GEO series
Evolution of myeloid-mediated immunotherapy resistance in prostate cancer
GSE274229
Homo sapiens; Mus musculus
Expression profiling by high throughput sequencing
52 samples
2024/12/04
GPL24676GPL24247
Summary
Patients with advanced metastatic castration-resistant prostate cancer (mCRPC) are refractory to immune checkpoint inhibitors (ICIs), partly because there are immunosuppressive myeloid cells in tumours. However, the heterogeneity of myeloid cells has made them difficult to target, making blockade of the colony stimulating factor-1 receptor (CSF1R) clinically ineffective. Here we use single-cell profiling on patient biopsies across the disease continuum and find that a distinct population of tumour-associated macrophages with elevated levels of SPP1 transcripts (SPP1hi-TAMs) becomes enriched with the progression of prostate cancer to mCRPC. In syngeneic mouse modelling, an analogous macrophage population suppresses CD8+ T cell activity in vitro and promotes ICI resistance in vivo. Furthermore, Spp1hi-TAMs are not responsive to anti-CSF1R antibody treatment. Pathway analysis identifies adenosine signalling as a potential mechanism for SPP1hi-TAM-mediated immunotherapeutic resistance. Indeed, pharmacological inhibition of adenosine A2A receptors (A2ARs) significantly reverses Spp1hi-TAM-mediated immunosuppression in CD8+ T cells in vitro and enhances CRPC responsiveness to programmed cell death protein 1 (PD-1) blockade in vivo. Consistent with preclinical results, inhibition of A2ARs using ciforadenant in combination with programmed death 1 ligand 1 (PD-L1) blockade using atezolizumab induces clinical responses in patients with mCRPC. Moreover, inhibiting A2ARs results in a significant decrease in SPP1hi-TAM abundance in CRPC, indicating that this pathway is involved in both induction and downstream immunosuppression. Collectively, these findings establish SPP1hi-TAMs as key mediators of ICI resistance in mCRPC through adenosine signalling, emphasizing their importance as both a therapeutic target and a potential biomarker for predicting treatment efficacy.
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Paper (PMID 39436703) ↗
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