Objective:

To elucidate the roles of myeloid cells in stomach adenocarcinoma (STAD) and establish a molecular classification based on myeloid states, while exploring their relationship with patient prognosis and therapeutic response.

Approach:

• Data Integration: Integrated single-cell RNA-seq profiles and 443 bulk RNA-seq profiles from the TCGA-STAD cohort.
• Myeloid State Identification: Identified myeloid state-related prognostic genes (MSRPGs) and constructed a molecular classification (STAD-MSC) using pseudotime analysis and survival analysis, along with correlation analysis to establish regulatory networks.
• Validation: Evaluated a 5-gene risk model in a public 355-patient validation cohort and assessed the STAD-MSC framework at the protein level in a 70-patient retrospective cohort.

Key Findings:

• Identified 32 MSRPGs across five distinct myeloid states.
• Stratified patients into three subtypes: low immune infiltration STAD (LI-STAD), moderate immune infiltration STAD (MI-STAD), and high immune infiltration STAD (HI-STAD).
• HI-STAD subtype exhibited the poorest overall survival (global log-rank p = 0.018).
• Constructed a 5-gene prognostic signature and identified subtype-specific drug response differences, including nominal associations for dabrafenib (p = 0.0051) and ruxolitinib (p = 0.041).

Interpretation:

The STAD-MSC framework provides a myeloid state-centric molecular taxonomy that stratifies STAD patients into subgroups with distinct prognoses and immunosuppressive features.

Limitations:

• The study relies on data from public cohorts, which may limit generalizability.
• Further validation in larger, independent cohorts is necessary to confirm findings.

Conclusion:

The study establishes a framework for immune-informed patient stratification in STAD based on myeloid states.