Discovery of pathway biomarkers from coupled proteomics and systems biology methods

Background

Breast cancer is worldwide the second most common type of cancer after lung cancer. Plasma proteome profiling may have a higher chance to identify protein changes between plasma samples such as normal and breast cancer tissues. Breast cancer cell lines have long been used by researches as model system for identifying protein biomarkers. A comparison of the set of proteins which change in plasma with previously published findings from proteomic analysis of human breast cancer cell lines may identify with a higher confidence a subset of candidate protein biomarker.

Results

In this study, we analyzed a liquid chromatography (LC) coupled tandem mass spectrometry (MS/MS) proteomics dataset from plasma samples of 40 healthy women and 40 women diagnosed with breast cancer. Using a two-sample t-statistics and permutation procedure, we identified 254 statistically significant, differentially expressed proteins, among which 208 are over-expressed and 46 are under-expressed in breast cancer plasma. We validated this result against previously published proteomic results of human breast cancer cell lines and signaling pathways to derive 25 candidate protein biomarkers in a panel. Using the pathway analysis, we observed that the 25 “activated” plasma proteins were present in several cancer pathways, including ‘Complement and coagulation cascades’, ‘Regulation of actin cytoskeleton’, and ‘Focal adhesion’, and match well with previously reported studies. Additional gene ontology analysis of the 25 proteins also showed that cellular metabolic process and response to external stimulus (especially proteolysis and acute inflammatory response) were enriched functional annotations of the proteins identified in the breast cancer plasma samples. By cross-validation using two additional proteomics studies, we obtained 86% and 83% similarities in pathway-protein matrix between the first study and the two testing studies, which is much better than the similarity we measured with proteins.

Conclusions

We presented a ‘systems biology’ method to identify, characterize, analyze and validate panel biomarkers in breast cancer proteomics data, which includes 1) t statistics and permutation process, 2) network, pathway and function annotation analysis, and 3) cross-validation of multiple studies. Our results showed that the systems biology approach is essential to the understanding molecular mechanisms of panel protein biomarkers.

     

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.     

Identification of tumor-associated plasma biomarkers using proteomic techniques: from mouse to human

In an effort to identify tumor-associated proteins from plasma of tumor-bearing mice that may be used as diagnostic biomarkers, we developed a strategy that combines a tumor xenotransplantation model in nude mice with comparative proteomic technology. Five human cancer cell lines (SC-M1, HONE-1, CC-M1, OECM1, GBM 8401) derived from stomach, nasopharyngeal, colon, oral and brain cancers were subcutaneously inoculated into nude mice and compared to control nude mice injected with phosphate-buffered saline. One month later, plasma from mice inoculated with cancer cells was collected for proteomic analysis using two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS). Comparison of plasma 2-DE maps from tumor-bearing mice with those produced from control mice revealed the overexpression of several mouse acute phase proteins (APPs) such as haptoglobin. Another APP, serum amyloid A (SAA), was found only in mice bearing tumors induced by the stomach cancer cell line SC-M1, which has not previously been demonstrated in xenotransplatation experiment. Furthermore, by using immunohistochemistry, SAA and haptoglobin were found to originate from the mouse hosts and not from the human cancer cell line donors. The protein alterations were further confirmed on patients with stomach cancers where up-regulated levels of SAA were also observed. These results indicate that APPs may be used as nonspecific tumor-associated serum markers. SAA in particular may serve as a potential marker for detecting stomach cancer. Taken together, the combination of the xenotransplatation model in nude mice and proteomics analysis provided a valuable impact for clinical applications in cancer diagnostics. In addition, our findings demonstrate that a panel of APPs might serve as screening biomarkers for early cancer detection.     

Targeting therapy for breast carcinoma by ATP synthase inhibitor aurovertin B

Targeting of tumor tissues is one of the most powerful approaches to accelerate the efficiency of anticancer treatments. The investigation of effective targets, including proteins specifically and abundantly expressed in abnormal regions, has been one of the most important research topics in cancer therapy. In this study, we performed a proteomic analysis on human breast carcinoma tissues to investigate the tumor-specific protein expression in breast carcinoma. Our study showed that ATP synthase was up-regulated in tumor tissues and was present on the plasma membrane of breast cancer cells. Furthermore, we treated the breast cancer cells with ATP synthase inhibitors and examined the inhibitory efficiency. Aurovertin B, an ATP synthase inhibitor, has strong inhibition on the proliferation of several breast cancer cell lines, but little influence on the normal cell line MCF-10A. Aurovertin B inhibits proliferation of breast cancer cells by inducing apoptosis and arresting cell cycle at the G0/G1 phase. This study showed aurovertin B can be used as an antitumorigenic agent and may be exploited in cancer chemotherapy.     

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

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.     

Quantitative proteomics study of breast cancer cell lines isolated from a single patient: Discovery of TIMM17A as a marker for breast cancer

The proteins involved in breast cancer initiation and progression are still largely elusive. To gain insights into these processes, we conducted quantitative proteomic analyses with 21T series of breast cell lines, which include a normal, primary tumor and a metastatic tumor that were isolated from a single patient. Stable isotope labeling of amino acid in cell culture followed by LC‐MS/MS analysis was performed and deregulated proteins were identified using statistical analysis. Gene ontology analysis revealed that proteins involved in metabolic processes were the most deregulated in both tumorigenesis and metastasis. Interaction network analysis indicated that ERBB2 signaling played a critical role in tumorigenesis. In addition to known markers such as ERBB2 and E‐cadherin, novel markers, including BRP44L, MTHFD2 and TIMM17A, were found to be overexpressed in 21T breast cancer cells and verified in additional breast cell lines. mRNA expression analysis as well as immunohistochemistry analysis in breast cancer tissues indicated that expression level of TIMM17A was directly correlated with tumor progression, and survival analysis suggested that TIMM17A was a powerful prognosis factor in breast cancer. More interestingly, overexpression and siRNA knockdown experiments indicated an oncogenic activity of TIMM17A in breast cancer. Our study provides a list of potential novel markers for breast cancer tumorigenesis and metastasis using a unique cell model. Further studies on TIMM17A as well as other markers on the list may reveal mechanisms that result in more effective therapeutics for cancer treatment.     

Comprehensive proteomic analysis of breast cancer cell membranes reveals unique proteins with potential roles in clinical cancer

Proteins associated with cancer cell plasma membranes are rich in known drug and antibody targets as well as other proteins known to play key roles in the abnormal signal transduction processes required for carcinogenesis. We describe here a proteomics process that comprehensively annotates the protein content of breast tumor cell membranes and defines the clinical relevance of such proteins. Tumor-derived cell lines were used to ensure an enrichment for cancer cell-specific plasma membrane proteins because it is difficult to purify cancer cells and then obtain good membrane preparations from clinical material. Multiple cell lines with different molecular pathologies were used to represent the clinical heterogeneity of breast cancer. Peptide tandem mass spectra were searched against a comprehensive data base containing known and conceptual proteins derived from many public data bases including the draft human genome sequences. This plasma membrane-enriched proteome analysis created a data base of more than 500 breast cancer cell line proteins, 27% of which were of unknown function. The value of our approach is demonstrated by further detailed analyses of three previously uncharacterized proteins whose clinical relevance has been defined by their unique cancer expression profiles and the identification of protein-binding partners that elucidate potential functionality in cancer.     

Proteomic identification of glycosylphosphatidylinositol anchor-dependent membrane proteins elevated in breast carcinoma

The glycosylphosphatidylinositol (GPI) anchor is a lipid and glycan modification added to the C terminus of certain proteins in the endoplasmic reticulum by the activity of a multiple subunit enzyme complex known as the GPI transamidase (GPIT). Several subunits of GPIT have increased expression levels in breast carcinoma. In an effort to identify GPI-anchored proteins and understand the possible role of these proteins in breast cancer progression, we employed a combination of strategies. First, alpha toxin from Clostridium septicum was used to capture GPI-anchored proteins from human breast cancer tissues, cells, and serum for proteomic analysis. We also expressed short interfering RNAs targeting the expression of the GPAA1 and PIGT subunits of GPIT in breast cancer cell lines to identify proteins in which membrane localization is dependent on GPI anchor addition. Comparative membrane proteomics using nano-ESI-RPLC-MS/MS led to the discovery of several new potential diagnostic and therapeutic targets for breast cancer. Furthermore, we provide evidence that increased levels of GPI anchor addition in malignant breast epithelial cells promotes the dedifferentiation of malignant breast epithelial cells in part by increasing the levels of cell surface markers associated with mesenchymal stem cells.     

Analysis of sera from breast cancer patients by radioimmunoassays

Summary The antibody reactivity of human breast cancer sera was evaluated by means of radioimmunoassays and established breast cancer cell lines. When tested against the MDA-MB 231 cell line, 30 of 324 sera had detectable antibody reactivity. All the positive sera, however, reacted with other cell lines as well, generally including cultures initiated from sites other than breast cancers, and often including animal cell cultures. In competition radioimmunoassays the positive sera fell into various groups, indicating that a diversity of antigens was being detected. Two patients' sera identified antigens that were expressed on breast cancer cells but that were not expressed on an assortment of other cell types. Sera like these two, which identify potentially important tumor markers, could serve as valuable reagents for the analysis of the tumor-assiciated antigens of human breast cancer cells.     

Identification of estrogen-responsive proteins in MCF-7 human breast cancer cells using label-free quantitative proteomics

17beta-Estradiol (E(2)) is a key regulatory steroid hormone that is involved in the control of a number of developmental and other functions. The aim of the present work was to identify estrogen-dependent proteomic changes by determining the levels of expressed proteins in MCF-7 human breast cancer cells following treatment with E(2). A number of methods exist for differential analysis of complex proteomic mixtures. Here, a label-free mass spectrometric approach comparing the ion intensities of tryptic peptides was adopted, which was combined with prefractionation of whole cell lysate proteins by 1-D SDS-PAGE. Using this approach, 60 proteins were found to be affected by E(2). These comprised 55 up-regulated and five down-regulated proteins. These proteins varied widely in their physiochemical properties with pIs of 4-12 and molecular weights of 9-500 kDa. Pathway analysis revealed that the majority of changes were related and together describe an up-regulated pathway consistent with the events of cell proliferation. The quantitative approach used here is relatively straightforward, avoids the use of costly labelling reagents, was reproducible within acceptable limits and has a linear response over a useful concentration range.     

A serum glycomics approach to breast cancer biomarkers

Because the glycosylation of proteins is known to change in tumor cells during the development of breast cancer, a glycomics approach is used here to find relevant biomarkers of breast cancer. These glycosylation changes are known to correlate with increasing tumor burden and poor prognosis. Current antibody-based immunochemical tests for cancer biomarkers of ovarian (CA125), breast (CA27.29 or CA15-3), pancreatic, gastric, colonic, and carcinoma (CA19-9) target highly glycosylated mucin proteins. However, these tests lack the specificity and sensitivity for use in early detection. This glycomics approach to find glycan biomarkers of breast cancer involves chemically cleaving oligosaccharides (glycans) from glycosylated proteins that are shed or secreted by breast cancer tumor cell lines. The resulting free glycan species are analyzed by MALDI-FT-ICR MS. Further structural analysis of the glycans can be performed in FTMS through the use of tandem mass spectrometry with infrared multiphoton dissociation. Glycan profiles were generated for each cell line and compared. These methods were then used to analyze sera obtained from a mouse model of breast cancer and a small number of serum samples obtained from human patients diagnosed with breast cancer or patients with no known history of breast cancer. In addition to the glycosylation changes detected in mice as mouse mammary tumors developed, glycosylation profiles were found to be sufficiently different to distinguish patients with cancer from those without. Although the small number of patient samples analyzed so far is inadequate to make any legitimate claims at this time, these promising but very preliminary results suggest that glycan profiles may contain distinct glycan biomarkers that may correspond to glycan "signatures of cancer."     

Proteomic characterization of Her2/neu-overexpressing breast cancer cells

The receptor tyrosine kinase HER2 is an oncogene amplified in invasive breast cancer and its overexpression in mammary epithelial cell lines is a strong determinant of a tumorigenic phenotype. Accordingly, HER2-overexpressing mammary tumors are commonly indicative of a poor prognosis in patients. Several quantitative proteomic studies have employed two-dimensional gel electrophoresis in combination with MS/MS, which provides only limited information about the molecular mechanisms underlying HER2/neu signaling. In the present study, we used a SILAC-based approach to compare the proteomic profile of normal breast epithelial cells with that of Her2/neu-overexpressing mammary epithelial cells, isolated from primary mammary tumors arising in mouse mammary tumor virus-Her2/neu transgenic mice. We identified 23 proteins with relevant annotated functions in breast cancer, showing a substantial differential expression. This included overexpression of creatine kinase, retinol-binding protein 1, thymosin 4 and tumor protein D52, which correlated with the tumorigenic phenotype of Her2-overexpressing cells. The differential expression pattern of two genes, gelsolin and retinol binding protein 1, was further validated in normal and tumor tissues. Finally, an in silico analysis of published cancer microarray data sets revealed a 23-gene signature, which can be used to predict the probability of metastasis-free survival in breast cancer patients.     

Biomarkers of breast cancer apoptosis induced by chemotherapy and TRAIL

Treatment of breast cancer is complex and challenging due to the heterogeneity of the disease. To avoid significant toxicity and adverse side-effects of chemotherapy in patients who respond poorly, biomarkers predicting therapeutic response are essential. This study has utilized a proteomic approach integrating 2D-DIGE, LC-MS/MS, and bioinformatics to analyze the proteome of breast cancer (ZR-75-1 and MDA-MB-231) and breast epithelial (MCF-10A) cell lines induced to undergo apoptosis using a combination of doxorubicin and TRAIL administered in sequence (Dox-TRAIL). Apoptosis induction was confirmed using a caspase-3 activity assay. Comparative proteomic analysis between whole cell lysates of Dox-TRAIL and control samples revealed 56 differentially expressed spots (≥2-fold change and p < 0.05) common to at least two cell lines. Of these, 19 proteins were identified yielding 11 unique protein identities: CFL1, EIF5A, HNRNPK, KRT8, KRT18, LMNA, MYH9, NACA, RPLP0, RPLP2, and RAD23B. A subset of the identified proteins was validated by selected reaction monitoring (SRM) and Western blotting. Pathway analysis revealed that the differentially abundant proteins were associated with cell death, cellular organization, integrin-linked kinase signaling, and actin cytoskeleton signaling pathways. The 2D-DIGE analysis has yielded candidate biomarkers of response to treatment in breast cancer cell models. Their clinical utility will depend on validation using patient breast biopsies pre- and post-treatment with anticancer drugs.     

Identification of annexin II as a novel secretory biomarker for breast cancer

Early prediction of metastatic breast cancer is important for improvement of prognosis and survival rate. The present study aimed to identify secreted protein biomarkers for detection of invasive breast cancer. To this end, we performed a comparative proteomic analysis by a combination of 2DE and MALDI‐TOF MS analysis of conditioned media from invasive H‐Ras MCF10A human breast epithelial cells and noninvasive MCF10A and N‐Ras MCF10A cells. We identified a list of 25 proteins that were strongly detected in media of H‐Ras MCF10A and focused on annexin II, which was shown to be involved in cell motility. Invasive triple‐negative human breast carcinoma cells, Hs578T, and MDA‐MB‐231, showed increased levels of annexin II in media, demonstrating that secretion of annexin II correlated well with the invasive phenotype of cells. We demonstrated a crucial role of annexin II in breast cell invasion/migration and actin cytoskeleton reorganization required for filopodia formation. Annexin II levels in the plasma samples and breast cancer tissues of breast cancer patients were significantly higher than those of normal groups, providing a clinical relevance to our in vitro findings. Taken together, we identified annexin II as a novel secretory biomarker candidate for invasive breast cancer, especially estrogen receptor‐negative breast cancer.     

RCAS1 is associated with ductal breast cancer progression

RCAS1/EBAG9 (receptor-binding cancer antigen expressed on SiSo cells/ estrogen receptor-binding fragment-associated gene 9), an estrogen-transcribed protein, has been shown to be expressed in a wide variety of cancers, including uterine, ovarian, and lung cancer cells. Soluble and membranous RCAS1 proteins may play a role in the immune escape of tumor cells by promoting T lymphocyte inhibition of growth and apoptosis. In the present report, the presence of RCAS1 was revealed in human ductal breast cancer biopsies by immunohistochemistry. Its cytoplasmic expression was exhibited in cancer cells obtained from tumor biopsies and in breast cancer cell lines. RCAS1 significantly correlated with tumor grade. In addition, RCAS1 was identified in MCF7 culture supernatants. Those observations suggest that RCAS1 is a new marker for breast cancer progression and a possible mechanism for breast cancer immune escape.     

Proteomic study reveals that proteins involved in metabolic and detoxification pathways are highly expressed in HER-2/neu-positive breast cancer

The receptor tyrosine kinase ErbB2 (HER-2/neu) is overexpressed in up to 30% of breast cancers and is associated with poor prognosis and an increased likelihood of metastasis especially in node-positive tumors. In this proteomic study, to identify the proteins that are associated with the aggressive phenotype of HER-2/neu-positive breast cancer, tumor cells from both HER-2/neu-positive and -negative tumors were procured by laser capture microdissection. Differentially expressed proteins in the two subsets of tumors were identified by two-dimensional electrophoresis and MALDI-TOF/TOF MS/MS. We found differential expression of several key cell cycle modulators, which were linked with increased proliferation of the HER-2/neu-overexpressing cells. Nine proteins involved in glycolysis (triose-phosphate isomerase (TPI), phosphoglycerate kinase 1 (PGK1), and enolase 1 (ENO1)), lipid synthesis (fatty acid synthase (FASN)), stress-mediated chaperonage (heat shock protein 27 (Hsp27)), and antioxidant and detoxification pathways (haptoglobin, aldo-keto reductase (AKR), glyoxalase I (GLO), and prolyl-4-hydrolase beta-isoform (P4HB)) were found to be up-regulated in HER-2/neu-positive breast tumors. HER-2/neu-dependent differential expression of PGK1, FASN, Hsp27, and GLO was further validated in four breast cancer cell lines and 12 breast tumors by immunoblotting and confirmed by partially switching off the HER-2/neu signaling in the high HER-2/neu-expressing SKBr3 cell line with Herceptin treatment. Statistical correlations of these protein expressions with HER-2/neu status were further verified by immunohistochemistry on a tissue microarray comprising 97 breast tumors. Our findings suggest that HER-2/neu signaling may result, directly or indirectly, in enhanced activation of various metabolic, stress-responsive, antioxidative, and detoxification processes within the breast tumor microenvironment. We hypothesize that these identified changes in the cellular proteome are likely to drive cell proliferation and tissue invasion and that the key cell cycle modulators involved, when uncovered by future research, would serve as naturally useful targets for the development of therapeutic strategies to negate the metastatic potential of HER-2/neu-positive breast tumors.