Lectures and seminars What is life? Why is there cancer? And why cancer treatment often backfires..

11-05-2021 3:00 pm Add to iCal
Online Zoom meeting (see link below)

Speaker: Sui Huang, ISB, Seattle
Host: Ingemar Ernberg

Zoom meeting information

Meeting ID: 611 3454 1156
Passcode: 005138

Click here to access the meeting online


Sui Huang, MD, PhD, obtained his doctorates in medicine and molecular biology at the University of Zurich in 1995 working on interferons.  After postdoctoral training in cancer biology, he became faculty at Harvard Medical School in Boston, where he studied cell fate decisions. At the University of Calgary he worked alongside Stuart Kauffman on gene regulatory networks and cancer differentiation therapy (=exiting the cancer attractor), before joining the Institute for Systems Biology in Seattle in 2011. Sui Huang demonstrated that cell types are attractor states in high-dimensional gene expression space and uncovered that cell state instability precedes cell fate decisions. His current laboratory at ISB combines single-cell omics technologies and theory of non-linear dynamical systems to better the fundamental inevitability of tumor progression.

Cancer appears to be universal in complex living organisms.  Therefore, it may be a necessary manifestation of their robustness – which is epitomized by regenerative capacity. In this talk I will review the theory of gene regulayory networks, concepts of the cell attractor, multistability, and the “rugged epigenetic landscape”, as well as the evolution of regeneration -- leading to stress-indcued stemness. From this follows that cytotoxic stress imparted by treatment itself will either kill the cancer cell or induce stemness, thereby planting the seed for recurrence.  Thus, tumors exhibit Nietzsche’s principle of “What does not kill me makes me stronger” – perhaps a manifestation of instability and (non-genetic) bifurcation dynamics. I will demonstrate the practical consequences for treatment (which is poised to “backfire”) – supported by the latest single-cell transcriptomics data.