Early Diagnosis of Pancreatic Cancer Via Deciphering Multi-modal Immunological Signatures

NCT06495749 | Not Yet Recruiting

• 1 other identifier: MULTIMODAL-1
• Study Type: observational
• Target: 3,000
• Locations: 1 country
• Sites: 2

Brief Summary

Prospective inclusion of 1000 patients with pancreatic cancer (early-stage pancreatic cancer accounts for approximately 75% of cases), 1000 patients with benign pancreatic diseases, and 1000 healthy individuals as controls. Peripheral blood samples were collected from newly diagnosed pancreatic cancer patients and healthy individuals. Using techniques such as plasma TCR/BCR-seq, CyTOF, and plasma proteomics, multi-modal individual immune characteristics were obtained and analyzed along with clinical information. An artificial intelligence predictive model was built based on these multi-modal individual immune characteristics to establish an early screening technique for pancreatic cancer. The sensitivity and specificity of this artificial intelligence model for early pancreatic cancer diagnosis were evaluated using an external multicenter sample test set.

Conditions

Pancreatic Cancer Resectable

Keywords

Early diagnosis; Pancreatic cancer; Artificial intelligence; Immunity decoding

Outcome Measures

Primary Outcomes (8)

• Peripheral blood mononuclear cell

  Using RNA seq technology to analyze differentially expressed genes in peripheral immune cells

  During the 1-7 day period before surgery

• Peripheral blood mononuclear cell

  TCR/BCR-seq:Using multiple amplification to obtain the CDR3（complementarities determining region3） region of TCR and BCR and analyzing the VDJ rearrangement pattern

  During the 1-7 day period before surgery

• Peripheral blood mononuclear cell

  Analyzing RNA expression in individual cells using scRNA-seq

  During the 1-7 day period before surgery

• Peripheral blood mononuclear cell

  scTCR/BCR-seq:Using multiple amplification to obtain the CDR3（complementarities determining region3） region of TCR and BCR and analyzing the VDJ rearrangement pattern in individual cells

  During the 1-7 day period before surgery

• Peripheral blood mononuclear cell

  Identification of open chromatin regions in individual cells using scATAC-seq technology

  During the 1-7 day period before surgery

• Peripheral blood mononuclear cell

  Detecting the abundance and type of some markers for peripheral blood mononuclear cell using CYTOF technology

  During the 1-7 day period before surgery

• CT

  Imaging data from the patient's initial visit

  Within 1 month before surgery

• MRI

  Imaging data from the patient's initial visit

  Within 1 month before surgery

Study Arms (3)

Pancreatic Cancer

The patient is diagnosed with pancreatic cancer for the first time and has not received any tumor treatment.

Benign Pancreatic Diseases

The patient is diagnosed with a benign pancreatic disease ，such as SCN、MCN、IPMN.and has not undergone any treatment.

Healthy controls

A healthy population without any pancreatic-related diseases or other cancers.

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Prospective inclusion of 1000 patients with pancreatic cancer (early-stage pancreatic cancer accounts for approximately 75% of cases), 1000 patients with benign pancreatic diseases, and 1000 healthy individuals as controls. Peripheral blood samples were collected from newly diagnosed pancreatic cancer patients and healthy individuals. Using techniques such as plasma TCR-seq, CyTOF, and plasma proteomics, multi-modal individual immune characteristics were obtained and analyzed along with clinical information. An artificial intelligence predictive model was built based on these multi-modal individual immune characteristics to establish an early screening technique for pancreatic cancer.

You may qualify if:

• Sign the informed consent form;
• Initial diagnosis as patients with pancreatic cancer, patients with benign pancreatic lesions, or healthy controls.

You may not qualify if:

• History of other malignancies;
• Presence of organ dysfunction;
• Concurrent immunodeficiency syndrome, active tuberculosis, HIV infection, etc.;
• Allogeneic transplantation requiring immunosuppressive therapy;
• Poor follow-up compliance.

Sponsors & Collaborators

• Zhejiang University: lead
• The Affiliated Hospital of the Chinese Academy of Military Medical Sciences: collaborator
• Nanjing Medical University: collaborator

Study Sites (2)

First Affiliated Hospital, Medical College of Zhejiang University

Hangzhou, Zhejiang, 310003, China

Location

the First Affiliated Hospital, School of Medicine, Zhejiang University

Hangzhou, Zhejiang, 310009, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

Blood analysed for RNA-seq、TCR/BCR-seq、scRNA-seq、scTCR/BCR-seq、scATAC-seq and CyTOF

MeSH Terms

Conditions

Disease; Pancreatic Neoplasms

Condition Hierarchy (Ancestors)

Pathologic Processes; Pathological Conditions, Signs and Symptoms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Endocrine Gland Neoplasms; Digestive System Diseases; Pancreatic Diseases; Endocrine System Diseases

Central Study Contacts

Qi Zhang, Associate professor

CONTACT

13819137113; qi.zhang@zju.edu.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: June 23, 2024
• First Posted: July 11, 2024
• Study Start: August 1, 2024
• Primary Completion (Estimated): January 1, 2027
• Study Completion (Estimated): December 31, 2027
• Last Updated: July 16, 2024

Record last verified: 2024-07

Data Sharing

• IPD Sharing: Will not share

Locations

CN (2)