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PubMed2026

Characterizing the Discordance between AT-Rich Interacting Domain 1A Protein and Genotype in Endometrioid-Type Endometrial Tumors.

ARID1A is one of the most frequently mutated genes in endometrial cancer, with approximately 40% of patients harboring an ARID1A mutation. However, relatively little is known about how AT-rich interacting domain 1A (ARID1A) protein loss shapes endometrial cancer pathogenesis. Mounting evidence from other malignancies suggests that ARID1A protein can be regulated post-translationally, independent of genotype. However, most studies in endometrial cancer evaluate genotype alone, overlooking the potential for alternative mechanisms of ARID1A loss. To address this gap, ARID1A protein expression and genotype were examined in endometrioid tumors, and associated transcriptional changes were characterized. Evaluation of ARID1A protein in 71 human endometrioid tumors demonstrates that protein loss can occur regardless of ARID1A genotype. Retention or deficiency of ARID1A protein was not significantly related to variant allele frequency or location of mutation in human tumors with mutant ARID1A. A human endometrial cancer cell model suggests that ARID1A protein loss can occur through proteasomal degradation. Furthermore, ARID1A protein expression was found to be a predictor of worse overall survival in The Cancer Genome Atlas cohort of ARID1A wild-type endometrioid tumors. Spatial transcriptomics of 16 human endometrioid tumors revealed that both genotype and protein expression of ARID1A play a role in shaping unique transcriptional signatures in endometrial cancer and can be used to predict patient prognosis. Suggesting evaluation of ARID1A should not be done solely by sequencing techniques.

Humans↗

PubMed2025

Single-Cell Splicing Isoform Atlas of the Adult Human Heart and Heart Failure.

BACKGROUND: Alternative splicing plays crucial roles in normal heart development and cardiac disease by influencing protein-coding sequences, functional domains, and molecular networks. However, a detailed characterization of the human heart isoform landscape remains incomplete. METHODS: Leveraging long-read single-nucleus RNA sequencing and computational analysis, we dissected full-length isoform heterogeneities, expression patterns, and usage shifts across cell types, cell states, and cardiac conditions of the adult left ventricle. We applied in silico approaches to assess the functional relevance of identified isoforms; validated isoform compositions of representative cardiac genes using reverse transcription quantitative polymerase chain reaction and targeted amplicon sequencing; and developed a web server for interactive navigation of our results. RESULTS: The data revealed that isoform heterogeneity is widespread in the cardiac cellular system, serving as a posttranscriptional buffer mechanism that calibrates the molecule reservoirs in human hearts. In healthy left ventricles, ≈30% of cell type-specific genes were polyform, using multiple isoforms tailored to cell type-specific programs. Among ubiquitously expressed genes, >300 showed differential isoform usage with cell type specificity in normal hearts. Comparisons of cardiomyocytes across conditions uncovered 379 genes with marked isoform usage shifts, most of which are predicted to change protein coding outcomes through direct changes in protein coding sequences and switches between intron retention and non-protein-coding biotypes. In contrast, cell state-specific programs tend to operate on monoform genes associated with changes among cell states. In addition, our data revealed heart failure-associated differential isoform usage events in stromal and immune cell types in the cardiac microenvironment. CONCLUSIONS: We present a comprehensive atlas of splicing isoforms in the normal adult heart and heart failure through long-read single-nucleus RNA sequencing and computational analyses. The results suggest crucial roles of isoforms in buffering core cellular programs and contributing to disease-associated cell states. The full-length details of these cell-specific isoforms serve as an important reference for downstream translational and mechanistic studies and are available on our online data portal at https://github.com/gaolabtools/heart-isoform-atlas.

Humans↗

PubMed2026

PLK1/FOXM1-associated tumor-cell state and macrophage-related immune features in endometrial cancer.

BACKGROUND: Polo-like kinase 1 (PLK1) and forkhead box M1 (FOXM1) have been widely studied in various cancers; however, their expression characteristics in endometrial cancer (EC) and their potential association with tumor microenvironment remodeling remain insufficiently characterized. METHODS: This study integrated The Cancer Genome Atlas uterine corpus endometrial carcinoma cohort, Gene Expression Omnibus, pan-cancer transcriptomic data, Human Protein Atlas/Clinical Proteomic Tumor Analysis Consortium, and local immunohistochemistry data to evaluate PLK1 expression and clinicopathological relevance across transcriptomic, proteomic, and histopathological data. Differential expression, survival, gene-set enrichment, transcription-factor enrichment, and immune-infiltration analyses characterized PLK1-associated features. In vitro experiments combined EC cell lines AN3CA and HEC-1A with co-immunoprecipitation, Western blotting, Transwell assays, and a THP-1 conditioned-medium model. Drug-response prediction and structure-based analysis prioritized candidate therapeutic hypotheses. RESULTS: PLK1 was consistently upregulated at both mRNA and protein levels in EC and was associated with higher tumor grade and International Federation of Gynecology and Obstetrics (FIGO) stage. In survival analysis, higher PLK1 expression was associated with poorer overall survival in univariable models but not after adjustment for age, tumor grade, and FIGO stage. Functional enrichment analysis showed that PLK1-associated genes were mainly involved in cell-cycle and mitotic processes. FOXM1 was identified as a potential candidate component of the PLK1-associated transcriptional program and was positively correlated with PLK1 expression and cell-cycle-related features. In vitro experiments supported an interaction between PLK1 and FOXM1 and suggested that FOXM1 Thr600 phosphorylation-related alterations were associated with migration and invasion phenotypes. Furthermore, the PLK1/FOXM1-associated tumor-cell state was linked to macrophage-related immune features and changes in the M2-like marker profile of THP-1-derived macrophage-like cells. Drug response analyses suggested differential predicted sensitivity patterns in PLK1-high tumors, providing candidate therapeutic hypotheses for further validation. CONCLUSION: The PLK1/FOXM1-associated tumor-cell state may represent a distinct molecular feature associated with proliferative activity, invasive phenotypes, and macrophage-related immune features in EC. This study provides preliminary evidence supporting the biological relevance of this molecular feature and highlights potential therapeutic directions for future investigation.

FoxM1↗

PubMed2026

Essence: A benchmarking-validated transformer framework for early diagnosis of Parkinson's disease using cerebrospinal fluid protein biomarkers.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. The lack of objective molecular biomarkers limits early diagnosis and personalized treatment. Here, we propose Essence, a benchmarking-validated framework integrating cerebrospinal fluid (CSF) proteomics with traditional and deep learning models to identify robust protein signatures for PD. Using data from two independent cohorts, 1266 high-confidence proteins are quantified, among which 178 exhibit differential abundance between PD and healthy controls (HC). Through systematic benchmarking of ten machine learning algorithms and four neural architectures, the Transformer model consistently outperforms alternatives across multiple feature selection strategies, achieving an area under the receiver operating characteristic curve (AUC) of 1.0000 with only 35 features. Functional analyses of the top-ranked 35 proteins reveal enrichment in neuroinflammatory, synaptic, and oxidative stress-related pathways. Importantly, spatial transcriptomic profiling based on the Allen Brain Atlas shows region-specific expression of these biomarkers in PD-relevant brain structures, including the striatum, subthalamic nucleus, hippocampus, and white matter tracts. This anatomical alignment supports the functional relevance of the identified markers and highlights their potential utility in early-stage diagnosis and mechanistic understanding of PD.

Benchmarking↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Journal Article↗

PubMed2024

Rare variant contribution to the heritability of coronary artery disease.

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Humans↗

PubMed2026

Long-read proteogenomic atlas of human neuronal differentiation reveals isoform diversity informing neurodevelopmental risk mechanisms.

RNA splicing shapes neuronal identity and disease risk, yet current maps lack the developmental resolution and depth to resolve this complexity. Here, we integrate deep long-read RNA sequencing and proteomics in induced pluripotent stem cell-derived cortical neurons to generate a high-resolution proteogenomic atlas of human neuron development. We identify 182,371 mRNA isoforms (over half previously unknown) and provide direct peptide evidence for the translation of hundreds of novel protein-coding sequences. Population genetics demonstrates that variants affecting novel exons and splice sites are under negative selection, underscoring the potential significance of these isoforms. During neuronal maturation, we observe that autism risk genes undergo dynamic isoform switching, including microexon inclusion and intron retention, that remodel key protein domains and regulatory regions. Furthermore, we uncover widespread, long-range coordination between alternative transcript processing events, including transcription start sites, exon splicing, and polyadenylation. Finally, our atlas enables variant reinterpretation in autism, highlighting the value of an isoform-centric view for interpreting pathogenic variation in neurodevelopment.

Humans↗

PubMed2026

Furmonertinib inhibits non-small cell lung cancer progression through ANGPT1-mediated regulation of cell migration and apoptosis.

BACKGROUND: Lung cancer remains one of the leading causes of cancer-related mortality worldwide, highlighting the urgent need for effective therapeutic agents. This study investigates the antitumor effects and underlying mechanisms of furmonertinib (FUR) in lung cancer cells. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to identify FUR target genes, followed by functional enrichment, survival, and protein-protein interaction (PPI) network analyses. Human lung cancer cell line A549 was treated with FUR and/or ANGPT1-specific siRNA. Cell migration, apoptosis, and protein expression were assessed by wound healing, flow cytometry, and Western blotting. Cellular thermal shift assay (CETSA) and drug affinity response target stability (DARTS) assays were used to assess FUR-induced stabilization of angiopoietin-1 (ANGPT1) protein. RESULTS: FUR treatment significantly inhibited cell migration and increased apoptosis in NSCLC cells. Bioinformatics analysis revealed 12 overlapping target genes of FUR from the PharmMapper and SwissTargetPrediction databases, with ANGPT1 emerging as a key candidate. ANGPT1 expression was downregulated in tumor tissues and positively correlated with patient survival. Western blotting confirmed that FUR upregulated ANGPT1 protein levels in a dose-dependent manner. Knockdown of ANGPT1 enhanced migration and suppressed apoptosis, while FUR reversed these effects. FUR treatment enhanced the stability of ANGPT1 under high-temperature conditions while reducing its sensitivity to protease. ANGPT1 may have affected tumor cell migration through cell adhesion and extracellular matrix (ECM) pathways. CONCLUSIONS: FUR suppresses lung cancer progression by upregulating ANGPT1, thereby inhibiting cell migration and promoting apoptosis. ANGPT1 is a potential therapeutic target and provides new insights into the anti-tumor mechanism of FUR in lung cancer.

Lung cancer↗

PubMed2026

Unifying multimodal single-cell data with a mixture-of-experts β-variational autoencoder framework.

Multimodal single-cell assays profile complementary layers of cell state, but integration is complicated by modality mismatch, sparsity, and uneven cohort coverage. Here, we present Unified Variational Inference (UniVI), a scalable mixture-of-experts β-variational autoencoder that learns a shared latent space while preserving modality-specific structure. UniVI couples modality-specific encoders/decoders with a shared latent prior and a symmetric cross-modal alignment objective, enabling consistent integration of paired measurements without curated feature-link graphs or preannotated reference atlases; optional supervised heads can be added when labels are available. Across paired RNA-protein (CITE-seq) and RNA-chromatin (10x Genomics Multiome, SHARE-seq) data spanning human PBMCs and mouse back skin-a nonhematopoietic tissue with continuous differentiation hierarchies-UniVI produces coherent embeddings, improves label transfer, and enables cross-modal reconstruction and denoising. Extending to trimodal measurements, UniVI maintains robust three-way alignment among RNA, chromatin accessibility, and surface proteins (TEA-seq), and accommodates DNA methylation in a paired scNMT-seq mouse gastrulation proof-of-concept under beta-binomial likelihoods. Performance degrades gracefully under severe cell type imbalance and in the presence of modality-exclusive populations. In an acute myeloid leukemia mosaic design, a paired RNA-protein bridge anchors independent RNA-only and protein+genotype cohorts, revealing genotype-associated neighborhoods that sharpen with mutation-aware fine-tuning. UniVI thus provides a flexible, interpretable framework for multimodal integration across paired, trimodal, and mosaic study designs and supports practical reference-to-query projection in partially observed studies.

Journal Article↗

PubMed2025

An RNA polymerase III tissue and tumor atlas uncovers context-specific activities linked to 3D epigenome regulatory mechanisms.

RNA polymerase III (Pol III) produces a plethora of small noncoding RNA species involved in diverse cellular processes, from transcription regulation and splicing to RNA stability, translation, and proteostasis. Though Pol III activity is broadly coupled with cellular demands for protein synthesis and growth, a more precise understanding of gene-level dynamics and context-specific expression patterns remains missing, in part due to challenges related to sequencing and mapping Pol III-derived small ncRNAs. Here, we establish a predictive multi-tissue map of human Pol III activity across 19 tissues and 23 primary cancer subtypes by comprehensively profiling the chromatin accessibility of canonical Pol III-transcribed gene classes. Our framework relies on the unique relationship between gene accessibility and Pol III transcription, inferring activity through uniform binary classification of ATAC-seq enrichment at Pol III-transcribed genes. By characterizing multi-context gene uniformity, we provide a definition of the core Pol III transcriptome, broadly active across specialized tissues, and catalog genes with varied levels of context specificity. Our genomic Pol III atlas uncovers variable levels of activity across tissues, including sharp contraction of the Pol III transcriptome in heart and brain tissues and frequent expansion across diverse cancers. We show that both tissue- and tumor-specific genes are significantly enriched within lamina-associated domains (LADs), and that aberrant expression of nuclear lamin proteins is sufficient to induce Pol III-emergent patterns at tumor-specific genes. Together, these findings link Pol III dynamics to subnuclear compartmentalization and provide a resource for better understanding Pol III expansion and small RNA biogenesis in cancer.

Journal Article↗

PubMed2026

An atlas of non-redundant sequences and structures of transcription factor assemblies across domains of life.

Transcription factors (TFs) regulate gene expression by controlling the recruitment of transcriptional machinery to regulatory regions of the genome. Nearly 10% of the human genome encodes TFs, making them one of the largest protein families. Despite their central roles in gene regulation, TFs are historically considered challenging therapeutic targets due to their complex interactions with DNA, RNA and associated proteins. Although recent progress in studying TFs both at molecular and structural level excels our understanding on their function, yet a universal rule decoding their recognition process remains elusive. Here, we present a curated non-redundant dataset of TFs with 3570 sequences and 377 structures. We further characterize "unique interfaces" by quantifying interface identity across interacting chains in TF assemblies. Surprisingly, our data shows that the "unique interfaces" have optimal size ranging from 2000 Å2 to 4000 Å2 irrespective of their quaternary assembly. To understand the functional diversity, we integrate sequence motifs, structural domains, subcellular localization and functional enrichment of TFs. We have also catalogued association of TFs with various human diseases. Our dataset provides a comprehensive platform to perform large scale analysis of TF-assemblies and aid in computational methods for their prediction across domains of life.

Gene regulation↗

PubMed2026

Reduced R-loop abundance at proinflammatory loci: a shared epigenetic mechanism in inflammatory and metabolic diseases.

INTRODUCTION: R-loops, RNA-DNA hybrid structures with a displaced single-stranded DNA loop, are key regulators of transcriptional control, chromatin architecture, and genome stability and have emerging roles in inflammatory signaling. However, the relationship between R-loop abundance and strongly modulated inflammatory effector genes in metabolic inflammation and influenza virus infection remains underexplored. METHODS: We performed a locus-centric integrative analysis combining robust differentially expressed genes (DEGs) from multiple inflammatory and infection-related murine and human transcriptomic disease models with experimentally validated multi-cell R-loop annotations from the reference atlas RLoopBase. Our correlation framework evaluated the directional relationship between R-loop abundance and inflammatory gene expression rather than assuming disease-sample-matched R-loop measurements. We further analyzed R-loop regulatory proteins, NRF2-associated R-loop regulators, and overlaps between R-loop regulators and CRISPRi-identified mitochondrial and cellular reactive oxygen species (ROS) regulators. RESULTS: In angiotensin II-infused apolipoprotein E-deficient (ApoE-/-) mice, a model of abdominal aortic aneurysm (AAA), genomic regions encoding the top significantly upregulated genes exhibited significantly fewer R-loops than those encoding downregulated genes at days 14 and 28. Similarly, in atherosclerotic ApoE-/- mice fed a high-fat diet for 32 and 78 weeks, upregulated genes were associated with fewer R-loops than downregulated genes. Reduced R-loop abundance was also observed in genomic regions encoding the top significantly upregulated genes in liver tissues from patients with non-alcoholic steatohepatitis (NASH), as well as in monosodium urate (MSU)-stimulated lymphatic endothelial cells (LECs) and influenza virus-infected human umbilical vein endothelial cells (HUVECs). R-loop regulatory proteins upregulated during metabolic inflammation were enriched in immune and inflammatory pathways. NRF2 was identified as a regulator of 27 R-loop regulatory proteins, including 10 positively and 17 negatively regulated proteins. Furthermore, 54 R-loop regulatory proteins overlapped with CRISPRi-identified mitochondrial and cellular ROS regulators, suggesting potential reciprocal regulation between R-loop homeostasis and ROS signaling. Disease-associated changes in pro-ROS and anti-ROS R-loop regulatory proteins further linked R-loop regulation to inflammatory and oxidative stress pathways. DISCUSSION: These findings identify reduced R-loop abundance at genomic regions encoding strongly upregulated inflammatory genes as a shared feature across multiple models of metabolic inflammation and influenza virus infection. The results further suggest that immune-associated R-loop regulatory proteins and the NRF2-ROS axis may contribute to R-loop remodeling during inflammatory disease. This integrative framework provides new insight into the potential role of R-loops and ROS-sensitive R-loop regulators in inflammatory and metabolic diseases and identifies candidate pathways for future mechanistic investigation and therapeutic targeting.

R-loop regulatory proteins↗

PubMed2026

A pan-cancer analysis of MEX3D in human tumors.

BACKGROUND: MEX3D, a member of the MEX3 RNA-binding protein family, has emerged as a potential regulatory molecule in cancer. However, its role across different tumor types remains largely unexplored. METHODS: We conducted a pan-cancer analysis of MEX3D using transcriptomic and proteomic data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Expression patterns, clinical correlations, survival outcomes, genetic alterations, RNA modification associations, immune infiltration, and functional enrichment were systematically evaluated. RESULTS: MEX3D was significantly dysregulated in numerous cancers at both mRNA and protein levels. Its expression correlated with tumor stage in ACC, LIHC, OV, SKCM, and THCA. Elevated MEX3D expression was associated with poor overall survival (OS) and disease-specific survival (DSS) in multiple malignancies, including ACC, LGG, LUAD, and MESO. Genetic alteration analysis revealed frequent amplifications and mutations, particularly in SARC and OV. MEX3D was positively correlated with RNA modification-related genes (m1A, m5C, m6A) and immune regulatory genes such as CD276, TGFB1, VEGFA, and ICOSLG. Additionally, MEX3D expression showed significant associations with tumor mutational burden (TMB), microsatellite instability (MSI), and cancer-associated fibroblast infiltration. Functional enrichment analyses indicated that MEX3D-related genes are involved in reproductive cellular processes, RNA binding, the Hippo signaling pathway, and microRNA-related oncogenic pathways. CONCLUSION: This pan-cancer analysis highlights the heterogeneous expression and cancer-specific prognostic significance of MEX3D. MEX3D is associated with immune infiltration, immune regulatory genes, RNA modification-related genes, TMB/MSI, and pathways involved in gene regulation and tumor progression. These findings suggest that MEX3D may participate in cancer-specific post-transcriptional and microenvironmental regulatory networks.

Biomarker↗

PubMed2026

Decoding the landscape of cell-type-specific co-expressed transcription factors in soybean.

Soybean (Glycine max) is an essential source of protein and oil with high nutritional value for human and animal consumption. To enhance our understanding of soybean biology, it is essential to have accurate information regarding the expression of each of its protein-coding genes. Here, we present Tabula Glycine max, a soybean single-cell resolution transcriptome atlas. This atlas comprises single-nucleus RNA-sequencing data from ten different G. max organs and morphological structures constituting the entire soybean plant. These nuclei are grouped into 156 different clusters based on their transcriptomic profiles. The breadth of various organs, tissues and cell types represented in Tabula Glycine max reveals that the pattern of co-expressed transcription factor genes is sufficient to define most cell types based on their function and organ of origin. Defining cell-type-specific co-expressed transcription factor genes offers a new perspective to engineer cell-type-specific programmes and enhance the biology of unique soybean cell types. This cellular resolution and breadth make the Tabula Glycine max an exceptional resource for the plant and soybean communities.

Journal Article↗

PubMed2026

Mapping cell-type- and age-dependent neuronal vulnerability through genome-wide in vivo CRISPRi screens in the mouse brain.

Current brain atlases are largely descriptive, cataloging correlative molecular snapshots such as gene expression signatures yet offering limited functional insight. Here, we develop a scalable, cell-type-resolved in vivo CRISPR interference (CRISPRi) platform enabling systematic gene function profiling in the mouse brain. Through genome-wide screens across four neuronal populations at three time points spanning youth to aging, we identify neuronal essential genes missed in vitro and define a consensus set of 269 neuronal core essential genes. The data reveal cell-type-specific genetic vulnerabilities, including divergent dependencies validated for exosome component 9 (Exosc9) and osteopetrosis-associated transmembrane protein 1 (Ostm1) between excitatory and inhibitory neurons. We uncover aging-specific dependencies enriched in mitochondrial and translational pathways, aligning with transcriptional changes in the aging human brain. Finally, we establish the CRISPRinvivo data portal as a community resource for in vivo screening. Altogether, this work provides a broadly applicable platform for in vivo functional genomics and a framework for building comprehensive gene-function brain atlases.

brain aging↗

PubMed2025

Rhythm profiling using COFE reveals multi-omic circadian rhythms in human cancers in vivo.

The study of ubiquitous circadian rhythms in human physiology requires regular measurements across time. Repeated sampling of the different internal tissues that house circadian clocks is both practically and ethically infeasible. Here, we present a novel unsupervised machine learning approach (COFE) that can use single high-throughput omics samples (without time labels) from individuals to reconstruct circadian rhythms across cohorts. COFE can simultaneously assign time labels to samples and identify rhythmic data features used for temporal reconstruction, while also detecting invalid orderings. With COFE, we discovered widespread de novo circadian gene expression rhythms in 11 different human adenocarcinomas using data from The Cancer Genome Atlas (TCGA) database. The arrangement of peak times of core clock gene expression was conserved across cancers and resembled a healthy functional clock except for the mistiming of a few key genes. Moreover, rhythms in the transcriptome were strongly associated with the cancer-relevant proteome. The rhythmic genes and proteins common to all cancers were involved in metabolism and the cell cycle. Although these rhythms were synchronized with the cell cycle in many cancers, they were uncoupled with clocks in healthy matched tissue. The targets of most of FDA-approved and potential anti-cancer drugs were rhythmic in tumor tissue with different amplitudes and peak times. These findings emphasize the utility of considering "time" in cancer therapy, and suggest a focus on clocks in healthy tissue rather than free-running clocks in cancer tissue. Our approach thus creates new opportunities to repurpose data without time labels to study circadian rhythms.

Humans↗

PubMed2025

Centromere protein I facilitates breast cancer tumorigenesis and disease progression through modulation of Wnt/β-Catenin signaling.

BACKGROUND: Breast cancer (BCa) is a major contributor to female mortality worldwide. Treatment resistance and tumor heterogeneity contribute to the lack of effective therapeutic targets, posing a significant challenge in BCa management. CENPI, a core centromere protein involved in chromosome segregation, has emerging evidence implicating it in oncogenesis across diverse malignancies. However, its functional and molecular mechanisms in BCa remain unclear. METHODS: We analyzed CENPI expression and its clinical significance by using the BCa dataset from the Cancer Genome Atlas (TCGA) and immunohistochemical staining of 3 human BCa tissue samples. Cellular functional assays and mice xenograft models were utilized to assess the effects of CENPI on BCa growth. RNA sequencing combined with bioinformatics analysis was conducted to elucidate the molecular mechanisms underlying CENPI function, with further validation through Western blotting, immunofluorescence, and TOP/FOP flash assays. RESULTS: CENPI was aberrantly overexpressed in BCa, with elevated expression levels strongly associated with disease progression and poor prognosis. Functional assays demonstrated that CENPI significantly promoted breast carcinogenesis in both cellular and animal models. Mechanistically, CENPI increased BCa progression and malignant phenotypes by modulating the Wnt/β-catenin axis. CONCLUSIONS: CENPI is a critical oncogene in BCa, driving tumorigenesis and disease progression via the Wnt/β-catenin axis, which represents a promising biomarker and therapeutic target for BCa.

Breast cancer↗