Dissecting the tumor microenvironment in response to immune checkpoint inhibitors via single-cell and spatial transcriptomics

Liu, Wendi; Puri, Anusha; Fu, Doris; Chen, Lee; Wang, Cassia; Kellis, Manolis; Yang, Jiekun

doi:10.1007/s10585-023-10246-2

Cited by 5 publications

(2 citation statements)

References 78 publications

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“…The different role of tumor and immune cell populations can be revealed by performing a spatially informed analysis of biomarkers for ICI. 17 Here we performed a complete spatial transcriptomic study attempting to discover new RNA biomarkers for resistance to ICI therapy using a spatially informed high-plex discovery tool, the GeoMx Digital Spatial Profiling (DSP) System. This tool provides an unsupervised measurement of 18,000+protein-coding genes and enables their assessment in a spatially informed manner in single formalin-fixed paraffin embedded (FFPE) tissue sections by using next-generation sequencing (NGS).…”

Section: Introductionmentioning

confidence: 99%

High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)

Moutafi,

Bates,

Aung

et al. 2024

J Immunother Cancer

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BackgroundDespite the impressive outcomes with immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC), only a minority of the patients show long-term benefits from ICI. In this study, we used retrospective cohorts of ICI treated patients with NSCLC to discover and validate spatially resolved protein markers associated with resistance to programmed cell death protein-1 (PD-1) axis inhibition.MethodsPretreatment samples from 56 patients with NSCLC treated with ICI were collected and analyzed in a tissue microarray (TMA) format in including four different tumor regions per patient using the GeoMx platform for spatially informed transcriptomics. 34 patients had assessable tissue with tumor compartment in all 4 TMA spots, 22 with leukocyte compartment and 12 with CD68 compartment. The patients’ tissue that was not assessable in fourfold redundancy in each compartment was designated as the validation cohort; cytokeratin (CK) (N=22), leukocytes CD45 (N=31), macrophages, CD68 (N=43). The human whole transcriptome, represented by~18,000 individual genes assessed by oligonucleotide-tagged in situ hybridization, was sequenced on the NovaSeq platform to quantify the RNAs present in each region of interest.Results54,000 gene variables were generated per case, from them 25,740 were analyzed after removing targets with expression lower than a prespecified frequency. Cox proportional-hazards model analysis was performed for overall and progression-free survival (OS, PFS, respectively). After identifying genes significantly associated with limited survival benefit (HR>1)/progression per spot per patient, we used the intersection of them across the four TMA spots per patient. This resulted in a list of 12 genes in the tumor-cell compartment (RPL13A, GNL3, FAM83A, CYBA, ACSL4, SLC25A6, EPAS1, RPL5, APOL1, HSPD1, RPS4Y1, ADI1). RPL13A, GNL3in tumor-cell compartment were also significantly associated with OS and PFS, respectively, in the validation cohort (CK: HR, 2.48; p=0.02 and HR, 5.33; p=0.04). In CD45 compartment, secreted frizzled-related protein 2, was associated with OS in the discovery cohort but not in the validation cohort. Similarly, in the CD68 compartmentARHGAPand PNN interacting serine and arginine rich protein were significantly associated with PFS and OS, respectively, in the majority but not all four spots per patient.ConclusionThis work highlightsRPL13AandGNL3as potential indicative biomarkers of resistance to PD-1 axis blockade that might help to improve precision immunotherapy strategies for lung cancer.

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Section: Introductionmentioning

confidence: 99%

High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)

Moutafi,

Bates,

Aung

et al. 2024

J Immunother Cancer

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“…Combination therapies, whether administered simultaneously or sequentially, are frequently used for increased efficacy in advanced cancer stages. The emergence of immune checkpoint inhibitors (ICIs) approximately a decade ago and their use in advanced melanoma revolutionized cancer treatment 1 . Prior to ICIs, patients with stage IV melanoma typically had a median lifespan of 6-9 months.…”

Section: Introductionmentioning

confidence: 99%

Mature and migratory dendritic cells promote immune infiltration and response to anti-PD-1 checkpoint blockade in metastatic melanoma

Yang,

Wang,

et al. 2024

Preprint

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Immune checkpoint inhibitors (ICIs) have heralded a remarkable shift in cancer care, significantly extending survival for advanced cancer patients. However, despite their remarkable clinical successes, a substantial majority of patients fail to achieve a lasting response to ICIs. To address this challenge and gain insights into the complex landscape of the tumor microenvironment (TME), we conducted an extensive analysis using single-cell RNA sequencing (scRNA; ∼216K cells across 39 samples) and single-nucleus transposase-accessible chromatin sequencing (snATAC; ∼43K cells from 15 samples) in a metastatic melanoma cohort. This systematic approach delineates 14 distinct cell types and 55 cell subtypes, including the identification of 15 transcriptional hallmarks of malignant cells. Through correlation analysis of cell subtype proportions, we unveiled six distinct clusters associated with varying tumor responses. Particularly intriguing was the identification of the mature DC enriched in immunoregulatory molecules (mregDC) subtype exhibiting correlations with naive T and B cells, forming an anti-tumor program that underscores the importance of multiple immune cell types in mediating anti-tumor immunity. Notably, we found that mregDC abundance represents a good prognostic predictor of progression-free survival (PFS) in the context of ICI treatment, and when combined with the TCF7+/- CD8 T cell ratio, it reliably predicts patient PFS across treatments beyond ICI. We validated our findings using an independent cohort of 274 ICI-treated melanoma samples analyzed using tissue-level expression. We next compared mregDCs and conventional dendritic cell types 1 and 2 (cDC1 and cDC2) using transcriptome signature, differentiation trajectory, interactome, cytokine milieu, and epigenome landscape analyses. This comparative analysis shed light on the unique attributes of mregDCs within the TME. Finally, we investigated cell type/subtype-specific genes, pathways, immune response enrichment, and ligand-receptor interactions closely associated with the proportions of mregDCs within the TME. These molecular and cellular insights, with their critical roles in enhancing the immune response against cancer, offer valuable prospects for predicting the efficacy of ICI regimens, and potentially guiding the selection of rational combinatorial therapies.

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Antigen presenting cells in cancer immunity and mediation of immune checkpoint blockade

Wang,

Chen,

et al. 2024

Clin Exp Metastasis

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Antigen-presenting cells (APCs) are pivotal mediators of immune responses. Their role has increasingly been spotlighted in the realm of cancer immunology, particularly as our understanding of immunotherapy continues to evolve and improve. There is growing evidence that these cells play a non-trivial role in cancer immunity and have roles dependent on surface markers, growth factors, transcription factors, and their surrounding environment. The main dendritic cell (DC) subsets found in cancer are conventional DCs (cDC1 and cDC2), monocyte-derived DCs (moDC), plasmacytoid DCs (pDC), and mature and regulatory DCs (mregDC). The notable subsets of monocytes and macrophages include classical and non-classical monocytes, macrophages, which demonstrate a continuum from a pro-inflammatory (M1) phenotype to an anti-inflammatory (M2) phenotype, and tumor-associated macrophages (TAMs). Despite their classification in the same cell type, each subset may take on an immune-activating or immunosuppressive phenotype, shaped by factors in the tumor microenvironment (TME). In this review, we introduce the role of DCs, monocytes, and macrophages and recent studies investigating them in the cancer immunity context. Additionally, we review how certain characteristics such as abundance, surface markers, and indirect or direct signaling pathways of DCs and macrophages may influence tumor response to immune checkpoint blockade (ICB) therapy. We also highlight existing knowledge gaps regarding the precise contributions of different myeloid cell subsets in influencing the response to ICB therapy. These findings provide a summary of our current understanding of myeloid cells in mediating cancer immunity and ICB and offer insight into alternative or combination therapies that may enhance the success of ICB in cancers.

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Dissecting the tumor microenvironment in response to immune checkpoint inhibitors via single-cell and spatial transcriptomics

Cited by 5 publications

References 78 publications

High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)

High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)

Mature and migratory dendritic cells promote immune infiltration and response to anti-PD-1 checkpoint blockade in metastatic melanoma

Antigen presenting cells in cancer immunity and mediation of immune checkpoint blockade

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