Fig. 2: Lactylation-associated molecular subtypes (a) t-SNE visualization showing distinct ovarian cancer subtype clustering (b) LDHA expression levels across the identified subtypes. | npj Precision Oncology

Fig. 2: Lactylation-associated molecular subtypes (a) t-SNE visualization showing distinct ovarian cancer subtype clustering (b) LDHA expression levels across the identified subtypes.

From: An AI-driven multi-omics framework identifies lactylation-mediated therapeutic targets to overcome drug resistance in ovarian cancer

Fig. 2: Lactylation-associated molecular subtypes (a) t-SNE visualization showing distinct ovarian cancer subtype clustering (b) LDHA expression levels across the identified subtypes.The alternative text for this image may have been generated using AI.

In Figure A, Subtype Clustering of Ovarian Cancer Samples Based on LDHA Expression. This t-distributed stochastic neighbor embedding (t-SNE) plot visualizes the clustering of ovarian cancer samples based on transcriptomic profiles of lactylation-associated genes. Samples are colored by LDHA expression subtype: LDHA-high (red) and LDHA-low (blue). The two-dimensional embedding (Dim1 and Dim2) highlights clear separation between the subtypes, indicating transcriptomic divergence associated with lactylation levels. B Differential LDHA Expression between Subtypes. This violin plot illustrates the distribution of LDHA expression across identified lactylation-based subtypes in ovarian cancer samples. The LDHA-high group (left, green) exhibits significantly elevated LDHA expression compared to the LDHA-low group (right, orange). The width of each violin represents the kernel density estimation of expression values, with embedded boxplots indicating median and interquartile range. These findings confirm LDHA as a distinguishing marker between lactylation-based subtypes.

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