Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Biomarkers in Predicting Response to Cetuximab in Patients With Advanced Colorectal Cancer

ABSTRACT: RATIONALE: Studying samples of tissue in the laboratory from patients who received cetuximab may help doctors understand and predict how well patients will respond to treatment. PURPOSE: This research study is studying biomarkers in predicting response to cetuximab in patients with advanced colorectal cancer.

DISEASE(S): Colorectal Cancer,Colorectal Neoplasms

PROVIDER: 2098259 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Json Xml

Similar Datasets

Biological Factors in Predicting Response to Treatment in Patients With Esophageal Cancer or Rectal Cancer

Project description:RATIONALE: Studying samples of tumor tissue and blood from patients with cancer in the laboratory may help doctors learn more about changes that occur in DNA and identify biomarkers related to cancer. It may also help doctors predict how patients will respond to treatment. PURPOSE: This clinical trial is studying how well biological factors work in predicting response to treatment in patients with esophageal cancer or rectal cancer.

| 2051618 | ecrin-mdr-crc

Identifying biomarkers predicting response to chemotherapy in Stage II and Stage III colorectal cancer patients

Project description:Defining molecular features that can predict the response to chemotherapy for stage II-III colorectal cancer (CRC) patients remains challenging in cancer research. Most available clinical samples are Formalin-Fixed and Paraffin-Embedded (FFPE). Affymetrix GeneChip® Human Transcriptome Array 2.0 (HTA) is one platform marketed for high-throughput gene expression profiling for FFPE tissue samples. In this study, we analyzed the whole transcriptom gene expression of 156 CRC patient samples measured by this platform to identify biomarkers predicting the response to chemotherapy for stage II-III CRC patients.

2021-11-04 | GSE106584 | GEO

Study of Biomarkers in Patients Undergoing Chemotherapy for Metastatic Colorectal Cancer

Project description:RATIONALE: Studying samples of blood and tumor tissue in the laboratory from patients with cancer receiving chemotherapy may help doctors understand the effect of chemotherapy on biomarkers. It may also help doctors predict how patients will respond to treatment. PURPOSE: This phase IV trial is studying biomarkers in patients undergoing chemotherapy for metastatic colorectal cancer.

| 2046477 | ecrin-mdr-crc

Telomere Length in Predicting Toxicity in Older Patients With Stage III-IV Colorectal Cancer Undergoing Chemotherapy

Project description:This pilot research trial studies telomere length in predicting toxicity in older patients with stage III-IV colorectal cancer undergoing chemotherapy. Studying samples of blood from patients with cancer in the laboratory may help doctors learn more about changes that occur in deoxyribonucleic acid (DNA) and predict how well patients will respond to treatment.

| 2150968 | ecrin-mdr-crc

Angiopredict: predicting response for bevacizumab treatment

Project description:In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers worked with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to bevacizumab containing therapy. In this retrospective study, copy number profiles were determined using whole genome shallow sequencing, and progression free survival and treatment data was collected.

| EGAS00001002724 | EGA

Identification of Novel Biomarkers in Pancreatic Tumor Tissue to Predict Response to Neoadjuvant ChemotherapyIdentification of Novel Biomarkers in Pancreatic Tumor Tissue to Predict Response to Neoadjuvant Chemotherapy

Project description:Neoadjuvant chemotherapy (NAC) has been of recent interest as an alternative to upfront surgery followed by adjuvant chemotherapy in patients with pancreatic ductal adenocarcinoma (PDAC). However, a subset of patients does not respond to NAC and may have been better managed by upfront surgery. Hence, there is an unmet need for accurate biomarkers for predicting NAC response in PDAC. This project aimed to identify upregulated proteins in tumor tissue from poor- and good-NAC responders.

2020-04-16 | PXD017051 | Pride

Potential Predictive Biomarkers in Patients Undergoing First-line Chemotherapy for Metastatic Colorectal Cancer

Project description:Chemoresistance remains an obstacle in treating people with metastatic colorectal cancer (mCRC). Studying samples of blood and tumor tissue in the laboratory from patients with mCRC receiving chemotherapy may help doctors understand the effect of chemotherapy on biomarkers. It may also help doctors predict how patients will respond to treatment. In this study, we aimed to evaluate biomarkers in chemotherapy regimens for first-line chemotherapy for mCRC.

| 2273508 | ecrin-mdr-crc

Retrospective Study Assessing Molecular Features Predicting Response to Cetuximab

Project description:The primary objective is to identify molecular features predicting response or resistance to cetuximab

| 2041321 | ecrin-mdr-crc

Biomarkers in Predicting Neurotoxicity in Patients With Colorectal Cancer Receiving Oxaliplatin

Project description:RATIONALE: Studying samples of blood in the laboratory from patients receiving oxaliplatin for cancer may help doctors learn more about changes that occur in DNA and identify biomarkers related to neurotoxicity. PURPOSE: This phase II trial is studying biomarkers in predicting neurotoxicity in patients with colorectal cancer receiving oxaliplatin.

| 2071054 | ecrin-mdr-crc

Proteomic Profiling and Biomarker Discovery for Predicting Response to PD-1 Inhibitor Immunotherapy in Gastric Cancer Patients

Project description:Revolutionizing cancer treatment, immune checkpoint inhibitors (ICIs) have nonetheless encountered a challenge: a substantial portion of gastric cancer (GC) patients don’t respond to this therapy. This pressing issue necessitates a deeper understanding of the resistance mechanisms against ICIs and the identification of robust biomarkers that can predict patient response to ICIs from the outset of treatment. In our project, we collected GC tissue samples from 28 patients prior to their initiation of anti-programmed death 1 (PD-1) immunotherapy. Employing high-resolution mass spectrometry (MS), we conducted comprehensive protein quantification. We then proceeded to analyze the disparities in protein expression profiles, associated pathways, and the characteristics of the tumor microenvironment (TME) between responder and non-responder groups. Ultimately, our aim is to delve into the mechanisms that give rise to differential therapeutic efficacy and thereby uncover reliable biomarkers for predicting ICI response in GC patients.

2024-02-29 | PXD050228 |

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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