Biomarkers of chemotherapy resistance in breast cancer identified by proteomics: current status

Gel Electrophoresis Chip Using Joule Heat Self-Dissipation, Short Run Time, and Online Dynamic Imaging

Gel electrophoresis (GE) is one of the most general tools in biomedicine. However, it suffers from low resolution, and its mechanism has not been fully revealed yet. Herein, we presented the dispersion model of w² (t) ∝ Tt, showing the band dispersion (w) via temperature (T) and running time (t) control. Second, we designed an efficient GE chip via the time control and rapid Joule heat self-dissipation by thermal conductive plastic (TCP) and electrode buffer. Third, we conducted the simulations on TCP and polymethylmethacrylate (PMMA) chips, unveiling that (i) the temperature of TCP was lower than the PMMA one, (ii) the temperature uniformity of TCP was better than the PMMA one, and (iii) the resolution of TCP was superior to the PMMA one. Fourth, we designed both TCP and PMMA chips for experimentally validating the dispersion model, TCP chip, and simulations. Finally, we applied the TCP chip to thalassemia and model urine protein assays. The TCP chip has merits of high resolution, rapid run of 6-10 min, and low cost. This work paves the way for greatly improving electrophoretic techniques in gel, chip, and capillary via temperature and time control for biologic study, biopharma quality control, clinical diagnosis, and so on.

High HNRNPA3 expression is associated with lymph node metastasis and poor prognosis in patients treated with radical cystectomy

OBJECTIVE

We sought to identify heterogeneous nuclear ribonucleoprotein A3 (HNRNPA3) expression in bladder cancer and its relationship to clinicopathological findings and prognosis.

METHODS

Immunohistochemical staining for HNRNPA3 was performed on 122 archived radical cystectomy specimens, with immunoreactivity being stratified on a 0 to 3 scale. The percentage of HNRNPA3 expressing tumor cells was calculated and multiplied by the staining score over an average of 5 areas to obtain a semiquantitative H-score (maximum value: 300). HNRNPA3 expression was categorized as high (≥80) or low (<80).

RESULTS

The patients' median age was 70 years, and the median follow-up period was 39.4 months. High HNRNPA3 expression was significantly associated with lymph node metastasis (P= 0.014) and S100A8, S100A9 and uroplakin III expression (P= 0.028, 0.002, and 0.047, respectively). Log-rank tests indicated that high HNRNPA3 expression was significantly associated with disease progression and cancer-specific death (P= 0.013 and 0.006, respectively). In the Cox proportional hazards regression analysis, only lymph node metastasis was associated with disease progression and cancer-specific survival.

CONCLUSION

HNRNPA3 may be a new biomarker to predict biologically aggressive cancers and determine the appropriate treatment modality in patients after radical cystectomy.

Proteomic patterns associated with response to breast cancer neoadjuvant treatment

Tumor relapse as a consequence of chemotherapy resistance is a major clinical challenge in advanced stage breast tumors. To identify processes associated with poor clinical outcome, we took a mass spectrometry-based proteomic approach and analyzed a breast cancer cohort of 113 formalin-fixed paraffin-embedded samples. Proteomic profiling of matched tumors before and after chemotherapy, and tumor-adjacent normal tissue, all from the same patients, allowed us to define eight patterns of protein level changes, two of which correlate to better chemotherapy response. Supervised analysis identified two proteins of proline biosynthesis pathway, PYCR1 and ALDH18A1, that were significantly associated with resistance to treatment based on pattern dominance. Weighted gene correlation network analysis of post-treatment samples revealed that these proteins are associated with tumor relapse and affect patient survival. Functional analysis showed that knockdown of PYCR1 reduced invasion and migration capabilities of breast cancer cell lines. PYCR1 knockout significantly reduced tumor burden and increased drug sensitivity of orthotopically injected ER-positive tumor in vivo, thus emphasizing the role of PYCR1 in resistance to chemotherapy.

Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review

Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.

Proteomic approach toward determining the molecular background of pazopanib resistance in synovial sarcoma

Pazopanib, a multitarget tyrosine kinase (TK) inhibitor, has been approved for treatment of soft tissue sarcoma. Elucidation of the molecular background of pazopanib resistance should lead to improved clinical outcomes in sarcomas; accordingly, we investigated this in synovial sarcoma using a proteomic approach. Pazopanib sensitivity was examined in four synovial sarcoma cell lines: SYO-1, HS-SYII, 1273/99, and YaFuSS. The 1273/99 cell line showed significantly higher IC₅₀ values than the others for pazopanib. Expression levels of 90 TKs in the cell lines were examined by western blotting. Among these, the levels of PDGFRB, DDR1, AXL, MET, and PYK2 were higher, and those of FGFR1 and VEGFR3 were lower in the 1273/99 cell line than the other cell lines. Gene silencing analysis of the TKs upregulated in 1273/99 cells showed differing effects on cell growth: PDGFRB, MET, and PYK2 knockdown induced cell growth inhibition, whereas DDR1 and AXL knockdown did not influence cell growth. Using the PamChip peptide microarray, we found that 18 peptide substrates were highly phosphorylated in the 1273/99 cell line compared with other cell lines. Using the PhosphoNet database, we found that kinases FGFR3, RET, VEGFR1, EPHA2, EPHA4, TRKA, and SRC phosphorylated these 18 peptide substrates. Moreover, the results for overexpressed and aberrantly activated TKs in pazopanib-resistant cells showed no overlap. Taken together, our study indicates that identification of comprehensive TK profiles represents an essential approach to determining the molecular background of pazopanib resistance in synovial sarcoma.

Complementary PTM Profiling of Drug Response in Human Gastric Carcinoma by Immunoaffinity and IMAC Methods with Total Proteome Analysis

Gaining insight into normal cellular signaling and disease biology is a critical goal of proteomic analyses. The ability to perform these studies successfully to extract the maximum value and discovery of biologically relevant candidate biomarkers is therefore of primary importance. Many successful studies in the past have focused on total proteome analysis (changes at the protein level) combined with phosphorylation analysis by metal affinity enrichment (changes at the PTM level). Here, we use the gastric carcinoma cell line MKN-45 treated with the c-Met inhibitor SU11274 and PKC inhibitor staurosporine to investigate the most efficient and most comprehensive strategies for both total protein and PTM analysis. Under the conditions used, total protein analysis yielded few changes in response to either compound, while analysis of phosphorylation identified thousands of sites that changed differentially between the two treatments. Both metal affinity and antibody-based enrichments were used to assess phosphopeptide changes, and the data generated by the two methods was largely complementary (non-overlapping). Label-free quantitation of peptide peak abundances was used to accurately determine fold-changes between control and treated samples. Protein interaction network analysis allowed the data to be placed in a biologically relevant context, and follow-up validation of selected findings confirmed the accuracy of the proteomic data. Together, this study provides a framework for start-to-finish proteomic analysis of any experimental system under investigation to maximize the value of the proteomic study and yield the best chance for uncovering actionable target candidates.

Advances in the proteomic discovery of novel therapeutic targets in cancer

Proteomic approaches are continuing to make headways in cancer research by helping to elucidate complex signaling networks that underlie tumorigenesis and disease progression. This review describes recent advances made in the proteomic discovery of drug targets for therapeutic development. A variety of technical and methodological advances are overviewed with a critical assessment of challenges and potentials. A number of potential drug targets, such as baculoviral inhibitor of apoptosis protein repeat-containing protein 6, macrophage inhibitory cytokine 1, phosphoglycerate mutase 1, prohibitin 1, fascin, and pyruvate kinase isozyme 2 were identified in the proteomic analysis of drug-resistant cancer cells, drug action, and differential disease state tissues. Future directions for proteomics-based target identification and validation to be more translation efficient are also discussed.

Different strategies to overcome multidrug resistance in cancer

The risk of acquisition of resistance to chemotherapy remains a major hurdle in the management of various types of cancer patients. Several cellular and noncellular mechanisms are involved in developing both intrinsic and acquired resistance in cancer cells toward chemotherapy. This review covers the various multidrug resistance (MDR) mechanisms observed in cancer cells as well as the various strategies developed to overcome these MDR mechanisms. Extensive studies have been conducted during the last several decades to enhance the efficacy of chemotherapy by suppressing or evading these MDR mechanisms including the use of new anticancer drugs that could escape from the efflux reaction, MDR modulators or chemosensitizers, multifunctional nanocarriers, and RNA interference (RNAi) therapy.

Functional classification of cellular proteome profiles support the identification of drug resistance signatures in melanoma cells

Drug resistance is a major obstacle in melanoma treatment. Recognition of specific resistance patterns, the understanding of the patho-physiology of drug resistance, and identification of remaining options for individual melanoma treatment would greatly improve therapeutic success. We performed mass spectrometry-based proteome profiling of A375 melanoma cells and HeLa cells characterized as sensitive to cisplatin in comparison to cisplatin resistant M24met and TMFI melanoma cells. Cells were fractionated into cytoplasm, nuclei and secretome and the proteome profiles classified according to Gene Ontology. The cisplatin resistant cells displayed increased expression of lysosomal as well as Ca²⁺ ion binding and cell adherence proteins. These findings were confirmed using Lysotracker Red staining and cell adhesion assays with a panel of extracellular matrix proteins. To discriminate specific survival proteins, we selected constitutively expressed proteins of resistant M24met cells which were found expressed upon challenging the sensitive A375 cells. Using the CPL/MUW proteome database, the selected lysosomal, cell adherence and survival proteins apparently specifying resistant cells were narrowed down to 47 proteins representing a potential resistance signature. These were tested against our proteomics database comprising more than 200 different cell types/cell states for its predictive power. We provide evidence that this signature enables the automated assignment of resistance features as readout from proteome profiles of any human cell type. Proteome profiling and bioinformatic processing may thus support the understanding of drug resistance mechanism, eventually guiding patient tailored therapy.

Plasma and tissue proteomic prognostic factors of response in primary breast cancer patients receiving neoadjuvant chemotherapy

A pathological complete response (pCR) after neoadjuvant chemotherapy is observed in approximately 20% of breast cancer patients. A proteomic analysis was performed on plasma and tumor tissue before treatment to evaluate its potential impact on the prediction of response. One hundred and forty-nine breast cancer patients eligible for neoadjuvant chemotherapy were included in the study between February 2004 and January 2009 at three centers. The proteomic analysis was performed using SELDI Technology (ProteinChip CM10 pH4, IMAC-Cu and H50). Three acquisition protocols were used according to the mass range. Plasma and tumor proteomic signatures were generated using generalized ROC criteria and cross-validation. Twenty-eight (18.8%) patients out of 149 experienced a pCR according to Sataloff criteria. In the cytosol analysis, respectively 4, 2 and 8 proteins had significantly different levels of expression in the responders and non-responders using IMAC-Cu, H50 and CM10 pH4. Among the 8 proteins of interest on CM10 pH4, 2 (C1 and C7) were selected and were validated in 95.0 and 85.6% of the models. In the plasma analysis, respectively 12, 6 and 2 proteins had different levels of expression using the same proteinchips. Among the 12 plasma proteins of interest on IMAC-Cu, 2 (P1 and P7) were selected and were validated in 94.8 and 97.6% of the models. A combined proteomic signature was generated, which remained statistically significant when adjusted for hormone receptor status and Ki-67. Our results show that proteomic analysis can differentiate complete pathological responders in breast cancer patients after neoadjuvant chemotherapy.

Pilot and feasibility study: comparative proteomic analysis by 2-DE MALDI TOF/TOF MS reveals 14-3-3 proteins as putative biomarkers of response to neoadjuvant chemotherapy in ER-positive breast cancer

Neoadjuvant chemotherapy is used to treat oestrogen receptor-positive breast cancer however chemo-resistance is a major obstacle in this molecular subtype. The ability to predict tumour response would allow chemotherapy administration to be directed towards patients who would most benefit, thus maximising treatment efficacy. We aimed to identify protein biomarkers associated with response to neoadjuvant chemotherapy, in a pilot study using comparative 2-DE MALDI TOF/TOF MS proteomic analysis of breast tumour samples. A total of 3 comparative proteomic experiments were performed, comparing protein expression between chemotherapy-sensitive and chemotherapy-resistant oestrogen receptor-positive invasive ductal carcinoma tissue samples. This identified a list of 132 unique proteins that were significantly differentially expressed (≥ 2 fold) in chemotherapy resistant samples, 57 of which were identified in at least two experiments. Ingenuity® Pathway Analysis was used to map the 57 DEPs onto canonical signalling pathways. We implicate several isoforms of 14-3-3 family proteins (theta/tau, gamma, epsilon, beta/alpha and zeta/delta), which have previously been associated with chemotherapy resistance in breast cancer. Extensive clinical validation is now required to fully assess the role of these proteins as putative markers of chemotherapy response in luminal breast cancer subtypes.

Proteomic studies in breast cancer (Review)

Breast cancer is one of the most common types of invasive cancer in females worldwide. Despite major advances in early cancer detection and emerging therapeutic strategies, further improvement has to be achieved for precise diagnosis to reduce the chance of metastasis and relapses. Recent proteomic technologies have offered a promising opportunity for the identification of new breast cancer biomarkers. Matrix-assisted laser desorption/ionization, time-of-flight mass spectrometry (MALDI-TOF MS) and the derived surface-enhanced laser desorption/ionization mass spectrometry (SELDI-TOF MS) enable the development of high-throughput proteome analysis based on comprehensive reliable biomarkers. In this review, we examined proteomic technologies and their applications, and provided focus on the proteomics-based profiling analyses of tumor tissues/cells in order to identify and confirm novel biomarkers of breast cancer.

PTMScan direct: identification and quantification of peptides from critical signaling proteins by immunoaffinity enrichment coupled with LC-MS/MS

Proteomic studies of post-translational modifications by metal affinity or antibody-based methods often employ data-dependent analysis, providing rich data sets that consist of randomly sampled identified peptides because of the dynamic response of the mass spectrometer. This can complicate the primary goal of programs for drug development, mutational analysis, and kinase profiling studies, which is to monitor how multiple nodes of known, critical signaling pathways are affected by a variety of treatment conditions. Cell Signaling Technology has developed an immunoaffinity-based LC-MS/MS method called PTMScan Direct for multiplexed analysis of these important signaling proteins. PTMScan Direct enables the identification and quantification of hundreds of peptides derived from specific proteins in signaling pathways or specific protein types. Cell lines, tissues, or xenografts can be used as starting material. PTMScan Direct is compatible with both SILAC and label-free quantification. Current PTMScan Direct reagents target key nodes of many signaling pathways (PTMScan Direct: Multipathway), serine/threonine kinases, tyrosine kinases, and the Akt/PI3K pathway. Validation of each reagent includes score filtering of MS/MS assignments, filtering by identification of peptides derived from expected targets, identification of peptides homologous to expected targets, minimum signal intensity of peptide ions, and dependence upon the presence of the reagent itself compared with a negative control. The Multipathway reagent was used to study sensitivity of human cancer cell lines to receptor tyrosine kinase inhibitors and showed consistent results with previously published studies. The Ser/Thr kinase reagent was used to compare relative levels of kinase-derived phosphopeptides in mouse liver, brain, and embryo, showing tissue-specific activity of many kinases including Akt and PKC family members. PTMScan Direct will be a powerful quantitative method for elucidation of changes in signaling in a wide array of experimental systems, combining the specificity of traditional biochemical methods with the high number of data points and dynamic range of proteomic methods.

Adseverin: a novel cisplatin-resistant marker in the human bladder cancer cell line HT1376 identified by quantitative proteomic analysis

Cisplatin is currently the most effective antitumor agent available against bladder cancer. However, a majority of patients eventually relapse with cisplatin-resistant disease. Chemoresistance thus remains a major obstacle in bladder cancer therapy. To clarify the molecular mechanisms underlying cisplatin resistance in bladder cancer, we established a cisplatin-resistant subline from the human bladder cancer cell line HT1376 (HT1376-CisR), and conducted large-scale analyses of the expressed proteins using two-dimensional (2D) gel electrophoresis coupled with mass spectrometry (MS). Comparative proteomic analysis of HT1376 and HT1376-CisR cells revealed 36 differentially expressed proteins, wherein 21 proteins were upregulated and 15 were downregulated in HT1376-CisR cells. Among the differentially regulated proteins, adseverin (SCIN), a calcium-dependent actin-binding protein, was overexpressed (4-fold upregulation) in HT1376-CisR, with the increase being more prominent in the mitochondrial fraction than in the cytosol fraction. SCIN mRNA knockdown significantly reduced cell proliferation with mitochondria-mediated apoptosis in HT1376-CisR cells. Immunoprecipitation analysis revealed voltage-dependent anion channels (VDACs) to be bound to SCIN in the mitochondrial fraction. Our results suggest that the VDAC-SCIN interaction may inhibit mitochondria-mediated apoptosis in cisplatin-resistant cells. Targeting the VDAC-SCIN interaction may offer a new therapeutic strategy for cisplatin-resistant bladder cancer.

Proteomic identification of predictive biomarkers of resistance to neoadjuvant chemotherapy in luminal breast cancer: a possible role for 14-3-3 theta/tau and tBID?

INTRODUCTION

Chemotherapy resistance is a major obstacle in effective neoadjuvant treatment for estrogen receptor-positive breast cancer. The ability to predict tumour response would allow chemotherapy administration to be directed towards only those patients who would benefit, thus maximising treatment efficiency. We aimed to identify putative protein biomarkers associated with chemotherapy resistance, using fresh tumour samples with antibody microarray analysis and then to perform pilot clinical validation experiments.

MATERIALS AND METHODS

Chemotherapy resistant and chemotherapy sensitive tumour samples were collected from breast cancer patients who had received anthracycline based neoadjuvant therapy consisting of epirubicin with cyclophosphamide followed by docetaxel. A total of 5 comparative proteomics experiments were performed using invasive ductal carcinomas which demonstrated estrogen receptor positivity (luminal subtype). Protein expression was compared between chemotherapy resistant and chemotherapy sensitive tumour samples using the Panorama XPRESS Profiler725 antibody microarray containing 725 antibodies from a wide variety of cell signalling and apoptosis pathways. A pilot series of archival samples was used for clinical validation of putative predictive biomarkers.

RESULTS

AbMA analysis revealed 38 differentially expressed proteins which demonstrated at least 1.8 fold difference in expression in chemotherapy resistant tumours and 7 of these proteins (Zyxin, 14-3-3 theta/tau, tBID, Pinin, Bcl-xL, RIP and MyD88) were found in at least 2 experiments. Clinical validation in a pilot series of archival samples revealed 14-3-3 theta/tau and tBID to be significantly associated with chemotherapy resistance.

CONCLUSIONS

For the first time, antibody microarrays have been used to identify proteins associated with chemotherapy resistance using fresh breast cancer tissue. We propose a potential role for 14-3-3 theta/tau and tBID as predictive biomarkers of neoadjuvant chemotherapy resistance in breast cancer. Further validation in a larger sample series is now required.

Discovery of IL-18 as a novel secreted protein contributing to doxorubicin resistance by comparative secretome analysis of MCF-7 and MCF-7/Dox

Background

Resistance to chemotherapy is the major cause of failure in breast cancer treatment. Recent studies suggest that secreted proteins may play important roles in chemoresistance. We sought to systematically characterize secreted proteins associated with drug resistance, which may represent potential serum biomarkers or novel drug targets.

Methodology/Principal Findings

In the present work, we adopted the proteomic strategy of one-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry to compare the secretome of MCF-7 and doxorubicin-resistant MCF-7/Dox. A total of 2,084 proteins were identified with at least two unique peptides in the conditioned media of two cell lines. By quantification with label-free spectral counting, 89 differentially expressed secreted proteins (DESPs) between the two cell lines were found. Among them, 57 DESPs were first found to be related to doxorubicin resistance in this work, including 24 extracellular matrix related proteins, 2 cytokines and 31 unclassified proteins. We focused on 13 novel DESPs with confirmed roles in tumor metastasis. Among them, the elevated expression of IL-18 in doxorubicin-resistant cell lines and breast tumor tissues was validated and its role in doxorubicin resistance was further confirmed by cell viability experiments in the presence or absence of this protein.

Conclusions/Significance

Comparative analysis of the secretome of MCF-7 and MCF-7/Dox identified novel secreted proteins related to chemotherapy resistance. IL-18 was further validated to contribute to doxorubicin resistance, in addition to its confirmed role in breast cancer metastasis. Due to its dual roles in both drug resistance and tumor metastasis, IL-18 may represent a useful drug target for breast cancer therapy.

Differential proteomics in the search for biomarkers of radiotherapy resistance

The individualization of radiotherapy treatment would be beneficial for cancer patients; however, there are no predictive biomarkers of radiotherapy resistance in routine clinical use. This article describes the body of work in this field where comparative proteomics methods have been used for the discovery of putative biomarkers associated with radiotherapy resistance. A large number of differentially expressed proteins have been reported, mostly from the study of novel radiotherapy-resistant cell lines. Here, we have assessed these putative biomarkers through the discovery, confirmation and validation phases of the biomarker pipeline, and inform the reader on the current status of proteomics-based findings. Suggested avenues for future work are discussed.

Antibody purification-independent microarrays (PIM) by direct bacteria spotting on TiO2-treated slides

The preparation of effective conventional antibody microarrays depends on the availability of high quality material and on the correct accessibility of the antibody active moieties following their immobilization on the support slide. We show that spotting bacteria that expose recombinant antibodies on their external surface directly on nanostructured-TiO(2) or epoxy slides (purification-independent microarray - PIM) is a simple and reliable alternative for preparing sensitive and specific microarrays for antigen detection. Variable domains of single heavy-chain antibodies (VHHs) against fibroblast growth factor receptor 1 (FGFR1) were used to capture the antigen diluted in serum or BSA solution. The FGFR1 detection was performed by either direct antigen labeling or using a sandwich system in which FGFR1 was first bound to its antibody and successively identified using a labeled FGF. In both cases the signal distribution within each spot was uniform and spot morphology regular. The signal-to-noise ratio of the signal was extremely elevated and the specificity of the system was proved statistically. The LOD of the system for the antigen was calculated being 0.4ng/mL and the dynamic range between 0.4ng/mL and 10μg/mL. The microarrays prepared with bacteria exposing antibodies remain fully functional for at least 31 days after spotting. We finally demonstrated that the method is suitable for other antigen-antibody pairs and expect that it could be easily adapted to further applications such as the display of scFv and IgG antibodies or the autoantibody detection using protein PIMs.

The application of SELDI-TOF-MS in clinical diagnosis of cancers

Cancer diagnosis is important, and the early diagnosis of cancers could predict a more successful treatment. The proteomic studies emerged to be useful in combined analyses of samples from patients and provide more accurate diagnosis when compared to the single-factor-based diagnosis. In recent years, cancer detection with surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) is flourishing and brought significant progress in this area. This paper summarizes some recent results with this technique for cancer diagnosis.

The challenges of integrating molecular imaging into the optimization of cancer therapy

We review novel, in vivo and tissue-based imaging technologies that monitor and optimize cancer therapeutics. Recent advances in cancer treatment centre around the development of targeted therapies and personalisation of treatment regimes to individual tumour characteristics. However, clinical outcomes have not improved as expected. Further development of the use of molecular imaging to predict or assess treatment response must address spatial heterogeneity of cancer within the body. A combination of different imaging modalities should be used to relate the effect of the drug to dosing regimen or effective drug concentration at the local site of action. Molecular imaging provides a functional and dynamic read-out of cancer therapeutics, from nanometre to whole body scale. At the whole body scale, an increase in the sensitivity and specificity of the imaging probe is required to localise (micro)metastatic foci and/or residual disease that are currently below the limit of detection. The use of image-guided endoscopic biopsy can produce tumour cells or tissues for nanoscopic analysis in a relatively patient-compliant manner, thereby linking clinical imaging to a more precise assessment of molecular mechanisms. This multimodality imaging approach (in combination with genetics/genomic information) could be used to bridge the gap between our knowledge of mechanisms underlying the processes of metastasis, tumour dormancy and routine clinical practice. Treatment regimes could therefore be individually tailored both at diagnosis and throughout treatment, through monitoring of drug pharmacodynamics providing an early read-out of response or resistance.

2D-DIGE proteomic analysis of changes in estrogen/progesterone-induced rat breast hyperplasia upon treatment with the Mongolian remedy RuXian-I

RuXian-I has traditionally been used as a remedy for breast hyperplasia in the Inner Mongolia Autonomous Region of China. As a first step toward the investigation of biomarkers associated with RuXian-I treatment, a proteome-wide analysis of rat breast tissue was conducted. First, rat breast hyperplasia was induced by injection of estradiol and progesterone. After treatment with RuXian-I, there is a marked decrease in the hyperplasia, as can be shown by decreases in the nipple diameter and the pathological changes in breast. Subsequently, we used an approach that integrates size-based 2D-DIGE, MALDI-TOF/TOF-MS, and bioinformatics to analyze data from the control group, the model group and the RuXian-I treatment group. Using this approach, seventeen affected proteins were identified. Among these, 15 (including annexin A1, annexin A2, superoxide dismutase [Mn], peroxiredoxin-1, translationally-controlled tumor protein and α B-crystallin) were significantly up-regulated in the model group and down-regulated upon treatment with RuXian-I, and two (Tpil protein and myosin-4) have the opposite change trend. The expression of annexin A1 was confirmed using immunohistochemistry. The expression of superoxide dismutase (SOD) activity was confirmed biochemically. These results indicated that RuXian-I treats rat breast hyperplasia through regulation of cell cycle, immune system, metabolic, signal transduction, etc. The differential expressions of these proteins (annexin A1, superoxide dismutase [Mn], alpha B-crystallins and translationally controlled tumor protein, among others) were associated with occurrence and metastasis of breast cancer. These findings might provide not only far-reaching valuable insights into the mechanism of RuXian-I action, but also leads for prognosis and diagnosis of breast hyperplasia and breast cancer.

Current status of methods to assess cancer drug resistance

Drug resistance is the main cause of the failure of chemotherapy of malignant tumors, resistance being either preexisting (intrinsic resistance) or induced by the drugs (acquired resistance). At present, resistance is usually diagnosed during treatment after a long period of drug administration.In the present paper, methods for a rapid assessment of drug resistance are described. Three main classes of test procedures can be found in the literature, i.e. fresh tumor cell culture tests, cancer biomarker tests and positron emission tomography (PET) tests. The methods are based on the evaluation of molecular processes, i.e. metabolic activities of cancer cells. Drug resistance can be diagnosed before treatment in-vitro with fresh tumor cell culture tests, and after a short time of treatment in-vivo with PET tests. Cancer biomarker tests, for which great potential has been predicted, are largely still in the development stage. Individual resistance surveillance with tests delivering rapid results signifies progress in cancer therapy management, by providing the possibility to avoid drug therapies that are ineffective and only harmful.