AML Resistance Pathway Mapper
When PI3K is blocked in AML cells, the cancer compensates by upregulating EZH1 — an escape route that can be closed by combining PI3K inhibitors with EZH1/2 dual inhibitors. This research makes a compelling case for systematically mapping known resistance bypass routes and their combination therapy…
AML Resistance Pathway Mapper
When PI3K is blocked in AML cells, the cancer compensates by upregulating EZH1 — an escape route that can be closed by combining PI3K inhibitors with EZH1/2 dual inhibitors. This research makes a compelling case for systematically mapping known resistance bypass routes and their combination therapy solutions.
Build a curated, interactive database of drug resistance bypass mechanisms in acute myeloid leukemia, organized by the primary therapy being resisted and the molecular escape route activated. Each entry would link to supporting preclinical or clinical data, relevant inhibitor pairs that overcome the resistance, and any ongoing trials testing the combination. The tool would be aimed at researchers and translational oncologists designing next-generation AML trials.
The database could grow through community curation (similar to CIViC for variant interpretation) and would accept structured submissions from research labs documenting new resistance mechanisms. A query interface would let users input a therapy and receive a structured view of known resistance pathways, suggested combination partners, and mechanistic rationale.
Why now: AML has notoriously high relapse rates driven by non-genetic resistance mechanisms, and the field is increasingly focused on rational combination therapies. A structured knowledge base for these mechanisms would prevent duplicated work and accelerate the design of trials that pre-empt resistance rather than react to it.
Who Is This For?
Translational oncology researchers, AML drug development teams, and hematology clinical trial designers who need a fast way to survey known resistance mechanisms when planning combination studies.
Skills & Tools Needed
- Biocuration and structured data modeling for molecular biology
- Web application development (React or Vue + REST API)
- Database design (PostgreSQL or similar relational DB)
- Literature mining or NLP for semi-automated curation
- Basic knowledge of AML biology and resistance mechanisms
Feasibility
medium — The core database and query interface are buildable with moderate web development effort, but sustained curation requires either automation or a committed contributor community.
Inspired by: Exploiting an Epigenetic Resistance Mechanism to PI3 Kinase Inhibition in Leukemic Stem Cells
