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

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.

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.