An observational study in Small Cell Lung Cancer, sponsored by Cancer Institute and Hospital, Chinese Academy of Medical Sciences. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-06-18.
Sponsored by Cancer Institute and Hospital, Chinese Academy of Medical Sciences · Observational
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.
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
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.
Study Design This is a prospective, single-center study aimed at establishing SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection of peripheral blood and paraffin-embedded samples.
Sample Collection Time Points
Patient Information Collection
The study requires collection of patients' demographic information before blood collection, imaging data related to disease diagnosis, hospital laboratory biochemical test results, tumor marker test results, pathological diagnosis results or other information providing diagnostic evidence, and underlying disease information. Specific information collected includes:
Information to be collected for all patients includes but is not limited to:
General demographic data: age, gender, race, etc.; Vital signs: blood pressure, pulse, heart rate, etc.; Previous major disease history and corresponding medication history; Tumor history and corresponding treatment history; Family genetic history; Smoking and drinking history; Multi-omics detection results.
7,243 studies on the registry are indexed under Lung Neoplasms; 1,557 are open to participants now.
This study's planned enrollment of 40 is below the median of 189 across 1,514 observational studies indexed under Lung Neoplasms.
Browse Lung Neoplasms studies →Cancer Institute and Hospital, Chinese Academy of Medical Sciences is the lead sponsor of 373 studies on the registry; 270 are open to participants now.
Counted across the registry records on this site, refreshed daily.
SCLC patients From Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Patients meeting the following criteria may have samples collected:
Exclusion Criteria:
Patients with any of the following conditions will be excluded from sample collection:
Small cell lung cancer with lymph node metastasis/distant metastasis
SCLC scoring models and molecular subtypes
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.
Time frame: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
Sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models
To investigate the sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models in patients with different stages of SCLC.
Time frame: 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
To analyze potential biomarkers and therapeutic targets in SCLC based on multi-omics data, and conduct an in-depth analysis of dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes.
Time frame: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
Plan to share: No
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Cancer Institute and Hospital, Chinese Academy of Medical Sciences