This study aimed to identify candidate shared transcriptomic signals between major depressive disorder and dermatomyositis through an integrative bioinformatic reanalysis of public GEO datasets with single-cell contextualization. The analytical workflow included Weighted Gene Co-expression Network Analysis (WGCNA) for key module identification, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for functional characterization, GeneMANIA- and a network visualization platform-based network analysis for candidate-gene prioritization, and evaluation of 113 machine-learning models combined with SHapley Additive exPlanations (SHAP) for diagnostic feature selection. Gene Set Enrichment Analysis (GSEA), immune infiltration analysis, and single-cell RNA-seq-based contextualization were subsequently performed to further characterize the immune-related cellular context of the identified signals. Integration of dermatomyositis-related GEO datasets identified 570 differentially expressed genes, from which 33 candidate shared genes were obtained via WGCNA. Functional enrichment and network analyses highlighted immune defense, cytotoxicity, and pathways including PPAR, IL-17, and antigen processing, with ELANE, PPBP, and CTSG emerging as highly connected nodes. Machine-learning-based feature prioritization retained 8 candidate model-selected genes, namely KIF4A, OLR1, KIR2DL4, KRT23, KIR3DS1, AZU1, SCG5, and LRRC37E. Immune infiltration analysis associated these shared genes with regulatory T cells (Tregs), resting mast cells, resting dendritic cells, and both classically activated (M1) and alternatively activated (M2) macrophages. Single-cell RNA-seq contextualization further suggested that CD8⁺ T-cell subsets with different candidate-gene score states showed distinct intercellular communication patterns. Among these, the MIF-(CD74+CD44) axis and signals from naive/central memory T cells were notable features requiring further validation. Overall, this study identified candidate shared transcriptomic signals between major depressive disorder and dermatomyositis and highlighted immune-related cellular contexts that warrant further validation in true comorbid cohorts.