Quantitative measurement of cancer tissue biomarkers in the lab and in the clinic

Lung Cancer Therapy: The Role of Personalized Medicine

Lung cancer is the deadliest cancer worldwide, exhibiting the highest incidence rate among all cancer types. Poor outcomes often characterize this cancer as it is commonly diagnosed in advanced stages due to its unspecific symptoms. After diagnosis, the therapeutic choice is a crucial stage that profoundly affects patients' survival. Treatment choices for lung cancer must be made carefully, acknowledging the histological type and genetic characteristics of the tumor. Non-small cell lung cancer, the most common and complex type, has a high mutational burden, making next-generation sequencing (NGS) essential for identifying specific mutations and guiding treatment. With several approved targeted therapies already available, this approach highlights the critical role of personalized medicine in lung cancer care. Despite the current therapeutic pipeline, research trying to develop new tailored drugs considering individual patient characteristics has evolved over the years. This article aims to outline the current therapeutic approach for each type of lung cancer and present the latest insights into emerging therapies, highlighting the role of personalized medicine in enhancing treatment outcomes and improving patients' quality of life.

Multi-Tissue Controls and Multiplex Immunocytochemistry in Pulmonary Cytology

INTRODUCTION

The World Health Organization 2021 lung cancer classification highlights the central role of immunohistochemistry (IHC) in diagnostic pathology. Despite traditional IHC being essential, its limitation to one marker per tissue section brings challenges, particularly when facing cytological limitedly sized samples. To overcome these challenges, multiplex immunocytochemistry (mICC) techniques offer the simultaneous detection of multiple markers from a single section. These advances complement the highly complex imaging techniques that enable additional analyses of cellular interactions.

METHODS

The present study outlines a comprehensive mICC methodology of an automated multiplex immunoperoxidase staining method and multiple tissue hybrid controls for ICC/mICC. Protocols are presented in detail and demonstrate a careful approach to optimizing various markers for diagnostic workup including immunotherapy.

CONCLUSION

Multiplex IHC/ICC emerges as a transformative force in biomedical diagnostics and research. Beyond simultaneous marker detection, it unravels complexities within tissues - unveiling co-localization nuances, deciphering expression patterns, and enhancing understanding of cellular populations. As personalized treatments gain prominence, the study emphasizes the heightened importance of diagnostic tools and sample adequacy. The present methodological study, encapsulating an automated multiplex immunoperoxidase staining method, symbolizes a stride towards precision in pulmonary carcinoma diagnosis. Multi-tissue controls represent a key element in quality assurance in pathology laboratories.

Prognostic biomarkers associated with immune checkpoint inhibitors in hepatocellular carcinoma

The treatment of hepatocellular carcinoma (HCC), particularly advanced HCC, has been a serious challenge. Immune checkpoint inhibitors (ICIs) are landmark drugs in the field of cancer therapy in recent years, which have changed the landscape of cancer treatment. In the field of HCC treatment, this class of drugs has shown good therapeutic prospects. For example, atezolizumab in combination with bevacizumab has been approved as first-line treatment for advanced HCC due to significant efficacy. However, sensitivity to ICI therapy varies widely among HCC patients. Therefore, there is an urgent need to search for determinants of resistance/sensitivity to ICIs and to screen biomarkers that can predict the efficacy of ICIs. This manuscript reviews the research progress of prognostic biomarkers associated with ICIs in HCC in order to provide a scientific basis for the development of clinically individualised precision medication regimens.

Noninvasive PET imaging of tumor PD-L1 expression with 64Cu-labeled Durvalumab

Breast cancer (BrCa) ranks as the most prevalent malignant neoplasm affecting women worldwide. The expression of programmed death-ligand 1 (PD-L1) in BrCa has recently emerged as a biomarker for immunotherapy response, but traditional immunohistochemistry (IHC)-based methods are hindered by spatial and temporal heterogeneity. Noninvasive and quantitative PD-L1 imaging using appropriate radiotracers can serve to determine PD-L1 expression in tumors. This study aims to demonstrate the viability of PET imaging with 64Cu-labeled Durvalumab (abbreviated as Durva) to assess PD-L1 expression using a murine xenograft model of breast cancer. Durvalumab, a human IgG1 monoclonal antibody against PD-L1, was assessed for specificity in vitro in two cancer cell lines (MDA-MB-231 triple-negative breast cancer cell line and AsPC-1 pancreatic cancer cell line) with positive and negative PD-L1 expression by flow cytometry. Next, we performed the in vivo evaluation of 64Cu-NOTA-Durva in murine models of human breast cancer by PET imaging and ex vivo biodistribution. Additionally, mice bearing AsPC-1 tumors were employed as a negative control. Tumor uptake was quantified based on a 3D region-of-interest (ROI) analysis of the PET images and ex vivo biodistribution measurements, and the results were compared against conventional IHC testing. The radiotracer uptake was evident in MDA-MB-231 tumors and showed minimal nonspecific binding, corroborating IHC-derived results. The results of the biodistribution showed that the MDA-MB-231 tumor uptake of 64Cu-NOTA-Durva was much higher than 64Cu-NOTA-IgG (a nonspecific radiolabeled IgG). In Conclusion, 64Cu-labeled Durvalumab PET/CT imaging offers a promising, noninvasive approach to evaluate tumor PD-L1 expression.

A new vision of photothermal therapy assisted with gold nanorods for the treatment of mammary cancers in adult female rats

Over the past decade, the therapeutic landscape has markedly changed for patients with breast cancers (BCs), yet few studies have evaluated the power of the photothermal therapy (PTT) technique. The present study aimed to assess the potency of 7,12-dimethylbenz[a]anthracene (DMBA)-induced mammary cancer treatment with this technique. In total, forty-two adult virgin female Wistar rats were categorized into seven groups, negative control, polyvinylpyrrolidone-capped gold nanorods (PVP-AuNRs) positive control (400 μL per rat ∼ 78 ppm), NIR laser irradiation 808 nm positive control with an intensity of (808 nm NIR CW diode laser, 200 mW cm-2 for 5 min), DMBA-treatment, DMBA-induced mammary cancer group treated with polyvinylpyrrolidone-capped gold nanorods, DMBA-induced mammary cancer group treated with NIR laser irradiation, and DMBA-induced mammary cancer group treated with polyvinylpyrrolidone-capped gold nanorods and NIR laser irradiation. Treatment with polyvinylpyrrolidone-capped gold nanorods and/or NIR laser irradiation was performed after three weeks of DMBA-induced mammary cancer. The mammary tumor lesions in the rat model induced with DMBA are highly invasive. Synthesis and characterization of gold nanorods (AuNRs) with an aspect ratio ranging from 2.8 to 3 were employed to validate the nanostructure and polyvinylpyrrolidone capping and their stability in absorbing near-infrared light. As a result, the therapy strategy, DMBA + PVP-AuNRs + NIR, effectively treated the tumor and halted its growth. The mammary glands were dissected and subjected to biochemical analysis for serum and tissue. Our treatment technique improved the histological aspects of mammary cancer in various forms of mammary cancer detected. Immuno-histochemical localization and TEM images supported these results reflecting the efficacy of this technique. Finally, our findings uncover for the first time the revolutionary effect of the PTT strategy using PVP-capped AuNRs in selectively destroying mammary cancer cells in rats.

The spatial coexistence of TIGIT/CD155 defines poorer survival and resistance to adjuvant chemotherapy in pancreatic ductal adenocarcinoma

Background: Targeting emerging T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT)/CD155 axis shows promise for restoring anti-tumor immunity, but its immune phenotypes and prognostic significance in a large cohort of pancreatic ductal adenocarcinoma (PDAC) are limited. Methods: Three seven-color multispectral panels were rationally designed to investigate the protein expression, immune-microenvironmental feature, prognostic value, and the response to adjuvant chemotherapy of TIGIT/CD155 in 272 PDAC specimens using multiplex immunohistochemistry. Results: We revealed low immunogenicity and high heterogeneity of the PDAC immune microenvironment featured by abundant CD3+ T cells and CD68+ macrophages and low infiltration of activated cytotoxic T lymphocytes. TIGIT and CD155 were highly expressed in PDAC tissues compared to paracancerous tissues. Tumor-infiltrating lymphocytes expressing TIGIT were correlated with high densities of CD45RO+ T cells; TIGTI+CD8+ T cells were associated with high infiltration of CD3+CD45RO+FOXP3+. CD155+CK+ were significantly related to high densities of CD3+ and CD3+CD8+CD45RO+ T cells. High positive rates for TIGIT in TCs, CD8+ T cells, and CD155 in macrophages were correlated with poor progression-free and disease-specific survival, respectively, and their clinical significance was correlated with PD-L1 status. Notably, spatial co-existence of TIGIT+CK+ or TIGIT+CD8+ and CD155+CD68+ indicated poor survival and resistance to adjuvant chemotherapy response in patients with PDAC. Conclusion: Our findings suggest that targeting TIGIT/CD155 immunosuppressive axis may guide patient stratification and improve the clinical outcome of PDAC.

Quantile Index Biomarkers Based on Single-Cell Expression Data

Current histocytometry methods enable single-cell quantification of biomolecules in tumor tissue sections by multiple detection technologies, including multiplex fluorescence-based immunohistochemistry or in situ hybridization. Quantitative pathology platforms can provide distributions of cellular signal intensity (CSI) levels of biomolecules across the entire cell populations of interest within the sampled tumor tissue. However, the heterogeneity of CSI levels is usually ignored, and the simple mean signal intensity value is considered a cancer biomarker. Here we consider the entire distribution of CSI expression levels of a given biomolecule in the cancer cell population as a predictor of clinical outcome. The proposed quantile index (QI) biomarker is defined as the weighted average of CSI distribution quantiles in individual tumors. The weight for each quantile is determined by fitting a functional regression model for a clinical outcome. That is, the weights are optimized so that the resulting QI has the highest power to predict a relevant clinical outcome. The proposed QI biomarkers were derived for proteins expressed in cancer cells of malignant breast tumors and demonstrated improved prognostic value compared with the standard mean signal intensity predictors. The R package Qindex implementing QI biomarkers has been developed. The proposed approach is not limited to immunohistochemistry data and can be based on any cell-level expressions of proteins or nucleic acids.

Selection of optimal quantile protein biomarkers based on cell-level immunohistochemistry data

BACKGROUND

Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell level. However, this rich quantitative cell-by-cell biomarker information is most often not exploited. Instead, it is reduced to a single mean across the cells of interest or converted into a simple proportion of binary biomarker-positive or -negative cells.

RESULTS

We investigated the utility of retaining all quantitative information at the single-cell level by considering the values of the quantile function (inverse of the cumulative distribution function) estimated from a sample of cell signal intensity levels in a tumor tissue. An algorithm was developed for selecting optimal cutoffs for dichotomizing cell signal intensity distribution quantiles as predictors of continuous, categorical or survival outcomes. The proposed algorithm was used to select optimal quantile biomarkers of breast cancer progression based on cancer cells' cell signal intensity levels of nuclear protein Ki-67, Proliferating cell nuclear antigen, Programmed cell death 1 ligand 2, and Progesterone receptor. The performance of the resulting optimal quantile biomarkers was validated and compared to the standard cancer compartment mean signal intensity markers using an independent external validation cohort. For Ki-67, the optimal quantile biomarker was also compared to established biomarkers based on percentages of Ki67-positive cells. For proteins significantly associated with PFS in the external validation cohort, the optimal quantile biomarkers yielded either larger or similar effect size (hazard ratio for progression-free survival) as compared to cancer compartment mean signal intensity biomarkers.

CONCLUSION

The optimal quantile protein biomarkers yield generally improved prognostic value as compared to the standard protein expression markers. The proposed methodology has a broad application to single-cell data from genomics, transcriptomics, proteomics, or metabolomics studies at the single cell level.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.

Bile acid distributions, sex-specificity, and prognosis in colorectal cancer

BACKGROUND

Bile acids are known to be genotoxic and contribute to colorectal cancer (CRC). However, the link between CRC tumor bile acids to tumor location, patient sex, microbiome, immune-regulatory cells, and prognosis is not clear.

METHODS

We conducted bile acid analysis using targeted liquid chromatography-mass spectrometry (LC-MS) on tumor tissues from CRC patients (n = 228) with survival analysis. We performed quantitative immunofluorescence (QIF) on tumors to examine immune cells.

RESULTS

Twelve of the bile acids were significantly higher in right-sided colon tumors compared to left-sided colon tumors. Furthermore, in male patients, right-sided colon tumors had elevated secondary bile acids (deoxycholic acid, lithocholic acid, ursodeoxycholic acid) compared to left-sided colon tumors, but this difference between tumors by location was not observed in females. A high ratio of glycoursodeoxycholic to ursodeoxycholic was associated with 5-year overall survival (HR = 3.76, 95% CI = 1.17 to 12.1, P = 0.026), and a high ratio of glycochenodeoxycholic acid to chenodeoxycholic acid was associated with 5-year recurrence-free survival (HR = 3.61, 95% CI = 1.10 to 11.84, P = 0.034). We also show correlation between these bile acids and FoxP3 + T regulatory cells.

CONCLUSIONS

This study revealed that the distribution of bile acid abundances in colon cancer patients is tumor location-, age- and sex-specific, and are linked to patient prognosis. This study provides new implications for targeting bile acid metabolism, microbiome, and immune responses for colon cancer patients by taking into account primary tumor location and sex.

Quantitative measurement of HER2 expression to subclassify ERBB2 unamplified breast cancer

The efficacy of the antibody drug conjugate (ADC) Trastuzumab deruxtecan (T-DXd) in HER2 low breast cancer patients suggests that the historical/conventional assays for HER2 may need revision for optimal patient care. Specifically, the conventional assay is designed to distinguish amplified HER2 from unamplified cases but is not sensitive enough to stratify the lower ranges of HER2 expression. Here we determine the optimal dynamic range for unamplified HER2 detection in breast cancer and then redesign an assay to increase the resolution of the assay to stratify HER2 expression in unamplified cases. We used the AQUA™ method of quantitative immunofluorescence to test a range of antibody concentrations to maximize the sensitivity within the lower range of HER2 expression. Then, using a cell line microarray with HER2 protein measured by mass spectrometry we determined the amount of HER2 protein in units of attomols/mm². Then by calculation of the limits of detection, quantification, and linearity of this assay we determined that low HER2 range expression in unamplified cell lines is between 2 and 20 attomol/mm². Finally, application of this assay to a serial collection of 364 breast cancer cases from Yale shows 67% of the population has HER2 expression above the limit of quantification and below the levels seen in HER2 amplified breast cancer. In the future, this assay could be used to determine the levels of HER2 required for response to T-DXd or similar HER2 conjugated ADCs.

Validation of an Accurate Automated Multiplex Immunofluorescence Method for Immuno-Profiling Melanoma

Multiplex immunofluorescence staining enables the simultaneous detection of multiple immune markers in a single tissue section, and is a useful tool for the identification of specific cell populations within the tumour microenvironment. However, this technology has rarely been validated against standard clinical immunohistology, which is a barrier for its integration into clinical practice. This study sought to validate and investigate the accuracy, precision and reproducibility of a multiplex immunofluorescence compared with immunohistochemistry (IHC), including tissue staining, imaging and analysis, in characterising the expression of immune and melanoma markers in both the tumour and its microenvironment. Traditional chromogenic IHC, single-plex immunofluorescence and multiplex immunofluorescence were each performed on serial tissue sections of a formalin-fixed paraffin-embedded (FFPE) tissue microarray containing metastatic melanoma specimens from 67 patients. The panel included the immune cell markers CD8, CD68, CD16, the immune checkpoint PD-L1, and melanoma tumour marker SOX10. Slides were stained with the Opal^™ 7 colour Kit (Akoya Biosciences) on the intelliPATH autostainer (Biocare Medical) and imaged using the Vectra 3.0.5 microscope. Marker expression was quantified using Halo v.3.2.181 (Indica Labs). Comparison of the IHC and single-plex immunofluorescence revealed highly significant positive correlations between the cell densities of CD8, CD68, CD16, PD-L1 and SOX10 marker positive cells (Spearman’s rho = 0.927 to 0.750, p < 0.0001). Highly significant correlations were also observed for all markers between single-plex immunofluorescence and multiplex immunofluorescence staining (Spearman’s rho >0.9, p < 0.0001). Finally, correlation analysis of the three multiplex replicates revealed a high degree of reproducibility between slides (Spearman’s rho >0.940, p < 0.0001). Together, these data highlight the reliability and validity of multiplex immunofluorescence in accurately profiling the tumour and its associated microenvironment using FFPE metastatic melanoma specimens. This validated multiplex panel can be utilised for research evaluating melanoma and its microenvironment, such as studies performed to predict patient response or resistance to immunotherapies.

Bidirectional Supramolecular Display and Signal Amplification on the Surface of Living Cells

The ability to display exogenous molecules or nanomaterials on the surface of cells holds great potential for biomedical applications such as cell imaging and delivery. Numerous methods have been well established to enhance the display of biomolecules and nanomaterials on the cell surface. However, it is challenging to remove these biomolecules or nanomaterials from the cell surface. The purpose of this study was to investigate the reversible display of supramolecular nanomaterials on the surface of living cells. The data show that DNA initiators could induce the self-assembly of DNA-alginate conjugates to form supramolecular nanomaterials and amplify the fluorescence signals on the cell surface. Complementary DNA (cDNA), DNase, and alginase could all trigger the reversal of the signals from the cell surface. However, these three molecules exhibited different triggering efficiencies in the order cDNA > alginase > DNase. The combination of cDNA and alginase led to the synergistic reversal of nanomaterials and fluorescent signals from the cell surface. Thus, this study has successfully demonstrated a method for the bidirectional display of supramolecular nanomaterials on the surface of living cells. This method may find its application in numerous fields such as intact cell imaging and separation.

Development of Planar Illumination Strategies for Solving Mysteries in the Sub-Cellular Realm

Optical microscopy has vastly expanded the frontiers of structural and functional biology, due to the non-invasive probing of dynamic volumes in vivo. However, traditional widefield microscopy illuminating the entire field of view (FOV) is adversely affected by out-of-focus light scatter. Consequently, standard upright or inverted microscopes are inept in sampling diffraction-limited volumes smaller than the optical system's point spread function (PSF). Over the last few decades, several planar and structured (sinusoidal) illumination modalities have offered unprecedented access to sub-cellular organelles and 4D (3D + time) image acquisition. Furthermore, these optical sectioning systems remain unaffected by the size of biological samples, providing high signal-to-noise (SNR) ratios for objective lenses (OLs) with long working distances (WDs). This review aims to guide biologists regarding planar illumination strategies, capable of harnessing sub-micron spatial resolution with a millimeter depth of penetration.

QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability

RNA in situ hybridization (RNA-ISH) is a powerful spatial transcriptomics technology to characterize target RNA abundance and localization in individual cells. This allows analysis of tumor heterogeneity and expression localization, which are not readily obtainable through transcriptomic data analysis. RNA-ISH experiments produce large amounts of data and there is a need for automated analysis methods. Here we present QuantISH, a comprehensive open-source RNA-ISH image analysis pipeline that quantifies marker expressions in individual carcinoma, immune, and stromal cells on chromogenic or fluorescent in situ hybridization images. QuantISH is designed to be modular and can be adapted to various image and sample types and staining protocols. We show that in chromogenic RNA in situ hybridization images of high-grade serous carcinoma (HGSC) QuantISH cancer cell classification has high precision, and signal expression quantification is in line with visual assessment. We further demonstrate the power of QuantISH by showing that CCNE1 average expression and DDIT3 expression variability, as captured by the variability factor developed herein, act as candidate biomarkers in HGSC. Altogether, our results demonstrate that QuantISH can quantify RNA expression levels and their variability in carcinoma cells, and thus paves the way to utilize RNA-ISH technology.

Best Practices for Technical Reproducibility Assessment of Multiplex Immunofluorescence

Multiplex immunofluorescence (mIF) tyramide signal amplification is a new and useful tool for the study of cancer that combines the staining of multiple markers in a single slide. Several technical requirements are important to performing high-quality staining and analysis and to obtaining high internal and external reproducibility of the results. This review manuscript aimed to describe the mIF panel workflow and discuss the challenges and solutions for ensuring that mIF panels have the highest reproducibility possible. Although this platform has shown high flexibility in cancer studies, it presents several challenges in pre-analytic, analytic, and post-analytic evaluation, as well as with external comparisons. Adequate antibody selection, antibody optimization and validation, panel design, staining optimization and validation, analysis strategies, and correct data generation are important for reproducibility and to minimize or identify possible issues during the mIF staining process that sometimes are not completely under our control, such as the tissue fixation process, storage, and cutting procedures.

Multiplex Tissue Imaging Harmonization: A Multicenter Experience from CIMAC-CIDC Immuno-Oncology Biomarkers Network

PURPOSE

The Cancer Immune Monitoring and Analysis Centers - Cancer Immunologic Data Commons (CIMAC-CIDC) network supported by the NCI Cancer Moonshot initiative was established to provide correlative analyses for clinical trials in cancer immunotherapy, using state-of-the-art technology. Fundamental to this initiative is implementation of multiplex IHC assays to define the composition and distribution of immune infiltrates within tumors in the context of their potential role as biomarkers. A critical unanswered question involves the relative fidelity of such assays to reliably quantify tumor-associated immune cells across different platforms.

EXPERIMENTAL DESIGN

Three CIMAC sites compared across their laboratories: (i) image analysis algorithms, (ii) image acquisition platforms, (iii) multiplex staining protocols. Two distinct high-dimensional approaches were employed: multiplexed IHC consecutive staining on single slide (MICSSS) and multiplexed immunofluorescence (mIF). To eliminate variables potentially impacting assay performance, we completed a multistep harmonization process, first comparing assay performance using independent protocols followed by the integration of laboratory-specific protocols and finally, validating this harmonized approach in an independent set of tissues.

RESULTS

Data generated at the final validation step showed an intersite Spearman correlation coefficient (r) of ≥0.85 for each marker within and across tissue types, with an overall low average coefficient of variation ≤0.1.

CONCLUSIONS

Our results support interchangeability of protocols and platforms to deliver robust, and comparable data using similar tissue specimens and confirm that CIMAC-CIDC analyses may therefore be used with confidence for statistical associations with clinical outcomes largely independent of site, antibody selection, protocol, and platform across different sites.

Spatial Analysis and Clinical Significance of HLA Class-I and Class-II Subunit Expression in Non-Small Cell Lung Cancer

PURPOSE

To analyze the distribution, associated immune contexture, and clinical significance of human leukocyte antigen (HLA) class-I and HLA class-II subunits in non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

Using spatially resolved and quantitative multiplexed immunofluorescence we studied the tumor/stromal tissue distribution, cancer cell-specific defects, and clinicopathologic/survival associations of β2 microglobulin (β2M), HLA-A, and HLA-B,-C heavy chains, as well as HLA class-II β chain in >700 immunotherapy-naïve NSCLCs from four independent cohorts. Genomic analysis of HLA genes in NSCLC was performed using two publicly available cohorts.

RESULTS

Cancer cell-specific downregulation of HLA markers was identified in 30.4% of cases. β2M was downregulated in 9.8% (70/714), HLA-A in 9% (65/722), HLA-B,-C in 12.1% (87/719), and HLA class-II in 17.7% (127/717) of evaluable samples. Concurrent downregulation of β2M, HLA-B,-C, and HLA class-II was commonly identified. Deleterious mutations in HLA genes were detected in <5% of lung malignancies. Tumors with cancer cell-specific β2M downregulation displayed reduced T cells and increased natural killer (NK)-cell infiltration. Samples with cancer cell HLA-A downregulation displayed modest increase in CD8⁺ T cells and NK-cell infiltration. Samples with cancer cell-selective HLA-B,-C or HLA class-II downregulation displayed reduced T cells and NK-cell infiltration. There was limited association of the markers with clinicopathologic variables and KRAS/EGFR mutations. Cancer cell-selective downregulation of the HLA subunits was associated with shorter overall survival.

CONCLUSIONS

Our results reveal frequent and differential defects in HLA class-I and HLA class-II protein subunit expression in immunotherapy-naïve NSCLCs associated with distinct tumor microenvironment composition and patient survival.

Three Distinct Stroma Types in Human Pancreatic Cancer Identified by Image Analysis of Fibroblast Subpopulations and Collagen

PURPOSE

Cancer-associated fibroblasts have emerged to be highly heterogenous and can play multifaceted roles in dictating pancreatic ductal adenocarcinoma (PDAC) progression, immunosuppression, and therapeutic response, highlighting the need for a deeper understanding of stromal heterogeneity between patients and even within a single tumor. We hypothesized that image analysis of fibroblast subpopulations and collagen in PDAC tissues might guide stroma-based patient stratification to predict clinical outcomes and tumor characteristics.

EXPERIMENTAL DESIGN

A novel multiplex IHC-based image analysis system was established to digitally differentiate fibroblast subpopulations. Using whole-tissue slides from 215 treatment-naïve PDACs, we performed concurrent quantification of principal fibroblast subpopulations and collagen and defined three stroma types: collagen-rich stroma, fibroblast activation protein α (FAP)-dominant fibroblast-rich stroma, and α smooth muscle actin (ACTA2)-dominant fibroblast-rich stroma. These stroma types were assessed for the associations with cancer-specific survival by multivariable Cox regression analyses and with clinicopathologic factors, including CD8⁺ cell density.

RESULTS

FAP-dominant fibroblasts and ACTA2-dominant fibroblasts represented the principal distinct fibroblast subpopulations in tumor stroma. Stroma types were associated with patient survival, SMAD4 status, and transcriptome signatures. Compared with FAP-dominant fibroblast-rich stroma, collagen-rich stroma correlated with prolonged survival [HR, 0.57; 95% confidence interval (CI), 0.33-0.99], while ACTA2-dominant fibroblast-rich stroma exhibited poorer prognosis (HR, 1.65; 95% CI, 1.06-2.58). FAP-dominant fibroblast-rich stroma was additionally characterized by restricted CD8⁺ cell infiltrates and intense neutrophil infiltration.

CONCLUSIONS

This study identified three distinct stroma types differentially associated with survival, immunity, and molecular features, thereby underscoring the importance of stromal heterogeneity in subtyping pancreatic cancers and supporting the development of antistromal therapies.

Analysis of Immune Checkpoint Drug Targets and Tumor Proteotypes in Non-Small Cell Lung Cancer

New therapeutics targeting immune checkpoint proteins have significantly advanced treatment of non-small cell lung cancer (NSCLC), but protein level quantitation of drug targets presents a critical problem. We used multiplexed, targeted mass spectrometry (MS) to quantify immunotherapy target proteins PD-1, PD-L1, PD-L2, IDO1, LAG3, TIM3, ICOSLG, VISTA, GITR, and CD40 in formalin-fixed, paraffin-embedded (FFPE) NSCLC specimens. Immunohistochemistry (IHC) and MS measurements for PD-L1 were weakly correlated, but IHC did not distinguish protein abundance differences detected by MS. PD-L2 abundance exceeded PD-L1 in over half the specimens and the drug target proteins all displayed different abundance patterns. mRNA correlated with protein abundance only for PD-1, PD-L1, and IDO1 and tumor mutation burden did not predict abundance of any protein targets. Global proteome analyses identified distinct proteotypes associated with high PD-L1-expressing and high IDO1-expressing NSCLC. MS quantification of multiple drug targets and tissue proteotypes can improve clinical evaluation of immunotherapies for NSCLC.

Cross-Platform Comparison of Computer-assisted Image Analysis Quantification of In Situ mRNA Hybridization in Investigative Pathology

Although availability of automated platforms has proliferated, there is no standard practice for computer-assisted generation of scores for mRNA in situ hybridization (ISH) visualized by brightfield microscopic imaging on tissue sections. To address this systematically, an ISH for peptidylprolyl isomerase B (PPIB) (cyclophilin B) mRNA was optimized and applied to a tissue microarray of archival non-small cell lung carcinoma cases, and then automated image analysis for PPIB was refined across 4 commercially available software platforms. Operator experience and scoring results from ImageScope, HALO, CellMap, and Developer XD were systematically compared with each other and to manual pathologist scoring. Markup images were compared and contrasted for accuracy, the ability of the platform to identify cells, and the ease of visual assessment to determine appropriate interpretation. Comparing weighted scoring approaches using H-scores (Developer XD, ImageScope, and manual scoring) a correlation was observed (R value=0.7955), and association between the remaining 2 approaches (HALO and CellMap) was of similar value. ImageScope showed the highest R value in comparison with manual scoring (0.7377). Mean-difference plots showed that HALO produced the highest relative normalized values, suggesting higher relative sensitivity. ImageScope overestimated PPIB ISH signal at the high end of the range scores; however, this tendency was not observed in other platforms. HALO emerged with the highest number of favorable observations, no apparent systematic bias in score generation compared with the other methods, and potentially higher sensitivity to detect ISH. HALO may serve as a tool to empower teams of investigative pathology laboratory scientists to assist pathologists readily with quantitative scoring of ISH.

Spatially multiplexed RNA in situ hybridization to reveal tumor heterogeneity

Multiplexed RNA in situ hybridization for the analysis of gene expression patterns plays an important role in investigating development and disease. Here, we present a method for multiplexed RNA-ISH to detect spatial tumor heterogeneity in tissue sections. We made use of a microfluidic chip to deliver ISH-probes locally to regions of a few hundred micrometers over time periods of tens of minutes. This spatial multiplexing method can be combined with ISH-approaches based on signal amplification, with bright field detection and with the commonly used format of formalin-fixed paraffin-embedded tissue sections. By using this method, we analyzed the expression of HER2 with internal positive and negative controls (ActB, dapB) as well as predictive biomarker panels (ER, PgR, HER2) in a spatially multiplexed manner on single mammary carcinoma sections. We further demonstrated the applicability of the technique for subtype differentiation in breast cancer. Local analysis of HER2 revealed medium to high spatial heterogeneity of gene expression (Cohen effect size r = 0.4) in equivocally tested tumor tissues. Thereby, we exemplify the importance of using such a complementary approach for the analysis of spatial heterogeneity, in particular for equivocally tested tumor samples. As the method is compatible with a range of ISH approaches and tissue samples, it has the potential to find broad applicability in the context of molecular analysis of human diseases.

Procedural Requirements and Recommendations for Multiplex Immunofluorescence Tyramide Signal Amplification Assays to Support Translational Oncology Studies

In the development of a multiplex immunofluorescence (IF) platform and the optimization and validation of new multiplex IF panels using a tyramide signal amplification system, several technical requirements are important for high-quality staining, analysis, and results. The aim of this review is to discuss the basic requirements for performing multiplex IF tyramide signal amplification (TSA) in formalin-fixed, paraffin-embedded cancer tissues to support translational oncology research. Our laboratory has stained approximately 4000 formalin-fixed, paraffin-embedded tumor samples using the multiplex IF TSA system for immune profiling of several labeled biomarkers in a single slide to elucidate cancer biology at a protein level and identify therapeutic targets and biomarkers. By analyzing several proteins in thousands of cells on a single slide, this technique provides a systems-level view of various processes in various tumor tissues. Although this technology shows high flexibility in cancer studies, it presents several challenges when applied to study different histology cancers. Our experience shows that adequate antibody validation, staining optimization, analysis strategies, and data generation are important steps for generating quality results. Tissue management, fixation procedures, storage, and cutting can also affect the results of the assay and must be standardized. Overall, this method is reliable for supporting translational research given a precise, step-by-step approach.

Objective quantification of BCL2 protein by multiplex immunofluorescence in routine biopsy samples of diffuse large B-cell lymphoma demonstrates associations with survival and BCL2 gene alterations

Up-regulation of BCL2 in cases of diffuse large B-cell lymphoma (DLBCL) can confer treatment resistance. Quantitative immunofluorescence (QIF) histology allows objective quantification of protein-based biomarkers. We investigated the utility of QIF for evaluating BCL2 as a biomarker in DLBCL by quantifying BCL2 selectively in CD20-expressing lymphoma cells in biopsy samples from 116 cases of DLBCL in two cohorts one of which consisted of relapsed/refractory cases from a clinical trial. BCL2 protein by QIF correlated with BCL2 mRNA abundance and was associated with both translocation and copy number gain of the BCL2 gene. Elevated BCL2 protein expression by QIF, but not immunohistochemistry or mRNA quantification, was associated with inferior overall and relapse-free survival in the relapsed/refractory cohort. QIF is an effective means of quantifying BCL2 protein objectively in routine cancer biopsy specimens and shows promise for identifying relapsed/refractory DLBCL patients at risk of inferior outcomes after salvage therapy.

Rapid micro-immunohistochemistry

We present a new and versatile implementation of rapid and localized immunohistochemical staining of tissue sections. Immunohistochemistry (IHC) comprises a sequence of specific biochemical reactions and allows the detection of specific proteins in tissue sections. For the rapid implementation of IHC, we fabricated horizontally oriented microfluidic probes (MFPs) with functionally designed apertures to enable square and circular footprints, which we employ to locally expose a tissue to time-optimized sequences of different biochemicals. We show that the two main incubation steps of IHC protocols can be performed on MDAMB468-1510A cell block sections in less than 30 min, compared to incubation times of an hour or more in standard protocols. IHC analysis on the timescale of tens of minutes could potentially be applied during surgery, enabling clinicians to react in more dynamically and efficiently. Furthermore, this rapid IHC implementation along with conservative tissue usage has strong potential for the implementation of multiplexed assays, allowing the exploration of optimal assay conditions with a small amount of tissue to ensure high-quality staining results for the remainder of the sample.

Qualifying antibodies for image-based immune profiling and multiplexed tissue imaging

Multiplexed tissue imaging enables precise, spatially resolved enumeration and characterization of cell types and states in human resection specimens. A growing number of methods applicable to formalin-fixed, paraffin-embedded (FFPE) tissue sections have been described, the majority of which rely on antibodies for antigen detection and mapping. This protocol provides step-by-step procedures for confirming the selectivity and specificity of antibodies used in fluorescence-based tissue imaging and for the construction and validation of antibody panels. Although the protocol is implemented using tissue-based cyclic immunofluorescence (t-CyCIF) as an imaging platform, these antibody-testing methods are broadly applicable. We demonstrate assembly of a 16-antibody panel for enumerating and localizing T cells and B cells, macrophages, and cells expressing immune checkpoint regulators. The protocol is accessible to individuals with experience in microscopy and immunofluorescence; some experience in computation is required for data analysis. A typical 30-antibody dataset for 20 FFPE slides can be generated within 2 weeks.

One-bead one-compound combinatorial library derived targeting ligands for detection and treatment of oral squamous cancer

Oral squamous cancers (OSC) are hallmarked by poor prognosis, delayed clinical detection, and a lack of defined, characteristic biomarkers. By screening combinatorial one-bead one-compound (OBOC) peptide libraries against oral squamous cancer cell lines, two cyclic peptide ligands, LLY12 and LLY13 were previously identified. These ligands are capable of specific binding to the oral cancer cell lines (MOK-101, HSC-3, SCC-4 and SCC-10a) but not non-cancerous keratinocytes, leukocytes, fibroblast, and endothelial cells. These two peptides were synthesized and evaluated for their binding property, cytotoxicity and cell permeability. In vitro studies indicate that both LLY12 and LLY13 were able to bind to oral cancer cells with high specificity but did not show any cytotoxicity against human keratinocytes. Biotinylated LLY13, in complex with streptavidin-alexa488 was taken up by live oral cancer cells, thus rendering it as an excellent candidate vehicle for efficient delivery of drug loaded-nanoparticles. In vivo and ex vivo near infra-red fluorescence imaging studies confirmed the in vivo targeting efficiency and specificity of LLY13 in oral cancer orthotopic murine xenograft model. In vivo studies also showed that LLY13 was able to accumulate in the OSC tumors and demarcate the tumor margins in orthotopic xenograft model. Together, our data supports LLY13 as a promising theranostic agent against OSC.

Characterization of the immune microenvironment of NSCLC by multispectral analysis of multiplex immunofluorescence images

Multiplex immunofluorescence (MIF) staining of tumor sections combined with computational pathology quantifies phenotypic variants of tumor and immune cells and assesses their spatial relationships. Here, we discuss a MIF panel composed of cytokeratin, PD-L1, PD1, CD8, CD68, and Ki67 applied to non-small cell lung cancer (NSCLC) to demonstrate key components of the immune response to this cancer. We also describe a method of whole-slide multiplex imaging and digital multispectral image analysis. Key aspects of marker labeling and digital tissue and cellular classification are highlighted. We then illustrate how digital analysis can measure the spatial relationships among important cell types. This approach is presented in the context of a multidisciplinary team of scientists who together can optimize the combined methods to increase the impact of the study findings. Recommendations are provided to assist others to apply similar methods to further understand the immune response to NSCLC.

Multiplex quantitative analysis of cancer-associated fibroblasts and immunotherapy outcome in metastatic melanoma

Background

The cancer-associated fibroblast (CAF) population is implicated in immune dysregulation. Here, we test the hypothesis that CAF profiles in pretreatment tumor specimens are associated with response to immune checkpoint blockade of programmed cell death 1 (PD-1).

Methods

Pretreatment whole tissue sections from 117 melanoma patients treated with anti-PD-1 therapy were assessed by multiplex immunofluorescence to detect CAFs defined by Thy1, smooth muscle actin (SMA), and fibroblast activation protein (FAP). Two independent image analysis technologies were used: inForm software (PerkinElmer) to quantify cell counts, and AQUA™ to measure protein by quantitative immunofluorescence (QIF). CAF parameters by both methodologies were assessed for association with previously measured immune markers (CD3, CD4, CD8, CD20, CD68, PD-L1), best overall response, progression-free survival (PFS), and overall survival (OS).

Results

CAF parameters, by cell counts or QIF, did not correlate with immune markers nor with best overall response. However, both Thy1 and FAP cell counts had significant positive associations with PFS (all P < 0.05) and OS (all P < 0.003). SMA cell counts showed negative associations with outcome in anti-PD-1 treated patients. Similar associations were not observed in a control cohort of historical melanoma patients predating immunotherapy. Instead, FAP was a negative prognostic biomarker (P = 0.01) in the absence of immunotherapy. Multivariable analyses revealed significant PFS and OS associations with the CAF parameters were independent of baseline variables.

Conclusions

Pretreatment CAF profiles are associated with melanoma immunotherapy outcome. Multiplex CAF analysis has potential as an objective companion diagnostic in immuno-oncology.

Electronic supplementary material

The online version of this article (10.1186/s40425-019-0675-0) contains supplementary material, which is available to authorized users.

Automated Identification and Quantification of Signals in Multichannel Immunofluorescence Images: The SignalFinder-IF Platform

Multimarker fluorescence analysis of tissue specimens offers the opportunity to probe the expression levels and locations of multiple markers in a single sample. Software is needed to fully capitalize on the advantages of this technology for sensitive, quantitative, and multiplexed data collection. A major challenge has been the automated identification and quantification of signals. We report on the software SignalFinder-IF, which meets that need. SignalFinder-IF uses a newly developed algorithm called Segment-Fit Thresholding, which showed robust performance for automated signal identification in side-by-side comparisons with several current methods. Two utilities provided with SignalFinder-IF enable downstream analyses. The first allows the quantification and mapping of relationships between an unlimited number of markers through user-defined sequences of AND, OR, and NOT operators. The second produces composite pictures of the signals or colocalization analysis on brightfield hematoxylin and eosin images, which is useful for understanding the morphologies and locations of cells meeting specific marker criteria. SignalFinder-IF enables high-throughput, rigorous analyses of whole-slide, multimarker data, and it promises to open new possibilities in many research and clinical applications.

High-Plex Predictive Marker Discovery for Melanoma Immunotherapy-Treated Patients Using Digital Spatial Profiling

PURPOSE

Protein expression in formalin-fixed, paraffin-embedded tissue is routinely measured by IHC or quantitative fluorescence (QIF) on a handful of markers on a single section. Digital spatial profiling (DSP) allows spatially informed simultaneous assessment of multiple biomarkers. Here we demonstrate the DSP technology using a 44-plex antibody cocktail to find protein expression that could potentially be used to predict response to immune therapy in melanoma.Experimental Design: The NanoString GeoMx DSP technology is compared with automated QIF (AQUA) for immune marker compartment-specific measurement and prognostic value in non-small cell lung cancer (NSCLC). Then we use this tool to search for novel predictive markers in a cohort of 60 patients with immunotherapy-treated melanoma on a tissue microarray using a 44-plex immune marker panel measured in three compartments (macrophage, leukocyte, and melanocyte) generating 132 quantitative variables.

RESULTS

The spatially informed variable assessment by DSP validates by both regression and variable prognostication compared with QIF for stromal CD3, CD4, CD8, CD20, and PD-L1 in NSCLC. From the 132 variables, 11 and 15 immune markers were associated with prolonged progression-free survival (PFS) and overall survival (OS). Notably, we find PD-L1 expression in CD68-positive cells (macrophages) and not in tumor cells was a predictive marker for PFS, OS, and response.

CONCLUSIONS

DSP technology shows high concordance with QIF and validates based on both regression and outcome assessment. Using the high-plex capacity, we found a series of expression patterns associated with outcome, including that the expression of PD-L1 in macrophages is associated with response.

The Status and Impact of Clinical Tumor Genome Sequencing

Since the discovery that DNA alterations initiate tumorigenesis, scientists and clinicians have been exploring ways to counter these changes with targeted therapeutics. The sequencing of tumor DNA was initially limited to highly actionable hot spots-areas of the genome that are frequently altered and have an approved matched therapy in a specific tumor type. Large-scale genome sequencing programs quickly developed technological improvements that enabled the deployment of whole-exome and whole-genome sequencing technologies at scale for pristine sample materials in research environments. However, the turning point for precision medicine in oncology was the innovations in clinical laboratories that improved turnaround time, depth of coverage, and the ability to reliably sequence archived, clinically available samples. Today, tumor genome sequencing no longer suffers from significant technical or financial hurdles, and the next opportunity for improvement lies in the optimal utilization of the technologies and data for many different tumor types.

Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes and Immunotherapy Outcome in Metastatic Melanoma

PURPOSE

Because durable response to programmed cell death 1 (PD-1) inhibition is limited to a subset of melanoma patients, new predictive biomarkers could have clinical utility. We hypothesize that pretreatment tumor-infiltrating lymphocyte (TIL) profiles could be associated with response.

EXPERIMENTAL DESIGN

Pretreatment whole tissue sections from 94 melanoma patients treated with anti-PD-1 therapy were profiled by multiplex immunofluorescence to perform TIL quantification (CD4, CD8, CD20) and assess TIL activation (CD3, GZMB, Ki67). Two independent image analysis technologies were used: inForm (PerkinElmer) to determine cell counts, and AQUA to measure protein by quantitative immunofluorescence (QIF). TIL parameters by both methodologies were correlated with objective response or disease control rate (ORR/DCR) by RECIST 1.1 and survival outcome.

RESULTS

Pretreatment lymphocytic infiltration, by cell counts or QIF, was significantly higher in complete or partial response than in stable or progressive disease, particularly for CD8 (P < 0.0001). Neither TIL activation nor dormancy was associated with outcome. CD8 associations with progression-free survival (HR > 3) were independently significant in multivariable analyses and accounted for similar CD3 associations in anti-PD-1-treated patients. CD8 was not associated with melanoma prognosis in the absence of immunotherapy. Predictive performance of CD8 cell count (and QIF) had an area under the ROC curve above 0.75 (ORR/DCR), which reached 0.83 for ipilimumab plus nivolumab.

CONCLUSIONS

Pretreatment lymphocytic infiltration is associated with anti-PD-1 response in metastatic melanoma. Quantitative TIL analysis has potential for application in digital precision immuno-oncology as an "indicative" companion diagnostic.

Clinical potential of mass spectrometry-based proteogenomics

Cancer genomics research aims to advance personalized oncology by finding and targeting specific genetic alterations associated with cancers. In genome-driven oncology, treatments are selected for individual patients on the basis of the findings of tumour genome sequencing. This personalized approach has prolonged the survival of subsets of patients with cancer. However, many patients do not respond to the predicted therapies based on the genomic profiles of their tumours. Furthermore, studies pairing genomic and proteomic analyses of samples from the same tumours have shown that the proteome contains novel information that cannot be discerned through genomic analysis alone. This observation has led to the concept of proteogenomics, in which both types of data are leveraged for a more complete view of tumour biology that might enable patients to be more successfully matched to effective treatments than they would using genomics alone. In this Perspective, we discuss the added value of proteogenomics over the current genome-driven approach to the clinical characterization of cancers and summarize current efforts to incorporate targeted proteomic measurements based on selected/multiple reaction monitoring (SRM/MRM) mass spectrometry into the clinical laboratory to facilitate clinical proteogenomics.

Ultra-fast and automated immunohistofluorescent multistaining using a microfluidic tissue processor

Multistaining of a tissue section targeting multiple markers allows to reveal complex interplays in a tumor environment. However, the resource-intensive and impractically long nature of iterative multiplexed immunostainings prohibits its practical implementation in daily routine, even when using work-flow automation systems. Here, we report a fully automated and ultra-fast multistaining using a microfluidic tissue processor (MTP) in as short as 20 minutes per marker, by immunofluorescent staining employing commercially available tyramide signal amplification polymer precipitation by horse-radish peroxidase (HRP) activation. The reported duration includes (i) 15 minutes for the entire fluidic exchange and reagent incubation necessary for the immunostaining and (ii) 5 minutes for the heat-induced removal of the applied antibodies. Using the automated MTP, we demonstrated a 4-plex automated multistaining with clinically relevant biomarkers within 84 minutes, showing perfect agreement with the state-of-the-art microwave treatment antibody removal. The presented HRP-based method is in principle extendable to multistaining by both tyramides accommodating higher number of fluorescent channels and multi-color chromogenic staining. We anticipate that our automated multi-staining with a turn-around time shorter than existing monoplex immunohistochemistry methods has the potential to enable multistaining in routine without disturbing the current laboratory workflow, opening perspectives for implementation of -omics approaches in tissue diagnostics.

Expression and clinical significance of PD-L1, B7-H3, B7-H4 and TILs in human small cell lung Cancer (SCLC)

Background

Small cell lung cancer (SCLC) accounts for 10–15% of all lung malignancies and its prognosis is dismal. Although early studies have shown promising clinical activity of immune checkpoint blockers, the immune composition and expression of potentially actionable immunostimulatory targets in this malignancy are poorly understood.

Methods

Using multiplexed quantitative immunofluorescence (QIF), we measured the levels of 3 different B7 family ligands PD-L1, B7-H3, B7-H4 and major tumor infiltrating lymphocyte (TIL) subsets in 90 SCLC samples represented in tissue microarray format. Associations between the marker levels, clinicopathological variables and survival were studied.

Results

PD-L1 protein was detected in 7.3%, B7-H3 in 64.9% and B7-H4 in 2.6% of SCLC cases. The markers showed limited co-expression and were not associated with the level of TILs, age, gender and stage. Elevated B7-H4 was associated with shorter 5-year overall survival. The levels of CD3+, CD8+ and CD20+ TILs and the ratio of total/effector T-cells were significantly lower in SCLC than in non-small cell lung cancer. High levels of CD3+, but not CD8+ or CD20+ TILs were significantly associated with longer survival.

Conclusions

Taken together, our study indicate variable expression and clinical role of B7-family ligands in SCLC with predominant expression of the candidate target B7-H3 and the presence of a limited cytotoxic anti-tumor immune response. These results support the evaluation of B7-H3 blockers and/or pro-inflammatory therapies in SCLC.

Ten years of sorafenib in hepatocellular carcinoma: Are there any predictive and/or prognostic markers?

Sorafenib has been considered the standard of care for patients with advanced unresectable hepatocellular carcinoma (HCC) since 2007 and numerous studies have investigated the role of markers involved in the angiogenesis process at both the expression and genetic level and clinical aspect. What results have ten years of research produced? Several clinical and biological markers are associated with prognosis. The most interesting clinical parameters are adverse events, Barcelona Clinic Liver Cancer stage, and macroscopic vascular invasion, while several single nucleotide polymorphisms and plasma angiopoietin-2 levels represent the most promising biological biomarkers. A recent pooled analysis of two phase III randomized trials showed that the neutrophil-to-lymphocyte ratio, etiology and extra-hepatic spread are predictive factors of response to sorafenib, but did not identify any predictive biological markers. After 10 years of research into sorafenib there are still no validated prognostic or predictive factors of response to the drug in HCC. The aim of the present review was to summarize 10 years of research into sorafenib, looking in particular at the potential of associated clinical and biological markers to predict its efficacy in patients with advanced HCC.

Breast cancer intratumour heterogeneity: current status and clinical implications

Breast cancer (BC) is a heterogeneous disease that varies in presentation, morphological features, behaviour, and response to therapy. High-throughput molecular profiling studies have revolutionised our understanding of BC heterogeneity, and have demonstrated that molecular profiles of tumours are variable not only between tumours, but also within individual tumours. Current evidence indicates that spatial and temporal intratumour heterogeneity of BC exists at levels beyond what are commonly expected. Intratumour heterogeneity poses critical challenges in the diagnosis, prediction of behaviour and management of BC. For instance, heterogeneous expression of oestrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 can be seen not only in primary tumours between different regions, but also between primary tumours and their corresponding metastatic/recurrent lesions. The demonstration of molecularly distinct subclones within individual tumours may explain, at least in part, the mechanisms controlling the variable behaviour of BC, and may change our approach to BC sampling and treatment. In this review, BC intratumour heterogeneity is highlighted, with a special emphasis on the current knowledge pertaining to the relationship between intratumour heterogeneity and BC pathogenesis, evolution, and progression, with consideration of its impact on disease diagnosis, management, and the emergence of novel therapeutic targets. The key role of high-throughput molecular and imaging techniques is also addressed.

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.

Spatially Resolved and Quantitative Analysis of VISTA/PD-1H as a Novel Immunotherapy Target in Human Non-Small Cell Lung Cancer

Purpose: Determine the localized expression pattern and clinical significance of VISTA/PD-1H in human non-small cell lung cancer (NSCLC).Experimental Design: Using multiplex quantitative immunofluorescence (QIF), we performed localized measurements of VISTA, PD-1, and PD-L1 protein in 758 stage I-IV NSCLCs from 3 independent cohorts represented in tissue microarray format. The targets were selectively measured in cytokeratin+ tumor epithelial cells, CD3+ T cells, CD4+ T-helper cells, CD8+ cytotoxic T cells, CD20+ B lymphocytes and CD68+ tumor-associated macrophages. We determined the association between the targets, clinicopathological/molecular variables and survival. Genomic analyses of lung cancer cases from TCGA were also performed.Results: VISTA protein was detected in 99% of NSCLCs with a predominant membranous/cytoplasmic staining pattern. Expression in tumor and stromal cells was seen in 21% and 98% of cases, respectively. The levels of VISTA were positively associated with PD-L1, PD-1, CD8+ T cells and CD68+ macrophages. VISTA expression was higher in T-lymphocytes than in macrophages; and in cytotoxic T cells than in T-helper cells. Elevated VISTA was associated with absence of EGFR mutations and lower mutational burden in lung adenocarcinomas. Presence of VISTA in tumor compartment predicted longer 5-year survival.Conclusions: VISTA is frequently expressed in human NSCLC and shows association with increased tumor-infiltrating lymphocytes, PD-1 axis markers, specific genomic alterations and outcome. These results support the immunomodulatory role of VISTA in human NSCLC and suggests its potential as therapeutic target. Clin Cancer Res; 24(7); 1562-73. ©2017 AACR.

PD-L1 expression and presence of TILs in small intestinal neuroendocrine tumours

BACKGROUND

The extent of resistance to immune surveillance in patients with well-differentiated (Wd) (grade 1/2) small-intestinal neuroendocrine tumours (Si-NETs) is unknown.

METHODS

Patients diagnosed with Wd Si-NETs (excluding appendix, which are considered to have a different biology to other midgut NETs) were eligible. Tumoural programmed death (PD)-ligand(L) 1 (PD-L1)/PD-L2/PD-1 and tumour infiltrating lymphocytes (TILs) [presence and phenotype] were analysed in archival tissue by immunohistochemistry (IHC); reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used for confirmation of IHC results.

RESULTS

Of 109 patients screened, 62 were eligible: 54.8% were male; median age was 63.7 years (95%-CI 59.7-67.2); disease stage II: 4.8%, III: 40.3% and IV: 54.8%; 41.9% were functional. Analysed samples (67.1% from primary tumours, 32.9% from metastases) were of grade 1 (67.1%) or 2 (32.86%) with a median Ki-67 of 2%. From the total of 62 eligible patients, 70 and 63 samples were suitable for IHC and RT-qPCR analysis, respectively. PD-L1 expression within tumour cells and TILs were identified in 12.8% and 24.3% of samples respectively; 30% of samples showed PD-L1 expression within tumour cells and/or TILs. PD-1 was present in TILs in 22.8% of samples. Majority of samples showed significant presence of CD4+ (focal 42.86%; moderate 2.86%) and CD8+ (focal 92.86%; moderate 4.29%) TILs. IHC findings were confirmed with RT-qPCR; which showed higher expression levels of PD-L1 (p-value 0.007) and PD-1 (p-value 0.001) in samples positive for IHC compared to negative-IHC.

CONCLUSIONS

Thirty-percent of patients express PD-L1 within tumour cells and/or TILs. Identification of presence of TILs was also significant and warrant the investigation of immunotherapy in this setting.

A hybridization-chain-reaction-based method for amplifying immunosignals

Immunosignal hybridization chain reaction (isHCR) combines antibody-antigen interactions with hybridization chain reaction (HCR) technology, which results in amplification of immunofluorescence signals by up to two to three orders of magnitude with low background. isHCR's highly modular and easily adaptable design enables the technique to be applied broadly, and we further optimized its use in multiplexed imaging and in state-of-the-art tissue expansion and clearing techniques.

Isolation of anti-extra-cellular vesicle single-domain antibodies by direct panning on vesicle-enriched fractions

Background

The thorough understanding of the physiological and pathological processes mediated by extracellular vesicles (EVs) is challenged by purification methods which are cumbersome, not reproducible, or insufficient to yield homogeneous material. Chromatography based on both ion-exchange and immune-capture can represent an effective method to improve EV purification and successive analysis.

Methods

Cell culture supernatant was used as a model sample for assessing the capacity of anion-exchange chromatography to separate distinct EV fractions and to isolate nanobodies by direct panning on whole EVs to recover binders specific for the native conformation of EV-surface epitopes and suitable to develop EV immune-capture reagents.

Results

Anion-exchange chromatography of cell culture supernatant separated distinct protein-containing fractions and all of them were positive for CD9, a biomarker associated to some EVs. This suggested the existence of several EV fractions but did not help in separating EVs from other contaminants. We further isolated several nanobodies instrumental for implementing immune-affinity protocols. These were able to immobilize EVs from both cell culture supernatant and biological samples, to be used in ELISA, flow-cytometry, and immune-purification.

Conclusions

Here we report the first successful isolation of anti-EV nanobodies for the use in immunoaffinity-based EV capture by panning a phage library directly on partially purified EVs. This achievement paves the way for the application of direct EV panning for the discovery of novel antibody-vesicle surface biomarker pairs and represents the preliminary requirement for the development of selective immune-capture that, in combination with anion-exchange chromatography, can simplify the systematic stratification of EV sub-populations and their individual characterization.

Electronic supplementary material

The online version of this article (10.1186/s12934-017-0856-9) contains supplementary material, which is available to authorized users.

Sorafenib response in hepatocellular carcinoma: MicroRNAs as tuning forks

Hepatocellular carcinoma (HCC) is the primary liver malignancy that contributes towards the second most common cause of cancer-related mortality. The targeted chemotherapeutic agent, sorafenib, is known to show a statistically significant but limited overall survival advantage in advanced HCC. However, the individual patient response towards sorafenib varies drastically, with most experiencing stable disease and few with partial response; complete response is very rare. Progressive disease despite the treatment is also evident in many patients, indicating drug resistance. These varied responses have been linked with the modulation of several intracellular signaling pathways. Notably, the regulation of these pathways through diverse operating biomolecules, including microRNAs (miRNAs), is the focus of recent studies. MicroRNAs are tiny, non-coding RNA molecules that regulate the expression of several target genes. In addition, miRNAs are known to play a role in the progression of HCC carcinogenesis. Interestingly, miRNAs have also been identified to play differential roles in terms of sorafenib response in HCC such as biomarkers and functional modulation of cellular response to sorafenib, hence, they are also being therapeutically evaluated. This review outlines the role of reported miRNAs in different aspects of sorafenib response in HCC.

High concordance of a closed-system, RT-qPCR breast cancer assay for HER2 mRNA, compared to clinically determined immunohistochemistry, fluorescence in situ hybridization, and quantitative immunofluorescence

Historically, mRNA measurements have been tested on several commercially available platforms, but none have gained broad acceptance for assessment of HER2. An mRNA measurement, as a continuous value, has the potential for use in adjudication of the equivocal category. Here we use a real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay in a closed, single-use cartridge, automated system. Multiple cores (1 mm in diameter) were retrospectively collected from 80 formalin-fixed paraffin-embedded (FFPE) tissue blocks with invasive breast cancer seen by Yale Pathology Labs between 1998 and 2011. Tissue cores were processed with a FFPE lysis kit to create lysates that were tested with the automated RT-qPCR assay. Results for IHC and FISH were extracted from the pathology reports and quantitative immunofluorescence (QIF) for each case was measured as previously described. Quality control testing showed that the GX platform RT-qPCR shows no case to case cross contamination on material from routine histology practices. Concordance between RT-qPCR and IHC/FISH was 91.25% (sensitivity=0.87; specificity=0.94; PPV=0.89; NPV=0.92) using a pre-defined delta Ct cut-off (dCt≥-1) for HER2. Concordance (OPA) between RT-qPCR and QIF was 94% (sensitivity=0.90; specificity=0.96; PPV=0.93; NPV=0.94) using dCt≥-1 and a previously defined cut-point for positivity by QIF. In conclusion, the closed system RT-qPCR assay shows >90% concordance with the ASCO/CAP HER2 IHC/FISH scoring. Additionally, the RT-qPCR assay is highly concordant (94%) with the continuous variable HER2 QIF assay, and may better reflect the true continuum of HER2 receptor status in invasive breast cancer. These initial results suggest that fast, closed system molecular assays may have future value for the adjudication of the ASCO/CAP HER2 equivocal category or possibly routine usage in time constrained or low resource settings.

Assessing Tumor-infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method From the International Immunooncology Biomarkers Working Group: Part 1: Assessing the Host Immune Response, TILs in Invasive Breast Carcinoma and Ductal Carcinoma In Situ, Metastatic Tumor Deposits and Areas for Further Research

Assessment of tumor-infiltrating lymphocytes (TILs) in histopathologic specimens can provide important prognostic information in diverse solid tumor types, and may also be of value in predicting response to treatments. However, implementation as a routine clinical biomarker has not yet been achieved. As successful use of immune checkpoint inhibitors and other forms of immunotherapy become a clinical reality, the need for widely applicable, accessible, and reliable immunooncology biomarkers is clear. In part 1 of this review we briefly discuss the host immune response to tumors and different approaches to TIL assessment. We propose a standardized methodology to assess TILs in solid tumors on hematoxylin and eosin sections, in both primary and metastatic settings, based on the International Immuno-Oncology Biomarker Working Group guidelines for TIL assessment in invasive breast carcinoma. A review of the literature regarding the value of TIL assessment in different solid tumor types follows in part 2. The method we propose is reproducible, affordable, easily applied, and has demonstrated prognostic and predictive significance in invasive breast carcinoma. This standardized methodology may be used as a reference against which other methods are compared, and should be evaluated for clinical validity and utility. Standardization of TIL assessment will help to improve consistency and reproducibility in this field, enrich both the quality and quantity of comparable evidence, and help to thoroughly evaluate the utility of TILs assessment in this era of immunotherapy.

Automated Classification of Benign and Malignant Proliferative Breast Lesions

Misclassification of breast lesions can result in either cancer progression or unnecessary chemotherapy. Automated classification tools are seen as promising second opinion providers in reducing such errors. We have developed predictive algorithms that automate the categorization of breast lesions as either benign usual ductal hyperplasia (UDH) or malignant ductal carcinoma in situ (DCIS). From diagnosed breast biopsy images from two hospitals, we obtained 392 biomarkers using Dong et al.'s (2014) computational tools for nuclei identification and feature extraction. We implemented six machine learning models and enhanced them by reducing prediction variance, extracting active features, and combining multiple algorithms. We used the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for performance evaluation. Our top-performing model, a Combined model with Active Feature Extraction (CAFE) consisting of two logistic regression algorithms, obtained an AUC of 0.918 when trained on data from one hospital and tested on samples of the other, a statistically significant improvement over Dong et al.'s AUC of 0.858. Pathologists can substantially improve their diagnoses by using it as an unbiased validator. In the future, our work can also serve as a valuable methodology for differentiating between low-grade and high-grade DCIS.

AKT1low quiescent cancer cells persist after neoadjuvant chemotherapy in triple negative breast cancer

BACKGROUND

Absence of pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) correlates with poor long-term survival in patients with triple negative breast cancer (TNBC). These incomplete treatment responses are likely determined by mechanisms that enable cancer cells to resist being killed. However, the detailed characterization of a drug-resistant cancer cell state in residual TNBC tissue after NACT has remained elusive. AKT1^low quiescent cancer cells (QCCs) are a quiescent, epigenetically plastic, and chemotherapy-resistant subpopulation initially identified in experimental cancer models. Here, we asked whether QCCs exist in primary tumors from patients with TNBC and persist after treatment with NACT.

METHODS

We obtained pre-treatment biopsy, post-treatment mastectomy, and metastatic specimens from a retrospective cohort of TNBC patients treated with NACT at Massachusetts General Hospital (n = 25). Using quantitative automated immunofluorescence microscopy, QCCs were identified as AKT^low/H3K9me2^low/HES1^high cancer cells using prespecified immunofluorescence intensity thresholds. QCCs were represented in 2D and 3D digital tumor maps and QCC percentage (QCC-P) and QCC cluster index (QCC-CI) were determined for each sample.

RESULTS

We showed that QCCs exist as non-random and heterogeneously distributed clusters within primary breast tumors. In addition, these QCC clusters persist after treatment with multi-agent, multi-cycle, neoadjuvant chemotherapy in both residual primary tumors and nodal and distant metastases in patients with triple negative breast cancer.

CONCLUSIONS

These first-in-human data potentially qualify AKT1^low quiescent cancer cells as a non-genetic cell state that persists after neoadjuvant chemotherapy in triple negative breast cancer patients and warrants further study.