A risk-reward examination of sample multiplexing reagents for single cell RNA-Seq.

Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNA-Seq experiments, facilitating more accurate and cost-effective studies.

scPipe: an extended preprocessing pipeline for comprehensive single-cell ATAC-Seq data integration in R/Bioconductor.

scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify 'true' cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.

Artificial intelligence takes center stage: exploring the capabilities and implications of ChatGPT and other AI-assisted technologies in scientific research and education.

The emergence of large language models (LLMs) and assisted artificial intelligence (AI) technologies have revolutionized the way in which we interact with technology. A recent symposium at the Walter and Eliza Hall Institute explored the current practical applications of LLMs in medical research and canvassed the emerging ethical, legal and social implications for the use of AI-assisted technologies in the sciences. This paper provides an overview of the symposium's key themes and discussions delivered by diverse speakers, including early career researchers, group leaders, educators and policy-makers highlighting the opportunities and challenges that lie ahead for scientific researchers and educators as we continue to explore the potential of this cutting-edge and emerging technology.

Type 1 conventional dendritic cell fate and function are controlled by DC-SCRIPT.

The functional diversification of dendritic cells (DCs) is a key step in establishing protective immune responses. Despite the importance of DC lineage diversity, its genetic basis is not fully understood. The transcription factor DC-SCRIPT is expressed in conventional DCs (cDCs) and their committed bone marrow progenitors but not in plasmacytoid DCs (pDCs). We show that mice lacking DC-SCRIPT displayed substantially impaired development of IRF8 (interferon regulatory factor 8)-dependent cDC1, whereas cDC2 numbers increased marginally. The residual DC-SCRIPT-deficient cDC1s had impaired capacity to capture and present cell-associated antigens and to secrete IL-12p40, two functional hallmarks of this population. Genome-wide mapping of DC-SCRIPT binding and gene expression analyses revealed a key role for DC-SCRIPT in maintaining cDC1 identity via the direct regulation of cDC1 signature genes, including Irf8 Our study reveals DC-SCRIPT to be a critical component of the gene regulatory program shaping the functional attributes of cDC1s.

Zebrafish MITF-Low Melanoma Subtype Models Reveal Transcriptional Subclusters and MITF-Independent Residual Disease.

The melanocyte-inducing transcription factor (MITF)-low melanoma transcriptional signature is predictive of poor outcomes for patients, but little is known about its biological significance, and animal models are lacking. Here, we used zebrafish genetic models with low activity of Mitfa (MITF-low) and established that the MITF-low state is causal of melanoma progression and a predictor of melanoma biological subtype. MITF-low zebrafish melanomas resembled human MITF-low melanomas and were enriched for stem and invasive (mesenchymal) gene signatures. MITF-low activity coupled with a p53 mutation was sufficient to promote superficial growth melanomas, whereas BRAFV600E accelerated MITF-low melanoma onset and further promoted the development of MITF-high nodular growth melanomas. Genetic inhibition of MITF activity led to rapid regression; recurrence occurred following reactivation of MITF. At the regression site, there was minimal residual disease that was resistant to loss of MITF activity (termed MITF-independent cells) with very low-to-no MITF activity or protein. Transcriptomic analysis of MITF-independent residual disease showed enrichment of mesenchymal and neural crest stem cell signatures similar to human therapy-resistant melanomas. Single-cell RNA sequencing revealed MITF-independent residual disease was heterogeneous depending on melanoma subtype. Further, there was a shared subpopulation of residual disease cells that was enriched for a neural crest G0-like state that preexisted in the primary tumor and remained present in recurring melanomas. These findings suggest that invasive and stem-like programs coupled with cellular heterogeneity contribute to poor outcomes for MITF-low melanoma patients and that MITF-independent subpopulations are an important therapeutic target to achieve long-term survival outcomes. SIGNIFICANCE: This study provides a useful model for MITF-low melanomas and MITF-independent cell populations that can be used to study the mechanisms that drive these tumors as well as identify potential therapeutic options.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/22/5769/F1.large.jpg.

Multilayered Heterogeneity of Glioblastoma Stem Cells: Biological and Clinical Significance.

Glioblastoma is a primary tumor of the brain with a poor prognosis. Pathological examination shows that this disease is characterized by intra-tumor morphological heterogeneity, while numerous and ongoing genomic analysis reveals multiple layers of heterogeneity. Intra-tumor and patient-to-patient heterogeneity is underpinned by cellular, genetic, and molecular heterogeneity, which is thought to be key determinants of time to tumor recurrence and resistance to therapy. The key cell type believed to contribute to the establishment and ongoing evolution of tumor heterogeneity is a glioma stem cell (GSC) subpopulation. In this chapter, we review, highlight, and discuss controversies and clinical relevance of glioblastoma heterogeneity and its cellular basis. Characterization of how cancer stem cells (CSCs) behave is important in understanding how tumors are initiated and how they recur following initial treatment.

Cell quiescence correlates with enhanced glioblastoma cell invasion and cytotoxic resistance.

Glioblastoma (GBM) tumor cells exhibit drug resistance and are highly infiltrative. GBM stem cells (GSCs), which have low proliferative capacity are thought to be one of the sources of resistant cells which result in relapse/recurrence. However, the molecular mechanisms regulating quiescent-specific tumor cell biology are not well understood. Using human GBM cell lines and patient-derived GBM cells, Oregon Green dye retention was used to identify and isolate the slow-cycling, quiescent-like cell subpopulation from the more proliferative cells in culture. Sensitivity of cell subpopulations to temozolomide and radiation, as well as the migration and invasive potential were measured. Differential expression analysis following RNAseq identified genes enriched in the quiescent cell subpopulation. Orthotopic transplantation of cells into mice was used to compare the in vivo malignancy and invasive capacity of the cells. Proliferative quiescence correlated with better TMZ resistance and enhanced cell invasion, in vitro and in vivo. RNAseq expression analysis identified genes involved in the regulation cell invasion/migration and a three-gene signature, TGFBI, IGFBP3, CHI3L1, overexpressed in quiescent cells which correlates with poor GBM patient survival.

PI3K activation in neural stem cells drives tumorigenesis which can be ameliorated by targeting the cAMP response element binding protein.

Background: Hyperactivation of phosphoinositide 3-kinase (PI3K) signaling is common in cancers, but the precise role of the pathway in glioma biology remains to be determined. Some understanding of PI3K signaling mechanisms in brain cancer comes from studies on neural stem/progenitor cells (NSPCs), where signals transmitted via the PI3K pathway cooperate with other intracellular pathways and downstream transcription factors to regulate critical cell functions. Methods: To investigate the role of the PI3K pathway in glioma initiation and development, we generated a mouse model targeting the inducible expression of a PIK3CAH1047A oncogenic mutant and deletion of the PI3K negative regulator, phosphatase and tensin homolog (PTEN), to NSPCs. Results: Expression of a Pik3caH1047A was sufficient to generate tumors with oligodendroglial features, but simultaneous loss of PTEN was required for the development of invasive, high-grade glioma. Pik3caH1047A-PTEN mutant NSPCs exhibited enhanced neurosphere formation which correlated with increased Wnt signaling, while loss of cAMP response element binding protein (CREB) in Pik3caH1047A-Pten mutant tumors led to longer symptom-free survival in mice. Conclusion: Taken together, our findings present a novel mouse model for glioma demonstrating that the PI3K pathway is important for initiation of tumorigenesis and that disruption of downstream CREB signaling attenuates tumor expansion.

Expression of CD133 and CD44 in glioblastoma stem cells correlates with cell proliferation, phenotype stability and intra-tumor heterogeneity.

Glioblastoma (GBM) is a heterogeneous tumor of the brain with a poor prognosis due to recurrence and drug resistance following therapy. Genome-wide profiling has revealed the existence of distinct GBM molecular subtypes that respond differently to aggressive therapies. Despite this, molecular subtype does not predict recurrence or drug resistance and overall survival is similar across subtypes. One of the key features contributing to tumor recurrence and resistance to therapy is proposed to be an underlying subpopulation of resistant glioma stem cells (GSC). CD133 expression has been used as a marker of GSCs, however recent evidence suggests the relationship between CD133 expression, GSCs and molecular subtype is more complex than initially proposed. The expression of CD133, Olig2 and CD44 was investigated using patient derived glioma stem-like cells (PDGCs) in vitro and in vivo. Different PDGCs exhibited a characteristic equilibrium of distinct CD133+ and CD44+ subpopulations and the influence of environmental factors on the intra-tumor equilibrium of CD133+ and CD44+ cells in PDGCs was also investigated, with hypoxia inducing a CD44+ to CD133+ shift and chemo-radiotherapy inducing a CD133+ to CD44+ shift. These data suggest that surveillance and modulation of intra-tumor heterogeneity using molecular markers at initial surgery and surgery for recurrent GBM may be important for more effective management of GBM.

Coexpression analysis of CD133 and CD44 identifies proneural and mesenchymal subtypes of glioblastoma multiforme.

Accumulating evidence suggests that the stem cell markers CD133 and CD44 indicate molecular subtype in Glioblastoma Multiforme (GBM). Gene coexpression analysis of The Cancer Genome Atlas GBM dataset was undertaken to compare markers of the Glioblastoma Stem-Progenitor Cell (GSPC) phenotype. Pearson correlation identified genes coexpressed with stem cell markers, which were then used to build a gene signature that classifies patients based on a CD133 coexpression module signature (CD133-M) or CD44-M subtype. CD133-M tumors were enriched for the Proneural (PN) GBM subtype compared to Mesenchymal (MES) subtype for CD44-M tumors. Gene set enrichment identified DNA replication/cell cycle genes in the CD133-M and invasion/migration in CD44-M, while functional experiments showed enhanced cellular growth in CD133 expressing cells and enhanced invasion in cells expressing CD44. As with the 4 major molecular subtypes of GBM, there was no long-term survival difference between CD44-M and CD133-M patients, although CD44-M patients responded better to temozolomide while CD133-M patients benefited from radiotherapy. The use of a targeted coexpression approach to predict functional properties of surface marker expressing cells is novel, and in the context of GBM, supports accumulating evidence that CD133 and CD44 protein marker expression correlates with molecular subtype.

Insights into the next generation of cancer stem cell research.

The understanding of how cancer stem cells (CSCs) or tumor-initiating cells (TICs) behave is important in understanding how tumors are initiated and how they recur following initial treatment. More specifically to understand how CSCs behave, the different signaling mechanisms orchestrating their growth, cell cycle dynamics, differentiation, trans-differentiation and survival following cytotoxic challenges need to be deciphered. Ultimately this will advance the ability to predict how these cells will behave in individual patients and under different therapeutic conditions. Second or next-generation sequencing (NGS) capabilities have provided researchers a window into the molecular and genetic clockwork of CSCs at an unprecedented resolution and depth, with throughput capabilities allowing sequencing of hundreds of samples in relatively short timeframes and at relatively modest costs More specifically NGS gives us the ability to accurately determine the genomic and transcriptomic nature of CSCs. These technologies and the publicly available cancer genome databases, together with the ever increasing computing power available to researchers locally or via cloud-based servers are changing the way biomedical cancer research is approached.

In vivo activity of combined PI3K/mTOR and MEK inhibition in a Kras(G12D);Pten deletion mouse model of ovarian cancer.

The phosphatidylinositol 3-kinase (PI3K)/Akt pathway is commonly dysregulated in human cancer, making it an attractive target for novel anticancer therapeutics. We have used a mouse model of ovarian cancer generated by Kras(G12D) activation and Pten deletion in the ovarian surface epithelium for the preclinical assessment of a novel PI3K/mTOR inhibitor PF-04691502. To enable higher throughput studies, we developed an orthotopic primary transplant model from these mice and evaluated therapeutic response to PF-04691502 using small-animal ultrasound and FDG-PET imaging. PF-04691502 inhibited tumor growth at 7 days by 72% ± 9. FDG-PET imaging revealed that PF-04691502 reduced glucose metabolism dramatically, suggesting FDG-PET may be exploited as an imaging biomarker of target inhibition by PF-04691502. Tissue biomarkers of PI3K/mTOR pathway activity, p-AKT (S473), and p-RPS6 (S240/244), were also dramatically inhibited following PF-04691502 treatment. However, as a single agent, PF-04691502 did not induce tumor regression and the long-term efficacy was limited, with tumor proliferation continuing in the presence of drug treatment. We hypothesized that tumor progression was because of concomitant activation of the mitogen-activated protein kinase pathway downstream of Kras(G12D) expression promoting cell survival and that the therapeutic effect of PF-04691502 would be enhanced by combinatory inhibition of MEK using PD-0325901. This combination induced striking tumor regression, apoptosis associated with upregulation of Bim and downregulation of Mcl-1, and greatly improved duration of survival. These data suggest that contemporaneous MEK inhibition enhances the cytotoxicity associated with abrogation of PI3K/mTOR signaling, converting tumor growth inhibition to tumor regression in a mouse model of ovarian cancer driven by PTEN loss and mutant K-Ras.