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PubMed2026

Pan-cancer analysis identifies KANSL2 as a cell-cycle-associated regulator of tumor progression and immunity in liver hepatocellular carcinoma.

KANSL2, a core component of the NSL histone acetyltransferase complex, has been implicated in tumorigenesis. However, its pan-cancer relevance and functional role in liver hepatocellular carcinoma (LIHC) remain unclear. Multi-omics data from TCGA, GEO, and HPA were integrated to systematically evaluate KANSL2 expression, clinical significance, genomic alterations, and immune associations across cancers. Functional enrichment, immune infiltration analyses, and single-cell transcriptomics were performed. In vitro assays were conducted to validate the biological effects of KANSL2 in LIHC cells. KANSL2 is broadly upregulated across cancers and exhibits strong diagnostic performance. Elevated KANSL2 expression correlates with unfavorable prognosis, particularly in LIHC. Mechanistically, KANSL2 and its co-expressed genes are enriched in cell-cycle progression. KANSL2 expression is also closely associated with immune infiltration and immunoregulatory signaling within the tumor microenvironment, with single-cell data indicating preferential expression in proliferative T-cell subsets. Functional experiments demonstrate that KANSL2 silencing suppresses proliferation, migration, and invasion, and induces G2/M phase arrest in LIHC cells. Notably, its effects on apoptosis are limited, suggesting that KANSL2 primarily drives tumor progression through cell-cycle-dependent mechanisms. This study identifies KANSL2 as a key regulator of tumor progression and immune remodeling in LIHC. By promoting malignancy predominantly via cell-cycle control, KANSL2 represents a promising biomarker for diagnosis and prognosis, and a potential therapeutic target.

Carcinoma, Hepatocellular↗

PubMed2026

Multimodal atlas of human atherosclerosis links granular vascular cell states to coronary artery disease risk.

Advances in single-cell and spatial assays have revolutionized the scale and resolution of molecular tissue profiling. Here we present MetaPlaq, a multimodal atlas of human atherosclerotic arterial beds comprising over a million cells across single-cell transcriptomics, epigenomics and high-resolution spatial expression assays. We map granular cell states and disease-relevant transcriptional programs within the native tissue context of coronary arteries. Furthermore, we map cardiovascular GWAS signals to smooth muscle cells (SMCs) and endothelial cells (ECs) and uncover the cis-regulatory architecture governing their phenotypic transitions. Our comprehensive epigenomic reference allowed us to build cell-specific enhancer-gene link maps and multimodal gene regulatory networks (GRNs) underlying disease-relevant states such as osteogenic SMCs and ECs undergoing mesenchymal transition. We also integrate SMC and EC disease-associated gene sets with GRNs to nominate key transcription factors such as PRRX1, BNC2 and ELK3 regulating atherosclerosis-relevant transcriptional programs. Finally, we layer single-cell and spatial modalities to fine-map GWAS variants with improved cell and anatomical context. We highlight candidate cell-specific regulatory mechanisms at less characterized CAD loci, including FGD5 and MCF2L in ECs. Together, this atlas represents an important step towards fully interpreting genetic risk loci and informing new therapeutic strategies for cardiovascular disease.

Journal Article↗

PubMed2026

LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.

Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-κB) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.

Humans↗

PubMed2026

TET2 promotes monocyte inflammatory activation in asthma via ALKBH5-m6A regulation and PI3K signaling: evidence from m6A-SNP and single-cell analyses.

Asthma is a complex inflammatory airway disease with strong genetic determinants, yet the functional relevance of most asthma-associated non-coding variants remains unclear. Emerging evidence suggests that N6-methyladenosine (m6A) modification may serve as a critical epitranscriptomic link between genetic variation and immune regulation. In this study, we aimed to systematically identify functionally relevant m6A-regulated genes in asthma by integrating large-scale GWAS data, m6A-SNP annotations, and single-cell transcriptomic analyses, and to investigate their roles in monocyte-driven airway inflammation. We identified TET2 as a key m6A-regulated gene associated with both asthma and lung function, which was selectively upregulated in monocytes during asthma and accompanied by activation of inflammatory and PI3K signaling pathways. Mechanistic experiments further demonstrated that inflammatory stimulation induced ALKBH5 expression, reduced m6A modification of TET2 mRNA, and increased TET2 protein levels, thereby promoting PI3K/AKT signaling and pro-inflammatory cytokine production, whereas inhibition of TET2 or ALKBH5 attenuated these effects. Collectively, these findings demonstrate that ALKBH5-mediated m6A regulation of TET2 enhances PI3K/AKT signaling in monocytes, thereby promoting inflammatory responses in asthma. Our study establishes TET2 as a key m6A-regulated gene linking genetic susceptibility to monocyte-driven inflammation, and highlights the ALKBH5-m6A-TET2 axis as a potential therapeutic target for modulating aberrant immune responses in asthma.

Humans↗

PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗

PubMed2025

Large-scale CRISPR screening in primary human 3D gastric organoids enables comprehensive dissection of gene-drug interactions.

Understanding how genes influence drug responses is critical for advancing personalized cancer treatments. However, identifying these gene-drug interactions in a physiologically relevant human system remains a challenge, as it requires a model that reflects the complexity and heterogeneity among individuals. Here we show that large-scale CRISPR-based genetic screens, including knockout, interference (CRISPRi), activation (CRISPRa), and single-cell approaches, can be applied in primary human 3D gastric organoids to systematically identify genes that affect sensitivity to cisplatin. Our screens uncover genes that modulate cisplatin response. By combining CRISPR perturbations with single-cell transcriptomics, we resolve how genetic alterations interact with cisplatin at the level of individual cells and uncover an unexpected link between fucosylation and cisplatin sensitivity. We identify TAF6L as a regulator of cell recovery from cisplatin-induced cytotoxicity. These results highlight the utility of human organoid models for dissecting gene-drug interactions and offer insights into therapeutic vulnerabilities in gastric cancer.

Humans↗

PubMed2026

Integrative Analysis Uncover the Effects and Multi-Omics Features of Thigh Muscle Fat Infiltration.

The health impacts and underlying biological pathways of thigh muscle fat infiltration (TMFI) remain incompletely understood. In this study, we analyzed TMFI measured by magnetic resonance imaging in 55,120 UK Biobank participants and found that higher TMFI was significantly associated with all-cause mortality as well as with all major system-specific diseases examined (p values ranged from 2.50 × 10-88 to 9.97 × 10-04). TMFI also mediated the effects of lifestyle factors on health-related outcomes, with mediation proportions ranging from 6.7% to 71.7%. A genome-wide association study (GWAS) identified 79 lead single nucleotide polymorphisms (SNPs) linked to TMFI, and the polygenic risk score for TMFI was significantly associated with mortality and all incident diseases across examined organ systems in an independent subset of UK Biobank participants of European ancestry who were not included in the TMFI GWAS (n = 362,286, all p < 0.05). Gene-drug interactions identified multiple drugs that could potentially modulate TMFI. Analysis of single-cell transcriptomic data indicated that myogenic cells were strongly linked to TMFI (p = 7.08 × 10-08). Summary-data-based Mendelian randomization and Transcriptome-Wide Association Study analyses revealed numerous genes whose expression in specific tissues was associated with TMFI. Proteomic and metabolomic profiling uncovered a broad array of circulating biomarkers associated with TMFI, many of which mediated the effects of modifiable factors and genetic risk on TMFI. Overall, our results highlight the biological relevance of TMFI to human health and provide insights into the multi-omics mechanisms underlying TMFI, identifying potential targets for interventions.

Humans↗

PubMed2026

Single-cell capture of on-ART SIV transcription reveals TGF-β-mediated metabolic control of viral latency.

We previously demonstrated that blocking TGF-β with galunisertib, a safe, orally available small drug, reactivated latent SIV in vivo by shifting T cells toward a transitional effector phenotype. Here, we investigated the mechanisms underlying this effect using single-cell RNA sequencing, metabolic profiling, and high-dimensional spectral flow cytometry of samples from SIV-infected, antiretroviral therapy-treated (ART-treated) macaques before and after galunisertib. To characterize virus-transcribing, infected cells during ART, we developed a novel, sensitive SIV Transcripts Capture Assay (SCAP) that detected 127 SIV-expressing cells within lymph node single-cell transcriptome libraries. Galunisertib drove broad metabolic reprogramming in CD4+ T cells, with transcriptional upregulation of inflammatory and mitochondrial biosynthesis pathways, confirmed by Seahorse profiling. Metabolomics revealed increased energy metabolites and amino acids and enhanced metabolic flux without proliferation. SIV transcript-positive cells before galunisertib were metabolically quiescent compared with cells without detectable viral transcripts. After galunisertib, virus-expressing cells showed a dramatic metabolic activation, with upregulation of glycolysis, fatty acid metabolism, and TNF-α signaling. High-dimensional flow cytometry demonstrated effects beyond CD4+ T cells, including fewer tissue-resident memory T cells, but more inflammatory macrophages. In conclusion, SCAP represents a specific tool for characterizing rare SIV-infected cells transcribing virus during ART, and it reveals TGF-β as a key mediator of viral latency in vivo through metabolic suppression.

Virus Latency↗

PubMed2026

Loss of PBRM1 accelerates pancreatic cancer progression by inducing acquisition of mesenchymal phenotype and inflammatory cancer-associated fibroblasts reprogramming.

BACKGROUND: PBRM1 is an important subunit of the SWI/SNF complex, which broadly regulates gene transcription by chromatin remodeling. Genomic alterations of PBRM1 have been found in patients with pancreatic ductal adenocarcinoma (PDAC), but its molecular functions remain unclear. METHODS: Clinical relevance of PBRM1 was analyzed by using human PDAC samples and public genomic datasets. Mice with concomitant pancreas-specific Pbrm1 deletion in Kras-driven genetic PDAC models were generated. Single-cell transcriptomics were performed to determine tumor phenotype and microenvironment reprogramming. RESULTS: Reduction of PBRM1 expression was observed in human PDAC tissues and correlated with poor prognosis and metastasis. Pbrm1 loss promoted ductal metaplasia and delayed epithelial recovery in mice with caerulein-induced pancreatic injury. In PDAC model with either mutant Kras alone or in combination with Trp53 mutation, lack of Pbrm1 markedly accelerated tumor development and progression. Bulk transcriptomics and scRNA-seq identified reprogramming of both tumor compartment with mesenchymal phenotype acquisition and stroma compartment with inflammatory cancer-associated fibroblasts (iCAFs) transformation. Mechanistically, Pbrm1 deletion induced Zeb1 upregulation through epigenetic chromatin remodeling, thereby enhancing epithelial-mesenchymal and basal-like subtype transition. CONCLUSIONS: These findings indicated a tumor-suppressing role of PBRM1 in PDAC. PBRM1-deficient PDAC constitutes a specific subgroup of patients with aggressive phenotype and prognostic significance.

Animals↗

PubMed2026

transFusion: a novel comprehensive platform for integration analysis of single-cell and spatial transcriptomics.

MOTIVATION: Understanding spatial organization, intercellular interactions, and regulatory networks within the spatial context of tissues is crucial for uncovering complex biological processes and disease mechanisms. Spatial transcriptomics technologies have revolutionized this field by enabling the spatially resolved profiling of gene expression. 10× Visium has emerged as the predominant spatial technology, but its low resolution and the complexity of integrating multimodal datasets present significant analytical challenges, particularly for researchers with limited computational and statistical expertise. Current spatial transcriptomics analysis platforms generally fall short of effectively integrating multimodal data and maximizing the utility of spatial information-such as uncovering complex cellular spatial dependencies, multimodal gradient patterns, and spatial coexpression of ligand-receptor pairs and regulatory networks related to disease or biological states-thereby limiting their ability to provide comprehensive end-to-end analytical workflows when analyzing 10× Visium data. RESULTS: To address these limitations, we developed transFusion, a novel, advanced web-based platform specializing in the most comprehensive and effective integration analysis of scRNA-seq and 10× Visium spatial transcriptomics data. transFusion offers 12 key functions, from basic visualization to advanced analyses, including intercellular dependency analysis, ligand-receptor coexpression identification and visualization, and spatial multimodal gradient variation patterns. Two case studies were used to demonstrate transFusion's capabilities in exploring tissue architecture, intercellular communication, dependency networks, and multimodal gradient variation patterns with minimal computational skills and statistical expertise. transFusion provides a flexible and powerful framework for multimodal data integration analysis. AVAILABILITY AND IMPLEMENTATION: transFusion is freely available at https://github.com/WQLin8/transFusion.

Spatial Transcriptomics↗

PubMed2025

Evolutionary fingerprints of epithelial-to-mesenchymal transition.

Mesenchymal plasticity has been extensively described in advanced epithelial cancers; however, its functional role in malignant progression is controversial1-5. The function of epithelial-to-mesenchymal transition (EMT) and cell plasticity in tumour heterogeneity and clonal evolution is poorly understood. Here we clarify the contribution of EMT to malignant progression in pancreatic cancer. We used somatic mosaic genome engineering technologies to trace and ablate malignant mesenchymal lineages along the EMT continuum. The experimental evidence clarifies the essential contribution of mesenchymal lineages to pancreatic cancer evolution. Spatial genomic analysis, single-cell transcriptomic and epigenomic profiling of EMT clarifies its contribution to the emergence of genomic instability, including events of chromothripsis. Genetic ablation of mesenchymal lineages robustly abolished these mutational processes and evolutionary patterns, as confirmed by cross-species analysis of pancreatic and other human solid tumours. Mechanistically, we identified that malignant cells with mesenchymal features display increased chromatin accessibility, particularly in the pericentromeric and centromeric regions, in turn resulting in delayed mitosis and catastrophic cell division. Thus, EMT favours the emergence of genomic-unstable, highly fit tumour cells, which strongly supports the concept of cell-state-restricted patterns of evolution, whereby cancer cell speciation is propagated to progeny within restricted functional compartments. Restraining the evolutionary routes through ablation of clones capable of mesenchymal plasticity, and extinction of the derived lineages, halts the malignant potential of one of the most aggressive forms of human cancer.

Animals↗

PubMed2025

Balancing LncRNA H19 and miR-675 Bioconversion as a Key Regulator of Embryonic Myogenesis Under Maternal Obesity.

BACKGROUND: Maternal obesity (MO) impairs fetal skeletal muscle development, but the underlying mechanisms remain poorly defined. The regulatory roles of lncRNA H19 and its first exon derived microRNA675 (miR675) in prenatal muscle development remain to be examined. H19/Igf2 are in the same imprinting cluster with H19 expressed from the maternal allele while Igf2 expresses paternally. H19 contains a G-rich loop, and KH-type splicing regulatory protein (KHSRP) mediates the biogenesis of pre-miRNAs containing G-rich loops, which depends on its phosphorylation by AKT, a key mediator of IGF2 signalling. This study aims to depict the elusive function of these regulators that are affected by MO during embryonic myogenesis. METHODS: Single-cell transcriptomic sequencing and GeoMx spatial RNA sequencing were performed to identify the differentially expressed genes between embryos from MO and control (CT) mice. Both E11.5 and E13.5 embryos were collected and analysed to validate the sequencing data. The roles of H19 and miR657 in myogenesis were further analysed in P19 embryonic cells via CRISPR/dCas9-mediated H19 activation and inhibition. The epigenetic changes of H19 were analysed by methylated DNA immunoprecipitation, and allele-targeted analysis of H19 was performed by crossing C57BL/6J and CAST/EiJ mice. RESULTS: Transcriptomic analysis showed that MO embryos contained less differentiated myocytes (1.34%) than CT embryos (2.86%). Myogenesis-related GO biological processes were down-regulated in the MO embryonic myotome region. MO embryos showed lower expression of myogenic transcription factors such as Myf5, Myod1, Myog, Mef2c and Myh3 (p < 0.05). MO altered epigenetic modifications of the H19 genomic cluster, showing a decreased methylation level in H19 imprinting control region (p < 0.05) and a diallelic expression pattern of H19, which elevated its expression in MO embryos. Overexpression of H19 inhibited myogenesis in P19 cells, but miR675 promoted myogenesis, suggesting the critical regulatory roles of bioconversion of H19 to miR675. A KHSRP mediates the biogenesis of miR675, a process that relies on its phosphorylation by IGF2/AKT signalling. Knocking-down of KHSRP and inhibition of AKT abolished miR675 biogenesis. MO suppressed IGF2/AKT signalling and blocked KHSRP-dependent miR675 biogenesis in embryos. CONCLUSIONS: We found differential effects of H19 and miR675 on embryonic myogenesis. MO up-regulates H19 but blocks its miR675 bioconversion via suppressing IGF2/AKT/KHSRP signalling axis. Myogenesis in MO embryos was impeded due to the highly accumulated H19 and blocked miR675 biogenesis.

RNA, Long Noncoding↗

PubMed2025

Cancer-associated fibroblast-derived SOD3 enhances lymphangiogenesis to drive metastasis in lung adenocarcinoma.

Despite advancements in diagnostic and therapeutic strategies, lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality due to its aggressive metastatic potential. Extracellular superoxide dismutase (SOD3) is an antioxidant enzyme that regulates oxidative stress and is regarded as a tumor suppressor. However, studies have demonstrated that SOD3 can either promote or inhibit cell proliferation and survival in various cancers, and its molecular mechanisms within the tumor microenvironment are poorly understood. In this study, we report a breakthrough in uncovering the role of SOD3 derived from cancer-associated fibroblasts (CAFs) in LUAD. Using LUAD xenograft models co-implanted with SOD3-overexpressing CAFs (CAFSOD3), we observe an aggressive tumor phenotype characterized by increased lymphangiogenesis and lymphatic vessel invasion (LVI) of the tumor. Additionally, LUAD patients with elevated SOD3 levels exhibit a higher incidence of LVI and metastasis. Notably, RNA sequencing of CAFSOD3 reveals that SOD3-mediated VEGF-dependent tumor progression and lymphangiogenesis are up-regulated. Furthermore, single-cell transcriptomic analysis of LUAD clinical samples confirms a strong correlation between SOD3 expression in fibroblasts and characteristics of tumor exacerbation, such as lymphangiogenesis and metastasis. These findings underscore new insights into the role of CAF-derived SOD3 in LUAD progression and highlight its potential as a biomarker and therapeutic target.

Lymphangiogenesis↗

PubMed2026

Pan-cancer single-cell atlas of immunotherapy response identifies ZNF385A as a regulator of immune evasion in small cell lung cancer.

Although immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape of solid tumors, response rates in patients with small cell lung cancer (SCLC) remain limited, and acquired resistance is highly prevalent. The underlying mechanisms of this immunotherapy resistance remain to be fully elucidated. Clinically, SCLC typically manifests as an "immune-cold" tumor, characterized by a low abundance of CD8+ T cell infiltration and the rare formation of tertiary lymphoid structures (TLS). While DNA damage repair (DDR) is closely linked to innate immune responses, how DDR networks orchestrate the SCLC immune microenvironment remains obscure. In this study, we integrated single-cell transcriptomic data (comprising 344,447 high-quality cells) from six cancer types (BCC, CRC, HCC, HNSCC, iCCA, and SCLC). Our comparative analysis revealed a fundamental depletion of TLS-associated cellular subpopulations (e.g., CXCL13+ CD8+ T cells, HLA-DRB5+ B cells, and CXCL9+ dendritic cells) in SCLC, which was significantly correlated with aberrant DDR activity. Through high-dimensional weighted gene co-expression network analysis (hdWGCNA), we identified ZNF385A as the core hub gene within the DDR-associated module. ZNF385A is highly expressed in SCLC and is associated with poorer prognosis. In vitro, ZNF385A depletion suppressed SCLC cell proliferation and induced apoptosis, accompanied by R-loop accumulation and activation of cGAS-STING signaling, indicating a potential link between ZNF385A, genomic stability and tumor-intrinsic innate immune signaling. Collectively, these findings identify ZNF385A as a potential regulator associated with TLS deficiency and immune evasion in SCLC.

Immunotherapy resistance↗

PubMed2026

Antibody-drug conjugates against multidrug-resistant cancers: Biomarker-guided patient selection, payload engineering, linker chemistry, and bystander effects.

Antibody-drug conjugates (ADCs) are one of the most significant advancements in modern cancer therapeutics. Combining the target selectivity of monoclonal antibodies with the cytotoxic potential of payloads, ADCs effectively kill cancer cells and offer hope to patients with even refractory cancer types. Beyond simply increasing the number of therapeutic options available for cancer patients, ADCs have become a powerful frontline agent in overcoming multidrug resistance (MDR). As one of the most challenging obstacles to effective cancer care, MDR is mediated by ATP-binding cassette (ABC) transporter-mediated drug efflux, target-based mutations, and dysregulated apoptosis. The clinical success of ADCs specifically engineered to overcome MDR, including in heterogeneous tumors and cancer cells that exhibit bypass signaling, is well established. This is especially evident with trastuzumab deruxtecan (T-DXd) in HER2-low, HER2-positive, and HER2-mutant cancers; sacituzumab govitecan (SG) in TROP2-expressing triple-negative breast cancer (TNBC) and urothelial carcinoma; and enfortumab vedotin in Nectin-4-positive bladder cancer. By overcoming MDR, ADCs have enabled more effective treatment algorithms across multiple malignancies. Most importantly, the clinical application of ADCs has become inextricably linked to cancer genomics. HER2 testing has evolved from a two-tiered system to a continuous spectrum including HER2-ultralow, HER2-low, HER2-positive, and ERBB2-mutant categories. Each of these categories exhibits different eligibility guidelines for ADC patient selection. As cancer cells continue to evolve and develop resistance to even ADCs through mutations and variants, researchers and clinicians have used pharmacogenomics to predict ADC response and resistance. To define the genomic architecture of ADC-resistant tumor subpopulations, single-cell transcriptomic studies and liquid biopsy approaches are being used to enable real-time examination of the tumor genome during ADC therapy, thereby optimizing treatment and circumventing resistance driven by emerging mutations and variants. This review provides a comprehensive analysis of the molecular structure of ADCs, the pharmacological principles underlying their potent cytotoxic activity against MDR cancer cells, the genomic and transcriptomic biomarkers that guide ADC patient selection, and the emerging resistance mechanisms that will shape the next generation of promising ADC development.

Humans↗

PubMed2026

Pharmacologic inhibition of SOX9-CDK4 by CYD-4-61 impairs gastric adenocarcinoma growth and amplifies anti-PD-1 response.

Gastric adenocarcinoma (GAC) remains a leading cause of cancer-related mortality, particularly in patients with peritoneal carcinomatosis, for whom effective therapies are limited. We investigated the therapeutic efficacy and molecular mechanism of CYD-4-61, a BAX activator, using human GAC cell lines, patient-derived xenograft models, genetically engineered mouse models, and a syngeneic mouse model. CYD-4-61 potently inhibited tumor cell proliferation, induced apoptosis, and suppressed cancer stem cell-like properties, with enhanced activity in radiation-resistant GAC cells. Mechanistically, CYD-4-61 activated the BAX-caspase pathway, leading to SOX9 protein reduction. Integrated bulk and single-cell transcriptomic analyses identified SOX9-dependent transcriptional programs as major targets of CYD-4-61. Functional rescue experiments together with chromatin immunoprecipitation and CUT&RUN analyses supported CDK4 as a SOX9-regulated gene and demonstrated suppression of the SOX9-CDK4 regulatory axis following CYD-4-61 treatment. In multiple preclinical models, CYD-4-61 significantly inhibited tumor growth and improved the therapeutic response to anti-programmed cell death protein 1 (PD-1) therapy while modulating the tumor immune microenvironment. Clinically, co-expression of SOX9 and CDK4 was associated with diffuse-type GAC and poor patient outcomes. These findings identify the BAX-SOX9-CDK4 axis as an important mechanism contributing to the antitumor activity of CYD-4-61 and provide a strong preclinical rationale for its further development as a therapeutic strategy for aggressive GAC.

Animals↗

PubMed2026

An integrated single-cell and spatial proteotranscriptomics atlas of fibroblast-driven immunoregulation within the human adult oral cavity.

The immunoregulatory architecture of human oral tissues remains poorly defined. We present an integrated single-cell and spatial proteotranscriptomic atlas profiling >250,000 single-cell transcriptomes and >4 million spatially resolved cells across 13 niches. Using our AI-enabled AstroSuite, we defined neighborhoods and interaction modules, revealing peri-epithelial fibroblast-centered hubs enriched in effector cytokines. We harmonized fibroblast subtypes (universal, immune, peri-epithelial, peri-vascular, peri-neural, antigen-presenting cell [APC]-like, stress responsive, and myofibroblasts) with stress-responsive subtypes partitioning between mucosae and glands (type I and II). Spatial multiomics mapped ligand-receptor programs and identified mucosal stress-responsive fibroblasts as putative immunoregulatory hubs. Niche-aware integration of healthy and diseased datasets revealed fibroblast rewiring into inflammatory and reparative niches. Disease neighborhoods exhibited expansion of major histocompatibility complex (MHC)-I+, MHC-II+, and programmed cell death ligand 1 (PD-L1)+ fibroblasts and predicted spatial engagement with T cells at tertiary lymphoid structures. Together, this atlas identifies fibroblasts as central regulators of structural immunity and provides a scalable framework to target stromal-immune interactions across barrier organs.

Journal Article↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗