Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies

Stereotypical Chronic Lymphocytic Leukemia B-Cell Receptors Recognize Survival Promoting Antigens on Stromal Cells

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the Western world. Survival of CLL cells depends on their close contact with stromal cells in lymphatic tissues, bone marrow and blood. This microenvironmental regulation of CLL cell survival involves the stromal secretion of chemo- and cytokines as well as the expression of adhesion molecules. Since CLL survival may also be driven by antigenic stimulation through the B-cell antigen receptor (BCR), we explored the hypothesis that these processes may be linked to each other. We tested if stromal cells could serve as an antigen reservoir for CLL cells, thus promoting CLL cell survival by stimulation through the BCR. As a proof of principle, we found that two CLL BCRs with a common stereotyped heavy chain complementarity-determining region 3 (previously characterized as “subset 1”) recognize antigens highly expressed in stromal cells – vimentin and calreticulin. Both antigens are well-documented targets of autoantibodies in autoimmune disorders. We demonstrated that vimentin is displayed on the surface of viable stromal cells and that it is present and bound by the stereotyped CLL BCR in CLL-stroma co-culture supernatant. Blocking the vimentin antigen by recombinant soluble CLL BCR under CLL-stromal cell co-culture conditions reduces stroma-mediated anti-apoptotic effects by 20–45%. We therefore conclude that CLL BCR stimulation by stroma-derived antigens can contribute to the protective effect that the stroma exerts on CLL cells. This finding sheds a new light on the understanding of the pathobiology of this so far mostly incurable disease

Synthesis and biological evaluation of triazole-vanillin molecular hybrids as anti-cancer agents

Background: Triazole based drugs are widely used in cancer patients for the treatment of life-threatening invasive fungal infections. A recent report on the usefulness of 1,2, 3- triazole scaffold for the inhibition of tyrosine kinases stimulated our curiosity to design new molecules based on this moiety. Methods: A series of new heterocyclic compounds containing 1,2,3 triazole moiety tethered to substituted vanillin or isovanillin were synthesized and analysed for their anticancer activity. The cyclopen-tyl/cyclohexyl ethers derived from vanillin and isovanillin were subsequently treated with MeMgI to give the carbinols. Reaction of these carbinols with TMSN 3 and ZrCl 4 as Lewis acid gave the desired azides. Click chemistry on azides with diverse acetylenes furnished the triazoles. The new triazole hybribs were screened o against 60 human cancer cell lines at a 10μM dose for their potential anticancer activity. Results: The two active compounds (8a, 10a) showed strong inhibitory effect against different cell lines, with highest inhibition against breast cancer panel. To elucidate the underlying molecular mechanisms, these compounds were examined for their clonogenic potential and anchorage-independent growth of estrogen receptor positive (MCF7 and T47D) and estrogen receptor negative (MDA-MB-231 and MDA-MB-468) breast cancer cells and investigated for induction apoptotic pathways. Conclusion: The outcomes from the current study will add much to the existing knowledge of the breast cancer research. This provides a rewarding conclusion and opens the way for future researchers to design and synthesize the novel active compounds against breast cancer

Prostate cancer-associated autoantibodies in serum against tumor-associated antigens as potential new biomarkers

The limitations of the current prostate cancer (PCa) screening tests demands new biomarkers for early diagnosis of PCa. In this study, we aim to investigate serum autoantibody signatures as PCa specific biomarkers. PCa proteins were resolved by 2-DE and then transferred onto polyvinylidene difluoride membrane, which were subsequently incubated with either pooled serum from PCa patients or from normal controls. Mass spectrometry results have identified 18 antigens from 21 different 2-DE spots associated with PCa. Autoantibody response to antigens PRDX2, PRDX6 and ANXA11 in PCa patient's sera was confirmed using recombinant antigens. Further validation with an independent set of PCa patient's sera have shown relatively increased abundance of PRDX6 and ANXA11 antibodies in PCa patients. Formal concept analysis method was applied to assess whether the abundance of these autoantibodies could influence the classification of patients. However, sensitivity of the single antibody to discriminate prostate tumor and healthy controls varies from 70% to 80%, whereas combination of both PRDX6 and ANXA11 antibodies increased sensitivity to 90% for tumors and 100% for healthy controls. Therefore, we hereby report that the detection of these antibodies in PCa patient's serum in combination with the existing non-invasive diagnostic procedures may have significance in PCa diagnosis. BIOLOGICAL SIGNIFICANCE: The present study aimed to investigate serum autoantibody signatures as new biomarkers for early diagnosis of prostate cancer (PCa). To investigate serum autoantibodies in patients with PCa, we used proteomics approach based on two-dimensional gel electrophoresis (2-DE) and mass spectrometry. Total tissue proteins extracted from prostate were separated by 2-DE and then transferred onto polyvinylidene difluoride (PVDF) membrane, which were subsequently incubated with either pooled serum from PCa patients or from normal controls with no history for PCa. Proteomic analysis results have identified 18 antigens that showed antibody response specifically to cancer patient's serum. For validation experiments using recombinant antigens, confirmed autoantibody response to three antigens PRDX2, PRDX6 and ANXA11. Further validation using a second independent set of PCa patient's sera has shown relatively increased abundance of PRDX6 and ANXA11 antibodies specifically in PCa patients. Partition analysis of patients based on abundance of autoantibodies highlighted a combination of both PRDX6 and ANXA11 antibodies in serum with 90% sensitivity in case of tumors and 100% in case of healthy controls. Therefore, we hereby report that the detection of these antibodies in PCa patient's serum in combination with known markers may have significance in diagnosis of PCa with further validation in larger cohort of samples

Peroxiredoxins 3 and 4 are overexpressed in prostate cancer tissue and affect the proliferation of prostate cancer cells in vitro

The present study aimed to investigate the proteome profiling of surgically treated prostate cancers. Hereto, 2D-DIGE and mass spectrometry were performed for protein identification, and data validation for peroxiredoxin 3 and 4 (PRDX3 and PRDX4) was accomplished by reverse phase protein arrays (RPPA). The Formal Concept Analysis (FCA) method was applied to assess whether the TMPRSS2-ERG gene fusion could influence the degree of overexpression of PRDX3 and PRDX4 in prostate cancer. Lastly, we performed an in vitro functional characterization of both PRDX3 and PRDX4 using the classical human prostate cancer cell lines DU145 and LNCaP. Reverse phase protein arrays verified that the overexpression of both PRDX3 and PRDX4 in tumor samples is negatively correlated with the presence of the TMPRSS2-ERG gene fusion. Functional characterization of PRDX3 and PRDX4 activity in PCa cell lines suggests a role of these members of the peroxiredoxin family in the pathophysiology of this tumor entit

Combination of a proteomics approach and reengineering of meso scale network models for prediction of mode-of-action for tyrosine kinase inhibitors

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs