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Lee, E. A.

Publications and source records attributed to Lee, E. A..

At least 19 recordsLinked to original sources

Hybrid transcriptome assembly and annotation of Japanese macaque prefrontal cortex

Japanese macaque (Macaca fuscata) is used in biomedical and neurobiology research, yet transcriptomic resources for the brain are limited. We present a hybrid RNA sequencing dataset and a prefrontal cortex transcriptome assembly from two healthy 6-year-old animals. Short-read Illumina ({approx}70 million paired-end reads per sample) and long-read Oxford Nanopore direct RNA sequencing ({approx}2.5 million reads per sample) were combined. Reads were quality controlled, aligned to the macFus_1.0 reference genome, and assembled with StringTie2. Transcripts were annotated using Trinotate and eggNOG-mapper, and open reading frames were predicted with TransDecoder. The released data package includes raw reads (NCBI SRA BioProject PRJNA1295993), transcript sequences and structural annotation files, predicted coding sequences and proteins, functional annotation tables, and transcript abundance estimates (TPM). Technical validation includes read-level QC and protein-level comparisons to expressed gene sets from human, rhesus macaque and chimpanzee prefrontal cortex. These resources enable reuse for transcript-level expression studies, isoform characterization and comparative primate neurogenomics.

neuroscience↗

Inhibition of IL-6 signaling with tocilizumab improves stroke outcomes in aged mice but requires sex-specific dosing

Post-stroke inflammation contributes to poor outcomes in both clinical and experimental studies. Interleukin-6 (IL-6) is a key inflammatory mediator in ischemic stroke, and higher circulating IL-6 levels are associated with greater stroke severity and worse clinical outcomes. Targeting IL-6 signaling therefore represents a potential therapeutic strategy. We tested whether inhibition of IL-6 signaling with the IL-6 receptor (IL-6R) blocking antibody tocilizumab (TCZ) improves recovery after experimental stroke. Aged mice (18-20 months) underwent 60 minutes of middle cerebral artery occlusion. TCZ (20 mg/kg) was administered 5 hours after ischemia onset, and behavioral outcomes were assessed weekly for 5 weeks. Delayed TCZ treatment improved long-term functional recovery in aged male mice but not in aged females. To explore this difference, we measured circulating soluble IL-6R (sIL-6R) levels in mice and patients with ischemic stroke. Females exhibited significantly higher post-stroke sIL-6R levels. Increasing the TCZ dose to 100 mg/kg restored efficacy in aged female mice and improved long-term outcomes. These findings support a role for IL-6R pathway modulation in improving recovery after experimental stroke and suggest that therapeutic response may differ by sex and target availability, potentially related to differences in circulating sIL-6R after ischemic injury.

neuroscience↗

Multi-platform framework for mapping somatic retrotransposition in human tissues

Mobile element insertions (MEI) shape the human genome in both germline and somatic tissues. While inherited MEIs are well characterized, mapping somatic MEIs (sMEI) in non-cancer tissues remains challenging due to their low allelic fraction and repetitive nature. We established an integrative framework for sMEI analysis leveraging modern sequencing technologies and analytical innovations. We first benchmarked sMEI detection and demonstrated advantages of long-read and MEI-targeted sequencing for ultra-low-frequency events using a mixture of well-established cell lines. We then showed that haplotype phasing and donor-specific assemblies refine sMEI detection, effectively distinguishing from germline and false signals in in-silico tumor-normal mixtures. We further developed a source-tracing strategy based on internal sequence variation, expanding the catalogue of active source elements beyond traditional transduction-based methods. Applying this framework to donor tissues, we identified 18 rare somatic L1 insertions, revealing structural and source diversity. Our work provides a foundational framework and biological insight into sMEIs.

genomics↗

VEGFR2 blockade overcomes acquired KRAS G12D inhibitor resistance driven by PI3Kγ activation

KRAS G12D mutation is a key oncogenic driver in many solid tumors, including pancreatic, gastric, and colorectal cancers. While recent studies have characterized features associated with primary and acquired resistance to KRAS inhibitors, strategies to overcome such resistance, particularly in the context of gastrointestinal cancers, remain underexplored. Here, we have generated nine human gastrointestinal cancer models, including three patient-derived organoids (PDOs), with acquired resistance to the KRAS G12D-selective inhibitor MRTX1133. Using single-cell RNA sequencing analysis, we identified the enrichment of angiogenesis, hypoxia, and epithelial-to-mesenchymal transition (EMT) signatures in the resistant model compared to the parental PDO. Across all resistant models, VEGFA expression and VEGFR2 phosphorylation were uniformly elevated, which were driven by AKT activation and SP1 nuclear translocation. Mechanistic investigations uncovered increased PI3K{gamma} activity in MRTX1133-resistant models via complex formation of KRAS with p110{gamma} and p101. This leads to an autocrine VEGFA-VEGFR2 signaling loop formation and EMT induction. Therapeutically, the disruption of VEGFA-VEGFR2 signaling restored MRTX1133 sensitivity and inhibited EMT. Furthermore, cancer-endothelial paracrine signaling amplified angiogenesis, hypoxia, and EMT signatures in cancer cells and simultaneously promoted endothelial cell proliferation, reinforcing an adaptive feedback mechanism. In a mouse model of MRTX1133-resistant tumor xenograft, a combination of anti-VEGFR2 therapy and MRTX1133 more effectively reduced tumor growth, angiogenesis, and proliferation markers than monotherapy without significant body weight change. These findings establish VEGFA-VEGFR2 signaling by PI3K{gamma} activation as a key driver of acquired resistance to KRAS G12D inhibition and provide a rationale for combining VEGFA-VEGFR2 inhibition with KRAS blockade in KRAS-mutant cancers. HighlightO_LIVEGFA-VEGFR2 signaling activation is a common feature of MRTX1133 resistance in KRASG12D cancer cells C_LIO_LINuclear translocation of SP1 by AKT activation promotes VEGFA transcription in MRTX1133-resistant models C_LIO_LIInteraction of p110{gamma}-p101 with KRAS activates PI3K{gamma} in the resistant models C_LIO_LIVEGFA-VEGFR2 inhibition reverses MRTX1133 resistance in vitro and in vivo C_LI

cancer biology↗

STRUMP-I: Structure-based machine learning approach to pMHC-I binding prediction using force field energy features

The adaptive immune system monitors cellular integrity by recognizing short peptides from intracellular proteins presented on Major Histocompatibility Complex class I (MHC-I) molecules, collectively termed peptide-MHC complexes (pMHC), enabling detection of foreign or mutated proteins. With the rising importance of immunotherapies targeting neoantigens in cancers, the ability to accurately predict which peptides will bind to the diverse population of MHC alleles is critically important. Current computational methods for pMHC-I prediction fall broadly into sequence-based methods, which rely heavily on large training datasets, and structure-based methods that leverage structural modeling and energetics of pMHC binding. While sequence-based methods have been popularly used, their performance is dependent on the size and quality of training data. On the other hands, while structure-based approaches can generalize better across diverse MHC alleles, they traditionally depend on identifying a single global minimum energy conformation, an assumption that often fails due to the inherent binding promiscuity of MHC-I molecules. To address these limitations, we developed a STRUMP-I (STRUcture-based pMHC Prediction (for class I)), a novel pMHC binding prediction tool that directly leverages a broad set of force-field-derived energy terms as machine-learning features. STRUMP-I achieves performance comparable to state-of-the-art sequence-based models while significantly outperforming them on MHC alleles with limited representation in training data. Furthermore, STRUMP-I demonstrates strong synergy when integrated with sequence-based methods, notably enhancing prediction precision. The robustness and generalizability of STRUMP-I were confirmed by evaluating its predictive performance on independent, previously unseen datasets, including an experimentally validated cancer neoantigen dataset. This combined approach advances our capability to reliably identify clinically relevant neoantigen targets. The source code and trained models are available at https://github.com/yoonjoolab/STRUMP-I

bioinformatics↗

Cell-type-specific patterns and consequences of somatic mutation in development and aging brain

Elucidating the role of somatic mutations in cancer, healthy tissues, and aging depends on methods that can accurately characterize somatic mosaicism across different cell types, as well as assay their impact on cellular function. Current technologies to study cell-type-specific somatic mutations within tissues are low-throughput. We developed Duplex-Multiome, incorporating duplex consensus sequencing to accurately identify somatic single-nucleotide variants (sSNV) from the same nucleus simultaneously analyzed for single-nucleus ATAC-seq (snATAC-seq) and RNA-seq (snRNA-seq). By introducing strand-tagging into the construction of snATAC-seq libraries, duplex sequencing reduces sequencing error by >10,000-fold while eliminating artifactual mutational signatures. When applied to 98%/2% mixed cell lines, Duplex-Multiome identified sSNVs present in 2% of cells with 92% precision and accurately captured known sSNV mutational spectra, while revealing unexpected subclonal lineages. Duplex-Multiome of > 51,400 nuclei from postmortem brain tissue captured sSNV burdens and spectra across all major brain cell types and subtypes, including those difficult to assay by single-cell whole-genome sequencing (scWGS). This revealed for the first time that diverse neuronal and glial cell types show distinct rates and patterns of age-related mutation, while also directly discovering developmental cell lineage relationships. Duplex-Multiome identified clonal sSNVs occurring at increased rates in glia of certain aged brains, as well as clonal sSNVs that correlated with changes in expression of nearby genes, in both neurotypical and autism spectrum disorder (ASD) individuals, directly demonstrating that somatic mutagenesis can contribute to gene expression phenotypes. Duplex-Multiome can be easily adopted into the 10X Multiome protocol and will bridge somatic mosaicism to a wide range of phenotypic readouts across cell types and tissues.

genomics↗

Clonal Hematopoiesis Mutations Increase Risk of Alzheimer's Disease with APOE ϵ3/ϵ3 Genotype

Clonal hematopoiesis of indeterminate potential (CHIP) represents clonal expansion of blood cells, and increases the risk of hematological malignancies and cardiovascular disorders. Recent studies have studied CHIP mutations in individuals with Alzheimers disease (AD), but it is unclear whether their role in AD pathogenesis is protective, detrimental, or neutral. In this study, we used molecular-barcoded deep gene panel sequencing ([~]400X) to examine CHIP mutations in 298 blood samples from AD and neurotypical individuals 60 years and older. The AD patients exhibited a significantly higher burden of CHIP mutations compared to the age-matched controls (p < 2e-7, odds ratio (OR) = 2.89), particularly in low-frequency variants often not captured by standard whole exome or whole genome sequencing (WGS). This increase was driven by individuals with the APOE {varepsilon}3/{varepsilon}3 genotype and absent in {varepsilon}4 carriers. Analysis of an independent dataset from the Alzheimers Disease Sequencing Project (ADSP), comprised of WGS data from [~]30,000 individuals, confirmed increased CHIP mutations in AD versus control (p < 0.02, OR = 1.32), again driven by individuals with APOE {varepsilon}3/{varepsilon}3 genotype. CHIP mutations in AD patients also showed stronger positive selection than in controls. Our results indicate that AD patients show significantly more CHIP mutations in their blood than controls, involving more than one third of AD patients, and contributing to AD risk through a mechanism independent of APOE {varepsilon}4.

genetics↗

Inverted Alu repeats in loop-out exon skipping across hominoid evolution

BackgroundChanges in RNA splicing over the course of evolution have profoundly diversified the functional landscape of the human genome. While DNA sequences proximal to intron-exon junctions are known to be critical for RNA splicing, the impact of distal intronic sequences remains underexplored. Emerging evidence suggests that inverted pairs of intronic Alu elements can promote exon skipping by forming RNA stem-loop structures. However, their prevalence and influence throughout evolution remain unknown. ResultsHere, we present a systematic analysis of inverted Alu pairs across the human genome to assess their impact on exon skipping through predicted RNA stem-loop formation and their relevance to hominoid evolution. We found that inverted Alu pairs, particularly pairs of AluY-AluSx1 and AluSz-AluSx, are enriched in the flanking regions of skippable exons genome-wide and are predicted to form stable stem-loop structures. Exons defined by weak 3' acceptor and strong 5' donor splice sites appear especially prone to this skipping mechanism. Through comparative genome analysis across nine primate species, we identified 67,126 hominoid-specific Alu insertions, primarily from AluY and AluS subfamilies, which form inverted pairs enriched across skippable exons in genes of ubiquitination-related pathways. Experimental validation of exon skipping among several hominoid-specific inverted Alu pairs further reinforced their potential evolutionary significance. ConclusionThis work extends our current knowledge of the roles of RNA secondary structure formed by inverted Alu pairs and details a newly emerging mechanism through which transposable elements have contributed to genomic innovation across hominoid evolution at the transcriptomic level.

genomics↗

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

Amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimers disease (AD) represent two major categories of neurodegenerative disorders--TDP-43 and tau proteinopathies--for which the mechanisms driving neuronal death remain unclear. Single-cell whole-genome sequencing of 469 neurons from C9ORF72 ALS, C9ORF72 FTD, AD, and control brains revealed increased somatic single nucleotide variants (sSNVs) and insertions/deletions (sIndels) in all three diseases. Mutational signature analysis identified a disease-associated sSNV signature consistent with oxidative damage and an sIndel process affecting 22% of ALS, 76% of FTD, and 61% of AD neurons--but only 2% of control neurons--resembling signature ID4, previously linked to topoisomerase 1 (TOP1)-mediated mutagenesis. Rapid Approach to DNA Adduct Recovery (RADAR) assays confirmed increased TOP1-DNA covalent complexes and duplex sequencing confirmed the increased sIndels and identified single-strand events as likely precursor lesions. TOP1-associated sIndel mutagenesis and genome instability thus represents a mechanism shared by both TDP-43 and tau neurodegeneration.

genomics↗

Diverse somatic genomic alterations in single neurons in chronic traumatic encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that is linked to exposure to repetitive head impacts (RHI), yet little is known about its pathogenesis. Applying two single-cell whole-genome sequencing methods to hundreds of neurons from prefrontal cortex of 15 individuals with CTE, and 4 with RHI without CTE, revealed increased somatic single-nucleotide variants in CTE, resembling a pattern previously reported in Alzheimers disease (AD). Furthermore, we discovered remarkably high burdens of somatic small insertions and deletions in a subset of CTE individuals, resembling a known pattern, ID4, also found in AD. Our results suggest that neurons in CTE experience stereotyped mutational processes shared with AD; the absence of similar changes in RHI neurons without CTE suggests that CTE involves mechanisms beyond RHI alone.

genomics↗

Multi-omic analysis of the ciliogenic transcription factor RFX3 reveals a role in promoting activity-dependent responses via enhancing CREB binding in human neurons

Heterozygous loss-of-function (LoF) variants in RFX3, a transcription factor known to play key roles in ciliogenesis, result in autism spectrum disorder (ASD) and neurodevelopmental delay. RFX binding motifs are also enriched upstream of genes found to be commonly dysregulated in transcriptomic analyses of brain tissue from individuals with idiopathic ASD. Still, the precise functions of RFX3 in the human brain is unknown. Here, we studied the impact of RFX3 deficiency using human iPSC-derived neurons and forebrain organoids. Biallelic loss of RFX3 disrupted ciliary gene expression and delayed neuronal differentiation, while monoallelic loss of RFX3 did not. Instead, transcriptomic and DNA binding analyses demonstrated that monoallelic RFX3 loss disrupted synaptic target gene expression and diminished neuronal activity-dependent gene expression. RFX3 binding sites co-localized with CREB binding sites near activity-dependent genes, and RFX3 deficiency led to decreased CREB binding and impaired induction of CREB targets in response to neuronal depolarization. This study demonstrates a novel role of the ASD-associated gene RFX3 in shaping neuronal synaptic development and plasticity.

neuroscience↗

Chromosomal rearrangements and instability caused by the LINE-1 retrotransposon

LINE-1 (L1) retrotransposition is widespread in many cancers, especially those with a high burden of chromosomal rearrangements. However, whether and to what degree L1 activity directly impacts genome integrity is unclear. Here, we apply whole-genome sequencing to experimental models of L1 expression to comprehensively define the spectrum of genomic changes caused by L1. Combining the analyses of experimental models of L1 induction and of cancer genomes, we demonstrate that L1 retrotransposition can directly generate reciprocal translocations, genomic DNA inversions, and foldback rearrangements resulting from illegitimate recombination of double-strand DNA ends generated by L1-encoded ORF2p. We further show that L1-induced rearrangements can produce unstable chromosomes that fuel the acquisition of complex rearrangements, large segmental copy-number alterations, and genetic heterogeneity through breakage-fusion bridge cycles or DNA fragmentation. Together, these findings suggest L1 as a potent mutagenic force capable of driving genome evolution in cancers.

genomics↗

High resolution kinematic approach for quantifying impaired mobility of dystrophic zebrafish larvae

Dystrophin-deficient zebrafish larvae are a small, genetically tractable vertebrate model of Duchenne muscular dystrophy well suited for early stage therapeutic development. However, current approaches for evaluating their impaired mobility, a physiologically relevant therapeutic target, are characterized by low resolution and high variability. To address this, we used high speed videography and deep learning-based markerless motion capture to develop linked-segment models of larval escape response (ER) swimming. Kinematic models provided repeatable, high precision estimates of larval ER performance. Effect sizes for ER peak instantaneous acceleration and speed, final displacement, and ER distance were 2 to 3.5 standard deviations less for dystrophin-deficient mutants vs. wild-types. Further analysis revealed that mutants swam slower because of a reduction in their tail stroke frequency with little change in tail stroke amplitude. Kinematic variables were highly predictive of the dystrophic phenotype with [&le;] 3% of larvae misclassified by random forest and support vector machine models. Tail kinematics also performed as well as in vitro assessments of tail muscle contractility in classifying larvae as mutants or wild-type, suggesting that ER kinematics could serve as a non-lethal proxy for direct measurements of muscle function. In summary, ER kinematics can be used as precise, physiologically relevant, non-lethal biomarkers of the dystrophic phenotype. The open-source approach described here may have applications not only for studies of skeletal muscle disease but for other disciplines that use larval mobility as an experimental outcome.

physiology↗

Image-based DNA Sequencing Encoding for Detecting Low-Mosaicism Somatic Mobile Element Insertions

Active LINE-1 (L1), Alu, and SVA mobile elements in the human genome are capable of retrotransposition, resulting in novel mobile element insertions (MEIs) in both germline and somatic tissues. Detecting MEIs through DNA sequencing relies on supporting reads overlapping MEI junctions; however, artifacts from DNA amplification, sequencing, and alignment errors produce numerous false positives. Systematic detection of somatic MEIs, particularly those with low mosaicism, remains a significant challenge. Previous methods had required a high number of supporting reads which limits the detection sensitivity, or human inspections that are susceptible to biases. Here, we developed RetroNet, an algorithm that encodes MEI-supporting sequencing reads into images, and employs a deep neural network to identify somatic MEIs with as few as two reads. Trained on extensive and diverse datasets and benchmarked across various conditions, RetroNet surpasses previous methods and eliminates the need for extensive manual examinations. The RetroNet analysis on the Illumina sequencing of 161x or 195x of a cancer cell line achieved an average precision of 0.885 and recall of 0.579 for detecting somatic L1 insertions that are present in as few as 1.79% of the cells. Additionally, we demonstrated that RetroNet is effective for analyzing highly degraded DNA, such as circulating tumor DNA. RetroNet is applicable to the rapidly generated short-read sequencing data and has the potential to provide further insights into the functional and pathological implications of somatic retrotranspositions.

genomics↗

Maternal obesity and offspring neurodevelopment are associated with hypoxic gene expression in term human placenta

One third of women in the United States are affected by obesity during pregnancy. Maternal obesity (MO) is associated with an increased risk of neurodevelopmental and metabolic disorders in the offspring. The placenta, located at the maternal-fetal interface, is a key organ determining fetal development and likely contributes to programming of long-term offspring health. We profiled the term placental transcriptome in humans (pre-pregnancy BMI 35+ [MO condition] or 18.5-25 [lean condition]) using single-nucleus RNA-seq to compare expression profiles in MO versus lean conditions, and to reveal potential mechanisms underlying offspring disease risk. We recovered 62,864 nuclei of high quality from 10 samples each from the maternal-facing and fetal-facing sides of the placenta. On both sides in several cell types, MO was associated with upregulation of hypoxia response genes. On the maternal-facing side only, hypoxia gene expression was associated with offspring neurodevelopmental measures, in Gen3G, an independent pregnancy cohort with bulk placental tissue RNA-seq. We leveraged Gen3G to determine genes that correlated with impaired neurodevelopment and found these genes to be most highly expressed in extravillous trophoblasts (EVTs). EVTs further showed the strongest correlation between neurodevelopment impairment gene scores (NDIGSs) and the hypoxia gene score. We reanalyzed gene expression of cultured EVTs, and found increased NDIGSs associated with exposure to hypoxia. Among EVTs, accounting for the hypoxia gene score attenuated 44% of the association between BMI and NDIGSs. These data suggest that hypoxia in EVTs may be a key process in the neurodevelopmental programming of fetal exposure to MO.

genomics↗

Somatic cancer driver mutations are enriched and associated with inflammatory states in Alzheimer's disease microglia

Alzheimers disease (AD) is an age-associated neurodegenerative disorder characterized by progressive neuronal loss and pathological accumulation of the misfolded proteins amyloid-{beta} and tau1,2. Neuroinflammation mediated by microglia and brain-resident macrophages plays a crucial role in AD pathogenesis1-5, though the mechanisms by which age, genes, and other risk factors interact remain largely unknown. Somatic mutations accumulate with age and lead to clonal expansion of many cell types, contributing to cancer and many non-cancer diseases6,7. Here we studied somatic mutation in normal aged and AD brains by three orthogonal methods and in three independent AD cohorts. Analysis of bulk RNA sequencing data from 866 samples from different brain regions revealed significantly higher ([~]two-fold) overall burdens of somatic single-nucleotide variants (sSNVs) in AD brains compared to age-matched controls. Molecular-barcoded deep (>1000X) gene panel sequencing of 311 prefrontal cortex samples showed enrichment of sSNVs and somatic insertions and deletions (sIndels) in cancer driver genes in AD brain compared to control, with recurrent, and often multiple, mutations in genes implicated in clonal hematopoiesis (CH)8,9. Pathogenic sSNVs were enriched in CSF1R+ microglia of AD brains, and the high proportion of microglia (up to 40%) carrying some sSNVs in cancer driver genes suggests mutation-driven microglial clonal expansion (MiCE). Analysis of single-nucleus RNA sequencing (snRNAseq) from temporal neocortex of 62 additional AD cases and controls exhibited nominally increased mosaic chromosomal alterations (mCAs) associated with CH10,11. Microglia carrying mCA showed upregulated pro-inflammatory genes, resembling the transcriptomic features of disease-associated microglia (DAM) in AD. Our results suggest that somatic driver mutations in microglia are common with normal aging but further enriched in AD brain, driving MiCE with inflammatory and DAM signatures. Our findings provide the first insights into microglial clonal dynamics in AD and identify potential new approaches to AD diagnosis and therapy.

genomics↗

Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Reveals Widespread Degeneration from Focal Mutations

Although mutations in many genes cause familial amyotrophic lateral sclerosis and frontotemporal dementia, most cases are sporadic (sALS and sFTD) with unclear etiology. We tested whether somatic mutations contribute to sALS and sFTD by deep targeted sequencing of 88 neurodegeneration-related genes in postmortem brain and spinal cord samples from 399 sporadic cases and 144 controls. Predicted deleterious somatic variants in ALS/FTD genes were observed in 2.1% of sporadic cases lacking deleterious germline variants. These variants occurred at very low allele fractions (typically <2%) and were often focal and enriched in disease-affected regions. Analysis of bulk RNA-seq data from an additional cohort identified deleterious somatic variants in DYNC1H1 and LMNA, genes associated with pediatric motor neuron degeneration. Targeted long-read sequencing further identified one sFTD case with de novo somatic C9orf72 repeat expansions. Together, these findings suggest that rare, focal somatic variants can contribute to sALS and sFTD and drive widespread neurodegeneration.

genetics↗

Pan-cancer analysis reveals multifaceted roles of retrotransposon-fusion RNAs

Transposon-derived transcripts are abundant in RNA sequences, yet their landscape and function, especially for fusion transcripts derived from unannotated or somatically acquired transposons, remains underexplored. Here, we developed a new bioinformatic tool to detect transposon-fusion transcripts in RNA-sequencing data and performed a pan-cancer analysis of 10,257 cancer samples across 34 cancer types as well as 3,088 normal tissue samples. We identified 52,277 cancer-specific fusions with [~]30 events per cancer and hotspot loci within transposons vulnerable to fusion formation. Exonization of intronic transposons was the most prevalent genic fusions, while somatic L1 insertions constituted a small fraction of cancer-specific fusions. Source L1s and HERVs, but not Alus showed decreased DNA methylation in cancer upon fusion formation. Overall cancer-specific L1 fusions were enriched in tumor suppressors while Alu fusions were enriched in oncogenes, including recurrent Alu fusions in EZH2 predictive of patient survival. We also demonstrated that transposon-derived peptides triggered CD8+ T-cell activation to the extent comparable to EBV viruses. Our findings reveal distinct epigenetic and tumorigenic mechanisms underlying transposon fusions across different families and highlight transposons as novel therapeutic targets and the source of potent neoantigens.

cancer biology↗