Most adult kidney cancers come in the form of clear
cell renal cell carcinoma (ccRCC). This latter is considered immunogenic, that
is, the immune system can recognize the tumor and launch a response against it.
Because of that property, the medical community is
working particularly on therapies targeting "immune checkpoints",
which are ligand-receptor interactions that normally serve to keep the immune
system from attacking its host. When the ligand is on a ccRCC cell however, it
stops the immune cell from launching an attack on the tumor. Thus, a number of
checkpoint inhibitors (e.g., anti-checkpoint antibodies) have been developed
and shown effective against ccRCC. Nonetheless, they do not work in numerous
patients, suggesting the existence of currently unknown immunosuppressive
mechanisms within the tumor or in its microenvironment. It is in this setting
that researchers from the Immuno-Hematology Research Department (SRHI), in
partnership with the Mathematics and Computer Science Laboratory for Complexity
and Systems (MICS; CentraleSupélec, Paris-Saclay University) decided to
identify novel checkpoints expressed specifically in ccRCC that may serve as
new therapeutic targets.
To achieve their objectives, the team paired, on one
hand, advanced statistical methods to analyze the transcriptomics data
collected by the Cancer Genome Atlas Program¹, and on the other,
immunohistochemical and flow cytometry biological validation protocols. That
approach enabled the identification and classification of 44 checkpoints, many
of which were previously unknown, expressed in ccRCC samples. The team
furthermore used recursive feature elimination to identify HLA-G and PD-L1 as
the most pertinent checkpoint proteins. Thus, targeting HLA-G either
concurrently with or in case of non-response to anti-PD1/PD-L1 treatments may
have potential as a therapeutic strategy.
The results of the SRHI-MICS study underline the
importance of expanding the search for treatment targets in ccRCC to guide the development
of personalized and more efficacious immunotherapies.
1 : The Cancer Genome Atlas was launched in 2005 to
catalog genetic mutations associated with cancer using genome sequencing and
bioinformatics. It is a joint project of the American National Cancer Institute
(NIH/NCI) and the National Human Genome Research Institute (NIH/NHGRI) and
financed by the American government.