Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Predicting Human Clinical Outcomes using Mouse Multi-Organ Transcriptome

ABSTRACT: Predicting Human Clinical Outcomes using Mouse Multi-Organ Transcriptome

PROVIDER: PRJNA595856 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR10699900.fastq.gz	Fastqsanger.gz
	SRR10699901.fastq.gz	Fastqsanger.gz
	SRR10699902.fastq.gz	Fastqsanger.gz
	SRR10699903.fastq.gz	Fastqsanger.gz
	SRR10699904.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 868

Similar Datasets

Predicting Human Clinical Outcomes using Mouse Multi-Organ Transcriptome

Project description:Approximately 90% of pre-clinically validated drugs fail in clinical trials due to unanticipated clinical outcomes, costing over several hundred million US dollars per drug. Despite such critical importance, translating pre-clinical data to clinical outcomes remain a major challenge. Herein, we designed a modality-independent and unbiased approach to predict clinical outcomes of drugs. The approach exploits their multi-organ transcriptome patterns induced in mice and a unique mouse-transcriptome database “humanized” by machine learning algorithms and human clinical outcome datasets. The cross-validation with small-molecule, antibody and peptide drugs shows effective and efficient identification of the previously known outcomes of 5,519 adverse events and 11,312 therapeutic indications. In addition, the approach is adaptable to deducing potential molecular mechanisms underlying these outcomes. Furthermore, the approach identifies previously unsuspected repositioning targets. These results, together with the fact that it requires no prior structural or mechanistic information of drugs, illustrate its versatile applications to drug development process.

2020-01-09 | GSE142068 | GEO

Predicting Human Clinical Outcomes Using Mouse Multi-Organ Transcriptome.

Project description:Approximately 90% of pre-clinically validated drugs fail in clinical trials owing to unanticipated clinical outcomes, costing over several hundred million US dollars per drug. Despite such critical importance, translating pre-clinical data to clinical outcomes remain a major challenge. Herein, we designed a modality-independent and unbiased approach to predict clinical outcomes of drugs. The approach exploits their multi-organ transcriptome patterns induced in mice and a unique mouse-transcriptome database "humanized" by machine learning algorithms and human clinical outcome datasets. The cross-validation with small-molecule, antibody, and peptide drugs shows effective and efficient identification of the previously known outcomes of 5,519 adverse events and 11,312 therapeutic indications. In addition, the approach is adaptable to deducing potential molecular mechanisms underlying these outcomes. Furthermore, the approach identifies previously unsuspected repositioning targets. These results, together with the fact that it requires no prior structural or mechanistic information of drugs, illustrate its versatile applications to drug development process.

| S-EPMC7033637 | biostudies-literature

Estrogen-triggered Monkey Multi-Organ Cell Atlas

Project description:Estrogen-triggered Monkey Multi-Organ Cell Atlas

| PRJNA1019778 | ENA

Genomic tumor correlates of clinical outcomes following organ-sparing chemoradiation therapy for bladder cancer

Project description:Genomic tumor correlates of clinical outcomes following organ-sparing chemoradiation therapy for bladder cancer

| PRJNA1009888 | ENA

Genomic tumor correlates of clinical outcomes following organ-sparing chemoradiation therapy for bladder cancer

Project description:Genomic tumor correlates of clinical outcomes following organ-sparing chemoradiation therapy for bladder cancer

| PRJNA1009889 | ENA

Inter-organ transmission of hepatocellular senescence induces multi-organ dysfunction through the TGFβ signalling pathway.

Project description:Cellular senescence is associated with aging but also impacts various physiological and pathological processes such as embryonic development and wound healing. Factors secreted by senescent cells can affect their microenvironment, including local spreading of senescence. Acute severe liver disease is associated with hepatocyte senescence and frequently progresses to multi-organ failure. Why the latter occurs is poorly understood however, the presence of hepatic senescence is associated with poor prognosis and extrahepatic organ failure in acute liver disease. Here, using genetic mouse models of hepatocyte-specific senescence, we demonstrate senescence development in extrahepatic organs and associated organ dysfunction in response to liver senescence. In patients with acute indeterminate hepatitis, the extent of hepatocellular senescence predicts the occurrence of extrahepatic dysfunction, need for liver transplantation and mortality. We identify the Transforming Growth Factor β (TGFβ) pathway as a critical mediator of systemic spread of senescence and TGFβ inhibition blocks senescence transmission to other organs preventing renal dysfunction. Our results highlight the systemic consequences of organ-specific senescence which, independent of aging, contributes to multi-organ dysfunction.

2024-08-23 | GSE262705 | GEO

Inter-organ transmission of hepatocellular senescence induces multi-organ dysfunction through the TGFbeta signalling pathway

Project description:Cellular senescence is associated with aging but also impacts various physiological and pathological processes such as embryonic development and wound healing. Factors secreted by senescent cells can affect their microenvironment, including local spreading of senescence. Acute severe liver disease is associated with hepatocyte senescence and frequently progresses to multi-organ failure. Why the latter occurs is poorly understood however, the presence of hepatic senescence is associated with poor prognosis and extrahepatic organ failure in acute liver disease. Here, using genetic mouse models of hepatocyte-specific senescence, we demonstrate senescence development in extrahepatic organs and associated organ dysfunction in response to liver senescence. In patients with acute indeterminate hepatitis, the extent of hepatocellular senescence predicts the occurrence of extrahepatic dysfunction, need for liver transplantation and mortality. We identify the Transforming Growth Factor Beta (TGFbeta) pathway as a critical mediator of systemic spread of senescence and TGFbeta inhibition blocks senescence transmission to other organs preventing renal dysfunction. Our results highlight the systemic consequences of organ-specific senescence which, independent of aging, contributes to multi-organ dysfunction.

2024-08-23 | GSE267196 | GEO

Transcription profiling of normal lung from 18 multi-organ donors to analyse variance of gene expression in lung

Project description:Peripheral sections of upper and lower lung from 18 human multi-organ donors without evidence of lung disease.

2007-10-02 | E-GEOD-1643 | biostudies-arrayexpress

Single cell analysis of MCF7-derived multi-organ metastases

Project description:Single cell analysis of MCF7-derived multi-organ metastases

| PRJNA961986 | ENA

Estrogen-triggered Monkey Multi-Organ Cell Atlas [scRNA-Seq]

Project description:Estrogen-triggered Monkey Multi-Organ Cell Atlas [scRNA-Seq]

| PRJNA1019782 | ENA