A comprehensive promoter landscape identifies a novel promoter for CD133 in restricted tissues, cancers, and stem cells

The Impact of Glycosylation on the Functional Activity of CD133 and the Accuracy of Its Immunodetection

The membrane glycoprotein CD133 (prominin-1) is widely regarded as the main molecular marker of cancer stem cells, which are the most malignant cell subpopulation within the tumor, responsible for tumor growth and metastasis. For this reason, CD133 is considered a promising prognostic biomarker and molecular target for antitumor therapy. Under normal conditions, CD133 is present on the cell membrane in glycosylated form. However, in malignancies, altered glycosylation apparently leads to changes in the functional activity of CD133 and the availability of some of its epitopes for antibodies. This review focuses on CD133's glycosylation in human cells and its impact on the function of this glycoprotein. The association of CD133 with proliferation, differentiation, apoptosis, autophagy, epithelial-mesenchymal transition, the organization of plasma membrane protrusions and extracellular trafficking is discussed. In this review, particular attention is paid to the influence of CD133's glycosylation on its immunodetection. A list of commercially available and custom antibodies with their characteristics is provided. The available data indicate that the development of CD133-based biomedical technologies should include an assessment of CD133's glycosylation in each tumor type.

Emerging roles of prominin-1 (CD133) in the dynamics of plasma membrane architecture and cell signaling pathways in health and disease

Prominin-1 (CD133) is a cholesterol-binding membrane glycoprotein selectively associated with highly curved and prominent membrane structures. It is widely recognized as an antigenic marker of stem cells and cancer stem cells and is frequently used to isolate them from biological and clinical samples. Recent progress in understanding various aspects of CD133 biology in different cell types has revealed the involvement of CD133 in the architecture and dynamics of plasma membrane protrusions, such as microvilli and cilia, including the release of extracellular vesicles, as well as in various signaling pathways, which may be regulated in part by posttranslational modifications of CD133 and its interactions with a variety of proteins and lipids. Hence, CD133 appears to be a master regulator of cell signaling as its engagement in PI3K/Akt, Src-FAK, Wnt/β-catenin, TGF-β/Smad and MAPK/ERK pathways may explain its broad action in many cellular processes, including cell proliferation, differentiation, and migration or intercellular communication. Here, we summarize early studies on CD133, as they are essential to grasp its novel features, and describe recent evidence demonstrating that this unique molecule is involved in membrane dynamics and molecular signaling that affects various facets of tissue homeostasis and cancer development. We hope this review will provide an informative resource for future efforts to elucidate the details of CD133's molecular function in health and disease.

Functional Roles of CD133: More than Stemness Associated Factor Regulated by the Microenvironment

CD133 protein has been one of the most used surface markers to select and identify cancer cells with stem-like features. However, its expression is not restricted to tumoral cells; it is also expressed in differentiated cells and stem/progenitor cells in various normal tissues. CD133 participates in several cellular processes, in part orchestrating signal transduction of essential pathways that frequently are dysregulated in cancer, such as PI3K/Akt signaling and the Wnt/β-catenin pathway. CD133 expression correlates with enhanced cell self-renewal, migration, invasion, and survival under stress conditions in cancer. Aside from the intrinsic cell mechanisms that regulate CD133 expression in each cellular type, extrinsic factors from the surrounding niche can also impact CD33 levels. The enhanced CD133 expression in cells can confer adaptive advantages by amplifying the activation of a specific signaling pathway in a context-dependent manner. In this review, we do not only describe the CD133 physiological functions known so far, but importantly, we analyze how the microenvironment changes impact the regulation of CD133 functions emphasizing its value as a marker of cell adaptability beyond a cancer-stem cell marker.

Therapy Approaches for Stargardt Disease

Despite being the most prevalent cause of inherited blindness in children, Stargardt disease is yet to achieve the same clinical trial success as has been achieved for other inherited retinal diseases. With an early age of onset and continual progression of disease over the life course of an individual, Stargardt disease appears to lend itself to therapeutic intervention. However, the aetiology provides issues not encountered with the likes of choroideremia and X-linked retinitis pigmentosa and this has led to a spectrum of treatment strategies that approach the problem from different aspects. These include therapeutics ranging from small molecules and anti-sense oligonucleotides to viral gene supplementation and cell replacement. The advancing development of CRISPR-based molecular tools is also likely to contribute to future therapies by way of genome editing. In this we review, we consider the most recent pre-clinical and clinical trial data relating to the different strategies being applied to the problem of generating a treatment for the large cohort of Stargardt disease patients worldwide.

NELL2-cdc42 signaling regulates BAF complexes and Ewing sarcoma cell growth

BAF chromatin remodeling complexes play important roles in chromatin regulation and cancer. Here, we report that Ewing sarcoma cells are dependent on the autocrine signaling mediated by NELL2, a secreted glycoprotein that has been characterized as an axon guidance molecule. NELL2 uses Robo3 as the receptor to transmit critical growth signaling. NELL2 signaling inhibits cdc42 and upregulates BAF complexes and EWS-FLI1 transcriptional output. We demonstrate that cdc42 is a negative regulator of BAF complexes, inducing actin polymerization and complex disassembly. Furthermore, we identify NELL2highCD133highEWS-FLI1high and NELL2lowCD133lowEWS-FLI1low populations in Ewing sarcoma, which display phenotypes consistent with high and low NELL2 signaling, respectively. We show that NELL2, CD133, and EWS-FLI1 positively regulate each other and upregulate BAF complexes and cell proliferation in Ewing sarcoma. These results reveal a signaling pathway regulating critical chromatin remodeling complexes and cancer cell proliferation.

PRRX1 induced by BMP signaling decreases tumorigenesis by epigenetically regulating glioma-initiating cell properties via DNA methyltransferase 3A

Glioma‐initiating cells (GICs), a major source of glioblastoma recurrence, are characterized by the expression of neural stem cell markers and the ability to grow by forming nonadherent spheres under serum‐free conditions. Bone morphogenetic proteins (BMPs), members of the transforming growth factor‐β family, induce differentiation of GICs and suppress their tumorigenicity. However, the mechanisms underlying the BMP‐induced loss of GIC stemness have not been fully elucidated. Here, we show that paired related homeobox 1 (PRRX1) induced by BMPs decreases the CD133‐positive GIC population and inhibits tumorigenic activity of GICs in vivo. Of the two splice isoforms of PRRX1, the longer isoform, pmx‐1b, but not the shorter isoform, pmx‐1a, induces GIC differentiation. Upon BMP stimulation, pmx‐1b interacts with the DNA methyltransferase DNMT3A and induces promoter methylation of the PROM1 gene encoding CD133. Silencing DNMT3A maintains PROM1 expression and increases the CD133‐positive GIC population. Thus, pmx‐1b promotes loss of stem cell‐like properties of GICs through region‐specific epigenetic regulation of CD133 expression by recruiting DNMT3A, which is associated with decreased tumorigenicity of GICs.

Cap Analysis of Gene Expression (CAGE): A Quantitative and Genome-Wide Assay of Transcription Start Sites

Cap analysis of gene expression (CAGE) is an approach to identify and monitor the activity (transcription initiation frequency) of transcription start sites (TSSs) at single base-pair resolution across the genome. It has been effectively used to identify active promoter and enhancer regions in cancer cells, with potential utility to identify key factors to immunotherapy. Here, we overview a series of CAGE protocols and describe detailed experimental steps of the latest protocol based on the Illumina sequencing platform; both experimental steps (see Subheadings 3.1-3.11) and computational processing steps (see Subheadings 3.12-3.20) are described.

MicroRNA-128 suppresses paclitaxel-resistant lung cancer by inhibiting MUC1-C and BMI-1 in cancer stem cells

The existence of cancer stem cells (CSCs) is the main reason for failure of cancer treatment caused by drug resistance. Therefore, eradicating cancers by targeting CSCs remains a significant challenge. In the present study, because of the important role of BMI-1 proto-oncogene, polycomb ring finger (BMI-1) and C-terminal Mucin1 (MUC1-C) in tumor growth and maintenance of CSCs, we aimed to confirm that microRNA miR-128, as an inhibitor of BMI-1 and MUC1-C, could effectively suppress paclitaxel (PTX)-resistant lung cancer stem cells. We showed that CSCs have significantly higher expression levels of BMI-1, MUC1-C, stemness proteins, signaling factors, and higher malignancy compared with normal tumor cells. After transfection with miR-128, the BMI-1 and MUC1-C levels in CSCs were suppressed. When miR-128 was stably expressed in PTX-resistant lung cancer stem cells, the cells showed decreased proliferation, metastasis, self-renewal, migration, invasive ability, clonogenicity, and tumorigenicity in vitro and in vivo and increased apoptosis compared with miR-NC (negative control) CSCs. Furthermore, miR-128 effectively decreased the levels of β-catenin and intracellular signaling pathway-related factors in CSCs. MiR-128 also decreased the luciferase activity of MUC1 reporter constructs and reduced the levels of transmembrane MUC1-C and BMI-1. These results suggested miR-128 as an attractive therapeutic strategy for PTX-resistant lung cancer via inhibition of BMI-1 and MUC1-C.

Distinct splicing signatures affect converged pathways in myelodysplastic syndrome patients carrying mutations in different splicing regulators

Myelodysplastic syndromes (MDS) are heterogeneous myeloid disorders with prevalent mutations in several splicing factors, but the splicing programs linked to specific mutations or MDS in general remain to be systematically defined. We applied RASL-seq, a sensitive and cost-effective platform, to interrogate 5502 annotated splicing events in 169 samples from MDS patients or healthy individuals. We found that splicing signatures associated with normal hematopoietic lineages are largely related to cell signaling and differentiation programs, whereas MDS-linked signatures are primarily involved in cell cycle control and DNA damage responses. Despite the shared roles of affected splicing factors in the 3' splice site definition, mutations in U2AF1, SRSF2, and SF3B1 affect divergent splicing programs, and interestingly, the affected genes fall into converging cancer-related pathways. A risk score derived from 11 splicing events appears to be independently associated with an MDS prognosis and AML transformation, suggesting potential clinical relevance of altered splicing patterns in MDS.

Iterative sorting reveals CD133+ and CD133- melanoma cells as phenotypically distinct populations

Background

The heterogeneity and tumourigenicity of metastatic melanoma is attributed to a cancer stem cell model, with CD133 considered to be a cancer stem cell marker in melanoma as well as other tumours, but its role has remained controversial.

Methods

We iteratively sorted CD133+ and CD133- cells from 3 metastatic melanoma cell lines, and observed tumourigenicity and phenotypic characteristics over 7 generations of serial xeno-transplantation in NOD/SCID mice.

Results

We demonstrate that iterative sorting is required to make highly pure populations of CD133+ and CD133- cells from metastatic melanoma, and that these two populations have distinct characteristics not related to the cancer stem cell phenotype. In vitro, gene set enrichment analysis indicated CD133+ cells were related to a proliferative phenotype, whereas CD133- cells were of an invasive phenotype. However, in vivo, serial transplantation of CD133+ and CD133- tumours over 7 generations showed that both populations were equally able to initiate and propagate tumours. Despite this, both populations remained phenotypically distinct, with CD133- cells only able to express CD133 in vivo and not in vitro. Loss of CD133 from the surface of a CD133+ cell was observed in vitro and in vivo, however CD133- cells derived from CD133+ retained the CD133+ phenotype, even in the presence of signals from the tumour microenvironment.

Conclusion

We show for the first time the necessity of iterative sorting to isolate pure marker-positive and marker-negative populations for comparative studies, and present evidence that despite CD133+ and CD133- cells being equally tumourigenic, they display distinct phenotypic differences, suggesting CD133 may define a distinct lineage in melanoma.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2759-2) contains supplementary material, which is available to authorized users.

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis

Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK) localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases). Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%). The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36) was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. Such an automated and integrated methodology has potential application in the identification of prognostic classifiers based on tumour cell heterogeneity.