Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma

Stemness in solid malignancies: coping with immune attack

Immunotherapy has become a key new pillar of cancer treatment, and this has sparked interest in understanding mechanisms of cancer immune evasion. It has long been appreciated that cancers are constituted by heterogeneous populations of tumour cells. This feature is often fuelled by specialized cells that have molecular programs resembling tissue stem cells. Although these cancer stem cells (CSCs) have capacity for unlimited self-renewal and differentiation, it is increasingly evident that some CSCs are capable of achieving remarkable immune resistance. Given that most immunotherapy regiments have overlooked CSC-specific immune-evasive mechanisms, many current treatment strategies often lead to cancer relapse. This Review focuses on advancements in understanding how CSCs in solid tumours achieve their unique immune-evasive properties, enabling them to drive tumour regrowth. Moreover, as cancers often arise from tissue stem cells that acquired oncogenic mutations, we discuss how tissue stem cells undergoing malignant transformation activate intrinsic immune-evasive mechanisms and establish close interactions with suppressive immune cells to escape immune surveillance. In addition, we summarize how in advanced disease stages, CSCs often hijack features of normal stem cells to resist antitumour immunity. Finally, we provide insights in how to design a new generation of cancer immunotherapies to ensure elimination of CSCs.

Glioblastoma functional heterogeneity and enrichment of cancer stem cells with tumor recurrence

Glioblastoma (GBM) is an incurable disease with high intratumoral heterogeneity. Bioinformatic studies have examined transcriptional heterogeneity with differing conclusions. Here, we characterize GBM heterogeneity and highlight critical phenotypic and hierarchical roles for quiescent cancer stem cells (qCSCs). Unsupervised single-cell transcriptomic analysis of patient-derived xenografts (PDXs) delineates six GBM transcriptional states with unique tumor exclusive gene signatures, five of which display congruence with central nervous system (CNS) cell lineages. We employ a surrogate tumor evolution assay by serial xenograft transplantation to demonstrate faithful preservation of somatic mutations, transcriptome, and qCSCs. PDX chemotherapy results in CSC resistance and expansion, also seen in recurrent patient GBM. In aggregate, these novel GBM transcriptional signatures exclusively identify tumor cells and define the hierarchical landscape as stable biologically discernible cell types that allow capture of their evolution upon recurrence, emphasizing the importance of CSCs and demonstrating general relevance to all GBM.

Multi-omic profiling highlights factors associated with resistance to immuno-chemotherapy in non-small-cell lung cancer

Although immune checkpoint blockade (ICB) therapies have shifted the treatment paradigm for non-small-cell lung cancer (NSCLC), many patients remain resistant. Here we characterize the tumor cell states and spatial cellular compositions of the NSCLC tumor microenvironment (TME) by analyzing single-cell transcriptomes of 232,080 cells and spatially resolved transcriptomes of tumors from 19 patients before and after ICB-chemotherapy. We find that tumor cells and secreted phosphoprotein 1-positive macrophages interact with collagen type XI alpha 1 chain-positive cancer-associated fibroblasts to stimulate the deposition and entanglement of collagen fibers at tumor boundaries, obstructing T cell infiltration and leading to poor prognosis. We also reveal distinct states of tertiary lymphoid structures (TLSs) in the TME. Activated TLSs are associated with improved prognosis, whereas a hypoxic microenvironment appears to suppress TLS development and is associated with poor prognosis. Our study provides novel insights into different cellular and molecular components corresponding to NSCLC ICB-chemotherapeutic responsiveness, which will benefit future individualized immuno-chemotherapy.

Pan-cancer single cell and spatial transcriptomics analysis deciphers the molecular landscapes of senescence related cancer-associated fibroblasts and reveals its predictive value in neuroblastoma via integrated multi-omics analysis and machine learning

Introduction

Cancer-associated fibroblasts (CAFs) are a diverse group of cells that significantly contribute to reshaping the tumor microenvironment (TME), and no research has systematically explored the molecular landscapes of senescence related CAFs (senes CAF) in NB.

Methods

We utilized pan-cancer single cell and spatial transcriptomics analysis to identify the subpopulation of senes CAFs via senescence related genes, exploring its spatial distribution characteristics. Harnessing the maker genes with prognostic significance, we delineated the molecular landscapes of senes CAFs in bulk-seq data. We established the senes CAFs related signature (SCRS) by amalgamating 12 and 10 distinct machine learning (ML) algorithms to precisely diagnose stage 4 NB and to predict prognosis in NB. Based on risk scores calculated by prognostic SCRS, patients were categorized into high and low risk groups according to median risk score. We conducted comprehensive analysis between two risk groups, in terms of clinical applications, immune microenvironment, somatic mutations, immunotherapy, chemotherapy and single cell level. Ultimately, we explore the biological function of the hub gene JAK1 in pan-cancer multi-omics landscape.

Results

Through integrated analysis of pan-cancer spatial and single-cell transcriptomics data, we identified distinct functional subgroups of CAFs and characterized their spatial distribution patterns. With marker genes of senes CAF and leave-one-out cross-validation, we selected RF algorithm to establish diagnostic SCRS, and SuperPC algorithm to develop prognostic SCRS. SCRS demonstrated a stable predictive capability, outperforming the previously published NB signatures and clinic variables. We stratified NB patients into high and low risk group, which showed the low-risk group with a superior survival outcome, an abundant immune infiltration, a different mutation landscape, and an enhanced sensitivity to immunotherapy. Single cell analysis reveals biologically cellular variations underlying model genes of SCRS. Spatial transcriptomics delineated the molecular variant expressions of hub gene JAK1 in malignant cells across cancers, while immunohistochemistry validated the differential protein levels of JAK1 in NB.

Conclusion

Based on multi-omics analysis and ML algorithms, we successfully developed the SCRS to enable accurate diagnosis and prognostic stratification in NB, which shed light on molecular landscapes of senes CAF and clinical utilization of SCRS.

Gene choice in cancer cells is exclusive in ion transport but concurrent in DNA replication

Cancers share common cellular and physiological features. Little is known about whether distinctive gene expression patterns can be displayed at the single-cell level by gene families in cancer cells. The expression of gene homologs within a family can exhibit concurrence and exclusivity. Concurrence can promote all-or-none expression patterns of related genes and underlie alternative physiological states. Conversely, exclusive gene families express the same or similar number of homologs in each cell, allowing a broad repertoire of cell identities to be generated. We show that gene families involved in the cell-cycle and antigen presentation are expressed concurrently. Concurrence in the DNA replication complex MCM reflects the replicative status of cells, including cell lines and cancer-derived organoids. Exclusive expression requires precise regulatory mechanism, but cancer cells retain this form of control for ion homeostasis and extend it to gene families involved in cell migration. Thus, the cell adhesion-based identity of healthy cells is transformed to an identity based on migration in the population of cancer cells, reminiscent of epithelial-mesenchymal transition.

Unveiling Immunotherapy Evasion in Lung Cancer: The Role of Fanconi Anemia and Stemness Genes in Shaping an Immunosuppressive Microenvironment

The study aimed to investigate the fanconi anemia (FA)-related and stemness-related genes in lung cancer (LC) patients. Firstly, we identified stemness-related genes through weighted gene co-expression network analysis combined with TCGA database. Further combined stemness-related genes with FA-related genes to screen for prognostic-related genes. Risk score was constructed from the screened genes and comprehensive bioinformatics analyses were performed. Finally, single-cell data and in vitro experiment were used to validate our results. We screened a total of eight genes to construct a risk score. The risk score was an independent prognostic factor for LC. The validation results of multiple GEO databases were consistent with our results. Functional and pathway enrichment analysis showed that risk score was associated with cell cycle, DNA replication, DNA damage repair, and immune-related pathways. The results showed to be related to the stem cell self-renewal and proliferation. Besides, we also found that patients with higher risk scores had lower immune activity and function, and the effectiveness of immunotherapy might be poorer, with a higher rate of immune escape. Finally, our results revealed that SLC2A1 had the highest correlation with B cells in single-cell data analysis, and we validated its correlation with B cells and its expression with FA-related genes, tumor invasiveness, stemness, and drug sensitivity. Our research constructed a risk score based on FA-related and tumor stemness-related specific genes. In addition to accurately predicting the prognosis of patients with LC, the risk score may also serve as an innovative and viable predictor of immunotherapy response.

SCInter: A comprehensive single-cell transcriptome integration database for human and mouse

Single-cell RNA sequencing (scRNA-seq), which profiles gene expression at the cellular level, has effectively explored cell heterogeneity and reconstructed developmental trajectories. With the increasing research on diseases and biological processes, scRNA-seq datasets are accumulating rapidly, highlighting the urgent need for collecting and processing these data to support comprehensive and effective annotation and analysis. Here, we have developed a comprehensive Single-Cell transcriptome integration database for human and mouse (SCInter, https://bio.liclab.net/SCInter/index.php), which aims to provide a manually curated database that supports the provision of gene expression profiles across various cell types at the sample level. The current version of SCInter includes 115 integrated datasets and 1016 samples, covering nearly 150 tissues/cell lines. It contains 8016,646 cell markers in 457 identified cell types. SCInter enabled comprehensive analysis of cataloged single-cell data encompassing quality control (QC), clustering, cell markers, multi-method cell type automatic annotation, predicting cell differentiation trajectories and so on. At the same time, SCInter provided a user-friendly interface to query, browse, analyze and visualize each integrated dataset and single cell sample, along with comprehensive QC reports and processing results. It will facilitate the identification of cell type in different cell subpopulations and explore developmental trajectories, enhancing the study of cell heterogeneity in the fields of immunology and oncology.

Single-cell transcriptomics reveals IRF7 regulation of the tumor microenvironment in isocitrate dehydrogenase wild-type glioma

Mutations in isocitrate dehydrogenase (IDH) are important markers of glioma prognosis. However, few studies have examined the gene expression regulatory network (GRN) in IDH-mutant and wild-type gliomas. In this study, single-cell RNA sequencing and spatial transcriptome sequencing were used to analyze the GRN of cell subsets in patients with IDH-mutant and wild-type gliomas. Through gene transcriptional regulation analysis, we identified the M4 module, whose transcription factor activity is highly expressed in IDH wild-type gliomas compared to IDH-mutants. Enrichment analysis revealed that these genes were predominantly expressed in microglia and macrophages, with significant enrichment in interferon-related signaling pathways. Interferon regulatory factor 7 (IRF7), a transcription factor within this pathway, showed the highest percentage of enrichment and was primarily localized in the core region of wild-type IDH tumors. A machine-learning prognostic model identified novel subgroups within the wild-type IDH population. Additionally, IRF7 was shown to promote the proliferation and migration of T98G and U251 cells in vitro, and its knockdown affected glioma cell proliferation in vivo. This study systematically established the regulatory mechanism of IDH transcriptional activity in gliomas at the single-cell level and drew a corresponding cell map. The study presents a transcriptional regulatory activity map for IDH wild-type gliomas, involving single-cell RNA sequencing and spatial transcriptomics to identify gene regulatory networks, machine learning models for IDH subtyping, and experimental validation, highlighting the role of IRF7 in glioma progression.

SOX10 mediates glioblastoma cell-state plasticity

Phenotypic plasticity is a cause of glioblastoma therapy failure. We previously showed that suppressing the oligodendrocyte-lineage regulator SOX10 promotes glioblastoma progression. Here, we analyze SOX10-mediated phenotypic plasticity and exploit it for glioblastoma therapy design. We show that low SOX10 expression is linked to neural stem-cell (NSC)-like glioblastoma cell states and is a consequence of temozolomide treatment in animal and cell line models. Single-cell transcriptome profiling of Sox10-KD tumors indicates that Sox10 suppression is sufficient to induce tumor progression to an aggressive NSC/developmental-like phenotype, including a quiescent NSC-like cell population. The quiescent NSC state is induced by temozolomide and Sox10-KD and reduced by Notch pathway inhibition in cell line models. Combination treatment using Notch and HDAC/PI3K inhibitors extends the survival of mice carrying Sox10-KD tumors, validating our experimental therapy approach. In summary, SOX10 suppression mediates glioblastoma progression through NSC/developmental cell-state transition, including the induction of a targetable quiescent NSC state. This work provides a rationale for the design of tumor therapies based on single-cell phenotypic plasticity analysis.

Ribosome biogenesis is essential for hemogenic endothelial cells to generate hematopoietic stem cells

Undergoing endothelial-to-hematopoietic transition, a small fraction of embryonic aortic endothelial cells specializes into hemogenic endothelial cells (HECs) and eventually gives rise to hematopoietic stem cells (HSCs). Previously, we found that the activity of ribosome biogenesis (RiBi) is highly enriched in the HSC-primed HECs compared with adjacent arterial endothelial cells; however, whether RiBi is required in HECs for the generation of HSCs remains to be determined. Here, we have found that robust RiBi is markedly augmented during the endothelial-to-hematopoietic transition in mouse. Pharmacological inhibition of RiBi completely impeded the generation of HSCs in explant cultures. Moreover, disrupting RiBi selectively interrupted the HSC generation potential of HECs rather than T1 pre-HSCs, which was in line with its influence on cell cycle activity. Further investigation revealed that, upon HEC specification, the master transcription factor Runx1 dramatically bound to the loci of genes involved in RiBi, thereby facilitating this biological process. Taken together, our study provides functional evidence showing the indispensable role of RiBi in generating HSCs from HECs, providing previously unreported insights that may contribute to the improvement of HSC regeneration strategies.

Exercise Induced Endothelial Mesenchymal Transition (EndMT) Facilitates Meniscal Fibrocartilage Regeneration

The meniscus is a semilunar wedge-shaped fibrocartilage tissue within the knee joint that is important for withstanding mechanical shock during joint motion. The intrinsic healing capacity of meniscus tissue is very limited, which makes meniscectomy the primary treatment method in the clinic. An effective translational strategy for regenerating the meniscus after total or subtotal meniscectomy, particularly for extensive meniscal lesions or degeneration, is yet to be developed. The present study demonstrates that the endothelial mesenchymal transition (EndMT) contributes to meniscal regeneration. The mechanical stimulus facilitated EndMT by activating TGF-β2 signaling. A handheld bioprinter system to intraoperatively fabricate a porous meniscus scaffold according to the resected meniscus tissue is developed; this can simplify the scaffold fabrication procedure and period. The transplantation of a porous meniscus scaffold combined with a postoperative regular exercise stimulus facilitated the regeneration of anisotropic meniscal fibrocartilaginous tissue and protected the joint cartilage from degeneration in an ovine subtotal meniscectomy model. Single-cell RNA sequencing and immunofluorescence co-staining analyses further confirmed the occurrence of EndMT during meniscal regeneration. EndMT-transformed cells gave rise to fibrochondrocytes, subsequently contributing to meniscal fibrocartilage regeneration. Thus, an efficient translational strategy to facilitate meniscal regeneration is developed.

PDGF-BB overexpression in p53 null oligodendrocyte progenitors increases H3K27me3 and induces transcriptional changes which favor proliferation

Proneural gliomas are brain tumors characterized by enrichment of oligodendrocyte progenitor cell (OPC) transcripts and genetic alterations. In this study we sought to identify transcriptional and epigenetic differences between OPCs with Trp53 deletion and PDGF-BB overexpression (BB-p53n) and those carrying only p53 deletion (p53n). In culture, the BB-p53n OPCs display growth characteristics more similar to glioma cells than p53n OPCs. When injected in mouse brains, BB-p53n OPC form tumors, while the p53n OPCs do not. Unbiased histone proteomics and transcriptomic analysis on these OPC populations identified higher levels of the histone H3K27me3 mark and lower levels of the histone H4K20me3. The transcriptome of the BB-p53n OPCs was characterized by higher levels of transcripts related to proliferation and cell adhesion compared to p53n OPCs. Pharmacological inhibition of the enzyme responsible for histone H3K27 trimethylation (EZH2i) in BB-p53n OPCs, reduced cell cycle transcripts and increased the expression of differentiation markers, but was not sufficient to restore their growth characteristics. This suggests that PDGF-BB overexpression in p53n OPCs favors the early stages of transformation, by promoting proliferation and halting differentiation in a H3K27me3-dependent pathway, and favoring growth characteristics in a H3K27me3 independent manner.

Granulocyte colony stimulating factor promotes scarless tissue regeneration

Mammals typically heal with fibrotic scars, and treatments to regenerate human skin and hair without a scar remain elusive. We discovered that mice lacking C-X-C motif chemokine receptor 2 (CXCR2 knockout [KO]) displayed robust and complete tissue regeneration across three different injury models: skin, hair follicle, and cartilage. Remarkably, wild-type mice receiving plasma from CXCR2 KO mice through parabiosis or injections healed wounds scarlessly. A comparison of circulating proteins using multiplex ELISA revealed a 24-fold higher plasma level of granulocyte colony stimulating factor (G-CSF) in CXCR2 KO blood. Local injections of G-CSF into wild-type (WT) mouse wound beds reduced scar formation and increased scarless tissue regeneration. G-CSF directly polarized macrophages into an anti-inflammatory phenotype, and both CXCR2 KO and G-CSF-treated mice recruited more anti-inflammatory macrophages into injured areas. Modulating macrophage activation states at early time points after injury promotes scarless tissue regeneration and may offer a therapeutic approach to improve healing of human skin wounds.

CXCL9, CXCL10, and CCL19 synergistically recruit T lymphocytes to skin in lichen planus

Lichen planus (LP) is a chronic, debilitating, inflammatory disease of the skin and mucous membranes that affects 1%-2% of Americans. Its molecular pathogenesis remains poorly understood, and there are no FDA-approved treatments. We performed single-cell RNA sequencing on paired blood and skin samples (lesional and nonlesional tissue) from 7 patients with LP. We discovered that LP keratinocytes and fibroblasts specifically secrete a combination of CXCL9, CXCL10, and CCL19 cytokines. Using an in vitro migration assay with primary human T cells, we demonstrated that CCL19 in combination with either of the other 2 cytokines synergistically enhanced recruitment of CD8+ T cells more than any individual cytokine. Moreover, exhausted T cells in lesional LP skin secreted CXCL13, which, along with CCL19, also enhanced recruitment of T cells, suggesting a feed-forward loop in LP. Finally, LP blood revealed decreased circulating naive CD8+ T cells compared with that in healthy volunteers, consistent with recruitment to skin. Molecular analysis of LP skin and blood samples increased our understanding of disease pathogenesis and identified CCL19 as a new therapeutic target for treatment.

Modeling Glioma Intratumoral Heterogeneity with Primary Human Neural Stem and Progenitor Cells

Glioblastoma multiforme (GBM) is a deadly form of glioma notable for its significant intratumoral heterogeneity, which is believed to drive therapy resistance. GBM has been observed to mimic a neural stem cell hierarchy reminiscent of normal brain development. However, it is still unclear how cell-of-origin shapes intratumoral heterogeneity. Here, we develop a model of glioma initiation using neural stem and progenitor cells (NSPCs) purified from fetal human brain tissue. We previously described a method to prospectively isolate and culture tripotent neural stem cells (NSCs), bipotent glial progenitor cells (GPCs), and unipotent oligodendrocyte precursor cells (OPCs). We transduced these isogenic lines with dominant-negative TP53R175H and NF1 knockdown, a commonly-used genetic model of GBM in mice. These reprogrammed lines robustly engrafted when transplanted into the brains of immunodeficient mice, and showed significant expansion over time. Engrafted cells were reextracted from the mouse brain for single cell RNA sequencing (scRNA-seq), in order to quantify how the cell-of-origin modulates the cellular subtypes found in the resulting tumor. This result revealed the strong influence the cell-of-origin plays in glioma heterogeneity. Our platform is highly adaptable and allows for modular and systematic interrogation of how cell-of-origin shape the tumor landscape.

Role of T Lymphocytes in Glioma Immune Microenvironment: Two Sides of a Coin

Glioma is known for its immunosuppressive microenvironment, which makes it challenging to target through immunotherapies. Immune cells like macrophages, microglia, myeloid-derived suppressor cells, and T lymphocytes are known to infiltrate the glioma tumor microenvironment and regulate immune response distinctively. Among the variety of immune cells, T lymphocytes have highly complex and multifaceted roles in the glioma immune landscape. T lymphocytes, which include CD4+ helper and CD8+ cytotoxic T cells, are known for their pivotal roles in anti-tumor responses. However, these cells may behave differently in the highly dynamic glioma microenvironment, for example, via an immune invasion mechanism enforced by tumor cells. Therefore, T lymphocytes play dual roles in glioma immunity, firstly by their anti-tumor responses, and secondly by exploiting gliomas to promote immune invasion. As an immunosuppression strategy, glioma induces T-cell exhaustion and suppression of effector T cells by regulatory T cells (Tregs) or by altering their signaling pathways. Further, the expression of immune checkpoint inhibitors on the glioma cell surface leads to T cell anergy and dysfunction. Overall, this dynamic interplay between T lymphocytes and glioma is crucial for designing more effective immunotherapies. The current review provides detailed knowledge on the roles of T lymphocytes in the glioma immune microenvironment and helps to explore novel therapeutic approaches to reinvigorate T lymphocytes.

Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations

Intratumor heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression and there is a pressing need to understand the functions of heterogeneous tumor cell subpopulations within a tumor, yet systems to study these processes in vitro are limited. Single-cell RNA sequencing (scRNA-seq) has revealed that some cancer cell lines include distinct subpopulations. Here, we present clusterCleaver, a computational package that uses metrics of statistical distance to identify candidate surface markers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. With clusterCleaver, ESAM and BST2/tetherin were experimentally validated as surface markers which identify and separate major transcriptomic subpopulations within MDA-MB-231 and MDA-MB-436 cells, respectively. clusterCleaver is a computationally efficient and experimentally validated workflow for identification of surface markers for tracking and isolating transcriptomically distinct subpopulations within cell lines. This tool paves the way for studies on coexisting cancer cell subpopulations in well-defined in vitro systems.

Integrated electrophysiological and genomic profiles of single cells reveal spiking tumor cells in human glioma

Prior studies have described the complex interplay that exists between glioma cells and neurons; however, the electrophysiological properties endogenous to glioma cells remain obscure. To address this, we employed Patch-sequencing (Patch-seq) on human glioma specimens and found that one-third of patched cells in IDH mutant (IDHmut) tumors demonstrate properties of both neurons and glia. To define these hybrid cells (HCs), which fire single, short action potentials, and discern if they are of tumoral origin, we developed the single cell rule association mining (SCRAM) computational tool to annotate each cell individually. SCRAM revealed that HCs possess select features of GABAergic neurons and oligodendrocyte precursor cells, and include both tumor and non-tumor cells. These studies characterize the combined electrophysiological and molecular properties of human glioma cells and describe a cell type in human glioma with unique electrophysiological and transcriptomic properties that may also exist in the non-tumor brain.

Regulatory network analysis of Dclk1 gene expression reveals a tuft cell-ILC2 axis that inhibits pancreatic tumor progression

Dclk1 expression defines a rare population of cells in the normal pancreas whose frequency is increased at early stages of pancreatic tumorigenesis. The identity and the precise roles of Dclk1 expressing cells in pancreas have been matter of debate, although evidence suggests their involvement in a number of key functions, including regeneration and neoplasia. We employed a recently developed Dclk1 reporter mouse model and single cell RNAseq analysis to define Dclk1 expressing cells in normal pancreas and pancreatic neoplasia. In normal pancreas, Dclk1 epithelial expression identifies subsets of ductal, islet and acinar cells. In pancreatic neoplasia, Dclk1 expression identifies five epithelial cell populations, among which acinar-to-ductal metaplasia (ADM)-like cells and tuft-like cells are predominant. These two cell populations play opposing roles in pancreatic neoplasia, with Dclk1+ ADM-like cells sustaining tumor growth while Dclk1+ tuft-like cells restraining tumor progression. The differentiation of Kras mutant acinar cells into Dclk1+ tuft-like cells requires the activation of the transcription factor SPIB and is further supported by a cellular paracrine loop involving cancer group 2 innate lymphoid cells (ILC2) and cancer activated fibroblasts (CAFs) that provide IL13 and IL33, respectively. In turn, Dclk1+ tuft-like cells release angiotensinogen that plays protective roles against pancreatic neoplasia. Overall, our study provides novel insights on the biology of Dclk1+ cells in normal pancreas and unveils a protective axis against pancreatic neoplasia, involving CAFs, ILC2 and Dclk1+ tuft-like cells, which ultimately results in angiotensinogen release.

IMMUNE AND MOLECULAR CORRELATES OF RESPONSE TO IMMUNOTHERAPY REVEALED BY BRAIN-METASTATIC MELANOMA MODELS

Despite the promising results of immune checkpoint blockade (ICB) therapy, outcomes for patients with brain metastasis (BrM) remain poor. Identifying resistance mechanisms has been hindered by limited access to patient samples and relevant preclinical models. Here, we developed two mouse melanoma BrM models that recapitulate the disparate responses to ICB seen in patients. We demonstrate that these models capture the cellular and molecular complexity of human disease and reveal key factors shaping the tumor microenvironment and influencing ICB response. BR1-responsive tumor cells express inflammatory programs that polarize microglia into reactive states, eliciting robust T cell recruitment. In contrast, BR3-resistant melanoma cells are enriched in neurological programs and exploit tolerance mechanisms to maintain microglia homeostasis and limit T cell infiltration. In humans, BR1 and BR3 expression signatures correlate positively or negatively with T cell infiltration and BrM patient outcomes, respectively. Our study provides clinically relevant models and uncovers mechanistic insights into BrM ICB responses, offering potential biomarkers and therapeutic targets to improve therapy efficacy.

Scalable, compressed phenotypic screening using pooled perturbations

High-throughput phenotypic screens using biochemical perturbations and high-content readouts are constrained by limitations of scale. To address this, we establish a method of pooling exogenous perturbations followed by computational deconvolution to reduce required sample size, labor and cost. We demonstrate the increased efficiency of compressed experimental designs compared to conventional approaches through benchmarking with a bioactive small-molecule library and a high-content imaging readout. We then apply compressed screening in two biological discovery campaigns. In the first, we use early-passage pancreatic cancer organoids to map transcriptional responses to a library of recombinant tumor microenvironment protein ligands, uncovering reproducible phenotypic shifts induced by specific ligands distinct from canonical reference signatures and correlated with clinical outcome. In the second, we identify the pleotropic modulatory effects of a chemical compound library with known mechanisms of action on primary human peripheral blood mononuclear cell immune responses. In sum, our approach empowers phenotypic screens with information-rich readouts to advance drug discovery efforts and basic biological inquiry.

XgCPred: Cell type classification using XGBoost-CNN integration and exploiting gene expression imaging in single-cell RNAseq data

BACKGROUND

The advent of single-cell RNA sequencing (scRNA-seq) has revolutionized transcriptomic research by enabling the exploration of gene expression at an individual cell level. This advancement sheds light on how cells differentiate and evolve over time. Effectively classification cell types within scRNA-seq datasets are essential for understanding the intricate cell compositions within tissues and elucidating the origins of various diseases. Challenges persist in the field, emphasizing the need for precise categorization across diverse datasets, addressing aggregated cell data, and managing the complexity of high-dimensional data spaces.

METHODOLOGY

XgCPred is a novel approach combining XGBoost with convolutional neural networks (CNNs) to provide cell type classification with better accuracy in single-cell RNA-seq data. This combo reveals how well CNNs can detect spatial hierarchy in gene expression images and how XGBoost performs with large volumes of data. XgCPred utilizes an imaging representation of gene expression that is based on the hierarchical organization of genes found in the KEGG BRITE database.

RESULTS

Rigorous testing of XgCPred across multiple scRNA-seq datasets, each presenting unique challenges such as varying cell counts, gene expression diversity, and cellular heterogeneity, has demonstrated its superiority compared to earlier methods. The algorithm shows remarkable accuracy and precision in cell type annotation, achieving near-perfect classification scores in some cases. These results underscore its capability to effectively manage data variability.

CONCLUSIONS

XgCPred distinguishes itself through its dependable and accurate cell type classification across a range of scRNA-seq datasets. Its effectiveness stems from sophisticated data handling and its ability to adapt to the complexities inherent in scRNA-seq data. XgCPred delivers reliable cell annotations essential for further biological analysis and research, marking a significant advancement in genomic studies. With scRNA-seq datasets growing in size and complexity, XgCPred offers a scalable and potent solution for cell type identification, potentially enhancing our understanding of cellular biology and aiding in the precise detection of diseases. XgCPred is a useful tool in genomic research and tailored therapy because it solves current constraints on computing efficiency and generalizability.

TGF-β signaling-related signature for predicting prognosis and therapeutic response in lower-grade glioma

Background

Low-grade glioma (LGG) is a tumor that includes World Health Organization (WHO) grade II and III glioma, the treatment of which consistently results in relapse and drug resistance. Transforming growth factor-beta (TGF-β) is a multifunctional cytokine that regulates various cellular processes, which is found to be abnormal in tumors and promotes glioma development and progression. In this study, we aimed to systematically evaluate the importance of the genes associated with TGF-β in LGG and discover the role of these genes in the prognosis and treatment response of LGG.

Methods

We used the "Bioconductor Limma" and "consensusClusterplus" R packages to screen differential and prognostic TGF-β-related genes. The R package "GSVA" was used to estimate the infiltration of immune cells and metabolism signature. The drug sensitivity for each TGF-β subtype was assessed by the R package "pRRophetic". The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to assess the copy number variation (CNV). The onco-print tool of the "complexheatmap package" was employed to visualize the somatic mutation and copy number alteration (CNA) among TGF clusters.

Results

We reported three subtypes (A, B, and C) of LGG according to the classification of TGF-β-related genes, where subtype A showed the best prognosis. Subtype B was highly enriched in immune cells. Somatic variations were observed to be diverse in all of the three TGF-β subtypes. Furthermore, another three genes (SHA, AC062021.1, and SNCG) related to TGF-β were identified, which can be a superior predictor of prognosis with a risk score.

Conclusions

LGG can be divided into three subtypes based on TGF-β signaling-related genes with distinct immune infiltration, metabolism, somatic variations, and prognosis.

Functional heterogeneity of cancer-associated fibroblasts with distinct neoadjuvant immunotherapy plus chemotherapy response in esophageal squamous cell carcinoma

Novel neoadjuvant immunotherapy combined with chemotherapy (neoICT) has improved outcomes for patients with esophageal squamous-cell carcinoma (ESCC), but challenges persist in low response rates and therapy resistance. Little is known about the intra-tumoral heterogeneity in the ESCC tumor microenvironment (TME) that underlies differential responses to neoadjuvant therapy. We applied single-cell RNA sequencing (scRNA-seq) profiling and multiplexed immunofluorescence staining to thoroughly decipher the TME in ESCC specimens from a neoadjuvant anti-PD1 combination therapy clinical trial. The cancer-associated fibroblasts (CAFs) population showed the significant alteration in abundance following neoadjuvant therapy. Specifically, IL6 + CCL2 + immunomodulatory CAFs and a novel CD248 + mechanoresponsive CAFs subset exhibited increasing infiltration. Mechanistically, CD248 + mechanoresponsive CAFs approached and lined the tumor nest to physically block the infiltration of CD8 + T cells and drug delivery, while IL6 + CCL2 + immunomodulatory CAFs induced therapeutic resistance with distinct IL-6 expression. Among patients treated with neoICT, we observed prominent CAF-T cell interactions. In particular, the NECTIN2-TIGIT ligand-receptor pair was enriched in treated samples, and TIGIT was identified as the major inhibitory checkpoint of T cells. Our findings demonstrate distinct alterations in TME constituent responses to neoadjuvant immunotherapy and identify functional phenotypes of CAFs associated with unfavorable therapeutic responses in patients. This provides potential targets to enhance responses to neoadjuvant therapy in ESCC.

DrugReSC: targeting disease-critical cell subpopulations with single-cell transcriptomic data for drug repurposing in cancer

The field of computational drug repurposing aims to uncover novel therapeutic applications for existing drugs through high-throughput data analysis. However, there is a scarcity of drug repurposing methods leveraging the cellular-level information provided by single-cell RNA sequencing data. To address this need, we propose DrugReSC, an innovative approach to drug repurposing utilizing single-cell RNA sequencing data, intending to target specific cell subpopulations critical to disease pathology. DrugReSC constructs a drug-by-cell matrix representing the transcriptional relationships between individual cells and drugs and utilizes permutation-based methods to assess drug contributions to cellular phenotypic changes. We demonstrate DrugReSC's superior performance compared to existing drug repurposing methods based on bulk or single-cell RNA sequencing data across multiple cancer case studies. In summary, DrugReSC offers a novel perspective on the utilization of single-cell sequencing data in drug repurposing methods, contributing to the advancement of precision medicine for cancer.

Impact of Hashimoto's thyroiditis on the tumor microenvironment in papillary thyroid cancer: insights from single-cell analysis

This study investigates the impact of Hashimoto's thyroiditis (HT), an autoimmune disorder, on the papillary thyroid cancer (PTC) microenvironment using a dataset of 140,456 cells from 11 patients. By comparing PTC cases with and without HT, we identify HT-specific cell populations (HASCs) and their role in creating a TSH-suppressive environment via mTE3, nTE0, and nTE2 thyroid cells. These cells facilitate intricate immune-stromal communication through the MIF-(CD74+CXCR4) axis, emphasizing immune regulation in the TSH context. In the realm of personalized medicine, our HASC-focused analysis within the TCGA-THCA dataset validates the utility of HASC profiling for guiding tailored therapies. Moreover, we introduce a novel, objective method to determine K-means clustering coefficients in copy number variation inference from bulk RNA-seq data, mitigating the arbitrariness in conventional coefficient selection. Collectively, our research presents a detailed single-cell atlas illustrating HT-PTC interactions, deepening our understanding of HT's modulatory effects on PTC microenvironments. It contributes to our understanding of autoimmunity-carcinogenesis dynamics and charts a course for discovering new therapeutic targets in PTC, advancing cancer genomics and immunotherapy research.

Performance comparison of high throughput single-cell RNA-Seq platforms in complex tissues

Single-cell transcriptomics has emerged as the preferred tool to define cell identity through the analysis of gene expression signatures. However, there are limited studies that have comprehensively compared the performance of different scRNAseq systems in complex tissues. Here, we present a systematic comparison of two well-established high throughput 3'-scRNAseq platforms: 10× Chromium and BD Rhapsody, using tumours that present high cell diversity. Our experimental design includes both fresh and artificially damaged samples from the same tumours, which also provides a comparable dataset to examine their performance under challenging conditions. The performance metrics used in this study consist of gene sensitivity, mitochondrial content, reproducibility, clustering capabilities, cell type representation and ambient RNA contamination. These analyses showed that BD Rhapsody and 10× Chromium have similar gene sensitivity, while BD Rhapsody has the highest mitochondrial content. Interestingly, we found cell type detection biases between platforms, including a lower proportion of endothelial and myofibroblast cells in BD Rhapsody and lower gene sensitivity in granulocytes for 10× Chromium. Moreover, the source of the ambient noise was different between plate-based and droplet-based platforms. In conclusion, our reported platform differential performance should be considered for the selection of the scRNAseq method during the study experimental designs.

HOXD12 defines an age-related aggressive subtype of oligodendroglioma

Oligodendroglioma, IDH-mutant and 1p/19q-codeleted has highly variable outcomes that are strongly influenced by patient age. The distribution of oligodendroglioma age is non-Gaussian and reportedly bimodal, which motivated our investigation of age-associated molecular alterations that may drive poorer outcomes. We found that elevated HOXD12 expression was associated with both older patient age and shorter survival in the TCGA (FDR < 0.01, FDR = 1e-5) and the CGGA (p = 0.03, p < 1e-3). HOXD12 gene body hypermethylation was associated with older age, higher WHO grade, and shorter survival in the TCGA (p < 1e-6, p < 0.001, p < 1e-3) and with older age and higher WHO grade in Capper et al. (p < 0.002, p = 0.014). In the TCGA, HOXD12 gene body hypermethylation and elevated expression were independently prognostic of NOTCH1 and PIK3CA mutations, loss of 15q, MYC activation, and standard histopathological features. Single-nucleus RNA and ATAC sequencing data showed that HOXD12 activity was elevated in neoplastic tissue, particularly within cycling and OPC-like cells, and was associated with a stem-like phenotype. A pan-HOX DNA methylation analysis revealed an age and survival-associated HOX-high signature that was tightly associated with HOXD12 gene body methylation. Overall, HOXD12 expression and gene body hypermethylation were associated with an older, atypically aggressive subtype of oligodendroglioma.

Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors

Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.

Mechano-osmotic signals control chromatin state and fate transitions in pluripotent stem cells

Acquisition of specific cell shapes and morphologies is a central component of cell fate transitions. Although signaling circuits and gene regulatory networks that regulate pluripotent stem cell differentiation have been intensely studied, how these networks are integrated in space and time with morphological transitions and mechanical deformations to control state transitions remains a fundamental open question. Here, we focus on two distinct models of pluripotency, primed pluripotent stem cells and pre-implantation inner cell mass cells of human embryos to discover that cell fate transitions associate with rapid changes in nuclear shape and volume which collectively alter the nuclear mechanophenotype. Mechanistic studies in human induced pluripotent stem cells further reveal that these phenotypical changes and the associated active fluctuations of the nuclear envelope arise from growth factor signaling-controlled changes in chromatin mechanics and cytoskeletal confinement. These collective mechano-osmotic changes trigger global transcriptional repression and a condensation-prone environment that primes chromatin for a cell fate transition by attenuating repression of differentiation genes. However, while this mechano-osmotic chromatin priming has the potential to accelerate fate transitions and differentiation, sustained biochemical signals are required for robust induction of specific lineages. Our findings uncover a critical mechanochemical feedback mechanism that integrates nuclear mechanics, shape and volume with biochemical signaling and chromatin state to control cell fate transition dynamics.

Recruitment of CXCR4+ type 1 innate lymphoid cells distinguishes sarcoidosis from other skin granulomatous diseases

Sarcoidosis is a multiorgan granulomatous disease that lacks diagnostic biomarkers and targeted treatments. Using blood and skin from patients with sarcoid and non-sarcoid skin granulomas, we discovered that skin granulomas from different diseases exhibit unique immune cell recruitment and molecular signatures. Sarcoid skin granulomas were specifically enriched for type 1 innate lymphoid cells (ILC1s) and B cells and exhibited molecular programs associated with formation of mature tertiary lymphoid structures (TLSs), including increased CXCL12/CXCR4 signaling. Lung sarcoidosis granulomas also displayed similar immune cell recruitment. Thus, granuloma formation was not a generic molecular response. In addition to tissue-specific effects, patients with sarcoidosis exhibited an 8-fold increase in circulating ILC1s, which correlated with treatment status. Multiple immune cell types induced CXCL12/CXCR4 signaling in sarcoidosis, including Th1 T cells, macrophages, and ILCs. Mechanistically, CXCR4 inhibition reduced sarcoidosis-activated immune cell migration, and targeting CXCR4 or total ILCs attenuated granuloma formation in a noninfectious mouse model. Taken together, our results show that ILC1s are a tissue and circulating biomarker that distinguishes sarcoidosis from other skin granulomatous diseases. Repurposing existing CXCR4 inhibitors may offer a new targeted treatment for this devastating disease.

Transcriptome sequencing reveals inflammation and macrophage heterogeneity in subacromial bursa from degenerative shoulder disorders

PURPOSE

We aimed to investigate the transcriptomic alterations that occur in the subacromial bursa (SAB) following degenerative or traumatic shoulder diseases.

MATERIALS AND METHODS

RNA sequencing was employed to evaluate the transcriptomic alterations of the SAB in individuals afflicted with degenerative rotator cuff tear (RCT), traumatic RCT and proximal humerus fracture (PHF). To gain insights into the biological significance of differentially expressed genes (DEGs), we conducted an enrichment analysis utilizing Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We further utilized single-cell RNA sequencing datasets of SAB from a recently published study to explore the associated cellular dynamics and alterations.

RESULTS

We detected 1,790 up-regulated and 1,964 down-regulated DEGs between degenerative RCT and PHF, 2,085 up-regulated and 1,919 down-regulated DEGs between degenerative RCT and traumatic RCT, and 20 up-regulated and 12 down-regulated DEGs between traumatic RCT and PHF. Given the similar expression pattern between traumatic RCT and PHF, they were integrated as the traumatic group. In comparison with the traumatic group, 1,983 up-regulated and 2,205 down-regulated DEGs were detected in degenerative SAB. Enrichment analysis of up-regulated DEGs uncovered an elevated inflammatory and immunologic responses in degenerative SAB. Single-cell transcriptomic analysis revealed macrophage represented the immune cell with the most DEGs between the degenerative and traumatic RCT.

CONCLUSION

Our results revealed that the SAB in degenerative RCT exhibited a different transcriptional signature compared to that in traumatic RCT, and enrichment analysis showed immunologic and inflammatory activations. Macrophages may play a fundamental role in this process.

Unveiling the cellular landscape: insights from single-cell RNA sequencing in multiple myeloma

Objective

The aim of this research was to gain a thorough understanding of the processes involved in cell communication and discover potential indicators for treating multiple myeloma (MM) through the use of single-cell RNA sequencing (scRNA-seq). And explored the expression of multiple myeloma-related subgroups on metal ion-related pathways to explore the relationship between MM and metal ions.

Methods

We performed a fair examination using single-cell RNA sequencing on 32 bone marrow specimens collected from 22 individuals at different points of MM advancement and 9 individuals without any health issues. To analyze the scRNA-seq data, we employed advanced computational algorithms, including Slingshot, Monocle2, and other methodologies. Specifically, Slingshot and Monocle2 enabled us to simulate the biological functionalities of different cell populations and map trajectories of cell developmental pathways. Additionally, we utilized the UMAP algorithm, a powerful dimension reduction technique, to cluster cells and identify genes that were differentially expressed across clusters.

Results

Our study revealed distinct gene expression patterns and molecular pathways within each patient, which exhibited associations with disease progression. The analysis provided insights into the tumor microenvironment (TME), intra- and inter-patient heterogeneity, and cell-cell interactions mediated by ligand-receptor signaling. And found that multiple myeloma-related subgroups were expressed higher levels in MMP and TIMP pathways, there were some associations.

Conclusion

Our study presents a fresh perspective for future research endeavors and clinical interventions in the field of MM. The identified gene expression patterns and molecular pathways hold immense potential as therapeutic targets for the treatment of multiple myeloma. The utilization of scRNA-seq technology has significantly contributed to a more precise understanding of the complex cellular processes and interactions within MM. Through these advancements, we are now better equipped to unravel the underlying mechanisms driving the development and progression of this complex disease.

Single-cell transcriptomics reveals tumor microenvironment remodeling in hepatocellular carcinoma with varying tumor subclonal complexity

Introduction

The complexity of tumor cell subclonal structure has been extensively investigated in hepatocellular carcinoma. However, the role of subclonal complexity in reshaping the tumor microenvironment (TME) remains poorly understood.

Methods

We integrated single-cell transcriptome sequencing data from four independent HCC cohorts, involving 30 samples, to decode the associations between tumor subclonal complexity and the TME. We proposed a robust metric to accurately quantify the degree of subclonal complexity for each sample based on discrete copy number variations (CNVs) profiles.

Results

We found that tumor cells in the high-complexity group originated from the cell lineage with FGB overexpression and exhibited high levels of transcription factors associated with poor survival. In contrast, tumor cells in low-complexity patients showed activation of more hallmark signaling pathways, more active cell-cell communications within the TME and a higher immune activation status. Additionally, cytokines signaling activity analysis suggested a link between HMGB1 expressed by a specific endothelial subtype and T cell proliferation.

Discussion

Our study sheds light on the intricate relationship between the complexity of subclonal structure and the TME, offering novel insights into potential therapeutic targets for HCC.

GABAergic neuronal lineage development determines clinically actionable targets in diffuse hemispheric glioma, H3G34-mutant

Diffuse hemispheric gliomas, H3G34R/V-mutant (DHG-H3G34), are lethal brain tumors lacking targeted therapies. They originate from interneuronal precursors; however, leveraging this origin for therapeutic insights remains unexplored. Here, we delineate a cellular hierarchy along the interneuron lineage development continuum, revealing that DHG-H3G34 mirror spatial patterns of progenitor streams surrounding interneuron nests, as seen during human brain development. Integrating these findings with genome-wide CRISPR-Cas9 screens identifies genes upregulated in interneuron lineage progenitors as major dependencies. Among these, CDK6 emerges as a targetable vulnerability: DHG-H3G34 tumor cells show enhanced sensitivity to CDK4/6 inhibitors and a CDK6-specific degrader, promoting a shift toward more mature interneuron-like states, reducing tumor growth, and prolonging xenograft survival. Notably, a patient with progressive DHG-H3G34 treated with a CDK4/6 inhibitor achieved 17 months of stable disease. This study underscores interneuronal progenitor-like states, organized in characteristic niches, as a distinct vulnerability in DHG-H3G34, highlighting CDK6 as a promising clinically actionable target.

Distinct tumor-TAM interactions in IDH-stratified glioma microenvironments unveiled by single-cell and spatial transcriptomics

Tumor-associated macrophages (TAMs) residing in the tumor microenvironment (TME) are characterized by their pivotal roles in tumor progression, antitumor immunity, and TME remodeling. However, a thorough comparative characterization of tumor-TAM crosstalk across IDH-defined categories of glioma remains elusive, likely contributing to mixed outcomes in clinical trials. We delineated the phenotypic heterogeneity of TAMs across IDH-stratified gliomas. Notably, two TAM subsets with a mesenchymal phenotype were enriched in IDH-WT glioblastoma (GBM) and correlated with poorer patient survival and reduced response to anti-PD-1 immune checkpoint inhibitor (ICI). We proposed SLAMF9 receptor as a potential therapeutic target. Inference of gene regulatory networks identified PPARG, ELK1, and MXI1 as master transcription factors of mesenchymal BMD-TAMs. Our analyses of reciprocal tumor-TAM interactions revealed distinct crosstalk in IDH-WT tumors, including ANXA1-FPR1/3, FN1-ITGAVB1, VEGFA-NRP1, and TNFSF12-TNFRSF12A with known contribution to immunosuppression, tumor proliferation, invasion and TAM recruitment. Spatially resolved transcriptomics further elucidated the architectural organization of highlighted communications. Furthermore, we demonstrated significant upregulation of ANXA1, FN1, NRP1, and TNFRSF12A genes in IDH-WT tumors using bulk RNA-seq and RT-qPCR. Longitudinal expression analysis of candidate genes revealed no difference between primary and recurrent tumors indicating that the interactive network of malignant states with TAMs does not drastically change upon recurrence. Collectively, our study offers insights into the unique cellular composition and communication of TAMs in glioma TME, revealing novel vulnerabilities for therapeutic interventions in IDH-WT GBM.

Clinical utility of a blood based assay for the detection of IDH1.R132H-mutant gliomas

Glioma represents the most common central nervous system neoplasm in adults. Current classification scheme utilizes molecular alterations, particularly IDH1.R132H, to stratify lesions into distinct prognostic groups. Identification of the single nucleotide variant through traditional tissue biopsy assessment poses procedural risks and does not fully reflect the heterogeneous and evolving tumor landscape. Here, we introduce a liquid biopsy assay, mt-IDH1dx. The blood-based test allows minimally invasive detection of tumor-derived extracellular vesicle RNA using only 2 ml plasma volume. We perform rigorous, blinded validation testing across the study population (n = 133), comprising of IDH1.R132H patients (n = 80), IDH1 wild-type gliomas (n = 44), and age matched healthy controls (n = 9). Results from our plasma testing demonstrate an overall sensitivity of 75.0% (95% CI: 64.1%-84.0%), specificity 88.7% (95% CI: 77.0%-95.7%), positive predictive value 90.9%, and negative predictive value 70.1% compared to the tissue gold standard. In addition to fundamental diagnostic applications, the study also highlights the utility of mt-IDH1dx platform for blood-based monitoring and surveillance, offering valuable prognostic information. Finally, the optimized workflow enables rapid and efficient completion of both tumor tissue and plasma testing in under 4 hours from the time of sampling.

PTBP1-mediated repression of neuron-specific CDC42 splicing constitutes a genomic alteration-independent, developmentally conserved vulnerability in IDH-wildtype glioblastoma

Gene co-expression networks may encode hitherto inadequately recognized vulnerabilities for adult gliomas. By identifying evolutionally conserved gene co-expression modules around EGFR (EM) or PDGFRA (PM), we recently proposed an EM/PM classification scheme, which assigns IDH-wildtype glioblastomas (GBM) into the EM subtype committed in neural stem cell compartment, IDH-mutant astrocytomas and oligodendrogliomas into the PM subtype committed in early oligodendrocyte lineage. Here, we report the identification of EM/PM subtype-specific gene co-expression networks and the characterization of hub gene polypyrimidine tract-binding protein 1 (PTBP1) as a genomic alteration-independent vulnerability in IDH-wildtype GBM. Supervised by the EM/PM classification scheme, we applied weighted gene co-expression network analysis to identify subtype-specific global gene co-expression modules. These gene co-expression modules were characterized for their clinical relevance, cellular origin and conserved expression pattern during brain development. Using lentiviral vector-mediated constitutive or inducible knockdown, we characterized the effects of PTBP1 on the survival of IDH-wildtype GBM cells, which was complemented with the analysis of PTBP1-depedent splicing pattern and overexpression of splicing target neuron-specific CDC42 (CDC42-N) isoform.  Transcriptomes of adult gliomas can be robustly assigned into 4 large gene co-expression modules that are prognostically relevant and are derived from either malignant cells of the EM/PM subtypes or tumor microenvironment. The EM subtype is associated with a malignant cell-intrinsic gene module involved in pre-mRNA splicing, DNA replication and damage response, and chromosome segregation, and a microenvironment-derived gene module predominantly involved in extracellular matrix organization and infiltrating immune cells. The PM subtype is associated with two malignant cell-intrinsic gene modules predominantly involved in transcriptional regulation and mRNA translation, respectively. Expression levels of these gene modules are independent prognostic factors and malignant cell-intrinsic gene modules are conserved during brain development. Focusing on the EM subtype, we identified PTBP1 as the most significant hub for the malignant cell-intrinsic gene module. PTBP1 is not altered in most glioma genomes. PTBP1 represses the conserved splicing of CDC42-N. PTBP1 knockdown or CDC42-N overexpression disrupts actin cytoskeleton dynamics, causing accumulation of reactive oxygen species and cell apoptosis. PTBP1-mediated repression of CDC42-N splicing represents a potential genomic alteration-independent, developmentally conserved vulnerability in IDH-wildtype GBM.

A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma

Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumor cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analyzed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms.

Modeling glioblastoma tumor progression via CRISPR-engineered brain organoids

Glioblastoma (GBM) is an aggressive form of brain cancer that is highly resistant to therapy due to significant intra-tumoral heterogeneity. The lack of robust in vitro models to study early tumor progression has hindered the development of effective therapies. Here, we develop engineered GBM organoids (eGBOs) harboring GBM subtype-specific oncogenic mutations to investigate the underlying transcriptional regulation of tumor progression. Single-cell and spatial transcriptomic analyses revealed that these mutations disrupt normal neurodevelopment gene regulatory networks resulting in changes in cellular composition and spatial organization. Upon xenotransplantation into immunodeficient mice, eGBOs form tumors that recapitulate the transcriptional and spatial landscape of human GBM samples. Integrative single-cell trajectory analysis of both eGBO-derived tumor cells and patient GBM samples revealed the dynamic gene expression changes in developmental cell states underlying tumor progression. This analysis of eGBOs provides an important validation of engineered cancer organoid models and demonstrates their utility as a model of GBM tumorigenesis for future preclinical development of therapeutics.

Concurrent Preimplantation Genetic Testing and Competence Assessment of Human Embryos by Transcriptome Sequencing

Preimplantation genetic testing (PGT) can minimize the risk of birth defects. However, the accuracy and applicability of routine PGT is confounded by uneven genome coverage and high allele drop-out rate from existing single-cell whole genome amplification methods. Here, a method to diagnose genetic mutations and concurrently evaluate embryo competence by leveraging the abundant mRNA transcript copies present in trophectoderm cells is developed. The feasibility of the method is confirmed with 19 donated blastocysts. Next, the method is applied to 82 embryos from 26 families with monogenic defects for simultaneous mutation detection and competence assessment. The accuracy rate of direct mutation detection is up to 95%, which is significantly higher than DNA-based method. Meanwhile, this approach correctly predicted seven out of eight (87.5%) embryos that failed to implant. Of six embryos that are predicted to implant successfully, four met such expectations (66.7%). Notably, this method is superior at conditions for mutation detection that are challenging when using DNA-based PGT, such as when detecting pathogenic genes with a high de novo rate, multiple pseudogenes, or an abnormal expansion of CAG trinucleotide repeats. Taken together, this study establishes the feasibility of an RNA-based PGT that is also informative for assessing implantation competence.

Single-cell RNA-seq reveals the transcriptional program underlying tumor progression and metastasis in neuroblastoma

Neuroblastoma (NB) is one of the most common childhood malignancies. Sixty percent of patients present with widely disseminated clinical signs at diagnosis and exhibit poor outcomes. However, the molecular mechanisms triggering NB metastasis remain largely uncharacterized. In this study, we generated a transcriptomic atlas of 15 447 NB cells from eight NB samples, including paired samples of primary tumors and bone marrow metastases. We used time-resolved analysis to chart the evolutionary trajectory of NB cells from the primary tumor to the metastases in the same patient and identified a common 'starter' subpopulation that initiates tumor development and metastasis. The 'starter' population exhibited high expression levels of multiple cell cycle-related genes, indicating the important role of cell cycle upregulation in NB tumor progression. In addition, our evolutionary trajectory analysis demonstrated the involvement of partial epithelial-to-mesenchymal transition (p-EMT) along the metastatic route from the primary site to the bone marrow. Our study provides insights into the program driving NB metastasis and presents a signature of metastasis-initiating cells as an independent prognostic indicator and potential therapeutic target to inhibit the initiation of NB metastasis.

Identification of Novel Prognostic Signature of Recurrent Low-Grade Glioma

OBJECTIVES

The prognosis of patients with recurrent low-grade glioma (rLGG) varies greatly. Some patients can survive >10 years after recurrence, whereas other patients have <1 year of survival.

METHODS

To identify the related risk factors affecting the prognosis of patients with rLGG, we performed a series of bioinformatics analyses on RNA sequencing data of rLGG based on the Chinese Glioma Genome Altas database.

RESULTS

We constructed a 12-gene prognostic signature, dividing all the patients with rLGG into high- and low-risk subgroups. The result showed an excellent predictive effect in both the training cohort and the validation cohort using LASSO-Cox regression. Moreover, multivariate Cox analysis identified 4 independent prognostic factors of rLGG; among them, ZCWPW1 is identified as a high-value protective factor.

CONCLUSIONS

In all, this prognostic model displayed robust predictive capability for the overall survival of patients with rLGG, providing a new monitoring method for rLGG. The 4 independent prognostic factors, especially ZCWPW1, can be potential targets for rLGG, bringing new possibilities for the treatment of patients with rLGG.

Accurate estimation of pathway activity in single cells for clustering and differential analysis

Inferring which and how biological pathways and gene sets change is a key question in many studies that utilize single-cell RNA sequencing. Typically, these questions are addressed by quantifying the enrichment of known gene sets in lists of genes derived from global analysis. Here we offer SiPSiC, a new method to infer pathway activity in every single cell. This allows more sensitive differential analysis and utilization of pathway scores to cluster cells and compute UMAP or other similar projections. We apply our method to COVID-19, lung adenocarcinoma and glioma data sets, and demonstrate its utility. SiPSiC analysis results are consistent with findings reported in previous studies in many cases, but SiPSiC also reveals the differential activity of novel pathways, enabling us to suggest new mechanisms underlying the pathophysiology of these diseases and demonstrating SiPSiC's high accuracy and sensitivity in detecting biological function and traits. In addition, we demonstrate how it can be used to better classify cells based on activity of biological pathways instead of single genes and its ability to overcome patient-specific artifacts.

Three-dimensional imaging of upper tract urothelial carcinoma improves diagnostic yield and accuracy

Upper tract urothelial carcinoma (UTUC) is a rare form of urothelial cancer with a high incidence of recurrence and a low survival rate. Almost two-thirds of UTUCs are invasive at the time of diagnosis; therefore, improving diagnostic methods is key to increasing survival rates. Histopathological analysis of UTUC is essential for diagnosis and typically requires endoscopy biopsy, tissue sectioning, and labeling. However, endoscopy biopsies are minute, and it is challenging to cut into thin sections for conventional histopathology; this complicates diagnosis. Here, we used volumetric 3-dimensional (3D) imaging to explore the inner landscape of clinical UTUC biopsies, without sectioning, revealing that 3D analysis of phosphorylated ribosomal protein S6 (pS6) could predict tumor grade and prognosis with improved accuracy. By visualizing the tumor vasculature, we discovered that pS6+ cells were localized near blood vessels at significantly higher levels in high-grade tumors than in low-grade tumors. Furthermore, the clustering of pS6+ cells was associated with shorter relapse-free survival. Our results demonstrate that 3D volume imaging of the structural niches of pS6 cells deep inside the UTUC samples improved diagnostic yield, grading, and prognosis prediction.

Advancing cancer therapeutics: Integrating scalable 3D cancer models, extracellular vesicles, and omics for enhanced therapy efficacy

Cancer remains as one of the highest challenges to human health. However, anticancer drugs exhibit one of the highest attrition rates compared to other therapeutic interventions. In part, this can be attributed to a prevalent use of in vitro models with limited recapitulative potential of the in vivo settings. Three dimensional (3D) models, such as tumor spheroids and organoids, offer many research opportunities to address the urgent need in developing models capable to more accurately mimic cancer biology and drug resistance profiles. However, their wide adoption in high-throughput pre-clinical studies is dependent on scalable manufacturing to support large-scale therapeutic drug screenings and multi-omic approaches for their comprehensive cellular and molecular characterization. Extracellular vesicles (EVs), which have been emerging as promising drug delivery systems (DDS), stand to significantly benefit from such screenings conducted in realistic cancer models. Furthermore, the integration of these nanomedicines with 3D cancer models and omics profiling holds the potential to deepen our understanding of EV-mediated anticancer effects. In this chapter, we provide an overview of the existing 3D models used in cancer research, namely spheroids and organoids, the innovations in their scalable production and discuss how omics can facilitate the implementation of these models at different stages of drug testing. We also explore how EVs can advance drug delivery in cancer therapies and how the synergy between 3D cancer models and omics approaches can benefit in this process.

Integration tools for scRNA-seq data and spatial transcriptomics sequencing data

Numerous methods have been developed to integrate spatial transcriptomics sequencing data with single-cell RNA sequencing (scRNA-seq) data. Continuous development and improvement of these methods offer multiple options for integrating and analyzing scRNA-seq and spatial transcriptomics data based on diverse research inquiries. However, each method has its own advantages, limitations and scope of application. Researchers need to select the most suitable method for their research purposes based on the actual situation. This review article presents a compilation of 19 integration methods sourced from a wide range of available approaches, serving as a comprehensive reference for researchers to select the suitable integration method for their specific research inquiries. By understanding the principles of these methods, we can identify their similarities and differences, comprehend their applicability and potential complementarity, and lay the foundation for future method development and understanding. This review article presents 19 methods that aim to integrate scRNA-seq data and spatial transcriptomics data. The methods are classified into two main groups and described accordingly. The article also emphasizes the incorporation of High Variance Genes in annotating various technologies, aiming to obtain biologically relevant information aligned with the intended purpose.

Genetic and epigenetic instability as an underlying driver of progression and aggressive behavior in IDH-mutant astrocytoma

In recent years, the classification of adult-type diffuse gliomas has undergone a revolution, wherein specific molecular features now represent defining diagnostic criteria of IDH-wild-type glioblastomas, IDH-mutant astrocytomas, and IDH-mutant 1p/19q-codeleted oligodendrogliomas. With the introduction of the 2021 WHO CNS classification, additional molecular alterations are now integrated into the grading of these tumors, given equal weight to traditional histologic features. However, there remains a great deal of heterogeneity in patient outcome even within these established tumor subclassifications that is unexplained by currently codified molecular alterations, particularly in the IDH-mutant astrocytoma category. There is also significant intercellular genetic and epigenetic heterogeneity and plasticity with resulting phenotypic heterogeneity, making these tumors remarkably adaptable and robust, and presenting a significant barrier to the design of effective therapeutics. Herein, we review the mechanisms and consequences of genetic and epigenetic instability, including chromosomal instability (CIN), microsatellite instability (MSI)/mismatch repair (MMR) deficits, and epigenetic instability, in the underlying biology, tumorigenesis, and progression of IDH-mutant astrocytomas. We also discuss the contribution of recent high-resolution transcriptomics studies toward defining tumor heterogeneity with single-cell resolution. While intratumoral heterogeneity is a well-known feature of diffuse gliomas, the contribution of these various processes has only recently been considered as a potential driver of tumor aggressiveness. CIN has an independent, adverse effect on patient survival, similar to the effect of histologic grade and homozygous CDKN2A deletion, while MMR mutation is only associated with poor overall survival in univariate analysis but is highly correlated with higher histologic/molecular grade and other aggressive features. These forms of genomic instability, which may significantly affect the natural progression of these tumors, response to therapy, and ultimately clinical outcome for patients, are potentially measurable features which could aid in diagnosis, grading, prognosis, and development of personalized therapeutics.

Ongoing genome doubling promotes evolvability and immune dysregulation in ovarian cancer

Whole-genome doubling (WGD) is a critical driver of tumor development and is linked to drug resistance and metastasis in solid malignancies. Here, we demonstrate that WGD is an ongoing mutational process in tumor evolution. Using single-cell whole-genome sequencing, we measured and modeled how WGD events are distributed across cellular populations within tumors and associated WGD dynamics with properties of genome diversification and phenotypic consequences of innate immunity. We studied WGD evolution in 65 high-grade serous ovarian cancer (HGSOC) tissue samples from 40 patients, yielding 29,481 tumor cell genomes. We found near-ubiquitous evidence of WGD as an ongoing mutational process promoting cell-cell diversity, high rates of chromosomal missegregation, and consequent micronucleation. Using a novel mutation-based WGD timing method, doubleTime , we delineated specific modes by which WGD can drive tumor evolution: (i) unitary evolutionary origin followed by significant diversification, (ii) independent WGD events on a pre-existing background of copy number diversity, and (iii) evolutionarily late clonal expansions of WGD populations. Additionally, through integrated single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signaling and cGAS-STING pathway activation result from ongoing chromosomal instability and are restricted to tumors that remain predominantly diploid. This contrasted with predominantly WGD tumors, which exhibited significant quiescent and immunosuppressive phenotypic states. Together, these findings establish WGD as an evolutionarily 'active' mutational process that promotes evolvability and dysregulated immunity in late stage ovarian cancer.

A hybrid epithelial/mesenchymal state in head and neck cancer: A biomarker for survival with differential prognosis by self-reported race

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the 6th leading cause of cancer-related mortality, with racial disparities amplifying the challenges in treatment. Although the relationship between hybrid epithelial/mesenchymal (E/M) states and tumor progression is of interest, no studies have characterized the clinical relevance of hybrid E/M states in head and neck cancer outcomes among self-reported racial cohorts.

METHODS

Given the overlap in gene expression between hybrid E/M malignant cells and cancer-associated fibroblasts, we utilized deconvolution of bulk RNA sequencing data from oral cavity and laryngeal squamous cell carcinoma tumors from The Cancer Genome Atlas. We utilized our previously collected single-cell profiles to generate inferred malignant profiles and then scored these for hybrid E/M. We then conducted a survival analysis on overall and disease-free survival among self-reported Black and White Americans.

FINDINGS

The hybrid E/M state was differentially associated with head and neck cancer survival by self-reported race and ethnicity, with a stronger association in non-Hispanic Black patients. Black patients with a high hybrid E/M score had a higher risk of death or recurrence (hazard ratio [HR]: 4.18 [95% confidence interval (CI): 2.06, 8.49]) than White patients with a high hybrid E/M score (HR: 1.58 [95% CI: 1.11, 2.26]).

CONCLUSION

Our results suggest a complex interplay of social structure, racism, and genetic diversity. We implore researchers to consider the social and biological context contributing to disparities.

FUNDING

A.L.M. received support from the National Institute of Minority Health and Health Disparities (K01MD013897 [principal investigator (PI), A.L.M.]). S.V.P. received support from the National Institute of Dental and Craniofacial Research (R01DE032865 [PI, S.V.P.] and R01DE032371 [PI, S.V.P.]).