In addition, patients with a higher-risk score on the immune signature were also more likely to have mutations in PBRM1 and SETD2, which are predictors of outcome in clear-cell renal carcinoma.5 Loss-of-function mutations in PBRM1 have also recently been described as a predictor of response to immunotherapy in clear-cell renal carcinoma.6

“It was very interesting that they were able to identify this immune signature that seems to correlate with outcomes. We are starting to get some data about the use of immunotherapy in papillary cancer, so these immune signatures, if we can validate them, can give us better clues to who may or may not respond to immunotherapies,” said Dr Lee.

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Immunotherapy targeting the PD-1/PD-L1 pathway has shown early promise in small trials involving KIRP patients, with nearly 30% showing some response, albeit in a very small number of patients.7 Despite recent work on predictors of immunotherapy response in other major type of cancers, nothing significant has currently been done on this in KIRP.

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“To really prove this in a functional way, some of this needs supporting wet-lab experiments in which these genes are altered in some kind of way to see differences in pathways. We need mouse models for papillary kidney cancers where you can make these manipulations and see if it recapitulates what you see in patients,” said Dr Lee.

The immune signature involves genes which are already associated with kidney cancers and for which the protein function is well characterized, but the approach requires validation before it can be used as a prognostic tool.

“It is correlative right now, really just describing the phenotype. It would be premature to say that this is causative,” said Dr Lee.

References

  1. Wang Z, Song Q, Yang Z, et al. Construction of immune-related risk signature for renal papillary cell carcinoma. Cancer Med. 2018;8(1):289-304.
  2. The Cancer Genome Atlas. National Institutes of Health. https://cancergenome.nih.gov/.
  3. The Cancer Genome Atlas Research Network et al. Comprehensive molecular characterization of papillary renal-cell carcinoma. N Engl J Med. 2016;374(2):135-145.
  4. Lan H, Zeng J, Chen G, Huang H. Survival prediction of kidney renal papillary cell carcinoma by comprehensive LncRNA characterization. Oncotarget. 2017;8(67):110811–110829.
  5. Piva F, Giulietti M, Occhipinti G, et al. Computational analysis of the mutations in BAP1, PBRM1 and SETD2 genes reveals the impaired molecular processes in renal cell carcinoma. Oncotarget. 2015;6(31):32161-32168.
  6. Miao D, Margolis CA, Gao W, et al. Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science. 2018;359(6377):801-806.
  7. Mckay RR, Bossé D, Xie W, et al. . Cancer Immunol Res. 2018;6(7):758-765. doi:10.1158/2326-6066.CIR-17-0475

Topics:

Biomarkers Kidney Cancer Renal Cell Carcinoma