Context
Researchers from S.N. Bose National Centre for Basic Sciences and Ashoka University have developed ACSCeND, an AI framework to identify hidden cancer stem-like cells from tumour gene-expression data. It may help predict tumour recurrence, metastasis and treatment response, supporting precision medicine.
Explanation
- Cancer stem-like cells (CSCs) are rare tumour cells capable of self-renewal and differentiation, contributing to recurrence, metastasis and therapy resistance.
- ACSCeND stands for AI-based Cancer Stem-like Cell Profiler and Neoplasm Deconvoluter.
- It identifies three developmental states: pluripotent-like, multipotent-like and unipotent-like cancer stem cells.
- It integrates single-cell sequencing knowledge with deep learning to analyse conventional bulk tumour RNA sequencing (RNA-seq) data.
- Unlike a single “stemness” score, it helps reveal tumour heterogeneity and hidden cell populations.
- Analysis of over 25,000 tumour samples linked pluripotent-like CSC enrichment with poorer survival, recurrence and reduced immunotherapy response.
- Such AI-genomics approaches can identify biomarkers, potential drug targets and high-risk patients, advancing precision medicine.
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