Biology subjects

Lin, P.

Publications and source records attributed to Lin, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Disease-associated NK-cell state remodeling reveals transcriptional profiles predictive of clinical phenotypes

Natural killer (NK) cells adapt their cellular states to diverse tissue and inflammatory environments, yet how this plasticity manifests across pathological contexts and relates to patient-level disease phenotypes remains poorly defined. Here we established the Human NK-cell Atlas (HNKA) from over 1 million NK cells, including samples from 1,632 donors spanning 50 diseases. Within a shared NK-cell state architecture, analyses of state abundance and matched-reference exceedance distinguished disease-biased redistribution from transcriptional displacement. Fine-grained analyses localized disease-associated remodeling to specific NK-cell states, including CD56dim NK ISG15 in infection and autoimmunity and CD56bright NK ITM2C in tumors. These patterns were accompanied by recurrent interferon responses and state-specific regulatory activity. Cytokine perturbations recapitulated key transcriptional features of disease-associated NK-cell states. We developed NKceiver, a model based on state-specific NK-cell expression profiles for patient-level prediction. It distinguished 18 diseases and predicted COVID-19 severity and response to immune checkpoint inhibitors, with predictive performance retained in unseen patients and studies. Collectively, our results reveal that disease-associated remodeling within the diverse NK-cell state repertoire resolved by HNKA is biologically interpretable and clinically informative, supporting disease discrimination and prediction of clinical phenotypes.

immunology↗

bioRxiv2026

A telomere-to-telomere genome of Holstein cattle resolves chromosome-end architecture and the genetic basis of telomere length

Telomeres safeguard chromosome-end integrity, yet population-scale dissection of telomere-length genetics has been largely restricted to humans. Here, we report a 3.01-Gb telomere-to-telomere (T2T) genome of Holstein cattle that resolves repeat-rich chromosome ends and centromeres and enables telomere-length quantification at single-chromosome-end resolution. Holstein chromosome ends show marked telomere-length asymmetry and end-specific variation in telomere variant repeats, subtelomeric tandem repeats, GC/CpG composition, and DNA methylation. Using sequencing-depth-corrected telomere-length phenotypes from 9,591 cows, teloGWAS identifies major loci encompassing RTEL1, CTC1, and TERT, while multi-tissue eQTL, sQTL, TWAS, and co-expression analyses prioritize CTC1 and implicate DNA replication, DNA repair, and stress-response networks. Together, these findings extend population-scale telomere genetics beyond humans and establish a sequence-resolved framework for chromosome-end biology and telomere-informed livestock genomics.

genomics↗

bioRxiv2026

CENO: A Genome-Scale World Model for Evolutionary Sequence Interpretation and Programmable Regulatory Design

DNA encodes biological function across a continuum of sequence scales, from single-nucleotide and motif-level grammar to regulatory neighborhoods, chromatin-scale organization and evolutionary constraint. A useful model of genomes should therefore do more than classify short sequence windows: it should maintain nucleotide-resolution state over long contexts, score counterfactual mutations, condition on homologous sequence evidence and generate candidates that can be evaluated against structural or functional objectives. We define such a system operationally as a genomic world model: a general-purpose generative model of genome sequence space that unifies sequence understanding and sequence design through a shared state and likelihood interface. Here we introduce CENO, a family of long-context generative genomic world models designed to preserve local DNA grammar while extending usable context to regulatory and chromatin scales. CENO combines Mamba sequence-mixing layers, sparse attention layers and mixture-of-experts capacity in a single autoregressive backbone, and is trained at 300M, 600M and 1B parameter scales with a staged curriculum that progresses from 8k-token cross-domain genomic pretraining to 131k- and 1M-token whole-genome long-context continuation. We evaluate CENO under a unified world-model benchmark paradigm spanning retrieval, representation, counterfactual perturbation, reconstruction, evolutionary conditioning and design. CENO retains practical long-context inference and retrieves distal sequence in synthetic assays. In zero-shot long-context analyses, without task-specific fine-tuning, long-context continuation yields annotation- and chromatin-boundary-associated attention patterns and frozen-state representations that generalize across human cell types and mouse cell or tissue settings. To incorporate evolutionary information, we further post-train CENO on packed real multiple-sequence-alignment contexts and score variants by reference-mutant likelihood deltas, improving matched variant-effect prediction and producing evolutionary enrichment signals across species. Complementing these perturbation-based variant tests, we evaluate zero-shot long-sequence generation by partial-gene continuation, asking whether the model can recover withheld gene-scale sequence structure across eukaryotic, bacterial and archaeal species; recovery improves with model scale and later whole-genome long-context training. Finally, we use CENO as the backbone for a cell-type-specific enhancer design workflow in mouse cortex, coupling a CENO-based accessibility oracle with conditional supervised fine-tuning and oracle-guided reinforcement learning. Together, CENO provides a genome-scale sequence world-model framework for sequence interpretation, evolutionary reasoning, gene-scale reconstruction and programmable regulatory sequence generation.

genomics↗

bioRxiv2026

Light-dependent and predator inducible aldehyde synthesis in Prochlorococcus for specific defense against Uronema

Cyanobacteria as a primary producer provide energy and carbon sources for the marine food web, of which predation-interactions play central roles in regulating global element cycles and marine ecosystem stability. Here, we report the anti-predation activity of a typical marine cyanobacterium Prochlorococcus MED4 to defend the predation by Uronema marinum. MED4 synthesize formaldehyde as the anti-predation chemical, of which the synthesis was light-dependent and predator-inducible. Compared to other protists, both the higher concentration of accumulated formaldehyde in U. marinum and the lower formaldehyde tolerance of U. marinum resulted in the specific anti-predation of MED4 against U. marinum. This specific anti-predation could regulate the cyanobacterial growth and the U. marinum infection of marine fishes. Metadata analyses showed the mutually exclusion of Prochlorococcus and Uronema in global marine environments. These findings significantly advance our understanding of the marine food web and biogeochemical cycles. Significance StatementPredation-driven interactions in the ocean are critical regulators of global biogeochemical cycles, yet active defense mechanisms in marine picophytoplankton remain largely unknown. This study reveals that Prochlorococcus MED4 as the most abundant primary producer in the ocean synthesize light-driven and predator-inducible aldehydes to actively and specifically defend predation against the ciliate Uronema marinum. The anti-predation of Prochlorococcus against Uronema could have broad implications in biocontrol of Uronema infection in marine fishes and regulation of the marine food web.

microbiology↗

bioRxiv2026

Metabolic Reprogramming Coordinates Mannose and Glutamine Metabolism to Maintain Glucose Homeostasis During Glycosuria

Glycosuria, whether genetically induced or triggered by SGLT2 inhibitors, activates compensatory glucose-producing pathways that limit glucose lowering in type 2 diabetes. To define these pathways, we studied renal Glut2 knockout mice, which progressively lose Slc5a2 (encoding SGLT2) expression yet maintain normoglycemia despite marked urinary glucose loss. Metabolic profiling and isotope tracing revealed coordinated adaptations in mannose and glutamine metabolism during glycosuria. Skeletal muscle reduced glucose utilization and instead oxidized mannose, while whole-body glycolysis declined, establishing a systemic glucose-sparing state. Disruption of glutamine transport or mannose utilization caused hypoglycemia in mice treated with an SGLT2 inhibitor, demonstrating dependence on these substrates to maintain glucose homeostasis during glycosuria. Multiomic profiling revealed increased expression and chromatin accessibility of mannose and glutamine transport pathways. These findings identify a kidney-driven metabolic program that preserves systemic glucose homeostasis during glycosuria and may inform strategies to optimize the glucose-lowering efficacy of SGLT2 inhibitors.

physiology↗

bioRxiv2026

GABA antagonises ABA perception and signalling in plants

Abscisic acid (ABA) is a central regulator of plant growth and stress responses. However, it also negatively impact germination, growth, and reproductive performance, highlighting the need for mechanisms that fine-tune its signalling. Here, we identify {gamma}-aminobutyric acid (GABA) as an endogenous antagonist of plant ABA receptor. We show that GABA binds the clade A protein phosphatase-ABI1, disrupting its association with the ABA receptor PYL1, blocking ABA binding, thereby attenuating ABA signalling. GABA modulates ABA-control of stomatal aperture and seed germination, demonstrating its broad physiological influence. Notably, GABA accumulation during stress coincides with the subsequent decline in ABA, consistent with a delayed feedback signal of ABA activity. Together, this work identifies GABA as an antagonist of ABA and provides a mechanism balancing plant stress resilience and growth.

plant biology↗

bioRxiv2026

EmbryoTempoFormer: clip-based developmental tempo inference from zebrafish brightfield time-lapse microscopy

Nominal hours post fertilization (hpf) are widely used to index zebrafish embryogenesis, yet under condition shifts--such as temperature change, genetic perturbation, or environmental stress--nominal time can decouple from true developmental progression. In such settings, biologically meaningful variation is better described as a systematic change in developmental tempo rather than a simple temporal offset. Here we introduce an embryo-resolved framework that treats developmental tempo as the primary quantity of interest in brightfield time-lapse imaging. We present EmbryoTempoFormer (ETF), a clip-based CNN-Transformer that predicts developmental progression from short time-lapse clips and is trained with a within-embryo temporal-difference consistency regularizer to promote temporally coherent trajectories. Crucially, we couple model predictions with an embryo-level inference and statistical workflow: temporally correlated clip-level outputs are aggregated into interpretable embryo-level tempo and stability readouts, and cross-condition effects are quantified using embryo-bootstrap confidence intervals with embryos--rather than frames or clips--as independent units, avoiding pseudo-replication. Using temperature perturbation as a representative domain shift, we robustly quantify condition-induced changes in global developmental dynamics and show that developmental delay predominantly manifests as reduced developmental tempo. This framework enables statistically principled, high-throughput phenotyping for perturbation screens, drug assays, and environmental stress studies. HIGHLIGHTSO_LIClip-based CNN-Transformer predicts developmental time from brightfield time-lapse microscopy. C_LIO_LIWithin-embryo temporal-difference consistency improves trajectory self-consistency. C_LIO_LIEmbryo-level anchored tempo slopes enable interpretable cross-condition comparisons. C_LIO_LIReproducible pipeline via code, scripts, and a Zenodo bundle with embryo-level inference C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/710433v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@ddbf01org.highwire.dtl.DTLVardef@26e975org.highwire.dtl.DTLVardef@a911d7org.highwire.dtl.DTLVardef@1d24f1b_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2026

Aging under immunosuppression reshapes human immune compartments and lowers clinical alloreactivity after heart transplantation

Solid-organ transplantation in aging recipients represents a unique opportunity to study how age-related immunity in the context of non-specific immunosuppression strategies balances infection, malignancy, and rejection. Heart transplantation is an exemplar platform, as routine endomyocardial biopsy for rejection surveillance is the clinical "gold standard" regardless of clinical status. Here, we undertook the largest granular study to date to characterize the association between increasing recipient age at heart transplantation with acute allograft rejection and age-related cell-specific transcriptomic changes in circulating immune cells. This single-center retrospective cohort study evaluated individuals undergoing heart transplantation between July 2013 and December 2023 at Vanderbilt University Medical Center. Eligible participants were aged [≥]18 years. A subset of individuals underwent single-cell RNA-sequencing of circulating immune cells. Among 799 adults, each one standard deviation increase in recipient age was associated with a [~]17% lower odds of allograft rejection (adjusted OR 0.83, 95% CI 0.71-0.98). In 40 individuals who underwent single-cell RNA-sequencing of circulating immune cells, increasing recipient age was associated with increases in CD4+ and CD8+ memory T cell subsets, monocytes, and NK cells. Furthermore, genes upregulated with increasing recipient age were associated with enrichment for pathways involved in immunosenescence and chronic low-grade inflammation while downregulated genes suggested decreased protein synthesis. These findings have clinical implications for an aging transplant population and support a more personalized approach to immunosuppression.

systems biology↗

bioRxiv2026

Harnessing Tumor-Specific Transcript Diversity Uncovers a Shared Neoantigen Reservoir for Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is refractory to immunotherapy due to its immunologically cold microenvironment and the scarcity of mutation-derived neoantigens. Here, we introduce NeoAPP, a computational tool designed to systematically decode neoantigens arising from tumor-specific transcripts (TSTs) generated by transcriptional dysregulation. Multi-cohort transcriptomic profiling of 413 PDAC samples using NeoAPP reveal a median of 351 neoantigens per sample derived from 56 neoantigen-encoding TSTs (neoTSTs), surpassing mutation-derived counterparts in both abundance and patient coverage. Mechanistic analyses show that non-canonical splicing junction and transposable element activation drive neoantigen generation, while FOXA2-regulated promoter usage constitutes a potential major source of neoTSTs. Tumor-derived neoTSTs are also detected in extracellular vesicles and cancer-associated fibroblasts, implicating stromal crosstalk in immune modulation. Vaccination with neoTSTs induce CD8+ T cell responses in HLA-A*02:01/A*11:01 transgenic mice and suppressed tumor growth in syngeneic PDAC models. Collectively, this work establishes TST-derived neoantigens as a dominant and therapeutically actionable antigen reservoir in PDAC, advancing a transcriptome-guided framework for neoantigen discovery with potential to overcome immune resistance in low-mutation cancers. Abstract Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/705024v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@82ff31org.highwire.dtl.DTLVardef@401342org.highwire.dtl.DTLVardef@b0771corg.highwire.dtl.DTLVardef@15c03ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

Serpin-Driven Green Camouflage and NIR Fluorescence in Frogs

Animals have evolved multiple strategies to generate optical traits and coloration. While most amphibians rely on a three-dimensional arrangement of chromatophores in the skin, hundreds of arboreal frog species achieve leaf-like green color through a different mechanism involving reduced pigmentation, subcutaneous biological mirrors, and high concentrations of the blood-derived pigment biliverdin. Although biliverdin is rapidly excreted in most vertebrates, hylid and centrolenid frogs can retain it through the binding to a serpin-family protein (BBS). Here we show that BBSs bind biliverdin with high affinity (Kd < 10 nM), comparable to hormone-receptor interactions. This interaction alters biliverdins spectral signature in ways that resemble those of green-leaf pigments. BBSs from different species exhibit distinct biophysical properties, accounting for interspecific differences in color saturation and hue. Unlike most serpins in vivo, BBS of the glassfrog Teratohyla pulverata is naturally cleaved, yielding a highly thermostable, thermodynamically favored protein, without loss of affinity. Using custom-designed hyperspectral photoacoustic tomography (PAT), we demonstrate that BBS is widely distributed throughout the body, contributing to whole-body color and camouflage. Furthermore, we show that BBSs emit near-infrared (NIR) fluorescence (>700 nm) rendering these frogs fluorescent in a spectral region where biological tissues are largely transparent. Together, BBSs shed light on serpin evolution, protein thermostability, amphibian color diversity, and the development of NIR molecular probes.

biochemistry↗

bioRxiv2026

Decomposing multi-scale dynamic regulation from single-cell multiomics with scMagnify

Deciphering the highly coupled regulatory circuits that drive cellular dynamics remains a fundamental goal in biology. However, capturing the multi-scale time-lagged dynamics and combinatorial regulatory logic of gene regulation remains computationally challenging. Here we present scMagnify, a deep-learning-based framework that leverages multiomic single-cell assays of chromatin accessibility and gene expression via nonlinear Granger causality to reconstruct and decompose multi-scale gene regulatory networks (GRNs). Benchmarking on both simulated and real datasets demonstrates that scMagnify achieves superior performance. scMagnify employs tensor decomposition to systematically identify combinatorial TF modules and their activation profiles across different time-lags. It enables a hierarchical dissection of the regulatory landscape-- from the activity of individual regulator to the combinatorial logic of regulatory modules and intercellular communications. We applied scMagnify to human hematopoiesis and mouse pancreas development, where it successfully recovered known lineage-driving regulators and provided novel insights into the combinatorial logic that governs cell fate decisions. Furthermore, in the context of kidney injury, scMagnifys intracellular communication module mapped key signaling-to-transcription cascades linking microenvironment cues to pathological epithelial cell changes. In summary, scMagnify provides a powerful and versatile computational framework for dissecting the multi-scale regulatory logic that governs complex biological processes in development and disease.

bioinformatics↗

bioRxiv2026

SPCoral: diagonal integration of spatial multi-omics across diverse modalities and technologies

Spatial multi-omics is indispensable for decoding the comprehensive molecular landscape of biological systems. However, the integration of multi-omics remains largely unresolved due to inherent disparities in molecular features, spatial morphology, and resolution. Here we developed SPCoral for diagonal integration of spatial multiomics across adjacent slices. SPCoral extracts spatial covariation patterns via graph attention networks, followed by the use of optimal transport to identify high-confidence anchors in an unsupervised, feature-independent manner. SPCoral utilizes a crossmodality attention network to enable seamless cross-resolution feature integration alongside robust cross-omics prediction. Comprehensive benchmarking demonstrates SPCorals superior performance across different technologies, modalities and varied resolutions. The integrated multi-omics representation further improves spatial domain identification, effectively augments experimental data, enables cross-modal association analysis, and facilitates cell-cell communication. SPCoral exhibits good scalability with data size, reveals biological insights that are not attainable using a single modality. In summary, SPCoral offers a powerful framework for spatial multi-omics integration across various technologies and biological scenarios.

bioinformatics↗

bioRxiv2025

Decoding Neoantigen-encoding Tumor-Specific Transcripts Unveils a Shared Target Reservoir for Immunotherapy in Hepatocellular Carcinoma

Background and AimsPrimary liver cancer, predominantly hepatocellular carcinoma (HCC), has limited therapeutic options. While mutation-derived neoantigen vaccine holds promise, its success is hindered by low antigen availability. This study explores transcriptome-derived neoantigens (neoantigen-encoding tumor-specific transcripts, neoTSTs) in HCC, characterizing their features, generation mechanisms, and therapeutic potential. Approach and ResultsWe analyzed RNA-seq data from 1,013 liver cancer patients and constructed a multi-layered reference dataset. Using a customized pipeline, we identified an average of 60 neoTSTs per patient, significantly surpassing mutation-derived neoantigens (neoMuts). NeoTSTs exhibited higher population frequencies, with 73.1% providing multiple epitopes, and were validated through mass spectrometry and HLA transgenic mouse models. Mechanistically, neoTSTs were generated via retained introns, transposable element activation, HNF4A-regulated alternative promoters, and de novo transmembrane domain (TMD) generation. Single-cell analysis revealed neoTSTs cover >75% of tumor cells and identified antigen-presenting cancer-associated fibroblasts (apCAFs) that enriched in immunotherapy responders and amplified CD4 T-cell responses via MHC-II presentation. In murine HCC models, neoTST vaccination outperformed neoMuts, inducing dual MHC-I/II activation and significant tumor growth inhibition. ConclusionsNeoTSTs represent a superior neoantigen source in HCC, compensating for the limitations of mutation-derived targets. Their abundance, sharedness, and dual MHC pathway activation highlight their potential for personalized immunotherapy, particularly in low-TMB tumors. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/692877v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1bedfedorg.highwire.dtl.DTLVardef@5f6c95org.highwire.dtl.DTLVardef@d1deb5org.highwire.dtl.DTLVardef@743e85_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Engineering Linear Cap-independent mRNA Vaccines with Intrinsic Adjuvanticity for Potent Cancer Immunotherapy

mRNA cancer vaccines have shown promising efficacy in early-phase clinical trials, but existing platforms struggle to boost antitumor efficacy without added cost or complexity. Here, we present a streamlined linear cap-independent RNA (LciRNA) cancer vaccine platform that achieves stable expression in vivo without 5 capping or ribonucleotide modification, and innately stimulates immune responses to enhance antitumor immunity. By fusing a UPA protective sequence, composed of a viral exoribonuclease-resistant RNA (xrRNA) and a poly(A) binding protein (PABP) motif, with an optimized Enterovirus A internal ribosome entry site, LciRNA resists 5 exonuclease decay and drives superior in vivo expression. Mechanistically, UPA sequence not only impedes exonuclease-mediated decay but also recruits RNA-binding proteins to stabilize LciRNA. Moreover, LciRNA robustly activates dendritic cell pattern-recognition receptor pathways, promotes dendritic cell maturation, and upregulates proinflammatory signals. In murine melanoma and HPV-associated tumor models, it elicits strong systemic and intra-tumoral T cell responses and superior tumor control, demonstrating how immune stimulation-translation synergy underpins its efficacy. This work establishes a next-generation cost-effective mRNA cancer vaccine platform with simplified production and enhanced efficacy, highlighting immuno-translation coupling as a paradigm for future mRNA cancer vaccines.

bioengineering↗

bioRxiv2025

The biosynthetic gene cluster landscape of the oral microbiome across health and dental caries

Specialized metabolites encoded by biosynthetic gene clusters (BGCs) in the oral microbiome remain largely unexplored in the context of oral health and disease. Previous genome-centric surveys have cataloged hundreds of uncharacterized BGCs in the oral cavity associated with health and disease, but these studies relied on reference genomes and did not capture strain-level variation or the native distribution of BGCs. Here, we assembled three independently sourced metagenomic datasets from healthy and dental caries samples, extracted BGCs, and quantified their abundance alongside expression in a metatranscriptomic dataset. We first identified that aryl polyene, ribosomally synthesized and post-translationally modified peptide (RiPP), and nonribosomal peptide (NRP) encoding BGCs were the most abundant BGC classes across all three metagenomic datasets. We then grouped these BGCs into homology-based families and found that homologous clusters were usually consistently associated with either health or dental caries, suggesting conserved community-level roles for BGCs. An elastic-net regression model further selected 45 BGCs out of >5000 that could distinguish healthy and dental caries samples in the metatranscriptomic dataset, which demonstrated that BGCs could be predictive markers of disease. This analysis emphasizes the importance of high-quality metagenomic and metatranscriptomic datasets to resolve BGC expression patterns and to guide discovery of metabolites relevant to oral health and disease.

bioinformatics↗

bioRxiv2025

CHD1 is a synthetic lethal vulnerability in MYC-driven breast cancer

The MYC transcription factor is a key regulator of growth during development and a potent cancer driver when its expression is dysregulated. Strategies to inhibit MYC oncogenic activity would mark a significant advance, but decades of efforts to target MYC directly have not been fruitful. Understanding how MYC drives transformation and tumor growth may provide new therapeutic avenues in a variety of cancers. By intersecting two independent genome-wide screens, we identified loss of the chromatin remodeler Chromodomain-Helicase DNA-binding 1 (CHD1) as a potential synthetic lethal target in MYC-driven breast cancer. Knockdown of CHD1 in a xenograft model of MYC-driven breast cancer suppresses tumor growth in vivo. In tissue culture models, we found that knockdown of CHD1 suppresses cell proliferation and induces cell death, specifically when MYC is overexpressed. Mechanistically, we found that CHD1 is required to maintain an open chromatin landscape and a transcriptional program associated with cancer progression in MYC overexpressing breast cells. Follow-up experiments indicate that this synthetic lethality may arise from nucleolar stress and p53 activation. These findings provide new insights on the chromatin-level regulation of MYC-driven breast cancer and uncover CHD1 as a novel synthetic vulnerability and potential therapeutic target.

cancer biology↗

bioRxiv2025

PLK1-mediated phosphorylation of PHGDH reprograms serine metabolism in advanced prostate cancer

Metabolic reprogramming is a hallmark of cancer, enabling tumor cells to meet their increased biosynthetic and energetic demands. While cells possess the capacity for de novo serine biosynthesis, most transformed cancer cells heavily depend on exogenous serine uptake to sustain their growth, yet the regulatory mechanisms driving this metabolic dependency remain poorly understood. Here, we uncover a novel mechanism by which Polo-like kinase 1 (PLK1), often overexpressed in prostate cancer, orchestrates a metabolic shift in serine and lipid metabolism through the phosphorylation of phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme of the serine synthesis pathway (SSP). We demonstrate that PLK1 phosphorylates PHGDH at three specific sites (S512, S513, S517), leading to a marked reduction in its protein level and enzymatic activity. This downregulation of SSP forces cancer cells to increase their reliance on exogenous serine uptake via the ASCT2 transporter, which, in turn, fuels the biosynthesis of lipids, including sphingolipids essential for tumor growth and survival. Targeting the SSP, serine uptake, or downstream lipid biosynthetic pathways may offer promising therapeutic avenues in PLK1-high advanced cancers.

cancer biology↗

bioRxiv2025

Transcriptomic splicing analysis reveals a gene-independent form of TE reactivation in tumors representing unrecognized source of oncogenes and neoantigens

Transposable elements (TEs) are reactivated in tumors and serve as significant contributors to tumor transcriptomic complexity and heterogeneity. However, their repetitive nature and diverse transcriptional forms have hindered efforts to characterize TE-derived transcripts independent of host gene contexts. Here, using our self-developed splicing-junction analysis tool ASJA, we systematically interrogated TE transcription across 32 cancer types, identifying transcripts autonomously initiated from and exclusively spliced among TEs with high TE content, termed TEtrans. Our analysis revealed 5,361 TEtrans exhibiting pan-cancer prevalence, tumor-specific expression and features of mature transcripts, including canonical splicing, 5 caps and polyA tails. Mostly unannotated and enriched in intergenic regions, TEtrans are predominantly derived from primate-specific classes with conserved splice pattern. TEtrans burden demonstrates heterogeneous associations with prognosis and immune activity across cancers, while their expression can be epigenetically dual-regulated by stemness- and inflammation-associated transcription factors. Functional studies uncovered that TEtrans could act as oncogenes, exemplified by tsTE1, a HERVH-derived transcript that promotes colorectal cancer proliferation by enhancing TOP1-mediated DNA supercoil relaxation. Remarkably, [~]7.2% of TEtrans are identified to encode tumor neoantigens, including viral proteins and unannotated peptides, which are shared among patients and validated by proteogenomic analysis. These TEtrans-derived neoantigens are immunogenic both in vitro and in vivo, and exceed neoepitopes from genomic alterations in abundance per tumor, particularly in cancers with low mutational burden. Collectively, as a gene-independent form of TE-derived transcripts, TEtrans represents a unique source of oncogenes and tumor neoantigens, expanding the functional repertoire of TEs in cancer biology and offering new avenues for therapeutic targeting. HighlightsO_LITEtrans are tumor-specific transcripts with conserved splicing patterns, predominantly derived from primate TEs in intergenic regions. C_LIO_LITEtrans expression is epigenetically activated and dually regulated by stemness/inflammation transcription factors. C_LIO_LITEtrans function as oncogenes, exemplified by tsTE1 enhancing TOP1-mediated DNA relaxation. C_LIO_LITEtrans encode tumor neoantigens that elicit CD8+ T cell responses, providing targets for immunotherapy, especially in low-mutation tumors. C_LI Abstract figure O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/640928v1_ufig1.gif" ALT="Figure 1"> View larger version (78K): org.highwire.dtl.DTLVardef@1d2d4cforg.highwire.dtl.DTLVardef@918f14org.highwire.dtl.DTLVardef@489465org.highwire.dtl.DTLVardef@1069d17_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗