Regulatory networks define phenotypic classes of human stem cell lines

TASOR expression in naive embryonic stem cells safeguards their developmental potential

The seamless transition through stages of pluripotency relies on a balance between transcription factor networks and epigenetic mechanisms. Here, we reveal the crucial role of the transgene activation suppressor (TASOR), a component of the human silencing hub (HUSH) complex, in maintaining cell viability during the transition from naive to primed pluripotency. TASOR loss in naive pluripotent stem cells (PSCs) triggers replication stress, disrupts H3K9me3 heterochromatin, and impairs silencing of LINE-1 (L1) transposable elements, with more severe effects in primed PSCs. Notably, the survival of Tasor knockout PSCs during this transition can be restored by inhibiting caspase or deleting the mitochondrial antiviral signaling protein (MAVS). This suggests that unscheduled L1 expression activates an innate immune response, leading to cell death specifically in cells exiting naive pluripotency. Our findings highlight the importance of epigenetic programs established in naive pluripotency for normal development.

Parallel genome-scale CRISPR-Cas9 screens uncouple human pluripotent stem cell identity versus fitness

Pluripotent stem cells have remarkable self-renewal capacity: the ability to proliferate indefinitely while maintaining the pluripotent identity essential for their ability to differentiate into almost any cell type in the body. To investigate the interplay between these two aspects of self-renewal, we perform four parallel genome-scale CRISPR-Cas9 loss-of-function screens interrogating stem cell fitness in hPSCs and the dissolution of primed pluripotent identity during early differentiation. These screens distinguish genes with distinct roles in pluripotency regulation, including mitochondrial and metabolism regulators crucial for stem cell fitness, and chromatin regulators that control pluripotent identity during early differentiation. We further identify a core set of genes controlling both stem cell fitness and pluripotent identity, including a network of chromatin factors. Here, unbiased screening and comparative analyses disentangle two interconnected aspects of pluripotency, provide a valuable resource for exploring pluripotent stem cell identity versus cell fitness, and offer a framework for categorizing gene function.

Advancing Parkinson's disease treatment: cell replacement therapy with neurons derived from pluripotent stem cells

The motor symptoms of Parkinson's disease (PD) are caused by the progressive loss of dopamine neurons from the substantia nigra. There are currently no treatments that can slow or reverse the neurodegeneration. To restore the lost neurons, international groups have initiated clinical trials using human embryonic or induced pluripotent stem cells (PSCs) to derive dopamine neuron precursors that are used as transplants to replace the lost neurons. Proof-of-principle experiments in the 1980s and 1990s showed that grafts of fetal ventral mesencephalon, which contains the precursors of the substantial nigra, could, under rare circumstances, reverse symptoms of the disease. Improvements in PSC technology and genomics have inspired researchers to design clinical trials using PSC-derived dopamine neuron precursors as cell replacement therapy for PD. We focus here on 4 such first-in-human clinical trials that have begun in the US, Europe, and Japan. We provide an overview of the sources of PSCs and the methods used to generate cells for transplantation. We discuss pros and cons of strategies for allogeneic, immune-matched, and autologous approaches and novel methods for overcoming rejection by the immune system. We consider challenges for safety and efficacy of the cells for durable engraftment, focusing on the genomics-based quality control methods to assure that the cells will not become cancerous. Finally, since clinical trials like these have never been undertaken before, we comment on the value of cooperation among rivals to contribute to advancements that will finally provide relief for the millions suffering from the symptoms of PD.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

The Epigenetic Modifiers HDAC2 and HDAC7 Inversely Associate with Cancer Stemness and Immunity in Solid Tumors

Dysregulation of histone deacetylases (HDACs) is closely associated with cancer development and progression. Here, we comprehensively analyzed the association between all HDAC family members and several clinicopathological and molecular traits of solid tumors across 22 distinct tumor types, focusing primarily on cancer stemness and immunity. To this end, we used publicly available TCGA data and several bioinformatic tools (i.e., GEPIA2, TISIDB, GSCA, Enrichr, GSEA). Our analyses revealed that class I and class II HDAC proteins are associated with distinct cancer phenotypes. The transcriptomic profiling indicated that class I HDAC members, including HDAC2, are positively associated with cancer stemness, while class IIA HDAC proteins, represented by HDAC7, show a negative correlation to cancer stem cell-like phenotypes in solid tumors. In contrast to tumors with high amounts of HDAC7 proteins, the transcriptome signatures of HDAC2-overexpressing cancers are significantly enriched with biological terms previously determined as stemness-associated genes. Moreover, high HDAC2-expressing tumors are depleted with immune-related processes, and HDAC2 expression correlates with tumor immunosuppressive microenvironments. On the contrary, HDAC7 upregulation is significantly associated with enhanced immune responses, followed by enriched infiltration of CD4+ and CD8+ T cells. This is the first comprehensive report demonstrating robust and versatile associations between specific HDAC family members, cancer dedifferentiation, and anti-tumor immune statuses in solid tumors.

Computational single-cell methods for predicting cancer risk

Despite recent biotechnological breakthroughs, cancer risk prediction remains a formidable computational and experimental challenge. Addressing it is critical in order to improve prevention, early detection and survival rates. Here, I briefly summarize some key emerging theoretical and computational challenges as well as recent computational advances that promise to help realize the goals of cancer-risk prediction. The focus is on computational strategies based on single-cell data, in particular on bottom-up network modeling approaches that aim to estimate cancer stemness and dedifferentiation at single-cell resolution from a systems-biological perspective. I will describe two promising methods, a tissue and cell-lineage independent one based on the concept of diffusion network entropy, and a tissue and cell-lineage specific one that uses transcription factor regulons. Application of these tools to single-cell and single-nucleus RNA-seq data from stages prior to invasive cancer reveal that they can successfully delineate the heterogeneous inter-cellular cancer-risk landscape, identifying those cells that are more likely to turn cancerous. Bottom-up systems biological modeling of single-cell omic data is a novel computational analysis paradigm that promises to facilitate the development of preventive, early detection and cancer-risk prediction strategies.

Cell-type and dynamic state govern genetic regulation of gene expression in heterogeneous differentiating cultures

Identifying the molecular effects of human genetic variation across cellular contexts is crucial for understanding the mechanisms underlying disease-associated loci, yet many cell-types and developmental stages remain underexplored. Here we harnessed the potential of heterogeneous differentiating cultures ( HDCs ), an in vitro system in which pluripotent cells asynchronously differentiate into a broad spectrum of cell-types. We generated HDCs for 53 human donors and collected single-cell RNA-sequencing data from over 900,000 cells. We identified expression quantitative trait loci in 29 cell-types and characterized regulatory dynamics across diverse differentiation trajectories. This revealed novel regulatory variants for genes involved in key developmental and disease-related processes while replicating known effects from primary tissues, and dynamic regulatory effects associated with a range of complex traits.

Metabologenomic characterization uncovers a clinically aggressive IDH mutant glioma subtype

Mutations in the pivotal metabolic isocitrate dehydrogenase (IDH) enzymes are recognized to drive the molecular footprint of diffuse gliomas, and patients with IDH mutant gliomas have overall favorable outcomes compared to patients with IDH wild-type tumors. However, survival still varies widely among patients with IDH mutated tumors. Here, we aimed to characterize molecular signatures that explain the range of IDH mutant gliomas. By integrating matched epigenome-wide methylome, transcriptome, and global metabolome data in 154 patients with gliomas, we identified a group of IDH mutant gliomas with globally altered metabolism that resembled IDH wild-type tumors. IDH-mutant gliomas with altered metabolism have significantly shorter overall survival from their IDH mutant counterparts that is not fully accounted for by recognized molecular prognostic markers of CDKN2A/B loss and glioma CpG Island Methylator Phenotype (GCIMP) status. IDH-mutant tumors with dysregulated metabolism harbored distinct epigenetic alterations that converged to drive proliferative and stem-like transcriptional profiles, providing a window to target novel dependencies in gliomas.

Mapping single-cell developmental potential in health and disease with interpretable deep learning

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cell fate in developmental systems. However, identifying the molecular hallmarks of potency - the capacity of a cell to differentiate into other cell types - has remained challenging. Here, we introduce CytoTRACE 2, an interpretable deep learning framework for characterizing potency and differentiation states on an absolute scale from scRNA-seq data. Across 31 human and mouse scRNA-seq datasets encompassing 28 tissue types, CytoTRACE 2 outperformed existing methods for recovering experimentally determined potency levels and differentiation states covering the entire range of cellular ontogeny. Moreover, it reconstructed the temporal hierarchy of mouse embryogenesis across 62 timepoints; identified pan-tissue expression programs that discriminate major potency levels; and facilitated discovery of cellular phenotypes in cancer linked to survival and immunotherapy resistance. Our results illuminate a fundamental feature of cell biology and provide a broadly applicable platform for delineating single-cell differentiation landscapes in health and disease.

Applications of Machine Learning (ML) and Mathematical Modeling (MM) in Healthcare with Special Focus on Cancer Prognosis and Anticancer Therapy: Current Status and Challenges

The use of data-driven high-throughput analytical techniques, which has given rise to computational oncology, is undisputed. The widespread use of machine learning (ML) and mathematical modeling (MM)-based techniques is widely acknowledged. These two approaches have fueled the advancement in cancer research and eventually led to the uptake of telemedicine in cancer care. For diagnostic, prognostic, and treatment purposes concerning different types of cancer research, vast databases of varied information with manifold dimensions are required, and indeed, all this information can only be managed by an automated system developed utilizing ML and MM. In addition, MM is being used to probe the relationship between the pharmacokinetics and pharmacodynamics (PK/PD interactions) of anti-cancer substances to improve cancer treatment, and also to refine the quality of existing treatment models by being incorporated at all steps of research and development related to cancer and in routine patient care. This review will serve as a consolidation of the advancement and benefits of ML and MM techniques with a special focus on the area of cancer prognosis and anticancer therapy, leading to the identification of challenges (data quantity, ethical consideration, and data privacy) which are yet to be fully addressed in current studies.

Epithelial and Mesenchymal-like Pancreatic Cancer Cells Exhibit Different Stem Cell Phenotypes Associated with Different Metastatic Propensities

Pancreatic ductal adenocarcinoma (PDAC) is mostly diagnosed at advanced or even metastasized stages, limiting the prognoses of patients. Metastasis requires high tumor cell plasticity, implying phenotypic switching in response to changing environments. Here, epithelial-mesenchymal transition (EMT), being associated with an increase in cancer stem cell (CSC) properties, and its reversion are important. Since it is poorly understood whether different CSC phenotypes exist along the EMT axis and how these impact malignancy-associated properties, we aimed to characterize CSC populations of epithelial and mesenchymal-like PDAC cells. Single-cell cloning revealed CSC (Holoclone) and non-CSC (Paraclone) clones from the PDAC cell lines Panc1 and Panc89. The Panc1 Holoclone cells showed a mesenchymal-like phenotype, dominated by a high expression of the stemness marker Nestin, while the Panc89 Holoclone cells exhibited a SOX2-dominated epithelial phenotype. The Panc89 Holoclone cells showed enhanced cell growth and a self-renewal capacity but slow cluster-like invasion. Contrarily, the Panc1 Holoclone cells showed slower cell growth and self-renewal ability but were highly invasive. Moreover, cell variants differentially responded to chemotherapy. In vivo, the Panc1 and Panc89 cell variants significantly differed regarding the number and size of metastases, as well as organ manifestation, leading to different survival outcomes. Overall, these data support the existence of different CSC phenotypes along the EMT axis in PDAC, manifesting different metastatic propensities.

Neurite Outgrowth and Gene Expression Profile Correlate with Efficacy of Human Induced Pluripotent Stem Cell-Derived Dopamine Neuron Grafts

Transplantation of human induced pluripotent stem cell-derived dopaminergic (iPSC-DA) neurons is a promising therapeutic strategy for Parkinson's disease (PD). To assess optimal cell characteristics and reproducibility, we evaluated the efficacy of iPSC-DA neuron precursors from two individuals with sporadic PD by transplantation into a hemiparkinsonian rat model after differentiation for either 18 (d18) or 25 days (d25). We found similar graft size and dopamine (DA) neuron content in both groups, but only the d18 cells resulted in recovery of motor impairments. In contrast, we report that d25 grafts survived equally as well and produced grafts rich in tyrosine hydroxylase-positive neurons, but were incapable of alleviating any motor deficits. We identified the mechanism of action as the extent of neurite outgrowth into the host brain, with d18 grafts supporting significantly more neurite outgrowth than nonfunctional d25 grafts. RNAseq analysis of the cell preparation suggests that graft efficacy may be enhanced by repression of differentiation-associated genes by REST, defining the optimal predifferentiation state for transplantation. This study demonstrates for the first time that DA neuron grafts can survive well in vivo while completely lacking the capacity to induce recovery from motor dysfunction. In contrast to other recent studies, we demonstrate that neurite outgrowth is the key factor determining graft efficacy and our gene expression profiling revealed characteristics of the cells that may predict their efficacy. These data have implication for the generation of DA neuron grafts for clinical application.

Modeling Global Genomic Instability in Chronic Myeloid Leukemia (CML) Using Patient-Derived Induced Pluripotent Stem Cells (iPSCs)

METHODS

We used a patient-specific induced pluripotent stem cell (iPSC) line treated with the mutagenic agent N-ethyl-N-nitrosourea (ENU). Genomic instability was validated using γ-H2AX and micronuclei assays and CGH array for genomic events.

RESULTS

An increased number of progenitors (x5-Fold), which proliferated in liquid cultures with a blast cell morphology, was observed in the mutagenized condition as compared to the unmutagenized one. CGH array performed for both conditions in two different time points reveals several cancer genes in the ENU-treated condition, some known to be altered in leukemia (BLM, IKZF1, NCOA2, ALK, EP300, ERG, MKL1, PHF6 and TET1). Transcriptome GEO-dataset GSE4170 allowed us to associate 125 of 249 of the aberrations that we detected in CML-iPSC with the CML progression genes already described during progression from chronic and AP to BC. Among these candidates, eleven of them have been described in CML and related to tyrosine kinase inhibitor resistance and genomic instability.

CONCLUSIONS

These results demonstrated that we have generated, for the first time to our knowledge, an in vitro genetic instability model, reproducing genomic events described in patients with BC.

Vascularization of cutaneous wounds by stem cells

Differentiated skin cells have limited self-renewal capacity; thus, the application of stem/progenitor cells, adult or induced stem cells, has attracted much attention for wound healing applications. Upon skin injury, vascularization, known as a highly dynamic process, occurs with the contribution of cells, the extracellular matrix, and relevant growth factors. Considering the importance of this process in tissue regeneration, several strategies have been proposed to enhance angiogenesis and accelerate wound healing. Previous studies report the effectiveness of stem/progenitor cells in skin wound healing by facilitating the vascularization process. This chapter reviews and highlights some of the key and recent investigations on application of stem/progenitor cells to induce skin revascularization after trauma.

Integration of Stemness Gene Signatures Reveals Core Functional Modules of Stem Cells and Potential Novel Stemness Genes

Stem cells encompass a variety of different cell types which converge on the dual capacity to self-renew and differentiate into one or more lineages. These characteristic features are key for the involvement of stem cells in crucial biological processes such as development and ageing. To decipher their underlying genetic substrate, it is important to identify so-called stemness genes that are common to different stem cell types and are consistently identified across different studies. In this meta-analysis, 21 individual stemness signatures for humans and another 21 for mice, obtained from a variety of stem cell types and experimental techniques, were compared. Although we observed biological and experimental variability, a highly significant overlap between gene signatures was identified. This enabled us to define integrated stemness signatures (ISSs) comprised of genes frequently occurring among individual stemness signatures. Such integrated signatures help to exclude false positives that can compromise individual studies and can provide a more robust basis for investigation. To gain further insights into the relevance of ISSs, their genes were functionally annotated and connected within a molecular interaction network. Most importantly, the present analysis points to the potential roles of several less well-studied genes in stemness and thus provides promising candidates for further experimental validation.

H3.3 contributes to chromatin accessibility and transcription factor binding at promoter-proximal regulatory elements in embryonic stem cells

BACKGROUND

The histone variant H3.3 is enriched at active regulatory elements such as promoters and enhancers in mammalian genomes. These regions are highly accessible, creating an environment that is permissive to transcription factor binding and the recruitment of transcriptional coactivators that establish a unique chromatin post-translational landscape. How H3.3 contributes to the establishment and function of chromatin states at these regions is poorly understood.

RESULTS

We perform genomic analyses of features associated with active promoter chromatin in mouse embryonic stem cells (ESCs) and find evidence of subtle yet widespread promoter dysregulation in the absence of H3.3. Loss of H3.3 results in reduced chromatin accessibility and transcription factor (TF) binding at promoters of expressed genes in ESCs. Likewise, enrichment of the transcriptional coactivator p300 and downstream histone H3 acetylation at lysine 27 (H3K27ac) is reduced at promoters in the absence of H3.3, along with reduced enrichment of the acetyl lysine reader BRD4. Despite the observed chromatin dysregulation, H3.3 KO ESCs maintain transcription from ESC-specific genes. However, upon undirected differentiation, H3.3 KO cells retain footprinting of ESC-specific TF motifs and fail to generate footprints of lineage-specific TF motifs, in line with their diminished capacity to differentiate.

CONCLUSIONS

H3.3 facilitates DNA accessibility, transcription factor binding, and histone post-translational modification at active promoters. While H3.3 is not required for maintaining transcription in ESCs, it does promote de novo transcription factor binding which may contribute to the dysregulation of cellular differentiation in the absence of H3.3.

Dynamic regulatory module networks for inference of cell type-specific transcriptional networks

Changes in transcriptional regulatory networks can significantly alter cell fate. To gain insight into transcriptional dynamics, several studies have profiled bulk multi-omic data sets with parallel transcriptomic and epigenomic measurements at different stages of a developmental process. However, integrating these data to infer cell type-specific regulatory networks is a major challenge. We present dynamic regulatory module networks (DRMNs), a novel approach to infer cell type-specific cis-regulatory networks and their dynamics. DRMN integrates expression, chromatin state, and accessibility to predict cis-regulators of context-specific expression, where context can be cell type, developmental stage, or time point, and uses multitask learning to capture network dynamics across linearly and hierarchically related contexts. We applied DRMNs to study regulatory network dynamics in three developmental processes, each showing different temporal relationships and measuring a different combination of regulatory genomic data sets: cellular reprogramming, liver dedifferentiation, and forward differentiation. DRMN identified known and novel regulators driving cell type-specific expression patterns, showing its broad applicability to examine dynamics of gene regulatory networks from linearly and hierarchically related multi-omic data sets.

Integrative molecular and clinical profiling of acral melanoma links focal amplification of 22q11.21 to metastasis

Acral melanoma, the most common melanoma subtype among non-White individuals, is associated with poor prognosis. However, its key molecular drivers remain obscure. Here, we perform integrative genomic and clinical profiling of acral melanomas from 104 patients treated in North America (n = 37) or China (n = 67). We find that recurrent, late-arising focal amplifications of cytoband 22q11.21 are a leading determinant of inferior survival, strongly associated with metastasis, and linked to downregulation of immunomodulatory genes associated with response to immune checkpoint blockade. Unexpectedly, LZTR1 - a known tumor suppressor in other cancers - is a key candidate oncogene in this cytoband. Silencing of LZTR1 in melanoma cell lines causes apoptotic cell death independent of major hotspot mutations or melanoma subtypes. Conversely, overexpression of LZTR1 in normal human melanocytes initiates processes associated with metastasis, including anchorage-independent growth, formation of spheroids, and an increase in MAPK and SRC activities. Our results provide insights into the etiology of acral melanoma and implicate LZTR1 as a key tumor promoter and therapeutic target.

The association between bromodomain (BrD) proteins and cancer stemness in different solid tumor types

Cancer stemness, which covers the stem cell‐like molecular traits of cancer cells, is essential for tumor development, progression and relapse. Both transcriptional and epigenetic aberrations are essentially connected with cancer stemness. The engagement of bromodomain (BrD) proteins—a family of epigenetic factors—has been presented in the pathogenesis of several tumor types, although their association with cancer stemness remains largely unknown. Here, we harnessed TCGA and GEO databases and used several bioinformatic tools (ie, Oncomine, PrognoScan, GEPIA2, TIMER2.0, TISIDB, GSEA, R2 platform) to characterize the association between the BrD family members' expression and cancer stemness in solid tumors. Our results demonstrate that significant upregulation of ATAD2 and SMARCA4, and downregulation of SMARCA2 is consistently associated with enriched cancer stem cell‐like phenotype, respectively. Especially, higher‐grade tumors that display stem cell‐like properties overexpress ATAD2. In contrast to most BrD members, the gene expression profiles of ATAD2^HIGH expressing tumors are strongly enriched with known markers of stem cells and with specific targets for c‐Myc transcription factor. For other BrD proteins, the association with cancer de‐differentiation status is rather tumor‐specific. Our results demonstrate for the first time the relation between distinct BrD family proteins and cancer stemness across 27 solid tumor types. Specifically, our approach allowed us to discover a robust association of high ATAD2 expression with cancer stemness and reveal its' versatility in tumors. As bromodomains are attractive targets from a chemical and structural perspective, we propose ATAD2 as a novel druggable target for de‐differentiated tumors, especially those overexpressing MYC.

Hyperoxia/Hypoxia Exposure Primes a Sustained Pro-Inflammatory Profile of Preterm Infant Macrophages Upon LPS Stimulation

Preterm infants are highly susceptible to sustained lung inflammation, which may be triggered by exposure to multiple environmental cues such as supplemental oxygen (O₂) and infections. We hypothesized that dysregulated macrophage (MФ) activation is a key feature leading to inflammation-mediated development of bronchopulmonary dysplasia (BPD) in preterm infants. Therefore, we aimed to determine age-dependent differences in immune responses of monocyte-derived MФ comparing cord blood samples derived from preterm (n=14) and term (n=19) infants as well as peripheral blood samples from healthy adults (n=17) after lipopolysaccharide (LPS) exposure. Compared to term and adult MФ, LPS-stimulated preterm MФ showed an enhanced and sustained pro-inflammatory immune response determined by transcriptome analysis, cytokine release inducing a RORC upregulation due to T cell polarization of neonatal T cells, and TLR4 surface expression. In addition, a double-hit model was developed to study pulmonary relevant exposure factors by priming MФ with hyperoxia (O₂ = 65%) or hypoxia (O₂ = 3%) followed by lipopolysaccharide (LPS, 100ng/ml). When primed by 65% O₂, subsequent LPS stimulation in preterm MФ led to an exaggerated pro-inflammatory response (e.g. increased HLA-DR expression and cytokine release) compared to LPS stimulation alone. Both, exposure to 65% or 3% O₂ together with subsequent LPS stimulation, resulted in an exaggerated pro-inflammatory response of preterm MФ determined by transcriptome analysis. Downregulation of two major transcriptional factors, early growth response gene (Egr)-2 and growth factor independence 1 (Gfi1), were identified to play a role in the exaggerated pro-inflammatory response of preterm MФ to LPS insult after priming with 65% or 3% O₂. Preterm MФ responses to LPS and hyperoxia/hypoxia suggest their involvement in excessive inflammation due to age-dependent differences, potentially mediated by downregulation of Egr2 and Gfi1 in the developing lung.

Cell Therapy: Types, Regulation, and Clinical Benefits

Cell therapy practices date back to the 19th century and continue to expand on investigational and investment grounds. Cell therapy includes stem cell- and non-stem cell-based, unicellular and multicellular therapies, with different immunophenotypic profiles, isolation techniques, mechanisms of action, and regulatory levels. Following the steps of their predecessor cell therapies that have become established or commercialized, investigational and premarket approval-exempt cell therapies continue to provide patients with promising therapeutic benefits in different disease areas. In this review article, we delineate the vast types of cell therapy, including stem cell-based and non-stem cell-based cell therapies, and create the first-in-literature compilation of the different "multicellular" therapies used in clinical settings. Besides providing the nuts and bolts of FDA policies regulating their use, we discuss the benefits of cell therapies reported in 3 therapeutic areas-regenerative medicine, immune diseases, and cancer. Finally, we contemplate the recent attention shift toward combined therapy approaches, highlighting the factors that render multicellular therapies a more attractive option than their unicellular counterparts.

Longitudinal Analysis of Human Pancreatic Adenocarcinoma Development Reveals Transient Gene Expression Signatures

Previous transcriptome studies of human pancreatic ductal adenocarcinoma (PDAC) compare non-cancerous pancreatic intraepithelial neoplasias (PanIN) with late-stage PDAC obtained from different patients, thus have limited ability to discern network dynamics that contribute to the disease progression. We demonstrated previously that the 10-22 cell line, an induced pluripotent stem cell-like line reprogrammed from late-stage human PDAC cells, recapitulated the progression from PanINs to PDAC upon transplantation into NOD/LtSz-scid/IL2R-gamma^null mice. Herein, we investigated the transition from precursor to PDAC using the isogenic model. We analyzed transcriptomes of genetically tagged 10-22 cells progressing from PanINs to PDAC in mice and validated the results using The Cancer Genome Atlas PDAC dataset, human clinical PanIN and PDAC tissues, and a well-established murine PDAC model. We functionally studied candidate proteins using human normal (H6C7) and cancerous (Miapaca2, Aspc1) pancreatic ductal epithelial cell lines. 10-22 cell-derived PDAC displayed the molecular signature of clinical human PDAC. Expression changes of many genes were transient during PDAC progression. Pathways for extracellular vesicle transport and neuronal cell differentiation were derepressed in the progression of PanINs to PDAC. HMG-box transcription factor 1 (HBP1) and BTB domain and CNC homolog 1 (BACH1) were implicated in regulating dynamically expressed genes during PDAC progression, and their expressions inversely correlated with PDAC patients' prognosis. Ectopic expression of HBP1 increased proliferation and migration of normal and cancerous pancreatic cells, indicating that HBP1 may confer the cell dissemination capacity in early PDAC progression. This unique longitudinal analysis provides insights into networks underlying human PDAC progression and pathogenesis. IMPLICATIONS: Manipulation of HBP1, BACH1, and RUN3 networks during PDAC progression can be harnessed to develop new targets for treating PDAC.

Positive correlation between transcriptomic stemness and PI3K/AKT/mTOR signaling scores in breast cancer, and a counterintuitive relationship with PIK3CA genotype

A PI3Kα-selective inhibitor has recently been approved for use in breast tumors harboring mutations in PIK3CA, the gene encoding p110α. Preclinical studies have suggested that the PI3K/AKT/mTOR signaling pathway influences stemness, a dedifferentiation-related cellular phenotype associated with aggressive cancer. However, to date, no direct evidence for such a correlation has been demonstrated in human tumors. In two independent human breast cancer cohorts, encompassing nearly 3,000 tumor samples, transcriptional footprint-based analysis uncovered a positive linear association between transcriptionally-inferred PI3K/AKT/mTOR signaling scores and stemness scores. Unexpectedly, stratification of tumors according to PIK3CA genotype revealed a "biphasic" relationship of mutant PIK3CA allele dosage with these scores. Relative to tumor samples without PIK3CA mutations, the presence of a single copy of a hotspot PIK3CA variant was associated with lower PI3K/AKT/mTOR signaling and stemness scores, whereas the presence of multiple copies of PIK3CA hotspot mutations correlated with higher PI3K/AKT/mTOR signaling and stemness scores. This observation was recapitulated in a human cell model of heterozygous and homozygous PIK3CAH1047R expression. Collectively, our analysis (1) provides evidence for a signaling strength-dependent PI3K-stemness relationship in human breast cancer; (2) supports evaluation of the potential benefit of patient stratification based on a combination of conventional PI3K pathway genetic information with transcriptomic indices of PI3K signaling activation.

Growth of Biological Complexity from Prokaryotes to Hominids Reflected in the Human Genome

The growth of complexity in evolution is a most intriguing phenomenon. Using gene phylostratigraphy, we showed this growth (as reflected in regulatory mechanisms) in the human genome, tracing the path from prokaryotes to hominids. Generally, the different regulatory gene families expanded at different times, yet only up to the Euteleostomi (bony vertebrates). The only exception was the expansion of transcription factors (TF) in placentals; however, we argue that this was not related to increase in general complexity. Surprisingly, although TF originated in the Prokaryota while chromatin appeared only in the Eukaryota, the expansion of epigenetic factors predated the expansion of TF. Signaling receptors, tumor suppressors, oncogenes, and aging- and disease-associated genes (indicating vulnerabilities in terms of complex organization and strongly enrichment in regulatory genes) also expanded only up to the Euteleostomi. The complexity-related gene properties (protein size, number of alternative splicing mRNA, length of untranslated mRNA, number of biological processes per gene, number of disordered regions in a protein, and density of TF–TF interactions) rose in multicellular organisms and declined after the Euteleostomi, and possibly earlier. At the same time, the speed of protein sequence evolution sharply increased in the genes that originated after the Euteleostomi. Thus, several lines of evidence indicate that molecular mechanisms of complexity growth were changing with time, and in the phyletic lineage leading to humans, the most salient shift occurred after the basic vertebrate body plan was fixed with bony skeleton. The obtained results can be useful for evolutionary medicine.

Redox Homeostasis and Regulation in Pluripotent Stem Cells: Uniqueness or Versatility?

Pluripotent stem cells (PSCs) hold great potential both in studies on developmental biology and clinical practice. Mitochondrial metabolism that encompasses pathways that generate ATP and produce ROS significantly differs between PSCs and somatic cells. Correspondingly, for quite a long time it was believed that the redox homeostasis in PSCs is also highly specific due to the hypoxic niche of their origin-within the pre-implantation blastocyst. However, recent research showed that redox parameters of cultivated PSCs have much in common with that of their differentiated progeny cells. Moreover, it has been proven that, similar to somatic cells, maintaining the physiological ROS level is critical for the regulation of PSC identity, proliferation, differentiation, and de-differentiation. In this review, we aimed to summarize the studies of redox metabolism and signaling in PSCs to compare the redox profiles of pluripotent and differentiated somatic cells. We collected evidence that PSCs possess metabolic plasticity and are able to adapt to both hypoxia and normoxia, that pluripotency is not strictly associated with anaerobic conditions, and that cellular redox homeostasis is similar in PSCs and many other somatic cells under in vitro conditions that may be explained by the high conservatism of the redox regulation system.

Low Levels of TRIM28-Interacting KRAB-ZNF Genes Associate with Cancer Stemness and Predict Poor Prognosis of Kidney Renal Clear Cell Carcinoma Patients

Simple Summary

This is the first report investigating the involvement of TRIM28-interacting KRAB-ZNFs in kidney cancer progression. We demonstrate a significant negative association between KRAB-ZNFs and cancer stemness followed by an attenuated immune-suppressive response and reveal the prognostic role for several KRAB-ZNFs. Our findings may help better understand the molecular basis of kidney cancer and ultimately pave the way to more appropriate prognostic tools and novel therapeutic strategies directly eradicating the dedifferentiated compartment of the tumor.

Abstract

Krüppel-associated box zinc finger (KRAB-ZNF) proteins are known to regulate diverse biological processes, such as embryonic development, tissue-specific gene expression, and cancer progression. However, their involvement in the regulation of cancer stemness-like phenotype acquisition and maintenance is scarcely explored across solid tumor types, and to date, there are no data for kidney renal clear cell cancer (KIRC). We have harnessed The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database transcriptomic data and used several bioinformatic tools (i.e., GEPIA2, GSCALite, TISIDB, GSEA, CIBERSORT) to verify the relation between the expression and genomic alterations in KRAB-ZNFs and kidney cancer, focusing primarily on tumor dedifferentiation status and antitumor immune response. Our results demonstrate a significant negative correlation between KRAB-ZNFs and kidney cancer dedifferentiation status followed by an attenuated immune-suppressive response. The transcriptomic profiles of high KRAB-ZNF-expressing kidney tumors are significantly enriched with stem cell markers and show a depletion of several inflammatory pathways known for favoring cancer stemness. Moreover, we show for the first time the prognostic role for several KRAB-ZNFs in kidney cancer. Our results provide new insight into the role of selected KRAB-ZNF proteins in kidney cancer development. We believe that our findings may help better understand the molecular basis of KIRC.

Autologous transplantation of thecal stem cells restores ovarian function in nonhuman primates

Premature ovarian insufficiency (POI) is defined as the loss of ovarian activity under the age of 40. Theca cells (TCs) play a vital role during folliculogenesis and TCs dysfunction participate in the pathogenesis of POI. Therefore, transplantation of thecal stem cells (TSCs), which are capable of self-renewal and differentiation into mature TCs, may provide a new strategy for treating POI. To investigate the feasibility, safety, and efficacy of TSCs transplantation in clinically relevant non-human primate (NHP) models, we isolate TSCs from cynomolgus monkeys, and these cells are confirmed to expand continuously and show potential to differentiate into mature TCs. In addition, engraftment of autologous TSCs into POI monkeys significantly improves hormone levels, rescues the follicle development, promotes the quality of oocytes and boosts oocyte maturation/fertilization rate. Taken together, these results for the first time suggest that autologous TSCs can ameliorate POI symptoms in primate models and shed new light on developing stem cell therapy for POI.

ARHGDIA Confers Selective Advantage to Dissociated Human Pluripotent Stem Cells

Human pluripotent stem cells (hPSCs) have generated significant interest in the scientific community based on their potential applications in regenerative medicine. However, numerous research groups have reported a propensity for genomic alterations during hPSC culture that poses concerns for basic research and clinical applications. Work from our laboratory and others has demonstrated that amplification of chromosomal regions is correlated with increased gene expression. To date, the phenotypic association of common genomic alterations remains unclear and is a cause for concern during clinical use. In this study, we focus on trisomy 17 and a list of candidate genes with increased gene expression to hypothesize that overexpressing 17q25 located ARHGDIA will confer selective advantage to hPSCs. HPSC lines overexpressing ARHGDIA exhibited culture dominance in co-cultures of overexpression lines with nonoverexpression lines. Furthermore, during low-density seeding, we demonstrate increased clonality of our ARHGDIA lines against matched controls. A striking observation is that we could reduce this selective advantage by varying the hPSC culture conditions with the addition of ROCK inhibitor (ROCKi). This work is unique in (1) demonstrating a novel gene that confers selective advantage to hPSCs when overexpressed and may help explain a common trisomy dominance, (2) providing a selection model for studying culture conditions that reduce the appearance of genomically altered hPSCs, and (3) aiding in elucidation of a mechanism that may act as a molecular switch during culture adaptation.

The transcriptional trajectories of pluripotency and differentiation comprise genes with antithetical architecture and repetitive-element content

Background

Extensive molecular differences exist between proliferative and differentiated cells. Here, we conduct a meta-analysis of publicly available transcriptomic datasets from preimplantation and differentiation stages examining the architectural properties and content of genes whose abundance changes significantly across developmental time points.

Results

Analysis of preimplantation embryos from human and mouse showed that short genes whose introns are enriched in Alu (human) and B (mouse) elements, respectively, have higher abundance in the blastocyst compared to the zygote. These highly expressed genes encode ribosomal proteins or metabolic enzymes. On the other hand, long genes whose introns are depleted in repetitive elements have lower abundance in the blastocyst and include genes from signaling pathways. Additionally, the sequences of the genes that are differentially expressed between the blastocyst and the zygote contain distinct collections of pyknon motifs that differ between up- and down-regulated genes. Further examination of the genes that participate in the stem cell-specific protein interaction network shows that their introns are short and enriched in Alu (human) and B (mouse) elements. As organogenesis progresses, in both human and mouse, we find that the primarily short and repeat-rich expressed genes make way for primarily longer, repeat-poor genes. With that in mind, we used a machine learning-based approach to identify gene signatures able to classify human adult tissues: we find that the most discriminatory genes comprising these signatures have long introns that are repeat-poor and include transcription factors and signaling-cascade genes. The introns of widely expressed genes across human tissues, on the other hand, are short and repeat-rich, and coincide with those with the highest expression at the blastocyst stage.

Conclusions

Protein-coding genes that are characteristic of each trajectory, i.e., proliferation/pluripotency or differentiation, exhibit antithetical biases in their intronic and exonic lengths and in their repetitive-element content. While the respective human and mouse gene signatures are functionally and evolutionarily conserved, their introns and exons are enriched or depleted in organism-specific repetitive elements. We posit that these organism-specific repetitive sequences found in exons and introns are used to effect the corresponding genes’ regulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-020-00928-8.

Gene Editing Correction of a Urea Cycle Defect in Organoid Stem Cell Derived Hepatocyte-like Cells

Urea cycle disorders are enzymopathies resulting from inherited deficiencies in any genes of the cycle. In severe cases, currently available therapies are marginally effective, with liver transplantation being the only definitive treatment. Donor liver availability can limit even this therapy. Identification of novel therapeutics for genetic-based liver diseases requires models that provide measurable hepatic functions and phenotypes. Advances in stem cell and genome editing technologies could provide models for the investigation of cell-based genetic diseases, as well as the platforms for drug discovery. This report demonstrates a practical, and widely applicable, approach that includes the successful reprogramming of somatic cells from a patient with a urea cycle defect, their genetic correction and differentiation into hepatic organoids, and the subsequent demonstration of genetic and phenotypic change in the edited cells consistent with the correction of the defect. While individually rare, there is a large number of other genetic-based liver diseases. The approach described here could be applied to a broad range and a large number of patients with these hepatic diseases where it could serve as an in vitro model, as well as identify successful strategies for corrective cell-based therapy.

Why isn't sex optional? Stem-cell competition, loss of regenerative capacity, and cancer in metazoan evolution

Animals that can reproduce vegetatively by fission or budding and also sexually via specialized gametes are found in all five primary animal lineages (Bilateria, Cnidaria, Ctenophora, Placozoa, Porifera). Many bilaterian lineages, including roundworms, insects, and most chordates, have lost the capability of vegetative reproduction and are obligately gametic. We suggest a developmental explanation for this evolutionary phenomenon: obligate gametic reproduction is the result of germline stem cells winning a winner-take-all competition with non-germline stem cells for control of reproduction and hence lineage survival. We develop this suggestion by extending Hamilton's rule, which factors the relatedness between parties into the cost/benefit analysis that underpins cooperative behaviors, to include similarity of cellular state. We show how coercive or deceptive cell-cell signaling can be used to make costly cooperative behaviors appear less costly to the cooperating party. We then show how competition between stem-cell lineages can render an ancestral combination of vegetative reproduction with facultative sex unstable, with one or the other process driven to extinction. The increased susceptibility to cancer observed in obligately-sexual lineages is, we suggest, a side-effect of deceptive signaling that is exacerbated by the loss of whole-body regenerative abilities. We suggest a variety of experimental approaches for testing our predictions.

Derivation of Intermediate Pluripotent Stem Cells Amenable to Primordial Germ Cell Specification

Dynamic pluripotent stem cell (PSC) states are in vitro adaptations of pluripotency continuum in vivo. Previous studies have generated a number of PSCs with distinct properties. To date, however, no known PSCs have demonstrated dual competency for chimera formation and direct responsiveness to primordial germ cell (PGC) specification, a unique functional feature of formative pluripotency. Here, by modulating fibroblast growth factor (FGF), transforming growth factor β (TGF-β), and WNT pathways, we derived PSCs from mice, horses, and humans (designated as XPSCs) that are permissive for direct PGC-like cell induction in vitro and are capable of contributing to intra- or inter-species chimeras in vivo. XPSCs represent a pluripotency state between naive and primed pluripotency and harbor molecular, cellular, and phenotypic features characteristic of formative pluripotency. XPSCs open new avenues for studying mammalian pluripotency and dissecting the molecular mechanisms governing PGC specification. Our method may be broadly applicable for the derivation of analogous stem cells from other mammalian species.

Chitosan 3D cell culture system promotes naïve-like features of human induced pluripotent stem cells: A novel tool to sustain pluripotency and facilitate differentiation

A simplified and cost-effective culture system for maintaining the pluripotency of human induced pluripotent stem cells (hiPSCs) is crucial for stem cell applications. Although recombinant protein-based feeder-free hiPSC culture systems have been developed, their manufacturing processes are expensive and complicated, which hinders hiPSC technology progress. Chitosan, a versatile biocompatible polysaccharide, has been reported as a biomaterial for three-dimensional (3D) cell culture system that promotes the physiological activities of mesenchymal stem cells and cancer cells. In the current study, we demonstrated that chitosan membranes sustained proliferation and pluripotency of hiPSCs in long-term culture (up to 365 days). Moreover, using vitronectin as the comparison group, the pluripotency of hiPSCs grown on the membranes was altered into a naïve-like state, which, for pluripotent stem cells, is an earlier developmental stage with higher stemness. On the chitosan membranes, hiPSCs self-assembled into 3D spheroids with an average diameter of ~100 μm. These hiPSC spheroids could be directly differentiated into lineage-specific cells from the three germ layers with 3D structures. Collectively, chitosan membranes not only promoted the naïve pluripotent features of hiPSCs but also provided a novel 3D differentiation platform. This convenient biomaterial-based culture system may enable the effective expansion and accessibility of hiPSCs for regenerative medicine, disease modeling, and drug screening.

Mapping global research trends in stem cell therapy for inflammatory bowel disease: a bibliometric analysis from 1991 to 2019

BACKGROUND

Inflammatory bowel disease (IBD) represents a series of digestive system abnormalities and parenteral manifestations. Stem cell therapy has been regarded as a promising treatment for IBD.

METHODS

We searched Web of Science Core Collection for publications of interest from 1991 to 2019. Publication performance was analyzed using several bibliometric parameters, including Statplanet to reveal the geographic distribution of the publications, VOSviewer to identify the research landscape of hot topics, and CiteSpace to show keywords with the strongest citation bursts.

RESULTS

A total of 1230 publications were identified, of which 674 articles were analyzed further. The United States was the most productive country and Spanish researchers published the highest quality articles. At a journal level, Gastroenterology published the greatest number of articles, while articles from Gut had the highest citation number. Results from the research landscape analysis of hot topics and the top 20 terms with the strongest citation bursts indicated that animal experiments, immunocytes, intestinal epithelial cells, cytokine expression, and clinical efficacy were the main focuses of research.

CONCLUSION

Stem cell therapy for IBD is currently receiving increasing attention by researchers, with focuses on animal experiments, immunocytes, intestinal epithelial cells, cytokine expression, and clinical efficacy.

Embryonic Program Activated during Blast Crisis of Chronic Myelogenous Leukemia (CML) Implicates a TCF7L2 and MYC Cooperative Chromatin Binding

Chronic myeloid leukemia (CML) is characterized by an inherent genetic instability, which contributes to the progression of the disease towards an accelerated phase (AP) and blast crisis (BC). Several cytogenetic and genomic alterations have been reported in the progression towards BC, but the precise molecular mechanisms of this event are undetermined. Transcription Factor 7 like 2 (TFC7L2) is a member of the TCF family of proteins that are known to activate WNT target genes such as Cyclin D1. TCF7L2 has been shown to be overexpressed in acute myeloid leukemia (AML) and represents a druggable target. We report here that TCF7L2 transcription factor expression was found to be correlated to blast cell numbers during the progression of the disease. In these cells, TCF7L2 CHIP-sequencing highlighted distal cis active enhancer, such as elements in SMAD3, ATF5, and PRMT1 genomic regions and a proximal active transcriptional program of 144 genes. The analysis of CHIP-sequencing of MYC revealed a significant overlapping of TCF7L2 epigenetic program with MYC. The β-catenin activator lithium chloride and the MYC-MAX dimerization inhibitor 10058-F4 significantly modified the expression of three epigenetic targets in the BC cell line K562. These results suggest for the first time the cooperative role of TCF7L2 and MYC during CML-BC and they strengthen previous data showing a possible involvement of embryonic genes in this process.

Transcriptional Profiling of Stem Cells: Moving from Descriptive to Predictive Paradigms

Transcriptional profiling is a powerful tool commonly used to benchmark stem cells and their differentiated progeny. As the wealth of stem cell data builds in public repositories, we highlight common data traps, and review approaches to combine and mine this data for new cell classification and cell prediction tools. We touch on future trends for stem cell profiling, such as single-cell profiling, long-read sequencing, and improved methods for measuring molecular modifications on chromatin and RNA that bring new challenges and opportunities for stem cell analysis.

Single-cell transcriptional diversity is a hallmark of developmental potential

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential-the number of expressed genes per cell-and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data. When applied to diverse tissue types and organisms, CytoTRACE outperformed previous methods and nearly 19,000 annotated gene sets for resolving 52 experimentally determined developmental trajectories. Additionally, it facilitated the identification of quiescent stem cells and revealed genes that contribute to breast tumorigenesis. This study thus establishes a key RNA-based feature of developmental potential and a platform for delineation of cellular hierarchies.

Cell-cycle dependence of transcriptome gene modules: comparison of regression lines

The transcriptome consists of various gene modules that can be mutually dependent, and ignoring these dependencies may lead to misinterpretation. The most important problem is module dependence on cell-cycle activity. Using meta-analysis of over 30 000 single-cell transcriptomes, we show gene module dependencies on cell-cycle signature, which can be consistently observed in various normal and cancer cells. Transcript levels of receptors, plasma membrane, and differentiation-related genes are negatively regressed on cell-cycle signature. Pluripotency, stress response, DNA repair, chromatin remodeling, proteasomal protein degradation, protein network connectivity, and unicellular evolutionary origin are regressed positively. These effects cannot be explained by partial overlap of corresponding gene sets because they remain if the overlapped genes were removed. We propose a visual analysis of gene module-specific regression lines as complement to an uncurated enrichment analysis. The different lines for a same gene module indicate different cell conditions. The approach is tested on several problems (polyploidy, pluripotency, cancer, phylostratigraphy). Intriguingly, we found variation in cell-cycle activity, which is independent of cell progression through the cycle. The upregulation of G2/M checkpoint genes with downregulation of G2/M transition and cytokinesis is revealed in polyploid cells. A temporal increase in cell-cycle activity at transition from pluripotent to more differentiated state is found in human embryonic stem cells. The upregulation of unicellular interactome cluster in human cancers is shown in single cells with control for cell-cycle activity. The greater scatter around regression line in cancer cells suggests greater heterogeneity caused by deviation from a line of normal cells.

Integrating hypertension phenotype and genotype with hybrid non-negative matrix factorization

MOTIVATION

Hypertension is a heterogeneous syndrome in need of improved subtyping using phenotypic and genetic measurements with the goal of identifying subtypes of patients who share similar pathophysiologic mechanisms and may respond more uniformly to targeted treatments. Existing machine learning approaches often face challenges in integrating phenotype and genotype information and presenting to clinicians an interpretable model. We aim to provide informed patient stratification based on phenotype and genotype features.

RESULTS

In this article, we present a hybrid non-negative matrix factorization (HNMF) method to integrate phenotype and genotype information for patient stratification. HNMF simultaneously approximates the phenotypic and genetic feature matrices using different appropriate loss functions, and generates patient subtypes, phenotypic groups and genetic groups. Unlike previous methods, HNMF approximates phenotypic matrix under Frobenius loss, and genetic matrix under Kullback-Leibler (KL) loss. We propose an alternating projected gradient method to solve the approximation problem. Simulation shows HNMF converges fast and accurately to the true factor matrices. On a real-world clinical dataset, we used the patient factor matrix as features and examined the association of these features with indices of cardiac mechanics. We compared HNMF with six different models using phenotype or genotype features alone, with or without NMF, or using joint NMF with only one type of loss We also compared HNMF with 3 recently published methods for integrative clustering analysis, including iClusterBayes, Bayesian joint analysis and JIVE. HNMF significantly outperforms all comparison models. HNMF also reveals intuitive phenotype-genotype interactions that characterize cardiac abnormalities.

AVAILABILITY AND IMPLEMENTATION

Our code is publicly available on github at https://github.com/yuanluo/hnmf.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PSCRIdb: A database of regulatory interactions and networks of pluripotent stem cell lines

Pluripotency in stem cells is regulated by a complex network between the transcription factors, signaling molecules, mRNAs, and epigenetic regulators like non-coding RNAs. Different pluripotent stem cell (PSC) lines were isolated and characterized to study the regulatory network topology to understand the mechanism that control developmental potential of pluripotent cells. PSCRIdb is a manually curated database of regulatory interactions including protein-protein, protein-DNA, gene-gene, and miRNA-mRNA interactions in mouse and human pluripotent stem cells including embryonic stem cells and embryonic carcinoma cells. At present, 22 different mouse and human pluripotent stem-cell-line-specific regulatory interactions are compiled in the database. Detailed information of the four types of interaction data are presented in tabular format and graphical network view in Cytoscape layout. The database is available at http://bicresources.jcbose.ac.in/ ssaha4/pscridb. The database contains 3037 entries of experimentally validated molecular interactions that can be useful for systematic study of pluripotency integrating multi-omics data. In summary, the database can be a useful resource for identification of regulatory networks present in different pluripotent stem cell lines.

Stem Cell Differentiation as a Non-Markov Stochastic Process

Pluripotent stem cells can self-renew in culture and differentiate along all somatic lineages in vivo. While much is known about the molecular basis of pluripotency, the mechanisms of differentiation remain unclear. Here, we profile individual mouse embryonic stem cells as they progress along the neuronal lineage. We observe that cells pass from the pluripotent state to the neuronal state via an intermediate epiblast-like state. However, analysis of the rate at which cells enter and exit these observed cell states using a hidden Markov model indicates the presence of a chain of unobserved molecular states that each cell transits through stochastically in sequence. This chain of hidden states allows individual cells to record their position on the differentiation trajectory, thereby encoding a simple form of cellular memory. We suggest a statistical mechanics interpretation of these results that distinguishes between functionally distinct cellular “macrostates” and functionally similar molecular “microstates” and propose a model of stem cell differentiation as a non-Markov stochastic process.

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We profile individual stem cells as they differentiate along the neural lineage

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Regulatory network changes and increased cell variability accompany differentiation

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Analysis of dynamics with a hidden Markov model reveals unobserved molecular states

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We propose a model of stem cell differentiation as a non-Markov stochastic process

Applying hydrodynamic pressure to efficiently generate induced pluripotent stem cells via reprogramming of centenarian skin fibroblasts

Induced pluripotent stem cell (iPSC)-technology is an important platform in medicine and disease modeling. Physiological degeneration and disease onset are common occurrences in the aging population. iPSCs could offer regenerative medical options for age-related degeneration and disease in the elderly. However, reprogramming somatic cells from the elderly is inefficient when successful at all. Perhaps due to their low rates of replication in culture, traditional transduction and reprogramming approaches with centenarian fibroblasts met with little success. A simple and reproducible reprogramming process is reported here which enhances interactions of the cells with the viral vectors that leads to improved iPSC generation. The improved methods efficiently generates fully reprogrammed iPSC lines from 105-107 years old subjects in feeder-free conditions using an episomal, Sendai-Virus (SeV) reprogramming vector expressing four reprogramming factors. In conclusion, dermal fibroblasts from human subjects older than 100 years can be efficiently and reproducibly reprogrammed to fully pluripotent cells with minor modifications to the standard reprogramming procedures. Efficient generation of iPSCs from the elderly may provide a source of cells for the regeneration of tissues and organs with autologous cells as well as cellular models for the study of aging, longevity and age-related diseases.

Genomic landscape analyses of reprogrammed cells using integrative and non-integrative methods reveal variable cancer-associated alterations

Recent development of cell reprogramming technologies brought a major hope for future cell therapy applications by the use of these cells or their derivatives. For this purpose, one of the major requirements is the absence of genomic alterations generating a risk of cell transformation. Here we analyzed by microarray-based comparative genomic hybridization human iPSC generated by two non-integrative and one integrative method at pluripotent stage as well as in corresponding teratomas. We show that all iPSC lines exhibit copy number variations (CNV) of several genes deregulated in oncogenesis. These cancer-associated genomic alterations were more pronounced in virally programmed hiPSCs and their derivative teratoma as compared to those found in iPSC generated by mRNA-mediated reprogramming. Bioinformatics analysis showed the involvement of these genes in human leukemia and carcinoma. We conclude that genetic screening should become a standard procedure to ensure that hiPSCs are free from cancer-associated genomic alterations before clinical use.

Proteotyping pluripotency with mass spectrometry

INTRODUCTION

Pluripotency emerges transiently during embryogenesis in two main forms with different developmental potential, termed naïve and primed states. Importantly, these pluripotent states can be recapitulated in vitro under specific culture conditions, representing a unique model to study the regulatory principles of development and cellular plasticity. Areas covered: A complex network of signaling pathways that senses intrinsic and extrinsic cues controls the fine balance between self-renewal and differentiation. Much of our knowledge on this tight regulation originates from epigenetic and transcriptomic approaches. However, the presence of post-transcriptional and post-translational mechanisms demands a direct assessment of the proteome in its multiple facets. Mass spectrometry-based proteomics is now a mature technique and has started to deliver new insights in the stem cell field. Expert opinion: Here, we review our current understanding on the mechanisms that dictate the spectrum of pluripotency levels. We put special emphasis on the emerging proteomic studies that focused on the molecular properties behind the naïve and primed states. In addition, we hypothesize on the impact that future developments in proteomic technologies can have to improve our view of pluripotency.

Therapeutic Targeting of Non-oncogene Dependencies in High-risk Neuroblastoma

PURPOSE

Neuroblastoma is a pediatric malignancy of the sympathetic nervous system with diverse clinical behaviors. Genomic amplification of MYCN oncogene has been shown to drive neuroblastoma pathogenesis and correlate with aggressive disease, but the survival rates for those high-risk tumors carrying no MYCN amplification remain equally dismal. The paucity of mutations and molecular heterogeneity has hindered the development of targeted therapies for most advanced neuroblastomas. We use an alternative method to identify potential drugs that target nononcogene dependencies in high-risk neuroblastoma.

EXPERIMENTAL DESIGN

By using a gene expression-based integrative approach, we identified prognostic signatures and potentially effective single agents and drug combinations for high-risk neuroblastoma.

RESULTS

Among these predictions, we validated in vitro efficacies of some investigational and marketed drugs, of which niclosamide, an anthelmintic drug approved by the FDA, was further investigated in vivo. We also quantified the proteomic changes during niclosamide treatment to pinpoint nucleoside diphosphate kinase 3 (NME3) downregulation as a potential mechanism for its antitumor activity.

CONCLUSIONS

Our results establish a gene expression-based strategy to interrogate cancer biology and inform drug discovery and repositioning for high-risk neuroblastoma.

Multilayer regulation of CD4 T cell subset differentiation in the era of single cell genomics

CD4 T cells are major immune cell types that mediate effector responses appropriate for diverse incoming threats. These cells have been categorized into different subsets based on how they are induced, expression of specific master transcription factors, and the resulting effector cell phenotypes as defined by expression of signature cytokines. However, recent studies assessing the expression of gene modules in single CD4 T cells, rather than expression of one or a few signature genes, have provided a more complex picture in which the canonical model does not fit as cleanly as proposed. Here, we review the concepts of lineage commitment, plasticity and functional heterogeneity in the context of this greater complexity. We then apply our current understanding of CD4 T cell subsets to discuss outstanding questions regarding follicular helper T cells and follicular regulatory T cells with respect to their shared features with other known CD4 T cell subsets.

DNA Methylation and Chromatin: Role(s) of Methyl-CpG-Binding Protein ZBTB38

DNA methylation plays an essential role in the control of gene expression during early stages of development as well as in disease. Although many transcription factors are sensitive to this modification of the DNA, we still do not clearly understand how it contributes to the establishment of proper gene expression patterns. We discuss here the recent findings regarding the biological and molecular function(s) of the transcription factor ZBTB38 that binds methylated DNA sequences in vitro and in cells. We speculate how these findings may help understand the role of DNA methylation and DNA methylation–sensitive transcription factors in mammalian cells.