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审核状态: Project audit state: |
通过审核 Successful |
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注册号: Registration number: |
ChiCTR2500115356 |
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最近更新日期: Date of Last Refreshed on: |
2025-12-25 08:38:33 |
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注册时间: Date of Registration: |
2025-12-25 00:00:00 |
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注册号状态: |
预注册 |
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Registration Status: |
Prospective registration |
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注册题目: |
前列腺癌多组学精准分型治疗 |
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Public title: |
Multi-omics Precision Subtyping and Treatment for Prostate Cancer |
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注册题目简写: |
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English Acronym: |
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研究课题的正式科学名称: |
前列腺癌多组学融合分子分型及精准分层治疗体系的构建与验证 |
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Scientific title: |
Construction and Validation of a Multi-Omics-Integrated Molecular Subtyping and Precision Stratification Therapeutic System for Prostate Cancer |
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研究课题代号(代码): Study subject ID: |
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在二级注册机构或其它机构的注册号: The registration number of the Partner Registry or other register: |
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申请注册联系人: |
张琦 |
研究负责人: |
张琦 |
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Applicant: |
Qi Zhang |
Study leader: |
Qi Zhang |
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申请注册联系人电话: Applicant telephone: |
+86 13858019285 |
研究负责人电话:
Study leader's |
+86 13858019285 |
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申请注册联系人传真 : Applicant Fax: |
研究负责人传真: Study leader's fax: |
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申请注册联系人电子邮件: Applicant E-mail: |
urology@zju.edu.cn |
研究负责人电子邮件: Study leader's E-mail: |
clinic@126.com |
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申请单位网址(自愿提供): Applicant website(voluntary supply): |
研究负责人网址(自愿提供): Study leader's website(voluntary supply): |
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申请注册联系人通讯地址: |
浙江省杭州市拱墅区上塘路158号 |
研究负责人通讯地址: |
浙江省杭州市拱墅区上塘路158号 |
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Applicant address: |
No. 158 Shangtang Road, Gongshu District Hangzhou, Zhejiang |
Study leader's address: |
No. 158 Shangtang Road, Gongshu District Hangzhou, Zhejiang |
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申请注册联系人邮政编码: Applicant postcode: |
研究负责人邮政编码: Study leader's postcode: |
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申请人所在单位: |
浙江省人民医院 |
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Applicant's institution: |
Zhejiang Provincial People's Hospital |
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研究负责人所在单位: |
浙江省人民医院 |
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Affiliation of the Leader: |
Zhejiang Provincial People's Hospital |
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是否获伦理委员会批准: |
是 |
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Approved by ethic committee: |
Yes |
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伦理委员会批件文号: Approved No. of ethic committee: |
浙人医伦审2025研第(456)号 |
伦理委员会批件附件: Approved file of Ethical Committee: |
查看附件View |
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批准本研究的伦理委员会名称: |
浙江省人民医院医学伦理委员会 |
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Name of the ethic committee: |
Ethical Committee of Zhejiang Provincial Peoples Hospital |
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伦理委员会批准日期: Date of approved by ethic committee: |
2025-11-17 00:00:00 | ||
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伦理委员会联系人: |
李青青 |
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Contact Name of the ethic committee: |
Li Qingqing |
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伦理委员会联系地址: |
浙江省杭州市拱墅区上塘路158号 |
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Contact Address of the ethic committee: |
No. 158 Shangtang Road, Gongshu District Hangzhou, Zhejiang |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 571 85893643 |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
zryllwyh@163.com |
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研究实施负责(组长)单位: |
浙江省人民医院 |
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Primary sponsor: |
Zhejiang Provincial People's Hospital |
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研究实施负责(组长)单位地址: |
浙江省杭州市拱墅区上塘路158号 |
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Primary sponsor's address: |
No. 158 Shangtang Road, Gongshu District Hangzhou, Zhejiang |
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试验主办单位(项目批准或申办者): Secondary sponsor: |
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经费或物资来源: |
浙江省自然科学基金 |
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Source(s) of funding: |
Zhejiang Provincial Natural Science Foundation |
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研究疾病: |
前列腺癌、去势抵抗性前列腺癌、骨转移前列腺癌 |
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Target disease: |
Prostate cancer, Castration-resistant prostate cancer, Prostate cancer with bone metastasis |
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研究疾病代码: |
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Target disease code: |
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研究类型: |
观察性研究 |
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Study type: |
Observational study |
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研究所处阶段: |
其它 | ||||||||||||||||||||||
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Study phase: |
N/A |
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研究设计: |
队列研究 |
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Study design: |
Cohort study |
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研究目的: |
前列腺癌是男性最常见的恶性肿瘤之一,其临床异质性显著,表现为发病机制复杂、进展速度差异大以及治疗反应多样。目前常规的临床与病理分型难以准确反映肿瘤的分子特征与生物行为,导致部分患者出现早期进展或对内分泌治疗原发耐药等临床困境。本研究拟依托多中心临床队列及前列腺癌生物样本库资源,整合基因组、转录组、表观遗传组、蛋白组、代谢组及影像组学等多层次数据,绘制中国人群特异的前列腺癌多维分子图谱,系统识别驱动疾病进展及治疗耐药的关键分子通路和特征模式。 在此基础上,本研究将利用人工智能与机器学习方法构建多组学融合的分子分型体系,明确前列腺癌的不同分子亚型特征,建立融合临床病理参数、分子标志物和影像特征的精准分层治疗模型。进一步通过分型结果指导个体化治疗策略,包括内分泌治疗优化、新型靶向药物联合方案及治疗反应预测模型的研发。通过多中心前瞻性临床验证,评估该体系在改善高危患者预后、提升治疗反应率及降低过度治疗中的实际效果,最终形成覆盖“分子分型—风险分层—精准治疗—临床验证”的前列腺癌精准诊疗体系,为我国人群前列腺癌个体化管理提供科学依据与可推广范式。 |
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Objectives of Study: |
Prostate cancer is one of the most common malignant tumors in men. It exhibits significant clinical heterogeneity, characterized by complex pathogenic mechanisms, wide variation in disease progression, and diverse therapeutic responses. At present, conventional clinical and pathological classification systems are insufficient to accurately reflect the molecular features and biological behavior of tumors, resulting in clinical challenges such as early disease progression and primary resistance to endocrine therapy in some patients.This study intends to rely on multicenter clinical cohorts and prostate cancer biobank resources, integrating multi-level data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, and radiomics, to depict a multidimensional molecular atlas of prostate cancer specific to the Chinese population, and systematically identify key molecular pathways and characteristic patterns driving disease progression and therapeutic resistance.On this basis, this study will use artificial intelligence and machine learning methods to construct a multi-omics-integrated molecular subtyping system, clarify the features of different molecular subtypes of prostate cancer, and establish a precision stratified treatment model integrating clinicopathological parameters, molecular biomarkers, and imaging features. Furthermore, personalized treatment strategies will be guided by the subtyping results, including optimization of endocrine therapy, develop |
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药物成份或治疗方案详述: |
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Description for medicine or protocol of treatment in detail: |
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纳入标准: |
1.经病理学明确诊断为前列腺腺癌,病理类型及分级符合WHO前列腺癌分类及ISUP/Gleason评分标准; |
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Inclusion criteria |
1. Histologically confirmed prostate adenocarcinoma, with pathological type and grade meeting the WHO prostate cancer classification and ISUP/Gleason scoring criteria; 2. Tumor tissue obtained by surgery or biopsy is available for immunohistochemistry, molecular, or metabolomic testing, and the sample quality meets testing requirements; 3. Complete clinical data are available, including imaging examinations (such as MRI, CT, and bone scan), serum PSA levels, pathology reports, and treatment information; 4. Age >= 18 years, male; 5. Good general condition (ECOG performance status 0–2) and able to tolerate tissue collection and related experimental procedures; 6. No other active malignancies or severe systemic diseases, and able to comply with study requirements; 7. Able to understand and voluntarily sign the informed consent form, and willing to provide specimens and relevant clinical information for this study. |
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排除标准: |
1.病理学诊断不明确或组织样本不足以满足后续检测要求者; |
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Exclusion criteria: |
1. Pathological diagnosis is inconclusive, or the tissue sample is insufficient to meet subsequent testing requirements; 2. Previously received systemic antitumor therapy (including chemotherapy, radiotherapy, endocrine therapy, or targeted therapy) without available tumor tissue specimens; 3. Presence of severe cardiovascular, hepatic, renal, or respiratory diseases, rendering the patient unable to tolerate sample collection or laboratory testing; 4. Presence of severe infection, autoimmune disease, or metabolic disorder that may affect the analysis of metabolic pathways; 5. Presence of severe mental disorders, cognitive impairment, or other conditions affecting compliance; 6. Participation in other interventional clinical trials that may interfere with the results of this study. |
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研究实施时间: Study execute time: |
从 From 2026-01-01 00:00:00至 To 2028-01-01 00:00:00 |
征募观察对象时间: Recruiting time: |
从 From 2026-01-01 00:00:00 至 To 2027-06-01 00:00:00 |
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干预措施: Interventions: |
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研究实施地点: Countries of recruitment and research settings: |
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测量指标: Outcomes: |
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采集人体标本:
Collecting sample(s)
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征募研究对象情况: Recruiting status: |
尚未开始 Not yet recruiting |
年龄范围: Participant age: |
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性别: |
男性 |
Gender: |
Male |
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随机方法(请说明由何人用什么方法产生随机序列): |
无 |
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Randomization Procedure (please state who generates the random number sequence and by what method): |
None |
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是否公开试验完成后的统计结果: Calculated Results after the Study Completed public access: |
不公开/Private |
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盲法: |
无 |
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Blinding: |
None |
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是否共享原始数据: IPD sharing |
否No |
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共享原始数据的方式(说明:请填入公开原始数据日期和方式,如采用网络平台,需填该网络平台名称和网址): |
本研究数据不对外公开。如需申请访问,需提交正式申请并通过伦理审批。 |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
Individual participant data (IPD) will not be publicly available. De-identified data may be considered upon reasonable request and ethical approval. |
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数据采集和管理(说明:数据采集和管理由两部分组成,一为病例记录表(Case Record Form, CRF),二为电子采集和管理系统(Electronic Data Capture, EDC),如ResMan即为一种基于互联网的EDC: |
数据采集和管理由病例报告表(Case Report Form, CRF)与电子数据采集系统(Electronic Data Capture, EDC)组成。 研究数据将通过EDC系统进行录入、存储与质量控制。 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
Data collection and management will include a Case Report Form (CRF) and an Electronic Data Capture (EDC) system. All study data will be entered, stored, and quality-controlled within the EDC system. |
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数据与安全监察委员会: Data and Safety Monitoring Committee: |
无/No |