Tumour sampling method can significantly influence gene expression profiles derived from neoadjuvant window studies
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE76728 | GEO | 2016/08/08
SECONDARY ACCESSION(S): PRJNA308460
REPOSITORIES: GEO
Similar Datasets
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2016-08-08 | E-GEOD-76728 | biostudies-arrayexpress
Project description:Patient-matched transcriptomic studies using tumour samples before and after treatment allow inter-patient heterogeneity to be controlled, but tend not to include an untreated comparison. Here, Illumina BeadArray technology was used to measure dynamic changes in gene expression from thirty-seven paired diagnostic core and surgically excised breast cancer biopsies obtained from women receiving no treatment prior to surgery, to determine the impact of sampling method and tumour heterogeneity. Despite a lack of treatment and perhaps surprisingly, consistent changes in gene expression were identified during the diagnosis-surgery interval (48 up, 2 down; Siggenes FDR 0.05) in a manner independent of both subtype and sampling-interval length. Instead, tumour sampling method was seen to directly impact gene expression, with similar effects additionally identified in six published breast cancer datasets. In contrast with previous findings, our data does not support the concept of a significant wounding or immune response following biopsy in the absence of treatment and instead implicates a hypoxic response following the surgical biopsy. Whilst sampling-related gene expression changes are evident in treated samples, they are secondary to those associated with response to treatment. Nonetheless, sampling method remains a potential confounding factor for neoadjuvant study design.
| S-EPMC4935948 | biostudies-literature
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.
2016-08-08 | E-GEOD-76726 | biostudies-arrayexpress
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.
2016-08-08 | E-GEOD-76727 | biostudies-arrayexpress
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.
2016-08-08 | GSE76726 | GEO
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.
2016-08-08 | GSE76727 | GEO
Project description:Tumour sampling method can significantly influence gene expression profiles derived from neoadjuvant window studies
| PRJNA308460 | ENA
Project description:Sequencing-based studies of the human faecal microbiota are increasingly common. Appropriate storage of sample material is essential to avoid the introduction of post-collection bias in microbial community composition. Rapid freezing to -80 °C is commonly considered to be best-practice. However, this is not feasible in many studies, particularly those involving sample collection in participants' homes. We determined the extent to which a range of stabilisation and storage strategies maintained the composition of faecal microbial community structure relative to freezing to -80 °C. Refrigeration at 4 °C, storage at ambient temperature, and the use of several common preservative buffers (RNAlater, OMNIgene.GUT, Tris-EDTA) were assessed relative to freezing. Following 72 hours of storage, faecal microbial composition was assessed by 16 S rRNA amplicon sequencing. Refrigeration was associated with no significant alteration in faecal microbiota diversity or composition. However, samples stored using other conditions showed substantial divergence compared to -80 °C control samples. Aside from refrigeration, the use of OMNIgene.GUT resulted in the least alteration, while the greatest change was seen in samples stored in Tris-EDTA buffer. The commercially available OMNIgene.GUT kit may provide an important alternative where refrigeration and cold chain transportation is not available.
| S-EPMC4648095 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below. The interplay between environmental and genetic factors conditions the fruit ripening program in plants. Transcriptome analysis of grapevine fruits can help understanding these interactions to consciously cope with conditions leading to detrimental effects for viticultural purposes. However, considering the grapevine characteristic ripening asynchrony, which can be intensified by contrasting conditions, accurate grape sampling may be essential for molecular comparisons. In this study, berry density sorting according to floatability in NaCl solutions was assessed as a grape ripening staging strategy. Total sugar content was more correlated with berry density than with other non-invasive ripening parameters. The transcriptome was compared between three density classes collected near commercial maturity using grapevine whole-genome NimbleGen microarrays. Expression profiles clearly related with ripening progression were detected in a density series simultaneously collected from a vineyard of Albariño. By contrast, considerable differences were detected when the same density series was sampled on two different dates from the same vineyard of Tempranillo. Functional analysis indicated that environmental differences between both sampling moments determined most of these expression differences. Ripening degree-dependent responses to the environment were also detected. Finally, the effect of the sorting procedures on the grape transcriptome showed negligible when it was directly tested. Altogether, these findings evidence the convenience of homogenizing the developmental stage and the sampling time conditions for transcriptome comparisons. Berry density sorting proved useful to this end, although this method could be limited when the berry sugar concentration is not determined by the ripening developmental program.
2016-05-22 | GSE76000 | GEO
Project description:A method of window exchange umbrella sampling molecular dynamics simulation is employed for transmembrane helix assembly. An analytical expression for the average acceptance probability between neighboring windows is derived and combined with the first passage time optimization method to predetermine a parameter set in an optimal range. With the parameter set, the method provides a substantially more efficient sampling of helix-helix interfaces together with the potential of mean force along the helix-helix distance of a transmembrane helix-dimer model, compared to the umbrella sampling method.
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