PD-L1 Tumor Expression as a Predictive Biomarker of Immune Checkpoint Inhibitors’ Response and Survival in Advanced Melanoma Patients in Brazil

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.

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.

Comparative Analysis of Inhibitory and Activating Immune Checkpoints PD-1, PD-L1, CD28, and CD86 in Non-Melanoma Skin Cancer

The establishment of immunotherapy applying immune checkpoint inhibitors (ICI) has provided an important new option for the treatment of solid malignant diseases. However, different tumor entities show dramatically different responses to this therapy. BCC responds worse to anti-PD-1 ICIs as compared to cSCC. Differential immune checkpoint expression could explain this discrepancy and, therefore, the aim of this study was to analyze activating and inhibitory immune checkpoints in cSCC and BCC tissues. Tissue microarrays of the invasive front as well as the tumor core of BCC and cSCC samples were used to evaluate PD-1, PD-L1, CD28, and CD86 expression and their topographic distribution profiles by chromogenic immunohistochemistry. QuPath was used to determine the labeling index. The expression of PD-1, PD-L1, and CD28 was significantly higher in both the tumor core and the invasive front of cSCC samples as compared to BCC (p < 0.001). In addition, the ratios of PD-L1/CD86 (p < 0.001) and CD28/CD86 (p < 0.001) were significantly higher in cSCC. The invasive front of both tumor entities showed higher expression levels of all immune markers compared to the tumor core in both tumor entities. The significantly higher expression of PD-1, PD-L1, and CD28 in cSCC, along with the predominance of the inhibitory ligand PD-L1 as compared to the activating CD86 in cSCC, provide a potential explanation for the better objective response rates to anti-PD-1 immunotherapy as compared to BCC. Furthermore, the predominant site of interaction between the immune system and the tumor was within the invasive front in both tumor types.

Advances in Melanoma: From Genetic Insights to Therapeutic Innovations

Advances in melanoma research have unveiled critical insights into its genetic and molecular landscape, leading to significant therapeutic innovations. This review explores the intricate interplay between genetic alterations, such as mutations in BRAF, NRAS, and KIT, and melanoma pathogenesis. The MAPK and PI3K/Akt/mTOR signaling pathways are highlighted for their roles in tumor growth and resistance mechanisms. Additionally, this review delves into the impact of epigenetic modifications, including DNA methylation and histone changes, on melanoma progression. The tumor microenvironment, characterized by immune cells, stromal cells, and soluble factors, plays a pivotal role in modulating tumor behavior and treatment responses. Emerging technologies like single-cell sequencing, CRISPR-Cas9, and AI-driven diagnostics are transforming melanoma research, offering precise and personalized approaches to treatment. Immunotherapy, particularly immune checkpoint inhibitors and personalized mRNA vaccines, has revolutionized melanoma therapy by enhancing the body's immune response. Despite these advances, resistance mechanisms remain a challenge, underscoring the need for combined therapies and ongoing research to achieve durable therapeutic responses. This comprehensive overview aims to highlight the current state of melanoma research and the transformative impacts of these advancements on clinical practice.

SPP1 could be an immunological and prognostic biomarker: From pan-cancer comprehensive analysis to osteosarcoma validation

Secreted phosphoprotein 1 (SPP1), also known as osteopontin, is a phosphorylated protein. High SPP1 expression levels have been detected in multiple cancers and are associated with poor prognosis and reduced survival rates. However, only a few pan-cancer analyses have targeted SPP1. We conducted a comprehensive analysis using multiple public databases, including TIMER and TCGA, to investigate the expression levels of SPP1 in 33 different tumor types. In addition, we verified the effect of SPP1 on osteosarcoma. To assess the impact of SPP1 on patient outcomes, we employed univariate Cox regression and Kaplan-Meier survival analyses to analyze overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in these tumor patients. We also explored SPP1 gene alterations in various tumor tissues using cBioPortal. We then examined the relationship between SPP1 and clinical characteristics, TME, immune regulatory genes, immune checkpoints, TMB, and MSI using R language. In addition, we used GSEA to investigate the molecular mechanisms underlying the role of SPP1. Bioinformatics analysis indicated that SPP1 was upregulated in 17 tumors. Overexpression of SPP1 results in poor OS, DSS, and PFI in CESC, ESCA, GBM, LGG, LIHC, PAAD, PRAD, and skin cutaneous melanoma. SPP1 expression was positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, and drug sensitivity in certain cancers. We found that high expression of SPP1 in osteosarcoma was related to drug resistance and metastasis and further demonstrated that SPP1 can stimulate osteosarcoma cell proliferation via CCND1 by activating the PI3K/Akt pathway. These findings strongly suggest that SPP1 is a potential prognostic marker and novel target for cancer immunotherapy.

Metabolomics reveals ascorbic acid inhibits ferroptosis in hepatocytes and boosts the effectiveness of anti-PD1 immunotherapy in hepatocellular carcinoma

BACKGROUND

Immunotherapy combined with molecular targeted therapy is increasingly popular in patients with advanced hepatocellular carcinoma (HCC). However, immune-related adverse events(irAEs) brought on by immunotherapy increase the likelihood of side effects, thus it is important to look into ways to address this issue.

METHODS

Different metabolite patterns were established by analyzing metabolomics data in liver tissue samples from 10 patients(divided into severe and mild liver injury) before and after immuno-targeted therapy. After establishing a subcutaneous tumor model of HCC, the mice were divided into PBS group, ascorbic acid(AA) group, and anti-PD1 + tyrosine kinase inhibitor (TKI) group, anti-PD1 + TKI + AA group. Liver tissue were stained with hematoxylin-eosin staining(HE) and the content of aspartate transaminase (AST) and alanine transaminase(ALT) in blood were determined. The mechanism was confirmed by western blotting, mass cytometry, and other techniques.

RESULTS

Through metabolomics analysis, AA was significantly reduced in the sample of patients with severe liver injury caused by immuno-targeted therapy compared to patients with mild liver injury. The addition of AA in vivo experiments demonstrated a reduction in liver injury in mice. In the liver tissues of the anti-PD1 + TKI + AA group, the protein expressions of SLC7A11,GPX4 and the level of glutathione(GSH) were found to be higher compared to the anti-PD1 + TKI group. Mass cytometry analysis revealed a significant increase in the CD11b+CD44+ PD-L1+ cell population in the AA group when compared to the PBS group.

CONCLUSIONS

AA could reduce liver injury by preventing hepatocyte SLC7A11/GPX4 ferroptosis and improve the immunotherapy effect of anti-PD1 by boosting CD11b+CD44+PD-L1+cell population in HCC.

Synergistic Immunoregulation: harnessing CircRNAs and PiRNAs to Amplify PD-1/PD-L1 Inhibition Therapy

The utilization of PD-1/PD-L1 inhibitors marks a significant advancement in cancer therapy. However, the efficacy of monotherapy is still disappointing in a substantial subset of patients, necessitating the exploration of combinational strategies. Emerging from the promising results of the KEYNOTE-942 trial, RNA-based therapies, particularly circRNAs and piRNAs, have distinguished themselves as innovative sensitizers to immune checkpoint inhibitors (ICIs). These non-coding RNAs, notable for their stability and specificity, were once underrecognized but are now known for their crucial roles in regulating PD-L1 expression and bolstering anti-cancer immunity. Our manuscript offers a comprehensive analysis of selected circRNAs and piRNAs, elucidating their immunomodulatory effects and mechanisms, thus underscoring their potential as ICIs enhancers. In conjunction with the recent Nobel Prize-awarded advancements in mRNA vaccine technology, our review highlights the transformative implications of these findings for cancer treatment. We also discuss the prospects of circRNAs and piRNAs in future therapeutic applications and research. This study pioneers the synergistic application of circRNAs and piRNAs as novel sensitizers to augment PD-1/PD-L1 inhibition therapy, demonstrating their unique roles in regulating PD-L1 expression and modulating immune responses. Our findings offer a groundbreaking approach for enhancing the efficacy of cancer immunotherapy, opening new avenues for treatment strategies. This abstract aims to encapsulate the essence of our research and the burgeoning role of these non-coding RNAs in enhancing PD-1/PD-L1 inhibition therapy, encouraging further investigation into this promising field.

DRG2 is required for surface localization of PD-L1 and the efficacy of anti-PD-1 therapy

More than half of tumor patients with high PD-L1 expression do not respond to anti-PD-1/PD-L1 therapy, and the underlying mechanisms are yet to be clarified. Here we show that developmentally regulated GTP-binding protein 2 (DRG2) is required for response of PD-L1-expressing tumors to anti-PD-1 therapy. DRG2 depletion enhanced IFN-γ signaling and increased the PD-L1 level in melanoma cells. However, it inhibited recycling of endosomal PD-L1 and reduced surface PD-L1 levels, which led to defects in interaction with PD-1. Anti-PD-1 did not expand effector-like T cells within DRG2-depleted tumors and failed to improve the survival of DRG2-depleted tumor-bearing mice. Cohort analysis revealed that patients bearing melanoma with low DRG2 protein levels were resistant to anti-PD-1 therapy. These findings identify DRG2 as a key regulator of recycling of endosomal PD-L1 and response to anti-PD-1 therapy and provide insights into how to increase the correlation between PD-L1 expression and response to anti-PD-1 therapy.

Refining mutanome-based individualised immunotherapy of melanoma using artificial intelligence

Using the particular nature of melanoma mutanomes to develop medicines that activate the immune system against specific mutations is a game changer in immunotherapy individualisation. It offers a viable solution to the recent rise in resistance to accessible immunotherapy alternatives, with some patients demonstrating innate resistance to these drugs despite past sensitisation to these agents. However, various obstacles stand in the way of this method, most notably the practicality of sequencing each patient's mutanome, selecting immunotherapy targets, and manufacturing specific medications on a large scale. With the robustness and advancement in research techniques, artificial intelligence (AI) is a potential tool that can help refine the mutanome-based immunotherapy for melanoma. Mutanome-based techniques are being employed in the development of immune-stimulating vaccines, improving current options such as adoptive cell treatment, and simplifying immunotherapy responses. Although the use of AI in these approaches is limited by data paucity, cost implications, flaws in AI inference capabilities, and the incapacity of AI to apply data to a broad population, its potential for improving immunotherapy is limitless. Thus, in-depth research on how AI might help the individualisation of immunotherapy utilising knowledge of mutanomes is critical, and this should be at the forefront of melanoma management.