Predictive immune checkpoint blockade classifiers identify tumors responding to inhibition of PD-1 and/or CTLA-4.

Abstract

RESULTS

We show that whereas the InTumor signature predicts response to anti-PD-1, the ExTumor predicts anti-CTLA-4 benefit. In PDX, InTumorLO, but not InTumorHI, tumors are effectively eliminated by cytotoxic T cells. When used in conjunction, the InTumor and ExTumor signatures identify not only patients who have a substantially higher chance of responding to combination treatment than to either monotherapy, but also those who are likely to benefit little from anti-CTLA-4 on top of anti-PD-1.

PURPOSE

Combining anti-PD-1 + anti-CTLA-4 immune checkpoint blockade (ICB) shows improved patient benefit, but it is associated with severe immune-related adverse events and exceedingly high cost. Therefore, there is a dire need to predict which patients respond to monotherapy, and which require combination ICB treatment.

CONCLUSION

These signatures may be exploited to distinguish melanoma patients who need combination ICB blockade from those who likely benefit from either monotherapy.

EXPERIMENTAL DESIGN

In patient-derived melanoma xenografts (PDX), human tumor microenvironment (TME) cells were swiftly replaced by murine cells upon transplantation. Using our XenofilteR deconvolution algorithm we curated human tumor cell RNA reads, which were subsequently subtracted in silico from bulk (tumor cell + TME) patients' melanoma RNA. This produced a purely tumor cell-intrinsic signature ("InTumor") and one comprising tumor cell-extrinsic RNA reads ("ExTumor").

More about this publication

Clinical cancer research : an official journal of the American Association for Cancer Research
  • Publication date 06-07-2021

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