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Melanoma, a skin cancer that develops from pigment cells, has been studied intensively, particularly in terms of the immune response to tumours, and has been used as a model for the development of immunotherapy. This is due, in part, to the high mutational burden observed in melanomas, which increases both their immunogenicity and the infiltration of immune cells into the tumours, compared with other types of cancers. The immune response to melanomas involves a complex set of components and interactions. As the tumour evolves, it accumulates an increasing number of genetic and epigenetic alterations, some of which contribute to the immunogenicity of the tumour cells and the infiltration of immune cells. However, tumour evolution also enables the development of resistance mechanisms, which, in turn, lead to tumour immune escape. Understanding the interactions between melanoma tumour cells and the immune system, and the evolving changes within the melanoma tumour cells, the immune system and the microenvironment, is essential for the development of new cancer therapies. However, current research suggests that other extrinsic factors, such as the microbiome, may play a role in the immune response to melanomas. Here, we review the mechanisms underlying the immune response in the tumour and discuss recent advances as well as strategies for treatment development.This Review discusses the mechanisms underlying the immune response to melanomas, as well as the mechanisms of response and resistance of these tumours to immunotherapies. The lessons learned in melanoma may apply to other tumour types.

Although novel therapies, including immunotherapy, have dramatically improved outcomes for many patients with cancer, overall outcomes are heterogeneous and existing biomarkers do not reliably predict response. To date, predictors of response to cancer therapy have largely focused on tumour-intrinsic features; however, there is growing evidence that other host factors (eg, host genomics and the microbiome) can substantially affect therapeutic response. The microbiome, which refers to microbiota within a host and their collective genomes, is becoming increasingly recognised for its influence on host immunity, as well as therapeutic responses to cancer treatment. Importantly, microbiota can be modified via several different strategies, affording new angles in cancer treatment to improve outcomes. In this Review, we examine the evidence on the role of the microbiome in cancer and therapeutic response, factors that influence and shape host microbiota, strategies to modulate the microbiome, and present key unanswered questions to be addressed in ongoing and future research.

Microorganisms within the gut and other niches may contribute to carcinogenesis, as well as shaping cancer immunosurveillance and response to immunotherapy. Our understanding of the complex relationship between different host-intrinsic microorganisms, as well as the multifaceted mechanisms by which they influence health and disease, has grown tremendously—hastening development of novel therapeutic strategies that target the microbiota to improve treatment outcomes in cancer. Accordingly, the evaluation of a patient’s microbial composition and function and its subsequent targeted modulation represent key elements of future multidisciplinary and precision-medicine approaches. In this Review, we outline the current state of research toward harnessing the microbiome to better prevent and treat cancer. There exists tremendous opportunity to target microorganisms in the gut and other niches to help treat or even prevent cancer. This Review outlines how microbial targeting could become a pillar of personalized cancer care over the next 5 to 10 years.

Discoveries made in the past 5 years indicate that the composition of the intestinal microbiota has a major influence on the effectiveness of anticancer immunosurveillance and thereby contributes to the therapeutic activity of immune-checkpoint inhibitors that target cytotoxic T lymphocyte protein 4 (CTLA-4) or the programmed cell death protein 1 (PD-1)–programmed cell death 1 ligand 1 (PD-L1) axis, as well as the activity of immunogenic chemotherapies. Herein, we highlight some of the bacteria, such as Akkermansia muciniphila, Bacteroides fragilis, Bifidobacterium spp. and Faecalibacterium spp., that have been associated with favourable anticancer immune responses in both preclinical tumour models and patients with cancer. Importantly, these bacteria also seem to have a positive influence on general health, thus reducing the incidence of metabolic disorders and a wide range of chronic inflammatory pathologies. We surmise that a diverse and propitious microbial ecosystem favours organismal homeostasis, particularly at the level of the cancer–immune dialogue.

Oncogenesis is associated with intestinal dysbiosis, and stool shotgun metagenomic sequencing in individuals with this condition might constitute a non-invasive approach for the early diagnosis of several cancer types. The prognostic relevance of antibiotic intake and gut microbiota composition urged investigators to develop tools for the detection of intestinal dysbiosis to enable patient stratification and microbiota-centred clinical interventions. Moreover, since the advent of immune-checkpoint inhibitors (ICIs) in oncology, the identification of biomarkers for predicting their efficacy before starting treatment has been an unmet medical need. Many previous studies addressing this question, including a meta-analysis described herein, have led to the description of Gut OncoMicrobiome Signatures (GOMS). In this Review, we discuss how patients with cancer across various subtypes share several GOMS with individuals with seemingly unrelated chronic inflammatory disorders who, in turn, tend to have GOMS different from those of healthy individuals. We discuss findings from the aforementioned meta-analysis of GOMS patterns associated with clinical benefit from or resistance to ICIs across different cancer types (in 808 patients), with a focus on metabolic and immunological surrogate markers of intestinal dysbiosis, and propose practical guidelines to incorporate GOMS in decision-making for prospective clinical trials in immuno-oncology.Many studies attempting to identify biomarkers for predicting of immune-checkpoint inhibitor (ICI) efficacy have led to the description of Gut OncoMicrobiome Signatures (GOMS). Several GOMS support an association between oncogenesis and intestinal dysbiosis, and other GOMS are shared between patients with several cancer subtypes and individuals with seemingly unrelated chronic inflammatory disorders. The authors of this Review discuss these patterns as well as the findings from a meta-analysis of GOMS associated with clinical benefit from ICIs, and propose practical guidelines to incorporate GOMS in decision-making in immuno-oncology.

Checkpoint blockade therapies that reactivate tumour-associated T cells can induce durable tumour control and result in the long-term survival of patients with advanced cancers 1 . Current predictive biomarkers for therapy response include high levels of intratumour immunological activity, a high tumour mutational burden and specific characteristics of the gut microbiota 2 , 3 . Although the role of T cells in antitumour responses has thoroughly been studied, other immune cells remain insufficiently explored. Here we use clinical samples of metastatic melanomas to investigate the role of B cells in antitumour responses, and find that the co-occurrence of tumour-associated CD8 + T cells and CD20 + B cells is associated with improved survival, independently of other clinical variables. Immunofluorescence staining of CXCR5 and CXCL13 in combination with CD20 reveals the formation of tertiary lymphoid structures in these CD8 + CD20 + tumours. We derived a gene signature associated with tertiary lymphoid structures, which predicted clinical outcomes in cohorts of patients treated with immune checkpoint blockade. Furthermore, B-cell-rich tumours were accompanied by increased levels of TCF7 + naive and/or memory T cells. This was corroborated by digital spatial-profiling data, in which T cells in tumours without tertiary lymphoid structures had a dysfunctional molecular phenotype. Our results indicate that tertiary lymphoid structures have a key role in the immune microenvironment in melanoma, by conferring distinct T cell phenotypes. Therapeutic strategies to induce the formation of tertiary lymphoid structures should be explored to improve responses to cancer immunotherapy. The co-occurrence of tumour-associated CD8 + T cells and CD20 + B cells, and the formation of tertiary lymphoid structures, are linked with improved survival in cohorts of patients with metastatic melanoma.

The gut microbiota is a crucial regulator of anti-tumour immunity during immune checkpoint inhibitor therapy. Several bacteria that promote an anti-tumour response to immune checkpoint inhibitors have been identified in mice 1 – 6 . Moreover, transplantation of faecal specimens from responders can improve the efficacy of anti-PD-1 therapy in patients with melanoma 7 , 8 . However, the increased efficacy from faecal transplants is variable and how gut bacteria promote anti-tumour immunity remains unclear. Here we show that the gut microbiome downregulates PD-L2 expression and its binding partner repulsive guidance molecule b (RGMb) to promote anti-tumour immunity and identify bacterial species that mediate this effect. PD-L1 and PD-L2 share PD-1 as a binding partner, but PD-L2 can also bind RGMb. We demonstrate that blockade of PD-L2–RGMb interactions can overcome microbiome-dependent resistance to PD-1 pathway inhibitors. Antibody-mediated blockade of the PD-L2–RGMb pathway or conditional deletion of RGMb in T cells combined with an anti-PD-1 or anti-PD-L1 antibody promotes anti-tumour responses in multiple mouse tumour models that do not respond to anti-PD-1 or anti-PD-L1 alone (germ-free mice, antibiotic-treated mice and even mice colonized with stool samples from a patient who did not respond to treatment). These studies identify downregulation of the PD-L2–RGMb pathway as a specific mechanism by which the gut microbiota can promote responses to PD-1 checkpoint blockade. The results also define a potentially effective immunological strategy for treating patients who do not respond to PD-1 cancer immunotherapy. Interactions between programmed death ligand 2 (PD-L2) and its binding partner RGMb are downregulated by the gut microbiota, a mechanism that may be exploited to enhance the efficacy of PD-1-based cancer immunotherapies.

Immune checkpoint blockade therapy targets T cell-negative costimulatory molecules such as cytotoxic T lymphocyte antigen-4 (CTLA-4) and programmed cell death-1 (PD-1). Combination anti–CTLA-4 and anti–PD-1 blockade therapy has enhanced efficacy, but it remains unclear through what mechanisms such effects are mediated. A critical question is whether combination therapy targets and modulates the same T cell populations as monotherapies. Using a mass cytometry-based systems approach, we comprehensively profiled the response of T cell populations to monotherapy and combination anti–CTLA-4 plus anti–PD-1 therapy in syngeneic murine tumors and clinical samples. Most effects of monotherapies were additive in the context of combination therapy; however, multiple combination therapy-specific effects were observed. Highly phenotypically exhausted cluster of differentiation 8 (CD8) T cells expand in frequency following anti–PD-1 monotherapy but not combination therapy, while activated terminally differentiated effector CD8 T cells expand only following combination therapy. Combination therapy also led to further increased frequency of T helper type 1 (Th1)-like CD4 effector T cells even though anti–PD-1 monotherapy is not sufficient to do so. Mass cytometry analyses of peripheral blood from melanoma patients treated with immune checkpoint blockade therapies similarly revealed mostly additive effects on the frequencies of T cell subsets along with unique modulation of terminally differentiated effector CD8 T cells by combination ipilimumab plus nivolumab therapy. Together, these findings indicate that dual blockade of CTLA-4 and PD-1 therapy is sufficient to induce unique cellular responses compared with either monotherapy.

Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells 1 – 7 . Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy 7 – 9 ; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues. Anti-cancer treatment often results in a subset of the clonal cell population developing resistance to therapy, with resistant cells displaying a diversity of fate types resulting from the intrinsic variability among the clonal population before treatment.

Cancer immunotherapy has flourished over the last 10–15 years, transforming the practice of oncology and providing long-term clinical benefit to some patients. During this time, three distinct classes of immune checkpoint inhibitors, chimeric antigen receptor-T cell therapies specific for two targets, and two distinct classes of bispecific T cell engagers, a vaccine, and an oncolytic virus have joined cytokines as a standard of cancer care. At the same time, scientific progress has delivered vast amounts of new knowledge. For example, advances in technologies such as single-cell sequencing and spatial transcriptomics have provided deep insights into the immunobiology of the tumor microenvironment. With this rapid clinical and scientific progress, the field of cancer immunotherapy is currently at a critical inflection point, with potential for exponential growth over the next decade. Recognizing this, the Society for Immunotherapy of Cancer convened a diverse group of experts in cancer immunotherapy representing academia, the pharmaceutical and biotechnology industries, patient advocacy, and the regulatory community to identify current opportunities and challenges with the goal of prioritizing areas with the highest potential for clinical impact. The consensus group identified seven high-priority areas of current opportunity for the field: mechanisms of antitumor activity and toxicity; mechanisms of drug resistance; biomarkers and biospecimens; unique aspects of novel therapeutics; host and environmental interactions; premalignant immunity, immune interception, and immunoprevention; and clinical trial design, endpoints, and conduct. Additionally, potential roadblocks to progress were discussed, and several topics were identified as cross-cutting tools for optimization, each with potential to impact multiple scientific priority areas. These cross-cutting tools include preclinical models, data curation and sharing, biopsies and biospecimens, diversification of funding sources, definitions and standards, and patient engagement. Finally, three key guiding principles were identified that will both optimize and maximize progress in the field. These include engaging the patient community; cultivating diversity, equity, inclusion, and accessibility; and leveraging the power of artificial intelligence to accelerate progress. Here, we present the outcomes of these discussions as a strategic vision to galvanize the field for the next decade of exponential progress in cancer immunotherapy.