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Melanoma pp 651-665 | Cite as

Melanoma Immunology and Immunotherapy

  • Ryan J. SullivanEmail author
  • F. Stephen Hodi
Reference work entry

Abstract

Immunotherapy has been a mainstay for decades, however in recent years a number of new approaches to harness the immune system have been developed and revolutionized the treatment of this disease. This chapter serves as an introduction to immunotherapy efforts in melanoma that includes a description of the immune system elements and tumor immune microenvironment and the justification for their targeting, presentation of proof of concept examples of effective immunotherapy, and a discussion of some of the present dilemmas in the field that need to be sorted out over the coming decade.

Keywords

PD-1 inhibitor Interleukin 2 CTLA4 Immune related adverse events Biomarkers 

Introduction

In the modern history of cancer therapy, distinct eras can be defined going back to the nineteenth century. With the rise of antiseptic technique, “heroic” and radical surgeries were made possible that focused on removing solid tumors and often the draining basin lymph nodes. In this era of surgery, the morbidity of surgery was significant, and it was not until nearly a full century had passed before modified surgeries, often followed by adjuvant radiation therapy to optimize local control, became the new standard of care (Fisher et al. 1989). While surgery and radiation therapy were well-established methods of controlling locoregional disease and, if performed “early,” or perhaps more accurately in patients with favorable biology, could be associated with improved survival, systemic therapy was always designed to treat disseminated disease. The early days of cytotoxic therapy led to the development of regimens that were designed to target different points in the cell division machinery and combined agents with non-overlapping, dose-limiting toxicities (Frei et al. 1958). During the era of chemotherapy, the care of hematologic malignancies and many solid tumors (e.g., testicular cancer, ovarian cancer, breast cancer) was revolutionized; however these efforts only minimally impacted the care of patients with certain tumor types, such as melanoma, and further discoveries were required to definitively impact the survival of these patients (Korn et al. 2008).

Over the past 20 years, so-called targeted therapies have been developed to treat a number of diseases, including melanoma. These include monoclonal antibodies that inhibit cell surface markers (CD-20; rituximab), cell surface receptors (erb-B2 receptor kinase (ERBB2/HER2); trastuzumab), and growth factors associated with angiogenesis (vascular endothelial growth factor (VEGF); bevacizumab), as well as small molecule inhibitors of a number of cellular targets (Imai and Takaoka 2006). This latter category includes inhibitors of driving oncoproteins including BRAF in melanoma and lung cancer, epidermal growth factor receptor (EGFR) in lung cancer, KIT in gastrointestinal stromal tumor (GIST), and many others. However, and with few exceptions, developing therapeutic regimens that include multiple targeted agents, whether monoclonal antibodies or small molecules, has been challenging due to overlapping toxicity, and these approaches tend to be associated with transient control of disease but rarely, if ever, cure.

The search for truly curative therapy has been the goal of cancer treatment efforts since the days of the morbid, radical surgeries defined above. Curiously, the origin of revolutionary therapies aimed at inspiring the patient’s immune system to kill the cancer rather than deliver agents designed to kill cancer cells directly has their roots in the era of surgery. Indeed, a surgeon named Thomas Coley observed near the turn of the twentieth century a curious, albeit rare, phenomenon of complete and durable tumor response during the recovery of a patient with a head and neck tumor and a life-threatening bacterial infection (Coley 1910). Subsequently, Coley attempted to harness the mediators of this type of response by designing and delivering a “toxin” derived from Streptococcus. While this ultimately was not proven effective for the treatment of cancer generally, it offered a proof of concept that the immune system could indeed be weaponized against an active and life-threatening malignancy. In the subsequent century, a fuller understanding of the immune system has been gained and more recently translated into the treatment of therapies that have efficacy in a number of indications.

A disease at the center of nearly all immunotherapy development is melanoma, a malignancy notoriously resistant to chemotherapy. In fact, nearly every type of immune therapy developed to date – cytokines, adoptive cell therapy (ACT), vaccines, checkpoint inhibitors, bi-specific antibodies – has been tested with some effectiveness in patients with melanoma. The initial efforts with the cytokines, interferon alpha 2b, and interleukin 2 (IL-2) were effective in a small percentage of patients and led to FDA approval of each agent in the adjuvant and metastatic setting, respectively (Kirkwood et al. 1996, 2004; Atkins et al. 1999). More importantly, the results with these agents set the stage for melanoma to be the training ground for new immunotherapy strategies. Building on the results of IL-2, ACT was developed by investigators at the National Cancer Institute and, initially, involved isolating tumor-infiltrating T cells (TIL), growing and activating these ex vivo, and then giving these back to the patient in the context of IL-2 following lymphodepleting chemotherapy (Rosenberg et al. 2011). Building upon this approach, cellular engineering to both TIL and peripherally isolated lymphocytes has led to new products called chimeric antigen receptor (CAR)-modified T cells and T-cell receptor (TCR)-engineered cells that provide more specific T-cell activation and perhaps more robust responses than generic TIL (Maus and June 2016; Robbins et al. 2011). And yet, perhaps the most important translatable discovery was the identification of the regulatory elements around T-cell activation and effector function that, when inhibited, led to dramatic responses in a significant percentage of patients (Hodi et al. 2010; Topalian et al. 2012). These so-called immune checkpoint inhibitors do not require any ex vivo work or cell engineering but rather are given by infusion every 2–3 weeks. More importantly, these agents have activity in a broad range of malignancies and have changed the field of oncology more than any class of agents to date.

What follows is an introduction to immunotherapy efforts in melanoma that includes a description of the immune system elements and tumor immune microenvironment and the justification for their targeting, presentation of proof-of-concept examples of effective immunotherapy, and discussion of some of the present dilemmas in the field that need to be sorted out over the coming decade.

Requirements for Anti-melanoma Immunity

Cancer in its development in a host has developed the ability to progress despite doing so within the context of an active immune system. Schreiber and colleagues described the three “Es” of the interaction between malignant cells and immune cells that either lead to the elimination of the tumor, a state of equilibrium between tumor and host immune system, or escape from immune regulation leading to the propagation of the malignant phenotype (Dunn et al. 2002). This process is, of course, hopelessly more complex that this simple model suggests, and an iterative process of malignant alterations, immune system adaptation to these alterations, leading to more malignant cell alterations and on and on. In melanoma, there are two unique aspects to the natural history of the disease that highlight this concept. First, it is a well-known phenomenon that long latencies may occur from the diagnosis of primary disease to widespread metastases. While the majority of patients with melanoma who relapse do so in the first 3 years from diagnosis, a small minority recur more than a decade afterward (Ossowski and Aguirre-Ghiso 2010). While this may be related to a number of factors, tumor-immune equilibrium remains a likely contributor to these types of cases. A second important aspect to melanoma natural history is that in a small percentage of cases, spontaneous tumor regression has been noted (summarized nicely by William Coley himself) and more commonly histologic regression in the primary tumor site (Coley and Hoguet 1916). This latter finding is also the theoretical reason behind the thinking that melanoma of unknown primary is typically considered to be from a cutaneous primary that has undergone complete regression. Further support for this theory is that genetic analyses of these unknown primary melanomas more closely match the pattern of driving mutations seen in cutaneous melanoma than in acral, mucosal, or uveal melanoma (Siroy et al. 2015). Interestingly, in the cases of melanoma of unknown primary, by definition, the elimination of the primary tumor is not associated with the prevention of metastatic disease, as some tumor cells were able to escape immune destruction in order to develop into a clinically identifiable tumor.

In essence, the mechanism of action of immunotherapy is to tip the balance of this interaction and lead to the elimination of escaped tumors or at least trigger a period of sustained equilibrium. However, the bulk of immunotherapy development has aimed to improve the activity of effector T lymphocytes that leads to more effective cell-mediated immunity. Chen and Mellman famously have described this process in a figure that has been utilized in seemingly every immunotherapy lecture since its publication in 2013 (Chen and Mellman 2013). The concept is that tumor immunity, and in particular T-cell immunity generated against tumor cells, involves a cyclical process that involves a number of critical steps that are all potentially druggable. The first steps involve the release of cancer antigens and their processing and presentation by antigen-presenting cells (APCs) in the context of major histocompatibility (MHC) molecules. T cells, via interaction of their T-cell receptor (TCR) with antigen, then undergo priming and activation. This process is highly regulated by a number of molecules, known as immune checkpoints, that either positively or negatively affect the activation status of the T cell. Once activated, T cells migrate to and infiltrate into tumors where they recognize tumor cells in an antigen-dependent manner, again through TCR interaction with antigen in the context of MGH, and then kill tumor cells.

At every step, this process can be altered or evaded (Chen and Mellman 2013, 2017). Negative regulators of T-cell priming and activation, such as the cytotoxic T-lymphocyte-associated antigen 4 (CTLA4), can reduce populations of antigen-specific T cells that are capable of leading to tumor elimination. Certain tumors, including some with genetic aberrations in beta-catenin signaling, exclude either T-cell trafficking or infiltration, leading to a tumor microenvironment state known as an immune desert devoid of immune elements (Spranger et al. 2015). Once present, activated T cells may be thwarted by tumors that have either downregulated antigen expression or have been enriched by regulatory elements such as T-regulatory cells (Tregs) and/or myeloid-derived suppressor cells (MDSCs) that impair effector T-cell function. However, it seems that the lowest common denominator required to protect the tumor from immune-mediated destruction is the expression (either on the tumor cells or in the immune microenvironment) of proteins that are capable of suppressing the activity of activated effector T cells. The most common of these are the programmed death 1 receptor ligands 1 and 2 (PD-L1, PD-L2) which interact with the programmed death 1 receptor (PD-1) that is expressed on activated T cells. When this interaction occurs, effector T cells are rendered ineffective. However, when this interaction is disrupted pharmacologically, for example, with monoclonal antibodies that inhibit PD-1 or PD-L1, tumors utilizing this mechanism to prevent immunologic destruction become vulnerable to antigen-specific T-cell-mediated immunity. It is this last concept that has led to revolutionary advances in immunotherapy, as anti-PD-1/PD-L1 agents have become the most effective immune oncology agents developed to date (Chen and Mellman 2017).

Immunotherapy Proof-of-Concept Examples in Melanoma

High-Dose Interleukin 2

The first “modern” immunotherapy developed and subsequently approved to treat metastatic melanoma was high-dose interleukin 2 (HD IL-2). Originally discovered as (and named) T-cell growth factor, IL-2 quickly was moved into the clinic (Mier and Gallo 1980). In patients with melanoma and renal cell carcinoma, complete and durable remissions were seen in a small minority of patients (Atkins et al. 1999; Fyfe et al. 1995). In a collection of 270 patients with metastatic melanoma treated at a number of specialized centers, the response rate was 16% with durable and complete responses seen in approximately 6% of patients. Additionally, the median overall survival was 11.4 months, longer than other contemporary studies, although patients enrolled tended to have better prognosis features due to the potential for life-threatening toxicity (Atkins et al. 1999). In fact, due to its limited efficacy and high toxicity, namely, a capillary leak syndrome that is associated with hypotension, renal insufficiency, edema, and neurologic toxicity, HD IL-2 was not widely adopted. Still, specialized centers continued to treat patients, typically younger and with lower tumor volume, excellent performance status, and excellent cardiac and pulmonary function. More contemporary datasets have corroborated response rates in the 16–20% range with durable benefit (progression-free at 18 months or greater) seen in 5–10% of patients, although in this era of more effective alternative systemic therapies, as expected, the overall survival of patients is improved to the historical dataset (Alva et al. 2016; Curti et al. 2017; Joseph et al. 2012). While this data is not nearly as strong as that seen with anti-PD-1 therapy in patients with metastatic melanoma, HD IL-2 is the original therapy that led to a discussion about considering where the “tail” on the survival curve is when determining the value of immunotherapy.

Interestingly, the major limitation to efficacy appears to be the fact that IL-2 receptors are found on both effector and regulatory T cells (Fontenot et al. 2005). This fact may be exploitable with certain modifications to IL-2, such as pegylation (PEG), and a number of modified IL-2s are in clinical trials as single agents and in combination with immune checkpoint inhibitors (NCT02350673, NCT02869295, NCT02983045, NCT03138889, NCT02799095) (Charych et al. 2017). Still, HD IL-2 is the original therapy that led to a discussion about considering where the “tail” on the survival curve is when determining the value of immunotherapy. The earliest data to emerge from these new takes on an old agent has been with NKTR-214, a 6-PEG IL-2 that preferentially binds to the beta-gamma subunits of the IL-2 receptor and not the alpha, which results in biased signaling of effector and natural killer T cells as opposed to regulatory T cells (Alva et al. 2016). In the Phase I single-agent study, NKTR-214 was considered to be safe and without the dose-limiting toxicities of high-dose IL-2 which allows for outpatient dosing (Bernatchez et al. 2017). Unfortunately, in this population of typically heavily pretreated patients, a clinical efficacy signal of single-agent therapy did not emerge. However, the initial data with NKTR-214 in combination with nivolumab was more encouraging. Specifically, in the first 41 patients treated at the recommended Phase II dose, responses were seen in 20 of the 38 evaluable patients, with 9 (24%) experiencing a complete response (Diab et al. 2018a). In the larger group of treated patients with a spectrum of solid tumor malignancies, it is important to note that the grade 3 or higher rate of immune-related adverse events is at least no different and numerically lower than predicted from single-agent nivolumab (Diab et al. 2018a, b). Based on the early results of this study, a randomized Phase III trial was launched (NCT03635983) .

Anti-CTLA4 Inhibition

The first immune checkpoint molecule identified was CTLA4, and its inhibition was associated with significant preclinical activity in immunocompetent mouse models (Leach et al. 1996). Specifically, the activity of CTLA4 blockade became evident when combined with a GM-CSF secreting B16 murine tumor vaccine (Soiffer et al. 2003). The potential for inflammatory events was noted as approximately half the mice lost pigment in their fur from this combination treatment. As a single agent in early clinical trials, ipilimumab demonstrated a single-digit response rate in previously treated patients with melanoma (Weber et al. 2008). As CTLA4 is a major regulator of T-cell activation, it was felt that the use of anti-CTLA therapy might be most useful in conjunction with a vaccination strategy (Quezada et al. 2006). Treatment with ipilimumab importantly demonstrated an influx of a variety of immune effector cells into the tumor microenvironment as a function of treatment (Hodi et al. 2003). Many of the first clinical efforts with ipilimumab included combination with or subsequent to a vaccination strategy (Hodi et al. 2008, 2010). Interestingly, it became clear that targeting CTLA4 might be sufficient, and a three-armed randomized trial of ipilimumab, ipilimumab plus a gp100 peptide vaccine, and gp100 peptide vaccine alone demonstrated clear superiority of the ipilimumab-containing regimens (hazard ratio (HR) for death 0.68, p-value <0.001), but no advantage of gp100 vaccination in combination with ipilimumab (HR 1.04, p-value = 0.76) (Hodi et al. 2010). This was the first study to show an improvement in overall survival in the setting of metastatic melanoma and led to the regulatory approval of ipilimumab including US FDA approval in 2011. In subsequent studies, it appears that treatment with ipilimumab is associated with long-term survival in approximately 22% of patients, marking a new benchmark for the “tail on the curve” for patients with metastatic melanoma (Schadendorf et al. 2015). Another important aspect to anti-CTLA4 inhibitors is the constellation of autoimmune toxicities that never before has been seen with conventional antineoplastic therapy. These so-called immune-related adverse events (irAEs) can be severe and even fatal, often require treatment with immunosuppression, and represent the major limitation of immune checkpoint inhibition (Weber et al. 2013).

Anti-PD-1 Inhibition

With the development of ipilimumab, the field of tumor immunology had a clear success, but it was of limited clinical value to the majority of patients. However, the initial data from the Phase I trial of nivolumab suggested that targeting anti-PD-1 might be a more effective strategy with less toxicity (Topalian et al. 2012). Specifically, responses in over 30% of patients with melanoma, all of whom had been treated with prior therapy, established a new benchmark for immunotherapy response rates. Indeed, both PD-1 inhibitors nivolumab and pembrolizumab were associated with response rates in the 30% range following ipilimumab, leading to regulatory approval of both agents in that patient population based on this data from open-label dosing with pembro (Keynote, KN, 001) and randomized trials of single-agent anti-PD versus chemotherapy (KN002, Checkmate, CM, 037) (Hamid et al. 2013; Weber et al. 2015; Ribas et al. 2015). However, in the frontline setting, as demonstrated in KN006 and CM067, these agents are clearly superior to ipilimumab with response rates in the 40–45% range, 1-year progression-free rates of approximately 40%, 2-year overall survival of 56–58%, and irAE rates of less than 20% (Larkin et al. 2015; Robert et al. 2015a). As with ipilimumab before, the data with these two anti-PD-1 inhibitors reset the bar for efficacy in this disease, and single-agent therapy with either of these agents became the indisputable frontline immunotherapy for patients with metastatic melanoma.

Combination Immune Checkpoint Inhibition

A consistent practice in the era of chemotherapy was to build combinatorial regimens of therapies with slightly different mechanisms of action and single-agent efficacy. With the development of ipilimumab and anti-PD-1 antibodies, it was a logical next step to evaluate the combination of the two in melanoma. In this case, there was strong preclinical data supporting the combination of ipilimumab and nivolumab (ipi/nivo) (Curran et al. 2010). The phase I trial of this regimen showed that ipilimumab 3 mg/kg in combination with nivolumab 1 mg/kg given every three weeks times four doses followed by full dose nivolumab every two weeks, was associated with unprecedented efficacy, response rates in excess of 50%, and toxicity and treatment-related irAE rates greater than 55%, as a clear majority of patients had an objective response to therapy and a majority of patients had severe or life-threatening irAEs (Wolchok et al. 2013). Based on this data, both randomized Phase II trial, CM069, comparing ipi/nivo with single-agent ipilimumab, and three-armed randomized Phase III trial, CM067, comparing the combination versus both single-agent ipilimumab and single-agent nivolumab, were conducted (Larkin et al. 2015; Postow et al. 2015). In both Phase II and III trials, the combination was shown to be superior to single-agent ipilimumab. However, it is less clear whether ipi/nivo is substantially better than single-agent nivolumab to justify the substantial increase in toxicity. For example, with at least 3 years of follow-up, the progression-free and overall survival rates, respectively, of the three arms were 39% and 58% for combination ipi/nivo, 32% and 52% for single-agent nivolumab, and 10% and 34% for ipilimumab. As this trial was not powered to compare the two nivolumab-containing regimens, these differences in those two arms are not statistically significant. However, the development of this combination marks an important milestone in the treatment of melanoma, and the lessons learned with this regimen in melanoma have been applied to a number of other malignancies where this combination (at various doses) is being evaluated.

In melanoma, the use of low-dose ipilimumab (typically 1 mg/kg) given in combination with standard-dose anti-PD-1 therapy has been explored in a number of studies. In the most recent update of KN029, a Phase I/II trial of standard-dose pembrolizumab with low-dose ipilimumab, the rate of grade 3/4 toxicity was 47%, with 26% rate of irAEs, as well as a 62% response rate and a 27% complete response rate (Long et al. 2018a). In CM511, alternative dosing regimens of ipi/nivo were compared. Specifically, the standard induction dosing (IPI 3/NIVO 1 every 3 weeks) was compared to NIVO 3/IPI1 followed by standard nivolumab maintenance (Lebbé et al. 2018). Not surprisingly, the rate of irAEs is lower in patients who received low-dose ipilimumab, but the preliminary progression-free and overall survival of the two cohorts were no different.

Oncolytic Viruses

The first routinely used immune therapy in melanoma was intralesional bacillus Calmette-Guerin (BCG), a tuberculosis vaccine that causes a robust T-cell-mediated response at the site of injection (Morton et al. 1974). While this often was associated with regression of tumors, in the setting of suboptimal systemic therapies, the true value of this approach was very limited. In recent years, renewed interest in intralesional therapies facilitated the development of talimogene laherparepvec (TVEC), an oncolytic herpesvirus engineered to secrete GM-CSF (Hu et al. 2006). In a Phase III trial (OPTIM), 436 patients with advanced Stage III or IV melanoma with palpable, injectable lesions were randomized, in a 2:1 fashion, to receive intralesional TVEC versus subcutaneous GM-CSF (Andtbacka et al. 2015). With respect to the primary end-point, durable response rate, TVEC was superior to GM-CSF in patients with local-regional or limited metastatic disease, leading to its approval (Andtbacka et al. 2015). There was also a strong trend to improved overall survival (HR 0.79, 95% confidence interval 0.62–1.00, p-value = 0.051), a key secondary endpoint, in patients randomized to TVEC. Importantly, the early data with combination with ipilimumab or pembrolizumab looks promising; suggesting that the ideal use of this agent may be in combination with immune checkpoint inhibition (Chesney et al. 2017; Ribas et al. 2017). For example, in the Phase I trial of ipilimumab plus TVEC, the response rate was 50%, a finding that led to a trial randomizing 175 patients to receive ipilimumab with or without TVEC (Chesney et al. 2017; Puzanov et al. 2016). While this study demonstrated a doubling of the response rate with combination therapy (39% vs. 18%), the progression-free survival of both cohorts was similar. More recently, the combination of pembrolizumab plus TVEC has been reported in a Phase I/II study (Ribas et al. 2017). The response rate was confirmed to be over 60%, with response seen in patients with and without pretreatment tumor characteristics associated, in other studies, with response (CD8 density, tumoral PD-L1 expression, interferon gamma gene expression profile scoring). Not surprisingly, there is a lot of interest in this approach generally, and it appears that TVEC is just the beginning, with a number of intralesional therapies, most commonly oncolytic viruses entering the clinic for the treatment of melanoma and other solid tumor malignancies.

Current Dilemmas and Future Directions of Immunotherapy for Patients with Melanoma

Predictive Biomarkers/Patient Selection Strategies

The most pressing clinical dilemma is determining selecting the correct treatment for the right patient. In oncology, this invariably includes histopathology and immunohistochemistry (IHC) to identify the specific type of malignancy (e.g., carcinoma of the lung) or, better yet, pathologic subset that may behave differently (e.g., small cell vs. non-small cell lung carcinoma). More recently, large-scale genomic testing has been performed in most cancers and helped to identify molecularly defined subsets that may be clinically relevant. In cutaneous melanoma, for example, four molecularly defined subsets have been identified by the type of driving genetic alteration (either oncogene or tumor suppressor gene) that is or is not present (Cancer Genome Atlas Network 2015). These include (Fisher et al. 1989) BRAF mutant (~50%), (Frei et al. 1958) NRAS mutant (~25%), (Korn et al. 2008) NF1 mutant (10–15%), and (Imai and Takaoka 2006) triple wild-type (~10–15%). In only the BRAF mutant population, and more specifically patients with a BRAFV600 mutation, are there agents that are proven to benefit this and only this population. These are the BRAF and MEK inhibitors, typically given in combination such as dabrafenib plus trametinib, vemurafenib plus cobimetinib, and encorafenib plus binimetinib (Dummer et al. 2018; Larkin et al. 2014; Long et al. 2015; Robert et al. 2015b). With respect to immunotherapy, there does not appear to be a major difference in outcomes with immunotherapy in patients with BRAF mutant or non-BRAF mutant melanoma (IL-2, ipi, nivo/pembro, ipi/nivo); however there are some data that patients with NRAS mutant melanoma may be more likely to benefit from IL-2 and immune checkpoint inhibitors, although this was not corroborated in a small study looking at using a next-generation sequencing (NGS) platform in patients treated with anti-PD-1/PD-L1 inhibitors (Joseph et al. 2012; Shahabi et al. 2012; Johnson et al. 2015, 2016). In that same NGS analysis, patients with NF1 mutations had a higher response rate but also had a significantly higher tumor mutational burden (TMB), which had been shown in this and other reports to be a strong predictor of response to immune checkpoint inhibitors (Johnson et al. 2016; Van Allen et al. 2015). Interestingly, in NSCLC, molecular defined populations where targeted therapy is available, namely, patients with either EGFR, ROS, or ALK aberrancy, anti-PD-1/PD-L1 therapy is ineffective (Gainor et al. 2016).

Beyond evaluating for specific genetic aberrations, such as activating (oncogenes) or inactivating (tumor suppressor gene) mutations, there have been a number of efforts to evaluate tumors and blood to help predict response to immune checkpoint inhibitor therapy. As described above, TMB has been associated with improved efficacy in patients with metastatic melanoma treated with immune checkpoint inhibitors (Johnson et al. 2016; Van Allen et al. 2015). This is predictable since TMB is a reflection of how altered from self is the tumor. The model follows that the more altered a tumor is, the more likely that the tumor would have immunogenic neoantigens produced, expressed on the cell surface in the context of major histocompatibility complex (MHC), and attract tumor-specific effector T cells. The subsequent response to immune cell infiltration may be expression of PD-L1, either in the tumor cells or induced in the tumor microenvironment, that will engage with PD-1 on the surface of activated effector T cells.

Given that PD-L1 expression seemingly is the final step to blunting a tumor-antigen specific response in the above model and that PD-L1 is involved in the mechanism of action of anti-PD-1 and PD-L1 inhibitors, it logically was the first tissue-based biomarker evaluated for responsiveness in melanoma and other diseases. The clear conclusion from the preponderance of evidence is that the presence of PD-L1 staining above a 1% cut-off is associated with improved outcomes, both in terms of response and survival endpoints. Interestingly, this is true for the anti-PD-1 antibodies pembrolizumab (Daud, JCO, 2016) and nivolumab (CM067, NEJM 2017) and the combination of ipilimumab plus nivolumab (CM067), but not with ipilimumab single-agent therapy (Daud et al. 2016; Wolchok et al. 2017). Specifically in 451 patients with melanoma enrolled onto the Phase I trial of pembrolizumab (KN001), which included first-line and previously treated patients, response rates in patients with below 1% were 10% and above 39% (Daud et al. 2016). In a frontline study comparing ipilimumab, nivolumab, and the combination of the two (Checkmate 067), the response rates in patients with <1% staining were 18%, 35%, and 54%, respectively, and in patients with ≥1%, they were 19%, 54%, and 65% (Wolchok et al. 2017). Still, given that a quarter to a third of patients with PD-L1 <1% respond to single-agent pembrolizumab or nivolumab, the value of PD-L1 staining is not strong enough to be used to exclude the use of these treatments. One possible use of PD-L1 staining in melanoma could be to discriminate those who might be offered single-agent versus combination ipilimumab and nivolumab, although in the Checkmate 067 study, generation of a receiver operating curve indicated that the use PD-L1 status to predict overall survival of either treatment was poor (Wolchok et al. 2017).

A number of markers independent to tissue PD-L1 status have been explored as a potential biomarker of efficacy in patients with melanoma. The data looks promising with a number of tissue markers including presence of CD8+ T cells interacting with PD-L1 at the leading edge of the tumor, interferon gamma signature, MHC I and II expression, and TMB (Johnson et al. 2016; Van Allen et al. 2015; Tumeh et al. 2014; Taube et al. 2012). More recently the presence of specific CD8+ T-cell subsets, particularly those expressing the transcription factor TCF7, has been identified from signal cell RNA sequencing (scRNA seq) data, demonstrated to be present with a validated immunofluorescence assay, and shown to predict responsiveness to PD-1 inhibition in patients with melanoma (Sade-Feldman et al. 2018). Additionally, certain markers have been associated with poor outcomes including absence of CD-8 positive cells, PTEN loss, wnt/beta-catenin pathway genetic aberrations, and a resistance gene expression program identified from scRNA seq and validated in bulk RNA sequencing data (Spranger et al. 2015; Peng et al. 2016; Jerby-Arnon et al. 2018). In the blood, a number of markers seem to be prognostic, including serum LDH, total lymphocyte count, and a serum proteomic signature (Martens et al. 2016; Weber et al. 2018). To date, however, none of these tests have been validated in large trials as a biomarker that can truly predict efficacy or non-efficacy.

Prediction/Mitigation of Toxicity

Perhaps the best sign to herald the coming wave of data demonstrating the efficacy immune checkpoint inhibitors in patients was the reports of true autoimmune toxicity in patients receiving ipilimumab (Beck et al. 2006; Maker et al. 2005; Yang et al. 2007). Since there have been volumes of literature written on the topic, and with the widespread approval of anti-PD-1/PD-L1 monoclonal antibodies for a variety of indications, the use of immune checkpoint inhibition is no longer limited to a smaller number of centers with experience using these agents. Thus, understanding the nature of common and rare toxicities is critical, as is the development of strategies to diagnose and treat or better yet predict and prevent these toxicities.

Immune checkpoint inhibitor toxicity may be mild or fatal and can involve every organ system (Postow et al. 2018). In general, tissue infiltration and/or expansion of inflammatory cells, typically T cells, can cause tissue damage that can manifest clinically. Early diagnosis and treatment is critical, since more severe toxicity will not resolve with discontinuation of the immune checkpoint inhibitor and rather can only be reversed with immune suppression (Puzanov et al. 2017). The best analogy to this is in oncology graft-versus-host disease (GVHD) seen with hematopoietic stem cell transplantation, although many of the autoimmune toxicities seen with checkpoint inhibitors mimic well-described autoimmune disease such as inflammatory bowel disease and inflammatory arthritis. As such, the treatment of these conditions has been crafted with the corresponding autoimmune condition. For example, the treatment of checkpoint inhibitor colitis involves corticosteroids followed by monoclonal antibodies against TNF, agents that are approved for the use of IBD (Puzanov et al. 2017). The concern with immunosuppressive therapy is that the introduction of these agents early into therapy may mitigate efficacy. While this is a theoretical concern, a fair amount of data supports the conclusion that immune suppression in the setting of checkpoint inhibitor toxicity is not associated with poorer outcomes.

One of the key issues in the field today is to better educate clinicians as to the potentially serious risks of these agents and to develop algorithms to work up and treat these toxicities. Over the past few years, professional societies such as the Society for Immunotherapy of Cancer (SITC) have been instrumental in providing educational material and published guidelines (Puzanov et al. 2017). More recently, the American Society of Clinical Oncology (ASCO) has also drafted and published guidelines for the diagnosis and management of these toxicities (Brahmer et al. 2018). These efforts are critical, but there is an opportunity, in the coming years, to leverage emerging technologies, such as single-cell RNA sequencing and wide-scale proteomic arrays, in order to have a deeper understanding of the driving forces in specific types of toxicity (e.g., colitis vs. pneumonitis vs. inflammatory arthritis). Once this has occurred, strategies may then be implemented to predict, monitor for the development of, better treat, and even prevent checkpoint inhibitor toxicity.

New Combinations

As opposed to blocking the brakes to the immune system, new immune targets are being explored including agonists such as OX40, GITR, CD137, and CD40. These agents have the potential to improve antigen presentation and immune activation, as well as deplete cells in the tumor microenvironment with immune regulatory function. With the efficacy of immune checkpoint blockade, there remains the constant effort to improve upon results through combination therapies. These include immuno-immuno combinations such as checkpoint blockade with agonist targets, priming with a variety of vaccination strategies including neoantigen vaccines, improving immune priming with TLR agonists, and combinations with targeted therapies (BRAF and MEK inhibition). Additional methods in attempt to improve current immune therapy strategies include targeting immunosuppressive metabolic pathways such as indoleamine 2,3-dioxygenase 1 (IDO1), transforming growth factor beta (TGF-beta), and nitric oxide, recognizing the importance of innate immunity by attempting to shift the myeloid cell populations in the tumor microenvironment to more tumoricidal that is immune suppressive as well as investigating means to improve NK cell function. These approaches likely represent the next wave of immunologic attempts to improve patient outcomes.

While there is excitement about a number of approaches to target alternative immune checkpoints (e.g., TIM3, LAG3, GITR, TIGIT, CD137, OX40/OX40L, etc.), microenvironment factors (IDO, TGF-beta, etc.), or other immune cells (Tregs, myeloid cells, B cells, etc.), it is important to remember the basics of drug development when moving potentially promising combination therapies forward. This is of particular importance in the setting of the data from the ECHO-301/KN-252 study that randomized 706 patients with previously untreated advanced melanoma to either pembrolizumab or pembrolizumab in combination with the IDO1 inhibitor epacadostat. The basis of this trial was promising data from the Phase I/II trial of this combination (ECHO-202/KN-037) demonstrating a response rate of 55% in the cohort of patients with treatment-naïve melanoma without substantial additional toxicity (Hamid et al. 2017). However, in the randomized trial, the addition of epacadostat to pembrolizumab was not associated with improvement in the primary endpoints, progression-free (HR 1.00) and overall survival (HR 1.13), or an improved response rate (Long et al. 2018b). In trying to figure out why a combination therapy with promising preliminary evidence could fail so spectacularly, it is clear that several key tenets of drug development were not followed. In fact, the supporting data failed to meet any of the following criteria that need to be met (at least one of the criteria) prior to advancing with a registration trial of a combination therapy. They are (Fisher et al. 1989) single-agent efficacy of both agents in the population being studied, (Frei et al. 1958) identification of a well-defined biomarker population that gleans the most benefit from the combination, (Korn et al. 2008) data showing improved efficacy of surrogate markers in a small randomized study, and (Imai and Takaoka 2006) efficacy with the combination in a population of patients resistant/refractory to one of the agents in the combination. Hopefully the field will learn from this study and vet promising combinations more thoroughly in the future.

Role of Cellular Therapy

The actual “drug” for high-dose IL-2, ipilimumab, and anti-PD-1/PD-L1 inhibitors is the effector T cell, meaning that each of these agents works by better enabling T cells to directly kill cancer cells. This concept has always been known, and furthermore the identification of tumor infiltrating lymphocytes (TIL) had been described many decades before the development of immune checkpoint inhibitors (Rosenberg et al. 1982). With the development of high-dose IL-2, it became clear that immunotherapy was feasible, but not effective for the majority of patients (Atkins et al. 1999). In an attempt to enhance the effects of IL-2, the NCI, under the leadership of Dr. Steven Rosenberg, launched a new type of immune therapy that involved the harvesting of tumors to isolate TIL, grow and expand these ex vivo, and then infuse back into the patient and treatment with IL-2 (Rosenberg et al. 2011; Rosenberg 2011). It became clear early on that lymphodepleting chemotherapy was required to enhance efficacy. With this inclusion, the basic framework of adoptive cell therapy (ACT) was in place. Since the early trials of basic TIL therapy, a number of newer approaches have been pursued. These include better selection of higher-affinity or effective TIL clones, as well as cellular engineering of TIL and, more recently, peripheral blood lymphocytes to insert receptors that better recognize tumor-expressed antigens. These constructs include engineering T cells to express tumor-specific T-cell receptors (TCR) against a shared (across patients) tumor antigen (e.g., MAGE A10) or to insert chimeric antigen receptors (CAR) that can recognize surface-expressed proteins that are not processed and expressed in the context of MHC (Maus and June 2016). The challenge with any engineered T cell, be it a TCR-T or CAR-T cell, is the specificity. Mainly, the target antigen must only be expressed tumor cells or only on tumor cells and host cells that are not critical for survival. For example, CAR-T cells against CD-19 lead to dramatic results in patients with B-cell malignancies; however a CAR-T against ERBB2 leads to rapid, lethal toxicity (Maude et al. 2018; Neelapu et al. 2017; Morgan et al. 2010). In melanoma, a number of ACT studies are ongoing, and those that have concluded show responses in the 40–50% range (Rosenberg et al. 2011). These include TIL therapy and TCR-T cell therapies against shared antigens such as MAGE, MART1, and gp100. However, to date, these approaches appear to be more complicated and, at best, no more effective than immune checkpoint inhibition. Thus, ACT only is being tested in the checkpoint inhibitor refractory population, although combination therapy with immune checkpoint inhibitors is a logical strategy in the future.

Conclusion

From Coley to combined immune checkpoint inhibition, the field of cancer immunotherapy has captured the minds of patients and doctors. With recent advances, the concept has become the most exciting type of anticancer therapy. However, with this success have arisen new challenges, namely, innate and acquired resistance to therapy as well as diagnosis and management of toxicity, that will surely be the focus of future work.

References

  1. Alva A, Daniels GA, Wong MK, Kaufman HL, Morse MA, McDermott DF et al (2016) Contemporary experience with high-dose interleukin-2 therapy and impact on survival in patients with metastatic melanoma and metastatic renal cell carcinoma. Cancer Immunol Immunother 65(12):1533–1544PubMedPubMedCentralCrossRefGoogle Scholar
  2. Andtbacka RH, Kaufman HL, Collichio F, Amatruda T, Senzer N, Chesney J et al (2015) Talimogene Laherparepvec improves durable response rate in patients with advanced melanoma. J Clin Oncol 33(25):2780–2788PubMedCrossRefGoogle Scholar
  3. Atkins MB, Lotze MT, Dutcher JP, Fisher RI, Weiss G, Margolin K et al (1999) High-dose recombinant interleukin 2 therapy for patients with metastatic melanoma: analysis of 270 patients treated between 1985 and 1993. J Clin Oncol 17(7):2105–2116PubMedCrossRefGoogle Scholar
  4. Beck KE, Blansfield JA, Tran KQ, Feldman AL, Hughes MS, Royal RE et al (2006) Enterocolitis in patients with cancer after antibody blockade of cytotoxic T-lymphocyte-associated antigen 4. J Clin Oncol 24(15):2283–2289PubMedPubMedCentralCrossRefGoogle Scholar
  5. Bernatchez C, Haymaker CL, Hurwitz ME, Kluger HM, Tetzlaff MT, Jackson N et al (eds) Effect of a novel IL-2 cytokine immune agonist (NKTR-214) on proliferating CD8+T cells and PD-1 expression on immune cells in the tumor microenvironment in patients with prior checkpoint therapy. ASCO 2017 annual meeting, 2017, Chicago. J Clin OncolGoogle Scholar
  6. Brahmer JR, Lacchetti C, Schneider BJ, Atkins MB, Brassil KJ, Caterino JM et al (2018) Management of Immune-Related Adverse Events in Patients Treated With Immune Checkpoint Inhibitor Therapy: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol 36:1714.  https://doi.org/10.1200/JCO.2017.77.6385PubMedPubMedCentralCrossRefGoogle Scholar
  7. Cancer Genome Atlas Network (2015) Genomic classification of cutaneous melanoma. Cell 161(7):1681–1696CrossRefGoogle Scholar
  8. Charych D, Khalili S, Dixit V, Kirk P, Chang T, Langowski J et al (2017) Modeling the receptor pharmacology, pharmacokinetics, and pharmacodynamics of NKTR-214, a kinetically-controlled interleukin-2 (IL2) receptor agonist for cancer immunotherapy. PLoS One 12(7):e0179431PubMedPubMedCentralCrossRefGoogle Scholar
  9. Chen DS, Mellman I (2013) Oncology meets immunology: the cancer-immunity cycle. Immunity 39(1):1–10PubMedCrossRefGoogle Scholar
  10. Chen DS, Mellman I (2017) Elements of cancer immunity and the cancer-immune set point. Nature 541(7637):321–330PubMedCrossRefGoogle Scholar
  11. Chesney J, Puzanov I, Collichio F, Singh P, Milhem MM, Glaspy J et al (2017) Randomized, open-label phase II study evaluating the efficacy and safety of Talimogene Laherparepvec in combination with Ipilimumab versus Ipilimumab alone in patients with advanced, unresectable melanoma. J Clin Oncol.  https://doi.org/10.1200/JCO.2017.73.7379PubMedCrossRefGoogle Scholar
  12. Coley WB (1910) The treatment of inoperable sarcoma by bacterial toxins (the mixed toxins of the Streptococcus erysipelas and the Bacillus prodigiosus). Proc R Soc Med 3(Surg Sect):1–48PubMedPubMedCentralGoogle Scholar
  13. Coley WB, Hoguet JP (1916) Melanotic cancer: with a report of 91 cases. Ann Surg 64(2):206–241PubMedPubMedCentralCrossRefGoogle Scholar
  14. Curran MA, Montalvo W, Yagita H, Allison JP (2010) PD-1 and CTLA-4 combination blockade expands infiltrating T cells and reduces regulatory T and myeloid cells within B16 melanoma tumors. Proc Natl Acad Sci U S A 107(9):4275–4280PubMedPubMedCentralCrossRefGoogle Scholar
  15. Curti B, Daniels GA, McDermott DF, Clark JI, Kaufman HL, Logan TF et al (2017) Improved survival and tumor control with Interleukin-2 is associated with the development of immune-related adverse events: data from the PROCLAIM(SM) registry. J Immunother Cancer 5(1):102PubMedPubMedCentralCrossRefGoogle Scholar
  16. Daud AI, Wolchok JD, Robert C, Hwu WJ, Weber JS, Ribas A et al (2016) Programmed death-ligand 1 expression and response to the anti-programmed death 1 antibody Pembrolizumab in melanoma. J Clin Oncol 34(34):4102–4109PubMedPubMedCentralCrossRefGoogle Scholar
  17. Diab A, Tykodi SS, Curti BD, Cho DC, Wong MK, Puzanov I et al (eds) Immune monitoring after NKTR-214 plus nivolumab (PIVOT-02) in previously untreated patients with metastatic stage IV melanoma. Society of Immunotherapy in Cancer (SITC) annual meeting; 2018a, Washington, DCGoogle Scholar
  18. Diab A, Hurwitz ME, Cho DC, Papadimitrakopoulou V, Curti BD, Tykodi SS et al (eds) NKTR-214 (CD122-biased agonist) plus nivolumab in patients with advanced solid tumors: Preliminary phase 1/2 results of PIVOT. ASCO 2018 annual meeting, 2018b, Chicago. J Clin OncolGoogle Scholar
  19. Dummer R, Ascierto PA, Gogas HJ, Arance A, Mandala M, Liszkay G et al (2018) Encorafenib plus binimetinib versus vemurafenib or encorafenib in patients with BRAF-mutant melanoma (COLUMBUS): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 19(5):603–615PubMedCrossRefGoogle Scholar
  20. Dunn GP, Bruce AT, Ikeda H, Old LJ, Schreiber RD (2002) Cancer immunoediting: from immunosurveillance to tumor escape. Nat Immunol 3(11):991–998PubMedCrossRefGoogle Scholar
  21. Fisher B, Redmond C, Poisson R, Margolese R, Wolmark N, Wickerham L et al (1989) Eight-year results of a randomized clinical trial comparing total mastectomy and lumpectomy with or without irradiation in the treatment of breast cancer. N Engl J Med 320(13):822–828PubMedCrossRefGoogle Scholar
  22. Fontenot JD, Rasmussen JP, Gavin MA, Rudensky AY (2005) A function for interleukin 2 in Foxp3-expressing regulatory T cells. Nat Immunol 6(11):1142–1151PubMedCrossRefGoogle Scholar
  23. Frei E 3rd, Holland JF, Schneiderman MA, Pinkel D, Selkirk G, Freireich EJ et al (1958) A comparative study of two regimens of combination chemotherapy in acute leukemia. Blood 13(12):1126–1148PubMedGoogle Scholar
  24. Fyfe G, Fisher RI, Rosenberg SA, Sznol M, Parkinson DR, Louie AC (1995) Results of treatment of 255 patients with metastatic renal cell carcinoma who received high-dose recombinant interleukin-2 therapy. J Clin Oncol 13(3):688–696PubMedCrossRefGoogle Scholar
  25. Gainor JF, Shaw AT, Sequist LV, Fu X, Azzoli CG, Piotrowska Z et al (2016) EGFR mutations and ALK rearrangements are associated with low response rates to PD-1 pathway blockade in non-small cell lung Cancer: a retrospective analysis. Clin Cancer Res 22(18):4585–4593PubMedPubMedCentralCrossRefGoogle Scholar
  26. Hamid O, Robert C, Daud A, Hodi FS, Hwu WJ, Kefford R et al (2013) Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. N Engl J Med 369(2):134–144PubMedPubMedCentralCrossRefGoogle Scholar
  27. Hamid O, Gajewski TF, Frankel AE, Bauer TM, Olszanski AJ, Luke JJ, et al (eds) Epacadostat plus Pembrolizumab in patients with advanced melanoma: phase 1 and 2 efficacy and safety results from ECHO-202/KEYNOTE-037. ESMO annual meeting, 2017, Madrid, ESPGoogle Scholar
  28. Hodi FS, Mihm MC, Soiffer RJ, Haluska FG, Butler M, Seiden MV et al (2003) Biologic activity of cytotoxic T lymphocyte-associated antigen 4 antibody blockade in previously vaccinated metastatic melanoma and ovarian carcinoma patients. Proc Natl Acad Sci U S A 100(8):4712–4717PubMedPubMedCentralCrossRefGoogle Scholar
  29. Hodi FS, Butler M, Oble DA, Seiden MV, Haluska FG, Kruse A et al (2008) Immunologic and clinical effects of antibody blockade of cytotoxic T lymphocyte-associated antigen 4 in previously vaccinated cancer patients. Proc Natl Acad Sci U S A 105(8):3005–3010PubMedPubMedCentralCrossRefGoogle Scholar
  30. Hodi FS, O’Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB et al (2010) Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 363(8):711–723PubMedPubMedCentralCrossRefGoogle Scholar
  31. Hu JC, Coffin RS, Davis CJ, Graham NJ, Groves N, Guest PJ et al (2006) A phase I study of OncoVEXGM-CSF, a second-generation oncolytic herpes simplex virus expressing granulocyte macrophage colony-stimulating factor. Clin Cancer Res 12(22):6737–6747PubMedCrossRefGoogle Scholar
  32. Imai K, Takaoka A (2006) Comparing antibody and small-molecule therapies for cancer. Nat Rev Cancer 6(9):714–727PubMedCrossRefGoogle Scholar
  33. Jerby-Arnon L, Shah P, Cuoco MS, Rodman C, Su MJ, Melms JC et al (2018) A Cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175(4):984–97.e24PubMedCrossRefGoogle Scholar
  34. Johnson DB, Lovly CM, Flavin M, Panageas KS, Ayers GD, Zhao Z et al (2015) Impact of NRAS mutations for patients with advanced melanoma treated with immune therapies. Cancer Immunol Res 3(3):288–295PubMedPubMedCentralCrossRefGoogle Scholar
  35. Johnson DB, Frampton GM, Rioth MJ, Yusko E, Xu Y, Guo X et al (2016) Targeted next generation sequencing identifies markers of response to PD-1 blockade. Cancer Immunol Res 4(11):959–967PubMedPubMedCentralCrossRefGoogle Scholar
  36. Joseph RW, Sullivan RJ, Harrell R, Stemke-Hale K, Panka D, Manoukian G et al (2012) Correlation of NRAS mutations with clinical response to high-dose IL-2 in patients with advanced melanoma. J Immunother 35(1):66–72PubMedPubMedCentralCrossRefGoogle Scholar
  37. Kirkwood JM, Strawderman MH, Ernstoff MS, Smith TJ, Borden EC, Blum RH (1996) Interferon alfa-2b adjuvant therapy of high-risk resected cutaneous melanoma: the Eastern Cooperative Oncology Group Trial EST 1684. J Clin Oncol 14(1):7–17PubMedCrossRefGoogle Scholar
  38. Kirkwood JM, Manola J, Ibrahim J, Sondak V, Ernstoff MS, Rao U (2004) A pooled analysis of eastern cooperative oncology group and intergroup trials of adjuvant high-dose interferon for melanoma. Clin Cancer Res 10(5):1670–1677PubMedCrossRefGoogle Scholar
  39. Korn EL, Liu PY, Lee SJ, Chapman JA, Niedzwiecki D, Suman VJ et al (2008) Meta-analysis of phase II cooperative group trials in metastatic stage IV melanoma to determine progression-free and overall survival benchmarks for future phase II trials. J Clin Oncol 26(4):527–534PubMedCrossRefGoogle Scholar
  40. Larkin J, Ascierto PA, Dreno B, Atkinson V, Liszkay G, Maio M et al (2014) Combined vemurafenib and cobimetinib in BRAF-mutated melanoma. N Engl J Med 371(20):1867–1876PubMedCrossRefGoogle Scholar
  41. Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Cowey CL, Lao CD et al (2015) Combined Nivolumab and Ipilimumab or monotherapy in untreated melanoma. N Engl J Med 373(1):23–34PubMedPubMedCentralCrossRefGoogle Scholar
  42. Leach DR, Krummel MF, Allison JP (1996) Enhancement of antitumor immunity by CTLA-4 blockade. Science 271(5256):1734–1736PubMedCrossRefGoogle Scholar
  43. Lebbé C, Meyer N, Mortier L, Marquez-Rodas I, Robert C, Rutkowski P et al (eds) Initial results from a phase 3b/4 study evaluating two dosing regimens of nivolumab (NIVO) in combination with ipilimumab (IPI) in patients with advanced melanoma. ESMO annual meeting, 2018, MunichGoogle Scholar
  44. Long GV, Stroyakovskiy D, Gogas H, Levchenko E, de Braud F, Larkin J et al (2015) Dabrafenib and trametinib versus dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial. Lancet 386(9992):444–451PubMedCrossRefGoogle Scholar
  45. Long GV, Atkinson V, Cebon JS, Jameson MB, Fitzharris BM, McNeil CM et al (eds) Long-term follow-up of standard-dose pembrolizumab plus reduced-dose ipilimumab in 153 patients with advanced melanoma: KEYNOTE-029 1B. Society for Melanoma Research Annual Congress, 2018a, ManchesterGoogle Scholar
  46. Long GV, Dummer R, Hamid O, Gajewski TF, Caglevic C, Dalle S et al (eds) Epacadostat plus Pembrolizumab versus Pembrolizumab alone in patients with Unresectable or metastatic melanoma: results of the phase 3 ECHO-301/KEYNOTE-252 study. ASCO annual meeting, 2018b, ChicagoGoogle Scholar
  47. Maker AV, Phan GQ, Attia P, Yang JC, Sherry RM, Topalian SL et al (2005) Tumor regression and autoimmunity in patients treated with cytotoxic T lymphocyte-associated antigen 4 blockade and interleukin 2: a phase I/II study. Ann Surg Oncol 12(12):1005–1016PubMedPubMedCentralCrossRefGoogle Scholar
  48. Martens A, Wistuba-Hamprecht K, Geukes Foppen M, Yuan J, Postow MA, Wong P et al (2016) Baseline peripheral blood biomarkers associated with clinical outcome of advanced melanoma patients treated with Ipilimumab. Clin Cancer Res 22(12):2908–2918PubMedPubMedCentralCrossRefGoogle Scholar
  49. Maude SL, Laetsch TW, Buechner J, Rives S, Boyer M, Bittencourt H et al (2018) Tisagenlecleucel in children and Young adults with B-cell lymphoblastic leukemia. N Engl J Med 378(5):439–448PubMedPubMedCentralCrossRefGoogle Scholar
  50. Maus MV, June CH (2016) Making better chimeric antigen receptors for adoptive T-cell therapy. Clin Cancer Res 22(8):1875–1884PubMedPubMedCentralCrossRefGoogle Scholar
  51. Mier JW, Gallo RC (1980) Purification and some characteristics of human T-cell growth factor from phytohemagglutinin-stimulated lymphocyte-conditioned media. Proc Natl Acad Sci U S A 77(10):6134–6138PubMedPubMedCentralCrossRefGoogle Scholar
  52. Morgan RA, Yang JC, Kitano M, Dudley ME, Laurencot CM, Rosenberg SA (2010) Case report of a serious adverse event following the administration of T cells transduced with a chimeric antigen receptor recognizing ERBB2. Mol Ther 18(4):843–851PubMedPubMedCentralCrossRefGoogle Scholar
  53. Morton DL, Eilber FR, Holmes EC, Hunt JS, Ketcham AS, Silverstein MJ et al (1974) BCG immunotherapy of malignant melanoma: summary of a seven-year experience. Ann Surg 180(4):635–643PubMedPubMedCentralCrossRefGoogle Scholar
  54. Neelapu SS, Locke FL, Bartlett NL, Lekakis LJ, Miklos DB, Jacobson CA et al (2017) Axicabtagene Ciloleucel CAR T-cell therapy in refractory large B-cell lymphoma. N Engl J Med 377(26):2531–2544PubMedPubMedCentralCrossRefGoogle Scholar
  55. Ossowski L, Aguirre-Ghiso JA (2010) Dormancy of metastatic melanoma. Pigment Cell Melanoma Res 23(1):41–56CrossRefGoogle Scholar
  56. Peng W, Chen JQ, Liu C, Malu S, Creasy C, Tetzlaff MT et al (2016) Loss of PTEN promotes resistance to T cell-mediated immunotherapy. Cancer Discov 6(2):202–216PubMedCrossRefGoogle Scholar
  57. Postow MA, Chesney J, Pavlick AC, Robert C, Grossmann K, McDermott D et al (2015) Nivolumab and ipilimumab versus ipilimumab in untreated melanoma. N Engl J Med 372(21):2006–2017PubMedPubMedCentralCrossRefGoogle Scholar
  58. Postow MA, Sidlow R, Hellmann MD (2018) Immune-related adverse events associated with immune checkpoint blockade. N Engl J Med 378(2):158–168PubMedCrossRefGoogle Scholar
  59. Puzanov I, Milhem MM, Minor D, Hamid O, Li A, Chen L et al (2016) Talimogene Laherparepvec in combination with Ipilimumab in previously untreated, unresectable stage IIIB-IV melanoma. J Clin Oncol 34(22):2619–2626PubMedCrossRefGoogle Scholar
  60. Puzanov I, Diab A, Abdallah K, Bingham CO 3rd, Brogdon C, Dadu R et al (2017) Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC) Toxicity Management Working Group. J Immunother Cancer 5(1):95PubMedPubMedCentralCrossRefGoogle Scholar
  61. Quezada SA, Peggs KS, Curran MA, Allison JP (2006) CTLA4 blockade and GM-CSF combination immunotherapy alters the intratumor balance of effector and regulatory T cells. J Clin Invest 116(7):1935–1945PubMedPubMedCentralCrossRefGoogle Scholar
  62. Ribas A, Puzanov I, Dummer R, Schadendorf D, Hamid O, Robert C et al (2015) Pembrolizumab versus investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): a randomised, controlled, phase 2 trial. Lancet Oncol 16(8):908–918PubMedCrossRefGoogle Scholar
  63. Ribas A, Dummer R, Puzanov I, VanderWalde A, Andtbacka RHI, Michielin O et al (2017) Oncolytic virotherapy promotes Intratumoral T cell infiltration and improves anti-PD-1 immunotherapy. Cell 170(6):1109–19.e10PubMedCrossRefGoogle Scholar
  64. Robbins PF, Morgan RA, Feldman SA, Yang JC, Sherry RM, Dudley ME et al (2011) Tumor regression in patients with metastatic synovial cell sarcoma and melanoma using genetically engineered lymphocytes reactive with NY-ESO-1. J Clin Oncol 29(7):917–924PubMedPubMedCentralCrossRefGoogle Scholar
  65. Robert C, Schachter J, Long GV, Arance A, Grob JJ, Mortier L et al (2015a) Pembrolizumab versus Ipilimumab in Advanced Melanoma. N Engl J Med 372(26):2521–2532PubMedCrossRefGoogle Scholar
  66. Robert C, Karaszewska B, Schachter J, Rutkowski P, Mackiewicz A, Stroiakovski D et al (2015b) Improved overall survival in melanoma with combined dabrafenib and trametinib. N Engl J Med 372(1):30–39PubMedCrossRefGoogle Scholar
  67. Rosenberg SA (2011) Cell transfer immunotherapy for metastatic solid cancer – what clinicians need to know. Nat Rev Clin Oncol 8(10):577–585PubMedPubMedCentralCrossRefGoogle Scholar
  68. Rosenberg SA, Eberlein TJ, Grimm EA, Lotze MT, Mazumder A, Rosenstein M (1982) Development of long-term cell lines and lymphoid clones reactive against murine and human tumors: a new approach to the adoptive immunotherapy of cancer. Surgery 92(2):328–336PubMedGoogle Scholar
  69. Rosenberg SA, Yang JC, Sherry RM, Kammula US, Hughes MS, Phan GQ et al (2011) Durable complete responses in heavily pretreated patients with metastatic melanoma using T-cell transfer immunotherapy. Clin Cancer Res 17(13):4550–4557PubMedPubMedCentralCrossRefGoogle Scholar
  70. Sade-Feldman M, Yizhak K, Bjorgaard SL, Ray JP, de Boer CG, Jenkins RW et al (2018) Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175(4):998–1013.e20PubMedPubMedCentralCrossRefGoogle Scholar
  71. Schadendorf D, Hodi FS, Robert C, Weber JS, Margolin K, Hamid O et al (2015) Pooled analysis of Long-term survival data from phase II and phase III trials of Ipilimumab in unresectable or metastatic melanoma. J Clin Oncol 33(17):1889–1894PubMedPubMedCentralCrossRefGoogle Scholar
  72. Shahabi V, Whitney G, Hamid O, Schmidt H, Chasalow SD, Alaparthy S et al (2012) Assessment of association between BRAF-V600E mutation status in melanomas and clinical response to ipilimumab. Cancer Immunol Immunother 61(5):733–737PubMedCrossRefGoogle Scholar
  73. Siroy AE, Boland GM, Milton DR, Roszik J, Frankian S, Malke J et al (2015) Beyond BRAF(V600): clinical mutation panel testing by next-generation sequencing in advanced melanoma. J Invest Dermatol 135(2):508–515PubMedCrossRefGoogle Scholar
  74. Soiffer R, Hodi FS, Haluska F, Jung K, Gillessen S, Singer S et al (2003) Vaccination with irradiated, autologous melanoma cells engineered to secrete granulocyte-macrophage colony-stimulating factor by adenoviral-mediated gene transfer augments antitumor immunity in patients with metastatic melanoma. J Clin Oncol 21(17):3343–3350PubMedCrossRefGoogle Scholar
  75. Spranger S, Bao R, Gajewski TF (2015) Melanoma-intrinsic beta-catenin signalling prevents anti-tumour immunity. Nature 523(7559):231–235CrossRefGoogle Scholar
  76. Taube JM, Anders RA, Young GD, Xu H, Sharma R, McMiller TL et al (2012) Colocalization of inflammatory response with B7-h1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape. Sci Transl Med 4(127):127ra37PubMedPubMedCentralCrossRefGoogle Scholar
  77. Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF et al (2012) Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med 366(26):2443–2454PubMedPubMedCentralGoogle Scholar
  78. Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L et al (2014) PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515(7528):568–571PubMedPubMedCentralGoogle Scholar
  79. Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L et al (2015) Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science 350(6257):207–211PubMedPubMedCentralCrossRefGoogle Scholar
  80. Weber JS, O'Day S, Urba W, Powderly J, Nichol G, Yellin M et al (2008) Phase I/II study of ipilimumab for patients with metastatic melanoma. J Clin Oncol 26(36):5950–5956PubMedCrossRefGoogle Scholar
  81. Weber JS, Dummer R, de Pril V, Lebbe C, Hodi FS (2013) Patterns of onset and resolution of immune-related adverse events of special interest with ipilimumab: detailed safety analysis from a phase 3 trial in patients with advanced melanoma. Cancer 119(9):1675–1682PubMedCrossRefGoogle Scholar
  82. Weber JS, D’Angelo SP, Minor D, Hodi FS, Gutzmer R, Neyns B et al (2015) Nivolumab versus chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial. Lancet Oncol 16(4):375–384PubMedCrossRefGoogle Scholar
  83. Weber JS, Sznol M, Sullivan RJ, Blackmon S, Boland G, Kluger HM et al (2018) A serum protein signature associated with outcome after anti-PD-1 therapy in metastatic melanoma. Cancer Immunol Res 6(1):79–86PubMedCrossRefGoogle Scholar
  84. Wolchok JD, Kluger H, Callahan MK, Postow MA, Rizvi NA, Lesokhin AM et al (2013) Nivolumab plus Ipilimumab in advanced melanoma. New Eng J Med 369:122PubMedCrossRefGoogle Scholar
  85. Wolchok JD, Chiarion-Sileni V, Gonzalez R, Rutkowski P, Grob JJ, Cowey CL et al (2017) Overall survival with combined Nivolumab and Ipilimumab in advanced melanoma. N Engl J Med 377(14):1345–1356PubMedPubMedCentralCrossRefGoogle Scholar
  86. Yang JC, Hughes M, Kammula U, Royal R, Sherry RM, Topalian SL et al (2007) Ipilimumab (anti-CTLA4 antibody) causes regression of metastatic renal cell cancer associated with enteritis and hypophysitis. J Immunother 30(8):825–830PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Center for MelanomaMGH Cancer CenterBostonUSA
  2. 2.Department of Medicine, Brigham and Women’s HospitalDana-Farber Cancer InstituteBostonUSA

Section editors and affiliations

  • David E. Fisher
    • 1
  • Nick Hayward
    • 2
  • David C. Whiteman
    • 3
  • Keith T. Flaherty
    • 4
  • F. Stephen Hodi
    • 5
    • 6
  • Hensin Tsao
    • 7
    • 8
  • Glenn Merlino
    • 9
  1. 1.Department of Dermatology, Harvard/MGH Cutaneous Biology Research Center, and Melanoma Program, MGH Cancer CenterMassachusetts General Hospital, Harvard Medical SchoolBostonUSA
  2. 2.QIMR Berghofer Medical Research InstituteHerstonAustralia
  3. 3.QIMR Berghofer Medical Research InstituteHerstonAustralia
  4. 4.Henri and Belinda Termeer Center for Targeted TherapiesMGH Cancer CenterCambridgeUSA
  5. 5.FraminghamUSA
  6. 6.Department of Medicine, Brigham and Women's HospitalDana-Farber Cancer InstituteBostonUSA
  7. 7.AuburndaleUSA
  8. 8.Harvard-MIT Health Sciences and TechnologyCambridgeUSA
  9. 9.Center for Cancer ResearchNational Cancer InstituteBethesdaUSA

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