High-dimensional multiplexed immunohistochemical characterization of immune contexture in human cancers

Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing

As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.

Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multiplexed proteomic data set from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcomes. We designed a multiplex immunohistochemistry antibody panel to compare T-cell functionality and spatial localization in resected tumors from treatment-naïve patients with localized pancreatic ductal adenocarcinoma (PDAC) with resected tumors from a second cohort of patients treated with neoadjuvant agonistic CD40 (anti-CD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both cohorts were assayed, and over 1,000 tumor microenvironment (TME) features were quantified. We then trained ML models to accurately predict anti-CD40 treatment status and disease-free survival (DFS) following anti-CD40 therapy based on TME features. Through downstream interpretation of the ML models' predictions, we found anti-CD40 therapy reduced canonical aspects of T-cell exhaustion within the TME, as compared with treatment-naïve TMEs. Using automated clustering approaches, we found improved DFS following anti-CD40 therapy correlated with an increased presence of CD44+CD4+ Th1 cells located specifically within cellular neighborhoods characterized by increased T-cell proliferation, antigen experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of ML in molecular cancer immunology applications, highlight the impact of anti-CD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for anti-CD40-treated patients with PDAC.

Mesothelin CAR T Cells Secreting Anti-FAP/Anti-CD3 Molecules Efficiently Target Pancreatic Adenocarcinoma and its Stroma

PURPOSE

Targeting solid tumors with chimeric antigen receptor (CAR) T cells remains challenging due to heterogenous target antigen expression, antigen escape, and the immunosuppressive tumor microenvironment (TME). Pancreatic cancer is characterized by a thick stroma generated by cancer-associated fibroblasts (CAF), which may contribute to the limited efficacy of mesothelin-directed CAR T cells in early-phase clinical trials. To provide a more favorable TME for CAR T cells to target pancreatic ductal adenocarcinoma (PDAC), we generated T cells with an antimesothelin CAR and a secreted T-cell-engaging molecule (TEAM) that targets CAF through fibroblast activation protein (FAP) and engages T cells through CD3 (termed mesoFAP CAR-TEAM cells).

EXPERIMENTAL DESIGN

Using a suite of in vitro, in vivo, and ex vivo patient-derived models containing cancer cells and CAF, we examined the ability of mesoFAP CAR-TEAM cells to target PDAC cells and CAF within the TME. We developed and used patient-derived ex vivo models, including patient-derived organoids with patient-matched CAF and patient-derived organotypic tumor spheroids.

RESULTS

We demonstrated specific and significant binding of the TEAM to its respective antigens (CD3 and FAP) when released from mesothelin-targeting CAR T cells, leading to T-cell activation and cytotoxicity of the target cell. MesoFAP CAR-TEAM cells were superior in eliminating PDAC and CAF compared with T cells engineered to target either antigen alone in our ex vivo patient-derived models and in mouse models of PDAC with primary or metastatic liver tumors.

CONCLUSIONS

CAR-TEAM cells enable modification of tumor stroma, leading to increased elimination of PDAC tumors. This approach represents a promising treatment option for pancreatic cancer.

Applicability of Spatial Technology in Cancer Research

This review explores spatial mapping technologies in cancer research, highlighting their crucial role in understanding the complexities of the tumor microenvironment (TME). The TME, which is an intricate ecosystem of diverse cell types, has a significant impact on tumor dynamics and treatment outcomes. This review closely examines cutting-edge spatial mapping technologies, categorizing them into capture-, imaging-, and antibody-based approaches. Each technology was scrutinized for its advantages and disadvantages, factoring in aspects such as spatial profiling area, multiplexing capabilities, and resolution. Additionally, we draw attention to the nuanced choices researchers face, with capture-based methods lending themselves to hypothesis generation, and imaging/antibody-based methods that fit neatly into hypothesis testing. Looking ahead, we anticipate a scenario in which multi-omics data are seamlessly integrated, artificial intelligence enhances data analysis, and spatiotemporal profiling opens up new dimensions.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Mapping cancer biology in space: applications and perspectives on spatial omics for oncology

Technologies to decipher cellular biology, such as bulk sequencing technologies and single-cell sequencing technologies, have greatly assisted novel findings in tumor biology. Recent findings in tumor biology suggest that tumors construct architectures that influence the underlying cancerous mechanisms. Increasing research has reported novel techniques to map the tissue in a spatial context or targeted sampling-based characterization and has introduced such technologies to solve oncology regarding tumor heterogeneity, tumor microenvironment, and spatially located biomarkers. In this study, we address spatial technologies that can delineate the omics profile in a spatial context, novel findings discovered via spatial technologies in oncology, and suggest perspectives regarding therapeutic approaches and further technological developments.

Decoding the tumor microenvironment with spatial technologies

Visualization of the cellular heterogeneity and spatial architecture of the tumor microenvironment (TME) is becoming increasingly important to understand mechanisms of disease progression and therapeutic response. This is particularly relevant in the era of cancer immunotherapy, in which the contexture of immune cell positioning within the tumor landscape has been proven to affect efficacy. Although single-cell technologies have mostly replaced conventional approaches to analyze specific cellular subsets within tumors, those that integrate a spatial dimension are now on the rise. In this Review, we assess the strengths and limitations of emerging spatial technologies with a focus on their applications in tumor immunology, as well as forthcoming opportunities for artificial intelligence (AI) and the value of integrating multiomics datasets to achieve a holistic picture of the TME.

Toward the clinical development of synthetic immunity to cancer

Synthetic biology (synbio) tools, such as chimeric antigen receptors (CARs), have been designed to target, activate, and improve immune cell responses to tumors. These therapies have demonstrated an ability to cure patients with blood cancers. However, there are significant challenges to designing, testing, and efficiently translating these complex cell therapies for patients who do not respond or have immune refractory solid tumors. The rapid progress of synbio tools for cell therapy, particularly for cancer immunotherapy, is encouraging but our development process should be tailored to increase translational success. Particularly, next-generation cell therapies should be rooted in basic immunology, tested in more predictive preclinical models, engineered for potency with the right balance of safety, educated by clinical findings, and multi-faceted to combat a range of suppressive mechanisms. Here, we lay out five principles for engineering future cell therapies to increase the probability of clinical impact, and in the context of these principles, we provide an overview of the current state of synbio cell therapy design for cancer. Although these principles are anchored in engineering immune cells for cancer therapy, we posit that they can help guide translational synbio research for broad impact in other disease indications with high unmet need.

Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer

Tumor molecular datasets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning to analyze a single-cell, spatial, and highly multiplexed proteomic dataset from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcome. A novel multiplex immunohistochemistry antibody panel was used to audit T cell functionality and spatial localization in resected tumors from treatment-naive patients with localized pancreatic ductal adenocarcinoma (PDAC) compared to a second cohort of patients treated with neoadjuvant agonistic CD40 (αCD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both treatment cohorts were assayed, and more than 1,000 tumor microenvironment (TME) features were quantified. We then trained machine learning models to accurately predict αCD40 treatment status and disease-free survival (DFS) following αCD40 therapy based upon TME features. Through downstream interpretation of the machine learning models' predictions, we found αCD40 therapy to reduce canonical aspects of T cell exhaustion within the TME, as compared to treatment-naive TMEs. Using automated clustering approaches, we found improved DFS following αCD40 therapy to correlate with the increased presence of CD44+ CD4+ Th1 cells located specifically within cellular spatial neighborhoods characterized by increased T cell proliferation, antigen-experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of machine learning in molecular cancer immunology applications, highlight the impact of αCD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for αCD40-treated patients with PDAC.

The Breast Cancer Proteome and Precision Oncology

The goal of precision oncology is to translate the molecular features of cancer into predictive and prognostic tests that can be used to individualize treatment leading to improved outcomes and decreased toxicity. Success for this strategy in breast cancer is exemplified by efficacy of trastuzumab in tumors overexpressing ERBB2 and endocrine therapy for tumors that are estrogen receptor positive. However, other effective treatments, including chemotherapy, immune checkpoint inhibitors, and CDK4/6 inhibitors are not associated with strong predictive biomarkers. Proteomics promises another tier of information that, when added to genomic and transcriptomic features (proteogenomics), may create new opportunities to improve both treatment precision and therapeutic hypotheses. Here, we review both mass spectrometry-based and antibody-dependent proteomics as complementary approaches. We highlight how these methods have contributed toward a more complete understanding of breast cancer and describe the potential to guide diagnosis and treatment more accurately.

Quantitative multiplexed imaging technologies for single-cell analysis to assess predictive markers for immunotherapy in thoracic immuno-oncology: promises and challenges

The past decade has witnessed a revolution in cancer treatment by the shift from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular the immune-checkpoint inhibitors (ICIs). These immunotherapies selectively release the host immune system against the tumour and have shown unprecedented durable remission for patients with cancers that were thought incurable such as advanced non-small cell lung cancer (aNSCLC). The prediction of therapy response is based since the first anti-PD-1/PD-L1 molecules FDA and EMA approvals on the level of PD-L1 tumour cells expression evaluated by immunohistochemistry, and recently more or less on tumour mutation burden in the USA. However, not all aNSCLC patients benefit from immunotherapy equally, since only around 30% of them received ICIs and among them 30% have an initial response to these treatments. Conversely, a few aNSCLC patients could have an efficacy ICIs response despite low PD-L1 tumour cells expression. In this context, there is an urgent need to look for additional robust predictive markers for ICIs efficacy in thoracic oncology. Understanding of the mechanisms that enable cancer cells to adapt to and eventually overcome therapy and identifying such mechanisms can help circumvent resistance and improve treatment. However, more than a unique universal marker, the evaluation of several molecules in the tumour at the same time, particularly by using multiplex immunostaining is a promising open room to optimise the selection of patients who benefit from ICIs. Therefore, urgent further efforts are needed to optimise to individualise immunotherapy based on both patient-specific and tumour-specific characteristics. This review aims to rethink the role of multiplex immunostaining in immuno-thoracic oncology, with the current advantages and limitations in the near-daily practice use.

MYC Deregulation and PTEN Loss Model Tumor and Stromal Heterogeneity of Aggressive Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Sequential Chromogenic IHC: Spatial Analysis of Lymph Nodes Identifies Contact Interactions between Plasmacytoid Dendritic Cells and Plasmablasts

Recent clinical observations have emphasized the critical role that the spatial organization of immune cells in lymphoid structures plays in the success of cancer immunotherapy and patient survival. However, implementing sequential chromogenic IHC (scIHC) to analyze multiple biomarkers on a single tissue section has been limited because of a lack of a standardized, rigorous guide to the development of customized biomarker panels and a need for user-friendly analysis pipelines that can extract meaningful data. In this context, we provide a comprehensive guide for the development of novel biomarker panels for scIHC, using practical examples and illustrations to highlight the most common complications that can arise during the setup of a new biomarker panel, and provide detailed instructions on how to prevent and detect cross-reactivity between secondary reagents and carryover between detection antibodies. We also developed a novel analysis pipeline based on non-rigid tissue deformation correction, Cellpose-inspired automated cell segmentation, and computational network masking of low-quality data. We applied this biomarker panel and pipeline to study regional lymph nodes from patients with head and neck cancer, identifying novel contact interactions between plasmablasts and plasmacytoid dendritic cells in vivo. Given that Toll-like receptors, which are highly expressed in plasmacytoid dendritic cells, play a key role in vaccine efficacy, the significance of this cell-cell interaction decisively warrants further studies. In summary, this work provides a streamlined approach to the development of customized biomarker panels for scIHC that will ultimately improve our understanding of immune responses in cancer.

Significance

We present a comprehensive guide for developing customized biomarker panels to investigate cell-cell interactions in the context of immune responses in cancer. This approach revealed novel contact interactions between plasmablasts and plasmacytoid dendritic cells in lymph nodes from patients with head and neck cancer.

Spatially resolved multimarker evaluation of CD274 (PD-L1)/PDCD1 (PD-1) immune checkpoint expression and macrophage polarisation in colorectal cancer

Background

The CD274 (PD-L1)/PDCD1 (PD-1) immune checkpoint interaction may promote cancer progression, but the expression patterns and prognostic significance of PD-L1 and PD-1 in the colorectal cancer microenvironment are inadequately characterised.

Methods

We used a custom 9-plex immunohistochemistry assay to quantify the expression patterns of PD-L1 and PD-1 in macrophages, T cells, and tumour cells in 910 colorectal cancer patients. We evaluated cancer-specific mortality according to immune cell subset densities using multivariable Cox regression models.

Results

Compared to PD-L1– macrophages, PD-L1+ macrophages were more likely M1-polarised than M2-polarised and located closer to tumour cells. PD-L1+ macrophage density in the invasive margin associated with longer cancer-specific survival [Ptrend = 0.0004, HR for the highest vs. lowest quartile, 0.52; 95% CI: 0.34–0.78]. T cell densities associated with longer cancer-specific survival regardless of PD-1 expression (Ptrend < 0.005 for both PD-1+ and PD-1– subsets). Higher densities of PD-1+ T cell/PD-L1+ macrophage clusters associated with longer cancer-specific survival (Ptrend < 0.005).

Conclusions

PD-L1+ macrophages show distinct polarisation profiles (more M1-like), spatial features (greater co-localisation with tumour cells and PD-1+ T cells), and associations with favourable clinical outcome. Our comprehensive multimarker assessment could enhance the understanding of immune checkpoints in the tumour microenvironment and promote the development of improved immunotherapies.

Panobinostat Induced Spatial In Situ Biomarkers Predictive of Anti-PD-1 Efficacy in Mouse Mammary Carcinoma

Immunotherapies, including anti-PD-1 immune checkpoint blocking (ICB) antibodies, have revolutionized the treatment of many solid malignancies. However, their efficacy in breast cancer has been limited to a subset of patients with triple-negative breast cancer, where ICBs are routinely combined with a range of cytotoxic and targeted agents. Reliable biomarkers predictive of the therapeutic response to ICB in breast cancer are critically missing, though a combination response has been associated with immunogenic cell death (ICD). Here, we utilized a recently developed integrated analytical platform, the multiplex implantable microdevice assay (MIMA), to evaluate the presence and spatial cell relations of literature-based candidate markers predictive of ICB efficacy in luminal mouse mammary carcinoma. MIMA integrates (i) an implantable microdevice for the localized delivery of small amounts of drugs inside the tumor bed with (ii) sequential multiplex immunohistochemistry (mIHC) and spatial cell analysis pipelines to rapidly (within days) describe drug mechanisms of action and find predictive biomarkers in complex tumor tissue. We show that the expression of cleaved caspase-3, ICAM-1, neuropilin-1, myeloperoxidase, calreticulin, galectin-3, and PD-L1 were spatially associated with the efficacy of panobinostat, a pan-HDAC inhibitor that was previously shown to induce immunogenic cell death and synergize with anti-PD-1 in breast cancer. PD-L1 by itself, however, was not a reliable predictor. Instead, ICB efficacy was robustly identified through the in situ hotspot detection of galectin-3-positive non-proliferating tumor zones enriched in cell death and infiltrated by anti-tumor cytotoxic neutrophils positive for ICAM-1 and neuropilin-1. Such hotspots can be specifically detected using distance-based cluster analyses. Single-cell measurements of the functional states in the tumor microenvironment suggest that both qualitative and quantitative effects might drive effective therapy responses. Overall, the presented study provides (i) complementary biological knowledge about the earliest cell events of induced anti-tumor immunity in breast cancer, including the emergence of resistant cancer stem cells, and (ii) newly identified biomarkers in form of specific spatial cell associations. The approach used standard cell-type-, IHC-, and FFPE-based techniques, and therefore the identified spatial clustering of in situ biomarkers can be readily integrated into existing clinical or research workflows, including in luminal breast cancer. Since early drug responses were detected, the biomarkers could be especially applicable to window-of-opportunity clinical trials to rapidly discriminate between responding and resistant patients, thus limiting unnecessary treatment-associated toxicities.

Modulation of myeloid and T cells in vivo by Bruton's tyrosine kinase inhibitor ibrutinib in patients with metastatic pancreatic ductal adenocarcinoma

BACKGROUND

In preclinical studies of pancreatic ductal adenocarcinoma (PDAC), ibrutinib improved the antitumor efficacy of the standard of care chemotherapy. This led to a phase 1b clinical trial to determine the safety, tolerability, and immunologic effects of ibrutinib treatment in patients with advanced PDAC.

METHODS

Previously untreated patients with PDAC were enrolled in a phase 1b clinical trial (ClinicalTrials.gov) to determine the safety, toxicity, and maximal tolerated dose of ibrutinib when administered with the standard regimen of gemcitabine and nab-paclitaxel. To study the immune response to ibrutinib alone, the trial included an immune response arm where patients were administered with ibrutinib daily for a week followed by ibrutinib combined with gemcitabine and nab-paclitaxel. Endoscopic ultrasonography-guided primary PDAC tumor biopsies and blood were collected before and after ibrutinib monotherapy. Changes in abundance and functional state of immune cells in the blood was evaluated by mass cytometry by time of flight and statistical scaffold analysis, while that in the local tumor microenvironment (TME) were assessed by multiplex immunohistochemistry. Changes in B-cell receptor and T-cell receptor repertoire were assessed by sequencing and analysis of clonality.

RESULTS

In the blood, ibrutinib monotherapy significantly increased the frequencies of activated inducible T cell costimulator⁺(ICOS⁺) CD4⁺ T cells and monocytes. Within the TME, ibrutinib monotherapy led to a trend in decreased B-cell abundance but increased interleukin-10⁺ B-cell frequency. Monotherapy also led to a trend in increased mature CD208⁺dendritic cell density, increased late effector (programmed cell death protein 1 (PD-1^-) eomesodermin (EOMES⁺)) CD8⁺ T-cell frequency, with a concomitantly decreased dysfunctional (PD-1⁺ EOMES⁺) CD8⁺ T-cell frequency. When ibrutinib was combined with chemotherapy, most of these immune changes were not observed. Patients with partial clinical responses had more diverse T and B cell receptor repertoires prior to therapy initiation.

CONCLUSION

Ibrutinib monotherapy skewed the immune landscape both in the circulation and TME towards activated T cells, monocytes and DCs. These effects were not observed when combining ibrutinib with standard of care chemotherapy. Future studies may focus on other therapeutic combinations that augment the immunomodulatory effects of ibrutinib in solid tumors.

TRIAL REGISTRATION NUMBER

NCT02562898.

Methods for assessment of the tumour microenvironment and immune interactions in non-small cell lung cancer. A narrative review

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer death worldwide. Immunotherapy with immune checkpoint inhibitors (ICI) has significantly improved outcomes in some patients, however 80-85% of patients receiving immunotherapy develop primary resistance, manifesting as a lack of response to therapy. Of those that do have an initial response, disease progression may occur due to acquired resistance. The make-up of the tumour microenvironment (TME) and the interaction between tumour infiltrating immune cells and cancer cells can have a large impact on the response to immunotherapy. Robust assessment of the TME with accurate and reproducible methods is vital to understanding mechanisms of immunotherapy resistance. In this paper we will review the evidence of several methodologies to assess the TME, including multiplex immunohistochemistry, imaging mass cytometry, flow cytometry, mass cytometry and RNA sequencing.

A multiplex implantable microdevice assay identifies synergistic combinations of cancer immunotherapies and conventional drugs

Systematically identifying synergistic combinations of targeted agents and immunotherapies for cancer treatments remains difficult. In this study, we integrated high-throughput and high-content techniques-an implantable microdevice to administer multiple drugs into different sites in tumors at nanodoses and multiplexed imaging of tumor microenvironmental states-to investigate the tumor cell and immunological response signatures to different treatment regimens. Using a mouse model of breast cancer, we identified effective combinations from among numerous agents within days. In vivo studies in three immunocompetent mammary carcinoma models demonstrated that the predicted combinations synergistically increased therapeutic efficacy. We identified at least five promising treatment strategies, of which the panobinostat, venetoclax and anti-CD40 triple therapy was the most effective in inducing complete tumor remission across models. Successful drug combinations increased spatial association of cancer stem cells with dendritic cells during immunogenic cell death, suggesting this as an important mechanism of action in long-term breast cancer control.

Multiplex immunohistochemistry reveals cochlear macrophage heterogeneity and local auditory nerve inflammation in cisplatin-induced hearing loss

Inner ear macrophages play a vital role in cochlear homeostasis. Recent studies have demonstrated the existence of macrophages at different sites of the cochlea, with increased cochlear infiltration as an inflammatory response mechanism to injury. However, current methods, such as conventional immunohistochemistry and flow cytometry, provide limited information about the diversity of cochlear macrophages. Recently, multiplex immunohistochemistry (mIHC) successfully identified the heterogeneity of immune cells in cancer tissue and thereby improved our understanding of the disease prognosis. In this study, we modified the mIHC technique for cochlear tissue and utilized it to investigate cochlear macrophage behavior and heterogeneity before and after exposure to ototoxic drugs such as cisplatin. Four-week-old C57BL/6N female mice were intraperitoneally injected with cisplatin at 5 mg/kg/day consecutively for 6 days. Their hearing levels were assessed before and after the injection. Their cochleae were harvested before (day 0) and on days 8 and 15 after the cisplatin injection. Paraffin-embedded sections were sequentially immunostained using macrophage surface markers to identify the different categories of macrophages. Each immunostaining cycle included incubation with primary antibody, incubation with secondary antibody, chromogenic staining, and image scanning. Thereafter, all antibodies were stripped out, and antigen retrieval was performed to prepare the tissue for the next cycle. The results revealed that activated cochlear macrophages were not entirely differentiated into M1 or M2 categories but into multi-marker M1/M2 mixed macrophages. Furthermore, the ratio of these mixed (M1/M2) macrophages to Iba1+ macrophages increased in the auditory nerve after cisplatin exposure, suggesting local auditory nerve inflammation. The increase in the population of activated macrophages in the auditory nerve region was concomitant with the temporary shift of hearing threshold on day 8 post-cisplatin injection. The findings of this study indicate the effectiveness of mIHC in identifying cochlear macrophage heterogeneity both in the resting state and after cisplatin exposure. Therefore, mIHC could be a powerful tool in cochlear immunology research. Our findings may provide new insights into the co-relation between the cochlear macrophage and cisplatin exposure.

A Cancer Cell-Intrinsic GOT2-PPARδ Axis Suppresses Antitumor Immunity

Despite significant recent advances in precision medicine, pancreatic ductal adenocarcinoma (PDAC) remains near uniformly lethal. Although immune-modulatory therapies hold promise to meaningfully improve outcomes for patients with PDAC, the development of such therapies requires an improved understanding of the immune evasion mechanisms that characterize the PDAC microenvironment. Here, we show that cancer cell-intrinsic glutamic-oxaloacetic transaminase 2 (GOT2) shapes the immune microenvironment to suppress antitumor immunity. Mechanistically, we find that GOT2 functions beyond its established role in the malate-aspartate shuttle and promotes the transcriptional activity of nuclear receptor peroxisome proliferator-activated receptor delta (PPARδ), facilitated by direct fatty acid binding. Although GOT2 is dispensable for cancer cell proliferation in vivo, the GOT2-PPARδ axis promotes spatial restriction of both CD4+ and CD8+ T cells from the tumor microenvironment. Our results demonstrate a noncanonical function for an established mitochondrial enzyme in transcriptional regulation of immune evasion, which may be exploitable to promote a productive antitumor immune response.

SIGNIFICANCE

Prior studies demonstrate the important moonlighting functions of metabolic enzymes in cancer. We find that the mitochondrial transaminase GOT2 binds directly to fatty acid ligands that regulate the nuclear receptor PPARδ, and this functional interaction critically regulates the immune microenvironment of pancreatic cancer to promote tumor progression. See related commentary by Nwosu and di Magliano, p. 2237.. This article is highlighted in the In This Issue feature, p. 2221.

Therapeutics That Promote Sympathetic Reinnervation Modulate the Inflammatory Response After Myocardial Infarction

Myocardial infarction (MI) triggers an inflammatory response that transitions from pro-inflammatory to reparative over time. Restoring sympathetic nerves in the heart after MI prevents arrhythmias. This study investigated if reinnervation altered the immune response after MI. This study used quantitative multiplex immunohistochemistry to identify the immune cells present in the heart 2 weeks after ischemia-reperfusion. Two therapeutics stimulated reinnervation, preventing arrhythmias and shifting the immune response from inflammatory to reparative, with fewer pro-inflammatory macrophages and more regulatory T cells and reparative macrophages. Treatments did not alter macrophage phenotype in vitro, which suggested reinnervation contributed to the altered immune response.

Mechanisms of dermatologic toxicities to immune checkpoint inhibitor cancer therapies

The discovery of immune checkpoint inhibition (ICI) sparked a revolution in the era of targeted anticancer therapy. While monoclonal antibodies targeting the CTLA-4 and PD-1 axes have improved survival in patients with advanced cancers, these immunotherapies are associated with a wide spectrum of dermatologic immune-related adverse events (irAEs). Several publications have addressed the clinical and histopathologic classification of these skin-directed irAEs, their impact on antitumor immunity and survival, and the critical role of supportive oncologic dermatology in their management. Here, we review the current understanding of the mechanistic drivers of immune-related skin toxicities with a focus on inflammatory, immunobullous, melanocyte/pigment-related reactions. We detail the specific immune-based mechanisms that may underlie different cutaneous reactions. We also discuss potential mechanisms as they relate to non-cutaneous irAEs and potential overlap with cutaneous irAEs, techniques to study differences in immune-related versus de novo skin reactions, and how treatment of these adverse events impacts cancer treatment, patient quality of life, and overall survival. An improved understanding of the mechanistic basis of cutaneous irAEs will allow us to develop and utilize blood-based biomarkers that could help ultimately predict onset and/or severity of these irAEs and to implement rational mechanistic-based treatment strategies that are targeted to the irAEs while potentially avoiding abrogating anti-tumor effect of ICIs.

Deciphering the Immune Complexity in Esophageal Adenocarcinoma and Pre-Cancerous Lesions With Sequential Multiplex Immunohistochemistry and Sparse Subspace Clustering Approach

Esophageal adenocarcinoma (EAC) develops from a chronic inflammatory environment across four stages: intestinal metaplasia, known as Barrett's esophagus, low- and high-grade dysplasia, and adenocarcinoma. Although the genomic characteristics of this progression have been well defined via large-scale DNA sequencing, the dynamics of various immune cell subsets and their spatial interactions in their tumor microenvironment remain unclear. Here, we applied a sequential multiplex immunohistochemistry (mIHC) platform with computational image analysis pipelines that allow for the detection of 10 biomarkers in one formalin-fixed paraffin-embedded (FFPE) tissue section. Using this platform and quantitative image analytics, we studied changes in the immune landscape during disease progression based on 40 normal and diseased areas from endoscopic mucosal resection specimens of chemotherapy treatment- naïve patients, including normal esophagus, metaplasia, low- and high-grade dysplasia, and adenocarcinoma. The results revealed a steady increase of FOXP3+ T regulatory cells and a CD163+ myelomonocytic cell subset. In parallel to the manual gating strategy applied for cell phenotyping, we also adopted a sparse subspace clustering (SSC) algorithm allowing the automated cell phenotyping of mIHC-based single-cell data. The algorithm successfully identified comparable cell types, along with significantly enriched FOXP3 T regulatory cells and CD163+ myelomonocytic cells as found in manual gating. In addition, SCC identified a new CSF1R+CD1C+ myeloid lineage, which not only was previously unknown in this disease but also increases with advancing disease stages. This study revealed immune dynamics in EAC progression and highlighted the potential application of a new multiplex imaging platform, combined with computational image analysis on routine clinical FFPE sections, to investigate complex immune populations in tumor ecosystems.

A framework for multiplex imaging optimization and reproducible analysis

Multiplex imaging technologies are increasingly used for single-cell phenotyping and spatial characterization of tissues; however, transparent methods are needed for comparing the performance of platforms, protocols and analytical pipelines. We developed a python software, mplexable, for reproducible image processing and utilize Jupyter notebooks to share our optimization of signal removal, antibody specificity, background correction and batch normalization of the multiplex imaging with a focus on cyclic immunofluorescence (CyCIF). Our work both improves the CyCIF methodology and provides a framework for multiplexed image analytics that can be easily shared and reproduced.

An approach for tissue image analysis applicable to highly multiplexed immunofluorescence imaging of the spatial distribution of multiple protein biomarkers is proposed, here applied to the analysis of multiplex IF using the multiplex imaging platform, CyCIF.

Characterization of anticancer drug resistance by reverse-phase protein array: new targets and strategies

INTRODUCTION

Drug resistance is the main barrier to achieving cancer cures with medical therapy. Cancer drug resistance occurs, in part, due to adaptation of the tumor and microenvironment to therapeutic stress at a proteomic level. Reverse-phase protein arrays (RPPA) are well suited to proteomic analysis of drug resistance due to high sample throughput, sensitive detection of phosphoproteins, and validation for a large number of critical cellular pathways.

AREAS COVERED

This review summarizes contributions of RPPA to understanding and combating drug resistance. In particular, contributions of RPPA to understanding resistance to PARP inhibitors, BRAF inhibitors, immune checkpoint inhibitors, and breast cancer investigational therapies are discussed. Articles reviewed were identified by MEDLINE, Scopus, and Cochrane search for keywords 'proteomics,' 'reverse-phase protein array,' 'drug resistance,' 'PARP inhibitor,' 'BRAF inhibitor,' 'immune checkpoint inhibitor,' and 'I-SPY' spanning October 1, 1960 - October 1, 2021.

EXPERT OPINION

Precision oncology has thus far failed to convert the armament of targeted therapies into durable responses for most patients, highlighting that genetic sequencing alone is insufficient to guide therapy selection and overcome drug resistance. Combined genomic and proteomic analyses paired with creative drug combinations and dosing strategies hold promise for maturing precision oncology into an era of improved patient outcomes.

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging

Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data. We demonstrate the use of MCMICRO on tissue and tumor images acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.

Safety and Efficacy of Pembrolizumab in Combination with Acalabrutinib in Advanced Head and Neck Squamous Cell Carcinoma: Phase 2 Proof-of-Concept Study

PURPOSE

Programmed cell death-1 (PD-1) receptor inhibitors have shown efficacy in head and neck squamous cell carcinoma (HNSCC), but treatment failure or secondary resistance occurs in most patients. In preclinical murine carcinoma models, inhibition of Bruton's tyrosine kinase (BTK) induces myeloid cell reprogramming that subsequently bolsters CD8+ T cell responses, resulting in enhanced antitumor activity. This phase 2, multicenter, open-label, randomized study evaluated pembrolizumab (anti-PD-1 monoclonal antibody) plus acalabrutinib (BTK inhibitor) in recurrent or metastatic HNSCC.

PATIENTS AND METHODS

Patients received pembrolizumab 200 mg intravenously every 3 weeks, alone or in combination with acalabrutinib 100 mg orally twice daily. Safety and overall response rate (ORR) were co-primary objectives. The secondary objectives were progression-free survival (PFS) and overall survival.

RESULTS

Seventy-six patients were evaluated (pembrolizumab, n = 39; pembrolizumab + acalabrutinib, n = 37). Higher frequencies of grade 3-4 treatment-emergent adverse events (AE; 65% vs. 39%) and serious AEs (68% vs. 31%) were observed with combination therapy versus monotherapy. ORR was 18% with monotherapy versus 14% with combination therapy. Median PFS was 2.7 [95% confidence interval (CI), 1.4-6.8] months in the combination arm and 1.7 (95% CI, 1.4-4.0) months in the monotherapy arm. The study was terminated due to lack of clinical benefit with combination treatment. To assess how tumor immune contexture was affected by therapy in patients with pre- and post-treatment biopsies, spatial proteomic analyses were conducted that revealed a trend toward increased CD45+ leukocyte infiltration of tumors from baseline at day 43 with pembrolizumab (monotherapy, n = 5; combination, n = 2), which appeared to be higher in combination-treated patients; however, definitive conclusions could not be drawn due to limited sample size.

CONCLUSIONS

Despite lack of clinical efficacy, immune subset analyses suggest that there are additive effects of this combination; however, the associated toxicity limits the feasibility of combination treatment with pembrolizumab and acalabrutinib in patients with recurrent or metastatic HNSCC.

Single-cell spatial architectures associated with clinical outcome in head and neck squamous cell carcinoma

There is increasing evidence that the spatial organization of cells within the tumor-immune microenvironment (TiME) of solid tumors influences survival and response to therapy in numerous cancer types. Here, we report results and demonstrate the applicability of quantitative single-cell spatial proteomics analyses in the TiME of primary and recurrent human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) tumors. Single-cell compositions of a nine patient, primary and recurrent (n = 18), HNSCC cohort is presented, followed by deeper investigation into the spatial architecture of the TiME and its relationship with clinical variables and progression free survival (PFS). Multiple spatial algorithms were used to quantify the spatial landscapes of immune cells within TiMEs and demonstrate that neoplastic tumor-immune cell spatial compartmentalization, rather than mixing, is associated with longer PFS. Mesenchymal (αSMA⁺) cellular neighborhoods describe distinct immune landscapes associated with neoplastic tumor-immune compartmentalization and improved patient outcomes. Results from this investigation are concordant with studies in other tumor types, suggesting that trends in TiME cellular heterogeneity and spatial organization may be shared across cancers and may provide prognostic value in multiple cancer types.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

Characterization of the tumor immune microenvironment of sinonasal squamous-cell carcinoma

BACKGROUND

Treatment and prognosis of sinonasal squamous-cell carcinoma (SNSCC) have not significantly improved despite improvements in radical therapy. Characterization of the tumor immune microenvironment (TiME) may identify patient subgroups associated with disease recurrence, and provide new biomarkers for improved patient stratification and treatment.

METHODS

The TiME was quantitatively evaluated by multiplex immunohistochemistry (mIHC) in archived tissue sections from 38 patients with SNSCC, and were assessed for differences between recurrent (n = 20) and nonrecurrent (n = 18) groups. Hierarchical clustering analyses were performed to identify phenotypic TiME subgroups within the cohort and were used to compare survival outcomes.

RESULTS

Our mIHC analysis revealed increased T-cell populations and decreased myeloid-cell populations in SNSCC patients without recurrent disease, as compared with patients with recurrent disease. Within T-cell subsets, there was a significantly higher percentage of granzyme B⁺ , T-bet⁺ , Eomes⁺ T cells, as well as higher proliferation of CD8⁺ T cells within the nonrecurrent group relative to the recurrent group. Furthermore, immune-cell complexity profiles of SNSCC revealed hyper- and hypo-T-cell-inflamed, myeloid-inflamed, B-cell-inflamed, and broadly hypoinflamed subtypes not previously identified by gene expression analyses. Our study revealed that presence of either hyper- or hypo-T-cell-inflamed TiME subtypes were associated with increased survival outcomes as compared with broadly hypoinflamed TiME subtypes (p = 0.035 and 0.0376, respectively).

CONCLUSIONS

The TiME of SNSCC reveals distinct subtypes, which may correlate with recurrence and survival outcomes.

From imaging a single cell to implementing precision medicine: an exciting new era

In the age of high-throughput, single-cell biology, single-cell imaging has evolved not only in terms of technological advancements but also in its translational applications. The synchronous advancements of imaging and computational biology have produced opportunities of merging the two, providing the scientific community with tools towards observing, understanding, and predicting cellular and tissue phenotypes and behaviors. Furthermore, multiplexed single-cell imaging and machine learning algorithms now enable patient stratification and predictive diagnostics of clinical specimens. Here, we provide an overall summary of the advances in single-cell imaging, with a focus on high-throughput microscopy phenomics and multiplexed proteomic spatial imaging platforms. We also review various computational tools that have been developed in recent years for image processing and downstream applications used in biomedical sciences. Finally, we discuss how harnessing systems biology approaches and data integration across disciplines can further strengthen the exciting applications and future implementation of single-cell imaging on precision medicine.

Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies

In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor rapid progressor, likely due to indifference to the effects of PARP inhibition. Together, identification of PARPi-induced emergent changes could be used to select patient specific combination therapies, based on tumor and immune state changes.

Fluorescent Multiplex Immunohistochemistry Coupled With Other State-Of-The-Art Techniques to Systematically Characterize the Tumor Immune Microenvironment

Our expanding knowledge of the interactions between tumor cells and their microenvironment has helped to revolutionize cancer treatments, including the more recent development of immunotherapies. Immune cells are an important component of the tumor microenvironment that influence progression and treatment responses, particularly to the new immunotherapies. Technological advances that help to decipher the complexity and diversity of the tumor immune microenvironment (TIME) are increasingly used in translational research and biomarker studies. Current techniques that facilitate TIME evaluation include flow cytometry, multiplex bead-based immunoassays, chromogenic immunohistochemistry (IHC), fluorescent multiplex IHC, immunofluorescence, and spatial transcriptomics. This article offers an overview of our representative data, discusses the application of each approach to studies of the TIME, including their advantages and challenges, and reviews the potential clinical applications. Flow cytometry and chromogenic and fluorescent multiplex IHC were used to immune profile a HER2+ breast cancer, illustrating some points. Spatial transcriptomic analysis of a luminal B breast tumor demonstrated that important additional insight can be gained from this new technique. Finally, the development of a multiplex panel to identify proliferating B cells, Tfh, and Tfr cells on the same tissue section demonstrates their co-localization in tertiary lymphoid structures.

The role of the tumor matrix environment in progression of head and neck cancer

PURPOSE OF REVIEW

Head and neck squamous cell carcinoma (HNSCC) tissue is composed of multiple cell types embedded in an extracellular matrix (ECM) that actively participates in disease progression, spread and treatment response. In this review, we provide an update of our current knowledge about the ECM landscape of HNSCC, its functions, methods of analysis, and nonimmunological stromal targeting strategies that modify the tumor ECM to improve conventional and emerging therapies.

RECENT FINDINGS

The tumor ECM differs significantly from that of normal tissue in abundance, composition, organization and mechanical properties. In HNSCC, signaling between malignant epithelial cells and stromal cells prompts the upregulation of a set of ECM components that serve as substrates for carcinoma cell migration, modulate the cytokine environment and promote immune evasion in these tumors. Advanced imaging techniques and molecular profiling at the single-cell level have provided valuable insights into our understanding of the tumor ECM and its role in malignancy, and opened new avenues for predictive and potentially actionable biomarker discovery for more effective management of the disease.

SUMMARY

ECM components upregulated in HNSCC can impact several cancer hallmarks by sustaining proliferative signaling, promoting angiogenesis, facilitating invasion and metastasis, modulating growth suppressor activity, and suppressing antitumoral immunity. The tumor ECM is also involved in treatment resistance, making it a potential therapeutic target.

Neoadjuvant Selicrelumab, an Agonist CD40 Antibody, Induces Changes in the Tumor Microenvironment in Patients with Resectable Pancreatic Cancer

PURPOSE

CD40 activation is a novel clinical opportunity for cancer immunotherapy. Despite numerous active clinical trials with agonistic CD40 monoclonal antibodies (mAb), biological effects and treatment-related modulation of the tumor microenvironment (TME) remain poorly understood.

PATIENTS AND METHODS

Here, we performed a neoadjuvant clinical trial of agonistic CD40 mAb (selicrelumab) administered intravenously with or without chemotherapy to 16 patients with resectable pancreatic ductal adenocarcinoma (PDAC) before surgery followed by adjuvant chemotherapy and CD40 mAb.

RESULTS

The toxicity profile was acceptable, and overall survival was 23.4 months (95% confidence interval, 18.0-28.8 months). Based on a novel multiplexed immunohistochemistry platform, we report evidence that neoadjuvant selicrelumab leads to major differences in the TME compared with resection specimens from treatment-naïve PDAC patients or patients given neoadjuvant chemotherapy/chemoradiotherapy only. For selicrelumab-treated tumors, 82% were T-cell enriched, compared with 37% of untreated tumors (P = 0.004) and 23% of chemotherapy/chemoradiation-treated tumors (P = 0.012). T cells in both the TME and circulation were more active and proliferative after selicrelumab. Tumor fibrosis was reduced, M2-like tumor-associated macrophages were fewer, and intratumoral dendritic cells were more mature. Inflammatory cytokines/sec CXCL10 and CCL22 increased systemically after selicrelumab.

CONCLUSIONS

This unparalleled examination of CD40 mAb therapeutic mechanisms in patients provides insights for design of subsequent clinical trials targeting CD40 in cancer.

Spatial omics and multiplexed imaging to explore cancer biology

Understanding intratumoral heterogeneity-the molecular variation among cells within a tumor-promises to address outstanding questions in cancer biology and improve the diagnosis and treatment of specific cancer subtypes. Single-cell analyses, especially RNA sequencing and other genomics modalities, have been transformative in revealing novel biomarkers and molecular regulators associated with tumor growth, metastasis and drug resistance. However, these approaches fail to provide a complete picture of tumor biology, as information on cellular location within the tumor microenvironment is lost. New technologies leveraging multiplexed fluorescence, DNA, RNA and isotope labeling enable the detection of tens to thousands of cancer subclones or molecular biomarkers within their native spatial context. The expeditious growth in these techniques, along with methods for multiomics data integration, promises to yield a more comprehensive understanding of cell-to-cell variation within and between individual tumors. Here we provide the current state and future perspectives on the spatial technologies expected to drive the next generation of research and diagnostic and therapeutic strategies for cancer.

Clinical and research applications of multiplexed immunohistochemistry and in situ hybridization

Over the past decade, invention and adoption of novel multiplexing technologies for tissues have made increasing impacts in basic and translational research and, to a lesser degree, clinical medicine. Platforms capable of highly multiplexed immunohistochemistry or in situ RNA measurements promise evaluation of protein or RNA targets at levels of plex and sensitivity logs above traditional methods - all with preservation of spatial context. These methods promise objective biomarker quantification, markedly increased sensitivity, and single-cell resolution. Increasingly, development of novel technologies is enabling multi-omic interrogations with spatial correlation of RNA and protein expression profiles in the same sample. Such sophisticated methods will provide unprecedented insights into tissue biology, biomarker science, and, ultimately, patient health. However, this sophistication comes at significant cost, requiring extensive time, practical knowledge, and resources to implement. This review will describe the technical features, advantages, and limitations of currently available multiplexed immunohistochemistry and spatial transcriptomic platforms. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Leukocyte Heterogeneity in Pancreatic Ductal Adenocarcinoma: Phenotypic and Spatial Features Associated with Clinical Outcome

Immunotherapies targeting aspects of T cell functionality are efficacious in many solid tumors, but pancreatic ductal adenocarcinoma (PDAC) remains refractory to these treatments. Deeper understanding of the PDAC immune ecosystem is needed to identify additional therapeutic targets and predictive biomarkers for therapeutic response and resistance monitoring. To address these needs, we quantitatively evaluated leukocyte contexture in 135 human PDACs at single-cell resolution by profiling density and spatial distribution of myeloid and lymphoid cells within histopathologically defined regions of surgical resections from treatment-naive and presurgically (neoadjuvant)-treated patients and biopsy specimens from metastatic PDAC. Resultant data establish an immune atlas of PDAC heterogeneity, identify leukocyte features correlating with clinical outcomes, and, through an in silico study, provide guidance for use of PDAC tissue microarrays to optimally measure intratumoral immune heterogeneity. Atlas data have direct applicability as a reference for evaluating immune responses to investigational neoadjuvant PDAC therapeutics where pretherapy baseline specimens are not available. SIGNIFICANCE: We provide a phenotypic and spatial immune atlas of human PDAC identifying leukocyte composition at steady state and following standard neoadjuvant therapies. These data have broad utility as a resource that can inform on leukocyte responses to emerging therapies where baseline tissues were not acquired.This article is highlighted in the In This Issue feature, p. 1861.

Single-cell transcriptomic analysis of mIHC images via antigen mapping

Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA sequencing data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling the systematic annotation of nuanced cell populations, spatial patterns of transcription, and interactions between cell types. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published cytometry and mIHC data of this organ.

Phosphorylation of SMAD3 in immune cells predicts survival of patients with early stage non-small cell lung cancer

Background

The interplay of immune and cancer cells takes place in the tumor microenvironment where multiple signals are exchanged. The transforming growth factor beta (TGFB) pathway is known to be dysregulated in lung cancer and can impede an effective immune response. However, the exact mechanisms are yet to be determined. Especially which cells respond and where does this signaling take place with respect to the local microenvironment.

Methods

Human non-small cell lung cancer samples were retrospectively analyzed by multiplexed immunohistochemistry for SMAD3 phosphorylation and programmed death ligand 1 expression in different immune cells with respect to their localization within the tumor tissue. Spatial relationships were studied to examine possible cell-cell interactions and analyzed in conjunction with clinical data.

Results

TGFB pathway activation in CD3, CD8, Foxp3 and CD68 cells, as indicated by SMAD3 phosphorylation, negatively impacts overall and partially disease-free survival of patients with lung cancerindependent of histological subtype. A high frequency of Foxp3 regulatory T cells positive for SMAD3 phosphorylation in close vicinity of CD8 T cells within the tumor discriminate a rapidly progressing group of patients with lung cancer.

Conclusions

TGFB pathway activation of local immune cells within the tumor microenvironment impacts survival of early stage lung cancer. This might benefit patients not eligible for targeted therapies or immune checkpoint therapy as a therapeutic option to re-activate the local immune response.

Prostate Cancer Peripheral Blood NK Cells Show Enhanced CD9, CD49a, CXCR4, CXCL8, MMP-9 Production and Secrete Monocyte-Recruiting and Polarizing Factors

Natural killer (NK) cells, effector lymphocytes of the innate immunity, have been shown to be altered in several cancers, both at tissue and peripheral levels. We have shown that in Non-Small Cell Lung Cancer (NSCLC) and colon cancer, tumour associated circulating NK (TA-NK) and tumour infiltrating NK (TI-NK) exhibit pro-angiogenic phenotype/functions. However, there is still a lack of knowledge concerning the phenotype of peripheral blood (PB) NK (pNK) cells in prostate cancer (PCa). Here, we phenotypically and functionally characterized pNK from PCa patients (PCa TA-NKs) and investigated their interactions with endothelial cells and monocytes/macrophages. NK cell subset distribution in PB of PCa patients was investigated, by multicolor flow cytometry, for surface antigens expression. Protein arrays were performed to characterize the secretome on FACS-sorted pNK cells. Conditioned media (CM) from FACS-sorted PCa pTA-NKs were used to determine their ability to induce pro-inflammatory/pro-angiogenic phenotype/functions in endothelial cells, monocytes, and macrophages. CM from three different PCa (PC-3, DU-145, LNCaP) cell lines, were used to assess their effects on human NK cell polarization in vitro, by multicolor flow cytometry. We found that PCa pTA-NKs acquire the CD56^brightCD9⁺CD49a⁺CXCR4⁺ phenotype, increased the expression of markers of exhaustion (PD-1, TIM-3) and are impaired in their degranulation capabilities. Similar effects were observed on healthy donor-derived pNK cells, exposed to conditioned media of three different PCa cell lines, together with increased production of pro-inflammatory chemokines/chemokine receptors CXCR4, CXCL8, CXCL12, reduced production of TNFα, IFNγ and Granzyme-B. PCa TA-NKs released factors able to support inflammatory angiogenesis in an in vitro model and increased the expression of CXCL8, ICAM-1, and VCAM-1 mRNA in endothelial cells. Secretome analysis revealed the ability of PCa TA-NKs to release pro-inflammatory cytokines/chemokines involved in monocyte recruitment and M2-like polarization. Finally, CMs from PCa pTA-NKs recruit THP-1 and peripheral blood CD14⁺ monocyte and polarize THP-1 and peripheral blood CD14⁺ monocyte-derived macrophage towards M2-like/TAM macrophages. Our results show that PCa pTA-NKs acquire properties related to the pro-inflammatory angiogenesis in endothelial cells, recruit monocytes and polarize macrophage to an M2-like type phenotype. Our data provides a rationale for a potential use of pNK profiling in PCa patients.

Prognostic significance of spatial immune profiles in human solid cancers

Immune-based tumor characteristics in the context of tumor heterogeneity are associated with suppression as well as promotion of cancer progression in various tumor types. As immunity typically functions based on intercellular contacts and short-distance cytokine communications, the location and spatial relationships of the tumor immune microenvironment can provide a framework to understand the biology and potential predictive biomarkers related to disease outcomes. Immune spatial analysis is a newly emerging form of cancer research based on recent methodological advances in in situ single-cell analysis, where cell-cell interaction and the tissue architecture can be analyzed in relation to phenotyping the tumor immune heterogeneity. Spatial characteristics of tumors can be stratified into the tissue architecture level and the single-cell level. At the tissue architecture level, the prognostic significance of the density of immune cell lineages, particularly T cells, is leveraged by understanding longitudinal changes in cell distribution in the tissue architecture such as intra-tumoral and peri-tumoral regions, and invasive margins. At the single-cell level, the proximity of the tumor to the immune cells correlates with disease aggressiveness and therapeutic resistance, providing evidence to understand biological interactions and characteristics of the tumor immune microenvironment. In this review, we summarize recent findings regarding spatial information of the tumor immune microenvironment and review advances and challenges in spatial single-cell analysis toward developing tissue-based biomarkers rooted in the immune spatial landscape.

Immune Surveillance in Clinical Regression of Preinvasive Squamous Cell Lung Cancer

Before squamous cell lung cancer develops, precancerous lesions can be found in the airways. From longitudinal monitoring, we know that only half of such lesions become cancer, whereas a third spontaneously regress. Although recent studies have described the presence of an active immune response in high-grade lesions, the mechanisms underpinning clinical regression of precancerous lesions remain unknown. Here, we show that host immune surveillance is strongly implicated in lesion regression. Using bronchoscopic biopsies from human subjects, we find that regressive carcinoma in situ lesions harbor more infiltrating immune cells than those that progress to cancer. Moreover, molecular profiling of these lesions identifies potential immune escape mechanisms specifically in those that progress to cancer: antigen presentation is impaired by genomic and epigenetic changes, CCL27-CCR10 signaling is upregulated, and the immunomodulator TNFSF9 is downregulated. Changes appear intrinsic to the carcinoma in situ lesions, as the adjacent stroma of progressive and regressive lesions are transcriptomically similar. SIGNIFICANCE: Immune evasion is a hallmark of cancer. For the first time, this study identifies mechanisms by which precancerous lesions evade immune detection during the earliest stages of carcinogenesis and forms a basis for new therapeutic strategies that treat or prevent early-stage lung cancer.See related commentary by Krysan et al., p. 1442.This article is highlighted in the In This Issue feature, p. 1426.