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Exosome-based Liquid Biopsies for Upper Gastrointestinal Cancers Diagnosis

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Capital Medical University

Status

Enrolling

Conditions

Esophagus Cancer
Gastric Cancer

Treatments

Other: Esophagus Cancer
Other: Gastric Cancer

Study type

Observational

Funder types

Other

Identifiers

NCT06278064
BFHHZML20240006

Details and patient eligibility

About

This study constitutes a case-control investigation employing a retrospective approach. Plasma samples from individuals with esophageal cancer, benign esophageal diseases, gastric cancer, benign gastric diseases, and a healthy control group were systematically collected. Advanced Data-Independent Acquisition (DIA) proteomics and single-vesicle membrane protein detection techniques were employed to quantify protein content within exosomes. Specific protein biomarkers indicative of early-stage upper gastrointestinal tumors were identified. External validation of these protein markers was conducted using Parallel Reaction Monitoring (PRM) technology on an independent validation cohort. The objective is to establish protein marker predictions for early diagnosis of upper gastrointestinal tumors and prognostication of therapeutic efficacy.

Full description

This study employs a multicenter, retrospective cohort design, collecting and analyzing plasma and tissue exosome protein data from patients with upper gastrointestinal tumors (Stage I-II), upper gastrointestinal benign diseases, and a healthy control group who have visited Beijing Friendship Hospital, and other relevant sub-center hospitals over the past five years. Concurrently, relevant clinical and pathological information is recorded.

Samples from the training cohort undergo traditional quantitative exosome proteomic analysis (Data-Independent Acquisition, DIA) and single-vesicle membrane protein analysis (PBA). A comprehensive upper gastrointestinal tumor-specific exosome protein database is constructed, incorporating extensive information. Subsequently, bioinformatics methods are employed to conduct in-depth analysis of the extensive protein data, screening for proteins with high specificity for upper gastrointestinal tumors, capable of direct detection on the exosome membrane surface. By establishing and evaluating diagnostic models, we aim to quantify the diagnostic potential of these markers, providing a scientific basis for future early screening methods for upper gastrointestinal tumors.

Finally, external validation of these protein markers in an independent validation cohort ensures their reliability and stability across different patient populations. The academic significance of this research lies in its thorough exploration of exosome proteomics in early cancer diagnosis, offering potential innovative breakthroughs for academic progress and clinical practice in this field.

Enrollment

562 estimated patients

Sex

All

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Confirmed diagnosis of upper gastrointestinal cancers or benign upper gastrointestinal diseases through gastroscopy and pathological examination.
  • Collection of plasma samples prior to surgical treatment.
  • Availability of complete clinical data.

Exclusion criteria

  • Previous reception of anti-tumor treatments (including radiotherapy, chemotherapy, etc.) before blood collection.
  • Coexistence of other systemic tumors.
  • Absence of plasma sample collection before surgical treatment.
  • Incomplete clinical data.
  • Pregnancy status

Trial design

562 participants in 3 patient groups

Gastric cancer group
Description:
Patients diagnosed with gastric cancer, including early gastric cancer and advanced gastric cancer
Treatment:
Other: Gastric Cancer
esophagus cancer group
Description:
Patients diagnosed with esophagus cancer, including early esophagus cancer and advanced esophagus cancer
Treatment:
Other: Esophagus Cancer
Non-cancer group
Description:
Patients diagnosed with benign upper gastrointestinal diseases or healthy controls

Trial contacts and locations

3

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Central trial contact

Chenjie Xu, Ph.D.; Li Min, Ph.D.

Data sourced from clinicaltrials.gov

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