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Figure: Top left & right: Depiction of an epigenetic Waddington landscape with various cell types illustrating the hierarchical process of differentiation (left) and how this process is altered in cancer (right). Top middle: diagram to illustrate how the normal multipotent cell suppresses tissue-specific transcription factors via an easily reversible epigenetic modification called H3K27me3. These H3K27me3 marks are removed once a cell differentiates into one that carries out a specific function in the tissue/organ (‘differentiated cells’). In cancer, the suppression by H3K27me3 is replaced by promoter DNA methylation, which is stable and leads to irreversible and increased suppression of tissue-specific transcription factors. CancerStemID can estimate the transcription factor inactivation load (TFIL) for any given cell. Bottom left: Illustration of how TFIL could identify the cells that are more stem-like and which drive cancer progression. Bottom middle: Heatmap of inactivation events of esophageal specific transcription factors in single cells from a precursor cancer lesion (low and high-grade intraepithelial neoplasia-LGIN/HGIN) in the human esophagus, with cells sorted by the TFIL. Bottom right: Violin plots displaying the significant association between TFIL and dedifferentiation, and between TFIL and a cancer risk score computed as relative similarity between a precancerous cell and those found in invasive cancer.

Predicting cancer risk with computational biology

Andrew Teschendorff, Professor at the Chinese Academy of Sciences, is developing computational systems-biological tools to identify cells at risk of turning cancerous.

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