Identification of distinct immune landscapes using an automated nine-color multiplex immunofluorescence staining panel and image analysis in paraffin tumor tissues

First-in-human dose escalation trial to evaluate the clinical safety and efficacy of an anti-MAGEA1 autologous TCR-transgenic T cell therapy in relapsed and refractory solid tumors

RATIONALE OF THE TRIAL

Although the use of engineered T cells in cancer immunotherapy has greatly advanced the treatment of hematological malignancies, reaching meaningful clinical responses in the treatment of solid tumors is still challenging. We investigated the safety and tolerability of IMA202 in a first-in-human, dose escalation basket trial in human leucocyte antigen A*02:01 positive patients with melanoma-associated antigen A1 (MAGEA1)-positive advanced solid tumors.

TRIAL DESIGN

The 2+2 trial design was an algorithmic design based on a maximally acceptable dose-limiting toxicity (DLT) rate of 25% and the sample size was driven by the algorithmic design with a maximum of 16 patients. IMA202 consists of autologous genetically modified cytotoxic CD8+ T cells expressing a T cell receptor (TCR), which is specific for a nine amino acid peptide derived from MAGEA1. Eligible patients underwent leukapheresis, T cells were isolated, transduced with lentiviral vector carrying MAGEA1-specific TCR and following lymphodepletion (fludarabine/cyclophosphamide), infused with a median of 1.4×109 specific T cells (range, 0.086×109-2.57×109) followed by interleukin 2. SAFETY OF IMA202: No DLT was observed. The most common grade 3-4 adverse events were cytopenias, that is, neutropenia (81.3%), lymphopenia (75.0%), anemia (50.0%), thrombocytopenia (50.0%) and leukopenia (25.0%). 13 patients experienced cytokine release syndrome, including one grade 3 event. Immune effector cell-associated neurotoxicity syndrome was observed in two patients and was grade 1 in both. EFFICACY OF IMA202: Of the 16 patients dosed, 11 (68.8%) patients had stable disease (SD) as their best overall response (Response Evaluation Criteria in Solid Tumors V.1.1). Five patients had initial tumor shrinkage in target lesions and one patient with SD experienced continued shrinkage in target lesions for 3 months in total but had to be classified as progressive disease due to progressive non-target lesions. IMA202 T cells were persistent in peripheral blood for several weeks to months and were also detectable in tumor tissue. Peak persistence was higher in patients who received higher doses.

CONCLUSION

In conclusion, IMA202 had a manageable safety profile, and it was associated with biological and potential clinical activity of MAGEA1-targeting genetically engineered TCR-T cells in a poor prognosis, multi-indication solid tumor cohort.

TRIAL REGISTRATION NUMBERS

NCT04639245, NCT05430555.

Hyperactivation of mTOR/eIF4E Signaling Pathway Promotes the Production of Tryptophan-To-Phenylalanine Substitutants in EBV-Positive Gastric Cancer

Although messenger RNA translation is tightly regulated to preserve protein synthesis and cellular homeostasis, chronic exposure to interferon-γ (IFN-γ) in several cancers can lead to tryptophan (Trp) shortage via the indoleamine-2,3-dioxygenase (IDO)- kynurenine pathway and therefore promotes the production of aberrant peptides by ribosomal frameshifting and tryptophan-to-phenylalanine (W>F) codon reassignment events (substitutants) specifically at Trp codons. However, the effect of Trp depletion on the generation of aberrant peptides by ribosomal mistranslation in gastric cancer (GC) is still obscure. Here, it is shows that the abundant infiltrating lymphocytes in EBV-positive GC continuously secreted IFN-γ, upregulated IDO1 expression, leading to Trp shortage and the induction of W>F substitutants. Intriguingly, the production of W>F substitutants in EBV-positive GC is linked to antigen presentation and the activation of the mTOR/eIF4E signaling pathway. Inhibiting either the mTOR/eIF4E pathway or EIF4E expression counteracted the production and antigen presentation of W>F substitutants. Thus, the mTOR/eIF4E pathway exposed the vulnerability of gastric cancer by accelerating the production of aberrant peptides and boosting immune activation through W>F substitutant events. This work proposes that EBV-positive GC patients with mTOR/eIF4E hyperactivation may benefit from anti-tumor immunotherapy.

Correlation of microscopic tumor extension with tumor microenvironment in esophageal cancer patients

OBJECTIVE

In the era of image-guided adaptive radiotherapy, definition of the clinical target volume (CTV) is a challenge in various solid tumors, including esophageal cancer (EC). Many tumor microenvironmental factors, e.g., tumor cell proliferation or cancer stem cells, are hypothesized to be involved in microscopic tumor extension (MTE). Therefore, this study assessed the expression of FAK, ILK, CD44, HIF-1α, and Ki67 in EC patients after neoadjuvant radiochemotherapy followed by tumor resection (NRCHT+R) and correlated these markers with the MTE.

METHODS

Formalin-fixed paraffin-embedded tumor resection specimens of ten EC patients were analyzed using multiplex immunofluorescence staining. Since gold fiducial markers had been endoscopically implanted at the proximal and distal tumor borders prior to NRCHT+R, correlation of the markers with the MTE was feasible.

RESULTS

In tumor resection specimens of EC patients, the overall percentages of FAK+, CD44+, HIF-1α+, and Ki67+ cells were higher in tumor nests than in the tumor stroma, with the outcome for Ki67+ cells reaching statistical significance (p < 0.001). Conversely, expression of ILK+ cells was higher in tumor stroma, albeit not statistically significantly. In three patients, MTE beyond the fiducial markers was found, reaching up to 31 mm.

CONCLUSION

Our findings indicate that the overall expression of FAK, HIF-1α, Ki67, and CD44 was higher in tumor nests, whereas that of ILK was higher in tumor stroma. Differences in the TME between patients with residual tumor cells in the original CTV compared to those without were not found. Thus, there is insufficient evidence that the TME influences the required CTV margin on an individual patient basis.

TRIAL REGISTRATION NUMBER AND DATE

BO-EK-148042017 and BO-EK-177042022 on 20.06.2022, DRKS00011886, https://drks.de/search/de/trial/DRKS00011886 .

Exploratory pilot study to characterize the immune landscapes of malignant pleural effusions and their corresponding primary tumors from patients with breast carcinoma and lung adenocarcinoma

INTRODUCTION

Malignant pleural effusion (MPE) is a frequent complication of advanced malignancies. In this pilot study, we characterized the immune landscapes of MPEs, compared them to their primary tumor (PT) samples from breast carcinoma (BC) and lung adenocarcinoma (LADC), and tested the utility of multiplexed image technology in cytological samples.

MATERIALS AND METHODS

We evaluated the immune contexture of 6 BC and 5 LADC MPEs and their PTs using 3 multiplex immunofluorescence panels. We explored the associations between sample characteristics and pleural effusion-free survival.

RESULTS

No MPE samples had positive programmed death-ligand 1 expression in malignant cells, although 3 of 11 PTs has positive programmed death-ligand 1 expression (more than 1% expression in malignant cells). Overall, in LADC samples, cluster of differentiation 3 (CD3)+ T cells and CD3+CD8+ cytotoxic T cells predominated (median percentages for MPEs versus PTs: 45.6% versus 40.7% and 4.7% versus 6.6%, respectively) compared with BC. CD68+ macrophages predominated in the BC samples (medians for MPEs 61.2% versus PTs for 57.1%) but not in the LADC samples. Generally in PTs, CD3+CD8+ forkhead box P3+ T cells and the median distances from the malignant cells to CD3+CD8+Ki67+ and CD3+ programmed cell death protein 1 + T cells correlated to earlier MPE after PT diagnosis.

CONCLUSIONS

The immune cell phenotypes in the MPEs and PTs were similar within each cancer type but different between BC versus LADC. An MPE analysis can potentially be used as a substitute for a PT analysis, but an expanded study of this topic is essential.

A randomized, non-comparative phase 2 study of neoadjuvant immune-checkpoint blockade in retroperitoneal dedifferentiated liposarcoma and extremity/truncal undifferentiated pleomorphic sarcoma

Based on the demonstrated clinical activity of immune-checkpoint blockade (ICB) in advanced dedifferentiated liposarcoma (DDLPS) and undifferentiated pleomorphic sarcoma (UPS), we conducted a randomized, non-comparative phase 2 trial ( NCT03307616 ) of neoadjuvant nivolumab or nivolumab/ipilimumab in patients with resectable retroperitoneal DDLPS (n = 17) and extremity/truncal UPS (+ concurrent nivolumab/radiation therapy; n = 10). The primary end point of pathologic response (percent hyalinization) was a median of 8.8% in DDLPS and 89% in UPS. Secondary end points were the changes in immune infiltrate, radiographic response, 12- and 24-month relapse-free survival and overall survival. Lower densities of regulatory T cells before treatment were associated with a major pathologic response (hyalinization > 30%). Tumor infiltration by B cells was increased following neoadjuvant treatment and was associated with overall survival in DDLPS. B cell infiltration was associated with higher densities of regulatory T cells before treatment, which was lost upon ICB treatment. Our data demonstrate that neoadjuvant ICB is associated with complex immune changes within the tumor microenvironment in DDLPS and UPS and that neoadjuvant ICB with concurrent radiotherapy has significant efficacy in UPS.

Mapping the single cell spatial immune landscapes of the melanoma microenvironment

Melanoma is a highly immunogenic malignancy with an elevated mutational burden, diffuse lymphocytic infiltration, and one of the highest response rates to immune checkpoint inhibitors (ICIs). However, over half of all late-stage patients treated with ICIs will either not respond or develop progressive disease. Spatial imaging technologies are being increasingly used to study the melanoma tumor microenvironment (TME). The goal of such studies is to understand the complex interplay between the stroma, melanoma cells, and immune cell-types as well as their association with treatment response. Investigators seeking a better understanding of the role of cell location within the TME and the importance of spatial expression of biomarkers are increasingly turning to highly multiplexed imaging approaches to more accurately measure immune infiltration as well as to quantify receptor-ligand interactions (such as PD-1 and PD-L1) and cell-cell contacts. CyTOF-IMC (Cytometry by Time of Flight - Imaging Mass Cytometry) has enabled high-dimensional profiling of melanomas, allowing researchers to identify complex cellular subpopulations and immune cell interactions with unprecedented resolution. Other spatial imaging technologies, such as multiplexed immunofluorescence and spatial transcriptomics, have revealed distinct patterns of immune cell infiltration, highlighting the importance of spatial relationships, and their impact in modulating immunotherapy responses. Overall, spatial imaging technologies are just beginning to transform our understanding of melanoma biology, providing new avenues for biomarker discovery and therapeutic development. These technologies hold great promise for advancing personalized medicine to improve patient outcomes in melanoma and other solid malignancies.

Exploration of cancer associated fibroblasts phenotypes in the tumor microenvironment of classical and pleomorphic Invasive Lobular Carcinoma

As the second most common subtype of breast carcinoma, Invasive Lobular Carcinoma (ILC) microenvironment features have not been thoroughly explored. ILC has different histological subtypes and elucidating differences in their microenvironments could lead to a comprehensive development of cancer therapies. We designed a custom-made cancer associated fibroblast (CAFs) panel and used multiplex immunofluorescence to identify the differences in tumor microenvironment between Classic ILC and Pleomorphic ILC.

Materials and methods

Multiplex immunofluorescence were performed on formalin fixed paraffin embedded tissues using Opal-7 color kit. The antibodies used for phenotyping CAFs were Pan CK (AE1/AE3), CD45, A-SMA, FAP, S100, Thy-1 with optimized dilutions. The images were acquired and analyzed using Vectra 3.0 imaging system and InForm software respectively.

Results

We studied 19 different CAFs colocalized phenotypes in the tumor, stroma and overall tissue compartments between classic and pleomorphic ILC. Total A-SMA+, A-SMA+FAP+S100+ and A-SMA+S100+ CAFs demonstrated higher densities in classic ILC cases while FAP+S100+ and S-100+ CAFs were increased in the pleomorphic subtype samples.

Conclusion

Our study explores multiple CAFs phenotypes between classical and pleomorphic ILC. We showed that CAFs subset differ between Classic ILC and Pleomorphic ILC. A-SMA CAFs are more prevalent in the TME of classic ILCs whereas Pleomorphic ILCs are dominated by CAFs without A-SMA expression. This also iterates the importance of exploring this particular type of breast carcinoma in more detail, paving the way for meaningful translational research.

Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications

Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing trials, a number of retrospective approaches can be adopted to understand differences in response, recurrence and progression by examining the patient's TME from tissue samples obtained at baseline and at various time points along the treatment. The multiplex immunofluorescence (mIF) technique provides insight on patient specific cell populations and their relative spatial distribution as qualitative measures of a favorable treatment outcome. Spatial analysis of these images provides an understanding of the intratumoral heterogeneity and clustering among cell populations in the TME. A number of mathematical models, which establish clustering as a measure of deviation from complete spatial randomness, can be applied to the mIF images represented as spatial point patterns. These mathematical models, developed for landscape ecology and geographic information studies, can be applied to the TME after careful consideration of the tumor type (cold vs. hot) and the tumor immune landscape. The spatial modelling of mIF images can show observable engagement of T cells expressing immune checkpoint molecules and this can then be correlated with single-cell RNA sequencing data.

CCF-GNN: A Unified Model Aggregating Appearance, Microenvironment, and Topology for Pathology Image Classification

Pathology images contain rich information of cell appearance, microenvironment, and topology features for cancer analysis and diagnosis. Among such features, topology becomes increasingly important in analysis for cancer immunotherapy. By analyzing geometric and hierarchically structured cell distribution topology, oncologists can identify densely-packed and cancer-relevant cell communities (CCs) for making decisions. Compared to commonly-used pixel-level Convolution Neural Network (CNN) features and cell-instance-level Graph Neural Network (GNN) features, CC topology features are at a higher level of granularity and geometry. However, topological features have not been well exploited by recent deep learning (DL) methods for pathology image classification due to lack of effective topological descriptors for cell distribution and gathering patterns. In this paper, inspired by clinical practice, we analyze and classify pathology images by comprehensively learning cell appearance, microenvironment, and topology in a fine-to-coarse manner. To describe and exploit topology, we design Cell Community Forest (CCF), a novel graph that represents the hierarchical formulation process of big-sparse CCs from small-dense CCs. Using CCF as a new geometric topological descriptor of tumor cells in pathology images, we propose CCF-GNN, a GNN model that successively aggregates heterogeneous features (e.g., appearance, microenvironment) from cell-instance-level, cell-community-level, into image-level for pathology image classification. Extensive cross-validation experiments show that our method significantly outperforms alternative methods on H&E-stained and immunofluorescence images for disease grading tasks with multiple cancer types. Our proposed CCF-GNN establishes a new topological data analysis (TDA) based method, which facilitates integrating multi-level heterogeneous features of point clouds (e.g., for cells) into a unified DL framework.

Guidelines for visualization and analysis of DC in tissues using multiparameter fluorescence microscopy imaging methods

This article is part of the Dendritic Cell Guidelines article series, which provides a collection of state-of-the-art protocols for the preparation, phenotype analysis by flow cytometry, generation, fluorescence microscopy, and functional characterization of mouse and human dendritic cells (DC) from lymphoid organs and various non-lymphoid tissues. Here, we provide detailed procedures for a variety of multiparameter fluorescence microscopy imaging methods to explore the spatial organization of DC in tissues and to dissect how DC migrate, communicate, and mediate their multiple functional roles in immunity in a variety of tissue settings. The protocols presented here entail approaches to study DC dynamics and T cell cross-talk by intravital microscopy, large-scale visualization, identification, and quantitative analysis of DC subsets and their functions by multiparameter fluorescence microscopy of fixed tissue sections, and an approach to study DC interactions with tissue cells in a 3D cell culture model. While all protocols were written by experienced scientists who routinely use them in their work, this article was also peer-reviewed by leading experts and approved by all co-authors, making it an essential resource for basic and clinical DC immunologists.

Feasibility and Safety of Personalized, Multi-Target, Adoptive Cell Therapy (IMA101): First-in-Human Clinical Trial in Patients with Advanced Metastatic Cancer

IMA101 is an actively personalized, multi-targeted adoptive cell therapy (ACT), whereby autologous T cells are directed against multiple novel defined peptide-HLA (pHLA) cancer targets. HLA-A*02:01-positive patients with relapsed/refractory solid tumors expressing ≥1 of 8 predefined targets underwent leukapheresis. Endogenous T cells specific for up to 4 targets were primed and expanded in vitro. Patients received lymphodepletion (fludarabine, cyclophosphamide), followed by T-cell infusion and low-dose IL2 (Cohort 1). Patients in Cohort 2 received atezolizumab for up to 1 year (NCT02876510). Overall, 214 patients were screened, 15 received lymphodepletion (13 women, 2 men; median age, 44 years), and 14 were treated with T-cell products. IMA101 treatment was feasible and well tolerated. The most common adverse events were cytokine release syndrome (Grade 1, n = 6; Grade 2, n = 4) and expected cytopenias. No patient died during the first 100 days after T-cell therapy. No neurotoxicity was observed. No objective responses were noted. Prolonged disease stabilization was noted in three patients lasting for 13.7, 12.9, and 7.3 months. High frequencies of target-specific T cells (up to 78.7% of CD8+ cells) were detected in the blood of treated patients, persisted for >1 year, and were detectable in posttreatment tumor tissue. Individual T-cell receptors (TCR) contained in T-cell products exhibited broad variation in TCR avidity, with the majority being low avidity. High-avidity TCRs were identified in some patients' products. This study demonstrates the feasibility and tolerability of an actively personalized ACT directed to multiple defined pHLA cancer targets. Results warrant further evaluation of multi-target ACT approaches using potent high-avidity TCRs. See related Spotlight by Uslu and June, p. 865.

Association between endometrial senescent cells and immune cells in women with repeated implantation failure

PURPOSE

The aim of this study was to compare women with recurrent implantation failure (RIF) and control group in terms of the associations between p16-positive senescent cells and certain types of immune cells in human endometrium during the mid-luteal phase METHODS: Immunohistochemical staining was performed in 116 endometrial biopsies taken from 57 women presenting RIF, and control group of 59 women who became pregnant after the first intracytoplasmic sperm injection. Endometrial tissue sections were stained immunohistochemically for p16 (Senescent cells), CD4 (T-helpers), CD8 (T-killers), CD14 (Monocytes), CD68 (Macrophages), CD56 (Natural killers), and CD79α (B-cells). The percentage of positively stained cells for each marker was calculated by HALO image analysis software. The quantity and the relationship between senescent cells and immune cells were assessed and compared between the two groups.

RESULTS

The correlation coefficient was highest between senescent cells and CD4+ cells and was lowest between senescent cells and CD14+ cells in RIF women, similarly to the control group. However, most of the observed correlations among senescent and immune cells weaken notably or disappear in the RIF group. When comparing senescent cell-to-immune cell quantitative ratios, only p16+/CD4+ cell ratio was significantly higher in RIF women as compared with patients from the control group.

CONCLUSION

Our study indicates that the quantity of senescent cells in human endometrium during the mid-luteal phase has the strongest association with the amount of T helpers. Moreover, the specificity of this association might have an important impact on the occurrence of RIF.

Chemically programmable bacterial probes for the recognition of cell surface proteins

Common methods to label cell surface proteins (CSPs) involve the use of fluorescently modified antibodies (Abs) or small-molecule-based ligands. However, optimizing the labeling efficiency of such systems, for example, by modifying them with additional fluorophores or recognition elements, is challenging. Herein we show that effective labeling of CSPs overexpressed in cancer cells and tissues can be obtained with fluorescent probes based on chemically modified bacteria. The bacterial probes (B-probes) are generated by non-covalently linking a bacterial membrane protein to DNA duplexes appended with fluorophores and small-molecule binders of CSPs overexpressed in cancer cells. We show that B-probes are exceptionally simple to prepare and modify because they are generated from self-assembled and easily synthesized components, such as self-replicating bacterial scaffolds and DNA constructs that can be readily appended, at well-defined positions, with various types of dyes and CSP binders. This structural programmability enabled us to create B-probes that can label different types of cancer cells with distinct colors, as well as generate very bright B-probes in which the multiple dyes are spatially separated along the DNA scaffold to avoid self-quenching. This enhancement in the emission signal enabled us to label the cancer cells with greater sensitivity and follow the internalization of the B-probes into these cells. The potential to apply the design principles underlying B-probes in therapy or inhibitor screening is also discussed here.

Prognostic impact of the post-treatment T cell composition and spatial organization in soft tissue sarcoma patients treated with neoadjuvant hyperthermic radio(chemo)therapy

Soft tissue sarcomas (STS) form a heterogeneous group of tumors sharing a mesenchymal origin. Despite good local control of the disease, the occurrence of distant metastases often limits survival of STS patients with localized, high-risk tumors of the extremities. Accumulating evidence suggests a central role for the tumor immune microenvironment in determining the clinical outcome and response to therapy. Thus, it has been reported that STS patients with a high immune signature and especially presence of B cells and tertiary lymphoid structures display improved overall survival and response to checkpoint inhibitor treatment. Here, we explored the effect of curative multimodal therapy on the T cell landscape of STS using multiplex immunohistochemistry. We analyzed the phenotype, frequency, and spatial distribution of STS-infiltrating CD8⁺ T cells by staining for CD8, 4-1BB, Granzyme B, Ki67, PD-1, and LAG-3 as well as CD3⁺ T helper cells using a panel consisting of CD3, T-bet, GATA3, RORγT, FoxP3, and Ki67. All patients received neoadjuvant radiotherapy plus locoregional hyperthermia with or without chemotherapy. While the treatment-naïve biopsy sample allows an analysis of baseline T cell infiltration levels, both intra- and peritumoral areas of the matched resected tissue were analyzed to assess composition and spatial distribution of the T cell compartment and its therapeutic modulation. Generally, post-treatment tissues displayed lower frequencies of CD3⁺ and CD8⁺ T cells. Association with clinical data revealed that higher post-treatment frequencies of peritumoral and intratumoral CD3⁺ T cells and intratumoral PD-1⁺ CD8⁺ T cells were significantly associated with improved disease-free survival (DFS), while these densities had no prognostic significance in the biopsy. Upon spatial analysis, a high ratio of intratumoral to peritumoral CD8⁺ T cells emerged as an independent prognostic marker for longer DFS. These results indicate that the STS T cell landscape is altered by multimodal therapy and may influence the clinical outcome of patients. An enhanced understanding of the STS immune architecture and its modulation by neoadjuvant therapy may pave the way towards novel treatment modalities and improve the long-term clinical outcome of STS patients.

Phase II trial of neoadjuvant sitravatinib plus nivolumab in patients undergoing nephrectomy for locally advanced clear cell renal cell carcinoma

Sitravatinib is an immunomodulatory tyrosine kinase inhibitor that can augment responses when combined with programmed death-1 inhibitors such as nivolumab. We report a single-arm, interventional, phase 2 study of neoadjuvant sitravatinib in combination with nivolumab in patients with locally advanced clear cell renal cell carcinoma (ccRCC) prior to curative nephrectomy (NCT03680521). The primary endpoint was objective response rate (ORR) prior to surgery with a null hypothesis ORR = 5% and the alternative hypothesis set at ORR = 30%. Secondary endpoints were safety; pharmacokinetics (PK) of sitravatinib; immune effects, including changes in programmed cell death-ligand 1 expression; time-to-surgery; and disease-free survival (DFS). Twenty patients were evaluable for safety and 17 for efficacy. The ORR was 11.8%, and 24-month DFS probability was 88·0% (95% CI 61.0 to 97.0). There were no grade 4/5 treatment-related adverse events. Sitravatinib PK did not change following the addition of nivolumab. Correlative blood and tissue analyses showed changes in the tumour microenvironment resulting in an immunologically active tumour by the time of surgery (median time-to-surgery: 50 days). The primary endpoint of this study was not met as short-term neoadjuvant sitravatinib and nivolumab did not substantially increase ORR.

Culprits of PDAC resistance to gemcitabine and immune checkpoint inhibitor: Tumour microenvironment components

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal cancer with a dismal five-year survival rate of 11%. Despite remarkable advancements in cancer therapeutics, PDAC patients rarely benefit from it due to insurmountable treatment resistance. Notably, PDAC is pathologically characterized by an extensive desmoplastic reaction and an extremely immunosuppressive tumour microenvironment (TME). The PDAC TME consists of cell components (e.g., tumour, immune and stromal cells) and noncellular components (e.g., extracellular matrix), exhibiting high complexity and their interplay resulting in resistance to chemotherapeutics and immune checkpoint inhibitors. In our review, we shed light on how crosstalk of complex environmental components modulates PDAC drug resistance, and we summarize related clinical trials. Moreover, we extend our discussion on TME exploration and exosome analysis, providing new insights into clinical applications, including personalized medicine, disease monitoring and drug carriers.

Multi-perspective comparison of the immune microenvironment of primary colorectal cancer and liver metastases

BACKGROUND

Liver metastases are a major contributor to the poor immunotherapy response in colorectal cancer patients. However, the distinctions in the immune microenvironment between primary tumors and liver metastases are poorly characterized. The goal of this study was to compare the expression profile of multiple immune cells to further analyze the similarities and differences between the microenvironments of liver metastases and the primary tumor.

METHODS

Tissues from 17 patients with colorectal cancer who underwent resection of primary and liver metastases was analyzed using multispectral immunofluorescence. The expression of multiple immune cells (CD8, Foxp3, CD68, CD163, CD20, CD11c, CD66b, CD56, PD-L1, INF-γ, Ki67 and VEGFR-2) in the tumor center (TC), tumor invasive front (< 150 µm from the tumor center, TF) and peritumoral region (≥ 150 µm from the tumor center, PT) was evaluated via comparison. The expression of CD68 and CD163 in different regions was further analyzed based on the cell colocalization method. In addition, different immune phenotypes were studied and compared according to the degree of CD8 infiltration.

RESULTS

The expression trends of 12 markers in the TF and TC regions were basically the same in the primary tumor and liver metastasis lesions. However, in comparison of the TF and PT regions, the expression trends were not identical between primary and liver metastases, especially CD163, which was more highly expressed in the PT region relative to the TF region. In the contrast of different space distribution, the expression of CD163 was higher in liver metastases than in the primary foci. Further analysis of CD68 and CD163 via colocalization revealed that the distribution of macrophages in liver metastases was significantly different from that in the primary foci, with CD68^-CD163⁺ macrophages predominating in liver metastases. In addition, among the three immunophenotypes, CD163 expression was highest in the immune rejection phenotype.

CONCLUSIONS

The immune cells found in the primary tumors of colorectal cancer differed from those in liver metastases in terms of their spatial distribution. More immunosuppressive cells were present in the liver metastases, with the most pronounced differential distribution found for macrophages. CD68^-CD163⁺ macrophages may be associated with intrahepatic immunosuppression and weak immunotherapeutic effects.

Urinary T cells are detected in patients with immune checkpoint inhibitor-associated immune nephritis that are clonotypically identical to kidney T cell infiltrates

Acute kidney injury (AKI) occurs in ~20% of patients receiving immune checkpoint inhibitor (ICI) therapy; however, only 2-5% will develop ICI-mediated immune nephritis. Conventional tests are nonspecific in diagnosing disease pathology and invasive procedures (i.e. kidney biopsy) may not be feasible. In other autoimmune renal diseases, urinary immune cells correlated with the pathology or were predictive of disease activity. Corresponding evidence and analysis are absent for ICI-mediated immune nephritis. We report the first investigation analyzing immune cell profiles of matched kidney biopsies and urine of patients with ICI-AKI. We demonstrated the presence of urinary T cells in patients with immune nephritis by flow cytometry analysis. Clonotype analysis of T cell receptor (TCR) sequences confirmed enrichment of kidney TCRs in urine. As ICI therapies become standard of care for more cancers, noninvasively assessing urinary immune cells of ICI therapy recipients can facilitate clinical management and an opportunity to tailor ICI-nephritis treatment.

Proteomics approaches to characterize the immune responses in cancer

Despite the dynamic development of cancer research, annually millions of people die of cancer. The human immune system is the major 'guard' against tumor development. Unfortunately, cancer cells have the ability to evade the immune system and continue to grow. The proper understanding of the intricate immune response in tumorigenesis remains the holy grail of cancer immunology and designing effective immunotherapy. To decode the immune responses in cancer, in recent years, proteomics studies have received considerable attention. Proteomics studies focus on the detection and quantification of proteins, which are the effectors of biological functions, and as such, are proven to reflect the cell state more accurately, in comparison to genomic or transcriptomic studies. In this review, we discuss the proteomics studies applied to characterize the immune responses in cancer and tumor immune microenvironment heterogeneity. Further, we describe emerging single-cell proteomics approaches that have the potential to be applied in cancer immunity studies.

Spatially Resolved and Highly Multiplexed Protein and RNA In Situ Detection by Combining CODEX With RNAscope In Situ Hybridization

Highly multiplexed protein and RNA in situ detection on a single tissue section concurrently is highly desirable for both basic and applied biomedical research. CO-detection by inDEXing (CODEX) is a new and powerful platform to visualize up to 60 protein biomarkers in situ, and RNAscope in situ hybridization (RNAscope) is a novel RNA detection system with high sensitivity and unprecedent specificity at a single-cell level. Nevertheless, to our knowledge, the combination of CODEX and RNAscope remained unreported until this study. Here, we report a simple and reproducible combination of CODEX and RNAscope. We also determined the cross-reactivities of CODEX anti-human antibodies to rhesus macaques, a widely used animal model of human disease.

Multiplexed immunofluorescence identifies high stromal CD68+PD-L1+ macrophages as a predictor of improved survival in triple negative breast cancer

Triple negative breast cancer (TNBC) comprises 10-15% of all breast cancers and has a poor prognosis with a high risk of recurrence within 5 years. PD-L1 is an important biomarker for patient selection for immunotherapy but its cellular expression and co-localization within the tumour immune microenvironment and associated prognostic value is not well defined. We aimed to characterise the phenotypes of immune cells expressing PD-L1 and determine their association with overall survival (OS) and breast cancer-specific survival (BCSS). Using tissue microarrays from a retrospective cohort of TNBC patients from St George Hospital, Sydney (n = 244), multiplexed immunofluorescence (mIF) was used to assess staining for CD3, CD8, CD20, CD68, PD-1, PD-L1, FOXP3 and pan-cytokeratin on the Vectra Polaris™ platform and analysed using QuPath. Cox multivariate analyses showed high CD68+PD-L1+ stromal cell counts were associated with improved prognosis for OS (HR 0.56, 95% CI 0.33-0.95, p = 0.030) and BCSS (HR 0.47, 95% CI 0.25-0.88, p = 0.018) in the whole cohort and in patients receiving chemotherapy, improving incrementally upon the predictive value of PD-L1+ alone for BCSS. These data suggest that CD68+PD-L1+ status can provide clinically useful prognostic information to identify sub-groups of patients with good or poor prognosis and guide treatment decisions in TNBC.

Multiplex Immunofluorescence for Detection of Spatial Distributions of Infiltrating T Cells Within Different Regions of Hepatic Lobules During Liver Transplantation Rejection

It remains unclear as to whether there are differences that exist in the types and functional status of immune cells within different areas of the liver lobules after rejection of liver transplantation. The composition of infiltrating T cells in liver allografts during liver transplantation rejection is indistinct and difficult to visualize within the same biopsy slide. In an attempt to rectify this problem, we applied multiplex immunofluorescent assays to assess the spatial distribution of various types of infiltrating T cells in different areas of the liver lobules after liver transplantation. In identical areas of the hepatic lobules, the percentage of CD4⁺ T, CD8⁺ T, and regulatory T (Treg) cells in the rejection group was greater than that observed in the non-rejection and normal groups. Within all three groups, the percentage of CD4⁺ T, CD8⁺ T, and Treg cells from the periportal to perivenous zones initially increased and then decreased. In the rejection group, the percentage of CD8⁺ T cells gradually increased from the periportal to perivenous zones, with maximal levels in the perivenous as compared with that in the transitional and periportal zones. In conclusion, levels of CD8⁺ T cells within different regions of liver lobules are closely related to levels of rejection after liver transplantation. Liver transplantation rejection may be linked with increases in CD8⁺ T cells within the perivenous zone. Although the regional percent of increase in CD4⁺ T cells may not reflect level of the rejection, the overall numbers of both of CD4⁺ and CD8⁺ T cells within different regions were closely related to rejection levels.

Best Practices for Technical Reproducibility Assessment of Multiplex Immunofluorescence

Multiplex immunofluorescence (mIF) tyramide signal amplification is a new and useful tool for the study of cancer that combines the staining of multiple markers in a single slide. Several technical requirements are important to performing high-quality staining and analysis and to obtaining high internal and external reproducibility of the results. This review manuscript aimed to describe the mIF panel workflow and discuss the challenges and solutions for ensuring that mIF panels have the highest reproducibility possible. Although this platform has shown high flexibility in cancer studies, it presents several challenges in pre-analytic, analytic, and post-analytic evaluation, as well as with external comparisons. Adequate antibody selection, antibody optimization and validation, panel design, staining optimization and validation, analysis strategies, and correct data generation are important for reproducibility and to minimize or identify possible issues during the mIF staining process that sometimes are not completely under our control, such as the tissue fixation process, storage, and cutting procedures.

Matter of TIME: the tumor-immune microenvironment of mesothelioma and implications for checkpoint blockade efficacy

Malignant pleural mesothelioma (MPM) is an incurable cancer with a dismal prognosis and few effective treatment options. Nonetheless, recent positive phase III trial results for immune checkpoint blockade (ICB) in MPM herald a new dawn in the fight to advance effective treatments for this cancer. Tumor mutation burden (TMB) has been widely reported to predict ICB in other cancers, but MPM is considered a low-TMB tumor. Similarly, tumor programmed death-ligand 1 (PD-L1) expression has not been proven predictive in phase III clinical trials in MPM. Consequently, the precise mechanisms that determine response to immunotherapy in this cancer remain unknown. The present review therefore aimed to synthesize our current understanding of the tumor immune microenvironment in MPM and reflects on how specific cellular features might impact immunotherapy responses or lead to resistance. This approach will inform stratified approaches to therapy and advance immunotherapy combinations in MPM to improve clinical outcomes further.

High-dose irradiation in combination with non-ablative low-dose radiation to treat metastatic disease after progression on immunotherapy: Results of a phase II trial

AIM

To report early findings from a phase II trial of high-dose radiotherapy (HD-RT) with or without low-dose RT (LD-RT) for metastatic cancer.

METHODS

Eligible patients had metastatic disease that progressed on immunotherapy within 6 months. Patients were given either HD-RT (20-70 Gy total; 3-12.5 Gy/f), or HD-RT + LD-RT (0.5-2 Gy/f up to 1-10 Gy total) to separate lesions, with continued immunotherapy. Radiographic response was assessed per RECIST 1.1 and Immune-Related Response Criteria (irRC). Primary endpoints: (1) 4-month disease control (DCR, complete/partial response [CR/PR] or stable disease [SD]) or an overall response (ORR, CR/PR) at any point in ≥10% of patients, per RECIST 1.1; (2) dose-limiting toxicity within 3 months not exceeding 30%. Secondary endpoint was lesion-specific response.

RESULTS

Seventy-four patients (NSCLC, n = 38; melanoma n = 21) were analyzed (39 HD-RT and 35 HD-RT + LD-RT). The median follow-up time was 13.6 months. The primary endpoint was met for 72 evaluable patients, with a 4-month DCR of 42% (47% [16/34] vs. 37% [14/38] in HD-RT + LD-RT vs. HD-RT, P = 0.38), and 19% ORR at any time (26% [9/34] vs. 13% [5/38] in HD-RT + LD-RT vs. HD-RT, P = 0.27). Three patients had toxicity ≥grade 3. LD-RT lesion response (53%) was improved compared to nonirradiated lesions in HD-RT + LD-RT (23%, P = 0.002) and HD-RT (11%, P < 0.001). T- and NK cell infiltration was enhanced in lesions treated with LD-RT.

CONCLUSIONS

HD-RT plus LD-RT safely improved lesion-specific response in patients with immune resistant solid tumors by promoting infiltration of effector immune cells into the tumor microenvironment.

Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data

Simple Summary

Immune modulation is considered a hallmark of cancer initiation and progression, and has offered promising opportunities for therapeutic manipulation. Multiplex immunofluorescence (mIF) technology has enabled the tumor immune microenvironment (TIME) to be studied at an increased scale, in terms of both the number of markers and the number of samples. Another benefit of mIF technology is the ability to measure not only the abundance but also the spatial location of multiple cells types within a tissue sample simultaneously, allowing for assessment of the co-localization of different types of immune markers. Thus, the use of mIF technologies have enable researchers to characterize patient, clinical, and tumor characteristics in the hope of identifying patients whom might benefit from immunotherapy treatments. In this review we outline some of the challenges and opportunities in the statistical analyses of mIF data to study the TIME.

Abstract

Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or “zero-inflated” data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.

Methods to Determine and Analyze the Cellular Spatial Distribution Extracted From Multiplex Immunofluorescence Data to Understand the Tumor Microenvironment

Image analysis using multiplex immunofluorescence (mIF) to detect different proteins in a single tissue section has revolutionized immunohistochemical methods in recent years. With mIF, individual cell phenotypes, as well as different cell subpopulations and even rare cell populations, can be identified with extraordinary fidelity according to the expression of antibodies in an mIF panel. This technology therefore has an important role in translational oncology studies and probably will be incorporated in the clinic. The expression of different biomarkers of interest can be examined at the tissue or individual cell level using mIF, providing information about cell phenotypes, distribution of cells, and cell biological processes in tumor samples. At present, the main challenge in spatial analysis is choosing the most appropriate method for extracting meaningful information about cell distribution from mIF images for analysis. Thus, knowing how the spatial interaction between cells in the tumor encodes clinical information is important. Exploratory analysis of the location of the cell phenotypes using point patterns of distribution is used to calculate metrics summarizing the distances at which cells are processed and the interpretation of those distances. Various methods can be used to analyze cellular distribution in an mIF image, and several mathematical functions can be applied to identify the most elemental relationships between the spatial analysis of cells in the image and established patterns of cellular distribution in tumor samples. The aim of this review is to describe the characteristics of mIF image analysis at different levels, including spatial distribution of cell populations and cellular distribution patterns, that can increase understanding of the tumor microenvironment.

Machine learning for cell classification and neighborhood analysis in glioma tissue

Multiplexed and spatially resolved single-cell analyses that intend to study tissue heterogeneity and cell organization invariably face as a first step the challenge of cell classification. Accuracy and reproducibility are important for the downstream process of counting cells, quantifying cell-cell interactions, and extracting information on disease-specific localized cell niches. Novel staining techniques make it possible to visualize and quantify large numbers of cell-specific molecular markers in parallel. However, due to variations in sample handling and artifacts from staining and scanning, cells of the same type may present different marker profiles both within and across samples. We address multiplexed immunofluorescence data from tissue microarrays of low-grade gliomas and present a methodology using two different machine learning architectures and features insensitive to illumination to perform cell classification. The fully automated cell classification provides a measure of confidence for the decision and requires a comparably small annotated data set for training, which can be created using freely available tools. Using the proposed method, we reached an accuracy of 83.1% on cell classification without the need for standardization of samples. Using our confidence measure, cells with low-confidence classifications could be excluded, pushing the classification accuracy to 94.5%. Next, we used the cell classification results to search for cell niches with an unsupervised learning approach based on graph neural networks. We show that the approach can re-detect specialized tissue niches in previously published data, and that our proposed cell classification leads to niche definitions that may be relevant for sub-groups of glioma, if applied to larger data sets.

Pathological Characterization of Tumor Immune Microenvironment (TIME) in Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) is a rare and highly aggressive disease that arises from pleural mesothelial cells, characterized by a median survival of approximately 13-15 months after diagnosis. The primary cause of this disease is asbestos exposure and the main issues associated with it are late diagnosis and lack of effective therapies. Asbestos-induced cellular damage is associated with the generation of an inflammatory microenvironment that influences and supports tumor growth, possibly in association with patients' genetic predisposition and tumor genomic profile. The chronic inflammatory response to asbestos fibers leads to a unique tumor immune microenvironment (TIME) composed of a heterogeneous mixture of stromal, endothelial, and immune cells, and relative composition and interaction among them is suggested to bear prognostic and therapeutic implications. TIME in MPM is known to be constituted by immunosuppressive cells, such as type 2 tumor-associated macrophages and T regulatory lymphocytes, plus the expression of several immunosuppressive factors, such as tumor-associated PD-L1. Several studies in recent years have contributed to achieve a greater understanding of the pathogenetic mechanisms in tumor development and pathobiology of TIME, that opens the way to new therapeutic strategies. The study of TIME is fundamental in identifying appropriate prognostic and predictive tissue biomarkers. In the present review, we summarize the current knowledge about the pathological characterization of TIME in MPM.