Quantitative proteomic profiling studies of pancreatic cancer stem cells

Abstract

Analyzing subpopulations of tumor cells in tissue is a challenging subject in proteomic studies. Pancreatic cancer stem cells (CSCs) are such a group of cells that only constitute 0.2-0.8% of the total tumor cells but have been found to be the origin of pancreatic cancer carcinogenesis and metastasis. Global proteome profiling of pancreatic CSCs from xenograft tumors in mice is a promising way to unveil the molecular machinery underlying the signaling pathways. However, the extremely low availability of pancreatic tissue CSCs (around 10,000 cells per xenograft tumor or patient sample) has limited the utilization of currently standard proteomic approaches which do not work effectively with such a small amount of material. Herein, we describe the profiling of the proteome of pancreatic CSCs using a capillary scale shotgun technique by coupling offline capillary isoelectric focusing(cIEF) with nano reversed phase liquid chromatography(RPLC) followed by spectral counting peptide quantification. A whole cell lysate from 10,000 cells which corresponds to approximately 1 microg of protein material is equally divided for three repeated cIEF separations where around 300 ng of peptide material is used in each run. In comparison with a nontumorigenic tumor cell sample, among 1159 distinct proteins identified with FDR less than 0.2%, 169 differentially expressed proteins are identified after multiple testing corrections where 24% of the proteins are upregulated in the CSCs group. Ingenuity Pathway analysis of these differential expression signatures further suggests significant involvement of signaling pathways related to apoptosis, cell proliferation, inflammation, and metastasis.

Figure1

Figure1(a): Experimental flow chart Figure1(b): Data Processing Strategy. Upper left matrix is the consolidated dataset. Lower left flowchart is the correction factor searching scheme and transformation algorithm.

Figure1

Figure1(a): Experimental flow chart Figure1(b): Data Processing Strategy. Upper left matrix is the consolidated dataset. Lower left flowchart is the correction factor searching scheme and transformation algorithm.

Figure2

Figure2(a): Theoretical pI distribution plot of the first run of CSC group. Fraction number shown in the X-axis is plotted against the average of peptides' pI value within each fraction shown in the Y-axis. Figure2(b): Distribution of number of identified peptides from each run of tumor group across pI range between 3.5 to 10. X-axis shows their pI value and Y-axis shows the number of identified peptides. Different tumor replicate runs are represented by different colors. Figure2(c): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and the second run of CSC group. Figure2(d): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and second replicate of tumor group.

Figure2

Figure2(a): Theoretical pI distribution plot of the first run of CSC group. Fraction number shown in the X-axis is plotted against the average of peptides' pI value within each fraction shown in the Y-axis. Figure2(b): Distribution of number of identified peptides from each run of tumor group across pI range between 3.5 to 10. X-axis shows their pI value and Y-axis shows the number of identified peptides. Different tumor replicate runs are represented by different colors. Figure2(c): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and the second run of CSC group. Figure2(d): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and second replicate of tumor group.

Figure2

Figure2(a): Theoretical pI distribution plot of the first run of CSC group. Fraction number shown in the X-axis is plotted against the average of peptides' pI value within each fraction shown in the Y-axis. Figure2(b): Distribution of number of identified peptides from each run of tumor group across pI range between 3.5 to 10. X-axis shows their pI value and Y-axis shows the number of identified peptides. Different tumor replicate runs are represented by different colors. Figure2(c): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and the second run of CSC group. Figure2(d): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and second replicate of tumor group.

Figure2

Figure2(a): Theoretical pI distribution plot of the first run of CSC group. Fraction number shown in the X-axis is plotted against the average of peptides' pI value within each fraction shown in the Y-axis. Figure2(b): Distribution of number of identified peptides from each run of tumor group across pI range between 3.5 to 10. X-axis shows their pI value and Y-axis shows the number of identified peptides. Different tumor replicate runs are represented by different colors. Figure2(c): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and the second run of CSC group. Figure2(d): Pearson correlation plot of all proteins detected with single or more spectral counts in the first and second replicate of tumor group.

Figure3

Monotonic plot of original data Vs transformed data. Different color and different shapes represent csc1, csc2, csc3, tumor1, tumor2, tumor3, tumor4, respectively. Y-axis represent original data and X-axis represent transformed data on log2 scale.

Figure4

Clustering results of the CSC group and tumor group after transforming by f=3.

Figure5

Figure5(a): Cellular Distribution of identified proteins from pooled CSC group. Figure5(b): Cellular Distribution of identified proteins from pooled tumor group.

Figure5

Figure5(a): Cellular Distribution of identified proteins from pooled CSC group. Figure5(b): Cellular Distribution of identified proteins from pooled tumor group.

Figure6

Canonical signaling pathways enriched with differentially expressed proteins ranked by significance. A threshold p-value < 0.1 is applied.

Figure7

The top1 connectivity network constructed by IPA. This network only consists of differentially expressed proteins from experimental data. Red and green circles indicate overexpression and underexpression in the CSC group versus the bulk tumor group, respectively.

Figure8

Global proteome profiling of pancreatic cancer stem cells(CSCs) is a promising way to unveil the molecular machinery underlying the signaling pathways. However, the extremely low availability of pancreatic tissue CSCs has limited the utilization of current standard proteomic approaches. We describe the profiling of the proteome of pancreatic CSCs using a capillary scale shotgun technique by coupling off-line capillary isoelectric focusing(cIEF) with nano reversed phase liquid chromatography(RPLC) to profile the proteome from < 1ug total protein.