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Monocarboxylate Transporter 2 (MCT2) Reduction Is Associated with Increased Lung Tumor Growth and Alterations in the Immune Microenvironment in a Subcutaneous Tumor Model.

Monocarboxylate transporter 2 (MCT2; SLC16A7) is a high-affinity pyruvate transporter implicated in cancer metabolism. However, its role in lung cancer progression and the tumor microenvironment remains unclear. This study examined the effects of MCT2 reduction on tumor growth and cell-type-specific transcriptional changes within the tumor microenvironment. MCT2 loxP/loxP mice were crossed with mCre-Tg mice, and MCT2 deletion was induced by tamoxifen. Control (CO) mice received vehicle treatment. TC1 cells (100,000 cells/mouse) were injected subcutaneously, and tumors were harvested after 24 days. Single-nucleus RNA sequencing (snRNA-seq) was performed on isolated tumor nuclei (4000 nuclei/sample; n = 3 per group) using the 10x Genomics Chromium platform. Data were processed with Cell Ranger v3.0.2 and Seurat v5.2.1, followed by differential expression and pathway enrichment analyses integrated with macrophage bulk RNA-seq data. Tumors in mice with systemic MCT2 reduction grew significantly faster than those in control mice, demonstrating an association between host MCT2 reduction and increased tumor growth. Transcriptomic analysis generated high-quality profiles from 6864 CO and 10,055 KO nuclei. Clustering identified 12 cellular populations and cell types. MCT2 reduction altered pathways involved in glycolysis, the tricarboxylic acid cycle, oxidative phosphorylation, and fatty acid metabolism across multiple populations. Macrophages showed prominent transcriptional changes, including enrichment of MAPK, PI3K-Akt, IgSF-CAM, ECM, and cytokine-cytokine signaling pathways. These findings were supported by macrophage bulk RNA-seq data. Systemic MCT2 reduction was associated with increased tumor growth and broad transcriptional alterations within the tumor micro-environment. Differences in metabolic and immune-related transcriptional programs, particularly in macrophages, identify potential mechanisms associated with tumor progression that warrant further functional investigation.

Animals

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans

Big data analytics for CLEC5A dynamics based on single cell genomics and proteomics reveal its diverse functions in human diseases.

BACKGROUND: CLEC5A (C-type lectin domain family 5 member A) is an innate immune receptor implicated in inflammatory signaling, contributing to hyperinflammatory responses in infections and sterile inflammation. However, CLEC5A dynamics in human diseases remain to be identified. Here, we systematically characterized CLEC5A dynamics in humans across cells, tissues, and disease states, and to explore the functional significance of CLEC5A in macrophage activation based on single-cell genomics. METHODS: With multi-omics (scRNA-seq, proteomics and big data analytics), we analyzed extensive human transcriptomic datasets (>42,000 samples) to profile CLEC5A expression by cell type, tissue, and disease. Single-nucleus RNA-seq (snRNA-seq) from pediatric congenital heart disease and a virtual CLEC5A gene knockout were also performed to characterize CLEC5A dynamics in humans. RESULTS: CLEC5A is highly enriched in innate immune cells, particularly in macrophages and neutrophils. Baseline CLEC5A in most tissues is low, but it is markedly upregulated in inflammatory and infectious diseases. CLEC5A expression has sex-specific differences in certain organs. Single-cell analysis showed that CLEC5A can be considered novel marker of proinflammatory macrophages with elevated cytokine production, antigen presentation, and impaired phagocytosis. Virtual CLEC5A knockout analysis identified coordinated perturbation of immune-regulatory pathways and overlapping genes linking CLEC5A to macrophage activation networks. CONCLUSION: CLEC5A is predominantly expressed in myeloid cells and acts as a key amplifier of inflammation in human diseases. Our findings highlight CLEC5A as a potential biomarker and therapeutic target in myeloid-driven hyperinflammatory conditions, warranting further experimental and translational validation.

Humans

Machine learning algorithm-based biomarker exploration and validation of mitochondria-related diagnostic genes in osteoarthritis.

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes associated with OA from a set of mitochondria-related genes (MRGs). First, the gene expression profiles of OA cartilage GSE114007 and GSE57218 were obtained from the Gene Expression Omnibus. And the limma method was used to detect differentially expressed genes (DEGs). Second, the biological functions of the DEGs in OA were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Wayne plots were employed to visualize the differentially expressed mitochondrial genes (MDEGs) in OA. Subsequently, the LASSO and SVM-RFE algorithms were employed to elucidate potential OA signature genes within the set of MDEGs. As a result, GRPEL and MTFP1 were identified as signature genes. Notably, GRPEL1 exhibited low expression levels in OA samples from both experimental and test group datasets, demonstrating high diagnostic efficacy. Furthermore, RT-qPCR analysis confirmed the reduced expression of Grpel1 in an in vitro OA model. Lastly, ssGSEA analysis revealed alterations in the infiltration abundance of several immune cells in OA cartilage tissue, which exhibited correlation with GRPEL1 expression. Altogether, this study has revealed that GRPEL1 functions as a novel and significant diagnostic indicator for OA by employing two machine learning methodologies. Furthermore, these findings provide fresh perspectives on potential targeted therapeutic interventions in the future.

Humans

GBMdeconvoluteR accurately infers proportions of neoplastic and immune cell populations from bulk glioblastoma transcriptomics data.

BACKGROUND: Characterizing and quantifying cell types within glioblastoma (GBM) tumors at scale will facilitate a better understanding of the association between the cellular landscape and tumor phenotypes or clinical correlates. We aimed to develop a tool that deconvolutes immune and neoplastic cells within the GBM tumor microenvironment from bulk RNA sequencing data. METHODS: We developed an IDH wild-type (IDHwt) GBM-specific single immune cell reference consisting of B cells, T-cells, NK-cells, microglia, tumor associated macrophages, monocytes, mast and DC cells. We used this alongside an existing neoplastic single cell-type reference for astrocyte-like, oligodendrocyte- and neuronal progenitor-like and mesenchymal GBM cancer cells to create both marker and gene signature matrix-based deconvolution tools. We applied single-cell resolution imaging mass cytometry (IMC) to ten IDHwt GBM samples, five paired primary and recurrent tumors, to determine which deconvolution approach performed best. RESULTS: Marker-based deconvolution using GBM-tissue specific markers was most accurate for both immune cells and cancer cells, so we packaged this approach as GBMdeconvoluteR. We applied GBMdeconvoluteR to bulk GBM RNAseq data from The Cancer Genome Atlas and recapitulated recent findings from multi-omics single cell studies with regards associations between mesenchymal GBM cancer cells and both lymphoid and myeloid cells. Furthermore, we expanded upon this to show that these associations are stronger in patients with worse prognosis. CONCLUSIONS: GBMdeconvoluteR accurately quantifies immune and neoplastic cell proportions in IDHwt GBM bulk RNA sequencing data and is accessible here: https://gbmdeconvoluter.leeds.ac.uk.

Humans

Genomic and transcriptomic insights into the virulence and adaptation of shock syndrome-causing Streptococcus anginosus.

Streptococcus anginosus is a common isolate of the oral cavity and an opportunistic pathogen for systemic infections. Although the pyogenic infections caused by S. anginosus are similar to those caused by Streptococcus pyogenes, S. anginosus lacks most of the well-characterized virulence factors of S. pyogenes. To investigate the pathogenicity of S. anginosus, we analysed the genome of a newly identified S. anginosus strain, KH1, which was associated with toxic shock-like syndrome in an immunocompetent adolescent. The genome of KH1 contains nine genomic islands, two Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated systems and many phage-related proteins, indicating that the genome is influenced by prophages and horizontal gene transfer. Comparative genome analysis of 355 S. anginosus strains revealed a significant difference between the sizes of the pan genome and core genome, reflecting notable strain variations. We further analysed the transcriptomes of KH1 under conditions mimicking either the oral cavity or the bloodstream. We found that in an artificial saliva medium, the expression of a putative quorum quenching system and pyruvate oxidase for H2O2 production was upregulated, which could optimize the competitiveness of S. anginosus in the oral ecosystem. Conversely, in a modified serum medium, purine and glucan biosynthesis, competence and bacteriocin production were significantly upregulated, likely facilitating the survival of KH1 in the bloodstream. These findings indicate that S. anginosus can utilize diverse mechanisms to adapt to different environmental niches and establish infection, despite its lack of toxin production.

Streptococcus anginosus

Molecular and immune profiling of HER2-low, HER2 ultra-low, and HER2-null male breast cancer.

BACKGROUND: HER2 expression is described along a biological continuum from null to positive and serves as a critical biomarker for therapeutic guidance in breast cancer (BC). While HER2-low and ultra-low categories have emerged as actionable targets for antibody-drug conjugates (ADCs) in female BC, their molecular and immune characteristics remain largely unexplored in male breast cancer. METHODS: We profiled 214 male breast tumors using next-generation sequencing and whole-transcriptome sequencing to assess mutational, transcriptomic, and immune landscapes. Tumor mutational burden (TMB) was defined as high if > 10 mutations/Mb. Immune cell fractions were inferred using Quantiseq deconvolution. RESULTS: Among 214 samples, 66 (30.8%) were HER2-null, 53 (24.8%) HER2 ultra-low, 80 (37.4%) HER2-low, and 15 (7.0%) HER2-positive. HER2 ultra-low tumors exhibited a higher prevalence of PIK3CA mutations (39.2% vs 22.6%, p ≤ 0.05) compared to HER2-null. No significant differences were observed in TMB-high frequency or PD-L1 expression across subgroups. Immune composition differed primarily between HER2-null and HER2-expressing subgroups: HER2-ultra-low tumors showed higher B-cell infiltration, whereas HER2-null tumors were enriched in neutrophils. Transcriptomic analysis revealed upregulation of selected stemness-associated genes (NANOG, KLF4, POU5F1) and CEACAM1 in HER2-null tumors, while HER2-low and HER2-ultra-low tumors were largely similar across most molecular and immune readouts in this cohort. CONCLUSIONS: HER2-null male breast cancer appears to represent the most biologically divergent subgroup within the HER2-negative spectrum, whereas HER2-low and HER2-ultra-low tumors were largely similar in this cohort. These findings support further investigation of HER2-null disease as a distinct biological state and provide hypothesis-generating data for biomarker development in this rare population.

Male

Distinct spatial transcriptomic patterns of substantia Nigra in Parkinson disease and Parkinsonian subtype of multiple system atrophy.

To investigate transcriptomic signatures of Parkinson's disease (PD) and the Parkinsonian subtype of Multiple System Atrophy (MSA-P) in substantia nigra pars compacta (SNpc), we conducted transcriptome analysis using in-situ hybridization on paraffin-embedded SNpc tissues from post-mortem brains. The study included 2 MSA-P patients, 2 PD patients, and 2 healthy controls (HC), with 12 regions of interest (ROIs) selected from the dorsal to ventral and medial to lateral aspects of the SNpc. A total of 72 ROIs from 6 participants were analyzed, and differentially expressed genes (DEGs) were identified by comparing MSA-P, PD and HC groups. The MSA-P group showed 88 upregulated DEGs and 326 downregulated DEGs (adjusted &#x1d45d;<0.05) compared to HC. The downregulated DEGs were significantly enriched in pathways related to ribosomal translation, immune processes, mitochondrial function, and autophagy. Notably, the dorsomedial quadrant was uniquely linked to antigen presentation, while other quadrants showed downregulation of protein synthesis. The PD group exhibited 165 upregulated DEGs and 350 downregulated DEGs (adjusted &#x1d45d;<0.05) compared to HC, with downregulated DEGs associated with ribosomal translation, mitochondrial function, and the ubiquitin-proteasome system. In both MSA-P and PD, the upregulated DEGs were not associated with any pathways or biological process in gene enrichment analysis. In network propagation analysis, amyloid precursor protein was the most significant network hub among DEGs in both MSA-P and PD. Comparing the transcriptomic signatures of SNpc between MSA-P and PD, we found immune/inflammation, mitochondrial function and neural signaling related genes were significantly downregulated in MSA-P compared to PD. Overall, the transcriptomic signature of the SNpc in MSA-P and PD revealed overlapping but distinct features, including alterations in protein synthesis, immune processes, mitochondrial function, and protein degradation systems. Future studies with larger cohorts and functional validation are needed to further elucidate these findings.

Humans

Immune profiling in a living human recipient of a gene-edited pig kidney.

Xenotransplantation of gene-edited pig kidneys offers a promising solution to the shortage of kidneys for organ transplantation. We recently performed a gene-edited pig kidney transplantation into a living human recipient with end-stage kidney disease. Here, using transcriptomics, proteomics, metabolomics and multiplexed imaging, we conducted high-dimensional immune profiling in this individual. Despite profound depletion of circulating T cells, early T cell-mediated rejection occurred within 1 week after transplantation, likely driven by subtherapeutic immunosuppression and the presence of residual CD8+ T cells in lymph nodes. This T cell-mediated rejection event was reversed by intensified immunosuppression. After treatment, adaptive immunity remained suppressed, whereas innate immune activation, characterized by sustained monocyte and macrophage activity along with elevated levels of interleukin-1 beta and granulocyte-macrophage colony-stimulating factor, persisted. Comparative transcriptomic analysis showed that xenograft rejection profiles resembled those typically observed in human allograft rejection, while also revealing unique innate immune signatures. We did not detect antibody-mediated rejection. The levels of circulating pig donor-derived cell-free DNA rose during the initial rejection episode and declined with treatment, supporting the potential of cell-free DNA measurements as a noninvasive biomarker of xenograft rejection. These findings define the distinct immune landscape of kidney xenotransplantation and highlight the need for regimens targeting both innate and adaptive immunity to improve outcomes.

Animals

Changes of DNA methylation and gene expression profile in placental villi and chorioamniotic membranes under preeclampsia.

BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication with elusive pathogenesis. Although epigenetic dysregulation is implicated, its layer-specific placental roles are poorly defined. This study aimed to identify shared and layer-specific epigenetic alterations in PE by profiling DNA methylation and gene expression in placental villi (PV) and chorioamniotic membranes (CAM). RESEARCH DESIGN AND METHODS: PV and CAM samples were collected from 7 normal and 8 PE pregnancies, and three public DNA methylation datasets (GSE98224, GSE44667, GSE75196) were integrated. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified based on whole-genome methylation and transcriptome sequencing. Layer-specific and shared gene sets were identified by cross-analysis, with functional annotation using Gene Ontology (GO). RESULTS: EM-seq revealed a hypermethylation-dominant, tissue-specific methylation landscape in PE placentas. Cross-tissue comparison identified shared DMGs between the two layers, including nine key genes consistently altered in public datasets. Integrated analysis in PV further identified 22 co-dysregulated genes, enriched in thermoregulation, maternal-fetal immunity, signal transduction, and cell differentiation. CONCLUSIONS: This study elucidates the shared and layer-specific dysregulation of gene networks at methylomic and transcriptomic levels in PE placenta. Comparing PV and CAM highlights placental epigenetic heterogeneity and dysfunction, offering novel clues for mechanistic research and layer-targeted therapies.

Humans

Intratumoral B cell and interferon signatures in newly diagnosed glioblastoma are associated with longer survival in patients treated with SurVaxM.

Glioblastoma (GBM) has proved difficult to treat, and there is dire need for more effective therapies. In a single arm phase IIa trial (NCT02455557), treatment of newly diagnosed GBM patients with the peptide vaccine SurVaxM resulted in promising median progression-free and overall survival. To investigate molecular features that associate with GBM responsiveness to SurVaxM, retrospective whole exome and RNA sequencing was performed on patient tumors (n&#x2009;=&#x2009;34) collected prior to standard of care treatment plus SurVaxM. Differential gene expression and mutational profiles were characterized between patients with short-term (OS&#x2009;<&#x2009;18&#xa0;months) or long-term (OS&#x2009;&#x2265;&#x2009;18&#xa0;months) overall survival. Greater expression of interferon, complement, and humoral immunity signatures were associated with long-term survival. Deconvolution of transcriptomes identified enrichment of intratumoral memory B cell populations in long-term survivors that were validated by CD20 staining in matched samples. A five-gene expression signature and a B cell specific signature predicted survival within the SurVaxM-treated cohort, however, these signatures were not associated with improved outcomes in a similarly treated population obtained from The Cancer Genome Atlas (TCGA) that did not receive immunotherapeutic intervention. Although prospective validation is ongoing, the findings in this discovery cohort specify molecular features of GBM associated with better overall survival and potential responsiveness to immunotherapy with SurVaxM.

Humans

Time-resolved mapping in calves reveals bovine herpesvirus 1 shift from mucosal replication to trigeminal ganglion neuroinvasion with promyelocytic leukemia protein-centered host-virus antagonism.

Although bovine herpesvirus 1 (BoHV-1) causes massive losses of cattle, the transition from mucosal replication to neuroinvasion remains poorly understood. Using a controlled calf model, we integrated quantitative virology and transcriptomics to map its pathogenesis and define the role of promyelocytic leukemia protein (PML). Calves inoculated intranasally and ocularly (1.4 &#xd7; 106 plaque-forming units/head) were sampled daily (1-14 days post-infection, dpi) for glycoprotein B (gB) qPCR. Tissues were analyzed at 4 and 14 dpi to measure viral DNA via gB-specific qPCR, and for mRNA-seq of trigeminal ganglia (TG). Shedding peaked at 3-6 dpi, being highest in nasal samples, lower in ocular samples, and substantially lower in rectal samples, and declined by 10-14 dpi. At 4 dpi, among the tissues sampled, the tonsils exhibited the highest viral burden. TG exhibited low viral levels at 4 dpi, although they remained detectable at 14 dpi, indicating neuroinvasion. The TG program shifted from early proteostasis priming (4 dpi) to immune/extracellular matrix activation with synaptic repression (14 dpi). In MDBK/Vero cells, IFN-&#x3b1; resulted in higher bovine PML (bPML) levels and enlarged PML nuclear bodies (PML-NBs), reducing very early viral DNA levels, whereas BoHV-1 disrupted PML-NB integrity. The different bPML isoforms exerted different effects on viral infection. STRING analysis revealed a conserved PML-SUMO1-UBE2I-DAXX-SP100 core. These findings delineate the mucosal-to-neuronal trajectory, establish PML as both an effector and viral target in complementary in vitro systems, and identify SUMO/ubiquitin-linked proteostasis as a tractable target for antiviral intervention.IMPORTANCEAlthough bovine herpesvirus 1 (BoHV-1) remains a major challenge to cattle health, the early transition from mucosal replication to trigeminal neuroinvasion has not been clearly mapped in natural-host calves. By integrating daily shedding kinetics, tissue viral DNA profiling, and time-resolved trigeminal ganglion transcriptomics, we delineate when and how BoHV-1 reaches the sensory neurons. Promyelocytic leukemia protein (PML) is identified as a key intrinsic antiviral factor that is upregulated by IFN-&#x3b1; and restricts very early viral genome accumulation, while viral BoHV-1-encoded infected cell protein 0 actively dismantles PML nuclear bodies. The discovery of opposing isoform-specific PML functions and a conserved PML-SUMO proteostasis hub provides mechanistic insight into BoHV-1 immune evasion. These findings refine our understanding of the mucosal-to-neuronal trajectory of infection and highlight proteostasis-linked antiviral pathways as promising targets for intervention.

Animals

Selective saccular plasticity under microgravity links peripheral transcriptomic remodeling to postflight vestibular dysfunction.

Long-duration exposure to microgravity disrupts human balance and spatial orientation, yet the molecular mechanisms underlying vestibular adaptation to spaceflight remain poorly understood. Here, we tested the hypothesis that the saccule, the primary gravity-sensing otolith organ, undergoes selective remodeling during spaceflight and contributes to transient postflight postural instability. Using a cross-species approach, we combined transcriptomic analysis of mouse otolith organs with physiological assessments in astronauts. Laser microdissection-based RNA sequencing of mouse otolith sensory epithelia after a 35-d spaceflight revealed pronounced, organ-specific transcriptomic remodeling in the saccule, whereas the utricle remained stable. Principal component and clustering analyses demonstrated that the saccular transcriptome shifted toward an utricle-like profile under microgravity, accompanied by changes in genes related to synaptic and neuronal function. Promoter motif analysis identified NFAT-associated transcriptional networks, suggesting Ca2+-dependent regulation of synaptic plasticity as a potential molecular substrate of gravity-dependent adaptation. In parallel, vestibular testing in astronauts following long-duration missions (157 to 328 d) revealed selective attenuation of saccule-mediated cervical vestibular-evoked myogenic potentials and increased postural sway immediately after return to Earth, while utricle-mediated responses and semicircular canal function were preserved. Both saccular function and postural stability recovered within approximately 10 d. Notably, early postflight postural instability was partially mitigated by noisy galvanic vestibular stimulation, consistent with stochastic resonance-mediated sensory enhancement. Together, these findings identify the saccule as a plastic gravity sensor and establish a mechanistic link between peripheral molecular remodeling and functional balance deficits after spaceflight, providing a framework for developing countermeasures to facilitate vestibular readaptation during human space exploration.

Animals

Next-generation sequencing in breast cancer: current clinical applications and future directions.

INTRODUCTION: Breast cancer is a heterogeneous disease that claims 670,000 lives by 2022. Omic technologies, particularly next generation sequencing (NGS) offers promising avenues for precision medicine. American Society of Clinical Oncology (ASCO) outlines genomic testing's utility, emphasizing prognostic and diagnostic potential. OBJECTIVES: This review succinctly explores NGS's evolution and clinical applications of NGS in breast cancer, thereby guiding future research to enhance patient care. METHODS: Comprehensive literature searches were conducted using databases such as PubMed, Google Scholar, and ResearchGate, focusing on keywords including breast cancer, HER-2 low breast cancer, circulating tumour DNA, single-cell RNA sequencing, and next-generation sequencing. Peer-reviewed, high-quality articles published in English were selected for inclusion. RESULTS: Previous studies have explored the evolution of NGS technology and its clinical applications in breast cancer, including genomic and transcriptomic characterization, treatment guidance, and resistance prediction. Molecular profiling of challenging entities such as early-onset breast cancer and HER-2 low tumours was summarized, with key findings highlighted. This review also discusses emerging technologies, including circulating DNA and single-cell sequencing, as promising avenues for discovery. CONCLUSION: NGS has revealed the genomic and transcriptomic diversity of breast cancer, identifying actionable alterations associated with chemotherapy response and resistance to therapies such as trastuzumab, TKIs, and CDK4/6 inhibitors. Circulating tumour DNA (ctDNA) shows potential for diagnosis, prediction, prognosis, and monitoring, despite tumour heterogeneity. Single-cell analysis enables exploration of individual cell transcriptomes, though high costs and low throughput remain barriers to widespread adoption. HER2-low tumours continue to pose significant research challenges.

Humans

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU&#xb7;mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays

Ten quick tips for spatial transcriptomics analysis.

Spatial transcriptomics (ST) enables genome-wide gene expression profiling while retaining spatial context within tissue sections. Since the foundational work by St&#xe5;hl et al. in 2016, the field has expanded rapidly, with diverse platforms now spanning sequencing-based (e.g., Visium, Visium HD, Slide-seq, Stereo-seq, and Seq-Scope) and imaging-based (e.g., MERFISH, Xenium, and CosMx SMI) approaches. The breadth of platforms, data structures, and computational tools, however, can be daunting for newcomers. Here, we present ten quick tips spanning the entire ST research workflow: whether ST suits a given biological question, how to select a platform aligned with study objectives, how to understand and process ST data, and which software tools to employ for analysis and visualization. We further discuss interpreting spatial patterns in biological context, integrating complementary modalities such as single-cell RNA sequencing and spatial proteomics, and leveraging public datasets and sharing results. Finally, we highlight current limitations of ST, particularly the challenge of reconstructing three-dimensional tissue architecture from serial tissue sections. This review provides biologists, bioinformaticians, and clinician-scientists with a concise, platform-neutral roadmap for incorporating ST into research, from experimental design to biological discovery.

Spatial Transcriptomics

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering.

Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcriptomics, delineating higher-order anatomical structures is critical for understanding how cellular organization affects function. However, the reliability of current benchmarks of spatially aware clustering (SAC) methods is undermined by their narrow focus on Visium and brain tissue datasets and the incorrect interpretation of manual annotation as ground truth. Here we present SACCELERATOR, a community-driven, extensible framework that standardizes data formatting, method integration and metric evaluation, enabling rapid inclusion of new methods and datasets. Our analysis revealed substantial limitations in the generalizability and reproducibility of SAC methods and shows that anatomical labels commonly used as ground truths are often biased, error prone and unsuitable for benchmarking. Rather than ranking methods, we propose a consensus-guided workflow where descriptive spatial metrics highlight high-entropy regions of method disagreement, enabling targeted feedback for tissue experts. Applied to brain and cancer datasets, this approach uncovered biologically meaningful patterns overlooked by individual SAC methods and manual annotations, highlighting the need for iterative, expert-in-the-loop evaluation.

Benchmarking