Evaluating the Predictive Capability of Transcriptomic Profiling for Identifying the Primary Site of Metastatic Tumors

Evaluative Study on Predicting the Primary Site of Metastatic Tumors Using Transcriptomic Profiling for Tumor Tissue Origin Identification

Status

Not yet recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07319949

Enrollment

Registered

2026-01-06

Start date

2026-01-15

Completion date

2026-10-13

Last updated

2026-01-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

CUP, Malignant Tumor With Metastasis

Keywords

Cancer of unknown primary, Specific RNA transcript, Tissue origin identification, Machine learning, Cancer diagnosis

Brief summary

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.

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Healthy volunteers

Inclusion criteria

1. Clinically confirmed diagnosis of malignant tumor with metastasis; 2. Metastatic lesions confirmed as malignant by histopathology; 3. Sufficient surgical resection or biopsy specimens retained to meet the requirements for next-generation sequencing; 4. 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.

Design outcomes

Primary

Measure	Time frame	Description
The accuracy of the transcriptomic profiling for tumor tissue origin identification in predicting the primary site of metastatic tumors	through study completion, an average of 1 year	Overall accuracy of the tumor tissue origin tracing transcriptome test for predicting the primary site of metastatic tumors (number of correct predictions/total evaluable cases); Specificity \[true negatives/(true negatives + false positives)\]; Sensitivity \[true positives/(true positives + false negatives)\].

Contacts

Primary ContactZhiao Chen, Ph.D.

zachen@fudan.edu.cn008618017312074

Outcome results