Identifying new therapeutic targets via modulation of protein corona formation by engineered nanoparticles

Background

We introduce a promising methodology to identify new therapeutic targets in cancer. Proteins bind to nanoparticles to form a protein corona. We modulate this corona by using surface-engineered nanoparticles, and identify protein composition to provide insight into disease development.

Methods/Principal Findings

Using a family of structurally homologous nanoparticles we have investigated the changes in the protein corona around surface-functionalized gold nanoparticles (AuNPs) from normal and malignant ovarian cell lysates. Proteomics analysis using mass spectrometry identified hepatoma-derived growth factor (HDGF) that is found exclusively on positively charged AuNPs (⁺AuNPs) after incubation with the lysates. We confirmed expression of HDGF in various ovarian cancer cells and validated binding selectivity to ⁺AuNPs by Western blot analysis. Silencing of HDGF by siRNA resulted s inhibition in proliferation of ovarian cancer cells.

Conclusion

We investigated the modulation of protein corona around surface-functionalized gold nanoparticles as a promising approach to identify new therapeutic targets. The potential of our method for identifying therapeutic targets was demonstrated through silencing of HDGF by siRNA, which inhibited proliferation of ovarian cancer cells. This integrated proteomics, bioinformatics, and nanotechnology strategy demonstrates that protein corona identification can be used to discover novel therapeutic targets in cancer.     

Modeling the Time Evolution of the Nanoparticle-Protein Corona in a Body Fluid

Background

Nanoparticles in contact with biological fluids interact with proteins and other biomolecules, thus forming a dynamic corona whose composition varies over time due to continuous protein association and dissociation events. Eventually equilibrium is reached, at which point the continued exchange will not affect the composition of the corona.

Results

We developed a simple and effective dynamic model of the nanoparticle protein corona in a body fluid, namely human plasma. The model predicts the time evolution and equilibrium composition of the corona based on affinities, stoichiometries and rate constants. An application to the interaction of human serum albumin, high density lipoprotein (HDL) and fibrinogen with 70 nm N-iso-propylacrylamide/N-tert-butylacrylamide copolymer nanoparticles is presented, including novel experimental data for HDL.

Conclusions

The simple model presented here can easily be modified to mimic the interaction of the nanoparticle protein corona with a novel biological fluid or compartment once new data will be available, thus opening novel applications in nanotoxicity and nanomedicine.     

Microfluidic electrochemical immunoarray for ultrasensitive detection of two cancer biomarker proteins in serum

A microfluidic electrochemical immunoassay system for multiplexed detection of protein cancer biomarkers was fabricated using a molded polydimethylsiloxane channel and routine machined parts interfaced with a pump and sample injector. Using off-line capture of analytes by heavily-enzyme-labeled 1 μm superparamagnetic particle (MP)-antibody bioconjugates and capture antibodies attached to an 8-electrode measuring chip, simultaneous detection of cancer biomarker proteins prostate specific antigen (PSA) and interleukin-6 (IL-6) in serum was achieved at sub-pg mL?1 levels. MPs were conjugated with ～90,000 antibodies and ～200,000 horseradish peroxidase (HRP) labels to provide efficient off-line capture and high sensitivity. Measuring electrodes feature a layer of 5 nm glutathione-decorated gold nanoparticles to attach antibodies that capture MP-analyte bioconjugates. Detection limits of 0.23 pg mL?1 for PSA and 0.30 pg mL?1 for IL-6 were obtained in diluted serum mixtures. PSA and IL-6 biomarkers were measured in serum of prostate cancer patients in total assay time 1.15 h and sensor array results gave excellent correlation with standard enzyme-linked immunosorbent assays (ELISA). These microfluidic immunosensors employing nanostructured surfaces and off-line analyte capture with heavily labeled paramagnetic particles hold great promise for accurate, sensitive multiplexed detection of diagnostic cancer biomarkers.     

Synthetic osteogenic extracellular matrix formed by coated silicon dioxide nanosprings

Background

Angiogenesis is widely investigated in conjunction with cancer development, in particular because of the possibility of early stage detection and of new therapeutic strategies. However, such studies are negatively affected by the limitations of imaging techniques in the detection of microscopic blood vessels (diameter 3-5 ??m) grown under angiogenic stress. We report that synchrotron-based X-ray imaging techniques with very high spatial resolution can overcome this obstacle, provided that suitable contrast agents are used.

Results

We tested different contrast agents based on gold nanoparticles (AuNPs) for the detection of cancer-related angiogenesis by synchrotron microradiology, microtomography and high resolution X-ray microscopy. Among them only bare-AuNPs in conjunction with heparin injection provided sufficient contrast to allow in vivo detection of small capillary species (the smallest measured lumen diameters were 3-5 ??m). The detected vessel density was 3-7 times higher than with other nanoparticles. We also found that bare-AuNPs with heparin allows detecting symptoms of local extravascular nanoparticle diffusion in tumor areas where capillary leakage appeared.

Conclusions

Although high-Z AuNPs are natural candidates as radiology contrast agents, their success is not guaranteed, in particular when targeting very small blood vessels in tumor-related angiography. We found that AuNPs injected with heparin produced the contrast level needed to reveal--for the first time by X-ray imaging--tumor microvessels with 3-5 ??m diameter as well as extravascular diffusion due to basal membrane defenestration. These results open the interesting possibility of functional imaging of the tumor microvasculature, of its development and organization, as well as of the effects of anti-angiogenic drugs.     

Characterization of the Human Cervical Mucous Proteome

Introduction

Cervical cancer is among the most common cancers in women worldwide. Discovery of biomarkers for the early detection of cervical cancer would improve current screening practices and reduce the burden of disease.

Objective

In this study, we report characterization of the human cervical mucous proteome as the first step towards protein biomarker discovery.

Methods

The protein composition was characterized using one- and two-dimensional gel electrophoresis, and liquid chromatography coupled with mass spectrometry. We chose to use this combination of traditional biochemical techniques and proteomics to allow a more comprehensive analysis.

Results and Conclusion

A total of 107 unique proteins were identified, with plasma proteins being most abundant. These proteins represented the major functional categories of metabolism, immune response, and cellular transport. Removal of high molecular weight abundant proteins by immunoaffinity purification did not significantly increase the number of protein spots resolved. We also analyzed phosphorylated and glycosylated proteins by fluorescent post-staining procedures. The profiling of cervical mucous proteins and their post-translational modifications can be used to further our understanding of the cervical mucous proteome.     

Quantitative proteomic analysis by iTRAQ<Superscript>®</Superscript> for the identification of candidate biomarkers in ovarian cancer serum

Background

Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ^®.

Results

Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ^® to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified.

Conclusions

This study provides the first analysis of immunodepleted serum in combination with iTRAQ^® to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

     

Proteomic Profiling of Ovarian Cancer Plasma using Immunoaffinity Depleted Plasma and Two-Dimensional PAGE

Objective

The aim of this study was to evaluate a multiple immunoaffinity protein depletion (multiple affinity removal system, MARS) pre-treatment strategy with subsequent two-dimensional polyacrylamide gel electrophoresis (2D PAGE) and peptide mass finger printing analysis for the detection of ovarian cancer-associated plasma proteins.

Materials and Methods

Following immunoaffinity depletion, total plasma protein content was reduced by 84.2?±?1.8% (mean?±?SE, n?=?32). The number of proteins detected in the control and ovarian cancer groups was 349 and 357, respectively. This represented an increase in spot detection of almost twofold when compared to 2D PAGE displays of untreated plasma (174 spots). Of the proteins displayed, post-depletion, 300 (control) and 302 (ovarian cancer, OC) were common within each group. PDQuest analysis indicated that 109 protein spots were statistically different between the two groups and, of these, 59 exhibited greater than or equal to twofold difference in spot density (Student’s t test, p?=?0.01). Thirty-nine of these proteins were successfully identified with reliable confidence.

Results and Discussion

The data obtained in this study demonstrates that immunodepletion of plasma before 2D PAGE profiling have generated identifiable plasma proteins that are differentially expressed in the high-grade ovarian cancer sample set compared to controls. This approach, therefore, may be useful in identifying candidate biomarkers for inclusion in multi-marker tests for ovarian cancer that may exhibit greater sensitivity and specificity than those currently available. It was evident, however, from the predominant identification of host response proteins that immunodepletion did not generate sufficient levels of enrichment of lower abundance tumor-specific proteins to facilitate detection.     

The additional value of TGFβ1 and IL-7 to predict the course of prostate cancer progression

Background

Given the fact that prostate cancer incidence will increase in the coming years, new prognostic biomarkers are needed with regard to the biological aggressiveness of the prostate cancer diagnosed. Since cytokines have been associated with the biology of cancer and its prognosis, we determined whether transforming growth factor beta 1 (TGFβ1), interleukin-7 (IL-7) receptor and IL-7 levels add additional prognostic information with regard to prostate cancer-specific survival.

Materials and methods

Retrospective survival analysis of forty-four prostate cancer patients, that underwent radical prostatectomy, was performed (1989–2001). Age, Gleason score and pre-treatment PSA levels were collected. IL-7, IL-7 receptor and TGFβ1 levels in prostate cancer tissue were determined by quantitative real-time RT-PCR and their additional prognostic value analyzed with regard to prostate cancer survival. Hazard ratios and their confidence intervals were estimated, and Akaike’s information criterion was calculated for model comparison.

Results

The predictive ability of a model for prostate cancer survival more than doubled when TGFβ1 and IL-7 were added to a model containing only the Gleason score and pre-treatment PSA (AIC: 18.1 and AIC: 6.5, respectively).

Conclusion

IL-7 and TGFβ1 are promising markers to indicate those at risk for poor prostate cancer survival. This additional information may be of interest with regard to the biological aggressiveness of the diagnosed prostate cancer, especially for those patients screened for prostate cancer and their considered therapy.     

Serum Proteome Pool Changes in Type 2 Diabetic Patients Treated with Anakinra

Introduction

High glucose concentrations induce the production of IL-1β in human pancreatic beta cells leading to impaired insulin secretion, decreased cell proliferation and apoptosis. Blockade of IL-1 signalling with the recombinant human IL-1 receptor antagonist anakinra reduces HbA_1c in patients with type 2 diabetes. The aims of the present study were to identify: (1) candidate surrogates for improved glycemia in type 2 diabetic patients following treatment with anakinra, (2) proteins that change serum concentration because of anakinra treatment and (3) candidate biomarkers that may predict improved glycemia in type 2 diabetic subjects treated with anakinra.

Methods

Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry was used to analyse serum from 67 type 2 diabetic patients who had received either placebo or anakinra for 13 weeks. Immunodepletion with magnetic protein G bead-coupled antibodies were used to identify three proteins and Western blotting confirmed the biomarker concentration pattern of four proteins.

Results

Twelve proteins, including transthyretin (TTR) and transferrin (Tf), were identified as candidate surrogates for improved glycemia. Six proteins, including retinol-binding protein 4 (RPB4) and a protein tentatively identified as modified apolipoprotein-A1 (apo-AI), increased expression as a consequence of anakinra treatment and four proteins were candidate biomarkers that may predict improved glycemia following anakinra treatment. Furthermore, we found increased RBP4 to be associated with improved beta cell secretory function and increased TTR, RBP4 and modified apo-AI (peak at 28,601 Da) to be associated with decreased inflammation.

Conclusions

Anakinra-induced changes in the serum proteome pool associated with a decreased cardiovascular disease risk, reduced inflammation and improved beta cell secretory function.     

Proteomic profiling of urine for the detection of colon cancer

Background

Colorectal cancer is the second most common cause of cancer related death in the developed world. To date, no blood or stool biomarkers with both high sensitivity and specificity for potentially curable early stage disease have been validated for clinical use. SELDI and MALDI profiling are being used increasingly to search for biomarkers in both blood and urine. Both techniques provide information predominantly on the low molecular weight proteome (<15 kDa). There have been several reports that colorectal cancer is associated with changes in the serum proteome that are detectable by SELDI and we hypothesised that proteomic changes would also be detectable in urine.

Results

We collected urine from 67 patients with colorectal cancer and 72 non-cancer control subjects, diluted to a constant protein concentration and generated MALDI and SELDI spectra. The intensities of 19 peaks differed significantly between cancer and non-cancer patients by both t-tests and after adjusting for confounders using multiple linear regressions. Logistic regression classifiers based on peak intensities identified colorectal cancer with up to 78% sensitivity at 87% specificity. We identified and independently quantified 3 of the discriminatory peaks using synthetic stable isotope peptides (an 1885 Da fragment of fibrinogen and hepcidin-20) or ELISA (β2-microglobulin).

Conclusion

Changes in the urine proteome may aid in the early detection of colorectal cancer.     

Comparison of Radioimmuno and Carbon Nanotube Field-Effect Transistor Assays for Measuring Insulin-Like Growth Factor-1 in a Preclinical Model of Human Breast Cancer

Background

To realize the promise of personalized medicine, diagnostic instruments used for detecting and measuring biomarkers must become smaller, faster and less expensive. Although most techniques used currently to detect biomarkers are sensitive and specific, many suffer from several disadvantages including their complexity, high cost and long turnaround time. One strategy to overcome these problems is to exploit carbon nanotube (CNT) based biosensors, which are sensitive, use inexpensive disposable components and can be easily adapted to current assay protocols. In this study we investigated the applicability of using a CNT field-effect transistor (CNT-FET) as a diagnostic instrument for measuring cancer biomarkers in serum using a mouse model of Breast Cancer Susceptibility 1-related breast cancer. Insulin like growth factor-1 (IGF-1) was chosen because it is highly relevant in breast cancer and because measuring serum IGF-1 levels by conventional methods is complicated due to specific IGF-1 serum binding proteins.

Findings

Our results show that there is good correlation between the two platforms with respect to detecting serum IGF-1. In fact, the CNT-FETs required only one antibody, gave real-time results and required approximately 100-fold less mouse serum than the radioimmunoassay.

Conclusions

Both IGF-1 radioimmuno and CNT-FET assays gave comparable results. Indeed, the CNT-FET assay was simpler and faster than the radioimmunoassay. Additionally, the low serum sample required by CNT-FETs can be especially advantageous for studies constricted by limited amount of human clinical samples and for mouse studies, since animals often need to be sacrificed to obtain enough serum for biomarker evaluation.     

Discovery and Validation of New Potential Biomarkers for Early Detection of Colon Cancer

Background

Accurate detection of characteristic proteins secreted by colon cancer tumor cells in biological fluids could serve as a biomarker for the disease. The aim of the present study was to identify and validate new serum biomarkers and demonstrate their potential usefulness for early diagnosis of colon cancer.

Methods

The study was organized in three sequential phases: 1) biomarker discovery, 2) technical and biological validation, and 3) proof of concept to test the potential clinical use of selected biomarkers. A prioritized subset of the differentially-expressed genes between tissue types (50 colon mucosa from cancer-free individuals and 100 normal-tumor pairs from colon cancer patients) was validated and further tested in a series of serum samples from 80 colon cancer cases, 23 patients with adenoma and 77 cancer-free controls.

Results

In the discovery phase, 505 unique candidate biomarkers were identified, with highly significant results and high capacity to discriminate between the different tissue types. After a subsequent prioritization, all tested genes (N = 23) were successfully validated in tissue, and one of them, COL10A1, showed relevant differences in serum protein levels between controls, patients with adenoma (p = 0.0083) and colon cancer cases (p = 3.2e-6).

Conclusion

We present a sequential process for the identification and further validation of biomarkers for early detection of colon cancer that identifies COL10A1 protein levels in serum as a potential diagnostic candidate to detect both adenoma lesions and tumor.

Impact

The use of a cheap serum test for colon cancer screening should improve its participation rates and contribute to decrease the burden of this disease.     

Glycans as cancer biomarkers

Background

Non-invasive biomarkers, such as those from serum, are ideal for disease prognosis, staging and monitoring. In the past decade, our understanding of the importance of glycosylation changes with disease has evolved.

Scope of review

We describe potential biomarkers derived from serum glycoproteins for liver, pancreatic, prostate, ovarian, breast, lung and stomach cancers. Methods for glycan analysis have progressed and newly developed high-throughput platform technologies have enabled the analysis of large cohorts of samples in an efficient manner. We also describe this evolution and trends to follow in the future.

Major conclusions

Many convincing examples of aberrant glycans associated with cancer have come about from glycosylation analyses. Most studies have been carried out to identify changes in serum glycan profiles or through the isolation and identification of glycoproteins that contain these irregular glycan structures. In a majority of cancers the fucosylation and sialylation expression are found to be significantly modified. Therefore, these aberrations in glycan structures can be utilized as targets to improve existing cancer biomarkers.

General significance

The ability to distinguish differences in the glycosylation of proteins between cancer and control patients emphasizes glycobiology as a promising field for potential biomarker identification. Furthermore, the high-throughput and reproducible nature of the chromatography platform have highlighted extensive applications in biomarker discovery and allowed integration of glycomics with other -omics fields, such as proteomics and genomics, making systems glycobiology a reality. This article is part of a Special Issue entitled Glycoproteomics.     

Serum Protein Profile at Remission Can Accurately Assess Therapeutic Outcomes and Survival for Serous Ovarian Cancer

Background

Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC) has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer.

Experimental Design

Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC) and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD), remission (RM) and recurrence (RC). The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis.

Results

Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC) have individually good area-under-the-curve (AUC) values (AUC = 0.69–0.86) and more than 10 three-marker combinations have excellent AUC values (0.91–0.93) in distinguishing active cancer samples (PD & RC) from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC). Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1) measured at remission can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p<10⁻³).

Conclusion

We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.     

Pathways affected by asbestos exposure in normal and tumour tissue of lung cancer patients

Background:

The early detection of prostate cancer has resulted in an increase in the number of patients with localized prostate cancer and has paralleled the reported reduction in prostate cancer mortality. The increased rate of detection of patients with localized prostate cancer may also increase the risk of potentially morbid therapy in a patient with indolent cancer. Defining the biomarker correlates of prostate cancer virulence will facilitate the appropriate application and development of therapy for patients with early disease.

Methods:

A 255 core prostate cancer tissue microarray (TMA) from 47 prostatectomy specimens with organ confined tumor was constructed. Prostate cancer foci of transition and peripheral zone origin were represented on the TMA. Further, replicate cores of the two Gleason grades comprising the Gleason score, representative of Gleason scores 5-9, were arrayed from each prostatectomy specimen. Standard immunohistochemical techniques were used to assess expression of nine, cell death and cell cycle regulatory proteins implicated in the pathogenesis of prostate cancer (bax, bcl-2, bcl-x_L, bin1, CD95, mdm2, p21, p53, and NFkB).

Results:

The Spearman correlation coefficient revealed a strong correlation of bax, bin1, FAS, p65 and p21 expression with Gleason grade. Spearman correlation coefficients showed that expression of, bax and bin1, bax and MDM2, Bax and p21, and bax and p65 NFkB was highly associated. Other significant associations were identified between bin1 and p21, bin1 and MDM2, bin1 and p65 NFkB and between p21 and p65 NFκB. A model for predicting the biological potential of Gleason score 7 prostate cancer using multivariable logistic regression methods was developed. The findings also indicate that the profile of specific markers for Gleason grade 3 prostate cancer correlates with the overall context of the Gleason score.

Conclusion:

These data support the view that important molecular differences exist among and between the Gleason scores. Furthermore, there is significant molecular heterogeneity among prostatectomy specimens containing Gleason grade 3 cancer. This observation may have broader implications regarding the determination of risk among patients with prostate cancer that is currently considered to be of either good prognosis or unclear prognosis, i.e. Gleason score 7 tumors.     

MicroRNAs associated with metastatic prostate cancer

Objective

Metastasis is the most common cause of death of prostate cancer patients. Identification of specific metastasis biomarkers and novel therapeutic targets is considered essential for improved prognosis and management of the disease. MicroRNAs (miRNAs) form a class of non-coding small RNA molecules considered to be key regulators of gene expression. Their dysregulation has been shown to play a role in cancer onset, progression and metastasis, and miRNAs represent a promising new class of cancer biomarkers. The objective of this study was to identify down- and up-regulated miRNAs in prostate cancer that could provide potential biomarkers and/or therapeutic targets for prostate cancer metastasis.

Methods

Next generation sequencing technology was applied to identify differentially expressed miRNAs in a transplantable metastatic versus a non-metastatic prostate cancer xenograft line, both derived from one patient''s primary cancer. The xenografts were developed via subrenal capsule grafting of cancer tissue into NOD/SCID mice, a methodology that tends to preserve properties of the original cancers (e.g., tumor heterogeneity, genetic profiles).

Results

Differentially expressed known miRNAs, isomiRs and 36 novel miRNAs were identified. A number of these miRNAs (21/104) have previously been reported to show similar down- or up-regulation in prostate cancers relative to normal prostate tissue, and some of them (e.g., miR-16, miR-34a, miR-126*, miR-145, miR-205) have been linked to prostate cancer metastasis, supporting the validity of the analytical approach.

Conclusions

The use of metastatic and non-metastatic prostate cancer subrenal capsule xenografts derived from one patient''s cancer makes it likely that the differentially expressed miRNAs identified in this study include potential biomarkers and/or therapeutic targets for human prostate cancer metastasis.     

Cancer Biomarker Discovery via Targeted Profiling of Multiclass Tumor Tissue-Derived Proteomes

Introduction

Tumor-derived proteins and naturally occurring peptides represent a rich source of potential cancer markers for multiclass cancer distinction.

Materials and Methods

In this study, proteomes/peptidomes derived from primary colon cancer, kidney cancer, liver cancer, and glioblastoma were analyzed by liquid chromatography coupled with mass spectrometry to identify multiclass cancer discriminative protein and peptide candidates. Spectral counting and peptidomic analyses found two biomarker panels, one with 12 proteins and the other with 53 peptides, both capable of multiclass cancer detection and classification.

Results and Discussion

Shed from tumor tissues through apoptosis/necrosis, cell secretion, or tumor-specific degradation of extracellular matrix proteins, these proteins/peptides are likely to enter into circulation and, therefore, have the potential to be configured into practical serological diagnostic and prognostic utilities.     

Down-regulation of phosphoglucomutase 3 mediates sulforaphane-induced cell death in LNCaP prostate cancer cells

Background

Sulforaphane (SFN) is an isothiocyanate found in cruciferous vegetables that exerts anti-oxidant, anti-inflammatory, anti-cancer and radio-sensitizing activities. Nonetheless, the mechanism responsible for SFN-induced cell death is not fully understood. In the present study, anti-cancer mechanism of SFN was elucidated in LNCaP prostate cancer cells.

Results

SFN exerted cytotoxicity and increased TUNEL positive cells in a concentration-dependent manner in LNCaP cells. Proteomics study revealed that levels of nine proteins including tubulin β-2, phosphoglucomutase-3 (PGM3), melanoma-derived leucine zipper containing extra-nuclear factor, activin A type I receptor precursor, smoothelin-A, KIA0073, hypothetical protein LOC57691 and two unnamed proteins were changed over 8 folds in SFN treated LNCaP cells compared to untreated control. We have further confirmed that SFN reduced PGM3 expression with western blotting and showed that PGM3 siRNA enhanced cytotoxicity demonstrated by cell morphology and TUNEL assays in LNCaP cells.

Conclusion

Taken together, these findings suggest that PGM3 plays a role in mediating SFN-induced cell death in LNCaP cells, and is a potential molecular therapeutic target for prostate cancer.     

Serum Autoantibodies in Chronic Prostate Inflammation in Prostate Cancer Patients

Background

Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens.

Methods

Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology.

Results

Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076).

Conclusions

We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation.