A hybrid breast cancer/mesenchymal stem cell population enhances chemoresistance and metastasis.

Patients with triple-negative breast cancer remain at risk for metastatic disease despite treatment. The acquisition of chemoresistance is a major cause of tumor relapse and death, but the mechanisms are far from understood. We have demonstrated that breast cancer cells (BCCs) can engulf mesenchymal stem/stromal cells (MSCs), leading to enhanced dissemination. Here, we show that clinical samples of primary invasive carcinoma and chemoresistant breast cancer metastasis contain a unique hybrid cancer cell population coexpressing pancytokeratin and the MSC marker fibroblast activation protein-α. We show that hybrid cells form in primary tumors and that they promote breast cancer metastasis and chemoresistance. Using single-cell microfluidics and in vivo models, we found that there are polyploid senescent cells within the hybrid cell population that contribute to metastatic dissemination. Our data reveal that Wnt Family Member 5A (WNT5A) plays a crucial role in supporting the chemoresistance properties of hybrid cells. Furthermore, we identified that WNT5A mediates hybrid cell formation through a phagocytosis-like mechanism that requires BCC-derived IL-6 and MSC-derived C-C Motif Chemokine Ligand 2. These findings reveal hybrid cell formation as a mechanism of chemoresistance and suggest that interrupting this mechanism may be a strategy in overcoming breast cancer drug resistance.

EZH2 T367 phosphorylation activates p38 signaling through lysine methylation to promote breast cancer progression.

Triple-negative breast cancers (TNBCs) are frequently poorly differentiated with high propensity for metastasis. Enhancer of zeste homolog 2 (EZH2) is the lysine methyltransferase of polycomb repressive complex 2 that mediates transcriptional repression in normal cells and in cancer through H3K27me3. However, H3K27me3-independent non-canonical functions of EZH2 are incompletely understood. We reported that EZH2 phosphorylation at T367 by p38α induces TNBC metastasis in an H3K27me3-independent manner. Here, we show that cytosolic EZH2 methylates p38α at lysine 139 and 165 leading to enhanced p38α stability and that p38 methylation and activation require T367 phosphorylation of EZH2. Dual inhibition of EZH2 methyltransferase and p38 kinase activities downregulates pEZH2-T367, H3K27me3, and p-p38 pathways in vivo and reduces TNBC growth and metastasis. These data uncover a cooperation between EZH2 canonical and non-canonical mechanisms and suggest that inhibition of these pathways may be a potential therapeutic strategy.

Monitoring Spontaneous Quiescence and Asynchronous Proliferation-Quiescence Decisions in Prostate Cancer Cells.

The proliferation-quiescence decision is a dynamic process that remains incompletely understood. Live-cell imaging with fluorescent cell cycle sensors now allows us to visualize the dynamics of cell cycle transitions and has revealed that proliferation-quiescence decisions can be highly heterogeneous, even among clonal cell lines in culture. Under normal culture conditions, cells often spontaneously enter non-cycling G0 states of varying duration and depth. This also occurs in cancer cells and G0 entry in tumors may underlie tumor dormancy and issues with cancer recurrence. Here we show that a cell cycle indicator previously shown to indicate G0 upon serum starvation, mVenus-p27K-, can also be used to monitor spontaneous quiescence in untransformed and cancer cell lines. We find that the duration of spontaneous quiescence in untransformed and cancer cells is heterogeneous and that a portion of this heterogeneity results from asynchronous proliferation-quiescence decisions in pairs of daughters after mitosis, where one daughter cell enters or remains in temporary quiescence while the other does not. We find that cancer dormancy signals influence both entry into quiescence and asynchronous proliferation-quiescence decisions after mitosis. Finally, we show that spontaneously quiescent prostate cancer cells exhibit altered expression of components of the Hippo pathway and are enriched for the stem cell markers CD133 and CD44. This suggests a hypothesis that dormancy signals could promote cancer recurrence by increasing the proportion of quiescent tumor cells poised for cell cycle re-entry with stem cell characteristics in cancer.

3D-printed Recoverable Microdrive and Base Plate System for Rodent Electrophysiology.

Extracellular recordings in freely moving animals allow the monitoring of brain activity from populations of neurons at single-spike temporal resolution. While state-of-the-art electrophysiological recording devices have been developed in recent years (e.g., µLED and Neuropixels silicon probes), implantation methods for silicon probes in rats and mice have not advanced substantially for a decade. The surgery is complex, takes time to master, and involves handling expensive devices and valuable animal subjects. In addition, chronic silicon neural probes are practically single implant devices due to the current low success rate of probe recovery. To successfully recover silicon probes, improve upon the quality of electrophysiological recording, and make silicon probe recordings more accessible, we have designed a miniature, low cost, and recoverable microdrive system. The addition of a novel 3D-printed skull baseplate makes the surgery less invasive, faster, and simpler for both rats and mice. We provide detailed procedural instructions and print designs, allowing researchers to adapt and flexibly customize our designs to their experimental usage.

Needle-compatible miniaturized optoelectronic sensor for pancreatic cancer detection.

Pancreatic cancer is one of the deadliest cancers, with a 5-year survival rate of <10%. The current approach to confirming a tissue diagnosis, endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA), requires a time-consuming, qualitative cytology analysis and may be limited because of sampling error. We designed and engineered a miniaturized optoelectronic sensor to assist in situ, real-time, and objective evaluation of human pancreatic tissues during EUS-FNA. A proof-of-concept prototype sensor, compatible with a 19-gauge hollow-needle commercially available for EUS-FNA, was constructed using microsized optoelectronic chips and microfabrication techniques to perform multisite tissue optical sensing. In our bench-top verification and pilot validation during surgery on freshly excised human pancreatic tissues (four patients), the fabricated sensors showed a comparable performance to our previous fiber-based system. The flexibility in source-detector configuration using microsized chips potentially allows for various light-based sensing techniques inside a confined channel such as a hollow needle or endoscopy.

Single-Cell Transcriptome Analysis of Colon Cancer Cell Response to 5-Fluorouracil-Induced DNA Damage.

DNA damage often induces heterogeneous cell-fate responses, such as cell-cycle arrest and apoptosis. Through single-cell RNA sequencing (scRNA-seq), we characterize the transcriptome response of cultured colon cancer cell lines to 5-fluorouracil (5FU)-induced DNA damage. After 5FU treatment, a single population of colon cancer cells adopts three distinct transcriptome phenotypes, which correspond to diversified cell-fate responses: apoptosis, cell-cycle checkpoint, and stress resistance. Although some genes are regulated uniformly across all groups of cells, many genes showed group-specific expression patterns mediating DNA damage responses specific to the corresponding cell fate. Some of these observations are reproduced at the protein level by flow cytometry and are replicated in cells treated with other 5FU-unrelated genotoxic drugs, camptothecin and etoposide. This work provides a resource for understanding heterogeneous DNA damage responses involving fractional killing and chemoresistance, which are among the major challenges in current cancer chemotherapy.

Early Prediction of Single-Cell Derived Sphere Formation Rate Using Convolutional Neural Network Image Analysis.

Functional identification of cancer stem-like cells (CSCs) is an established method to identify and study this cancer subpopulation critical for cancer progression and metastasis. The method is based on the unique capability of single CSCs to survive and grow to tumorspheres in harsh suspension culture environment. Recent advances in microfluidic technology have enabled isolating and culturing thousands of single cells on a chip. However, tumorsphere assay takes a relatively long period of time, limiting the throughput of this assay. In this work, we incorporated machine learning with single-cell analysis to expedite tumorsphere assay. We collected 1,710 single-cell events as the database and trained a convolutional neural network model that predicts whether a single cell could grow to a tumorsphere on Day 14 based on its Day 4 image. With this future-telling model, we precisely estimated the sphere formation rate of SUM159 breast cancer cells to be 17.8% based on Day 4 images. The estimation was close to the ground truth of 17.6% on Day 14. The preliminary work demonstrates not only the feasibility to significantly accelerate tumorsphere assay but also a synergistic combination between single-cell analysis with machine learning, which can be applied to many other biomedical applications.

NFATC4 promotes quiescence and chemotherapy resistance in ovarian cancer.

Development of chemotherapy resistance is a major problem in ovarian cancer. One understudied mechanism of chemoresistance is the induction of quiescence, a reversible nonproliferative state. Unfortunately, little is known about regulators of quiescence. Here, we identify the master transcription factor nuclear factor of activated T cells cytoplasmic 4 (NFATC4) as a regulator of quiescence in ovarian cancer. NFATC4 is enriched in ovarian cancer stem-like cells and correlates with decreased proliferation and poor prognosis. Treatment of cancer cells with cisplatin resulted in NFATC4 nuclear translocation and activation of the NFATC4 pathway, while inhibition of the pathway increased chemotherapy response. Induction of NFATC4 activity resulted in a marked decrease in proliferation, G0 cell cycle arrest, and chemotherapy resistance, both in vitro and in vivo. Finally, NFATC4 drove a quiescent phenotype in part via downregulation of MYC. Together, these data identify NFATC4 as a driver of quiescence and a potential new target to combat chemoresistance in ovarian cancer.

Co-culture of functionally enriched cancer stem-like cells and cancer-associated fibroblasts for single-cell whole transcriptome analysis.

Considerable evidence suggests that breast cancer development and metastasis are driven by cancer stem-like cells (CSCs). Due to their unique role in tumor initiation, the interaction between CSCs and stromal cells is especially critical. In this work, we developed a platform to reliably isolate single cells in suspension and grow single-cell-derived spheres for functional enrichment of CSCs. The platform also allows adherent culture of stromal cells for cancer-stromal interaction. As a proof of concept, we grew SUM149 breast cancer cells and successfully formed single-cell-derived spheres. Cancer-associated fibroblasts (CAFs) as stromal cells were found to significantly enhance the formation and growth of cancer spheres, indicating elevated tumor-initiation potential. After on-chip culture for 14 days, we retrieved single-cell derived spheres with and without CAF co-culture for single-cell transcriptome sequencing. Whole transcriptome analysis highlights that CAF co-culture can boost cancer stemness especially ALDHhigh CSCs and alter epithelial/mesenchymal status. Single-cell resolution allows identification of individual CSCs and investigation of cancer cellular heterogeneity. Incorporating whole transcriptome sequencing data with public patient database, we discovered novel genes associated with cancer-CAF interaction and critical to patient survival. The preliminary works demonstrated a reliable platform for enrichment of CSCs and studies of cancer-stromal interaction.

Single-cell RNA-sequencing of migratory breast cancer cells: discovering genes associated with cancer metastasis.

Considerable evidence suggests breast cancer metastasis arises from cells undergoing epithelial-to-mesenchymal-transition (EMT) and cancer stem-like cells (CSCs). Using a microfluidic device that enriches migratory breast cancer cells with enhanced capacity for tumor formation and metastasis, we identified genes differentially expressed in migratory cells by high-throughput single-cell RNA-sequencing. Migratory cells exhibited overall signatures of EMT and CSCs with variable expression of marker genes, and they retained expression profiles of EMT over time. With single-cell resolution, we discovered intermediate EMT states and distinct epithelial and mesenchymal sub-populations of migratory cells, indicating breast cancer cells can migrate rapidly while retaining an epithelial state. Migratory cells showed differential profiles for regulators of oxidative stress, mitochondrial morphology, and the proteasome, revealing potential vulnerabilities and unexpected consequences of drugs. We also identified novel genes correlated with cell migration and outcomes in breast cancer as potential prognostic biomarkers and therapeutic targets to block migratory cells in metastasis.

Single-cell proteolytic activity measurement using microfluidics for rare cell populations.

Proteolytic degradation of the extracellular matrix represents a key step in cancer dissemination and metastasis. To probe cellular proteolytic activity, fluorescent sensing substrate was developed, yet prior studies focused on average activity of thousands of cells. Considerable evidence suggests a specialized subset of cancer cells are driving metastasis, highlighting the value of single-cell approach to reveal cancer cellular heterogeneity. In addition, when only a small number of cells are available, single-cell analysis is required to draw a statistical conclusion. Here, we present a microfluidic platform that provides high-efficiency cell loading and simple valveless isolation, so the proteolytic activity of a small number (10-100) of cells can be individually characterized. Furthermore, the platform allows monitoring single cells at multiple time points for the investigation of dynamics in proteolytic activity. The presented platform represents a simple and reliable tool for single-cell proteolytic analysis, illuminating the heterogeneous and dynamic nature of cancer cells.

Label-Free Estimation of Therapeutic Efficacy on 3D Cancer Spheres Using Convolutional Neural Network Image Analysis.

Despite recent advances in cancer treatment, developing better therapeutic reagents remains an essential task for oncologists. To accurately characterize drug efficacy, 3D cell culture holds great promise as opposed to conventional 2D monolayer culture. Due to the advantages of cell manipulation in high-throughput, various microfluidic platforms have been developed for drug screening with 3D models. However, the dissemination of microfluidic technology is overall slow, and one missing part is fast and low-cost assay readout. In this work, we developed a microfluidic chip forming 1920 tumor spheres for drug testing, and the platform is supported by automatic image collection and cropping for analysis. Using conventional LIVE/DEAD staining as the ground truth of sphere viability, we trained a convolutional neural network to estimate sphere viability based on its bright-field image. The estimated sphere viability was highly correlated with the ground truth (R-value > 0.84). In this manner, we precisely estimated drug efficacy of three chemotherapy drugs, doxorubicin, oxaliplatin, and irinotecan. We also cross-validated the trained networks of doxorubicin and oxaliplatin and found common bright-field morphological features indicating sphere viability. The discovery suggests the potential to train a generic network using some representative drugs and apply it to many different drugs in large-scale screening. The bright-field estimation of sphere viability saves LIVE/DEAD staining reagent cost and fluorescence imaging time. More importantly, the presented method allows viability estimation in a label-free and nondestructive manner. In short, with image processing and machine learning, the presented method provides a fast, low-cost, and label-free method to assess tumor sphere viability for large-scale drug screening in microfluidics.

Mesenchymal Stem/Stromal Cell Engulfment Reveals Metastatic Advantage in Breast Cancer.

Twenty percent of breast cancer (BC) patients develop distant metastasis for which there is no cure. Mesenchymal stem/stromal cells (MSCs) in the tumor microenvironment were shown to stimulate metastasis, but the mechanisms are unclear. Here, we identified and quantified cancer cells engulfing stromal cells in clinical samples of BC metastasis by dual immunostaining for EZH2 and ALDH1 expression. Using flow cytometry and a microfluidic single-cell paring and retrieval platform, we show that MSC engulfment capacity is associated with BC cell metastatic potential and generates cells with mesenchymal-like, invasion, and stem cell traits. Whole-transcriptome analyses of selectively retrieved engulfing BC cells identify a gene signature of MSC engulfment consisting of WNT5A, MSR1, ELMO1, IL1RL2, ZPLD1, and SIRPB1. These results delineate a mechanism by which MSCs in the tumor microenvironment promote metastasis and provide a microfluidic platform with the potential to predict BC metastasis in clinical samples.

Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells.

Molecular analysis of circulating tumor cells (CTCs) at single-cell resolution offers great promise for cancer diagnostics and therapeutics from simple liquid biopsy. Recent development of massively parallel single-cell RNA-sequencing (scRNA-seq) provides a powerful method to resolve the cellular heterogeneity from gene expression and pathway regulation analysis. However, the scarcity of CTCs and the massive contamination of blood cells limit the utility of currently available technologies. Here, we present Hydro-Seq, a scalable hydrodynamic scRNA-seq barcoding technique, for high-throughput CTC analysis. High cell-capture efficiency and contamination removal capability of Hydro-Seq enables successful scRNA-seq of 666 CTCs from 21 breast cancer patient samples at high throughput. We identify breast cancer drug targets for hormone and targeted therapies and tracked individual cells that express markers of cancer stem cells (CSCs) as well as of epithelial/mesenchymal cell state transitions. Transcriptome analysis of these cells provides insights into monitoring target therapeutics and processes underlying tumor metastasis.

A Pan-ALDH1A Inhibitor Induces Necroptosis in Ovarian Cancer Stem-like Cells.

Ovarian cancer is typified by the development of chemotherapy resistance. Chemotherapy resistance is associated with high aldehyde dehydrogenase (ALDH) enzymatic activity, increased cancer "stemness," and expression of the stem cell marker CD133. As such, ALDH activity has been proposed as a therapeutic target. Although it remains controversial which of the 19 ALDH family members drive chemotherapy resistance, ALDH1A family members have been primarily linked with chemotherapy resistant and stemness. We identified two ALDH1A family selective inhibitors (ALDH1Ai). ALDH1Ai preferentially kills CD133+ ovarian cancer stem-like cells (CSCs). ALDH1Ai induce necroptotic CSC death, mediated, in part, by the induction of mitochondrial uncoupling proteins and reduction in oxidative phosphorylation. ALDH1Ai is highly synergistic with chemotherapy, reducing tumor initiation capacity and increasing tumor eradication in vivo. These studies link ALDH1A with necroptosis and confirm the family as a critical therapeutic target to overcome chemotherapy resistance and improve patient outcomes.

Plasminogen Activator Inhibitor 1 (PAI1) Promotes Actin Cytoskeleton Reorganization and Glycolytic Metabolism in Triple-Negative Breast Cancer.

Migration and invasion of cancer cells constitute fundamental processes in tumor progression and metastasis. Migratory cancer cells commonly upregulate expression of plasminogen activator inhibitor 1 (PAI1), and PAI1 correlates with poor prognosis in breast cancer. However, mechanisms by which PAI1 promotes migration of cancer cells remain incompletely defined. Here we show that increased PAI1 drives rearrangement of the actin cytoskeleton, mitochondrial fragmentation, and glycolytic metabolism in triple-negative breast cancer (TNBC) cells. In two-dimensional environments, both stable expression of PAI1 and treatment with recombinant PAI1 increased migration, which could be blocked with the specific inhibitor tiplaxtinin. PAI1 also promoted invasion into the extracellular matrix from coculture spheroids with human mammary fibroblasts in fibrin gels. Elevated cellular PAI1 enhanced cytoskeletal features associated with migration, actin-rich migratory structures, and reduced actin stress fibers. In orthotopic tumor xenografts, we discovered that TNBC cells with elevated PAI1 show collagen fibers aligned perpendicular to the tumor margin, an established marker of invasive breast tumors. Further studies revealed that PAI1 activates ERK signaling, a central regulator of motility, and promotes mitochondrial fragmentation. Consistent with known effects of mitochondrial fragmentation on metabolism, fluorescence lifetime imaging microscopy of endogenous NADH showed that PAI1 promotes glycolysis in cell-based assays, orthotopic tumor xenografts, and lung metastases. Together, these data demonstrate for the first time that PAI1 regulates cancer cell metabolism and suggest targeting metabolism to block motility and tumor progression. IMPLICATIONS: We identified a novel mechanism through which cancer cells alter their metabolism to promote tumor progression.

A miRNA-Mediated Approach to Dissect the Complexity of Tumor-Initiating Cell Function and Identify miRNA-Targeting Drugs.

Tumor-initiating cells (TICs) contribute to drug resistance and tumor recurrence in cancers, thus experimental approaches to dissect the complexity of TICs are required to design successful TIC therapeutic strategies. Here, we show that miRNA-3' UTR sensor vectors can be used as a pathway-based method to identify, enrich, and analyze TICs from primary solid tumor patient samples. We have found that an miR-181ahigh subpopulation of cells sorted from primary ovarian tumor cells exhibited TIC properties in vivo, were enriched in response to continuous cisplatin treatment, and showed activation of numerous major stem cell regulatory pathways. This miRNA-sensor-based platform enabled high-throughput drug screening leading to identification of BET inhibitors as transcriptional inhibitors of miR-181a. Taken together, we provide a valuable miRNA-sensor-based approach to broaden the understanding of complex TIC regulatory mechanisms in cancers and to identify miRNA-targeting drugs.

Morphology-based prediction of cancer cell migration using an artificial neural network and a random decision forest.

Metastasis is the cause of death in most patients of breast cancer and other solid malignancies. Identification of cancer cells with highly migratory capability to metastasize relies on markers for epithelial-to-mesenchymal transition (EMT), a process increasing cell migration and metastasis. Marker-based approaches are limited by inconsistences among patients, types of cancer, and partial EMT states. Alternatively, we analyzed cancer cell migration behavior using computer vision. Using a microfluidic single-cell migration chip and high-content imaging, we extracted morphological features and recorded migratory direction and speed of breast cancer cells. By applying a Random Decision Forest (RDF) and an Artificial Neural Network (ANN), we achieved over 99% accuracy for cell movement direction prediction and 91% for speed prediction. Unprecedentedly, we identified highly motile cells and non-motile cells based on microscope images and a machine learning model, and pinpointed and validated morphological features determining cell migration, including not only known features related to cell polarization but also novel ones that can drive future mechanistic studies. Predicting cell movement by computer vision and machine learning establishes a ground-breaking approach to analyze cell migration and metastasis.

Scalable Multiplexed Drug-Combination Screening Platforms Using 3D Microtumor Model for Precision Medicine.

Cancer heterogeneity is a notorious hallmark of this disease, and it is desirable to tailor effective treatments for each individual patient. Drug combinations have been widely accepted in cancer treatment for better therapeutic efficacy as compared to a single compound. However, experimental complexity and cost grow exponentially with more target compounds under investigation. The primary challenge remains to efficiently perform a large-scale drug combination screening using a small number of patient primary samples for testing. Here, a scalable, easy-to-use, high-throughput drug combination screening scheme is reported, which has the potential of screening all possible pairwise drug combinations for arbitrary number of drugs with multiple logarithmic mixing ratios. A "Christmas tree mixer" structure is introduced to generate a logarithmic concentration mixing ratio between drug pairs, providing a large drug concentration range for screening. A three-layer structure design and special inlets arrangement facilitate simple drug loading process. As a proof of concept, an 8-drug combination chip is implemented, which is capable of screening 172 different treatment conditions over 1032 3D cancer spheroids on a single chip. Using both cancer cell lines and patient-derived cancer cells, effective drug combination screening is demonstrated for precision medicine.

p38-mediated phosphorylation at T367 induces EZH2 cytoplasmic localization to promote breast cancer metastasis.

Overexpression of EZH2 in estrogen receptor negative (ER-) breast cancer promotes metastasis. EZH2 has been mainly studied as the catalytic component of the Polycomb Repressive Complex 2 (PRC2) that mediates gene repression by trimethylating histone H3 at lysine 27 (H3K27me3). However, how EZH2 drives metastasis despite the low H3K27me3 levels observed in ER- breast cancer is unknown. Here we show that in human invasive carcinomas and distant metastases, cytoplasmic EZH2 phosphorylated at T367 is significantly associated with ER- disease and low H3K27me3 levels. p38-mediated EZH2 phosphorylation at T367 promotes EZH2 cytoplasmic localization and potentiates EZH2 binding to vinculin and other cytoskeletal regulators of cell migration and invasion. Ectopic expression of a phospho-deficient T367A-EZH2 mutant is sufficient to inhibit EZH2 cytoplasmic expression, disrupt binding to cytoskeletal regulators, and reduce EZH2-mediated adhesion, migration, invasion, and development of spontaneous metastasis. These results point to a PRC2-independent non-canonical mechanism of EZH2 pro-metastatic function.