Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry

CelloType: a unified model for segmentation and classification of tissue images

Cell segmentation and classification are critical tasks in spatial omics data analysis. Here we introduce CelloType, an end-to-end model designed for cell segmentation and classification for image-based spatial omics data. Unlike the traditional two-stage approach of segmentation followed by classification, CelloType adopts a multitask learning strategy that integrates these tasks, simultaneously enhancing the performance of both. CelloType leverages transformer-based deep learning techniques for improved accuracy in object detection, segmentation and classification. It outperforms existing segmentation methods on a variety of multiplexed fluorescence and spatial transcriptomic images. In terms of cell type classification, CelloType surpasses a model composed of state-of-the-art methods for individual tasks and a high-performance instance segmentation model. Using multiplexed tissue images, we further demonstrate the utility of CelloType for multiscale segmentation and classification of both cellular and noncellular elements in a tissue. The enhanced accuracy and multitask learning ability of CelloType facilitate automated annotation of rapidly growing spatial omics data.

Therapeutic potential of Xihuang Pill in colorectal cancer: Metabolomic and microbiome-driven approaches

Introduction

The Xihuang Pill (XHP), a venerated traditional Chinese medicine, has demonstrated significant anti-cancer capabilities. Despite its proven efficacy, the scarcity of comprehensive pharmacological studies limits the widespread application of XHP. This research endeavor seeks to demystify the therapeutic underpinnings of XHP, particularly in the realm of colorectal cancer (CRC) therapy.

Methods

In this study, mice harboring CT26 tumors were divided into four groups, each administered with either XHP monotherapy, 5-fluorouracil (5-FU), or a combination of both. The tumor growth trajectory was closely monitored to evaluate the effectiveness of these anti-neoplastic interventions. Advanced techniques, including 16S-rDNA gene sequencing and ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), were harnessed to scrutinize the gut microbiota and serum metabolite profiles. Immunohistochemical assays were employed to gauge the expression levels of CD4, CD8, and Foxp3, thereby providing insights into the dynamics of tumor-infiltrating lymphocytes within the tumor microenvironment.

Results

Our findings indicate that XHP effectively suppresses the initiation and progression of colorectal tumors. The combinatorial therapy of XHP with 5-FU exhibited an enhanced inhibitory effect on tumor growth. Metabolic profiling revealed that XHP induced notable metabolic shifts, particularly impacting pathways such as steroid hormone synthesis, arachidonic acid metabolism, purine biosynthesis, and renin secretion. Notably, 17α-ethinyl estradiol and α-ergocryptine were identified as serum metabolites with the most substantial increase following XHP administration. Analysis of the gut microbiome suggested that XHP promoted the expansion of specific bacterial taxa, including Lachnospiraceae_NK4A136_group, Clostridiales, Desulfovibrionaceae, and Anaerotignum_sp., while suppressing the proliferation of others such as Ligilactobacilus, Lactobacillus_taiwanensis, and Candidatus_saccharimonas. Immunohistochemical staining indicated an upregulation of CD4 and CD8 post-XHP treatment.

Conclusion

This study delineates a potential mechanism by which XHP inhibits CRC tumorigenesis through modulating the gut microbiota, serum metabolites, and reshaping the tumor immune microenvironment in a murine CRC model. These findings contribute to a more profound understanding and potentially broaden the clinical utility of XHP in oncology.

CelloType: A Unified Model for Segmentation and Classification of Tissue Images

Cell segmentation and classification are critical tasks in spatial omics data analysis. We introduce CelloType, an end-to-end model designed for cell segmentation and classification of biomedical microscopy images. Unlike the traditional two-stage approach of segmentation followed by classification, CelloType adopts a multi-task learning approach that connects the segmentation and classification tasks and simultaneously boost the performance of both tasks. CelloType leverages Transformer-based deep learning techniques for enhanced accuracy of object detection, segmentation, and classification. It outperforms existing segmentation methods using ground-truths from public databases. In terms of classification, CelloType outperforms a baseline model comprised of state-of-the-art methods for individual tasks. Using multiplexed tissue images, we further demonstrate the utility of CelloType for multi-scale segmentation and classification of both cellular and non-cellular elements in a tissue. The enhanced accuracy and multi-task-learning ability of CelloType facilitate automated annotation of rapidly growing spatial omics data.

Novel Chromogens for Immunohistochemistry in Spatial Biology

Spatial relations between tumor cells and host-infiltrating cells are increasingly important in both basic science and clinical research. In this study, we have tested the feasibility of using standard methods of immunohistochemistry (IHC) in a multiplex staining system using a newly developed set of chromogenic substrates for the peroxidase and alkaline phosphatase enzymes. Using this approach, we have developed a set of chromogens characterized by (1) providing fine cellular detail, (2) non-overlapping spectral profiles, (3) an absence of interactions between chromogens, (4) stability when stored, and (5) compatibility with current standard immunohistochemistry practices. When viewed microscopically under brightfield illumination, the chromogens yielded the following colors: red, black, blue, yellow, brown, and green. By selecting compatible color combinations, we have shown feasibility for four-color multiplex staining. Depending on the particular type of analysis being performed, visual analysis, without the aid of computer-assisted image analysis, was sufficient to differentiate up to four different markers.

A neutrophil extracellular traps-related classification predicts prognosis and response to immunotherapy in colon cancer

Neutrophil extracellular traps (NETs) have been categorized as a form of inflammatory cell death mode of neutrophils (NETosis) involved in natural immunity and the regulation of adaptive immunity. More and more studies revealed the ability of NETs to reshape the tumor immune microenvironment (TIME) by limiting antitumor effector cells, which may impair the efficacy of immunotherapy. To explore whether NETs-related genes make vital impacts on Colon carcinoma (COAD), we have carried out a systematic analysis and showed several findings in the present work. First, we obtained the patient's data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset, aiming to detect two NETs-associated subtypes by consensus clustering. For the purpose of annotating the roles of NETs-related pathways, gene ontology enrichment analyses were adopted. Next, we constructed a 6 novel NETs-related genes score using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model. We found that the NETs risk score was notably upregulated in COAD patient samples, and its levels were notably correlated with tumor clinicopathological and immune traits. Then, according to NETs-associated molecular subtypes and the risk signature, this study compared immune cell infiltration calculated through the estimate, CIBERSORT, TIMER, ssGSEA algorithms, tumor immune dysfunction, as well as exclusion (TIDE). Furthermore, we confirm that MPO(myeloperoxidase) was significantly upregulated in COAD patient samples, and its levels were significantly linked to tumor malignancy and clinic outcome. Moreover, multiplex immunohistochemistry (mIHC) spatial analysis confirmed that MPO was closely related to Treg and PD-1 + Treg in spatial location which suggested MPO may paly an important role in TIME formation. Altogether, the obtained results indicated that a six NETs-related genes prognostic signature was conducive to estimating the prognosis and response of chemo-/immuno-therapy of COAD patients.

Conditional Knockout of Hypoxia-Inducible Factor 1-Alpha in Tumor-Infiltrating Neutrophils Protects against Pancreatic Ductal Adenocarcinoma

Large numbers of neutrophils infiltrate tumors and comprise a notable component of the inflammatory tumor microenvironment. While it is established that tumor cells exhibit the Warburg effect for energy production, the contribution of the neutrophil metabolic state to tumorigenesis is unknown. Here, we investigated whether neutrophil infiltration and metabolic status promotes tumor progression in an orthotopic mouse model of pancreatic ductal adenocarcinoma (PDAC). We observed a large increase in the proportion of neutrophils in the blood and tumor upon orthotopic transplantation. Intriguingly, these tumor-infiltrating neutrophils up-regulated glycolytic factors and hypoxia-inducible factor 1-alpha (HIF-1α) expression compared to neutrophils from the bone marrow and blood of the same mouse. This enhanced glycolytic signature was also observed in human PDAC tissue samples. Strikingly, neutrophil-specific deletion of HIF-1α (HIF-1αΔNφ) significantly reduced tumor burden and improved overall survival in orthotopic transplanted mice, by converting the pro-tumorigenic neutrophil phenotype to an anti-tumorigenic phenotype. This outcome was associated with elevated reactive oxygen species production and activated natural killer cells and CD8+ cytotoxic T cells compared to littermate control mice. These data suggest a role for HIF-1α in neutrophil metabolism, which could be exploited as a target for metabolic modulation in cancer.

Transducin β-like protein 1 controls multiple oncogenic networks in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common Non-Hodgkin's lymphoma and is characterized by a remarkable heterogeneity with diverse variants that can be identified histologically and molecularly. Large-scale gene expression profiling studies have identified the germinal center B-cell (GCB-) and activated B-cell (ABC-) subtypes. Standard chemo-immunotherapy remains standard front line therapy, curing approximately two thirds of patients. Patients with refractory disease or those who relapse after salvage treatment have an overall poor prognosis highlighting the need for novel therapeutic strategies. Transducin β-like protein 1 (TBL1) is an exchange adaptor protein encoded by the TBL1X gene and known to function as a master regulator of the Wnt signalling pathway by binding to β-CATENIN and promoting its downstream transcriptional program. Here, we show that, unlike normal B-cells, DLBCL cells express abundant levels of TBL1 and its overexpression correlates with poor clinical outcome regardless of DLBCL molecular subtype. Genetic deletion of TBL1 and pharmacological approach using tegavivint, a first-in-class small molecule targeting TBL1 (Iterion Therapeutics), promotes DLBCL cell death in vitro and in vivo. Through an integrated genomic, biochemical, and pharmacologic analyses, we characterized a novel, β-CATENIN independent, post-transcriptional oncogenic function of TBL1 in DLBCL where TBL1 modulates the stability of key oncogenic proteins such as PLK1, MYC, and the autophagy regulatory protein BECLIN-1 through its interaction with a SKP1-CUL1-F-box (SCF) protein supercomplex. Collectively, our data provide the rationale for targeting TBL1 as a novel therapeutic strategy in DLBCL.

Delineating the breast cancer immune microenvironment in the era of multiplex immunohistochemistry/immunofluorescence

Breast cancer is the most common malignancy and the leading cause of cancer death in females worldwide. Treatment is challenging, especially for those who are triple-negative. Increasing evidence suggests that diverse immune populations are present in the breast tumour microenvironment, which opens up avenues for personalised drug targets. Historically, our investigations into the immune constitution of breast tumours have been restricted to analyses of one or two markers at a given time. Recent technological advances have allowed simultaneous labelling of more than 35 markers and detailed profiling of tumour-immune infiltrates at the single-cell level, as well as determining the cellular composition and spatial analysis of the entire tumour architecture. In this review, we describe emerging technologies that have contributed to the field of breast cancer diagnosis, and discuss how to interpret the vast data sets obtained in order to effectively translate them for clinically relevant use.

Evaluation of an open-source machine-learning tool to quantify bone marrow plasma cells

AIMS

The objective of this study was to develop and validate an open-source digital pathology tool, QuPath, to automatically quantify CD138-positive bone marrow plasma cells (BMPCs).

METHODS

We analysed CD138-scanned slides in QuPath. In the initial training phase, manual positive and negative cell counts were performed in representative areas of 10 bone marrow biopsies. Values from the manual counts were used to fine-tune parameters to detect BMPCs, using the positive cell detection and neural network (NN) classifier functions. In the testing phase, whole-slide images in an additional 40 cases were analysed. Output from the NN classifier was compared with two pathologist's estimates of BMPC percentage.

RESULTS

The training set included manual counts ranging from 2403 to 17 287 cells per slide, with a median BMPC percentage of 13% (range: 3.1%-80.7%). In the testing phase, the quantification of plasma cells by image analysis correlated well with manual counting, particularly when restricted to BMPC percentages of <30% (Pearson's r=0.96, p<0.001). Concordance between the NN classifier and the pathologist whole-slide estimates was similarly good, with an intraclass correlation of 0.83 and a weighted kappa for the NN classifier of 0.80 with the first rater and 0.90 with the second rater. This was similar to the weighted kappa between the two human raters (0.81).

CONCLUSIONS

This represents a validated digital pathology tool to assist in automatically and reliably counting BMPC percentage on CD138-stained slides with an acceptable error rate.

Comparative Analysis of Immunohistochemical Staining Intensity Determined by Light Microscopy, ImageJ and QuPath in Placental Hofbauer Cells

Software based analyses of immunohistochemical staining are designed for obtaining quantitative, reproducible, and objective data. However, often times only a certain type of positive cells or structures need to be quantified thus whole image analysis cannot be performed. Such an example is Hofbauer placental cells, which show positivity of some antigens together with trophoblast, but only Hofbauer cells represent the regions of interest (ROIs). Two independent observers evaluated the immunohistochemical staining intensity of Hofbauer cells in placenta samples stained for cytoplasmic antigens by ImageJ, QuPath and light microscopy. Thus, the precise manual determination of ROIs, i.e. Hofbauer cells, was necessary. We detected low inter-observer variability in staining intensity. Almost perfect agreement between observers was reached for ImageJ and QuPath whilst substantial agreement was reached for light microscopy evaluation. As for the comparison of ImageJ, QuPath and light microscopy, the agreement of all three methods (identical immunohistochemical intensity) was achieved for 38.1% samples. The almost perfect agreement of staining intensities was reached between ImageJ and QuPath, and moderate agreement for comparison of the light microscopy to both software. Software analyses are much more time-consuming, thus their utilization is at least questionable to evaluate ROIs with selection.

Multiomic analysis and immunoprofiling reveal distinct subtypes of human angiosarcoma

Angiosarcomas are rare, clinically aggressive tumors with limited treatment options and a dismal prognosis. We analyzed angiosarcomas from 68 patients, integrating information from multiomic sequencing, NanoString immuno-oncology profiling, and multiplex immunohistochemistry and immunofluorescence for tumor-infiltrating immune cells. Through whole-genome sequencing (n = 18), 50% of the cutaneous head and neck angiosarcomas exhibited higher tumor mutation burden (TMB) and UV mutational signatures; others were mutationally quiet and non-UV driven. NanoString profiling revealed 3 distinct patient clusters represented by lack (clusters 1 and 2) or enrichment (cluster 3) of immune-related signaling and immune cells. Neutrophils (CD15+), macrophages (CD68+), cytotoxic T cells (CD8+), Tregs (FOXP3+), and PD-L1+ cells were enriched in cluster 3 relative to clusters 2 and 1. Likewise, tumor inflammation signature (TIS) scores were highest in cluster 3 (7.54 vs. 6.71 vs. 5.75, respectively; P < 0.0001). Head and neck angiosarcomas were predominant in clusters 1 and 3, providing the rationale for checkpoint immunotherapy, especially in the latter subgroup with both high TMB and TIS scores. Cluster 2 was enriched for secondary angiosarcomas and exhibited higher expression of DNMT1, BRD3/4, MYC, HRAS, and PDGFRB, in keeping with the upregulation of epigenetic and oncogenic signaling pathways amenable to targeted therapies. Molecular and immunological dissection of angiosarcomas may provide insights into opportunities for precision medicine.

CD30+OX40+ Treg is associated with improved overall survival in colorectal cancer

Regulatory T cells (Tregs) are often enriched in tumors, where their immunosuppressive function has a key role in tumor persistence and progression. In colorectal cancer (CRC), however, Tregs are frequently associated with an improved clinical outcome. Tumor-infiltrating Tregs have been shown to exhibit a distinct signature comprising the co-stimulatory molecules (OX40, 4-1BB), cytokine receptors (IL1R2, IL21R, CCR8, CD30), and co-inhibitory molecules (PD-L1, TIGIT). Here, we showed by flow cytometry that circulating CD45RO⁺ Tregs from patients with CRC (n = 25) have elevated CD30 and OX40 expression compared to healthy subjects (n = 14). We identified co-expression of CD30 and OX40 on circulating CD45RO⁺ Tregs using single-cell images captured by the DEPArray^™ system. The frequency of CD30⁺OX40⁺CD45RO⁺ Tregs was significantly higher in CRC patients than in healthy subjects (P < 0.001). Importantly, receiver operating characteristic analysis confirmed that this CD30⁺OX40⁺ Treg subset could strongly discriminate between CRC patients and healthy subjects with the highest accuracy of 92.3%, an AUC of 0.92, a sensitivity of 88%, a specificity of 100%, a positive predictive value of 100%, a negative predictive value of 82.35%, and a trade-off value of 3.44%, compared to other Treg subsets. Consistently, multiplex-IHC/IF of tumor-infiltrating Tregs revealed a significant association between high densities of CD30⁺OX40⁺ Tregs and improved overall survival; no such association was found for other subsets. These data suggest a potential role for CD30⁺OX40⁺ Tregs as a diagnostic or prognostic biomarker in CRC.

Immunohistochemical scoring of CD38 in the tumor microenvironment predicts responsiveness to anti-PD-1/PD-L1 immunotherapy in hepatocellular carcinoma

Introduction

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-associated mortality globally. Immune-checkpoint blockade (ICB) is one of the systemic therapy options for HCC. However, response rates remain low, necessitating robust predictive biomarkers. In the present study, we examined the expression of CD38, a molecule involved in the immunosuppressive adenosinergic pathway, on immune cells present in the tumor microenvironment. We then investigated the association between CD38 and ICB treatment outcomes in advanced HCC.

Methods

Clinically annotated samples from 49 patients with advanced HCC treated with ICB were analyzed for CD38 expression using immunohistochemistry (IHC), multiplex immunohistochemistry/immunofluorescence (mIHC/IF) and multiplex cytokine analysis.

Results

IHC and mIHC/IF analyses revealed that higher intratumoral CD38⁺ cell proportion was strongly associated with improved response to ICB. The overall response rates to ICB was significantly higher among patients with high proportion of total CD38⁺cells compared with patients with low proportion (43.5% vs 3.9%, p=0.019). Higher responses seen among patients with a high intratumoral CD38⁺cell proportion translated to a longer median progression-free survival (mPFS, 8.21 months vs 1.64 months, p=0.0065) and median overall survival (mOS, 19.06 months vs 9.59 months, p=0.0295). Patients with high CD38⁺CD68⁺macrophage density had a better mOS of 34.43 months compared with 9.66 months in patients with low CD38⁺CD68⁺ macrophage density. CD38^hi macrophages produce more interferon γ (IFN-γ) and related cytokines, which may explain its predictive value when treated with ICB.

Conclusions

A high proportion of CD38⁺ cells, determined by IHC, predicts response to ICB and is associated with superior mPFS and OS in advanced HCC.

Hyperspectral and multispectral imaging in digital and computational pathology: a systematic review [Invited]

Hyperspectral imaging (HSI) and multispectral imaging (MSI) technologies have the potential to transform the fields of digital and computational pathology. Traditional digitized histopathological slides are imaged with RGB imaging. Utilizing HSI/MSI, spectral information across wavelengths within and beyond the visual range can complement spatial information for the creation of computer-aided diagnostic tools for both stained and unstained histological specimens. In this systematic review, we summarize the methods and uses of HSI/MSI for staining and color correction, immunohistochemistry, autofluorescence, and histopathological diagnostic research. Studies include hematology, breast cancer, head and neck cancer, skin cancer, and diseases of central nervous, gastrointestinal, and genitourinary systems. The use of HSI/MSI suggest an improvement in the detection of diseases and clinical practice compared with traditional RGB analysis, and brings new opportunities in histological analysis of samples, such as digital staining or alleviating the inter-laboratory variability of digitized samples. Nevertheless, the number of studies in this field is currently limited, and more research is needed to confirm the advantages of this technology compared to conventional imagery.

Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy

Conventional immunohistochemistry (IHC) is a widely used diagnostic technique in tissue pathology. However, this technique is associated with a number of limitations, including high inter-observer variability and the capacity to label only one marker per tissue section. This review details various highly multiplexed techniques that have emerged to circumvent these constraints, allowing simultaneous detection of multiple markers on a single tissue section and the comprehensive study of cell composition, cellular functional and cell-cell interactions. Among these techniques, multiplex Immunohistochemistry/Immunofluorescence (mIHC/IF) has emerged to be particularly promising. mIHC/IF provides high-throughput multiplex staining and standardized quantitative analysis for highly reproducible, efficient and cost-effective tissue studies. This technique has immediate potential for translational research and clinical practice, particularly in the era of cancer immunotherapy.

Tertiary lymphoid structures and associated plasma cells play an important role in the biology of triple-negative breast cancers

PURPOSE

Triple-negative breast cancers (TNBC) are aggressive tumours that exhibit abundant lymphoid infiltrates which modulate tumour behaviour. Recent findings suggest that TNBC with higher densities of plasma cells are associated with a favourable prognosis, and tertiary lymphoid structures (TLS) have prognostic significance. Here, we studied the phenotype and function of plasma cells in TNBCs by assessing their association with IgG Kappa light chain expression, B cells, and TLS.

METHODS

A retrospective analysis of 269 TNBC cases was performed. Tumour-infiltrating CD38+ plasma cells, CD20+ B cells, and TLS were evaluated on conventional haematoxylin-eosin-stained and immunohistochemical-stained sections of TNBC. We then selected TNBC cases demonstrating the highest and lowest densities of plasma cells, and examined their association with TLS, B cells, as well as immunoglobulin expression using Opal-Vectra multiplex immunofluorescence (IF).

RESULTS

TNBC with high density of plasma cells showed significantly higher numbers of IgG Kappa+ CD38+ cells (p = 0.0089, p < 0.0001), and higher numbers of TLS (p < 0.0001), compared to TNBC with low density of plasma cells. TNBC with high density of plasma cells also showed higher numbers of CD20+ B cells in the tumour core (p < 0.0001), invasive margin (p < 0.0001), as well as stromal (p = 0.015) compartments.

CONCLUSION

TNBC with high density of plasma cells are associated with higher numbers of IgG Kappa+ CD38+ cells, CD20+ B cells, and TLS. Further studies to characterize the function of plasma cell infiltrates and how they may interact with other tumour-infiltrating lymphocytes and TLS in TNBC may help improve existing immunotherapy strategies.

Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) for PD-L1 testing in triple-negative breast cancer: a translational assay compared with conventional IHC

BACKGROUND

Programmed death-ligand 1 (PD-L1) monoclonal antibody therapy has recently gained approval for treating metastatic triple-negative breast cancer (TNBC) -, in particular in the PD-L1⁺ patient subgroup of the recent IMpassion130 trial. The SP142 PD-L1 antibody clone was used as a predictive assay in this trial, but this clone was found to be an outlier in previous harmonisation studies in lung cancer.

AIMS

To address the comparability of PD-L1 clones in TNBC, we evaluated the concordance between conventional immunohistochemistry (IHC) and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) that allowed simultaneous quantification of three different PD-L1 antibodies (22C3, SP142 and SP263).

METHODS

Our cohort comprised 25 TNBC cases, 12 non-small-cell lung carcinomas and 8 other cancers. EpCAM labelling was used to distinguish tumour cells from immune cells.

RESULTS

Moderate-to-strong correlations in PD-L1 positivity were found between results obtained through mIHC/IF and IHC. Individual concordance rates in the study ranged from 67% to 100%, with Spearman's rank correlation coefficient values up to 0.88.

CONCLUSIONS

mIHC/IF represents a promising tool in the era of cancer immunotherapy, as it can simultaneously detect and quantify PD-L1 labelling with multiple antibody clones, and allow accurate evaluation of tumour and immune cells. Clinicians and pathologists require this information to predict patient response to anti-PD-1/PD-L1 therapy. The adoption of this assay may represent a significant advance in the management of therapeutically challenging cancers. Further analysis and assay harmonisation are essential for translation to a routine diagnostic setting.

Digital image analysis of multiplex fluorescence IHC in colorectal cancer recognizes the prognostic value of CDX2 and its negative correlation with SOX2

Flourescence-based multiplex immunohistochemistry (mIHC) combined with multispectral imaging and digital image analysis (DIA) is a quantitative high-resolution method for determination of protein expression in tissue. We applied this method for five biomarkers (CDX2, SOX2, SOX9, E-cadherin, and β-catenin) using tissue microarrays of a Norwegian unselected series of primary colorectal cancer. The data were compared with previously obtained chromogenic IHC data of the same tissue cores, visually assessed by the Allred method. We found comparable results between the methods, although confirmed that DIA offered improved resolution to differentiate cases with high and low protein expression. However, we experienced inherent challenges with digital image analysis of membrane staining, which was better assessed visually. DIA and mIHC enabled quantitative analysis of biomarker coexpression on the same tissue section at the single-cell level, revealing a strong negative correlation between the differentiation markers CDX2 and SOX2. Both methods confirmed known prognostic associations for CDX2, but DIA improved data visualization and detection of clinicopathological and biological associations. In summary, mIHC combined with DIA is an efficient and reliable method to evaluate protein expression in tissue, here shown to recapitulate and improve detection of known clinicopathological and survival associations for the emerging biomarker CDX2, and is therefore a candidate approach to standardize CDX2 detection in pathology laboratories.

Expression of CD38 on Macrophages Predicts Improved Prognosis in Hepatocellular Carcinoma

Background: CD38 is involved in the adenosine pathway, which represents one of the immunosuppressive mechanisms in cancer. CD38 is broadly expressed across immune cell subsets, including human macrophages differentiated in vitro from monocytes, but expression by tissue-resident macrophages remains to be demonstrated. Methods: Tissue samples were obtained from 66 patients with hepatocellular carcinoma (HCC) from Singapore and analyzed using immunohistochemistry. Tumor-infiltrating leukocytes (TILs) were further examined using DEPArray™, and the phenotype of freshly isolated TILs was determined using flow cytometry. Results: CD38 was frequently co-expressed with the macrophage-specific marker CD68. CD38⁺CD68⁺ macrophage density was associated with improved prognosis after surgery, while total CD68⁺ macrophage density was associated with poor prognosis. DEPArray™ analysis revealed the presence of large (>10 μm), irregularly shaped CD45⁺CD14⁺ cells that resembled macrophages, with concurrent CD38⁺ expression. Flow cytometry also revealed that majority of CD14⁺HLA-DR⁺ cells expressed CD38. Conclusion: CD38 expression was clearly demonstrated on human macrophages in an in vivo setting. The positive association identified between CD38⁺ macrophage density and prognosis may have implications for routine diagnostic work.

Evaluation of phospho-histone H3 in Asian triple-negative breast cancer using multiplex immunofluorescence

PURPOSE

We used multiplex immunofluorescence (mIF) to determine whether mitotic rate represents an independent prognostic marker in triple-negative breast cancer (TNBC). Secondary aims were to confirm the prognostic significance of immune cells in TNBC, and to investigate the relationship between immune cells and proliferating tumour cells.

METHODS

A retrospective Asian cohort of 298 patients with TNBC diagnosed from 2003 to 2015 at the Singapore General Hospital was used in the present study. Formalin-fixed, paraffin-embedded breast cancer samples were analysed on tissue microarrays using mIF, which combined phospho-histone H3 (pHH3) expression with cytokeratin (CK) and leukocyte common antigen (CD45) expression to identify tumour and immune cells, respectively.

RESULTS

Multivariate analysis showed that a high pHH3 index was associated with significantly improved overall survival (OS; p = 0.004), but this was not significantly associated with disease-free survival (DFS; p = 0.22). Similarly, multivariate analysis also revealed that a pHH3 positive count of > 1 cell per high-power field in the malignant epithelial compartment was an independent favourable prognostic marker for OS (p = 0.033) but not for DFS (p = 0.250). Furthermore, a high CD45 index was an independent favourable prognostic marker for DFS (p = 0.018), and there was a significant positive correlation between CD45 and pHH3 index (Spearman rank correlation coefficient, 0.250; p < 0.001).

CONCLUSIONS

Mitotic rates as determined by pHH3 expression in epithelial cells are significantly associated with improved survival in TNBC. mIF analysis of pHH3 in combination with CK and CD45 could help clinicians in prognosticating patients with TNBC.

The role of Ki-67 in Asian triple negative breast cancers: a novel combinatory panel approach

The proliferation marker Ki-67 is frequently used to assess aggressiveness in the pathological evaluation of cancer, but its role remains uncertain in triple-negative breast cancer (TNBC). We aimed to quantify and localize Ki-67 expression in both epithelial and immune compartments in TNBC and investigate its association with clinicopathological parameters and survival outcomes. A total of 406 TNBC cases diagnosed between 2003 and 2015 at Singapore General Hospital were recruited. Using state-of-the-art, 7-colour multiplex immunofluorescence (mIF) tissue microarrays (TMAs) were stained to assess the abundance, density and spatial distribution of Ki-67-positive tumour cells and immune cells co-decorated with cytokeratin (CK) and leukocyte common antigen (CD45) respectively. Furthermore, MKI67 mRNA profiles were analysed using NanoString technology. In multivariate analysis adjusted for tumour size, histologic grade, age at diagnosis, and lymph node stage, a high Ki-67 labelling index (LI) > 0.3% was associated with improved disease-free survival (DFS; HR = 0.727; p = 0.027). High Ki-67-positive immune cell count per TMA was a favourable prognostic marker for both DFS (HR = 0.379; p = 0.00153) and overall survival (OS; HR = 0.473; p = 0.0482). The combination of high Ki-67 LI and high MKI67 expression was associated with improved DFS (HR = 0.239; p = 0.00639) and OS (HR = 0.213; p = 0.034). This study is among the first to highlight that Ki-67 is associated with favourable prognosis in an adjuvant setting in TNBC, and the mIF-based evaluation of Ki-67 expression on both tumour and immune cells represents a novel prognostic approach.

Prognostic value of CD8 + PD-1+ immune infiltrates and PDCD1 gene expression in triple negative breast cancer

The role of programmed cell death protein-1 (PD-1)/programmed cell death ligand 1 (PD-L1) in triple negative breast cancer (TNBC) remains to be fully understood. In this study, we investigated the role of PD-1 as a prognostic marker for TNBC in an Asian cohort (n = 269). Samples from patients with TNBC were labeled with antibodies against PD-L1 and PD-1, and subjected to NanoString assays to measure the expression of immune-related genes. Associations between disease-free survival (DFS), overall survival (OS) and biomarker expression were investigated. Multivariate analysis showed that tumors with high PD-1⁺ immune infiltrates harbored significantly increased DFS, and this increase was significant even after controlling for clinicopathological parameters (HR 0.95; P = 0.030). In addition, the density of cells expressing both CD8 and PD-1, but not the density of CD8⁻PD-1⁺ immune infiltrates, was associated with improved DFS. Notably, this prognostic significance was independent of clinicopathological parameters and the densities of total CD8⁺ cell (HR 0.43, P = 0.011). At the transcriptional level, high expression of PDCD1 within the tumor was significantly associated with improved DFS (HR 0.38; P = 0.027). In line with these findings, high expression of IFNG (HR 0.38; P = 0.001) and IFN signaling genes (HR 0.46; p = 0.027) was also associated with favorable DFS. Inclusion of PD-1 immune infiltrates and PDCD1 gene expression added significant prognostic value for DFS (ΔLRχ² = 6.35; P = 0.041) and OS (ΔLRχ² = 9.53; P = 0.008), beyond that provided by classical clinicopathological variables. Thus, PD-1 mRNA and protein expression status represent a promising, independent indicator of prognosis in TNBC.

An integrated automated multispectral imaging technique that simultaneously detects and quantitates viral RNA and immune cell protein markers in fixed sections from Epstein-Barr virus-related tumours

BACKGROUND/AIM

Epstein-Barr virus (EBV) is an oncovirus that is commonly associated with the development of lymphomas and epithelial carcinomas. In the era of immunotherapy, histological evaluation of EBV-related cancers is currently a multi-sample, multi-technique process requiring separate time-consuming detection of EBV-encoded small RNAs by in situ hybridisation (ISH), and parallel labelling of sections for cancer-associated protein markers.

METHODS

Using EBV-associated tumours as proof-of-concept for feasibility, here we developed an approach that allows simultaneous detection of EBV RNAs and multiple protein markers such as PD-L1, EBV-LMP, CD8, CD4, CD20, CD30 and CD15on a single tissue section based on our recently reported automated staining protocol.

RESULTS

We successfully combined multiplex immunofluorescence (mIF) to detect 3 abovementioned protein markers involved in cancer, with ISH, and applied the protocol to f tissue samples from patients diagnosed with EBV-associated pulmonary lymphoepithelioma-like carcinoma (LELC), gastric carcinoma and Hodgkin's Lymphoma. Empowered by the Vectra 3 Automated Quantitative Pathology Imaging System, we demonstrate the utility and potential of this integrated approach to concurrently detect and quantitate viral RNA and protein biomarkers of immune and tumour cells.

CONCLUSION

This study represents an important step forward in the research and diagnosis of EBV-associated cancers, and could be readily modified to include other proteins and RNA markers to apply to other malignancies. More importantly, the novel automated ISH-mIF protocol that we detailly described here could also be readily reproduced by most of the diagnostic and research lab to future projects that aim to look at both RNA and protein markers.

Principles and approaches for reproducible scoring of tissue stains in research

Evaluation of tissues is a common and important aspect of translational research studies. Labeling techniques such as immunohistochemistry can stain cells/tissues to enhance identification of specific cell types, cellular activation states, and protein expression. While qualitative evaluation of labeled tissues has merit, use of semiquantitative and quantitative scoring approaches can greatly enhance the rigor of the tissue data. Adhering to key principles for reproducible scoring can enhance the quality and reproducibility of the tissue data so as to maximize its biological relevance and scientific impact.

Human relaxins (RLNH1, RLNH2), their receptor (RXFP1) and fetoplacental growth

Relaxin, a systemic and placental hormone, has potential roles in fetoplacental growth. Human placenta expresses two RLN genes, RLNH1 and RLNH2 Maternal obesity is common and is associated with abnormal fetal growth. Our aims were to relate systemic and cord blood RLNH2, placental RLNs and their receptor (RXFP1) with fetoplacental growth in context of maternal body mass index, and associations with insulin-like growth factor 2 (IGF2) and vascular endothelial growth factor A (VEGFA) in the same placentas. Systemic, cord blood and placental samples were collected prior to term labor, divided by prepregnancy body mass index: underweight/normal (N = 25) and overweight/obese (N = 44). Blood RLNH2 was measured by ELISA; placental RLNH2, RLNH1, RXFP1, IGF2 and VEGFA were measured by quantitative immunohistochemistry and mRNAs were measured by quantitative reverse transcription PCR. Birthweight increased with systemic RLNH2 only in underweight/normal women (P = 0.036). Syncytiotrophoblast RLNH2 was increased in overweight/obese patients (P = 0.017) and was associated with placental weight in all subjects (P = 0.038). RLNH1 had no associations with birthweight or placental weight, but was associated with increased trophoblast and endothelial IGF2 and VEGFA, due to female fetal sex. Thus, while systemic RLNH2 may be involved in birthweight regulation in underweight/normal women, placental RLNH2 in all subjects may be involved in placental weight. A strong association of trophoblast IGF2 with birthweight and placental weight in overweight/obese women suggests its importance. However, an association of only RLNH1 with placental IGF2 and VEGFA was dependent upon female fetal sex. These results suggest that both systemic and placental RLNs may be associated with fetoplacental growth.

Quantitative Analysis of Immunohistochemistry in Melanoma Tumors

Identification of positive staining is often qualitative and subjective. This is particularly troublesome in pigmented melanoma lesions, because melanin is difficult to distinguish from the brown stain resulting from immunohistochemistry (IHC) using horse radish peroxidase developed with 3,3'-Diaminobenzidine (HRP-DAB). We sought to identify and quantify positive staining, particularly in melanoma lesions. We visualized G-protein coupled estrogen receptor (GPER) expression developed with HRP-DAB and counterstained with Azure B (stains melanin) in melanoma tissue sections (n = 3). Matched sections (n = 3), along with 22 unmatched sections, were stained only with Azure B as a control. Breast tissue (n = 1) was used as a positive HRP-DAB control. Images of the stained tissues were generated using a Nuance Spectral Imaging Camera. Analysis of the images was performed using the Nuance Spectral Imaging software and SlideBook. Data was analyzed using a Kruskal-Wallis one way analysis of variance (ANOVA). We showed that a pigmented melanoma tissue doubly stained with anti-GPER HRP-DAB and Azure B can be unmixed using spectra derived from a matched, Azure B-only section, and an anti-GPER HRP-DAB control. We unmixed each of the melanoma lesions using each of the Azure B spectra, evaluated the mean intensity of positive staining, and examined the distribution of the mean intensities (P = .73; Kruskal-Wallis). These results suggest that this method does not require a matched Azure B-only stained control tissue for every melanoma lesion, allowing precious tissues to be conserved for other studies. Importantly, this quantification method reduces the subjectivity of protein expression analysis, and provides a valuable tool for accurate evaluation, particularly for pigmented tissues.

Considerations for standardizing predictive molecular pathology for cancer prognosis

INTRODUCTION

Molecular tests that were once ancillary to the core business of cyto-histopathology are becoming the most relevant workload in pathology departments after histopathology/cytopathology and before autopsies. This has resulted from innovations in molecular biology techniques, which have developed at an incredibly fast pace. Areas covered: Most of the current widely used techniques in molecular pathology such as FISH, direct sequencing, pyrosequencing, and allele-specific PCR will be replaced by massive parallel sequencing that will not be considered next generation, but rather, will be considered to be current generation sequencing. The pre-analytical steps of molecular techniques such as DNA extraction or sample preparation will be largely automated. Moreover, all the molecular pathology instruments will be part of an integrated workflow that traces the sample from extraction to the analytical steps until the results are reported; these steps will be guided by expert laboratory information systems. In situ hybridization and immunohistochemistry for quantification will be largely digitalized as much as histology will be mostly digitalized rather than viewed using microscopy. Expert commentary: This review summarizes the technical and regulatory issues concerning the standardization of molecular tests in pathology. A vision of the future perspectives of technological changes is also provided.

A Comparative Performance Analysis of Multispectral and RGB Imaging on HER2 Status Evaluation for the Prediction of Breast Cancer Prognosis

Despite the extensive application of multispectral imaging (MSI) in biomedical multidisciplinary researches, there is a paucity of data available regarding the implication of MSI in tumor prognosis prediction. We compared the behaviors of multispectral (MS) and conventional red-green-blue (RGB) images on assessment of human epidermal growth factor receptor 2 (HER2) immunohistochemistry to explore their impact on outcome in patients with invasive breast cancer (BC). Tissue microarrays containing 240 BC patients were introduced to compare the performance of MS and RGB imaging methods on the quantitative assessment of HER2 status and the prognostic value of 5-year disease-free survival (5-DFS). Both the total and average signal optical density values of HER2 MS and RGB images were analyzed, and all patients were divided into two groups based on the different 5-DFS. The quantification of HER2 MS images was negatively correlated with 5-DFS in lymph node–negative and –positive patients (P < .05), but RGB images were not in lymph node–positive patients (P = .101). Multivariate analysis indicated that the hazard ratio (HR) of HER2 MS was higher than that of HER2 RGB (HR = 2.454; 95% confidence interval [CI], 1.636-3.681 vs HR = 2.060; 95% CI, 1.361-3.119). Additionally, area under curve (AUC) by receiver operating characteristic analysis for HER2 MS was greater than that for HER2 RGB (AUC = 0.649; 95% CI, 0.577-0.722 vs AUC = 0.596; 95% CI, 0.522-0.670) in predicting the risk for recurrence. More importantly, the quantification of HER2 MS images has higher prediction accuracy than that of HER2 RGB images (69.6% vs 65.0%) on 5-DFS. Our study suggested that better information on BC prognosis could be obtained from the quantification of HER2 MS images and MS images might perform better in predicting BC prognosis than conventional RGB images.

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Immunohistochemistry is a commonly used clinical and research lab detection technique for investigating protein expression and localization within tissues. Many semi-quantitative systems have been developed for scoring expression using immunohistochemistry, but inherent subjectivity limits reproducibility and accuracy of results. Furthermore, the investigation of spatially overlapping biomarkers such as nuclear transcription factors is difficult with current immunohistochemistry techniques. We have developed and optimized a system for simultaneous investigation of multiple proteins using high throughput methods of multiplexed immunohistochemistry and multispectral imaging. Multiplexed immunohistochemistry is performed by sequential application of primary antibodies with secondary antibodies conjugated to horseradish peroxidase or alkaline phosphatase. Different chromogens are used to detect each protein of interest. Stained slides are loaded into an automated slide scanner and a protocol is created for automated image acquisition. A spectral library is created by staining a set of slides with a single chromogen on each. A subset of representative stained images are imported into multispectral imaging software and an algorithm for distinguishing tissue type is created by defining tissue compartments on images. Subcellular compartments are segmented by using hematoxylin counterstain and adjusting the intrinsic algorithm. Thresholding is applied to determine positivity and protein co-localization. The final algorithm is then applied to the entire set of tissues. Resulting data allows the user to evaluate protein expression based on tissue type (ex. epithelia vs. stroma) and subcellular compartment (nucleus vs. cytoplasm vs. plasma membrane). Co-localization analysis allows for investigation of double-positive, double-negative, and single-positive cell types. Combining multispectral imaging with multiplexed immunohistochemistry and automated image acquisition is an objective, high-throughput method for investigation of biomarkers within tissues.

Application of multispectral imaging in quantitative immunohistochemistry study of breast cancer: a comparative study

Multispectral imaging (MSI) based on imaging and spectroscopy, as relatively novel to the field of histopathology, has been used in biomedical multidisciplinary researches. We analyzed and compared the utility of multispectral (MS) versus conventional red-green-blue (RGB) images for immunohistochemistry (IHC) staining to explore the advantages of MSI in clinical-pathological diagnosis. The MS images acquired of IHC-stained membranous marker human epidermal growth factor receptor 2 (HER2), cytoplasmic marker cytokeratin5/6 (CK5/6), and nuclear marker estrogen receptor (ER) have higher resolution, stronger contrast, and more accurate segmentation than the RGB images. The total signal optical density (OD) values for each biomarker were higher in MS images than in RGB images (all P < 0.05). Moreover, receiver operator characteristic (ROC) analysis revealed that a greater area under the curve (AUC), higher sensitivity, and specificity in evaluation of HER2 gene were achieved by MS images (AUC = 0.91, 89.1 %, 83.2 %) than RGB images (AUC = 0.87, 84.5, and 81.8 %). There was no significant difference between quantitative results of RGB images and clinico-pathological characteristics (P > 0.05). However, by quantifying MS images, the total signal OD values of HER2 positive expression were correlated with lymph node status and histological grades (P = 0.02 and 0.04). Additionally, the consistency test results indicated the inter-observer agreement was more robust in MS images for HER2 (inter-class correlation coefficient (ICC) = 0.95, r s = 0.94), CK5/6 (ICC = 0.90, r s = 0.88), and ER (ICC = 0.94, r s = 0.94) (all P < 0.001) than that in RGB images for HER2 (ICC = 0.91, r s = 0.89), CK5/6 (ICC = 0.85, r s = 0.84), and ER (ICC = 0.90, r s = 0.89) (all P < 0.001). Our results suggest that the application of MS images in quantitative IHC analysis could obtain higher accuracy, reliability, and more information of protein expression in relation to clinico-pathological characteristics versus conventional RGB images. It may become an optimal IHC digital imaging system used in quantitative pathology.

Evaluation of cytokeratin-19 in breast cancer tissue samples: a comparison of automatic and manual evaluations of scanned tissue microarray cylinders

BACKGROUND

Digital image (DI) analysis avoids visual subjectivity in interpreting immunohistochemical stains and provides more reproducible results. An automated procedure consisting of two variant methods for quantifying the cytokeratin-19 (CK19) marker in breast cancer tissues is presented.

METHODS

The first method (A) excludes the holes inside selected CK19 stained areas, and the second (B) includes them. 93 DIs scanned from complete cylinders of tissue microarrays were evaluated visually by two pathologists and by the automated procedures.

RESULTS AND CONCLUSIONS

There was good concordance between the two automated methods, both of which tended to identify a smaller CK19-positive area than did the pathologists. The results obtained with method B were more similar to those of the pathologists; probably because it takes into account the entire positive tumoural area, including the holes. However, the pathologists overestimated the positive area of CK19. Further studies are needed to confirm the utility of this automated procedure in prognostic studies.

Measuring PI3K Activation: Clinicopathologic, Immunohistochemical, and RNA Expression Analysis in Prostate Cancer

Assessing the extent of PI3K pathway activity in cancer is vital to predicting sensitivity to PI3K-targeting drugs, but the best biomarker of PI3K pathway activity in archival tumor specimens is unclear. Here, PI3K pathway activation was assessed, in clinical tissue from 1,021 men with prostate cancers, using multiple pathway nodes that include PTEN, phosphorylated AKT (pAKT), phosphorylated ribosomal protein S6 (pS6), and stathmin. Based on these markers, a 9-point score of PI3K activation was created using the combined intensity of the 4-markers and analyzed its association with proliferation (Ki67), apoptosis (TUNEL), and androgen receptor (AR) status, as well as pathologic features and cancer-specific outcomes. In addition, the PI3K activation score was compared with mRNA expression profiling data for a large subset of men. Interestingly, those tumors with higher PI3K activation scores also had higher Gleason grade (P = 0.006), increased AR (r = 0.37; P < 0.001) and Ki67 (r = 0.24; P < 0.001), and decreased TUNEL (r = -0.12; P = 0.003). Although the PI3K activation score was not associated with an increased risk of lethal outcome, a significant interaction between lethal outcome, Gleason and high PI3K score (P = 0.03) was observed. Finally, enrichment of PI3K-specific pathways was found in the mRNA expression patterns differentiating the low and high PI3K activation scores; thus, the 4-marker IHC score of PI3K pathway activity correlates with features of PI3K activation.

IMPLICATIONS

The relationship of this activation score to sensitivity to anti-PI3K agents remains to be tested but may provide more precision guidance when selecting patients for these therapies.

E3-ligase Skp2 predicts poor prognosis and maintains cancer stem cell pool in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is one of the severe head and neck carcinomas, which is rare in west countries but has high incidence in Southern Asia especially South China. Although NPC is relatively sensitive to radiotherapy, the prognosis of patients is poor due to the advanced stage at the time of diagnosis. Therefore, it is important to understand the mechanisms involved in tumorigenesis and develop early diagnostic techniques. S-phase kinase associated protein 2 (Skp2) is overexpressed in several human cancers and associates with poor prognosis. However, its function in NPC has not been fully addressed. In this study we found Skp2 was highly expressed in NPC specimen and correlated with poor prognosis. We generated Skp2 knockdown cells to further delineate its role in NPC development. Knockdown of Skp2 partially reduced cell proliferation, promoted cellular senescence, and decreased the population of stem cell like aldehyde dehydrogenase1 positive cells as well as their self-renewal ability. Our study not only interprets the predictive role of Skp2 in the poor prognosis of NPC patients, but also reveals that Skp2 regulates the NPC cancer stem cell maintenance, which shed lights on the target therapy and early diagnosis of NPC in clinical application.

KSHV Down-regulates Tropoelastin in Both an in-vitro and in-vivo Kaposi's Sarcoma Model

Kaposi's sarcoma (KS), a common cancer in individuals with HIV/AIDS, lacks a curative therapy. Few studies have examined changes in extracellular matrix (ECM) protein profiles in the development of KS. Here we used an in vitro (human dermal microvascular endothelial cells, DMVEC) and an in vivo mECK mouse model of Kaposi's to study the impact of infection on tropoelastin. Using DMVEC, Kaposi's sarcoma-associated herpesvirus (KSHV) reduced tropoelastin transcription when examined at 2, 5, 7, and 10 days post addition, a finding that was inversely correlated with a rise in viral latency associated nuclear antigen (LANA) transcription. Immunohistochemical/immunofluorescence data confirmed that DMVEC cells were KSHV-infected (evidenced by LANA production) and that there was a loss of tropoelastin protein compared to controls. Using the mECK36 mouse model of KS we observed a reduced expression of tropoelastin mRNA in 3 of 3 tumor biopsies compared to controls. Immunofluorescence staining showed high levels of viral LANA expression in the tumor core, while immunohistochemical staining showed high levels of LANA expression and spindle cells in tumors. Dual label immunohistochemistry on formalin-fixed paraffin-embedded tumor tissue revealed reduced expression of tropoelastin in LANA positive spindle cell regions quantified by Ariol SL-50 scanning analysis. Together, this suggests that alterations in tropoelastin may play an important role in the development of Kaposi's and could serve as an early marker of this disease. This information will also allow us to explore the potential role of tropoelastin anti angiogenic properties in an in vivo model for KS disease.

Somatostatin receptor immunohistochemistry in neuroendocrine tumors: comparison between manual and automated evaluation

BACKGROUND

Manual evaluation of somatostatin receptor (SSTR) immunohistochemistry (IHC) is a time-consuming and cost-intensive procedure. Aim of the study was to compare manual evaluation of SSTR subtype IHC to an automated software-based analysis, and to in-vivo imaging by SSTR-based PET/CT.

METHODS

We examined 25 gastroenteropancreatic neuroendocrine tumor (GEP-NET) patients and correlated their in-vivo SSTR-PET/CT data (determined by the standardized uptake values SUVmax,-mean) with the corresponding ex-vivo IHC data of SSTR subtype (1, 2A, 4, 5) expression. Exactly the same lesions were imaged by PET/CT, resected and analyzed by IHC in each patient. After manual evaluation, the IHC slides were digitized and automatically evaluated for SSTR expression by Definiens XD software. A virtual IHC score "BB1" was created for comparing the manual and automated analysis of SSTR expression.

RESULTS

BB1 showed a significant correlation with the corresponding conventionally determined Her2/neu score of the SSTR-subtypes 2A (rs: 0.57), 4 (rs: 0.44) and 5 (rs: 0.43). BB1 of SSTR2A also significantly correlated with the SUVmax (rs: 0.41) and the SUVmean (rs: 0.50). Likewise, a significant correlation was seen between the conventionally evaluated SSTR2A status and the SUVmax (rs: 0.42) and SUVmean (rs: 0.62).

CONCLUSION

Our data demonstrate that the evaluation of the SSTR status by automated analysis (BB1 score), using digitized histopathology slides ("virtual microscopy"), corresponds well with the SSTR2A, 4 and 5 expression as determined by conventional manual histopathology. The BB1 score also exhibited a significant association to the SSTR-PET/CT data in accordance with the high affinity profile of the SSTR analogues used for imaging.

SPINK1 protein expression and prostate cancer progression

PURPOSE

SPINK1 overexpression has been described in prostate cancer and is linked with poor prognosis in many cancers. The objective of this study was to characterize the association between SPINK1 overexpression and prostate cancer-specific survival.

EXPERIMENTAL DESIGN

The study included 879 participants in the U.S. Physicians' Health Study and Health Professionals Follow-Up Study, diagnosed with prostate cancer (1983-2004) and treated by radical prostatectomy. Protein tumor expression of SPINK1 was evaluated by immunohistochemistry on tumor tissue microarrays.

RESULTS

Seventy-four of 879 (8%) prostate cancer tumors were SPINK1 positive. Immunohistochemical data were available for PTEN, p-Akt, pS6, stathmin, androgen receptor (AR), and ERG (as a measure of the TMPRSS2:ERG translocation). Compared with SPINK1-negative tumors, SPINK1-positive tumors showed higher PTEN and stathmin expression, and lower expression of AR (P < 0.01). SPINK1 overexpression was seen in 47 of 427 (11%) ERG-negative samples and in 19 of 427 (4%) ERG-positive cases (P = 0.0003). We found no significant associations between SPINK1 status and Gleason grade or tumor stage. There was no association between SPINK1 expression and biochemical recurrence (P = 0.56). Moreover, there was no association between SPINK1 expression and prostate cancer mortality (there were 75 lethal cases of prostate cancer during a mean of 13.5 years follow-up; HR = 0.71; 95% confidence interval, 0.29-1.76).

CONCLUSIONS

Our results suggest that SPINK1 protein expression may not be a predictor of recurrence or lethal prostate cancer amongst men treated by radical prostatectomy. SPINK1 and ERG protein expression do not seem to be entirely mutually exclusive, as some previous studies have suggested.

Garbage in, garbage out: a critical evaluation of strategies used for validation of immunohistochemical biomarkers

The use of immunohistochemistry (IHC) in clinical cohorts is of paramount importance in determining the utility of a biomarker in clinical practice. A major bottleneck in translating a biomarker from bench-to-bedside is the lack of well characterized, specific antibodies suitable for IHC. Despite the widespread use of IHC as a biomarker validation tool, no universally accepted standardization guidelines have been developed to determine the applicability of particular antibodies for IHC prior to its use. In this review, we discuss the technical challenges faced by the use of immunohistochemical biomarkers and rigorously explore classical and emerging antibody validation technologies. Based on our review of these technologies, we provide strict criteria for the pragmatic validation of antibodies for use in immunohistochemical assays.

Quantitative and spatial image analysis of tumor and draining lymph nodes using immunohistochemistry and high-resolution multispectral imaging to predict metastasis

Immunohistochemistry is an essential tool for clinical and translational research laboratories. It is mostly used as a qualitative measure of morphology and cell types within tissue. We have developed a high-resolution multispectral imaging method to expand the uses of immunohistochemistry by making it quantitative. In this chapter we describe the technology, both hardware and software, that we use for this method and give examples of applications.

Veterinary and human biobanking practices: enhancing molecular sample integrity

Animal models have historically informed veterinary and human pathophysiology. Next-generation genomic sequencing and molecular analyses using analytes derived from tissue require integrative approaches to determine macroanalyte integrity as well as morphology for imaging algorithms that can extend translational applications. The field of biospecimen science and biobanking will play critical roles in tissue sample collection and processing to ensure the integrity of macromolecules, aid experimental design, and provide more accurate and reproducible downstream genomic data. Herein, we employ animal experiments to combine protein expression analysis by microscopy with RNA integrity number and quantitative measures of morphologic changes of autolysis. These analyses can be used to predict the effect of preanalytic variables and provide the basis for standardized methods in tissue sample collection and processing. We also discuss the application of digital imaging with quantitative RNA and tissue-based protein measurements to show that genomic methods augment traditional in vivo imaging to support biospecimen science. To make these observations, we have established a time course experiment of murine kidney tissues that predicts conventional measures of RNA integrity by RIN analysis and provides reliable and accurate measures of biospecimen integrity and fitness, in particular for time points less than 3 hours post-tissue resection.

When tissue antigens and antibodies get along: revisiting the technical aspects of immunohistochemistry--the red, brown, and blue technique

Once focused mainly on the characterization of neoplasms, immunohistochemistry (IHC) today is used in the investigation of a broad range of disease processes with applications in diagnosis, prognostication, therapeutic decisions to tailor treatment to an individual patient, and investigations into the pathogenesis of disease. This review addresses the technical aspects of immunohistochemistry (and, to a lesser extent, immunocytochemistry) with attention to the antigen-antibody reaction, optimal fixation techniques, tissue processing considerations, antigen retrieval methods, detection systems, selection and use of an autostainer, standardization and validation of IHC tests, preparation of proper tissue and reagent controls, tissue microarrays and other high-throughput systems, quality assurance/quality control measures, interpretation of the IHC reaction, and reporting of results. It is now more important than ever, with these sophisticated applications, to standardize the entire IHC process from tissue collection through interpretation and reporting to minimize variability among laboratories and to facilitate quantification and interlaboratory comparison of IHC results.

Spatial organization of dendritic cells within tumor draining lymph nodes impacts clinical outcome in breast cancer patients

BACKGROUND

Dendritic cells (DCs) are important mediators of anti-tumor immune responses. We hypothesized that an in-depth analysis of dendritic cells and their spatial relationships to each other as well as to other immune cells within tumor draining lymph nodes (TDLNs) could provide a better understanding of immune function and dysregulation in cancer.

METHODS

We analyzed immune cells within TDLNs from 59 breast cancer patients with at least 5 years of clinical follow-up using immunohistochemical staining with a novel quantitative image analysis system. We developed algorithms to analyze spatial distribution patterns of immune cells in cancer versus healthy intra-mammary lymph nodes (HLNs) to derive information about possible mechanisms underlying immune-dysregulation in breast cancer. We used the non-parametric Mann-Whitney test for inter-group comparisons, Wilcoxon Matched-Pairs Signed Ranks test for intra-group comparisons and log-rank (Mantel-Cox) test for Kaplan Maier analyses.

RESULTS

Degree of clustering of DCs (in terms of spatial proximity of the cells to each other) was reduced in TDLNs compared to HLNs. While there were more numerous DC clusters in TDLNs compared to HLNs,DC clusters within TDLNs tended to have fewer member DCs and also consisted of fewer cells displaying the DC maturity marker CD83. The average number of T cells within a standardized radius of a clustered DC was increased compared to that of an unclustered DC, suggesting that DC clustering was associated with T cell interaction. Furthermore, the number of T cells within the radius of a clustered DC was reduced in tumor-positive TDLNs compared to HLNs. Importantly, clinical outcome analysis revealed that DC clustering in tumor-positive TDLNs correlated with the duration of disease-free survival in breast cancer patients.

CONCLUSIONS

These findings are the first to describe the spatial organization of DCs within TDLNs and their association with survival outcome. In addition, we characterized specific changes in number, size, maturity, and T cell co-localization of such clusters. Strategies to enhance DC function in-vivo, including maturation and clustering, may provide additional tools for developing more efficacious DC cancer vaccines.

Automated reagent-dispensing system for microfluidic cell biology assays

Microscale systems that enable measurements of oncological phenomena at the single-cell level have a great capacity to improve therapeutic strategies and diagnostics. Such measurements can reveal unprecedented insights into cellular heterogeneity and its implications into the progression and treatment of complicated cellular disease processes such as those found in cancer. We describe a novel fluid-delivery platform to interface with low-cost microfluidic chips containing arrays of microchambers. Using multiple pairs of needles to aspirate and dispense reagents, the platform enables automated coating of chambers, loading of cells, and treatment with growth media or other agents (e.g., drugs, fixatives, membrane permeabilizers, washes, stains, etc.). The chips can be quantitatively assayed using standard fluorescence-based immunocytochemistry, microscopy, and image analysis tools, to determine, for example, drug response based on differences in protein expression and/or activation of cellular targets on an individual-cell level. In general, automation of fluid and cell handling increases repeatability, eliminates human error, and enables increased throughput, especially for sophisticated, multistep assays such as multiparameter quantitative immunocytochemistry. We report the design of the automated platform and compare several aspects of its performance to manually-loaded microfluidic chips.