Single-cell Transcriptomics Research Articles

M5C related-regulator-mediated methylation modification patterns and prognostic significance in breast cancer

5-Methylcytosine (m5C) is closely associated with cancer. However, the role of m5C in breast cancer(BC)remains unclear. This study combined single-cell RNA sequencing (scRNA-Seq) and transcriptomics datasets to screen m5C regulators associated with BC progression and analyze their clinical values. Firstly, This study elucidates the mechanisms of the m5C landscape and the specific roles of m5C regulators in BC patients. we found that the dysregulation of m5C regulators with m5Cscore play the essential role of the carcinogenesis and progression in epithelial cells and myeloid cells of BC at single cell level. External validation was conducted using an independent scRNA-Seq datasets. Then, three distinct m5C modification patterns were identified by transcriptomics datasets. Based on the m5C differentially expressed regulators, the m5Cscore was constructed, and used to divide patients with BC into high and low m5Cscore groups. Patients with a high m5Cscore had more abundant immune cell infiltration, stronger antitumor immunity, and better prognoses. Finally, Quantitative real-time (PCR) and immunohistochemistry were used for the in vitro experimental validation, which had extensive prognostic value. In this study, we aimed to assess the expression of m5C regulators involved in BC and investigate their correlation with the tumor microenvironment, clinicopathological characteristics, and prognosis of BC. The m5C regulators could be used to effectively assess the cell specific regulation prognosis of patients with BC and develop more effective immunotherapy strategies.

ANGI-08. SPATIAL TRANSCRIPTOMIC COMPARISONS OF GLIOBLASTOMA TISSUE REVEAL UPREGULATION OF NEURODEVELOPMENTAL PATHWAYS AND SYNAPTIC GENES IN INFILTRATING TUMOR CELLS

Abstract Glioblastoma remains one of the deadliest brain malignancies. First-line therapy consists of maximal surgical tumor resection, chemotherapy, and radiotherapy. Malignant cells escape surgical resection by migrating into the surrounding healthy brain tissue, where they give rise to the recurrent tumor. Gene expression profiling allows glioblastoma tumor cores to be classified into mesenchymal, proneural, and classical subtypes, each with distinct genetic alterations and cellular compositions. In contrast, the adjacent brain parenchyma where infiltrating malignant cells escape surgical resection is less characterized in patients. Using single-cell and multicellular resolution spatial transcriptomics on tissues from both the tumor core and infiltrated brain tissue (n = 11), we compared the transcriptional profiles of malignant cells in these regions. Malignant cells near regions with microvascular proliferation showed increased expression of genes related to vascular homeostasis. Within tumor cores, proneural and mesenchymal subtypes exhibited distinct spatial gene expression patterns, although these differences were reduced in the infiltrated brain tissue, apart from gene expression due to chromosomal alterations specific to the proneural subtype. We identified two transcriptional patterns of brain infiltration, with the dominant pattern showing a transition from mesenchymal to proneural states. This transition was accompanied by increased expression of genes linked to neurodevelopmental pathways and glial cell differentiation. Additionally, one gene module upregulated in infiltrating malignant cells was predictive of poor patient survival and enriched for genes associated with differentiated neuronal cells. Together, our findings provide an updated view of the spatial landscape of glioblastomas and infiltrated brain tissue, furthering our understanding of the malignant cells that invade healthy brain. This insight offers new avenues for targeted therapy after surgical resection of the primary tumor.

IMMU-36. MULTI-OMIC CHARACTERIZATION OF A SYNGENEIC MOUSE CANCER STEM CELL MODEL OF GBM FOR PRECLINICAL APPLICATIONS

Abstract Glioblastoma (GBM) is resistant to many therapies including immunotherapies. There is an urgent need to explore the role of the microenvironment in resistance to therapy with tailored pre-clinical models. Using multi-omic approaches we describe a syngeneic cancer stem cell mouse model of GBM, with a spontaneous amplification of Igf2. We investigate whether Igf2 influences tumour and microenvironment cells to promote immunosuppression in GBM. Three cell lines were previously established from spontaneous brain tumours in C57Bl/6 Trp53+/-/Nf1+/- mice and maintained under neural stem cell culture conditions. Whole genome sequencing (WGS) was used to determine single nucleotide, copy number, and structural variation, revealing loss of both copies of Trp53 and Nf1 in all three cell lines. However only one cell line, mBT0309, developed tumors when orthotopically allografted. Analysis of genomic alterations and transcriptomics revealed that mBT309 exhibits amplification of the Igf2 loci and overexpression was confirmed at the RNA and protein level. Spatial and single cell transcriptomics showed that Igf2 is overexpressed in mBT0309 allografted tumours and correlated with specific transcriptomic programs. A high-parameter Imaging Mass Cytometry (IMCTM) panel was used for spatial proteomic analysis, to monitor the development of tumours in a time-course experiment. In vitro growth characteristics and stem marker expression in both transcriptomic and spatial IMC data suggest that high levels of Igf2 may regulate GBM stemness features. Analysis of human GBM datasets revealed that Igf2 amplified tumours have reduced CXCL11 expression. These findings suggest that high levels of Igf2 may influence immunosuppression by reducing T-cell recruitment. This syngeneic immunocompetent GBM stem cell model harbouring Igf2 amplification adds to the suite of models to study the GBM microenvironment and its role in immunosuppression and resistance to therapy.

Integrated multiomics analysis identified comprehensive crosstalk between diverse programmed cell death patterns and novel molecular subtypes in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly aggressive malignancy with increasing global prevalence and is one of the leading causes of cancer-related mortality in the human population. Developing robust clinical prediction models and prognostic stratification strategies is crucial for developing individualized treatment plans. A range of novel forms of programmed cell death (PCD) plays a role in the pathological progression and advancement of HCC, and in-depth study of PCD is expected to further improve the prognosis of HCC patients. Sixteen patterns (apoptosis, autophagy, anoikis, lysosome-dependent cell death, immunogenic cell death, necroptosis, ferroptosis, netosis, pyroptosis, disulfidptosis, entotic cell death, cuproptosis, parthanatos, netotic cell death, alkaliptosis, and oxeiptosis) related to PCD were collected from the literatures and used for subsequent analysis. Supervised (Elastic net, Random Forest, XgBoost, and Boruta) and unsupervised (Nonnegative Matrix Factorization, NMF) clustering algorithms were applied to develop and validate a novel classifier for the individualized management of HCC patients at the transcriptomic, proteomic and single-cell levels. Multiple machine learning algorithms developed a programmed cell death index (PCDI) comprising five robust signatures (FTL, G6PD, SLC2A1, HTRA2, and DLAT) in four independent HCC cohorts, and a higher PCDI was predictive of higher pathological grades and worse prognoses. Furthermore, a higher PCDI was found to be correlated with the presence of a repressive tumor immune microenvironment (TME), as determined through an integrated examination of bulk and single-cell transcriptome data. In addition, patients with TP53 mutation had higher PCDI in comparison with TP53 WT patients. Three HCC subtypes were identified through unsupervised clustering (NMF), exhibiting distinct prognoses and significant biological processes, among the three subtypes, PCDcluster 3 was of particular interest as it contained a large proportion of patients with high risk and low metabolic activity. Construction and evaluation of the Nomogram model was drawn based on the multivariate logistic regression analysis, and highlighted the robustness of the Nomogram model in other independent HCC cohorts. Finally, to explore the prognostic value, we also validated the frequent upregulation of DLAT in a real-world cohort of human HCC specimens by qPCR, western blot, and immunohistochemical staining (IHC). Together, our work herein comprehensively emphasized PCD-related patterns and key regulators, such as DLAT, contributed to the evolution and prognosis of tumor foci in HCC patients, and strengthened our understanding of PCD characteristics and promoted more effective risk stratification strategies.

STEM-14. INTEGRATED ANALYSIS OF GLIOBLASTOMA PROGENITOR SUBTYPES REVEALS A TUMOR-DERIVED STEM CELL POPULATION WITH NEURAL AND VASCULAR POTENTIAL

Abstract Glioblastoma (GBM) exhibits a vast heterogeneity in cell types and states. Recent research highlights the reactivation of neurodevelopmental programs in GBM, contributing to this heterogeneity and, ultimately, therapy resistance. To characterize the landscape of progenitor cell types in human primary GBM, we compiled a meta-atlas of single-cell transcriptomes from seven published studies. Using a novel bioinformatic method for gene program analysis, we derived GBM gene expression meta-modules represented across multiple tumors. Our analyses validated previously described GBM gene programs and revealed novel tumor progenitor subtypes. Among these subtypes, we identified a tumor-derived stem cell population exhibiting a mixed vascular identity and transcriptional programs reminiscent of neural stem cells, which we identified as a putative neurovascular progenitor (NVP). To our knowledge, this population has not been previously described in GBM. We validated the existence of NVPs in situ using immunofluorescence from primary patient GBM samples. We then performed an enrichment for NVPs using fluorescence-activated cell sorting direct from patient tumors, followed by single-cell RNA sequencing. Examination of data from traditional model systems, including gliomaspheres and mouse GBM models, confirmed the preservation of NVP identity across systems. In vivo analysis of NVPs in multiple mouse models of GBM elucidate the influence of NVPs on GBM cell type composition, highlighting their role as multipotent progenitors. Finally, we utilized single-cell lineage barcoding to trace the progeny of patient-derived NVP cells in a novel organoid transplantation model, revealing NVP differentiation into vascular-like and neural-like cells. These data indicate that NVP cells play crucial roles in tumor plasticity and may represent a valuable therapeutic target for future exploration.

RBIO-02. DEVELOPMENT OF FLASH-CAR RADIOIMMUNOTHERAPY FOR PEDIATRIC BRAIN TUMORS

Abstract Pediatric brain tumors including medulloblastoma and high-grade glioma are generally refractory to T cell-based immunotherapy, largely due to an immune-hostile microenvironment infiltrated extensively with immunosuppressive macrophages. Ultra-high dose rate (FLASH) radiotherapy holds promise for treating solid tumors, given the potential lower toxicity in normal tissues and possible favorable impact on tumor immunity. Using a genetically engineered mouse model of medulloblastoma and glioma, we show that FLASH radiation stimulates pro-inflammatory polarization in tumor macrophages. Single-cell transcriptome analysis shows that FLASH proton beam radiation skews macrophages towards proinflammatory phenotypes and increases T cell infiltration in the medulloblastoma model. Further bulk transcriptome analyses reveal that FLASH radiation reduces peroxisome proliferator-activated receptor (PPAR)-γ and arginase-1 expression and inhibits immunosuppressive macrophage polarization under stimulus-inducible conditions. Mechanistically, FLASH radiation abrogates lipid oxidase expression and oxidized low-density lipid (oxLDL) generation to reduce PPARγ activity, while standard radiation induces reactive oxygen species (ROS)-dependent PPARγ activation in macrophages. Notably, FLASH radiotherapy improves infiltration and activation of chimeric antigen receptor (CAR) T cells and sensitizes tumors to GD2 CAR T immunotherapy in the autochthonous medulloblastoma and syngeneic glioma models. These findings suggest that FLASH radiotherapy may reprogram macrophage lipid metabolism to reverse tumor immunosuppression and that combination FLASH-CAR radioimmunotherapy may offer exciting opportunities for treatment of pediatric brain tumor.

IDog: a multi-omics resource for canids study.

iDog (https://ngdc.cncb.ac.cn/idog/) is a comprehensive public resource for domestic dogs (Canis lupus familiaris) and wild canids, designed to integrate multi-omics data and provide data services for the worldwide canine research community. Notably, iDog 2.0 features a 15-fold increase in genomic samples, including 29.55 million single nucleotide polymorphisms (SNPs) and 16.54 million insertions/deletions (InDels) from 1929 modern samples and 29.09 million SNPs from 111 ancient Canis samples. Additionally, 43487 breed-specific SNPs and 530 disease/trait-associated variants have been identified and integrated. The platform also includes data from 141 BioProjects involving gene expression analyses and a single-cell transcriptome module containing data from 105057 Beagle hippocampus cells. iDog 2.0 also includes an epignome module that evaluates DNA methylation patterns across 547 samples and chromatin accessibility across 87 samples for the analysis of gene expression regulation. Additionally, it provies phenotypic data for 897 dog diseases, 3207 genotype-to-phenotype (G2P) pairs, and 349 dog disease-associated genes, along with two newly constructed ontologies for breed and disease standardization. Finally, 13 new analytical tools have been added. Given these enhancements, the updated iDog 2.0 is an invaluable resource for the global cannie research community.

CNSC-52. OLIGODENDROGLIOMA SPATIAL TRANSCRIPTOMIC SEQUENCING REVEALS THERAPY-DEPENDENT EVOLUTION OVER TIME

Abstract Oligodendroglioma evolution is incompletely understood. Here we analyze serial oligodendroglioma samples to define genomic and cellular mechanisms underlying treatment resistance. RNA sequencing was performed on 53,406 spatial transcriptomes from 31 oligodendrogliomas (IDH mutant, 1p/19q-codeleted) that were resected from 16 patients. There were 15 CNS WHO grade 2 and 16 grade 3 oligodendrogliomas, which were stratified for temporal progression across grades (n=5 grade 2 to 2, n=5 grade 2 to 3, n=6 grade 3 to 3) and treatments between serial resections (n=2 TMZ/RT, n=2 TMZ, n=1 mTOR inhibition, n=1 IDH inhibition, n=10 surgical monotherapy). Spatial transcriptomic clusters were defined using cell signature gene sets, cell cycle analysis, differentially expressed marker genes, immunohistochemistry, spatial copy number alterations (CNAs), and deconvolution of 18,628 oligodendroglioma single-cell transcriptomes from 16 independent patients. Specificity was tested using immunofluorescence on independent oligodendrogliomas that did not recur after surgical monotherapy (n=8 samples, median follow-up 8.4 years) and spatial transcriptomic sequencing on 8 matched-paired astrocytomas from 4 patients. Integrated uniform manifold approximation and projection revealed a proneural/NPC-like cluster that was enriched in grade 3 oligodendroglioma samples and represented the starting point in oligodendroglioma lineage differentiation using RNA velocity, Monocle, and subclonal spatiotemporal CNA evolution. Comparison across treatment regimens showed (1) enrichment of the proneural/NPC-like cluster in recurrent versus primary tumors that were treated with surgical monotherapy, (2) enrichment of a proneural/OPC-like cluster and depletion of an oligodendrocyte-like cluster after TMZ/RT, (3) enrichment of proneural/NPC-like and immediate-early response clusters after TMZ/RT, (4) enrichment of the oligodendrocyte-like cluster following mTOR inhibition, and (5) enrichment of cancer associated fibroblasts (CAFs) following IDH inhibition. These data show the spatiotemporal landscape of oligodendroglioma is associated with branched lineage differentiation that is modified by postoperative therapy, and suggest that therapy-dependent druggable dependencies may exist to treat oligodendrogliomas that are resistant to standard interventions.

TMIC-69. HUMAN ORGANOID TUMOR TRANSPLANTATION IDENTIFIES FUNCTIONAL GLIOBLASTOMA MICROENVIRONMENTAL COMMUNICATION MEDIATED BY PTPRZ1

Abstract Glioblastoma, the most aggressive form of primary brain cancer, is driven by both intrinsic cellular properties and extrinsic factors from the tumor microenvironment (TME). Here, we leverage our novel human organoid tumor transplantation (HOTT) system to explore how external cues modulate glioblastoma cell type specification, heterogeneity, and migration. Comparing the single-cell transcriptomes of HOTT and matched primary tumors, we found that HOTT recapitulates not only core features of major patient tumor cell types but also those of peritumor non-neoplastic cell types. This enables us to explore tumor-TME interactions and identify PTPRZ1, a receptor tyrosine phosphatase implicated in brain tumor migration, as a key mediator in intercellular communication. This finding was further confirmed by interrogation of published datasets from patients containing non-neoplastic microenvironmental cells. PTPRZ1 activation, resulting from the reactivation of developmental programs in both the tumor and its TME, highlights the relevance of the organoid system for modeling the GBM microenvironment. Moreover, HOTT uniquely allows for perturbations in either patient tumors or their microenvironments, or both, to verify PTPRZ1 function. Tumor knockdown of PTPRZ1 confirmed its role in promoting tumor migration and maintaining progenitor identity. Surprisingly, environmental PTPRZ1 knockdown in human cortical organoids before tumor transplantation inhibited tumor migration and promoted differentiation, even without direct tumor manipulation. Overall, this fundamental result demonstrates that a single treatment delivered to the tumor and its TME can exert opposite effects on the tumor. Consequently, it underscores the necessity of studying human glioblastoma within a human microenvironment context, such as HOTT, especially when evaluating therapeutic efficacy in GBM, as effective treatments must address both the tumor and its complex TME, rather than the tumor alone.

IMMU-22. TWIST1-MEDIATED ENDOTHELIAL PLASTICITY DRIVES GLIOBLASTOMA RESISTANCE TO CAR T IMMUNOTHERAPY

Abstract Glioblastoma (GBM) is the most common and most aggressive malignant primary brain tumor in adults. Among the most lethal human malignancies, GBM is highly resistant to cytotoxic treatments and molecularly targeted therapies, and also generally refractory to T cell–based immunotherapies, largely due to their immunologically cold nature, i.e., characterized by a paucity of tumor T cell infiltrates that result from the immunosuppressive microenvironment. Here, we identify a distinct mechanism driven by spatiotemporal interaction of leukocytes with tumor stromal cells, namely, mesenchymal-like population of endothelial cells (ECs) form an immunosuppressive vascular niche that regulates macrophage polarization and induces GBM resistance to CAR T immunotherapy. Our single-cell transcriptome analyses of human and mouse GBM tumors identify a subpopulation of ECs acquire robust immunosuppressive phonotypes to drive alternative macrophage polarization. These ECs are spatially localized proximately to immunosuppressive macrophages and selectively express Twist1. Furthermore, we reveal a Twist1/SATB1-mediated sequential transcriptional activation mechanism, through which Twist1+ tumor ECs produce osteopontin to locally promote immunosuppressive macrophage phenotypes. Genetic or pharmacological ablation of Twist1 reverses macrophage-mediated immunosuppression and enhances T cell infiltration and activation, leading to reduced GBM growth and extended mouse survival. Importantly, pharmacological inhibition and lipid nanoparticle-mediated targeted inactivation of Twist1 overcome GBM resistance to Egfrviii CAR T cell immunotherapy. Thus, these findings uncover a spatially restricted mechanism controlling vasculature-mediated tumor immunity and suggest that targeting endothelial Twist1 may offer exciting opportunities for GBM immunotherapy.

Single cell analysis identified a basal cell transition state associated with the development and progression of bladder cancer

BackgroundBladder cancer (BC) is a prevalent malignancy characterized by significant cellular heterogeneity. While single-cell multi-omics studies have provided valuable insights, much of the existing data remains underexplored, limiting our understanding of BC’s molecular mechanisms. Uncovering the pathogenesis of BC and finding new treatment methods are urgent problems to be solved. This study aims to address this gap by re-analyzing available single-cell datasets to uncover novel insights into BC.MethodsIn this study, we retrieved three single-cell transcriptome datasets by searching the Gene Expression Omnibus (GEO) database, focusing on single-cell sequencing of normal mouse bladder within the past 5 years. Through quality control and batch effect elimination, we obtained a total of 24,930 cells including epithelial, stromal, and immune cells. Subgroup analysis, pseudotemporal analysis, cell–cell communication, and transcription factor analysis were conducted specifically on epithelial cells to identify a transitional state during basal cell differentiation. We further compared the expression profiles of key transcription factors in cancer and normal tissues. In addition, we also performed immunohistochemical staining and survival analysis for key transcription factors.ResultsSubgroup analysis revealed multiple subtypes of epithelial cells, including basal, umbrella, and intermediate cells. Through pseudotemporal analysis, we discovered the developmental trajectory from basal cells to umbrella cells and further found that Basal_I is a transitional state for basal cell differentiation. Cell-to-cell communication analyses highlighted the pivotal role of Basal_I in cell–cell interactions, and key ligand-receptor pairs associated with cancer progression were also identified. Furthermore, elevated expression levels of key transcription factors in Basal_I were found to be closely associated with the stage and prognosis of BC. Immunohistochemical staining results further confirmed the upregulated expression of these transcription factors in BC.ConclusionsCollectively, we found a transitional state of basal cells in normal bladder epithelial cells in mice, which may be related to the occurrence and development of BC, providing important clues for further understanding of the pathogenesis of BC. Our study provided possible molecular mechanisms or target for the research and treatment of BC.

Maternal COVID-19 infection associated with offspring neurodevelopmental disorders.

Maternal COVID-19 infection increases the incidence of neurodevelopmental disorders (NDDs) in offspring, although the underlying mechanisms have not been elucidated. This study demonstrated that COVID-19 infection during pregnancy disrupted the balance of maternal and fetal immune environments, driving alterations in astrocytes, endothelial cells, and excitatory neurons. A risk score was established using 47 unique genes in the single-cell transcriptome of gestational mothers. The high risk score in CD4 proliferating T cell level served as an indicator for increased risk of offspring NDDs. Summary-based Mendelian randomization and phenome-wide association study analyses were conducted to identify the causal association of the transcriptional changes with the increased risk of offspring NDDs. Additionally, 10 drugs were identified as potential therapeutic candidates. Our findings support a model where the maternal COVID-19 infection changed the levels of CD4 proliferating T cells, leading to the alterations of astrocytes, endothelial cells, and excitatory neurons in offspring, contributing to the increased risk of NDDs in these individuals.

Fibroblast Heterogeneity in Hepatocellular Carcinoma and Identification of Prognostic Markers Based on Single-cell Transcriptome Analysis.

HCC is a malignant tumor with high morbidity and mortality. Fibroblasts play a key role in the tumor microenvironment (TME). However, the transcriptional regulatory mechanisms of fibroblasts remained unclear in HCC. The aim of this study was to explore the complex role of fibroblasts in hepatocellular carcinoma (HCC) and to reveal their transcriptional regulatory mechanisms. The goal of this study was to discover potential prognostic markers for HCC by analyzing the genetic variations and differentiation process of fibroblasts. Single-cell transcriptome data from the non-tumor liver site and primary tumor site of HCC were acquired from GSE149614, processed, and clustered using the Seurat pipeline. The inferCNV algorithm was applied to infer copy number variations (CNVs) in fibroblasts. Subsequently, the mechanism underlying the interaction between fibroblasts and other cells in the TME of HCC was analyzed using CellChat software. The trajectory of cellular differentiation of fibroblasts from normal state to malignant state was examined using Monocle 2. SCENIC analysis was performed to identify key transcription factors (TFs) in fibroblasts and assess their correlation with HCC prognosis. Finally, qRT-PCR and Transwell assays were carried out to analyze the mRNA expression and cell metastasis. We identified a total of nine different cell types (B cells, cycling cells, endothelial cells, epithelial cells, fibroblasts, hepatocytes, macrophages, plasma cells, and T cells) based on the single-cell transcriptomic data of HCC. Among them, fibroblasts were highly enriched at the primary tumor site, and their number increased with advanced stages. In addition, significant deletions were detected on chromosome 6p of fibroblasts, and genes in this region were remarkably enriched in pathways associated with antigen processing and presentation. Intercellular communication showed that epithelial cells regulated fibroblasts the most. The differentiation of fibroblasts was mainly accompanied by a transition from normal to malignant state. Importantly, CEBPD and FOSB, the TFs most associated with the putative timing of fibroblasts, were under-expressed in human hepatocytes and showed a significant correlation with HCC prognosis. Overexpressed CEBPD inhibited HCC cell migration and invasion. In conclusion, our study revealed that fibroblast recruitment and differentiation, as well as copy number loss at chromosome 6p, were associated with a higher degree of malignancy and immune dysfunction in HCC. The current discoveries provided new insights into the clinical treatment and diagnosis of HCC.

Unveiling the influence of tumor and immune signatures on immune checkpoint therapy in advanced lung cancer.

This study investigates the variability among patients with non-small cell lung cancer (NSCLC) in their responses to immune checkpoint inhibitors (ICIs). Recognizing that patients with advanced-stage NSCLC rarely qualify for surgical interventions, it becomes crucial to identify biomarkers that influence responses to ICI therapy. We conducted an analysis of single-cell transcriptomes from 33 lung cancer biopsy samples, with a particular focus on 14 core samples taken before the initiation of palliative ICI treatment. Our objective was to link tumor and immune cell profiles with patient responses to ICI. We discovered that ICI non-responders exhibited a higher presence of CD4+ regulatory T cells, resident memory T cells, and TH17 cells. This contrasts with the diverse activated CD8+ T cells found in responders. Furthermore, tumor cells in non-responders frequently showed heightened transcriptional activity in the NF-kB and STAT3 pathways, suggesting a potential inherent resistance to ICI therapy. Through the integration of immune cell profiles and tumor molecular signatures, we achieved an discriminative power (area under the curve [AUC]) exceeding 95% in identifying patient responses to ICI treatment. These results underscore the crucial importance of the interplay between tumor and immune microenvironment, including within metastatic sites, in affecting the effectiveness of ICIs in NSCLC.

Unveiling the influence of tumor and immune signatures on immune checkpoint therapy in advanced lung cancer

This study investigates the variability among patients with non-small cell lung cancer (NSCLC) in their responses to immune checkpoint inhibitors (ICIs). Recognizing that patients with advanced-stage NSCLC rarely qualify for surgical interventions, it becomes crucial to identify biomarkers that influence responses to ICI therapy. We conducted an analysis of single-cell transcriptomes from 33 lung cancer biopsy samples, with a particular focus on 14 core samples taken before the initiation of palliative ICI treatment. Our objective was to link tumor and immune cell profiles with patient responses to ICI. We discovered that ICI non-responders exhibited a higher presence of CD4+ regulatory T cells, resident memory T cells, and TH17 cells. This contrasts with the diverse activated CD8+ T cells found in responders. Furthermore, tumor cells in non-responders frequently showed heightened transcriptional activity in the NF-kB and STAT3 pathways, suggesting a potential inherent resistance to ICI therapy. Through the integration of immune cell profiles and tumor molecular signatures, we achieved an discriminative power (area under the curve [AUC]) exceeding 95% in identifying patient responses to ICI treatment. These results underscore the crucial importance of the interplay between tumor and immune microenvironment, including within metastatic sites, in affecting the effectiveness of ICIs in NSCLC.

Molecular pathology of skin fragility

The skin's barrier function is primarily maintained by the cohesion of its layers and the specialized stratum corneum. Genetic and autoimmune disorders that result in skin fragility have significantly contributed to understanding the role of various molecular components in the skin. These conditions, characterized by blisters, erosions, wounds, and impaired wound healing, are rare but must be considered in clinical differential diagnoses. Key cutaneous adhesion structures include the epidermal basement membrane, anchoring fibrils, cell-matrix adhesions (e.g., hemidesmosomes and focal adhesions), and cell-cell adhesions (e.g., desmosomes and corneodesmosomes). These multiprotein suprastructures not only provide structural support but also participate in signaling processes and physiological or pathological conditions such as skin aging and wound healing. Additionally, dermal connective tissue plays astructural role and serves as areservoir for proteases, growth factors, and cytokines. Modern techniques like single-cell and spatial transcriptomics, combined with artificial intelligence algorithms, are advancing the molecular mapping of human skin. Moreover, this review highlights the molecular composition of adhesion structures and the specific diseases associated with deficiencies in these components.

Transcriptomic heterogeneity of non-beta islet cells is associated with type 2 diabetes development in mouse models.

The aim of this work was to understand the role of non-beta cells in pancreatic islets at early stages of type 2 diabetes pathogenesis. Specific clustering was employed to single-cell transcriptome data from islet cells of obese mouse strains differing in their diabetes susceptibility (diabetes-resistant B6.V.Lepob/ob [OB] and diabetes-susceptible New Zealand Obese [NZO] mice) on a diabetogenic diet. Refined clustering analysis revealed several heterogeneous subpopulations for alpha cells, delta cells and macrophages, of which 133 mapped to human diabetes genes identified by genome-wide association studies. Importantly, a similar non-beta cell heterogeneity was found in a dataset of human islets from donors at different stages of type 2 diabetes. The predominant alpha cell cluster in NZO mice displayed signs of cellular stress and lower mitochondrial capacity (97 differentially expressed genes [DEGs]), whereas delta cells from these mice exhibited higher expression levels of maturation marker genes (Hhex and Sst) but lower somatostatin secretion than OB mice (184 DEGs). Furthermore, a cluster of macrophages was almost twice as abundant in islets of OB mice, and displayed extensive cell-cell communication with beta cells of OB mice. Treatment of beta cells with IL-15, predicted to be released by macrophages, activated signal transducer and activator of transcription (STAT3), which may mediate anti-apoptotic effects. Similar to mice, humans without diabetes possess a greater number of macrophages than those with prediabetes (39 mmol/mol [5.7%] < HbA1c < 46 mmol/mol [6.4%]) and diabetes. Our study indicates that the transcriptional heterogeneity of non-beta cells has an impact on intra-islet crosstalk and participates in beta cell (dys)function. scRNA-seq data from the previous study are available in gene expression omnibus under gene accession number GSE159211 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159211 ).

Nature and nurture in fruit fly hearing

As for human language learning and birdsong acquisition, fruit flies adjust their auditory perception based on past sound experiences. This phenomenon is known as song preference learning in flies. Recent advancements in omics databases, such as the single-cell transcriptome and brain connectomes, have been integrated into traditional molecular genetics, making the fruit fly an outstanding model for studying the neural basis of “Nature and Nurture” in auditory perception and behaviors. This minireview aims to provide an overview of song preference in flies, including the nature of the phenomenon and its underlying neural mechanisms. Specifically, we focus on the neural circuitry involved in song preference learning, with which auditory experiences shape the song preference of flies. This shaping process depends on an integration hub that processes external sensory stimuli and internal states to enable flexible control of behavior. We also briefly review recent findings on the signals that feed into this integration hub, modulating song preference of flies in an experience-dependent manner.

Integration of single-cell and spatial transcriptome sequencing identifies CDKN2A as a senescent biomarker in endothelial cells implicating hepatocellular carcinoma malignancy.

Highly complex tumor microenvironment makes hepatocellular carcinoma (HCC) as one of the most malignant tumors worldwide. The role of cellular senescence in HCC has been gradually recognized. The present study aimed to comprehensively elucidate the senescence-related features of HCC in single-cell and spatial dimension. Single-cell RNA sequencing (scRNA-Seq) data was used to clarify the heterogeneity of senescence-related genes (SRGs) among multiple cell types within HCC. Spatial transcriptome RNA sequencing (stRNA-Seq) data was used for depicting SRGs features in spatial dimension. A prognostic model based on SRGs was constructed by using of bulk sequencing (bulk-Seq) data of HCC. The cell-cell interaction of senescent endothelial cells (ECs) in tumor microenvironment was analyzed. Then, the role of senescent ECs was verified through in vitro and in vivo experiments. The level of senescence demonstrated substantial heterogeneity among different cell types within tumor microenvironment of HCC, where ECs exhibited the most prominent senescent phenotype. Senescent ECs activated specific regulatory pathways through communicating with other cell types, with a potential impact on tumor progression. Spatial analysis revealed senescent ECs mainly located in the core region of HCC. The interaction of senescent ECs and immune cells implicated their role in tumor progression and immunotherapeutic response. In addition, CDKN2A was identified as an independent risk factor for HCC prognosis by constructing a prognostic model. Patients with high risk displayed an even worse outcome. The experimental verification indicated senescence of ECs determined by CDKN2A exhibited a secretory phenotype. Furthermore, senescent ECs with CDKN2A overexpression promote the proliferation and migration of HCC. The present study recognizes the critical effect of senescent ECs defined by CDKN2A in the promotion of tumor progression, which sheds new light on the investigation of ECs senescence in HCC.

Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics

Background/Objectives: High-throughput single-cell RNA sequencing (scRNA-seq) workflows produce libraries that demand extensive sequencing. However, standard next-generation sequencing (NGS) methods remain expensive, contributing to the high running costs of single-cell experiments and often negatively affecting the sample numbers and statistical strength of such projects. In recent years, a plethora of new sequencing technologies have become available to researchers through several manufacturers, often providing lower-cost alternatives to standard NGS. Methods: In this study, we compared data generated from mouse scRNA-seq libraries sequenced with both standard Illumina sequencing by synthesis (Illumina SBS) and MGI’s DNA nanoball sequencing (DNBSEQ). Results: Our findings reveal similar overall performance using both technologies. DNBSEQ exhibited mildly superior sequence quality compared to Illumina SBS, as evidenced by higher Phred scores, lower read duplication rates and a greater number of genes mapping to the reference genome. Yet these improvements did not translate into meaningful differences in single-cell analysis parameters in our experiments, including detection of additional genes within cells, gene expression saturation levels and numbers of identified cells, with both technologies demonstrating equally robust performance in these aspects. The data produced by both sequencing platforms also produced comparable analytical outcomes for single-cell analysis. No significant difference in the annotation of cells into different cell types was observed and the same top genes were differentially expressed between populations and experimental conditions. Conclusions: Overall, our data demonstrate that alternative technologies can be applied to sequence scRNA-seq libraries, generating virtually indistinguishable results compared to standard methods, and providing cost-effective alternatives.