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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT05847855
Other study ID # CSPAC-NEN-3
Secondary ID
Status Not yet recruiting
Phase
First received
Last updated
Start date April 27, 2023
Est. completion date June 30, 2026

Study information

Verified date April 2023
Source Fudan University
Contact Xianjun Yu, MD, PhD
Phone 021-64175590-88503
Email yuxianjun@fudanpci.org
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

This prospective study aims to evaluate the sensitivity and specificity of an integrated model using fragmentomic profiles of plasma cell-free DNA for early detection of pancreatic neuroendocrine tumors.


Description:

Pancreatic neuroendocrine tumors (pNETs) are insidious and difficult to diagnose early. Approximately 36.8% of pNET patients have lymph node metastasis[1], and 20% -64% of patients have liver metastasis at the time of diagnosis[2]. The prognosis of pNETs is closely related to tumor grade and the American Joint Committee on Cancer (AJCC) staging. Among patients with known pathological grades in the United States, well-differentiated NETs had the highest median overall survival (OS, 16.2 years), moderately differentiated NETs had the worse OS (8.3 years), and poorly differentiated or undifferentiated NETs had the worst OS (10 months)[3]. The 5-year overall survival rates of localized, locally advanced, and metastatic pNETs were 93%, 77%, and 27%, respectively[4]. Given that the prognosis of early-stage pNETs is significantly better than that of advanced pNETs, early detection of pNETs can provide a cure opportunity and significantly improve survival. In the past few decades, the application of 68Ga-DOTANOC PET/CT, magnetic resonance imaging (MRI), computed tomography (CT), and endoscopic ultrasound (EUS) has improved the detection rate of pNETs. But their application is limited by high costs, lack of sufficient sensitivity or specificity, and radiation exposure. Therefore, there is an urgent need for accurate and less invasive approaches to use in clinical practice for the early detection of pNETs. Recently, the study of cell-free DNA (cfDNA) has provided a noninvasive approach for the diagnosis of solid malignancies. cfDNAs represent extracellular DNA fragments released from cell apoptosis and necrosis into human body fluids like plasma, thus carrying the genetic and epigenetic information from the cell and tissue of origin[5]. Among them, circulating tumor DNA (ctDNA), as a part of the total cfDNA, is released into the blood by tumor cells[6]. cfDNA fragmentomics depends on whole genome sequencing, and its characteristics mainly include copy number variation (CNV), nucleosome footprint, fragment length and motif[5, 7, 8], with targets covering the entire genome level. cfDNA fragmentomics has shown excellent predictive performance in multiple studies[5, 9-11]. Therefore, this prospective study aims to evaluate the sensitivity and specificity of an integrated model using fragmentomic profiles of plasma cell-free DNA (cfDNA) for early detection of pancreatic neuroendocrine tumors.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 440
Est. completion date June 30, 2026
Est. primary completion date December 31, 2025
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - Age 18 and above, regardless of gender; - Histopathological diagnosis with pancreatic neuroendocrine tumor before surgery; - Not receiving any anti-tumor treatment before surgery, including chemotherapy, embolization, ablation, radiotherapy, and molecular targeted therapy; - No obvious surgical contraindications; - Able to comply with research plans, follow-up plans, and other protocol requirements; - Voluntary participation and signed informed consent. Exclusion Criteria: - Pathological diagnosis was nonpancreatic neuroendocrine tumor; - Currently diagnosed with other types of tumors or any cancer history; - Diagnosed with familial syndromes; - Receiving anti-tumor treatment before surgery, including chemotherapy, embolization, ablation, radiotherapy, and molecular targeted therapy; - Ongoing fever or recipient of anti-inflammation therapy within 14 days prior to study blood draw; - Recipient of blood transfusion within 30 days prior to study blood draw; - Recipient of organ transplant or prior non-autologous (allogeneic) bone marrow or stem cell transplant; - Poor health condition and not suitable for blood draw; - Any other disease/condition deemed not suitable for study enrollment by researcher.

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
Fragmentomic profiles of plasma cfDNA
Blood collection and early detection testing based on fragmentomic profiles of plasma cfDNA

Locations

Country Name City State
n/a

Sponsors (1)

Lead Sponsor Collaborator
Fudan University

References & Publications (9)

Bao H, Wang Z, Ma X, Guo W, Zhang X, Tang W, Chen X, Wang X, Chen Y, Mo S, Liang N, Ma Q, Wu S, Xu X, Chang S, Wei Y, Zhang X, Bao H, Liu R, Yang S, Jiang Y, Wu X, Li Y, Zhang L, Tan F, Xue Q, Liu F, Cai S, Gao S, Peng J, Zhou J, Shao Y. Letter to the Editor: An ultra-sensitive assay using cell-free DNA fragmentomics for multi-cancer early detection. Mol Cancer. 2022 Jun 11;21(1):129. doi: 10.1186/s12943-022-01594-w. — View Citation

Dasari A, Shen C, Halperin D, Zhao B, Zhou S, Xu Y, Shih T, Yao JC. Trends in the Incidence, Prevalence, and Survival Outcomes in Patients With Neuroendocrine Tumors in the United States. JAMA Oncol. 2017 Oct 1;3(10):1335-1342. doi: 10.1001/jamaoncol.2017.0589. — View Citation

Fece de la Cruz F, Corcoran RB. Methylation in cell-free DNA for early cancer detection. Ann Oncol. 2018 Jun 1;29(6):1351-1353. doi: 10.1093/annonc/mdy134. No abstract available. — View Citation

Fischer L, Bergmann F, Schimmack S, Hinz U, Priess S, Muller-Stich BP, Werner J, Hackert T, Buchler MW. Outcome of surgery for pancreatic neuroendocrine neoplasms. Br J Surg. 2014 Oct;101(11):1405-12. doi: 10.1002/bjs.9603. Epub 2014 Aug 13. — View Citation

Guo W, Chen X, Liu R, Liang N, Ma Q, Bao H, Xu X, Wu X, Yang S, Shao Y, Tan F, Xue Q, Gao S, He J. Sensitive detection of stage I lung adenocarcinoma using plasma cell-free DNA breakpoint motif profiling. EBioMedicine. 2022 Jul;81:104131. doi: 10.1016/j.ebiom.2022.104131. Epub 2022 Jun 30. — View Citation

Ma X, Chen Y, Tang W, Bao H, Mo S, Liu R, Wu S, Bao H, Li Y, Zhang L, Wu X, Cai S, Shao Y, Liu F, Peng J. Multi-dimensional fragmentomic assay for ultrasensitive early detection of colorectal advanced adenoma and adenocarcinoma. J Hematol Oncol. 2021 Oct 26;14(1):175. doi: 10.1186/s13045-021-01189-w. — View Citation

Mathios D, Johansen JS, Cristiano S, Medina JE, Phallen J, Larsen KR, Bruhm DC, Niknafs N, Ferreira L, Adleff V, Chiao JY, Leal A, Noe M, White JR, Arun AS, Hruban C, Annapragada AV, Jensen SO, Orntoft MW, Madsen AH, Carvalho B, de Wit M, Carey J, Dracopoli NC, Maddala T, Fang KC, Hartman AR, Forde PM, Anagnostou V, Brahmer JR, Fijneman RJA, Nielsen HJ, Meijer GA, Andersen CL, Mellemgaard A, Bojesen SE, Scharpf RB, Velculescu VE. Detection and characterization of lung cancer using cell-free DNA fragmentomes. Nat Commun. 2021 Aug 20;12(1):5060. doi: 10.1038/s41467-021-24994-w. — View Citation

Snyder MW, Kircher M, Hill AJ, Daza RM, Shendure J. Cell-free DNA Comprises an In Vivo Nucleosome Footprint that Informs Its Tissues-Of-Origin. Cell. 2016 Jan 14;164(1-2):57-68. doi: 10.1016/j.cell.2015.11.050. — View Citation

Zhang X, Wang Z, Tang W, Wang X, Liu R, Bao H, Chen X, Wei Y, Wu S, Bao H, Wu X, Shao Y, Fan J, Zhou J. Ultrasensitive and affordable assay for early detection of primary liver cancer using plasma cell-free DNA fragmentomics. Hepatology. 2022 Aug;76(2):317-329. doi: 10.1002/hep.32308. Epub 2022 Jan 26. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Sensitivity and specificity Sensitivity and specificity of the integrated model using fragmentomic profiles of plasma cfDNA for early detection of pNETs From date of first blood draw until first documented pNETs diagnosis, assessed up to 3 years
Secondary Positive predictive value and negative predictive value Positive predictive value (PPV) and negative predictive value (NPV) of the integrated model using fragmentomic profiles of plasma cfDNA for early detection of pNETs From date of first blood draw until first documented pNETs diagnosis, assessed up to 3 years
Secondary Sensitivity and specificity in distinguishing different AJCC stages Sensitivity and specificity of the integrated model using fragmentomic profiles of plasma cfDNA in distinguishing different AJCC stages From date of first blood draw until first documented pNETs diagnosis, assessed up to 3 years
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