PRISM: Recovering cell type specific expression profiles from individual composite RNA-seq samples
Zhang Kaiyang; Carpén Olli; Hietanen Sakari; Lehtonen Rainer; Andersson Noora; Hynninen Johanna; Mansuri Naziha; Häkkinen Antti; Kaipio Katja; Dai Jun; Lamminen Tarja; Huhtinen Kaisa; Alkodsi Amjad; Vähärautio Anna; Hautaniemi Sampsa; Pekcan Erkan Erdogan
https://urn.fi/URN:NBN:fi-fe2022012711026
Tiivistelmä
Motivation: A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample composition changes systematically due to chemotherapy and between the anatomical sites, preventing direct comparison of treatment-naive and treated samples.
Results: To overcome this, we developed PRISM, a latent statistical framework to simultaneously extract the sample composition and cell type specific whole-transcriptome profiles adapted to each individual sample. Our results indicate that the PRISM-derived composition-free transcriptomic profiles and signatures derived from them predict the patient response better than the composite raw bulk data. We validated our findings in independent ovarian cancer and melanoma cohorts, and verified that PRISM accurately estimates the composition and cell type specific expression through whole-genome sequencing and RNA in situ hybridization experiments.
Kokoelmat
- Rinnakkaistallenteet [19207]