A Multi-omics Sequencing-based Model for Predicting Efficacy and Dynamic Monitoring of Treatment in Small Cell Lung Cancer

Sponsor
Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Study ID
NCT07026669
Status
Recruiting
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Conditions

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Study Details

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.

Key Dates

First listed
Jun 18, 2025
Start date
Jan 1, 2025
Status verified
Jun 2025
Primary completion
Dec 1, 2027
Completion
Dec 1, 2027

Study Design

Enrollment
40 participants (estimated)

Arms

  • Arm: Limited-stage/Extensive-stage small cell lung cancer
    Small cell lung cancer with lymph node metastasis/distant metastasis

Primary Outcome Measure

SCLC scoring models and molecular subtypes [ Time Frame: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression. ]

Central Contacts

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