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Whatever doesn’t kill cancer makes it stronger, says Sui Huang. This finding informs his cutting-edge, transdisciplinary approach to cancer and genetics. Challenging more traditional oncology in therapeutics, he helps listeners understand why conceiving of cancer differently may lead to better treatment.

Listen and learn

  • How he and colleagues work to bridge genomic and DNA-sequencing disciplines with holistic approaches,
  • What this means for biopsy in cancer cell research and the chemotherapy process,
  • How he describes cancer as a disease of the tissue caught in a detrimental feedback loop, and
  • What are exciting and hopeful therapeutic possibilities based on this work.

Sui Huang is a professor with the Institute for Systems Biology, a group founded in 2000 as a collaborative and cross-disciplinary nonprofit dedicated to taking on the biggest challenges of modern medicine with a systems biology approach. Dr. Huang gets specific about what that means for cancer prevention and early detection programs.

He adds that only studying, for example, tumor cells versus normal cells in terms of genes and gene sequencing misses the forest for the trees. Rather, he keeps in view the complex systems of the human organism to get the true picture of how cancer functions.

He elucidates what that means for how he and colleagues research genealogies of tumor cells and cancer as an evolutionary mal adaptation machine. Professor Huang notes that cancer is less common in more primitive organisms and most common in mammals, signifying its ability to take advantage of complex systems for its growth.

In addition, he summarizes some of the recent surprising findings such as how heterogeneity affects efforts to kill cancer cells, what the genealogy of a tumor shows regarding cell relatedness, and how cancer cells communicate.

Listen in for more on how a nontraditional systems approach to cancer may lead to discoveries that have major impacts on clinical treatments.

Episode also available on Apple Podcasts: apple.co/30PvU9C

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