Browse
Submit Data
Databases
API
Help

Dataset Information

46 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Integrative Omics Analysis for Colorectal Cancer and Metastasis

ABSTRACT: The pathogenesis of Colorectal cancer (CRC) metastasis remains unclear.We collect clinical data from our center and use Integrative omics to analyze and predict candidate biomarkers of colorectal cancer and distant metastasis.

DISEASE(S): Neoplasm Metastasis,Colorectal Cancer,Colorectal Neoplasms

PROVIDER: 2743637 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Json Xml

Similar Datasets

chinse healthy integrative omics project cohort

Project description:chinse healthy integrative omics project

| PRJEB36271 | ENA

Integrative omics analysis in HCC samples

Project description:Integrative omics analysis in HCC samples

| PRJNA327799 | ENA

Integrative Multi‑omics Analysis Reveals Candidate Biomarkers for Oral Squamous Cell Carcinoma

Project description:Integrative Multi‑omics Analysis Reveals Candidate Biomarkers for Oral Squamous Cell Carcinoma

| PRJNA775998 | ENA

Proteogenomic characterization and comprehensive integrative genomic analysis of human colorectal cancer liver metastasis

Project description:Colorectal cancer (CRC) is the third most common cancer worldwide and liver metastasis remains the major cause of death in CRC. Extensive genomic analysis provided valuable insight into the pathogenesis and progression of CRC. However, the major proteogenomic characterization of CRC liver metastasis is still unknown. We investigated proteogenomic characterization and performed comprehensive integrative genomic analysis of human colorectal cancer liver metastasis.

2019-12-27 | GSE93286 | GEO

Multi-Omics Analysis of Brain Metastasis Outcomes Following Craniotomy

Project description:Purpose: To reveal multi-omics features and disease subtypes associated with brain metastasis outcomes following craniotomy Methods: We executed a single institution retrospective collection of brain metastasis from patients who were diagnosed with lung, breast, and other primary tumors. The brain metastatic samples were sent for RNA sequencing, proteomic and metabolomic analysis of brain metastasis. The primary outcome was distant brain failure after definitive therapies that included craniotomy resection and radiation to surgical bed. Novel prognostic subtypes were discovered using transcriptomic data and sparse non-negative matrix factorization. Results: We discovered two molecular subtypes showing statistically significant differential prognosis irrespective of tumor subtype. The median survival time of the good and the poor prognostic subtypes were 7.89 and 42.27 months, respectively. Further integrated characterization and analysis of these two distinctive prognostic subtypes using transcriptomic, proteomic, and metabolomic molecular profiles of patients identified key pathways and metabolites. The analysis suggested that immune microenvironment landscape as well as proliferation and migration signaling pathways may be responsible to the observed survival difference. Conclusions: A multi-omics approach to characterization of brain metastasis provides an opportunity to identify clinically impactful biomarkers and associated prognostic subtypes and generate provocative integrative understanding of disease.

2021-01-04 | GSE164150 | GEO

Integrative multi-omics analysis in sepsis-associated liver dysfunction

Project description:we conducted integrative multiple levels of omics data including transcriptome, phosphoproteome, proteome and metabolome in different time-course of sepsis-associated liver dysfunction (SALD). This is the first trial to suggest the statistical pathway of integrative multi-omics data in sepsis. Given the increasing number of studies collecting multi-omics data but limited overview of the methodological framework for integrative analyses (Liu, Ding et al. 2013, Petersen, Zeilinger et al. 2014, Shah, Bonder et al. 2015), integrative approach in sepsis with liver dysfunction in this study will provide novel insights into the development of sepsis and ultimately offer new tools for overcoming the present diagnostic limitation. Therefore, a combined multi-omics dataset will give better accessibility of adoption in disease, and insight to identify the promising candidates for therapeutic strategies.

2023-06-21 | PXD025800 | Pride

Integrative omics analysis in HCC samples [mRNA expression]

Project description:38 paires of tumor tissues and adjacent non-tumor tissues from HCC patients The number of known lncRNAs increased sharply upon the tiling microarrays and RNA-sequencing were applied to identify lncRNAs. However, only about a dozen of lncRNAs have been well characterized and demonstrated to be tightly associated with development and progression of HCC. A major challenge remains to identify functional lncRNAs associated with HCC. Previous reports mainly selected differentially expressed lncRNAs in cancer tissue or cell lines as candidates for further validation and characterizing. Here, based on mRNA and lncRNA gene expression profiles data collected from tumor and adjacent normal tissues of thirty-eight HCC patients, we adapted integrative omics strategy to identify HCC-associated lncRNAs.

2017-06-21 | GSE84005 | GEO

Integrative omics analysis in HCC samples [lncRNA expression]

2017-06-21 | GSE84004 | GEO

A multi-omics integrative network map of maize.

Project description:A multi-omics integrative network map of maize.

| PRJNA822292 | ENA

Integrative multi-omics analysis of intestinal organoid differentiation

Project description:Integrative multi-omics analysis of intestinal organoid differentiation

| PRJNA464352 | ENA