INSPIRE: a Multi-Cancer Early Detection Study

Last updated: February 19, 2025
Sponsor: Singlera Genomics Inc.
Overall Status: Active - Recruiting

Phase

N/A

Condition

Breast Cancer

Lung Cancer

Colorectal Cancer

Treatment

N/A

Clinical Study ID

NCT06440018
multiple
  • Ages 40-75
  • All Genders

Study Summary

This research constitutes a multi-centric, case-control designed investigation aimed at developing and implementing a blinded validation of a machine learning-powered, multi-cancer early detection model. This is to be achieved through the prospective collection of blood specimens from newly diagnosed cancer patients and individuals devoid of a confirmed cancer diagnosis

Eligibility Criteria

Inclusion

Inclusion Criteria for Case Arm Participants:

  • 40-75 years old

  • Clinically and/or pathologically diagnosed cancer

  • No prior or undergoing any systemic or local antitumor therapy, including but not limited to surgical resection, radiochemotherapy, endocrinotherapy, targeted therapy, immunotherapy, interventional therapy, etc.

  • Able to provide a written informed consent and willing to comply with all part of the protocol procedures

Exclusion Criteria for Case Arm Participants:

  • Pregnancy or lactating women

  • Known prior or current diagnosis of other types of malignancies comorbidities

  • Have participated in an "interventional" clinical trial within the past 30 days and have taken the experimental drug;

  • Recipients of organ transplant or prior bone marrow transplant or stem cell transplant

  • Recipients of blood transfusion within 30 days prior to screen

  • Recipients of therapy in past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide

  • Failure to collect blood on time according to plan

  • The blood sample does not meet the requirements

Inclusion Criteria for Control Arm Participants:

  • 40-75 years old

  • Without confirmed cancer diagnosis

  • Able to provide a written informed consent and willing to comply with all part of the protocol procedures

Exclusion Criteria for Control Arm Participants:

  • Pregnancy or lactating women

  • No previous history of malignancy in other sites

  • Recipients of organ transplant or prior bone marrow transplant or stem cell transplant

  • Recipients of blood transfusion within 30 days prior to screen

  • Recipients of therapy in the past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide

  • Unsuitable for this trial determined by the researchers

Study Design

Total Participants: 5350
Study Start date:
July 20, 2024
Estimated Completion Date:
February 28, 2025

Study Description

Cancerous tissues, their adjacent non-cancerous tissues, along with white blood cells (WBCs) and normal tissue samples will be utilized to identify potential methylation candidate markers and investigate variations in methylation patterns among patients diagnosed with distinct cancer types. Building upon previous research and current study, a comprehensive methylation signature panel tailored specifically to cancer patients will be established.

We will prospectively collect blood samples from newly diagnosed cancer patients and non-cancer individuals to analyze and identify specific cancer signals via the detection of cfDNA methylation patterns. Following a rigorous and comprehensive research framework, a machine learning-driven model will be developed and validated through blinded testing in an independent cohort. The study aims to enroll approximately 2,650 cancer patients, with a focus on including early-stage cases to enhance the model's sensitivity in detecting cancers with favorable prognoses. Furthermore, around 2,400 control subjects, matched with cancer patients by age and gender and screened negative for cancer through routine tests, will participate as healthy or benign-condition volunteers in model development. Lastly, samples from an additional 300 patients with other tumors will be gathered to conduct interference testing, ensuring the robustness of the model's performance.

Connect with a study center

  • Fudan University

    Shanghai, Shnaghai 200433
    China

    Active - Recruiting

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