Markers and Reporters to Reveal the Hierarchy in Heterogeneous Cancer Stem Cells

A subpopulation within cancer, known as cancer stem cells (CSCs), regulates tumor initiation, chemoresistance, and metastasis. At a closer look, CSCs show functional heterogeneity and hierarchical organization. The present review is an attempt to assign marker profiles to define the functional heterogeneity and hierarchical organization of CSCs, based on a series of single-cell analyses. The evidences show that analogous to stem cell hierarchy, self-renewing Quiescent CSCs give rise to the Progenitor CSCs with limited proliferative capacity, and later to a Progenitor-like CSCs, which differentiates to Proliferating non-CSCs. Functionally, the CSCs can be tumor-initiating cells (TICs), drug-resistant CSCs, or metastasis initiating cells (MICs). Although there are certain marker profiles used to identify CSCs of different cancers, molecules like CD44, CD133, ALDH1A1, ABCG2, and pluripotency markers [Octamer binding transcriptional factor 4 (OCT4), SOX2, and NANOG] are used to mark CSCs of a wide range of cancers, ranging from hematological malignancies to solid tumors. Our analysis of the recent reports showed that a combination of these markers can demarcate the heterogeneous CSCs in solid tumors. Reporter constructs are widely used for easy identification and quantification of marker molecules. In this review, we discuss the suitability of reporters for the widely used CSC markers that can define the heterogeneous CSCs. Since the CSC-specific functions of CD44 and CD133 are regulated at the post-translational level, we do not recommend the reporters for these molecules for the detection of CSCs. A promoter-based reporter for ABCG2 may also be not relevant in CSCs, as the expression of the molecule in cancer is mainly regulated by promoter demethylation. In this context, a dual reporter consisting of one of the pluripotency markers and ALDH1A1 will be useful in marking the heterogeneous CSCs. This system can be easily adapted to high-throughput platforms to screen drugs for eliminating CSCs.

Variant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines

Matters Arising from: Sharma, A., Cao, E.Y., Kumar, V. et al. Longitudinal single-cell RNA sequencing of patient-derived primary cells reveals drug-induced infidelity in stem cell hierarchy. Nat Commun9, 4931 (2018). https://doi.org/10.1038/s41467-018-07261-3.In Sharma, A. et al. Nat Commun9, 4931 (2018) the authors employ longitudinal single-cell transcriptomic data from patient-derived primary and metastatic oral squamous cell carcinomas cell lines, to investigate possible divergent modes of chemo-resistance in tumor cell subpopulations. We integrated the analyses presented in the manuscript, by performing variant calling from scRNA-seq data via GATK Best Practices. As a main result, we show that an extremely high number of singlenucleotide variants representative of the identity of a specific patient is unexpectedly found in the scRNA-seq data of the cell line derived from a second patient, and vice versa. This finding likely suggests the existence of a sample swap, thus jeopardizing some of the translational conclusions of the article. Our results prove the efficacy of a joint analysis of the genotypic and transcriptomic identity of single-cells.

Robot technology identifies a Parkinsonian therapeutics repurpose to target stem cells of glioblastoma

Aim: Glioblastoma is a heterogeneous lethal disease, regulated by a stem-cell hierarchy and the neurotransmitter microenvironment. The identification of chemotherapies targeting individual cancer stem cells is a clinical need. Methodology: A robotic workstation was programmed to perform a drug concentration to cell-growth analysis on an in vitro model of glioblastoma stem cells (GSCs). Mode-of-action analysis of the selected top substance was performed with manual repetition assays and acquisition of further parameters. Results: We identified 22 therapeutic potential substances. Three suggested a repurpose potential of neurotransmitter signal-modulating agents to target GSCs, out of which the Parkinson's therapeutic trihexyphenidyl was most effective. Manual repetition assays and initial mode of action characterization revealed suppression of cell proliferation, cell cycle and survival. Conclusion: Anti-neurotransmitter signaling directed therapy has potential to target GSCs. We established a drug testing facility that is able to define a mid-scale chemo responsome of in vitro cancer models, possibly also suitable for other cell systems.

A unified simulation model for understanding the diversity of cancer evolution

Because cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

A unified simulation model for understanding the diversity of cancer evolution

ABSTRACTBecause cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

Pathobiology and genetics of adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is a rare malignancy with an incidence worldwide of 0.7–2.0 cases/million/year. Initial staging is the most important factor in determining prognosis. If diagnosed early, complete surgical resection +/− adjuvant treatment can lead to 5-year survival of up to 80%. However, often it is diagnosed late and in advanced disease, 5-year survival is <15% with a high recurrence rate even after radical surgery. The mainstay of adjuvant treatment is with the drug mitotane. Mitotane has a specific cytotoxic effect on steroidogenic cells of the adrenal cortex, but despite this, progression through treatment is common. Developments in genetic analysis in the form of next-generation sequencing, aided by bioinformatics, have enabled high-throughput molecular characterisation of these tumours. This, in addition to a better appreciation of the processes of physiological, homeostatic self-renewal of the adrenal cortex, has furthered our understanding of the pathogenesis of this malignancy. In this review, we have detailed the pathobiology and genetic alterations in adrenocortical carcinoma by integrating current understanding of homeostasis and self-renewal in the normal adrenal cortex with molecular profiling of tumours from recent genetic analyses. Improved understanding of the mechanisms involved in self-renewal and stem cell hierarchy in normal human adrenal cortices, together with the identification of cell populations likely to be co-opted by oncogenic mutations, will enable further progress in the definition of the molecular pathways involved in the pathogenesis of ACC. The combination of these advances eventually will lead to the development of novel, effective and personalised strategies to eradicate molecularly annotated ACCs.