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临床试验/NCT06146127
NCT06146127招募中不适用

Precision Medicine for Combined Hepatocellular-Cholangiocarcinoma

Inserm U9551 个研究点 分布在 1 个国家目标入组 300 人开始时间: 2001年1月15日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
发起方
入组人数
300
试验地点
1
主要终点
Diagnosos

研究概览

简要总结

Our project is a large-scale characterisation of cHCC-CCA will allow us to determine which subsets harbor actionable gene alterations. We will also aim to improve diagnosis of this tumor type by the use of immunohistochemical biomarkers and the development of deep-learning based models able to help cHCC-CCA diagnosis. This will represent an important step towards precision medicine for the patients with this highly aggressive malignancy.

详细描述

  • Scientific background Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare liver cancer characterized by a dual hepatocytic and biliary differentiation. It is resistant to conventional anti-cancer treatments and there is currently no effective systemic therapy available. Inter-observer agreement for diagnosis of cHCC-CCA is low, even among expert pathologists, and the development of clinical trials remain thus challenging. The molecular mechanisms that drive its progression also remain under-investigated.
  • Project objectives and brief description of the methods which will be used to achieve them We aim to perform an integrative molecular, immune and phenotypical study of cHCC-CCA that will allow the distinction of different tumor subgroups linked to particular actionable genetic/immune alterations. The development of immunohistochemical markers and artificial intelligence-based approaches is also likely to improve the diagnosis of cHCC-CCA.

A overall multicentric series of 357 cHCC-CCA samples, already available in our biobanks, will be investigated by means of gene and RNA sequencing, digital pathology and immunohistochemistry in order to build a morphomolecular classification of this tumor. Spatial transcriptomics and in situ proteomics will be performed to decipher the intra-tumor heterogeneity and identify biomarkers of the different subclasses. Finally, deep-learning based models will be developed in order to 1) improve the diagnosis of cHCC-CCA and 2) identify the morphological features linked to prognosis.

• Expected results This large-scale characterisation of cHCC-CCA will allow us to determine which subsets harbor actionable gene alterations. We will also aim to improve diagnosis of this tumor type by the use of immunohistochemical biomarkers and the development of deep-learning based models able to help cHCC-CCA diagnosis. This will represent an important step towards precision medicine for the patients with this highly aggressive malignancy.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Retrospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • histological diagnosis of combined tumor biological sample available

排除标准

  • unequivocal histological features

结局指标

主要结局

Diagnosos

时间窗: 3 yrs

Tumor subgroups

次要结局

未报告次要终点

研究者

发起方
Inserm U955
申办方类型
Other
责任方
Principal Investigator
主要研究者

Julien Calderaro

Full Professor

Inserm U955

研究点 (1)

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