Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Molecular and functional landscape of malignant serous effusions for precision oncology [MSE_drug_treated]

ABSTRACT: Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells. These patients frequently develop malignant serous effusions (MSE). The value of MSE-based tumor cell characterization for guiding precision oncology is, however, currently unclear. Here, we present a comprehensive characterization of a pan-cancer cohort of 150 MSE samples at the cellular, molecular, and functional level. Our integrative analysis reveals dynamic cellular heterogeneity in MSE, and uncovers links between tumor driver mutations and ex vivo growth patterns. Strong concordance between genomic and transcriptional profiles of MSE and their corresponding solid tumors validates their use as a model system for solid tumor biology. We link baseline gene expression patterns to global ex vivo drug sensitivity, and demonstrate that drug-induced transcriptional changes in MSE are highly indicative of compound mode of action. Two case studies exemplify the utility of our approach in investigating acquired resistance to targeted therapy and identifying treatment options for relapsed solid tumors. In summary, our study provides a functional multi-omics view on a pan-cancer MSE cohort and underlines the utility of MSE-based precision oncology.

ORGANISM(S): Homo sapiens

PROVIDER: GSE240951 | GEO | 2024/08/26

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Molecular and functional landscape of malignant serous effusions for precision oncology [MSE_baseline]

Project description:Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells. These patients frequently develop malignant serous effusions (MSE). The value of MSE-based tumor cell characterization for guiding precision oncology is, however, currently unclear. Here, we present a comprehensive characterization of a pan-cancer cohort of 150 MSE samples at the cellular, molecular, and functional level. Our integrative analysis reveals dynamic cellular heterogeneity in MSE, and uncovers links between tumor driver mutations and ex vivo growth patterns. Strong concordance between genomic and transcriptional profiles of MSE and their corresponding solid tumors validates their use as a model system for solid tumor biology. We link baseline gene expression patterns to global ex vivo drug sensitivity, and demonstrate that drug-induced transcriptional changes in MSE are highly indicative of compound mode of action. Two case studies exemplify the utility of our approach in investigating acquired resistance to targeted therapy and identifying treatment options for relapsed solid tumors. In summary, our study provides a functional multi-omics view on a pan-cancer MSE cohort and underlines the utility of MSE-based precision oncology.

2024-08-26 | GSE240952 | GEO

Lipid Profiles of Human Brain Tumors Obtained by High-Resolution Negative Mode Ambient Mass Spectrometry

Project description:<p>Alterations in cell metabolism, including changes in lipid composition occurring during malignancy, are well characterized for various tumor types. However, a significant part of studies that deal with brain tumors have been performed using cell cultures and animal models. Here, we present a dataset of 124 high-resolution negative ionization mode lipid profiles of human brain tumors resected during neurosurgery. The dataset is supplemented with 38 non-tumor pathological brain tissue samples resected during elective surgery. The change in lipid composition alterations of brain tumors enables the possibility of discriminating between malignant and healthy tissues with the implementation of ambient mass spectrometry. On the other hand, the collection of clinical samples allows the comparison of the metabolism alteration patterns in animal models or in vitro models with natural tumor samples ex vivo. The presented dataset is intended to be a data sample for bioinformaticians to test various data analysis techniques with ambient mass spectrometry profiles, or to be a source of clinically relevant data for lipidomic research in oncology.</p>

2021-11-18 | MTBLS1558 | MetaboLights

A Single-Cell Tumor Immune Atlas for Precision Oncology

Project description:A Single-Cell Tumor Immune Atlas for Precision Oncology

| PRJNA666613 | ENA

Synthetic lethality-mediated precision oncology via the tumor transcriptome

Project description:Synthetic lethality-mediated precision oncology via the tumor transcriptome

| PRJNA700986 | ENA

Deconvolution of Cell Type-Specific Drug Responses in Human Tumor Tissue with Single-Cell RNA-seq

Project description:Precision oncology requires the timely selection of effective drugs or drug combinations for individual patients. The ideal platform would enable rapid screening of cell type-specific drug sensitivities directly in patient tumor tissue and reveal strategies to overcome intratumoral heterogeneity. Here we combine multiplexed drug perturbation in acute slice culture from freshly resected tumors with single-cell RNA sequencing (scRNA-seq) to profile transcriptome-wide drug responses in individual patients. We applied this approach to glioblastoma (GBM) and demonstrated that acute slice cultures recapitulate the cellular and molecular features of the originating tumor tissue. Detailed investigation of etoposide, a topoisomerase poison, and the histone deacetylase (HDAC) inhibitor Panobinostat in acute slice cultures revealed cell type-specific responses across multiple patients, including unexpected effects on the immune microenvironment. We anticipate that this approach will facilitate rapid, personalized drug screening to identify effective therapies for solid tumors.

2020-04-18 | GSE148842 | GEO

A Single-Cell Tumor Immune Atlas for Precision Oncology

Project description:The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell resolved tumor immune cell atlas, jointly analyzing >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system for a harmonized interpretation. To enable in situ mapping of immune populations for digital pathology, we developed SPOTlight, a computational tool that identified striking spatial immune cell patterns in tumor sections. We expect the atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification strategies for prognosis and immuno-therapy response.

2020-10-27 | GSE158803 | GEO

Characterization of a large panel of patient-derived hepatocellular carcinoma xenograft tumor models for preclinical development

Project description:We have generated a collection of patient-derived xenograft (PDX) tumor models and characterized them at the molecular level to facilitate precision oncology.

2014-03-13 | GSE55828 | GEO

Transcription profiling of mouse P5 cerebellum to investigate conserved mechanisms across development and tumorigenesis revealed by a mouse development perspective of neuroblastoma

Project description:Identification of common mechanisms underlying organ development and primary tumor formation should yield new insights into tumor biology and facilitate the generation of relevant cancer models. We have developed a novel method to project the gene expression profiles of medulloblastomas (MBs)—human cerebellar tumors—onto a mouse cerebellar development sequence: postnatal days 1-60 (P1-P60). Genomically, human medulloblastomas were closest to mouse P1-P10 cerebella, and normal human cerebella were closest to mouse P30-P60 cerebella. Furthermore, metastatic MBs were highly associated with mouse P5 cerebella, suggesting that a clinically distinct subset of tumors is identifiable by molecular similarity to a precise developmental stage. Genewise, down- and up-regulated MB genes segregate to late and early stages of development, respectively. Comparable results for human lung cancer vis-a-vis the developing mouse lung suggest the generalizability of this multiscalar developmental perspective on tumor biology. Our findings indicate both a recapitulation of tissue-specific developmental programs in diverse solid tumors and the utility of tumor characterization on the developmental time axis for identifying novel aspects of clinical and biological behavior. Experiment Overall Design: Time series with technical (split aliquots) replicates.

2009-01-30 | E-GEOD-14514 | biostudies-arrayexpress

Synthetic lethality-mediated precision oncology via the tumor transcriptome

Project description:Precision oncology has made significant advances in the last few years, mainly by targeting actionable mutations in cancer driver genes. However, the proportion of patients whose tumors can be targeted therapeutically remains limited. Recent studies have begun to explore the benefit of analyzing tumor transcriptomics data to guide patient treatment, raising the need for new approaches for systematically accomplishing that. Here we show that computationally derived genetic interactions can successfully predict patient response.

2021-02-11 | GSE166449 | GEO

Medium-throughput drug screening of patient-derived organoids from colorectal peritoneal metastases can be used to guide therapy

Project description:Purpose: Colorectal cancer (CRC) patients with peritoneal metastases (CRPM) have limited treatment options and the lowest CRC survival rates. We aimed to determine whether organoid testing could help guide precision treatment for CRPM patients, as the clinical utility of prospective, functional drug screening including non-standard agents is unknown. Experimental Design: CRPM organoids (peritonoids) isolated from patients underwent parallel next-generation sequencing and medium-throughput drug panel testing ex vivo to identify specific drug sensitivities for each patient. We measured the utility of such a service including: success of peritonoid generation, time to cultivate peritonoids, reproducibility of the medium-throughput drug testing, and documented changes to clinical therapy as a result of the testing. Results: Peritonoids were successfully generated and validated from 68% (19/28) of patients undergoing standard care. Genomic and drug profiling was completed within 8 weeks and a formal report ranking drug sensitivities was provided to the medical oncology team upon failure of standard care treatment. This resulted in a treatment change for 2 patients, one of whom had a partial response despite previously progressing on multiple rounds of standard care chemotherapy. The barrier to implementing this technology in Australia is the need for drug access and funding for off-label indications. Conclusions: Our approach is feasible, reproducible and can guide novel therapeutic choices in this poor prognosis cohort, where new treatment options are urgently needed. This platform is relevant to many solid organ malignancies.

2020-05-31 | GSE147971 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data