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PubMed2026

Interpretable data integration for single-cell and spatial multi-omics.

Integrating single-cell or spatial transcriptomic and epigenomic data enables scrutinizing the transcriptional regulatory mechanisms controlling cell fate. Current integration methods usually align multi-omics data into a shared latent space but fail to reveal the underlying connections between genes and regulatory elements. The correlation- or regression-based regulatory inference methods cannot dissect different transcriptional regulation codes for cells under different spatial and temporal states. To address both problems, we develop a feature-guided optimal transport (FGOT) method, which simultaneously uncovers cellular heterogeneity and their associated transcriptional regulatory links. FGOT also provides post hoc interpretability for existing integration methods. FGOT is applicable for paired/unpaired single-cell multi-omics data and paired spatial multi-omics data. Benchmarking and validating via histone modification data or three-dimensional (3D) genomics data show good robustness and accuracy in integration and inference of regulatory links. The method allows systematic screening of cell-state and spatial-location-specific regulatory elements in diseases at the single-cell level. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

PubMed2021

Comparative cellular analysis of motor cortex in human, marmoset and mouse.

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Animals↗

PubMed2003

Targeted cellular process profiling approach for uterine leiomyoma using cDNA microarray, proteomics and gene ontology analysis.

This study utilized both cDNA microarray and two-dimensional protein gel electrophoresis technology to investigate the multiple interactions of genes and proteins involved in uterine leiomyoma pathophysiology. Also, the gene ontology analysis was used to systematically characterize the global expression profiles at cellular process levels. We profiled differentially expressed transcriptome and proteome in six-paired leiomyoma and normal myometrium. Screening up to 17 000 genes identified 21 upregulated and 50 downregulated genes. The gene-expression profiles were classified into mutually dependent 420 functional sets, resulting in 611 cellular processes according to the gene ontology. Also, protein analysis using two-dimensional gel electrophoresis identified 33 proteins (17 upregulated and 16 downregulated) of more than 500 total spots, which was classified into 302 cellular processes. Of these functional profilings, downregulations of transcriptomes and proteoms were shown in cell adhesion, cell motility, organogenesis, enzyme regulator, structural molecule activity and response to external stimulus functional activities that are supposed to play important roles in pathophysiology. In contrast, the upregulation was only shown in nucleic acid-binding activity. Taken together, potentially significant pathogenetic cellular processes were identified and showed that the downregulated functional profiling has a significant impact on the discovery of pathogenic pathway in leiomyoma. Also, the gene ontology analysis can overcome the complexity of expression profiles of cDNA microarray and two-dimensional protein analysis via its cellular process-level approach. Therefore, a valuable prognostic candidate gene with relevance to disease-specific pathogenesis can be found at cellular process levels.

Cell Communication↗

PubMed2006

A comprehensive proteomics and genomics analysis reveals novel transmembrane proteins in human platelets and mouse megakaryocytes including G6b-B, a novel immunoreceptor tyrosine-based inhibitory motif protein.

The platelet surface is poorly characterized due to the low abundance of many membrane proteins and the lack of specialist tools for their investigation. In this study we identified novel human platelet and mouse megakaryocyte membrane proteins using specialist proteomics and genomics approaches. Three separate methods were used to enrich platelet surface proteins prior to identification by liquid chromatography and tandem mass spectrometry: lectin affinity chromatography, biotin/NeutrAvidin affinity chromatography, and free flow electrophoresis. Many known, abundant platelet surface transmembrane proteins and several novel proteins were identified using each receptor enrichment strategy. In total, two or more unique peptides were identified for 46, 68, and 22 surface membrane, intracellular membrane, and membrane proteins of unknown subcellular localization, respectively. The majority of these were single transmembrane proteins. To complement the proteomics studies, we analyzed the transcriptome of a highly purified preparation of mature primary mouse megakaryocytes using serial analysis of gene expression in view of the increasing importance of mutant mouse models in establishing protein function in platelets. This approach identified all of the major classes of platelet transmembrane receptors, including multitransmembrane proteins. Strikingly 17 of the 25 most megakaryocyte-specific genes (relative to 30 other serial analysis of gene expression libraries) were transmembrane proteins, illustrating the unique nature of the megakaryocyte/platelet surface. The list of novel plasma membrane proteins identified using proteomics includes the immunoglobulin superfamily member G6b, which undergoes extensive alternate splicing. Specific antibodies were used to demonstrate expression of the G6b-B isoform, which contains an immunoreceptor tyrosine-based inhibition motif. G6b-B undergoes tyrosine phosphorylation and association with the SH2 domain-containing phosphatase, SHP-1, in stimulated platelets suggesting that it may play a novel role in limiting platelet activation.

Animals↗

PubMed2006

Identification of organ-specific T cell populations by analysis of multiparameter flow cytometry data using DNA-chip analysis software.

BACKGROUND: The analysis of cells from multiple experimental groups by multiparameter flow cytometry leads to the generation of complex data sets, for which adequate analysis tools are not commonly available. We report here that software designed for transcriptomics applications can be used in multiparameter flow cytometry. METHODS: Lymphocytes isolated from nine different mouse organs were stained and subjected to 10-parameter flow cytometry. The resulting data set contained 594 different T cell subsets per organ per mouse and was organized into a so-called flow cytometry array (FCA). RESULTS: Computation of a hierarchical tree revealed that lymph nodes and spleen were populated by similar T cell subsets, while T cells from peripheral organs displayed a diverse subset composition. Furthermore, organ-specific T cell subsets were identified. CONCLUSIONS: This new FCA concept in flow cytomics proved to be a valuable tool for the fast and unbiased analysis of complex multiparameter flow cytometry data sets. It can be used for assessing disease progression and therapeutic intervention, and for the association of disease-related biomarkers on the protein level.

Animals↗

PubMed2026

Spatially resolved single-cell atlas reveals the macroevolutionary trajectory of animal hearts.

Animal hearts display diverse anatomical structures during adaptive evolution. Here, we present a multiomics atlas of adult hearts from 27 species across chordates, arthropods, and mollusks. Joint analysis indicates that Bilateria hearts share a core gene repertoire, taking a stepwise "add-on" approach as a universal evolutionary strategy. The "proto-heart" is populated by key cell types, including cardiomyocytes, fibroblasts, endothelial cells, and neural cells, which maintained core signatures while evolving with shifts in living environments and corresponding adaptations in the cardiovascular system. Additionally, we reveal an evolutionarily conserved cardiomyocyte state dynamic potentially linked to cardiac development and stress responses. Finally, we identify a common molecular program underpinning chamber evolution from a ventricular foundation. This work establishes a resource for understanding the intrinsic mechanisms of heart evolution.

Animals↗

PubMed2026

Bioinformatics Analysis and Experimental Validation of Key Genes Associated With Hypoxia and Ischemia in Myocardial Infarction.

BACKGROUND: This study aimed to screen and identify core hypoxia-ischemia-related genes associated with myocardial infarction (MI). METHOD: Two transcriptomic datasets, GSE97320 and GSE48060, were retrieved from the Gene Expression Omnibus (GEO) database. After data integration and batch effect elimination, differential expression analysis was performed to screen differentially expressed genes (DEGs), and the corresponding visualization analysis was conducted. Hypoxia-ischemia-related genes were acquired from the GeneCards database; hypoxia-ischemia related genes (HIRGs) were subsequently identified by intersecting the retrieved genes with screened DEGs. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were implemented to explore the biological functions and underlying signaling pathways of HIRGs. A combination of protein-protein interaction (PPI) network analysis and random forest (RF) algorithm was applied to screen hub genes from HIRGs. The external GEO dataset GSE66360 was utilized to validate the expression patterns of candidate hub genes. Furthermore, an acute myocardial infarction (AMI) mouse model was established, and quantitative real-time polymerase chain reaction (qPCR) was performed to detect the mRNA expression levels of hub genes in myocardial tissues for in vivo validation. RESULTS: A total of 633 DEGs and 308 hypoxia-ischemia-related genes were screened in the present study, among which 21 overlapping HIRGs were obtained. PLAUR and IL1B were finally identified as two hub genes from HIRGs based on PPI network and random forest algorithm. The qPCR results revealed that the expression levels of PLAUR and IL1B were significantly upregulated in the AMI group compared with the sham operation group (p < 0.05). CONCLUSION: The present findings demonstrated that PLAUR and IL1B serve as pivotal genes involved in the pathological hypoxia-ischemia process of AMI. These two genes may act as novel biomarkers and promising therapeutic targets for the recognition and clinical intervention of hypoxia-ischemia injury following AMI.

Myocardial Infarction↗

PubMed2025

Multi-omics Mendelian randomization integrating RNA-seq, eQTL and pQTL data revealed CPXM1 as a potential drug target for osteoporosis.

Osteoporosis, a prevalent skeletal disorder characterized by decreased bone mineral density and increased fracture risk, continues to be a major global health concern. Traditional treatments for osteoporosis have limited efficacy and safety profiles, highlighting the need for novel therapeutic targets. This study integrates multi-omics data, including RNA-seq, expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data, through Mendelian randomization (MR) to identify potential drug targets for osteoporosis. By leveraging bidirectional two-sample MR analysis, we identified CPXM1 (Carboxypeptidase X, M14 family member 1) as a novel gene that is causally linked to osteoporosis risk. Through transcriptomic and proteomic validation, we demonstrate that CPXM1 was upregulated in aged bone tissues and osteoporotic conditions in both human and murine models. Gene set enrichment analysis (GSEA) revealed significant dysregulation of bone homeostasis pathways, including increased extracellular matrix degradation and suppression of osteoblast differentiation in aged mice. Furthermore, phenome-wide association studies (PheWAS) confirmed minimal off-target effects of CPXM1, reinforcing its potential as a therapeutic target. Finally, computational drug repurposing predicted several promising drug candidates, including Doxorubicin, 5-Fluorouracil, and 2-Methylcholine, which may target CPXM1 pathways for osteoporosis treatment. These findings highlight CPXM1 as a potential biomarker and therapeutic target, offering new avenues for osteoporosis therapy.

Osteoporosis↗

PubMed2006

Identification of stress-responsive genes in an indica rice (Oryza sativa L.) using ESTs generated from drought-stressed seedlings.

The impacts of drought on plant growth and development limit cereal crop production worldwide. Rice (Oryza sativa) productivity and production is severely affected due to recurrent droughts in almost all agroecological zones. With the advent of molecular and genomic technologies, emphasis is now placed on understanding the mechanisms of genetic control of the drought-stress response. In order to identify genes associated with water-stress response in rice, ESTs generated from a normalized cDNA library, constructed from drought-stressed leaf tissue of an indica cultivar, Nagina 22 were used. Analysis of 7794 cDNA sequences led to the identification of 5815 rice ESTs. Of these, 334 exhibited no significant sequence homology with any rice ESTs or full-length cDNAs in public databases, indicating that these transcripts are enriched during drought stress. Analysis of these 5815 ESTs led to the identification of 1677 unique sequences. To characterize this drought transcriptome further and to identify candidate genes associated with the drought-stress response, the rice data were compared with those for abiotic stress-induced sequences obtained from expression profiling studies in Arabidopsis, barley, maize, and rice. This comparative analysis identified 589 putative stress-responsive genes (SRGs) that are shared by these diverse plant species. Further, the identified leaf SRGs were compared to expression profiles for a drought-stressed rice panicle library to identify common sequences. Significantly, 125 genes were found to be expressed under drought stress in both tissues. The functional classification of these 125 genes showed that a majority of them are associated with cellular metabolism, signal transduction, and transcriptional regulation.

Adaptation, Physiological↗

PubMed2006

Group testing for pathway analysis improves comparability of different microarray datasets.

MOTIVATION: The wide use of DNA microarrays for the investigation of the cell transcriptome triggered the invention of numerous methods for the processing of microarray data and lead to a growing number of microarray studies that examine the same biological conditions. However, comparisons made on the level of gene lists obtained by different statistical methods or from different datasets hardly converge. We aimed at examining such discrepancies on the level of apparently affected biologically related groups of genes, e.g. metabolic or signalling pathways. This can be achieved by group testing procedures, e.g. over-representation analysis, functional class scoring (FCS), or global tests. RESULTS: Three public prostate cancer datasets obtained with the same microarray platform (HGU95A/HGU95Av2) were analyzed. Each dataset was subjected to normalization by either variance stabilizing normalization (vsn) or mixed model normalization (MMN). Then, statistical analysis of microarrays was applied to the vsn-normalized data and mixed model analysis to the data normalized by MMN. For multiple testing adjustment the false discovery rate was calculated and the threshold was set to 0.05. Gene lists from the same method applied to different datasets showed overlaps between 42 and 52%, while lists from different methods applied to the same dataset had between 63 and 85% of genes in common. A number of six gene lists obtained by the two statistical methods applied to the three datasets was then subjected to group testing by Fisher's exact test. Group testing by GSEA and global test was applied to the three datasets, as well. Fisher's exact test followed by global test showed more consistent results with respect to the concordance between analyses on gene lists obtained by different methods and different datasets than the GSEA. However, all group testing methods identified pathways that had already been described to be involved in the pathogenesis of prostate cancer. Moreover, pathways recurrently identified in these analyses are more likely to be reliable than those from a single analysis on a single dataset.

Biomarkers, Tumor↗

PubMed2004

An integrated approach for comparative mapping in rice and barley with special reference to the Rph16 resistance locus.

The accumulated sequence information of the almost completed rice genome and the transcriptome of other cereals provide an excellent starting point for comparative genome analysis. We performed targeted synteny-based marker saturation for the Rph16 leaf rust resistance locus in barley by extensively exploiting these newly available resources. Out of a collection of over 320,000 public barley ESTs 309 non-redundant candidate syntenic clones have been identified for this region in a two-step in silico selection procedure. For mapping, 54 barley cDNA-clones were selected due to the even distribution of their homologs on a putatively collinear 3-Mb rice BAC contig. Out of these, 97% (30) of the polymorphic markers could be genetically assigned in collinearity to the target region in barley and a set of 11 markers was integrated into an rph16 high-resolution map. Although, the collinear target region of rice does not contain an obvious candidate gene for rph16 the results demonstrate the potential of the presented procedure to efficiently utilize EST resources for synteny-based marker saturation. The systematic genome-wide exploitation of the increasing sequence data resources will strongly improve our current view of genome conservation and likely facilitate a synteny-based isolation of genes conserved across cereal species.

Chromosome Mapping↗

PubMed2005

Functional genome of the human pathogenic fungus Paracoccidioides brasiliensis.

Paracoccidioides brasiliensis is a dimorphic and thermo-regulated fungus which is the causative agent of paracoccidioidomycosis, an endemic disease widespread in Latin America. Pathogenicity is assumed to be a consequence of the cellular differentiation process that this fungus undergoes from mycelium to yeast cells during human infection. In an effort to elucidate the molecular mechanisms involved in this process a network of Brazilian laboratories carried out a transcriptome project for both cell types. This review focuses on the data analysis yielding a comprehensive view of the fungal metabolism and the molecular adaptations during dimorphism in P. brasiliensis from analysis of 6022 groups, related to expressed genes, which were generated from both mycelium and yeast phases.

Expressed Sequence Tags↗

PubMed2026

Antagonistic regulation by mango MiSPL9a and MiSPL9b regulates flowering time, drought and salt stress in Arabidopsis.

SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) transcription factors, which are unique to plants, contain a highly conserved SBP domain that regulates gene expression by binding to downstream targets. They play critical roles in various biological processes, especially in the regulation of flowering in plants. In this study, two SPL-like genes (MiSPL9a and MiSPL9b) were identified from mango genomic and transcriptomic data, and their sequence, expression and function were further analyzed. Sequence analysis revealed that MiSPL9a and MiSPL9b have open reading frames of 1173 bp and 1158 bp, respectively, with slight differences in the number of cis-regulatory elements within their promoter regions. Expression analysis under stress conditions revealed distinct patterns: MiSPL9a expression significantly differed under drought stress but did not significantly differ under salt stress, whereas MiSPL9b expression responded significantly to salt stress but changed minimally under drought stress. Phenotypic analysis of the transgenic Arabidopsis lines revealed that MiSPL9a overexpression delayed flowering, whereas MiSPL9b overexpression promoted early flowering. Under stress conditions, compared with wild-type plants, MiSPL9a-overexpressing plants presented increased drought tolerance but did not significantly differ. In contrast, MiSPL9b-overexpressing plants were sensitive to salt stress, with no notable phenotypic differences observed under drought conditions. Physiological assays revealed that under drought stress, MiSPL9a transgenic plants presented significantly reduced levels of malondialdehyde (MDA) and hydrogen peroxide (H2O2) and increased proline (Pro) content and superoxide dismutase (SOD) activity. Under salt stress, MiSPL9b transgenic plants presented opposite trends in terms of these physiological markers. In summary, both MiSPL9a and MiSPL9b are involved in the regulation of plant flowering time and stress responses, but their functions differ.

Arabidopsis↗

PubMed2026

Biological characterization of Candida parapsilosis haploids induced by voriconazole.

OBJECTIVES: Candida parapsilosis is an important opportunistic fungal pathogen causing serious human infections in nosocomial settings. It has long been thought that C. parapsilosis has a diploid genome with a high homozygosity between chromosome homologs. METHODS: In this study, we report the discovery of C. parapsilosis haploids induced by voriconazole, a triazole with broad antifungal activity against fungal pathogens, in an experimental evolutionary assay. RESULTS: The haploid strains were able to undergo auto-diploidization under in vitro culture conditions or during systemic infection at a low frequency. Compared to the progenitor diploid strain, C. parapsilosis haploid and auto-diploid strains exhibited a reduced ability of invasive growth and biofilm formation. Global transcriptional expression analysis indicated that haploid and auto-diploid strains had a similar transcriptomic profile, which showed a remarkable difference from the progenitor diploid strain perhaps due to the loss of chromosome heterozygosity. Moreover, the haploid and diploid strains had distinct fungal burdens in different animal tissues, suggesting the haploid state could have a colonization advantage over the diploids in certain tissues such as the brain and spleen. CONCLUSIONS: The discovery of C. parapsilosis haploids not only sheds lights on the biology of this important fungal pathogen, but also provides a tool for genetic modifications for the field.

Voriconazole↗

PubMed2026

From wild to domestic: Single-cell transcriptomic perspectives on hippocampal regulation and evolution.

How domestication shapes brain evolution remains an open question. In this study, we integrated single-nucleus RNA sequencing (snRNA-seq), population genomics, and machine learning to investigate the hippocampal evolution under domestication. Across-species comparisons revealed that hippocampal cell type profiles are largely conserved across vertebrate species, while supporting the presence of adult hippocampal neurogenesis in birds. We further found that domestication and selective breeding likely influence the cellular composition and molecular regulation of the hippocampus. Our findings provide cellular evidence supporting the hypothesis that domestication affects adult hippocampal neurogenesis. Additionally, we showed that genes associated with neural progenitor cells (NPC) states and cell-marker programs are enriched for signatures of selection. Many of these genes function as regulators of neurogenesis and pathways mediating stress and fear reduction. Specifically, we identified selection at the FKBP5 promoter that may influence its expression in the NPC lineage, potentially contributing to stress-response regulation during domestication. Collectively, these results suggest that domestication is associated with hippocampal remodeling as part of an adaptive response to human-managed environments. This study provides a cellular and genetic perspective on how domestication reshapes the brain and offers a basis for further investigation into the mechanisms of neural evolution within the context of microevolution.

Animals↗

PubMed2004

Virus-host cell interactions during hepatitis C virus RNA replication: impact of polyprotein expression on the cellular transcriptome and cell cycle association with viral RNA synthesis.

Considerable controversy surrounds the impact of hepatitis C virus (HCV) protein expression on viability of host cells and regulation of the cell cycle. Both promotion of cellular proliferation and apoptosis have been observed in different experimental systems. To determine whether expression of the entire complement of HCV proteins in the context of ongoing viral RNA replication significantly alters the host cell transcriptome and cell cycle regulatory processes, we carried out high-density oligonucleotide microarray studies and analyzed cell cycle distributions and S-phase entry in Huh7 cell clones harboring selectable, full-length, replicating HCV RNAs that express the entire genotype 1b, HCV-N polyprotein, and clonally related cells in which all viral RNA was eliminated by prior treatment with alpha interferon. Oligonucleotide microarray analyses revealed only subtle, coordinated differences in the mRNA profiles of cells containing replicating viral RNA and their interferon-cured progeny, with variation between different cell clones having a greater influence on the cellular transcriptome than the presence or absence of replicating HCV RNA. Flow cytometric analysis demonstrated no significant differences in cell cycle distribution among populations of asynchronously growing cells of both types. Cell lines containing replicating viral RNA and their interferon-cured progeny were able to reenter the cell cycle similarly after transient G(1) arrest. In contrast, although viral protein expression and genome replication did not alter cell cycle control in these cells, HCV genome replication was highly dependent on cellular proliferation, with viral RNA synthesis strongly decreased in poorly proliferating, confluent, or serum-starved cells and substantially enhanced in the S phase of the cell cycle.

Cell Cycle↗

PubMed2025

HMGA2 links morphological evolution and microenvironment dynamics to systemic therapy response in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits significant heterogeneity due to morphological changes and tumor microenvironment dynamics, influencing systemic therapy responses. While the role of high-mobility group AT-hook 2 (HMGA2) in tumor progression has been implicated in other cancers, its significance in ccRCC remains unclear. This study investigates the role of HMGA2 in these processes and its clinical impact. METHODS: Spatial transcriptomics (ST) was performed on primary ccRCC samples to investigate expression trajectories associated with HMGA2 expression and morphological evolution. In metastatic ccRCC cohorts treated with systemic therapy, immunohistochemistry and bulk RNA sequencing data were analyzed to evaluate molecular and clinical features in relation to HMGA2. Single-cell RNA sequencing (scRNA-seq) data were used to explore immune cell populations and their interactions. Based on these findings, multiplex immunohistochemistry (mIHC) assessed spatial distribution, cell-cell interactions, and pathological responses of key immune populations. RESULTS: HMGA2 expression was associated with aggressive morphological patterns, such as solid sheets and rhabdoid/sarcomatoid. ST revealed a progressive increase in HMGA2 expression along the morphological trajectory, marked by a shift from clear to eosinophilic cytoplasm, with eccentric nuclei and prominent nucleoli, and loss of vascular architecture. HMGA2-high tumors exhibited aggressive phenotypes driven by cell cycle, epithelial-mesenchymal transition, and inflammatory signaling pathways. Clinically, patients with high HMGA2 had worse progression-free survival but responded better to immune checkpoint inhibitor combination (Combo-ICI) therapy than to tyrosine kinase inhibitor monotherapy. To assess the immune landscape, scRNA-seq data revealed that HMGA2-high tumors were enriched with progenitor exhausted CD8+ T cells (Tpex), along with increased frequencies of conventional dendritic cell type 1 (cDC1) and inflammatory cDC type 2, which were found to interact with Tpex via ICAM-1. mIHC confirmed that Tpex were enriched among Combo-ICI responders in HMGA2-high tumors, with higher densities and closer proximity to ICAM-1+ cDC1. CONCLUSIONS: These findings suggest that dynamic HMGA2 expression contributes to morphological evolution and modulates immune responses through enhanced Tpex-cDCs engagement, serving as a potential marker for systemic therapy response in ccRCC. However, additional experimental studies are required to validate these mechanisms.

Humans↗

PubMed2026

Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.

Single-cell and spatial omics (SPOs) technologies have advanced how healthcare physicians characterise brain tumours by enabling detailed understanding of their cellular architecture, functional states, and microenvironmental dynamics. These approaches provide high-resolution detection of tumour heterogeneity and allow precise analysis of the brain tumour microenvironment. Their application has also led to the discovery of novel biomarkers used for early brain tumour detection, prognosis, and improved tumour stratification. Furthermore, integrative multi-omic analyses have revealed new therapeutic targets, clarified mechanisms of drug resistance, and uncovered molecular pathways underpinning treatment failure. By bridging cellular-level insights with spatial context, SPOs hold significant promise for advancing personalised diagnostics, predicting therapeutic response, and guiding the development of targeted interventions for brain tumours. Despite these advances, several limitations constrain the full translational potential of SPOs, including high experimental costs, substantial computational demands, lack of standardised protocols, and challenges in data integration and reproducibility. Addressing these barriers through scalable bioinformatic pipelines, consensus experimental frameworks, and cost-effective platforms remains critical for broadening accessibility and enabling clinical adoption.

Brain Neoplasms↗