bluuebunny/crossref_metadata_2025_split huggingface dataset:
ScDrugAct: a comprehensive database to dissect tumor microenvironment cell heterogeneity contributing to drug action and resistance across human cancers
Authors: Xu Yanjun , Zhang Yifang , Song Kaiyue , Liu Jiaqi , Zhao Rui , Zhang Xiaomeng , Pei Liying , Li Mengyue , Chen Zhe , Zhang Chunlong , Wang Peng , Li Feng 
Published: November 2024

Abstract
The transcriptional heterogeneity of tumor microenvironment (TME) cells is a crucial factor driving the diversity of cellular response to drug treatment and resistance. Therefore, characterizing the cells associated with drug treatment and resistance will help us understand therapeutic mechanisms, discover new therapeutic targets and facilitate precision medicine. Here, we describe a database, scDrugAct (http://bio-bigdata.hrbmu.edu.cn/scDrugAct/), which aims to establish connections among drugs, genes and cells and dissect the impact of TME cellular heterogeneity on drug action and resistance at single-cell resolution. ScDrugAct is curated with drug–cell connections between 3838 223 cells across 34 cancer types and 13 857 drugs and identifies 17 274 drug perturbation/resistance-related genes and 276 559 associations between &gt;10 000 drugs and 53 cell types. ScDrugAct also provides multiple flexible tools to retrieve and analyze connections among drugs, genes and cells; the distribution and developmental trajectories of drug-associated cells within the TME; functional features affecting the heterogeneity of cellular responses to drug perturbation and drug resistance; the cell-specific drug-related gene network; and drug–drug similarities. ScDrugAct serves as an important resource for investigating the impact of the cellular heterogeneity of the TME on drug therapies and can help researchers understand the mechanisms of action and resistance of drugs, as well as discover therapeutic targets.
EPCO-07. INTEGRATING SPATIALLY RESOLVED MULTI-OMICS DATA TO UNCOVER DYSFUNCTIONAL METABOLISM DRIVEN NETWORKS THAT ENHANCE INFILTRATION OF DIFFUSE GLIOMAS
Authors: Ma Yanxia , Nguyen Nhat , Singh Sanjay , Basi Akshay , Mak Duncan , Gomez Javier , Burks Jared , Seely Erin , Lang Frederick , Ene Chibawanye 
Published: November 2024

Abstract

BACKGROUND
Diffuse infiltration is an aggressive feature of high-grade gliomas with survival implications. The contribution of crosstalk between non-neoplastic and neoplastic cells to tumor infiltration remains largely understudied due to the lack of profiling techniques that retain spatial information. Spatial multi-omic profiling is a promising approach to comprehensively analyze transcript-omics, prote-omics and metabol-omics on the same tissue section while preserving information about the spatial organization of cells. Integration of these spatial studies allows for inferring the consequences of complex cell-cell communication underlying tumor infiltration. We hypothesize that the glioma edge is enriched with pro-infiltration ligands-receptors driving tumor infiltration. Strategies that disrupt these ligand-receptor networks may suppress glioma infiltration and improve clinical outcomes.

METHODS
We utilized a glioma tissue micro-array (TMA) to establish the neoplastic and non-neoplastic heterogeneity in the GBM infiltration edge. Each TMA slide consists of pathologist annotated tumor core and edge samples of Glioblastoma (IDH Wildtype, WHO Grade 4; n=10), Diffuse Astrocytoma (IDH Mutant, WHO Grade 3; n=3), Oligodendroglioma (IDH mutant, WHO Grade 2; n=5) and 2 non-brain control samples. We performed spatial multi-omics profiling on adjacent sections of the TMA using 10x Xenium spatial transcriptomics, imaging mass cytometry (IMC) and mass spectrometry imaging (MSI). Integration, visualization, and quantification of the spatial data was done on VisioPharm.

RESULTS
In GBM, we identified candidate mRNA transcripts and proteins for ligands enriched at the infiltrating edge (compared to tumor core; p&lt;0.0001) that correlated with a poor progression free survival (PFS; r2=0.22). These candidate ligands were also significantly enriched at the edge of oligodendroglioma WHO Grade 2 and astrocytoma WHO Grade 3.

CONCLUSIONS
Spatial multi-omics profiling on a TMA consisting of Glioma WHO grades 2-4 identified differentially expressed and targetable pro-tumor infiltration ligands associated with lower PFS in GBM. Functional studies to uncover the role of metabolites enriched at the glioma edge for the expression of the identified pro-infiltration ligands are ongoing.
EPCO-10. PROTEIN GENERATOR ENABLES PROTEOMICS-BASED SUBTYPING OF IDH MUTANT ASTROCYTOMA
Authors: Wang Hui , Tang Jihong , Liu Xing , Fan Wenhua , Jiang Tao , Wang Jiguang 
Published: November 2024

Abstract
The understanding of the proteomic landscape of IDH mutant astrocytoma has been limited in previous studies. To address this knowledge gap, we developed an innovative approach using artificial intelligence (AI) to generate proteomic profiles of tumors based on their transcriptome data. Particularly, we employed a combination of Variational Auto-Encoder and Contrastive Language Image Pretraining techniques to develop an AI model. The model was trained on publicly available databases containing matched RNA and protein data. Leveraging this extensive dataset, we applied the trained model to infer proteomic profiles for over one thousand adult IDH mutant astrocytoma specimens using their transcriptome sequencing data. This novel approach allowed us to explore and identify previously undiscovered subtypes based on the predicted proteomic profiles. As a result, we identified seven distinct clusters: IDHmut-noncodel-Proliferative, IDHmut-noncodel-Mesenchymal, IDHmut-noncodel-Mitochondrial, IDHmut-NFkB-signal, IDHmut-codel-Proliferative, IDHmut-Metabolism, and IDHmut-Neuronal. Of particular clinical significance, the IDHmut-noncodel-Proliferative and IDHmut-noncodel-Immune-Mesenchymal subtypes displayed the worst prognoses, while the IDHmut-Neuronal, IDHmut-NFkB-signal, and IDHmut-Metabolism subtypes exhibited relatively better survival outcomes. Remarkably, within the IDHmut-noncodel-Proliferative cluster, we observed a high prevalence of CDKN2A homozygous deletion, providing a potential explanation for its poor survival prognosis. Conversely, the IDHmut-noncodel-Mesenchymal cluster did not demonstrate any significant genetic events but exhibited elevated expression of mesenchymal marker genes. Furthermore, this cluster displayed notable characteristics, including the presence of gemistocytic differentiated tumor cells and infiltration of activated CD8 T lymphocytes. Moreover, we encompassed an evolutionary analysis of 189 initial-recurrent IDH mutant astrocytoma pairs, and discovered that gemistocytic differentiation represents an early event in tumor progression. In summary, we introduced a novel method utilizing an AI model to generate proteomic profiles, thus enabling the discovery of previously unknown subtypes of IDH mutant glioma with clinical relevance. These findings contribute to a deeper understanding of the molecular landscape of IDH mutant astrocytoma, potentially leading to improved prognostication and personalized treatment strategies.
EPCO-13. HUMAN ENDOGENOUS RETROVIRUS (HERV) PLAYS A CRITICAL ROLE IN ONCOGENIC MECHANISM INIDH1-WILD TYPE GLIOBLASTOMAS
Authors: Johnson William E , Malgulwar Prit Benny , Huse Jason T 
Published: November 2024

Abstract
IDH1-wildtype (WT) GBMs are the most common and aggressive tumors of the central nervous system (CNS), with a median survival rate of 12-15 months, and are resistant to clinical therapies due to their heterogenous molecular phenotype. In this study, we developed a pipeline to dissect the potential role of human endogenous retroviruses (HERVs) in patient derived glioma stem cells (GSCs) and integrated our findings with published epigenomic datasets for enhancers (H3K27ac), CTCF, and chromatin toplogy (Hi-C). We found high expression of several HERV transcripts in IDH1-WT GBMs as compared to IDH1-mutant variants. Epigenomic analysis of these upregulated HERVs showed association with both enhancer marks and CTCF deposition. Annotation of HERVs to their nearest genes, followed by Gene Set Enrichment Analysis (GSEA), identified involvement of actin-filament based mechanisms and regulation of immune phenotype. Integration of these findings identified MER61 (ERVMER61-1), a potential regulator of Interleukin-6 and showed alteration in chromatin looping and enhancer occupancy. To summarize, our work points to novel mechanisms of GBM pathogenesis, through involvement of HERVs in cell migratory and immune dysfunction, warranting further investigations into these oncogenic mechanism to identify and develop novel therapeutic options for GBM.
EPCO-16. METHOD TO MODEL AND CORRECT NOISE IN SINGLE-NUCLEI RNA-SEQUENCING DATA FROM POST-MORTEM BRAIN
Authors: Peng Jacqueline J , O’Rourke Donald M , Nasrallah MacLean P , Binder Zev A , Silverbush Dana 
Published: November 2024

Abstract
Post-mortem brain samples are crucial for neuropathological research. For brain cancers, they provide insights about disease progression, microenvironmental factors, and treatment resistance. In some brain diseases, brain tissue may only be available post-mortem. Establishing a reference atlas of healthy brain also requires post-mortem donations. Beyond logistical and ethical challenges of post-mortem samples, there are also post-mortem factors that mask biological signal. In this study, we specifically aim to model post-mortem gene expression changes in single-nuclei RNA-sequencing (snRNA-seq) data. We analyze a public snRNA-seq dataset of pediatric high-grade glioma (pHGG) that has matched samples at initial resection and autopsy. We find a clear gene signature, composed of mitochondrial genes, stress-related genes, and metabolism-related genes, that is upregulated post-mortem. This signature also appears in post-mortem snRNA-seq data from other brain diseases and healthy donors. We classify it as “post-mortem noise”. We model the post-mortem noise as a combination of technical and biological artifact. The technical artifact is correlated with the percentage of mitochondrial reads and is a general measure of sample quality. The biological artifact is correlated with post-mortem interval and represents gene expression changes due to post-mortem stress. We apply our model to the pHGG data by regressing out the technical and biological artifact. Removing the post-mortem noise results in an improvement in malignant versus normal cell prediction, cell type classification, and the uncovering of pathways related to glioma progression. We confidently identify several normal cell types and predict their interactions with cancer cells, highlighting the utility of wider possible margins post-mortem. Therefore, after removing post-mortem noise, we analyze glioma progression at an unparalleled timepoint and characterize late-stage changes in the tumor microenvironment. In conclusion, we develop a method that models post-mortem noise in snRNA-seq brain data. Our method can be broadly applied to future brain cancer studies using post-mortem tissue.
EPCO-33. OMICON: A CLOUD PLATFORM FOR FAIR RESEARCH ON GENE COEXPRESSION NETWORKS IN NORMAL HUMAN BRAIN AND BRAIN TUMORS
Authors: Eliscu Rebecca , Padmanabhan Divya , Sudhakaran Sanoj , Nair Sharat , Suresh Shravan , Joseph Pratheeksh , Jacob Alex , Ravindran Vineet , Feroz Mizba , Ajayakumar Akshay , Reghuvaran Renjith , Raj Shiny , Vijay Aswathy , Lakshmi Gouri , Vava Remya , Escobar Carolina , Thormann Martin , Shamsian Shawn , Oldham Michael 
Published: November 2024

Abstract
Genome-wide coexpression analysis of bulk human brain samples is a powerful approach for identifying highly reproducible transcriptional signatures of cell types and cell states, since it can survey huge numbers of individuals, cells, and transcripts. However, it is difficult to optimize gene coexpression network construction, compare gene coexpression modules from independent datasets, or even locate gene expression datasets with similar attributes. To address these challenges, we have developed the OMICON platform (theomicon.ucsf.edu) to promote FAIR (Findable, Accessible, Interoperable, Reusable) research practices involving human brain gene coexpression networks. OMICON contains structured gene expression data for &gt;17K bulk human brain samples (~10K normal and ~7K malignant glioma), which were collected from diverse public repositories and consortia (e.g., GEO, TCGA, CGGA, CPTAC, REMBRANDT, IvyGAP, GTEx, NABEC, the Allen Institute). To promote interoperability, we have standardized metadata for hundreds of dataset and sample attributes, including single-nucleotide and copy-number mutations. For each dataset, we have used the FindModules R function to construct dozens of gene coexpression networks by iterating over module detection parameters. These efforts have identified ~100K gene coexpression modules, which have been extensively characterized via enrichment analysis with thousands of curated gene sets. All datasets, metadata, gene coexpression networks, enrichment results, and analysis steps can be browsed with an interactive workflow visualization tool, which promotes accessibility, reusability, and reproducibility by maintaining complete data provenance with unique identifiers. To promote findability, we have built an advanced search engine to identify datasets, samples, modules, and more, by filtering standardized metadata (e.g., find gene coexpression modules in human glioblastoma datasets that are significantly enriched with markers of T-cells). A detailed description of OMICON’s functionality is described on our Help page: theomicon.ucsf.edu/home/help. Through this functionality, OMICON seeks to build community and focus therapeutic efforts around reproducible analyses of transcriptional variation in normal human brain and brain tumors.
EPCO-34. DECIPHERING THE LONGITUDINAL TRAJECTORIES OF GLIOBLASTOMA BY INTEGRATIVE SINGLE-CELL GENOMICS
Authors: Spitzer Avishay , Johnson Kevin C , Nomura Masashi , Garofano Luciano , Nehar-belaid Djamel , Darnell Noam Galili , Greenwald Alissa C , Bussema Lillian , Oh Young Taek , Varn Frederick S , D’Angelo Fulvio , Gritsch Simon , Anderson Kevin J , Migliozzi Simona , Castro L Nicolas Gonzalez , Chowdhury Tamrin , Robine Nicolas , Reeves Catherine , Park Jong Bae , Lipsa Anuja , Hertel Frank , Golebiewska Anna , Niclou Simone P , Nusrat Labeeba , Kellet Sorcha , Das Sunit , Moon Hyo-Eun , Paek Sun Ha , Bielle Franck , Laurenge Alice , Stefano Anna Luisa Di , Mathon Bertrand , Picca Alberto , Sanson Marc , Tanaka Shota , Saito Nobuhito , Ashley David M , Keir Stephen T , Huse Jason T , Yung W K Alfred , Lasorella Anna , Iavarone Antonio , Verhaak Roel G W , Tirosh Itay , Suvà Mario L 
Published: November 2024

Abstract
The evolution of cellular heterogeneity in IDH-wildtype glioblastoma (GBM) after standard-of-care therapy remains poorly understood. To address it, we assembled a longitudinal cohort of 121 primary and recurrent GBM specimens from 59 patients, with extensive clinical annotations, and profiled it by single-nucleus RNA-sequencing and bulk tumor DNA sequencing. In most cases, longitudinal samples diverged in their composition of cell types and cell states. However, almost all theoretical trajectories were observed in our cohort such that the overall distribution of cell types and cell states was comparable between primary and recurrent samples. The most consistent longitudinal effect (66% of patients) was a lower malignant cell fraction at recurrence and a reciprocal increase in proportions of glio-neuronal TME cell types; in some cases, this was further accompanied by a coordinated shift of malignant cells towards neuronal-like states. MGMT methylation and radiation-related small deletion phenotypes were linked to particular trajectories, with depletion of mesenchymal-like cells and enrichment of hypoxia-related malignant cells, respectively. Importantly, changes in malignant states were also associated with specific changes in TME composition. In summary, our analysis highlights diverse longitudinal GBM trajectories that are shaped by treatment response and TME interactions.
EPCO-38. IDENTIFYING THE MOLECULAR SIGNATURE OF INFILTRATING EDGE IN GLIOBLASTOMA AS DRIVERS OF TUMOUR INVASION AND RECURRENCE
Authors: Ivanova Alyona , Ayyadhury Shamini , Wu Megan , Munoz David G , Pugh Trevor , Das Sunit 
Published: November 2024

Abstract
Complete tumour resection in glioblastoma patients is not possible. Residual therapy-resistant edge-derived cells drive tumour recurrence and infiltrative expansion in glioblastoma. Features that are specific to malignant edge-derived cells may serve as predictive biomarkers to allow individual tailoring of the treatment plan to slow down tumour invasion and prevent tumour recurrence in GBM patients following standard therapy. Intratumoural spatial heterogeneity facilitates therapeutic resistance and recurrence in glioblastoma. Our knowledge on glioblastoma heterogeneity is mostly restricted to the surgically resectable tumour core, while the functional characterization of tumour cells at the infiltrating edge remains largely elusive due to the presence of normal functional brain tissue in the peritumoural lesion. Edge-derived cells exhibit larger capacity for infiltrative expansion and are the main drivers of treatment failure and tumour recurrence, making them action targets for novel treatment approaches in glioblastoma. To resolve the transcriptional heterogeneity of GBM within the spatial context, we profiled gene expression of different tumour regions (“edge” and “core”) obtained at initial surgical resection from primary and recurrent IDH-WT GBM patients with Visium 10x and GeoMx. We show that infiltrative edge-derived cells are spatially segregated and are characterized by regionally shared distinct genomic and transcriptomic signatures that promote invasiveness and underly disease recurrence. Tumour edge is enriched for neuronal signatures, while tumour core displays larger transcriptional subpopulation diversity and abundance of proliferative cells with a high capacity for self-renewal, consistent with the proliferative and cancer stem cell-enriched phenotype in early GBM progressors. Upregulated DEGs of tumour edge cells are significantly associated with ion regulation of transport, chemical synaptic transmission, and nervous system development. These modules may represent tumour cell hijacking of neuronal programs specifically at the tumour periphery as described in the context of glioma-neuron synaptic communication and formation of neurite-like microtubes. Upregulation of ion regulation transport at the tumour periphery indicates enhanced neuronal activity and excitability driving infiltrating growth.
EPCO-40. TRANSCRIPTIONAL TRAJECTORY INFERENCE OF IMAGE-LOCALIZED, MULTI-REGIONAL HIGH-GRADE GLIOMA BIOPSIES REVEALS DISTINCT POPULATION ECOLOGIES AND SEX-ASSOCIATED ENRICHED PATHWAYS
Authors: Curtin Lee , Bond Kamila , Singleton Kyle , Jackson Pamela , Sereduk Christopher , Krishna Chandan , Zimmerman Richard , Patra Devi , Donev Kliment , Mrugala Maciej , Tran Nhan , Hu Leland , Bendok Bernard , Al-Dalahmah Osama , Canoll Peter , Swanson Kristin 
Published: November 2024

Abstract
The intra- and inter-patient heterogeneity in high-grade glioma (HGG) continues to contribute to its poor prognosis. Clinical biopsies are often harvested from limited regions and typically are not image localized. Thus, they fail to capture the diversity within tumor regions, immune expression or normal cell abundances that play key roles in tumor development. It is important to gain an understanding of these subpopulation ecologies, their spatial resolution, and interactions between them that may then be exploited for future therapeutic benefit. Further, these may differ by patient characteristics such as sex, age at diagnosis and treatment status. Using an ongoing image-localized biopsy collection protocol, we have so far evaluated the bulk transcriptomics of 202 multi-regional biopsies from 58 patients to characterize HGG heterogeneity. These samples were processed through Monocle, a reverse graph embedding algorithm that groups samples into states and orders them along developmental trajectories. Deconvolution methods were previously used to predict relative abundances of 7 normal, 6 glioma, and 5 immune cell subpopulations for each sample, which we have now overlaid on the Monocle graph. Monocle classified HGG into 4 main states along a three-pronged trajectory. These states reveal distinct population ecologies with associated enriched gene pathways. We also note significant immune pathway enrichments that differ between state and patient-reported sex. Together, these algorithms reveal a simple transcriptomic trajectory that helps us understand the development and evolution of HGG. Characterizing the in vivo diversity within and between high grade gliomas is important for understanding prognosis, stratifying future treatments and ultimately improving patient outcome.
EPCO-41. THE NUCLEOSOME REMODELING AND DEACETYLASE COMPLEX UNDERLIES SELECTIVE DEPENDENCY IN H3 G34-MUTANT DIFFUSE HEMISPHERIC GLIOMA
Authors: Roach Jordan , Kasper Lawryn , Andrews Jared , He Chen , Hover Laura , Adorno Jennifer Ocasio , Teis Robert , Laffy Julie , Nomura Masashi , Boop Frederick , Klimo Paul , Chiang Jason , Abraham Brian , Tirosh Itay , Suvà Mario , Baker Suzanne 
Published: November 2024

Abstract
Pediatric-type diffuse high-grade gliomas are fatal central nervous system malignancies of childhood. Recurrent mutations in histone H3.3 at amino acid 34 (glycine to arginine/valine) are a defining molecular feature of diffuse hemispheric glioma, H3 G34-mutant (H3 G34-mutant DHG), which arises preferentially in adolescents and young adults. Single-nuclei sequencing of age and anatomically matched H3 wild-type and H3 G34-mutant primary patient tumors identified aberrant neuronal-like transcriptional programs enriched for signatures of cortical interneurons derived from the medial ganglionic eminence. The extent to which these molecular signatures reflect cancer dependencies in H3 G34-mutant DHG is poorly understood. To identify transcriptional vulnerabilities governing cellular state and underlying developmental lineage, we performed CRISPR screening targeting the DNA-binding domains of 1,427 proteins in H3 G34-mutant DHG (n=6) and H3 K27-altered diffuse midline glioma (DMG) (n=3). Through these efforts, we identified developmentally relevant transcription factor vulnerabilities corresponding to neuronal and oligodendrocyte precursor cell-like hierarchies comprising H3 G34-mutant DHG and H3 K27-altered DMG cellular states, respectively. Intriguingly, we also identified multiple members of the nucleosome remodeling and deacetylase (NuRD) complex as selective dependencies in H3 G34-DHG compared to H3 K27-altered DMG and 32 other cancer cell line models screened using the same DNA-binding domain library. Genetic perturbation of the holo-NuRD structural subunit MBD3 conferred an upregulation of genes involved in neuronal differentiation and synapse formation consistent with NuRD-mediated modulation of the aberrant neuronal-like cell hierarchy observed in H3 G34-mutant DHG. To therapeutically target NuRD-associated class I HDAC activity, patient-derived H3 G34-mutant DHG cell lines were treated with quisinostat, a highly potent class I and II HDAC inhibitor. Pharmacologic inhibition of HDAC activity was sufficient to impair cell growth in vitro. Ongoing experiments are evaluating dependencies in vivo. Our results may suggest a differential requirement for chromatin repressive complex dysregulation in the pathogenesis of oncohistone-mutant pediatric-type diffuse high-grade gliomas.