Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA137447 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
2013-07-01 | E-GEOD-46691 | biostudies-arrayexpress
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:Integrative Genomic and Proteomic Analysis of Prostate Cancer Reveals Signatures of Metastatic Progression
| PRJNA93223 | ENA
Project description:Optimizing molecular signatures for prostate cancer recurrence
| PRJNA134591 | ENA
Project description:RNA extracted at 240min. Samples are rRNA depleted. Expression measurement of Homo sapiens genes.
2019-07-31 | GSE114179 | GEO
Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.
2013-07-01 | GSE46691 | GEO
Project description:Protein 4.1B suppresses prostate cancer progression and metastasis
| PRJNA100091 | ENA
Project description:The level of copy number alteration (CNA), or CNA burden, in cancer genomes is associated with recurrence and metastasis in prostate cancer. As clinical genomic analysis of tumors and tumor biopsies becomes widespread, there is a growing need to understand the prognostic factors captured by genomic features, especially in prostate cancer where conservative treatment approaches are increasingly common. Here we analyze the CNA landscape of conservatively treated prostate cancer in a prostate cancer biopsy and transurethral resection cohort. We find that CNA burden is prognostic for metastasis and cancer-specific survival, independent of clinical prognostic factors such as Gleason and CAPRA score, in conservatively treated prostate cancer.
2018-08-18 | GSE103665 | GEO
Project description:As the evolution of miRNA genes has been found to be one of the important factors in formation of the modern type of man, we performed a comparative analysis of the evolution of miRNA genes in two archaic hominines, Homo sapiens neanderthalensis and Homo sapiens denisova, and elucidated the expression of their target mRNAs in bain.A comparative analysis of the genomes of primates, including species in the genus Homo, identified a group of miRNA genes having fixed substitutions with important implications for the evolution of Homo sapiens neanderthalensis and Homo sapiens denisova. The mRNAs targeted by miRNAs with mutations specific for Homo sapiens denisova exhibited enhanced expression during postnatal brain development in modern humans. By contrast, the expression of mRNAs targeted by miRNAs bearing variations specific for Homo sapiens neanderthalensis was shown to be enhanced in prenatal brain development.Our results highlight the importance of changes in miRNA gene sequences in the course of Homo sapiens denisova and Homo sapiens neanderthalensis evolution. The genetic alterations of miRNAs regulating the spatiotemporal expression of multiple genes in the prenatal and postnatal brain may contribute to the progressive evolution of brain function, which is consistent with the observations of fine technical and typological properties of tools and decorative items reported from archaeological Denisovan sites. The data also suggest that differential spatial-temporal regulation of gene products promoted by the subspecies-specific mutations in the miRNA genes might have occurred in the brains of Homo sapiens denisova and Homo sapiens neanderthalensis, potentially contributing to the cultural differences between these two archaic hominines.
| S-EPMC4686780 | biostudies-literature
Project description:PurposeWe investigated the evidence of recent positive selection in the human phototransduction system at single nucleotide polymorphism (SNP) and gene level.MethodsSNP genotyping data from the International HapMap Project for European, Eastern Asian, and African populations was used to discover differences in haplotype length and allele frequency between these populations. Numeric selection metrics were computed for each SNP and aggregated into gene-level metrics to measure evidence of recent positive selection. The level of recent positive selection in phototransduction genes was evaluated and compared to a set of genes shown previously to be under recent selection, and a set of highly conserved genes as positive and negative controls, respectively.ResultsSix of 20 phototransduction genes evaluated had gene-level selection metrics above the 90th percentile: RGS9, GNB1, RHO, PDE6G, GNAT1, and SLC24A1. The selection signal across these genes was found to be of similar magnitude to the positive control genes and much greater than the negative control genes.ConclusionsThere is evidence for selective pressure in the genes involved in retinal phototransduction, and traces of this selective pressure can be demonstrated using SNP-level and gene-level metrics of allelic variation. We hypothesize that the selective pressure on these genes was related to their role in low light vision and retinal adaptation to ambient light changes. Uncovering the underlying genetics of evolutionary adaptations in phototransduction not only allows greater understanding of vision and visual diseases, but also the development of patient-specific diagnostic and intervention strategies.
| S-EPMC3743458 | biostudies-literature