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NCT04219137RECRUITINGanonymous

Molecular Characteristics of Gastroesophageal Adenocarcinoma (MOCHA): A Prospective Feasibility Study

Sponsor

Source record

University Health Network, Toronto

Phase

Source record

Observational

Modality

AI-normalized

gene therapy

Target

AI-normalized

Molecular characteristics and genomic profiling of gastroesophageal adenocarcinoma (GEA), including potential predictive signatures for treatment response.

Indication / condition

AI-normalized

Esophagogastric Adenocarcinoma

Intervention

Source record

Molecular Profiling

Source & freshness

Source record

NCT ID

NCT04219137

Original source

ClinicalTrials.gov

Source last updated

May 14, 2025

Ingested at

Jun 19, 2026

Internal sync

Jun 19, 2026

Model version

trialsignal-ai-v1

Normalized confidence

96%

Validation status

validated

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NCT ID

NCT04219137

Title

Molecular Characteristics of Gastroesophageal Adenocarcinoma (MOCHA): A Prospective Feasibility Study

Sponsor

University Health Network, Toronto

Status

RECRUITING

Phase

Observational

Condition raw

Esophagogastric Adenocarcinoma

Condition normalized

Esophagogastric Adenocarcinoma

Modality raw

gene therapy

Modality normalized

gene therapy

Target raw

Molecular characteristics and genomic profiling of gastroesophageal adenocarcinoma (GEA), including potential predictive signatures for treatment response.

Target normalized

Molecular characteristics and genomic profiling of gastroesophageal adenocarcinoma (GEA), including potential predictive signatures for treatment response.

Interventions

Molecular Profiling

Public preview

Source record

The MOCHA study, sponsored by the University Health Network in Toronto, aims to enhance understanding of gastroesophageal adenocarcinoma through molecular profiling. This research could lead to personalized treatment protocols, potentially positioning the sponsor as a leader in GEA management. The market for GEA therapies is significant, with increasing demand for targeted treatments. The study's outcomes may inform future clinical trials and therapeutic strategies, impacting competitive positioning in the oncology landscape. Companies focusing on molecular diagnostics and personalized medicine may find collaboration or acquisition opportunities arising from the findings.

AI-generated analysis supports research triage only. Verify source records, publications, sponsor disclosures and IP databases before making diligence decisions. Model: trialsignal-ai-v1.

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