Single-cell based precision oncology: First steps in addressing and overcoming tumor heterogeneity

Share on facebook
Share on twitter
Share on linkedin
Share on email
Share on print

Tumor heterogeneity is a well-recognized hurdle to successful cancer therapy, often leading to resistance and treatment failure. 

To access this subscriber-only content please log in or subscribe.

If your institution has a site license, log in with IP-login or register for a sponsored account.*
*Not all site licenses are enrolled in sponsored accounts.

Login Subscribe
Sanju Sinha, PhD
Assistant professor, Cancer Molecular Therapeutics Program, NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute
Eytan Ruppin, MD, PhD
Chief, Data Science Laboratory, Head, Computational Precision Oncology Section, Senior investigator, Center for Cancer Research, National Cancer Institute
Table of Contents

YOU MAY BE INTERESTED IN

Artificial intelligence is rapidly transforming biomedical research and healthcare. Large language models, foundation models, and AI agents are increasingly being deployed to assist with data interpretation, literature review, clinical decision support, and translational research. 
How’s this for a paradox: The better cancer centers become at keeping patients alive, the more expensive cancer care becomes. This brutal tradeoff hits harder in rural areas, where the cancer burden is higher and the investigator and clinical trial representation is lower.
Sanju Sinha, PhD
Assistant professor, Cancer Molecular Therapeutics Program, NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute
Eytan Ruppin, MD, PhD
Chief, Data Science Laboratory, Head, Computational Precision Oncology Section, Senior investigator, Center for Cancer Research, National Cancer Institute

Never miss an issue!

Get alerts for our award-winning coverage in your inbox.

Login