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Идёт набор NCT06642857

Multi-omics Based Prediction of Treatment Response to Immunotherapy Combined with Chemotherapy in Advanced Gastric/Gastroesophageal Junction Cancer.

— Наблюдательное Advanced Gastric Carcinoma Advanced Gastroesophageal Junction Adenocarcinoma

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают
В протоколе указаны: Peripheral blood, tougue coating, saliva, and feces.
Кому может быть актуально
Состояния в реестре: Advanced Gastric Carcinoma, Advanced Gastroesophageal Junction Adenocarcinoma. Базовые параметры: 18 лет — 75 лет · Все.
Что важно проверить
Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится
Китай
Следующий шаг
Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →

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Официальное название

Predicting Treatment Response to Immunotherapy Combined with Chemotherapy in Advanced Gastric/gastroesophageal Junction Cancer Based on the Multi-omics Information During Tumor Evolution.

Обзор

In this project, based on the information of advanced gastric/gastroesophageal junction cancer in evolution under immunotherapy combined with chemotherapy treatment, we will integrate multi-omics dynamic data to identify essential features that correlate to therapeutic effects of immunotherapy therapy, screen potential molecular markers/dominant microbiota for predicting the efficacy of immunotherapy and establish a multimodal predictive model for patients that benefit from immunotherapy. Our project could provide evidence to predict response to immunotherapy for patients with advanced gastric/gastroesophageal junction cancer and potentially optimize the clinical decision-making about therapy for advanced gastric/gastroesophageal junction cancer.

Подробное описание

Main objective: to extract and identify multi omics information tags related to the efficacy of immunotherapy for advanced gastric / gastroesophageal junction cancer

Secondary objective: to construct and validate the efficacy prediction model of chemotherapy combined with immunotherapy for gastric cancer, in order to optimize the scheme decision of advanced gastric cancer treatment

Exploratory purpose: to screen potential molecular markers / dominant flora for predicting the efficacy of immunotherapy in patients with advanced gastric / gastroesophageal junction cancer

Вмешательства

  • Другое Peripheral blood, tougue coating, saliva, and feces
    Peripheral blood, coating, saliva, and feces on the tongue and clinical data of patients with advanced gastric cancer patients who received chemotherapy combined with immunotherapy will be collected.

Первичные конечные точки

  • Objective Best Tumor Response [Срок оценки: 12 months]
  • Overall Survival [Срок оценки: 60 months]
Вторичные конечные точки (1)
  • Progression-free Survival [Срок оценки: 36 months]

Критерии участия

Inclusion criteria：

  • Patients with gastric or gastroesophageal junction adenocarcinoma confirmed by pathology and with advanced or metastatic disease that cannot be resected
  • HER2 negative
  • Not received any anti-tumor treatment before.
  • After evaluation, the treatment plan is chemotherapy combined with immunotherapy.
  • Aged 18 to 75 years old, gender is not limited.
  • Expected survival time is greater than or equal to 3 months. Exclusion criteria：
  • Patients with malignant tumors other than gastric cancer or those with tumors metastasized to the stomach from other sites.
  • Patients who have previously received anti-tumor treatments such as surgery, radiotherapy and chemotherapy, targeted therapy or immunotherapy.
  • Patients with severe infections.
  • Those with a history of mental illness cannot cooperate with the research.
  • Patients with severe heart, liver, kidney and other diseases.
  • Pregnant or lactating patients.
  • HER2 positive.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения
Когортное

Центры проведения

Китай · 1 центр
  • Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital — Ханчжоу

Публикации

  • Yuan L, Yang L, Zhang S, Xu Z, Qin J, Shi Y, Yu P, Wang Y, Bao Z, Xia Y, Sun J, He W, Chen T, Chen X, Hu C, Zhang Y, Dong C, Zhao P, Wang Y, Jiang N, Lv B, Xue Y, Jiao B, Gao H, Chai K, Li J, Wang H, Wang X, Guan X, Liu X, Zhao G, Zheng Z, Yan J, Yu H, Chen L, Ye Z, You H, Bao Y, Cheng X, Zhao P, Wang L, Zeng W, Tian Y, Chen M, You Y, Yuan G, Ruan H, Gao X, Xu J, Xu H, Du L, Zhang S, Fu H, Cheng X PMID 36825238
  • Li MY, Zhu DJ, Xu W, Lin YJ, Yung KL, Ip AWH. Application of U-Net with Global Convolution Network Module in Computer-Aided Tongue Diagnosis. J Healthc Eng. 2021 Nov 18;2021:5853128. doi: 10.1155/2021/5853128. eCollection 2021. PMID 34840700
  • Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023 Jan;73(1):17-48. doi: 10.3322/caac.21763. PMID 36633525

Идентификаторы

NCT: NCT06642857 · IRB-2024-175

Первоисточники (государственные реестры)

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