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Total proteome analysis identifies migration defects as a major pathogenetic factor in immunoglobulin heavy chain variable region (IGHV)-unmutated chronic lymphocytic leukemia.

Eagle GL, Zhuang J, Jenkins RE, Till KJ, Jithesh PV, Lin K, Johnson GG, Oates M, Park K, Kitteringham NR, Pettitt AR - Mol. Cell Proteomics (2015)

Bottom Line: Furthermore, UM-CLL cells underexpressed proteins associated with cytoskeletal remodeling and overexpressed proteins associated with transcriptional and translational activity.Taken together, our findings indicate that UM-CLL cells are less migratory and more adhesive than M-CLL cells, resulting in their retention in lymph nodes, where they are exposed to proliferative stimuli.Our study illustrates the potential of total proteome analysis to elucidate pathogenetic mechanisms in cancer.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Department of Molecular and Clinical Cancer Medicine.

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Related in: MedlinePlus

Bioinformatic analysis of proteins identified by iTRAQ-MS.A, Venn diagram showing the number of proteins reproducibly identified between the three separate iTRAQ-MS experiments. In total, 3521 proteins were identified, 2024 of which were identified in all three experiments, and 2715 proteins were identified in two or more experiments. B, PCA showing the separation of UM-CLL and M-CLL samples based on relative protein levels. C, volcano plot of the entire protein data set obtained by iTRAQ-based MS showing differences in protein expression between M-CLL and UM-CLL according to magnitude and p value (t test). Protein expression was remarkably similar in the two CLL subsets, with 92% (n = 3247) of identified proteins sharing similar levels of expression across the sample cohort (p > 0.05). However, >270 proteins were differentially expressed between the two CLL subsets, giving a p value of <0.05, with 147 proteins being expressed at lower levels and 127 proteins expressed at higher levels in UM-CLL compared with M-CLL. D, heat map showing levels of differentially expressed proteins for which relative quantitative values were obtained for all 18 CLL cases (n = 186). Hierarchical clustering of CLL cases based on the relative expression of these proteins generated two clusters comprising the nine cases of UM-CLL and the nine cases of M-CLL, respectively.
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Figure 1: Bioinformatic analysis of proteins identified by iTRAQ-MS.A, Venn diagram showing the number of proteins reproducibly identified between the three separate iTRAQ-MS experiments. In total, 3521 proteins were identified, 2024 of which were identified in all three experiments, and 2715 proteins were identified in two or more experiments. B, PCA showing the separation of UM-CLL and M-CLL samples based on relative protein levels. C, volcano plot of the entire protein data set obtained by iTRAQ-based MS showing differences in protein expression between M-CLL and UM-CLL according to magnitude and p value (t test). Protein expression was remarkably similar in the two CLL subsets, with 92% (n = 3247) of identified proteins sharing similar levels of expression across the sample cohort (p > 0.05). However, >270 proteins were differentially expressed between the two CLL subsets, giving a p value of <0.05, with 147 proteins being expressed at lower levels and 127 proteins expressed at higher levels in UM-CLL compared with M-CLL. D, heat map showing levels of differentially expressed proteins for which relative quantitative values were obtained for all 18 CLL cases (n = 186). Hierarchical clustering of CLL cases based on the relative expression of these proteins generated two clusters comprising the nine cases of UM-CLL and the nine cases of M-CLL, respectively.

Mentions: A total of 3521 proteins were identified within a 1% global false discovery rate and with a high confidence of correct peptide sequence assignment (Fig. 1A and the full list of proteins provided in the supplemental data). Of these, 2024 proteins were identified in all three separate iTRAQ-MS experiments (Fig. 1A). To determine whether protein expression was similar between UM-CLL and M-CLL samples, we subjected the data to PCA. As shown in Fig. 1B, PCA showed a distinction between UM-CLL and M-CLL samples based on protein expression.


Total proteome analysis identifies migration defects as a major pathogenetic factor in immunoglobulin heavy chain variable region (IGHV)-unmutated chronic lymphocytic leukemia.

Eagle GL, Zhuang J, Jenkins RE, Till KJ, Jithesh PV, Lin K, Johnson GG, Oates M, Park K, Kitteringham NR, Pettitt AR - Mol. Cell Proteomics (2015)

Bioinformatic analysis of proteins identified by iTRAQ-MS.A, Venn diagram showing the number of proteins reproducibly identified between the three separate iTRAQ-MS experiments. In total, 3521 proteins were identified, 2024 of which were identified in all three experiments, and 2715 proteins were identified in two or more experiments. B, PCA showing the separation of UM-CLL and M-CLL samples based on relative protein levels. C, volcano plot of the entire protein data set obtained by iTRAQ-based MS showing differences in protein expression between M-CLL and UM-CLL according to magnitude and p value (t test). Protein expression was remarkably similar in the two CLL subsets, with 92% (n = 3247) of identified proteins sharing similar levels of expression across the sample cohort (p > 0.05). However, >270 proteins were differentially expressed between the two CLL subsets, giving a p value of <0.05, with 147 proteins being expressed at lower levels and 127 proteins expressed at higher levels in UM-CLL compared with M-CLL. D, heat map showing levels of differentially expressed proteins for which relative quantitative values were obtained for all 18 CLL cases (n = 186). Hierarchical clustering of CLL cases based on the relative expression of these proteins generated two clusters comprising the nine cases of UM-CLL and the nine cases of M-CLL, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4390271&req=5

Figure 1: Bioinformatic analysis of proteins identified by iTRAQ-MS.A, Venn diagram showing the number of proteins reproducibly identified between the three separate iTRAQ-MS experiments. In total, 3521 proteins were identified, 2024 of which were identified in all three experiments, and 2715 proteins were identified in two or more experiments. B, PCA showing the separation of UM-CLL and M-CLL samples based on relative protein levels. C, volcano plot of the entire protein data set obtained by iTRAQ-based MS showing differences in protein expression between M-CLL and UM-CLL according to magnitude and p value (t test). Protein expression was remarkably similar in the two CLL subsets, with 92% (n = 3247) of identified proteins sharing similar levels of expression across the sample cohort (p > 0.05). However, >270 proteins were differentially expressed between the two CLL subsets, giving a p value of <0.05, with 147 proteins being expressed at lower levels and 127 proteins expressed at higher levels in UM-CLL compared with M-CLL. D, heat map showing levels of differentially expressed proteins for which relative quantitative values were obtained for all 18 CLL cases (n = 186). Hierarchical clustering of CLL cases based on the relative expression of these proteins generated two clusters comprising the nine cases of UM-CLL and the nine cases of M-CLL, respectively.
Mentions: A total of 3521 proteins were identified within a 1% global false discovery rate and with a high confidence of correct peptide sequence assignment (Fig. 1A and the full list of proteins provided in the supplemental data). Of these, 2024 proteins were identified in all three separate iTRAQ-MS experiments (Fig. 1A). To determine whether protein expression was similar between UM-CLL and M-CLL samples, we subjected the data to PCA. As shown in Fig. 1B, PCA showed a distinction between UM-CLL and M-CLL samples based on protein expression.

Bottom Line: Furthermore, UM-CLL cells underexpressed proteins associated with cytoskeletal remodeling and overexpressed proteins associated with transcriptional and translational activity.Taken together, our findings indicate that UM-CLL cells are less migratory and more adhesive than M-CLL cells, resulting in their retention in lymph nodes, where they are exposed to proliferative stimuli.Our study illustrates the potential of total proteome analysis to elucidate pathogenetic mechanisms in cancer.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Department of Molecular and Clinical Cancer Medicine.

Show MeSH
Related in: MedlinePlus