Browse
Submit Data
Databases
API
Help

Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

12 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

CRC samples for FOLFOX therapy prediction

ABSTRACT: The aim of this study is to identify responders to FOLFOX therapy by applying the Random Forests (RF) algorithm to gene expression data. Eighty-three unresectable colorectal cancer (CRC) patients including 42 responders and 41 non-responders were divided into training (54 patients) and test (29 patients) sets. Samples were divided (approximately 2:1 ratio) into training and test sets. As a result, 54 of 83 samples obtained in the first half of this period were selected for the training set, and the remaining 29 samples in the latter half were selected as the test set.

ORGANISM(S): Homo sapiens

SUBMITTER: Shingo Tsuji

PROVIDER: E-GEOD-28702 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Publications

Potential responders to FOLFOX therapy for colorectal cancer by Random Forests analysis.

Tsuji S S Midorikawa Y Y Takahashi T T Yagi K K Takayama T T Yoshida K K Sugiyama Y Y Aburatani H H

British journal of cancer 20111117 1

<h4>Background</h4>Molecular characterisation using gene-expression profiling will undoubtedly improve the prediction of treatment responses, and ultimately, the clinical outcome of cancer patients.<h4>Methods</h4>To establish the procedures to identify responders to FOLFOX therapy, 83 colorectal cancer (CRC) patients including 42 responders and 41 non-responders were divided into training (54 patients) and test (29 patients) sets. Using Random Forests (RF) algorithm in the training set, predict ...[more]

PMID: 22095227

Similar Datasets

CRC samples for FOLFOX therapy prediction

Project description:The aim of this study is to identify responders to FOLFOX therapy by applying the Random Forests (RF) algorithm to gene expression data. Eighty-three unresectable colorectal cancer (CRC) patients including 42 responders and 41 non-responders were divided into training (54 patients) and test (29 patients) sets.

2011-11-21 | GSE28702 | GEO

Resistance to aerobic exercise training causes metabolic dysfunction and reveals novel exercise-regulated signaling networks

Project description:Low aerobic exercise capacity is a risk factor for diabetes and strong predictor of mortality; yet some individuals are exercise resistant, and unable to improve exercise capacity through exercise training. To test the hypothesis that resistance to aerobic exercise training underlies metabolic disease-risk, we used selective breeding for 15 generation to develop rat models of low- and high-aerobic response to training. Before exercise training, rats selected as low- and high-responders had similar exercise capacities. However, after 8-wks of treadmill training low-responders failed to improve their exercise capacity, while high-responders improved by 54%. Remarkably, low-responders to aerobic training exhibited pronounced metabolic dysfunction characterized by insulin resistance and increased adiposity, demonstrating that the exercise resistant phenotype segregates with disease risk. Low-responders had impaired exercise-induced angiogenes0is in muscle; however, mitochondrial capacity was intact and increased normally with exercise training, demonstrating that mitochondria are not limiting for aerobic adaptation or responsible for metabolic dysfunction in low-responders. Low-responders had increased stress/inflammatory signaling and altered TGFβ signaling, characterized by hyperphosphorylation of a novel exercise-regulated phosphorylation site on SMAD2. Using this powerful biological model system we have discovered key pathways for low exercise training response that may represent novel targets for the treatment of metabolic disease.

2014-05-23 | GSE57880 | GEO

Resistance to aerobic exercise training causes metabolic dysfunction and reveals novel exercise-regulated signaling networks

Project description:Low aerobic exercise capacity is a risk factor for diabetes and strong predictor of mortality; yet some individuals are exercise resistant, and unable to improve exercise capacity through exercise training. To test the hypothesis that resistance to aerobic exercise training underlies metabolic disease-risk, we used selective breeding for 15 generation to develop rat models of low- and high-aerobic response to training. Before exercise training, rats selected as low- and high-responders had similar exercise capacities. However, after 8-wks of treadmill training low-responders failed to improve their exercise capacity, while high-responders improved by 54%. Remarkably, low-responders to aerobic training exhibited pronounced metabolic dysfunction characterized by insulin resistance and increased adiposity, demonstrating that the exercise resistant phenotype segregates with disease risk. Low-responders had impaired exercise-induced angiogenes0is in muscle; however, mitochondrial capacity was intact and increased normally with exercise training, demonstrating that mitochondria are not limiting for aerobic adaptation or responsible for metabolic dysfunction in low-responders. Low-responders had increased stress/inflammatory signaling and altered TGFM-NM-2 signaling, characterized by hyperphosphorylation of a novel exercise-regulated phosphorylation site on SMAD2. Using this powerful biological model system we have discovered key pathways for low exercise training response that may represent novel targets for the treatment of metabolic disease. Cardiac and skeletal muscle from 3 high and 3 low responder rats were examined for differential miRNA expression using Exiqon microarrays

2014-05-23 | E-GEOD-57880 | biostudies-arrayexpress

Gene expression signature and the prediction of liver metastasis in colorectal cancer by DNA microarray

Project description:Samples were taken from colorectal cancers in surgically resected specimens in 189 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133 Plus 2.0 arrays. Comparison between the sample groups allow to identify a set of discriminating genes that can be used for molecular markers for predicting liver metastasis. Keywords: repeat One hundred and eighty nine patients who underwent surgical resection of colorectal cancer were included in this study. Patients were evaluated at 3-month intervals for the first postoperative year and at 6-month intervals thereafter. Liver metastases were identified by clinical and laboratory examination, completed by liver ultrasound or CT scan. Patients were divided randomly into a training and a validation set. A training set consisted of 160 patients, while a test set 29 patients.

2011-08-25 | E-GEOD-14095 | biostudies-arrayexpress

A novel combination of serum microRNAs for detecting breast cancer in the early stage

Project description:MicroRNAs (miRNAs), which are stably present in serum, have been reported to be potentially useful for detecting cancer. In the present study, we examined the expression profiles of serum miRNAs in large cohorts to identify the miRNAs that can be used to detect breast cancer in the early stage. We comprehensively evaluated serum miRNA expression profiles using highly sensitive microarray analysis. A total of 1,280 serum samples of breast cancer patients stored in the National Cancer Center Biobank were used. Additionally, 2,836 serum samples were obtained from non-cancer controls and 514 from patients with other types of cancers or benign diseases. The samples were divided to a training cohort including non-cancer controls, other cancers and breast cancer and a test cohort including non-cancer controls and breast cancer. The training cohort was used to identify a combination of miRNAs that detect breast cancer, and the test cohort was used to validate that combination. miRNA expression was compared between breast cancer and non-breast cancer serum , and a combination of five miRNAs (miR-1246, miR-1307-3p, miR-4634, miR-6861-5p, and miR-6875-5p) was found to detect breast cancer. This combination had a sensitivity of 97.3%, specificity of 82.9%, and accuracy of 89.7% for breast cancer in the test cohort Additionally, the combination could detect breast cancer in the early stage (sensitivity of 98.0% for T0). 1280 breast cancer serums (74 in training cohort, 1206 in test cohort), 54 benign breast diseases serums in test cohort, 2836 non-cancer control serums (1493 in training cohort, 1343 in test cohort), 514 non-breast benign diseases serums in training cohort. 150 of the non-cancer control serums in training cohort and 412 of the non-breast benign diseases serums in training cohort have been uploaded previously and are avaialable under GSE59856 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59856).

2016-01-21 | E-GEOD-73002 | biostudies-arrayexpress

Integrated proteomics and phosphoproteomics revealed druggable kinases in neoadjuvant chemotherapy resistant tongue cancer

Project description:Tongue squamous cell carcinoma is characterised by poor prognosis and high metastatic events. Patients with unresectable tumors are benefiting from neoadjuvant chemotherapy (NACT) which surgical resection, and controls distant metastasis, and locoregional recurrence. However, resistance to NACT limit the success of the treatment regimen. In this study, we investigated the altered proteome and phosphoproteome of NACT resistant and sensitive cohort using Mass spectrometry-based proteomics. We carried out proteomic as well as phosphoproteomic analysis of treatment naïve tongue cancer patients whose response to NACT is recorded. Proteomic analysis revealed distinct protein expression between the responders and non-responders. The Phosphoproteomic analysis revealed kinases and the pathways associated with NACT resistance in tongue cancer.

2023-03-11 | PXD037356 | Pride

Plasma Proteomic Analysis Based on 4D-DIA Evaluates the Clinical Response to Imrecoxib in the Early Treatment of Osteoarthritis

Project description:Nonsteroidal anti-inflammatory drugs (NSAIDs) are the primary treatment for osteoarthritis (OA), but prolonged use has adverse effects and varying efficacy. Among NSAIDs, imrecoxib, a selective cyclooxygenase-2 (COX-2) inhibitor, reduces side effects yet remains ineffective for half the patient population. This study aims to identify biomarkers for early imrecoxib efficacy evaluation in OA for personalized therapy optimization. From September 2021 to January 2022, imrecoxib was administered to patients with OA at Nanjing Drum Tower Hospital. Plasma samples from these patients underwent proteomic analysis through the four-dimensional data-independent acquisition (4D-DIA) method, followed by bioinformatics analysis. Potential differentially expressed proteins (DEPs) were validated using enzyme-linked immunosorbent assay (ELISA). Sixty-six patients with knee OA were included and divided into responders (n=35) and non-responders (n=31). Proteomic analysis was conducted on 15 patients from each group, and ELISA validation was performed for every patient. We found 140 DEPs between the two groups after administering imrecoxib treatment, characterized by 29 proteins showing up-regulation and 111 displaying down-regulation (p < 0.05, fold change > ±1.2). Galectin-1 (LGALS1), galectin-3 (LGALS3), and the cluster of differentiation 44 (CD44) could be utilized to evaluate the clinical response to imrecoxib in the treatment of OA after ELISA validation.This study successfully identified biomarkers for evaluating imrecoxib's clinical response in OA patients using 4D-DIA technology. These biomarkers may play a vital role in future personalized OA treatment strategies, pending further confirmation.

2024-01-19 | PXD047236 | Pride

A Nine-gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

Project description:A total of 156 LARC patients (training cohort n = 60; validation cohort n = 96) were included in the study who underwent surgical resection post PCRT. By using univariate and multivariate logistic regression, we identified a 9-gene signature that differentiated between responders and non-responders. ; The novel 9-gene signature is robust in predicting response to PCRT in LARC patients. Tailored treatment approaches in good and poor responders to PCRT may improve the oncologic outcomes of patients with LARC.

2019-10-23 | GSE139255 | GEO

Transcription profiling of human leukocytes from chronic myeloid leukemia patients exhibiting differing responses to imatinib

Project description:This is a class prediction experiment, where the class is the response status to imatinib (also called Gleevec), a drug used to treat patients with chronic myelogenous leukemia (CML). There are two data sets, a training set (from Leipzig, 8 Responders and 5 Non-Responders) and a validation set (from Mannheim, 8 Responders and 7 Non-Responders). The objective is to identify differentially regulated genes between CML patients who respond and those who do not respond to imatinib and confirm the results in the validation data set. The samples from blood or bone marrow of CML patients were hybridized to Affymetrix HG-U95Av2 chip and RMA was used to generate the normalized signal values.

2007-08-25 | E-GEOD-2535 | biostudies-arrayexpress

Global phosphoproteome analysis of human bone marrow reveals predictive phosphorylation markers for the treatment of acute myeloid leukemia with quizartinib

Project description:Treatment with inhibitors of the receptor tyrosine kinase FLT3 are currently studied as promising therapies in acute myeloid leukemia (AML). However, only a subset of patients benefit from these treatments and the presence of activating mutations within FLT3 can predict response to a certain extent only. AC220 (quizartinib) is an example of a potent FLT3 inhibitor1 that was studied in a recent phase II open-label study in patients with relapsed/refractory AML. The complete remission rate (including CRp and CRi) in FLT3-ITD-positive patients was 54% (50/92) and the corresponding partial remission rate (PR) was 17% (16/92)2 Thus, although the FLT3-ITD mutation status correlates with response, the error rate in stratification of patients into responders and non-responders is high, as still 29% of the FLT3-ITD-positive patients failed to respond. Exclusion of FLT3-ITD-negative patients from AC220 treatment also seems critical, as the total response rate (CRþPR) in FLT3-ITD-negative patients is substantially lower (41%, 17/41). As AC220 is a tyrosine kinase inhibitor, we hypothesized that investigating phosphorylation-based signaling on a system-wide scale in AML cells allows for identification of markers enabling more accurate prediction of therapy response as compared to commonly used genetic markers. Hence, we applied quantitative mass spectrometry to decipher a multivariate phosphorylation site marker, which we refer to as phosphosignature, in patient-derived AML blasts that might be useful as predictive biomarkers for AC220 treatment.

2017-05-10 | PXD006475 | Pride

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