Oncogenic pathway combinations predict clinical prognosis in gastric cancer

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Solid cancers display significant heterogeneity in oncogenic pathway deregulation.
• Gastric cancer (GC) is a leading cause of cancer mortality globally.
• Understanding major oncogenic pathways in GC is crucial for improving patient outcomes.

Purpose of the Study:

• To identify major oncogenic pathways in gastric cancer (GC) associated with patient survival.
• To stratify GC patients based on oncogenic pathway activation patterns.
• To explore the role of pathway interactions in GC disease behavior.

Main Methods:

• Utilized gene expression signatures for an in silico strategy.
• Mapped oncogenic pathway activation patterns in 301 primary gastric cancers.
• Functionally validated pathway predictions in gastric cancer cell lines.

Main Results:

• Identified three key deregulated oncogenic pathways in over 70% of GCs: proliferation/stem cell, NF-kappaB, and Wnt/beta-catenin.
• Demonstrated reproducible and significant survival differences across patient cohorts stratified by pathway combinations.
• Showcased the ability to taxonomize individual GCs into biologically and clinically relevant subgroups based on pathway activity.

Conclusions:

• Gastric cancer heterogeneity can be characterized by specific oncogenic pathway deregulation.
• Pathway interactions significantly influence GC disease behavior and patient survival.
• In silico prediction of pathway activity enables large-scale study of interacting pathways in primary cancers.