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Purpose: This study characterizes intratumoral macrophage populations within baseline melanoma biopsies from patients with advanced melanoma who received either anti-PD-1 monotherapy or a combination with anti-CTLA-4. Particularly, FcγRIIIa (CD16)-expressing macrophage densities were investigated for associations with response and progression-free survival. Experimental Design: Patients with advanced melanoma who received either anti-PD-1 monotherapy or combination anti-PD-1 and anti-CTLA-4 were retrospectively identified. Macrophage populations were analyzed within baseline melanoma biopsies via multiplex IHC in relation to treatment outcomes. Results: Patients who responded to combination immune checkpoint inhibitor contained higher CD16+ macrophage densities than those who did not respond (196 vs. 7 cells/mm2; P = 0.0041). There was no diffidence in CD16+ macrophage densities in the PD-1 monotherapy-treated patients based on response (118 vs. 89 cells/mm2; P = 0.29). A significantly longer 3-year progression-free survival was observed in combination-treated patients with high intratumoral densities of CD16+ macrophages compared with those with low densities (87% vs. 42%, P = 0.0056, n = 40). No association was observed in anti-PD-1 monotherapy-treated patients (50% vs. 47%, P = 0.4636, n = 50). Melanoma biopsies with high densities of CD16+ macrophages contained upregulated gene expression of critical T-cell recruiting chemokines (CXCL9, CXCL10, and CXCL11). Conclusions: Our data demonstrate that tumor microenvironments enriched with CD16+ macrophages are favorable for response to combination anti-PD-1 and anti-CTLA-4 therapy but not anti-PD-1 monotherapy. These data provides a potential biomarker of response for combination immunotherapies in patients with metastatic melanoma.

C1Q and PD-1 expression on CD16+ macrophages in on treatment biopsies of melanoma patients treated with PD-1 or PD-1+CTLA-4 ICB. Dynamics between pretreatment and early-during treatment biopsies on (a) CD16+ macrophages as a proportion of all macrophages (b) CD16+ C1q+ macrophages as a proportion of all C1q+ macrophages (c) PD-1+ CD16+ macrophages as a proportion of PD-1+ macrophages (d) PD-1+ CD16+ C1q+ macrophages as a proportion of all macrophages (e) C1q+ CD16+ macrophages as a proportion of CD16+ macrophages (f) PD-1+ CD16+ macrophages as a proportion of CD16+ macrophages. (g) Log2 RNA expression of C1qa-c in pretreatment (PRE) and early during treatment (EDT) biopsies of responding and non-responding patients treated with PD-1 or PD-1+CTLA-4 ICB. (h) Flow cytometry analysis of ipilimumab (IgG1) and/or secondary anti-IgG1 binding to CD16+ and CD16- macrophages in a melanoma patient's tumor dissociate. FMO, a no-secondary control.

Differential expression analysis gene list of FACS sorted CD16+ compared to CD16- macrophages from human melanoma dissociates.

Supplementary Table 1: Baseline characteristics for patients included in the integrated gene set enrichment analysis (Figure 2-3) by cohort; Supplementary Table 6: The most frequent somatic alterations (alts) in patients with regionally metastatic melanoma by body mass index from The Cancer Genome Atlas cohort; Supplemental Table 7: Integrated gene set enrichment analysis for pathways associated with fatty acid metabolism by body mass index; Supplemental Table 8: Gene expression of selected genes of interest involved in fatty acid metabolism.

Integrated gene set enrichment analysis by body mass index (BMI) with correction for S phase. This figure presents a dotplot of genes differentially up- or downregulated in OW/OB patients versus NL BMI patients. Red indicates upregulation in OW/OB verse NL. The far left column is all patients, and then, an analysis controlling for sex, cohort, and tissue site is shown in the 3 columns to the right.

Differential gene expression analysis for each subgroup.

Purpose:Overweight/obese (OW/OB) patients with metastatic melanoma unexpectedly have improved outcomes with immune checkpoint inhibitors (ICI) and BRAF-targeted therapies. The mechanism(s) underlying this association remain unclear, thus we assessed the integrated molecular, metabolic, and immune profile of tumors, as well as gut microbiome features, for associations with patient body mass index (BMI).Experimental Design:Associations between BMI [normal (NL < 25) or OW/OB (BMI ≥ 25)] and tumor or microbiome characteristics were examined in specimens from 782 patients with metastatic melanoma across 7 cohorts. DNA associations were evaluated in The Cancer Genome Atlas cohort. RNA sequencing from 4 cohorts (n = 357) was batch corrected and gene set enrichment analysis (GSEA) by BMI category was performed. Metabolic profiling was conducted in a subset of patients (x = 36) by LC/MS, and in flow-sorted melanoma tumor cells (x = 37) and patient-derived melanoma cell lines (x = 17) using the Seahorse XF assay. Gut microbiome features were examined in an independent cohort (n = 371).Results:DNA mutations and copy number variations were not associated with BMI. GSEA demonstrated that tumors from OW/OB patients were metabolically quiescent, with downregulation of oxidative phosphorylation and multiple other metabolic pathways. Direct metabolite analysis and functional metabolic profiling confirmed decreased central carbon metabolism in OW/OB metastatic melanoma tumors and patient-derived cell lines. The overall structure, diversity, and taxonomy of the fecal microbiome did not differ by BMI.Conclusions:These findings suggest that the host metabolic phenotype influences melanoma metabolism and provide insight into the improved outcomes observed in OW/OB patients with metastatic melanoma treated with ICIs and targeted therapies.See related commentary by Smalley, p. 5

Purpose:This study characterizes intratumoral macrophage populations within baseline melanoma biopsies from patients with advanced melanoma who received either anti-PD-1 monotherapy or a combination with anti-CTLA-4. Particularly, FcγRIIIa (CD16)-expressing macrophage densities were investigated for associations with response and progression-free survival.Experimental Design:Patients with advanced melanoma who received either anti-PD-1 monotherapy or combination anti-PD-1 and anti-CTLA-4 were retrospectively identified. Macrophage populations were analyzed within baseline melanoma biopsies via multiplex IHC in relation to treatment outcomes.Results:Patients who responded to combination immune checkpoint inhibitor contained higher CD16+ macrophage densities than those who did not respond (196 vs. 7 cells/mm2; P = 0.0041). There was no diffidence in CD16+ macrophage densities in the PD-1 monotherapy-treated patients based on response (118 vs. 89 cells/mm2; P = 0.29). A significantly longer 3-year progression-free survival was observed in combination-treated patients with high intratumoral densities of CD16+ macrophages compared with those with low densities (87% vs. 42%, P = 0.0056, n = 40). No association was observed in anti-PD-1 monotherapy-treated patients (50% vs. 47%, P = 0.4636, n = 50). Melanoma biopsies with high densities of CD16+ macrophages contained upregulated gene expression of critical T-cell recruiting chemokines (CXCL9, CXCL10, and CXCL11).Conclusions:Our data demonstrate that tumor microenvironments enriched with CD16+ macrophages are favorable for response to combination anti-PD-1 and anti-CTLA-4 therapy but not anti-PD-1 monotherapy. These data provides a potential biomarker of response for combination immunotherapies in patients with metastatic melanoma.

Differential gene expression analysis for covariates controlled.

Body mass index values by patient ID for all RNASeq cohorts.

Purpose:Immunotherapies targeting costimulating and coinhibitory checkpoint receptors beyond PD-1 and CTLA-4 have entered clinical trials. Little is known about the relative abundance, coexpression, and immune cells enriched for each specific drug target, limiting understanding of the biological basis of potential treatment outcomes and development of predictive biomarkers for personalized immunotherapy. We sought to assess the abundance of checkpoint receptors during melanoma disease progression and identify immune cells enriched for them.Experimental Design: Multiplex immunofluorescence staining for immune checkpoint receptors (ICOS, GITR, OX40, PD-1, TIM-3, VISTA) was performed on 96 melanoma biopsies from 41 treatment-naïve patients, including patient-matched primary tumors, nodal metastases, and distant metastases. Mass cytometry was conducted on tumor dissociates from 18 treatment-naïve melanoma metastases to explore immune subsets enriched for checkpoint receptors.Results:A small subset of tumor-infiltrating leukocytes expressed checkpoint receptors at any stage of melanoma disease. GITR and OX40 were the least abundant checkpoint receptors, with +/CD103+/CD8+) were enriched for TIGIT (>70%) and other coinhibitory but not costimulatory receptors. The proportion of GITR+ T cells decreased from primary melanoma (>5%) to lymph node (P = 0.04) and distant metastases (P = 0.0005).Conclusions:This study provides the first comprehensive assessment of immune checkpoint receptor expression in any cancer and provides important data for rational selection of targets for trials and predictive biomarker development.

Antibodies used in CYTOF experiment

Figure S7 shows the gene expression profile of macrophages and other immune cell subsets in cancer patients

Supplementary Tables 1-2, and Figures 1-5.

Purpose:Response rates to immune checkpoint blockade (ICB; anti-PD-1/anti-CTLA-4) correlate with the extent of tumor immune infiltrate, but the mechanisms underlying the recruitment of T cells following therapy are poorly characterized. A greater understanding of these processes may see the development of therapeutic interventions that enhance T-cell recruitment and, consequently, improved patient outcomes. We therefore investigated the chemokines essential for immune cell recruitment and subsequent therapeutic efficacy of these immunotherapies.Experimental Design:The chemokines upregulated by dual PD-1/CTLA-4 blockade were assessed using NanoString-based analysis with results confirmed at the protein level by flow cytometry and cytometric bead array. Blocking/neutralizing antibodies confirmed the requirement for key chemokines/cytokines and immune effector cells. Results were confirmed in patients treated with immune checkpoint inhibitors using single-cell RNA-sequencing (RNA-seq) and paired survival analyses.Results:The CXCR3 ligands, CXCL9 and CXCL10, were significantly upregulated following dual PD-1/CTLA-4 blockade and both CD8+ T-cell infiltration and therapeutic efficacy were CXCR3 dependent. In both murine models and patients undergoing immunotherapy, macrophages were the predominant source of CXCL9 and their depletion abrogated CD8+ T-cell infiltration and the therapeutic efficacy of dual ICB. Single-cell RNA-seq analysis of patient tumor-infiltrating lymphocytes (TIL) revealed that CXCL9/10/11 was predominantly expressed by macrophages following ICB and we identified a distinct macrophage signature that was associated with positive responses to ICB.Conclusions:These data underline the fundamental importance of macrophage-derived CXCR3 ligands for the therapeutic efficacy of ICB and highlight the potential of manipulating this axis to enhance patient responses.

Purpose: Therapeutic blockade of immune checkpoints has revolutionized cancer treatment. Durable responses, however, occur in less than half of those treated, and efforts to improve treatment efficacy are confounded by a lack of understanding of the characteristics of the cells that initiate antitumor immune response.Patients and Methods: We performed multiparameter flow cytometry and quantitative multiplex immunofluorescence staining on tumor specimens from immunotherapy-naïve melanoma patients and longitudinal biopsy specimen obtained from patients undergoing anti–PD-1 therapy.Results: Increased numbers of CD69+CD103+ tumor-resident CD8+ T cells were associated with improved melanoma-specific survival in immunotherapy-naïve melanoma patients. Local IL15 expression levels strongly correlated with these tumor-resident T-cell numbers. The expression of several immune checkpoints including PD-1 and LAG3 was highly enriched in this subset, and these cells significantly expanded early during anti–PD-1 immunotherapy.Conclusions: Tumor-resident CD8+ T-cell numbers are more prognostic than total CD8+ T cells in metastatic melanoma. In addition, they are likely to initiate response to anti–PD-1 and anti–LAG-3 treatments. We propose that the immune profile of these cells prior to treatment could inform strategies for immune checkpoint blockade. Clin Cancer Res; 24(13); 3036–45. ©2018 AACR.

Supplementary Figure Legends

Checkpoint expression in PD-1 negative biopsies and VISTA expression in tumors

Supplementary data on flow cytometry analysis

These are the supplementary data figure legends (S1-S4)

Clinical characteristics of melanoma biopsies used in CYTOF

Supplementary table with clinical data

Purpose:BRAF V600E and V600K melanomas have distinct clinicopathologic features, and V600K appear to be less responsive to BRAFi±MEKi. We investigated mechanisms for this and explored whether genotype affects response to immunotherapy.Experimental Design:Pretreatment formalin-fixed paraffin-embedded tumors from patients treated with BRAFi±MEKi underwent gene expression profiling and DNA sequencing. Molecular results were validated using The Cancer Genome Atlas (TCGA) data. An independent cohort of V600E/K patients treated with anti–PD-1 immunotherapy was examined.Results:Baseline tissue and clinical outcome with BRAFi±MEKi were studied in 93 patients (78 V600E, 15 V600K). V600K patients had numerically less tumor regression (median, −31% vs. −52%, P = 0.154) and shorter progression-free survival (PFS; median, 5.7 vs. 7.1 months, P = 0.15) compared with V600E. V600K melanomas had lower expression of the ERK pathway feedback regulator dual-specificity phosphatase 6, confirmed with TCGA data (116 V600E, 17 V600K). Pathway analysis showed V600K had lower expression of ERK and higher expression of PI3K-AKT genes than V600E. Higher mutational load was observed in V600K, with a higher proportion of mutations in PIK3R1 and tumor-suppressor genes. In patients treated with anti–PD-1, V600K (n = 19) had superior outcomes than V600E (n = 84), including response rate (53% vs. 29%, P = 0.059), PFS (median, 19 vs. 2.7 months, P = 0.049), and overall survival (20.4 vs. 11.7 months, P = 0.081).Conclusions:BRAF V600K melanomas appear to benefit less from BRAFi±MEKi than V600E, potentially due to less reliance on ERK pathway activation and greater use of alternative pathways. In contrast, these melanomas have higher mutational load and respond better to immunotherapy.

Purpose: Overweight/obese (OW/OB) patients with metastatic melanoma unexpectedly have improved outcomes with immune checkpoint inhibitors (ICI) and BRAF-targeted therapies. The mechanism(s) underlying this association remain unclear, thus we assessed the integrated molecular, metabolic, and immune profile of tumors, as well as gut microbiome features, for associations with patient body mass index (BMI). Experimental Design: Associations between BMI [normal (NL < 25) or OW/OB (BMI ≥ 25)] and tumor or microbiome characteristics were examined in specimens from 782 patients with metastatic melanoma across 7 cohorts. DNA associations were evaluated in The Cancer Genome Atlas cohort. RNA sequencing from 4 cohorts (n = 357) was batch corrected and gene set enrichment analysis (GSEA) by BMI category was performed. Metabolic profiling was conducted in a subset of patients (x = 36) by LC/MS, and in flow-sorted melanoma tumor cells (x = 37) and patient-derived melanoma cell lines (x = 17) using the Seahorse XF assay. Gut microbiome features were examined in an independent cohort (n = 371). Results: DNA mutations and copy number variations were not associated with BMI. GSEA demonstrated that tumors from OW/OB patients were metabolically quiescent, with downregulation of oxidative phosphorylation and multiple other metabolic pathways. Direct metabolite analysis and functional metabolic profiling confirmed decreased central carbon metabolism in OW/OB metastatic melanoma tumors and patient-derived cell lines. The overall structure, diversity, and taxonomy of the fecal microbiome did not differ by BMI. Conclusions: These findings suggest that the host metabolic phenotype influences melanoma metabolism and provide insight into the improved outcomes observed in OW/OB patients with metastatic melanoma treated with ICIs and targeted therapies. See related commentary by Smalley, p. 5

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 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.

Background: While immune checkpoint inhibitors (ICI) have become the standard-of-care for advanced melanoma patients, only half of treated patients will survive beyond 5-years and many develop significant toxicity. The PIP study is combining pre-treatment clinical, molecular, and immunological profiles of melanoma patients to provide accurate prediction of response to ICI therapies. Methods: 504 patients with advanced melanoma who received anti-PD-1±CTLA-4 ICI were studied to develop predictive models of resistance to ICI. Resistance was defined as patients with progressive disease as best response, or partial response/stable disease with Results: Models were developed and validated using sequential addition of omics features to relevant clinical factors. Baseline clinical data alone achieved an AUC of 68%. Clinical plus three-tier TMB (20 mut/mb) achieved an AUC of 78%. Clinical data plus GEP achieved 79% AUC, inclusive of tumor inflammation, antigen presentation and T-cell related signatures. Clinical and MIF spatial pathology achieved an 82% AUC including the distances between T-cells, CD16+ cells and melanoma cells as features in the model. Finally, the combination of TMB and GEP achieved an 83% AUC. Prospective validation of the models is awaiting follow-up milestones. Conclusion: Multi-omic models using pre-treatment tissue and clinicopathology can significantly improve the accuracy of predicting patient outcomes to ICI treatments compared to baseline clinical data alone. Several models may be required based on different omic combinations to account for the reality of biopsy suitability and assay failures. These findings prove personalized precision treatment of patients with immunotherapies is possible in the clinical setting and such approaches should become routine care. Citation Format: Tuba N. Gide, Nurudeen A. Adegoke, Yizhe Mao, Monica Lennox, Saurab Raj, Camelia Quek, Ismael A. Vergara, Nigel Maher, Alison Potter, Robyn P. Saw, John F. Thompson, Andrew J. Spillane, Kerwin F. Shannon, Matteo S. Carlino, Maria Gonzalez, Serigne N. Lo, Alexander M. Menzies, Inês Pires da Silva, Richard A. Scolyer, Georgina V. Long, James S. Wilmott. Predictive biomarker models of immunotherapy response in patients with metastatic melanoma: genomic, transcriptomic, and immune profiles from the Personalised Immunotherapy Program (PIP). [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 5701.

Purpose: Response rates to immune checkpoint blockade (ICB; anti-PD-1/anti-CTLA-4) correlate with the extent of tumor immune infiltrate, but the mechanisms underlying the recruitment of T cells following therapy are poorly characterized. A greater understanding of these processes may see the development of therapeutic interventions that enhance T-cell recruitment and, consequently, improved patient outcomes. We therefore investigated the chemokines essential for immune cell recruitment and subsequent therapeutic efficacy of these immunotherapies. Experimental Design: The chemokines upregulated by dual PD-1/CTLA-4 blockade were assessed using NanoString-based analysis with results confirmed at the protein level by flow cytometry and cytometric bead array. Blocking/neutralizing antibodies confirmed the requirement for key chemokines/cytokines and immune effector cells. Results were confirmed in patients treated with immune checkpoint inhibitors using single-cell RNA-sequencing (RNA-seq) and paired survival analyses. Results: The CXCR3 ligands, CXCL9 and CXCL10, were significantly upregulated following dual PD-1/CTLA-4 blockade and both CD8+ T-cell infiltration and therapeutic efficacy were CXCR3 dependent. In both murine models and patients undergoing immunotherapy, macrophages were the predominant source of CXCL9 and their depletion abrogated CD8+ T-cell infiltration and the therapeutic efficacy of dual ICB. Single-cell RNA-seq analysis of patient tumor-infiltrating lymphocytes (TIL) revealed that CXCL9/10/11 was predominantly expressed by macrophages following ICB and we identified a distinct macrophage signature that was associated with positive responses to ICB. Conclusions: These data underline the fundamental importance of macrophage-derived CXCR3 ligands for the therapeutic efficacy of ICB and highlight the potential of manipulating this axis to enhance patient responses.

Small non-coding RNAs (ncRNA), including microRNAs (miRNA), enclosed in exosomes are being utilised for biomarker discovery in disease. Two common exosome isolation methods involve differential ultracentrifugation or differential ultracentrifugation coupled with Optiprep gradient fractionation. Generally, the incorporation of an Optiprep gradient provides better separation and increased purity of exosomes. The question of whether increased purity of exosomes is required for small ncRNA profiling, particularly in diagnostic and biomarker purposes, has not been addressed and highly debated. Utilizing an established neuronal cell system, we used next-generation sequencing to comprehensively profile ncRNA in cells and exosomes isolated by these 2 isolation methods. By comparing ncRNA content in exosomes from these two methods, we found that exosomes from both isolation methods were enriched with miRNAs and contained a diverse range of rRNA, small nuclear RNA, small nucleolar RNA and piwi-interacting RNA as compared with their cellular counterparts. Additionally, tRNA fragments (30–55 nucleotides in length) were identified in exosomes and may act as potential modulators for repressing protein translation. Overall, the outcome of this study confirms that ultracentrifugation-based method as a feasible approach to identify ncRNA biomarkers in exosomes.

Melanoma is a form of skin cancer that develops in the skin’s pigment cells, known as melanocytes, and can spread via blood and the lymphatic system to nearby tissues or distant organs in the body [...]

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene or protein expression by targeting mRNAs and triggering either translational repression or mRNA degradation. Distinct expression levels of miRNAs, including miR-29b, have been detected in various biological fluids and tissues from a large variety of disease models. However, how miRNAs “react” and function in different cellular environments is still largely unknown. In this study, the regulation patterns of miR-29b between human and mouse cell lines were compared for the first time. CRISPR/Cas9 gene editing was used to stably knockdown miR-29b in human cancer HeLa cells and mouse fibroblast NIH/3T3 cells with minimum off-targets. Genome editing revealed mir-29b-1, other than mir-29b-2, to be the main source of generating mature miR-29b. The editing of miR-29b decreased expression levels of its family members miR-29a/c via changing the tertiary structures of surrounding nucleotides. Comparing transcriptome profiles of human and mouse cell lines, miR-29b displayed common regulation pathways involving distinct downstream targets in macromolecular complex assembly, cell cycle regulation, and Wnt and PI3K-Akt signalling pathways; miR-29b also demonstrated specific functions reflecting cell characteristics, including fibrosis and neuronal regulations in NIH/3T3 cells and tumorigenesis and cellular senescence in HeLa cells.

Immune-related adverse events represent a major hurdle to the success of immunotherapy. The immunological mechanisms underlying their development and relation to antitumor responses are poorly understood. By examining both systemic and tissue-specific immune changes induced by combination anti-CTLA-4 and anti-PD-1 immunotherapy, we found distinct repertoire changes in patients who developed moderate-severe colitis, irrespective of their antitumor response to therapy. The proportion of circulating monocytes were significantly increased at baseline in patients who subsequently developed colitis compared with patients who did not develop colitis, and biopsies from patients with colitis showed monocytic infiltration of both endoscopically and histopathologically normal and inflamed regions of colon. The magnitude of systemic expansion of T cells following commencement of immunotherapy was also greater in patients who developed colitis. Importantly, we show expansion of specific T cell subsets within inflamed regions of the colon, including tissue-resident memory CD8+ T cells and Th1 CD4+ T cells in patients who developed colitis. Our data also suggest that CD8+ T cell expansion was locally induced, while Th1 cell expansion was systemic. Together, our data show that exaggerated innate and T cell responses to combination immunotherapy synergize to propel colitis in susceptible patients.

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.

Simple Summary Immune checkpoint therapies have significantly improved the survival of patients with metastatic melanoma, however approximately 50% of patients exhibit no response. Understanding the underlying clinical, pathologic and genetic factors associated with failed response to immunotherapies is key to identifying therapeutic strategies to overcome resistance. Here, we investigated the baseline tumour characteristics of patients with innate resistance to anti-PD-1-based immunotherapies. This study is the first on non-responders to integrate detailed clinical and molecular analyses and has identified two distinct clusters of patients with clinically relevant key targetable proteins. Abstract While immune checkpoint inhibitors targeting the CTLA-4 and PD-1 receptors have significantly improved outcomes of many patients with metastatic melanoma, there remains a group of patients who demonstrate no benefit. In this study, we sought to characterise patients who do not respond to anti-PD-1-based therapies based on their clinical, genetic and immune profiles. Forty patients with metastatic melanoma who did not respond to anti-PD-1 +/− anti-CTLA-4 treatment were identified. Targeted RNA sequencing (n = 37) was performed on pretreatment formalin-fixed paraffin-embedded (FFPE) melanoma specimens. Patients clustered into two groups based on the expression profiles of 26 differentially expressed genes: an immune gene rich group (n = 17) expressing genes associated with immune and T cell signalling, and a second group (n = 20) expressing genes associated with metabolism, signal transduction and neuronal signalling. Multiplex immunohistochemistry validated significantly higher densities of tumour-infiltrating lymphocytes (TILs) and macrophages in the immune gene-rich group. This TIL-high subset of patients also demonstrated higher expression of alternative immune-regulatory drug targets compared to the TIL-low group. Patients were also subdivided into rapid progressors and other progressors (cut-off 2 mo progression-free survival), with significantly lower TILs (p = 0.04) and CD68+ macrophages (p = 0.0091) in the rapid progressors. Furthermore, a trend towards a higher tumour burden was observed in rapid progressors (p = 0.06). These data highlight the need for a personalised and multilayer (clinical and molecular) approach for identifying the most appropriate treatments for anti-PD-1 resistant patients and provides insight into how individual treatment strategies can be achieved.