinoma (PDAC) cancers and known or suspected Peritoneal Carcinomatosis (PC) before or after institutional Standard of Care (SoC) imaging. The primary objective is to evaluate the diagnostic performance of GEH300079 (68Ga) PET/CT for the detection of PC in patients with colorectal, gastric, or ovarian primary cancers, using a composite standard of truth (SoT), in a region-based analysis. The detection of PC in patients with primary PDAC will be explored in the Phase 2 part of the study. The study is comprised of 2 distinct parts: Phase 2 aims to confirm the statistical and scientific assumptions for the Phase 3 part, and to confirm the optimal dose and timing of acquisition of GEH300079 (68Ga) PET/CT in the PC indication. Phase 2 includes 2 cohorts: Cohort A (participants with colorectal, ovarian and gastric primary cancer), and Cohort B (participants with primary PDAC), where analysis of Cohort B is descriptive only. Phase 3 aims to demonstrate the safety and efficacy of GEH300079 (68Ga) PET/CT for the detection of PC in patients with confirmed colorectal, gastric or ovarian primary cancers.

Tissue Procurement for Gastric Cancer, Gastrointestinal Stromal Tumors (GIST), Esophageal Cancer, Pancreas Cancer, Hepatocellular Cancer, Biliary Cancer, Neuroendocrine, Peritoneal Mesothelioma, Anal Cancer and Colorectal Cancer in Patients Undergoing Surgery or Biopsy

The purpose of this study is to collect and store normal and malignant tissue from patients with gastric cancer, GIST, esophageal cancer, pancreas cancer, hepatocellular cancer, biliary cancer, neuroendocrine, peritoneal mesothelioma, anal cancer and colorectal cancer, an estimated 50 to 100 of each tumor type. To collect and store blood samples from patients with gastric cancer, GIST, esophageal cancer, pancreas cancer, hepatocellular cancer, biliary cancer, neuroendocrine, peritoneal mesothelioma, anal cancer and colorectal cancer. To create a database for the collected tissue and allow access to relevant clinical information for current and future protocols. To create tissue microarrays for each gastrointestinal cancer subtype, namely, gastric cancer, GIST, esophageal cancer, pancreas cancer, hepatocellular cancer, biliary cancer, neuroendocrine, peritoneal mesothelioma, anal cancer and colorectal cancer, to facilitate future molecular studies. To grant access to Dr Kindler, Dr. Salgia, and Dr. Catenacci to this database (as it is being acquired) of the coupled patient tissue samples (normal and malignant) and relevant clinical information for the investigation of tyrosine kinases, such as Met and Ron, receptor tyrosine kinase family members, STATs, paxillin, focal adhesion proteins, cell motility/migration proteins, tyrosine/serine/threonine kinase family members, related molecules, and downstream targets implicated in the pathogenesis of GI cancers. Examples of molecular testing include evaluation of DNA mutation, alternative splice variants, protein expression and phosphorylation, and immunohistochemistry on samples. These studies will be correlated with clinical information as stated above.

Analysis of Lymph Node Metastasis and Tumor Deposit in the Short Gastric Mesentery Following Total Gastrectomy for Gastric Cancer

This study aims to explore lymph node metastasis in the short gastric mesentery following total gastrectomy with D2 lymphadenectomy plus complete mesogastric excision, providing evidence-based medicine for standardizing lymph node dissection in gastric cancer.

Robotic Gastrectomy for Locally Advanced Gastric Cancer After Neoadjuvant Therapy

This study is a prospective, open-label, single-arm phase II clinical trial designed to evaluate the safety and efficacy of robotic radical gastrectomy in patients with locally advanced gastric adenocarcinoma after undergoing neoadjuvant therapy. Conducted at multiple centers, the study aims to include 40 patients confirmed via histopathological and/or cytological analysis. Eligible participants must have stage III resectable gastric or gastroesophageal junction (GEJ) adenocarcinoma based on imaging studies such as ultrasound endoscopy, CT, or MRI. Patients will receive 3-4 cycles of neoadjuvant therapy, followed by imaging evaluations to assess the treatment response and determine eligibility for radical D2 gastrectomy. Within 2-6 weeks of the final neoadjuvant treatment cycle, eligible patients will undergo robotic radical gastrectomy. Key outcomes include post-surgical complications, pathological responses (pCR, MPR, TRG), and objective response rates (ORR), alongside disease-free survival (DFS) and overall survival (OS).

QL1706 Combined With SOX Used in Theperioperative Treatment

This is a single-center, single-arm clinical study to evaluate the efficacy and safety of QL1706 combined with SOX for the treatment of resectable locally advanced gastric or gastroesophageal junction adenocarcinoma. The study consists of the following two phases: Phase 1: The safety introduction phase of QL1706 combined with SOX, using a 3+3 design, enrolled about 6 to 12 patients with locally advanced gastric/gastroesophageal junction adenocarcinoma (primary clinical stage ≥T3 or N+, M0) and underwent 3-week DLT evaluation. Phase 2: This phase plans to enroll 42 to 45 patients, using investigator-evaluated pCR as the primary endpoint. QL1706 is administered by intravenous infusion of RP2D as defined in Part 1 starting from cycle 1. Preoperative QL1706 RP2D combined with SOX (3 cycles) → radical surgery (D2) → postoperative QL1706 RP2D combined with SOX (5 cycles) → postoperative maintenance of QL1706 RP2D (up to 1 year before and after surgery); neoadjuvant therapy Surgery should be performed within 3 to 6 weeks after the last dosing, with a minimum interval of 4 weeks after surgery and a maximum interval of 6 weeks recommended for postoperative adjuvant therapy.

Correlation of Psychological Distress and Immune Checkpoint Inhibitors in Gastric Cancer

1. Background Gastric cancer (GC) is a leading global cause of cancer-related mortality, with over 1 million new cases and 769,000 deaths in 2020. In China, 80% of patients present with advanced disease, for whom perioperative chemotherapy, surgery, and lymphadenectomy are standard. Recent phase III trials (Checkmate-649, KEYNOTE-062, ORIENT-16) demonstrate that immune checkpoint inhibitors (ICIs) combined with chemotherapy improve progression-free survival (PFS: 2.8-10.5 months) and overall survival (OS: 11.1-18.4 months) compared to chemotherapy alone. However, outcomes remain suboptimal, necessitating exploration of novel predictive biomarkers and resistance mechanisms. Emerging evidence implicates chronic stress in cancer progression and treatment response. Chronic stress activates the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic nervous system, elevating cortisol, catecholamines, and glucocorticoids. These hormones suppress immune function by reducing CD8+ T cells and natural killer (NK) cell activity while increasing immunosuppressive cells (e.g., regulatory T cells, myeloid-derived suppressor cells). Preclinical studies link chronic stress to metastasis via extracellular trap (NET) formation, impaired antitumor immunity, and resistance to PD-1/PD-L1 blockade. Clinically, chronic stress correlates with worse survival in non-small-cell lung cancer patients receiving ICIs. Despite these findings, psychological screening remains underutilized in oncology. This study aims to investigate the impact of chronic stress on ICI efficacy in advanced gastric cancer. 2. Objectives Primary Objective: Evaluate the association between chronic stress and tumor response (via Tumor Regression Grade, TRG) in advanced gastric cancer patients undergoing neoadjuvant immunotherapy. Secondary Objectives: Assess the effect of chronic stress on post-gastrectomy quality of life (QoL). Analyze correlations between chronic stress biomarkers and survival outcomes (PFS, OS). 3. Study Endpoints Primary Endpoint: Pathological response assessed by TRG (Mandard criteria). Secondary Endpoints: QoL (EORTC QLQ-C30/STO22 questionnaires). PFS and OS. Exploratory Endpoints: Dynamic changes in chronic stress biomarkers (serum cortisol, ACTH, epinephrine, norepinephrine, serotonin). Correlation of biomarker levels with TRG and survival. 4. Study Design Type: Single-center, prospective observational study. Duration: 36 months. Sample Size: 268 patients (134 high chronic stress, 134 low chronic stress). Inclusion Criteria: Age 18-75 years. Histologically confirmed gastric adenocarcinoma (per Japanese Gastric Cancer Guidelines, 2017). Scheduled for neoadjuvant immunotherapy + radical gastrectomy. Informed consent. Exclusion Criteria: Pregnancy/breastfeeding. Prior upper abdominal surgery (excluding cholecystectomy). Active infection, autoimmune disease, or corticosteroid use within 1 month. Psychiatric disorders or investigator-deemed unsuitability. Withdrawal Criteria: Patient request, loss to follow-up, or safety concerns. 5. Methods Chronic Stress Assessment: Validated psychological questionnaires (e.g., Hospital Anxiety and Depression Scale) at baseline and treatment milestones. Biomarker analysis: Serum cortisol, ACTH, epinephrine, norepinephrine, serotonin at key timepoints (pre-treatment, post-neoadjuvant therapy, post-surgery). Clinical Data Collection: TRG evaluation post-surgery. QoL assessments at 1, 3, 6, 12, 18, 24, and 36 months post-surgery. Survival tracking via hospital records and follow-up visits. Statistical Analysis: Stratification by baseline stress scores (high/low). Cox regression for survival outcomes; logistic regression for TRG-QoL correlations. Significance threshold: \*p\* \< 0.05. 6. Significance This study addresses a critical gap in understanding how psychological factors modulate ICI efficacy. By identifying chronic stress as a predictor of treatment response, results may guide personalized interventions (e.g., beta-blockers, behavioral therapy) to improve outcomes in advanced gastric cancer.

Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis

The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening. The study includes healthy individuals, patients at risk of cancer, and patients with diagnosed cancers. The main questions it aims to answer are: * Evaluating the deep-learning model's accuracy and specificity in identifying cancer-specific features in Raman spectral data and determining whether this method can accurately classify patients based on risk. * Identifying which model is more adaptable to the Raman spectrum * Providing an interpretable analysis of the model-generated diagnosis Participants are already being diagnosed and follow-up to determine the type of cancer.

The Association Between Microplastics and Macrogenomics and Metabolomics in Gastric Cancer

The aim of this study was to identify and quantify microplastics in blood, stool, and tumor surgical specimens from gastric cancer patients by analyzing the nature, type, and abundance of microplastics using laser direct infrared (LDIR) spectroscopy, scanning electron microscopy (SEM), and pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS). Meanwhile, combining macro-genomic and metabolomic techniques to explore the association between microplastics and host microbiota and metabolic profiles, and to reveal the potential effects of microplastics on gastric cancer incidence and development will provide new insights into the relationship between microplastic contamination and gastric cancer, as well as an important scientific basis for future public health strategies and cancer prevention and control measures.

The Effect of Environmental Factors on Gastric Cancer Based on Macrogenome

The objectives of this study were to clarify how environmental factors such as air pollution affect the occurrence and development of gastric cancer; to identify patient-specific macrogenomic markers of gastric cancer; and to investigate the mechanism of gastric cancer development based on environmental factors and macrogenomic data.

Predictive Value of Air Pollution and Metabolomics for Gastric Cancer.

As one of the common malignant tumours worldwide, gastric cancer continues to have a high incidence and mortality rate, especially in Asia. Although a large number of studies have focused on its underlying genetic and lifestyle factors, the specific role of environmental factors in gastric cancer development and progression has not been fully elucidated. Air pollution, a growing environmental problem, and its major components such as PM2.5, PM10, and NO2 have been shown to be closely associated with the occurrence and development of many chronic diseases. Recent studies have gradually revealed the association between air pollution and certain cancer types (e.g., lung cancer), but its relationship with gastric cancer remains relatively unexplored. Against this background, the application of metabolomics provides new perspectives and methods to study the association between gastric cancer and environmental factors. Metabolomics is capable of systematically analysing the metabolite composition and changes in individuals under different environmental exposures, revealing the potential effects of environmental factors, such as air pollution, on individual metabolic functions. By combining air pollution data and metabolomics analysis, investigators can deeply explore the role of environmental factors in the occurrence, development and prognosis of gastric cancer, and thus provide a scientific basis for the development of prevention and treatment strategies.

AI-Assisted Non-Contrast CT for Multi-Cancer Screening

Cancer poses a major public health challenge in China. Early detection can improve treatment outcomes and survival rates. In this study, we will conduct a large-scale, prospective, multi-center cohort study to evaluate the utility of AI-assisted non-contrast CT for multi-cancer screening. The study aims to enroll 1 million asymptomatic participants undergoing routine health examinations, using an AI imaging model based on non-contrast CT to detect seven cancers such as lung, liver, gastric, colorectal, esophageal, pancreatic, and breast cancers. Positive cases will be required to be referred to Shanghai Changhai Hospital for further imaging and care based on National Comprehensive Cancer Network (NCCN) and American College of Radiology (ACR) guidelines. The goal is to assess the AI model's diagnostic performance for seven cancer types, especially for early-stage, resectable tumors.

Predictive Effect of Abdominal Fat and Muscle Area Calculated Based on Abdominal CT on Gastric Cancer Patients

This study aims to create a clinical prediction model. Abdominal fat and muscle area also play an important role in the prediction of surgical outcomes in colorectal cancer. Studies have shown that excess visceral fat and low skeletal muscle mass (sarcopenia) are associated with poorer postoperative outcomes, including a higher risk of postoperative complications and lower survival. Preoperative imaging techniques such as CT, MRI and ultrasound that provide accurate measurements to assess abdominal fat and muscle area can help surgeons develop individualized surgical and rehabilitation plans, improve surgical success, reduce complications and improve long-term patient prognosis. In this study, the investigators expected to construct a prediction model of abdominal fat and muscle area on the short- and long-term outcomes of gastric and colorectal cancer patients by calculating the abdominal fat and muscle area in different levels of abdominal CT images, in order to further adjust and guide the treatment plan.