Correlation of tumor PD-L1 expression in different tissue types and outcome of PD-1-based immunotherapy in metastatic melanoma - analysis of the DeCOG prospective multicenter cohort study ADOREG/TRIM

Exploring immune checkpoint inhibitors: Focus on PD-1/PD-L1 axis and beyond

Immunotherapy emerges as a promising approach, marked by recent substantial progress in elucidating how the host immune response impacts tumor development and its sensitivity to various treatments. Immune checkpoint inhibitors have revolutionized cancer therapy by unleashing the power of the immune system to recognize and eradicate tumor cells. Among these, inhibitors targeting the programmed cell death protein 1 (PD-1) and its ligand (PD-L1) have garnered significant attention due to their remarkable clinical efficacy across various malignancies. This review delves into the mechanisms of action, clinical applications, and emerging therapeutic strategies surrounding PD-1/PD-L1 blockade. We explore the intricate interactions between PD-1/PD-L1 and other immune checkpoints, shedding light on combinatorial approaches to enhance treatment outcomes and overcome resistance mechanisms. Furthermore, we discuss the expanding landscape of immune checkpoint inhibitors beyond PD-1/PD-L1, including novel targets such as CTLA-4, LAG-3, TIM-3, and TIGIT. Through a comprehensive analysis of preclinical and clinical studies, we highlight the promise and challenges of immune checkpoint blockade in cancer immunotherapy, paving the way for future advancements in the field.

Gastrointestinal tumor personalized immunotherapy: an integrated analysis from molecular genetics to imaging biomarkers

The immunotherapy landscape for gastrointestinal (GI) tumors is rapidly evolving. There is an urgent need for reliable biomarkers capable of predicting treatment outcomes to optimize therapeutic strategies and enhance patient prognosis. This review presents a comprehensive overview of biomarkers associated with the immunotherapy response of GI tumors, covering advances in molecular genetics, histopathological markers, and imaging. Key molecular biomarkers, such as microsatellite instability, tumor mutational burden, and programmed death-ligand 1 expression, remain critical for identifying patients likely to benefit from immune checkpoint inhibitors. The significance of tumor-infiltrating lymphocytes, notably the CD8+ T cell to regulatory T cell ratio, as a predictor of immunotherapy response is explored. In addition, advanced imaging techniques, including computed tomography (CT), magnetic resonance imaging, and positron emission tomography-CT, facilitate the noninvasive evaluation of tumor biology and therapeutic response. By bridging molecular and imaging data, this integrated strategy enhances precision in patient selection, treatment monitoring, and adaptive therapy design. Future studies should aim to validate these biomarkers in larger, multicenter cohorts and focus on clinical translation to advance precision medicine in GI oncology.

Prognostic Biomarkers in Evolving Melanoma Immunotherapy

Melanoma, a highly aggressive form of skin cancer, has seen significant advancements in treatment through the introduction of immunotherapy. However, the variability in patient responses underscores the need for reliable biomarkers to guide treatment decisions. This article reviews key biomarkers in melanoma immunotherapy, such as PD-L1 expression, tumor mutational burden (TMB), and gene expression profiles (GEPs). It also explores emerging biomarkers, including LAG-3 expression, immune cell phenotyping in tissue and blood, gut microbiota, and circulating tumor DNA (ctDNA). Notably, ctDNA may offer valuable insights into the efficacy of T cell-engaging bispecific molecules, such as tebentafusp. The review provides a comprehensive overview of the evolving landscape of melanoma biomarkers, their role in personalizing treatment, and future research directions, including neoadjuvant immune checkpoint inhibition.

Spatial proteomics reveals sirtuin 1 to be a determinant of T-cell infiltration in human melanoma

BACKGROUND

The tumour microenvironment significantly influences the clinical response of patients to therapeutic immune checkpoint inhibition (ICI), but a comprehensive understanding of the underlying immune-regulatory proteome is still lacking.

OBJECTIVES

To decipher targetable biologic processes that determine tumour-infiltrating lymphocytes (TiLs) as a cellular equivalent of clinical response to ICI.

METHODS

We mapped the spatial distribution of proteins in TiL-enriched vs. TiL-low compartments in melanoma by combining microscopy, matrix-assisted laser desorption mass spectrometry imaging and liquid chromatography-mass spectrometry, as well as computational data mining. Pharmacological modulation of sirtuin 1 (SIRT1) activity in syngeneic mouse models was used to evaluate the efficacy of pharmacological SIRT1 activation in two syngeneic melanoma mouse models, one known to be α-programmed cell death protein 1 (PD-1) sensitive and the other α-PD-1 resistant.

RESULTS

Spatial proteomics and gene ontology-based enrichment analysis identified > 145 proteins enriched in CD8high tumour compartments, including negative regulators of mammalian target of rapamycin signalling such as SIRT1. Multiplexed immunohistochemistry confirmed that SIRT1 protein was expressed more in CD8high than in CD8low compartments. Further analysis of bulk and single-cell RNA sequencing data from melanoma tissue samples suggested the expression of SIRT1 by different lymphocyte subpopulations (CD8+ T cells, CD4+ T cells and B cells). Furthermore, we showed in vivo that pharmacological SIRT1 activation increased the immunological effect of α-PD-1 ICI against melanoma cells in mice, which was accompanied by an increase in T-cell infiltration and T-cell-related cytokines, including interferon (IFN)-γ, CCL4, CXCL9, CXCL10 and tumour necrosis factor-α. In silico analysis of large transcriptional data cohorts showed that SIRT1 was positively associated with the proinflammatory T-cell chemokines CXCL9, CXCL10 and IFN-γ, and prolonged overall survival of patients with melanoma.

CONCLUSIONS

Our study deciphers the proteomics landscape in human melanoma, providing important information on the tumour microenvironment and identifying SIRT1 as having important prognostic and therapeutic implications.

Prognostic value of immune biomarkers in melanoma loco-regional metastases

The prognosis for patients with melanoma loco-regional metastases is very heterogenous. Adjuvant PD-L1-inhibitors have improved clinical outcome for this patient group, but the prognostic impact of tumour PD-L1 expression and number of tumour infiltrating lymphocytes (TILs) is still largely unknown. Here, we investigated the impact on survival for CD3, CD8, FOXP3 and PD-L1 TIL counts and tumour PD-L1 expression in melanoma loco-regional metastases. In a patient series of loco-regional metastases from nodular melanomas (n = 78; n = 26 skin metastases, n = 52 lymph node metastases), expression of PD-L1 in tumour cells and the number of CD3, CD8, FOXP3 and PD-L1 positive TILs were determined by immunohistochemistry on tissue microarray (TMA) slides. Due to limited tumour tissue in the paraffin blocks, 67 of the 78 cases were included for tissue microarrays. Low FOXP3 TIL count and negative tumour PD-L1 expression (cut off 1%) were both significantly associated with reduced survival in lymph node metastases. Low FOXP3 TIL count was significantly associated with low CD8, CD3 and PD-L1 TIL counts. Negative tumour PD-L1 expression was significantly associated with low CD8 and PD-L1 TIL count, large lymph node metastasis tumour size and presence of necrosis in lymph node metastases. Our findings demonstrate for the first time the negative prognostic value of low FOXP3 TIL count and confirm a negative prognostic value of negative tumour PD-L1 expression in melanoma lymph node metastases.

European consensus-based interdisciplinary guideline for melanoma. Part 1: Diagnostics - Update 2024

This guideline was developed in close collaboration with multidisciplinary experts from the European Association of Dermato-Oncology (EADO), the European Dermatology Forum (EDF) and the European Organization for Research and Treatment of Cancer (EORTC). Recommendations for the diagnosis and treatment of melanoma were developed on the basis of systematic literature research and consensus conferences. Cutaneous melanoma (CM) is the most dangerous form of skin tumor and accounts for 90 % of skin cancer mortality. The diagnosis of melanoma can be made clinically and must always be confirmed by dermoscopy. If melanoma is suspected, a histopathological examination is always required. Sequential digital dermoscopy and whole-body photography can be used in high-risk patients to improve the detection of early-stage melanoma. If available, confocal reflectance microscopy can also improve the clinical diagnosis in special cases. Melanoma is classified according to the 8th version of the American Joint Committee on Cancer classification. For thin melanomas up to a tumor thickness of 0.8 mm, no further diagnostic imaging is required. From stage IB, lymph node sonography is recommended, but no further imaging examinations. From stage IIB/C, whole-body examinations with computed tomography or positron emission tomography CT in combination with magnetic resonance imaging of the brain are recommended. From stage IIB/C and higher, a mutation test is recommended, especially for the BRAF V600 mutation. It is important to perform a structured follow-up to detect relapses and secondary primary melanomas as early as possible. A stage-based follow-up regimen is proposed, which in the experience of the guideline group covers the optimal requirements, although further studies may be considered. This guideline is valid until the end of 2026.

Dual Immune Checkpoint Inhibition in Melanoma and PD-L1 Expression: The Jury Is Still Out

This comment discusses the use of PD-L1 as a biomarker to guide treatment decisions for metastatic melanoma.

PD-L1, PD-1, and CTLA-4 mRNA In Situ Expression by Canine Oral Melanoma Cells and Immune Cells of the Tumour Microenvironment

Canine oral melanoma (OM) exhibits poor prognosis and limited treatment options. The success of immune checkpoint inhibitors (ICIs) in human melanoma has driven interest in similar therapeutic approaches in the dog, although the immunosuppressive mechanisms adopted by canine OM remain unclear. This study aimed to evaluate the expression of the immune checkpoints PD-1/PD-L1 and CTLA-4 by RNAscope in situ hybridization (ISH) in canine OM, to investigate their expression pattern and explore their potential role in melanoma progression. Twenty-four formalin-fixed, paraffin-embedded canine OM were included in the study. PD-L1 expression by tumour cells was detected in 100% melanomas (score 1-3), especially at the host-tumour interface. PD-1 and CTLA-4 expression by tumour cells was detected in 13/24 (54%, score 1-2) and 18/24 (75%, score 1) melanomas, respectively. Dual ISH-immunohistochemistry with Melanoma Triple Cocktail, CD3, CD20 and Iba1 demonstrated the expression of tested immune checkpoints in neoplastic and immune cells. Notably, PD-1 and CTLA-4 were predominantly expressed by tumour-infiltrating T lymphocytes, while PD-L1 was primarily expressed by tumour-associated macrophages. PD-1 expression in neoplastic cells was significantly correlated with mitotic count (p < 0.05), while no associations were found between immune checkpoint expression and disease-free interval or overall survival. Whole tumour PD-L1 and PD-1 expression, assessed by image analysis, correlated to PD-L1 scores in neoplastic cells and the grade of tumour-infiltrating lymphocytes, respectively. Collectively, PD-L1, PD-1 and CTLA-4 likely contribute to immunosuppression in canine OM. Further studies are warranted to investigate whether ISH can serve as a biomarker for selecting patients suitable for ICI treatment.

Remodelling of the immune landscape by IFNγ counteracts IFNγ-dependent tumour escape in mouse tumour models

Loss of IFNγ-sensitivity by tumours is thought to be a mechanism enabling evasion, but recent studies suggest that IFNγ-resistant tumours can be sensitised for immunotherapy, yet the underlying mechanism remains unclear. Here, we show that IFNγ receptor-deficient B16-F10 mouse melanoma tumours are controlled as efficiently as WT tumours despite their lower MHC class I expression. Mechanistically, IFNγ receptor deletion in B16-F10 tumours increases IFNγ availability, triggering a remodelling of the immune landscape characterised by inflammatory monocyte infiltration and the generation of 'mono-macs'. This altered myeloid compartment synergises with an increase in antigen-specific CD8+ T cells to promote anti-tumour immunity against IFNγ receptor-deficient tumours, with such an immune crosstalk observed around blood vessels. Importantly, analysis of transcriptomic datasets suggests that similar immune remodelling occurs in human tumours carrying mutations in the IFNγ pathway. Our work thus serves mechanistic insight for the crosstalk between tumour IFNγ resistance and anti-tumour immunity, and implicates this regulation for future cancer therapy.

Response and outcome of patients with melanoma skin metastases and immune checkpoint inhibition

It is known, that different metastatic organ systems respond differently to immune checkpoint inhibitors (ICIs). In this study, we aimed to investigate the extent to which skin/subcutaneous metastases respond to ICI or targeted therapies (TTs) and whether the response rate differs from that of distant metastases in the same patient. Patients with melanoma diagnosed between January 2021 and September 2023 with at least one skin/subcutaneous metastasis who had received therapy with ICI or TT in an advanced setting were included in the analysis. Best overall response (BOR) was classified according to the revised response evaluation criteria in solid tumors (RECIST). The BOR of skin metastases and visceral metastases to ICI and TT was compared using the chi-square test. Skin metastases treated with ICI a first-line setting showed an overall response rate (ORR) of 44.1%. In contrast, visceral metastases had a higher ORR of 51.1%. However, the difference was not statistically significant (p = .77). Regarding TT, the ORR for skin metastases was 57.1%, compared to 38.5% for visceral metastases (p = .59). Interestingly, the ORR for skin/subcutaneous metastases was notably lower with ICI compared to visceral metastases, in contrast to patients who underwent TT. Skin metastases showed a poorer response to ICI than visceral metastases. Therefore, careful monitoring is recommended to detect non-response early in patients with skin metastases as skin metastases may have a worse response than TT. A larger cohort is needed for a comprehensive analysis and confirmation of our results.

Immune biomarkers and predictive signatures in gastric cancer: Optimizing immunotherapy responses

Gastric cancer is a malignant disease with a poor prognosis and few therapeutic options once it has advanced. Immunotherapy using ICIs has emerged as a viable therapeutic method; nevertheless, reliable immunological biomarkers are required to identify who may benefit from these therapies. It focuses on key immune biomarkers and predictive signatures in gastric cancer, such as PD-L1 expression, microsatellite instability (MSI), tumor mutational burden (TMB), and Epstein-Barr virus (EBV) status, to optimize gastric cancer patients' immunotherapy responses. PD-L1 expression is a popular biomarker for ICI effectiveness. Tumors with high MSI-H and TMB are the most susceptible to ICIs because they are highly immunogenic. EBV-positive stomach tumors are highly immunogenic, and immunotherapy has a high response rate. Combining composite biomarker panels with multi-omics-based techniques improved patient selection accuracy. In recent years, machine learning models have been integrated into next-generation sequencing. Dynamic, real-time-monitorable biomarkers for real-time immune response monitoring are also being considered. Thus, enhancing biomarker-driven immunotherapy is critical for improving clinical outcomes with gastric cancer. There is still more work to be done in this field, and verifying developing biomarkers will be an important component in the future of customized cancer therapy.

Tumor-Infiltrating Immune Cells and HLA Expression as Potential Biomarkers Predicting Response to PD-1 Inhibitor Therapy in Stage IV Melanoma Patients

PD-1 inhibitors are known to be effective in melanoma; however, a considerable proportion of patients fail to respond to therapy, necessitating the identification of predictive markers. We examined the predictive value of tumor cell HLA class I and II expression and immune cell infiltration in melanoma patients treated with PD-1 inhibitors. Pretreatment surgical samples from 40 stage IV melanoma patients were studied immunohistochemically for melanoma cell expression of HLA class I molecules (using four antibody clones with different specificities), HLA-II, and immune cell infiltration (using a panel of 10 markers). Among the responders, the ratio of patients showing melanoma cell HLA-II expression was higher compared to non-responders (p = 0.0158), and similar results were obtained in the case of two anti-HLA-I antibodies. A combined score of HLA-I/II expression also predicted treatment response (p = 0.0019). Intratumoral infiltration was stronger in the responders for most immune cell types. Progression-free survival showed an association with HLA-II expression, the combined HLA score, and the density of immune cells expressing CD134 and PD-1, while overall survival was significantly associated only with HLA class II expression. Our findings corroborate previous results indicating the importance of immune cell infiltration and tumor cell HLA-II expression in the efficacy of PD-1 inhibitor treatment in a "real world" patient cohort and suggest the potential predictive role of HLA class I expression.

The roles of PD-L1 in the various stages of tumor metastasis

The interaction between tumor programmed death ligand 1 (PD-L1) and T-cell programmed cell death 1 (PD-1) has long been acknowledged as a mechanism for evading immune surveillance. Recent studies, however, have unveiled a more nuanced role of tumor-intrinsic PD-L1 in reprograming tumoral phenotypes. Preclinical models emphasize the synchronized effects of both intracellular and extracellular PD-L1 in promoting metastasis, with intricate interactions with the immune system. This review aims to summarize recent findings to elucidate the spatiotemporal heterogeneity of PD-L1 expression and the pro-metastatic roles of PD-L1 in the entire process of tumor metastasis. For example, PD-L1 regulates the epithelial-to-mesenchymal transition (EMT) process, facilitates the survival of circulating tumor cells, and induces the formation of immunosuppressive environments at pre-metastatic niches and metastatic sites. And the complexed and dynamic regulation process of PD-L1 for tumor metastasis is related to the spatiotemporal heterogeneity of PD-L1 expression and functions from tumor primary sites to various metastatic sites. This review extends the current understandings for the roles of PD-L1 in mediating tumor metastasis and provides new insights into therapeutic decisions in clinical practice.

Spatial oncology: Translating contextual biology to the clinic

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Dual PD-L1/SOX10 Immunohistochemistry Combined With Digital Imaging Enhances Stratification Accuracy of Patients With Metastatic Melanoma

Immune checkpoint inhibitor therapy has demonstrated an overall survival benefit in patients with advanced melanoma. Though the significance of programmed death-ligand 1 (PD-L1) expression on melanoma cells as a predictive biomarker of response remains inconclusive, some reports indicate that a PD-L1 expression of <1% of tumor cells may be associated with better outcomes with dual immunotherapy. Adequate patient selection for combination therapy is critical given the higher frequency of adverse effects compared with monotherapy. Immunohistochemical (IHC) PD-L1 interpretation in tumor cells is challenging when inflammatory cells are present and cutoffs are low. We studied 36 metastatic melanoma biopsies from Immune checkpoint inhibitor-naive patients, previously stained and scored for PD-L1 IHC using the tumor proportion score (TPS). Cases were classified into 3 groups: <1%, 1% to 5%, and >5%. After de-coverslipping, SRY-related HMG-box-10 (SOX10) IHC was performed on PD-L1 IHC slides with a red chromogen, and subsequently scanned and scored by ≥2 dermatopathologists. This assessment determined that 25% of cases (9/36) had a TPS ≥ 1%, in contrast to the single IHC assay (63.8%). The majority of the 1-5% group (11/13, 84.6%) underwent a change of category to <1% TPS. In the >5% group, 60% of cases (6/10) were downgraded to <1% and 1% to 5% (4 and 2 cases, respectively). Our study suggests that PD-L1 IHC evaluation could benefit from dual PD-L1/SOX10 IHC. Dual IHC is expected to decrease the interference caused by PD-L1 expression on inflammatory cells, and digital imaging proves useful for the preservation and analysis of stains. Refining PD-L1 evaluation in metastatic melanoma may improve clinical decisions between single and combination immunotherapy, with potentially profound consequences in response and quality of life.

Gal-3 blocks the binding between PD-1 and pembrolizumab

INTRODUCTION

Immune checkpoint inhibitors (ICI) have revolutionized the treatment of metastatic malignant melanoma (MM) and improved long-term survival. Despite the impressive results, some patients still have progressive disease, and the search for biomarkers predicting response to ICI treatment is ongoing. In this search, galectin-3 (Gal-3) has been suggested as a molecule of interest, both as a marker of treatment response and as a treatment target to potentiate ICI therapy. We have previously demonstrated the binding between programmed cell death 1 (PD-1) and Gal-3, and here, we investigated the interaction between PD-1, pembrolizumab, and Gal-3 in metastatic MM patients.

METHODS

The binding between PD-1, pembrolizumab and Gal-3 was investigated by surface plasmon resonance (SPR) and cryogenic electron microscopy (cryo-EM). The function was studied in in vitro cultures and soluble levels of both PD-1 and Gal-3 were measured in metastatic MM patients, treated with pembrolizumab.

RESULTS

By SPR, we demonstrated that Gal-3 can block the binding between PD-1 and pembrolizumab, and further visualized a steric inhibition using cryo-EM. T cells cultured with Gal-3 had reduced pro-inflammatory cytokine production, which could not be rescued by pembrolizumab. In patients with metastatic MM, high levels of Gal-3 in plasma were found in patients with a longer progression-free survival in the study period, whereas high Gal-3 expression in the tumor was seen in patients with disease progression. Soluble PD-1 levels in plasma increased after treatment with pembrolizumab and correlated with disease progression.

CONCLUSION

We demonstrate that the interaction between PD-1 and Gal-3 interferes with the binding of pembrolizumab, supporting that an immune suppression induced by Gal-3 in the tumor microenvironment cannot be rescued by pembrolizumab.

Early versus late response to PD-1-based immunotherapy in metastatic melanoma

BACKGROUND

Immune checkpoint inhibition (ICI) currently is the most effective treatment to induce durable responses in metastatic melanoma. The aims of this study are the characterization of patients with early, late and non-response to ICI and analysis of survival outcomes in a real-world patient cohort.

METHODS

Patients who received PD-1-based immunotherapy for non-resectable stage-IV melanoma in any therapy line were selected from the prospective multicenter real-world DeCOG study ADOREG-TRIM (NCT05750511). Patients showing complete (CR) or partial (PR) response already during the first 3 months of treatment (Early Responders, EarlyR) were compared to patients showing CR/PR at a later time (Late Responders, LateR), a stable disease (SD) and to patients showing progressive disease (Non-Responders, NonR).

RESULTS

Of 522 patients, 8.2 % were EarlyR (n = 43), 19.0 % were LateR (n = 99), 37.0 % had a SD (n = 193) and 35.8 % were NonR (n = 187). EarlyR, LateR and SD patients had comparable baseline characteristics. Multivariate logbinomial regression analyses adjusted for age and sex revealed positive tumor PD-L1 (RR=1.99, 95 %-CI=1.14-3.46, p = 0.015), and normal serum CRP (RR=1.59, 95 %-CI=0.93-2.70, p = 0.036) as independently associated with the achievement of an early response compared to NonR. The median progression-free and overall survival was 46.0 months (95 % CI 19.1; NR) and 47.8 months (95 %-CI 36.9; NR) for EarlyR, NR (95 %-CI NR; NR) for LateR, 8.1 months (7.0; 10.4) and 35.4 months (29.2; NR) for SD, and 2.0 months (95 %-CI 1.9; 2.1) and 6.1 months (95 %-CI 4.6; 8.8) for NonR patients.

CONCLUSION

Less than 10 % of metastatic melanoma patients achieved an early response during the first 3 months of PD-1-based immunotherapy. Early responders were not superior to late responders in terms of response durability and survival.

Differential predictive value of tissue-specific PD-L1 expression scores in adjuvant immunotherapy of melanoma

BACKGROUND

Adjuvant treatment of stage II-IV melanoma with PD-1-based immune checkpoint inhibitors (ICI) has improved relapse-free survival (RFS) and has therefore become a standard-of-care treatment option. Approximately 25%-30% of patients still recur within 1 year. Predictive biomarkers reflecting real-world data are desired. The predictive relevance of tumour tissue PD-L1 expression in the adjuvant setting remains inconclusive.

OBJECTIVES

This retrospective, observational study was conducted to evaluate the value of PD-L1 expression scores in different tumour tissue locations in predicting response towards adjuvant immunotherapeutic treatment.

METHODS

Tumour tissue taken prior to anti-PD-1 adjuvant ICI in 243 stage II-IV melanoma patients was collected at University Skin Cancer Center Hamburg. PD-L1 expression was evaluated on immune cells (ICS), tumour cells (TPS) and combined (CPS). Scores were determined by independent pathological physician quantification and correlated with therapy outcome at different cut-off (CO) levels (relapse-free survival, RFS) for different tumour tissue locations (primary tumour, metastases).

RESULTS

A total of 104 patients were eligible for analysis. Positivity of ICS, TPS and CPS showed no predictive RFS outcome association at different CO levels when analysed irrespective of tissue origin. In primary tumours, ICS at CO 1% showed a significantly improved RFS upon positivity (HR 0.22). In contrast, positivity to TPS (CO 1%) correlated significantly and independently with improved RFS when evaluated in metastatic tumour tissue specimens (HR 0.37).

CONCLUSIONS

PD-L1 tumour tissue expression may serve as a predictive biomarker for adjuvant ICI treatment response stratification in melanoma, but caution should be spent on the origin of tumour tissue analysed. The cell-type relevant for the predictive value of PD-L1 expression is tissue-specific with immune cells being important in primary tumours while tumour cells are key in metastases. The present results should be validated in a multicentre cohort.

Evolutionary Trend Analysis of Research on Immunotherapy for Brain Metastasis Based on Machine-Learning Scientometrics

Brain metastases challenge cancer treatments with poor prognoses, despite ongoing advancements. Immunotherapy effectively alleviates advanced cancer, exhibiting immense potential to revolutionize brain metastasis management. To identify research priorities that optimize immunotherapies for brain metastases, 2164 related publications were analyzed. Scientometric visualization via R software, VOSviewer, and CiteSpace showed the interrelationships among literature, institutions, authors, and topic areas of focus. The publication rate and citations have grown exponentially over the past decade, with the US, China, and Germany as the major contributors. The University of Texas MD Anderson Cancer Center ranked highest in publications, while Memorial Sloan Kettering Cancer Center was most cited. Clusters of keywords revealed six hotspots: 'Immunology', 'Check Point Inhibitors', 'Lung Cancer', 'Immunotherapy', 'Melanoma', 'Breast Cancer', and 'Microenvironment'. Melanoma, the most studied primary tumor with brain metastases offers promising immunotherapy advancements with generalizability and adaptability to other cancers. Our results outline the holistic overview of immunotherapy research for brain metastases, which pinpoints the forefront in the field, and directs researchers toward critical inquiries for enhanced mechanistic insight and improved clinical outcomes. Moreover, governmental and funding agencies will benefit from assigning financial resources to entities and regions with the greatest potential for combating brain metastases through immunotherapy.

A novel molecular subtyping based on multi-omics analysis for prognosis predicting in colorectal melanoma: A 16-year prospective multicentric study

Colorectal melanoma (CRM) is a rare malignant tumor with severe complications, and there is currently a lack of systematic research. We conducted a study that combined proteomics and mutation data of CRM from a cohort of three centers over a 16-years period (2005-2021). The patients were divided into a training set consisting of two centers and a testing set comprising the other center. Unsupervised clustering was conducted on the training set to form two molecular subtypes for clinical characterization and functional analysis. The testing set was used to validate the survival differences between the two subtypes. The comprehensive analysis identified two subtypes of CRM: immune exhausted C1 cluster and DNA repair C2 cluster. The former subtype exhibited characteristics of metabolic disturbance, immune suppression, and poor prognosis, along with APC mutations. A machine learning algorithm named Support Vector Machine (SVM) was applied to predict the classification of CRM patients based on protein expression in the external testing cohort. Two subtypes of primary CRM with clinical and proteomic characteristics provides a reference for subsequent diagnosis and treatments.

The outcome in patients with BRAF-mutated metastatic melanoma treated with anti-programmed death receptor-1 monotherapy or targeted therapy in the real-world setting

BACKGROUND

Immunotherapy and targeted therapy are currently two alternative backbones in the therapy of BRAF-mutated malignant melanoma. However, predictive biomarkers that would help with treatment selection are lacking.

METHODS

This retrospective study investigated outcomes of anti-programmed death receptor-1 monotherapy and targeted therapy in the first-line setting in patients with metastatic BRAF-mutated melanoma, focusing on clinical and laboratory parameters associated with treatment outcome.

RESULTS

Data from 174 patients were analysed. The median progression-free survival (PFS) was 17.0 months (95% CI; 8-39) and 12.5 months (95% CI; 9-14.2) for immunotherapy and targeted therapy, respectively. The 3-year PFS rate was 39% for immunotherapy and 25% for targeted therapy. The objective response rate was 72% and 51% for targeted therapy and immunotherapy. The median overall (OS) survival for immunotherapy has not been reached and was 23.6 months (95% CI; 16.1-38.2) for targeted therapy, with a 3-year survival rate of 63% and 40%, respectively. In a univariate analysis, age < 70 years, a higher number of metastatic sites, elevated serum LDH and a neutrophil-lymphocyte ratio above the cut-off value were associated with inferior PFS regardless of the therapy received, but only serum LDH level and the presence of lung metastases remained significant predictors of PFS in a multivariate analysis.

CONCLUSIONS

Present real-world data document the high effectiveness of immunotherapy and targeted therapy. Although targeted therapy had higher response rates, immunotherapy improved PFS and OS. While the prognostic value of LDH was confirmed, the potential use of blood cell count-derived parameters to predict outcomes needs further investigation.

PD-L1 is a biomarker of real-world clinical outcomes for anti-CTLA-4 plus anti-PD-1 or anti-PD-1 monotherapy in metastatic melanoma

BACKGROUND

Metastatic melanoma (MM) is commonly treated with a combination of nivolumab and ipilimumab, regardless of tumor PD-L1 expression.

METHODS

We conducted a population-based study including all patients with MM (except ocular melanoma) treated in Denmark with first-line combination therapy or anti-PD-1 monotherapy since January 2017. Baseline data including known prognostic characteristics were used in multivariable and propensity-matched score (PMS) analyses to assess progression-free survival (PFS), melanoma-specific survival (MSS), and overall survival (OS) according to PD-L1 expression.

RESULTS

We identified 1341 eligible patients, with known PD-L1 status for 1081 patients (43% PD-L1 ≥ 1%, 57% PD-L1 < 1%). PD-L1 ≥ 1% was an independent positive prognostic biomarker for survival in the overall cohort (MSS: HR 0.66, CI 0.52-0.83, p < 0.001). In the PMS PD-L1 ≥ 1% cohort, combination therapy showed similar clinical outcomes to monotherapy (PFS: HR 1.41, CI 0.94-2.11, p = 0.101; MSS: HR 1.21, CI 0.70-2.11, p = 0.49; OS: HR 1.17, CI 0.68-2.00, p = 0.567). In contrast, in the PMS PD-L1 < 1% and in the PMS PD-L1 < 1% BRAF WT cohorts, combination therapy improved PFS (respectively with HR 0.70, CI 0.53-0.93, p = 0.013; and HR 0.54, CI 0.37-0.78, p = 0.001), but did not reach statistically significant improvements of MSS (HR 0.72, CI 0.50-1.02, p = 0.065; and HR 0.79, CI 0.51-1.21, p = 0.278) or OS (HR 0.78, CI 0.56-1.08, p = 0.135; and HR 0.81, CI 0.54-1.21, p = 0.305) compared to monotherapy.

CONCLUSION

Our findings support previous exploratory analyses of Checkmate-067, highlighting that improved clinical outcomes with combination therapy are not established in unselected patients with high (≥1%) tumor PD-L1 expression.

Salmonella-mediated methionine deprivation drives immune activation and enhances immune checkpoint blockade therapy in melanoma

BACKGROUND

Although immune checkpoint inhibitor (ICI)-based therapy is advantageous for patients with advanced melanoma, resistance and relapse are frequent. Thus, it is crucial to identify effective drug combinations and develop new therapies for the treatment of melanoma. SGN1, a genetically modified Salmonella typhimurium species that causes the targeted deprivation of methionine in tumor tissues, is currently under investigation in clinical trials. However, the inhibitory effect of SGN1 on melanoma and the benefits of SGN1 in combination with ICIs remain largely unexplored. Therefore, this study aims to investigate the antitumor potential of SGN1, and its ability to enhance the efficacy of antibody-based programmed cell death-ligand 1 (PD-L1) inhibitors in the treatment of murine melanoma.

METHODS

The antitumor activity of SGN1 and the effect of SGN1 on the efficacy of PD-L1 inhibitors was studied through murine melanoma models. Further, The Cancer Genome Atlas-melanoma cohort was clustered using ConsensusClusterPlus based on the methionine deprivation-related genes, and immune characterization was performed using xCell, Microenvironment Cell Populations-counter, Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data, and immunophenoscore (IPS) analyses. The messenger RNA data on programmed death-1 (PD-1) immunotherapy response were obtained from the Gene Expression Omnibus database. Gene Set Enrichment Analysis of methionine deprivation-up gene set was performed to determine the differences between pretreatment responders and non-responders.

RESULTS

This study showed that both, the intratumoral and the intravenous administration of SGN1 in subcutaneous B16-F10 melanomas, suppress tumor growth, which was associated with an activated CD8+T-cell response in the tumor microenvironment. Combination therapy of SGN1 with systemic anti-PD-L1 therapy resulted in better antitumor activity than the individual monotherapies, respectively, and the high therapeutic efficacy of the combination was associated with an increase in the systemic level of tumor-specific CD8+ T cells. Two clusters consisting of methionine deprivation-related genes were identified. Patients in cluster 2 had higher expression of methionine_deprivation_up genes, better clinical outcomes, and higher immune infiltration levels compared with patients in cluster 1. Western blot, IPS analysis, and immunotherapy cohort study revealed that methionine deficiency may show a better response to ICI therapy CONCLUSIONS：: This study reports Salmonella-based SGN1 as a potent anticancer agent against melanoma, and lays the groundwork for the potential synergistic effect of ICIs and SGN1 brought about by improving the immune microenvironment in melanomas.

Programmed Cell Death Ligand 1 Immunohistochemical Expression and Cutaneous Melanoma: A Controversial Relationship

Cutaneous melanoma (CM) is traditionally considered one of the most "immunogenic" tumors, eliciting a high immune response. However, despite the presence of tumor-infiltrating lymphocytes (TILs), melanoma cells use strategies to suppress antitumor immunity and avoid being eliminated by immune surveillance. The PD-1 (programmed death-1)/PD-L1 (programmed death-ligand 1) axis is a well-known immune escape system adopted by neoplastic cells. Therefore, immunotherapy with PD-1 and PD-L1 inhibitors is quickly becoming the main treatment approach for metastatic melanoma patients. However, the clinical utility of PD-L1 expression assessment in CM is controversial, and the interpretation of PD-L1 scores in clinical practice is still a matter of debate. Nonetheless, the recent literature data show that by adopting specific PD-L1 assessment methods in melanoma samples, a correlation between the expression of such a biomarker and a positive response to PD-1-based immunotherapy can be seen. Our review aims to describe the state-of-the-art knowledge regarding the prognostic and predictive role of PD-L1 expression in CM while also referring to possible biological explanations for the variability in its expressions and related treatment responses.

Predictive Factors in Metastatic Melanoma Treated with Immune Checkpoint Inhibitors: From Clinical Practice to Future Perspective

The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.