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NCT Number: NCT05847855

Plasma cfDNA Fragmentomics for Early pNET Detection and Differential Diagnosis of Solid Pancreatic Tumors

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 and differential diagnosis of solid pancreatic tumors.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Fudan University shanghai cancer center, Shanghai, Shanghai Municipality, China

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About this study

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.

Additionally, once a pancreatic lesion is detected, accurate discrimination between pancreatic ductal adenocarcinoma (PDAC), pNETs and solid pseudopapillary tumor (SPT) is essential. This study therefore has two co-primary objectives: (1) to develop a fragmentomic assay that flags asymptomatic individuals likely to harbor a pNET; (2) to build a differential model that distinguishes PDAC vs pNETs vs SPT in patients with confirmed solid pancreatic neoplasms."

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 18 and above, regardless of gender;
  • Histopathological diagnosis with non-functional pancreatic neuroendocrine tumor, pancreatic ductal adenocarcinoma or solid pseudopapillary tumor;
  • 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 not pancreatic neuroendocrine tumor, pancreatic ductal adenocarcinoma or solid pseudopapillary 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.

Treatment and study plan

Blood collection

Diagnostic Test

Blood collection for fragmentomic profiles of plasma cell-free DNA. The sub-center shall use the same blood collection consumables (EDTA anticoagulant vacutainer tubes) and blood collection volume (10ml) as the main center; plasma separation shall be completed within 2 hours after blood collection, and all operations shall comply with the study's unified SOP.

Primary outcomes

  1. Sensitivity and specificity of the integrated fragmentomic model for detecting pNETs

    Time frame: From date of first blood draw until first documented pNETs diagnosis, assessed up to 3 years.

    Sensitivity and specificity of the integrated model using fragmentomic profiles of plasma cfDNA for early detection of pNETs

  2. Sensitivity and specificity of the model for differential diagnosis among solid pancreatic tumors

    Time frame: From first blood draw until histopathological diagnosis, up to 3 years

    Sensitivity and specificity of the model for differential diagnosis among PDAC, pNET and SPT.

Secondary outcomes

  1. Positive predictive value and negative predictive value

    Time frame: From date of first blood draw until first documented pNETs diagnosis, assessed up to 3 years

    Positive predictive value (PPV) and negative predictive value (NPV) of the integrated model using fragmentomic profiles of plasma cfDNA for early detection of pNETs

  2. Accuracy of the model in predicting AJCC stage (where applicable) and tumor grade

    Time frame: From date of first blood draw until first documented histopathological diagnosis, assessed up to 3 years

    Sensitivity and specificity of the integrated model using fragmentomic profiles of plasma cfDNA in predicting AJCC stage (where applicable) and tumor grade

Study contacts

Contact information is provided by the study sponsor or research team.

Shunrong Ji, MD, PhD

CONTACT

[email protected]

13788993956

Xianjun Yu, MD, PhD

CONTACT

[email protected]

021-64175590-88503

Sponsors and collaborators

Lead sponsor

Fudan University

Other

Collaborators

  • West China Hospital

Registry information

Official study title

A Prospective Study of Plasma Cell-free DNA Fragmentomics for Early Detection of Pancreatic Neuroendocrine Tumors and Differential Diagnosis of Solid Pancreatic Tumors

Important dates

Study start
2023
Primary completion
2026
Study completion
2026
First posted
May 8, 2023
Registry last updated
Mar 25, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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