The bone microenvironment invigorates metastatic seeds for further dissemination.

Metastasis has been considered as the terminal step of tumor progression. However, recent genomic studies suggest that many metastases are initiated by further spread of other metastases. Nevertheless, the corresponding pre-clinical models are lacking, and underlying mechanisms are elusive. Using several approaches, including parabiosis and an evolving barcode system, we demonstrated that the bone microenvironment facilitates breast and prostate cancer cells to further metastasize and establish multi-organ secondary metastases. We uncovered that this metastasis-promoting effect is driven by epigenetic reprogramming that confers stem cell-like properties on cancer cells disseminated from bone lesions. Furthermore, we discovered that enhanced EZH2 activity mediates the increased stemness and metastasis capacity. The same findings also apply to single cell-derived populations, indicating mechanisms distinct from clonal selection. Taken together, our work revealed an unappreciated role of the bone microenvironment in metastasis evolution and elucidated an epigenomic reprogramming process driving terminal-stage, multi-organ metastases.

A drosophila genetic resource of mutants to study mechanisms underlying human genetic diseases.

Invertebrate model systems are powerful tools for studying human disease owing to their genetic tractability and ease of screening. We conducted a mosaic genetic screen of lethal mutations on the Drosophila X chromosome to identify genes required for the development, function, and maintenance of the nervous system. We identified 165 genes, most of whose function has not been studied in vivo. In parallel, we investigated rare variant alleles in 1,929 human exomes from families with unsolved Mendelian disease. Genes that are essential in flies and have multiple human homologs were found to be likely to be associated with human diseases. Merging the human data sets with the fly genes allowed us to identify disease-associated mutations in six families and to provide insights into microcephaly associated with brain dysgenesis. This bidirectional synergism between fly genetics and human genomics facilitates the functional annotation of evolutionarily conserved genes involved in human health.

Dual targeting of brain region-specific kinases potentiates neurological rescue in Spinocerebellar ataxia type 1.

A critical question in neurodegeneration is why the accumulation of disease-driving proteins causes selective neuronal loss despite their brain-wide expression. In Spinocerebellar ataxia type 1 (SCA1), accumulation of polyglutamine-expanded Ataxin-1 (ATXN1) causes selective degeneration of cerebellar and brainstem neurons. Previous studies revealed that inhibiting Msk1 reduces phosphorylation of ATXN1 at S776 as well as its levels leading to improved cerebellar function. However, there are no regulators that modulate ATXN1 in the brainstem-the brain region whose pathology is most closely linked to premature death. To identify new regulators of ATXN1, we performed genetic screens and identified a transcription factor-kinase axis (ZBTB7B-RSK3) that regulates ATXN1 levels. Unlike MSK1, RSK3 is highly expressed in the human and mouse brainstems where it regulates Atxn1 by phosphorylating S776. Reducing Rsk3 rescues brainstem-associated pathologies and deficits, and lowering Rsk3 and Msk1 together improves cerebellar and brainstem function in an SCA1 mouse model. Our results demonstrate that selective vulnerability of brain regions in SCA1 is governed by region-specific regulators of ATXN1, and targeting multiple regulators could rescue multiple degenerating brain areas.

CoRegNet: unraveling gene co-regulation networks from public RNA-Seq repositories using a beta-binomial statistical model.

Millions of RNA sequencing samples have been deposited into public databases, providing a rich resource for biological research. These datasets encompass tens of thousands of experiments and offer comprehensive insights into human cellular regulation. However, a major challenge is how to integrate these experiments that acquired at different conditions. We propose a new statistical tool based on beta-binomial distributions that can construct robust gene co-regulation network (CoRegNet) across tens of thousands of experiments. Our analysis of over 12 000 experiments involving human tissues and cells shows that CoRegNet significantly outperforms existing gene co-expression-based methods. Although the majority of the genes are linearly co-regulated, we did discover an interesting set of genes that are non-linearly co-regulated; half of the time they change in the same direction and the other half they change in the opposite direction. Additionally, we identified a set of gene pairs that follows the Simpson's paradox. By utilizing public domain data, CoRegNet offers a powerful approach for identifying functionally related gene pairs, thereby revealing new biological insights.

A Comprehensive and Integrative Approach to MeCP2 Disease Transcriptomics.

Mutations in MeCP2 result in a crippling neurological disease, but we lack a lucid picture of MeCP2's molecular role. Individual transcriptomic studies yield inconsistent differentially expressed genes. To overcome these issues, we demonstrate a methodology to analyze all modern public data. We obtained relevant raw public transcriptomic data from GEO and ENA, then homogeneously processed it (QC, alignment to reference, differential expression analysis). We present a web portal to interactively access the mouse data, and we discovered a commonly perturbed core set of genes that transcends the limitations of any individual study. We then found functionally distinct, consistently up- and downregulated subsets within these genes and some bias to their location. We present this common core of genes as well as focused cores for up, down, cell fraction models, and some tissues. We observed enrichment for this mouse core in other species MeCP2 models and observed overlap with ASD models. By integrating and examining transcriptomic data at scale, we have uncovered the true picture of this dysregulation. The vast scale of these data enables us to analyze signal-to-noise, evaluate a molecular signature in an unbiased manner, and demonstrate a framework for future disease focused informatics work.

Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer.

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer.

Environmental oxygen affects ex vivo growth and proliferation of mesenchymal progenitors by modulating mitogen-activated protein kinase and mammalian target of rapamycin signaling.

BACKGROUND AIMS: Stem and progenitor cells of hematopoietic and mesenchymal lineages reside in the bone marrow under low oxygen (O2) saturation. O2 levels used in ex vivo expansion of multipotent mesenchymal stromal cells (MSCs) affect proliferation, metabolism and differentiation. METHODS: Using cell-based assays and transcriptome and proteome data, the authors compared MSC cultures simultaneously grown under a conventional 19.95% O2 atmosphere or at 5% O2. RESULTS: In 5% O2, MSCs showed better proliferation and higher self-renewal ability, most probably sustained by enhanced signaling activity of mitogen-activated protein kinase and mammalian target of rapamycin pathways. Non-oxidative glycolysis-based energy metabolism supported growth and proliferation in 5% O2 cultures, whereas MSCs grown under 19.95% O2 also utilized oxidative phosphorylation. Cytoprotection mechanisms used by cells under 5% O2 differed from 19.95% O2  suggesting differences in the triggers of cell stress between these two O2  conditions. CONCLUSIONS: Based on the potential benefits for the growth and metabolism of MSCs, the authors propose the use of 5% O2 for MSC culture.

Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors.

Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all 3 World Health Organization (WHO) grades (I through III) using clinical, gene expression, and sequencing data. Unsupervised clustering analysis identified 3 molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which classifies more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell-cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors.

Cluster Analysis of Short Sensory Profile Data Reveals Sensory-Based Subgroups in Autism Spectrum Disorder.

Autism spectrum disorder is a common, heterogeneous neurodevelopmental disorder lacking targeted treatments. Additional features include restricted, repetitive patterns of behaviors and differences in sensory processing. We hypothesized that detailed sensory features including modality specific hyper- and hypo-sensitivity could be used to identify clinically recognizable subgroups with unique underlying gene variants. Participants included 378 individuals with a clinical diagnosis of autism spectrum disorder who contributed Short Sensory Profile data assessing the frequency of sensory behaviors and whole genome sequencing results to the Autism Speaks' MSSNG database. Sensory phenotypes in this cohort were not randomly distributed with 10 patterns describing 43% (162/378) of participants. Cross comparison of two independent cluster analyses on sensory responses identified six distinct sensory-based subgroups. We then characterized subgroups by calculating the percent of patients in each subgroup who had variants with a Combined Annotation Dependent Depletion (CADD) score of 15 or greater in each of 24,896 genes. Each subgroup exhibited a unique pattern of genes with a high frequency of variants. These results support the use of sensory features to identify autism spectrum disorder subgroups with shared genetic variants.

Reversal of phenotypes in MECP2 duplication mice using genetic rescue or antisense oligonucleotides.

Copy number variations have been frequently associated with developmental delay, intellectual disability and autism spectrum disorders. MECP2 duplication syndrome is one of the most common genomic rearrangements in males and is characterized by autism, intellectual disability, motor dysfunction, anxiety, epilepsy, recurrent respiratory tract infections and early death. The broad range of deficits caused by methyl-CpG-binding protein 2 (MeCP2) overexpression poses a daunting challenge to traditional biochemical-pathway-based therapeutic approaches. Accordingly, we sought strategies that directly target MeCP2 and are amenable to translation into clinical therapy. The first question that we addressed was whether the neurological dysfunction is reversible after symptoms set in. Reversal of phenotypes in adult symptomatic mice has been demonstrated in some models of monogenic loss-of-function neurological disorders, including loss of MeCP2 in Rett syndrome, indicating that, at least in some cases, the neuroanatomy may remain sufficiently intact so that correction of the molecular dysfunction underlying these disorders can restore healthy physiology. Given the absence of neurodegeneration in MECP2 duplication syndrome, we propose that restoration of normal MeCP2 levels in MECP2 duplication adult mice would rescue their phenotype. By generating and characterizing a conditional Mecp2-overexpressing mouse model, here we show that correction of MeCP2 levels largely reverses the behavioural, molecular and electrophysiological deficits. We also reduced MeCP2 using an antisense oligonucleotide strategy, which has greater translational potential. Antisense oligonucleotides are small, modified nucleic acids that can selectively hybridize with messenger RNA transcribed from a target gene and silence it, and have been successfully used to correct deficits in different mouse models. We find that antisense oligonucleotide treatment induces a broad phenotypic rescue in adult symptomatic transgenic MECP2 duplication mice (MECP2-TG), and corrected MECP2 levels in lymphoblastoid cells from MECP2 duplication patients in a dose-dependent manner.

Loss of Capicua alters early T cell development and predisposes mice to T cell lymphoblastic leukemia/lymphoma.

Capicua (CIC) regulates a transcriptional network downstream of the RAS/MAPK signaling cascade. In Drosophila, CIC is important for many developmental processes, including embryonic patterning and specification of wing veins. In humans, CIC has been implicated in neurological diseases, including spinocerebellar ataxia type 1 (SCA1) and a neurodevelopmental syndrome. Additionally, we and others have reported mutations in CIC in several cancers. However, whether CIC is a tumor suppressor remains to be formally tested. In this study, we found that deletion of Cic in adult mice causes T cell acute lymphoblastic leukemia/lymphoma (T-ALL). Using hematopoietic-specific deletion and bone marrow transplantation studies, we show that loss of Cic from hematopoietic cells is sufficient to drive T-ALL. Cic-null tumors show up-regulation of the KRAS pathway as well as activation of the NOTCH1 and MYC transcriptional programs. In sum, we demonstrate that loss of CIC causes T-ALL, establishing it as a tumor suppressor for lymphoid malignancies. Moreover, we show that mouse models lacking CIC in the hematopoietic system are robust models for studying the role of RAS signaling as well as NOTCH1 and MYC transcriptional programs in T-ALL.

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research.

Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models.

Splicing regulation is an important step of post-transcriptional gene regulation. It is a highly dynamic process orchestrated by RNA-binding proteins (RBPs). RBP dysfunction and global splicing dysregulation have been implicated in many human diseases, but the in vivo functions of most RBPs and the splicing outcome upon their loss remain largely unexplored. Here we report that constitutive deletion of Rbm17, which encodes an RBP with a putative role in splicing, causes early embryonic lethality in mice and that its loss in Purkinje neurons leads to rapid degeneration. Transcriptome profiling of Rbm17-deficient and control neurons and subsequent splicing analyses using CrypSplice, a new computational method that we developed, revealed that more than half of RBM17-dependent splicing changes are cryptic. Importantly, RBM17 represses cryptic splicing of genes that likely contribute to motor coordination and cell survival. This finding prompted us to re-analyze published datasets from a recent report on TDP-43, an RBP implicated in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), as it was demonstrated that TDP-43 represses cryptic exon splicing to promote cell survival. We uncovered a large number of TDP-43-dependent splicing defects that were not previously discovered, revealing that TDP-43 extensively regulates cryptic splicing. Moreover, we found a significant overlap in genes that undergo both RBM17- and TDP-43-dependent cryptic splicing repression, many of which are associated with survival. We propose that repression of cryptic splicing by RBPs is critical for neuronal health and survival. CrypSplice is available at www.liuzlab.org/CrypSplice.

Loss of MeCP2 in the rat models regression, impaired sociability and transcriptional deficits of Rett syndrome.

Mouse models of the transcriptional modulator Methyl-CpG-Binding Protein 2 (MeCP2) have advanced our understanding of Rett syndrome (RTT). RTT is a 'prototypical' neurodevelopmental disorder with many clinical features overlapping with other intellectual and developmental disabilities (IDD). Therapeutic interventions for RTT may therefore have broader applications. However, the reliance on the laboratory mouse to identify viable therapies for the human condition may present challenges in translating findings from the bench to the clinic. In addition, the need to identify outcome measures in well-chosen animal models is critical for preclinical trials. Here, we report that a novel Mecp2 rat model displays high face validity for modelling psychomotor regression of a learned skill, a deficit that has not been shown in Mecp2 mice. Juvenile play, a behavioural feature that is uniquely present in rats and not mice, is also impaired in female Mecp2 rats. Finally, we demonstrate that evaluating the molecular consequences of the loss of MeCP2 in both mouse and rat may result in higher predictive validity with respect to transcriptional changes in the human RTT brain. These data underscore the similarities and differences caused by the loss of MeCP2 among divergent rodent species which may have important implications for the treatment of individuals with disease-causing MECP2 mutations. Taken together, these findings demonstrate that the Mecp2 rat model is a complementary tool with unique features for the study of RTT and highlight the potential benefit of cross-species analyses in identifying potential disease-relevant preclinical outcome measures.

Comprehensive evaluation of RNA-seq quantification methods for linearity.

BACKGROUND: Deconvolution is a mathematical process of resolving an observed function into its constituent elements. In the field of biomedical research, deconvolution analysis is applied to obtain single cell-type or tissue specific signatures from a mixed signal and most of them follow the linearity assumption. Although recent development of next generation sequencing technology suggests RNA-seq as a fast and accurate method for obtaining transcriptomic profiles, few studies have been conducted to investigate best RNA-seq quantification methods that yield the optimum linear space for deconvolution analysis. RESULTS: Using a benchmark RNA-seq dataset, we investigated the linearity of abundance estimated from seven most popular RNA-seq quantification methods both at the gene and isoform levels. Linearity is evaluated through parameter estimation, concordance analysis and residual analysis based on a multiple linear regression model. Results show that count data gives poor parameter estimations, large intercepts and high inter-sample variability; while TPM value from Kallisto and Salmon shows high linearity in all analyses. CONCLUSIONS: Salmon and Kallisto TPM data gives the best fit to the linear model studied. This suggests that TPM values estimated from Salmon and Kallisto are the ideal RNA-seq measurements for deconvolution studies.

TCGA2STAT: simple TCGA data access for integrated statistical analysis in R.

MOTIVATION: Massive amounts of high-throughput genomics data profiled from tumor samples were made publicly available by the Cancer Genome Atlas (TCGA). RESULTS: We have developed an open source software package, TCGA2STAT, to obtain the TCGA data, wrangle it, and pre-process it into a format ready for multivariate and integrated statistical analysis in the R environment. In a user-friendly format with one single function call, our package downloads and fully processes the desired TCGA data to be seamlessly integrated into a computational analysis pipeline. No further technical or biological knowledge is needed to utilize our software, thus making TCGA data easily accessible to data scientists without specific domain knowledge. AVAILABILITY AND IMPLEMENTATION: TCGA2STAT is available from the https://cran.r-project.org/web/packages/TCGA2STAT/index.html SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: zhandong.liu@bcm.edu.

NLRP7 affects trophoblast lineage differentiation, binds to overexpressed YY1 and alters CpG methylation.

Maternal-effect mutations in NLRP7 cause rare biparentally inherited hydatidiform moles (BiHMs), abnormal pregnancies containing hypertrophic vesicular trophoblast but no embryo. BiHM trophoblasts display abnormal DNA methylation patterns affecting maternally methylated germline differentially methylated regions (gDMRs), suggesting that NLRP7 plays an important role in reprogramming imprinted gDMRs. How NLRP7-a component of the CATERPILLAR family of proteins involved in innate immunity and apoptosis-causes these specific DNA methylation and trophoblast defects is unknown. Because rodents lack NLRP7, we used human embryonic stem cells to study its function and demonstrate that NLRP7 interacts with YY1, an important chromatin-binding factor. Reduced NLRP7 levels alter DNA methylation and accelerate trophoblast lineage differentiation. NLRP7 thus appears to function in chromatin reprogramming and DNA methylation in the germline or early embryonic development, functions not previously associated with members of the NLRP family.

Combinatorial therapy discovery using mixed integer linear programming.

MOTIVATION: Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction. RESULTS: Here we proposed to formulate the optimal combinatorial therapy problem into two complementary mathematical algorithms, Balanced Target Set Cover (BTSC) and Minimum Off-Target Set Cover (MOTSC). Given a disease gene set, BTSC seeks a balanced solution that maximizes the coverage on the disease genes and minimizes the off-target hits at the same time. MOTSC seeks a full coverage on the disease gene set while minimizing the off-target set. Through simulation, both BTSC and MOTSC demonstrated a much faster running time over exhaustive search with the same accuracy. When applied to real disease gene sets, our algorithms not only identified known drug combinations, but also predicted novel drug combinations that are worth further testing. In addition, we developed a web-based tool to allow users to iteratively search for optimal drug combinations given a user-defined gene set. AVAILABILITY: Our tool is freely available for noncommercial use at http://www.drug.liuzlab.org/. CONTACT: zhandong.liu@bcm.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Maternal loss-of-function of Nlrp2 results in failure of epigenetic reprogramming in mouse oocytes.

Background: NLRP2 belongs to the subcortical maternal complex (SCMC) of mammalian oocytes and preimplantation embryos. This multiprotein complex, encoded by maternal-effect genes, plays a pivotal role in the zygote-to-embryo transition, early embryogenesis, and epigenetic (re)programming. The maternal inactivation of genes encoding SCMC proteins has been linked to infertility and subfertility in mice and humans. However, the underlying molecular mechanisms for the diverse functions of the SCMC, particularly how this cytoplasmic structure influences DNA methylation, which is a nuclear process, are not fully understood. Results: We undertook joint transcriptome and DNA methylome profiling of pre-ovulatory germinal-vesicle oocytes from Nlrp2-null, heterozygous (Het), and wild-type (WT) female mice. We identified numerous differentially expressed genes (DEGs) in Het and Nlrp2-null when compared to WT oocytes. The genes for several crucial factors involved in oocyte transcriptome modulation and epigenetic reprogramming, such as DNMT1, UHRF1, KDM1B and ZFP57 were overexpressed in Het and Nlrp2-null oocytes. Absence or reduction of Nlrp2, did not alter the distinctive global DNA methylation landscape of oocytes, including the bimodal pattern of the oocyte methylome. Additionally, although the methylation profile of germline differentially methylated regions (gDMRs) of imprinted genes was preserved in oocytes of Het and Nlrp2-null mice, we found altered methylation in oocytes of both genotypes at a small percentage of the oocyte-characteristic hyper- and hypomethylated domains. Through a tiling approach, we identified specific DNA methylation differences between the genotypes, with approximately 1.3% of examined tiles exhibiting differential methylation in Het and Nlrp2-null compared to WT oocytes. Conclusions: Surprisingly, considering the well-known correlation between transcription and DNA methylation in developing oocytes, we observed no correlation between gene expression differences and gene-body DNA methylation differences in Nlrp2-null versus WT oocytes or Het versus WT oocytes. We therefore conclude that post-transcriptional changes in the stability of transcripts rather than altered transcription is primarily responsible for transcriptome differences in Nlrp2-null and Het oocytes.

Multi-omics delineate growth factor network underlying exercise effects in an Alzheimer's mouse model.

Physical exercise represents a primary defense against age-related cognitive decline and neurodegenerative disorders like Alzheimer's disease (AD). To impartially investigate the underlying mechanisms, we conducted single-nucleus transcriptomic and chromatin accessibility analyses (snRNA-seq and ATAC-seq) on the hippocampus of mice carrying AD-linked NL-G-F mutations in the amyloid precursor protein gene (APPNL-G-F) following prolonged voluntary wheel-running exercise. Our study reveals that exercise mitigates amyloid-induced changes in both transcriptomic expression and chromatin accessibility through cell type-specific transcriptional regulatory networks. These networks converge on the activation of growth factor signaling pathways, particularly the epidermal growth factor receptor (EGFR) and insulin signaling, correlating with an increased proportion of immature dentate granule cells and oligodendrocytes. Notably, the beneficial effects of exercise on neurocognitive functions can be blocked by pharmacological inhibition of EGFR and the downstream phosphoinositide 3-kinases (PI3K). Furthermore, exercise leads to elevated levels of heparin-binding EGF (HB-EGF) in the blood, and intranasal administration of HB-EGF enhances memory function in sedentary APPNL-G-F mice. These findings offer a panoramic delineation of cell type-specific hippocampal transcriptional networks activated by exercise and suggest EGF-related growth factor signaling as a druggable contributor to exercise-induced memory enhancement, thereby suggesting therapeutic avenues for combatting AD-related cognitive decline.