CD55 is a membrane complement regulatory protein that attenuates complement-mediated cytotoxicity. Saygin et al. elucidate a new role for CD55 as a signaling hub for cancer stem cell self-renewal and cisplatin resistance pathways in endometrioid tumors and open a new line of research into chemotherapeutic-refractory cancers.

The second International Cancer Stem Cell Conference in Cleveland, Ohio, on September 20–23, 2016, convened 330 attendees from academic, industrial, and clinical organizations. It featured a debate on the concepts and challenges of the cancer stem cells (CSC) as well as CSC-centered scientific sessions on clinical trials, genetics and epigenetics, tumor microenvironment, immune suppression, metastasis, therapeutic resistance, and emerging novel concepts. The conference hosted 35 renowned speakers, 100 posters, 20 short talks, and a preconference workshop. The reported advances of CSC research and therapies fostered new collaborations across national and international borders, and inspired the next generation’s young scientists.

Purpose of review: Here, we identify shortcomings of standard compartment-based mathematical models of cancer stem-cells, and propose a continuous formalism which includes the tumor microenvironment. Recent findings: Stem-cell models of tumor growth have provided explanations for various phenomena in oncology including, metastasis, drug-and radio-resistance, and functional heterogeneity in the face of genetic homogeneity. While some of the newer models allow for plasticity, or de-differentiation, there is no consensus on the mechanisms driving this. Recent experimental evidence suggests that tumor microenvironment factors like hypoxia, acidosis and nutrient deprivation have causative roles. Summary: To settle the dissonance between the mounting experimental evidence surrounding the effects of the microenvironment on tumor stemness, We propose a continuous mathematical model where we model microenvironmental perturbations like forces, which then shape the distribution of stemness within the tumor. We propose methods by which to systematically measure and charaterize these forces, and show results of a simple experiment which support our claims.

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Asymmetric cell division (ACD) enables the maintenance of a stem cell population while simultaneously generating differentiated progeny. Cancer stem cells (CSCs) undergo multiple modes of cell division during tumor expansion and in response to therapy, yet the functional consequences of these division modes remain to be determined. Using a fluorescent reporter for cell surface receptor distribution during mitosis, we found that ACD generated a daughter cell with enhanced therapeutic resistance and increased coenrichment of EGFR and neurotrophin receptor (p75NTR) from a glioblastoma CSC. Stimulation of both receptors antagonized differentiation induction and promoted self-renewal capacity. p75NTR knockdown enhanced the therapeutic efficacy of EGFR inhibition, indicating that coinheritance of p75NTR and EGFR promotes resistance to EGFR inhibition through a redundant mechanism. These data demonstrate that ACD produces progeny with coenriched growth factor receptors, which contributes to the generation of a more therapeutically resistant CSC population.

Cancer stem cells have been identified in primary tumors, patient derived xenografts, and established cancer cell lines. The development of reporters has enabled investigators to rapidly enrich for these cells and more importantly track these cells in real time. Here we describe the current state of the reporter field and their use and limitations in multiple cancers.

Cancer stem cells (CSCs) are a heterogeneous and dynamic population that stands at the top of tumor cellular hierarchy and is responsible for maintenance of the tumor microenvironment. As methods of CSC isolation and functional interrogation advance, there is a need for a reliable and accessible quantitative approach to assess heterogeneity and state transition dynamics in CSCs. We developed a High-throughput Automated Single Cell Imaging Analysis (HASCIA) approach for quantitative assessment of protein expression with single cell resolution and applied the method to investigate spatiotemporal factors that influence CSC state transition using glioblastoma (GBM) CSC as a model system. We were able to validate the quantitative nature of this approach through comparison of the protein expression levels determined by HASCIA to those determined by immunoblotting. A virtue of HASCIA was exemplified by detection of a subpopulation of SOX2-low cells, which expanded in fraction size during state transition. HASCIA also revealed that CSCs were committed to loose stem cell state at an earlier time point than the average SOX2 level decreased. Functional assessment of stem cell frequency in combination with quantification of SOX2 expression by HASCIA defined a stable cut-off of SOX2 expression level for stem cell state. We also developed an approach to assess local cell density and found that denser monolayer areas possess higher average levels of SOX2, higher cell diversity and a presence of a sub-population of slowly proliferating SOX2-low CSCs. HASCIA is an open source software that facilitates understanding the dynamics of heterogeneous cell population such as that of CSCs and their progeny. It is a powerful and easy-to-use image analysis and statistical analysis tool available at https://hascia.lerner.ccf.org.

Breast cancer is the most prevalent malignancy and second leading cause of death in women worldwide, with hormone receptor-positive luminal breast cancers being the most widespread subtype. While these tumors are generally amenable to endocrine therapy, cellular heterogeneity and acquired ability of tumor cells to undergo cell state switching makes these populations difficult to be fully targeted and eradicated through conventional methods. We have leveraged a quality-by-design (QbD) approach that integrates biological responses with predictive mathematical modeling to identify key combinations of commercially available drugs to induce estrogen receptor expression for therapeutic targeting. This technology utilizes a high level of automation through a custom-built platform to reduce bias as well as design-of-experiments methodology to minimize the experimental iterations required. Utilizing this approach, we identified a combination of clinical compounds, each at concentrations well below their efficacious dose, able to induce the expression of estrogen receptor alpha (ESR1) in hormone-positive breast cancer cells. Induction of ESR1 in luminal cells leads to chemosensitization. These findings provide proof of concept for the utility of the QbD strategy and identify a unique drug cocktail able to sensitize breast cancer cells to tamoxifen.