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

Official title

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

Overview

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.

Detailed 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.

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."

Interventions

• Diagnostic test Blood collection
  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 outcome measures

• 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 model for differential diagnosis among solid pancreatic tumors [Time frame: From first blood draw until histopathological diagnosis, up to 3 years]

Secondary outcome measures (2)

• 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]
• 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]

Eligibility criteria

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.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Cohort

Study locations

China · 2 centers

• Fudan University shanghai cancer center — Shanghai
• West China Hospital, Sichuan University — Chengdu

Publications

• 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. PMID 25132004
• 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. PMID 28448665
• 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. PMID 34954829
• 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. PMID 29668834
• 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, Bojes PMID 34417454
• 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. PMID 26771485
• 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. PMID 35780566
• 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 PMID 35690859

Identifiers

NCT: NCT05847855 · CSPAC-NEN-4

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗