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Links from GEO DataSets

Items: 20

1.

Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.
Organism:
Homo sapiens
Type:
Genome variation profiling by genome tiling array; Expression profiling by array
Platforms:
GPL16070 GPL570
1048 Samples
Download data:
GEO (CEL, GPR)
Series
Accession:
GSE40967
ID:
200040967
2.

Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [CGH]

(Submitter supplied) From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. more...
Organism:
Homo sapiens
Type:
Genome variation profiling by genome tiling array
Platform:
GPL16070
463 Samples
Download data:
GEO (GPR, TXT)
Series
Accession:
GSE40966
ID:
200040966
3.

Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]

(Submitter supplied) From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and 19 non-tumoral colorectal mucosas, and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Platform:
GPL570
585 Samples
Download data:
GEO (CEL)
Series
Accession:
GSE39582
ID:
200039582
4.

The prognostic and predictive value of a six-microRNA-based classifier in stage II colon cancer

(Submitter supplied) microRNA profiling of colon tumor tissues vs adjacent normal tissues
Organism:
Homo sapiens
Type:
Non-coding RNA profiling by array
Platform:
GPL17496
80 Samples
Download data:
GEO (GPR)
Series
Accession:
GSE49246
ID:
200049246
5.

Genome-wide DNA methylation study in bladder cancer

(Submitter supplied) Genome-wide DNA methylation profiles were determined on a set of fresh 44 bladder cancer tissues using normal blood as control. DNA amplicons were prepared using Differential Methylation Hybridization (DMH) method, subsequently hybridized on to the Agilent Human CpG island Microarray. The goal was to unravel the DNA methylation patterns in different subgropus of bladder cancer along with finding markers for progresssion and early diagnosis.
Organism:
Homo sapiens
Type:
Methylation profiling by genome tiling array
Platform:
GPL4126
44 Samples
Download data:
GEO (TXT)
Series
Accession:
GSE35824
ID:
200035824
6.

Gene level expression profiling of colorectal cancer tissue samples (test sample series)

(Submitter supplied) This series is part of a larger series (GSE24549) of colorectal cancer tissue samples analyzed for global gene expression. The expression measures were used to develope a gene signature for prediction of prognosis in stage II and III colorectal cancer.
Organism:
Homo sapiens
Type:
Expression profiling by array
Platform:
GPL5175
95 Samples
Download data:
GEO (CEL, CHP)
Series
Accession:
GSE30378
ID:
200030378
7.

Gene level expression profiling of colorectal cancer tissue samples

(Submitter supplied) By the use of whole genome transcription analysis, we aimed to develop a gene expression classifier to increase the likelihood of identifying stage II colorectal cancer (CRC) samples with a poor prognostic outcome. Gene expression measurement were measured by the GeneChip® Human Exon 1.0 ST Arrays from Affymetrix.
Organism:
Homo sapiens
Type:
Expression profiling by array
Platform:
GPL5175
50 Samples
Download data:
GEO (CEL, CHP)
Series
Accession:
GSE29638
ID:
200029638
8.

Exon level expression profiling of colorectal cancer tissue samples

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.
Organism:
Homo sapiens
Type:
Expression profiling by array
Platforms:
GPL5175 GPL11028
333 Samples
Download data:
GEO (CEL, CHP)
Series
Accession:
GSE24551
ID:
200024551
9.

Exon level expression profiling of colorectal cancer tissue samples (validation sample series).

(Submitter supplied) Colorectal cancer is a heterogeneous disease molecularly characterized by inherent genomic instabilities, chromosome instability and microsatellite instability. In the present study we propose transcriptome instability as an analogue to genomic instability on the transcriptome level. Exon microarray data from two independent series of altoghether 160 colorectal cancer tissue samples was used for global alternative splicing detection using the FIRMA algorithm (aroma.affymetrix). more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Platforms:
GPL11028 GPL5175
167 Samples
Download data:
GEO (CEL, CHP)
Series
Accession:
GSE24550
ID:
200024550
10.

Exon level expression profiling of colorectal cancer tissue samples (test sample series).

(Submitter supplied) Colorectal cancer is a heterogeneous disease molecularly characterized by inherent genomic instabilities, chromosome instability and microsatellite instability. In the present study we propose transcriptome instability as an analogue to genomic instability on the transcriptome level. Exon microarray data from two independent series of altoghether 160 colorectal cancer tissue samples was used for global alternative splicing detection using the FIRMA algorithm (aroma.affymetrix). more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Platforms:
GPL5175 GPL11028
166 Samples
Download data:
GEO (CEL, CHP)
Series
Accession:
GSE24549
ID:
200024549
11.

Gene expression profiling of the 20 human early breast carcinomas by three miaroarray platforms

(Submitter supplied) In this study, we profiled gene expressions on 20 biopsy tissues of early stage breast carcinoma using Applied Biosystem’s Human Genome Survey Microarrays. Two main previously defined clinically relevant subtypes of breast tumors, Luminal A (longest survival time) and Basal (shortest survival time) were identified. Statistical analysis identified 1210 genes as signature genes characterizing the two subtypes of breast cancer. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Platforms:
GPL1843 GPL1426 GPL1708
80 Samples
Download data:
GEO
Series
Accession:
GSE3155
ID:
200003155
12.

Chronic hypoxia in patients with colon carcinoma

(Submitter supplied) In Western countries, colorectal cancer (CRC) is the third most common cancer in both men and women and the second leading cause of cancer-related deaths (approximately 500,000 deaths annually). For CRC, the tumor stage is the main prognostic factor for survival or relapse after surgery. Current staging is based on the AJCC classification which takes into account tumor size/depth, lymph node involvement and distant metastases. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Platform:
GPL6480
8 Samples
Download data:
GEO (TXT)
Series
Accession:
GSE31079
ID:
200031079
13.

Gastric Cancer Subtyping (Australian Patient Cohort)

(Submitter supplied) Genome-wide mRNA expression profiles of 70 primary gastric tumors from the Australian patient cohort. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Dataset:
GDS4198
Platform:
GPL570
70 Samples
Download data:
GEO (CEL)
Series
Accession:
GSE35809
ID:
200035809
14.

Gastric cancer subtyping (Singapore Patient Cohort, batch B)

(Submitter supplied) Genome-wide mRNA expression profiles of 56 primary gastric tumors from the Singapore patient cohort, batch B. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Platform:
GPL570
56 Samples
Download data:
GEO (CEL, XLS)
Series
Accession:
GSE34942
ID:
200034942
15.

Genetic Landscape of Copy Number Alterations in Gastric Cancer

(Submitter supplied) Genome-wide DNA copy number profiling of gastric tumors and matched non-maligant samples. The affymetrix SNP6 array was used to obtain DNA copy number profiles in 193 gastric tumors and 98 matched gastric non-malignant samples.
Organism:
Homo sapiens
Type:
Genome variation profiling by SNP array
Platform:
GPL6801
291 Samples
Download data:
GEO (CEL, CNCHP)
Series
Accession:
GSE31168
ID:
200031168
16.

Epigenetic analysis of gastric cancer

(Submitter supplied) Genome-wide DNA methylation profiling of gastric tumors and matched gastric non-malignant samples. The Illumina HumanMethylation27 BeadChip was used to obtain DNA methylation profiles across 27,578 CpGs in 203 gastric tumors and 94 matched non-malignant gastric samples.
Organism:
Homo sapiens
Type:
Methylation profiling by array
Platform:
GPL8490
297 Samples
Download data:
GEO (TXT)
Series
Accession:
GSE30601
ID:
200030601
17.

GEMINI (Gastric Encyclopedia of Molecular Interactions and Nodes for Intervention) : 37 unique Gastric cancer cell lines

(Submitter supplied) Genome-wide mRNA expression profiles of 37 unique gastric cancer cell lines (GCCLs). Keywords: gastric cancer, cell culture
Organism:
Homo sapiens
Type:
Expression profiling by array
Platform:
GPL570
37 Samples
Download data:
GEO (CEL)
Series
Accession:
GSE22183
ID:
200022183
18.

Gastric Cancer Project '08 (Singapore Patient Cohort)

(Submitter supplied) Genome-wide mRNA expression profiles of 200 primary gastric tumors from the Singapore patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Platform:
GPL570
200 Samples
Download data:
GEO (CEL, XLS)
Series
Accession:
GSE15459
ID:
200015459
19.
Full record GDS4198

Australian patient cohort: gastric adenocarcinoma

Analysis of 70 primary gastric tumors representing 3 subtypes (invasive, metabolic, and proliferative) from the Australian patient cohort (AU-2). Gastric adenocarcinomas show sizable heterogeneity between patients. Results provide insight into molecular characterization of gastric cancer subtypes.
Organism:
Homo sapiens
Type:
Expression profiling by array, transformed count, 3 disease state sets
Platform:
GPL570
Series:
GSE35809
70 Samples
Download data:
GEO (CEL)
DataSet
Accession:
GDS4198
ID:
4198
20.

Correlation of molecular profiles and clinical outcome of stage UICC II colon cancer patients

(Submitter supplied) Background Published multi-gene classifiers suggested outcome prediction for patients with stage UICC II colon cancer based on different gene expression signatures. However, there is currently no translation of these classifiers for application in routine diagnostic. Therefore, we aimed at validating own and published gene expression signatures employing methods which enable RNA and protein detection in routine diagnostic specimens. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Dataset:
GDS4513
Platform:
GPL570
53 Samples
Download data:
GEO (CEL)
Series
Accession:
GSE18088
ID:
200018088
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