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Interferon-stimulated neutrophils identified in preclinical models may serve as a potential biomarker for immunotherapy response in human

ABSTRACT: Despite the remarkable success of immunotherapy, only ~20-30% of cancer patients display an extended durable response. Pre-existing biomarkers for immunotherapy outcome are significantly limited in their predictive power. While mice are the most widely used and cost-effective model to study human disease, translating preclinical biomarkers into clinical practice faces significant obstacles – in part due to the lack of diverse or appropriate models. Here, to improve translatability and identify novel biomarkers, we showcase an approach encompassing several pre-clinical models - each capturing one possible mechanistic aspect of immunotherapy response, such as tumor- and host-dependency, in order to reflect the variability seen in human cancers. Using this approach, we identify interferon-stimulated, Ly6Ehi neutrophils as a pre-treatment, blood-borne biomarker for anti-PD1 response in mice. We subsequently validate this result in cohorts of immunotherapy-treated non-small cell lung cancer (NSCLC) and melanoma patients, where the abundance of Ly6Ehi neutrophils predicts anti-PD1 response and further validated these results using available datasets for other cancers. Moreover, we demonstrate that these cells sensitize otherwise resistant tumors to anti-PD1 therapy, in part by directly activating cytotoxic T cells and contributing to tumor cell killing, while operate upstream of T cells in the immunotherapy response. Collectively, our study identifies a new and functionally active biomarker to predict immunotherapy outcome with potential clinical relevance.

ORGANISM(S): Mus musculus

PROVIDER: GSE226962 | GEO | 2024/01/05

REPOSITORIES: GEO

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Project description:Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

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Interferon-stimulated neutrophils identified in preclinical models may serve as a potential biomarker for immunotherapy response in human

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