James E. Verdone

Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters

Significance Conventional models of cancer progression propose that single cells leave the primary tumor, enter the circulation, and seed clonal metastases. However, metastases can contain multiple clones, raising the question: How do polyclonal metastases form? We demonstrate that cancer cells seed distant organs as cohesive clusters, composed of two molecularly distinct subpopulations, whose proportions vary systematically during metastasis. We establish that collective dissemination is a frequent mechanism for metastasis and identify a molecular program in the most invasive, keratin 14+ (K14+) cancer cells, regulating cell–cell adhesion, cell–matrix adhesion, and immune evasion. We demonstrate that this metastatic phenotype is dependent upon K14 expression. Understanding the molecular basis of collective dissemination may therefore enable novel prognostics and therapies to improve patient outcomes. Recent genomic studies challenge the conventional model that each metastasis must arise from a single tumor cell and instead reveal that metastases can be composed of multiple genetically distinct clones. These intriguing observations raise the question: How do polyclonal metastases emerge from the primary tumor? In this study, we used multicolor lineage tracing to demonstrate that polyclonal seeding by cell clusters is a frequent mechanism in a common mouse model of breast cancer, accounting for >90% of metastases. We directly observed multicolored tumor cell clusters across major stages of metastasis, including collective invasion, local dissemination, intravascular emboli, circulating tumor cell clusters, and micrometastases. Experimentally aggregating tumor cells into clusters induced a >15-fold increase in colony formation ex vivo and a >100-fold increase in metastasis formation in vivo. Intriguingly, locally disseminated clusters, circulating tumor cell clusters, and lung micrometastases frequently expressed the epithelial cytoskeletal protein, keratin 14 (K14). RNA-seq analysis revealed that K14+ cells were enriched for desmosome and hemidesmosome adhesion complex genes, and were depleted for MHC class II genes. Depletion of K14 expression abrogated distant metastases and disrupted expression of multiple metastasis effectors, including Tenascin C (Tnc), Jagged1 (Jag1), and Epiregulin (Ereg). Taken together, our findings reveal K14 as a key regulator of metastasis and establish the concept that K14+ epithelial tumor cell clusters disseminate collectively to colonize distant organs.

Technical challenges in the isolation and analysis of circulating tumor cells

Increasing evidence suggests that cancer cells display dynamic molecular changes in response to systemic therapy. Circulating tumor cells (CTCs) in the peripheral blood represent a readily available source of cancer cells with which to measure this dynamic process. To date, a large number of strategies to isolate and characterize CTCs have been described. These techniques, however, each have unique limitations in their ability to sensitively and specifically detect these rare cells. In this review we focus on the technical limitations and pitfalls of the most common CTC isolation and detection strategies. Additionally, we emphasize the difficulties in correctly classifying rare cells as CTCs using common biomarkers. As for assays developed in the future, the first step must be a uniform and clear definition of the criteria for assigning an object as a CTC based on disease-specific biomarkers.

Circulating tumour cells as biomarkers of prostate, bladder, and kidney cancer

Circulating tumour cells (CTCs) have been studied as biomarkers of a number of solid malignancies. Potential clinical applications for CTC analysis include early cancer detection, disease staging, monitoring for recurrence, prognostication, and to aid in the selection of therapy. In the field of urologic oncology, CTCs have been most widely studied as prognostic biomarkers of castration-resistant prostate cancer. Additionally, emerging data support a role for CTCs to help identify which patients are most likely to respond to novel androgen-pathway targeted therapies, such as abiraterone and enzalutamide. CTCs have also been studied as predictive biomarkers of bladder cancer, in particular as a means to identify patients whose disease has been clinically understaged. Less is known regarding CTCs in kidney cancer; this has been attributed to the fact that a minority of renal tumours express EpCAM, the epithelial cell surface protein commonly used by CTC assays for positive cell selection. However, alternative approaches using markers specific for kidney cancer are being explored.

Disseminated tumor cells and dormancy in prostate cancer metastasis.

It has been reported that disseminated tumor cells (DTCs) can be found in the majority of prostate cancer (PCa) patients, even at the time of primary treatment with no clinical evidence of metastatic disease. This suggests that these cells escaped the primary tumor early in the disease and exist in a dormant state in distant organs until they develop in some patients as overt metastases. Understanding the mechanisms by which cancer cells exit the primary tumor, survive the circulation, settle in a distant organ, and exist in a quiescent state is critical to understanding tumorigenesis, developing new prognostic assays, and designing new therapeutic modalities to prevent and treat clinical metastases.

A phased strategy to differentiate human CD14+monocytes into classically and alternatively activated macrophages and dendritic cells

There are currently several in vitro strategies to differentiate human CD14(+) monocytes isolated from peripheral blood mononuclear cells (PBMCs) into the M1 or M2 macrophage cell types. Each cell type is then verified using flow cytometric analysis of cell-surface markers. Human CD14(+) monocytes have the potential to differentiate into M1 and M2 macrophages, both of which demonstrate varying degrees of cell-surface antigen overlap. Using multiple surface markers with current macrophage polarization protocols, our data reveal several limitations of currently used methods, such as highly ambiguous cell types that possess cell-surface marker overlap and functional similarities. Utilizing interleukin-6 (IL-6) and two phases of cytokine exposure, we have developed a protocol to differentiate human monocytes into M1, M2, or dendritic cells (DCs) with greater efficiency and fidelity relative to macrophages and DCs that are produced by commonly used methods. This is achieved via alterations in cytokine composition, dosing, and incubation times, as well as improvements in verification methodology. Our method reliably reproduces human in vitro monocyte-derived DCs and macrophage models that will aid in better defining and understanding innate and adaptive immunity, as well as pathologic states.

Alternative CD44 splicing identifies epithelial prostate cancer cells from the mesenchymal counterparts

An epithelial to mesenchymal transition (EMT) has been shown to be a necessary precursor to prostate cancer metastasis. Additionally, the differential expression and splicing of mRNAs has been identified as a key means to distinguish epithelial from mesenchymal cells by qPCR, western blotting and immunohistochemistry. However, few markers exist to differentiate between these cells by flow cytometry. We previously developed two cell lines, PC3-Epi (epithelial) and PC3-EMT (mesenchymal). RNAseq was used to determine the differential expression of membrane proteins on PC3-Epi/EMT. We used western blotting, qPCR and flow cytometry to validate the RNAseq results. CD44 was one of six membrane proteins found to be differentially spliced between epithelial and mesenchymal PC3 cells. Although total CD44 was positive in all PC3-Epi/EMT cells, PC3-Epi cells had a higher level of CD44v6 (CD44 variant exon 6). CD44v6 was able to differentiate epithelial from mesenchymal prostate cancer cells using either flow cytometry, western blotting or qPCR.

Chemotherapy Increases Aggressiveness of Prostate Cancer via Epithelial Mesenchymal Transition

Chemotherapy Increases Aggressiveness of Prostate Cancer via Epithelial Mesenchymal Transition Although chemotherapy has been used as a major therapeutic weapon against advanced prostate cancer, overcoming drug resistance is still a major challenge. Cancer has been known to diminish therapeutic effect by several molecular mechanisms– increasing efflux by recruiting cell membrane pumps and limiting drug diffusion by constructing leaky vasculature. Moreover, recent studies suggest that long-term treatment with chemotherapy may have detrimental effects for patients presenting with solid tumors. Specifically, prostate cancer epithelial cells develop resistance to chemotherapy and may convert into mesenchymal cells. This switching process, known as Epithelial to Mesenchymal Transition (EMT), is a critical precursor in prostate cancer invasion and metastasis.

3D Cell Nuclear Morphology: Microscopy Imaging Dataset and Voxel-Based Morphometry Classification Results

Cell deformation is regulated by complex underlying biological mechanisms associated with spatial and temporal morphological changes in the nucleus that are related to cell differentiation, development, proliferation, and disease. Thus, quantitative analysis of changes in size and shape of nuclear structures in 3D microscopic images is important not only for investigating nuclear organization, but also for detecting and treating pathological conditions such as cancer. While many efforts have been made to develop cell and nuclear shape characteristics in 2D or pseudo-3D, several studies have suggested that 3D morphometric measures provide better results for nuclear shape description and discrimination. A few methods have been proposed to classify cell and nuclear morphological phenotypes in 3D, however, there is a lack of publicly available 3D data for the evaluation and comparison of such algorithms. This limitation becomes of great importance when the ability to evaluate different approaches on benchmark data is needed for better dissemination of the current state of the art methods for bioimage analysis. To address this problem, we present a dataset containing two different cell collections, including original 3D microscopic images of cell nuclei and nucleoli. In addition, we perform a baseline evaluation of a number of popular classification algorithms using 2D and 3D voxel-based morphometric measures. To account for batch effects, while enabling calculations of AUROC and AUPR performance metrics, we propose a specific cross-validation scheme that we compare with commonly used k-fold cross-validation. Original and derived imaging data are made publicly available on the project web-page: http://www.socr.umich.edu/projects/3d-cell-morphometry/data.html.

The prostate metastasis suppressor gene NDRG1 differentially regulates cell motility and invasion

Experimental and clinical evidence suggests that N‐myc downregulated gene 1 (NDRG1) functions as a suppressor of prostate cancer metastasis. Elucidating pathways that drive survival and invasiveness of NDRG1‐deficient prostate cancer cells can help in designing therapeutics to target metastatic prostate cancer cells. However, the molecular mechanisms that lead NDRG1‐deficient prostate cancer cells to increased invasiveness remain largely unknown. In this study, we demonstrate that NDRG1‐deficient prostate tumors have decreased integrin expression and reduced cell adhesion and motility. Our data indicate that loss of NDRG1 differentially affects Rho GTPases. Specifically, there is a downregulation of active RhoA and Rac1 GTPases with a concomitant upregulation of active Cdc42 in NDRG1‐deficient cells. Live cell imaging using a fluorescent sensor that binds to polymerized actin revealed that NDRG1‐deficient cells have restricted actin dynamics, thereby affecting cell migration. These cellular and molecular characteristics are in sharp contrast to what is expected after loss of a metastasis suppressor. We further demonstrate that NDRG1‐deficient cells have increased resistance to anoikis and increased invasiveness which is independent of its elevated Cdc42 activity. Furthermore, NDRG1 regulates expression and glycosylation of EMMPRIN, a master regulator of matrix metalloproteases. NDRG1 deficiency leads to an increase in EMMPRIN expression with a concomitant increase in matrix metalloproteases and thus invadopodial activity. Using a three‐dimensional invasion assay and an in vivo metastasis assay for human prostate xenografts, we demonstrate that NDRG1‐deficient prostate cancer cells exhibit a collective invasion phenotype and are highly invasive. Thus, our findings provide novel insights suggesting that loss of NDRG1 leads to a decrease in actin‐mediated cellular motility but an increase in cellular invasion, resulting in increased tumor dissemination which positively impacts metastatic outcome.

Nucleolin staining may aid in the identification of circulating prostate cancer cells

Micro‐Abstract In advanced prostate cancer, there is a need for biomarkers to monitor response to therapy and determine prognosis. Current tests for circulating tumor cells (CTCs) rely on epithelial markers with limited sensitivity and specificity. We showed that the staining pattern of nucleolin, a protein associated with proliferative cells, aids in the classification of prostate cancer CTCs. Introduction: Circulating tumor cells (CTCs) have great potential as circulating biomarkers for solid malignancies. Currently available assays for CTC detection rely on epithelial markers with somewhat limited sensitivity and specificity. We found that the staining pattern of nucleolin, a common nucleolar protein in proliferative cells, separates CTCs from white blood cells (WBCs) in men with metastatic prostate cancer. Patients and Methods: Whole peripheral blood from 3 men with metastatic prostate cancer was processed with the AccuCyte CTC system (RareCyte, Seattle, WA). Slides were immunostained with 4′,6‐diamidino‐2‐phenylindole (DAPI), anti–pan‐cytokeratin, anti‐CD45/CD66b/CD11b/CD14/CD34, and anti‐nucleolin antibodies and detected using the CyteFinder system. DAPI nucleolin colocalization and staining pattern wavelet entropy were measured with novel image analysis software. Results: A total of 33,718 DAPI‐positive cells were analyzed with the novel imaging software, of which 45 (0.13%) were known CTCs based on the established AccuCyte system criteria. Nucleolin staining pattern for segmentable CTCs demonstrated greater wavelet entropy than that of WBCs (median wavelet entropy, 6.86 × 107 and 3.03 × 106, respectively; P = 2.92 × 10−22; approximated z statistic = 9.63). Additionally, the total nucleolin staining of CTCs was greater than that of WBCs (median total pixel intensity, 1.20 × 105 and 2.55 × 104 integrated pixel units, respectively; P = 2.40 × 10−21; approximated z statistic = 9.41). Conclusion: Prostate cancer CTCs displayed unique nucleolin expression and localization compared to WBCs. This finding has the potential to serve as the basis for a sensitive and specific CTC detection method.