Recent advances in single-cell transcriptomics have greatly improved knowledge of complex transcriptional programs, rapidly expanding our knowledge of cellular phenotypes and functions within the tumour microenvironment and immune system. Several new single-cell technologies have been developed over recent years that have enabled expanded understanding of the mechanistic cells and biological pathways targeted by immunotherapies such as immune checkpoint inhibitors, which are now routinely used in patient management with high-risk early-stage or advanced melanoma. These technologies have method-specific strengths, weaknesses and capabilities which need to be considered when utilising them to answer translational research questions. Here, we provide guidance for the implementation of single-cell transcriptomic analysis platforms by reviewing the currently available experimental and analysis workflows. We then highlight the use of these technologies to dissect the tumour microenvironment in the context of cancer patients treated with immunotherapy. The strategic use of single-cell analytics in clinical settings are discussed and potential future opportunities are explored with a focus on their use to rationalise the design of novel immunotherapeutic drug therapies that will ultimately lead to improved cancer patient outcomes.
Melanoma is known as one of the most immunogenic tumours and is often characterised by high mutation burden, neoantigen load and immune infiltrate. The application of immunotherapies has led to impressive improvements in the clinical outcomes of advanced stage melanoma patients. The standard of care immunotherapies leverage the host immunological influence on tumour cells, which entail complex interactions among the tumour, stroma, and immune cells at the tumour microenvironmental level. However, not all cancer patients can achieve a long-term durable response to immunotherapy, and a significant proportion of patients develops resistance and still die from their disease. Owing to the multi-faceted problems of tumour and microenvironmental heterogeneity, identifying the key factors underlying tumour progression and immunotherapy resistance poses a great challenge. In this review, we outline the main challenges to current cancer immunotherapy research posed by tumour heterogeneity and microenvironment complexities including genomic and transcriptomic variability, selective outgrowth of tumour subpopulations, spatial and temporal tumour heterogeneity and the dynamic state of host immunity and microenvironment orchestration. We also highlight the opportunities to dissect tumour heterogeneity using single-cell sequencing and spatial platforms. Integrative analyses of large-scale datasets will enable in-depth exploration of biological questions, which facilitates the clinical application of translational research.
Introduction The complex spatial cellular interactions of immune cell populations within the melanoma TIME are associated with patient prognosis and immunotherapy response. Novel multiplex immunofluorescence (mIHC) and spatial analysis techniques enable comprehensive investigation of these interactions. This study aimed to develop an automated spatial analysis workflow for large patient cohorts and to determine immunospatial patterns associated with outcome in patients (pts) with primary melanoma as well as pts with stage III melanoma treated with adjuvant immunotherapy. Methods Two cohorts with available clinical & mIHC data were studied: one of primary melanoma pts (primary cohort, n=46), and another of baseline resected stage III melanoma pts who received adjuvant anti-PD-1 (stage III cohort, n=119). Melanoma tissue was stained for CD8+ T cells and the markers CD103, PD-1 and CD39 in both cohorts and the primary cohort was additionally stained for NK cells, B cells, and Langerhans cells (LCs). mIHC data was investigated using the SPIAT spatial analysis R package. Immune-melanoma and immune-immune spatial relationships were quantified throughout the entire tissue and analysed using neighborhood analysis and cell colocalization metrics including entropy and mixing interaction scores. Results In the primary melanoma cohort, 11 neighborhood metaclusters (NMCs) were identified from 1617 neighborhoods. NMCs with high B cells, CD39+CD103+ CD8+ T cells, or LCs were associated with improved outcomes in this cohort. Neighborhood composition varied significantly based on tissue localisation, with B cells, LCs and NK cells significantly increased in marginal and stromal neighborhoods (p<0.0001). Over 100 B cell aggregate (BCA) neighborhoods were identified predominantly at the tumor margins and adjacent stroma. These BCAs were likely early TLSs based on their localisation and immune composition. BCA composition was further compared based on patient outcomes, with those harboring increased CD103-PD-1+ CD8+ T cells associated with poor outcome. In-depth pairwise analysis of immune phenotypes with melanoma cells found that increased B cell-melanoma and CD103+PD-1- CD8+ T cell-melanoma interaction was associated with improved outcomes in the primary cohort. In the stage III cohort, increased intratumoral immune diversity was associated with reduced melanoma recurrence (p=0.0004). Conclusions In developing a cohort-wide TIME spatial analytic approach and workflow, we identified multiple immunospatial associations with patient outcome in primary and stage III metastatic melanoma. Intratumoral immune diversity and immune cell neighborhoods indicate beneficial anti-tumor immune functions contributing towards improved patient outcomes. Citation Format: Grace Heloise Attrill, Eva R. Shteinman, Xinyu Bai, Felix Marsh-Wakefield, Camelia Quek, Umaimainthan Palendira, Ismael A. Vergara, Georgina V. Long, Richard A. Scolyer, James S. Wilmott. Spatial organization of the tumour immune microenvironment (TIME) in primary and metastatic melanoma is associated with patient outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2369.
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