Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| West China Hospital | OTHER |
Not provided
Not provided
Not provided
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.
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."
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| pNETs | Patients with pancreatic neuroendocrine tumors (pNETs). The prospective cases enrolled by the sub-center shall strictly comply with the study's inclusion/exclusion criteria, consistent with the main center, and no independent adjustment of the enrollment criteria is allowed. |
| |
| Healthy | Healthy volunteers. The prospective cases enrolled by the sub-center shall strictly comply with the study's inclusion/exclusion criteria, consistent with the main center, and no independent adjustment of the enrollment criteria is allowed. |
| |
| PDAC | Patients with pancreatic ductal adenocarcinoma (PDAC) . The prospective cases enrolled by the sub-center shall strictly comply with the study's inclusion/exclusion criteria, consistent with the main center, and no independent adjustment of the enrollment criteria is allowed. |
| |
| SPT | Patients with solid pseudopapillary tumor (SPT) of pancreas. The prospective cases enrolled by the sub-center shall strictly comply with the study's inclusion/exclusion criteria, consistent with the main center, and no independent adjustment of the enrollment criteria is allowed. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity and specificity of the integrated fragmentomic model for detecting pNETs | 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. |
| Sensitivity and specificity of the model for differential diagnosis among solid pancreatic tumors | Sensitivity and specificity of the model for differential diagnosis among PDAC, pNET and SPT. | From first blood draw until histopathological diagnosis, up to 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| 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 |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
The study population enrolled by the main center and the sub-center is uniformly divided into four groups with the same enrollment criteria for all.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xianjun Yu, MD, PhD | Contact | 021-64175590-88503 | yuxianjun@fudanpci.org | |
| Shunrong Ji, MD, PhD | Contact | 13788993956 | jishunrong@fudanpci.org |
| Name | Affiliation | Role |
|---|---|---|
| Xianjun Yu, MD, PhD | Fudan University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Fudan University shanghai cancer center | Recruiting | Shanghai | Shanghai Municipality | 200032 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25132004 | Background | 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. | |
| 28448665 | Background | 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. |
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D007516 | Adenoma, Islet Cell |
| ID | Term |
|---|---|
| D000236 | Adenoma |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |
| D009369 | Neoplasms |
Not provided
Not provided
| ID | Term |
|---|---|
| D001800 | Blood Specimen Collection |
| ID | Term |
|---|---|
| D013048 | Specimen Handling |
| D019411 | Clinical Laboratory Techniques |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
Not provided
Not provided
Not provided
Not provided
Not provided
Plasma samples
|
| Accuracy of the model in predicting AJCC stage (where applicable) and tumor grade |
Sensitivity and specificity of the integrated model using fragmentomic profiles of plasma cfDNA in predicting AJCC stage (where applicable) and tumor grade |
| From date of first blood draw until first documented histopathological diagnosis, assessed up to 3 years |
| West China Hospital, Sichuan University | Recruiting | Chengdu | Sichuan | 610041 | China |
|
| 34954829 | Background | 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. |
| 29668834 | Background | 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. |
| 34417454 | Background | 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. |
| 26771485 | Background | 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. |
| 35780566 | Background | 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. |
| 35690859 | Background | 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. |
| 34702327 | Background | 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. |
| D010190 |
| Pancreatic Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D004701 | Endocrine Gland Neoplasms |
| D004066 | Digestive System Diseases |
| D010182 | Pancreatic Diseases |
| D004700 | Endocrine System Diseases |
| D011677 | Punctures |
| D013514 | Surgical Procedures, Operative |
| D008919 | Investigative Techniques |