The Cancer Immunogram as a Framework for Personalized Immunotherapy in Urothelial Cancer.

Abstract

EVIDENCE SYNTHESIS

Here, we propose a UC immunogram, based on currently available clinical and translational data. The UC immunogram describes several tumor- and host-specific parameters that are required for successful immunotherapy treatment. These seven parameters are tumor foreignness, immune cell infiltration, absence of inhibitory checkpoints, general performance and immune status, absence of soluble inhibitors, absence of inhibitory tumor metabolism, and tumor sensitivity to immune effectors.

EVIDENCE ACQUISITION

A literature review was conducted on UC immunotherapy, clinical trial data, and biomarkers of response to checkpoint inhibition.

OBJECTIVE

To develop a comprehensive framework based on tumor- and host-specific parameters to understand immunotherapy response in UC. This framework can inform rational, biology-driven clinical trials and ultimately guide us toward individualized patient treatment.

CONTEXT

The abysmal outlook of urothelial cancer (UC) has changed with the introduction of immunotherapy. Still, many patients do not respond and distinctive biomarkers are currently lacking. The rise of this novel armamentarium of immunotherapy treatments, in combination with the complex biology of an immunological tumor response, warrants the development of a comprehensive framework that can provide an overview of important immunological processes at play in individual patients.

PATIENT SUMMARY

Here, we propose the urothelial cancer immunogram, a novel way of describing important immunological characteristics of urothelial cancer patients and their tumors. Seven characteristics determine the chance of having an immunological tumor response. Using this immunogram, we aim to better understand why some patients respond to immunotherapy and some do not, to ultimately improve anticancer therapy.

CONCLUSIONS

Longitudinal integration of individual patient parameters may ultimately lead to personalized and dynamic immunotherapy, to adjust to the Darwinian forces that drive tumor evolution. Incorporating multiparameter biomarkers into quantitative predictive models will be a key challenge to integrate the immunogram into daily clinical practice.