Yunxia Sui

Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue

Limitations on the number of unique protein and DNA molecules that can be characterized microscopically in a single tissue specimen impede advances in understanding the biological basis of health and disease. Here we present a multiplexed fluorescence microscopy method (MxIF) for quantitative, single-cell, and subcellular characterization of multiple analytes in formalin-fixed paraffin-embedded tissue. Chemical inactivation of fluorescent dyes after each image acquisition round allows reuse of common dyes in iterative staining and imaging cycles. The mild inactivation chemistry is compatible with total and phosphoprotein detection, as well as DNA FISH. Accurate computational registration of sequential images is achieved by aligning nuclear counterstain-derived fiducial points. Individual cells, plasma membrane, cytoplasm, nucleus, tumor, and stromal regions are segmented to achieve cellular and subcellular quantification of multiplexed targets. In a comparison of pathologist scoring of diaminobenzidine staining of serial sections and automated MxIF scoring of a single section, human epidermal growth factor receptor 2, estrogen receptor, p53, and androgen receptor staining by diaminobenzidine and MxIF methods yielded similar results. Single-cell staining patterns of 61 protein antigens by MxIF in 747 colorectal cancer subjects reveals extensive tumor heterogeneity, and cluster analysis of divergent signaling through ERK1/2, S6 kinase 1, and 4E binding protein 1 provides insights into the spatial organization of mechanistic target of rapamycin and MAPK signal transduction. Our results suggest MxIF should be broadly applicable to problems in the fields of basic biological research, drug discovery and development, and clinical diagnostics.

Quantitative single cell analysis of cell population dynamics during submandibular salivary gland development and differentiation

Summary Epithelial organ morphogenesis involves reciprocal interactions between epithelial and mesenchymal cell types to balance progenitor cell retention and expansion with cell differentiation for evolution of tissue architecture. Underlying submandibular salivary gland branching morphogenesis is the regulated proliferation and differentiation of perhaps several progenitor cell populations, which have not been characterized throughout development, and yet are critical for understanding organ development, regeneration, and disease. Here we applied a serial multiplexed fluorescent immunohistochemistry technology to map the progressive refinement of the epithelial and mesenchymal cell populations throughout development from embryonic day 14 through postnatal day 20. Using computational single cell analysis methods, we simultaneously mapped the evolving temporal and spatial location of epithelial cells expressing subsets of differentiation and progenitor markers throughout salivary gland development. We mapped epithelial cell differentiation markers, including aquaporin 5, PSP, SABPA, and mucin 10 (acinar cells); cytokeratin 7 (ductal cells); and smooth muscle &agr;-actin (myoepithelial cells) and epithelial progenitor cell markers, cytokeratin 5 and c-kit. We used pairwise correlation and visual mapping of the cells in multiplexed images to quantify the number of single- and double-positive cells expressing these differentiation and progenitor markers at each developmental stage. We identified smooth muscle &agr;-actin as a putative early myoepithelial progenitor marker that is expressed in cytokeratin 5-negative cells. Additionally, our results reveal dynamic expansion and redistributions of c-kit- and K5-positive progenitor cell populations throughout development and in postnatal glands. The data suggest that there are temporally and spatially discreet progenitor populations that contribute to salivary gland development and homeostasis.

Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism

The phenotypic diversity of cancer results from genetic and nongenetic factors. Most studies of cancer heterogeneity have focused on DNA alterations, as technologies for proteomic measurements in clinical specimen are currently less advanced. Here, we used a multiplexed immunofluorescence staining platform to measure the expression of 27 proteins at the single-cell level in formalin-fixed and paraffin-embedded samples from treatment-naive stage II/III human breast cancer. Unsupervised clustering of protein expression data from 638,577 tumor cells in 26 breast cancers identified 8 clusters of protein coexpression. In about one-third of breast cancers, over 95% of all neoplastic cells expressed a single protein coexpression cluster. The remaining tumors harbored tumor cells representing multiple protein coexpression clusters, either in a regional distribution or intermingled throughout the tumor. Tumor uptake of the radiotracer 18F-fluorodeoxyglucose was associated with protein expression clusters characterized by hormone receptor loss, PTEN alteration, and HER2 gene amplification. Our study demonstrates an approach to generate cellular heterogeneity metrics in routinely collected solid tumor specimens and integrate them with in vivo cancer phenotypes.

Optimized multiplex immunofluorescence single-cell analysis reveals tuft cell heterogeneity

Intestinal tuft cells are a rare, poorly understood cell type recently shown to be a critical mediator of type 2 immune response to helminth infection. Here, we present advances in segmentation algorithms and analytical tools for multiplex immunofluorescence (MxIF), a platform that enables iterative staining of over 60 antibodies on a single tissue section. These refinements have enabled a comprehensive analysis of tuft cell number, distribution, and protein expression profiles as a function of anatomical location and physiological perturbations. Based solely on DCLK1 immunoreactivity, tuft cell numbers were similar throughout the mouse small intestine and colon. However, multiple subsets of tuft cells were uncovered when protein coexpression signatures were examined, including two new intestinal tuft cell markers, Hopx and EGFR phosphotyrosine 1068. Furthermore, we identified dynamic changes in tuft cell number, composition, and protein expression associated with fasting and refeeding and after introduction of microbiota to germ-free mice. These studies provide a foundational framework for future studies of intestinal tuft cell regulation and demonstrate the utility of our improved MxIF computational methods and workflow for understanding cellular heterogeneity in complex tissues in normal and disease states.

Stromal-Based Signatures for the Classification of Gastric Cancer

Treatment of metastatic gastric cancer typically involves chemotherapy and monoclonal antibodies targeting HER2 (ERBB2) and VEGFR2 (KDR). However, reliable methods to identify patients who would benefit most from a combination of treatment modalities targeting the tumor stroma, including new immunotherapy approaches, are still lacking. Therefore, we integrated a mouse model of stromal activation and gastric cancer genomic information to identify gene expression signatures that may inform treatment strategies. We generated a mouse model in which VEGF-A is expressed via adenovirus, enabling a stromal response marked by immune infiltration and angiogenesis at the injection site, and identified distinct stromal gene expression signatures. With these data, we designed multiplexed IHC assays that were applied to human primary gastric tumors and classified each tumor to a dominant stromal phenotype representative of the vascular and immune diversity found in gastric cancer. We also refined the stromal gene signatures and explored their relation to the dominant patient phenotypes identified by recent large-scale studies of gastric cancer genomics (The Cancer Genome Atlas and Asian Cancer Research Group), revealing four distinct stromal phenotypes. Collectively, these findings suggest that a genomics-based systems approach focused on the tumor stroma can be used to discover putative predictive biomarkers of treatment response, especially to antiangiogenesis agents and immunotherapy, thus offering an opportunity to improve patient stratification. Cancer Res; 76(9); 2573-86. ©2016 AACR.

Single-cell heterogeneity in ductal carcinoma in situ of breast.

Heterogeneous patterns of mutations and RNA expression have been well documented in invasive cancers. However, technological challenges have limited the ability to study heterogeneity of protein expression. This is particularly true for pre-invasive lesions such as ductal carcinoma in situ of the breast. Cell-level heterogeneity in ductal carcinoma in situ was analyzed in a single 5 μm tissue section using a multiplexed immunofluorescence analysis of 11 disease-related markers (EGFR, HER2, HER4, S6, pmTOR, CD44v6, SLC7A5 and CD10, CD4, CD8 and CD20, plus pan-cytokeratin, pan-cadherin, DAPI, and Na+K+ATPase for cell segmentation). Expression was quantified at cell level using a single-cell segmentation algorithm. K-means clustering was used to determine co-expression patterns of epithelial cell markers and immune markers. We document for the first time the presence of epithelial cell heterogeneity within ducts, between ducts and between patients with ductal carcinoma in situ. There was moderate heterogeneity in a distribution of eight clusters within each duct (average Shannon index 0.76; range 0–1.61). Furthermore, within each patient, the average Shannon index across all ducts ranged from 0.33 to 1.02 (s.d. 0.09–0.38). As the distribution of clusters within ducts was uneven, the analysis of eight ducts might be sufficient to represent all the clusters ie within- and between-duct heterogeneity. The pattern of epithelial cell clustering was associated with the presence and type of immune infiltrates, indicating a complex interaction between the epithelial tumor and immune system for each patient. This analysis also provides the first evidence that simultaneous analysis of both the epithelial and immune/stromal components might be necessary to understand the complex milieu in ductal carcinoma in situ lesions.

Abstract 2499: Application of a multiplexed fluorescence microscopy method (MultiOmyxTM) to dissect proteomic biomarkers of (18)F-fluorodeoxy-glucose ((18)FDG) uptake in breast cancer

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Background: While routinely collected human tumor specimen can now readily be examined for genetic alterations on a genome wide scale, multi-parameter measurements of protein expression remain challenging. We developed a multiplexed fluorescence microscopy method (MultiOmyxTM) for the quantitative characterization of multiple analytes in formalin-fixed paraffin-embedded tissue (PMID23818604). We now applied this platform to human breast cancer samples to determine the expression of 25 proteins at a single-cell level and examine their relationship to tumor uptake of the Positron Emission Tomography (PET) radiotracer (18)F-fluorodeoxy-glucose ((18)FDG). Methodology: We stained a single 5 µm section of breast carcinoma from each of 18 patients with antibodies against members of growth factor signaling pathways (HER2, IGF1R, PTEN, p-EGFR, p-PDK1, p-ERK1/2, p-S6 Ribosomal Protein, p-4EBP1, p-eIF4E), the glycolysis pathway (Glut-1, HK2, LDH-A), hormone receptors (ER, PR, AR), tumor cell proliferation markers (KI-67 and phospho-histone H3), and markers of hypoxia (HIF-1α, CA IX), and angiogenesis (CD31). 28-30 representative fields of view (FOVs) were randomly selected in each tumor, each comprising 300-500 cells. Images were automatically separated into subcellular and histopathological compartments based on the staining of tumor cells with a panel of segmentation markers (NaK-ATPase, pan-Cadherin, pan-cytokeratin, S6, and DAPI). A breast pathologist assessed and annotated the histologic composition of each FOV. Further analysis focused on FOVs (n=390) containing only invasive ductal carcinoma without admixed DCIS or normal breast tissue. Multivariate analysis between marker expression and FDG uptake was performed using logistic regression and Cox proportional hazard models. All patients had (18)-FDG PET within four weeks prior to collection of the tumor specimen. Results: Staining results with our MultiOmyxTM platform correlated closely with the results from CLIA-certified single marker biomarker assays (e.g., ER IHC and HER2 FISH assay) performed independently on the same set of samples (PMID: 21646475). Nuclear ER staining was associated with low FDG uptake (p=0.02). KI-67 was higher in tumors with high FDG uptake (p=0.04). K-median clustering identified molecular breast cancer subtypes. Conclusions: Our study illustrates the feasibility of quantitative proteomic measurements using a new in-situ multiplexed fluorescence microscopy platform on only a single routinely collected FFPE tissue section. Quantitative staining results from many thousand cells per tumor support the previously reported relationship between hormone receptor status, tumor cell proliferation, and FDG-uptake in breast cancer. Multiple protein markers showed a high degree of intra- and inter-tumoral heterogeneity. Citation Format: Anup Sood, Alexandra M. Miller, Fiona Ginty, Elizabeth McDonough, Yunxia Sui, Alexander Bordwell, Qing Li, Sireesha Kaanumalle, Zhengyu Pang, Franklin Torres, Edi Brogi, Steven Larson, Ingo Mellinghoff. Application of a multiplexed fluorescence microscopy method (MultiOmyxTM) to dissect proteomic biomarkers of (18)F-fluorodeoxy-glucose ((18)FDG) uptake in breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2499. doi:10.1158/1538-7445.AM2014-2499

Abstract P1-06-02: Impact of heterogeneity of DCIS on immune cell infiltrations

Background: Ductal carcinoma in situ (DCIS) accounts for at least 20% of breast cancers. Factors associated with recurrence of DCIS or progression to invasive carcinoma are not well delineated. The goals of the current study were to profile the epithelial and immune cells using the MultiOmyx hyperplexed immuno-fluorescent based analyses. This was coupled with semi-automated algorithms to characterize the inter-relationships between cell populations within individual DCIS lesions. Patients and Methods: Analysis for 15 antibody markers (EGFR, Her2, Her4, S6, pMTOR, PCAD, CD44v6, NaKATPase, SLC7A5, CD4, CD8, CD20, CD68, and CD10) was performed on a single FFPE section containing 10-20 distinct ducts from 13 cases of DCIS. Briefly, approximately 40 fields of view (FOV) from digitized sections containing DCIS or normal tissue were sequentially (cyclically) stained for the 15 markers. Each cycle entailed staining with 2-3 markers followed by imaging, dye inactivation, and re-staining. DAPI was used for nuclear demarcation and for registration of the images, while S6, pan-cadherin, Na+K+ATPase and pan-cytokeratin were used for epithelial segmentation. K-means clustering was used to determine patterns of co-expression of markers at the single cell, duct, and patient levels. These clusters were then correlated with immune marker expression by tumor infiltrating lymphocytes (TILs) by marker type (CD4, CD8, and CD20) and tumor compartment (stromal versus intraepithelial). Results: Analysis of the epithelial component in each of 13 cases of DCIS (n= 415 ducts) revealed 8 distinct expression patterns (clusters) using a panel of 7 markers (EGFR, Her2, Her4, pmTOR, CD44v6, SLC7A5, and CD10). The frequency and distribution of clusters, annotated at the single cell level, showed that 4 DCIS9s were dominated (>80%) by a single cell phenotype represented by cluster groups 3 and 7 (high Her2), cluster 6 (High Her4 and SLC7A5 and low Her2), or cluster 4 (non-descript). In 5 pts, the pattern was more heterogeneous consisting of mixture of cell populations with 50-70% of the cells belonging to cluster 1 (moderate to high levels for all markers except EGFR and CD10). The remaining pts had a strong representation of cluster 4 and 5 (CD44v6 and phospho-mTOR) cells. The distribution of both intra-epithelial and stromal TILs in DCIS cases were either consisted of a mixed B-cell (CD20+) and T-cell response (n=4), or one dominated by T-cells. Cluster 2 (High EGFR and CD10) was associated with a largely T-cell response (rs = 0.83, P value = 0.0004), while Cluster 7 (strong HER2) was associated with a B-cell response (rs = 0.68, P value = is 0.009). Conclusions: Analysis 15 markers and use of K-means clustering algorithm, shows prominent inter-tumoral (but not intra-tumoral) heterogeneity in DCIS. Furthermore, epithelial cell specific clusters (high HER2 or EGFR) were associated with distinct B or T cell infiltration by TILs. Additional ongoing studies will determine the clinical significance of the clusters with respect to recurrence of DCIS and development of invasive carcinomas. Citation Format: Badve S, Gokmen-Polar Y, Harris AL, Sui Y, Sevinsky C, Santamaria-Pang A, Ginty F, Tan PH, Gerdes MJ. Impact of heterogeneity of DCIS on immune cell infiltrations [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-06-02.

Abstract 1467: Multiplexed immunofluorescence quantitation and validation of multiple immune cell types in colon cancer epithelium and stroma

Immune response to tumor growth and development is highly complex and varies with stromal and tumor cell composition and secreted factors. Different immune cell types can have opposing functions (tumor suppressive or immune suppressive) and their density, location and activation state can have profound effects on tumor outcome. Routine immune-profiling methods based on sample homogenization or limited in situ detection capabilities may be insufficient to measure this diversity. To fully decipher tumor immune response and contribution of different cell types, there is urgent need to develop new imaging tools for in situ immune cell-typing and quantification. MultiOmyx® technology allows repeated staining, imaging and cell-level analysis of multiple biomarkers (at least 60) on the same FFPE tissue section. Together with epithelial and stromal cell analysis, the relative location and quantity of immune cells can be established, enabling regional assessment of immune infiltration and activation status. Using this workflow, 747 stage I-III colorectal cancer patient samples in TMA format were multiplexed for a total of 61 proteins, including CD3 (all T-cells), CD8 (cytotoxic T-cells), CD20 (B-cells), CD68 (macrophages) and pan-cytokeratin (epithelial tumor cells). All images were registered, auto-fluorescence subtracted and illumination corrected. Individual cells were segmented using automated image analysis workflow, consisting of nuclei segmentation, epithelium segmentation and stroma-epithelial cell nuclei classification. We applied a probabilistic multi-class, multi-label classification algorithms based on multi-parametric models to build statistical models of CD protein expression and classify immune cells. Using selected images, expert annotations of the following immune cells were made [CD20+ (n = 4282 (cells)), CD3+ (n = 5600), CD8+ (n = 5346), and CD68+ (n = 4261), and defects (n = 1739)]. Support Vector Machines (SVM) were used to derive a statistical model for cell classification. To objectively evaluate the cell classification accuracy, we performed 10-fold cross validation. The methods described performed well in classifying cell-types, yielding ≥97% accuracy, relative to expert user annotations, for all immune cell types. Classification accuracy was slightly higher for lymphocytes vs. macrophages, likely due to more diffuse localization of CD68. In line with previous reports, higher T-cell infiltration was significantly correlated with recurrence-free survival in the entire cohort. In summary, we have developed a highly accurate quantitation method for in situ analysis of immune cells in tumor and stroma. Using the same workflow, additional cell lineage and functional markers can be added for deeper phenotyping and identification of innate and adaptive immune cell lineages, generating new insights into role of immune response in tumor progression. Citation Format: Christopher Sevinsky, Alberto Santamaria-Pang, Anup Sood, Yunxia Sui, Qing Li, Nicole LaPlante, Raghav Padmanabhan, Fiona Ginty. Multiplexed immunofluorescence quantitation and validation of multiple immune cell types in colon cancer epithelium and stroma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1467.

Abstract P2-04-06: Demonstration of immune cell and pathway heterogeneity in Singapore DCIS samples using novel hyperplexing method (MultiOmyx®)

Breast cancer is the most common malignancy in Singapore women with rising incidence across all ethnic groups (Chinese, Malays and Indians). Ductal carcinoma in situ (DCIS) is the earliest non-invasive stage of disease and has been shown to account for approximately 26% of diagnoses in all women participating in the Breast-Screen Singapore program. Despite availability of breast screening, there are still Singapore women presenting with locally advanced breast cancer. The goal of the current study was to investigate pathway and immune cell heterogeneity in low, intermediate and high nuclear grade DCIS using a newly developed method for in situ hyperplexed analysis of multiple proteins in a single FFPE tissue (MultiOmyx). FFPE samples from patients (n= 15) diagnosed with DCIS were provided by Singapore General Hospital. Patients were of Chinese origin, ranged from 50-59 years, were all post-menopausal, and included low (n=5), intermediate (n=5) and high grade (n=5) samples. All histological diagnoses were reviewed by a single pathologist. Following a single antigen retrieval step, DAPI and cytokeratin staining was conducted and imaged at 10X. Based on DAPI, cytokeratin and autofluorescence, an HE San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-04-06.