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Advanced GC Multi-omic Characterization in EU and CELAC Populations

Advanced GC Multi-omic Characterization in EU and CELAC Populations

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04015466
Acronym
LEGACY-2
Enrollment
800
Registered
2019-07-11
Start date
2019-06-12
Completion date
2023-12-31
Last updated
2024-05-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gastric Cancer

Keywords

Gastric Cancer, Personalized medicine, Oncology, Solid tumor, Primary Intervention

Brief summary

Observational study (cohort type) of advanced GC patients that will be recruited prospectively to study biological factors associated with the disease and relevant clinical outcomes.

Detailed description

Despite of multiple attempts to improve treatment in recent decades, none strategies has improved prognosis in locally advanced stage III and IV GC. A therapeutic approach to GC based on current histological and image criteria (Tumour Node Metastasis -TNM- stage) is insufficient. Although multiple targeted agents are currently under investigation, so far, only trastuzumab and ramucirumab have demonstrated efficacy in advanced GC and have a regulatory approval. For this reason, the identification of specific targets that could be susceptible for drug inhibition, is an urgent requirement. Moreover, most studies and current international databases on late-stage/advanced GC are largely based on Asian populations, in sharp contrast tumour biology and genome of EU or CELAC populations remain poorly known. The primary objective of this study are to: 1. Characterize a multi-centric cohort including EU and CELAC populations diagnosed with advanced GC through a multi-omic approach including proteomics, genomics, transcriptomics, microbiome and exposome analysis due to study the determinants of GC. 2. Identify the regional differences in EU and CELAC populations recruiting patients for this study for each omic characterization due to identify the high-risk group populations. 3. Identify and select from the multi-omic approach those biomarkers useful for the development of an algorithm to guide the therapeutic approach for advanced GC.

Interventions

None listed

Sponsors

Instituto Nacional de Cancerologia de Mexico
CollaboratorOTHER
Amsterdam UMC, location VUmc
CollaboratorOTHER
Pontificia Universidad Catolica de Chile
CollaboratorOTHER
Vall d'Hebron Institute of Oncology
CollaboratorOTHER
INSTITUTO ALEXANDER FLEMING
CollaboratorUNKNOWN
Hospital Central del IPS
CollaboratorOTHER
IPATIMUP - Instituto De Patologia E Imunologia Molecular Da Universidade Do Porto
CollaboratorOTHER
Fundación para la Investigación del Hospital Clínico de Valencia
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 90 Years

Inclusion criteria

Cases: * Inclusion criteria: * Subjects ≥18 years old. * GC diagnosis stages III and IV (including gastroesophageal junction cancer) and/or a gastroscopy indication due to the high diagnostic suspicion of GC as part of the study of his disease. * Has given and signed the IC to participate in this study. *

Exclusion criteria

• Patients diagnosed with GC early disease (stage I and II) suitable for resectable strategy. * Withdrawal criteria: * Patients initially recruited with high suspicion of GC diagnosis but not confirmed by the pathological report. Controls: * Inclusion criteria (only for microbiome analysis): * Subjects ≥18 years old. * Subjects to whom a gastroscopy is indicated within clinical care and is confirmed absent of GC in the same centres will be matched in age (+/- 10 years), gender and pertaining from the same region of the GC case. * Has given and signed the IC to participate in this study. *

Design outcomes

Primary

MeasureTime frameDescription
Development of a new diagnostic algorithm for gastric cancer that includes molecular landscape, patient history, histopathological and environmental factors, personal microbiome and immune landscape3 yearsThe project will look for an integrative diagnostic algorithm that incorporates multi-parameter inputs and apply artificial intelligence to provide more personalized risk estimates and which will form the basis for future development of a clinical tool

Secondary

MeasureTime frameDescription
Genomics (tumour next-generation sequencing)3 yearsDetermine differences in the genetic mutational profile of different populations
Transcriptomics (Nanostring immune gene expression panel)3 yearsDetermine differences in the genetic expression profile of different populations
Microbiota sequencing (including level of Epstein-Barr virus [EBV] DNA)3 yearsDetermine differences in the microbiota profile of different populations
Proteomic analysis of gastric cancer tissue3 yearsDetermine the expression of certain proteins using ICH and ISH
Biological risk factors as assessed through medical chart review3 yearsDetermine differences in biological risk factors of different populations and its correlation with risk to develop gastric cancer
Daily routines as assessed by a new study-specific questionnaire3 yearsDetermine differences daily routines of different populations and its correlation with risk to develop gastric cancer
Dietary habits as assessed by a new study-specific questionnaire3 yearsDetermine differences in dietary habits of different populations and its correlation with risk to develop gastric cancer

Countries

Argentina, Chile, Mexico, Netherlands, Paraguay, Portugal, Spain

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 17, 2026