Spatial immunophenotyping of the tumour microenvironment in non-small cell lung cancer

Spatial distribution of tertiary lymphoid structures in the molecular and clinical context of non-small cell lung cancer

INTRODUCTION

Tertiary lymphoid structures (TLS) are lymphocyte aggregates resembling secondary lymphoid organs and are pivotal in cancer immunity. The ambiguous morphological definition of TLS makes it challenging to ascertain their clinical impact on patient survival and response to immunotherapy.

OBJECTIVES

This study aimed to characterize TLS in hematoxylin-eosin tissue sections from lung cancer patients, assessing their occurrence in relation to the local immune environment, mutational background, and patient outcome.

METHODS

Two pathologists evaluated one whole tissue section from resection specimens of 680 NSCLC patients. TLS were spatially quantified within the tumor area or periphery and further categorized based on the presence of germinal centers (mature TLS). Metrics were integrated with immune cell counts, genomic and transcriptomic data, and correlated with clinical parameters.

RESULTS

TLS were present in 86% of 536 evaluable cases, predominantly in the tumor periphery, with a median of eight TLS per case. Mature TLS were found in 24% of cases. TLS presence correlated positively with increased plasma cell (CD138+) and lymphocytic cell (CD3+, CD8+, FOXP3+) infiltration. Tumors with higher tumor mutational burden exhibited higher numbers of peripheral TLS. The overall TLS quantity was independently associated with improved patient survival, irrespective of TLS maturation status. This prognostic association held true for peripheral TLS but not for tumor TLS.

CONCLUSION

TLS in NSCLC is common and their correlation with a specific immune phenotype suggests biological relevance in the local immune reaction. The prognostic significance of this scoring system on routine hematoxylin-eosin sections has the potential to augment diagnostic algorithms for NSCLC patients.

Understanding the Dual Role of Macrophages in Tumor Growth and Therapy: A Mechanistic Review

Macrophages are heterogeneous cells that are the mediators of tissue homeostasis. These immune cells originated from monocytes and are classified into two basic categories, M1 and M2 macrophages. M1 macrophages exhibit anti-tumorous inflammatory reactions due to the behavior of phagocytosis. M2 macrophages or tumor-associated macrophages (TAMs) are the most abundant immune cells in the tumor microenvironment (TME) and have a basic role in tumor progression by interacting with other immune cells in TME. By the expression of various cytokines, chemokines, and growth factors, TAMs lead to strengthening tumor cell proliferation, angiogenesis, and suppression of the immune system which further support invasion and metastasis. This review discusses recent and updated mechanisms regarding tumor progression by M2 macrophages. Moreover, the current therapeutic approaches targeting TAMs, their advantages, and limitations are also summarized, and further treatment approaches are outlined along with an elaboration of the tumor regression role of macrophages. This comprehensive review article possibly helps to understand the mechanisms underlying the tumor progression and regression role of macrophages in a comparative way from a basic level to the advanced one.

Spatial Cancer-Immune Phenotypes Predict Shorter Recurrence-Free Survival in the No Specific Molecular Profile Molecular Subtype of Endometrial Carcinoma

Compartmentation of the immune response into 3 main spatial cancer-immune phenotypes (SCIs) - inflamed, excluded, and desert - has been proposed as the main predictor of response to immune checkpoint inhibitors in solid tumors. The objective of the study was to define and characterize the SCI in a consecutive series of 213 endometrial carcinomas (ECs) by correlating it with molecular subtypes, clinicopathologic features, and prognosis. Immunohistochemistry (IHC) and next-generation sequencing were used to assign surrogate molecular EC subtypes: POLE mutant (POLE), mismatch repair deficient (MMRd), TP53 mutant (p53abn), and no specific molecular profile (NSMP). Immune cell markers (CD20, CD3, CD8, CD68, PD-L1) were assessed by IHC on whole sections and quantified by digital image analysis to define the 3 SCIs. ECs were stratified into 4 molecular subtypes: 17 (8.0%) POLE, 68 (31.9%) MMRd, 42 (19.7%) p53abn, and 86 (40.4%) NSMP. SCI determination showed 105 (49.3%) inflamed, 62 (29.1%) desert, and 46 (25.6%) excluded tumors. The inflamed phenotype was more prevalent in MMRd (64.7%) and POLE (76.5%) subtypes compared with NSMP (45.3%) and p53abn (21.4%). SCI revealed a strong correlation with disease-free survival in NSMP tumors: inflamed 96.2%, desert 83.2%, and excluded 40.5%. The SCI prognostic impact was also maintained in NSMP cases treated with adjuvant therapy resulting in a significant difference in recurrence between the inflamed and excluded phenotypes. To simplify SCI determination, a subset of immune cell markers was selected as appropriate to define the 3 SCI patterns: high intraepithelial CD8 for the inflamed phenotype; CD68, CD20, and PD-L1 to discriminate between desert and excluded tumors. The integration of SCI into molecular classification could be a promising opportunity to improve the prognostic risk stratification of patients and may guide the therapeutic approach, particularly in the NSMP subtype. Thus, the different patterns of immune response are a new prognostic parameter in the NSMP subtype.

CD69+CD103+CD8+ tissue-resident memory T cells possess stronger anti-tumor activity and predict better prognosis in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. Despite advancements in therapeutic methodologies, it still causes a high rate of patient mortality. CD8+ tissue-resident memory T (TRM) cells are strategically positioned to mediate effective anti-tumor responses. However, the characteristic surface molecules and functions of CD8+ TRM cells exhibit significant heterogeneity.

METHODS

The roles and anti-tumor biological functions of different CD8+ TRM subsets in CRC were determined by clinical CRC samples, bioinformatics analysis, and in vitro experiments including co-culture experiments and transwell migration assays. The signaling pathways that synergistically regulate the differentiation of CD8+ TRM cells were identified by in vitro CD8+ T cell activation and inhibition assays, and the functioning transcription factors were predicted using the UCSC and JASPAR databases.

RESULTS

We found that different CD8+ TRM subsets existed in CRC tumor tissues, which were identified as CD69-CD103-CD8+ TRM, CD69+CD103-CD8+ TRM (SP CD8+ TRM), and CD69+CD103+CD8+ TRM (DP CD8+ TRM) subsets. Compared with SP CD8+ TRM cells, increased infiltration of DP CD8+ TRM cells predicted better prognosis and played a protective role mainly in tumor invasion and lymph node metastasis of CRC. DP CD8+ TRM cells expressed higher levels of effector molecules and exerted stronger anti-tumor effects in a FAS/FASL pathway-dependent manner. Additionally, DP CD8+ TRM cells secreted higher levels of CXCL13 and recruited B cells into tumor tissues through the CXCL13/CXCR5 signaling axis to form tertiary lymphoid structures, participating in anti-tumor immune responses. Notch and TGF-β signaling pathways synergistically regulate the differentiation of DP CD8+ TRM cells.

CONCLUSIONS

We clarified the roles and mechanisms of different CD8+ TRM subsets in CRC and identified that DP CD8+ TRM cells exert stronger anti-tumor effects and predict better prognosis, which provides ideas for developing new clinically available therapeutic targets.

PD-1/PD-L1 interaction score and NKT-like cell infiltration predict immunotherapy efficacy in non-small cell lung cancer patients

OBJECTIVE

The currently available biomarkers are insufficient to accurately predict the immunotherapy response in patients. This work attempted to investigate effects of PD-1/PD-L1 interaction score combined with NKT-like cell infiltration level in tumor microenvironment on predicting immunotherapy efficacy.

METHODS

24 non-small cell lung cancer (NSCLC) patients who underwent immunotherapy were analyzed using multiplex immunofluorescence to quantitatively assess positive cells of target biomarkers and their spatial localization. Correlation between PD-1/PD-L1 interaction score in combination with NKT-like cell infiltration level and immunotherapy response was analyzed. The predictive performance of two individual biomarkers and combined novel biomarkers in immunotherapy efficacy was assessed through receiver operating characteristic curve analysis. Relationships between these factors and patient survival prognosis were analyzed using Kaplan-Meier curves.

RESULTS

Among responders, PD-1/PD-L1 interaction score and NKT-like cell infiltration level were significantly higher than nonresponders (P < 0.05), and PD-1/PD-L1 interaction score and NKT-like cell infiltration level could effectively identify the population with immunotherapy response, with area under the curves (AUCs) of 0.7571 and 0.8643, respectively. Combination of the two had the best performance in predicting the efficacy of immunotherapy (AUC = 0.9070). High PD-1/PD-L1 interaction scores and high levels of NKT-like cell infiltration significantly improved progression-free survival (HR = 0.2544, P = 0.0053) and overall survival (HR = 0.2820, P = 0.0053) in patients.

CONCLUSIONS

Combination of PD-1/PD-L1 interaction score and NKT-like cell infiltration level had favorable performance in predicting immunotherapy response in NSCLC patients, contributing to accurately identify patients who may benefit from immunotherapy.

Spatial analysis by current multiplexed imaging technologies for the molecular characterisation of cancer tissues

Tumours are composed of tumour cells and the surrounding tumour microenvironment (TME), and the molecular characterisation of the various elements of the TME and their interactions is essential for elucidating the mechanisms of tumour progression and developing better therapeutic strategies. Multiplex imaging is a technique that can quantify the expression of multiple protein markers on the same tissue section while maintaining spatial positioning, and this method has been rapidly developed in cancer research in recent years. Many multiplex imaging technologies and spatial analysis methods are emerging, and the elucidation of their principles and features is essential. In this review, we provide an overview of the latest multiplex imaging techniques by type of imaging and staining method and an introduction to image analysis methods, primarily focusing on spatial cellular properties, providing deeper insight into tumour organisation and spatial molecular biology in the TME.

Assessing the Tumor Immune Landscape Across Multiple Spatial Scales to Differentiate Immunotherapy Response in Metastatic Non-Small Cell Lung Cancer

Although immune checkpoint inhibitor-based therapy has shown promising results in non-small cell lung cancer patients with high programmed death-ligand 1 expression, not all patients respond to therapy. The tumor microenvironment (TME) is complex and heterogeneous, making it challenging to understand the key agents and features that influence response to therapies. In this study, we leverage multiplex fluorescent immunohistochemistry to quantitatively assess interactions between tumor and immune cells in an effort to identify patterns occurring at multiple spatial levels of the TME. To do so, we introduce several computational methods novel to a data set of 1,269 multiplex fluorescent immunohistochemistry images from a cohort of 52 patients with metastatic non-small cell lung cancer. With the spatial G-cross function, we quantify the degree of cell interaction at an entire image level, where we see significantly increased activity of cytotoxic T cells and helper T cells with epithelial tumor cells in responders to immune checkpoint inhibitor-based (P = .022 and P < .001, respectively) and decreased activity of T-regulatory cells with epithelial tumor cells compared with nonresponders (P = .010). By leveraging spatial overlap methods, we define tumor subregions (which we call the tumor "periphery," "edge." and "center") and discover more localized immune-immune interactions influencing positive response, including those between cytotoxic T cells and helper T cells with antigen presenting cells in these subregions specifically. Finally, we trained an interpretable deep learning model that identified key cellular regions of interest that most influenced response classification (area under the curve = 0.71 ± 0.02). Assessing spatial interactions within these subregions further revealed new insights that were not significant at the whole image level, particularly the elevated association of antigen presenting cells and T-regulatory cells with one another in responder groups (P = .024). Altogether, we demonstrate that elucidating patterns of cell composition and interplay across multiple levels of spatial analyses can improve our understanding of the TME and better differentiate patient responses to immunotherapy.

Prognostic significance of immune-cell distribution and tumoral spread through air spaces - Multiplex spatial immunophenotyping analysis

Objectives

Spread through air spaces (STAS) is a form of lung cancer invasion that extends beyond the tumor edge and is associated with a worse prognosis. Recent advances in immunotherapy highlight the importance of understanding the tumor microenvironment. This study aimed to investigate the prognostic significance of immune-cell distribution in lung cancer, focusing on the association with STAS.

Materials and methods

We retrospectively analyzed 283 patients who underwent curative-intent lung resection for primary lung cancer. Multiplex immunofluorescence staining/phenotyping was performed on tissue microarrays to assess the distribution of CD4, CD8, CD20, CD68, and FoxP3 immune cells within the center and tumor edge. We defined the delta-Edge value (Δ) as the difference in the number of immune cells between the tumor edge and center. Recurrence-free probability (RFP) was analyzed using Kaplan-Meier and Cox proportional hazard models.

Results

High ΔCD4 and ΔCD8 values were significantly associated with worse RFP. In stage I adenocarcinoma patients, STAS, and high ΔCD8 were independent risk factors for recurrence. Effect modification analysis revealed that high ΔFoxP3 was significantly associated with worse RFP in patients with STAS, but not in those without STAS. Patients with STAS and high Δimmune cell values had the lowest RFP among all groups.

Conclusion

Immune-cell distribution, particularly CD4, CD8, and FoxP3, is a crucial prognostic factor in lung cancer. STAS and specific immune cell distribution patterns can be used to further stratify patient prognosis. Understanding these interactions may provide insights into potential therapeutic targets for personalized lung cancer treatment.

Examining the spatial distribution of tumor-infiltrating immune cells in patients with stage I to IIIA LUAD

This study aimed to examine the spatial distribution of immune cells by application of Gcross function in 170 patients with stage I to IIIA lung adenocarcinoma (LUAD) and explore its prognostic value. A total of 170 stage I to IIIA LUAD patients who underwent radical surgery were enrolled. Paraffinized tumor sections were collected for 2 panels of multicolor immunofluorescence staining (panel 1: CD4, CD8, FOXP3, CD69, CD39, CD73, and DAPI; panel 2: CD68, CD163, CD20, CD11c, PDL1, IDO, and DAPI). The immune cells were categorized as CD8+, CD4+ T helper cell (CD4Th), regulatory T cell, macrophage type 1 (M1), M2, dendritic cell (DC), and B cell. The immune cell numbers were enumerated, and the immune cell proximity score was calculated employing the Gcross function. The correlation between immune cell variables and disease-free survival (DFS) was explored through univariate Cox regression analyses. Factors with P < 0.05 were subjected to multivariate analyses. According to univariate Cox regression analyses, total PDL1+ and PDL1+ DC counts were negative factors (P = 0.003 and 0.031, respectively). CD4Th and IDO-DC counts were positive factors (P = 0.022 and 0.024, respectively). The proximity score (M1 to M2) was a positive factor for DFS (P = 0.032), and the proximity score (PDL1 + DC to M1) was a negative factor (P = 0.009) according to univariate Cox analyses. In multivariate analyses, stage (IIIA vs I + II) (hazard ratio [HR]: 1.77 [95% confidence interval (CI): 1.18-2.64], P = 0.006) and proximity score (PDL1 + DC to M1) (HR: 1.60 [95% CI: 1.07-2.37], P = 0.021) were independent negative factors and CD4Th counts (HR: 0.60 [95% CI: 0.40-0.90], P = 0.013) was an independent positive factor. Our study indicated that a higher level of tumor-infiltrating CD4Th cells predicted longer DFS, and a closer proximity of PDL1+ DCs to M1 cells was associated with dismal DFS in stage I to IIIA LUAD patients.

Tertiary lymphoid structure-related immune infiltrates in NSCLC tumor lesions correlate with low tumor-reactivity of TIL products

Adoptive transfer of tumor infiltrating lymphocytes (TIL therapy) has proven highly effective for treating solid cancers, including non-small cell lung cancer (NSCLC). However, not all patients benefit from this therapy for yet unknown reasons. Defining markers that correlate with high tumor-reactivity of the autologous TIL products is thus key for achieving better tailored immunotherapies. We questioned whether the composition of immune cell infiltrates correlated with the tumor-reactivity of expanded TIL products. Unbiased flow cytometry analysis of immune cell infiltrates of 26 early-stage and 20 late-stage NSCLC tumor lesions was used for correlations with the T cell differentiation and activation status, and with the expansion rate and anti-tumor response of generated TIL products. The composition of tumor immune infiltrates was highly variable between patients. Spearman's Rank Correlation revealed that high B cell infiltration negatively correlated with the tumor-reactivity of the patient's expanded TIL products, as defined by cytokine production upon exposure to autologous tumor digest. In-depth analysis revealed that tumor lesions with high B cell infiltrates contained tertiary lymphoid structure (TLS)-related immune infiltrates, including BCL6+ antibody-secreting B cells, IgD+BCL6+ B cells and CXCR5+BLC6+ CD4+ T cells, and higher percentages of naïve CD8+ T cells. In conclusion, the composition of immune cell infiltrates in NSCLC tumors associates with the functionality of the expanded TIL product. Our findings may thus help improve patient selection for TIL therapy.

Dysfunction of CD8+ T cells around tumor cells leads to occult lymph node metastasis in NSCLC patients

Occult lymph node metastasis (OLNM) is one of the main causes of regional recurrence in inoperable N0 non-small cell lung cancer (NSCLC) patients following stereotactic ablation body radiotherapy (SABR) treatment. The integration of immunotherapy and SABR (I-SABR) has shown preliminary efficiency in mitigating this recurrence. Therefore, it is necessary to explore the functional dynamics of critical immune effectors, particularly CD8+ T cells in the development of OLNM. In this study, tissue microarrays (TMAs) and multiplex immunofluorescence (mIF) were used to identify CD8+ T cells and functional subsets (cytotoxic CD8+ T cells/predysfunctional CD8+ T cells (CD8+ Tpredys)/dysfunctional CD8+ T cells (CD8+ Tdys)/other CD8+ T cells) among the no lymph node metastasis, OLNM, and clinically evident lymph node metastasis (CLNM) groups. As the degree of lymph node metastasis escalated, the density of total CD8+ T cells and CD8+ Tdys cells, as well as their proximity to tumor cells, increased progressively and remarkably in the invasive margin (IM). In the tumor center (TC), both the density and proximity of CD8+ Tpredys cells to tumor cells notably decreased in the OLNM group compared with the group without metastasis. Furthermore, positive correlations were found between the dysfunction of CD8+ T cells and HIF-1α+CD8 and cancer microvessels (CMVs). In conclusion, the deterioration in CD8+ T cell function and interactive dynamics between CD8+ T cells and tumor cells play a vital role in the development of OLNM in NSCLC. Strategies aimed at improving hypoxia or targeting CMVs could potentially enhance the efficacy of I-SABR.

Density of tumor-infiltrating NK and Treg cells is associated with 5 years progression-free and overall survival in resected lung adenocarcinoma

Surgical resection of pulmonary adenocarcinoma is considered to be curative but progression-free survival (PFS) has remained highly variable. Antitumor immune response may be important, however, the prognostic significance of tumor-infiltrating natural killer (NK) and regulatory T (Treg) lymphocytes is uncertain. Resected pulmonary adenocarcinoma tissues (n = 115) were studied by immunohistochemical detection of NKp46 and FoxP3 positivity to identify NK and Treg cells, respectively. Association of cell densities with clinicopathological features and progression-free survival (PFS) as well as overall survival (OS) were analyzed with a follow-up time of 60 months. Both types of immune cells were accumulated predominantly in tumor stroma. NK cell density showed association with female gender, non-smoking and KRAS wild-type status. According to Kaplan-Meier analysis, PFS and OS proved to be longer in patients with high NK or Treg cell densities (p = 0.0293 and p = 0.0375 for PFS, p = 0.0310 and p = 0.0448 for OS, respectively). Evaluating the prognostic effect of the combination of NK and Treg cell density values revealed that PFS and OS were significantly longer in NKhigh/Treghigh cases compared to the other groups combined (p = 0.0223 and p = 0.0325, respectively). Multivariate Cox regression analysis indicated that high NK cell density was independent predictor of longer PFS while high NK and high Treg cell densities both proved significant predictors of longer OS. The NKhigh/Treghigh combination also proved to be an independent prognostic factor for both PFS and OS. In conclusion, NK and Treg cells can be components of the innate and adaptive immune response at action against progression of pulmonary adenocarcinoma.

CRTAC1 identified as a promising diagnosis and prognostic biomarker in lung adenocarcinoma

CRTAC1, one of the pyroptosis-related genes, has been identified as a protective factor in certain kinds of cancer, such as gastric adenocarcinoma and bladder cancer. The study aimed to investigate the role of CRTAC1 in lung adenocarcinoma (LUAD). LUAD datasets were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), pyroptosis-related genes from GeneCard. Limma package used to find differentially expressed genes (DEGs), least absolute shrinkage and selection operator (LASSO) regression and weighted genes co-expression network analysis (WGCNA) to identify CRTAC1 as hub gene. CRTAC1 expression was confirmed in a real-world cohort using quantitative polymerase chain reaction (qPCR) and Western Blot (WB) analyses. Cellular experiments were conducted to investigate CRTAC1's potential oncogenic mechanisms. CRTAC1 mRNA expression was significantly lower in LUAD tissues (p < 0.05) and showed high accuracy in diagnosing LUAD. Reduced CRTAC1 expression was associated with a poor prognosis. Higher CRTAC1 expression correlated with increased immune cell infiltration. Individuals with high CRTAC1 expression showed increased drug sensitivity. Additionally, qPCR and WB analyses showed that CRTAC1 expression was lower in tumor tissue compared to adjacent normal tissue at both the RNA and protein levels. Upregulation of CRTAC1 significantly inhibited LUAD cell proliferation, invasion, and migration in cellular experiments. CRTAC1 has the potential to serve as a diagnostic and prognostic biomarker in LUAD.

Redefining clinical practice through spatial profiling: a revolution in tissue analysis

Spatial biology, which combines molecular biology and advanced imaging, enhances our understanding of tissue cellular organisation. Despite its potential, spatial omics encounters challenges related to data complexity, computational requirements and standardisation of analysis. In clinical applications, spatial omics has the potential to revolutionise biomarker discovery, disease stratification and personalised treatments. It can identify disease-specific cell patterns, and could help risk stratify patients for clinical trials and disease-appropriate therapies. Although there are challenges in adopting it in clinical practice, spatial omics has the potential to significantly enhance patient outcomes. In this paper, we discuss the recent evolution of spatial biology, and its potential for improving our tissue level understanding and treatment of disease, to help advance precision and effectiveness in healthcare interventions.

Spatial insights into immunotherapy response in non-small cell lung cancer (NSCLC) by multiplexed tissue imaging

The spatial localisation of immune cells within tumours are key to understand the intercellular communications that can dictate clinical outcomes. Here, we demonstrate an analysis pipeline for highly multiplexed CODEX data to phenotype and profile spatial features and interactions in NSCLC patients that subsequently received PD1 axis immunotherapy. We found that regulatory T cells (Tregs) are enriched in non-responding patients and this was consistent with their localization within stromal and peripheral tumour-margins. Proximity-based interactions between Tregs and both monocytes (p = 0.009) and CD8+ T cells (p = 0.009) were more frequently found in non-responding patients, while macrophages were more frequently located in proximity to HLADR+ tumour cells (p = 0.01) within responding patients. Cellular neighbourhoods analysis indicated that both macrophages (p = 0.003) and effector CD4+ T cells (p = 0.01) in mixed tumour neighbourhoods, as well as CD8+ T cells (p = 0.03) in HLADR+ tumour neighbourhoods were associated with favorable clinical response. Evaluation of the inferred regulatory functions between immune cells relative to the tumour suggested that macrophages exhibit an immunosuppressive phenotype against both CD4+ and CD8+ T cells, and that this association scores more highly in ICI refractory patients. These spatial patterns are associated with overall survival in addition to ICI response and may thus indicate features for the functional understanding of the tumour microenvironment.

Exploring histological predictive biomarkers for immune checkpoint inhibitor therapy response in non-small cell lung cancer

Treatment challenges persist in advanced lung cancer despite the development of therapies beyond the traditional platinum-based chemotherapy. The early 2000s marked a shift to tyrosine kinase inhibitors targeting epidermal growth factor receptor, ushering in personalized genetic-based treatment. A further significant advance was the development of immune checkpoint inhibitors (ICIs), especially for non-small cell lung cancer. These target programmed death-ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen 4, which enhanced the immune response against tumor cells. However, not all patients respond, and immune-related toxicities arise. This review emphasizes identifying biomarkers for ICI response prediction. While PD-L1 is a widely used, validated biomarker, its predictive accuracy is imperfect. Investigating tumor-infiltrating lymphocytes, tertiary lymphoid structure, and emerging biomarkers such as high endothelial venule, Human leukocyte antigen class I, T-cell immunoreceptors with Ig and ITIM domains, and lymphocyte activation gene-3 counts is promising. Understanding and exploring additional predictive biomarkers for ICI response are crucial for enhancing patient stratification and overall care in lung cancer treatment.

Macrophage barrier in the tumor microenvironment and potential clinical applications

The tumor microenvironment (TME) constitutes a complex microenvironment comprising a diverse array of immune cells and stromal components. Within this intricate context, tumor-associated macrophages (TAMs) exhibit notable spatial heterogeneity. This heterogeneity contributes to various facets of tumor behavior, including immune response modulation, angiogenesis, tissue remodeling, and metastatic potential. This review summarizes the spatial distribution of macrophages in both the physiological environment and the TME. Moreover, this paper explores the intricate interactions between TAMs and diverse immune cell populations (T cells, dendritic cells, neutrophils, natural killer cells, and other immune cells) within the TME. These bidirectional exchanges form a complex network of immune interactions that influence tumor immune surveillance and evasion strategies. Investigating TAM heterogeneity and its intricate interactions with different immune cell populations offers potential avenues for therapeutic interventions. Additionally, this paper discusses therapeutic strategies targeting macrophages, aiming to uncover novel approaches for immunotherapy. Video Abstract.

Cellular crosstalk of macrophages and therapeutic implications in non-small cell lung cancer revealed by integrative inference of single-cell transcriptomics

Introduction: Non-small cell lung cancer (NSCLC) exhibits heterogeneity with diverse immune cell infiltration patterns that can influence tumor cell behavior and immunotherapy. A comprehensive characterization of the tumor microenvironment can guide precision medicine. Methods: Here, we generated a single-cell atlas of 398170 cells from 52 NSCLC patients, and investigated the imprinted genes and cellular crosstalk for macrophages. Subsequently, we evaluated the effect of tumor cells on macrophages and verified the expression of marker genes using co-culture experiments, flow cytometry and RT-qPCR assays. Results: Remarkable macrophage adaptability to NSCLC environment was observed, which contributed to generating tumor-associated macrophages (TAMs). We identified 5 distinct functional TAM subtypes, of which the majority were SELENOP-positive macrophages, with high levels of SLC40A1 and CCL13. The TAMs were also involved in mediating CD8+ T cell activity and form intercellular interaction with cancer cells, as indicated by receptor-ligand binding. Indirect coculture of tumor cells SPC-A1 and THP-1 monocytes, produced M2-like TAMs that highly expressed several markers of SELENOP-positive macrophages. The abundance of this type TAMs seemed to be associated with poorer overall survival rates [hazard ratio (HR) = 1.34, 95% confidence interval (CI) = 0.98-1.83, p = 0.068] based on deconvolution of TCGA-LUAD dataset. Discussion: In summary, we provided a high-resolution molecular resource of TAMs, and displayed the acquired properties in the tumor microenvironment. Dynamic crosstalk between TAMs and tumor cells via multiple ligand-receptor pairs were revealed, emphasizing its role in sustaining the pro-tumoral microenvironment and its implications for cancer therapy.

Advancing Understanding of Non-Small Cell Lung Cancer with Multiplexed Antibody-Based Spatial Imaging Technologies

Non-small cell lung cancer (NSCLC) remains a cause of significant morbidity and mortality, despite significant advances made in its treatment using immune checkpoint inhibitors (ICIs) over the last decade; while a minority experience prolonged responses with ICIs, benefit is limited for most patients. The development of multiplexed antibody-based (MAB) spatial tissue imaging technologies has revolutionised analysis of the tumour microenvironment (TME), enabling identification of a wide range of cell types and subtypes, and analysis of the spatial relationships and interactions between them. Such study has the potential to translate into a greater understanding of treatment susceptibility and resistance, factors influencing prognosis and recurrence risk, and identification of novel therapeutic approaches and rational treatment combinations to improve patient outcomes in the clinic. Herein we review studies that have leveraged MAB technologies to deliver novel insights into the TME of NSCLC.