Synthetic Metabolic and Genetic Networks for Medical Diagnosics

NCT ID: NCT04518072

Last Updated: 2025-06-11

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

TERMINATED

Total Enrollment

134 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-01-06

Study Completion Date

2025-06-06

Brief Summary

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This is a category 3 human study, prospective, comparative, in parallel groups. A comparative qualitative and quantitative analysis of several markers in 250 samples is proposed.

Detailed Description

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The assumption is that researchers can engineer synthetic metabolic and genetic networks to expand the panel of molecules that are currently known to be detected by natural systems. The investigators also hypothesize synthetic metabolic and genetic networks can be tuned for decisions making and in particular to diagnose diseases from biomarkers detections.

This project proposes for the first time a hybrid analogue / digital solution for the multiplexed detection of biomarkers using bacterial and paper-based biosensors. Biosensors can be designed using analog or digital devices. Digital devices in synthetic and natural systems are noise-resistant and useful for decision-making. Analog devices are useful for signal transmission and processing. Here the investigators take advantage of signal transmission and processing via analog transducers and adders, and then decision-making via genetic switches. Such a hybrid analogue / digital approach has not yet been developed for biosensing. Another novelty of the project is to use synthetic metabolic pathways to develop analog devices. The advantage in term of treatment, for example, consists in the fact that the speed of enzymatic reactions in an analog adder far exceeds the speed of gene expression required to create a genetic logic matrix; it becomes even more pronounced when the devices are connected in series. The methodology will be illustrated for the detection of biomarkers of prostate tumors, but it is broad enough to be applicable to other diagnoses. The choice to develop biosensors for prostate disease is of practical relevance since the current screening strategy (based on PSA measurement) can lead to overdiagnosis and cannot differentiate between patients with aggressive tumors and those with an indolent illness.This study propose to mainly develop a bacterial and paper-based biosensor system

Conditions

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Prostate Cancer

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

PROSPECTIVE

Study Groups

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Biopsy prostatic group

positive biopsy (100) negative biopsy (100)

Blood sample (1 EDTA tube, 1 SST tube, 1 Streck tube) and urine sample (100 ml)

Intervention Type OTHER

assessed biomarker in clinical samples

Control group

No prostate cancer (50)

Blood sample (1 EDTA tube, 1 SST tube, 1 Streck tube) and urine sample (100 ml)

Intervention Type OTHER

assessed biomarker in clinical samples

Interventions

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Blood sample (1 EDTA tube, 1 SST tube, 1 Streck tube) and urine sample (100 ml)

assessed biomarker in clinical samples

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Men aged over 18
* Informed, written consent of the patient for the biological collection
* Subject affiliated to a French social security scheme or beneficiary of such a scheme


\- Admitted to care prostate disease or suspicion of prostate cancer and with a positive or negative PSA blood result


\- Man free from all prostate or bladder pathologies


* Patient with current prostatic or urinary infection
* History of treatment for prostate cancer other than surveillance management

Exclusion Criteria

* Patient under legal protection
* Persons deprived of their liberty, protected adults or vulnerable persons
* Participants may withdraw their consent at any time and for any reason whatsoever without incurring any negative consequences without change in their usual care
Minimum Eligible Age

18 Years

Eligible Sex

MALE

Accepts Healthy Volunteers

No

Sponsors

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MICALIS

UNKNOWN

Sponsor Role collaborator

CBS

UNKNOWN

Sponsor Role collaborator

University Hospital, Montpellier

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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University Hospital

Montpellier, Hérault, France

Site Status

Clinique Beau Soleil

Montpellier, , France

Site Status

Countries

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France

Other Identifiers

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2019-A00234-53

Identifier Type: OTHER

Identifier Source: secondary_id

RECHMPL18_0404

Identifier Type: -

Identifier Source: org_study_id

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