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

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."