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

INTRODUCTION: Malignant pleural effusion (MPE) is a frequent complication of advanced malignancies. In this pilot study, we characterized the immune landscapes of MPEs, compared them to their primary tumor (PT) samples from breast carcinoma (BC) and lung adenocarcinoma (LADC), and tested the utility of multiplexed image technology in cytological samples. MATERIALS AND METHODS: We evaluated the immune contexture of 6 BC and 5 LADC MPEs and their PTs using 3 multiplex immunofluorescence panels. We explored the associations between sample characteristics and pleural effusion-free survival. RESULTS: No MPE samples had positive programmed death-ligand 1 expression in malignant cells, although 3 of 11 PTs has positive programmed death-ligand 1 expression (more than 1% expression in malignant cells). Overall, in LADC samples, cluster of differentiation 3 (CD3)+ T cells and CD3+CD8+ cytotoxic T cells predominated (median percentages for MPEs versus PTs: 45.6% versus 40.7% and 4.7% versus 6.6%, respectively) compared with BC. CD68+ macrophages predominated in the BC samples (medians for MPEs 61.2% versus PTs for 57.1%) but not in the LADC samples. Generally in PTs, CD3+CD8+ forkhead box P3+ T cells and the median distances from the malignant cells to CD3+CD8+Ki67+ and CD3+ programmed cell death protein 1 + T cells correlated to earlier MPE after PT diagnosis. CONCLUSIONS: The immune cell phenotypes in the MPEs and PTs were similar within each cancer type but different between BC versus LADC. An MPE analysis can potentially be used as a substitute for a PT analysis, but an expanded study of this topic is essential.

Pan-cancer proteogenomics characterization of tumor immunity.

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

Multi-omics Analysis Reveals Immune Features Associated with Immunotherapy Benefit in Patients with Squamous Cell Lung Cancer from Phase III Lung-MAP S1400I Trial.

PURPOSE: Identifying molecular and immune features to guide immune checkpoint inhibitor (ICI)-based regimens remains an unmet clinical need. EXPERIMENTAL DESIGN: Tissue and longitudinal blood specimens from phase III trial S1400I in patients with metastatic squamous non-small cell carcinoma (SqNSCLC) treated with nivolumab monotherapy (nivo) or nivolumab plus ipilimumab (nivo+ipi) were subjected to multi-omics analyses including multiplex immunofluorescence (mIF), nCounter PanCancer Immune Profiling Panel, whole-exome sequencing, and Olink. RESULTS: Higher immune scores from immune gene expression profiling or immune cell infiltration by mIF were associated with response to ICIs and improved survival, except regulatory T cells, which were associated with worse overall survival (OS) for patients receiving nivo+ipi. Immune cell density and closer proximity of CD8+GZB+ T cells to malignant cells were associated with superior progression-free survival and OS. The cold immune landscape of NSCLC was associated with a higher level of chromosomal copy-number variation (CNV) burden. Patients with LRP1B-mutant tumors had a shorter survival than patients with LRP1B-wild-type tumors. Olink assays revealed soluble proteins such as LAMP3 increased in responders while IL6 and CXCL13 increased in nonresponders. Upregulation of serum CXCL13, MMP12, CSF-1, and IL8 were associated with worse survival before radiologic progression. CONCLUSIONS: The frequency, distribution, and clustering of immune cells relative to malignant ones can impact ICI efficacy in patients with SqNSCLC. High CNV burden may contribute to the cold immune microenvironment. Soluble inflammation/immune-related proteins in the blood have the potential to monitor therapeutic benefit from ICI treatment in patients with SqNSCLC.

The Immunological Landscape of M1 and M2 Macrophages and Their Spatial Distribution in Patients with Malignant Pleural Mesothelioma.

BACKGROUND: Several tumor-associated macrophages (TAMs) have shown promise as prognosticators in cancer. Our aim was to validate the importance of TAMs in malignant pleural mesothelioma (MPM) using a two-stage design. METHODS: We explored The Cancer Genome Atlas (TCGA-MESO) to select immune-relevant macrophage genes in MPM, including M1/M2 markers, as a discovery cohort. This computational cohort was used to create a multiplex immunofluorescence panel. Moreover, a cohort of 68 samples of MPM in paraffin blocks was used to validate the macrophage phenotypes and the co-localization and spatial distribution of these immune cells within the TME and the stromal or tumor compartments. RESULTS: The discovery cohort revealed six immune-relevant macrophage genes (CD68, CD86, CD163, CD206, ARG1, CD274), and complementary genes were differentially expressed by M1 and M2 phenotypes with distinct roles in the tumor microenvironment and were associated with the prognosis. In addition, immune-suppressed MPMs with increased enrichment of CD68, CD86, and CD163 genes and high densities of M2 macrophages expressing CD163 and CD206 proteins were associated with worse overall survival (OS). Interestingly, below-median distances from malignant cells to specific M2a and M2c macrophages were associated with worse OS, suggesting an M2 macrophage-driven suppressive component in these tumors. CONCLUSIONS: The interactions between TAMs in situ and, particularly, CD206+ macrophages are highly relevant to patient outcomes. High-resolution technology is important for identifying the roles of macrophage populations in tissue specimens and identifying potential therapeutic candidates in MPM.

Exploring the expression of Adenosine Pathway-Related Markers CD73 and CD39 in Colorectal and Pancreatic Carcinomas Characterized by Multiplex Immunofluorescence: A Pilot Study.

INTRODUCTION: Generating high levels of immunosuppressive adenosine in the tumor microenvironment contributes to cancer immune evasion. CD39 and CD73 hydrolyze adenosine triphosphate into adenosine; thus, efforts have been made to target this pathway for cancer immunotherapy. Our objective was optimizing a multiplex immunofluorescence (mIF) panel to explore the role of CD39 and CD73 within the tumor microenvironment. MATERIALS AND METHODS: In three-time points, a small cohort (n=8 ) of colorectal and pancreatic adenocarcinomas were automated staining using an mIF panel against CK, CD3, CD8, CD20, CD39, CD73 and CD68 to compare them with individual markers immunohistochemistry (IHC) for internal panel validation. Densities of immune cells and distances from different tumor-associated immune cells to tumor cells were exploratory assessment and compared with clinicopathologic variables and outcomes. RESULTS: Comparing the three-time points and individual IHC staining results, we demonstrated high reproducibility of the mIF panel. CD39 and CD73 expression was low in malignant cells; the exploratory analysis showed higher densities of CD39 expression by various cells, predominantly stromal cells, followed by T cells, macrophages, and B cells. No expression of CD73 by B cells or macrophages was detected. Distance analysis revealed proximity of cytotoxic T cells, macrophages, and T cells expressing CD39 to malignant cells, suggesting a close regulatory signal driven by this adenosine marker. CONCLUSIONS: We optimized an mIF panel for detection of markers in the adenosine pathway, an emerging clinically relevant pathway. The densities and spatial distribution demonstrated that this pathway may modulate aspects of the tumor immune microenvironment.

Microbiome alteration via fecal microbiota transplantation is effective for refractory immune checkpoint inhibitor-induced colitis.

Immune checkpoint inhibitors (ICIs) target advanced malignancies with high efficacy but also predispose patients to immune-related adverse events like immune-mediated colitis (IMC). Given the association between gut bacteria with response to ICI therapy and subsequent IMC, fecal microbiota transplantation (FMT) represents a feasible way to manipulate microbial composition in patients, with a potential benefit for IMC. Here, we present a large case series of 12 patients with refractory IMC who underwent FMT from healthy donors as salvage therapy. All 12 patients had grade 3 or 4 ICI-related diarrhea or colitis that failed to respond to standard first-line (corticosteroids) and second-line immunosuppression (infliximab or vedolizumab). Ten patients (83%) achieved symptom improvement after FMT, and three patients (25%) required repeat FMT, two of whom had no subsequent response. At the end of the study, 92% achieved IMC clinical remission. 16S rRNA sequencing of patient stool samples revealed that compositional differences between FMT donors and patients with IMC before FMT were associated with a complete response after FMT. Comparison of pre- and post-FMT stool samples in patients with complete responses showed significant increases in alpha diversity and increases in the abundances of Collinsella and Bifidobacterium, which were depleted in FMT responders before FMT. Histologically evaluable complete response patients also had decreases in select immune cells , including CD8+ T cells, in the colon after FMT when compared with non-complete response patients (n = 4). This study validates FMT as an effective treatment strategy for IMC and gives insights into the microbial signatures that may play a critical role in FMT response.

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.

Naproxen chemoprevention induces proliferation of cytotoxic lymphocytes in Lynch Syndrome colorectal mucosa.

Background: Recent clinical trial data from Lynch Syndrome (LS) carriers demonstrated that naproxen administered for 6-months is a safe primary chemoprevention that promotes activation of different resident immune cell types without increasing lymphoid cellularity. While intriguing, the precise immune cell types enriched by naproxen remained unanswered. Here, we have utilized cutting-edge technology to elucidate the immune cell types activated by naproxen in mucosal tissue of LS patients. Methods: Normal colorectal mucosa samples (pre- and post-treatment) from a subset of patients enrolled in the randomized and placebo-controlled 'Naproxen Study' were obtained and subjected to a tissue microarray for image mass cytometry (IMC) analysis. IMC data was processed using tissue segmentation and functional markers to ascertain cell type abundance. Computational outputs were then used to quantitatively compare immune cell abundance in pre- and post-naproxen specimens. Results: Using data-driven exploration, unsupervised clustering identified four populations of immune cell types with statistically significant changes between treatment and control groups. These four populations collectively describe a unique cell population of proliferating lymphocytes within mucosal samples from LS patients exposed to naproxen. Conclusions: Our findings show that daily exposure of naproxen promotes T-cell proliferation in the colonic mucosa, which paves way for developing combination of immunoprevention strategies including naproxen for LS patients.

Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer.

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns-an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions.

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples.

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is an effective methodology for tumor evaluation that improves the understanding of the tumor microenvironment. The visualization of protein expression in formalin-fixed, paraffin-embedded tissues is achieved when a specific fluorophore is annealed to an antibody-bound barcode via complementary oligonucleotides and then sample imaging is performed; indeed, this method allows for the use of customizable panels of more than 40 antibodies in a single tissue staining reaction. This method is compatible with fresh frozen tissue, formalin-fixed, paraffin-embedded tissue, cultured cells, and peripheral blood mononuclear cells, meaning that researchers can use this technology to view a variety of sample types at single-cell resolution. This method starts with a manual staining and fixing protocol, and all the antibody barcodes are applied using an antibody cocktail. The staining fluidics instrument is fully automated and performs iterative cycles of labeling, imaging, and removing spectrally distinct fluorophores until all the biomarkers have been imaged using a standard fluorescence microscope. The images are then collected and compiled across all the imaging cycles to achieve single-cell resolution for all the markers. The single-step staining and gentle fluorophore removal not only allow for highly multiplexed biomarker analysis but also preserve the sample for additional downstream analysis if desired (e.g., hematoxylin and eosin staining). Furthermore, the image analysis software enables image processing-drift compensation, background subtraction, cell segmentation, and clustering-as well as the visualization and analysis of the images and cell phenotypes for the generation of spatial network maps. In summary, this technology employs a computerized microfluidics system and fluorescence microscope to iteratively hybridize, image, and strip fluorescently labeled DNA probes that are complementary to tissue-bound, oligonucleotide-conjugated antibodies.

Impact of Region-of-Interest Size on Immune Profiling Using Multiplex Immunofluorescence Tyramide Signal Amplification for Paraffin-Embedded Tumor Tissues.

INTRODUCTION: Representative regions of interest (ROIs) analysis from the whole slide images (WSI) are currently being used to study immune markers by multiplex immunofluorescence (mIF) and single immunohistochemistry (IHC). However, the amount of area needed to be analyzed to be representative of the entire tumor in a WSI has not been defined. METHODS: We labeled tumor-associated immune cells by mIF and single IHC in separate cohorts of non-small cell lung cancer (NSCLC) samples and we analyzed them as whole tumor area as well as using different number of ROIs to know how much area will be need to represent the entire tumor area. RESULTS: For mIF using the InForm software and ROI of 0.33 mm2 each, we observed that the cell density data from five randomly selected ROIs is enough to achieve, in 90% of our samples, more than 0.9 of Spearman correlation coefficient and for single IHC using ScanScope tool box from Aperio and ROIs of 1 mm2 each, we found that the correlation value of more than 0.9 was achieved using 5 ROIs in a similar cohort. Additionally, we also observed that each cell phenotype in mIF influence differently the correlation between the areas analyzed by the ROIs and the WSI. Tumor tissue with high intratumor epithelial and immune cells phenotype, quality, and spatial distribution heterogeneity need more area analyzed to represent better the whole tumor area. CONCLUSION: We found that at minimum 1.65 mm2 area is enough to represent the entire tumor areas in most of our NSCLC samples using mIF.

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

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

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

As the second most common subtype of breast carcinoma, Invasive Lobular Carcinoma (ILC) microenvironment features have not been thoroughly explored. ILC has different histological subtypes and elucidating differences in their microenvironments could lead to a comprehensive development of cancer therapies. We designed a custom-made cancer associated fibroblast (CAFs) panel and used multiplex immunofluorescence to identify the differences in tumor microenvironment between Classic ILC and Pleomorphic ILC. Materials and methods: Multiplex immunofluorescence were performed on formalin fixed paraffin embedded tissues using Opal-7 color kit. The antibodies used for phenotyping CAFs were Pan CK (AE1/AE3), CD45, A-SMA, FAP, S100, Thy-1 with optimized dilutions. The images were acquired and analyzed using Vectra 3.0 imaging system and InForm software respectively. Results: We studied 19 different CAFs colocalized phenotypes in the tumor, stroma and overall tissue compartments between classic and pleomorphic ILC. Total A-SMA+, A-SMA+FAP+S100+ and A-SMA+S100+ CAFs demonstrated higher densities in classic ILC cases while FAP+S100+ and S-100+ CAFs were increased in the pleomorphic subtype samples. Conclusion: Our study explores multiple CAFs phenotypes between classical and pleomorphic ILC. We showed that CAFs subset differ between Classic ILC and Pleomorphic ILC. A-SMA CAFs are more prevalent in the TME of classic ILCs whereas Pleomorphic ILCs are dominated by CAFs without A-SMA expression. This also iterates the importance of exploring this particular type of breast carcinoma in more detail, paving the way for meaningful translational research.

Immunogenomic profiling of lung adenocarcinoma reveals poorly differentiated tumors are associated with an immunogenic tumor microenvironment.

OBJECTIVES: Pathologists have routinely observed distinct histologic patterns of growth in early-stage lung adenocarcinoma (LUAD), which have been suggested to be associated with prognosis. Herein, we investigated the relationship between LUAD patterns of growth, as defined by the updated international association for the study of lung cancer (IASLC) grading criteria, and differences in the tumor immune microenvironment to identify predictors of response to immunotherapy. METHODS: 174 resected stage I-III LUAD tumors were classified by histologic pattern of growth (i.e. solid, micropapillary, acinar, papillary, and lepidic) and then grouped as well differentiated, moderately differentiated, and poorly differentiated. Comprehensive multiplatform analysis including whole exome sequencing, gene expression profiling, immunohistochemistry, CIBERSORT, and T-cell receptor sequencing was performed and groups were compared for differences in genomic drivers, immune cell infiltrate, clonality, and survival. Finally, multivariate analysis was performed adjusting for pathologic stage and smoking status. RESULTS: Poorly differentiated tumors demonstrated a strong association with smoking relative to moderately differentiated or well differentiated tumors. However, unlike in prior reports, poorly differentiated tumors were not associated with a worse survival after curative-intent resection. Genomic analysis revealed that poorly differentiated tumors are associated with high tumor mutation burden but showed no association with oncogenic drivers. Immune analyses revealed that poorly differentiated tumors are associated with increased T-cell clonality, expression of PD-L1, and infiltration by cytotoxic CD8 T-cells, activated CD4 T-cells, and pro-inflammatory (M1) macrophages. Finally, multivariate analysis controlling for stage and smoking status confirmed independence of immune differences between IASLC grade groups. CONCLUSIONS: Poorly differentiated tumors, as defined by the updated IASLC grading criteria, are associated with a distinct immunogenic tumor microenvironment that predicts for therapeutic response to immune agents, including checkpoint inhibitors, and should be included in the clinical trial design of immunotherapy studies in early-stage lung adenocarcinoma.

Durvalumab plus tremelimumab in advanced or metastatic soft tissue and bone sarcomas: a single-centre phase 2 trial.

BACKGROUND: Few standard treatment options are available for patients with metastatic sarcomas. We did this trial to evaluate the efficacy, safety, and changes in the tumour microenvironment for durvalumab, an anti-PD-L1 drug, and tremelimumab, an anti-CTLA-4 drug, across multiple sarcoma subtypes. METHODS: In this single-centre phase 2 trial, done at The University of Texas MD Anderson Cancer Center (Houston, TX USA), patients aged 18 years or older with advanced or metastatic sarcoma with an Eastern Cooperative Oncology Group performance status of 0 or 1 who had received at least one previous line of systemic therapy were enrolled in disease subtype-specific groups (liposarcoma, leiomyosarcoma, angiosarcoma, undifferentiated pleomorphic sarcoma, synovial sarcoma, osteosarcoma, alveolar soft-part sarcoma, chordoma, and other sarcomas). Patients received 1500 mg intravenous durvalumab and 75 mg intravenous tremelimumab for four cycles, followed by durvalumab alone every 4 weeks for up to 12 months. The primary endpoint was progression-free survival at 12 weeks in the intention-to-treat population (all patients who received at least one dose of treatment). Safety was also analysed in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT02815995, and is completed. FINDINGS: Between Aug 17, 2016, and April 9, 2018, 62 patients were enrolled, of whom 57 (92%) received treatment and were included in the intention-to-treat population. With a median follow-up of 37·2 months (IQR 1·8-10·1), progression-free survival at 12 weeks was 49% (95% CI 36-61). 21 grade 3-4 treatment-related adverse events were reported, the most common of which were increased lipase (four [7%] of 57 patients), colitis (three [5%] patients), and pneumonitis (three [5%] patients). Nine (16%) patients had a treatment related serious adverse event. One patient had grade 5 pneumonitis and colitis. INTERPRETATION: The combination of durvalumab and tremelimumab is an active treatment regimen for advanced or metastatic sarcoma and merits evaluation in specific subsets in future trials. FUNDING: AstraZeneca.

Expanding the Comprehension of the Tumor Microenvironment using Mass Spectrometry Imaging of Formalin-Fixed and Paraffin-Embedded Tissue Samples.

Advances in immune-based therapies have revolutionized cancer treatment and research. This has triggered growing demand for the characterization of the tumor immune landscape. Although standard immunohistochemistry is suitable for studying tissue architecture, it is limited to the analysis of a small number of markers. Conversely, techniques such as flow cytometry can evaluate multiple markers simultaneously, although information about tissue morphology is lost. In recent years, multiplexed strategies that integrate phenotypic and spatial analysis have emerged as comprehensive approaches to the characterization of the tumor immune landscape. Herein, we discuss an innovative technology combining metal-labeled antibodies and secondary ion mass spectrometry focusing on the technical steps in assay development and optimization, tissue preparation, and image acquisition and processing. Before staining, a metal-labeled antibody panel must be developed and optimized. This hi-plex image system supports up to 40 metal-tagged antibodies in a single tissue section. Of note, the risk of signal interference increases with the number of markers included in the panel. After panel design, particular attention should be given to the metal isotope assignment to the antibody to minimize this interference. Preliminary panel testing is performed using a small subset of antibodies and subsequent testing of the entire panel in control tissues. Formalin-fixed, paraffin-embedded tissue sections are obtained and mounted on gold-coated slides and further stained. The staining takes 2 days and closely resembles standard immunohistochemical staining. Once samples are stained, they are placed in the image acquisition instrument. Fields of view are selected, and images are acquired, uploaded, and stored. The final stage is image preparation for the filtering and removal of interference using the system's image processing software. A disadvantage of this platform is the lack of analytical software. However, the images generated are supported by different computational pathology software.

Multiplex Immunofluorescence and the Digital Image Analysis Workflow for Evaluation of the Tumor Immune Environment in Translational Research.

A robust understanding of the tumor immune environment has important implications for cancer diagnosis, prognosis, research, and immunotherapy. Traditionally, immunohistochemistry (IHC) has been regarded as the standard method for detecting proteins in situ, but this technique allows for the evaluation of only one cell marker per tissue sample at a time. However, multiplexed imaging technologies enable the multiparametric analysis of a tissue section at the same time. Also, through the curation of specific antibody panels, these technologies enable researchers to study the cell subpopulations within a single immunological cell group. Thus, multiplexed imaging gives investigators the opportunity to better understand tumor cells, immune cells, and the interactions between them. In the multiplexed imaging technology workflow, once the protocol for a tumor immune micro environment study has been defined, histological slides are digitized to produce high-resolution images in which regions of interest are selected for the interrogation of simultaneously expressed immunomarkers (including those co-expressed by the same cell) by using an image analysis software and algorithm. Most currently available image analysis software packages use similar machine learning approaches in which tissue segmentation first defines the different components that make up the regions of interest and cell segmentation, then defines the different parameters, such as the nucleus and cytoplasm, that the software must utilize to segment single cells. Image analysis tools have driven dramatic evolution in the field of digital pathology over the past several decades and provided the data necessary for translational research and the discovery of new therapeutic targets. The next step in the growth of digital pathology is optimization and standardization of the different tasks in cancer research, including image analysis algorithm creation, to increase the amount of data generated and their accuracy in a short time as described herein. The aim of this review is to describe this process, including an image analysis algorithm creation for multiplex immunofluorescence analysis, as an essential part of the optimization and standardization of the different processes in cancer research, to increase the amount of data generated and their accuracy in a short time.

Pathological Response and Immune Biomarker Assessment in Non-Small-Cell Lung Carcinoma Receiving Neoadjuvant Immune Checkpoint Inhibitors.

Lung cancer is the leading cause of cancer incidence and mortality worldwide. Adjuvant and neoadjuvant chemotherapy have been used in the perioperative setting of non-small-cell carcinoma (NSCLC); however, the five-year survival rate only improves by about 5%. Neoadjuvant treatment with immune checkpoint inhibitors (ICIs) has become significant due to improved survival in advanced NSCLC patients treated with immunotherapy agents. The assessment of pathology response has been proposed as a surrogate indicator of the benefits of neaodjuvant therapy. An outline of recommendations has been published by the International Association for the Study of Lung Cancer (IASLC) for the evaluation of pathologic response (PR). However, recent studies indicate that evaluations of immune-related changes are distinct in surgical resected samples from patients treated with immunotherapy. Several clinical trials of neoadjuvant immunotherapy in resectable NSCLC have included the study of biomarkers that can predict the response of therapy and monitor the response to treatment. In this review, we provide relevant information on the current recommendations of the assessment of pathological responses in surgical resected NSCLC tumors treated with neoadjuvant immunotherapy, and we describe current and potential biomarkers to predict the benefits of neoadjuvant immunotherapy in patients with resectable NSCLC.

Diminished Immune Surveillance during Histologic Progression of Intraductal Papillary Mucinous Neoplasms Offers a Therapeutic Opportunity for Cancer Interception.

PURPOSE: Intraductal papillary mucinous neoplasms (IPMN) are bona fide precursors to pancreatic ductal adenocarcinoma (PDAC). While genomic alterations during multistep IPMN progression have been well cataloged, the accompanying changes within the tumor immune microenvironment (TIME) have not been comprehensively studied. Herein, we investigated TIME-related alterations during IPMN progression, using multiplex immunofluorescence (mIF) coupled with high-resolution image analyses. EXPERIMENTAL DESIGN: Two sets of formalin-fixed, paraffin-embedded tissue samples from surgically resected IPMNs were analyzed. The training set of 30 samples consisted of 11 low-grade IPMN (LG-IPMN), 17 high-grade IPMN (HG-IPMN), and 2 IPMN with PDAC, while a validation set of 93 samples comprised of 55 LG-IPMN and 38 HG-IPMN. The training set was analyzed with two panels of immuno-oncology-related biomarkers, while the validation set was analyzed with a subset of markers found significantly altered in the training set. RESULTS: Cell types indicative of enhanced immune surveillance, including cytotoxic and memory T cells, and antigen-experienced T cells and B cells, were all found at higher densities within isolated LG-IPMNs compared with HG-IPMNs. Notably, the TIME of LG-IPMNs that had progressed at the time of surgical resection (progressor LGD) resembled that of the synchronous HG-IPMNs, underscoring that attenuated immune surveillance occurs even in LG-IPMNs destined for progression. CONCLUSIONS: Our findings provide a basis for interception of cystic neoplasia to PDAC, through maintenance of sustained immune surveillance using vaccines and other prevention approaches.