Comment on “ANKRD46 as a shared diagnostic and therapeutic marker in keloid and type 2 diabetes mellitus identified via multi omics and experimental validation”

Dear Editor, We were pleased to read the article by Yu et al, titled “ANKRD46 as a Shared Diagnostic and Therapeutic Marker in Keloid and Type 2 Diabetes Mellitus Identified via Multi Omics and Experimental Validation,” published in the International Journal of Surgery (DOI: 10.1097/JS9.0000000000004116)[1]. Following the TITAN 2025 guideline on artificial intelligence transparency[2], a generative AI-based language model was used exclusively for language polishing and did not impact the scientific content. This study systematically investigated the shared molecular basis between keloids and type 2 diabetes mellitus through the integration of bioinformatics analysis and experimental validation. Specifically, ANKRD46 was identified as a core diagnostic biomarker by employing differential expression analysis and machine learning approaches. Subsequent experiments confirmed its significant upregulation in both diseases, demonstrating excellent diagnostic performance. Further investigations revealed that ANKRD46 expression closely correlates with immune cell infiltration, including plasmacytoid dendritic cells and activated B cells, and activates the IL6-JAK-STAT3 pathway to promote fibrosis, while its expression is regulated by miR-21. In conclusion, this study establishes ANKRD46 as a key therapeutic target linking both diseases for the first time, positioning it not only as a potential shared diagnostic marker but also providing a new direction for developing combination therapeutic strategies targeting this pathway. While this work is compelling, several aspects warrant further investigation: First, the study exhibits limitations in its selection of cellular models, primarily focusing on human keloid-derived primary fibroblasts. However, it fails to adequately justify the exclusion of other critical cell types involved in keloid pathogenesis, such as keratinocytes, endothelial cells, and various immune cells[3,4], which play essential roles in wound healing, inflammatory responses, and fibrotic processes. Future investigations should conduct systematic validation across multiple relevant cell types within a more comprehensive pathological microenvironment framework to better elucidate the cell-type specificity and functional heterogeneity of ANKRD46. Notably, the data analysis in this study could be further optimized. The core analysis integrated datasets from different tissue sources (GSE7890 from keloid fibroblasts, GSE95849 from diabetic peripheral blood, with validation sets GSE92566 and GSE76895 from skin biopsies and pancreatic islets, respectively). While this multi-tissue approach helps reflect systemic disease characteristics, significant differences in cellular composition and expression profiles across tissues may introduce systematic bias. Additionally, batch effect correction and normalization procedures for cross-platform data were insufficiently described, which may potentially affect differential gene identification. If follow-up studies use validation with tissue-matched samples or single-cell sequencing to resolve cell type-specific shared expression patterns, the persuasiveness of the conclusion could be further enhanced. Finally, the clinical translation pathway for this biomarker requires further clarification. Although the study suggests potential detection in either lesional tissues or peripheral blood samples, the optimal detection strategy remains undetermined due to the lack of correlative data between these two sample types. It is recommended that future studies should employ well-designed clinical cohorts to conduct parallel testing of paired lesional tissue and peripheral blood samples from the same patients. This would enable systematic evaluation of ANKRD46 expression stability across sample types and practical detection feasibility, thereby providing empirical evidence for establishing standardized and generalizable detection protocols. In summary, this study provides evidence elucidating the critical role of ANKRD46 in the shared mechanisms between keloids and type 2 diabetes mellitus, although its specific mechanisms require further clarification. Their work opens new avenues for developing cross-disease therapeutic strategies by targeting the immune-metabolic interaction network. We commend the authors’ efforts and hope that future prospective clinical research will translate these findings into practical diagnostic and therapeutic approaches.