📦 Pasta R package + tutorials → github.com/jsalignon/pasta • Preprint doi.org/pqhh • Feedback welcome!
🙏 Cooked with 💙 by @fedpie.bsky.social ChristianRiedel, PatriciaMarques, MariaTsiokou, at @ki.se @stockholm-uni.bsky.social #Bioinformatics #Longevity

🧬Integration with DepMap highlighted the pivotal role of epigenetic regulation and splicing pathways in shaping cellular responses to pro-rejuvenating signals, and of mitochondrial translation and type I interferon in responses to pro-aging signals. #RegenerativeMedicine

💊 FDA-approved anti-cancer drugs were highly enriched in Pasta’s pro-aging hits—strongly supporting the idea that chemotherapy works by aging cancer cells. This data-driven approach may help uncover safe, cancer-specific therapies. #Chemotherapy

💻 Screening 3 million CMAP profiles revealed pro-aging and pro-rejuvenation genetic and chemical perturbations. Importantly, these two sets were enriched in known pro-senescence and pro-stemness factors, respectively.

🩺In TCGA tumors, Pasta’s scores correlated better with tumor grade than chronological age, indicating its value as a biological age predictor. Pasta’s scores were also predictive of patient survival for certain cancers. #CancerResearch

🔍A novel age-shift modeling strategy yielded more accurate and biologically meaningful predictions, based on p53-related genes, than traditional regression models. Pasta also cleanly separated senescence, quiescence, stemness & differentiation in static and dynamic settings.

📊 Trained on 21 heterogeneous datasets to predict relative age, Pasta was designed to be broadly applicable to many kinds of transcriptomic data (i.e., microarrays, L1000…). It outperformed other RNA-Seq-specific tools without requiring reprocessing or batch correction.

Great work! Congrats!