Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptomic profiling of sequential tumours from breast cancer patients provides a global view of metastatic expression changes following endocrine therapy

ABSTRACT: We profiled primary breast cancer, nodal and liver metastatic tumours from three patients. At the time of initial diagnosis, all three patients presented with luminal breast cancer with adjacent nodal metastasis. They all received 5 years of enodrine therapy and all subsequently developed liver metastasis. Examination of mRNA differences between primary, nodal and metastatic tumour samples.

ORGANISM(S): Homo sapiens

SUBMITTER: Leonie Young

PROVIDER: E-GEOD-58708 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Transcriptomic Profiling of Sequential Tumors from Breast Cancer Patients Provides a Global View of Metastatic Expression Changes Following Endocrine Therapy.

McBryan Jean J Fagan Ailís A McCartan Damian D Bane Fiona T FT Varešlija Damir D Cocchiglia Sinéad S Byrne Christopher C Bolger Jarlath J McIlroy Marie M Hudson Lance L Tibbitts Paul P Gaora Peadar Ó PÓ Hill Arnold D AD Young Leonie S LS

Clinical cancer research : an official journal of the American Association for Cancer Research 20150803 23

<h4>Purpose</h4>Disease recurrence is a common problem in breast cancer and yet the mechanisms enabling tumor cells to evade therapy and colonize distant organs remain unclear. We sought to characterize global expression changes occurring with metastatic disease progression in the endocrine-resistant setting.<h4>Experimental design</h4>Here, for the first time, RNAsequencing has been performed on matched primary, nodal, and liver metastatic tumors from tamoxifen-treated patients following diseas ...[more]

PMID: 26240272

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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.

Dataset Information

Transcriptomic profiling of sequential tumours from breast cancer patients provides a global view of metastatic expression changes following endocrine therapy

Publications

Transcriptomic Profiling of Sequential Tumors from Breast Cancer Patients Provides a Global View of Metastatic Expression Changes Following Endocrine Therapy.

Similar Datasets

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