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PubMed2026

Parietal Cortex Transcriptomics Refines Parkinson Disease GWAS Nomination and Highlights STAT3 as a Putative Upstream Glial Regulator.

Parkinson disease (PD) affects more than 1.1 million individuals in the United States and around 12 million worldwide. Although Genome Wide Association Studies (GWAS) have substantially advanced our understanding of PD genetic architecture, the regulatory mechanisms linking PD risk loci to disease-relevant gene expression remain incompletely characterized, limiting our ability to infer disease mechanisms from genetic associations. Here, we integrated disease-state parietal cortex transcriptomics with the International Parkinson's Disease Genomics Consortium (iPDGC) locus prioritization to refine PD gene nomination and identify biologically plausible candidates missed by GWAS-only approaches. Using bulk RNA-seq from 99 neuropathologically confirmed PD cases and 30 neuropathologically confirmed controls, we prioritized candidate genes across 78 loci and classified them according to concordance between genetic evidence and differential expression in diseased cortices. This integrative approach recovered candidate genes not captured by external GWAS-based prioritization methods and highlighted synaptic, lysosomal, and proteostasis pathways as major components of PD risk biology. Network and transcription factor analyses further suggested coordinated regulation of these genes, with STAT3 emerging as a putative upstream glial regulator. Together, these findings suggest that integrating disease-state transcriptomics with genetic prioritization can refine PD risk-gene nomination and uncover regulatory programs that may be missed by GWAS alone.

Journal Article↗

PubMed2026

Integrated Pan-Cancer, Single-Cell, and Spatial Transcriptomic Analyses Identify ZDHHC12 as a Biomarker Associated with Macrophage Infiltration and the Immune Landscape in Glioma.

BACKGROUND: The tumor immune microenvironment (TME) critically influences cancer progression and therapeutic response. However, the pan-cancer expression landscape, prognostic relevance, and spatial distribution of ZDHHC12 remain incompletely characterized. This study investigated the prognostic value of ZDHHC12 and its associations with immune microenvironmental features and drug sensitivity. METHODS: Data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets were used to evaluate ZDHHC12 expression and prognosis across cancer types. Immune infiltration analyses, single-cell RNA sequencing, and spatial transcriptomics were integrated to characterize the associations of ZDHHC12 with the cancer immunity cycle and the spatial architecture of glioma. Drug sensitivity and immunotherapy-related metrics were assessed using pharmacogenomic databases and computational prediction models. RESULTS: ZDHHC12 was aberrantly expressed across multiple tumors and was associated with patient prognosis. Its expression was broadly correlated with immune cell recruitment- and activation-related signatures. In glioma, single-cell and spatial transcriptomic analyses showed enrichment of ZDHHC12 in monocyte/macrophage populations and spatial co-localization with BAK1, CD68, and CD163. ZDHHC12 expression was also associated with predicted drug sensitivity and immunotherapy-related metrics. CONCLUSION: ZDHHC12 may serve as a candidate pan-cancer prognostic biomarker. In glioma, its expression is associated with macrophage-enriched and immunosuppressive microenvironmental features. Functional studies are required to establish causality and determine its therapeutic relevance.

GBM↗

PubMed2026

Spatial transcriptomics of primary and metastatic ALK-rearranged NSCLC reveals site-specific adaptations.

INTRODUCTION: Genetic alterations and the tumor microenvironment (TME) influence treatment response in anaplastic lymphoma kinase-rearranged non-small cell lung cancer (ALK+ NSCLC). This study maps site-specific TME adaptations and exploratory risk-associated signatures in lymph node metastases (LNT) to investigate metastatic evolution. METHOD: We applied spatial transcriptomics to profile tumor (PanCK+) and stromal (PanCK-) compartments in a pilot cohort of 16 cases: primary lung tumors (LT, n = 3), LNT (n = 10), and brain metastases (BT, n = 3), with three site-matched non-tumor controls. LNT-derived prognostic signatures were evaluated using The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA LUAD) cohorts. RESULTS: Distinct, site-specific TME features were observed. LNT stroma was enriched in fibroblasts and macrophages, while tumor segments showed increased neutrophils. BT exhibited a macrophage-associated immunosuppressive TME. Tumor cells evolved divergently: LT retained pulmonary identity and showed trend towards translation-associated programs, LNT cells shifted toward senescence and epigenetic remodeling, and BT cells showed activation of Class A/1 (Rhodopsin-like) receptor, GPCR and drug metabolism pathways. In LNT, exploratory risk-associated differences were observed. Low-risk cases (n = 6) showed adaptive immune signatures, whereas high-risk cases (n = 4) showed enrichment for stromal MET signaling and stress-response pathways. Because treatment exposure differed markedly between the risk groups, these observations should be interpreted as hypothesis-generating. TCGA LUAD analysis suggested the broader biological relevance of immune-associated markers, but reflected general LUAD rather than ALK+ specific biology. Discordant associations for GCLC and TIMP1 underscored the importance of spatial context. CONCLUSION: Site-specific microenvironments may influence tumor adaptation across metastatic niches in ALK+ NSCLC. The exploratory risk-associated findings require validation in larger, uniformly treated cohorts.

Humans↗

PubMed2026

Genomic and transcriptomic features of HBV integration in treatment-naïve, HBeAg-positive children with chronic HBV infection.

BACKGROUND: Hepatitis B virus (HBV) integration represents a major obstacle to curing HBV; however, the landscape of HBV integration and local immune response to transcriptionally active viral integration in children with chronic HBV infection remain unclear. Herein, we aimed to elucidate this landscape in this population. METHODS: Genomic analyses using a probe-based capture strategy were performed on 18 children and 28 adults with chronic HBV infection. Spatial transcriptomics (ST) was performed on 12 children from our cohort and 3 adults from a public database. FINDINGS: All patients were hepatitis B e antigen (HBeAg)-positive and treatment-naïve. Genomically, children exhibited significantly lower clonal expansion level of HBV-integrated hepatocytes than adults, despite comparable unique breakpoint counts. After adjusting for confounding variables, age was identified as an independent risk factor for total frequency of unique integration breakpoints (b = 3.22, P = 0.005). Spatially, ST revealed that spots with transcriptionally active viral integration exhibited a sparse distribution and accounted for a low proportion of all spots in children. Notably, at these spots, children showed reduced adaptive immune cells (e.g., CD8+ T cells) but increased innate components (myeloid cells, Kupffer cells, activated dendritic cells) and APC co-stimulation, whereas adults exhibited a uniform reduction of immune cell populations. INTERPRETATION: Compared with adults, children exhibit lower clonal expansion of HBV-integrated hepatocytes and distinct immune profiles in response to transcriptionally active viral integration, offering new insights into their differing clinical course. FUNDING: Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education).

Humans↗

PubMed2026

Decoding regional keratinization in human oral mucosa through high-resolution spatial transcriptomics.

Oral mucosa exhibits region-specific keratinization, essential for periodontal health, yet the spatial and molecular mechanisms driving these differences remain poorly understood. This study aimed to generate a high-resolution spatial transcriptomic atlas of the human oral mucosa around the mucogingival junction, to reveal stromal-epithelial interactions, that distinguish keratinized from non-keratinized programs. Formalin-fixed paraffin-embedded specimens from the mucogingival junction area of two healthy donors were analyzed with the 10 × Genomics Visium HD platform, yielding two keratinized and two non-keratinized regions. Spatial clustering, pseudotime trajectory inference, cell-type integration with a single-cell reference, and ligand-receptor network analysis were applied to delineate epithelial and stromal compartments. Sixteen reproducible clusters, recapitulating tissue architecture, were identified and revealed distinct transcriptional signatures, distinguishing gingiva from lining mucosa. Pseudotime analysis revealed bifurcating epithelial lineages, originating from a shared basal progenitor layer into keratinized and non-keratinized programs. Gingival keratinization was driven by stromal collagen ligands (COL1A1, COL1A2, COL6A1, COL6A2) engaging epithelial receptors (CD44, SDC1), further reinforced within the epithelium by desmosomal adhesion via DSG1-DSC2/3. Gingival keratinization emerges from integrated stromal collagen signaling and epithelial adhesion. This spatially resolved framework advances understanding of oral mucosal specialization and provides a foundation for biologically guided regenerative therapies.

Humans↗

PubMed2026

GenOT: generative optimal transport enables spatiotemporal interpolation and generation in cross-platform spatial transcriptomics.

Spatial transcriptomics technologies have revolutionized the analysis of spatial gene expression, yet integrating spatial information and generating data across heterogeneous samples remain challenging. We present GenOT, a generative framework combining multi-scale graph self-supervised contrastive learning with optimal transport barycenter theory for efficient cross-slice and cross-platform spatiotemporal interpolation. The core innovation of GenOT lies in introducing an optimal transport barycenter-based interpolation algorithm, which mathematically models spatial distribution differences across heterogeneous samples to reconstruct spatiotemporal gene expression dynamics. Extensive evaluations demonstrate that GenOT consistently outperforms existing approaches in spatial domain identification, cross-platform interpolation, and developmental trajectory reconstruction.

Spatial Transcriptomics↗

PubMed2026

Diving Deeper Into Mechanisms of Acrylamide-Induced Toxicity: RNA Sequencing Reveals Transcriptomic Alteration and Retrotransposon Expression in Drosophila melanogaster.

Given the inevitability of human and animal exposure to acrylamide, there is increasing concern regarding its potential health risks. While a number of molecular mechanisms have been proposed, the complexity of acrylamide toxicological pathways and interactions remains incompletely characterized. In this study, we employed a transcriptomic approach to investigate the transcriptional responses of Drosophila melanogaster following exposure to acrylamide (100 mg/kg). Our analysis identified 634 differentially expressed genes (DEGs), with 362 upregulated and 272 downregulated. Functional analysis revealed these DEGs are enriched in pathways related to reproduction, detoxification, cellular and metabolic processes, signaling, synaptic formation and organization. Notably, acrylamide exposure upregulated the expression of tau and beta-amyloid protein precursor-like genes, both implicated in Alzheimer's disease pathology. An aversive memory test further demonstrated that acrylamide impaired the short-term memory of treated flies. Additionally, acrylamide-induced toxicity altered the expression of nine long terminal repeat retrotransposons, belonging to the gypsy and pao superfamilies. By exploring the potential role of transposable element activity in acrylamide-mediated toxicity, this study provides novel insights into the molecular mechanisms underlying its effects. Collectively, these findings offer a more comprehensive understanding of the mechanisms and pathways associated with the toxic action and detoxification of acrylamide in D. melanogaster.

Animals↗

PubMed2025

Paired Single-Cell Transcriptome and DNA Barcode Detection in Zebrafish Using ScarTrace.

ScarTrace is a CRISPR/Cas9-based genetic lineage tracing method that allows for uniquely barcoding the DNA of single cells at a target GFP sequence during developing zebrafish embryos. Single cells from barcoded adult zebrafish can be isolated from various tissues (e.g., marrow, brain, eyes, fins), and their transcriptome and barcode sequences are captured by single-cell cDNA amplification and genomic DNA nested PCR, respectively. Computationally, cell type and barcode identification permit clone tracing and lineage tree reconstruction of tissues to unravel fate decisions during embryogenesis.

Animals↗

PubMed2026

Integrative pooled transcriptomic analysis reveals shared and distinct molecular signatures in adult T-cell leukemia/lymphoma and peripheral T-cell lymphoma.

Adult T-cell leukemia/lymphoma (ATLL) and peripheral T-cell lymphomas (PTCLs) are aggressive neoplasms of mature T cells with poor prognosis and limited therapies. ATLL originates from HTLV-1 infection, while PTCL comprises heterogeneous subtypes without a defined etiologic factor. Comparative molecular profiling of these malignancies remains limited. We conducted an integrative pooled transcriptomic analysis of publicly available Gene Expression Omnibus (GEO) microarray datasets to compare ATLL, PTCL, and normal T-cell samples. Differential expression, functional enrichment, and protein-protein interaction (PPI) network analyses were performed using STRING, Cytoscape, and Gephi. Key hub genes and functional modules were further analyzed through KEGG and Enrichr databases. Comparative analyses revealed upregulation of extracellular matrix (ECM) components (COL1A1, COL3A1, FN1, SPARC, THBS1) and immune-regulatory molecules (CD163, CXCL12-CXCR4, complement subunits). Shared pathways included ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling. PTCL showed enrichment in coagulation and angiogenesis, while ATLL displayed distinct enrichment of cytoskeletal, chemokine, immune-regulatory, and signaling-associated pathways. PPI networks identified ECM and chemokine signaling as key hubs, with subtype-specific modules related to immune regulation, proliferation, and metabolism. This integrative approach uncovers common and distinct oncogenic programs in ATLL and PTCL, emphasizing ECM remodeling and immune modulation as shared hallmarks. Hub genes such as COL1A1, FN1, and CXCL12-CXCR4 may represent candidate molecular signatures that warrant validation in independent patient cohorts and functional studies before their clinical utility can be established.

Humans↗

PubMed2026

Transcriptomic insights into the molecular mechanism of antifouling agent-induced settlement inhibition in the Pacific oyster Crassostrea gigas.

Marine biofouling remains a persistent challenge to maritime industries and marine ecosystems worldwide. In this study, we systematically evaluated the acute toxicity, settlement inhibitory efficacy, and underlying molecular mechanisms of an N-oleyl-1,3-propanediamine-based antifouling agent using pediveliger larvae of the Pacific oyster Crassostrea gigas. The 96 h-LC50 of the agent was determined to be 0.81 mg/L, and exposure to 1.68 mg/L achieved complete larval settlement inhibition without inducing significant acute toxicity. Transcriptomic analysis identified 791 differentially expressed genes, dominated by downregulated genes associated with ribosomal function, translation, cell adhesion, and cytoskeletal organization. The agent exerts its inhibitory effect primarily through the global suppression of protein synthesis, disruption of cell-substrate adhesion and cytoskeletal integrity, and induction of proteotoxic stress responses. These findings reveal a multi-pathway molecular mechanism underlying antifouling agent-induced settlement inhibition in oyster larvae and provide key molecular biomarkers to support the development of eco-friendly antifouling technologies.

Animals↗

PubMed2026

Transcriptomic responses of Porphyrophora sophorae larvae during licorice root colonization reveal coordinated remodeling of translation, mitochondrial energy metabolism and defense-related genes.

BACKGROUND: Porphyrophora sophorae is a subterranean piercing-sucking scale insect that damages licorice (Glycyrrhiza uralensis) roots, but the molecular responses associated with larval root colonization remain insufficiently defined. METHODS: We compared non-parasitic larvae (NP) and root-colonizing larvae (RC) using six RNA-seq libraries, de novo transcriptome assembly, DESeq2-based differential expression analysis, GO/KEGG enrichment, annotation-based candidate gene screening, and RT-qPCR validation of selected genes. RESULTS: Sequencing yielded 260.91 million clean reads, and de novo assembly produced 60,794 non-redundant transcripts. DESeq2 identified 703 FDR-significant DEGs, including 49 upregulated and 654 downregulated genes in RC larvae. Upregulated genes were mainly associated with translation- and ribosome-related processes, whereas downregulated genes were enriched in mitochondrial, oxidation-reduction, energy metabolism, and oxidative phosphorylation-related functions. Annotation-based screening identified 75 FDR-significant candidate genes associated with chemosensation, defense-related responses, and energy metabolism, with mitochondrial energy metabolism-related genes forming the largest module. RT-qPCR validation based on the raw Ct data showed concordant expression directions for ten selected transcript targets. CONCLUSIONS: Root colonization in P. sophorae larvae was associated with coordinated transcriptional remodeling involving selective activation of translation-related processes, adjustment of mitochondrial energy metabolism, and changes in defense-related gene expression. These results provide candidate molecular targets for future functional studies of host contact, feeding establishment, and physiological adjustment in this subterranean scale insect.

Animals↗

PubMed2026

Antennal transcriptome analysis of chemosensory proteins in the raspberry weevil, Aegorhinus superciliosus (Coleoptera: Curculionidae).

Aegorhinus superciliosus (Coleoptera: Curculionidae) is a polyphagous pest of economic importance in southern Chile, the chemical ecology of which remains poorly characterized. Across insect species, chemosensory proteins, including odorant receptors (ORs), gustatory receptors (GRs), ionotropic receptors (IRs), odorant-binding proteins (OBPs), chemosensory proteins (CSPs), and sensory neuron membrane proteins (SNMPs), mediate the detection of chemical cues involved in host selection, reproduction, and other ecologically relevant behaviors. In this study, the antennal transcriptome of adult A. superciliosus was sequenced and analyzed using a de novo RNA-seq approach. Three independent biological replicates per sex were used for RNA-seq, and the same number of independent biological replicates was used for RT-qPCR validation; sequencing yielded 147,409,936 high-quality reads after quality filtering. A total of 112 candidate chemosensory genes were identified, comprising 43 ORs, 34 OBPs, 10 CSPs, 18 IRs, 5 GRs, and 2 SNMPs. Phylogenetic analyses assigned these candidate proteins to established clades, providing a comparative framework for functional inference for ORs and OBPs. Sex- and tissue-biased expression analyses revealed that several ORs, including AsupOR4, AsupOR19, and AsupOBP13, exhibit antennal enrichment and sex-specific expression patterns. Notably, AsupOR19 and AsupOBP13 displayed strong female-biased expression. In addition, transcripts of selected ORs and OBPs were detected in non-antennal tissues, such as the rostrum and legs, suggesting potential functional versatility beyond canonical olfaction. Together, these findings represent the first molecular identification of the chemosensory repertoire of A. superciliosus. This study establishes a foundation for reverse chemical ecology approaches aimed at identifying behaviorally active volatile organic compounds (VOCs) toward environmentally sustainable strategies for integrated pest management.

Animals↗

PubMed2026

Distinct molecular responses to acute cold exposure revealed by comparative transcriptomic and metabolomic profiling in the bay scallop Argopecten irradians.

Acute cold stress can elicit distinct molecular responses even when bay scallop populations show similar phenotypic outcomes. We compared a seventh-generation fast-growing bay scallop line (BS) with a commercial control population (CC) during a 72-h acute cold exposure at -1 ± 0.3 °C. RNA-seq was used as the discovery layer, representative BS cold-responsive genes were evaluated by qRT-PCR, and paired LC-MS profiles provided a comparative metabolic layer. At baseline, 138 genes differed between BS and CC; after cold exposure, 134 of these baseline differences disappeared and 61 of 65 cold-state differences newly emerged. BS showed a larger transcriptomic response magnitude than CC, with 1129 cold-responsive genes compared with 28 genes in CC, and this ordering remained robust across multiple sensitivity analyses. Survival after 72 h was identical in BS and CC (83/90, 92.2% in each population). Biochemical responses were time-dependent and marker-specific: CAT, LZM, T-SOD and T-AOC showed population-by-time interactions, whereas GSH-Px and MDA did not, and the 72-h differences were not consistently favourable to BS. Metabolomic cold effects were strongly concordant between populations, and no feature showed a significant population-by-cold interaction. Features putatively assigned to arachidonic acid metabolism were enriched, but this provider-annotated pathway signal remains exploratory because authentic-standard confirmation was not performed. These findings indicate population-specific differences in molecular responsiveness but do not establish superior cold tolerance in BS.

Animals↗

PubMed2026

Integrated transcriptomic and metabolomic analyses provide new insights into the response of black rockfish (Sebastes schlegelii) larvae to temperature fluctuations.

Sebastes schlegelii usually encounter elevated and fluctuating water temperatures near its upper thermal limit in summer, yet the hepatic responses of larvae to repeated temperature fluctuation regimes remain unclear. To address this question, S. schlegelii larvae were exposed for 8 days to four thermal regimes: constant 18 °C (CT), constant 28 °C (HT), intermittent cooling from 18 to 8 °C followed by recovery to 18 °C (FL), and intermittent warming from 18 to 28 °C followed by recovery to 18 °C (FH). Survival rate was evaluated, and integrated liver transcriptomic and metabolomic analyses were performed. Final survival rates were 96.67% in the CT group, 97.78% in the FL group, and 77.78% in the FH group. Survival rate in the HT group (38.89%) was significantly lower than that in the other three groups (P < 0.05). HTvsCT, FLvsCT, FHvsCT, and FHvsHT comparisons identified 2598, 1207, 622, and 2404 differentially expressed genes and 627, 606, 690, and 610 differential metabolites, respectively. KEGG enrichment analyses of DEGs and SDMs in HTvsCT highlighted HSP-mediated proteostasis, endoplasmic-reticulum protein processing, branched-chain and sulfur amino acid metabolism, glutathione metabolism, and central carbon metabolism, with upregulated hsp90aa1, bckdha, gclc, and pfkp and reduced levels of branched-chain amino acids and methionine. Compared with HT, FH showed attenuated disturbances in proteostasis, amino acid and redox regulation, and central carbon metabolism, together with recovery-associated glycerophospholipid turnover. FL primarily induced polyunsaturated fatty acid (PUFA)-related membrane lipid remodeling. These findings indicate that hepatic responses differed between continuous high-temperature exposure and temperature fluctuations and between fluctuation regimes.

Animals↗

PubMed2026

Transcriptomic and RNAi analyses reveal chloride channel 3-associated osmoregulation in Litopenaeus vannamei under low-salinity stress.

Chloride channels and transporters are important for cellular volume regulation and salinity adaptation in euryhaline crustaceans, yet the intestinal transcriptional relationship between plasma-membrane and intracellular chloride pathways remains unclear in Litopenaeus vannamei. In this study, RNA interference of anoctamin 1 (ANO1) was combined with intestinal transcriptome sequencing under the production-relevant low-salinity condition of salinity 3. ANO1 silencing produced a focused transcriptional response, with 16 differentially expressed genes (DEGs) identified (11 upregulated and 5 downregulated). Functional enrichment indicated that these genes were associated with transporter activity, cytoskeletal organization, extracellular matrix-receptor interaction, membrane lipid metabolism, and vesicular processes. Notably, a transcript encoding chloride channel protein 3 (CLC-3) was significantly upregulated following ANO1 knockdown, suggesting a potential transcriptional relationship between ANO1 and CLC-3 in chloride homeostasis. Based on this finding, CLC-3 was selected for full-length cDNA cloning, sequence characterization, salinity-gradient expression analysis, and RNAi-based functional assessment. The cloned CLC-3 cDNA was 2883 bp in length and encoded an 850 amino acid protein containing a conserved voltage-gated chloride channel (Voltage-CLC) domain and two cystathionine β-synthase domains. Phylogenetic analysis placed LvCLC-3 within the intracellular CLC-c clade, and tissue distribution analysis showed the highest CLC-3 expression in the intestine. Intestinal CLC-3 expression responded nonlinearly to salinity variation, peaking at salinity 20. Under salinity 3, CLC-3 knockdown reduced ANO1, Na+/K+-ATPase alpha subunit, and Na+-K+-2Cl- cotransporter transcript levels, whereas glutamate-gated chloride channel expression increased. Mild hepatopancreatic structural alterations were also observed after CLC-3 knockdown. These findings suggest that CLC-3 is a salinity-responsive intracellular chloride-transporter candidate associated with intestinal ion-transport-related transcriptional responses after ANO1 suppression in L. vannamei, although the underlying physiological mechanism requires further validation.

Animals↗

PubMed2025

Combined somatic mutation and transcriptome analysis reveals region-specific differences in clonal architecture in human cortex.

The human cerebral cortex is specialized into regions, but little is known about how human cellular lineages shape cortical regional variation and neuronal cell-type distribution during development. Here, we map single-cell lineages of human cortical regions and neuronal subtypes using >1,000 somatic single-nucleotide variants (sSNVs) identified from deep bulk whole-genome sequencing and analyzed over 25 regions and >72,000 single cells. In the fronto-parietal cortex, sSNVs are rarely restricted, marking neuron-generating clones that disperse into neighboring regions. In contrast, the primary visual cortex harbors 30%-70% more sSNVs than the neighboring secondary visual cortex. Clones at this border exhibit more restricted dispersion, suggesting late developmental lineage segregation. Single-nucleus sSNV and whole-transcriptome analysis reveal glutamatergic neuron clones with modest regional restrictions that share low-mosaic sSNVs with some GABAergic neurons, suggesting a recent dorsal cortical progenitor. Our analysis reveals human-specific cortical lineage patterns, regional differences in clonal patterns, and late divergence of some glutamatergic/GABAergic lineages.

Humans↗

PubMed2025

Colorectal Liver Metastasis Pathomics Model: Integrating Single-Cell and Spatial Transcriptome Analysis With Pathomics for Predicting Liver Metastasis in Colorectal Cancer.

The liver is the primary target organ for hematologic metastasis of colorectal cancer (CRC), and CRC liver metastasis (CRLM) often precludes radical resection, making it the leading cause of death in patients with CRC. To improve the identification and prediction of liver metastasis risk, we identified a cell type of liver metastasis--triggering malignant cells (LMTMCs) through integrating single-cell RNA sequencing and spatial transcriptome analysis. Multiomics cell communication analysis indicated that the interaction between fibroblasts and LMTMCs through the COL1A1-CD44/SDC4 and LAMA4-CD44 signaling axes could promote CRLM. By applying the one-class logistic regression algorithm, we developed a CRLM scoring system in the bulk RNA-sequencing data according to the abundance of LMTMCs in each individual. Using the grouping labels derived from the CRLM scoring system in the bulk data and the corresponding whole-slide images without any manual annotations at the region or pixel level, processed via slide-level weakly supervised learning, a deep-learning model based on the ResNet18 architecture, called Colorectal Liver Metastasis Pathomics Model, was developed to predict the risk of liver metastasis in patients with CRC. The Colorectal Liver Metastasis Pathomics Model achieved an area under the curve of 0.84 at the internal test set of The Cancer Genome Atlas-CRC histology images. In the external independent validation sets, namely the Affiliated Hospital of Southwest Medical University and the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University cohorts, the areas under the curve were 0.89 and 0.72, respectively, indicating effective classification performances. This study provided new insights and tools for the early identification of CRLM and demonstrated the potential of combining multiomics with deep learning-based pathomics in cancer research.

Humans↗

PubMed2025

An Integrated Clinical Genomic and Transcriptomic Subgrouping of Central Chondrosarcoma.

Central conventional chondrosarcoma, a malignant cartilage-producing bone tumor, is the second most common bone sarcoma. Chondrosarcomas are histologically graded, which is so far the best predictor of survival. Early mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are frequent, leading to the production of the oncometabolite D-2-hydroxyglutarate, which affects DNA methylation, resulting in a preferred chondrogenic differentiation over osteogenic differentiation of mesenchymal stem cells, which are currently considered the precursor cells of chondrosarcoma. DNA methylation profiling has previously revealed distinct profiles between IDH-mutant and IDH-wild-type chondrosarcomas, but the presence of further DNA methylation subgroups indicates that classification based solely on IDH status is too simplistic. In this study, we aim to identify biological subgroups in a total of 116 chondrosarcomas by integrating clinical data, IDH mutation status, gene expression, and genome-wide loss of heterozygosity (LOH). Clinical associations were observed between several factors, including sex and histological grade, as well as tumor site and IDH mutation status. RNA sequencing and genome-wide LOH confirmed the distinction between IDH-wild-type and IDH-mutant chondrosarcomas, where the number of chromosome arms affected by LOH was significantly higher in IDH-wild-type tumors than in IDH-mutant tumors. However, no clear subgroups emerged within each IDH group. Further clustering on RNA expression of differentiation markers identified subgroups characterized by chondrogenic, osteogenic, resting chondrocyte, or dedifferentiated profiles. These different subgroups showed a specific clinical presentation and suggest different precursor cells. Instead of a simple dichotomy between IDH-mutant and IDH-wild-type, our integrated approach highlights interconnected clinical, genomic, and transcriptomic patterns that offer a more nuanced view of chondrosarcoma biology and might potentially guide treatment stratification.

Humans↗