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- Jamshidi, Neema, et al.
(författare)
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The Radiogenomic Risk Score : construction of a Prognostic Quantitative, Noninvasive Image-based Molecular Assay for Renal Cell Carcinoma
- 2015
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Ingår i: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 277:1, s. 114-123
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To evaluate the feasibility of constructing radiogenomic-based surrogates of molecular assays (SOMAs) in patients with clear-cell renal cell carcinoma (CCRCC) by using data extracted from a single computed tomographic (CT) image.Materials and Methods: In this institutional review board approved study, gene expression profile data and contrast material–enhanced CT images from 70 patients with CCRCC in a training set were independently assessed by two radiologists for a set of predefined imaging features. A SOMA for a previously validated CCRCC-specific supervised principal component (SPC) risk score prognostic gene signature was constructed and termed the radiogenomic risk score (RRS). It uses the microarray data and a 28-trait image array to evaluate each CT image with multiple regression of gene expression analysis. The predictive power of the RRS SOMA was then prospectively validated in an independent dataset to confirm its relationship to the SPC gene signature (n = 70) and determination of patient outcome (n = 77). Data were analyzed by using multivariate linear regression–based methods and Cox regression modeling, and significance was assessed with receiver operator characteristic curves and Kaplan-Meier survival analysis.Results: Our SOMA faithfully represents the tissue-based molecular assay it models. The RRS scaled with the SPC gene signature (R = 0.57,P < .001, classification accuracy 70.1%, P < .001) and predicted disease-specific survival (log rank P < .001). Independent validation confirmed the relationship between the RRS and the SPC gene signature (R = 0.45, P < .001, classification accuracy 68.6%, P < .001) and disease-specific survival (log-rank P < .001) and that it was independent of stage, grade, and performance status (multivariate Cox model P < .05, log-rank P < .001).Conclusion: A SOMA for the CCRCC-specific SPC prognostic gene signature that is predictive of disease-specific survival and independent of stage was constructed and validated, confirming that SOMA construction is feasible.
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| 2. |
- Lapointe, Jacques, et al.
(författare)
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Gene expression profiling identifies clinically relevant subtypes of prostate cancer
- 2004
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 101:3, s. 811-816
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Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer, a leading cause of cancer death, displays a broad range of clinical behavior from relatively indolent to aggressive metastatic disease. To explore potential molecular variation underlying this clinical heterogeneity, we profiled gene expression in 62 primary prostate tumors, as well as 41 normal prostate specimens and nine lymph node metastases, using cDNA microarrays containing ≈26,000 genes. Unsupervised hierarchical clustering readily distinguished tumors from normal samples, and further identified three subclasses of prostate tumors based on distinct patterns of gene expression. High-grade and advanced stage tumors, as well as tumors associated with recurrence, were disproportionately represented among two of the three subtypes, one of which also included most lymph node metastases. To further characterize the clinical relevance of tumor subtypes, we evaluated as surrogate markers two genes differentially expressed among tumor subgroups by using immunohistochemistry on tissue microarrays representing an independent set of 225 prostate tumors. Positive staining for MUC1, a gene highly expressed in the subgroups with "aggressive" clinicopathological features, was associated with an elevated risk of recurrence (P = 0.003), whereas strong staining for AZGP1, a gene highly expressed in the other subgroup, was associated with a decreased risk of recurrence (P = 0.0008). In multivariate analysis, MUC1 and AZGP1 staining were strong predictors of tumor recurrence independent of tumor grade, stage, and preoperative prostate-specific antigen levels. Our results suggest that prostate tumors can be usefully classified according to their gene expression patterns, and these tumor subtypes may provide a basis for improved prognostication and treatment stratification.
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| 3. |
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| 4. |
- Zhao, Hongjuan, et al.
(författare)
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Alteration of gene expression signatures of cortical differentiation and wound response in lethal clear cell renal cell carcinomas.
- 2009
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Ingår i: PloS one. - : Public Library of Science (PLoS). - 1932-6203. ; 4:6, s. e6039-
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Tidskriftsartikel (refereegranskat)abstract
- Clear cell renal cell carcinoma (ccRCC) is the most common malignancy of the adult kidney and displays heterogeneity in clinical outcomes. Through comprehensive gene expression profiling, we have identified previously a set of transcripts that predict survival following nephrectomy independent of tumor stage, grade, and performance status. These transcripts, designated as the SPC (supervised principal components) gene set, show no apparent biological or genetic features that provide insight into renal carcinogenesis or tumor progression. We explored the relationship of this gene list to a set of genes expressed in different anatomical segments of the normal kidney including the cortex (cortex gene set) and the glomerulus (glomerulus gene set), and a gene set expressed after serum stimulation of quiescent fibroblasts (the core serum response or CSR gene set). Interestingly, the normal cortex, glomerulus (part of the normal renal cortex), and CSR gene sets captured more than 1/5 of the genes in the highly prognostic SPC gene set. Based on gene expression patterns alone, the SPC gene set could be used to sort samples from normal adult kidneys by the anatomical regions from which they were dissected. Tumors whose gene expression profiles most resembled the normal renal cortex or glomerulus showed better survival than those that did not, and those with expression features more similar to CSR showed poorer survival. While the cortex, glomerulus, and CSR signatures predicted survival independent of traditional clinical parameters, they were not independent of the SPC gene list. Our findings suggest that critical biological features of lethal ccRCC include loss of normal cortical differentiation and activation of programs associated with wound healing.
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