Evaluating the Predictive Capability of Transcriptomic Profiling for Identifying the Primary Site of Metastatic Tumors
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Malignant Tumor With Metastasis, CUP. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Evaluative Study on Predicting the Primary Site of Metastatic Tumors Using Transcriptomic Profiling for Tumor Tissue Origin Identification
Overview
This study will enroll patients with metastatic malignancies. Tumor samples (fresh or formalin-fixed paraffin-embedded tissue specimens) will undergo RNA extraction and next-generation sequencing (RNA-seq). Once the raw data is obtained, the system will analyze the transcriptomic feature values (cancer-specific RNA transcripts and tissue-specific RNA transcripts) expressed in the tumor tissue samples to further predict tissue origin using a machine learning model. The output includes probabilities and confidence intervals for tissue origin.
Detailed description
This is a non-interventional, observational study. Through a single-center, prospective clinical trial, the study aims to utilize the transcriptomic profiling for tumor tissue origin identification to predict the tissue origin of primary sites in metastatic tumors and evaluate the accuracy and specificity of this prediction solution.
Primary Endpoint:
The accuracy of the transcriptomic profiling for tumor tissue origin identification in predicting the primary site of metastatic tumors (expressed as overall accuracy with its 95% confidence interval).
Secondary Endpoints:
1. The specificity and sensitivity of the transcriptomic profiling for tumor tissue origin identification in predicting the primary site of metastatic tumors. 2. Exploratory analysis of characteristic molecular markers expressed in metastatic lesions from different primary sites.
Primary outcome measures
- The accuracy of the transcriptomic profiling for tumor tissue origin identification in predicting the primary site of metastatic tumors [Time frame: through study completion, an average of 1 year]
Eligibility criteria
Inclusion criteria
- Clinically confirmed diagnosis of malignant tumor with metastasis;
- Metastatic lesions confirmed as malignant by histopathology;
- Sufficient surgical resection or biopsy specimens retained to meet the requirements for next-generation sequencing;
- The participant (or their legal representative/guardian) has signed the informed consent form, confirming full understanding of the study's purpose and procedures, and voluntarily agrees to participate.
Exclusion criteria
1\. The investigator deems the patient unable to provide informed consent.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Case-only
Study locations
Center list to be confirmed — check the primary protocol.
Publications
- Shi Q, Li X, Liu Y, Chen Z, He X. FLIBase: a comprehensive repository of full-length isoforms across human cancers and tissues. Nucleic Acids Res. 2024 Jan 5;52(D1):D124-D133. doi: 10.1093/nar/gkad745. PMID 37697439
- Shi Q, Liu T, Hu W, Chen Z, He X, Li S. SRTdb: an omnibus for human tissue and cancer-specific RNA transcripts. Biomark Res. 2022 Apr 26;10(1):27. doi: 10.1186/s40364-022-00377-1. PMID 35473935
- Lee MS, Sanoff HK. Cancer of unknown primary. BMJ. 2020 Dec 7;371:m4050. doi: 10.1136/bmj.m4050. PMID 33288500
Identifiers
NCT: NCT07319949 · SRTCD-NO001