Literature DB >> 32235439

Modern Aspects of Immunotherapy with Checkpoint Inhibitors in Melanoma.

Vera Petrova1,2, Ihor Arkhypov1,2, Rebekka Weber1,2, Christopher Groth1,2, Peter Altevogt1,2, Jochen Utikal1,2, Viktor Umansky1,2.   

Abstract

Although melanoma is one of the most immunogenic tumors, it has an ability to evade anti-tumor immune responses by exploiting tolerance mechanisms, including negative immune checkpoint molecules. The most extensively studied checkpoints represent cytotoxic T lymphocyte-associated protein-4 (CTLA-4) and programmed cell death protein 1 (PD-1). Immune checkpoint inhibitors (ICI), which were broadly applied for melanoma treatment in the past decade, can unleash anti-tumor immune responses and result in melanoma regression. Patients responding to the ICI treatment showed long-lasting remission or disease control status. However, a large group of patients failed to respond to this therapy, indicating the development of resistance mechanisms. Among them are intrinsic tumor properties, the dysfunction of effector cells, and the generation of immunosuppressive tumor microenvironment (TME). This review discusses achievements of ICI treatment in melanoma, reasons for its failure, and promising approaches for overcoming the resistance. These methods include combinations of different ICI with each other, strategies for neutralizing the immunosuppressive TME and combining ICI with other anti-cancer therapies such as radiation, oncolytic viral, or targeted therapy. New therapeutic approaches targeting other immune checkpoint molecules are also discussed.

Entities:  

Keywords:  immune checkpoint inhibitors; immunosuppression; immunotherapy; melanoma; tumor microenvironment

Mesh:

Substances:

Year:  2020        PMID: 32235439      PMCID: PMC7178114          DOI: 10.3390/ijms21072367

Source DB:  PubMed          Journal:  Int J Mol Sci        ISSN: 1422-0067            Impact factor:   5.923


1. Introduction

The concept of cancer immunosurveillance is based on the fact that tumor cells can be recognized and eliminated by immune system [1,2]. Immunogenicity of malignant melanoma is based on a high ultraviolet-driven mutational burden [3]. This leads to the overexpression of tumor specific antigens enabling the formation of the antigen specific immune response [4,5]. However, development of aggressive metastatic melanoma shows that tumors are edited by the immune system, and selected resistant variants could escape the immune control [6,7]. Therefore, several immune-based therapeutic approaches such as vaccination [8], adoptive transfers [9] and immune checkpoint-blockade [10] were applied, aiming at reinvigorating anti-tumor immune response and improving survival of advanced-stage melanoma patients [11]. The most studied negative immune checkpoint molecules and broadly accepted targets for immunotherapy are cytotoxic T lymphocyte-associated protein-4 (CTLA-4) and programmed cell death protein 1 (PD-1). CTLA-4 is upregulated on the T cell surface early during activation in lymph nodes, binds to CD80/CD86 reducing co-stimulation through CD28 and functions as a negative downstream loop for T cell receptor (TCR) signaling [12]. PD-1 interaction with its ligands PD-L1 and PD-L2 inhibits effector T cell functions in peripheral tissues [13]. Playing a pivotal role in the maintenance of self-tolerance under physiological conditions, these checkpoint molecules could be exploited by tumors to evade the immune responses. Hence, inhibiting such interactions could reactivate anti-tumor immune reactions [14]. Moreover, the combination of anti-CTLA-4 and anti-PD-1 antibodies was shown to work synergistically by expanding activated effector CD8 T cells [15,16]. Another approach was shown to implicate the combination of PD-L1-CD80 heterodimerization and the suppression of the CTLA-4/CD80 axis [17]. Currently used antibodies to target CTLA-4 are ipilimumab and tremelimumab, to target PD-1 are nivolumab, pembrolizumab, cemiplimab and to target PD-L1 are atezolizumab and avelumab [14,18,19]. This review will focus on current achievements in the therapy with immune checkpoint inhibitors (ICI) in melanoma and will discuss the strategies to improve of treatment efficacy by combining ICI with other therapies.

2. Therapeutic Effects of Immune Checkpoint Inhibitors

Latest clinical guidelines on melanoma management consider immune checkpoint blockade (anti-PD-1 alone or in combination with anti-CTLA4) as a first-line treatment option for unresectable stage III and IV melanoma patients [20,21]. In cases of resectable melanoma, anti-PD1 agents are prescribed as well in an adjuvant setting [22]. This treatment is currently investigating in a neoadjuvant setting [23]. Since the responses of tumors to immunotherapy and chemotherapy are different, immune-related response criteria and immune-response evaluation criteria in solid tumors were developed [24,25]. Such criteria improve the evaluation of additional response patterns during immunotherapy such as pseudoprogression. Currently achieved response to ICI treatment of melanoma patients reached 52% for pembrolizumab and 58% for combination of nivolumab and ipilimumab [26,27,28]. The 5-year survival rate was reported to be 41% and 52% in these two trials, respectively. These therapeutic achievements were associated with a high toxicity up to 59% of grade 3 and 4 adverse events in patients treated with the combination of nivolumab and ipilimumab [27]. Another trial studied a ipilimumab combination with pembrolizumab, which does not yet belong to the approved settings. The objective response was achieved by 61% of patients, 1-year overall survival (OS) was 89%, and 1-year progression-free survival was 69%. Grade 3 and 4 adverse events occurred in 27% of patients [29]. These data represent a favorable effect of such combinations with increased response values and less high-grade adverse effects. However, many patients remained resistant to ICI therapy since tumor cells could develop resistance to anti-tumor immune reactions or induce a profound immunosuppression in the tumor microenvironment [30].

3. Tumor Cells Evade Immune Responses

A characteristic gene profile was described for melanoma cells resistant to ICI. It includes the repression of genes, which control antigen presentation and interferon (IFN)-γ signaling as well as the induction of genes regulating epithelial-mesenchymal transition, remodeling of extracellular matrix, cell adhesion and angiogenesis [31,32,33,34]. Interestingly, down-regulation of major histocompatibility complex (MHC) class I protein expression was found to be associated with the resistance to anti-CTLA-4, but not to anti-PD-1 therapy [35]. In the same work, MHC class II expression in >1% melanoma cells was shown to predict response to anti-PD-1, but not to anti-CTLA-4 therapy. This suggests that tumor cells disrupt antigen presentation limiting the efficient anti-tumor response. In fact, anti-PD-1 blockade before antigen priming of T cells leads to accumulation of the dysfunctional PD-1+CD38hiCD8+ cells abolishing the effects of the therapy [36]. Moreover, tumor cells can prevent the formation of anti-tumor T cell memory in the draining lymph node by secreting PD-L1-bearing extracellular vesicles (EV), contributing to the resistance to anti-PD-1 antibodies [37].

4. Immunosuppressive Tumor Microenvironment as an Important Factor of ICI Treatment Failure

A deeper investigation of the immunosuppressive networks within the TME could help to understand the limitations of ICI treatment and to develop strategies for increasing treatment efficiency. Immunosuppression in the TME is mediated by various cells and soluble factors described below.

4.1. Myeloid-Derived Suppressor Cells (MDSC)

MDSC represent a heterogeneous population of immunosuppressive myeloid cells, generating under chronic inflammation conditions and cancer and accumulating in the TME [38]. In humans, three MDSC subsets have been described: CD11b+CD14+HLA-DRlow/−CD15−Lin− monocytic (M-MDSC), CD14CD11b+CD15+HLA-DRlow/−Lin− polymorphonuclear (PMN) MDSC, and HLA-DR low/−CD33dimCD66b−Lin− early-stage MDSC (e-MDSC) [39]. MDSC could inhibit anti-tumor functions of T and natural killer (NK) cells via different mechanisms. They can express PD-L1 and FasL and cause T cell anergy and apoptosis [40]. The induction of hypoxia-inducible factor-1α (HIF-1α) through transforming growth factor-β (TGF-β) and hypoxic conditions leads to the upregulation of the ectoenzymes CD39 and CD73, producing immunosuppressive adenosine in the extracellular space [40,41]. Reactive oxygen species (ROS) and nitric oxide (NO) produced by MDSC induce T cell apoptosis and the down-regulation of TCR ζ-chain expression [41,42]. Furthermore, MDSC can stimulate regulatory T cell (Treg) activity [43]. Previous studies demonstrated that high frequency of MDSC in the peripheral blood of advanced melanoma patients correlated with disease progression, decreased overall and progression free survival as well as decreased efficacy of immunotherapy, making them a promising therapeutic target [44,45,46,47]. There are different ways to suppress the immunosuppressive activity of MDSC [48]. Normalization of myelopoiesis and depletion of immunosuppressive MDSC could be achieved by using all-trans retinoic acid (ATRA) [49,50], tyrosine-kinase inhibitors [51,52] or some chemotherapeutic agents such as gemcitabine or paclitaxel [53,54]. Another approach of targeting MDSC represents an inhibition of their immunosuppressive activity. Based on the preclinical data showing that phosphodiesterase (PDE)-5 inhibitor sildenafil could suppress MDSC activity, enhance T cell functionality and prolong survival of melanoma-bearing mice [55,56], another PDE-5 inhibitor tadalafil was applied in advanced, therapy-resistant melanoma patients. Therapy was well-tolerated, and 25% of treated patients showed stable disease (SD) with the progression free survival (PFS) of 4.6 months [57]. Moreover, patients with SD showed increased infiltration of activated CD8+ T cells in the metastasis as compared to non-responding patients. Since the main immunosuppressive effect of MDSC is observed in the TME, the inhibitors of their recruitment to the tumor were tested. Small molecule inhibitor of C-X-C motif chemokine receptor (CXCR) 1 and CXCR2 SX-682 was demonstrated to suppress PMN-MDSC migration and activity, and enhance the efficiency of ICI therapy in mouse oral carcinoma and Lewis lung carcinoma model [58]. In human, SX-682 has been recently applied to advanced melanoma patients alone or in combination with pembrolizumab (Table 1). This table contains ongoing clinical trials, including the combination of ICI with targeting of various immunosuppressive cells (MDSC, CAF, TAM, Treg) and tumor cells as well as with targeting of processes and molecules such as hypoxia, microbiome, neoantigens, and epigenetic mutations. In addition, we included trials combining classical ICI with targeted therapies and new immune checkpoint molecules as well.
Table 1

Ongoing combinatorial clinical trials.

TargetsTrial NumberInterventionDiseaseTrial Phase
MDSCNCT03200847ATRA (Vesanoid) + pembrolizumabAdvanced melanomaI, II
NCT02403778ATRA + ipilimumabAdvanced melanomaII
NCT03161431SX-682 alone or in combination with pembrolizumabMelanoma (III, IV)I
NCT02259231RTA 408 (Omaveloxolone) + nivolumab or ipilimumabUnrespectable or metastatic melanomaIb, II
CAFNCT03875079RO6874281 + pembrolizumabMetastatic melanomaIb
TAMNCT01363206GM-CSF (Leukine, Sargramostim) + ipilimumabUnresectable metastatic melanomaII
TregNCT02203604Aldesleukin (IL-2) + ipilimumabMetastatic melanoma (IIIA–IV)II
NCT02983045NKTR-214 (PEGylated IL-2) + nivolumab with or without ipilimumabAdvanced malignancies, including melanomaI, II
NCT03548467NKTR-214 after prior anti-PD-1 therapyAdvanced malignancies, including melanomaI, II
NCT03635983NKTR-214 + nivolumab or nivolumab aloneUntreated, inoperable or metastatic melanomaIII
NCT03138889NKTR-214 + pembrolizumabAdvanced malignancies, including melanomaI, II
NCT03435640Intratumoral NKTR-262 + systemic NKTR-214 with or without nivolumabMelanoma and other cancer typesI, II
NCT03635983NKTR-214 + nivolumab or nivolumab aloneUntreated, inoperable or metastatic melanomaIII
MicrobiomeNCT03341143Fecal microbiota transplant (FMT) + pembrolizumabAdvanced melanoma patients, non-respondersII
NCT03817125Vancomycin or placebo pretreatment + nivolumab + SER-401 or placeboUnresectable or metastatic melanomaIb
NCT03772899FMT for a healthy donor a week before approved melanoma treatment (pembrolizumab/nivolumab)Advanced melanomaI
NCT03643289Comparison of gut microbiome before and during anti-PD-1 therapy (till week 9)Advanced melanoma stage IVObservational
HypoxiaNCT03311308Metformin + pembrolizumab or pembrolizumab aloneAdvanced, unresectable melanoma stage III or IVI
NCT03171064Exercise + nivolumab or pembrolizumabMetastatic melanomaII
Tumor cellsNCT02799901Hypofractionated radiation therapy (RT) (27 Gy over 3 fractions) + nivolumabAdvanced melanomaII
NCT03693014Hypofractionated RT + Ipilimumab, Nivolumab or Pembrolizumab, continued according to the standard scheduleMetastatic cancer, including melanomaII
NCT02406183Ipilimumab + RTMetastatic melanomaI
NCT04042506Nivolumab + RTMetastatic melanomaII
NCT04017897Anti-PD1 (pembrolizumab or nivolumab) + RTUnresectable, naive metastatic melanoma(IIIB to IVM1c)II
NCT01449279Ipilimumab + RTMetastatic melanomaII
NCT01689974Ipilimumab + RT or ipilimumab aloneMetastatic melanomaII
NCT01769222Ipilimumab + RT or ipilimumab aloneRecurrent malignancies, including melanomaI, II
NCT02659540Nivolumab + ipilimumab in combination with conventional or hypofractionated RTUnresectable melanoma stage IVI
NCT02263508Pembrolizumab + T-VEC or placeboStage IIIB-IVM1c melanomaIII
NCT04068181Pembrolizumab + T-VEC after progression on anti-PD-1 therapyStage IIIB-IVM1d melanomaII
NCT01740297Ipilimumab + T-VEC or ipilimumab aloneStage IIIB–IV metastatic melanomaI, II
NCT02965716Pembrolizumab + T-VECStage IIIB–IV metastatic melanomaII
NCT03842943Neoadjuvant pembrolizumab + T-VECResectable stage 3 melanomaII
Tumor mutationsNCT02902042Encorafenib + binimetinib + pembrolizumabMetastatic BRAF V600 mutant melanomaI, II
NCT02910700Nivolumab + trametinib with or without dabrafenibBRAF-mutated or wild type metastatic stage III-IV melanomaII
NCT02908672Cobimetinib + vemurafenib with atezolizumab or placebo Metastatic BRAF V600 mutant melanomaIII
NCT02303951Vemurafenib + cobimetinib + atezolizumabBRAF V600 mutant stage IIIC-IV melanomaII
NCT01767454Dabrafenib + ipilimumab or dabrafenib + trametinib + ipilimumabMetastatic or unresectable BRAF V600 mutant melanomaI
Epigenetic modificationsNCT03765229Entinostat + pembrolizumabStage III–IV metastatic melanomaII
NCT02437136Entinostat + pembrolizumabAdvanced malignancies, including melanomaIb, II
NeoantigensNCT03929029NeoVax + Montanide® with nivolumab + ipilimumabAdvanced melanomaIb
NCT02385669Peptide Vaccine + IpilimumabStage IIA–IV melanoma (advanced, adjuvant, neoadjuvant)I, II
NCT03047928PD-L1/IDO peptide vaccine + nivolumabMetastatic melanomaI, II
NCT03633110GEN-009 Adjuvant Vaccine + pembrolizumab or nivolumabSolid tumors, including melanomaI, II
NCT04072900Personalized neoantgen peptide vaccine + anti-PD-1 + rhGM-CSF + Imiquimod 5% Topical CreamMetastatic melanomaI
NCT04091750Nivolumab + ipilimumab + cabozantinib followed by nivolumab + cabozantinibAdvanced melanomaII
Other immune checkpoint moleculesNCT02676869IMP321 + pembrolizumabStage III–IV advanced melanomaI
NCT02519322Nivolumab + relatimab or + ipilimumab or alone before surgeryStage IIIb–IV advanced melanomaII
NCT03743766Relatimab + nivolumab or each drug alone followed by relatimab + nivolumab in all subjectsUnresectable or metastatic melanomaII
NCT03470922Relatimab + nivolumab or nivolumab aloneUnresectable or metastatic melanomaII, III
NCT03652077INCAGN02390 antibody against TIM-3 aloneAdvanced malignancies, including melanomaI
NCT04139902Neoadjuvant therapy with PD-1 inhibitor dostarlimab (TSR-042) or dostarlimab (TSR-042) + TSR-022 (TIM-3 inhibitor)Stage IIIB–IV advanced melanomaII
NCT03708328RO7121661, bispecific anti-PD-1 and anti-TIM-3 antibodyAdvanced malignancies, including melanomaI
NCT02817633TSR-022 (anti-TIM-3) alone or + TSR-042 (anti-PD-1) or triple combination of TSR-022 (anti-TIM-3), TSR-042 (anti-PD-1) and TSR-033 (anti-LAG3)Advanced malignancies, including melanomaI
NCT03628677AB154 (anti-TIGIT) alone or + AB122 (anti-PD-1)Advanced malignancies, including melanomaI
NCT03119428OMP-313M32 (anti-TIGIT) alone or + nivolumabAdvanced malignancies, including melanomaI

4.2. Neutrophils

Exposed by high amounts of TGF-β, granulocyte-colony stimulating factor (G-CSF) and IFN-β, tumor associated neutrophils (TAN) lose their anti-tumor functions and start to support tumor progression [59]. TAN have been described to enhance tumor angiogenesis and promote metastasis [60]. High neutrophil to lymphocyte ratio (≥4) at the baseline is considered as a powerful prognostic factor associated with reduced PFS and OS in melanoma patients treated with immune checkpoint inhibitors [61,62].

4.3. Cancer-Associated Fibroblasts (CAF)

CAF are a major component of the tumor stroma [63]. They produce different cytokines such as TGF-β, fibroblast growth factor 2 (FGF-2) and vascular endothelial growth factor (VEGF), which lead to the tumor progression [64]. Moreover, an accumulation of CAF was described to correlate with low efficiency of anti-PD-1 therapy [65]. CAF secret fibroblast activation protein (FAP), which suppresses T cells function and recruitment [66,67]. In addition, FAP was reported to be a negative prognostic marker in the absence of immunotherapy but a positive indicative biomarker in ICI treated melanoma patients with a positive impact on PFS and OS [65]. In the murine melanoma model it was shown that stromal fibroblast matrix metalloproteinase-9 mediated surface PD-L1 cleavage, thus leading to the anti-PD-1 therapy resistance [68]. There is an ongoing trial (NCT03875079) to investigate the activity of the FAP-targeting agent RO6874281 in combination with pembrolizumab.

4.4. Tumor-Associated Macrophages (TAM)

TAM are known to produce interleukin (IL)-1β, cyclooxygenase-2, angiotensin, IFN-γ promoting tumorigenesis [69]. These cells can recruit regulatory T cells (Treg) and inhibit effector T cells by secreting IL-10 and expressing PD-L1 [70]. CD68+ TAM in tumor cell nests were described to be associated with a negative prognosis and recurrence in cutaneous melanoma [70]. Furthermore, the ratio of CD8+ T cells to CD68+ macrophages was shown to predict a disease specific survival in melanoma [71]. CD163+ macrophages were reported to accumulate in the TME of melanoma patients resistant to ICI therapy and to play a role in the maintenance of the immunosuppression. The depletion of CD163+ macrophages led to the invasion of activated T cells and inflammatory monocytes into the tumor, resulting in tumor regression [72,73].

4.5. Regulatory T Cells

Treg represent another important part of TME. It has been shown that the amount of forkhead box protein P3 positive (FOXP3+) Treg is upregulated in the peripheral blood of melanoma patients [74]. Furthermore, the frequency of circulating FOXP3+ Treg is associated with a poor prognosis in melanoma [75]. Tumor infiltrating Treg have been described to be a predominant cluster of the cells with high CTLA-4 expression [76]. It was found that the therapy with common anti-CTLA-4 antibodies (ipilimumab) did not deplete Treg in the tumor [77], however, Fc-engineered anti-CTLA-4 antibodies can specifically deplete FOXP3+ Treg and promote CD8+ T cell expansion, suggesting their higher clinical efficiency than the widely used non-Fc-engineered ipilimumab [76]. In another study, it was reported that the presence of Fcγ receptor-expressing macrophages within the TME is critical for the depletion of tumor-infiltrating Treg [78]. The application of NKTR-214, an engineered cytokine with biased IL-2 receptor binding, was demonstrated to selectively stimulate CD8+ T cells and to deplete Treg in patients with advanced or metastatic solid tumors [79].

5. Role of Microbiome in the ICI Therapy of Melanoma

It has recently been clearly demonstrated that the microbiome could influence the ICI therapy in melanoma patients [80]. Although oral microbiome showed no effect on the response to cancer immunotherapy, an enrichment of Clostridiales, Ruminococcaceae, and Faecalibacterium in the gut was associated with response, while an enrichment of Bacteroidales was observed in non-responders and associated with increased risk of relapse [80]. The same study demonstrated that a favorable gut microbiome composition at the baseline was associated with increased CD8+ T cell infiltration and anti-tumor immune responses. Furthermore, the fecal transplantation from melanoma patients responding to ICI to germ-free mice led to a better response to anti-PD-1 therapy as compared to mice, receiving gut transplants from non-responding patients [80]. Another study demonstrated that the presence of Bifidobacterium longum, Collinsella aerofaciens, and Enterococcus faecium was associated with a better prognosis in melanoma patients [81]. Moreover, the anti-cancer immunity was described to be affected by the alteration in the metabolism of specific bacterial species but not by their presence [82]. There are several ongoing clinical trials dealing with the gut microbiota transplantation in melanoma patients (Table 1).

6. Predicting the Response to the ICI Therapy

Since the response rates to ICI treatment are still restricted [26,27,28,29,83], the identification of response-biomarkers before or shortly after the therapy initiation is one of the biggest challenges in the immuno-oncology. Current approaches to predict response to ICI in melanoma are based on the radiology, tumor biopsy and liquid biopsy [84,85]. Radiological imaging (body computer tomography (CT) scan, head magnetic resonance imaging (MRI)) is used to assess the response to ICI treatment in melanoma patients and is routinely performed three months after the start of treatment. Prediction of response in the earlier time points is possible by using 18F-FDG PET/CT, where response criteria were developed using the scans made at 21 to 28 days after the start of treatment [86]. This approach was also shown to be beneficial in long-term response prediction and guidance of ICI withdrawal [87,88,89]. As a part of PD-1/PD-L1 axis, amount of PD-L1 expression on tumor cells was thought to be a distinct predictive marker for therapy response. Although PD-L1 overexpressing tumors showed an association with the higher response to ICI, durable responses could be also observed in PD-L1 negative tumors [90,91]. Therefore, complementary approaches are needed to improve the prognostic value of tumor PD-L1, including a dynamic monitoring of PD-L1 expression or PD-L1 RNA sequencing [92,93]. Further interest attracts the measurement of PD-L1 (soluble and expressed in extracellular vesicles, EV) in liquid biopsies. Soluble PD-L1 is a splice variant without a transmembrane domain capable to directly inhibit T cell proliferation and IFN-γ production [94]. Elevated basal levels of soluble PD-L1 in the plasma of melanoma patients was associated with progressive disease [95]. Furthermore, the measurement of PD-L1 in EV could help to predict the response to ICI, demonstrating an advantage of the detection in EV over tumor biopsies [96]. Melanoma patients responding to pembrolizumab could be distinguished from non-responders by increased levels of EV PD-L1 at 3 to 6 weeks after the start of therapy [97]. In another study, it was shown that exosomal PD-L1 mRNA levels decreased during nivolumab or pembrolizumab treatment of melanoma patients with complete or partial response, while in patients with progressive disease EV PD-L1 expression was increased [98]. Besides PD-L1, soluble CD163 and macrophage-related chemokines (e.g., C-X-C motif chemokine ligand (CXCL) 5, 10) were reported to predict efficacy of ICI [85]. Decreased serum levels of IL-8 at 2 to 4 weeks after the start of ICI treatment were associated with the response in patients even with the initial pseudoprogression [99]. Induction of CXCR3 ligands in murine melanoma model was described to increase the response to the therapy with anti-PD1 antibodies, and elevated CXCR3 levels were observed in plasma of responding melanoma patients [100]. Another predictive marker could be the amount of tumor-infiltrating T cells. It has been shown that T cells dominated among other immune cells, accumulated in human melanoma metastatic tissue [101]. Strong pre-existing T cell infiltration, IFN-γ–related gene expression signatures in the tumor and high serum level of IFN-γ were reported to be associated with a good clinical prognosis and to predict the response to anti-PD-1 therapy in melanoma patients [101,102,103,104,105]. It was reported that 98% of PD-L1+ tumors were associated with high TIL numbers and the PD-L1+ melanoma cells were localized adjacent to TILs [106].

7. Increasing Effectiveness of ICI Therapy

In order to enhance the beneficial therapeutic effect of ICI, this treatment was combined with other anti-tumor therapies. Since radiation therapy (RT) is used in melanoma patients and can induce antigen release from tumors, its combination with immunotherapy was applied, leading to the T cell activation and improvement of OS without increasing the number of adverse events [107,108]. In a retrospective study with 208 melanoma patients with brain metastasis treated with anti-PD-1 antibodies and RT, the survival rates at 6 and 12 months after the start of treatment were 77% and 70%, respectively [109]. There are numerous ongoing trials investigating the combination of immuno- and radiation therapy in metastatic melanoma patients (Table 1). Another promising approach to increase the efficiency of ICI is to combine it with metformin, a drug for type II diabetes. Metformin was shown to induce not only cell cycle arrest in melanoma cells, leading to their autophagy and apoptosis, but also to affect the TME [110]. It is known that metformin activates AMP-activated protein kinase a (AMPKa) in mitochondria, which lead to the downregulation of HIF-1α expression, resulting in reduced intratumoral hypoxia. Metformin was also reported to promote T cell activity in the combination with ICI, leading to B16 melanoma rejection in mice [111]. In a clinical trial, it was shown that the combination of ICI and metformin increased objective response rate (ORR), disease control rate (DCR), PFS and OS in comparison with the group treated with ICI alone [112]. However, due to a small patient cohort, these changes were not statistically significant. Interestingly, the reduction of tumor hypoxia could be achieved by a physical exercise as well. In B16F10 mouse melanoma model, voluntary wheel running resulted in the epinephrine-dependent, IL-6-sensitive NK cell activation and increased migration of NK and T cells into the tumor [113]. In addition, a physical activity prior to tumor cells inoculation led to a strong reduction of primary tumor growth and numbers of lung metastasis in those mice. Other study demonstrated that the growth of B16F10 melanoma in mice on high-fat diet was accelerated as compared to mice receiving a balanced diet [114]. Importantly, this growth increase was significantly reduced by continuous physical exercise that was associated with the lymphocyte proliferation [114]. In melanoma patients, exercises undertaken before diagnosis were not significantly correlated with a reduction in cancer-related or overall mortality [115]. However, in patients with unresectable stage III or IV melanoma undergoing immunotherapy, the reduction of fatigue was shown to be the main positive impact of physical activity [116]. The ongoing combinational trial is represented in the Table 1. Targeted therapies (BRAF and MEK-inhibitors) are known to be effective in patients with BRAF-V600 mutation and achieve rapid response with a high response rate [117]. The median maintenance of response to this therapy is approximately one year because of the development of acquired resistance [118], while ICI have been described to induce durable response. It was reported that 33% of melanoma patients achieved complete response when treated with the combination of dabrafenib and trametinib with spartalizumab (anti-PD-L1-antibody); the 1-year OS was 86%; however, the number of grade ≥3 adverse events was 75% [119]. In another study, dabrafenib and trametinib were combined with pembrolizumab (triple therapy) or placebo (double therapy) [120]. The median duration of response in tripled therapy group was 18.7 months and 12.5 months in double therapy group. PFS was 16.0 months in triple and 10.3 months in double therapy. In a smaller patient’s cohort, an objective response was achieved in 73% of patients, and 40% maintained the response at a median follow-up of 27.0 months [121]. 73% of patients from the same cohort developed grade 3 and 4 adverse events. Another trial, investigating the combination of atezolizumab (anti-PD-L1-anibody), cobimetinib and vemurafenib showed similar results with an objective response rate of 71.8% and median duration of response of 17.4 months; 39.4% of patients maintained response for 29.9 months of follow-up [122]. These data suggest that this combination therapy can increase the maintenance of the response, but the high grades of adverse events need to be taken into account. Ongoing trials to the triple combination are shown in Table 1. ICI could also be combined with the oncolytic virus talimogen laherparepvec (T-VEC) that was approved for melanoma immunotherapy. T-VEC is a genetically modified virus, which replicates in tumor cells causing cancer cell lysis [123]. It has been reported that the intratumoral T-VEC injection in combination with pembrolizumab led to increased CD8+ T cells infiltration associated with the ORR rate of 62% and the CR in 33% of patients [124]. Combination of all-trans retinoic acid (ATRA) with ipilimumab was reported to decrease frequency of circulating MDSC as well as the expression of PD-L1, IL-10, and indoleamine 2,3-dioxygenase by MDSC, whereas in the ipilimumab monotherapy group the MDSC frequency increased during the treatment [125]. Furthermore, patients receiving combinational treatment tend to have an increased activated CD107a+ IFN-γ+CD8+ T cell numbers compared to the patients treated with ipilimumab alone. Combination of NKTR-214 and Nivolumab was shown to achieve response rates of 53%, which correlated with high IFN-γ levels [126]. Furthermore, the accumulation of IFN-γ and CD8+ TIL in tumor tissue had been seen in favorable as well as in unfavorable tumor microenvironment. The ongoing trials investigating the combination of NKTR-214 with ICI in metastatic melanoma patients are listed in Table 1. It was demonstrated that epigenetic modulation induced by the histone deacetylase inhibitor entinostat (MS-275) could enhance the antigen presentation in tumor cells and inhibit immunosuppressive activity of MDSC and Treg [127,128]. After combining entinostat with the anti-PD-1 antibodies, 19 % of non-responding to anti-PD-1 therapy melanoma patients, achieved objective response [129]. These data represent a new approach to overcome resistance using epigenetics. Other ongoing trials using this combination are listed in Table 1. A new approach of targeting different TME components using nanoparticles has been recently proposed [130]. In melanoma mouse models, nanoparticles were shown to potentiate the efficiency of PD-1 blockade [131,132,133], to reduce the tumor volume and to prolong mouse survival [134].

8. Other ICI in Malignant Melanoma

In addition to PD-L1 and CTLA-4, several other immune checkpoint molecules have been investigated during the last decade. Among them are lymphocyte activation gene-3 (LAG-3), T-cell immunoglobulin- and mucin domain- containing molecule 3 (TIM-3) and T cell immunoreceptor with Ig and ITIM domains (TIGIT). All these molecules were reported to be highly expressed on immune cells in the TME, especially on TILs and Treg, which makes them a promising target for cancer immunotherapy [135]. LAG-3 is expressed on activated CD4+ and CD8+ T cells, Treg, B and NK cells as well as DC [136]. It interacts with MHCII molecules on APC or with Galectin-3 and liver sinusoidal endothelial cell lectin (LSECtin) on cancer cells, leading to the inhibition of CD4+ and CD8+T cell proliferation and decreased cytokine secretion [137]. Such inhibition of T cell function was found to be associated with the promotion of tumor growth and tumor escape [138,139]. LAG-3 blocking could be achieved by LAG-3-Ig fusion protein or LAG-3 targeting antibody (relatlimab). The treatment of melanoma patients with relatlimab resulted in the ORR of 16% and DCR of 45% [140]. Interestingly, only 9% of patients had grade 3 or 4 adverse events that was comparable to the therapy with nivolumab. TIM-3 is expressed on CD4+ and CD8+ T cells, Treg, B cells, NK cells, DC, mast cells and macrophages. Under physiological conditions, it serves as a negative regulator of Th1 response and Th1 related production of TNF and IFN-γ; therefore, its blockade could lead to autoimmune disease [141]. Interaction of TIM-3 with Galectin-9 expressed on tumor cells was reported to result in CD8 TIL apoptosis in colon cancer [142]. In melanoma high expression of TIM-3 was associated with CD8 T cell exhaustion [143]. TIGIT was reported to be involved in the inhibition of CD8+T cells and modulation of DC activity, resulting in the upregulation of IL-10 and downregulation of IL-12 production [144,145]. Moreover, TIGIT was demonstrated to play a crucial role in the maturation of naïve T cells to Foxp3+ Treg [146]. TIGIT+ Tregs showed higher immunosuppressive potential than their TIGIT- counterparts [147]. In malignant melanoma, the co-expression of PD-L1, LAG-3, TIM-3 and TIGIT was demonstrated to induce CD8+ TILs with most exhausted phenotype [125,126]. Double blockage of PD-1 and TIGIT in melanoma led to an increased proliferation and cytokine production of CD8+ TIL and was considered to be a promising approach in immunotherapy [148]. The ongoing clinical trials evaluating the efficiency of LAG-3, TIM-3 and TIGIT blockade are shown in Table 1.

9. Conclusions

Despite of melanoma immunogenicity, this tumor develops immune escape mechanisms that stimulate a fast melanoma progression. Such mechanisms include impaired antigen presentation by tumor cells, accumulation of dysfunctional effector T cells and generation of the immunosuppressive TME represented by MDSC, TAN, CAF, TAM, and Treg. Therefore, numerous approaches were developed to reinvigorate the anti-tumor immune response. Recently approved immunotherapies with ICI (anti-PD-1, anti-PD-L1 and anti-CTLA-4 antibodies) have revolutionized the treatment of melanoma. This treatment significantly increased the survival of melanoma patients and provided a durable control of the disease [26,27,28]. However, the response rates to ICI are still restricted. Thus, further efforts should be undertaken to maximize the efficacy of ICI treatment. This aim could be achieved by improving the selection of patients who might benefit from the ICI therapy, by applying early radiological findings and by measuring predictive markers from tumor and liquid biopsies. Furthermore, the combination of different ICI (such as ipilimumab and nivolumab), their combination with targeting of the immunosuppressive TME or with other anti-cancer therapies could significantly improve the efficacy of tumor immunotherapy. Furthermore, targeting of other immune checkpoints (such as LAG-3, TIM-3, TIGIT) and its combination with approved ICI are currently under investigation (Table 1). Approved ICI, their targets, and targets for combined treatments are summarized in the Figure 1.
Figure 1

Immune checkpoint inhibitors in melanoma and their combination with other therapies. Currently used antibodies against PD-1 (atezolizumab, avelumab), PD-L1 (nivolumab, pembrolizumab, cepilimumab) and CTLA-4 (ipilimumab, tremelimumab) as well as strategies to increase the efficiency of immune checkpoint inhibitors (ICI) are presented. ADP: adenosine diphosphate; APC: antigen presenting cell; ATP: adenosine triphosphate; ATRA: all-trans retinoic acid; CAF: cancer-associated fibroblasts; COX-2: cyclooxygenase-2; CTLA-4: cytotoxic T lymphocyte-associated protein-4; FAP: fibroblast activation protein; FGF-2: fibroblast growth factor 2; GM-CSF: granulocyte-macrophage colony stimulating factor; IFN-β: interferon-β; IL: interleukin; LAG-3: lymphocyte activation gene-3; LSECtin: liver sinusoidal endothelial cell lectin; MDSC: myeloid-derived suppressor cells; MHC: major histocompatibility complex; MMP-9: matrix metallopeptidase 9; NO: nitric oxide; PD-1: programmed cell death protein 1; PD-L1: programmed cell death ligand 1; ROS: reactive oxygen species; RT: radiation therapy; TAM: tumor-associated macrophages; TAN: tumor associated neutrophils; TCR: T-cell receptor; TGF-β: transforming growth factor-β; TIGIT: T cell immunoreceptor with Ig and ITIM domains; TIM-3: T-cell immunoglobulin- and mucin domain- containing molecule 3; Treg; regulatory T cells; T-VEC: talimogen laherparepvec; VEGF: vascular endothelial growth factor.

  145 in total

1.  Nanoenabled Modulation of Acidic Tumor Microenvironment Reverses Anergy of Infiltrating T Cells and Potentiates Anti-PD-1 Therapy.

Authors:  Yu-Xue Zhang; Yang-Yang Zhao; Jizhou Shen; Xun Sun; Yi Liu; Hang Liu; Yucai Wang; Jun Wang
Journal:  Nano Lett       Date:  2019-04-05       Impact factor: 11.189

Review 2.  The Immunology of Melanoma.

Authors:  Jennifer S Ko
Journal:  Clin Lab Med       Date:  2017-09       Impact factor: 1.935

3.  Anti-PD1 in the wonder-gut-land.

Authors:  Marie Vetizou; Giorgio Trinchieri
Journal:  Cell Res       Date:  2018-01-16       Impact factor: 25.617

Review 4.  Melanoma: a prototype of cancer-testis antigen-expressing malignancies.

Authors:  Sepideh Faramarzi; Soudeh Ghafouri-Fard
Journal:  Immunotherapy       Date:  2017-10       Impact factor: 4.196

5.  Subpopulations of myeloid-derived suppressor cells impair T cell responses through independent nitric oxide-related pathways.

Authors:  Patrick L Raber; Paul Thevenot; Rosa Sierra; Dorota Wyczechowska; Daniel Halle; Maria E Ramirez; Augusto C Ochoa; Matthew Fletcher; Cruz Velasco; Anna Wilk; Krzysztof Reiss; Paulo C Rodriguez
Journal:  Int J Cancer       Date:  2013-12-03       Impact factor: 7.396

6.  Talimogene Laherparepvec Improves Durable Response Rate in Patients With Advanced Melanoma.

Authors:  Robert H I Andtbacka; Howard L Kaufman; Frances Collichio; Thomas Amatruda; Neil Senzer; Jason Chesney; Keith A Delman; Lynn E Spitler; Igor Puzanov; Sanjiv S Agarwala; Mohammed Milhem; Lee Cranmer; Brendan Curti; Karl Lewis; Merrick Ross; Troy Guthrie; Gerald P Linette; Gregory A Daniels; Kevin Harrington; Mark R Middleton; Wilson H Miller; Jonathan S Zager; Yining Ye; Bin Yao; Ai Li; Susan Doleman; Ari VanderWalde; Jennifer Gansert; Robert S Coffin
Journal:  J Clin Oncol       Date:  2015-05-26       Impact factor: 44.544

7.  Dabrafenib, trametinib and pembrolizumab or placebo in BRAF-mutant melanoma.

Authors:  Paolo Antonio Ascierto; Pier Francesco Ferrucci; Antoni Ribas; Rosalie Fisher; Michele Del Vecchio; Victoria Atkinson; Henrik Schmidt; Jacob Schachter; Paola Queirolo; Georgina V Long; Anna Maria Di Giacomo; Inge Marie Svane; Michal Lotem; Gil Bar-Sela; Felix Couture; Bijoyesh Mookerjee; Razi Ghori; Nageatte Ibrahim; Blanca Homet Moreno
Journal:  Nat Med       Date:  2019-06-06       Impact factor: 53.440

8.  Dynamic Changes in PD-L1 Expression and Immune Infiltrates Early During Treatment Predict Response to PD-1 Blockade in Melanoma.

Authors:  Ricardo E Vilain; Alexander M Menzies; James S Wilmott; Hojabr Kakavand; Jason Madore; Alexander Guminski; Elizabeth Liniker; Benjamin Y Kong; Adam J Cooper; Julie R Howle; Robyn P M Saw; Valerie Jakrot; Serigne Lo; John F Thompson; Matteo S Carlino; Richard F Kefford; Georgina V Long; Richard A Scolyer
Journal:  Clin Cancer Res       Date:  2017-05-16       Impact factor: 12.531

Review 9.  Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion.

Authors:  Robert D Schreiber; Lloyd J Old; Mark J Smyth
Journal:  Science       Date:  2011-03-25       Impact factor: 47.728

10.  Moderate physical exercise improves lymphocyte function in melanoma-bearing mice on a high-fat diet.

Authors:  Cesar Miguel Momesso Dos Santos; Vinicius Leonardo Sousa Diniz; André Luis Lacerda Bachi; Laiane Cristina Dos Santos de Oliveira; Tamara Ghazal; Maria Elizabeth Pereira Passos; Heloisa Helena de Oliveira; Gilson Murata; Laureane Nunes Masi; Amanda Roque Martins; Adriana Cristina Levada-Pires; Rui Curi; Sandro Massao Hirabara; Donald F Sellitti; Tania Cristina Pithon-Curi; Renata Gorjão
Journal:  Nutr Metab (Lond)       Date:  2019-09-12       Impact factor: 4.169

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  12 in total

1.  Development and Validation of a Novel Ferroptosis-Related LncRNA Signature for Predicting Prognosis and the Immune Landscape Features in Uveal Melanoma.

Authors:  Xiaochen Ma; Sejie Yu; Bin Zhao; Wei Bai; Yubo Cui; Jinglan Ni; Qinghua Lyu; Jun Zhao
Journal:  Front Immunol       Date:  2022-06-14       Impact factor: 8.786

2.  Antigen mimicry as an effective strategy to induce CSPG4-targeted immunity in dogs with oral melanoma: a veterinary trial.

Authors:  Lidia Tarone; Mariateresa Camerino; Davide Giacobino; Soldano Ferrone; Paolo Buracco; Federica Cavallo; Federica Riccardo; Selina Iussich; Giuseppina Barutello; Maddalena Arigoni; Laura Conti; Elisabetta Bolli; Elena Quaglino; Irene Fiore Merighi; Emanuela Morello; Alfredo Dentini
Journal:  J Immunother Cancer       Date:  2022-05       Impact factor: 12.469

Review 3.  Current management of melanoma patients with nodal metastases.

Authors:  Dale Han; Alexander C J van Akkooi; Richard J Straker; Adrienne B Shannon; Giorgos C Karakousis; Lin Wang; Kevin B Kim; Douglas Reintgen
Journal:  Clin Exp Metastasis       Date:  2021-05-07       Impact factor: 4.510

Review 4.  Is There a Place for Immune Checkpoint Inhibitors in Vulvar Neoplasms? A State of the Art Review.

Authors:  Fulvio Borella; Mario Preti; Luca Bertero; Giammarco Collemi; Isabella Castellano; Paola Cassoni; Stefano Cosma; Andrea Roberto Carosso; Federica Bevilacqua; Niccolò Gallio; Chiara Benedetto; Leonardo Micheletti
Journal:  Int J Mol Sci       Date:  2020-12-27       Impact factor: 5.923

5.  Baseline and early functional immune response is associated with subsequent clinical outcomes of PD-1 inhibition therapy in metastatic melanoma patients.

Authors:  Alexandre Gérard; Jerome Doyen; Henri Montaudié; Barbara Seitz-Polski; Marion Cremoni; Laurent Bailly; Kevin Zorzi; Caroline Ruetsch-Chelli; Vesna Brglez; Alexandra Picard-Gauci; Laura Troin; Vincent L M Esnault; Thierry Passeron
Journal:  J Immunother Cancer       Date:  2021-06       Impact factor: 13.751

Review 6.  The Influence of Tumor Microenvironment on Immune Escape of Melanoma.

Authors:  Aleksandra Simiczyjew; Ewelina Dratkiewicz; Justyna Mazurkiewicz; Marcin Ziętek; Rafał Matkowski; Dorota Nowak
Journal:  Int J Mol Sci       Date:  2020-11-07       Impact factor: 5.923

Review 7.  Tumor Lysis Syndrome After a Single Dose of Atezolizumab with Nab-Paclitaxel: A Case Report and Review of Literature.

Authors:  Xavier Carrier; Sumit Gaur; Alexander Philipovskiy
Journal:  Am J Case Rep       Date:  2020-09-16

Review 8.  Targeting Tumor-Associated Macrophages to Increase the Efficacy of Immune Checkpoint Inhibitors: A Glimpse into Novel Therapeutic Approaches for Metastatic Melanoma.

Authors:  Claudia Ceci; Maria Grazia Atzori; Pedro Miguel Lacal; Grazia Graziani
Journal:  Cancers (Basel)       Date:  2020-11-17       Impact factor: 6.639

Review 9.  Myeloid Cell Modulation by Tumor-Derived Extracellular Vesicles.

Authors:  Ihor Arkhypov; Samantha Lasser; Vera Petrova; Rebekka Weber; Christopher Groth; Jochen Utikal; Peter Altevogt; Viktor Umansky
Journal:  Int J Mol Sci       Date:  2020-08-31       Impact factor: 5.923

10.  Cancer Stemness Associated With Prognosis and the Efficacy of Immunotherapy in Adrenocortical Carcinoma.

Authors:  Xiaoxi Shi; Yuanlin Liu; Shuai Cheng; Haidi Hu; Jian Zhang; Minjie Wei; Lin Zhao; Shijie Xin
Journal:  Front Oncol       Date:  2021-07-21       Impact factor: 6.244

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