The Effect of Environmental Factors on Gastric Cancer Based on Macrogenome

N/AActive Not RecruitingNCT06854146

Dong Peng200 enrolled

Overview

The objectives of this study were to clarify how environmental factors such as air pollution affect the occurrence and development of gastric cancer; to identify patient-specific macrogenomic markers of gastric cancer; and to investigate the mechanism of gastric cancer development based on environmental factors and macrogenomic data.

Study Type

OBSERVATIONAL

Enrollment

200

Conditions

Gastric Cancers Air Pollution

Interventions

gastric cancerDIAGNOSTIC_TEST

patients diagnosed with gastric cancer

healthyDIAGNOSTIC_TEST

healthy participants

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * age ≥ 18 years; * patients with preoperative diagnosis of gastric cancer confirmed by pathologic biopsy; * no chemotherapy, radiotherapy, targeted and immunotherapy, etc. before enrollment; * willing to participate in the study and sign the informed consent form; * complete clinical data. Exclusion Criteria: * concurrent primary malignant tumor other than gastric cancer; * patients with systemic diseases, such as severe cardiopulmonary; * insufficiency, that affect the choice of treatment plan; * not suitable for enrollment as assessed by the investigator; * incomplete clinical data.

Locations (1)

The First Affiliated Hospital of Chongqing Medical University

Chongqing, Chongqing Municipality, China

Outcomes

Primary Outcomes

Overall Survival (OS)

Description: Time from diagnosis to death from any cause, measured via medical records and follow-up interviews. Unit: Months

Time frame: From date of diagnosis until the date of death from any cause or or loss to follow-up, whichever came first, assessed up to 60 months

Secondary Outcomes

Gut microbiome composition differences assessed by shotgun metagenomic sequencing

Measuring Tool: Shotgun metagenomic sequencing (Illumina NovaSeq 6000). Analysis Parameters: Alpha diversity (Shannon index); Beta diversity (Bray-Curtis dissimilarity); Differential abundance of bacterial species (ANCOM-BC). Unit: Relative abundance (%) / Diversity indices.

Time frame: Tissue samples collected intraoperatively, sequencing completed within 1 week post-surgery.

Data from ClinicalTrials.gov

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