Myeloid subsets impede the efficacy of anti-PD1 therapy in patients with advanced gastric cancer (WJOG10417GTR study).

Background: Gastric cancer (GC) is one of the most common and deadly malignant diseases worldwide. Despite revolutionary advances, the therapeutic efficacy of anti-PD1/PDL1 monoclonal antibodies in advanced GC is still low due to the emergence of innate and acquired resistance to treatment. Myeloid cells represent the majority of human immune cells. Therefore, their increase, decrease, and abnormality could have a significant impact on the patient's immune system and the progression of cancer, and reprogramming, inhibiting, and eliminating the tumor-supportive types may improve the immunological situation and efficacy of immunotherapy. However, the significance of myeloid cells in anti-PD1/PDL1 therapy remains unclear in GC. In the WJOG10417GTR study on GC, we sought to identify myeloid determinants that could predict anti-PD1 therapeutic efficacy and also serve as potential therapeutic targets.

Methods: We collected tumor tissues and peripheral blood from 96 patients with advanced GC before and 1 month after anti-PD1 nivolumab monotherapy, and the isolated whole leucocytes were analyzed by flow cytometry for various immune cell populations, including many myeloid subsets. Then, the relationship between the cellular levels and progression-free survival (PFS) or overall survival (OS) was statistically analyzed.

Results: We found that high levels of several myeloid subsets expressing molecules that have been targeted in drug discovery but not yet approved for clinical use were significantly associated with shorter PFS/OS as compared with low levels: PDL1⁺ and CTLA4⁺ myeloid subsets within tumors at baseline, PDL1⁺, B7H3⁺ and CD115⁺ myeloid subsets in peripheral blood at baseline, and LAG3⁺, CD155⁺ and CD115⁺ myeloid subsets in peripheral blood at post-treatment.

Conclusions: This study revealed that these myeloid subsets are significant risk factors in nivolumab therapy for advanced GC. Targeting them may be useful as diagnostic biomarkers to predict potential anti-PD1 therapeutic efficacy, and also as therapeutic targets for accelerating the development of new drugs to improve clinical outcomes in immunotherapy for GC.