AZGP1 deficiency promotes angiogenesis in prostate cancer.

BACKGROUND: Loss of AZGP1 expression is a biomarker associated with progression to castration resistance, development of metastasis, and poor disease-specific survival in prostate cancer. However, high expression of AZGP1 cells in prostate cancer has been reported to increase proliferation and invasion. The exact role of AZGP1 in prostate cancer progression remains elusive. METHOD: AZGP1 knockout and overexpressing prostate cancer cells were generated using a lentiviral system. The effects of AZGP1 under- or over-expression in prostate cancer cells were evaluated by in vitro cell proliferation, migration, and invasion assays. Heterozygous AZGP1± mice were obtained from European Mouse Mutant Archive (EMMA), and prostate tissues from homozygous knockout male mice were collected at 2, 6 and 10 months for histological analysis. In vivo xenografts generated from AZGP1 under- or over-expressing prostate cancer cells were used to determine the role of AZGP1 in prostate cancer tumor growth, and subsequent proteomics analysis was conducted to elucidate the mechanisms of AZGP1 action in prostate cancer progression. AZGP1 expression and microvessel density were measured in human prostate cancer samples on a tissue microarray of 215 independent patient samples. RESULT: Neither the knockout nor overexpression of AZGP1 exhibited significant effects on prostate cancer cell proliferation, clonal growth, migration, or invasion in vitro. The prostates of AZGP1-/- mice initially appeared to have grossly normal morphology; however, we observed fibrosis in the periglandular stroma and higher blood vessel density in the mouse prostate by 6 months. In PC3 and DU145 mouse xenografts, over-expression of AZGP1 did not affect tumor growth. Instead, these tumors displayed decreased microvessel density compared to xenografts derived from PC3 and DU145 control cells, suggesting that AZGP1 functions to inhibit angiogenesis in prostate cancer. Proteomics profiling further indicated that, compared to control xenografts, AZGP1 overexpressing PC3 xenografts are enriched with angiogenesis pathway proteins, including YWHAZ, EPHA2, SERPINE1, and PDCD6, MMP9, GPX1, HSPB1, COL18A1, RNH1, and ANXA1. In vitro functional studies show that AZGP1 inhibits human umbilical vein endothelial cell proliferation, migration, tubular formation and branching. Additionally, tumor microarray analysis shows that AZGP1 expression is negatively correlated with blood vessel density in human prostate cancer tissues. CONCLUSION: AZGP1 is a negative regulator of angiogenesis, such that loss of AZGP1 promotes angiogenesis in prostate cancer. AZGP1 likely exerts heterotypical effects on cells in the tumor microenvironment, such as stromal and endothelial cells. This study sheds light on the anti-angiogenic characteristics of AZGP1 in the prostate and provides a rationale to target AZGP1 to inhibit prostate cancer progression.

Identification of unique rectal cancer-specific subtypes.

BACKGROUND: Existing colorectal cancer subtyping methods were generated without much consideration of potential differences in expression profiles between colon and rectal tissues. Moreover, locally advanced rectal cancers at resection often have received neoadjuvant chemoradiotherapy which likely has a significant impact on gene expression. METHODS: We collected mRNA expression profiles for rectal and colon cancer samples (n = 2121). We observed that (i) Consensus Molecular Subtyping (CMS) had a different prognosis in treatment-naïve rectal vs. colon cancers, and (ii) that neoadjuvant chemoradiotherapy exposure produced a strong shift in CMS subtypes in rectal cancers. We therefore clustered 182 untreated rectal cancers to find rectal cancer-specific subtypes (RSSs). RESULTS: We identified three robust subtypes. We observed that RSS1 had better, and RSS2 had worse disease-free survival. RSS1 showed high expression of MYC target genes and low activity of angiogenesis genes. RSS2 exhibited low regulatory T cell abundance, strong EMT and angiogenesis signalling, and high activation of TGF-ß, NF-κB, and TNF-α signalling. RSS3 was characterised by the deactivation of EGFR, MAPK and WNT pathways. CONCLUSIONS: We conclude that RSS subtyping allows for more accurate prognosis predictions in rectal cancers than CMS subtyping and provides new insight into targetable disease pathways within these subtypes.

Spatial Effects of Infiltrating T cells on Neighbouring Cancer Cells and Prognosis in Stage III CRC patients.

Colorectal cancer (CRC) is one of the most frequently occurring cancers, but prognostic biomarkers identifying patients at risk of recurrence are still lacking. In this study, we aimed to investigate in more detail the spatial relationship between intratumoural T cells, cancer cells, and cancer cell hallmarks, as prognostic biomarkers in stage III colorectal cancer patients. We conducted multiplexed imaging of 56 protein markers at single cell resolution on resected fixed tissue from stage III CRC patients who received adjuvant 5-fluorouracil-based chemotherapy. Images underwent segmentation for tumour, stroma and immune cells, and cancer cell 'state' protein marker expression was quantified at a cellular level. We developed a Python package for estimation of spatial proximity, nearest neighbour analysis focusing on cancer cell - T cell interactions at single-cell level. In our discovery cohort (MSK), we processed 462 core samples (total number of cells: 1,669,228) from 221 adjuvant 5FU-treated stage III patients. The validation cohort (HV) consisted of 272 samples (total number of cells: 853,398) from 98 stage III CRC patients. While there were trends for an association between percentage of cytotoxic T cells (across the whole cancer core), it did not reach significance (Discovery cohort: p = 0.07, Validation cohort: p = 0.19). We next utilized our region-based nearest neighbourhood approach to determine the spatial relationships between cytotoxic T cells, helper T cells and cancer cell clusters. In the both cohorts, we found that lower distance between cytotoxic T cells, T helper cells and cancer cells was significantly associated with increased disease-free survival. An unsupervised trained model that clustered patients based on the median distance between immune cells and cancer cells, as well as protein expression profiles, successfully classified patients into low-risk and high-risk groups (Discovery cohort: p = 0.01, Validation cohort: p = 0.003).

Experimental and Theoretical Exploration of the Kinetics and Thermodynamics of the Nucleophile-Induced Fragmentation of Ylidenenorbornadiene Carboxylates.

Ylidenenorbornadienes (YNDs), prepared by [4 + 2] cycloadditions between fulvenes and acetylene carboxylates, react with thiol nucleophiles to yield mixtures of four to eight diastereomers depending on the symmetry of the YND substrate. The mixtures of diastereomers fragment via a retro-[4 + 2] cycloaddition with a large variation in rate, with half-lives ranging from 16 to 11,000 min at 80 °C. The diastereomer-enriched samples of propane thiol adducts [YND-propanethiol (PTs)] were isolated and identified by nuclear Overhauser effect spectroscopy (NOESY) correlations. Simulated kinetics were used to extrapolate the rate constants of individual diastereomers from the observed rate data, and it correlated well with rate constants measured directly and from isolated diastereomer-enriched samples. The individual diastereomers of a model system fragment at differing rates with half-lives ranging from 5 to 44 min in CDCl3. Density functional theory calculations were performed to investigate the mechanism of fragmentation and support an asynchronous retro-[4 + 2] cycloaddition transition state. The computations generally correlated well with the observed free energies of activation for four diastereomers of the model system as a whole, within 2.6 kcal/mol. However, the observed order of the fragmentation rates across the set of diastereomers deviated from the computational results. YNDs display wide variability in the rate of fragmentation, dependent on the stereoelectronics of the ylidene substituents. A Hammett study showed that the electron-rich aromatic rings attached to the ylidene bridge increase the fragmentation rate, while electron-deficient systems slow fragmentation rates.

Organ Mapping Antibody Panels: a community resource for standardized multiplexed tissue imaging.

Multiplexed antibody-based imaging enables the detailed characterization of molecular and cellular organization in tissues. Advances in the field now allow high-parameter data collection (>60 targets); however, considerable expertise and capital are needed to construct the antibody panels employed by these methods. Organ mapping antibody panels are community-validated resources that save time and money, increase reproducibility, accelerate discovery and support the construction of a Human Reference Atlas.

3D reconstruction of skin and spatial mapping of immune cell density, vascular distance and effects of sun exposure and aging.

Mapping the human body at single cell resolution in three dimensions (3D) is important for understanding cellular interactions in context of tissue and organ organization. 2D spatial cell analysis in a single tissue section may be limited by cell numbers and histology. Here we show a workflow for 3D reconstruction of multiplexed sequential tissue sections: MATRICS-A (Multiplexed Image Three-D Reconstruction and Integrated Cell Spatial - Analysis). We demonstrate MATRICS-A in 26 serial sections of fixed skin (stained with 18 biomarkers) from 12 donors aged between 32-72 years. Comparing the 3D reconstructed cellular data with the 2D data, we show significantly shorter distances between immune cells and vascular endothelial cells (56 µm in 3D vs 108 µm in 2D). We also show 10-70% more T cells (total) within 30 µm of a neighboring T helper cell in 3D vs 2D. Distances of p53, DDB2 and Ki67 positive cells to the skin surface were consistent across all ages/sun exposure and largely localized to the lower stratum basale layer of the epidermis. MATRICS-A provides a framework for analysis of 3D spatial cell relationships in healthy and aging organs and could be further extended to diseased organs.

Predicting Breast Cancer Events in Ductal Carcinoma In Situ (DCIS) Using Generative Adversarial Network Augmented Deep Learning Model.

Standard clinicopathological parameters (age, growth pattern, tumor size, margin status, and grade) have been shown to have limited value in predicting recurrence in ductal carcinoma in situ (DCIS) patients. Early and accurate recurrence prediction would facilitate a more aggressive treatment policy for high-risk patients (mastectomy or adjuvant radiation therapy), and simultaneously reduce over-treatment of low-risk patients. Generative adversarial networks (GAN) are a class of DL models in which two adversarial neural networks, generator and discriminator, compete with each other to generate high quality images. In this work, we have developed a deep learning (DL) classification network that predicts breast cancer events (BCEs) in DCIS patients using hematoxylin and eosin (H & E) images. The DL classification model was trained on 67 patients using image patches from the actual DCIS cores and GAN generated image patches to predict breast cancer events (BCEs). The hold-out validation dataset (n = 66) had an AUC of 0.82. Bayesian analysis further confirmed the independence of the model from classical clinicopathological parameters. DL models of H & E images may be used as a risk stratification strategy for DCIS patients to personalize therapy.

Multiplexed Immunofluorescence Imaging Reveals an Immune-Rich Tumor Microenvironment in Mucinous Rectal Cancer Characterized by Increased Lymphocyte Infiltration and Enhanced Programmed Cell Death Protein 1 Expression.

BACKGROUND: Mucinous rectal cancer is associated with a higher incidence of microsatellite instability and a poorer response to neoadjuvant chemoradiotherapy compared to other subtypes of rectal adenocarcinoma. Immune checkpoint inhibitors are an emerging family of anticancer therapeutics associated with highly variable outcomes in colorectal cancer. Although the immune landscape of mucinous rectal cancer has not been fully explored, the presence of mucin is thought to act as a barrier preventing immune-cell infiltration. OBJECTIVE: The aim of this study was to determine the immune properties of mucinous rectal cancer and investigate the degree of lymphocyte infiltration in this cohort. DESIGN: This is a retrospective cohort study that involved multiplexed immunofluorescence staining of tumor microarrays. SETTINGS: Samples originated from a single university teaching hospital. PATIENTS: Our cohort included 15 cases of mucinous and 43 cases of nonmucinous rectal cancer. MAIN OUTCOME MEASURES: Immune cells were classified and quantified. Immune-cell counts were compared between mucinous and nonmucinous cohorts. Immune marker expression within tumor epithelial tissue was evaluated to determine the degree of lymphocyte infiltration. RESULTS: Cytotoxic ( p = 0.022) and regulatory T cells ( p = 0.010) were found to be overrepresented in the mucinous cohort compared to the nonmucinous group. Programmed cell death protein 1 expression was also found to be significantly greater in the mucinous group ( p = 0.001). CD3 ( p = 0.001) and CD8 ( p = 0.054) expressions within the tumor epithelium were also higher in the mucinous group, suggesting adequate immune infiltration despite the presence of mucin. In our analysis, microsatellite instability status was not a predictor of immune marker expression. LIMITATIONS: The relatively small size of the cohort. CONCLUSIONS: Mucinous rectal cancer is associated with an immune-rich tumor microenvironment, which was not associated with microsatellite instability status. See Video Abstract at http://links.lww.com/DCR/C65 . IMGENES DE INMUNOFLUORESCENCIA MULTIPLEXADAS REVELAN UN MICROAMBIENTE TUMORAL RICO EN INMUNIDAD EN EL CNCER RECTAL MUCINOSO CARACTERIZADO POR UNA MAYOR INFILTRACIN DE LINFOCITOS Y UNA EXPRESIN MEJORADA DE PD: ANTECEDENTES:El cáncer rectal mucinoso se asocia con una mayor incidencia de inestabilidad de microsatélites y una peor respuesta a la quimiorradioterapia neoadyuvante en comparación con otros subtipos de adenocarcinoma rectal. Los inhibidores de puntos de control inmunitarios son una familia emergente de tratamientos contra el cáncer asociados con resultados muy variables en el cáncer colorrectal. Aunque el panorama inmunitario del cáncer rectal mucinoso no se ha explorado completamente, se cree que la presencia de mucina actúa como una barrera que previene la infiltración de células inmunitarias.OBJETIVO:El objetivo de este estudio fue determinar las propiedades inmunes del cáncer de recto mucinoso e investigar el grado de infiltración de linfocitos en esta cohorte.DISEÑO:Este es un estudio de cohorte retrospectivo que involucró la tinción de inmunofluorescencia multiplexada de micromatrices tumorales.AJUSTES:Las muestras se originaron en un solo hospital docente universitario.PACIENTES:Nuestra cohorte incluyó 15 casos de cáncer de recto mucinoso y 43 casos de cáncer de recto no mucinosoPRINCIPALES MEDIDAS DE RESULTADO:Las células inmunitarias se clasificaron y cuantificaron. Se compararon los recuentos de células inmunitarias entre cohortes mucinosas y no mucinosas. Se evaluó la expresión del marcador inmunitario dentro del tejido epitelial tumoral para determinar el grado de infiltración de linfocitos.RESULTADOS:Se encontró que las células T citotóxicas ( p = 0,022) y reguladoras ( p = 0,010) estaban sobrerrepresentadas en la cohorte mucinosa en comparación con el grupo no mucinoso. También se encontró que la expresión de PD-1 era significativamente mayor en el grupo mucinoso ( p = 0,001). La expresión de CD3 ( p = 0,001) y CD8 ( p = 0,054) dentro del epitelio tumoral también fue mayor en el grupo mucinoso, lo que sugiere una infiltración inmunitaria adecuada a pesar de la presencia de mucina. En nuestro análisis, no se encontró que el estado de inestabilidad de los microsatélites sea un predictor de la expresión del marcador inmunitario.LIMITACIONES:El tamaño relativamente pequeño de la cohorte.CONCLUSIONES:El cáncer rectal mucinoso se asocia con un microambiente tumoral rico en inmunidad, que no se asoció con el estado de inestabilidad de microsatélites. Consulte el Video del Resumen en http://links.lww.com/DCR/C65 . (Traducción- Dr. Yesenia Rojas-Khalil ).

Deep learning-based automated pipeline for blood vessel detection and distribution analysis in multiplexed prostate cancer images.

Introduction: Prostate cancer is a highly heterogeneous disease, presenting varying levels of aggressiveness and response to treatment. Angiogenesis is one of the hallmarks of cancer, providing oxygen and nutrient supply to tumors. Micro vessel density has previously been correlated with higher Gleason score and poor prognosis. Manual segmentation of blood vessels (BVs) In microscopy images is challenging, time consuming and may be prone to inter-rater variabilities. In this study, an automated pipeline is presented for BV detection and distribution analysis in multiplexed prostate cancer images. Methods: A deep learning model was trained to segment BVs by combining CD31, CD34 and collagen IV images. In addition, the trained model was used to analyze the size and distribution patterns of BVs in relation to disease progression in a cohort of prostate cancer patients (N = 215). Results: The model was capable of accurately detecting and segmenting BVs, as compared to ground truth annotations provided by two reviewers. The precision (P), recall (R) and dice similarity coefficient (DSC) were equal to 0.93 (SD 0.04), 0.97 (SD 0.02) and 0.71 (SD 0.07) with respect to reviewer 1, and 0.95 (SD 0.05), 0.94 (SD 0.07) and 0.70 (SD 0.08) with respect to reviewer 2, respectively. BV count was significantly associated with 5-year recurrence (adjusted p = 0.0042), while both count and area of blood vessel were significantly associated with Gleason grade (adjusted p = 0.032 and 0.003 respectively). Discussion: The proposed methodology is anticipated to streamline and standardize BV analysis, offering additional insights into the biology of prostate cancer, with broad applicability to other cancers.

Apoptotic and Necroptotic Mediators are Differentially Expressed in Mucinous and Non-Mucinous Colorectal Cancer.

Background: Mucinous colorectal cancer (CRC) represents 10% of all CRC and is associated with chemotherapy resistance. This study aimed to determine expression of apoptosis and necroptosis mediators in mucinous CRC. Methods: RNA gene expression data were extracted from TCGA. Protein levels in 14 mucinous and 39 non-mucinous tumors were measured by multiplexed immunofluorescence. Levels of apoptosis and necroptosis signalling proteins were analysed in SW1463 (mucinous rectal), SW837 (non-mucinous rectal), LS174T (mucinous colon) and HCT116 (non-mucinous colon) cell lines by western blot. Cell death was investigated by flow cytometry measurement of propidium iodide stained cells. Results: High cleaved-Caspase 3 expression was noted in resected mucinous tumors. Western blot identified alterations in apoptosis proteins in mucinous CRC, most prominently downregulation of Bcl-xL protein levels (p=0.029) which was also observed at the mRNA level in patients by analysis of TCGA gene expression data (p<0.001). Treatment with 5-FU did not significantly elevate cell death in mucinous cells, while non-mucinous cells showed robust cell death responses. However, 5-FU-induced phosphorylation of MLKL in mucinous cancer cells, suggestive of a switch to necroptotic cell death signaling. Conclusion: Apoptotic and necroptotic mediators are differentially expressed in mucinous and non-mucinous colorectal cancers and represent targets for investigation of cell death mechanisms in the mucinous subtype.

Ylidenenorbornadiene Carboxylates: Experimental Kinetic Analysis of a Nucleophile-Induced Fragmentation Reaction.

Ylidenenorbornadienes (YNDs), prepared by [4 + 2] cycloadditions between fulvenes and acetylene carboxylates, react with beta-mercaptoethanol to yield a mixture of four diastereomers. These four diastereomers fragment via a retro-[4 + 2] cycloaddition at differing rates. A simulated kinetics approach extrapolated the rate constants of the diastereomers from the observed rate data. YNDs display wide variability in rate of fragmentation, dependent on the stereoelectronics of the ylidene substituents. A substrate containing one carboxylic ester proved exceptionally stable to fragmentation.

Tumor MHC Class I Expression Associates with Intralesional IL2 Response in Melanoma.

Cancer immunotherapy can result in lasting tumor regression, but predictive biomarkers of treatment response remain ill-defined. Here, we performed single-cell proteomics, transcriptomics, and genomics on matched untreated and IL2 injected metastases from patients with melanoma. Lesions that completely regressed following intralesional IL2 harbored increased fractions and densities of nonproliferating CD8+ T cells lacking expression of PD-1, LAG-3, and TIM-3 (PD-1-LAG-3-TIM-3-). Untreated lesions from patients who subsequently responded with complete eradication of all tumor cells in all injected lesions (individuals referred to herein as "extreme responders") were characterized by proliferating CD8+ T cells with an exhausted phenotype (PD-1+LAG-3+TIM-3+), stromal B-cell aggregates, and expression of IFNγ and IL2 response genes. Loss of membranous MHC class I expression in tumor cells of untreated lesions was associated with resistance to IL2 therapy. We validated this finding in an independent cohort of metastatic melanoma patients treated with intralesional or systemic IL2. Our study suggests that intact tumor-cell antigen presentation is required for melanoma response to IL2 and describes a multidimensional and spatial approach to develop immuno-oncology biomarker hypotheses using routinely collected clinical biospecimens.

Stratification of chemotherapy-treated stage III colorectal cancer patients using multiplexed imaging and single-cell analysis of T-cell populations.

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Biomarkers for identification of patients at increased risk of disease recurrence following adjuvant chemotherapy are currently lacking. In this study, we assessed immune signatures in the tumor and tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single-cell analysis technology (Cell DIVETM) and evaluated their correlations with patient outcomes. Tissue microarrays (TMAs) with up to three 1 mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin (FOLFOX) chemotherapy. Single sections underwent multiplexed immunofluorescence staining for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and tumor/cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase, and S6). We used annotations and a probabilistic classification algorithm to build statistical models of immune cell types. Images were also qualitatively assessed independently by a Pathologist as 'high', 'moderate' or 'low', for stromal and total immune cell content. Excellent agreement was found between manual assessment and total automated scores (p < 0.0001). Moreover, compared to single markers, a multi-marker classification of regulatory T cells (Tregs: CD3+/CD4+FOXP3+/PD1-) was significantly associated with disease-free survival (DFS) and overall survival (OS) (p = 0.049 and 0.032) of FOLFOX-treated patients. Our results also showed that PD1- Tregs rather than PD1+ Tregs were associated with improved survival. These findings were supported by results from an independent FOLFOX-treated cohort of 191 stage III CRC patients, where higher PD1- Tregs were associated with an increase overall survival (p = 0.015) for CD3+/CD4+/FOXP3+/PD1-. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cell types with stronger correlations with outcomes.

FLINO: a new method for immunofluorescence bioimage normalization.

MOTIVATION: Multiplexed immunofluorescence bioimaging of single-cells and their spatial organization in tissue holds great promise to the development of future precision diagnostics and therapeutics. Current multiplexing pipelines typically involve multiple rounds of immunofluorescence staining across multiple tissue slides. This introduces experimental batch effects that can hide underlying biological signal. It is important to have robust algorithms that can correct for the batch effects while not introducing biases into the data. Performance of data normalization methods can vary among different assay pipelines. To evaluate differences, it is critical to have a ground truth dataset that is representative of the assay. RESULTS: A new immunoFLuorescence Image NOrmalization method is presented and evaluated against alternative methods and workflows. Multiround immunofluorescence staining of the same tissue with the nuclear dye DAPI was used to represent virtual slides and a ground truth. DAPI was restained on a given tissue slide producing multiple images of the same underlying structure but undergoing multiple representative tissue handling steps. This ground truth dataset was used to evaluate and compare multiple normalization methods including median, quantile, smooth quantile, median ratio normalization and trimmed mean of the M-values. These methods were applied in both an unbiased grid object and segmented cell object workflow to 24 multiplexed biomarkers. An upper quartile normalization of grid objects in log space was found to obtain almost equivalent performance to directly normalizing segmented cell objects by the middle quantile. The developed grid-based technique was then applied with on-slide controls for evaluation. Using five or fewer controls per slide can introduce biases into the data. Ten or more on-slide controls were able to robustly correct for batch effects. AVAILABILITY AND IMPLEMENTATION: The data underlying this article along with the FLINO R-scripts used to perform the evaluation of image normalizations methods and workflows can be downloaded from https://github.com/GE-Bio/FLINO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An atlas of inter- and intra-tumor heterogeneity of apoptosis competency in colorectal cancer tissue at single-cell resolution.

Cancer cells' ability to inhibit apoptosis is key to malignant transformation and limits response to therapy. Here, we performed multiplexed immunofluorescence analysis on tissue microarrays with 373 cores from 168 patients, segmentation of 2.4 million individual cells, and quantification of 18 cell lineage and apoptosis proteins. We identified an enrichment for BCL2 in immune, and BAK, SMAC, and XIAP in cancer cells. Ordinary differential equation-based modeling of apoptosis sensitivity at single-cell resolution was conducted and an atlas of inter- and intra-tumor heterogeneity in apoptosis susceptibility generated. Systems modeling at single-cell resolution identified an enhanced sensitivity of cancer cells to mitochondrial permeabilization and executioner caspase activation compared to immune and stromal cells, but showed significant inter- and intra-tumor heterogeneity.

Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging.

Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells have been largely based on single-cell sequencing approaches, which lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient depth, several multiplexed protein imaging methods have been recently developed. Though these technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this Perspective, we provide essential resources, key considerations for obtaining robust and reproducible imaging data, and specialized knowledge from domain experts and technology developers.

Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast.

BACKGROUND: There is limited knowledge about DCIS cellular composition and relationship with breast cancer events (BCE). METHODS: Immunofluorescence multiplexing (MxIF) was used to image and quantify 32 cellular biomarkers in FFPE DCIS tissue microarrays. Over 75,000 DCIS cells from 51 patients (median 9 years follow-up for non-BCE cases) were analysed for profiles predictive of BCE. K-means clustering was used to evaluate cellular co-expression of epithelial markers with ER and HER2. RESULTS: Only ER, PR and HER2 significantly correlated with BCE. Cluster analysis identified 6 distinct cell groups with different levels of ER, Her2, cMET and SLC7A5. Clusters 1 and 3 were not significant. Clusters 2 and 4 (high ER/low HER2 and SLC7A5/mixed cMET) significantly correlated with low BCE risk (P = 0.001 and P = 0.034), while cluster 6 (high HER2/low ER, cMET and SLC7A5) correlated with increased risk (P = 0.018). Cluster 5 (similar to cluster 6, except high SLC7A5) trended towards significance (P = 0.072). A continuous expression score (Escore) based on these 4 clusters predicted likelihood of BCE (AUC = 0.79, log-rank test P = 5E-05; LOOCV AUC = 0.74, log-rank test P = 0.006). CONCLUSION: Multiplexed spatial analysis of limited tissue is a novel method for biomarker analysis and predicting BCEs. Further validation of Escore is needed in a larger cohort.

Quantitative patterns of motor cortex proteinopathy across ALS genotypes.

Degeneration of the primary motor cortex is a defining feature of amyotrophic lateral sclerosis (ALS), which is associated with the accumulation of microscopic protein aggregates in neurons and glia. However, little is known about the quantitative burden and pattern of motor cortex proteinopathies across ALS genotypes. We combined quantitative digital image analysis with multi-level generalized linear modelling in an independent cohort of 82 ALS cases to explore the relationship between genotype, total proteinopathy load and cellular vulnerability to aggregate formation. Primary motor cortex phosphorylated (p)TDP-43 burden and microglial activation were more severe in sporadic ALS-TDP disease than C9-ALS. Oligodendroglial pTDP-43 pathology was a defining feature of ALS-TDP in sporadic ALS, C9-ALS and ALS with OPTN, HNRNPA1 or TARDBP mutations. ALS-FUS and ALS-SOD1 showed less cortical proteinopathy in relation to spinal cord pathology than ALS-TDP, where pathology was more evenly spread across the motor cortex-spinal cord axis. Neuronal pTDP-43 aggregates were rare in GAD67+ and Parvalbumin+ inhibitory interneurons, consistent with predominant accumulation in excitatory neurons. Finally, we show that cortical microglia, but not astrocytes, contain pTDP-43. Our findings suggest divergent quantitative, genotype-specific vulnerability of the ALS primary motor cortex to proteinopathies, which may have implications for our understanding of disease pathogenesis and the development of genotype-specific therapies.

Comparison of Multiplexed Immunofluorescence Imaging to Chromogenic Immunohistochemistry of Skin Biomarkers in Response to Monkeypox Virus Infection.

Over the last 15 years, advances in immunofluorescence-imaging based cycling methods, antibody conjugation methods, and automated image processing have facilitated the development of a high-resolution, multiplexed tissue immunofluorescence (MxIF) method with single cell-level quantitation termed Cell DIVETM. Originally developed for fixed oncology samples, here it was evaluated in highly fixed (up to 30 days), archived monkeypox virus-induced inflammatory skin lesions from a retrospective study in 11 rhesus monkeys to determine whether MxIF was comparable to manual H-scoring of chromogenic stains. Six protein markers related to immune and cellular response (CD68, CD3, Hsp70, Hsp90, ERK1/2, ERK1/2 pT202_pY204) were manually quantified (H-scores) by a pathologist from chromogenic IHC double stains on serial sections and compared to MxIF automated single cell quantification of the same markers that were multiplexed on a single tissue section. Overall, there was directional consistency between the H-score and the MxIF results for all markers except phosphorylated ERK1/2 (ERK1/2 pT202_pY204), which showed a decrease in the lesion compared to the adjacent non-lesioned skin by MxIF vs an increase via H-score. Improvements to automated segmentation using machine learning and adding additional cell markers for cell viability are future options for improvement. This method could be useful in infectious disease research as it conserves tissue, provides marker colocalization data on thousands of cells, allowing further cell level data mining as well as a reduction in user bias.

Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations.