Transmembrane Protein TMEM230, Regulator of Glial Cell Vascular Mimicry and Endothelial Cell Angiogenesis in High-Grade Heterogeneous Infiltrating Gliomas and Glioblastoma.

High-grade gliomas (HGGs) and glioblastoma multiforme (GBM) are characterized by a heterogeneous and aggressive population of tissue-infiltrating cells that promote both destructive tissue remodeling and aberrant vascularization of the brain. The formation of defective and permeable blood vessels and microchannels and destructive tissue remodeling prevent efficient vascular delivery of pharmacological agents to tumor cells and are the significant reason why therapeutic chemotherapy and immunotherapy intervention are primarily ineffective. Vessel-forming endothelial cells and microchannel-forming glial cells that recapitulate vascular mimicry have both infiltration and destructive remodeling tissue capacities. The transmembrane protein TMEM230 (C20orf30) is a master regulator of infiltration, sprouting of endothelial cells, and microchannel formation of glial and phagocytic cells. A high level of TMEM230 expression was identified in patients with HGG, GBM, and U87-MG cells. In this study, we identified candidate genes and molecular pathways that support that aberrantly elevated levels of TMEM230 play an important role in regulating genes associated with the initial stages of cell infiltration and blood vessel and microchannel (also referred to as tumor microtubule) formation in the progression from low-grade to high-grade gliomas. As TMEM230 regulates infiltration, vascularization, and tissue destruction capacities of diverse cell types in the brain, TMEM230 is a promising cancer target for heterogeneous HGG tumors.

Physical Interventions Restore Physical Frailty and the Expression of CXCL-10 and IL-1ß Inflammatory Biomarkers in Old Individuals and Mice.

BACKGROUND: Frailty is a geriatric syndrome associated with negative health outcomes that represents a dynamic condition with a potential of reversibility after physical exercise interventions. Typically, inflammatory and senescence markers are increased in frail individuals. However, the impact that physical exercise exerts on inflammatory and senescence biomarkers remains unknown. We assessed the effect of physical intervention in old individuals and mice and determined the expression of inflammatory and senescence markers. METHODS: Twelve elderly individuals were enrolled from a primary care setting to a 3-month intervention. Frailty was measured by SPPB and the expression of biomarkers by cytokine array and RT-qPCR. In addition, 12 aged C57BL/6 mice completed an intervention, and inflammation and senescence markers were studied. RESULTS: The physical intervention improved the SPPB score, reducing frail and pre-frail individuals. This was correlated with a reduction in several pro-inflammatory biomarkers such as IL-6, CXCL-1, CXCL-10, IL-1ß, IL-7, GM-CSF as well as p16INK4a and p21CIP1 senescence markers. Otherwise, the levels of anti-inflammatory biomarker IL-4 were significantly increased. Moreover, the physical intervention in mice also improved their functional capacity and restored the expression of inflammatory (Il-1ß, Cxcl-10, Il-6, and Cxcl-1) and senescence (p21Cip1) markers. Additionally, PLSDA and ROC curve analysis revealed CXCL-10 and IL-1ß to be the biomarkers of functional improvement in both cohorts. CONCLUSIONS: Our results showed that a physical intervention improves physical frailty, and reverses inflammation and senescence biomarkers comprising CXCL-10 and IL-1ß.

Human skeletal muscle organoids model fetal myogenesis and sustain uncommitted PAX7 myogenic progenitors.

In vitro culture systems that structurally model human myogenesis and promote PAX7+ myogenic progenitor maturation have not been established. Here we report that human skeletal muscle organoids can be differentiated from induced pluripotent stem cell lines to contain paraxial mesoderm and neuromesodermal progenitors and develop into organized structures reassembling neural plate border and dermomyotome. Culture conditions instigate neural lineage arrest and promote fetal hypaxial myogenesis toward limb axial anatomical identity, with generation of sustainable uncommitted PAX7 myogenic progenitors and fibroadipogenic (PDGFRa+) progenitor populations equivalent to those from the second trimester of human gestation. Single-cell comparison to human fetal and adult myogenic progenitor /satellite cells reveals distinct molecular signatures for non-dividing myogenic progenitors in activated (CD44High/CD98+/MYOD1+) and dormant (PAX7High/FBN1High/SPRY1High) states. Our approach provides a robust 3D in vitro developmental system for investigating muscle tissue morphogenesis and homeostasis.

Humans contains around 650 skeletal muscles which allow the body to move around and maintain its posture. Skeletal muscles are made up of individual cells that bundle together into highly organized structures. If this group of muscles fail to develop correctly in the embryo and/or fetus, this can lead to muscular disorders that can make it painful and difficult to move. One way to better understand how skeletal muscles are formed, and how this process can go wrong, is to grow them in the laboratory. This can be achieved using induced pluripotent stem cells (iPSCs), human adult cells that have been 'reprogrammed' to behave like cells in the embryo that can develop in to almost any cell in the body. The iPSCs can then be converted into specific cell types in the laboratory, including the cells that make up skeletal muscle. Here, Mavrommatis et al. created a protocol for developing iPSCs into three-dimensional organoids which resemble how cells of the skeletal muscle look and arrange themselves in the fetus. To form the skeletal muscle organoid, Mavrommatis et al. treated iPSCs that were growing in a three-dimensional environment with various factors that are found early on in development. This caused the iPSCs to organize themselves in to embryonic and fetal structures that will eventually give rise to the parts of the body that contain skeletal muscle, such as the limbs. Within the organoid were cells that produced Pax7, a protein commonly found in myogenic progenitors that specifically mature into skeletal muscle cells in the fetus. Pax 7 is also present in 'satellite cells' that help to regrow damaged skeletal muscle in adults. Indeed, Mavrommatis et al. found that the myogenic progenitors produced by the organoid were able to regenerate muscle when transplanted in to adult mice. These findings suggest that this organoid protocol can generate cells that will give rise to skeletal muscle. In the future, these lab-grown progenitors could potentially be created from cells isolated from patients and used to repair muscle injuries. The organoid model could also provide new insights in to how skeletal muscles develop in the fetus, and how genetic mutations linked with muscular disorders disrupt this process.

A distinct circular DNA profile intersects with proteome changes in the genotoxic stress-related hSOD1G93A model of ALS.

BACKGROUND: Numerous genes, including SOD1, mutated in familial and sporadic amyotrophic lateral sclerosis (f/sALS) share a role in DNA damage and repair, emphasizing genome disintegration in ALS. One possible outcome of chromosomal instability and repair processes is extrachromosomal circular DNA (eccDNA) formation. Therefore, eccDNA might accumulate in f/sALS with yet unknown function. METHODS: We combined rolling circle amplification with linear DNA digestion to purify eccDNA from the cervical spinal cord of 9 co-isogenic symptomatic hSOD1G93A mutants and 10 controls, followed by deep short-read sequencing. We mapped the eccDNAs and performed differential analysis based on the split read signal of the eccDNAs, referred as DifCir, between the ALS and control specimens, to find differentially produced per gene circles (DPpGC) in the two groups. Compared were eccDNA abundances, length distributions and genic profiles. We further assessed proteome alterations in ALS by mass spectrometry, and matched the DPpGCs with differentially expressed proteins (DEPs) in ALS. Additionally, we aligned the ALS-specific DPpGCs to ALS risk gene databases. RESULTS: We found a six-fold enrichment in the number of unique eccDNAs in the genotoxic ALS-model relative to controls. We uncovered a distinct genic circulome profile characterized by 225 up-DPpGCs, i.e., genes that produced more eccDNAs from distinct gene sequences in ALS than under control conditions. The inter-sample recurrence rate was at least 89% for the top 6 up-DPpGCs. ALS proteome analyses revealed 42 corresponding DEPs, of which 19 underlying genes were itemized for an ALS risk in GWAS databases. The up-DPpGCs and their DEP tandems mainly impart neuron-specific functions, and gene set enrichment analyses indicated an overrepresentation of the adenylate cyclase modulating G protein pathway. CONCLUSIONS: We prove, for the first time, a significant enrichment of eccDNA in the ALS-affected spinal cord. Our triple circulome, proteome and genome approach provide indication for a potential importance of certain eccDNAs in ALS neurodegeneration and a yet unconsidered role as ALS biomarkers. The related functional pathways might open up new targets for therapeutic intervention.

Single-cell RNA sequencing of human non-hematopoietic bone marrow cells reveals a unique set of inter-species conserved biomarkers for native mesenchymal stromal cells.

BACKGROUND: Native bone marrow (BM) mesenchymal stem/stromal cells (BM-MSCs) participate in generating and shaping the skeleton and BM throughout the lifespan. Moreover, BM-MSCs regulate hematopoiesis by contributing to the hematopoietic stem cell niche in providing critical cytokines, chemokines and extracellular matrix components. However, BM-MSCs contain a heterogeneous cell population that remains ill-defined. Although studies on the taxonomy of native BM-MSCs in mice have just started to emerge, the taxonomy of native human BM-MSCs remains unelucidated. METHODS: By using single-cell RNA sequencing (scRNA-seq), we aimed to define a proper taxonomy for native human BM non-hematopoietic subsets including endothelial cells (ECs) and mural cells (MCs) but with a focal point on MSCs. To this end, transcriptomic scRNA-seq data were generated from 5 distinct BM donors and were analyzed together with other transcriptomic data and with computational biology analyses at different levels to identify, characterize and classify distinct native cell subsets with relevant biomarkers. RESULTS: We could ascribe novel specific biomarkers to ECs, MCs and MSCs. Unlike ECs and MCs, MSCs exhibited an adipogenic transcriptomic pattern while co-expressing genes related to hematopoiesis support and multilineage commitment potential. Furthermore, by a comparative analysis of scRNA-seq of BM cells from humans and mice, we identified core genes conserved in both species. Notably, we identified MARCKS, CXCL12, PDGFRA, and LEPR together with adipogenic factors as archetypal biomarkers of native MSCs within BM. In addition, our data suggest some complex gene nodes regulating critical biological functions of native BM-MSCs together with a preferential commitment toward an adipocyte lineage. CONCLUSIONS: Overall, our taxonomy for native BM non-hematopoietic compartment provides an explicit depiction of gene expression in human ECs, MCs and MSCs at single-cell resolution. This analysis helps enhance our understanding of the phenotype and the complexity of biological functions of native human BM-MSCs.

Systemic Lupus Erythematosus Patients with DNASE1L3·Deficiency Have a Distinctive and Specific Genic Circular DNA Profile in Plasma.

Cell-free (cf) extrachromosomal circular DNA (eccDNA) has a potential clinical application as a biomarker. Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with a complex immunological pathogenesis, associated with autoantibody synthesis. A previous study found that SLE patients with deoxyribonuclease 1-like 3 (DNASE1L3) deficiency exhibit changes in the frequency of short and long eccDNA in plasma compared to controls. Here, using the DifCir method for differential analysis of short-read sequenced purified eccDNA data based on the split-read signal of the eccDNA on circulomics data, we show that SLE patients with DNASE1L3 deficiency have a distinctive profile of eccDNA excised by gene regions compared to controls. Moreover, this profile is specific; cf-eccDNA from the top 93 genes is detected in all SLE with DNASE1L3 deficiency samples, and none in the control plasma. The top protein coding gene producing eccDNA-carrying gene fragments is the transcription factor BARX2, which is involved in skeletal muscle morphogenesis and connective tissue development. The top gene ontology terms are 'positive regulation of torc1 signaling' and 'chondrocyte development'. The top Harmonizome terms are 'lymphopenia', 'metabolic syndrome x', 'asthma', 'cardiovascular system disease', 'leukemia', and 'immune system disease'. Here, we show that gene associations of cf-eccDNA can serve as a biomarker in the autoimmune rheumatic diseases.

Skeletal Muscles of Sedentary and Physically Active Aged People Have Distinctive Genic Extrachromosomal Circular DNA Profiles.

To bring new extrachromosomal circular DNA (eccDNA) enrichment technologies closer to the clinic, specifically for screening, early diagnosis, and monitoring of diseases or lifestyle conditions, it is paramount to identify the differential pattern of the genic eccDNA signal between two states. Current studies using short-read sequenced purified eccDNA data are based on absolute numbers of unique eccDNAs per sample or per gene, length distributions, or standard methods for RNA-seq differential analysis. Previous analyses of RNA-seq data found significant transcriptomics difference between sedentary and active life style skeletal muscle (SkM) in young people but very few in old. The first attempt using circulomics data from SkM and blood of aged lifelong sedentary and physically active males found no difference at eccDNA level. To improve the capability of finding differences between circulomics data groups, we designed a computational method to identify Differentially Produced per Gene Circles (DPpGCs) from short-read sequenced purified eccDNA data based on the circular junction, split-read signal, of the eccDNA, and implemented it into a software tool DifCir in Matlab. We employed DifCir to find to the distinctive features of the influence of the physical activity or inactivity in the aged SkM that would have remained undetected by transcriptomics methods. We mapped the data from tissue from SkM and blood from two groups of aged lifelong sedentary and physically active males using Circle_finder and subsequent merging and filtering, to find the number and length distribution of the unique eccDNA. Next, we used DifCir to find up-DPpGCs in the SkM of the sedentary and active groups. We assessed the functional enrichment of the DPpGCs using Disease Gene Network and Gene Set Enrichment Analysis. To find genes that produce eccDNA in a group without comparison with another group, we introduced a method to find Common PpGCs (CPpGCs) and used it to find CPpGCs in the SkM of the sedentary and active group. Finally, we found the eccDNA that carries whole genes. We discovered that the eccDNA in the SkM of the sedentary group is not statistically different from that of physically active aged men in terms of number and length distribution of eccDNA. In contrast, with DifCir we found distinctive gene-associated eccDNA fingerprints. We identified statistically significant up-DPpGCs in the two groups, with the top up-DPpGCs shed by the genes AGBL4, RNF213, DNAH7, MED13, and WWTR1 in the sedentary group, and ZBTB7C, TBCD, ITPR2, and DDX11-AS1 in the active group. The up-DPpGCs in both groups carry mostly gene fragments rather than whole genes. Though the subtle transcriptomics difference, we found RYR1 to be both transcriptionally up-regulated and up-DPpGCs gene in sedentary SkM. DifCir emphasizes the high sensitivity of the circulome compared to the transcriptome to detect the molecular fingerprints of exercise in aged SkM. It allows efficient identification of gene hotspots that excise more eccDNA in a health state or disease compared to a control condition.

Prediction of patient admission and readmission in adults from a Colombian cohort with bipolar disorder using artificial intelligence.

Introduction: Bipolar disorder (BD) is a chronically progressive mental condition, associated with a reduced quality of life and greater disability. Patient admissions are preventable events with a considerable impact on global functioning and social adjustment. While machine learning (ML) approaches have proven prediction ability in other diseases, little is known about their utility to predict patient admissions in this pathology. Aim: To develop prediction models for hospital admission/readmission within 5 years of diagnosis in patients with BD using ML techniques. Methods: The study utilized data from patients diagnosed with BD in a major healthcare organization in Colombia. Candidate predictors were selected from Electronic Health Records (EHRs) and included sociodemographic and clinical variables. ML algorithms, including Decision Trees, Random Forests, Logistic Regressions, and Support Vector Machines, were used to predict patient admission or readmission. Survival models, including a penalized Cox Model and Random Survival Forest, were used to predict time to admission and first readmission. Model performance was evaluated using accuracy, precision, recall, F1 score, area under the receiver operating characteristic curve (AUC) and concordance index. Results: The admission dataset included 2,726 BD patients, with 354 admissions, while the readmission dataset included 352 patients, with almost half being readmitted. The best-performing model for predicting admission was the Random Forest, with an accuracy score of 0.951 and an AUC of 0.98. The variables with the greatest predictive power in the Recursive Feature Elimination (RFE) importance analysis were the number of psychiatric emergency visits, the number of outpatient follow-up appointments and age. Survival models showed similar results, with the Random Survival Forest performing best, achieving an AUC of 0.95. However, the prediction models for patient readmission had poorer performance, with the Random Forest model being again the best performer but with an AUC below 0.70. Conclusion: ML models, particularly the Random Forest model, outperformed traditional statistical techniques for admission prediction. However, readmission prediction models had poorer performance. This study demonstrates the potential of ML techniques in improving prediction accuracy for BD patient admissions.

Cell-Free Genic Extrachromosomal Circular DNA Profiles of DNase Knockouts Associated with Systemic Lupus Erythematosus and Relation with Common Fragile Sites.

Cell-free extrachromosomal circular DNA (cf-eccDNA) has been proposed as a promising early biomarker for disease diagnosis, progression and drug response. Its established biomarker features are changes in the number and length distribution of cf-eccDNA. Another novel promising biomarker is a set of eccDNA excised from a panel of genes specific to a condition compared to a control. Deficiencies in two endonucleases that specifically target DNA, Dnase1 and Dnase1l3, are associated with systemic lupus erythematosus (SLE). To study the genic eccDNA profiles in the case of their deficiencies, we mapped sequenced eccDNA data from plasma, liver and buffy coat from Dnase1 and Dnase1l3 knockouts (KOs), and wild type controls in mouse. Next, we performed an eccDNA differential analysis between KO and control groups using our DifCir algorithm. We found a specific genic cf-eccDNA fingerprint of the Dnase1l3 group compared to the wild type controls involving 131 genes; 26% of them were associated with human chromosomal fragile sites (CFSs) and with a statistically significant enrichment of CFS-associated genes. We found six genes in common with the genic cf-eccDNA profile of SLE patients with DNASE1L3 deficiency, namely Rorb, Mvb12b, Osbpl10, Fto, Tnik and Arhgap10; all of them were specific and present in all human plasma samples, and none of them were associated with CFSs. A not so distinctive genic cf-eccDNA difference involving only seven genes was observed in the case of the Dnase1 group compared to the wild type. In tissue-liver and buffy coat-we did not detect the same genic eccDNA difference observed in the plasma samples. These results point to a specific role of a set of genic eccDNA in plasma from DNase KOs, as well as a relation with CFS genes, confirming the promise of the genic cf-eccDNA in studying diseases and the need for further research on the relationship between eccDNA and CFSs.

Lack of evidence for increased transcriptional noise in aged tissues.

Aging is often associated with a loss of cell type identity that results in an increase in transcriptional noise in aged tissues. If this phenomenon reflects a fundamental property of aging remains an open question. Transcriptional changes at the cellular level are best detected by single-cell RNA sequencing (scRNAseq). However, the diverse computational methods used for the quantification of age-related loss of cellular identity have prevented reaching meaningful conclusions by direct comparison of existing scRNAseq datasets. To address these issues we created Decibel, a Python toolkit that implements side-to-side four commonly used methods for the quantification of age-related transcriptional noise in scRNAseq data. Additionally, we developed Scallop, a novel computational method for the quantification of membership of single cells to their assigned cell type cluster. Cells with a greater Scallop membership score are transcriptionally more stable. Application of these computational tools to seven aging datasets showed large variability between tissues and datasets, suggesting that increased transcriptional noise is not a universal hallmark of aging. To understand the source of apparent loss of cell type identity associated with aging, we analyzed cell type-specific changes in transcriptional noise and the changes in cell type composition of the mammalian lung. No robust pattern of cell type-specific transcriptional noise alteration was found across aging lung datasets. In contrast, age-associated changes in cell type composition of the lung were consistently found, particularly of immune cells. These results suggest that claims of increased transcriptional noise of aged tissues should be reformulated.

The human body contains hundreds of different cell types which vary greatly in shape and size despite all sharing the same genetic material. This is because each cell switches on, or 'expresses', a unique set of genes that gives them a specific identity, such as becoming a nerve or a muscle cell. Recent studies have shown that cells in some tissues tend to lose their identity with age, and activate some of the genes that define them less strongly. This results in seemingly identical cells expressing the same genes in a more variable way, a phenomenon commonly referred to as noise. A technique called single-cell RNA sequencing is typically used to measure the activity of genes in individual cells, and has been used to study the role of noise in a wide range of aging tissues. However, the results of these studies have been analyzed using different computational methods, making it difficult to make comparisons between tissues and organisms. This has led to an ongoing debate about whether increased noise is a signature feature of aging, and if it is experienced throughout the body or restricted to certain cell types. To overcome this, Ibáñez-Solé, Ascensión et al. developed two new computational tools for analyzing noise and changes in cell identity: these were then applied to seven unique sequencing datasets which had been collected from various tissues in humans and mice at different ages. While there were some differences in the level of noise between young and old cells, these changes were not consistent across tissues and organisms. In contrast, other features associated with aging were consistently found in each of the sequencing datasets. The role of noise in aging has been gaining increasingly more attention in the scientific literature. However, the findings of Ibáñez-Solé, Ascensión et al. suggest that this phenomenon is not a hallmark of the aging process, and that the field should focus on other factors that reduce the health of tissues and cells as organisms get older. The computational approach they developed could also be used to evaluate the role of noise in other contexts, such as certain diseases.

Differential DNA Methylation of THOR and hTAPAS in the Regulation of hTERT and the Diagnosis of Cancer.

BACKGROUND: Although DNA methylation in the gene promoters usually represses gene expression, the TERT hypermethylated oncological region (THOR) located 5' of the hTERT gene is hypermethylated when hTERT is expressed in diverse cancer types, including urothelial cancer (UC). METHODS: Comprehensive MeDIP and DNA methylation array analyses complemented by the technically independent method of bisulfite genomic sequencing were applied on pathologically reviewed and classified urothelial carcinoma specimens and healthy urothelial tissue samples to reveal the methylation status of THOR in detail. RESULTS: The detailed DNA methylation profiles reveal the exact positions of differentially methylated CpG dinucleotides within THOR in urothelial cancer and provide evidence ofa diverging role of methylation of these CpGs in the regulation of hTERT. In particular, our data suggest a regulating mechanism in which THOR methylation acts on hTERT expression through epigenetic silencing of the lncRNA hTERT antisense promoter-associated (hTAPAS), which represses hTERT. CONCLUSIONS: These findings precisely define the most differentially methylated CpGs of THOR in early urothelial cancer, enabling optimal design of Methylation-Specific PCR (MSPCR) primers to reliably probe these methylation differences for diagnostic and prognostic purposes. In addition, this strategy presents a prime example that is also applicable to many other malignancies. Finally, the first evidence for the underlying epigenetic mechanism regulating hTERT expression through the methylation status of THOR is provided.

Senescence plays a role in myotonic dystrophy type 1.

Myotonic dystrophy type 1 (DM1; MIM #160900) is an autosomal dominant disorder, clinically characterized by progressive muscular weakness and multisystem degeneration. The broad phenotypes observed in patients with DM1 resemble the appearance of an accelerated aging process. However, the molecular mechanisms underlying these phenotypes remain largely unknown. Transcriptomic analysis of fibroblasts derived from patients with DM1 and healthy individuals revealed a decrease in cell cycle activity, cell division, and DNA damage response in DM1, all of which related to the accumulation of cellular senescence. The data from transcriptome analyses were corroborated in human myoblasts and blood samples, as well as in mouse and Drosophila models of the disease. Serial passage studies in vitro confirmed the accelerated increase in senescence and the acquisition of a senescence-associated secretory phenotype in DM1 fibroblasts, whereas the DM1 Drosophila model showed reduced longevity and impaired locomotor activity. Moreover, functional studies highlighted the impact of BMI1 and downstream p16INK4A/RB and ARF/p53/p21CIP pathways in DM1-associated cellular phenotypes. Importantly, treatment with the senolytic compounds Quercetin, Dasatinib, or Navitoclax reversed the accelerated aging phenotypes in both DM1 fibroblasts in vitro and in Drosophila in vivo. Our results identify the accumulation of senescence as part of DM1 pathophysiology and, therefore, demonstrate the efficacy of senolytic compounds in the preclinical setting.

Induced Endothelial Cell-Integrated Liver Assembloids Promote Hepatic Maturation and Therapeutic Effect on Cholestatic Liver Fibrosis.

The transplantation of pluripotent stem cell (PSC)-derived liver organoids has been studied to solve the current donor shortage. However, the differentiation of unintended cell populations, difficulty in generating multi-lineage organoids, and tumorigenicity of PSC-derived organoids are challenges. However, direct conversion technology has allowed for the generation lineage-restricted induced stem cells from somatic cells bypassing the pluripotent state, thereby eliminating tumorigenic risks. Here, liver assembloids (iHEAs) were generated by integrating induced endothelial cells (iECs) into the liver organoids (iHLOs) generated with induced hepatic stem cells (iHepSCs). Liver assembloids showed enhanced functional maturity compared to iHLOs in vitro and improved therapeutic effects on cholestatic liver fibrosis animals in vivo. Mechanistically, FN1 expressed from iECs led to the upregulation of Itgα5/ß1 and Hnf4α in iHEAs and were correlated to the decreased expression of genes related to hepatic stellate cell activation such as Lox and Spp1 in the cholestatic liver fibrosis animals. In conclusion, our study demonstrates the possibility of generating transplantable iHEAs with directly converted cells, and our results evidence that integrating iECs allows iHEAs to have enhanced hepatic maturation compared to iHLOs.

Role of Furin in Colon Cancer Stem Cells Malignant Phenotype and Expression of LGR5 and NANOG in KRAS and BRAF-Mutated Colon Tumors.

Proprotein convertases or PCs are known to regulate the malignant phenotype of colon cancer cells by different mechanisms, but their effects on cancer stem cells (CSCs) have been less widely investigated. Here, we report that PCs expression is altered in colon CSCs, and the inhibition of their activity reduced colon CSCs growth, survival, and invasion in three-dimensional spheroid cultures. In vivo, repression of PCs activity by the general PC inhibitors α1-PDX, Spn4A, or decanoyl-RVKR-chloromethylketone (CMK) significantly reduced tumor expression levels of the stem cell markers LGR5 and NANOG that are associated with reduced tumor xenografts. Further analysis revealed that reduced tumor growth mediated by specific silencing of the convertase Furin in KRAS or BRAF mutated-induced colon tumors was associated with reduced expression of LGR5 and NANOG compared to wild-type KRAS and BRAF tumors. Analysis of various calcium regulator molecules revealed that while the calcium-transporting ATPase 4 (ATP2B4) is downregulated in all the Furin-silenced colon cancer cells, the Ca2+-mobilizing P2Y receptors, was specifically repressed in BRAF mutated cells and ORAI1 and CACNA1H in KRAS mutated cells. Taken together, our findings indicate that PCs play an important role in the malignant phenotype of colon CSCs and stem cell markers' expression and highlight PCs repression, particularly of Furin, to target colon tumors with KRAS or BRAF mutation.

Triku: a feature selection method based on nearest neighbors for single-cell data.

BACKGROUND: Feature selection is a relevant step in the analysis of single-cell RNA sequencing datasets. Most of the current feature selection methods are based on general univariate descriptors of the data such as the dispersion or the percentage of zeros. Despite the use of correction methods, the generality of these feature selection methods biases the genes selected towards highly expressed genes, instead of the genes defining the cell populations of the dataset. RESULTS: Triku is a feature selection method that favors genes defining the main cell populations. It does so by selecting genes expressed by groups of cells that are close in the k-nearest neighbor graph. The expression of these genes is higher than the expected expression if the k-cells were chosen at random. Triku efficiently recovers cell populations present in artificial and biological benchmarking datasets, based on adjusted Rand index, normalized mutual information, supervised classification, and silhouette coefficient measurements. Additionally, gene sets selected by triku are more likely to be related to relevant Gene Ontology terms and contain fewer ribosomal and mitochondrial genes. CONCLUSION: Triku is developed in Python 3 and is available at https://github.com/alexmascension/triku.

A balanced Oct4 interactome is crucial for maintaining pluripotency.

Oct4 collaborates primarily with other transcriptional factors or coregulators to maintain pluripotency. However, how Oct4 exerts its function is still unclear. Here, we show that the Oct4 linker interface mediates competing yet balanced Oct4 protein interactions that are crucial for maintaining pluripotency. Oct4 linker mutant embryonic stem cells (ESCs) show decreased expression of self-renewal genes and increased expression of differentiation genes, resulting in impaired ESC self-renewal and early embryonic development. The linker mutation interrupts the balanced Oct4 interactome. In mutant ESCs, the interaction between Oct4 and Klf5 is decreased. In contrast, interactions between Oct4 and Cbx1, Ctr9, and Cdc73 are increased, disrupting the epigenetic state of ESCs. Control of the expression level of Klf5, Cbx1, or Cdc73 rebalances the Oct4 interactome and rescues the pluripotency of linker mutant ESCs, indicating that such factors interact with Oct4 competitively. Thus, we provide previously unidentified molecular insights into how Oct4 maintains pluripotency.

Epigenetics in the Diagnosis and Therapy of Malignant Melanoma.

Epigenetic mechanisms are fundamentally important for cancer initiation and development. However, a survey of the literature reveals that, to date, they appear less comprehensively investigated in melanoma than in many other cancers, e.g., prostate, breast, and colon carcinoma. The aim of this review is to provide a short summary of epigenetic aspects of functional relevance for melanoma pathogenesis. In addition, some new perspectives from epigenetic research in other cancers with potential for melanoma diagnosis and therapy are introduced. For example, the PrimeEpiHit hypothesis in urothelial carcinoma, which, similarly to malignant melanoma, can also be triggered by a single exogenous noxa, states that one of the first steps for cancer initiation could be epigenetic changes in key genes of one-carbon metabolism. The application of such insights may contribute to further progress in the diagnosis and therapy of melanoma, a deadly type of cancer.