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ORIGINAL RESEARCH ARTICLE

Lactylation-orchestrated Tprolif dynamics in skin cutaneous melanoma: Prognostic significance and therapeutic implications

Qianyu Shen1 ,  Sirui Qian1 ,  Yanan Yan1 ,  Xinhan Wu1 ,  Yingjia Ni1 ,  Maorong Suo1* ,  Yuan Wu1*
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1 Department of Biology and Environment, College of Jiyang, Zhejiang A&F University, Hangzhou, Zhejiang, China
IMO, 026200023 https://doi.org/10.36922/IMO026200023
Received: 11 May 2026 | Revised: 2 June 2026 | Accepted: 9 June 2026 | Published online: 7 July 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Skin cutaneous melanoma is a highly aggressive malignancy with poor prognosis, particularly in advanced stages. Lactylation, a post-translational modification, plays a crucial role in shaping the tumor microenvironment and contributing to immune suppression, making it a potential therapeutic target. In this study, single-cell RNA sequencing data from the Tumor Immune Single-cell Hub database and bulk RNA sequencing data from The Cancer Genome Atlas and Gene Expression Omnibus were analyzed. Lactylation-related genes were obtained from the Molecular Signatures Database, and lactylation scores for each cell type were computed using the AUCell R package. Cell–cell communication networks were constructed using CellChat, and a prognostic model was developed based on machine learning—including least absolute shrinkage and selection operator, random forest, and XGBoost. Drug candidates were identified via the L1000 Fireworks Display database and the Comparative Toxicogenomics Database, followed by molecular docking for drug–target interaction assessment. Results revealed that Tprolif cells exhibited the highest lactylation levels, indicating their immunosuppressive role in the tumor microenvironment, with the macrophage migration inhibitory factor receptor–ligand pathway identified as a key interaction hub. The eight lactylation-related genes–Tprolif prognostic model demonstrated moderate predictive ability for patient survival, and BG-FA-0953 emerged as a potential therapeutic candidate that may target lactylation-related pathways, warranting further investigation. This study provides novel insights into lactylation-driven immune modulation in skin cutaneous melanoma, with potential implications for risk stratification and therapeutic intervention in advanced-stage melanoma.

Graphical abstract
Keywords
Skin cutaneous melanoma
Lactylation
Tumor microenvironment
Machine learning
Prognosis
Therapeutic targets
Funding
This work was supported by the Research Development Fund for Talent Startup Project of Jiyang College, Zhejiang A&F University (grant number: RC2025F02), and the General Scientific Research Project of Zhejiang Provincial Department of Education in 2025 (Y202558493).
Conflict of interest
The authors declare that they have no conflict of interest related to this study.
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