Niche-dependent gene expression profile of intratumoral heterogeneous ovarian cancer stem cell populations

Detection of lung cancer metastasis from blood using L-MISC nanosensor: Targeting circulating metastatic cues for improved diagnosis

Metastatic lung cancers are considered one of the most clinically significant malignancies, comprising about 40% of deaths caused by cancers. Detection of lung cancer metastasis prior to symptomatic relapse is critical for timely diagnosis and clinical management. The onset of cancer metastasis is indicated by the manifestation of tumor-shed signatures from the primary tumor in peripheral circulation. A subset of this population, characterized as the metastasis-initiating stem cells, are capable of invasion, tumor initiation, and propagation of metastasis at distant sites. In this study, we have developed a SERS-functionalised L-MISC (Lung-Metastasis Initiating Stem Cells) nanosensor to accurately capture the trace levels of metastatic signatures directly from patient blood. We investigated the signatures of cancer stem cell enriched heterogenous population of primary and metastatic lung cancer cells to establish a metastatic profile unique to lung cancer. Multivariate statistical analyses revealed statistically significant differences in the molecular profiles of healthy, primary, and metastatic cell populations. The single-cell sensitivity of L-MISC nanosensor enabled a label-free detection of MISCs with high sensitivity and specificity. By employing a robust machine learning model, our diagnostic methodology can accurately detect metastatic lung cancer from not more than 5 μl of blood. A pilot validation of our study was carried out using clinical samples for the prediction of metastatic lung cancers resulting in 100% diagnostic sensitivity. The L-MISC nanosensor is a potential tool for highly rapid, non-invasive, and accurate diagnosis of lung cancer metastasis.

Endometriosis-associated Ovarian Clear Cell Carcinoma: A Special Entity?

Endometriosis is an estrogen-dependent disease, which serves as a precursor of ovarian cancer, especially clear cell carcinoma (OCCC) and endometrial carcinoma. Although micro-environmental factors such as oxidative stress, immune cell dysfunction, inflammation, steroid hormones, and stem cells required for malignant transformation have been found in endometriosis, the exact carcinogenic mechanism remains unclear. Recent research suggest that many putative driver genes and aberrant pathways including ARID1A mutations, PIK3CA mutations, MET activation, HNF-1β activation, and miRNAs dysfunction, play crucial roles in the malignant transformation of endometriosis to OCCC. The clinical features of OCCC are different from other histological types. Patients usually present with a large, unilateral pelvic mass, and occasionally have thromboembolic vascular complications. OCCC patients are easier to be resistant to chemotherapy, have a worse prognosis, and are usually difficult to treat. To improve the survival of OCCC patients, it is necessary to better understand its specific carcinogenic mechanism and explore new treatment strategy, including molecular target.

The hallmarks of ovarian cancer stem cells and niches: Exploring their harmonious interplay in therapy resistance

The concept of a "cancer stem cell" has evolved over the past decades, and research on cancer stem cell biology has entered into a stage of remarkable progress. Cancer stem cells are a major determining factor contributing to the establishment of phenotypic and functional intratumoral heterogeneity in synchronization with their surrounding "cancer stem cell niches." They serve as the driving force for cancer initiation, metastasis, and therapeutic resistance in various types of malignancies. In verity, reciprocal interplay between ovarian cancer stem cells and their niches involves a complex but ingeniously orchestrated tumor microenvironment within the intraperitoneal milieu and especially contribute to chemotherapy resistance in patients with advanced ovarian cancer. Herein, we review the principles of our current understanding of the biological features of ovarian cancer stem cells, focusing mainly on the precise mechanisms underlying acquired chemotherapy resistance. Furthermore, we highlight the specific roles of various cancer-associated stromal and immune cells in creating possible cancer stem cell niches that regulate ovarian cancer stemness.

Metabolic Plasticity in Ovarian Cancer Stem Cells

Ovarian Cancer is the fifth most common cancer in females and remains the most lethal gynecological malignancy as most patients are diagnosed at late stages of the disease. Despite initial responses to therapy, recurrence of chemo-resistant disease is common. The presence of residual cancer stem cells (CSCs) with the unique ability to adapt to several metabolic and signaling pathways represents a major challenge in developing novel targeted therapies. The objective of this study is to investigate the transcripts of putative ovarian cancer stem cell (OCSC) markers in correlation with transcripts of receptors, transporters, and enzymes of the energy generating metabolic pathways involved in high grade serous ovarian cancer (HGSOC). We conducted correlative analysis in data downloaded from The Cancer Genome Atlas (TCGA), studies of experimental OCSCs and their parental lines from Gene Expression Omnibus (GEO), and Cancer Cell Line Encyclopedia (CCLE). We found positive correlations between the transcripts of OCSC markers, specifically CD44, and glycolytic markers. TCGA datasets revealed that NOTCH1, CD133, CD44, CD24, and ALDH1A1, positively and significantly correlated with tricarboxylic acid cycle (TCA) enzymes. OVCAR3-OCSCs (cancer stem cells derived from a well-established epithelial ovarian cancer cell line) exhibited enrichment of the electron transport chain (ETC) mainly in complexes I, III, IV, and V, further supporting reliance on the oxidative phosphorylation (OXPHOS) phenotype. OVCAR3-OCSCs also exhibited significant increase in CD36, ACACA, SCD, and CPT1A, with CD44, CD133, and ALDH1A1 exhibiting positive correlations with lipid metabolic enzymes. TCGA data show positive correlations between OCSC markers and glutamine metabolism enzymes, whereas in OCSC experimental models of GSE64999, GSE28799, and CCLE, the number of positive and negative correlations observed was significantly lower and was different between model systems. Appropriate integration and validation of data model systems with those in patients' specimens is needed not only to bridge our knowledge gap of metabolic programing of OCSCs, but also in designing novel strategies to target the metabolic plasticity of dormant, resistant, and CSCs.

The Role of Intra-Tumoral Heterogeneity and Its Clinical Relevance in Epithelial Ovarian Cancer Recurrence and Metastasis

Epithelial ovarian cancer is the deadliest gynecologic cancer, due in large part to recurrent tumors. Recurrences tend to have metastasized, mainly in the peritoneal cavity and developed resistance to the first line chemotherapy. Key to the progression and ultimate lethality of ovarian cancer is the existence of extensive intra-tumoral heterogeneity (ITH). In this review, we describe the genetic and epigenetic changes that have been reported to give rise to different cell populations in ovarian cancer. We also describe at length the contributions made to heterogeneity by both linear and parallel models of clonal evolution and the existence of cancer stem cells. We dissect the key biological signals from the tumor microenvironment, both directly from other cell types in the vicinity and soluble or circulating factors. Finally, we discuss the impact of tumor heterogeneity on the choice of therapeutic approaches in the clinic. Variability in ovarian tumors remains a major barrier to effective therapy, but by leveraging future research into tumor heterogeneity, we may be able to overcome this barrier and provide more effective, personalized therapy to patients.

Presence and role of stem cells in ovarian cancer

Ovarian cancer is the deadliest gynecological malignancy. It is typically diagnosed at advanced stages of the disease, with metastatic sites disseminated widely within the abdominal cavity. Ovarian cancer treatment is challenging due to high disease recurrence and further complicated pursuant to acquired chemoresistance. Cancer stem cell (CSC) theory proposes that both tumor development and progression are driven by undifferentiated stem cells capable of self-renewal and tumor-initiation. The most recent evidence revealed that CSCs in terms of ovarian cancer are not only responsible for primary tumor growth, metastasis and relapse of disease, but also for the development of chemoresistance. As the elimination of this cell population is critical for increasing treatment success, a deeper understanding of ovarian CSCs pathobiology, including epithelial-mesenchymal transition, signaling pathways and tumor microenvironment, is needed. Finally, before introducing new therapeutic agents for ovarian cancer, targeting CSCs, accurate identification of different ovarian stem cell subpopulations, including the very small embryonic-like stem cells suggested as progenitors, is necessary. To these ends, reliable markers of ovarian CSCs should be identified. In this review, we present the current knowledge and a critical discussion concerning ovarian CSCs and their clinical role.

Reciprocal Reprogramming of Cancer Cells and Associated Mesenchymal Stem Cells in Gastric Cancer

The interactions of cancer stem cells (CSCs) within the tumor microenvironment (TME), contribute to the overall phenomenon of intratumoral heterogeneity, which also involve CSC interactions with noncancer stromal cells. Comprehensive understanding of the tumorigenesis process requires elucidating the coordinated gene expression between cancer and tumor stromal cells for each tumor. We show that human gastric cancer cells (GSC1) subvert gene expression and cytokine production by mesenchymal stem cells (GSC-MSC), thus promoting tumor progression. Using mixed composition of human tumor xenografts, organotypic culture, and in vitro assays, we demonstrate GSC1-mediated specific reprogramming of "naïve" MSC into specialized tumor associated MSC equipped with a tumor-promoting phenotype. Although paracrine effect of GSC-MSC or primed-MSC is sufficient to enable 2D growth of GSC1, cell-cell interaction with GSC-MSC is necessary for 3D growth and in vivo tumor formation. At both the transcriptional and at the protein level, RNA-Seq and proteome analyses, respectively, revealed increased R-spondin expression in primed-MSC, and paracrine and juxtacrine mediated elevation of Lgr5 expression in GSC1, suggesting GSC-MSC-mediated support of cancer stemness in GSC1. CSC properties are sustained in vivo through the interplay between GSC1 and GSC-MSC, activating the R-spondin/Lgr5 axis and WNT/β-catenin signaling pathway. β-Catenin+ cell clusters show β-catenin nuclear localization, indicating the activation of the WNT/β-catenin signaling pathway in these cells. The β-catenin+ cluster of cells overlap the Lgr5+ cells, however, not all Lgr5+ cells express β-catenin. A predominant means to sustain the CSC contribution to tumor progression appears to be subversion of MSC in the TME by cancer cells. Stem Cells 2018 Stem Cells 2019;37:176-189.

Transcriptomic but not genomic variability confers phenotype of breast cancer stem cells

Background

Breast cancer stem cells (BCSCs) are considered responsible for cancer relapse and drug resistance. Understanding the identity of BCSCs may open new avenues in breast cancer therapy. Although several discoveries have been made on BCSC characterization, the factors critical to the origination of BCSCs are largely unclear. This study aimed to determine whether genomic mutations contribute to the acquisition of cancer stem-like phenotype and to investigate the genetic and transcriptional features of BCSCs.

Methods

We detected potential BCSC phenotype-associated mutation hotspot regions by using whole-genome sequencing on parental cancer cells and derived serial-generation spheres in increasing order of BCSC frequency, and then performed target deep DNA sequencing at bulk-cell and single-cell levels. To identify the transcriptional program associated with BCSCs, bulk-cell and single-cell RNA sequencing was performed.

Results

By using whole-genome sequencing of bulk cells, potential BCSC phenotype-associated mutation hotspot regions were detected. Validation by target deep DNA sequencing, at both bulk-cell and single-cell levels, revealed no genetic changes specifically associated with BCSC phenotype. Moreover, single-cell RNA sequencing showed profound transcriptomic variability in cancer cells at the single-cell level that predicted BCSC features. Notably, this transcriptomic variability was enriched during the transcription of 74 genes, revealed as BCSC markers. Breast cancer patients with a high risk of relapse exhibited higher expression levels of these BCSC markers than those with a low risk of relapse, thereby highlighting the clinical significance of predicting breast cancer prognosis with these BCSC markers.

Conclusions

Transcriptomic variability, not genetic mutations, distinguishes BCSCs from non-BCSCs. The identified 74 BCSC markers have the potential of becoming novel targets for breast cancer therapy.

Electronic supplementary material

The online version of this article (10.1186/s40880-018-0326-8) contains supplementary material, which is available to authorized users.

Doxorubicin-provoked increase of mitotic activity and concomitant drain of G0-pool in therapy-resistant BE(2)-C neuroblastoma

In this study chemotherapy response in neuroblastoma (NB) was assessed for the first time in a transplantation model comprising non-malignant human embryonic microenvironment of pluripotent stem cell teratoma (PSCT) derived from diploid bona fide hESC. Two NB cell lines with known high-risk phenotypes; the multi-resistant BE(2)-C and the drug sensitive IMR-32, were transplanted to the PSCT model and the tumour growth was exposed to single or repeated treatments with doxorubicin, and thereafter evaluated for cell death, apoptosis, and proliferation. Dose dependent cytotoxic effects were observed, this way corroborating the experimental platform for this type of analysis. Notably, analysis of doxorubicin-resilient BE(2)-C growth in the PSCT model revealed an unexpected 1,5-fold increase in Ki67-index (p<0.05), indicating that non-cycling (G0) cells entered the cell cycle following the doxorubicin exposure. Support for this notion was obtained also in vitro. A pharmacologically relevant dose (1μM) resulted in a marked accumulation of Ki67 positive BE(2)-C cells (p<0.0001), as well as a >3-fold increase in active cell cycle (i.e. cells positive staining for PH3 together with incorporation of EdU) (p<0.01). Considering the clinical challenge for treating high-risk NB, the discovery of a therapy-provoked growth-stimulating effect in the multi-resistant and p53-mutated BE(2)-C cell line, but not in the drug-sensitive p53wt IMR-32 cell line, warrants further studies concerning generality and clinical significance of this new observation.

Theranostic barcoded nanoparticles for personalized cancer medicine

Personalized medicine promises to revolutionize cancer therapy by matching the most effective treatment to the individual patient. Using a nanoparticle-based system, we predict the therapeutic potency of anticancer medicines in a personalized manner. We carry out the diagnostic stage through a multidrug screen performed inside the tumour, extracting drug activity information with single cell sensitivity. By using 100 nm liposomes, loaded with various cancer drugs and corresponding synthetic DNA barcodes, we find a correlation between the cell viability and the drug it was exposed to, according to the matching barcodes. Based on this screen, we devise a treatment protocol for mice bearing triple-negative breast-cancer tumours, and its results confirm the diagnostic prediction. We show that the use of nanotechnology in cancer care is effective for generating personalized treatment protocols.

Determining the most effective treatment for each cancer patient is a key challenge in cancer therapy. In this article, the authors show, in a mouse model of breast cancer, that DNA barcoded nanoparticles can be used for pre-screening the efficacy of anticancer drugs.

Patient-derived xenografts as tools in pharmaceutical development

Successful drug development in oncology is grossly suboptimal, manifested by the very low percentage of new agents being developed that ultimately succeed in clinical approval. This poor success is in part due to the inability of standard cell-line xenograft models to accurately predict clinical success and to tailor chemotherapy specifically to a group of patients more likely to benefit from the therapy. Patient-derived xenografts (PDXs) maintain the histopathological architecture and molecular features of human tumors, and offer a potential solution to maximize drug development success and ultimately generate better outcomes for patients. Although imperfect in mimicking all aspects of human cancer, PDXs are a more predictable platform for preclinical evaluation of treatment effect and in selected cases can guide therapeutic decision making in the clinic. This article summarizes the current status of PDX models, challenges associated with modeling human cancer, and various approaches that have been applied to overcome these challenges and improve the clinical relevance of PDX cancer models.

Tumor Specific Recruitment and Reprogramming of Mesenchymal Stem Cells in Tumorigenesis

Non-neoplastic stromal cells harvested from patient tumors were identified as tumor-derived mesenchymal stem cells (MSCs) by their multipotential capacity to differentiate into adipocytes, osteoblasts, and chondrocytes and by the expression of MSC specific cell surface markers. These procedures yielded also epithelial cancer cells and their counterpart MSC from gastric carcinoma (GSC1) and lung carcinoma (LC2). While the LC2 cancer cell growth is independent of their LC-MSC, the GSC1 cancer cell growth is critically dependent on the presence of their counterpart GSC-MSC or their conditioned medium (CM). The fact that none of the various other tumor-derived MSCs was able to restore the specific effect of GSC-MSC on GSC1 cancer cell growth suggests specificity of tumor-derived MSC, which are specifically recruited and "educated"/reprogrammed by the cancer cells to support tumor growth. Using cytokine array analysis, we were able to demonstrate that GSC1 cell growth is mediated through hepatocyte growth factor (HGF)/c-MET signaling pathway which is activated exclusively by HGF secreted from GSC-MSC. An innovative approach demonstrates GSC1-mediated specific tropism of "naïve" MSC from the adjacent tissue in a tumor specific manner to support tumor progression. The results suggest that specific tumor tropic "naïve" MSC are reprogrammed in a tumor-specific manner to support gastric tumor progression. Understanding the mechanisms involved in the interactions of the tumor cancer cells and tumor-derived MSC will constitute the basis for developing multimodal anticancer therapeutic strategies that will also take into account the specific tumor tropism properties of MSC and their reprogramming.

Molecular changes in endometriosis-associated ovarian clear cell carcinoma

BACKGROUND

Endometriosis is frequently associated with and thought of having propensity to develop into ovarian clear cell carcinoma (OCCC), although the molecular transformation mechanism is not completely understood.

METHODS

We employed immunohistochemical (IHC) staining for marker expression along the potential progression continuum. Expression profiling of microdissected endometriotic and OCCC cells from patient-matched formalin-fixed, paraffin-embedded samples was performed to explore the carcinogenic pathways. Function of novel biomarkers was confirmed by knockdown experiments.

RESULTS

PTEN was significantly lost in both endometriosis and invasive tumour tissues, while oestrogen receptor (ER) expression was lost in OCCC relative to endometriosis. XRCC5, PTCH2, eEF1A2 and PPP1R14B were significantly overexpressed in OCCC and associated endometriosis, but not in benign endometriosis (p ⩽ 0.004). Knockdown experiments with XRCC5 and PTCH2 in a clear cell cancer cell line resulted in significant growth inhibition. There was also significant silencing of a panel of target genes with histone H3 lysine 27 trimethylation, a signature of polycomb chromatin-remodelling complex in OCCC. IHC confirmed the loss of expression of one such polycomb target gene, the serous ovarian cancer lineage marker Wilms' tumour protein 1 (WT1) in OCCC, while endometriotic tissues showed significant co-expression of WT1 and ER.

CONCLUSIONS

Loss of PTEN expression is proposed as an early and permissive event in endometriosis development, while the loss of ER and polycomb-mediated transcriptional reprogramming for pluripotency may play an important role in the ultimate transformation process. Our study provides new evidence to redefine the pathogenic programme for lineage-specific transformation of endometriosis to OCCC.

BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis

BioXpress is a gene expression and cancer association database in which the expression levels are mapped to genes using RNA-seq data obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, Expression Atlas and publications. The BioXpress database includes expression data from 64 cancer types, 6361 patients and 17 469 genes with 9513 of the genes displaying differential expression between tumor and normal samples. In addition to data directly retrieved from RNA-seq data repositories, manual biocuration of publications supplements the available cancer association annotations in the database. All cancer types are mapped to Disease Ontology terms to facilitate a uniform pan-cancer analysis. The BioXpress database is easily searched using HUGO Gene Nomenclature Committee gene symbol, UniProtKB/RefSeq accession or, alternatively, can be queried by cancer type with specified significance filters. This interface along with availability of pre-computed downloadable files containing differentially expressed genes in multiple cancers enables straightforward retrieval and display of a broad set of cancer-related genes.

Database URL:http://hive.biochemistry.gwu.edu/tools/bioxpress

Experimental teratoma: at the crossroad of fetal- and onco-development

Xenografting is the so far only available in vivo model for assessing pluripotency of human stem cells. This review describes known biological features of experimental teratoma from human pluripotent stem cells. We focus on the dual nature mimicking both normal and abnormal development, and propose this model system to be particularly interesting for investigations of the relationship between developmentally controlled differentiation and neoplasia of embryonic origin. In resemblance to the wide range of clinical teratomas, pluripotent stem cell (PSC) induced teratoma (PSCT) typically shows a mixture of developing tissues in randomly distributed compartments. The combined literature suggests that for teratomas derived from human diploid bona fide PSC the embryonic development in the separate tissue-niches can show a controlled differentiation into organoid patterns closely mimicking early development. In the experimental situation such PSCT human homologous in vivo tissue-niches have been shown to provide also matching microenvironment for a micrometastatic colonization and outgrowth of embryonic tumors transplanted directly from patients. Single or small clusters of normal and neoplastic cells can easily be visualized together in microscope-based imaging systems, enabling multi-parameter detection of in the scans of tissue slides/specimens.