Lung CancerINSPIRENCT06440018
INSPIRE: a Multi-Cancer Early Detection Study
An observational study of Lung Cancer and Gastric Cancer, run by Singlera Genomics Inc. at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 40 to 75 years
- Conditions the study is for
- Lung Cancer, Gastric Cancer, Liver Cancer
- How many people
- 5,350 participants
- Where
- 1 siteChina
- Study dates
- 20 Jul 2024to 28 Feb 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: A consenting professional will invite participants, including cancer patients and healthy controls, from the main center and affiliated hospitals, to take part in a comprehensive case-control study.
Who may be able to join
- 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
- 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
Who cannot join
- 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
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- Failure to collect blood on time according to plan
- The blood sample does not meet the requirements
- 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
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Fudan University
Shanghai, Shnaghai, 200433
Chen Suo, PhD, 86-21-54237625, suochen@fudan.edu.cn
About this study
Official title: INSPIRE: Integrating Circulating DNA Methylation and Fragmentomics to Scan and Pinpoint Cancer Signals Effectively
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
Read the detailed 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.
- Conditions
- Lung Cancer, Gastric Cancer, Liver Cancer, Colorectal Cancer, Pancreatic Cancer, Esophageal Cancer
- Medical subject headings
- Lung Neoplasms, Stomach Neoplasms, Liver Neoplasms, Colorectal Neoplasms, Pancreatic Neoplasms, Esophageal Neoplasms, Breast Neoplasms, Uterine Cervical Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Case arm | Participants newly diagnosed with cancer, belonging to one of thirteen distinct cancer types. | |
| Control arm | Healthy or benign condition participants with no cancer diagnosis subsequent to routine cancer screening tests. |
What is being measured
The primary outcome is the main question the study is designed to answer.
The AUC, sensitivity, specificity and tissue origin accuracy of the multi-cancer early detection model in detecting cancer or non-cancer
Measured: 12 months
Secondary outcomes (2)
The performance of the multi-cancer early detection model in early stage cancer and precancerous lesion cases
Measured: 12 months
The performance of the multi-cancer early detection model in different subgroups (such as age, gender, cancer pathological classification, and clinical stage)
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Jun 2024
- Study start20 Jul 2024
- Primary completion28 Feb 2025 (estimated)
- Study completion28 Feb 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 5,350 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Singlera Genomics Inc.
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Fudan University, Hubei Cancer Hospital, China-Japan Friendship Hospital, Shanxi Province Cancer Hospital, Xuhui Central Hospital, Fudan University, Shanghai Electric Power Hospital, Shanghai East Hospital of Tongji University, First Affiliated Hospital Xi'an Jiaotong University, GaoZhou People's Hosipital, Anhui Provincial Hospital, Beijing Friendship Hospital
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06440018
- Sponsor's protocol ID
- multiple
- Acronym
- INSPIRE
- Status last verified
- May 2024
- First submitted
- 28 May 2024
- Last updated
- 21 Feb 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- INSPIRE: Integrating Circulating DNA Methylation and Fragmentomics to Scan and Pinpoint Cancer Signals Effectively
- ClinicalTrials.gov ID
- NCT06440018
- Acronym / sponsor ID
- INSPIRE / multiple
- Conditions
- Lung Cancer, Gastric Cancer, Liver Cancer, Colorectal Cancer, Pancreatic Cancer, Esophageal Cancer
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 5,350 participants (estimated)
- Lead sponsor
- Singlera Genomics Inc.Industry (pharma, biotech, devices)
- Collaborators
- Fudan University, Hubei Cancer Hospital, China-Japan Friendship Hospital, Shanxi Province Cancer Hospital, Xuhui Central Hospital, Fudan University, Shanghai Electric Power Hospital, Shanghai East Hospital of Tongji University, First Affiliated Hospital Xi'an Jiaotong University, GaoZhou People's Hosipital, Anhui Provincial Hospital, Beijing Friendship Hospital
- Study start
- 20 Jul 2024 (actual)
- Primary completion
- 28 Feb 2025 (estimated)
- Study completion
- 28 Feb 2025 (estimated)
- First posted
- 3 Jun 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
Detailed 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.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Case arm | – | –Participants newly diagnosed with cancer, belonging to one of thirteen distinct cancer types. |
| Control arm | – | –Healthy or benign condition participants with no cancer diagnosis subsequent to routine cancer screening tests. |
Who may qualify
- Ages
- 40 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- A consenting professional will invite participants, including cancer patients and healthy controls, from the main center and affiliated hospitals, to take part in a comprehensive case-control study.
Key inclusion criteria (7 listed)
- 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
- 40-75 years old
Key exclusion criteria (14 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
The AUC, sensitivity, specificity and tissue origin accuracy of the multi-cancer early detection model in detecting cancer or non-cancer
Time frame: 12 months
2 secondary outcomes
The performance of the multi-cancer early detection model in early stage cancer and precancerous lesion cases
Time frame: 12 months
The performance of the multi-cancer early detection model in different subgroups (such as age, gender, cancer pathological classification, and clinical stage)
Time frame: 12 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Feb 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer and Gastric Cancer, run by Singlera Genomics Inc. at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 14 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 21 Feb 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Zhixi Su, PHD (+862180113170 ext. 1022, zhixi.su@singlera.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The AUC, sensitivity, specificity and tissue origin accuracy of the multi-cancer early detection model in detecting cancer or non-cancer (time frame: 12 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Feb 2025; AzTrials last refreshed its copy on 29 Oct 2026.