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AI Framework OncoMark Decodes Cancer Molecular Secrets for Better Treatment

AI Framework OncoMark Decodes Cancer’s Molecular Secrets

Indian scientists have developed an artificial intelligence framework called OncoMark that could fundamentally change cancer understanding and treatment by analyzing the disease’s molecular personality rather than just tumor size.

Key Takeaways

  • OncoMark analyzes 10 cancer hallmarks with over 96% accuracy
  • Framework tested on 3.1 million single cells across 14 cancer types
  • Validated on 20,000 real-world patient samples
  • Helps identify aggressive cancers missed by standard staging

Beyond Traditional Cancer Staging

For decades, doctors have relied on TNM (tumor, nodes, metastasis) staging to assess cancer progression. However, this approach often misses why patients with identical stages experience dramatically different outcomes.

Cancer is powered by biological programs called ‘hallmarks of cancer’ – hidden processes that explain how healthy cells turn malignant, spread, evade immunity, and resist treatment.

How OncoMark Works

Scientists from SN Bose National Centre for Basic Sciences and Ashoka University created OncoMark to read cancer’s ‘molecular mind.’ The AI analyzed 3.1 million single cells across 941 tumors spanning 14 cancer types, creating synthetic pseudo-biopsies that represent hallmark-driven tumor states.

“Quantifying the biological processes that drive cancer progression remains a key challenge in oncology. Although the hallmarks of cancer provide a foundational framework for understanding tumour behaviour, existing diagnostic tools rarely measure these hallmarks directly. Here we present a neural multi-task learning-based framework that estimates hallmark activity using gene expression data from tumour biopsies,” the researchers said in their study published recently in Communications Biology.

Proven Accuracy and Applications

OncoMark achieved over 99% accuracy in internal testing and maintained above 96% accuracy across five independent validation cohorts. The framework was tested on 20,000 real-world patient samples from eight major datasets.

For the first time, scientists can visualize how hallmark activity increases with advancing cancer stage, according to the Ministry of Science and Technology.

Personalized Treatment Potential

The framework identifies which of the 10 cancer hallmarks are active in individual patients’ tumors, guiding doctors toward drugs that directly target those specific processes. It can also detect aggressive cancers that appear less dangerous under standard staging, enabling earlier intervention.

The technology represents a significant step toward truly personalized cancer treatment by understanding each tumor’s unique biological drivers.

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