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SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection.

SUMMARY: SISTEM is a software package and mathematical framework for simulating tumor evolution and cell migrations at single-cell resolution. Unlike existing frameworks which simulate cancer cell populations under the neutral coalescent or using simple birth-death models, SISTEM simulates tumor populations under somatic clonal selection using an agent-based framework. SISTEM can generate mutation profiles, read counts, and DNA sequencing reads along with ground truth cell lineages and migration graphs under a number of easily customizable mutation and selection models. For improved realism, SISTEM allows for cell fitness to be driven by genomic events of various scales including single nucleotide variants, segmental gains and losses, whole-chromosomal and chromosome-arm aberrations, and whole-genome duplications. SISTEM also includes numerous migration models to simulate metastatic cancers, facilitating the exploration and evaluation of diverse migration patterns. AVAILABILITY AND IMPLEMENTATION: SISTEM is written in Python and is freely available open-source under GNU GPLv3 from: https://github.com/samsonweiner/sistem.

Software↗

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on characterizing oocytes and ovarian tissue composition, as well as understanding the molecular mechanisms that guide ovarian function throughout its lifecycle. High-throughput omics technologies have enabled the characterization of different molecular layers, leading to substantial advances in our understanding of their complex dynamics. However, not all molecular aspects are studied equally, and studies examining the same modalities often show inconsistencies, underscoring the need for data standardization and highlighting the potential for using transformative artificial intelligence and machine-learning (AI/ML) methods for ovary studies. OBJECTIVE AND RATIONALE: This study aims to evaluate how multi-omic studies have advanced our understanding of the ovarian lifecycle from fetal development to postmenopause. We systematically reviewed published studies that have investigated molecular/omic layers, including the genome, methylome, transcriptome, and proteome throughout ovarian development and aging. Our analysis identified key molecular and cellular patterns, highlighted inconsistencies across studies and addressed gaps in data analysis, interpretation, and reproducibility to guide future research. SEARCH METHODS: We conducted a systematic literature search of Medline (PubMed), Embase (Ovid), and Web of Science Core Collection (Clarivate) using a combination of controlled and free text terms for human ovary, oogenesis, folliculogenesis, ovary development and (epi)genome, transcriptome, proteome, and multi-omic mechanisms to find relevant articles published before August 2025. To focus the scope of the current review, studies of domesticated and farm animals, rodents and other model organisms, non-human primates, as well as those examining various human ovarian pathologies were excluded. OUTCOMES: The search identified 23 546 studies for screening, of which 637 full-text studies were assessed for eligibility. Subsequently, we extracted data from 121 studies. Most studies analyzed the transcriptome of oocytes, granulosa cells, and ovarian tissue from reproductive-age individuals (n = 91), with fewer studies examining samples from individuals of advanced reproductive age (n = 45) and fetal (n = 16) samples. Transcriptome analyses were most common (n = 103, 85%), followed by proteome (n = 19, 16%) and epigenome (n = 14, 12%) studies. We found substantial variation in how studies defined and reported participants' groups as well as in their sequencing technologies and data analysis methods, with a lack of standardized reporting of background clinical information, data analysis methods, and pipeline details. The key findings underscore the prevailing consensus on genes defining major ovarian cell types and their roles throughout the ovarian lifespan, from prenatal development to postmenopausal transformation. This review highlighted the underrepresentation of certain patient groups, particularly prepubertal and peri-/postmenopausal individuals, among researched populations, due to obvious clinical and ethical reasons. WIDER IMPLICATIONS: This scoping review offers a comprehensive overview and benchmark of the current state of high-throughput omics-based research on ovarian cellular composition and molecular dynamics. To address these shortcomings, we propose general recommendations for multi-omics ovary studies and emphasize the necessity for more thorough multi-omic data integration by effectively applying novel AI/ML approaches. They can potentially improve the quality of multi-omics analyses at both single-cell and tissue levels despite limited sample sizes and enable integration of molecular profiling data with clinical and radiology datasets, enabling a more comprehensive understanding of ovarian biology. Such advancements can enhance reproducibility of research findings and guide future research to deepen our understanding of ovarian biology and ultimately support the development of medical technologies for better preserving fertility and alleviating infertility. REGISTRATION NUMBER: A protocol was published a priori on the Open Science Framework (https://osf.io/z38gb/).

Female↗

Genetic architecture of endometriosis: risk factors, comorbidities and clinical implications.

BACKGROUND: In 1999, Dr Susan Treloar and colleagues conducted a landmark twin study in Australia and reported their estimate of 51% for the heritability of endometriosis. This important result led several groups to begin mapping genetic factors contributing to increased endometriosis risk. Despite early challenges, advances in genome-wide association studies (GWAS) have identified multiple genetic risk factors and some target genes implicated in follow-up studies on genetic regulation of transcription. Access to large publicly available genetic datasets and analysis with endometriosis GWAS results is also providing new opportunities to answer important questions about comorbid conditions associated with endometriosis and their implications for clinical practice. OBJECTIVE AND RATIONALE: The objective of the review is to summarize the last 25 years of genetic studies in endometriosis, outline contributions to our understanding of the disease, and suggest future directions to accelerate biological insights from genetic studies to improve clinical outcomes. SEARCH METHODS: A comprehensive review of scientific literature on the genetics of endometriosis was conducted through searches in PubMed and Google Scholar up to June 2026. Search terms included "endometriosis AND (genetics OR GWAS OR genetic risk factors)", For studies addressing the functional characterization of genetic risk loci, additional searches employed the terms "endometriosis AND (genotype-phenotype associations OR colocalization OR eQTL OR mQTL OR multi omics methods)". To identify studies examining shared genetic risk between endometriosis and comorbid conditions, the search strategy included "endometriosis AND (genetic correlation OR colocalization OR Mendelian randomisation)". Publications reporting discoveries related to genetic risk factors for endometriosis and studies interpreting their biological and clinical significance were critically evaluated, and 144 publications were discussed in the review. OUTCOMES: Discovery of genetic risk factors started slowly and has accelerated in recent years with developments in technology and international collaborations to combine data and increase statistical power. GWAS have mapped 80 genetic risk factors that implicate gene regulation of hormonal targets, development of the reproductive tract, regulation of cell proliferation, and regulation of epithelial cell differentiation. In common with most other complex diseases, effects of individual common genetic risk factors are small. However, several examples demonstrate that small effect sizes are not a good predictor for the impact of drugs developed against genetically validated targets. Genetic risk factors implicate five genes regulating gonadotrophin release and oestrogen action, the major target pathway of current drugs for treatment of endometriosis demonstrating proof-of-principal for biologically meaningful results. Genetic correlation and Mendelian Randomization studies highlight important causal relationships between endometriosis and comorbid conditions including a possible role for testosterone during development and shared genetic risk factors for gynaecological, gastrointestinal, pain, psychiatric, and inflammatory conditions. Understanding causal relationships between endometriosis and related conditions will aid clinical management and more personalized treatments. WIDER IMPLICATIONS: Genetic studies provide novel insights into endometriosis pathogenesis and associations with related comorbid conditions. Genetic factors modifying gene regulation and disease risk likely act in specific cell types, and access to datasets from genetically informed cell-based models, single-cell and spatial omics data are needed to accelerate progress. Future studies should address critical questions of heterogeneity and disease subtypes, expand the search for genetic risk factors to non-European populations, evaluate the role of rare and structural variants, and better integrate data from functional, genomics, genetics, and clinical studies to reduce diagnostic delay, develop novel treatment strategies, and translate discoveries into personalized management strategies for affected individuals. REGISTRATION NUMBER: N/A.

comorbid conditions↗

Single-nucleus profiling of postmortem diffuse midline gliomas identifies mitochondrial biogenesis as a resistance mechanism to imipridone therapy.

BACKGROUND: Imipridone ONC201 is the first FDA-approved therapy for H3K27-altered diffuse midline glioma; however, clinical responses remain limited. Defining tumor-intrinsic determinants and microenvironmental, extrinsic factors that shape sensitivity or resistance to imipridones will identify actionable therapeutic opportunities and inform improved clinical strategies. METHODS: To identify mechanisms of imipridone resistance, we obtained postmortem brain tissue from DMG patients who had received imipridones and/or standard care. Single-nucleus RNA and open-chromatin sequencing were performed on N = 22 cases. Immunofluorescence-based myeloid phenotyping was performed on N = 46 cases. Mitochondrial copy-number analysis was performed on N = 19 cases. Validation of imipridone sensitivity, its effect on mitochondrial density, and its synergy with inhibition of mitochondrial biogenesis were assessed in DMG primary cells. RESULTS: We established a single-cell RNA/open-chromatin atlas from postmortem DMG cases and found imipridone treatment resulting in regressed mesenchymal transition, reduced myeloid-derived suppressive cells, and reversed aberrant H3K27-altered enhancer activity. Resistant tumors showed increased mitochondrial density, turnover, and membrane potential. Mitochondrial biogenesis and PPARGC1A emerged as resistance biomarkers and actionable targets. CONCLUSIONS: These studies implicate mitochondrial biogenesis as a biomarker of imipridone resistance and a focus for the development of combinatorial strategies to provide effective therapeutic options for a challenging pediatric brain tumor.

Humans↗

Unlocking the Full Potential of Spatial Omics in Plants: Practical Challenges, Solutions, and a Path Forward.

Spatial omics technologies are providing new opportunities for plant biology by enabling molecular profiling within structurally intact tissues, revealing spatially organised cell states, developmental gradients, and regulatory interactions. While spatial transcriptomics has driven early advances, the field is rapidly expanding toward integrated spatial multi-omics by combining single-cell and spatial transcriptomic, epigenomic, proteomic, and metabolomic data. These approaches offer new opportunities to study development, physiology, and plant biotic and abiotic interactions in spatially preserved cellular contexts. However, despite rapid adoption, the field remains constrained by plant-specific challenges when applying technologies largely developed for animal systems. Compared with animal systems, plant tissues pose additional challenges due to rigid cell walls, and diverse chemistries, complicating sample preparation, cell and subcellular segmentation, signal detection, and data integration. As a result, many studies rely on bespoke protocols and analysis pipelines that are often difficult to reproduce or generalise. Here, we provide a practical, solution-oriented synthesis of current bottlenecks across experimental and computational pipelines, highlight emerging strategies to overcome these limitations, and propose a roadmap for community-driven protocol sharing, benchmarking, and integration across spatial and multi-omics modalities. Addressing these challenges will be essential to establish spatial omics as a routine and scalable tool for plant biology.

Journal Article↗

Recurrent patterns of widespread neuronal genomic damage shared by major neurodegenerative disorders.

Amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer's disease (AD) are common neurodegenerative disorders for which the mechanisms driving neuronal death remain unclear. Single-cell whole-genome sequencing of 429 neurons from three C9ORF72 ALS, six C9ORF72 FTD, seven AD, and twenty-three neurotypical control brains revealed significantly increased burdens in somatic single nucleotide variant (sSNV) and insertion/deletion (sIndel) in all three disease conditions. Mutational signature analysis identified a disease-associated sSNV signature suggestive of oxidative damage and an sIndel process, affecting 28% of ALS, 79% of FTD, and 65% of AD neurons but only 5% of control neurons (diseased vs. control: OR=31.20, p = 2.35×10-10). Disease-associated sIndels were primarily two-basepair deletions resembling signature ID4, which was previously linked to topoisomerase 1 (TOP1)-mediated mutagenesis. Duplex sequencing confirmed the presence of sIndels and identified similar single-strand events as potential precursor lesions. TOP1-associated sIndel mutagenesis and resulting genome instability may thus represent a common mechanism of neurodegeneration.

Journal Article↗

Spatial Transcriptomics Identifies Characteristic Immunological Niches in Atopic Dermatitis.

BACKGROUND: Atopic dermatitis (AD) is primarily driven by a Type 2 immune response, with T helper (TH2) cells producing IL-4 and IL-13, thereby promoting inflammation, itch, and a compromised skin barrier. Yet, the spatial organization of pathogenic immune cells and their interactions with stromal and epithelial compartments in human AD skin remain incompletely understood. METHODS: We performed 10× Genomics Visium spatial transcriptomics on FFPE skin biopsies from patients with AD (n = 6), psoriasis (n = 2), and healthy controls (n = 5). Data were integrated with AD single-cell RNA sequencing (scRNA-seq) datasets and complemented by imaging mass cytometry (IMC) and multiplex immunofluorescence (IF) to validate the spatial localization of immune cells. Cell-cell communication analysis revealed putative signaling interactions within immune niches. RESULTS: Spatial clustering resolved tissue compartments and demonstrated transcriptional dysregulation in keratinocytes in AD and psoriasis. AD lesions showed a conserved spatial organization of immune aggregates within the superficial dermis. Integration of scRNA-seq signatures revealed spatially organized co-localization of T cells and mature migratory dendritic cells (mmDCs). We developed a ring-based neighborhood analysis to characterize the cellular organization of the immune-stromal niches, revealing T cell-enriched regions surrounded by inflammatory fibroblasts and activated keratinocytes. Intercellular communication analysis further identified putative signaling within mmDC-T cell niches that may promote pathogenic T cell recruitment and activation. Application of tertiary lymphoid structure (TLS) signatures indicated the presence of TLS-like regions. IMC and IF validated the close spatial proximity between activated TH2 cells and mmDCs. CONCLUSION: AD lesions contain spatially organized TLS-like immune niches at the dermal-epidermal junction, characterized by the close association of T cells and mmDCs and coordinated interactions with surrounding stromal and epithelial compartments. These mmDC-T cell niches may represent potential targets for future therapeutic strategies aimed at disrupting persistent local inflammatory pathways and improving long-term disease control.

atopic dermatitis↗

HIF1A+CSF3R+ neutrophils-dominated hypoxic niche induced metabolic reprogramming for neoadjuvant therapy resistance in NSCLC.

BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the frequently occurring cancers characterized by molecular heterogeneity and multiple immune cell infiltration patterns, which are associated with treatment sensitivity and resistance. However, the specific microenvironmental cells and their mechanisms that lead to treatment resistance in patients need to be explored in greater depth. METHODS: On the basis of patients receiving neoadjuvant therapy in our center, a multicenter, multicohort NSCLC spatial transcriptome, single-cell transcriptome, T-cell receptor repertoire sequencing, bulk RNA transcriptome, phosphorylated proteome, genome mutation, and clinical data were included for a comprehensive assessment of the therapeutic and prognostic impact of HIF1A+ CSF3R+ neutrophils in NSCLC. In vitro experiments validated the functional phenotype of HIF1A+ CSF3R+ neutrophils and co-localization interactions with other cellular subpopulations. Gradient boosting machine (GBM) constructed region of interest (ROI) models for evaluation. Computer-aided drug design (CADD) was used to predict targeted small molecule drugs, and in vivo mouse models were constructed to assess the effectiveness of the combination treatment regimen. RESULTS: Centered on HIF1A+ CSF3R+ neutrophils, recruited exhausted T cells and stromal cells form a hypoxic niche within the tumor region, which was enriched in non-response patients. ROI composed of these specific cellular subpopulations, associated with senescence and glycolysis, accurately predicting NSCLC progression, prognosis, and microenvironment composition. CADD analysis identified that platycodin-D2 specifically targeted CSF3R, reducing HIF1A expression and inhibiting neutrophil activity. Combining navitoclax, platycodin-D2 with anti-programmed cell death protein 1 (PD-1) significantly suppressed tumor proliferation and improved the immunosuppressive microenvironment. CONCLUSION: Our study emphasized the role of HIF1A+ CSF3R+ neutrophils in immunotherapeutic resistance of NSCLC, constructed a microenvironmental immune dysregulation network in a hypoxic ecological niche with HIF1A+ CSF3R+ neutrophils as the center. Platycodin-D2 specifically targeted HIF1A+ CSF3R+ neutrophils, enhancing the efficacy of anti-PD-1 therapy in NSCLC.

Humans↗

Human Variation-Informed Prioritization of MPHOSPH6 in Lung Adenocarcinoma: A Source-Aware Multiomics Evidence Framework.

Moving from an association signal to a clinically credible biomarker requires several links that are often conflated: verified variant identity, aligned allelic effects, reproducible gene-level association, relevant cellular expression, and a plausible functional consequence. We developed a source-aware multiomics framework to assess MPHOSPH6 in lung adenocarcinoma (LUAD) while keeping those evidence classes separate. Six prespecified rsIDs were recovered from the harmonized TRICL LUAD dataset, of which five reached p < 5 &#xd7; 10 - 8. Only rs112333466 and rs76474922 were available with alignable alleles in FinnGen R10, and both showed concordant directions. Fixed-effect estimates were OR = 1.592 for rs112333466-T (95% CI, 1.401-1.809; p = 9.91 &#xd7; 10 - 13) and OR = 0.819 for rs76474922-C (95% CI, 0.773-0.867; p = 1.03 &#xd7; 10 - 11). In a prespecified two-variant GTEx v8 lung model, genetically predicted MPHOSPH6 expression was positively associated with LUAD in TRICL (Z = 3.341, p = 8.35 &#xd7; 10 - 4) and FinnGen (Z = 2.697, p = 0.0070). This gene-level result did not establish colocalization or connect MPHOSPH6 to the six susceptibility rsIDs. Patient-level analysis of 89,241 immune cells from six paired tumor and normal-adjacent lung samples found no significant difference in MPHOSPH6 pseudobulk abundance (exact paired Wilcoxon p = 0.3125). None of 688 lung-lineage pharmacogenomic tests remained significant after false-discovery-rate correction. Ten recorded MPHOSPH6 missense alleles, including five ClinVar variants of uncertain significance, were curated; structural analysis identified I58 at an experimental RNA-exosome interface and defined a focused perturbation series. MPHOSPH6 is therefore supported as a human-variation-informed candidate for functional evaluation, not as a validated LUAD biomarker, pathogenic gene, drug-response predictor, or therapeutic target.

Humans↗

The Novel Hypomethylating Agent NTX-301 Reprograms Epigenetic and Hippo Signaling Pathways and Exhibits Preclinical Activity in Venetoclax-Resistant and TP53-Mutant AML.

PURPOSE: Hypomethylating agent (HMA) and the BCL-2 inhibitor venetoclax (VEN) combinations have evolved into first-line therapies for patients with acute myeloid leukemia (AML), yielding high response rates. However, most patients ultimately relapse, particularly those with TP53 mutations. We investigated mechanisms of action and therapeutic efficacy of NTX-301, a next-generation HMA. EXPERIMENTAL DESIGN: Methods used include flow cytometry-based cell viability assays, Western blotting, reverse-phase protein arrays, RNA sequencing, Cytometry by Time-Of-Flight single-cell mass cytometry, and methylation profiling in various therapy-resistant AML models. RESULTS: We demonstrate that NTX-301 exhibits superior efficacy compared with 5-azacytidine (5-AZA) in 5-AZA- or VEN-resistant AML. It synergizes with VEN in VEN- or VEN/HMA-resistant and TP53-mutant AML blasts and stem/progenitor cells (combination index <1). NTX-301 inhibits DNA methyltransferase 1 (DNMT1) and increases p73 and caspase 8 (CASP8)/activated CASP8 levels in TP53 wild-type and TP53-mutant AML and activates p53 signaling. It extends survival (&#x2265;45%) in both xenograft and patient-derived xenograft models. Methylation profiling revealed that NTX-301 is a more targeted HMA compared with 5-AZA, enabling suppression of functionally enriched genes/pathways. Pathway analysis of 954 commonly hypomethylated genes showed profoundly greater enrichment of Hippo signaling in NTX-301-treated compared with 5-AZA-treated cells and enrichment of insulin signaling, VEGF pathway, and cell cycle selectively in NTX-301- but not in 5-AZA-treated cells. NTX-301-mediated Hippo signaling was validated at protein levels. CONCLUSIONS: Data suggest that NTX-301 exerts potent antileukemic activities superior to 5-AZA and synergizes with VEN in VEN-resistant and TP53-mutant AML, in part by suppressing DNMT1, inducing DNA damage responses and apoptosis through p53 signaling, and demethylating LATS1/2, thereby activating Hippo signaling.

Humans↗

Tumor microbial burden drives immune responses through regulation of Interferon signaling.

Tumor microbes are increasingly recognized for modulating tumor behavior and therapy responses. Intratumoral microbial burden (ITMB) analysis across cancers revealed regulation of immune pathways, and activated mast cells, mostly in colorectal (CRC) and gastric (STAD) cancers. High ITMB CRC leads to interferon regulation and is associated with improved outcomes in advanced disease. Single-cell sequencing revealed induction of interferon-related genes (IRGs) within microbes-containing human CRC. GI-luminal mismatch repair deficiency (MMRd) tumors had higher ITMB than proficient tumors (MMRp). In a rectal MMRd cohort with 100% remission after immune checkpoint blockade (ICB), tumor microbes and microbes-containing mast cells increased. In ICB-sensitive syngeneic murine MMRd tumor models, local tumor microbial depletion, impaired ICB efficacy while downregulating IFN signaling. Forced upregulation of IRGs in ADAR1-deficient cancer cells restored immunotherapy responses during microbial ablation. These data highlight dynamic interplay between ITMB, host defense, and immunogenicity which seems key to determine therapy responses.

Journal Article↗

Multiomic analysis identifies T cell subsets and mechanisms of epithelial interaction in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease characterized by progressive scarring and respiratory failure. While T cells are elevated in IPF lungs, their contributions to fibrosis beyond inflammation remain poorly understood. Here, we performed multiplex imaging and single-cell RNA and protein profiling on about 90,000 CD3+ T cells from control and fibrotic lungs, revealing 11 distinct subsets of CD4+ and CD8+ T cells, including a rare CD56+ regulatory T cell. In addition to increased T cell numbers in severely fibrotic lungs compared with non-diseased controls, we observed CD4+ and CD8+ T cells localized near epithelial cells and in niches of abnormal epithelium. CXCR4/MIF signaling emerged as a central axis mediating T cell-epithelial interactions, while epidermal growth factor receptor (EGFR) and TGF-&#x3b2; pathways dominated in multiple T cell subsets. Our findings support the concept that T cells in IPF adopt nonclassical activation patterns that are driven by epithelial interactions within the fibrotic microenvironment. These studies provide a foundation for exploring alternative therapeutic strategies in IPF lungs by modulating T cell behavior and communication networks.

Idiopathic Pulmonary Fibrosis↗

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type, and sex specificity of gene expression with novel genetic risk for MERTK in female.

BackgroundAlzheimer's disease (AD), the most common age-related neurodegenerative disease, is closely associated with both amyloid-&#x3b2; plaque and neuroinflammation. Two thirds of AD patients are female, and they have a higher disease risk; women with AD have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration.ObjectiveThis study aimed to determine how sex difference induces structural brain changes and molecular cell vulnerabilities in AD, with a focus on identifying sex-specific transcriptional alterations and genetic risk factors.MethodsWe performed single nucleus RNA sequencing on postmortem brains from individuals with AD and age- and sex-matched controls, focusing on the middle temporal gyrus, a cortical brain region strongly affected by the disease, and integrated single nucleus RNA sequencing results with genome-wide association study (GWAS) data using cell type-specific enrichment and generalized gene-set analysis approaches. The analysis pipeline is provided with threshold information.ResultsWe identified a selectively vulnerable subpopulation of layer 2/3 excitatory neurons that were RORB-negative and CDH9-expressing in both males and females. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of AD brains differed between males and females. Integrating single cell transcriptomic data with results from GWAS, we identified MERTK genetic variation as a candidate novel risk factor for AD selectively in females.ConclusionsTaken together, our single cell atlas of middle temporal gyrus revealed a unique cellular-level view of sex-specific transcriptional changes in AD, illuminating GWAS identification of sex-specific AD genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of AD.

Alzheimer's disease↗

Putative function and prognostic molecular marker of mast cells in colorectal cancer.

BACKGROUND: The increased demand for markers for colorectal cancer (CRC) highlights the importance of investigating immune cells involved in CRC progression. This study aims to dissect the mast cells in CRC, characterize the role of mast cells in CRC development, coordinate molecular communication between mast cells and malignant cells, and construct and validate a prognostic classification model based on mast cell markers. METHODS: Single-cell transcriptome data of CRC patients were extracted from GSE146771 for cell classification and annotation. The malignant cells were identified by copykat and the communication between mast cells and malignant cells was analyzed by CellChat. Least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis of mast cell markers were performed in the TCGA-COAD cohort to construct a prognostic classification model. qRT-PCR was performed to detect the mRNA expression of the molecules in the classification model in P815 and MC-9 cells. The co-culture experiment of MC38 and P815 cells&#xa0;were performed in 12-well transwell dish. Wound healing assay and Transwell assay were performed to detect cell migration and invasion. RESULTS: 10,186 high-quality cells in GSE146771 were annotated to 9&#xa0;cell types. Six markers in mast cells (HDC, GATA2, ASAH1, BTBD19, TIMP1, FAM110A) were selected to construct a classification model. The high-risk score defined showed high infiltration of immunosuppressive cells, including endothelial cells, CAFs, Tregs and high angiogenesis and epithelial-mesenchymal transition (EMT) activities. In the model, HDC were abnormally low expressed in P815 cells, while BTBD19, FAM110A, GATA2, ASAH1 and TIMP1 showed excessive expression in P815 cells. Knockdown of GATA2 in the co-culture system of P815 and MC38 cells&#xa0;blocked cell migration and invasion. CONCLUSION: This study identified the cell types within CRC, elaborated the cellular functions of mast cells in CRC development and their molecular communication to coordinate malignant cells, and highlighted the molecular components and biological features that constitute promising prognostic classification model.

Mast Cells↗

Analysis and validation of abnormal signaling pathways and immune cell infiltration characteristics in digestive system cancers based on peroxisome-related genes.

BACKGROUND: Although emerging evidence suggests a role for peroxisomes in tumorigenesis, their functions in digestive cancers remain unclear. This study aims to investigate the association between peroxisomes and digestive tract tumors. METHODS: To systematically investigate peroxisomal functions in digestive cancers, we first constructed and validated tumor-specific prognostic signatures based on peroxisome-related genes (PRGs) through univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. We then characterized the tumor immune microenvironment (TIME) with CIBERSORT, X-CELL, and EPIC algorithms, and identified tumor-specific and common signalings via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Focusing on hepatocellular carcinoma (HCC), we experimentally validated peroxisome-related therapeutic responses by profiling signature genes in radioresistant cells and an orthotopic transarterial chemoembolization (TACE) rat model. PEX13 knockdown further assessed peroxisomal role in radiosensitivity and targeted therapy response. Clinical relevance of PEX13 was evaluated in HCC cohort. Single-cell RNA sequencing dataset and lipidomics further revealed peroxisomal mechanisms in HCC progression. Finally, peroxisomal function in colorectal cancer (CRC) was validated in vitro. RESULTS: Novel peroxisome-related prognostic signatures demonstrated strong predictive power in HCC, colon adenocarcinoma, rectal adenocarcinoma, pancreatic adenocarcinoma, gastric adenocarcinoma, esophageal adenocarcinoma, esophageal squamous cell carcinoma, and cholangiocarcinoma. High-risk patients displayed an immunosuppressive microenvironment, characterized by increased infiltration of regulatory T cells, M2 macrophages, Th2 cells, or cancer-associated fibroblasts, or Th1 cells' reduction. Peroxisomes engaged in several distinct yet convergent pathways, most notably "positive regulation of response to stimuli". HCC prognostic genes were dynamically regulated in response to therapeutic stimuli, including radiotherapy, targeted therapy, and TACE. Clinically, the expression of PEX13 was markedly upregulated in tumor tissues from therapy-resistant HCC patients. Mechanistically, peroxisomal dysfunction induced by silencing PEX13 in HCC or UBE2D2 in CRC may overcome therapeutic resistance (radiotherapy/ lenvatinib resistance in HCC, radioresistance in CRC) through reprogramming lipid metabolism. CONCLUSIONS: Peroxisomes act as pivotal regulators of digestive cancer progression by modulating signaling pathways, the TIME, therapeutic resistance, and lipid metabolism. Targeting peroxisomal function, particularly in high-risk subgroups of HCC and CRC, warrants further exploration as a promising therapeutic strategy.

Peroxisomes↗

TFPI-high myofibroblast states and a meta-program-related five-gene prognostic signature in breast cancer.

Intratumoral heterogeneity and tumor-microenvironment interactions limit prognostic stratification in breast cancer, but the prognostic relevance and cellular context of recurrent transcriptional meta-programs remain unclear. We aimed to derive a meta-program-related prognostic signature and characterize its component transcripts at single-cell resolution. Six paired institutional tumors and adjacent non-tumor tissues served as a proof-of-concept comparison. Univariable Cox screening and least absolute shrinkage and selection operator Cox regression were used to derive a five-gene score from a prespecified meta-program-related candidate set in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) training cohort; the score was tested internally and assessed in GSE20685 using fixed coefficients and cohort-specific median cutoffs. GSE161529 single-cell transcriptomic data were used to map signature transcripts across 136,526 quality-controlled cells, while donor-aware pseudobulk analysis compared upper- and lower-quartile TFPI expression states in annotated myofibroblasts. The score comprised TCN1, FOXJ1, PIGR, SLAIN1, and TFPI and was associated with overall survival in the training, testing, and external cohorts, with concordance indices of 0.782, 0.756, and 0.721, respectively. TFPI transcripts were detected across endothelial, fibroblast, and myofibroblast compartments. TFPI-high myofibroblasts showed transcriptional enrichment of extracellular matrix and collagen fibril organization, transforming growth factor beta signaling, epithelial-mesenchymal transition, and myogenesis, together with lower oxidative phosphorylation and fatty acid metabolism programs. In bulk TCGA-BRCA tissue, TFPI expression correlated positively with stromal (r&#xa0;= 0.48), immune (r&#xa0;= 0.25), and composite microenvironment scores (r&#xa0;= 0.40; all p&#xa0;< 0.001). These findings identify a hypothesis-generating five-gene bulk-tissue prognostic signature and an expression-associated TFPI-high myofibroblast state but do not establish a discrete lineage, the cellular source of bulk TFPI, a TFPI-dependent mechanism, or clinical utility. Independent prospective cohorts, spatial and protein-level validation, and functional perturbation studies are required.

Journal Article↗

KLHL17 as a Prognostic Indicator and Therapeutic Target in Cervical Cancer: A Comprehensive Analysis.

INTRODUCTION: This study aims to clarify the role of kelch like family member 17 (KLHL17) in cervical cancer (CESC) is unclear. OBJECTIVE: To clarify this uncertainty, our research employed bioinformatics analysis coupled with experimental corroboration. METHODS: We utilized the Cancer Genome Atlas (TCGA) database to assess the expression of KLHL17 in various cancers, specifically CESC, and to explore its association with clinical characteristics, diagnostic utility, and prognostic significance in CESC. The current investigation delved into the potential regulatory pathways related to KLHL17, examining its connection with the infiltration of immune cells, the expression of immune checkpoint genes, the status of microsatellite instability (MSI), and the efficacy of diverse therapeutic agents in CESC. The research analyzed KLHL17 expression patterns using single-cell sequencing data from CESC samples and investigated the genetic variations of KLHL17 within this context. KLHL17 expression was validated using GSE145372. The presence and levels of KLHL17 in different cell lines were validated through quantitative real-time PCR (qRT-PCR) assays. RESULTS: KLHL17 exhibited irregular expression profiles across various cancer types, including CESC. Furthermore, increased KLHL17 levels in CESC patients were significantly associated with a lower progression-free survival (PFS) rate (hazard ratio: 1.62; 95% confidence interval: 1.01-2.60, p = 0.044). Moreover, KLHL17 expression emerged as a distinct prognostic indicator for CESC patients (p = 0.031). It has been associated with various biological pathways, such as cytokine-cytokine receptor interaction, primary immunodeficiency, cell adhesion molecules (CAMs), chemokine signaling pathway, steroid hormone biosynthesis, and others. The expression levels of KLHL17 were found to correlate with the presence of immune cells, the expression of immune checkpoint genes, and the status of MSI within CESC. Furthermore, KLHL17 expression exhibited a significant and inverse correlation with XMD15-27, rTRAIL, Paclitaxel, tp4ek, and tp4ek-k6. Furthermore, KLHL17 was found to be significantly positively regulated in CESC cell lines. DISCUSSION: The findings suggest that KLHL17 is involved in the progression of CESC and may serve as a potential prognostic marker and therapeutic target. KLHL17's association with immune cell infiltration and immune checkpoint genes indicates a role in immuneevasion. Future research should focus on validating these findings through independent datasets and experimental studies to elucidate the molecular mechanisms underlying KLHL17's role in CESC progression and immune regulation. CONCLUSION: KLHL17 is a promising prognostic marker and potential therapeutic target in CESC.

Humans↗

Pre-treatment T cell features and immune-milieu characteristics shape treatment-induced exhaustion and resistance to Blinatumomab in B-cell acute lymphoblastic leukemia.

BACKGROUND: Blinatumomab (Blina), a CD19&#xd7;CD3 bispecific T cell engager, is approved for the treatment of B-cell precursor acute lymphoblastic leukemia (BCP-ALL), yet resistance remains a major challenge and the mechanisms driving treatment failure remain poorly understood. METHODS: To define the immunological determinants of resistance, we performed longitudinal profiling of peripheral blood T cells and the immune milieu of 34 patients receiving Blina using flow cytometry (n=19), single-cell CITE-seq (n=13), ex vivo Blina-induced cytotoxicity (n=26) and serum proteomics (n=17). RESULTS: At baseline, Responders (R) were enriched for CD8+ effector memory T cells (TEM) expressing higher levels of cytotoxic genes and their transcriptional regulator ZNF683. Conversely, CD8+ TEM from Non-Responders (NR) displayed transcriptional features of activation without proportionate cytotoxic commitment. Over the course of the first treatment cycle, NR exhibited a progressive expansion of TIM3+CD8+ T cells that correlated with a rapid loss of ex vivo cytotoxic function. Linking baseline state to post-treatment T-cell exhaustion, the magnitude of TIM3+CD8+ expansion correlated inversely with baseline ZNF683 expression in CD8+TEM. Beyond T-cell-intrinsic features, NR harbored an immunosuppressive milieu characterized by higher circulating levels of M2-polarizing factors (CSF-1, HGF) and the TIM-3 ligand Galectin-9, which correlated positively with the magnitude of TIM3+CD8+ T-cell expansion. CONCLUSIONS: These findings indicate that post-Blina CD8+ T-cell exhaustion is associated with resistance and it is shaped by both reduced ZNF683-dependent cytotoxic programming in CD8+ TEM and an immunosuppressive milieu. This provides a rationale for risk stratification based on baseline transcriptional profiling of CD8+ TEM and for combinatorial strategies targeting the suppressive microenvironment.

Humans↗