Multi-scale Modeling and Therapeutic Evaluation of Colorectal Tumorigenesis in Drosophila melanogaster Midgut

Multi-scale models integrating biomolecular data from genetic, transcriptional, and translational levels, coupled with extra-cellular microenvironments can assist in decoding mechanisms underlying complex organ-level diseases such as cancer. Cancer is the manifestation of multifactorial dere

Project Title

Multi-scale Modeling and Therapeutic Evaluation of Colorectal Tumorigenesis in Drosophila melanogaster Midgut

Project Area of Specialization

Biomedical Engineering

Project Summary

Multi-scale models integrating biomolecular data from genetic, transcriptional, and translational levels, coupled with extra-cellular microenvironments can assist in decoding mechanisms underlying complex organ-level diseases such as cancer.

Cancer is the manifestation of multifactorial deregulation in biomolecular pathways. These deregulations arise from a complex multi-scale interplay between cellular and extracellular factors. Such multifactorial aberrations at gene, protein and extracellular scales need to be investigated systematically towards decoding the underlying mechanisms and orchestrating therapeutic interventions for patient treatment. To this end, we have developed “TISON”, a next-generation web-based multiscale modeling platform for clinical systems oncology. In this project, we aim to construct a case study in TISON that involves an in silico model for colorectal cancer using Drosophila melanogaster as a model organism. This multi-scale model will then be validated using experimental techniques.

Anatomically, the Drosophila melanogaster gut tract is composed of epithelial cells surrounded by visceral muscles and nerves. Depending on the function, the gut has been classified into three major compartments i.e. the foregut, midgut (anterior, middle and posterior), and hindgut (Figure 1). The adult Drosophila midgut is similar in its cellular composition and organization to the human colon. More so, the biomolecular signaling pathways involved in maintaining homeostasis and differentiation are conserved in both. This gives credence to the utilization of Drosophila midgut models to investigate human colorectal cancer and consequently discover therapies for it to improve colon cancer prognosis and treatment. 

Project Objectives

The project has two main objectives,

1.0) To construct an in silico model 

1.1) We will first construct an in-silico Boolean network for colon cancer in Drosophila using exhaustive literature research and boolean logic rules.

1.2) Next, introduce therapy using the same model by targeting a set of nodes that are known as therapeutic targets for colon cancer using machine learning and data mining approaches.

1.3) Further to construct an in silico cell decision circuit (using finite state machines (FSM) in TISON) using TISONs three; circuit, environment and phenotypic editors which will allow us to visualize how a cell grows in a specific microenvironment and develops into a mesh of cells forming a tissue.

1.4) This will also allow us to mimic cell behavior in stressful and cancerous conditions.

(2.0) Experimental Validation of the Multi-scale System Model.

2.1) Simultaneously, to validate our in silico results we will use the same known target nodes/proteins and feed cancer containing flies drugs against specific proteins, expected to be upregulated in cancer, and perform Western Blotting to see protein expression with and without the drugs. The hypothesis is that the flies which have had the drug will have a lower protein expression as compared to flies that were not given the drug and still have cancer.

2.2) We will further expand the project using luciferase Assay technique for 96 well plates which can allow us to find more drugs for a more precise targetted therapy. 

Project Implementation Method

Up till now, numerous mathematical and computational models have been reported for investigating the emergent properties of biological systems (Anderson et al., 2009; Stolarska et al., 2009; Silva et al., 2011; Chaudhary et al., 2011; Barbarroux et al., 2016; Szabó and Merks, 2017; Kumar et al., 2018; Unni, 2019). These include models of morphological development of solid tumors in normoxia and hypoxia (Gerlee and Anderson, 2007), decoding the dynamics of homeostasis from cell-based multi-scale models of colon crypts (Fletcher et al., 2015), and model of glucose metabolism and its role in cancer growth and progression (Shamsi et al., 2018).

To develop a multi-scale system-level model of tumorigenesis in Drosophila melanogaster midgut, we are assembling the conserved regulatory cell signaling pathways involved in giving rise to Colorectal Cancer (CRC). These pathways will be translated into Boolean rules and analyzed using ATLANTIS, a MATLAB based tool, for analysis and abstracting dynamic biomolecular regulation in cells.

Further, we will use these networks to form Boolean logic rules for Deterministic Analysis in TISON (www.tison.lums.edu.pk), which is a web-based theater for in silico oncology. The emergent network properties i.e. cell fate and attractor landscape will exhibit different phenotypic expressions for different input stimuli. Using cell fate programming, to represent in silico CRC, we will also introduce driver mutations including APC and RAS, for adenoma and successive carcinoma formation in the midgut. These mutations are expected to pilot towards hallmarks of cancer such as hyperproliferation, loss of apoptosis and differentiation shown by cell fate landscape. 

We will also employ Finite State Machines (FSM) using TISON to construct cell decision circuits. The circuits will also import environmental conditions that will be orchestrated using a Partial Differential Equation (PDE) solver in TISON. 

Simultaneously, to substantiate in silico results from TISON, we will also perform in vivo validation, in collaboration with Dr. Muhammad Tariq‘s Epigenetics Lab and Dr. Amir Faisal‘s Cancer Therapeutic Lab. We have already imported two flies’ stocks having APC2APC and RasV12 mutations, from Dr. Casali’s lab in Spain, and the set up their crosses, the resulting progeny has a 25% chance of developing colon cancer.

For induction of therapeutic drug delivery in Drosophila, we will prepare low melt fly food and introduced these flies and then performed fly gut fine dissection on tumor and non-tumor flies and view results using confocal microscopy. The flies have a GFP tag, so we will receive a green signal where the gut was blocked due to hyperproliferation. The experiment will be further validated through Western Blotting on the lysed gut to analyze and confirm drug treatment on the fly colon.

Benefits of the Project

The project would enable us to construct a novel multi-scale system-level in silico model for Drosophila melanogaster. This multi-scale model will be able to help researchers to undertake biomolecular target identification towards novel target discovery. Since the Drosophila genome is 60% similar to humans this will also help us with new drug target discovery for human CRC as well. The validation with the model would further provide insights on how cancer progresses and metastasis. 

Technical Details of Final Deliverable

A preclinical multi-scale systems model of Colorectal Cancer tumorigenesis using Drosophila melanogaster for therapeutic evaluation in CRC. 

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Medical

Other Industries

Health

Core Technology

Big Data

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com