Biology subjects

Prahallad, A.

Publications and source records attributed to Prahallad, A..

3 recordsLinked to original sources

bioRxiv2018

Modelling Signalling Networks from Perturbation Data

MotivationIntracellular signalling is realized by complex signalling networks which are almost impossible to understand without network models, especially if feedbacks are involved. Modular Response Analysis (MRA) is a convenient modelling method to study signalling networks in various contexts.\n\nResultsWe developed a derivative of MRA that is suited to model signalling networks from incomplete perturbation schemes and multi-perturbation data. We applied the method to study the effect of SHP2, a protein that has been implicated in resistance to targeted therapy in colon cancer, using data from a knock out and parental colon cancer cell line. We find that SHP2 is required for MAPK signalling, whereas AKT signalling only partially depends on SHP2.\n\nAvailabilityAn R-package is available at https://github.com/MathurinD/STASNet\n\nContactnils.bluethgen@charite.de

bioinformatics↗

bioRxiv2018

Comparative Network Reconstruction using Mixed Integer Programming

New anti-cancer drugs that specifically target oncogenes involved in signalling show great clinical promise. However, the effectiveness of such targeted treatments is often hampered by innate or acquired resistance due to feedbacks, crosstalks or network adaptations in response to drug treatment. Addressing this problem requires an understanding of these networks and how they differ between cells with different oncogenic mutations or between sensitive and resistant cells. Here, we present Comparative Network Reconstruction (CNR), a computational method to reconstruct signaling networks based on incomplete perturbation data, and to identify which edges differ quantitatively between two or more signalling networks. Prior knowledge about network topology is not required but can straightforwardly be incorporated. We extensively tested our approach using simulated data and applied it to perturbation data from a BRAF mutant cell line that developed resistance to BRAF inhibition. Comparing the reconstructed networks of sensitive and resistant cells suggests that the resistance mechanism involves re-establishing wildtype MAPK signaling, possibly through an alternative RAF-isoform.

systems biology↗

bioRxiv2017

A system-wide approach to monitor responses to synergistic BRAF and EGFR inhibition in colorectal cancer cells

Intrinsic and/or acquired resistance represents one of the great challenges in targeted cancer therapy. A deeper understanding of the molecular biology of cancer has resulted in more efficient strategies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has also been observed in colorectal cancer patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block intrinsic resistance to BRAF inhibitors. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant colorectal cancer cells as a model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both known and novel responses. We primarily observe widespread upregulation of receptors tyrosine kinases and metabolic pathways upon BRAF inhibition. These findings point to mechanisms by which the drug-treated cells switch energy sources and enter a quiescent-like state as a defensive response, while additionally reactivating the MAPK pathway.

cancer biology↗