MIF inhibition as a strategy for overcoming resistance to immune checkpoint blockade therapy in melanoma

ABSTRACT

Immune checkpoint blockade (ICB) has demonstrated an impressive outcome in patients with metastatic melanoma, yet, durable complete response; even with Ipilimumab/Nivolumab combo are under 30%. Primary and acquired resistance in response to ICB is commonly due to a tumor immune escape mechanism dictated by the tumor microenvironment (TME). Macrophage Migratory Inhibition Factor (MIF) has emerged as an immunosuppressive factor secreted in the TME. We have previously demonstrated that blockade of the MIF-CD74 signaling on macrophages and dendritic cells restored the anti-tumor immune response against melanoma. Here, we report that inhibition of the MIF-CD74 axis combined with ipilimumab could render resistant melanoma to better respond to anti-CTLA-4 treatment. We provide evidence that blocking the MIF-CD74 signaling potentiates CD8+ T-cells infiltration and drives pro-inflammatory M1 conversion of macrophages in the TME. Furthermore, MIF inhibition resulted in reprogramming the metabolic pathway by reducing lactate production, HIF-1α and PD-L1 expression in the resistant melanoma cells. Melanoma patient data extracted from the TCGA database supports the hypothesis that high MIF expression strongly correlates with poor response to ICB therapy. Our findings provide a rationale for combining anti-CTLA-4 with MIF inhibitors as a potential strategy to overcome resistance to ICB therapy in melanoma, turning a “cold” tumor into a “hot” one mediated by the activation of innate immunity and reprogramming of tumor metabolism and reduced PD-L1 expression in melanoma cells.

KEYWORDS:

• Melanoma
• Macrophage Migratory Inhibition Factor
• tumor microenvironment
• immune checkpoint therapy
• combined modality therapy

Acknowledgments

We thank the funding from the FAPESP (Grants numbers: 2017/09393-6 and 2018/18385-0).

Disclosure of potential conflicts of interest

The authors declare no potential conflicts of interest.

Authors’ contributions

Conception and design: RAA, ES, and MBE;

Analysis and interpretation of data: RAA, SW, MBE;

Microarray conception, design and analysis: ARJ, AL, MAC;

PD-1 TCGA analysis conception and design: GM.

Writing, review, and/or revision of manuscript: RAA, ES, SW, MAC, GM, LRT, MBE.

Study supervision: LRT and MBE

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Additional information

Funding

This study was supported by grants primarily from the São Paulo Research Fundation (FAPESP) [Grants numbers: 2017/09393-6 and 2018/18385-0].