Single‐Cell and Machine Learning Analyses Identify MYDGF as an Immune‐Related Biomarker Associated With the Tumor Microenvironment in Clear Cell Renal Cell Carcinoma
Single‐cell transcriptomics and machine learning methods are increasingly used to identify immune‐related biomarkers in solid tumors, yet their combined application to microenvironment‐related drivers of therapeutic resistance in clear cell renal cell carcinoma (ccRCC) is still limited. Here, we investigated the biological and clinical significance of myeloid‐derived growth factor (MYDGF) through an integrative strategy spanning single‐cell profiling, bulk multiomics, and functional validation. Analysis of scRNA‐seq data (GSE156632) revealed that MYDGF is preferentially detected in malignant epithelial subpopulations and associated with the composition of myeloid and lymphoid compartments. Integration with TCGA‐KIRC transcriptomic and clinical datasets demonstrated strong associations between MYDGF expression and immune‐checkpoint activation, immune dysfunction signatures, and PI3K/AKT–MAPK pathway activity. Tumors with high MYDGF expression exhibited an immune‐infiltrated yet functionally impaired microenvironment and were predicted to show reduced responsiveness to immune checkpoint blockade. Differential expression and enrichment analyses further highlighted MYDGF‐associated genes involved in inflammatory, extracellular, and receptor‐binding functions. A machine learning pipeline using LASSO Cox regression identified a preliminary 19‐gene MYDGF‐related prognostic gene set that requires further validation. Functional experiments confirmed that MYDGF knockdown suppressed proliferation, migration, and invasion in ccRCC cells. Overall, our analyses characterize MYDGF as a microenvironment‐related biomarker linked to immune‐associated features, signaling‐associated alterations, and adverse prognosis in ccRCC. These results nominate MYDGF as a candidate prognostic biomarker and show the value of pairing single‐cell resolution with computational modeling for biomarker discovery in renal cancer.