Personalized Morphology, Replication Timing, and RNA based Gene Expression Networks for Basal-like and Classical subtyping genes in Pancreatic Adenocarcinoma.

Network biology traditionally identifies gene correlations that reflect biological pathways. While LIONESS enables individualized gene networks, the influence of replication timing on these correlations remains unexplored. Replication timing reflects the temporal order of DNA synthesis and is tightly linked to chromatin state, methylation, and transcriptional stability, all of which affect tumor behavior. Integrating replication-timing proxies derived from methylation data therefore offers a bridge between epigenetic state and functional gene coordination, while morphology provides an additional route for inferring gene expression. This is the first study to integrate replication-timing proxies and morphological embeddings into individualized LIONESS gene networks. The aim is to determine how replication timing and morphology derived from bulk methylation and image embeddings influence gene coexpression in pancreatic cancer. Patient-specific networks were generated for basal and classical pancreatic ductal adenocarcinoma subtypes using TCGA data. Results show an 80% AUC for RNA-replication-timing-based subtype prediction modules and a 75% AUC for morphology-based networks. Incorporating replication timing and morphology increased network robustness while maintaining classification performance. Notably, the 80% AUC was achieved using only 17 of the 50 Moffitt genes, with 16 overlapping the PURIST gene set, indicating that replication timing captures clinically relevant regulatory structure. These findings suggest that replication-timing proxies can act as epigenetic indicators of mechanistic gene coordination and may help identify patients with distinct replication stress or chromatin accessibility profiles relevant to therapeutic response.