Scientific rationale
Why interpret and investigate.
Interpret · Model · Screen · Observe · Review
From genome to biological response.
Five stages, two kinds of evidence. Step through each stage — or play them all — to see what happens, what it needs and what it does not establish.
Stage 01 · OnKommon Interpreter
Genomic interpretation
The tumour genome is sequenced by whole-exome sequencing. Variants are catalogued, filtered and annotated, and each alteration is weighed against curated evidence.
- Inputs
- Solid-tumour whole-exome sequencing data and relevant clinical context.
- Intended output
- A structured molecular interpretation: drivers, response biomarkers, supporting evidence and the findings to watch.
- Why it matters
- It tells AVATAR which drivers to carry into the living model.
The question
Reading an alteration and testing a treatment are different tasks
Genomic analysis can show that a tumour carries an alteration associated with tumour growth, drug sensitivity or resistance. It cannot, by itself, show how candidate therapies affect a living biological system carrying that alteration. AVATAR is designed to explore that second question experimentally, while keeping clear that a model is not a patient.
Stream 1
The computational rationale
Interpretation needs cancer-specific context and a systematic review of the evidence. The OnKommon Interpreter catalogues, filters and annotates variants and weighs each against curated evidence — separating potential drivers from background variants, identifying response biomarkers, grading the strength of evidence and keeping unresolved findings visible.
Stream 2
The biological rationale
Drosophila melanogaster has a long history in genetics and cancer biology research. Many core growth-control and signalling pathways are conserved between flies and humans, and engineered flies can be produced and studied relatively quickly — which makes them a practical system for asking how selected alterations behave and how candidate compounds affect them.
In AVATAR, mutations found by the genomic analysis guide the design of the model: chosen mutations are introduced into the fly genome to study selected aspects of the tumour's biology. Candidate drugs and combinations are then tested for measurable outcomes.
Integration
Why combine the two
Experimental screening adds evidence beyond computational prediction. Bringing both into one integrated report allows a multidisciplinary review to consider where the two streams agree, where they differ, and what remains uncertain — always within clinical context.
Multidisciplinary review
KPCIRC Molecular Tumour Board; treating oncologist finalises.
Clinical context
The patient's diagnosis, history and treatment goals.
Biological screening observations
Experimental evidence from the engineered model.
Computational interpretation
Evidence-weighted reading of the alterations.
Genomic findings
Alterations identified by whole-exome sequencing.
Limits
Where translation stops
- A fruit-fly model represents selected aspects of tumour biology, not the complete human cancer.
- Drug exposure, metabolism, toxicity and the immune system in a fly differ from those in a person.
- A response in the model is a research observation — not evidence of efficacy or safety in a patient.
- Investigational findings do not independently establish clinical efficacy or predict an individual's treatment response.