Project description:Background: Gene expression profiling has been used extensively within breast cancer research. Patient matched transcriptomic studies of tumour samples before and after treatment offer great potential and have been initiated, but tend not to include a control group. Here we examine gene expression changes between patient-matched core biopsies and surgical resection samples in the absence of treatment, to consider sampling methods and tumour heterogeneity. Patients and Methods: Illumina BeadArray technology was used to measure dynamic changes in gene expression from thirty-seven paired baseline and surgically excised breast tumour samples obtained from women receiving no treatment prior to surgery. Results: Patient-matched sample pairs had significantly higher correlations than samples between different individuals, demonstrating that tumour heterogeneity and intra-tumour differences are less prominent than inter-tumour/patient differences. Perhaps surprisingly, consistent changes in gene expression were identified during the diagnosis-surgery interval, despite a lack of treatment. 50 genes were significantly differentially expressed (48 up, 2 down; FDR 0.05) in a manner that appears independent of both subtype and the sampling-interval length. Gene set enrichment analysis using four independent treated datasets has implicated the tumour sampling method as the likely cause of these expression changes which include increases in early growth response genes such as EGR1, 2 and 3 along with DUSP1 and FOS. Our data does not support the idea that there is a significant wounding or immune response. Conclusion: This is the largest cohort of patient-matched transcriptome profiling of tumours from patients receiving no treatment between diagnosis and surgery to date. It has revealed that consistent changes in gene expression do exist between diagnostic core biopsy and the surgical excision sample. We have confirmed these findings in a number of published breast cancer datasets. Ultimately, researchers should be aware of the potential for the tumour sampling method to introduce a confounding factor in future neoadjuvant studies.

Project description:Background: Gene expression profiling has been used extensively within breast cancer research. Patient matched transcriptomic studies of tumour samples before and after treatment offer great potential and have been initiated, but tend not to include a control group. Here we examine gene expression changes between patient-matched core biopsies and surgical resection samples in the absence of treatment, to consider sampling methods and tumour heterogeneity. Patients and Methods: Illumina BeadArray technology was used to measure dynamic changes in gene expression from thirty-seven paired baseline and surgically excised breast tumour samples obtained from women receiving no treatment prior to surgery. Results: Patient-matched sample pairs had significantly higher correlations than samples between different individuals, demonstrating that tumour heterogeneity and intra-tumour differences are less prominent than inter-tumour/patient differences. Perhaps surprisingly, consistent changes in gene expression were identified during the diagnosis-surgery interval, despite a lack of treatment. 50 genes were significantly differentially expressed (48 up, 2 down; FDR 0.05) in a manner that appears independent of both subtype and the sampling-interval length. Gene set enrichment analysis using four independent treated datasets has implicated the tumour sampling method as the likely cause of these expression changes which include increases in early growth response genes such as EGR1, 2 and 3 along with DUSP1 and FOS. Our data does not support the idea that there is a significant wounding or immune response. Conclusion: This is the largest cohort of patient-matched transcriptome profiling of tumours from patients receiving no treatment between diagnosis and surgery to date. It has revealed that consistent changes in gene expression do exist between diagnostic core biopsy and the surgical excision sample. We have confirmed these findings in a number of published breast cancer datasets. Ultimately, researchers should be aware of the potential for the tumour sampling method to introduce a confounding factor in future neoadjuvant studies. 37 paired patient-matched whole-transcriptome profiled primary breast tumours from patients receiving no treatment between diagnosis and surgery. Superseries is a product of two integrated individual batches.

Project description:We looked for the presence of prostatic cells and RNAs (cellular and acellular) of prostatic origin in the ejaculate semen from fertile and sterilized men and from men with prostate cancer, to ascertain the suitability of ejaculate semen for studying and monitoring prostate health. Methods. For prostatic cells, semen from fertile and sterile men and men with prostate cancer were subjected to density gradient centrifugation on a 60% cushion of Suprasperm™ and fractions containing somatic cells were washed and cytospun onto coated slides prior to fixation and immunocytochemistry with antibodies recognizing prostatic markers. Small RNAs were isolated from liquefied semen clarified of all cellular and other insoluble material by high-speed ultra-centrifugation. Sequencing libraries were prepared from fractions isolated by PAGE, corresponding to small non-coding (snc) RNAs in the 18-23 nt and 30-35 nt size ranges. Libraries were interrogated by next generation sequencing and analysed to generate lists of differentially expressed RNAs associated with cancer and sterility. Results. Cells positive for cytokeratin 18, PSMA, NKX3.1 and CD24 were observed in most ejaculate samples by indirect immunocytochemistry as either discrete cellular entities or within clumps of cell containing material (DAPI+; antigen positive and negative) and cytoplasmic fragments (DAP–; antigen positive and negative). RNA from populations of cells enriched by differential density gradient centrifugation supported their immunocytochemical designation as prostatic cells. Small RNAs (18 - 43 nt) from seminal plasma were highly heterogeneous although tRNAs and 5SRNAs were the dominant forms. A degree of overlap between the respective differential expression profiles of small RNAs from sterile and cancer samples, suggested a common feature, perhaps indicating an inflammatory response. Conclusion. This study supports a wider appraisal of ejaculate semen for studying and monitoring prostate health.

Dataset Information

SAT: a Surrogate-Assisted Two-wave case boosting sampling method, with application to EHR-based association studies.

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Materials and methods

Results

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SAT: a Surrogate-Assisted Two-wave case boosting sampling method, with application to EHR-based association studies.

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