Multi-dimensional Fragmentomic Assay for Early Detection of Pancreatic Neuroendocrine Tumors
Study Details
Study Description
Brief 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.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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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.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| pNETs Patients with pancreatic neuroendocrine tumors (pNETs). |
Diagnostic Test: Fragmentomic profiles of plasma cfDNA
Blood collection and early detection testing based on fragmentomic profiles of plasma cfDNA
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| Healthy Healthy volunteers. |
Diagnostic Test: Fragmentomic profiles of plasma cfDNA
Blood collection and early detection testing based on fragmentomic profiles of plasma cfDNA
|
Outcome Measures
Primary Outcome Measures
- Sensitivity and specificity [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
Secondary Outcome Measures
- Positive predictive value and negative predictive value [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
- Sensitivity and specificity in distinguishing different AJCC stages [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 in distinguishing different AJCC stages
Eligibility Criteria
Criteria
Inclusion Criteria:
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Age 18 and above, regardless of gender;
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Histopathological diagnosis with pancreatic neuroendocrine tumor before surgery;
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Not receiving any anti-tumor treatment before surgery, including chemotherapy, embolization, ablation, radiotherapy, and molecular targeted therapy;
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No obvious surgical contraindications;
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Able to comply with research plans, follow-up plans, and other protocol requirements;
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Voluntary participation and signed informed consent.
Exclusion Criteria:
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Pathological diagnosis was nonpancreatic neuroendocrine tumor;
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Currently diagnosed with other types of tumors or any cancer history;
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Diagnosed with familial syndromes;
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Receiving anti-tumor treatment before surgery, including chemotherapy, embolization, ablation, radiotherapy, and molecular targeted therapy;
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Ongoing fever or recipient of anti-inflammation therapy within 14 days prior to study blood draw;
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Recipient of blood transfusion within 30 days prior to study blood draw;
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Recipient of organ transplant or prior non-autologous (allogeneic) bone marrow or stem cell transplant;
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Poor health condition and not suitable for blood draw;
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Any other disease/condition deemed not suitable for study enrollment by researcher.
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Fudan University
Investigators
- Principal Investigator: Xianjun Yu, MD, PhD, Fudan University
Study Documents (Full-Text)
None provided.More Information
Publications
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- CSPAC-NEN-3