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Functional genomics and gene expression profiling in sepsis: beyond class prediction.

Functional genomics involving genome-wide expression analyses is rapidly finding applications in clinical medicine. New technologies now permit the simultaneous analysis of mRNA levels for the entire human transcriptome from as few as 1000 cells. This approach is dramatically changing the way we define health and disease, allowing, for the first time, an unbiased view of the global changes in gene expression that are occurring. For the study of trauma biology and sepsis, this technology offers a powerful tool to develop molecular signatures for inflamed tissues and specific cell populations. At present, functional genomics is being used to classify the progress of disease and survival in response to traumatic and burn injury, sepsis and visceral ischemia, and reperfusion injury, as well as to describe patterns of gene expression in response to varying microbial pathogens. As the number of bioinformatics tools increases, functional genomics is beginning to reveal the underlying complexity of the biological response to a variety of inflammatory diseases and is providing new approaches for their exploration. Functional genomics is becoming a standard tool in inflammation research as a means to unravel the basic biological processes.

Animals↗

scBaseCount: An AI agent-curated, standardized, auto-updated single-cell data repository.

Single-cell RNA sequencing has transformed cell biology by enabling precise transcriptomic measurements of individual cells. The Sequence Read Archive (SRA) is the largest public repository of sequencing reads, yet much of it remains underutilized due to unstandardized metadata. Here, we introduce scBaseCount, a database that leverages an AI agent to automate discovery and metadata extraction and standardize data processing. Built by mining all 10x Genomics datasets, scBaseCount is the largest public repository of single-cell gene expression data, comprising over 502 million cells across 27 organisms and 75 tissues. It offers an unbiased view of the data landscape within the SRA and enables the training of more performant computational models through access to broader phenotypic diversity. Uniform processing enables measurement of both intronic and exonic reads and non-coding gene expression and improves alignment across experiments. Moreover, scBaseCount provides a blueprint for how AI can be leveraged to autonomously curate biological data repositories.

Single-Cell Analysis↗

Gene expression analysis of Tek/Tie2 signaling.

The elaboration of the vasculature during embryonic development involves restructuring of the early vessels into a more complex vascular network. Of particular importance to this vascular remodeling process is the requirement of the Tek/Tie2 receptor tyrosine kinase. Mouse gene-targeting studies have shown that the Tie2-deficient embryos succumb to embryonic death at midgestation due to insufficient sprouting and remodeling of the primary capillary plexus. To identify the underlying genetic mechanisms regulating the process of vascular remodeling, transcriptomes modulated by Tie2 signaling were analyzed utilizing serial analysis of gene expression (SAGE). Two libraries were constructed and sequenced using embryonic day 8.5 yolk sac tissues from Tie2 wild-type and the Tie2-null littermates. After tag extraction, 45,689 and 45,275 SAGE tags were obtained for the Tie2 wild-type and Tie2-null libraries, respectively, yielding a total of 21,376 distinct tags. Close to 62% of the tags were uniquely annotated, whereas 10% of the total tags were unknown. Using semiquantitative PCR, the differential expression of eight genes was confirmed that included Elk3, an important angiogenic switch gene which was upregulated in the absence of Tie2 signaling. The results of this study provide valuable insight into the potential association between Tie2 signaling and other known angiogenic pathways as well as genes that might have novel functions in vascular remodeling.

Animals↗

Reversible histone acetylation and deacetylation mediate genome-wide, promoter-dependent and locus-specific changes in gene expression during plant development.

Histone acetylation and deacetylation activate or repress transcription, yet the physiological relevance of reversible changes in chromatin structure and gene expression is poorly understood. We have shown that disrupting the expression of AtHD1 that encodes a putative Arabidopsis thaliana histone deacetylase induces a variety of developmental abnormalities. However, causal effects of the AtHD1 disruption on chromatin structure and gene expression are unknown. Using Arabidopsis spotted oligo-gene microarray analysis, here we report that >7% of the transcriptome was up- or downregulated in A. thaliana plants containing a T-DNA insertion in AtHD1 (athd1-t1), indicating that AtHD1 provides positive and negative control of transcriptional regulation. Remarkably, genes involved in ionic homeostasis and protein synthesis were ectopically expressed, whereas genes in ionic homeostasis, protein transport, and plant hormonal regulation were repressed in athd1-t1 leaves or flowers, suggesting a role of AtHD1 in developmental and environmental regulation of gene expression. Moreover, defective AtHD1 induced site-specific and reversible acetylation changes in H3-Lys9, H4-Lys12, and H4 tetra-lysines (residues 5, 8, 12, and 16) in homozygous recessive and heterozygous plants. Transcriptional activation was locus specific and often associated with specific acetylation sites in the vicinity of promoters, whereas gene repression did not correlate with changes in histone acetylation or correlated directly with H3-Lys9 methylation but not with DNA methylation. The data suggest that histone acetylation and deacetylation are promoter dependent, locus specific, and genetically reversible, which provides a general mechanism for reversible gene regulation responsive to developmental and environmental changes.

Acetylation↗

Single-cell RNA sequencing defines developmental progression and reproductive transitions of Pneumocystis carinii.

UNLABELLED: Pneumocystis species are host-obligate fungal pathogens that cause severe pneumonia in immunocompromised individuals. Despite their clinical importance, their life cycle remains poorly understood, in part because Pneumocystis depends on the host environment for most nutrients and requires sexual reproduction for survival, which occurs exclusively in vivo. This study presents the first single-cell RNA sequencing (scRNA-seq) atlas of Pneumocystis carinii, generated from isolated organisms recovered from the bronchoalveolar lavage fluid of infected rats to map the life cycle of P. carinii. Transcriptomes from 87,716 cells were analyzed using the 10× Genomics platform, revealing 13 transcriptionally distinct clusters representing key developmental stages, including biosynthetically active trophic forms, mating-competent intermediates, and asci undergoing sporulation. These states were characterized by expression of MAPK signaling components, β-glucan-modifying enzymes, and spore-associated genes, respectively. The scRNA-seq data support previous evidence that these host-obligate fungi undergo sexual reproduction and provide new insights into the gene expression patterns associated with different life cycle phases. Biomarkers associated with ascus formation identified by scRNA-seq were validated by RT-qPCR, showing decreased expression levels in ascus-depleted populations treated with anidulafungin, a drug that halts ascus formation. More broadly, this approach provides a strategy for studying the full life cycles of fungal pathogens that cannot be continuously cultured. IMPORTANCE: Pneumocystis species (spp.) are clinically significant fungal pathogens that cannot be sustainably cultured in vitro due to their host-obligate nature. This longstanding limitation has impeded progress in understanding their life cycle and identifying therapeutic vulnerabilities. Here, we apply scRNA-seq to P. carinii isolated directly from infected rat lungs, generating the first transcriptional map of its developmental progression. Our results define discrete gene expression states associated with trophic growth, mating activation, and ascus formation and provide transcriptional evidence for a structured life cycle, clarifying key developmental transitions and identifying potential regulatory targets for therapeutic intervention. Importantly, this study demonstrates that scRNA-seq can resolve the developmental biology of host-restricted fungal pathogens that cannot be cultured in vitro. This approach offers a generalizable framework for investigating other unculturable or obligate microbial pathogens directly within their native host environments, where traditional experimental tools are limited.

Pneumocystis carinii↗

Multiomics analysis reveals that senescent CXCL16+ macrophages promote lung adenocarcinoma progression through TGF-β signalling.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer and remains a leading cause of cancer-related mortality worldwide. Although, immunotherapy has become a cornerstone of first-line treatment, only 20-30% of patients achieve a durable clinical benefit, largely because of the complexity and heterogeneity of the tumour immune microenvironment. Emerging evidence indicates that cellular senescence, particularly within immune cells, contributes to tumour progression by impairing antitumour immunity; however, its mechanistic role in LUAD remains incompletely understood. METHODS: We performed an integrative multiomics analysis incorporating genome-wide association studies (GWASs), bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomics to characterize immune heterogeneity in LUAD. Cellular senescence was validated by performing staining for senescence-associated β-galactosidase and the canonical markers p16 and p21. SHAP analysis was applied to evaluate the contribution of CXCL16+ macrophages. Functional roles were assessed using coculture assays, in vitro and in vivo tumour models, orthotopic tumour implantation, and multiplex immunofluorescence staining of clinical specimens. RESULTS: A summary data-based on Mendelian randomization analysis integrating GWAS and TCGA data identified CXCL16 as a senescence-associated gene that is causally linked to the LUAD risk. Single-cell RNA sequencing revealed that CXCL16 is predominantly expressed in macrophages, and the pseudotime analysis together with β-galactosidase staining confirmed its association with macrophage senescence. Spatial transcriptomics and immunofluorescence staining showed the marked enrichment of CXCL16+ macrophages in LUAD tissues. The cell-cell communication analysis further revealed a strong association between the number of CXCL16+ macrophages and the activation of the TGF-β signalling pathway within the tumour microenvironment. Functionally, CXCL16+ macrophages promoted LUAD progression via TGF-β signalling, as validated in vitro and in subcutaneous and orthotopic tumour models. Molecular dynamics simulations additionally suggested that LUAD patients with high levels of CXCL16+ macrophage infiltration may exhibit increased sensitivity to bosutinib. CONCLUSIONS: CXCL16 promotes macrophage senescence, and senescent CXCL16+ macrophages drive LUAD progression through TGF-β signalling. These findings identify CXCL16+ macrophages as a biologically and therapeutically relevant immune cell population, highlighting a potential target for precision intervention in LUAD.

Humans↗

Translational profiling: the genome-wide measure of the nascent proteome.

Translation in eukaryotic cells is both physically and temporally separated from transcription. This provides cells with extended options to alter their proteome: (1) directly, by synchronizing translation with an altering transcriptional profile; (2) by imposing a changed translational control over transcripts already present in the transcriptome; or (3) by a combination of (1) and (2). In this paper, recent findings in the controlled translation of the transcriptome using microarray analyses are reviewed. A guide to the current technologies and data analysis is also provided, and future directions in the study of translational control as the interface between the transcriptome and the proteome are outlined. This survey is focused on the yeast Saccharomyces cerevisiae, but the topics covered have universal relevance to the control of translation in eukaryotic cells.

Gene Expression Profiling↗

Comparison of changes in fruit gene expression in tomato introgression lines provides evidence of genome-wide transcriptional changes and reveals links to mapped QTLs and described traits.

Total soluble solids content is a key determinant of tomato fruit quality for processing. Several tomato lines carrying defined introgressions from S. pennellii in a S. lycopersicum background produce fruit with elevated Brix, a refractive index measure of soluble solids. The genetic basis for this trait can be determined by fine-mapping each QTL to a single gene, but this is time-consuming and technically demanding. As an alternative, high-throughput analytical technologies can be used to provide useful information that helps characterize molecular changes in the introgression lines. This paper presents a study of transcriptomic changes in six introgression lines with increased fruit Brix. Each line also showed altered patterns of fruit carbohydrate accumulation. Transcriptomic changes in fruit at 20 d after anthesis (DAA) were assessed using a 12 000-element EST microarray and significant changes analysed by SAM (significance analysis of microarrays). Each non-overlapping introgression resulted in a unique set of transcriptomic changes with 78% of significant changes being unique to a single line. Principal components analysis allowed a clear separation of the six lines, but also revealed evidence of common changes; lines with quantitatively similar increases in Brix clustered together. A detailed examination of genes encoding enzymes of primary carbon metabolism demonstrated that few of the known introgressed alleles were altered in expression at the 20 DAA time point. However, the expression of other metabolic genes did change. Particularly striking was the co-ordinated up-regulation of enzymes of sucrose mobilization and respiration that occurred only in the two lines with the highest Brix increase. These common downstream changes suggest a similar mechanism is responsible for large Brix increases.

Carbohydrate Metabolism↗

Pathway analysis of kidney cancer using proteomics and metabolic profiling.

BACKGROUND: Renal cell carcinoma (RCC) is the sixth leading cause of cancer death and is responsible for 11,000 deaths per year in the US. Approximately one-third of patients present with disease which is already metastatic and for which there is currently no adequate treatment, and no biofluid screening tests exist for RCC. In this study, we have undertaken a comprehensive proteomic analysis and subsequently a pathway and network approach to identify biological processes involved in clear cell RCC (ccRCC). We have used these data to investigate urinary markers of RCC which could be applied to high-risk patients, or to those being followed for recurrence, for early diagnosis and treatment, thereby substantially reducing mortality of this disease. RESULTS: Using 2-dimensional electrophoresis and mass spectrometric analysis, we identified 31 proteins which were differentially expressed with a high degree of significance in ccRCC as compared to adjacent non-malignant tissue, and we confirmed some of these by immunoblotting, immunohistochemistry, and comparison to published transcriptomic data. When evaluated by several pathway and biological process analysis programs, these proteins are demonstrated to be involved with a high degree of confidence (p values < 2.0 E-05) in glycolysis, propanoate metabolism, pyruvate metabolism, urea cycle and arginine/proline metabolism, as well as in the non-metabolic p53 and FAS pathways. In a pilot study using random urine samples from both ccRCC and control patients, we performed metabolic profiling and found that only sorbitol, a component of an alternative glycolysis pathway, is significantly elevated at 5.4-fold in RCC patients as compared to controls. CONCLUSION: Extensive pathway and network analysis allowed for the discovery of highly significant pathways from a set of clear cell RCC samples. Knowledge of activation of these processes will lead to novel assays identifying their proteomic and/or metabolomic signatures in biofluids of patient at high risk for this disease; we provide pilot data for such a urinary bioassay. Furthermore, we demonstrate how the knowledge of networks, processes, and pathways altered in kidney cancer may be used to influence the choice of optimal therapy.

Adult↗

Characterization of salivary RNA by cDNA library analysis.

Oral fluid (saliva) meets the demands for a noninvasive and accessible diagnostic medium. Recent reports by our group and others described the presence and use of human RNA in saliva as a diagnostic or forensic tool, including the use for oral cancer detection. To gain insights into the integrity of salivary RNA, we examined in detail the integrity of salivary RNA by generating a cDNA library from pooled supernatant saliva of 10 healthy donors. From a library with a primary library titer of 1.3 x 10(6) cfu/mL of which 95% of the clones had inserts, we successfully sequenced 117 random colonies containing recombinant clones. BLAST search results indicated that all of these clones contained sequences of human origin. Most of the salivary RNAs appeared to be endonucleolytically cleaved at random positions as indicated by comparisons to respective full length parental RNAs from the Genbank. Twelve of the insert sequences matched to the normal salivary core transcriptome sequences, which are highly abundant mRNAs present in healthy individuals. This study provides an in-depth molecular analysis of the saliva transcriptome and should be a useful resource for future basic and translational studies of RNA in human saliva. In addition, this paper presents unequivocal evidence for the presence of RNA in saliva as determined by the use of diverse techniques such as reverse transcriptase quantitative polymerase chain reaction (RT-qPCR), in vitro translation, and the construction of a salivary cDNA library.

Adult↗

The Multi-Omics Landscape of Enzymatic Alterations in Systemic Lupus Erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is an autoimmune disease closely associated with enzyme dysfunction, yet its underlying molecular mechanisms remain incompletely understood. This study aims to characterize enzyme-network alterations associated with SLE status and disease activity and to identify candidate molecules with potential clinical relevance. METHODS: We integrated proteomic and phosphoproteomic data from peripheral blood mononuclear cells (PBMCs) of 130 SLE patients and 90 healthy controls (HC), along with transcriptomic data from 1461 SLE patients. Through systematic analysis of key enzyme phosphorylation sites, upstream transcription factors (TFs), and computationally prioritized candidate compounds, we sought to characterize enzyme-centered regulatory associations. RESULTS: Integrated proteomic and phosphoproteomic analyses revealed significant metabolic and signaling pathway disturbances, along with distinct phosphorylation patterns in SLE immune cells. Multiple SLE-associated and disease-activity-associated candidate molecules were identified. Regulatory network analysis uncovered an upstream transcription factor cluster centered around STAT1. Computational drug screening identified computationally prioritized candidate compounds with multi-gene DSigDB associations, which require further clinical safety evaluation and experimental validation. CONCLUSIONS: This study constructs a molecular map of SLE, highlighting associations between enzyme-network alterations, catalytic dysregulation, and SLE-related immune molecular signatures, and identifies candidate molecules for future clinical and functional evaluation.

Humans↗

The identification of human tumour antigens: Current status and future developments.

The biggest challenge facing us today in cancer control and prevention is the identification of novel biomarkers for detection and improved therapeutic interventions to reduce mortality and morbidity rates. Biomarkers are important indicators to inform us of the physiological state of the cell at a specific time. It is now clear that malignant transformation occurs by changes in cellular DNA and protein expression with subsequent clonal proliferation of the altered cells. The affected genes and their expressed protein products or biomarkers are those involved in the normal growth and maintenance of the cancerous cells. These biomarkers could prove pivotal for the identification of early cancer and people at risk of developing cancer. Altered proteins or changes in gene expression in malignant cells may lead to the expression of tumour antigens recognised by host immune system. In this review we discuss current research into the molecular technologies making possible the global genomic-wide analysis of changes in DNA (genotyping), RNA expression (transcriptomics) and protein expression (proteomics) that have accelerated the rate of new biomarker/tumour antigen discovery. To gain a comprehensive understanding of the physiology and pathophysiology of cancer an approach that harmoniously integrates the various 'omic' platforms are key to unraveling the complexity 'needle-in-a-haystack' quality of biomarker/tumour antigen discovery.

Antigens, Neoplasm↗

Whole-transcriptome RNA sequencing and ceRNA network analyses provide novel insights into the antibacterial immune response of Hippocampus abdominalis against Vibrio harveyi.

Long non-coding RNAs (lncRNAs) stand as newly-arisen molecular types that exert regulatory effects, able to operate as competitive endogenous RNAs (ceRNAs) to engage microRNAs (miRNAs) in interaction, resulting in the recovery of target mRNA expression and activity. Increasing evidences indicate that the ceRNA network affects various biological processes in mammals, including development, cellular differentiation, metabolism, immune response, and disease pathogenesis. In teleost fish, the lncRNA-miRNA-mRNA regulatory networks have been reported occasionally. However, up to now, the roles of lncRNAs in the big-belly seahorse (Hippocampus abdominalis) remains unclear. In this study, we reported for the first time, via whole-transcriptome RNA sequencing, the lncRNA mediated ceRNA regulatory network in Vibrio harveyi-infected H. abdominalis. A total of 4197 differentially expressed mRNAs (DE-mRNAs), 1317 DE-lncRNAs, and 183 DE-miRNAs were identified. Furthermore, the crosstalk between miRNAs and lncRNAs as well as between miRNAs and mRNAs was inferred based on the negative correlations between miRNAs and their target lncRNAs/mRNAs. A core immune associated lncRNA-miRNA-mRNA putative regulatory network was thus constructed, comprising 211 lncRNA-miRNA and 224 mRNA-miRNA pairs. In conclusion, our findings provide an integrative overview of the ceRNA regulatory networks on the underlying immune responses to V. harveyi infection in the big-belly seahorse, and offer a solid theoretical foundation for the comparative immunological research of teleost fish.

Animals↗

Region-Resolved Integrative Multi-Omic Characterization Reveals Diverse Tumor and Microenvironment Features of Pituitary Neuroendocrine Tumors.

Pituitary neuroendocrine tumors are frequently invasive, with cavernous sinus invasion leading to poor treatment outcomes and high recurrence. Regional differences within these tumors remain poorly understood, hindering targeted therapy development. Here, we present the first integrative multi-omics analysis combining proteomics, metabolomics and single-cell transcriptomics to characterize tumors from the cavernous sinus and saddle regions. Our results reveal profound regional and cellular heterogeneity: cavernous sinus tumors exhibit significantly enhanced cell proliferation, driven by cancer-associated fibroblasts through the IGF1-IGF1R-MAPK1 axis. Cancer-associated fibroblasts in the cavernous sinus secrete IGF1 under regulation of the transcription factor FOXO1, which binds to receptors on tumor cells to activate proliferation. Metabolomic profiling identifies proline as a key enriched metabolite that stimulates cancer-associated fibroblasts to produce collagen fibers, reinforcing a pro-tumorigenic microenvironment. Single-cell transcriptomics further delineates a distinct subpopulation of receptor-positive malignant cells and a high abundance of cancer-associated fibroblasts in the cavernous sinus. These findings establish core mechanisms underlying the aggressive behavior of cavernous sinus-invading tumors, providing novel actionable targets for precision therapeutic strategies tailored to distinct tumor regions.

Humans↗

Functional genomics: lessons from yeast.

Functional genomics represents a systematic approach to elucidating the function of the novel genes revealed by complete genome sequences. Such an approach should adopt a hierarchical strategy since this will both limit the number of experiments to be performed and permit a closer and closer approximation to the function of any individual gene to be achieved. Moreover, hierarchical analyses have, in their early stages, tremendous integrative power and functional genomics aims at a comprehensive and integrative view of the workings of living cells. The first draft of the human genome sequence has just been produced, and the complete genome sequences of a number of eukaryotic human pathogens (including the parasitic protozoa Plasmodium, Leishmania, and Trypanosoma) will soon be available. However, the most rapid progress in the elucidation of gene function will initially be made using model organisms. Yeast is an excellent eukaryotic model and at least 40% of single-gene determinants of human heritable diseases find homologues in yeast. We have adopted a systematic approach to the functional analysis of the Saccharomyces cerevisiae genome. A number of the approaches for the functional analysis of novel yeast genes are discussed. The different approaches are grouped into four domains: genome, transcriptome, proteome, and metabolome. The utility of genetic, biochemical, and physico-chemical methods for the analysis of these domains is discussed, and the importance of framing precise biological questions, when using these comprehensive analytical methods, is emphasized. Finally, the prospects for elucidating the function of protozoan genes by using the methods pioneered with yeast, and even exploiting Saccharomyces itself, as a surrogate, are explored.

Fungal Proteins↗

Maximizing the efficacy of SAGE analysis identifies novel transcripts in Arabidopsis.

The efficacy of using Serial Analysis of Gene Expression (SAGE) to analyze the transcriptome of the model dicotyledonous plant Arabidopsis was assessed. We describe an iterative tag-to-gene matching process that exploits the availability of the whole genome sequence of Arabidopsis. The expression patterns of 98% of the annotated Arabidopsis genes could theoretically be evaluated through SAGE and using an iterative matching process 79% could be identified by a tag found at a unique site in the genome. A total of 145,170 reliable experimental tags from two Arabidopsis leaf tissue SAGE libraries were analyzed, of which 29,632 were distinct. The majority (93%) of the 12,988 experimental tags observed greater than once could be matched within the Arabidopsis genome. However, only 78% were matched to a single locus within the genome, reflecting the complexities associated with working in a highly duplicated genome. In addition to a comprehensive assessment of gene expression in Arabidopsis leaf tissue, we describe evidence of transcription from pseudo-genes as well as evidence of alternative mRNA processing and anti-sense transcription. This collection of experimental SAGE tags could be exploited to assist in the on-going annotation of the Arabidopsis genome.

Antisense Elements (Genetics)↗

Proteomic snapshot of pattern triggered immunity in the Arabidopsis leaf apoplast.

The apoplast is a critical interface in plant-pathogen interactions, particularly in the context of pattern-triggered immunity (PTI), which is initiated by recognition of microbe-associated molecular patterns. Our study characterizes the proteomic profile of the Arabidopsis apoplast during PTI induced by flg22, a 22-amino-acid bacterial flagellin epitope, to elucidate the output of PTI. Apoplastic washing fluid was extracted with minimal cytoplasmic contamination for liquid chromatography-tandem mass spectrometry analysis. By comparing our data to publicly available transcriptome profiles of flg22 treatment from 1 to 18&#x2009;h, we observed that several highly abundant proteins exhibit relatively unchanged gene expression across all time points. We also observed topological bias in peptide recovery of 19 enriched receptor-like kinases with peptides predominantly recovered from their ectodomains. Notably, tetraspanin 8, an exosome marker, was enriched in PTI samples. We additionally confirmed increased concentrations of exosomes during PTI. This study enhances our understanding of the proteomic changes in the apoplast during plant immune responses and lays the groundwork for future investigations into the molecular mechanisms of plant defense under recognition of pathogen molecular patterns.

Arabidopsis↗

Genomic subtypes of non-muscle-invasive bladder cancer: guiding immunotherapy decision-making for patients exposed to aristolochic acid.

BACKGROUND: The limited genomic data on non-muscle-invasive bladder cancer (NMIBC) hampers our understanding of its carcinogenesis and development. Specifically, Aristolochic acid (AA), a potent human carcinogenic compound from aristolochia plants and commonly found in Chinese herbal medicine, has been extensively documented as being closely associated with the onset and progression of bladder cancer. However, the field of AA-induced NMIBC remains largely unexplored in terms of its genomic and molecular characteristics, as well as clinical therapeutic strategies. METHODS: To bridge this knowledge gap, we conducted a comprehensive study using a cohort of 81 NMIBC samples. We performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) to obtain detailed genomic and transcriptomic data. We subjected these datasets to genomic analysis and subtype analysis to gain valuable insights into NMIBC. RESULTS: By temporally dissecting mutations in NMIBC specimens, we identified a comprehensive mutational landscape of NMIBC and the associations of these mutations with recurrence-free survival. Additionally, we discerned four genomic subtypes of NMIBC: AA-like, FGFR3/HRAS, FGFR3 & chr9Del, and genome instability (GI). The AA-like subtype presented a high frequency of gene mutations along with a pronounced AA mutagenesis signature of SBS22 (Fisher test: P-value 3.5e-4, OR 25.25) even after temporal dissection. The FGFR3/HRAS subtype exhibited FGFR3 or HRAS mutations with few copy number alterations (CNAs). The FGFR3 & chr9Del subtype was characterized by the co-occurrence of chr9p and chr9q deletions as well as FGFR3 mutations, while the GI subtype showed a high frequency of CNAs. Notably, the AA-like and GI subtypes demonstrated better outcomes after immunotherapy, whereas the FGFR3/HRAS subtype showed poorer outcomes. CONCLUSIONS: Our findings provide novel perspectives on the genomics of NMIBC, unveiling four prominent genomic subtypes, each showing different outcomes following immunotherapy. TRIAL REGISTRATION: No. 2019PHB268-01 (retrospectively registered on February 14, 2020).

Humans↗