Therapies targeting immune checkpoint molecules CTLA-4 and PD-1/PD-L1 have advanced the field of cancer immunotherapy. New mAbs targeting different immune checkpoint molecules, such as TIM3, CD27, and OX40, are being developed and tested in clinical trials. To make educated decisions and design new combination treatment strategies, it is vital to learn more about coexpression of both inhibitory and stimulatory immune checkpoints on individual cells within the tumor microenvironment. Recent advances in multiple immunolabeling and multispectral imaging have enabled simultaneous analysis of more than three markers within a single formalin-fixed paraffin-embedded tissue section, with accurate cell discrimination and spatial information. However, multiplex immunohistochemistry with a maximized number of markers presents multiple difficulties. These include the primary Ab concentrations and order within the multiplex panel, which are of major importance for the staining result. In this article, we report on the development, optimization, and application of an eight-color multiplex immunohistochemistry panel, consisting of PD-1, PD-L1, OX40, CD27, TIM3, CD3, a tumor marker, and DAPI. This multiplex panel allows for simultaneous quantification of five different immune checkpoint molecules on individual cells within different tumor types. This analysis revealed major differences in the immune checkpoint expression patterns across tumor types and individual tumor samples. This method could ultimately, by characterizing the tumor microenvironment of patients who have been treated with different immune checkpoint modulators, form the rationale for the design of immune checkpoint-based immunotherapy in the future.

Dendritic cells (DCs) can initiate and direct adaptive immune responses. This ability is exploitable in DC vaccination strategies, in which DCs are educated ex vivo to present tumor antigens and are administered into the patient with the aim to induce a tumor-specific immune response. DC vaccination remains a promising approach with the potential to further improve cancer immunotherapy with little or no evidence of treatment-limiting toxicity. However, evidence for objective clinical antitumor activity of DC vaccination is currently limited, hampering the clinical implementation. One possible explanation for this is that the most commonly used monocyte-derived DCs may not be the best source for DC-based immunotherapy. The novel approach to use naturally circulating DCs may be an attractive alternative. In contrast to monocyte-derived DCs, naturally circulating DCs are relatively scarce but do not require extensive culture periods. Thereby, their functional capabilities are preserved, the reproducibility of clinical applications is increased, and the cells are not dysfunctional before injection. In human blood, at least three DC subsets can be distinguished, plasmacytoid DCs, CD141 + and CD1c + myeloid/conventional DCs, each with distinct functional characteristics. In completed clinical trials, either CD1c + myeloid DCs or plasmacytoid DCs were administered and showed encouraging immunological and clinical outcomes. Currently, also the combination of CD1c + myeloid and plasmacytoid DCs as well as the intratumoral use of CD1c + myeloid DCs is under investigation in the clinic. Isolation and culture strategies for CD141 + myeloid DCs are being developed. Here, we summarize and discuss recent clinical developments and future prospects of natural DC-based immunotherapy.

Edited by L aszl o NagyMacrophages are innate immune cells that play a role not only in host defense against infections, but also in the pathophysiology of autoimmune and autoinflammatory disorders, as well as cancer. An important feature of macrophages is their high plasticity, with high ability to adapt to environmental changes by adjusting their cellular metabolism and immunological phenotype. Macrophages are one of the most abundant innate immune cells within the tumor microenvironment that have been associated with tumor growth, metastasis, angiogenesis and poor prognosis. In the context of cancer, however, so far little is known about metabolic changes in macrophages, which have been shown to determine functional fate of the cells in other diseases. Here, we review the current knowledge regarding the cellular metabolism of tumor-associated macrophages (TAMs) and discuss its implications for cell function. Understanding the regulation of the cellular metabolism of TAMs may reveal novel therapeutic targets for treatment of malignancies.Keywords: fatty acid; glycolysis; immunometabolism; oxidative phosphorylation; tumor-associated macrophage Abbreviations 2DG, 2-deoxyglucose; 5-LOX, 5-lipoxygenase; ACC, acetyl CoA carboxylase; AcCoA, acetyl coenzyme A; ACLY, ATP citrate lyase; AMPK, AMP-activated protein kinase; ANGPTL4, angiopoietin-like 4; ARG1, arginase 1; BMDMs, bone-marrow-derived macrophages; CARKL, sedoheptulokinase; COX, cyclooxygenase; CPT1, carnitine palmitoyl transferases I; E-FABP, epidermal fatty acid binding protein; ENO1, enolase 1; ETC, electron transfer chain; FA, fatty acid; FADH 2 , flavin adenine dinucleotide; FAO, fatty acid oxidation; FASN, fatty acid synthase; G6P, glucose-6-phosphate; Glu1, glutamine synthetase; HDAC, histone acetyl deacetylase; HIF1a, hypoxia-inducible factor 1-alpha; HK2, hexokinase-2; HO-1, hemeoxygenase; IDO, indoleamine-2,3-dioxygenase; IFN-c, interferon-c; IL, interleukin; iNOS, inducible nitric oxide synthase; LAL, lysosomal acid lipase; LCN, lipocalin; LDL, low-density lipoprotein; LLC, Lewis lung carcinoma; LPL, lipoprotein lipase; LPS, lipopolysaccharides; LRP5, LDL receptor-related protein; MAPK8, mitogen-activated protein kinase 8; MDSCs, myeloid-derived suppressor cells; MMP, matrix metalloproteinase; mTOR, mechanistic target of rapamycin; NAD, nicotinamide adenine dinucleotide; NO, nitric oxide; ODC, ornithine decarboxylase; oxLDL, oxidized LDL; OXPHOS, oxidative phosphorylation; PDK4, pyruvate dehydrogenase kinase 4; PFKFB1, 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1; PFKFB3, 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3; PGE 2 , prostaglandin E2; PI3K, phosphoinositide 3-kinase; PIP3, phosphatidylinositol (3,4,5)-trisphosphate; PKM2, pyruvate kinase 2; PLIN2, perilipin-2; PPAR, peroxisome proliferator-activated receptor; PPP, pentose phosphate pathway; RCC, renal cell carcinoma; REDD1, regulated in development and DNA damage response 1; ROS, reactive oxygen species; SDH, succinate dehydrogenase; SREBP1c, sterol regulatory element bind...

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BackgroundTumor-associated macrophages (TAMs) are key components of the tumor microenvironment (TME) in non-medullary thyroid carcinoma (TC) and neuroblastoma (NB), being associated with a poor prognosis for patients. However, little is known about how tumors steer the specific metabolic phenotype and function of TAMs.MethodsIn a human coculture model, transcriptome, metabolome and lipidome analysis were performed on TC-induced and NB-induced macrophages. The metabolic shift was correlated to functional readouts, such as cytokine production and reactive oxygen species (ROS) production, including pharmacological inhibition of metabolic pathways.ResultsBased on transcriptome and metabolome analysis, we observed a strong upregulation of lipid biosynthesis pathways in TAMs. Subsequently, lipidome analysis revealed that tumor-induced macrophages have an increased total lipid content and enriched levels of intracellular lipids, especially phosphoglycerides and sphingomyelins. Strikingly, this metabolic shift in lipid synthesis contributes to their protumoral functional characteristics: blocking key enzymes of lipid biosynthesis in the tumor-induced macrophages reversed the increased inflammatory cytokines and the capacity to produce ROS, two well-known protumoral factors in the TME.ConclusionsTaken together, our data show that tumor cells can stimulate lipid biosynthesis in macrophages to induce protumoral cytokine and ROS responses and advocate lipid biosynthesis as a potential therapeutic target to reprogram the TME.

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Tumor associated macrophages (TAMs) are important components of the tumor microenvironment (TME). They are characterized by a remarkable functional plasticity, thereby mostly promoting cancer progression. Changes in immune cell metabolism are paramount for this functional adaptation. Here, we review the functional consequences of the metabolic programming of TAMs and the influence of local and systemic targeted therapies on the metabolic characteristics of the TME that shape the functional phenotype of the TAMs. Understanding these metabolic changes within the context of the cross-talk between the different components of the TME including the TAMs and the tumor cells is an essential step that can pave the way towards identifications of ways to improve responses to different treatments, to overcome resistance to treatments, tumor progression and reduce treatment-specific toxicity.

Melanocytic BAP1-associated intradermal tumors (MBAITs) are epithelioid spitzoid looking, mostly intradermally located melanocytic tumors that often have tumor-infiltrating lymphocytes and a common nevus component. They occur sporadically but also in the context of an underlying BAP1 germline mutation. Recognition of these lesions is important because they can be a marker for an underlying BAP1-associated cancer syndrome. Most cases reported in the literature thus far were found to have both a BRAF and BAP1 mutation. Here, we report an unusual case of an MBAIT lesion with a combined NRAS and BAP1 mutation. A BAP1 germline mutation was excluded. Our case is the second case reported until now with this combination of mutations in this subset of lesions. In the other reported NRAS-/BAP1-mutated MBAIT case, presence of a BAP1 germline mutation was not tested. Our case confirms that the mutational spectrum in MBAITs is broader than previously thought. Just as in the BRAF-mutated cases, it is likely that a subset might be associated with a BAP1 germline mutation. In case of suspicion of an MBAIT lesion based on histological examination, diagnostic work-up should include assessment of protein expression and/or mutation analysis of at least BRAF, NRAS, and BAP1. Work-up should not be limited to analyzing only BRAF protein expression or mutation, since NRAS-mutated MBAITs might be missed.