High-dimensional immune-profiling in cancer: implications for immunotherapy

The evolution of immune profiling: will there be a role for nanoparticles?

Immune profiling provides insights into the functioning of the immune system, including the distribution, abundance, and activity of immune cells. This understanding is essential for deciphering how the immune system responds to pathogens, vaccines, tumors, and other stimuli. Analyzing diverse immune cell types facilitates the development of personalized medicine approaches by characterizing individual variations in immune responses. With detailed immune profiles, clinicians can tailor treatment strategies to the specific immune status and needs of each patient, maximizing therapeutic efficacy while minimizing adverse effects. In this review, we discuss the evolution of immune profiling, from interrogating bulk cell samples in solution to evaluating the spatially-rich molecular profiles across intact preserved tissue sections. We also review various multiplexed imaging platforms recently developed, based on immunofluorescence and imaging mass spectrometry, and their impact on the field of immune profiling. Identifying and localizing various immune cell types across a patient's sample has already provided important insights into understanding disease progression, the development of novel targeted therapies, and predicting treatment response. We also offer a new perspective by highlighting the unprecedented potential of nanoparticles (NPs) that can open new horizons in immune profiling. NPs are known to provide enhanced detection sensitivity, targeting specificity, biocompatibility, stability, multimodal imaging features, and multiplexing capabilities. Therefore, we summarize the recent developments and advantages of NPs, which can contribute to advancing our understanding of immune function to facilitate precision medicine. Overall, NPs have the potential to offer a versatile and robust approach to profile the immune system with improved efficiency and multiplexed imaging power.

Intratumoral Microbiome: Foe or Friend in Reshaping the Tumor Microenvironment Landscape?

The role of the microbiome in cancer and its crosstalk with the tumor microenvironment (TME) has been extensively studied and characterized. An emerging field in the cancer microbiome research is the concept of the intratumoral microbiome, which refers to the microbiome residing within the tumor. This microbiome primarily originates from the local microbiome of the tumor-bearing tissue or from translocating microbiome from distant sites, such as the gut. Despite the increasing number of studies on intratumoral microbiome, it remains unclear whether it is a driver or a bystander of oncogenesis and tumor progression. This review aims to elucidate the intricate role of the intratumoral microbiome in tumor development by exploring its effects on reshaping the multileveled ecosystem in which tumors thrive, the TME. To dissect the complexity and the multitude of layers within the TME, we distinguish six specialized tumor microenvironments, namely, the immune, metabolic, hypoxic, acidic, mechanical and innervated microenvironments. Accordingly, we attempt to decipher the effects of the intratumoral microbiome on each specialized microenvironment and ultimately decode its tumor-promoting or tumor-suppressive impact. Additionally, we portray the intratumoral microbiome as an orchestrator in the tumor milieu, fine-tuning the responses in distinct, specialized microenvironments and remodeling the TME in a multileveled and multifaceted manner.

Tissue biomarkers of immune checkpoint inhibitor therapy

Cancer immunotherapy has been rejuvenated by the growing understanding of the immune system's role in tumor activity over the past two decades. During cancer initiation and progression, tumor cells employ various mechanisms that resemble peripheral immune tolerance to evade the antitumor responses of the immune system. Immune checkpoint molecules are the major mechanism of immune resistance that are exploited by tumor cells to inhibit T-cell activation and suppress immune responses. The targeting of immune checkpoint pathways has led to substantial improvements in survival rates in a number of solid cancers. However, a lack of understanding of the heterogeneity of the tumor microenvironment (TME) has resulted in inefficient therapy responses. A greater understanding of the TME is needed to identify patients likely to respond, and those that will have resistance to immune checkpoint inhibitors (ICIs). Advancement in spatial single-cell technologies has allowed deeper insight into the phenotypic and functional diversities of cells in the TME. In this review, we provide an overview of ICI biomarkers and highlight how high-dimensional spatially resolved, single-cell approaches provide deep molecular insights into the TME and allow for the discovery of biomarkers of clinical benefit.

Translational research on drug development and biomarker discovery for hepatocellular carcinoma

Translational research plays a key role in drug development and biomarker discovery for hepatocellular carcinoma (HCC). However, unique challenges exist in this field because of the limited availability of human tumor samples from surgery, the lack of homogenous oncogenic driver mutations, and the paucity of adequate experimental models. In this review, we provide insights into these challenges and review recent advancements, with a particular focus on the two main agents currently used as mainstream therapies for HCC: anti-angiogenic agents and immunotherapy. First, we examine the pre-clinical and clinical studies to highlight the challenges of determining the optimal therapeutic combinations with biologically effective dosage for HCC. Second, we discuss biomarker studies focusing on anti-PD1/anti-PD-L1-based combination therapy. Finally, we discuss the progress made in our collective understanding of tumor immunology and in multi-omics analysis technology, which enhance our understanding of the mechanisms underlying immunotherapy, characterize different patient subgroups, and facilitate the development of novel combination approaches to improve treatment efficacy. In summary, this review provides a comprehensive overview of efforts in translational research aiming at advancing our understanding of and improving the treatment of HCC.

A transcriptional evaluation of the melanoma and squamous cell carcinoma TIL compartment reveals an unexpected spectrum of exhausted and functional T cells

Introduction

Significant heterogeneity exists within the tumor-infiltrating CD8 T cell population, and exhausted T cells harbor a subpopulation that may be replicating and may retain signatures of activation, with potential functional consequences in tumor progression. Dysfunctional immunity in the tumor microenvironment is associated with poor cancer outcomes, making exploration of these exhausted T cell subpopulations critical to the improvement of therapeutic approaches.

Methods

To investigate mechanisms associated with terminally exhausted T cells, we sorted and performed transcriptional profiling of CD8+ tumor-infiltrating lymphocytes (TILs) co-expressing the exhaustion markers PD-1 and TIM-3 from large-volume melanoma tumors. We additionally performed immunologic phenotyping and functional validation, including at the single-cell level, to identify potential mechanisms that underlie their dysfunctional phenotype.

Results

We identified novel dysregulated pathways in CD8+PD-1+TIM-3+ cells that have not been well studied in TILs; these include bile acid and peroxisome pathway-related metabolism and mammalian target of rapamycin (mTOR) signaling pathways, which are highly correlated with immune checkpoint receptor expression.

Discussion

Based on bioinformatic integration of immunophenotypic data and network analysis, we propose unexpected targets for therapies to rescue the immune response to tumors in melanoma.

Predictive Biomarkers for Immunotherapy in Gastric Cancer: Current Status and Emerging Prospects

Gastric cancer presents substantial management challenges, and the advent of immunotherapy has ignited renewed hope among patients. Nevertheless, a significant proportion of patients do not respond to immunotherapy, and adverse events associated with immunotherapy also occur on occasion, underscoring the imperative to identify suitable candidates for treatment. Several biomarkers, including programmed death ligand-1 expression, tumor mutation burden, mismatch repair status, Epstein-Barr Virus infection, circulating tumor DNA, and tumor-infiltrating lymphocytes, have demonstrated potential in predicting the effectiveness of immunotherapy in gastric cancer. However, the quest for the optimal predictive biomarker for gastric cancer immunotherapy remains challenging, as each biomarker carries its own limitations. Recently, multi-omics technologies have emerged as promising platforms for discovering novel biomarkers that may help in selecting gastric cancer patients likely to respond to immunotherapy. The identification of reliable predictive biomarkers for immunotherapy in gastric cancer holds the promise of enhancing patient selection and improving treatment outcomes. In this review, we aim to provide an overview of clinically established biomarkers of immunotherapy in gastric cancer. Additionally, we introduce newly reported biomarkers based on multi-omics studies in the context of gastric cancer immunotherapy, thereby contributing to the ongoing efforts to refine patient stratification and treatment strategies.

CTLA-4 inhibition facilitates follicular T and B cell interaction and the production of tumor-specific antibodies

Immune checkpoint inhibitors (ICIs) induce activation and expansion of cytotoxic T cells. To depict a comprehensive immune cell landscape reshaped by the CTLA-4 checkpoint inhibitor, we performed single-cell RNA sequencing in a mouse syngeneic tumor transplant model. After CTLA-4 inhibition, tumor regression was accompanied by massive immune cell expansion, especially in T and B cells. We found that B cells in tumor transplant represented follicular, germinal center and plasma B cells, some of which shared identical B cell receptor clonotypes and possessed tumor reactivity. Furthermore, the posttreatment tumor contained a tertiary lymphoid-like structure with intermingled T and B cells. These data suggest germinal center formation within the tumor mass and in situ differentiation of tumor-specific plasma cells. Taken together, our data provide a panoramic view of the immune microenvironment after CTLA-4 inhibition and suggest a role for tumor-specific B cells in antitumor immunity.

A comprehensive multiparameter flow cytometry panel for immune profiling and functional studies of frozen tissue, bone marrow, and spleen

Flow cytometry (FC) is a highly informative technology that can provide valuable information about immune phenotype monitoring and immune cell states. However, there is a paucity of comprehensive panels developed and validated for use on frozen samples. Here, we developed a 17-plex flow cytometry panel to detect subtypes, frequencies, and functions of different immune cells that can be leveraged to study the different cellular characteristics in different disease models, physiological, and pathological conditions. This panel identifies surface markers to characterize T cells (CD8+, CD4+), natural killer (NK) cells and their subtypes (immature, cytotoxic, exhausted, activated),natural killer T (NKT) cells, neutrophils, macrophages (M1 (pro-inflammatory) and M2 (anti-inflammatory)), monocytes and their subtypes (classical and non-classical), dendritic cells (DC) and their subtypes (DC1, DC2), and eosinophils. The panel was designed to include only surface markers to avoid the necessity for fixation and permeabilization steps. This panel was optimized using cryopreserved cells. Immunophenotyping of spleen and bone marrow using the proposed panel was efficient in correctly differentiating the immune cell subtypes in inflammatory model of ligature-induced periodontitis, in which we found increased percentage of NKT cells, activated and mature/cytotoxic NK cells in the bone marrow of affected mice. This panel enables in-depth immunophenotyping of murine immune cells in bone marrow, spleen, tumors, and other non-immune tissues of mice. It could be a tool for systematic analysis of immune cell profiling in inflammatory conditions, systemic diseases, and tumor microenvironments.

Integrated Bioinformatic Analysis of the Correlation of HOXA10 Expression with Survival and Immune Cell Infiltration in Lower Grade Glioma

Homeobox A10 (HOXA10) encodes a transcription factor that regulates developmental processes. Whether HOXA10 mRNA levels in lower grade glioma (LGG) correlate with survival and immune cell infiltration has not been evaluated. The differential expression of HOXA10 in different tumors and their corresponding normal tissues was evaluated by exploring public datasets. The correlations between HOXA10 and survival, tumor immune cell infiltration, diverse gene mutation characteristics, and tumor mutation burden in LGG were also investigated using several independent datasets. Pathway enrichment analysis was conducted to identify HOXA10-associated signaling pathways. We found that HOXA10 expression levels did not significantly differ between LGG tumors and normal tissues. Upon assessing the association between HOXA10 expression and immune cell infiltration in LGG, as expected, HOXA10 gene mRNA levels were positively associated with B-cell and dendritic cell infiltration levels in public online datasets. Different HOXA10 expression groups showed diverse gene mutation characteristics and TMB, and low HOXA10 expression was closely related to improved LGG patient survival. Pathway enrichment analysis of HOXA10-associated genes indicated that the cell cycle signaling pathway may participate in affecting the outcomes of LGG patients. Our findings showed that HOXA10 expression was associated with LGG prognosis and tumor immunity.

MALDI HiPLEX-IHC: multiomic and multimodal imaging of targeted intact proteins in tissues

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is one of the most widely used methods for imaging the spatial distribution of unlabeled small molecules such as metabolites, lipids and drugs in tissues. Recent progress has enabled many improvements including the ability to achieve single cell spatial resolution, 3D-tissue image reconstruction, and the precise identification of different isomeric and isobaric molecules. However, MALDI-MSI of high molecular weight intact proteins in biospecimens has thus far been difficult to achieve. Conventional methods normally require in situ proteolysis and peptide mass fingerprinting, have low spatial resolution, and typically detect only the most highly abundant proteins in an untargeted manner. In addition, MSI-based multiomic and multimodal workflows are needed which can image both small molecules and intact proteins from the same tissue. Such a capability can provide a more comprehensive understanding of the vast complexity of biological systems at the organ, tissue, and cellular levels of both normal and pathological function. A recently introduced top-down spatial imaging approach known as MALDI HiPLEX-IHC (MALDI-IHC for short) provides a basis for achieving this high-information content imaging of tissues and even individual cells. Based on novel photocleavable mass-tags conjugated to antibody probes, high-plex, multimodal and multiomic MALDI-based workflows have been developed to image both small molecules and intact proteins on the same tissue sample. Dual-labeled antibody probes enable multimodal mass spectrometry and fluorescent imaging of targeted intact proteins. A similar approach using the same photocleavable mass-tags can be applied to lectin and other probes. We detail here several examples of MALDI-IHC workflows designed to enable high-plex, multiomic and multimodal imaging of tissues at a spatial resolution as low as 5 µm. This approach is compared to other existing high-plex methods such as imaging mass cytometry, MIBI-TOF, GeoMx and CODEX. Finally, future applications of MALDI-IHC are discussed.

Implementation of Whole-Genome and Transcriptome Sequencing Into Clinical Cancer Care

PURPOSE

The combination of whole-genome and transcriptome sequencing (WGTS) is expected to transform diagnosis and treatment for patients with cancer. WGTS is a comprehensive precision diagnostic test that is starting to replace the standard of care for oncology molecular testing in health care systems around the world; however, the implementation and widescale adoption of this best-in-class testing is lacking.

METHODS

Here, we address the barriers in integrating WGTS for cancer diagnostics and treatment selection and answer questions regarding utility in different cancer types, cost-effectiveness and affordability, and other practical considerations for WGTS implementation.

RESULTS

We review the current studies implementing WGTS in health care systems and provide a synopsis of the clinical evidence and insights into practical considerations for WGTS implementation. We reflect on regulatory, costs, reimbursement, and incidental findings aspects of this test.

CONCLUSION

WGTS is an appropriate comprehensive clinical test for many tumor types and can replace multiple, cascade testing approaches currently performed. Decreasing sequencing cost, increasing number of clinically relevant aberrations and discovery of more complex biomarkers of treatment response, should pave the way for health care systems and laboratories in implementing WGTS into clinical practice, to transform diagnosis and treatment for patients with cancer.

Immunology of Oral Squamous Cell Carcinoma-A Comprehensive Insight with Recent Concepts

This review aims to understand the concept of oral cancer immunology through the notion of immune profiling, immunoediting and immunotherapy, and to gain knowledge regarding its application for the management of oral cancer patients. Oral cancer is an immunogenic tumor where the cells of the tumor microenvironment play an important role in tumorigenesis. Understanding the mechanism of these modulations can help design immunotherapeutic strategies in oral cancer patients. This article gives an overview of immunomodulation in the oral cancer tumor microenvironment, with concepts of immune profiling, immunoediting and immunotherapy. English literature searches via Google Scholar, Web of Science, EBSCO, Scopus, and PubMed database were performed with the key words immunology, tumor microenvironment, cells, cross talk, immune profiling, biomarkers, inflammation, gene expression, techniques, immunoediting, immunosurveillance, tumor escape, immunotherapy, immune checkpoint inhibitors, vaccines in cancer, oral cancer, and head and neck cancer. Original research articles, reviews, and case reports published from 2016-2021 (n = 81) were included to appraise different topics, and were discussed under the following subsections. Literature published on oral cancer immunology reveals that oral cancer immune profiling with appropriate markers and techniques and knowledge on immunoediting concepts can help design and play an effective role in immunotherapeutic management of oral cancer patients. An evaluation of oral cancer immunology helps to determine its role in tumorigenesis, and immunotherapy could be the emerging drift in the effective management of oral cancer.

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.

Spatial heterogeneity and organization of tumor mutation burden with immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer

Background

High tumor mutation burden (TMB-H) could result in an increased number of neoepitopes from somatic mutations expressed by a patient's own tumor cell which can be recognized and targeted by neighboring tumor-infiltrating lymphocytes (TILs). Deeper understanding of spatial heterogeneity and organization of tumor cells and their neighboring immune infiltrates within tumors could provide new insights into tumor progression and treatment response.

Methods

Here we first developed computational approaches using whole slide images (WSIs) to predict bladder cancer patients' TMB status and TILs across tumor regions, and then investigate spatial heterogeneity and organization of regions harboring TMB-H tumor cells and TILs within tumors, as well as their prognostic utility. Results: In experiments using WSIs from The Cancer Genome Atlas (TCGA) bladder cancer (BLCA), our findings show that computational pathology can reliably predict patient-level TMB status and delineate spatial TMB heterogeneity and co-organization with TILs. TMB-H patients with low spatial heterogeneity enriched with high TILs show improved overall survival.

Conclusions

Computational approaches using WSIs have the potential to provide rapid and cost-effective TMB testing and TILs detection. Survival analysis illuminates potential clinical utility of spatial heterogeneity and co-organization of TMB and TILs as a prognostic biomarker in BLCA which warrants further validation in future studies.

PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements

Ultra-multiplexed fluorescence imaging requires the use of spectrally overlapping fluorophores to label proteins and then to unmix the images of the fluorophores. However, doing this remains a challenge, especially in highly heterogeneous specimens, such as the brain, owing to the high degree of variation in the emission spectra of fluorophores in such specimens. Here, we propose PICASSO, which enables more than 15-color imaging of spatially overlapping proteins in a single imaging round without using any reference emission spectra. PICASSO requires an equal number of images and fluorophores, which enables such advanced multiplexed imaging, even with bandpass filter-based microscopy. We show that PICASSO can be used to achieve strong multiplexing capability in diverse applications. By combining PICASSO with cyclic immunofluorescence staining, we achieve 45-color imaging of the mouse brain in three cycles. PICASSO provides a tool for multiplexed imaging with high accessibility and accuracy for a broad range of researchers.

Multifunctional Lipid Bilayer Nanocarriers for Cancer Immunotherapy in Heterogeneous Tumor Microenvironments, Combining Immunogenic Cell Death Stimuli with Immune Modulatory Drugs

In addition to the contribution of cancer cells, the solid tumor microenvironment (TME) has a critical role in determining tumor expansion, antitumor immunity, and the response to immunotherapy. Understanding the details of the complex interplay between cancer cells and components of the TME provides an unprecedented opportunity to explore combination therapy for intervening in the immune landscape to improve immunotherapy outcome. One approach is the introduction of multifunctional nanocarriers, capable of delivering drug combinations that provide immunogenic stimuli for improvement of tumor antigen presentation, contemporaneous with the delivery of coformulated drug or synthetic molecules that provide immune danger signals or interfere in immune-escape, immune-suppressive, and T-cell exclusion pathways. This forward-looking review will discuss the use of lipid-bilayer-encapsulated liposomes and mesoporous silica nanoparticles for combination immunotherapy of the heterogeneous immune landscapes in pancreatic ductal adenocarcinoma and triple-negative breast cancer. We describe how the combination of remote drug loading and lipid bilayer encapsulation is used for the synthesis of synergistic drug combinations that induce immunogenic cell death, interfere in the PD-1/PD-L1 axis, inhibit the indoleamine-pyrrole 2,3-dioxygenase (IDO-1) immune metabolic pathway, restore spatial access to activated T-cells to the cancer site, or reduce the impact of immunosuppressive stromal components. We show how an integration of current knowledge and future discovery can be used for a rational approach to nanoenabled cancer immunotherapy.

Characterization of adipose depot-specific stromal cell populations by single-cell mass cytometry

The increased prevalence of obesity and metabolic diseases has heightened interest in adipose tissue biology and its potential as a therapeutic target. To better understand cellular heterogeneity and complexity of white adipose tissue (WAT), we employed cytometry by time-of-flight (CyTOF) to characterize immune and stromal cells in visceral and subcutaneous WAT depots under normal and high-fat diet feeding, by quantifying the expression levels of 32 surface marker proteins. We observed comparable proportions of immune cells in two WAT depots under steady state, but depot-distinct subtypes of adipose precursor cells (APC), suggesting differences in their adipogenic and fibrogenic potential. Furthermore, in addition to pro-inflammatory immune cell shifts, significant pro-fibrotic changes were observed in APCs under high-fat diet, suggesting that APCs are early responders to dietary challenges. We propose CyTOF as a complementary and alternative tool to current high-throughput single-cell transcriptomic analyses to better understand the function and plasticity of adipose tissue.

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Application of CyTOF for cellular characterization in two adipose depots

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Adipose depot-distinct APC subpopulations

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APCs are early responders under obesogenic conditions to regulate WAT fibrosis

Irradiation immunity interactions

The immune system can influence cancer development by both impeding and/or facilitating tumour growth and spread. A better understanding of this complex relationship is fundamental to optimise current and future cancer therapeutic strategies. Although typically regarded as a localised and immunosuppressive anti‐cancer treatment modality, radiation therapy has been associated with generating profound systemic effects beyond the intended target volume. These systemic effects are immune‐driven suggesting radiation therapy can enhance anti‐tumour immunosurveillance in some instances. In this review, we summarise how radiation therapy can positively and negatively affect local and systemic anti‐tumour immune responses, how co‐administration of immunotherapy with radiation therapy may help promote anti‐tumour immunity, and how the use of immune biomarkers may help steer radiation therapy‐immunotherapy personalisation to optimise clinical outcomes.

Immunomodulation by radiotherapy in tumour control and normal tissue toxicity

Radiotherapy (RT) is a highly effective anticancer treatment that is delivered to more than half of all patients with cancer. In addition to the well-documented direct cytotoxic effects, RT can have immunomodulatory effects on the tumour and surrounding tissues. These effects are thought to underlie the so-called abscopal responses, whereby RT generates systemic antitumour immunity outside the irradiated tumour. The full scope of these immune changes remains unclear but is likely to involve multiple components, such as immune cells, the extracellular matrix, endothelial and epithelial cells and a myriad of chemokines and cytokines, including transforming growth factor-β (TGFβ). In normal tissues exposed to RT during cancer therapy, acute immune changes may ultimately lead to chronic inflammation and RT-induced toxicity and organ dysfunction, which limits the quality of life of survivors of cancer. Here we discuss the emerging understanding of RT-induced immune effects with particular focus on the lungs and gut and the potential immune crosstalk that occurs between these tissues.

Resolving the heterogeneous tumor-centric cellular neighborhood through multiplexed, spatial paracrine interactions in the setting of immune checkpoint blockade

Direct interactions between tumor and immune cells mediate the antitumor effect of all modern cancer immunotherapeutic agents. Simultaneously, tumor cells have evolved mechanisms of evasion including the downregulation of HLA-I potentially disrupting the mechanism of action employed by many immune checkpoint inhibitors. And yet the in situ interplay between these cells within the tumor immune microenvironment (TIME) remains elusive. Recent advances in histologic multiplex bioimaging platforms have enabled in-depth molecular characterization of single cells within spatially-preserved and clinically archived tumor tissues. Herein, we applied multiplex immunofluorescence (MxIF) to excisional lymph node biopsies from 14 patients with metastatic melanoma who experienced clear objective responses to immunotherapy (7 complete response; 7 progressive disease) to determine distinguishing features of the TIME in the pretreatment setting. Distinct regions of the TIME were evaluated using 35 proteins probing tumor, immune and vasculature components across 323 fields of view. Single cell compositional analysis confirmed established prognostic immune cell types including increased prevalence of cytotoxic T cells within the tumor core FOVs of responders. Integrating single cell quantification with the spatial arrangement of cellular neighborhoods surrounding tumor cells revealed novel, spatial immune signatures capable of stratifying TIME based on clinical response. Our analysis revealed dynamic cellular composition of the TCCN based on anatomical subregion, functional expression of HLA-I by the index tumor cell and ultimately clinical response to immunotherapy. Overall, this study provides an analytical framework to resolve the cellular complexity of the TIME, increasingly relevant to the outcomes of modern cancer immunotherapy.

Peripheral Blood Transcriptome in Breast Cancer Patients as a Source of Less Invasive Immune Biomarkers for Personalized Medicine, and Implications for Triple Negative Breast Cancer

Transcriptome studies of peripheral blood cells can advance our understanding of the systemic immune response to the presence of cancer and the mechanisms underlying cancer onset and progression. This enables the identification of novel minimally invasive immune biomarkers for early cancer detection and personalized cancer management and may bring forward new immunotherapy options. Recent blood gene expression analyses in breast cancer (BC) identified distinct patient subtypes that differed in the immune reaction to cancer and were distinct from the clinical BC subtypes, which are categorized based on expression of specific receptors on tumor cells. Introducing new BC subtypes based on peripheral blood gene expression profiles may be appropriate, since it may assist in BC prognosis, the identification of patients likely to benefit from immunotherapy, and treatment efficacy monitoring. Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous, and difficult-to-treat disease, and identification of novel biomarkers for this BC is crucial for clinical decision-making. A few studies have reported TNBC-enriched blood transcriptional signatures, mostly related to strong inflammation and augmentation of altered immune signaling, that can differentiate TNBC from other classical BC subtypes and facilitate diagnosis. Future research is geared toward transitioning from expression signatures in unfractionated blood cells to those in immune cell subpopulations.

Targeting innate immune system by nanoparticles for cancer immunotherapy

Various cancer therapies have advanced remarkably over the past decade. Unlike the direct therapeutic targeting of tumor cells, cancer immunotherapy is a new strategy that boosts the host's immune system...

Interplay between copy number alterations and immune profiles in the early breast cancer Scandinavian Breast Group 2004-1 randomized phase II trial: results from a feasibility study

Emerging data indicate that genomic alterations can shape immune cell composition in early breast cancer. However, there is a need for complementary imaging and sequencing methods for the quantitative assessment of combined somatic copy number alteration (SCNA) and immune profiling in pathological samples. Here, we tested the feasibility of three approaches-CUTseq, for high-throughput low-input SCNA profiling, multiplexed fluorescent immunohistochemistry (mfIHC) and digital-image analysis (DIA) for quantitative immuno-profiling- in archival formalin-fixed paraffin-embedded (FFPE) tissue samples from patients enrolled in the randomized SBG-2004-1 phase II trial. CUTseq was able to reproducibly identify amplification and deletion events with a resolution of 100 kb using only 6 ng of DNA extracted from FFPE tissue and pooling together 77 samples into the same sequencing library. In the same samples, mfIHC revealed that CD4 + T-cells and CD68 + macrophages were the most abundant immune cells and they mostly expressed PD-L1 and PD-1. Combined analysis showed that the SCNA burden was inversely associated with lymphocytic infiltration. Our results set the basis for further applications of CUTseq, mfIHC and DIA to larger cohorts of early breast cancer patients.

High-Throughput Nucleotide Resolution Predictions of Assay Limitations Increase the Reliability and Concordance of Clinical Tests

PURPOSE

The ability of next-generation sequencing (NGS) assays to interrogate thousands of genomic loci has revolutionized genetic testing. However, translation to the clinic is impeded by false-negative results that pose a risk to patients. In response, regulatory bodies are calling for reliability measures to be reported alongside NGS results. Existing methods to estimate reliability do not account for sample- and position-specific variability, which can be significant. Here, we report an approach that computes reliability metrics for every genomic position and sample interrogated by an NGS assay.

METHODS

Our approach predicts the limit of detection (LOD), the lowest reliably detectable variant fraction, by taking technical factors into account. We initially explored how LOD is affected by input material amount, library conversion rate, sequencing coverage, and sequencing error rate. This revealed that LOD depends heavily on genomic context and sample properties. Using these insights, we developed a computational approach to predict LOD on the basis of a biophysical model of the NGS workflow. We focused on targeted assays for cell-free DNA, but, in principle, this approach applies to any NGS assay.

RESULTS

We validated our approach by showing that it accurately predicts LOD and distinguishes reliable from unreliable results when screening 580 lung cancer samples for actionable mutations. Compared with a standard variant calling workflow, our approach avoided most false negatives and improved interassay concordance from 94% to 99%.

CONCLUSION

Our approach, which we name LAVA (LOD-aware variant analysis), reports the LOD for every position and sample interrogated by an NGS assay. This enables reliable results to be identified and improves the transparency and safety of genetic tests.

Mutational profiling of low-grade gliomas identifies prognosis and immunotherapy-related biomarkers and tumour immune microenvironment characteristics

Low-grade glioma (LGG) is a heterogeneous tumour with the median survival rate less than 10 years. Therefore, it is urgent to develop efficient immunotherapy strategies of LGG. In this study, we analysed mutation profiles based on the data of 510 LGG patients from the Cancer Genome Atlas (TCGA) database and investigated the prognostic value of mutated genes and evaluate their immune infiltration. Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to indicate the characteristics of gliomas that respond to immune checkpoint blockade (ICB) therapy. Univariate and multivariate cox regression analysis was performed to identify indicators to construct the nomogram model. 485 (95.47%) of 508 LGG samples showed gene mutation, and 9 mutated genes were significantly related to overall survival (OS), among which 6 mutated genes were significantly correlated with OS between mutation and wildtypes. Immune infiltration and immune score analyses revealed that these six mutated genes were significantly associated with tumour immune microenvironment in LGG. The response of LGG with different characteristics to ICB was evaluated by TIDE algorithm. Finally, CIC gene was screened through both univariate and multivariate Cox regression analyses, and the nomogram model was established to determine the potential prognostic value of CIC in LGG. Our study provides comprehensive analysis of mutated genes in LGG, supporting modulation of mutated genes in the management of LGG.

A Tale of Two Checkpoints: ATR Inhibition and PD-(L)1 Blockade

Innate immunity and the DNA damage response (DDR) pathway are inextricably linked. Within the DDR, ataxia telangiectasia and Rad3-related (ATR) is a key kinase responsible for sensing replication stress and facilitating DNA repair through checkpoint activation, cell cycle arrest, and promotion of fork recovery. Recent studies have shed light on the immunomodulatory role of the ATR-CHK1 pathway in the tumor microenvironment and the specific effects of ATR inhibition in stimulating an innate immune response. With several potent and selective ATR inhibitors in developmental pipelines, the combination of dual ATR and PD-(L)1 blockade has attracted increasing interest in cancer therapy. In this review, we summarize the clinical and preclinical data supporting the combined inhibition of ATR and PD-(L)1, discuss the potential challenges surrounding this approach, and highlight biomarkers relevant for selected patients who are most likely to benefit from the blockade of these two checkpoints. Expected final online publication date for the Annual Review of Medicine, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Deep immunophenotyping at the single-cell level identifies a combination of anti-IL-17 and checkpoint blockade as an effective treatment in a preclinical model of data-guided personalized immunotherapy

BACKGROUND

Although immune checkpoint blockade is effective for several malignancies, a substantial number of patients remain refractory to treatment. The future of immunotherapy will be a personalized approach adapted to each patient's cancer-immune interactions in the tumor microenvironment (TME) to prevent suppression of antitumor immune responses. To demonstrate the feasibility of this kind of approach, we developed combination therapy for a preclinical model guided by deep immunophenotyping of the TME.

METHODS

Gastric cancer cell lines YTN2 and YTN16 were subcutaneously inoculated into C57BL/6 mice. YTN2 spontaneously regresses, while YTN16 grows progressively. Bulk RNA-Seq, single-cell RNA-Seq (scRNA-Seq) and flow cytometry were performed to investigate the immunological differences in the TME of these tumors.

RESULTS

Bulk RNA-Seq demonstrated that YTN16 tumor cells produced CCL20 and that CD8⁺ T cell responses were impaired in these tumors relative to YTN2. We have developed a vertical flow array chip (VFAC) for targeted scRNA-Seq to identify unique subtypes of T cells by employing a panel of genes reflecting T cell phenotypes and functions. CD8⁺ T cell dysfunction (cytotoxicity, proliferation and the recruitment of interleukin-17 (IL-17)-producing cells into YTN16 tumors) was identified by targeted scRNA-Seq. The presence of IL-17-producing T cells in YTN16 tumors was confirmed by flow cytometry, which also revealed neutrophil infiltration. IL-17 blockade suppressed YTN16 tumor growth, while tumors were rejected by the combination of anti-IL-17 and anti-PD-1 (Programmed cell death protein 1) mAb treatment. Reduced neutrophil activation and enhanced expansion of neoantigen-specific CD8⁺ T cells were observed in tumors of the mice receiving the combination therapy.

CONCLUSIONS

Deep phenotyping of YTN16 tumors identified a sequence of events on the axis CCL20->IL-17-producing cells->IL-17-neutrophil-angiogenesis->suppression of neoantigen-specific CD8⁺ T cells which was responsible for the lack of tumor rejection. IL-17 blockade together with anti-PD-1 mAb therapy eradicated these YTN16 tumors. Thus, the deep immunological phenotyping can guide immunotherapy for the tailored treatment of each individual patient's tumor.

The future of microfluidics in immune checkpoint blockade

Recent advances in microfluidic techniques have enabled researchers to study sensitivities to immune checkpoint therapy, to determine patients' response to particular antibody treatment. Utilization of this technology is helpful in antibody discovery and in the design of personalized medicine. A variety of microfluidic approaches can provide several functions in processes such as immunologic, genomic, and/or transcriptomic analysis with the aim of improving the efficacy and coverage of immunotherapy, particularly immune checkpoint blockade (ICB). To achieve this requires researchers to overcome the challenges in the current state of the technology. This review looks into the advancements in microfluidic technologies applied to researches on immune checkpoint blockade treatment and its potential shift from proof-of-principle stage to clinical application.

An overview of multiplexed analyses of CAR T-cell therapies: insights and potential

INTRODUCTION

Cancer immunotherapy is a rapidly growing field with exponential advancement in engineered immune cell-based therapies. For instance, an engineered chimeric antigen receptor (CAR) can be introduced in T-cells or other immune cells and adoptively transferred to target and kill cancer cells in hematologic malignancies or solid tumors. The first CAR-T-cell (CAR-T) therapy has been developed against CD19, a B-cell marker expressed on lymphoma and lymphoblastic leukemia. To allow for personalized treatment, proteomics approaches could provide insights into biomarkers for CAR-T therapy efficacy and toxicity.

AREAS COVERED

We researched the most recent technology methods of biomarker evaluation used in the laboratory and clinical setting. Publications of CAR-T biomarkers were then systematically reviewed to provide a narrative of the most validated biomarkers of CAR-T efficacy and toxicity. Examples of biomarkers include CAR-T functionality and phenotype as well as interleukin-6 and other cytokines.

EXPERT COMMENTARY

Biomarkers of CAR-T efficacy and toxicity have been identified, but still need to be validated and standardized across institutions. Moreover, few are used in the clinical setting due to limitations in real-time technology. Expansion of biomarker research could provide better understanding of patient response and risk of life-threatening side effects with potential for improved precision medicine.

Tumor immunology in the age of single-cell genomics

Immunotherapies that were developed based on our understandings of tumor immunology have revolutionized cancer treatment. However, the success of immunotherapy is eclipsed by several grand challenges, including low response rate, intrinsic/acquired resistance and adverse effects. While a deeper understanding of the interaction between tumor and our immune system, especially the tumor immune niche, is essential to overcome those challenges, we are limited by the fact that most of our knowledge about tumor immunology is based on studies analyzing bulk populations of cells, which are often unable to fully characterize the various cell types and states engaged in immune cell functions. The advent of cutting single-cell genomic technologies empowers us to dissect the tumor immune niche in a genome-wide and spatially resolved manner in single cells, trace their clonal histories, and unveil their regulatory circuits. Future studies on tumor immunology in the age of single-cell genomics, therefore, hold the promise to develop more effective and precise immunotherapies for human cancers. In this perspective, we will discuss how advanced single-cell genomics approaches will revolutionize tumor immunology research and immunotherapies by catering the demand in the field of tumor immunology.

The critical role of CD4+ T cells in PD-1 blockade against MHC-II-expressing tumors such as classic Hodgkin lymphoma

Classic Hodgkin lymphoma (cHL) responds markedly to PD-1 blockade therapy, and the clinical responses are reportedly dependent on expression of major histocompatibility complex class II (MHC-II). This dependence is different from other solid tumors, in which the MHC class I (MHC-I)/CD8+ T-cell axis plays a critical role. In this study, we investigated the role of the MHC-II/CD4+ T-cell axis in the antitumor effect of PD-1 blockade on cHL. In cHL, MHC-I expression was frequently lost, but MHC-II expression was maintained. CD4+ T cells highly infiltrated the tumor microenvironment of MHC-II-expressing cHL, regardless of MHC-I expression status. Consequently, CD4+ T-cell, but not CD8+ T-cell, infiltration was a good prognostic factor in cHL, and PD-1 blockade showed antitumor efficacy against MHC-II-expressing cHL associated with CD4+ T-cell infiltration. Murine lymphoma and solid tumor models revealed the critical role of antitumor effects mediated by CD4+ T cells: an anti-PD-1 monoclonal antibody exerted antitumor effects on MHC-I-MHC-II+ tumors but not on MHC-I-MHC-II- tumors, in a cytotoxic CD4+ T-cell-dependent manner. Furthermore, LAG-3, which reportedly binds to MHC-II, was highly expressed by tumor-infiltrating CD4+ T cells in MHC-II-expressing tumors. Therefore, the combination of LAG-3 blockade with PD-1 blockade showed a far stronger antitumor immunity compared with either treatment alone. We propose that PD-1 blockade therapies have antitumor effects on MHC-II-expressing tumors such as cHL that are mediated by cytotoxic CD4+ T cells and that LAG-3 could be a candidate for combination therapy with PD-1 blockade.

Multiplex Immunofluorescence Tyramide Signal Amplification for Immune Cell Profiling of Paraffin-Embedded Tumor Tissues

Every day, more evidence is revealed regarding the importance of the relationship between the response to cancer immunotherapy and the cancer immune microenvironment. It is well established that a profound characterization of the immune microenvironment is needed to identify prognostic and predictive immune biomarkers. To this end, we find phenotyping cells by multiplex immunofluorescence (mIF) a powerful and useful tool to identify cell types in biopsy specimens. Here, we describe the use of mIF tyramide signal amplification for labeling up to eight markers on a single slide of formalin-fixed, paraffin-embedded tumor tissue to phenotype immune cells in tumor tissues. Different panels show different markers, and the different panels can be used to characterize immune cells and relevant checkpoint proteins. The panel design depends on the research hypothesis, the cell population of interest, or the treatment under investigation. To phenotype the cells, image analysis software is used to identify individual marker expression or specific co-expression markers, which can differentiate already selected phenotypes. The individual-markers approach identifies a broad number of cell phenotypes, including rare cells, which may be helpful in a tumor microenvironment study. To accurately interpret results, it is important to recognize which receptors are expressed on different cell types and their typical location (i.e., nuclear, membrane, and/or cytoplasm). Furthermore, the amplification system of mIF may allow us to see weak marker signals, such as programmed cell death ligand 1, more easily than they are seen with single-marker immunohistochemistry (IHC) labeling. Finally, mIF technologies are promising resources for discovery of novel cancer immunotherapies and related biomarkers. In contrast with conventional IHC, which permits only the labeling of one single marker per tissue sample, mIF can detect multiple markers from a single tissue sample, and at the same time, deliver extensive information about the cell phenotypes composition and their spatial localization. In this matter, the phenotyping process is critical and must be done accurately by a highly trained personal with knowledge of immune cell protein expression and tumor pathology.

Testing Cancer Immunotherapy in a Human Immune System Mouse Model: Correlating Treatment Responses to Human Chimerism, Therapeutic Variables and Immune Cell Phenotypes

Over the past decade, immunotherapies have revolutionized the treatment of cancer. Although the success of immunotherapy is remarkable, it is still limited to a subset of patients. More than 1500 clinical trials are currently ongoing with a goal of improving the efficacy of immunotherapy through co-administration of other agents. Preclinical, small-animal models are strongly desired to increase the pace of scientific discovery, while reducing the cost of combination drug testing in humans. Human immune system (HIS) mice are highly immune-deficient mouse recipients rtpeconstituted with human hematopoietic stem cells. These HIS-mice are capable of growing human tumor cell lines and patient-derived tumor xenografts. This model allows rapid testing of multiple, immune-related therapeutics for tumors originating from unique clinical samples. Using a cord blood-derived HIS-BALB/c-Rag2nullIl2rγnullSIRPαNOD (BRGS) mouse model, we summarize our experiments testing immune checkpoint blockade combinations in these mice bearing a variety of human tumors, including breast, colorectal, pancreatic, lung, adrenocortical, melanoma and hematological malignancies. We present in-depth characterization of the kinetics and subsets of the HIS in lymph and non-lymph organs and relate these to protocol development and immune-related treatment responses. Furthermore, we compare the phenotype of the HIS in lymph tissues and tumors. We show that the immunotype and amount of tumor infiltrating leukocytes are widely-variable and that this phenotype is tumor-dependent in the HIS-BRGS model. We further present flow cytometric analyses of immune cell subsets, activation state, cytokine production and inhibitory receptor expression in peripheral lymph organs and tumors. We show that responding tumors bear human infiltrating T cells with a more inflammatory signature compared to non-responding tumors, similar to reports of "responding" patients in human immunotherapy clinical trials. Collectively these data support the use of HIS mice as a preclinical model to test combination immunotherapies for human cancers, if careful attention is taken to both protocol details and data analysis.

Recent Advances in Integrative Multi-Omics Research in Breast and Ovarian Cancer

The underlying molecular heterogeneity of cancer is responsible for the dynamic clinical landscape of this disease. The combination of genomic and proteomic alterations, including both inherited and acquired mutations, promotes tumor diversity and accounts for variable disease progression, therapeutic response, and clinical outcome. Recent advances in high-throughput proteogenomic profiling of tumor samples have resulted in the identification of novel oncogenic drivers, tumor suppressors, and signaling networks; biomarkers for the prediction of drug sensitivity and disease progression; and have contributed to the development of novel and more effective treatment strategies. In this review, we will focus on the impact of historical and recent advances in single platform and integrative proteogenomic studies in breast and ovarian cancer, which constitute two of the most lethal forms of cancer for women, and discuss the molecular similarities of these diseases, the impact of these findings on our understanding of tumor biology as well as the clinical applicability of these discoveries.

The current landscape of single-cell transcriptomics for cancer immunotherapy

Immunotherapies such as immune checkpoint blockade and adoptive cell transfer have revolutionized cancer treatment, but further progress is hindered by our limited understanding of tumor resistance mechanisms. Emerging technologies now enable the study of tumors at the single-cell level, providing unprecedented high-resolution insights into the genetic makeup of the tumor microenvironment and immune system that bulk genomics cannot fully capture. Here, we highlight the recent key findings of the use of single-cell RNA sequencing to deconvolute heterogeneous tumors and immune populations during immunotherapy. Single-cell RNA sequencing has identified new crucial factors and cellular subpopulations that either promote tumor progression or leave tumors vulnerable to immunotherapy. We anticipate that the strategic use of single-cell analytics will promote the development of the next generation of successful, rationally designed immunotherapeutics.

Changing the landscape of tumor immunology: novel tools to examine T cell specificity

Immunotherapy has established itself as a stalwart arm in patient care and with precision medicine forms the new paradigm in cancer treatment. T cells are an important group of immune cells capable of potent cancer immune surveillance and immunity. The advent of bioinformatics, particularly more recent advances incorporating algorithms employing machine learning, provide a seemingly limitless ability for T cell analysis and hypothesis generation. Such endeavors have become indispensable to research efforts accelerating and evolving to such an extent that there exists an appreciable gap between knowledge and proof of function and application. Exciting new technologies such as DNA barcoding, cytometry by time-of-flight (CyTOF), and peptide-exchangeable pHLA multimers inclusive of rare and difficult HLA alleles offer high-throughput cell-by-cell analytical capabilities. These outstanding recent contributions to T cell research will help close this gap and potentially bring practical benefit to patients.

Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume II-practical challenges

The development of strongly predictive validated biomarkers is essential for the field of immuno-oncology (IO) to advance. The highly complex, multifactorial data sets required to develop these biomarkers necessitate effective, responsible data-sharing efforts in order to maximize the scientific knowledge and utility gained from their collection. While the sharing of clinical- and safety-related trial data has already been streamlined to a large extent, the sharing of biomarker-aimed clinical trial derived data and data sets has been met with a number of hurdles that have impaired the progression of biomarkers from hypothesis to clinical use. These hurdles include technical challenges associated with the infrastructure, technology, workforce, and sustainability required for clinical biomarker data sharing. To provide guidance and assist in the navigation of these challenges, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to outline the challenges that researchers currently face, both at the conceptual level (Volume I) and at the technical level (Volume II). The committee also suggests possible solutions to these problems in the form of professional standards and harmonized requirements for data sharing, assisting in continued progress toward effective, clinically relevant biomarkers in the IO setting.

Interrogating the microenvironmental landscape of tumors with computational image analysis approaches

The tumor microenvironment is an interacting heterogeneous collection of cancer cells, resident as well as infiltrating host cells, secreted factors, and extracellular matrix proteins. With the growing importance of immunotherapies, it has become crucial to be able to characterize the composition and the functional orientation of the microenvironment. The development of novel computational image analysis methodologies may enable the robust quantification and localization of immune and related biomarker-expressing cells within the microenvironment. The aim of the review is to concisely highlight a selection of current and significant contributions pertinent to methodological advances coupled with biomedical or translational applications. A further aim is to concisely present computational advances that, to our knowledge, have currently very limited use for the assessment of the microenvironment but have the potential to enhance image analysis pipelines; on this basis, an example is shown for the detection and segmentation of cells of the microenvironment using a published pipeline and a public dataset. Finally, a general proposal is presented on the conceptual design of automation-optimized computational image analysis workflows in the biomedical and clinical domain.

Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise

Intratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can confer a high success rate, selective pressures coupled with dynamic evolution within a tumour can drive the emergence of drug-resistant clones that allow tumours to persist in certain patients. To improve immunotherapy efficacy, researchers have used transcriptional spatial profiling techniques to identify and subsequently block the source of tumour heterogeneity. In this review, we describe and assess the different technologies available for such profiling within a cancer tissue. We first outline two well-known approaches, in situ hybridization and digital spatial profiling. Then, we highlight the features of an emerging technology known as Visium Spatial Gene Expression Solution. Visium generates quantitative gene expression data and maps them to the tissue architecture. By retaining spatial information, we are well positioned to identify novel biomarkers and perform computational analyses that might inform on novel combinatorial immunotherapies.