Ewing Sarcoma – A Complex Disease That Requires Looking Beyond the Catalog of a Person’s Genetic Information

Ewing’s is sneaky in that kids feel healthy except for what they (and their parents) consider “normal growing pains”.  Little do they know that the “growing pains” are a symptom of an incredibly dangerous and aggressive disease that is attacking them.  Routine visits to the doctor will monitor biological data over months and years but will not disclose the presence of this horrific cancer.

Ewing’s illustrates the need to look beyond the genome, the complete catalog of an organism’s genetic information. In many ways, a genome is like a paper map of the world. That map shows where the cities are. But it doesn’t say anything about which nations trade with each other, which towns have fierce football rivalries or which states will swing for a particular political candidate.

To figure out what’s really happening within an organism — or within a particular organ or cell — researchers are linking the genome with data about the output of those genes at specific times, in specific places, in response to specific environmental pressures.

We have to look beyond simply focusing on individual molecules, Genomics (study of the genome) or Proteomics (large scale study of proteins) or Metabolomics (metabolic status and global biochemical events in a person) and look to build a Multi-omic representation of Ewing’s:

Ewing Sarcoma

For many complex human diseases, in particular for Sarcomas, Lymphomas; e.g. Ewing Sarcoma, non-Hodgkin’s lymphoma, finding new treatment strategies remains challenging due to the complexity of the molecular mechanisms that underlie the disease causality and progression. In addition, the lack of an overall systemic view of how these diseases affect all cellular functions is lacking.  The literature is full of reductionist studies on small portions of the affected cellular systems but an integrated, encompassing useable representation does not exist.  Our intent with this study is to move beyond the limited reductionist methodologies currently being used to understand cancer and develop an integrated, systemic representation of Ewing Sarcoma.

Connections between genes and their outputs or within omic layers can provide some clues to what’s happening inside an organism. But integrating omic datasets through Multi-omic analysis and modeling can reveal a human body systems view of biological activity as we can see here:

Ewing Sarcoma Connections

Source: K. Yugi et al. Trans-omics: How to reconstruct biochemical networks across multiple ‘omic’ layers. Trends in Biotechnology. Vol. 34, April 2016, p. 276. doi:10.1016/j.tibtech.2015.12.013.

Which is much more complete, and holistic than the microscopically focused investigations that are the dominant theme of cancer research today.

This need for a more Holistic, Human Body/ Systems Level approach to understanding and curing complex diseases like Ewing Sarcoma has motivated us to undertake this project, entitled:

Development Of Systematic Treatment Methods For Ewing Sarcoma Through The Revelation Of Its Molecular Mechanisms And Construction Of A Disease Progression Model

The Challenge:

System level treatments and cures for Cancer have been a dream of the medical community for many years, but they have proven elusive.  The Hallmarks of Cancer (HoC) provide an approach that could be utilized for systematic treatment, through functional decomposition of cancer into its various subsystems and their interrelationships.  While progress has been made in characterizing various hallmark cancer processes, a comprehensive, detailed and unified Systems Engineering description of cancer that can be used and applied for treatment has yet to be achieved.

The Innovations:

The first Innovation of the project will be to develop an integrated, detailed, systemic mechanistic computational representation of Ewing Sarcoma (ES), an aggressive malignant tumor of bone and soft tissue in children and adolescents, using the HoC as an overall guide to more fully understand the disease by including the spectrum of other –omics technologies.  No such representation of Ewing Sarcoma currently exists.

To understand the molecular mechanisms of tumorigenesis and metastatic processes in ES, this model will focus on development of a determination of the molecular mechanisms of ES progression through integration of the human ES biological networks (INs) including Genome-scale metabolic models (GEMs), Signaling Networks (SNs), Transcriptional Regulatory Networks (TRNs) and protein-protein interaction (PPINs) networks.

This Innovation will reveal, mathematize, parameterize, and validate a Disease Progression Model (DPM) of ES in order to use it in a Systems Engineering based systematic treatment biomarker, drug repurposing/ development strategy. We will use this model to identify biomarkers for the early detection of ES and tracking of disease progression. We will highlight important biological processes and underestimated contributors to tumorigenesis (such as metabolic pathways) and identify key isoforms and molecular players in ES tumor progression (enzymes, transcription factors, etc.).

The second Innovation of the project will be to use the DPM to identify targets against which existing drugs and/or novel treatments that can be repurposed or developed for effective treatment of ES.  ES presents in three phenotypes: solid, metastasized and recurrent (Ludwig, Current Opinion in Oncology 2008, 20:412–418) and others have observed that phenotypic heterogeneity contributes to tumor growth (Krook, Lawlor et al, Oncotarget, August 12, 2016) and phenotypic variability. Unfortunately, it is quite difficult the develop one or two drugs for the treatment of all ES patients since de novo drug discovery and development is a 10–17 year process from idea to marketed drug. Successfully repurposing existing drugs for ES and more focused targeting of interventions will deliver a needed productivity increase for pharma/biotech R&D.

The Impact:

The project is of strategic importance to:

Humanity:

  • The methods and techniques developed here will be extensible to other forms of Cancer as well as other disease types.

Health care sector: The proposed project will provide broad knowledge of ES in systems level and will help clinicians to improve the existing diagnosis and treatment strategies of ES in a very short time frame. Project results will:

  • Facilitate early diagnosis, allowing a shift from disease treatment to disease prevention.
  • Be a key enabling technology for individualized medicine, avoiding inappropriate prescription of drugs to non-responders or to patients likely to suffer from severe side effects.
  • Enable systematic treatment tracking, management and immediate response to resistance.
  • Allow the patient to be proactively and personally engaged by providing quantitative measures of progress to facilitate patient-physician conversations and treatment choices.

Pharmaceutical industry:  Research-based pharmaceutical programs are rapidly adopting systems biology approaches.  This project is expected to advance this progress through:

  • Identification of novel drug targets
  • Improving insights into the modes of action of existing drugs
  • Enabling early termination of provably unsuccessful drug development before excess investment is sunk,

Rationale

No system level, integrated representation of Ewing Sarcoma currently exists.  Current research is focused on individual details of how Ewing’s responds to a specific treatment or how specific entities are implicated in portions of the disease genotype, heterogeneity, phenotype or progression.  However, no systemic focus is provided nor are these individual details translated into the systemic representation which is required to systematically and comprehensively diagnose, monitor, and treat ES.

The determination of the molecular mechanisms of ES progression and a subsequent Disease Progression Model through integration of the human ES biological networks (INs) including Genome-scale metabolic models (GEMs), Signaling Networks (SNs), Transcriptional Regulatory Networks (TRNs) and protein-protein interaction (PPINs) networks is of critical importance if we are to truly come to grips with, and cure, this horrific and deadly pediatric disease.