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Impact of sample acquisition and linear amplification on gene expression profiling of lung adenocarcinoma: laser capture micro-dissection cell-sampling versus bulk tissue-sampling.

Klee EW, Erdogan S, Tillmans L, Kosari F, Sun Z, Wigle DA, Yang P, Aubry MC, Vasmatzis G - BMC Med Genomics (2009)

Bottom Line: Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost.The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Medicine, Mayo Clinic, Rochester, MN, USA. klee.eric@mayo.edu

ABSTRACT

Background: The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.

Methods: Expression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.

Results: The direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.

Conclusion: LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.

No MeSH data available.


Related in: MedlinePlus

Probesets with significant changes in expression level between bulk, LCM, and linear amplified bulk samples. There is a similar distribution of overlapping probesets between the bulk samples and either of the amplified samples (LCM or Linear Amplified Bulk). Between amplified samples, there are very few probesets with significant changes in expression level, suggesting most of the changes observed between bulk and LCM are a by-product of an amplification protocol bias. These observations were consistent in both (A) normal tissue samples, and (B) cancer tissue samples.
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Figure 2: Probesets with significant changes in expression level between bulk, LCM, and linear amplified bulk samples. There is a similar distribution of overlapping probesets between the bulk samples and either of the amplified samples (LCM or Linear Amplified Bulk). Between amplified samples, there are very few probesets with significant changes in expression level, suggesting most of the changes observed between bulk and LCM are a by-product of an amplification protocol bias. These observations were consistent in both (A) normal tissue samples, and (B) cancer tissue samples.

Mentions: To estimate whether the second round of RNA amplification, required for LCM sample processing, induced a bias in the expression data, RNA from two normal-bulk and two cancer-bulk tissue samples were linearly amplified. Using the two-sample average probeset expression values from the linear-amplified bulk, bulk, and LCM microarrays, the previous comparisons were repeated. As evident in Figure 2, very few probesets were identified with substantially different expression levels in the LCM samples compared to the linear amplified bulk samples. However, when comparing expression levels in the LCM samples to that in the bulk samples, or when comparing expression levels in the linear-amplified bulk samples with that in the bulk samples, there were substantially more divergent probesets identified. These observations were consistent in both the normal samples (Figure 2a) and cancer samples (Figure 2b). A further elaboration of these observations is presented in Additional file 1.


Impact of sample acquisition and linear amplification on gene expression profiling of lung adenocarcinoma: laser capture micro-dissection cell-sampling versus bulk tissue-sampling.

Klee EW, Erdogan S, Tillmans L, Kosari F, Sun Z, Wigle DA, Yang P, Aubry MC, Vasmatzis G - BMC Med Genomics (2009)

Probesets with significant changes in expression level between bulk, LCM, and linear amplified bulk samples. There is a similar distribution of overlapping probesets between the bulk samples and either of the amplified samples (LCM or Linear Amplified Bulk). Between amplified samples, there are very few probesets with significant changes in expression level, suggesting most of the changes observed between bulk and LCM are a by-product of an amplification protocol bias. These observations were consistent in both (A) normal tissue samples, and (B) cancer tissue samples.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2667433&req=5

Figure 2: Probesets with significant changes in expression level between bulk, LCM, and linear amplified bulk samples. There is a similar distribution of overlapping probesets between the bulk samples and either of the amplified samples (LCM or Linear Amplified Bulk). Between amplified samples, there are very few probesets with significant changes in expression level, suggesting most of the changes observed between bulk and LCM are a by-product of an amplification protocol bias. These observations were consistent in both (A) normal tissue samples, and (B) cancer tissue samples.
Mentions: To estimate whether the second round of RNA amplification, required for LCM sample processing, induced a bias in the expression data, RNA from two normal-bulk and two cancer-bulk tissue samples were linearly amplified. Using the two-sample average probeset expression values from the linear-amplified bulk, bulk, and LCM microarrays, the previous comparisons were repeated. As evident in Figure 2, very few probesets were identified with substantially different expression levels in the LCM samples compared to the linear amplified bulk samples. However, when comparing expression levels in the LCM samples to that in the bulk samples, or when comparing expression levels in the linear-amplified bulk samples with that in the bulk samples, there were substantially more divergent probesets identified. These observations were consistent in both the normal samples (Figure 2a) and cancer samples (Figure 2b). A further elaboration of these observations is presented in Additional file 1.

Bottom Line: Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost.The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Medicine, Mayo Clinic, Rochester, MN, USA. klee.eric@mayo.edu

ABSTRACT

Background: The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.

Methods: Expression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.

Results: The direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.

Conclusion: LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.

No MeSH data available.


Related in: MedlinePlus