title: Lipid metabolism dysregulation in solar lentigo: a multi-system-level analysis reveals membrane instability and energy homeostasis disruption

city: Seoul

first: Soonhyo

last: Kwon

address: 892 Dongnam-ro, Gangdong-gu

institute: Kyung Hee University Hospital at Gangdong

summary: Solar lentigo is a common hyperpigmented skin condition caused by chronic ultraviolet exposure, primarily affecting photoaged skin. While previous investigations focused on inflammatory and melanogenic mechanisms, the comprehensive role of lipid metabolism in pathogenesis remains unclear. We aimed to investigate systemic alterations in lipid metabolism and their contribution to solar lentigo development. We performed comprehensive analysis of RNA sequencing data from solar lentigo lesions and control skin samples (n=7 per group) using metabolic flux simulations, gene co-expression networks, and protein-protein interaction analysis. These multi-system approaches were integrated to identify coordinated alterations in lipid metabolic pathways. Solar lentigo samples exhibited coordinated inhibition of fatty acid elongation, acetyl-CoA carboxylase activity, and sphingolipid biosynthesis, alongside impaired cholesterol synthesis via reduced squalene epoxidase and 7-dehydrocholesterol reductase activity. Compensatory upregulation of phospholipid synthesis enzymes and dihydroceramide desaturases was observed. Pathway disruption and altered calcium signaling, indicating aberrant cellular energy metabolism and membrane integrity. These findings demonstrate that solar lentigo pathogenesis involves systematic lipid metabolism dysregulation beyond melanogenesis, causing membrane instability, energy homeostasis disruption and redox imbalance. The identification of specific metabolic bottlenecks reveals novel targets for lipid-based therapeutic approaches in pigmentary diseases.

overall_design:
The dataset comprised paired tissue samples from solar lentigo lesions and adjacent normal skin obtained from seven patients.

***************************************************************
Raw files for human/patient samples were not submitted to GEO due to concerns about submitting personally identifiable sequence data for open access.
***************************************************************

first: Man

middle: S

last: Kim


title: Establishing the Oocyte Proteome at the Primordial Follicle Stage and Cisplatin-induced Shifts through in situ APEX2-driven Biotinylation

status: Public on Feb 06 2026

city: Hangzhou

first: Heng-yu

last: Fan

state: Zhejiang

address: Yuhangtang Road

country: China

institute: Life Sciences  Institute

type: Expression profiling by high throughput sequencing

summary: The number and quality of primordial follicles play a decisive role in female fertility. The high sensitivity of oocytes in primordial follicles to chemotherapeutics makes antitumor therapy extremely prone to premature ovarian insufficiency and infertility; however, the specific mechanism remains unclear. A systematic proteomic profile of oocytes in primordial follicles is urgently needed to support basic and clinical research, which has been hindered by the rarity of oocyte samples and the technical challenges associated with isolating oocytes from primordial follicles. In this study, utilizing in vivo protein labeling by engineered ascorbate peroxidase (APEX) fluorescent mice, we identified 641 proteins and 2020 gene transcripts in primordial follicular oocytes, from which the abundance of several proteins involved in processes associated with DNA damage repair and histone modification changed after ovary exposure to the chemotherapeutic cisplatin. Notably, a histone modifier, EZH2, was induced by cisplatin in oocytes, and the simultaneous application of its inhibitor, GSK126, partially relieved cisplatin-induced oocyte developmental defects. Our study provides the first description of the primordial follicular oocyte proteome and further illustrates the dynamic shifts in protein abundance associated with chemotherapeutic agents, laying the foundation for further development of effective and targeted drugs to protect and prolong female fertility.

overall_design: The biotinylated RNAs from APEXflox/+;Gdf9-Cre mice were subjected to RNA-seq using the Smart-seq2 method with minor modifications.

first: Zhiyan

last: Jiang

first: Xuan

last: Wu

first: MO

last: Li

first: Hengyu


title: Alterations to the bronchial gene-expression effects of tobacco smoking in people living with HIV

status: Public on Feb 05 2026

city: Boston

first: Adam

middle: C

last: Gower

state: MA

address: 72 East Concord Street, E632

department: Department of Medicine

country: USA

institute: Boston University School of Medicine

summary: Background: Although acquired immunodeficiency syndrome-related mortality has decreased since the introduction of antiretroviral therapy, the incidence of lung cancer in patients living with HIV (PLWH) remains high. Understanding the effects of tobacco smoke on airway gene expression in PLWH may provide insight into the elevated lung cancer risk associated with HIV. Methods: Airway epithelial brushings were collected from 12 PLWH who smoke and 19 PLWH who have never smoked and profiled using RNA-seq. Linear models were used to identify genes differentially expressed between people who smoke and have never smoked and between people who previously smoked and have never smoked. Gene set enrichment analysis was used to validate smoking-related gene signatures across datasets. Data was integrated with gene expression data from a cohort of patients without HIV to identify genes differentially modulated by both smoking and HIV status. Results: We found that previous smoking-related gene signatures are similarly associated with smoking in PLWH, including the persistent differential expression of a subset of "irreversibly altered" genes in people who previously smoked compared to people who have never smoked. We also identified and validated two gene signatures specifically modulated in people who smoke without HIV. Conclusions: Many of the effects of smoking on bronchial gene expression are shared between PLWH and non-HIV individuals. Of the subset of genes that differ between PLWH and non-HIV individuals, it appears that the effect of smoking on gene expression is more attenuated in PLWH.  This includes genes related to oxidative stress and epithelial integrity, and suggests potential mechanisms that may contribute to smoking-related outcomes that are more prevalent in PLWH, such as lung cancer.

overall_design:
Airway epithelial brushings were collected from 12 PLWH who smoke and 19 PLWH who have never smoked and profiled using RNA-seq.

***************************************************************
Raw files for human/patient samples were not submitted to GEO due to concerns about submitting personally identifiable sequence data for open access.
***************************************************************

first: Minyi

last: Lee

first: Marc

middle: E

last: Lenburg


title: Multi-omics analysis of human placentas from first year of the COVID-19 pandemic reveals sex-dependant effects

city: Laval

first: Cathy

last: Vaillancourt

state: QC

address: 531 boulevard des Prairies

department: Centre Armand Frappier Santé Biotechnologie

country: Canada

institute: INRS

summary: The COVID-19 pandemic affected millions of pregnant persons, yet the consequences of maternal SARS-CoV-2 infection on the placental function and the fetal health remain poorly characterized. While inflammatory and structural alterations have been described in placentas from exposed pregnancies, the underlying molecular mechanisms are still unclear. The aim of this study was to evaluate transcriptomic alterations in placentas exposed to maternal SARS-CoV-2 infection (COVID+) compared to unexposed placentas (COVID-). We analyzed 67 placentas collected between March 2020 and June 2021 from singleton pregnancies with (n = 41) or without (n = 26) a history of maternal SARS-CoV-2 infection during pregnancy. Demographic, obstetric, placental, and fetal data were extracted from the medical records. SARS-CoV-2 RNA was not detected in any placental sample. Bulk RNA-sequencing was performed on villous biopsies preserved either frozen or in RNALater. Global transcriptomic analysis comparing COVID+ and COVID- placentas revealed an upregulation of genes involved in cytoskeleton organization. Stratified analysis by fetal sex identified a marked sex-specific response, with 43 differentially expressed genes (DEGs) in placenta from female fetuses (XX) in the COVID+ group compared to COVID-, whereas only one DEG was identified in placenta from male fetuses (XY). In XX COVID+ placentas, pathways related to cytoskeleton organization, pregnancy specific processes, and muscle development were altered. These results highlight a sex-specific dysregulation of placental gene expression following maternal SAR-CoV-2 infection, predominantly affecting placentas from female fetuses.

overall_design: Bulk rRNA-depleted RNA sequencing was performed on placental villous biopsies from human pregnancies with or without a history of maternal SARS-CoV-2 infection. Transcriptomic analyses were conducted globally and stratified by fetal sex.

first: Hélène

last: Pinatel

first: Marie-Pier

last: Scott-Boyer

first: Marie-Ève

last: Brien

first: Sylvie

last: Girard

first: Arnaud

last: Droit

first: Géraldine

last: Delbès

first: Laurent

last: Chatel-Chaix


title: Deciphering sepsis molecular subtypes using large-scale data to identify subtype-specific drug repurposing

city: Gainesville

first: Leslie

middle: Anne

last: Smith

state: Fl

address: 1889 Museum Rd

department: Computer Information Science and Engineering

institute: University of Florida

summary:
Rationale: Sepsis is a life-threatening syndrome that can quickly cause organ failure and death if untreated. Patient variability complicates therapy development, and its molecular mechanisms remain poorly understood. Advancing knowledge of these mechanisms is essential for effective treatments and clearer phenotype definitions.
Objectives: To address this issue, we created a large-scale transcriptomic atlas of publicly available adult sepsis patient data with which we performed molecular phenotyping to evaluate patterns of gene expression and identified potential phenotype-specific drug therapies.
Methods: We identified studies of bacterial sepsis in three genomic databases (SRA, GEO, and refine.bio) and reviewed metadata from each study to ensure samples met our predetermined inclusion criteria. We combined this data into one large comprehensive data atlas and harmonized gene expression and associated metadata from each sample. Molecular phenotypes of sepsis were identified via clustering analysis of this sepsis transcriptomic data atlas. We then examined clinical correlates of each phenotype and identified gene signatures associated with each. We performed gene set enrichment analysis on those signatures and identified phenotype-specific potential drug repurposing candidates. We also evaluated the associations between computed phenotypes and mortality.
Measurements and Main Results: We harmonized data from 3,713 samples (all are included in this dataset) across 28 data sets, of which 2,251 were sepsis patients. Clustering analysis identified four phenotypes within the data. We identified statistically significant phenotype associations with survival, disease, and age. Pathway analysis revealed that MHC class II functions, DNA damage, homeostatic pathways and coagulation may characterize underlying response phenotypes, and may have the potential to guide drug development of sepsis therapeutics.
Conclusions: We created the largest transcriptomic sepsis atlas to date, from which we identified four molecular sepsis phenotypes. We described underlying dysregulated molecular mechanisms of these phenotypes, associated clinical covariates, and several potential candidate therapies specific to each phenotype. Future studies should seek to validate such drug-phenotype links to advance sepsis precision medicine.

overall_design:
Meta-analysis of sepsis transcriptomic studies for adult sepsis patients with bulk transcriptomic data. The datasets used for analysis in this study consists of 1 new dataset of RNA-Seq sepsis samples as well as samples from 27 reanalyzed studies from one of three data repositories: GEO, SRA, or refine.bio. The pipeline for preprocessing of reanalyzed samples differs slightly depending on the source repository. Processing information for each study is described below. All samples were adult patients who met sepsis/septic shock criteria and had bulk RNA-Seq expression data from whole blood with blood being drawn within 48 hours.
Processing of reanalyzed studies:
Reanalyzed studies (10 total) from GEO:
GSE100159 - All samples available in the expression matrix for GSE100159 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE13015 - All samples available in the expression matrix for GSE13015 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE131761 - All samples available in the expression matrix for GSE131761 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE137340 - All samples available in the expression matrix for GSE137340 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE236713 - All samples available in the expression matrix for GSE236713 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE236892 - All samples available in the expression matrix for GSE236892 on GEO were reanalyzed. The expression matrix was downloaded from GEO. Ensembl gene IDs were mapped to HUGO symbols in R using biomaRt (v2.56.1) with ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE32707 - All samples available in the expression matrix for GSE32707 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE69063 -  All samples available in the expression matrix for GSE69063 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE134347 - All samples available in the expression matrix for GSE134347 on GEO were reanalyzed. The expression matrix and associated platform mapping probe IDs were downloaded from GEO. Probe IDs were mapped to associated value in expression matrix in R. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE189400 - All samples available in the expression matrix for GSE189400 on GEO were reanalyzed. The expression matrix was downloaded from GEO. Ensembl gene IDs were mapped to HUGO symbols in R using biomaRt (v2.56.1) with ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
Reanalyzed studies (11 total) from SRA:
SRP198776 - All RNA-Seq reads available on SRA for SRP198776 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE154918 - All RNA-Seq reads available on SRA for GSE154918 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE185263 - All RNA-Seq reads available on SRA for GSE185263 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE196117 - All RNA-Seq reads available on SRA for GSE196117 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE199816 - All RNA-Seq reads available on SRA for GSE199816 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE211210 - All RNA-Seq reads available on SRA for GSE211210 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE216902 - All RNA-Seq reads available on SRA for GSE216902 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE222393 - All RNA-Seq reads available on SRA for GSE222393 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE232404 - All RNA-Seq reads available on SRA for GSE232404 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE232753 - All RNA-Seq reads available on SRA for GSE232753 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE63311 - All RNA-Seq reads available on SRA for GSE63311 were reanalyzed. The following processing pipeline used for available reads followed the pipeline defined by refine.bio. Reads for each available sample in the dataset were initially downloaded from SRA using prefetch and fasterq-dump. Fastp was used for read trimming and quality control. Transcript quantification was performed using Salmon. The transcript level estimates for the expression matrix were done using tximport in R. Gene ananotation was done with Ensembl gene annotations. Duplicate gene HUGO symbol IDs were merged by taking the mean of expression as is done in refine.bio processing. Samples were then quantile normalized in R using preprocess Core (v1.62.1) with the reference distribution provided by refine.bio (downloaded from https://api.refine.bio/v1/qn_targets/ on June 28th 2022). This expression matrix was combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
Reanalyzed studies (6 total) from refine.bio:
GSE33118 - All samples available in the expression matrix for GSE33118 on refine.bio were reanalyzed. The expression matrix was downloaded from refine.bio, no transformations were selected/performed at the time of download. Quantile normalization is performed as part of the refine.bio download process. The dataset was downloaded from refine.bio independently (not as part of a larger downloaded dataset) in order to ensure quantile normalization is performed independently on the dataset. After download Ensembl gene names were mapped to HUGO Symbols using biomaRt (v2.56.1) with ensembl gene annotations. This expression matrix was then combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE57065 - All samples available in the expression matrix for GSE57065 on refine.bio were reanalyzed. The expression matrix was downloaded from refine.bio, no transformations were selected/performed at the time of download. Quantile normalization is performed as part of the refine.bio download process. The dataset was downloaded from refine.bio independently (not as part of a larger downloaded dataset) in order to ensure quantile normalization is performed independently on the dataset. After download Ensembl gene names were mapped to HUGO Symbols using biomaRt (v2.56.1) with ensembl gene annotations.  This expression matrix was then combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE65682 - All samples available in the expression matrix for GSE65682 on refine.bio were reanalyzed. The expression matrix was downloaded from refine.bio, no transformations were selected/performed at the time of download. Quantile normalization is performed as part of the refine.bio download process. The dataset was downloaded from refine.bio independently (not as part of a larger downloaded dataset) in order to ensure quantile normalization is performed independently on the dataset. After download Ensembl gene names were mapped to HUGO Symbols using biomaRt (v2.56.1) with ensembl gene annotations.  This expression matrix was then combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE66890 - All samples available in the expression matrix for GSE66890 on refine.bio were reanalyzed. The expression matrix was downloaded from refine.bio, no transformations were selected/performed at the time of download. Quantile normalization is performed as part of the refine.bio download process. The dataset was downloaded from refine.bio independently (not as part of a larger downloaded dataset) in order to ensure quantile normalization is performed independently on the dataset. After download Ensembl gene names were mapped to HUGO Symbols using biomaRt (v2.56.1) with ensembl gene annotations.  This expression matrix was then combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE74224 - All samples available in the expression matrix for GSE74224 on refine.bio were reanalyzed. The expression matrix was downloaded from refine.bio, no transformations were selected/performed at the time of download. Quantile normalization is performed as part of the refine.bio download process. The dataset was downloaded from refine.bio independently (not as part of a larger downloaded dataset) in order to ensure quantile normalization is performed independently on the dataset. After download Ensembl gene names were mapped to HUGO Symbols using biomaRt (v2.56.1) with ensembl gene annotations.  This expression matrix was then combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.
GSE95233 - All samples available in the expression matrix for GSE95233 on refine.bio were reanalyzed. The expression matrix was downloaded from refine.bio, no transformations were selected/performed at the time of download. Quantile normalization is performed as part of the refine.bio download process. The dataset was downloaded from refine.bio independently (not as part of a larger downloaded dataset) in order to ensure quantile normalization is performed independently on the dataset. After download Ensembl gene names were mapped to HUGO Symbols using biomaRt (v2.56.1) with ensembl gene annotations.  This expression matrix was then combined with all other datasets included in the study and batch corrected using ComBat from the sva (v3.48) package for final use in analysis.

middle: A

first: Kiley

last: Graim

first: Faheem

last: Guirgis

first: Beulah

last: Augustin

first: Vinitha

last: Jacob

first: Lauren

middle: P

last: Black

first: Andrew

last: Bertrand

first: Emilio

last: Cagmat

first: Susmita

last: Datta

first: Srinivasa

middle: T

last: Reddy

first: Charlotte

last: Hopson


title: Pathway-Specific Canalization and Plasticity of Gene Expression during C. elegans Dauer Development

city: Buffalo

first: Johnny

last: Cruz Corchado

state: NY

address: Elm & Carlton Streets Buffalo,L3-L125

department: Cell Stress

institute: Roswell Park Comprehensive Cancer Institue

summary: Caenorhabditis elegans development, where different environmental or genetic stimuli can each induce larvae to switch from continuous growth to a seemingly identical dauer (dormancy) state, provides a tractable model to explore this question. To identify dauer features that differ or are invariant, we compared gene expression of dauers induced by different dauer-inducing conditions, globally and within >100 sets of curated covarying genes or “modules” enriched for functional features such as ‘protein expression’, mitochondria’, ‘germline’, etc., through gene co-expression network analyses.

overall_design: Comparative gene expression profiling analysis of RNA-seq data for  C. elegans dauer following treatment with Pheromone and Starvation

last: Cruz

first: Kavinila

last: Selvarasu

first: Veena

last: Prahlad


title: Single-cell RNA-sequencing of bronchoalveolar lavage cells from humans with bronchiectasis

city: Stockholm

first: Tim

last: Willinger

address: Center for Infectious Medicine (CIM), Alfred Nobels allé 8, level 7

department: Department of Medicine Huddinge

country: Sweden

institute: Karolinska Institutet

summary: Bronchiectasis is a lung disease characterized by irreversible dilation of the large airways (bronchodilatation), which often causes recurrent airway infection and non-resolving inflammation. In this study, we performed single-cell RNA-sequencing (scRNA-seq) to determine the heterogeneity of immune cells in the airways of bronchiectasis patients.

overall_design:
Bronchoalveolar lavage (BAL) fluid was obtained by bronchoscopy from 6 individuals with bronchiectasis. BAL cells were isolated by density gradient centrifugation and cell aliquots frozen.  For single-cell RNA-sequencing, frozen BAL cells were thawed and treated with 50 U/ml Benzonase Endonuclease (Merck) for 20 minutes at 37°C. Human immune cells (excluding neutrophils) were then purified by cell sorting as live CD45+CD66- BAL cells.

***As Swedish legislation and GDPR prevent unrestricted distribution of raw sequencing data, raw sequence data cannot be provided, including through controlled access databases.***

first: Elza

last: Evren


title: RNA localization to nuclear speckles follows splicing logic

city: New York

first: Oded

last: Regev

address: 215 Mercer St

institute: New York University

summary: Nuclear speckles are membraneless organelles implicated in multiple RNA processing steps. In this work, we systematically characterize the sequence logic determining RNA localization to nuclear speckles. We find extensive similarities between the speckle localization code and the RNA splicing code, even for transcripts that do not undergo splicing. Specifically, speckle localization is enhanced by the presence of unspliced exon-like or intron-like sequence features. We demonstrate that interactions required for early spliceosomal complex assembly contribute to speckle localization. We also show that speckle localization of isolated endogenous exons is reduced by disease-associated single nucleotide variants. Finally, we find that speckle localization strongly correlates with splicing kinetics of splicing-competent constructs and is linked to the decision between exon inclusion and skipping. Together, these results suggest a model in which RNA speckle localization is associated with the formation of the early spliceosomal complex and enhances the efficiency of splicing reactions.

overall_design: To ensure that RNA transcribed from our synthetic constructs does not deviate from the intended sequence, we performed Nanopore full-length RNA sequencing after plasmid transfection. We applied unbiased transcriptome-wide sequencing without using any gene-specific primers, ensuring that even transcripts significantly deviating from the intended sequence (e.g., cryptic transcription start site, or cryptic splicing) will be captured.

first: Li

last: Wen

first: Mauricio

last: Arias

first: Xinqi

last: Fan

first: Joyce

last: Xie

first: Sneha

last: Paul

first: Susan

last: Liao

first: Marek

last: Sobczyk

first: Jingyi

last: Fei


title: Developing a multimodal therapy for glioblastoma using oncolytic virus delivering CD19 and EGFRvIII antigens and bi-specific CARs

city: Duarte

first: Guihua

last: Sun

state: CA

address: 1500 East Duarte Rd.

department: Department of Neurodegenerative Diseases

institute: City of hope

summary: Glioblastoma (GBM) is the most malignant primary brain tumor with no cure. While chimeric antigen receptor (CAR)-T cell therapy has exhibited considerable success for hematopoietic malignancies, CAR-T therapy for GBM is limited by heterogeneous tumor antigen expression, antigen loss after treatment with CAR-T targeting single antigens, and an immunosuppressive tumor microenvironment (TME). To address these challenges, we developed a multimodal immunotherapy platform for effective GBM treatment by combining bispecific CAR-T (BiCAR-T) cells with oncolytic virus carrying dual antigens and membrane-bound cytokines. Specifically, we developed a dual-antigen-encoding oncolytic virus (OVDual) that delivers truncated CD19 (CD19t) and EGFRvIII (EGFRvIIIt) antigens to GBM cells and BiCAR-T cells that are equipped with both CD19 CAR and EGFRvIII CAR. We demonstrated that OVDual effectively delivers CD19t and EGFRvIIIt to GBM cells and that BiCAR-T cells exhibited superior tumor-killing efficacy when combined with OVDual. To improve immune cell expansion/persistence and cytotoxicity, we engineered an OV expressing membrane-bound IL-15 and IL-21 (OVmIL15/21) and showed that OVmIL15/21 enhanced the expansion and killing activity of BiCAR-T and BiCAR-NK cells against GBM cells in vitro and boosted the anti-tumor effect in vivo. The combination of OVDual with BiCAR-T or BiCAR-NK cells allowed us to address the main challenges associated with inefficient CAR-T therapy for GBM, including heterogeneous antigen expression, antigen escape, and the immunologically ‘cold’ TME, and cytokine-armed OV further boosted the expansion/persistence and cytotoxicity of CAR immune cells. The multimodal platform developed in this study offers promising potential for effective GBM therapeutic development.

overall_design: GBM cells were infected with an oncolytic virus encoding truncated CD19 and EGFRvIII antigens at a multiplicity of infection (MOI) of 1 for 4 hours, together with an oncolytic virus encoding membrane-bound IL-15 and membrane-bound IL-21 (mIL15/mIL21) or a control virus encoding GFP. After infection,Bi-specific CAR-T cells were added at a 1:1 effector-to-target (E:T) ratio. Following 48 hours of co-culture, cells were collected for RNA extraction using TRIzol reagent. The purified RNA samples were subsequently submitted to the vendor for bulk RNA sequencing (RNA-seq) analysis.

first: Jia

last: Li

first: Yanhong

last: Shi


title: Global knockout of VEGFB improves lipoprotein lipase activity leading to an improved lipid profile during diabetes

status: Public on Feb 04 2026

city: Vancouver

first: Hualin

last: Wang

state: BC

address: 2405 Wesbrook Mall

department: Faculty of Pharmaceutical Sciences

institute: University of British Columbia

summary: Diabetes affects over half a billion people worldwide, with cardiovascular disease Q7 being its leading cause of death, either occurring secondary to atherosclerosis or due to an intrinsic defect in heart muscle (diabetic cardiomyopathy, DbCM). One instigator for DbCM is impaired cardiac metabolism characterized by excessive fatty acid (FA) delivery and utilization by the heart, causing oxidative stress and toxic lipid accumulation. Inhibition of vascular endothelial growth factor B (VEGFB) has been shown to counter these factors associated with abnormal cardiac metabolism by inducing metabolic flexibility and preventing cardiac lipid accumulation in Type 2 diabetes. However, its impact on lipoprotein lipase (LPL) and the sources of FA for cardiac use in Type 1 diabetes is unknown. Global Vegfb knockout (VegfbKO) in rats caused limited phenotype and cardiac transcriptome changes under normal conditions but notably reduced cardiac LPL activity, probably by impeding LPL translocation from cardiomyocyte to the coronary vasculature. Under streptozotocin (STZ)-induced diabetes, VegfbKO rats exhibited increased cardiac LPL activity, protecting animals from dyslipidemia, decreased plasma saturated FA, and provided a safer cardiac FA source, LPL-derived FA. Knockout of Vegfb also protected animals from DbCM by inhibiting excess FA oxidation, preserving angiogenesis and alleviating cell death in the heart. Inhibiting VEGFB may offer a promising therapeutic approach to address the current lack of mechanism-based treatments for DbCM.

overall_design: VEGFB knockout (KO) rats were created on a Sprague Dawley background rats by inserting a beta-glucosidase gene to disrupt the VEGFB gene using zinc-finger nucleases. Wildtype and global VEGFB KO rats were housed until 7 weeks of age. Diabetes was induced by intravenous administration of streptozotocin (55 mg/kg) to kill insulin production beta cell. Given the sex differences in the susceptibility to STZ diabetes, only male rats were used for this study. All animals injected with STZ developed hyperglycemia and hypoinsulinemia within 24 hours. Animals were monitored for 4 days. On day 4 of diabetes, cardiac tissue was collected from diabetic rats and their littermate-matched controls. So we have four experimental groups: wildtype control (WTC), wildtype diabetic (WTD), VEGFB KO control (KOC), and VEGFB KO diabetic (KOD)(n = 5 for each group).  Total RNA was extracted from frozen ventricular tissue using TRIzol reagent according to the manufacturer’s protocol. The concentration and purity of the RNA samples were checked by Qubit fluorometer. And the RNA integrity of the RNA samples was checked by Bioanalyzer. Then, we sent our qualified RNA sample to Sequencing Core Facility for library preparation and sequencing. The sequencing library was prepared using NEBNext Ultra II Directional RNA library Prep Kit and sequenced using Illumina Nextseq 500 platform to generate paired-end reads.

first: Rui

last: Shang

first: Chae Syng

last: Lee

first: Bahira

last: Hussein

first: Brian

last: Rodrigues


title: Boosting Sensory Nerve-to-Bone Interactions Enhances Hedgehog Mediated Calvarial Bone Repair

city: Baltimore

first: Aaron

last: James

state: Maryland

address: 720 Rutland Avenue, Ross Bldg., Room 529

department: Pathology

institute: Johns Hopkins University

summary: Any person that has broken a bone can attest to the existence of sensory innervation of the skeleton. Beyond afferent functions, sensory neurons have been implicated in the orchestration of bone repair via the release of neuroregulatory signals. Yet, these neurosecretory effects have principally been deciphered through loss-of-function studies. Indeed, the potential therapeutic benefit of boosting nerve-to-bone interactions remains cursorily studied. Here, using a mouse calvarial bone defect model, pharmacologic activation of TrkA with a small molecule partial agonist induced bone-associated nerve ingrowth and significantly improved calvarial bone healing. Single-cell RNA sequencing analysis of cells from the defect site revealed shifts in cluster proportions, with enrichment of immune cell populations in TrkA agonist-treated mice. Within the skeletal cell lineage, TrkA agonism enhanced osteoblast differentiation while suppressing fibroblastic differentiation. Pathway analysis showed increased Hedgehog signaling activity, and interactome analyses between trigeminal ganglia sensory neurons and skeletal cells implicated Hedgehog signaling. The pro-regenerative effects of TrkA agonism were abolished in conditional knockout mice lacking Smoothened (Smo) in PDGFRα+ skeletal progenitor cells. In summary, boosting sensory nerve signaling enhances membranous bone repair after injury, at least in part via Hedgehog pathway activation in osteoprogenitor cells.

overall_design: 2 samples were analyzed comparing mRNA from mice. One is a control group which received intraperitoneal (IP) injection of vehicle control (10% DMSO). The other is a GA group which received IP injection of gambogic amide. Gambogic amide (GA)  was used to activate TrkA. Mice received intraperitoneal (IP) injection of either 100 μL vehicle control (10% DMSO) or GA (1.2 mg/kg in 10% DMSO). Treatment began 24h prior to calvarial injury, and continued daily thereafter for 1 week. Skulls were microdissected 7 days after defect creation. Cranial bone with a defect at the center, with an approximate edge length of 3mm, was minced and subjected to six sequential enzymatic digestions with a mixture containing collagenase type I (1 mg/ml) and collagenase type II (1 mg/ml).

first: Zhao

first: Xin

last: Xing

middle: W


title: Multi-omics identification of key targets for the osteogenic differentiation of human bone marrow mesenchymal stromal cells under oxidative stress

city: guiyang

first: dong

last: wentao

state: guizhou

address: No. 28, Guiyi Street

institute: The Affliated Hospital of Guizhou Medical University

summary:
Background: Human bone marrow mesenchymal stromal cells (hBMSCs) are multipotent stromal cells capable of osteogenic differentiation, making them a promising cell source for bone tissue engineering and regenerative medicine. Identifying key factors that regulate hBMSCs osteogenic differentiation is crucial for enhancing bone regeneration strategies.
Objective: This study aims to identify target genes underlying impaired osteogenic differentiation of hBMSCs under oxidative stress (OS) through integrated transcriptomic and proteomic approaches, and delineate the role of proenkephalin (PENK) in this process.
Methods: OS model and impaired osteogenic differentiation model were established in hBMSCs using hydrogen peroxide (H2O2). Cellular oxidative stress levels were assessed using Dihydroethidium (DHE) fluorescent probes and JC-1 staining. Osteogenic differentiation was evaluated by alkaline phosphatase (ALP) activity and Alizarin Red staining (ARS). Key genes and proteins were predicted via integrated transcriptomic and proteomic analyses. The role of PENK in osteogenic differentiation was validated using lentiviral transfection.
Results: This study established 400 μM H2O2 as the optimal concentration for inducing impaired osteogenic differentiation in hBMSCs. Integrated transcriptomic and proteomic analysis identified 18 pivotal regulatory genes that orchestrate impaired osteogenic differentiation of hBMSCs under OS. Among these, PENK was identified as a potential therapeutic target involved in regulating oxidative stress-impaired osteogenic differentiation of hBMSCs. Functional validation confirmed that PENK overexpression promotes osteogenic differentiation in hBMSCs.
Conclusion: OS contributes to impaired osteogenic differentiation in hBMSCs. PENK regulates osteogenic differentiation of hBMSCs under OS and holds promise as a novel therapeutic target for bone regeneration and repair.

overall_design: This study aims to elucidate the transcriptomic landscape underlying the impaired osteogenic differentiation of human bone marrow mesenchymal stromal cells (hBMSCs) under oxidative stress (OS). A multi-group comparison design was employed: Experimental Groups: Control: hBMSCs in standard growth medium. OS: hBMSCs treated with 400 μM H₂O₂. Osteogenic Differentiation (OD): hBMSCs in osteogenic induction medium. OS+OD (Key Model): hBMSCs treated with 400 μM H₂O₂ and cultured in osteogenic induction medium (model of impaired osteogenesis). PENK OE + OS+OD (Functional Validation): PENK-overexpressing hBMSCs subjected to the OS+OD condition. Primary Comparison: The core analysis compares the OS+OD group versus the OD group to directly pinpoint genes specifically dysregulated during osteogenesis under OS conditions. Replication: Each group was analyzed with 3 biological replicates to ensure statistical robustness. Validation: Key candidate genes identified from transcriptomic analysis (prioritizing PENK) were functionally validated using lentiviral overexpression.

first: Wentao

last: Dong

first: Yangyang

last: Zheng

first: Yongfang

last: Zhou

first: Tao

first: Jiexin

last: Yang

first: Huaying

first: Wuxun

last: Peng


title: V gamma 1 gamma-delta T cells steer airway macrophages towards a pro-fibrotic response in an autochthonous lung cancer mouse model. [RNA-Seq]

city: Glasgow

first: Robin

last: Shaw

address: Switchback Road

country: United Kingdom

institute: CRUK Scotland Institute

summary: Gamma-delta T cells are important for host defence at the respiratory mucosa, acting directly or through interactions with other cells. However, how Gamma-Delta T cells influence other immune cells in the lung remains unclear. Using a genetically engineered mouse model of lung cancer, we show that tumours drive expansion of both CD27+ and CD27— Gamma-Delta T cells. Advanced microscopy techniques indicated that CD27— Gamma-Delta T cells are enriched in tumours, while CD27+ Gamma-Delta T cells are more prone to interact with macrophages in tumour-associated adventitial cuffs. SiglecFlow pro-fibrotic airway macrophages were more prevalent in lung tumour-bearing mice than tumour-free mice. This pro-fibrotic subset was reduced in lungs when the cancer model was crossed to Tcrd knockout mice or treated with V Gamma1-depleting antibodies, but not in TcrgV4/6 knockout mice. Thus, our findings implicate V Gamma1 Gamma-Delta T cells in driving tumour-associated airway macrophage functional imprinting. Determining the translatability to human health may offer new avenues for refining patient management and immunotherapeutic strategies.

overall_design: Bulk RNA-seq was performed on FACS-isolated alveolar macrophage subsets from: 1) Tumour-bearing KM lungs from Tcrd knockout mice vs wild type to identify differentially expressed genes. These genes were used to create a module score for assessing scRNA-seq clusters. 2) Tumour-bearing KM lungs, comparing SiglecF low and SiglecF hi AMs to define transcriptional programmes associated with profibrotic versus immunoreactive states; these signatures were then related back to scRNA-seq clusters.

first: Ximena L.

last: Raffo-Iraolagoitia

first: Amanda J.

last: McFarlane

first: Sarah

last: Laing

first: Ryan

last: Corbyn

first: Lindsey W. G.

last: Arnott

first: Frédéric

last: Fercoq

first: Lynn

last: McGarry

first: Judith

last: Secklehner

first: Marco

last: De Donatis

first: John B. G.

last: Mackey

first: Bjorn

last: Kruspig

first: Robert

last: Wiesheu

first: Ya-Ching

last: Hsieh

first: Kai

last: Rakovic

first: John

last: Le Quesne

first: Graeme

last: Clark

first: Colin

last: Nixon

first: Crispin

last: Miller

first: Kristina

last: Kirschner

first: Calum C.

last: Bain

first: Daniel J.

last: Murphy

first: Seth B.

last: Coffelt

first: Leo M.

last: Carlin


title: V gamma 1  gamma-delta T cells steer airway macrophages towards a pro-fibrotic response in an autochthonous lung cancer mouse model  [scRNA-Seq]

first: Robin

last: Shaw

overall_design: Lung tissue from Mus musculus was extracted, and three distinct regions were sampled: tumour tissue, tumour-distant tissue, and normal tissue. Macrophages were isolated from each sample using flow cytometry. The sorted cell populations were then sequenced using the 10X Genomics Chromium Single Cell 3′ protocol.

first: Ximena L.

last: Raffo-Iraolagoitia

first: Amanda J.

last: McFarlane

first: Sarah

last: Laing

first: Ryan

last: Corbyn

first: Lindsey W. G.

last: Arnott

first: Frédéric

last: Fercoq

first: Lynn

last: McGarry


title: Spatial analysis of IPMNs defines a paradoxical KRT17-positive, low-grade epithelial population harboring malignant features [scRNA-seq]

city: Ann Arbor

first: Eileen

last: Carpenter

state: MI

address: 1137 E Catherine St Med Sci II R 7712

department: Internal Medicine

institute: University of Michigan

summary:
Background & Aims:
Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cysts that represent one of the few radiologically identifiable precursors to pancreatic ductal adenocarcinoma (PDAC). Though the IPMN-bearing patient population represents a unique opportunity for early detection and interception, current guidelines provide insufficient accuracy in determining which patients should undergo resection versus surveillance, resulting in a sizable fraction of resected IPMNs only harboring low-grade dysplasia, suggesting that there may be overtreatment of this clinical entity.
Methods:
To investigate the transcriptional changes that occur during IPMN progression, we performed spatial transcriptomics using the Nanostring GeoMx on patient samples containing the entire spectrum of IPMN disease including low-grade dysplasia, high-grade dysplasia, and IPMN-derived carcinoma.  Single cell RNA sequencing was performed on side branch and main duct IPMN biospecimens.
Results:
We identified a subpopulation of histologically low-grade IPMN epithelial cells that express malignant transcriptional features including  KRT17, S100A10 and CEACAM5,  markers that are enriched in PDAC. We validated this high-risk gene signature in both single-cell RNA sequenced samples and an external ST dataset containing a larger number of IPMN samples including non-tumor bearing IPMN (i.e. low-grade IPMN in isolation). Immunofluorescence staining of a large cohort of patient tissues confirmed the presence of KRT17-positive cells, which were found to comprise a small subset of epithelial cells within histologically low-grade IPMN in a patchy distribution.
Conclusions:
Our study demonstrates that KRT17 marks a distinct transcriptional signature in a subpopulation of epithelial cells within histologically low-grade IPMN.  This population of cells likely represents a transitional state of histologically low-grade epithelial cells undergoing progression to a higher grade of dysplasia and thus may represent a higher risk of progression to carcinoma.

overall_design:
We obtained two freshly acquired IPMN samples in the following manner: Sample 1556 was a side branch IPMN with a mural nodule within the cyst; sample was obtained via endoscopic fine needle biopsy performed during endoscopic ultrasound evaluation. Sample 1593 was acquired from a total pancreatectomy of a patient with main duct IPMN; sample was acquired by longitudinally bisecting and shaving off a portion of the dilated main duct.

***************************************************************
Raw files for human/patient samples are being made available in dbGaP (https://www.ncbi.nlm.nih.gov/gap/) for controlled access to the personally identifiable sequence data.
***************************************************************


title: The Oxysterol Receptor GPR183 Senses Metabolic Niche Signals that Promote Differentiation of Monocytes into Tissue-Resident Lung Macrophages

city: Liège

first: Thomas

last: Marichal

address: Avenue de l'Hopital 11

department: GIGA Institute

country: Belgium

institute: University of Liege

summary: Monocytes populate tissues when local niches are depleted of tissue-resident macrophages, yet the tissue-derived signals controlling monocyte-to-macrophage differentiation are largely undefined. Here, we discovered that the oxysterol receptor GPR183 enables monocytes to sense metabolic niche signals that induce lung macrophage differentiation. We found that interstitial macrophages that continuously turn over express the oxysterol receptor GPR183, whereas alveolar macrophages that derive from embryonic progenitors and slowly turn over did not. Models of conditional tissue-resident macrophage depletion showed that newcomer monocyte-derived macrophages expressed GPR183 along their differentiation trajectory. Recruited GPR183+ monocytes interacted with fibroblasts and lack of GPR183 caused defective lung macrophage differentiation. Single-cell RNA analysis over time identified lung fibroblasts as the source of the GPR183 ligand 7a,25-dihydroxycholesterol in the empty niche. Our findings identify oxysterols as key instructive signals for tissue-resident macrophage development from monocytes.

overall_design: To define the cellular source of the GPR183 ligand, single-cell RNAseq was performed in lung fibroblasts, endothelial cells, and epithelial cells before and after DT-mediated alveolar macrophage depletion.

first: Domien

last: Vanneste

first: Qiang

last: Bai

first: Joan

last: Abinet


title: Human intranasal olfactory biopsy analysis of Alzheimer's Disease subjects

city: Durham

first: Bradley

last: Goldstein

state: NC

address: 40 Duke Medicine Cir

institute: Duke University

summary: Single-cell RNA sequencing was performed on brush biopsy samples from the human olfactory epithelium (n = 22 donors) spanning control (n = 6), pre-clinical (n = 9) and clinical (n = 7) Alzheimer’s disease stages. The dataset comprises ~200,000 high-quality live cells encompassing neuronal, epithelial and immune lineages. These profiles enable comparative analyses of early neuroimmune changes associated with Alzheimer’s progression and provide a resource for identifying peripheral biomarkers of disease.

overall_design: Single cell 3' and 5' RNAseq of live olfactory epithelium from 22 adult human Control (n=6), Pre-Clinical Alzheimer's (n=9) or Clinical Alzheimer's (n=7) (based on cognitive function and CSF Aβ42/Aβ40 ratio) using the 10X Genomics Chromium platform and sequenced on Illumina NovaSeqX. Control Subject 20, Clinical AD Subject 21, and Clinical AD Subject 22 were 5' scRNAseq, rest are 3' scRNAseq.

first: Vincent

middle: M

last: D'Anniballe

middle: J


title: Prehabilitation as a biologically active intervention reprograms pancreatic tumor-immune microenvironment to enhance antitumor immunity

city: HOUSTON

first: HONG

last: ZHAO

state: Texas

address: 6670 Bertner Ave

institute: HOUSTON METHODIST HOSPITAL

summary: This dataset contains NanoString GeoMx Digital Spatial Profiling data generated from surgically resected pancreatic ductal adenocarcinoma (PDAC) specimens collected from patients who underwent a multimodal prehabilitation program and matched untreated controls. Spatial transcriptomic profiling was performed across immune (CD45 positive), tumor (PanCK positive), and stromal regions of interest to investigate the biological effects of prehabilitation on the PDAC tumor microenvironment. Differential expression, pathway enrichment, and immune deconvolution analyses were used to evaluate transcriptional changes associated with cytotoxic immune activation, stromal remodeling, and oncogenic signaling. The goal of this exploratory dataset is to provide an initial resource for investigating how prehabilitation may influence immune–tumor interactions in PDAC and to support future studies integrating biological and clinical endpoints.

sample_organism:
Homo sapiens
synthetic construct

platform_organism:
Homo sapiens
synthetic construct

overall_design:
Formalin-fixed paraffin-embedded pancreatic ductal adenocarcinoma (PDAC) tissues were obtained from patients who participated in a multimodal prehabilitation program prior to surgical resection and from matched control patients who underwent standard management. Spatial transcriptomic profiling was performed using the NanoString GeoMx Digital Spatial Profiler with whole-transcriptome probes. Regions of interest were selected based on immunofluorescent segmentation markers to capture immune (CD45 positive), tumor (PanCK positive), and stromal compartments within each specimen. Raw DSP count matrices were generated for each compartment and used for downstream differential expression, pathway enrichment, and immune deconvolution analyses. The dataset was generated as part of an exploratory pilot study to examine the biological effects of prehabilitation on the tumor microenvironment in PDAC.

UPDATE: [Apr-15-2026] The Sample titles were updated. The original titles are in the 'description' field.

first: Hong

last: Zhao

first: Renee

last: Stubbins


title: Isolated DNA repeat units nucleate heterochromatin through Integrator-coupled transcriptional attenuation

city: Freiburg im Breisgau

first: Galina

last: Erikson

address: Stübeweg 51

country: Germany

institute: Max Planck Institute of Immunobiology and Epigenetics

type: Genome binding/occupancy profiling by high throughput sequencing

summary: Heterochromatin defines a transcription-repressive chromatin state. In mouse cells, heterochromatin is associated with underlying arrays of A/T-rich, 234 bp DNA repeat elements, called the major satellite repeats (MaSat or MSR). We have examined > 18,000 copies of MSR repeat units in mouse ES cells and identified that heterochromatin is only formed at transcriptionally competent MSR variants. To directly dissect the function of MSR DNA, we inserted isolated MSR copies into an inert genomic region that is repeat- and gene-free. Insertion of three or more intact MSR units, but not one MSR unit, induced heterochromatic histone marks, recruitment of HP1 and incorporation of histone H1. Only transcriptionally competent MSR copies, but not permutated MSR variants or other DNA repeats, such as LINE1 5’UTR elements can form de novo heterochromatin. MSR-derived transcription is bi-directional and MSR driven transcripts are attenuated by the RNA polymerase II (RNAPII) associated Integrator complex. These data link RNA processing of MSR transcripts by the Integrator with heterochromatin formation. This study resolves a long-standing paradox between heterochromatic and euchromatic transcriptional activity and uncovers a DNA/RNA based logic for the establishment of heterochromatin in the mouse epigenome.

overall_design: To investigate whether Integrator complex is presented at endogenous MSR. Wild type mESCs (WT26) are fixed by double cross-linking (2 mM DSG and 1% formaldehyde) and proccessed using RELACS nuclei barcoding protocol (Arrigoni et al., 2018).

first: Yi-Hsuan

last: Lo

last: Jenuwein


title: Cochlear tissue from heterzygous or homozygous Myo7a Shaker mutant mice [RNA-seq]

city: Paris

first: Fiorella

last: Grandi

address: 105 Bld d'Hopital

department: Centre de Recherche de Myologie

country: France

institute: Sorbonne Universite

overall_design: Cochlear tissue from heterzygous or homozygous Myo7a Shaker mutant mice were dissected. Coclea from 4-5 mice were pooled per gentoype and RNA was extracted uisng the Qiagen microRNAeasy kit and sequenced .

first: Walter

last: Marcotti


title: singIST: an integrative method for comparative single-cell transcriptomics between disease models and humans

first: Poulami

last: Dey

address: 1301 Catherine St

institute: Michigan Medicine

summary: Disease models are fundamental tools in drug discovery and early-stage drug development, but they only approximate human disease, and selecting a suitable model is challenging. Quantitative computational methods exist to assess molecular resemblance to human conditions, but approaching that work at single-cell resolution, and doing so in an explainable and generalizable way, remain very limited. We present singIST, a computational method for comparative single-cell transcriptomics analysis between disease models and human conditions. singIST provides explainable quantitative measures on disease model similarity to the human reference at the pathway, cell type and gene levels. These measures jointly account for gene orthology, cell type presence in the model, cell type and gene importance in the human condition, and gene level fold changes in the model, within a unifying framework that controls for the intrinsic complexities of single-cell data. We first test singIST in three well-characterized murine models against moderate-to-severe Atopic Dermatitis, showing that it recapitulates established biology while generating new hypotheses. We then apply it to Hidradenitis Suppurativa, comparing in vivo human lesions with ex vivo skin explants with and without CD3/CD28 stimulation, and show that stimulation selectively improves pathways that already recapitulate the human signal. Finally, we perform simulation studies that: (i) unit-test the implementation and behaviour of the algorithm under controlled scenarios and (ii) compare singIST against a na¨ıve baseline based on overlapping differentially expressed genes.

overall_design: Human skin biopsies from affected individuals were collected and processed for library prep and next-generation sequencing at the Advanced Genomics Core at the University of Michigan

first: Johann

last: Gudjonsson

first: Lam

last: Tsoi


title: Spatial analysis of IPMNs defines a paradoxical KRT17-positive, low-grade epithelial population harboring malignant features

first: Eileen

last: Carpenter

summary: Background & Aims: Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cysts that represent one of the few radiologically identifiable precursors to pancreatic ductal adenocarcinoma (PDAC). Though the IPMN-bearing patient population represents a unique opportunity for early detection and interception, current guidelines provide insufficient accuracy in determining which patients should undergo resection versus surveillance, resulting in a sizable fraction of resected IPMNs only harboring low-grade dysplasia, suggesting that there may be overtreatment of this clinical entity. Methods: To investigate the transcriptional changes that occur during IPMN progression, we performed spatial transcriptomics using the Nanostring GeoMx on patient samples containing the entire spectrum of IPMN disease including low-grade dysplasia, high-grade dysplasia, and IPMN-derived carcinoma.  Single cell RNA sequencing was performed on side branch and main duct IPMN biospecimens. Results: We identified a subpopulation of histologically low-grade IPMN epithelial cells that express malignant transcriptional features including  KRT17, S100A10 and CEACAM5,  markers that are enriched in PDAC. We validated this high-risk gene signature in both single-cell RNA sequenced samples and an external ST dataset containing a larger number of IPMN samples including non-tumor bearing IPMN (i.e. low-grade IPMN in isolation). Immunofluorescence staining of a large cohort of patient tissues confirmed the presence of KRT17-positive cells, which were found to comprise a small subset of epithelial cells within histologically low-grade IPMN in a patchy distribution. Conclusions: Our study demonstrates that KRT17 marks a distinct transcriptional signature in a subpopulation of epithelial cells within histologically low-grade IPMN.  This population of cells likely represents a transitional state of histologically low-grade epithelial cells undergoing progression to a higher grade of dysplasia and thus may represent a higher risk of progression to carcinoma.

overall_design: A total of 3 slides containing tissue sections from pancreatic cysts, associated malignancy, and/or adjacent normal tissue was submitted for spatial transcriptomics.  The Solid Tumor TME Morphology Kit was utilized according to manufacturer instructions to detect epithelial cells (pan-cytokeratin [CK]) together with DAPI for nuclei detection. 310 ROIs were captured for whole transcriptome profiling.


title: Transcriptional competence defines the heterochromatin nucleating potential of isolated MSR copies [H3K9me3_ChIP]

summary: Heterochromatin defines a transcription-repressive chromatin state. In mouse cells, heterochromatin is associated with underlying arrays of A/T-rich, 234 bp DNA repeat elements, called the major satellite repeats (MaSat or MSR). We have examined > 18,000 copies of MSR repeat units in mouse ES cells and identified that heterochromatin is only formed at transcriptionally competent MSR variants. To directly dissect the function of MSR DNA, we inserted isolated MSR copies into an inert genomic region that is repeat- and gene-free. Insertion of three or more intact MSR units, but not one MSR unit, induced heterochromatic histone marks, recruitment of HP1 and incorporation of histone H1. Only transcriptionally competent MSR copies, but not permutated MSR variants or other DNA repeats, such as LINE1 5’UTR elements can form de novo heterochromatin. MSR-derived transcription is bi-directional and MSR driven transcripts are attenuated by the RNA polymerase II (RNAPII) associated Integrator complex. This study resolves a long-standing paradox between heterochromatic and euchromatic transcriptional activity and uncovers a DNA/RNA based logic for the establishment of heterochromatin in the mouse epigenome.

overall_design: To investigate whether H3K9me3 is altered at endogenous MSR variants upon INTS11 depletion for 24 hrs. INTS11-degron mESCs (E14) were fixed by double cross-linking (2 mM DSG and 1% formaldehyde) and proccessed using RELACS nuclei barcoding protocol (Arrigoni et al., 2018).

first: Thomas


title: Identification of IL1R2 as a Spermatogonial Stem Cell-specific Sorted Protein in Humans and Mice

status: Public on Feb 03 2026

city: Beijing

first: yu

middle: peng

last: Li

address: Dong Dan San Tiao 5 Beijing , China

institute: Peking Union Medical College

summary: Self-renewal and differentiation of spermatogonial stem cell (SSCs) are critical for sustaining spermatogenesis in adult mammals. SSC populations are highly heterogeneous and dynamic, imposing great challenges in their isolation and functional characterization. The current study aimed to generate Il1r2CreERT2/+; Rosa26mTmG/+ mice to pulse-label Il1r2-expressing cells; through lineage tracing, we discovered that IL1R2+ SSCs, essential for spermiogenesis, possess long-term capacities of self-renewal and differentiation. Under injury-induced regenerative conditions, disruption of spermatogenesis can reactivate IL1R2+ SSCs for proliferation via the PI3K-AKT-mTOR pathway to replenish the SSC pool. We further validated our discovery by systematically characterizing both mouse and human IL1R2+ SSCs isolated. Our findings confirmed the important role of IL1R2+ SSCs in the maintenance of spermatogenesis and regeneration after spermatogenic injury; IL1R2 might serve as a promising marker for enriching human and mouse SSCs.

overall_design: To characterize IL1R2+ SSCs, we isolated IL1R2+, THY1+, and c-KIT+ cells from mouse testes using FACS for RNA-Seq analysis


title: Human epicardial organoids from pluripotent stem cells resemble fetal stage with potential cardiomyocyte-transdifferentiation

city: Hangzhou

first: Chengchen

address: Dunyu Road No.600, Xihu District

institute: Westlake University

summary: Epicardium, the most outer mesothelium, exerts crucial functions in fetal heart development and adult heart regeneration. Here we use a three-step manipulation of WNT signalling entwined with BMP and RA signalling for generating a self-organized epicardial organoid that highly express with epicardium makers WT1 and TCF21 from human embryonic stem cells. After 8-days treatment of TGF-beta following by bFGF, cells enter into epithelium-mesenchymal transition and give rise to smooth muscle cells. Epicardium could also integrate and invade into mouse heart with SNAI1 expression, and give birth to numerous cardiomyocyte-like cells. Single-cell RNA seq unveils the heterogeneity and multipotency exhibited by epicardium-derived-cells and fetal-like epicardium. Meanwhile, extracellular matrix and growth factors secreted by epicardial organoid mimics the ecology of subepicardial space between the epicardium and cardiomyocytes. As such, this epicardial organoid offers a unique ground for investigating and exploring the potential of epicardium in heart development and regeneration

overall_design: H9 samples. All samples were collected for single-cell sequencing on day 7.5, 9.5 and 18.5

first: XINLE

last: ZOU

first: FANWEN

last: WANG

first: HUILING

last: ZHENG

first: TIANCI

last: KONG


title: DGCR8 controls retrotransposon-derived double-stranded RNA accumulation and interferon activation

city: Castellón de la Plana

first: Guillermo

last: Peris

state: CAstellón

address: Av. Vicent Sos Baynat, s/n

department: Llenguatges i Sistemes Informàtics

country: Spain

institute: Universitat Jaume I

summary: The type I interferon (IFN) response is the main innate immune pathway against viruses in mammals and must be tightly regulated to stop viral spread without excessive immune reaction. Here, we show that inactivation of the double-stranded RNA (dsRNA)-binding protein DGCR8 unleashes the IFN response in human cells. Remarkably, we demonstrate that, independently of its function in miRNA biogenesis, DGCR8 prevents the accumulation of endogenous dsRNA. These dsRNAs derive from protein-coding mRNAs enriched in transposable elements (TEs), mostly Alu elements. We propose that DGCR8 binding to TE-rich mRNAs is key to resolve dsRNA structures. In the absence of DGCR8, these unresolved dsRNAs signal through the RIG-I-like signalling pathway triggering the IFN response. This mechanism may be particularly relevant to conditions such as the 22q11.2 deletion syndrome (22qDS), where DGCR8 expression is reduced. Supporting this, we show that cells derived from 22qDS patients exhibit an exacerbated type I IFN response, highlighting the importance of suppressing endogenous dsRNA accumulation to prevent unwanted immune activation.

overall_design: Data analysis from J2 dsRNA immunoprecipitation for WT PA1 cells and two different DGCR8 heterozygous clones.

first: Ana

last: Gazquez

first: Sara

last: Macias

middle: R

last: Heras


title: Dopamine Enhances Surface Glial Glycolysis via Acetylcholine and Insulin/Insulin-Like Growth Factor Signaling in Honeybee

city: Changchun

first: Miaoran

last: Zhang

state: Jilin

address: Xinmin Street

institute: Department of Physiology, College of Basic Medical Sciences, Jilin University

summary: Glycolysis plays a crucial role in maintaining neuronal functional homeostasis and is regulated by neuroendocrine signals, particularly dopamine. However, the underlying regulatory mechanisms remain poorly understood. Here, we investigate dopamine driven neuroendocrine control of glial glycolysis in honeybee through integrated metabolomics and single-cell transcriptomics. Activation of dopamine 2 receptors(D2R) via bromocriptine significantly enhanced glycolytic flux in worker bees, as evidenced by elevated glucose levels, accumulation of glycolytic intermediates, and suppression of pentose phosphate pathway metabolites. Single-cell and single-nucleus RNA sequencing revealed that acetylcholine (ACh) secreted by Kenyon cells (KCs) is a critical node in dopamine-regulated glycolysis. Bromocriptine treatment reduced ACh secretion and directly enhanced surface glial (SG) specific glycolytic gene expression, while also increasing insulin signaling from cortex glial to surface glial. Our findings uncover a dual regulatory mechanism, in which the dopamine-ACh axis coordinates with IIS signaling to orchestrate metabolic plasticity in glial through cell type-specific precision. This study provides insights into how social insects integrate neuroendocrine signals to optimize energy metabolism and highlights the role of ACh in this process.

overall_design: We employed single-nucleus RNA sequencing (snRNA-seq) using the 10x Genomics platform to investigate the effects of bromocriptine, a dopamine agonist, on the neural transcriptome of honeybee (Apis mellifera) forager brains. For this study, foraging bees were divided into two experimental groups: one treated with bromocriptine and the other with water as a control. Brains from 15 foragers per group were dissected and processed for snRNA-seq to resolve cell-type-specific transcriptional responses. This work represents the first application of single-nucleus transcriptomics to explore neuropharmacological modulation in honeybees, offering unprecedented insights into how dopaminergic signaling influences neural plasticity and foraging-related behaviors in a eusocial insect model. By comparing bromocriptine-exposed and control groups, our findings may advance understanding of conserved neuromodulatory pathways and their roles in social insect behavior

first: Peng

last: Chen

first: Xingan


title: H3K115 marks fragile nucleosomes at regulatory sites (Sucrose Gradient fractions rep2)

city: Edinburgh

first: Yatendra

last: Kumar

email: yaten2020@gmail.com, ykumar@ed.ac.uk

address: Crewe Road south

department: MRC HGU

institute: MRC Human Genetics Unit, The University Of Edinburgh

summary: Acetylation of lysine residues in the tail domain of histone H3 at active regulatory elements are well characterised, but the less studied acetylations of histone globular domain lysines also hold regulatory potential based on their potential impact on nucleosome dynamics and stability. Here we have mapped the genome-wide distribution of acetylated H3 lysine 115 (H3K115ac), a residue on the lateral surface of the nucleosomes, in mouse embryonic stem cells. We find that H3K115ac is associated with highly active promoters, especially those associated with CpG islands, and with enhancers. H3K115ac is dynamic, changing in line with gene activation during differentiation and correlated with changes in local chromatin accessibilityas assyed by ATAC-seq. Distinct from other commony studied histone acetylation marks, H3K115ac is enriched on non-canonical “fragile” nucleosomes precisely at the transcription start sites of active gene promoters and within the binding sites of pluripotency transcription factors. Surprisingly we also detect H3K115ac-marked fragile nucleosomes at sites most strongly occupied by CTCF, within the CTCF footprint and oriented relative to the CTCF motif. This unique enrichment and genomic distribution of modified fragile nucleosomes suggests a previously unappreciated role for H3K115ac in gene regulation and chromatin structure. We propose that H3K115ac is a very precise marker for identifying regulatory elements in mammalian genomes.

overall_design: Native Mnase ChIP-seq of H3K115ac on mESC chromatin fractionated on sucrose gradients


title: A synergistic interaction between PRMT5 and LSD1 inhibitors in AML

city: NYC

first: Nayeli

last: Gutierrez

state: NYC

address: Hess CSM Building, 1470 Madison Ave, 6, 108

department: Oncological Sciences

institute: Icahn School of Medicine at Mount Sinai

summary: Acute myeloid leukemia (AML) is a hematopoietic malignancy caused by abnormal proliferation and differentiation of blasts. PRMT5, a methyltransferase that catalyzes symmetric di-methylation of arginine residues, has been implicated in cancer stem cell homeostasis and shown to be a potential therapeutic target in MLL-fusion AMLs. However, given the toxicity of complete PRMT5 inhibition, there is a need to identify effective synergistic therapies. Through a targeted screen of compounds that inhibit key nodes of pathways either regulated by PRMT5 or known to be relevant for AML (e.g. intracellular signaling, splicing and transcription), we have identified a synthetic lethality between inhibition of LSD1, a lysine demethylase known to affect AML blast differentiation, and PRMT5. The two inhibitors broadly reshape the transcriptome of targeted cells and synergize to promote AML differentiation and eventually growth inhibition and apoptosis, in a p53-dependent manner. To leverage this synthetic lethal interaction, we have generated a new set of dual compounds that inhibit both PRMT5 and LSD1. Mechanistically, we show that these dual compounds elicit transcriptional and post-transcriptional (splicing) defects that recapitulate the combination therapy. Last, we were able to solve the X-ray co-crystal structure of one of the designed inhibitors with LSD1, thus elucidating its binding mode and providing a structural basis for the rational design of further inhibitors. In summary, our findings identify a novel drug combination strategy for the treatment of AML.

overall_design: To understand the mechanism underlying the synergistic cytotoxic effects of combinatorial PRMT5 and LSD1 inhibition, we performed RNA-sequencing on MV4-11 cells treated with DMSO, PRT220 (3nM), GSK-LSD1 (10nM) or both drugs combined for 3 days. Analysis of gene expression was performed to determine if there were changes in expression patterns that can explain the synergistic phenotype seen upon PRT220 and GSK-LSD1 combination in MV4-11.

first: Ernesto

last: Guccione

first: Antonello

last: Mai

first: Luca

last: Pignata


title: Glucocorticoids suppress early lung inflammation and impair control of SARS-CoV-2 in non-human primates.

city: Bethesda

first: Tom

last: Hill

address: NIHBC 10 - CLINICAL CENTER BG RM 11N244A, 10 CENTER DR

institute: NIAID

summary: In severe cases of COVID-19, glucocorticoid treatment improves clinical outcomes. However, in non-hospitalized patients, glucocorticoids have limited benefit and may impair viral control. The cell types regulated by glucocorticoids during SARS-CoV-2 infection are currently unknown. Here, we used rhesus macaques to examine the effects of glucocorticoids during the first 14 days of acute SARS-CoV-2 infection. Glucocorticoid treatment decreased local lung inflammation measured with 18FDG-PET/CT imaging. However, glucocorticoid treated animals also had evidence of elevated SARS-CoV-2 viral titers in the lower airways and pulmonary draining lymph nodes. Glucocorticoid treatment blunted plasmacytoid dendritic cell (pDC), eosinophil, innate-like CD8 T cell and early SARS-CoV-2 specific CD8 T cell responses in the airways. These data reveal the cell types that are directly impacted by immunosuppression with glucocorticoids and provide mechanistic insights into the discordant effects of glucocorticoids during SARS-CoV-2 infection.

overall_design: Single cell RNA sequencing using 10x genomics 3' kits v3.1 with sample pooling using hashtag barcodes (Biolegend TotalSeqA #1-10). Samples are a time-course (t0, t1, t2, t3, t4) of bronchoalveolar lavage samples from 10 rhesus macaques infected with SARS-CoV-2, with and without glucocorticoid immunosuppression (n=5 of each). Samples from each treatment group were pooled separately for each of the 5 time points. n=5 control animals (hashtags 1-5) n=5 glucocorticoid animals (hashtags 6-10) Pooling resulted in one control and one glucocorticoid sample at each timepoint. We would like help aligning the data, QC, normalizing, scaling, dimensional reduction and perhaps clustering. We have previously used the Seurat pipeline.

first: Christine E.

last: Nelson

first: Keith D.

last: Kauffman

first: Shunsuke

last: Sakai

first: Taylor

last: Newbolt

first: Jay

last: Bucchnan

first: Taylor W.

last: Foreman

first: April M.

last: Walker

first: Felipe

last: Gomez

first: Joel D.

last: Fleegle

first: Richard

last: Herbet

first: Justin

last: Lack

first: Sevilay

last: Turan

first: Reed

last: Johnson

first: Laura E.

last: Via

first: Daniel L.

last: Barber


title: Transcriptional competence defines the heterochromatin nucleating potential of isolated MSR copies. [RNA-Seq]

first: Galina

last: Erikson

overall_design: To investigate the effect of INTS11 on regulating transcription of MSR repeats.

first: Lo

last: Yi-Hsuan

first: Erikson

last: Galina

first: Jenuwein

last: Thomas


title: Transcriptomics of 3D pentaculture models of high grade serous ovarian cancer microenvironment

city: London

first: Eleni

last: Maniati

address: John Vane Science Centre, Charterhouse Square

department: Barts Cancer Institute

institute: Queen Mary University of London

summary: High-grade serous ovarian cancer (HGSOC) is characterized by a complex, immunosuppressive tumor microenvironment (TME) that contributes to poor clinical outcomes and resistance to therapy. To better replicate the human TME in vitro, we developed a 3D pentaculture model incorporating five human cell types: malignant HGSOC cells, primary fibroblasts, mesothelial cells, adipocytes, and monocytes. Bulk RNASequeing was performed to investigate the role of malignant cells in modulating the TME .

overall_design: We constructed three omental microenvironments by incorporating primary adipocytes, fibroblasts, and mesothelial cells isolated from three different donors as biological replicates. Monocytes from a single donor were used in all experiments. Additionally  2D monocultures of fibroblasts (n = 3), mesothelial cells (n = 1), monocytes (n = 1), malignant cells (n = 2 per cell line) and non-diseased omentum free of malignant tissue (n = 3) were included in the analysis.

first: Beatrice

last: Malacrida

first: Samar

last: Elorbany

first: Joash

last: Joy

first: Frances

last: Balkwill


title: H3K115 marks fragile nucleosomes at regulatory sites (Sucrose Gradient fractions rep1)

first: Yatendra

last: Kumar


title: Transcriptional competence defines the heterochromatin nucleating potential of isolated MSR copies [HP1a_ChIP]

overall_design: To investigate whether HP1⍺ is altered at endogenous MSR variants upon INTS11 depletion for 24 hrs. INTS11-degron mESCs (E14) were fixed by double cross-linking (2 mM DSG and 1% formaldehyde) and proccessed using RELACS nuclei barcoding protocol (Arrigoni et al., 2018).

first: Yi-Hsuan

last: Lo

first: Thomas

last: Jenuwein


title: H3K115 marks fragile nucleosomes at regulatory sites [ATAC-seq]

overall_design: Dynamics of chromatin accessiblility during ESCs differentiating into NPCs using ATAC-seq


title: Cerebellar microglia-derived IL-17A compensates for autism-related deficits [purified cerebellar microglia]

city: Nanjing

first: Jun-Yi

last: Chen

state: Jiangsu

address: Xianlin Campus, Nanjing University, No.163 Xianlin Avenue, Qixia District

institute: Nanjing University

summary: Interleukin-17 (IL-17) is a pleiotropic cytokine produced mainly by peripheral Th17 cells. Yet, brain functions of IL-17 derived from central nervous cells remain poorly understood. Here, we find an aberrant IL-17A signaling in the cerebellum of Fmr1-KO mice, a well-established genetic model for autism spectrum disorder (ASD). Cerebellar IL-17A, derived exclusively from microglia, is essential for the regulation of social behaviors by maintaining neuronal excitability and selectively suppressing inhibitory neurotransmission of Purkinje cells (PCs) in the cerebellar Crus I, a brain region critically involved in social cognition. Specific downregulation of IL-17 receptor-mediated signaling in cerebellar PCs recapitulates ASD-like social deficits and repetitive behaviors. Notably, both direct administration of IL-17A and induction of IL-17A release from cerebellar microglia by poly(I:C) effectively restore PC excitability and ameliorate ASD-like symptoms. The findings uncover an indispensable role of microglia-derived IL-17A for cerebellar social processing and suggest potential therapeutic strategies targeting IL-17A signaling for ASD.

overall_design: Comparative gene expression profiling analysis of RNA-seq data in purified microlias from cerebellum for the vehicle and poly(I:C) treated Fmr1 knock out mice.

first: Shu-Tao

last: Xie

first: Jun

last: Yin

first: Xiao-Yang

last: Zhang

first: Jing-Ning

last: Zhu


title: H3K115 marks fragile nucleosomes at regulatory sites

summary: This SuperSeries is composed of the SubSeries listed below.

overall_design: Refer to individual Series


title: Cerebellar microglia-derived IL-17A compensates for autism-related deficits [cerebellar crus 1]

overall_design: Comparative gene expression profiling analysis of RNA-seq data in cerebellar crus 1 for the vehicle and poly(I:C) treated Fmr1 knock out mice and FVB background mice.


title: H3K115 marks fragile nucleosomes at regulatory sites [ChIP-seq]

overall_design: Native MNase ChIP-seq employed to explore globular and tail-domain acetyl marks in histone H3 in mouse embryonic cells and neural progenitors.


title: Novel Molecular Marker for Nociceptors

status: Public on Feb 02 2026

city: Solna

first: Saida

last: Hadjab

address: Solnavägen 9

department: Neuroscience

institute: Karolinska Institutet

summary: Chronic pain affects approximately 20% of the global population and represents a major unmet medical need. Improved molecular characterization of pain-sensing neurons is essential for the development of more precise therapeutic strategies.

overall_design: Following tamoxifen injection DAPI+NeuN+ stained nuclei from dorsal root ganglia were isolated using fluoresence activate cell sorting (FACS) and analyzed using snRNA-seq.

first: Kaiwen

first: Prach

last: Techameena


title: Generation of persistent HIV CAR-TSCM cells by treatment with a novel common-gamma-chain cytokine-based fusion molecule

city: Bronx

first: Harris

last: Goldstein

address: 1300 Morris Park Avenue

department: Pediatrics

institute: Albert Einstein College of Medicine

summary: Anti-CD3/CD28 (αCD3/28) activation efficiently enables T cells to be transformed by transduction with CAR-expressing lentiviral vectors (LV) into chimeric antigen receptor (CAR)-T cells. However, the long-term effectiveness of this approach is compromised by the more differentiated phenotype of these CAR-Ts, associated with reduced in vivo functional persistence. Treatment with IL-7, IL-15, and/or IL-21 expands CAR-Ts with a T-stem-cell (TSCM) phenotype. We investigated whether we could use an alternative strategy to generate CAR-Ts, by using a scaffold-linked IL-7, IL-15, and IL-21 (HCW9206) to render T cells permissive for LV transduction and thereby promote the generation of HIV-specific duoCAR-T cells (duoCAR-T) enriched in a TSCM phenotype to enhance in vivo persistence. Compared to αCD3/28-generated duoCAR-Ts, HCW9206-generated duoCAR-Ts were markedly enriched for TSCM (> 50%), displayed potent in vitro HIV-1 viral suppression, and antigen-induced TNFα and IFNγ production. RNA sequencing analysis of the transcriptome of duoCAR-T cells generated by IL-7, IL-15, and IL-21 treatment delivered by HCW9206, compared to αCD3/αCD28 activation, identified multiple uniquely expressed genes. These results suggested that duoCAR-T-HCW9206 cells are enriched in both a TSCM phenotype, as indicated by pro-survival and TSCM-like gene signatures, as well as more differentiated effector-like phenotypes, likely contributing to the potent HIV suppression observed both in vitro and in vivo, despite primarily displaying a TSCM phenotype. Our results indicate that scaffold-linked IL-7, IL-15, and IL-21 fusion-treatment represents an alternative method for CAR-T cell generation, more effective than standard αCD3/28 activation for producing functionally persistent CAR-Ts.

overall_design: To evaluate the transcriptional differences between anti-HIV duoCAR-T cells generated by standard anti-CD3/CD28 stimulation (duoCAR-T-αCD3/28) and treatment with the novel human cytokine-based scaffold HCW9206 (duoCAR-T-HCW9206). The CAR-T transcriptomes were compared with or without stimulation with 293T cells expressing HIV-1 envelope protein (293T-gp120). CD8+ duoCAR-T-αCD3/28 cells and duoCAR-T-HCW9206 cells were cultured with 293T cells (unactivated) or cultured with 293T-gp120 cells (activated) for 16 hours. CD8+ duoCAR-T cells were purified by FACS, and total RNA was isolated. 2 biological replicates underwent treatment, cell sorting, RNA isolation, and sequencing independently.

first: Erin

last: Cole

first: Hong Beom

last: Hur

first: Christopher

last: Hiner

first: Manoj

last: Kandpal