What happened: ACSCeND identifies hidden cancer stem-like cell states using AI

S. N. Bose National Centre for Basic Sciences (SNBNCBS), an autonomous institute of the Department of Science and Technology (DST), Government of India, along with Ashoka University, developed the AI framework ACSCeND (AI-based Cancer Stem-like Cell Profiler and Neoplasm Deconvoluter). The framework is designed to reveal hidden cancer stem-like cell states from tumour gene-expression data, using deep learning with knowledge from single-cell biology.

ACSCeND addresses a key cancer research challenge: rare cancer stem-like cells can survive treatment, drive tumour recurrence and spread, and can change their identity over time. Traditional approaches often summarise tumour “stemness” as a single score; ACSCeND identifies three distinct developmental states of cancer stem-like cells: pluripotent-like, multipotent-like and unipotent-like.

ACSCeND combines knowledge learned from high-resolution single-cell sequencing with deep learning to analyse conventional bulk tumour RNA sequencing. The approach is meant to enable analysis of thousands of samples where single-cell experiments may not be available.

Background and earlier position: OncoMark and AI for hidden patterns in cancer data

The ACSCeND work builds on an earlier AI platform named OncoMark. OncoMark was reported to decode biological hallmarks that drive cancer progression across millions of cells with over 99% predictive accuracy.

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