All Diseases

Acute Myeloid Leukemia

AML is one of the most heterogeneous human cancers — characterized by complex clonal architectures, differentiation hierarchies, and diverse pathway dependency patterns that require multi-dimensional biological analysis.

Biological Heterogeneity in AML

Clonal Architecture

AML tumors harbor multiple co-existing clones with distinct mutation profiles, creating a complex evolutionary landscape that influences disease trajectory and relapse dynamics. Standard classification based on individual driver mutations provides a partial view of this complexity.

Differentiation Hierarchy

Leukemic cells span a spectrum of differentiation states — from stem-like progenitors to more mature myeloid forms — each with distinct preclinical response profiles and functional properties. Understanding where a patient sits in this landscape is essential for biological interpretation.

Microenvironment & Immune Context

The bone marrow microenvironment plays a critical role in AML biology, influencing compound resistance mechanisms, immune evasion, and disease progression. Integrated analysis of tumor and microenvironment is required for a complete biological picture.

Functional States

Through multi-omics integration, Helomnix identifies interpretable functional states in AML that reflect:

Transcriptional programs governing differentiation and stemness
Metabolic signatures linked to preclinical response profiles
Immune contexture and microenvironment composition
Regulatory network dependencies and therapeutic vulnerabilities

Questions the Digital Twin Supports

1
What functional disease states exist within an AML cohort?
2
Which molecular programs distinguish mechanistically distinct functional states?
3
How do clonal architectures relate to functional disease states?
4
What therapeutic vulnerabilities are associated with specific functional disease states?
5
How can multi-omics data be structured to support translational hypothesis generation?

Helomnix digital twins provide structured biological representations for research and translational support. They are not intended for clinical decision-making.