ArticleTranslational cancer research2026
Ability of lactylation-related genes to stratify patients with ovarian cancer and predict immunotherapy response.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Lactate and lactylation-related genes (LRGs) have demonstrated promising effects in mitigating tumor growth and improving clinical outcomes, but their role in the ovarian cancer (OV) microenvironment and immunotherapy has not been extensively examined. This study aimed to characterize the relationship between LRGs and the outcomes of patients with OV. Methods: We collected bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) OV dataset via the University of California, Santa Cruz (UCSC) Xena and bulk RNA fragments per kilobase of transcript per million mapped reads (FPKM) sequences of normal ovarian tissues via the Genotype-Tissue Expression (GTEx) project. We then analyzed the relationship of 22 LRGs with programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) and compared the prognosis of patients with different expressions of LRGs in response to anti-PD-1/PD-L1 immunotherapy. We used the hierarchical clustering method to delineate subtypes of patients with OV according to LRG and PD-1 and PD-L1 expression and compared their tumor microenvironment (TME) compositions. A neural network was trained based on LRGs to predict the immunotherapy response in patients with OV, and single-cell RNA (scRNA) analysis was used to clarify the mechanisms underlying the LRGs' predictive capacity. Meanwhile, a tissue array was used to determine the LRG hub genes' influence on the prognosis of patients with OV. Results: Most of the LRGs examined were associated with the prognosis of patients with OV undergoing anti-PD-1/PD-L1 immunotherapy. According to the expression of the LRG panel, patients with OV could be clustered in subtypes, with each cluster exhibiting a distinct TME composition and immune-cell ratio. The neural network based on LRG expression could predict the immunotherapy response of patients with OV, with Conclusions: The expression of lactylation-related hub genes can be used to stratify patients with OV and predict their response to immunotherapy.
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