Deciphering the Lactylation Landscape in Glioma: A Novel Gene Signature Predicts Patient Survival and Immunotherapy Sensitivity

Xiaolong Tang^1*Yi Liu²Congying Yang²Honglan Zhang²Gongming Zhang²Qiao Wang²Sujie Jiang²Xuzhu Gao³Yongshuo Liu^4*Yanbin Dong^2*

• ¹Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
• ²The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
• ³The Second People's Hospital of Lianyungang, Lianyungang, China
• ⁴Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China

Background: Glioma, the most prevalent primary brain tumor, takes advantage of lactylation, a metabolic modification linked to tumor behavior and clinical outcomes. Despite its significance, the role of lactylation in the pathogenesis and prognosis of glioma remains underexplored. This study established a lactylation-derived molecular signature to predict survival and response to immunotherapy in glioma. Methods: Leveraging the TCGA glioma cohort, we established a lactylation-related gene (LRG) signature via LASSO and Cox regression analyses, and its prognostic value was validated in independent cohorts. We comprehensively characterized the associations between the LRGs signature and clinicopathological features, tumor immunity (immune infiltration and response to immunotherapy), genomic instability (mutational burden and heterogeneity), tumor stemness, and therapeutic vulnerability. In vitro validation of the oncogenicity of HSPE1 was conducted using the CCK-8, colony formation, transwell, and apoptosis assays in U87 and U251 glioma cells. Results: A four-gene lactylation signature (KIF2C, CALD1, HSPE1, and IFI16) was identified. Elevated LRGs score were correlated with advanced tumor grade, poor prognosis, and reduced response to immunotherapy. Patients in the LRGs-high group exhibited adverse clinicopathological features, including advanced age, higher WHO grade, IDH wild-type status, and 1p/19q non-codeletion. The nomogram model based on the LRGs score exhibited robust prognostic accuracy (C-index = 0.860). LRGs-related genes were enriched in immune regulatory pathways, such as cytokine signaling and interferon-γ response pathways. The LRGs-high group displayed increased infiltration of immunosuppressive cells, such as M2 macrophages, MDSCs, and CAFs, and distinct genomic instability profiles. Crucially, HSPE1 knockdown significantly suppressed the proliferation and invasion of glioma cell lines. Conclusions: We defined a novel LRGs signature integrating metabolic and immune dysregulation in glioma. This signature served as an independent predictor of prognosis and immunotherapy. Furthermore, we identified HSPE1 as a critical driver of glioma progression.