Validation of an Accurate Automated Multiplex Immunofluorescence Method for Immuno-Profiling Melanoma

Multi-Tissue Controls and Multiplex Immunocytochemistry in Pulmonary Cytology

INTRODUCTION

The World Health Organization 2021 lung cancer classification highlights the central role of immunohistochemistry (IHC) in diagnostic pathology. Despite traditional IHC being essential, its limitation to one marker per tissue section brings challenges, particularly when facing cytological limitedly sized samples. To overcome these challenges, multiplex immunocytochemistry (mICC) techniques offer the simultaneous detection of multiple markers from a single section. These advances complement the highly complex imaging techniques that enable additional analyses of cellular interactions.

METHODS

The present study outlines a comprehensive mICC methodology of an automated multiplex immunoperoxidase staining method and multiple tissue hybrid controls for ICC/mICC. Protocols are presented in detail and demonstrate a careful approach to optimizing various markers for diagnostic workup including immunotherapy.

CONCLUSION

Multiplex IHC/ICC emerges as a transformative force in biomedical diagnostics and research. Beyond simultaneous marker detection, it unravels complexities within tissues - unveiling co-localization nuances, deciphering expression patterns, and enhancing understanding of cellular populations. As personalized treatments gain prominence, the study emphasizes the heightened importance of diagnostic tools and sample adequacy. The present methodological study, encapsulating an automated multiplex immunoperoxidase staining method, symbolizes a stride towards precision in pulmonary carcinoma diagnosis. Multi-tissue controls represent a key element in quality assurance in pathology laboratories.

Current status and progress of PD-L1 detection: guiding immunotherapy for non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths and represents a substantial disease burden worldwide. Immune checkpoint inhibitors combined with chemotherapy are the standard first-line therapy for advanced NSCLC without driver mutations. Programmed death-ligand 1 (PD-L1) is currently the only approved immunotherapy marker. PD-L1 detection methods are diverse and have developed rapidly in recent years, such as improved immunohistochemical detection methods, the application of liquid biopsy in PD-L1 detection, genetic testing, radionuclide imaging, and the use of machine learning methods to construct PD-L1 prediction models. This review focuses on the detection methods and challenges of PD-L1 from different sources, and discusses the influencing factors of PD-L1 detection and the value of combined biomarkers. Provide support for clinical screening of immunotherapy-advantage groups and formulation of personalized treatment decisions.

Quantitative performance assessment of Ultivue multiplex panels in formalin-fixed, paraffin-embedded human and murine tumor specimens

We present a rigorous validation strategy to evaluate the performance of Ultivue multiplex immunofluorescence panels. We have quantified the accuracy and precision of four different multiplex panels (three human and one mouse) in tumor specimens with varying levels of T cell density. Our results show that Ultivue panels are typically accurate wherein the relative difference in cell proportion between a multiplex image and a 1-plex image is less than 20% for a given biomarker. Ultivue panels exhibited relatively high intra-run precision (CV ≤ 25%) and relatively low inter-run precision (CV >> 25%) which can be remedied by using local intensity thresholding to gate biomarker positivity. We also evaluated the reproducibility of cell-cell distance estimates measured from multiplex images which show high intra- and inter-run precision. We introduce a new metric, multiplex labeling efficiency, which can be used to benchmark the overall fidelity of the multiplex data across multiple batch runs. Taken together our results provide a comprehensive characterization of Ultivue panels and offer practical guidelines for analyzing multiplex images.

Stroma-infiltrating T cell spatiotypes define immunotherapy outcomes in adolescent and young adult patients with melanoma

The biological underpinnings of therapeutic resistance to immune checkpoint inhibitors (ICI) in adolescent and young adult (AYA) melanoma patients are incompletely understood. Here, we characterize the immunogenomic profile and spatial architecture of the tumor microenvironment (TME) in AYA (aged ≤ 30 years) and older adult (aged 31-84 years) patients with melanoma, to determine the AYA-specific features associated with ICI treatment outcomes. We identify two ICI-resistant spatiotypes in AYA patients with melanoma showing stroma-infiltrating lymphocytes (SILs) that are distinct from the adult TME. The SILhigh subtype was enriched in regulatory T cells in the peritumoral space and showed upregulated expression of immune checkpoint molecules, while the SILlow subtype showed a lack of immune activation. We establish a young immunosuppressive melanoma score that can predict ICI responsiveness in AYA patients and propose personalized therapeutic strategies for the ICI-resistant subgroups. These findings highlight the distinct immunogenomic profile of AYA patients, and individualized TME features in ICI-resistant AYA melanoma that require patient-specific treatment strategies.

An update on methods for detection of prognostic and predictive biomarkers in melanoma

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient's disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.

Classification of the tumor immune microenvironment and associations with outcomes in patients with metastatic melanoma treated with immunotherapies

BACKGROUND

Tumor microenvironment (TME) characteristics are potential biomarkers of response to immune checkpoint inhibitors in metastatic melanoma. This study developed a method to perform unsupervised classification of TME of metastatic melanoma.

METHODS

We used multiplex immunohistochemical and quantitative pathology-derived assessment of immune cell compositions of intratumoral and peritumoral regions of metastatic melanoma baseline biopsies to classify TME in relation to response to anti-programmed cell death protein 1 (PD-1) monotherapy or in combination with anti-cytotoxic T-cell lymphocyte-4 (ipilimumab (IPI)+PD-1).

RESULTS

Spatial profiling of CD8+T cells, macrophages, and melanoma cells, as well as phenotypic PD-1 receptor ligand (PD-L1) and CD16 proportions, were used to identify and classify patients into one of three mutually exclusive TME classes: immune-scarce, immune-intermediate, and immune-rich tumors. Patients with immune-rich tumors were characterized by a lower proportion of melanoma cells and higher proportions of immune cells, including higher PD-L1 expression. These patients had higher response rates and longer progression-free survival (PFS) than those with immune-intermediate and immune-scarce tumors. At a median follow-up of 18 months (95% CI: 6.7 to 49 months), the 1-year PFS was 76% (95% CI: 64% to 90%) for patients with an immune-rich tumor, 56% (95% CI: 44% to 72%) for those with an immune-intermediate tumor, and 33% (95% CI: 23% to 47%) for patients with an immune-scarce tumor. A higher response rate was observed in patients with an immune-scarce or immune-intermediate tumor when treated with IPI+PD-1 compared with those treated with PD-1 alone.

CONCLUSIONS

Our study provides an automatic TME classification method that may predict the clinical efficacy of immunotherapy for patients with metastatic melanoma.

Exploring the Complex and Multifaceted Interplay between Melanoma Cells and the Tumor Microenvironment

Malignant melanoma is a very aggressive skin cancer, characterized by a heterogeneous nature and high metastatic potential. The incidence of melanoma is continuously increasing worldwide, and it is one of the most common cancers in young adults. In the past twenty years, our understanding of melanoma biology has increased profoundly, and disease management for patients with disseminated disease has improved due to the emergence of immunotherapy and targeted therapy. However, a significant fraction of patients relapse or do not respond adequately to treatment. This can partly be explained by the complex signaling between the tumor and its microenvironment, giving rise to melanoma phenotypes with different patterns of disease progression. This review focuses on the key aspects and complex relationship between pathogenesis, genetic abnormalities, tumor microenvironment, cellular plasticity, and metabolic reprogramming in melanoma. By acquiring a deeper understanding of the multifaceted features of melanomagenesis, we can reach a point of more individualized and patient-centered disease management and reduced costs of ineffective treatments.

Induction of IL-32 in the immune response of keratinocytes to Mycobacterium marinum infection

Keratinocytes are the predominant cell type in the skin epidermis, and they not only protect the skin from the influence of external physical factors but also function as an immune barrier against microbial invasion. However, little is known regarding the immune defence mechanisms of keratinocytes against mycobacteria. Here, we performed single-cell RNA sequencing (scRNA-seq) on skin biopsy samples from patients with Mycobacterium marinum infection and bulk RNA sequencing (bRNA-seq) on M. marinum-infected keratinocytes in vitro. The combined analysis of scRNA-seq and bRNA-seq data revealed that several genes were upregulated in M. marinum-infected keratinocytes. Further in vitro validation of these genes by quantitative polymerase chain reaction and western blotting assay confirmed the induction of IL-32 in the immune response of keratinocytes to M. marinum infection. Immunohistochemistry also showed the high expression of IL-32 in patients' lesions. These findings suggest that IL-32 induction is a possible mechanism through which keratinocytes defend against M. marinum infection; this could provide new targets for the immunotherapy of chronic cutaneous mycobacterial infections.

Recent advancements in tumour microenvironment landscaping for target selection and response prediction in immune checkpoint therapies achieved through spatial protein multiplexing analysis

Immune checkpoint therapies have significantly advanced cancer treatment. Nevertheless, the high costs and potential adverse effects associated with these therapies highlight the need for better predictive biomarkers to identify patients who are most likely to benefit from treatment. Unfortunately, the existing biomarkers are insufficient to identify such patients. New high-dimensional spatial technologies have emerged as a valuable tool for discovering novel biomarkers by analysing multiple protein markers at a single-cell resolution in tissue samples. These technologies provide a more comprehensive map of tissue composition, cell functionality, and interactions between different cell types in the tumour microenvironment. In this review, we provide an overview of how spatial protein-based multiplexing technologies have fuelled biomarker discovery and advanced the field of immunotherapy. In particular, we will focus on how these technologies contributed to (i) characterise the tumour microenvironment, (ii) understand the role of tumour heterogeneity, (iii) study the interplay of the immune microenvironment and tumour progression, (iv) discover biomarkers for immune checkpoint therapies (v) suggest novel therapeutic strategies.

Recent Advancement of PD-L1 Detection Technologies and Clinical Applications in the Era of Precision Cancer Therapy

Programmed death-1 is a protein found on the surface of immune cells that can interact with its ligand, programmed death-ligand 1 (PD-L1), which is expressed on the plasma membrane, the surface of secreted cellular exosomes, in cell nuclei, or as a circulating soluble protein. This interaction can lead to immune escape in cancer patients. In clinical settings, PD-L1 plays an important role in tumor disease diagnosis, determining therapeutic effectiveness, and predicting patient prognosis. PD-L1 inhibitors are also essential components of tumor immunotherapy. Thus, the detection of PD-L1 levels is crucial, especially in the era of precision cancer therapy. In recent years, innovations have been made in traditional immunoassay methods and the development of new immunoassays for PD-L1 detection. This review aims to summarize recent research progress in tumor PD-L1 detection technology and highlight the clinical applications of PD-L1.

Detailed spatial immunophenotyping of primary melanomas reveals immune cell subpopulations associated with patient outcome

While the tumor immune microenvironment (TIME) of metastatic melanoma has been well characterized, the primary melanoma TIME is comparatively poorly understood. Additionally, although the association of tumor-infiltrating lymphocytes with primary melanoma patient outcome has been known for decades, it is not considered in the current AJCC melanoma staging system. Detailed immune phenotyping of advanced melanoma has revealed multiple immune biomarkers, including the presence of CD8+ T-cells, for predicting response to immunotherapies. However, in primary melanomas, immune biomarkers are lacking and CD8+ T-cells have yet to be extensively characterized. As recent studies combining immune features and clinicopathologic characteristics have created more accurate predictive models, this study sought to characterize the TIME of primary melanomas and identify predictors of patient outcome. We first phenotyped CD8+ T cells in fresh stage II primary melanomas using flow cytometry (n = 6), identifying a CD39+ tumor-resident CD8+ T-cell subset enriched for PD-1 expression. We then performed Opal multiplex immunohistochemistry and quantitative pathology-based immune profiling of CD8+ T-cell subsets, along with B cells, NK cells, Langerhans cells and Class I MHC expression in stage II primary melanoma specimens from patients with long-term follow-up (n = 66), comparing patients based on their recurrence status at 5 years after primary diagnosis. A CD39+CD103+PD-1- CD8+ T-cell population (P2) comprised a significantly higher proportion of intratumoral and stromal CD8+ T-cells in patients with recurrence-free survival (RFS) ≥5 years vs those with RFS <5 years (p = 0.013). Similarly, intratumoral B cells (p = 0.044) and a significantly higher B cell density at the tumor/stromal interface were associated with RFS. Both P2 and B cells localized in significantly closer proximity to melanoma cells in patients who remained recurrence-free (P2 p = 0.0139, B cell p = 0.0049). Our results highlight how characterizing the TIME in primary melanomas may provide new insights into how the complex interplay of the immune system and tumor can modify the disease outcomes. Furthermore, in the context of current clinical trials of adjuvant anti-PD-1 therapies in high-risk stage II primary melanoma, assessment of B cells and P2 could identify patients at risk of recurrence and aid in long-term treatment decisions at the point of primary melanoma diagnosis.

Bright-Field Multiplex Immunohistochemistry Assay for Tumor Microenvironment Evaluation in Melanoma Tissues

Simple Summary

Bright-field (BF) immunohistochemistry (IHC) remains the gold standard for histopathological evaluations. The development of new BF multiplex IHC could be very useful for the study and characterization of the tumor microenvironment (TME) in melanoma samples. We herein compared different BF IHC multiplex protocols for the study of TME in primary cutaneous melanoma tissues and offered the best optimized protocol for visualization and evaluation. These methodologies are studied to maximize the quality of staining considering the tissue characteristics under examination, maintaining a high level of standardization and reproducibility.

Abstract

The tumor microenvironment (TME) plays a crucial role in melanoma development, progression and response to treatment. As many of the most relevant TME cell phenotypes are defined by the simultaneous detection of more than two markers, the bright-field (BF) multiplex immunohistochemistry (IHC) technique has been introduced for the quantitative assessment and evaluation of the relative spatial distances between immune cells and melanoma cells. In the current study, we aimed to validate BF multiplex IHC techniques in the Ventana Discovery Ultra Immunostainer to be applied to the evaluation of the TME in variably pigmented melanoma tissues. The BF multiplex IHC staining was performed using different combinations of six immune-cell markers—CD3, CD4, CD8, CD20, CD68 and CD163—and the melanoma cell marker SOX10. Our results show that the BF double IHC Yellow/Purple protocol guarantees the maximum contrast in all the cell populations tested and the combination SOX10 (Green), CD8 (Yellow) and CD163 (Purple) of the BF triple IHC protocol ensures the best contrast and discrimination between the three stained cell populations. Furthermore, the labeled cells were clearly distinct and easily identifiable using the image analysis software. Our standardized BF IHC multiplex protocols can be used to better assess the immune contexts of melanoma patients with potential applications to drive therapeutic decisions within clinical trials.