Molecular Subsets in Renal Cancer Determine Outcome to Checkpoint and Angiogenesis Blockade.

Journal:
Cancer Cell
Published:
DOI:
10.1016/j.ccell.2020.10.011
Affiliations:
11
Authors:
22

Research Highlight

A precision medicine boost for kidney cancer

© SEBASTIAN KAULITZKI/SCIENCE PHOTO LIBRARY/Getty

A new strategy for stratifying kidney cancers according to their genetic signatures could help clinicians personalize therapies for patients with this deadly cancer.

A team co-led by scientists at Genentech, a Roche subsidiary, characterized DNA alterations and gene-expression patterns found in 823 tumours from patients with advanced renal cell carcinoma. Their analysis revealed seven subtypes of the disease, each with its own molecular, immunological and metabolic profiles.

All the patients had been treated with drugs directed at angiogenesis — the process by which new blood vessels form to fuel cancer growth — either alone or in combination with a drug designed to boost anti-tumour immunity.

The seven cancer subtypes responded differently to the different drug regimens, highlighting the potential of using gene-expression profiles to guide treatment decisions.

The team also identified new molecular targets for future therapeutic development.

Supported content

References

  1. Cancer Cell 38, 803–817 (2020). doi: 10.1016/j.ccell.2020.10.011
Institutions Authors Share
Genentech, Inc., United States of America (USA)
13.000000
13.000000
0.59
Memorial Sloan Kettering Cancer Center (MSKCC), United States of America (USA)
1.000000
0.05
Beth Israel Deaconess Medical Center (BIDMC), United States of America (USA)
1.000000
0.05
Georgetown University Medical Center (GUMC), United States of America (USA)
1.000000
0.05
Institute Gustave-Roussy (IGR), France
1.000000
0.05
Calithera Biosciences, United States of America (USA)
1.000000
0.05
Crescendo Biologics Ltd., United Kingdom (UK)
1.000000
0.05
Foundation Medicine, Inc., United States of America (USA)
1.000000
0.05
Vanderbilt University Medical Center (VUMC), United States of America (USA)
1.000000
0.05
Queen Mary University of London (QMUL), United Kingdom (UK)
0.500000
0.02
Royal Free Hospital, United Kingdom (UK)
0.500000
0.02