Proteomic alterations in early stage cervical cancer

Abstract

Laser capture microdissection (LCM) allows the capture of cell types or well-defined structures in tissue. We compared in a semi-quantitative way the proteomes from an equivalent of 8,000 tumor cells from patients with squamous cell cervical cancer (SCC, n = 22) with healthy epithelial and stromal cells obtained from normal cervical tissue (n = 13). Proteins were enzymatically digested into peptides which were measured by high-resolution mass spectrometry and analyzed by "all-or-nothing" analysis, Bonferroni, and Benjamini-Hochberg correction for multiple testing. By comparing LCM cell type preparations, 31 proteins were exclusively found in early stage cervical cancer (n = 11) when compared with healthy epithelium and stroma, based on criteria that address specificity in a restrictive "all-or-nothing" way. By Bonferroni correction for multiple testing, 30 proteins were significantly up-regulated between early stage cervical cancer and healthy control, including six members of the MCM protein family. MCM proteins are involved in DNA repair and expected to be participating in the early stage of cancer. After a less stringent Benjamini-Hochberg correction for multiple testing, we found that the abundances of 319 proteins were significantly different between early stage cervical cancer and healthy controls. Four proteins were confirmed in digests of whole tissue lysates by Parallel Reaction Monitoring (PRM). Ingenuity Pathway Analysis using correction for multiple testing by permutation resulted in two networks that were differentially regulated in early stage cervical cancer compared with healthy tissue. From these networks, we learned that specific tumor mechanisms become effective during the early stage of cervical cancer.

Keywords: LCM; PRM; biomarker; cervical cancer; proteomics.

Figure 1

Differentially expressed proteins between early stage (A) and late stage (B) cervical cancer compared to healthy epithelium illustrated by a volcano plot. The x-axis represents the ²log fold-change and y-axis the (−)¹⁰log p-value. Examples of proteins that are differentially expressed with high significance are indicated with their names.

Figure 2. Ingenuity pathway analysis (IPA) of the 30 significantly up- and down-regulated proteins (after Bonferroni analysis) for early stage cervical cancer versus healthy controls

Pathway analysis indicated that the network “DNA Replication, Recombination, and Repair”, containing fourteen out of the 30 significant proteins, is up-regulated. The network itself consists of 35 proteins. The up-regulated proteins in early stage cervical cancer are marked red, while those that that were down-regulated were not identified in this pathway. The intensity of the color relates to fold-change. Proteins indicated with a red asterisk were found by LCM, although not differential. Benjamini-Hochberg analysis of the same data resulted in two more proteins (encircled in purple) belonging to this network (MCM5 and WDHD1). The symbols shown in the network are explained at http://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis

Figure 3. The 319 significantly proteins (up- and down-regulated) that were found by Benjamini-Hochberg analysis for early stage cervical cancer were applied to the IPA analysis tool

The pathway analysis resulted in two networks with identical scores that passed the threshold. The indicated network matched to “DNA Replication, Recombination, and Repair” containing 29 out of the 319 significant proteins. The network itself consists of 35 proteins. The up-regulated proteins in early stage cervical cancer are marked red, while those that that were down-regulated were not identified in this pathway. The intensity of the color relates to fold-change. The NF-κB complex protein indicated with a red asterisk was identified once (99% protein- and 95% peptide probability with at least one peptide) by LCM, although not differential. The second network that passed the permutation background score is represented in Figure 4. The symbols shown in the network are explained at http://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis

Figure 4. The second network with identical score as shown in previous network (Figure 3)

The 319 significantly proteins (up- and down-regulated) that were found by Benjamini-Hochberg analysis for early stage cervical cancer were applied to the IPA analysis tool. The pathway analysis resulted in the finding of the network “Cardiac Arrythmia, Cardiovascular Disease, Organismal Injury and Abnormalities” containing 29 out of the 319 significant proteins. The network itself consists of 35 proteins. The up-regulated proteins in early stage cervical cancer are marked red and those up-regulated in healthy epithelial cells are marked green. The intensity of the color (red or green) relates to fold-change. Interestingly, almost 50% (13 out of 29) of proteins identified were down-regulated. The symbols shown in the network are explained at http://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis

Figure 5. The 140 significantly proteins (up- and down-regulated) that were found by Benjamini-Hochberg analysis for late stage cervical cancer were applied to the IPA analysis tool

The pathway analysis resulted in the finding of the network “DNA Replication, Recombination, and Repair” containing 27 out of the 140 significant proteins. The network itself consists of 35 proteins. The up-regulated proteins in late stage cervical cancer are marked red and two proteins which were up-regulated in healthy epithelial cells are indicated with a green color. The intensity of the color (red or green) relates to fold-change. Proteins (n = 5) indicated with a red asterisk have been identified minimal once (99% protein- and 95% peptide probability with at least one peptide) by LCM, although not differential. The symbols shown in the network are explained at http://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis

Figure 6

Hierarchical clustering of fourteen proteins found by the IPA tool related to early stage cervical cancer (EC), late stage cervical cancer (LC) and healthy epithelium (HE) visualizes the heterogeneity among individual samples. For the early and late stage cervical cancer group, clustering of MCM proteins was readily observed and showed high similarity between samples. Interestingly, the MCM2, MCM3, MCM6 and MCM4, MCM7 clustered in two different clusters. For the healthy epithelium group, the result was different compared to early and late stage cervical cancer group in which only MCM6 from the MCM2-7 family clustered separately. The abundance levels of proteins were indicated with red (high) and black (low). Sample numbers correspond to those shown in Table 1.

Figure 7

Laser microdissected healthy epithelial cells were compared in a semi-quantitative way with early (A) and late (B) stage cervical cancer, a cervical cancer derived cell line (HeLa) and two cell lines that were derived from brain tumor (U87) and normal embryonal kidney tissue (HEK). Most of the fourteen differential proteins which were from the network behave similar between healthy epithelium and various tumor types, except for a few. The proteins PLAA, POLD1 and S100P were only observed in cervical cancer and HeLa digests when comparing to healthy epithelium (zero counts were converted into 0.125 to allow logarithm calculation). It was shown that MCM proteins in cervical cancer can have a 32-fold increase (²log fold-change of 5, e.g. MCM4) in abundance compared to healthy epithelium.

Figure 8. Example of targeted mass spectrometry by PRM

Total amount (in nanograms) of the proteins MCM3, CEACAM5, S100P and ICAM1 were determined in digests of whole tissue lysates. Total tissue areas (mm²) and UV peak areas (mAU*min) were applied on top of the figure to estimate the amount of tissue used. Blue, red and green bars correspond to early stage cancer, late stage cancer and healthy samples, respectively.

Figure 9. Experimental design of technical and methodological reproducibility