Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA141331 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Response to Neoadjuvant Chemotherapy in Triple Negative Breast tumors.
| PRJNA187494 | ENA
Project description:Molecular Subtype Predicts Response to Neoadjuvant Chemotherapy in Breast Cancer
| PRJNA127177 | ENA
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:Prediction of breast cancer pathological complete response to anthracycline/taxane chemotherapy.
| PRJNA99107 | ENA
Project description:Gene profiling and prediction of response to anastrozole neoadjuvant treatment in breast cancer
| PRJNA118149 | ENA
Project description:Kynureninase is a member of a large family of catalytically diverse but structurally homologous pyridoxal 5'-phosphate (PLP) dependent enzymes known as the aspartate aminotransferase superfamily or alpha-family. The Homo sapiens and other eukaryotic constitutive kynureninases preferentially catalyze the hydrolytic cleavage of 3-hydroxy-l-kynurenine to produce 3-hydroxyanthranilate and l-alanine, while l-kynurenine is the substrate of many prokaryotic inducible kynureninases. The human enzyme was cloned with an N-terminal hexahistidine tag, expressed, and purified from a bacterial expression system using Ni metal ion affinity chromatography. Kinetic characterization of the recombinant enzyme reveals classic Michaelis-Menten behavior, with a Km of 28.3 +/- 1.9 microM and a specific activity of 1.75 micromol min-1 mg-1 for 3-hydroxy-dl-kynurenine. Crystals of recombinant kynureninase that diffracted to 2.0 A were obtained, and the atomic structure of the PLP-bound holoenzyme was determined by molecular replacement using the Pseudomonas fluorescens kynureninase structure (PDB entry 1qz9) as the phasing model. A structural superposition with the P. fluorescens kynureninase revealed that these two structures resemble the "open" and "closed" conformations of aspartate aminotransferase. The comparison illustrates the dynamic nature of these proteins' small domains and reveals a role for Arg-434 similar to its role in other AAT alpha-family members. Docking of 3-hydroxy-l-kynurenine into the human kynureninase active site suggests that Asn-333 and His-102 are involved in substrate binding and molecular discrimination between inducible and constitutive kynureninase substrates.
| S-EPMC2531291 | biostudies-literature
Project description:RNA extracted at 240min. Samples are rRNA depleted. Expression measurement of Homo sapiens genes.
2019-07-31 | GSE114179 | GEO
Project description:Genomic copy number alterations as predictive markers of neoadjuvant chemotherapy response in breast cancer
| PRJNA108979 | ENA
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