RESUMO
PURPOSE: By utilizing both protein and mRNA expression patterns, we can identify more detailed and diverse immune cells, providing insights into understanding the complex immune landscape in cancer ecosystems. MATERIALS AND METHODS: This study was performed by obtaining publicly available Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus database. A total of 94674 total cells were analyzed, of which 32412 were T cells. There were 228 protein features and 16262 mRNA features in the data. The Seurat package was used for quality control and preprocessing, principal component analysis was performed, and Uniform Manifold Approximation and Projection was used to visualize the clusters. Protein and mRNA levels in the CITE-seq were analyzed. RESULTS: We observed that a subset of T cells in the clusters generated at the protein level divided better. By identifying mRNA markers that were highly correlated with the CD4 and CD8 proteins and cross-validating CD26 and CD99 markers using flow cytometry, we found that CD4+ and CD8+ T cells were better discriminated in PBMCs. Weighted Nearest Neighbor clustering results identified a previously unobserved T cell subset. CONCLUSION: In this study, we used CITE-seq data to confirm that protein expression patterns could be used to identify cells more precisely. These findings will improve our understanding of the heterogeneity of immune cells in the future and provide valuable insights into the complexity of the immune response in health and disease.
Assuntos
Transcriptoma , Humanos , Linfócitos T CD8-Positivos/metabolismo , Linfócitos T CD8-Positivos/imunologia , Leucócitos Mononucleares/metabolismo , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Linfócitos T CD4-Positivos/metabolismo , Perfilação da Expressão Gênica/métodos , Linfócitos T/metabolismo , Linfócitos T/imunologia , Epitopos/genética , Epitopos/imunologiaRESUMO
Immune checkpoint inhibitors are effective first-line therapy for solid cancers. However, low response rate and acquired resistance over time has led to the need for additional therapeutic options. Here, we evaluated synergistic antitumor efficacy of EGFR × MET targeting bispecific antibody, amivantamab with PD-L1 immunotherapy, pembrolizumab in head and neck squamous cell carcinoma (HNSCC) and lung squamous cell carcinoma tumor-bearing humanized patient-derived xenograft (PDX) models. We demonstrated that pembrolizumab or amivantamab alone was ineffective and that combination treatment induced a significant reduction of tumor growth in both models (P < 0.0001 and P < 0.01, respectively). It appeared that combination of amivantamab and pembrolizumab significantly enhanced infiltration of granzyme B-producing CD8 T cells was in the TME of HNSCC PDX (P < 0.01) and enhanced neoantigen-associated central memory CD8 T cells in circulating immune cells. Analysis of single-cell RNA transcriptomics suggested that the tumor cells dramatically upregulated EGFR and MET in response to PD-L1 immunotherapy, potentially creating a metabolic state fit for tumor persistence in the tumor microenvironment (TME) and rendered pembrolizumab ineffective. We demonstrated that EGFRHIGHMETHIGH subcluster displayed an increased expression of genes implicated in production of lactate [SLC16A3 and lactate dehydrogenase A (LDHA)] compared to the EGFRLOWMETLOW cluster. Accumulation of lactate in the TME has been associated with immunosuppression by hindering the infiltration of tumor killing CD8 T and NK cells. This study proved that amivantamab reduced glycolytic markers in the EGFRHIGHMETHIGH subcluster including SLC16A3 and LDHA and highlighted remodeling of the TME by combination treatment, providing rationale for additional therapy of amivantamab with PD-1 immunotherapy. SIGNIFICANCE: Amivantamab in synergy with pembrolizumab effectively eradicated EGFRHIGHMETHIGH tumor subcluster in the tumor microenvironment of head and neck squamous cell carcinoma and overcame resistance against anti-PD-1 immunotherapy.
Assuntos
Anticorpos Monoclonais Humanizados , Neoplasias Pulmonares , Carcinoma de Células Escamosas de Cabeça e Pescoço , Microambiente Tumoral , Humanos , Anticorpos Monoclonais Humanizados/farmacologia , Anticorpos Monoclonais Humanizados/uso terapêutico , Anticorpos Monoclonais Humanizados/administração & dosagem , Carcinoma de Células Escamosas de Cabeça e Pescoço/tratamento farmacológico , Carcinoma de Células Escamosas de Cabeça e Pescoço/imunologia , Carcinoma de Células Escamosas de Cabeça e Pescoço/patologia , Animais , Camundongos , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/imunologia , Microambiente Tumoral/efeitos dos fármacos , Microambiente Tumoral/imunologia , Neoplasias de Cabeça e Pescoço/tratamento farmacológico , Neoplasias de Cabeça e Pescoço/patologia , Neoplasias de Cabeça e Pescoço/imunologia , Ensaios Antitumorais Modelo de Xenoenxerto , Protocolos de Quimioterapia Combinada Antineoplásica/farmacologia , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Inibidores de Checkpoint Imunológico/farmacologia , Inibidores de Checkpoint Imunológico/uso terapêutico , Linfócitos T CD8-Positivos/efeitos dos fármacos , Linfócitos T CD8-Positivos/imunologia , Antígeno B7-H1/metabolismo , Linhagem Celular TumoralRESUMO
Introduction: Aryl hydrocarbon receptor (AhR) is a transcription factor that performs various functions upon ligand activation. Several studies have explored the role of AhR expression in tumor progression and immune surveillance. Nevertheless, investigations on the distribution of AhR expression, specifically in cancer or immune cells in the tumor microenvironment (TME), remain limited. Examining the AhR expression and distribution in the TME is crucial for gaining insights into the mechanism of action of AhR-targeting anticancer agents and their potential as biomarkers. Methods: Here, we used multiplexed immunohistochemistry (mIHC) and image cytometry to investigate the AhR expression and distribution in 513 patient samples, of which 292 are patients with one of five solid cancer types. Additionally, we analyzed the nuclear and cytosolic distribution of AhR expression. Results: Our findings reveal that AhR expression was primarily localized in cancer cells, followed by stromal T cells and macrophages. Furthermore, we observed a positive correlation between the nuclear and cytosolic expression of AhR, indicating that the expression of AhR as a biomarker is independent of its localization. Interestingly, the expression patterns of AhR were categorized into three clusters based on the cancer type, with high AhR expression levels being found in regulatory T cells (Tregs) in non-small cell lung cancer (NSCLC). Discussion: These findings are anticipated to serve as pivotal evidence for the design of clinical trials and the analysis of the anticancer mechanisms of AhR-targeting therapies.
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Neoplasias , Receptores de Hidrocarboneto Arílico , Microambiente Tumoral , Receptores de Hidrocarboneto Arílico/metabolismo , Humanos , Microambiente Tumoral/imunologia , Neoplasias/imunologia , Neoplasias/metabolismo , Neoplasias/patologia , Biomarcadores Tumorais/metabolismo , Fatores de Transcrição Hélice-Alça-Hélice Básicos/metabolismoRESUMO
Introduction: To understand the immune system within the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC), it is crucial to elucidate the characteristics of molecules associated with T cell activation. Methods: We conducted an in-depth analysis using single-cell RNA sequencing data obtained from tissue samples of 19 NSCLC patients. T cells were classified based on the Tumor Proportion Score (TPS) within the tumor region, and molecular markers associated with activation and exhaustion were analyzed in T cells from high TPS areas. Results: Notably, tetraspanins CD81 and CD82, belonging to the tetraspanin protein family, were found to be expressed in activated T cells, particularly in cytotoxic T cells. These tetraspanins showed strong correlations with activation and exhaustion markers. In vitro experiments confirmed increased expression of CD81 and CD82 in IL-2-stimulated T cells. T cells were categorized into CD81highCD82high and CD81lowCD82low groups based on their expression levels, with CD81highCD82high T cells exhibiting elevated activation markers such as CD25 and CD69 compared to CD81lowCD82low T cells. This trend was consistent across CD3+, CD8+, and CD4+ T cell subsets. Moreover, CD81highCD82high T cells, when stimulated with anti-CD3, demonstrated enhanced secretion of cytokines such as IFN-γ, TNF-α, and IL-2, along with an increase in the proportion of memory T cells. Bulk RNA sequencing results after sorting CD81highCD82high and CD81lowCD82low T cells consistently supported the roles of CD81 and CD82. Experiments with overexpressed CD81 and CD82 showed increased cytotoxicity against target cells. Discussion: These findings highlight the multifaceted roles of CD81 and CD82 in T cell activation, cytokine production, memory subset accumulation, and target cell cytolysis. Therefore, these findings suggest the potential of CD81 and CD82 as promising candidates for co-stimulatory molecules in immune therapeutic strategies for cancer treatment within the intricate TME.
Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Carcinoma Pulmonar de Células não Pequenas/metabolismo , Antígenos CD/metabolismo , Linfócitos do Interstício Tumoral , Interleucina-2/metabolismo , Microambiente Tumoral , Neoplasias Pulmonares/metabolismo , Citocinas/metabolismo , Tetraspaninas/metabolismo , Tetraspanina 28 , Proteína Kangai-1/metabolismoRESUMO
(1) Background: This study investigated whether polo-like kinase 4 (PLK4) is a suitable therapeutic target or biomarker for lung adenocarcinoma (LUAD). (2) Methods: We acquired LUAD data from The Cancer Genome Atlas (TCGA) database through the UCSC Xena data portal. Gene expression, clinical, survival, and mutation data from multiple samples were analyzed. Gene enrichment analysis, unsupervised clustering of PLK4-related pathways, and differential gene expression analyses were performed. Additionally, correlations, t-tests, survival analyses, and statistical analyses were performed. (3) Results: PLK4 expression was higher in LUAD tissues than in normal tissues and was associated with poor prognosis for both overall and progression-free survival in LUAD. PLK4 was highly correlated with cell-proliferation-related pathways using Gene Ontology (GO) biological process terms. PLK4 expression and pathways that were highly correlated with PLK4 expression levels were upregulated in patients with LUAD with the TP53 mutation. (4) Conclusions: PLK4 expression affects the survival of patients with LUAD and is a potential therapeutic target for LUAD with TP53 mutations.