Signal pathway profiling of prostate cancer using reverse phase protein arrays

Reverse phase protein arrays represent a new proteomics microarray technology with which to study the fluctuating state of the proteome in minute quantities of cells. The activation status of cell signaling pathways controls cellular fate and deregulation of these pathways underpins carcinogenesis. Changes in pathway activation that occur between early stage prostatic epithelial lesions, prostatic stroma and the extracellular matrix can be analyzed by obtaining pure populations of cell types by laser capture microdissection (LCM) and analyzing the relative states of several key phosphorylation points within the cellular circuitry. We have applied reverse phase protein array technology to analyze the status of key points in cell signaling involved in pro-survival, mitogenic, apoptotic and growth regulation pathways in the progression from normal prostate epithelium to invasive prostate cancer. Using multiplexed reverse phase protein arrays coupled with LCM, the states of signaling changes during disease progression from prostate cancer study sets were analyzed. Focused analysis of phospho-specific endpoints revealed changes in cellular signaling events through disease progression and between patients. We have used a new protein array technology to study specific molecular pathways believed to be important in cell survival and progression from normal epithelium to invasive carcinoma directly from human tissue specimens. With the advent of molecular targeted therapeutics, the identification, characterization and monitoring of the signaling events within actual human biopsies will be critical for patient-tailored therapy.     

HER-2 assessment in formalin-fixed paraffin-embedded breast cancer tissue by well-based reverse phase protein array

Background

The human epidermal growth factor receptor-2 (HER-2) expression level is a critical element for determining the prognosis and management of breast cancer. HER-2 targeted therapy in breast cancer depends on the reliable assessment of HER-2 expression status but current standard methods are lacking a rigorous quantitative assay. To address this challenge, we developed an assessment of HER-2 expression method by well-based reverse phase protein array (RPPA).

Results

Well-based RPPA is based on a robust protein isolation methodology paired with a novel electrochemiluminescence detection system. HER-2 value of well-based RPPA significantly correlated with dot blotting results (R² = 0.939). By well-based RPPA, we successfully detected HER-2 expression in 76 human breast formalin-fixed paraffin-embedded tissue samples. We observed 93.4% (71/76) concordance between well-based RPPA and current HER-2 immunohistochemical assessment guideline. When the cutoff level of HER-2 value was set to 0.689 (HER-2/GAPDH) on the basis of receiver-operating characteristic curve, the area under the curve was 0.975 (95% CI, 0.941-1.000). Sensitivity and specificity of well-based RPPA was 92.1% and 94.7%, respectively.

Conclusions

HER-2 value by well-based RPPA was correlated with the current HER-2 status guideline, suggesting that this normalized HER-2 assessment may offer advantages over unnormalized current immunohistochemical assessment methods.     

Increasing the sensitivity of reverse phase protein arrays by antibody-mediated signal amplification

Background  

Reverse phase protein arrays (RPPA) emerged as a useful experimental platform to analyze biological samples in a high-throughput format. Different signal detection methods have been described to generate a quantitative readout on RPPA including the use of fluorescently labeled antibodies. Increasing the sensitivity of RPPA approaches is important since many signaling proteins or posttranslational modifications are present at a low level.     

RNAi-based validation of antibodies for reverse phase protein arrays

Background  

Reverse phase protein arrays (RPPA) have been demonstrated to be a useful experimental platform for quantitative protein profiling in a high-throughput format. Target protein detection relies on the readout obtained from a single detection antibody. For this reason, antibody specificity is a key factor for RPPA. RNAi allows the specific knockdown of a target protein in complex samples and was therefore examined for its utility to assess antibody performance for RPPA applications.     

Pathway alterations during glioma progression revealed by reverse phase protein lysate arrays

The progression of gliomas has been extensively studied at the genomic level using cDNA microarrays. However, systematic examinations at the protein translational and post-translational levels are far more limited. We constructed a glioma protein lysate array from 82 different primary glioma tissues, and surveyed the expression and phosphorylation of 46 different proteins involved in signaling pathways of cell proliferation, cell survival, apoptosis, angiogenesis, and cell invasion. An analysis algorithm was employed to robustly estimate the protein expressions in these samples. When ranked by their discriminating power to separate 37 glioblastomas (high-grade gliomas) from 45 lower-grade gliomas, the following 12 proteins were identified as the most powerful discriminators: IBalpha, EGFRpTyr845, AKTpThr308, phosphatidylinositol 3-kinase (PI3K), BadpSer136, insulin-like growth factor binding protein (IGFBP) 2, IGFBP5, matrix metalloproteinase 9 (MMP9), vascular endothelial growth factor (VEGF), phosphorylated retinoblastoma protein (pRB), Bcl-2, and c-Abl. Clustering analysis showed a close link between PI3K and AKTpThr308, IGFBP5 and IGFBP2, and IBalpha and EGFRpTyr845. Another cluster includes MMP9, Bcl-2, VEGF, and pRB. These clustering patterns may suggest functional relationships, which warrant further investigation. The marked association of phosphorylation of AKT at Thr308, but not Ser473, with glioblastoma suggests a specific event of PI3K pathway activation in glioma progression.     

Multi-parametric MRI lesion heterogeneity biomarkers for breast cancer diagnosis

PurposeTo identify intra-lesion imaging heterogeneity biomarkers in multi-parametric Magnetic Resonance Imaging (mpMRI) for breast lesion diagnosis.MethodsDynamic Contrast Enhanced (DCE) and Diffusion Weighted Imaging (DWI) of 73 female patients, with 85 histologically verified breast lesions were acquired. Non-rigid multi-resolution registration was utilized to spatially align sequences. Four (4) DCE (2^nd post-contrast frame, Initial-Enhancement, Post-Initial-Enhancement and Signal-Enhancement-Ratio) and one (1) DWI (Apparent-Diffusion-Coefficient) representations were analyzed, considering a representative lesion slice. 11 1^st-order-statistics and 16 texture features (Gray-Level-Co-occurrence-Matrix (GLCM) and Gray-Level-Run-Length-Matrix (GLRLM) based) were derived from lesion segments, provided by Fuzzy C-Means segmentation, across the 5 representations, resulting in 135 features. Least-Absolute-Shrinkage and Selection-Operator (LASSO) regression was utilized to select optimal feature subsets, subsequently fed into 3 classification schemes: Logistic-Regression (LR), Random-Forest (RF), Support-Vector-Machine-Sequential-Minimal-Optimization (SVM-SMO), assessed with Receiver-Operating-Characteristic (ROC) analysis.ResultsLASSO regression resulted in 7, 6 and 7 features subsets from DCE, DWI and mpMRI, respectively. Best classification performance was obtained by the RF multi-parametric scheme (Area-Under-ROC-Curve, (AUC) ± Standard-Error (SE), AUC ± SE = 0.984 ± 0.025), as compared to DCE (AUC ± SE = 0.961 ± 0.030) and DWI (AUC ± SE = 0.938 ± 0.032) and statistically significantly higher as compared to DWI. The selected mpMRI feature subset highlights the significance of entropy (1^st-order-statistics and 2^nd-order-statistics (GLCM)) and percentile features extracted from 2^nd post-contrast frame, PIE, SER maps and ADC map.ConclusionCapturing breast intra-lesion heterogeneity, across mpMRI lesion segments with 1^st-order-statistics and texture features (GLCM and GLRLM based), offers a valuable diagnostic tool for breast cancer.     

Mycoplasma contamination of leukemic cell lines alters protein expression determined by reverse phase protein arrays

Mycoplasma contamination is a major problem in cell culturing, potentially altering the results of cell line-based experiments in largely uncharacterized ways. To define the consequences of mycoplasma infection at the level of protein expression we utilized the reverse phase protein array technology to analyze the expression of 235 proteins in mycoplasma infected, uninfected post treatment, and never-infected leukemic cell lines. Overall, protein profiles of cultured cells remained relatively stable after mycoplasma infection. However, paired comparisons for individual proteins identified that 18.7% of the proteins significantly changed between the infected and the never-infected cell line samples, and that 14.0% of the proteins significantly altered between the infected and the post treatment samples. Six percent of the proteins were affected in the post treatment samples compared to the never-infected samples, and 7.2% compared to treated cells that had never had mycoplasma infection before. Proteins that were significantly altered in the infected cells were enriched for apoptotic signaling processes and auto-phosphorylation, suggesting an increased cellular stress and a decreased growth rate. In conclusion, this study shows that mycoplasma infection of leukemic cell lines alters the proteins expression levels, potentially confounding experimental results. This reinforces the need for regular testing of mycoplasma.     

Characterization of protein expression levels with label-free detected reverse phase protein arrays

In reverse-phase protein arrays (RPPA), one immobilizes complex samples (e.g., cellular lysate, tissue lysate or serum etc.) on solid supports and performs parallel reactions of antibodies with immobilized protein targets from the complex samples. In this work, we describe a label-free detection of RPPA that enables quantification of RPPA data and thus facilitates comparison of studies performed on different samples and on different solid supports. We applied this detection platform to characterization of phosphoserine aminotransferase (PSAT) expression levels in Acanthamoeba lysates treated with artemether and the results were confirmed by Western blot studies.     

Utility of reverse phase protein arrays: Applications to signalling pathways and human body arrays

Brief Funct     

Blocking and detection chemistries affect antibody performance on reverse phase protein arrays

Antibody specificity is critical for RP protein arrays (RPA). The effects of blocking and detection chemistries on antibody specificity were evaluated for Western blots and RPA. Blocking buffers significantly affected nonspecific banding on Western blots, with corresponding effects on arrays. Tyramide signal amplification (TSA) increased both specific and nonspecific signals on Westerns and arrays, masking the expected gradations in signal intensity. These results suggest that consistent blocking and detection conditions should be used for antibody validation and subsequent RPA experiments.     

Utility of reverse phase protein arrays: applications to signalling pathways and human body arrays.

Protein microarrays offer a new means by which to conduct quantitative profiling of disease-associated proteins. The knowledge gained may provide novel strategies for early detection, diagnosis and therapeutic intervention. A variety of sophisticated approaches, including gene arrays, sequencing consortiums and large-scale two-dimensional gel electrophoresis, continue to generate lists of proteins potentially linked to disease aetiology and progression. The challenge is to evaluate quantitatively promising lead protein candidates using matched normal and diseased cell populations. In contrast to the antibody array, the reverse phase protein microarrays (RPPA) do not require labelling of cellular protein lysates, and constitute a sensitive high throughput platform for marker screening, pathophysiology investigation and therapeutic monitoring. In this paper, examples will be provided using RPPAs in the study of the apoptotic signalling cascade and in the evaluation of the expression of organ-specific protein makers using microdissected human organ cell lysates configured as 'human body arrays'.     

Spatiotemporal expression profiling of proteins in rat sciatic nerve regeneration using reverse phase protein arrays

Background  

Protein expression profiles throughout 28 days of peripheral nerve regeneration were characterized using an established rat sciatic nerve transection injury model. Reverse phase protein microarrays were used to identify the spatial and temporal expression profile of multiple proteins implicated in peripheral nerve regeneration including growth factors, extracellular matrix proteins, and proteins involved in adhesion and migration. This high-throughput approach enabled the simultaneous analysis of 3,360 samples on a nitrocellulose-coated slide.     

The anti-apoptotic protein lifeguard is expressed in breast cancer cells and tissues

Lifeguard (LFG) is an anti-apoptotic protein that inhibits Fas-mediated death in tumour cells. However, the molecular function of human LFG in the carcinogenesis of human breast cells is uncertain. We studied the expression and function of endogenous LFG in four breast cancer cell lines (MCF-7, MDA-MB-231, T-47D and HS 578T), a human breast epithelial cell line (HS 578Bst), and in healthy and cancerous breast tissues. Molecular (Western blot and RT-PCR) and immunohistochemical techniques were used to investigate the LFG expression. To investigate the breast cancer cell proliferation in the presence of Fas, we performed fluorescent cell viability assays. The possible association of Fas with LFG was analyzed by immunofluorescence microscopy. In this paper, we provide convincing evidence that LFG is overexpressed in several human breast cancer cell lines. More importantly, we found that the LFG expression correlates with high tumour grades in primary breast tumours. Finally, we demonstrated that Fas sensitivity is reduced in breast cancer cell lines expressing LFG. Our results indicated that LFG is strongly expressed in breast cancer epithelial cells. Moreover, the overexpression of LFG correlated with tumour grade and reduced Fas sensitivity. Our findings support the idea that LFG may have a role in the downregulation of apoptosis in breast cancer cells.     

RPPAML/RIMS: A metadata format and an information management system for reverse phase protein arrays

Background  

Reverse Phase Protein Arrays (RPPA) are convenient assay platforms to investigate the presence of biomarkers in tissue lysates. As with other high-throughput technologies, substantial amounts of analytical data are generated. Over 1000 samples may be printed on a single nitrocellulose slide. Up to 100 different proteins may be assessed using immunoperoxidase or immunoflorescence techniques in order to determine relative amounts of protein expression in the samples of interest.     

Determining proteome-wide expression levels using reverse protein arrays in fission yeast

Global protein expression profiling of various mutants or growth conditions is currently a major challenge in biology. Here we provide a protocol for a strategy that we recently developed that couples ORFeome-based (ORF denotes open reading frame) expression to reverse protein arrays; this approach accurately quantifies more than 99% of the predicted fission yeast proteins in various genetic backgrounds. The first stage of this two-stage protocol requires mass mating between any fertile fission yeast mutant of interest and the integrated fission yeast-tagged ORFeome followed by selection of recombinant haploids. The second stage of the protocol, called reverse protein arrays, involves simple large-scale extraction of total proteins, which are then spotted on nitrocellulose membranes for detection by quantitative dot blot. When handled manually, the entire protocol takes about 2 months. However, the process could easily be automated and should also be applicable to other organisms.     

Quantitative cell-cycle protein expression in oral cancer assessed by computer-assisted system

The knowledge of cell-cycle control has shown that the capacity of malignant growth is acquired by the stepwise accumulation of defects in specific genes regulating cell growth. Histologic diagnosis might be improved by a quantitative evaluation of more specific diagnosis biomarkers, which could help to precisely identify pre-malignant and malignant oral lesions. The aim of the present study is to evaluate whether computer-based quantitative assessment of p53, PCNA and Ki-67 immunohistochemical expression, could be used clinically to foresee the risk of oral malignant transformation. This retrospective study was carried out in ninety-five oral biopsies, 27 were classified as fibrous inflammatory hyperplasia, 40 as leukoplakia and 28 as oral squamous cell carcinoma. Sixteen out of the 40 leukoplakia were diagnosed as non-dysplastic leukoplakia, the other 24 being dysplastic leukoplakia, of which 50.0% were classified as moderate to severe dysplasia. Comparison of the four groups of oral tissues showed significant rises in p53 and Ki-67 positivity index, which increased steadily in the order benign, pre-malignant, and malignant. In contrast, it was not possible to relate higher PCNA levels with pre-malignant and malignant oral lesions. We therefore conclude that PCNA immunohistochemistry expression is probably an inappropriate marker to identify oral carcinogenesis, whereas joint quantitative evaluation of p53 and Ki-67, appears to be useful as a tumor marker, providing a pre-diagnostic estimate of the potential for cell-cycle deregulation of the oral proliferate status.     

Grade-specific diagnostic and prognostic biomarkers in breast cancer

An integrative approach is presented to identify grade-specific biomarkers for breast cancer. Grade-specific molecular interaction networks were constructed with differentially expressed genes (DEGs) of cancer grade 1, 2, and 3. We observed that the molecular network of grade3 is predominantly associated with cancer-specific processes. Among the top ten connected DEGs in the grade3, the increase in the expression of UBE2C and CCNB2 genes was statistically significant across different grades. Along with UBE2C and CCNB2 genes, the CDK1, KIF2C, NDC80, and CCNB2 genes are also profoundly expressed in different grades and reduce the patient's survival. Gene set enrichment analysis of these six genes reconfirms their role in metastatic phenotype. Moreover, the coexpression network shows a strong association of these six genes promotes cancer specific biological processes and possibly drives cancer from lower to a higher grade. Collectively the identified genes can act as potential biomarkers for breast cancer diagnosis and prognosis.     

Potential plasma lipid biomarkers in early-stage breast cancer

Objective

To find new biomarkers for early diagnosis of breast cancer.

Results

847 lipid species were identified from 78 plasma samples (37 breast cancer samples and 41 healthy controls) by ultra HPLC coupled with quadrupole time-of-flight tandem mass spectrometry. These include 321 glycerophospholipids (GPs), 265 glycerolipids (GLs), 91 sphingolipids (SPs), 77 fatty acyls (FAs), 68 sterol lipids (STs), 18 prenol lipids (PRs), 6 polyketides (PKs), and 1 saccharolipid (SL). Separation was observed from an orthogonal signal correction Partial Least Square Discrimination Analysis model. Based on this analysis, six differentiating lipids were identified: PC (20:2/20:5), PC (22:0/24:1), TG (12:0/14:1), and DG (18:1/18:2) had high levels, whereas PE (15:0/19:1) and N-palmitoyl proline had low levels in the breast cancer samples compared with the healthy controls. Furthermore, significant differences in metabolites were found among some clinical characteristics.

Conclusions

Our results reveal that six specific lipids could serve as potential biomarkers for early diagnosis of breast cancer.