A Multi-omics Sequencing-based Model for Predicting Efficacy and Dynamic Monitoring of Treatment in Small Cell Lung Cancer: A Prospective, Non-interventional Study
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 40
- 试验地点
- 1
- 主要终点
- SCLC scoring models and molecular subtypes
研究概览
简要总结
Lung cancer is one of the malignant tumors with the highest incidence and mortality rates globally, with small cell lung cancer (SCLC) accounting for approximately 15%. SCLC is characterized by high malignancy, propensity for metastasis and drug resistance, and a 5-year survival rate below 7%. Despite partial progress in chemotherapy and immunotherapy, SCLC patients generally have extremely poor prognosis, and there is a lack of precise therapeutic efficacy prediction and dynamic monitoring approaches. Existing biomarkers (such as TP53/RB1 mutations) are inadequate for clinical needs due to high heterogeneity and insufficient dynamic characteristics. The rapid development of multi-omics technologies provides new opportunities for analyzing SCLC molecular features; however, previous studies have predominantly focused on single omics approaches with insufficient systematic integration, limiting clinical translation. This study aims to systematically integrate multiple omics technologies to construct predictive and dynamic monitoring models for SCLC therapeutic efficacy, providing new methods and evidence for SCLC clinical treatment and dynamic monitoring.
详细描述
Study Objectives To comprehensively analyze the molecular characteristics of small cell lung cancer (SCLC) through multi-omics technologies based on peripheral blood and paraffin-embedded samples, and establish and validate multi-omics data-based models for therapeutic efficacy prediction and dynamic monitoring.
Primary Objectives
- To collect blood and paraffin-embedded samples from SCLC patients before treatment and analyze multi-omics sequencing characteristics of these patients.
- To establish and validate SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection, constructing SCLC scoring models and molecular subtypes.
Secondary Objectives To investigate the sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models in patients with different stages of SCLC.
Exploratory Objectives To analyze potential biomarkers and therapeutic targets in SCLC based on multi-omics data, and conduct in-depth analysis of dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients meeting the following criteria may have samples collected:
- •Voluntary signing of informed consent;
- •Age ≥18 years;
- •Expected survival time ≥3 months;
- •Eastern Cooperative Oncology Group (ECOG) performance status score of 0 or 1;
- •Treatment-naïve limited-stage or extensive-stage SCLC confirmed by histology or cytology;
- •Agreement to provide blood samples and paraffin-embedded samples;
- •Measurable target lesions for efficacy evaluation.
排除标准
- •Patients with any of the following conditions will be excluded from sample collection:
- •Archived tumor tissue or pre-treatment tumor biopsy or histological examination showing previous histological or cytological evidence of non-small cell or small cell/non-small cell mixed components;
- •Investigator-determined unsuitability for peripheral blood collection due to complications or other conditions;
- •Active, known, or suspected autoimmune disease (excluding vitiligo, type I diabetes, residual hypothyroidism caused by autoimmune thyroiditis requiring only hormone replacement therapy, or conditions not expected to recur without external stimulation);
- •Active tuberculosis (TB) infection based on chest X-ray, sputum examination, and clinical examination. Patients with active pulmonary TB infection history within the previous year should be excluded even if treated. Patients with active pulmonary TB infection history more than one year ago should also be excluded unless previous anti-TB treatment can be proven adequately effective;
- •Comorbidities requiring immunosuppressive drug treatment, or requiring systemic or local corticosteroid use at immunosuppressive doses;
- •Pregnancy or lactation;
- •Positive human immunodeficiency virus antibody (HIVAb), active hepatitis B virus infection (HBsAg positive and HBV-DNA >10³ copies/ml), or hepatitis C virus infection (HCV antibody positive and HCV-RNA > lower limit of detection at study center);
- •History of severe neurological or psychiatric disorders, including but not limited to: dementia, depression, seizures, bipolar disorder, etc.;
- •Use of any anti-tumor drugs before blood sample collection;
- •Previous history of other malignant tumors (excluding non-melanoma skin cancer and the following carcinoma in situ: bladder, gastric, colon, endometrial, cervical/dysplasia, melanoma, or breast cancer);
- •Patients receiving live vaccines within 28 days before blood sample collection.
结局指标
主要结局
SCLC scoring models and molecular subtypes
时间窗: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
To establish and validate SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection, and construct SCLC scoring models and molecular subtypes.
次要结局
- Sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models(From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.)
- Dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes(From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.)
研究者
Zhijie Wang
Professor
Cancer Institute and Hospital, Chinese Academy of Medical Sciences