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PROVIDER: PRJNA230289 | ENA |
REPOSITORIES: ENA
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Project description:Gene signature predictive of response to chemotherapy in mCRC [array]
| PRJNA230290 | ENA
Project description:Gene signature predictive of response to chemotherapy in mCRC [RT-PCR]
| PRJNA229147 | ENA
Project description:The objective is to generate a robust and validated predictor profile for chemotherapy response in patients with mCRC using microarray gene expression profiles of primary colorectal cancer tissue. To define a gene signature of response to chemotherapy in metastatic colorectal cancer, samples were obtained from 40 patients from Marques de Valdecilla Hospital who underwent primary surgery. Gene expression was detected and quantified using the Human Whole Genome U133 Plus 2.0 array (Affymetrix), containing 54675 human gene probes. Adequate RNA and microarray analysis were obtained from only 37 patients.
2013-12-01 | E-GEOD-52735 | biostudies-arrayexpress
Project description:Background: For the majority of patients of metastatic colorectal cancer (mCRC), systematic chemotherapy has been a choice for palliative treatment. When first-line chemotherapies do not work, targeted therapies are administered. Because of inter-individual genetic and epigenetic variations, patients with mCRC who are treated with these therapies may respond differently. It is of great clinical interest to elucidate response mechanisms that could be utilized in predicting individual response to these treatments. Methods: A highly sensitive technique, the 5hmC-Seal was applied to profile genome-wide 5-hydroxymethylcytosines (5hmC) in 155 cfDNA samples from patients with mCRC recruited for two clinical trials at Zhongshan Hospital, Fudan University in China. Response to systematic chemotherapy and targeted therapy (becacizumab or cetuximab) (CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease) was measured and a 5hmC-based predictive model in cfDNA was developed using a machine learning approach in the PROVE Study (NCT03679039) (n = 100), followed by validation in the METHOD Study (NCT03599947) (n = 55). Results: Genome-wide mapping of 5hmC in patient-derived cfDNA suggested a distinct 5hmC landscape showing tissue origin and gene regulatory relevance. A eleven-gene model involving relevant pathways such as Rap1 signaling pathway, cAMP signaling pathway, Phospholipase D signaling pathway and cGMP-PKG signaling pathway, distinguished patients with mCRC who responded to chemotherapy, regardless of targeted therapy, resectability, or mutation status in the validation samples (AUC=0.77; 95% CI, 0.64-0.90), outperforming RAS mutation status (AUC=0.70; 95% CI, 0.57-0.83). In addition, the 5hmC model also showed a trend of capacity for predicting progression-free survival (PFS) for mCRC. Conclusions: Genome-wide mapping reflected relevant pathways and functional interaction networks implicated in the determination of treatment response for patients with mCRC. The 5hmC-Seal model in cfDNA provided a promising non-invasive method for predicting response to systematic chemotherapy in patients with mCRC, who will be essential for personalized medicine.
2025-01-01 | GSE203071 | GEO
Project description:KRAS mutation is a negative predictive factor for treatment with anti-epidermal growth factor receptor (EGFR) antibodies in metastatic colorectal cancer (mCRC). Novel predictive markers are required to further improve the selection of patients for this treatment. Here, we assessed the influence of modification of KRAS by gene copy number aberration (CNA) and microRNAs (miRNAs) in correlation to clinical outcome in mCRC patients treated with cetuximab in combination with chemotherapy and bevacizumab. Formalin-fixed paraffin-embedded primary tumour tissue was used from 34 mCRC patients in a phase III trial, who were selected based upon their good (n=17) or poor (n=17) progression-free survival (PFS) upon treatment with cetuximab in combination with capecitabine, oxaliplatin, and bevacizumab. Gene copy number at the KRAS locus was assessed using high resolution genome-wide array CGH and the expression levels of 17 miRNAs targeting KRAS were determined by real-time PCR. Good response was associated with 12p12.1 copy number loss, even in patients with a KRAS mutation, while copy number gain in wild-type KRAS patients was correlated with a poor response. In KRAS mutated tumours increased miR-200b and decreased miR-143 expression were associated with a good response. In wild-type KRAS patients, miRNA expression did not predict response in a multivariate model. Thus, assessment of KRAS CNA and miRNAs targeting KRAS might further optimize the selection of patients eligible for anti-EGFR therapy. Copy number detection was performed using NimbleScan and Nexus software
2012-01-01 | GSE32048 | GEO
Project description:Purpose:The identification of biomarkers predictive of neoadjuvant chemotherapy response in breast cancer patients would be an important advancement in personalized cancer therapy. We hypothesized that due to similarities between radiation and chemotherapy induced cellular response mechanisms, radiation responsive genes may be useful in predicting response to neoadjuvant chemotherapy. Materials and Methods: Murine p53 null breast cancer cell lines representative of the luminal, basal-like and claudin-low human breast cancer subtypes were irradiated to identify radiation responsive genes. These murine radiation induced genes were then converted to their human orthologs. These genes were then used to develop a predictor of pathologic complete response (pCR) that was validated on two independent published neoadjuvant chemotherapy data sets of genomic data with response. Results: A radiation induced gene signature consisting of 30 genes was identified on a training set of 337 human primary breast cancer tumor samples that was prognostic for survival. Mean expression of this signature was calculated for individual samples in two independent published datasets and was found to be significantly predictive of pathologic complete response. Multivariate logistic regression analysis in both independent datasets showed that this 30 gene signature added significant predictive information independent of that provided by standard clinical predictors and other gene expression based predictors of pathologic complete response. Conclusion: This study provides new biologic information regarding response to neoadjuvant chemotherapy and a means of possibly improving the prediction of pathologic complete response. reference x sample
2015-01-21 | E-GEOD-48073 | biostudies-arrayexpress
Project description:KRAS mutation is a negative predictive factor for treatment with anti-epidermal growth factor receptor (EGFR) antibodies in metastatic colorectal cancer (mCRC). Novel predictive markers are required to further improve the selection of patients for this treatment. Here, we assessed the influence of modification of KRAS by gene copy number aberration (CNA) and microRNAs (miRNAs) in correlation to clinical outcome in mCRC patients treated with cetuximab in combination with chemotherapy and bevacizumab. Formalin-fixed paraffin-embedded primary tumour tissue was used from 34 mCRC patients in a phase III trial, who were selected based upon their good (n=17) or poor (n=17) progression-free survival (PFS) upon treatment with cetuximab in combination with capecitabine, oxaliplatin, and bevacizumab. Gene copy number at the KRAS locus was assessed using high resolution genome-wide array CGH and the expression levels of 17 miRNAs targeting KRAS were determined by real-time PCR. Good response was associated with 12p12.1 copy number loss, even in patients with a KRAS mutation, while copy number gain in wild-type KRAS patients was correlated with a poor response. In KRAS mutated tumours increased miR-200b and decreased miR-143 expression were associated with a good response. In wild-type KRAS patients, miRNA expression did not predict response in a multivariate model. Thus, assessment of KRAS CNA and miRNAs targeting KRAS might further optimize the selection of patients eligible for anti-EGFR therapy. Copy number detection was performed using NimbleScan and Nexus software Formalin-fixed paraffin-embedded primary tumour tissue was used from 34 metastisized colorectal cancer patients in a phase III trial (CKTO 2005-02; ClinTrials.gov NCT00208546) of the Dutch Colorectal Cancer Group (DCCG), who were selected based upon their good (n=17) or poor (n=17) progression-free survival (PFS) upon treatment with cetuximab in combination with capecitabine, oxaliplatin, and bevacizumab.
2012-01-01 | E-GEOD-32048 | biostudies-arrayexpress
Project description:The objective is to generate a robust and validated predictor profile for chemotherapy response in patients with mCRC using microarray gene expression profiles of primary colorectal cancer tissue.
2013-12-01 | GSE52735 | GEO
Project description:The objective is to generate a robust and validated predictor profile for chemotherapy response in patients with mCRC using microarray gene expression profiles of primary colorectal cancer tissue.
2013-11-20 | GSE52513 | GEO
Project description:Purpose:The identification of biomarkers predictive of neoadjuvant chemotherapy response in breast cancer patients would be an important advancement in personalized cancer therapy. We hypothesized that due to similarities between radiation and chemotherapy induced cellular response mechanisms, radiation responsive genes may be useful in predicting response to neoadjuvant chemotherapy. Materials and Methods: Murine p53 null breast cancer cell lines representative of the luminal, basal-like and claudin-low human breast cancer subtypes were irradiated to identify radiation responsive genes. These murine radiation induced genes were then converted to their human orthologs. These genes were then used to develop a predictor of pathologic complete response (pCR) that was validated on two independent published neoadjuvant chemotherapy data sets of genomic data with response. Results: A radiation induced gene signature consisting of 30 genes was identified on a training set of 337 human primary breast cancer tumor samples that was prognostic for survival. Mean expression of this signature was calculated for individual samples in two independent published datasets and was found to be significantly predictive of pathologic complete response. Multivariate logistic regression analysis in both independent datasets showed that this 30 gene signature added significant predictive information independent of that provided by standard clinical predictors and other gene expression based predictors of pathologic complete response. Conclusion: This study provides new biologic information regarding response to neoadjuvant chemotherapy and a means of possibly improving the prediction of pathologic complete response.
2015-01-21 | GSE48073 | GEO