Protein-based identification of quantitative trait loci associated with malignant transformation in two HER2+ cellular models of breast cancer

Abstract

Background: A contemporary view of the cancer genome reveals extensive rearrangement compared to normal cells. Yet how these genetic alterations translate into specific proteomic changes that underpin acquiring the hallmarks of cancer remains unresolved. The objectives of this study were to quantify alterations in protein expression in two HER2+ cellular models of breast cancer and to infer differentially regulated signaling pathways in these models associated with the hallmarks of cancer.

Results: A proteomic workflow was used to identify proteins in two HER2 positive tumorigenic cell lines (BT474 and SKBR3) that were differentially expressed relative to a normal human mammary epithelial cell line (184A1). A total of 64 (BT474-184A1) and 69 (SKBR3-184A1) proteins were uniquely identified that were differentially expressed by at least 1.5-fold. Pathway inference tools were used to interpret these proteins in terms of functionally enriched pathways in the tumor cell lines. We observed "protein ubiquitination" and "apoptosis signaling" pathways were both enriched in the two breast cancer models while "IGF signaling" and "cell motility" pathways were enriched in BT474 and "amino acid metabolism" were enriched in the SKBR3 cell line.

Conclusion: While "protein ubiquitination" and "apoptosis signaling" pathways were common to both the cell lines, the observed patterns of protein expression suggest that the evasion of apoptosis in each tumorigenic cell line occurs via different mechanisms. Evidently, apoptosis is regulated in BT474 via down regulation of Bid and in SKBR3 via up regulation of Calpain-11 as compared to 184A1.

Figure 1

Representative 2-D proteomic profiles of cell lines (A) 184A1, (B) BT474 and (C) SKBR3. The first dimension was resolved on IPG strip 4-7, 7 cm. The second dimension is a 12% SDS-PAGE spanning molecular weight region 10-250 kDa, stained with coomassie blue and scanned using Typhoon 9400 scanner. (D) Quantitative image analysis using Ludesi REDFIN reveals the gel reproducibility and protein loading with no significant difference in the number of identified protein spots on the gel replicates across each cell line. Error bars represent S.E.M. Scatter plots of average normalized intensities are plotted on a logarithmic scale for matching protein spots showing the dynamic range of spot detection and correlation for the normal cell line 184A1 versus (E) BT474 and (F) SKBR3.

Figure 2

Montage showing differential expression of (A) Rnase11 and (B) Hibadh on each gel across both comparisons (identified spot border is in red and neighboring spot borders are in blue). Densitometric quantitation of the normalized volume of the spot on each gel with the associated fold-change and corresponding p-value is shown for (C) Rnase 11 and (D) Hibadh. Mass spectra for each peptide digest was acquired between mass values of 800 and 3000, deisotoped using PLGS2.1 and submitted for peptide mass fingerprinting. The mass spectra is shown for (D) Rnase11 and (E) Hibadh with the peptide mass values that contributed towards successful identification of the protein indicated in bold and numbered on the spectrum.

Figure 3

Proteome map for 184A1 with red circles indicating protein spots differentially expressed by at least 1.5-fold (p < 0.05) that were identified in (A) BT474 and (B) SKBR3. Identified proteins are shown in Additional File 2: Table S1 (184A1-BT474) and Table S2 (184A1-SKBR3).

Figure 4

Significant canonical pathways (p < 0.05) for proteins differentially expressed in BT474 (black) and SKBR3 (gray) in comparison with 184A1 cell line. The negative of the log₁₀ (p-value) (long dash dot dot) and ratio (number of focus molecules involved in the pathway/total number of molecules in the pathway) are plotted on the primary and secondary Y-axis respectively. Pathways for BT474 are indicated by black columns and the ratio is indicated by a solid line joined by squares. Similarly, pathways for SKBR3 are indicated by gray columns and corresponding ratio is indicated by long dashes joined by circles. (Panel A) Canonical pathways unique to each cell line. (Panel B) Canonical pathways common to both the cell lines. (Panel C) Functional clustering of gene ontology (GO) terms associated with apoptosis for differentially expressed proteins obtained using DAVID. Green region of the heat map indicates corresponding GO association positively reported and the black region indicates the GO association not reported as yet. Gene symbols colored red are down-regulated and colored green are up-regulated in tumor cell lines in comparison with 184A1.

Figure 5

Proteins differentially expressed in (A) BT474 and (B) SKBR3 in comparison with 184A1 were overlaid onto a global molecular network developed from information contained in the Ingenuity Knowledge Base (IKB). Genes or gene products are represented as nodes, and the biological relationship between two nodes is represented as an edge (line). Solid lines indicate a direct relationship and dashed lines indicate an indirect relationship between nodes. The intensity of the node color represents the degree of up- (red) or down- (green) regulation. White nodes represent the IKB molecules associated with focus genes. Network reflects (A) Cellular Function and Maintenance, Cell Death, and Protein Synthesis (p < 10^-48) and (B) Cell Morphology, Cellular Function and Maintenance, and Protein Degradation (p < 10^-57).

Figure 6

Western blot validation of identified proteins to confirm the expression trend as inferred from 2DE. Protein levels were normalized against GAPDH. Error bars represent S.E.M. * represents (p < 0.05) and ** represents (p < 0.01).