TISON: a next-generation multi-scale modeling theatre for in silico systems oncology

Author:

Gondal Mahnoor N,Sultan Muhammad U,Arif Ammar,Rehman Abdul,Awan Hira A,Arshad Zainab,Ahmed Waleed,Chaudhary Muhammad FA,Khan Salaar,Tanveer Zain B,Butt Rida Nasir,Hussain Risham,Khawar Huma,Amina Bibi,Akbar Rida,Abbas Fatima,Jami Misha N,Nasir Zainab,Shah Osama S,Hameed Hadia,Butt Muhammad FA,Mustafa Ghulam,Ahmad Muhammad M,Ahmed Sameer,Qazi Romena,Ahmed Fayyaz,Ishaq Omer,Nabi Syed W,Vanderbauwhede Wim,Wajid Bilal,Shehwana Huma,Uddin Emad,Safdar Muhammad,Javed Irfan,Tariq Muhammad,Faisal Amir,Chaudhary Safee U

Abstract

AbstractMulti-scale models integrating biomolecular data from genetic, transcriptional, and translational levels, coupled with extracellular microenvironments can assist in decoding the complex mechanisms underlying system-level diseases such as cancer. To investigate the emergent properties and clinical translation of such cancer models, we present Theatre for in silico Systems Oncology (TISON, https://tison.lums.edu.pk), a next-generation web-based multi-scale modeling and simulation platform for in silico systems oncology. TISON provides a “zero-code” environment for multi-scale model development by seamlessly coupling scale-specific information from biomolecular networks, microenvironments, cell decision circuits, in silico cell lines, and organoid geometries. To compute the temporal evolution of multi-scale models, a simulation engine and data analysis features are also provided. Furthermore, TISON integrates patient-specific gene expression data to evaluate patient-centric models towards personalized therapeutics. Several literature-based case studies have been developed to exemplify and validate TISON’s modeling and analysis capabilities. TISON provides a cutting-edge multi-scale modeling pipeline for scale-specific as well as integrative systems oncology that can assist in drug target discovery, repositioning, and development of personalized therapeutics.

Publisher

Cold Spring Harbor Laboratory

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