M&M: an RNA-seq based pan-cancer classifier for paediatric tumours.

ABSTRACT:

Background

With many rare tumour types, acquiring the correct diagnosis is a challenging but crucial process in paediatric oncology. Historically, this is done based on histology and morphology of the disease. However, advances in genome wide profiling techniques such as RNA sequencing now allow the development of molecular classification tools.

Methods

Here, we present M&M, a pan-paediatric cancer ensemble-based machine learning algorithm tailored towards inclusion of rare tumour types.

Findings

The RNA-seq based algorithm can classify 52 different tumour types (precision ∼99%, recall ∼80%), plus the underlying 96 tumour subtypes (precision ∼96%, recall ∼70%). For low-confidence classifications, a comparable precision is achieved when including the three highest-scor

SUBMITTER: Wallis FSA 

PROVIDER: S-EPMC11784659 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature