Analysis of albumin-associated peptides and proteins from ovarian cancer patients

BACKGROUND: Albumin binds low-molecular-weight molecules, including proteins and peptides, which then acquire its longer half-life, thereby protecting the bound species from kidney clearance. We developed an experimental method to isolate albumin in its native state and to then identify [mass spectrometry (MS) sequencing] the corresponding bound low-molecular-weight molecules. We used this method to analyze pooled sera from a human disease study set (high-risk persons without cancer, n = 40; stage I ovarian cancer, n = 30; stage III ovarian cancer, n = 40) to demonstrate the feasibility of this approach as a discovery method. METHODS: Albumin was isolated by solid-phase affinity capture under native binding and washing conditions. Captured albumin-associated proteins and peptides were separated by gel electrophoresis and subjected to iterative MS sequencing by microcapillary reversed-phase tandem MS. Selected albumin-bound protein fragments were confirmed in human sera by Western blotting and immunocompetition. RESULTS: In total, 1208 individual protein sequences were predicted from all 3 pools. The predicted sequences were largely fragments derived from proteins with diverse biological functions. More than one third of these fragments were identified by multiple peptide sequences, and more than one half of the identified species were in vivo cleavage products of parent proteins. An estimated 700 serum peptides or proteins were predicted that had not been reported in previous serum databases. Several proteolytic fragments of larger molecules that may be cancer-related were confirmed immunologically in blood by Western blotting and peptide immunocompetition. BRCA2, a 390-kDa low-abundance nuclear protein linked to cancer susceptibility, was represented in sera as a series of specific fragments bound to albumin. CONCLUSION: Carrier-protein harvesting provides a rich source of candidate peptides and proteins with potential diverse tissue and cellular origins that may reflect important disease-related information.     

Adipocyte-derived collagen VI affects early mammary tumor progression in vivo, demonstrating a critical interaction in the tumor/stroma microenvironment

The interactions of transformed cells with the surrounding stromal cells are of importance for tumor progression and metastasis. The relevance of adipocyte-derived factors to breast cancer cell survival and growth is well established. However, it remains unknown which specific adipocyte-derived factors are most critical in this process. Collagen VI is abundantly expressed in adipocytes. Collagen(-/-) mice in the background of the mouse mammary tumor virus/polyoma virus middle T oncogene (MMTV-PyMT) mammary cancer model demonstrate dramatically reduced rates of early hyperplasia and primary tumor growth. Collagen VI promotes its growth-stimulatory and pro-survival effects in part by signaling through the NG2/chondroitin sulfate proteoglycan receptor expressed on the surface of malignant ductal epithelial cells to sequentially activate Akt and beta-catenin and stabilize cyclin D1. Levels of the carboxyterminal domain of collagen VIalpha3, a proteolytic product of the full-length molecule, are dramatically upregulated in murine and human breast cancer lesions. The same fragment exerts potent growth-stimulatory effects on MCF-7 cells in vitro. Therefore, adipocytes play a vital role in defining the ECM environment for normal and tumor-derived ductal epithelial cells and contribute significantly to tumor growth at early stages through secretion and processing of collagen VI.     

Use of proteomic analysis to monitor responses to biological therapies

Proteomics has the potential to revolutionise diagnosis and disease management. Serum protein pattern profiling by surface-enhanced laser desorption/ionisation time of flight (SELDI-TOF) mass spectrometry is emerging as a novel approach to discover protein patterns capable of distinguishing disease and disease-free states with high sensitivity and specificity. This method has shown great promise for early diagnosis of ovarian cancer and is being applied to a range of pathological states. Protein microarray technology is being evaluated as a new means to track biological responses to therapy. Through the measurement of key protein phosphorylation sites at different stages of disease progression or before and after treatment, protein signal pathways can be mapped and thus become the starting point for individualised therapy. Laser capture microdissection (LCM) coupled with immunostaining of protein microarrays allows isolation of pure cell populations and relative quantitation of phosphorylated and non-phosphorylated forms of the cell's key signalling proteins. This technology is currently in use at the National Institutes of Health in Phase II clinical trials of metastatic breast and ovarian cancer. Cell survival and apoptotic protein pathways are monitored as biological markers of disease progression in these clinical trials. Proteomic technologies, such as serum protein pattern profiling, combined with protein microarray technologies, constitute a new paradigm for detecting disease and monitoring disease response to therapy. Ultimately, proteomics and genomics will become integrated into cancer patient management through the design and tracking of individualised therapy.     

Phosphoproteomic analysis of signaling pathways in head and neck squamous cell carcinoma patient samples

Molecular targeted therapy represents a promising new strategy for treating cancers because many small-molecule inhibitors targeting protein kinases have recently become available. Reverse-phase protein microarrays (RPPAs) are a useful platform for identifying dysregulated signaling pathways in tumors and can provide insight into patient-specific differences. In the present study, RPPAs were used to examine 60 protein end points (predominantly phosphoproteins) in matched tumor and nonmalignant biopsy specimens from 23 patients with head and neck squamous cell carcinoma to characterize the cancer phosphoproteome. RPPA identified 18 of 60 analytes globally elevated in tumors versus healthy tissue and 17 of 60 analytes that were decreased. The most significantly elevated analytes in tumor were checkpoint kinase (Chk) 1 serine 345 (S345), Chk 2 S33/35, eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) S65, protein kinase C (PKC) ζ/ι threonine 410/412 (T410/T412), LKB1 S334, inhibitor of kappaB alpha (IκB-α) S32, eukaryotic translation initiation factor 4E (eIF4E) S209, Smad2 S465/67, insulin receptor substrate 1 (IRS-1) S612, mitogen-activated ERK kinase 1/2 (MEK1/2) S217/221, and total PKC ι. To our knowledge, this is the first report of elevated PKC ι in head and neck squamous cell carcinoma that may have significance because PKC ι is an oncogene in several other tumor types, including lung cancer. The feasibility of using RPPA for developing theranostic tests to guide personalized therapy is discussed in the context of these data.     

Combination of SELDI-TOF-MS and data mining provides early-stage response prediction for rectal tumors undergoing multimodal neoadjuvant therapy

OBJECTIVE: We investigated whether proteomic analysis of the low molecular weight region of the serum proteome could predict histologic response of locally advanced rectal cancer to neoadjuvant radiochemotherapy (RCT). SUMMARY BACKGROUND DATA: Proteomic analysis of serum is emerging as a powerful new modality in cancer, in terms of both screening and monitoring response to treatment. No study has yet assessed its ability to predict and monitor the response of rectal cancer to RCT. METHODS: Sequential serum samples from 20 patients undergoing RCT were prospectively collected. Time points sampled were as follows: pretreatment, 24/48 hours, 1 week, 2 weeks, 3 weeks, 5 weeks (last day of RCT), and presurgery. Response to treatment was measured using a 5-point tumor regression grade (TRG) based on the degree of residual tumor to fibrosis. All serum samples were analyzed in duplicate using surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). Support vector machine (SVM) analysis of spectra was used to generate a predictive algorithm for each time point based on proteins that were maximally differentially expressed between good and poor responders. This algorithm was then tested using leave-one-out cross validation. RESULTS: In total, 230 spectra were generated representing all available time points from 9 good responders (TRG 1+2) and 11 poor responders (TRG 3-5). SVM analysis indicated that changes within the serum proteome at the 24/48 hours time point into treatment provided optimal classification accuracy. In more detail, a cohort of 14 protein peaks were identified that collectively differentiated between good and poor responders, with 87.5% sensitivity and 80% specificity. CONCLUSIONS: Serum proteomic analysis may represent an early response predictor in multimodal treatment regimens of rectal cancer. These data suggest that this novel, minimally invasive modality may be a useful adjunct in the multimodal management of rectal cancer, and in the design of future clinical trials.     

Cancer biomarkers: closer to delivering on their promise

Taguchi et?al. describe, in this issue of Cancer Cell, a quantitative comparative biomarker discovery approach that integrates animal lung cancer models with validation in well-controlled human clinical study sets. This approach overcomes many of the major barriers that have held back the field of cancer biomarkers in the past.     

Phosphoprotein pathway mapping: Akt/mammalian target of rapamycin activation is negatively associated with childhood rhabdomyosarcoma survival

Mapping of protein signaling networks within tumors can identify new targets for therapy and provide a means to stratify patients for individualized therapy. Despite advances in combination chemotherapy, the overall survival for childhood rhabdomyosarcoma remains approximately 60%. A critical goal is to identify functionally important protein signaling defects associated with treatment failure for the 40% nonresponder cohort. Here, we show, by phosphoproteomic network analysis of microdissected tumor cells, that interlinked components of the Akt/mammalian target of rapamycin (mTOR) pathway exhibited increased levels of phosphorylation for tumors of patients with short-term survival. Specimens (n = 59) were obtained from the Children's Oncology Group Intergroup Rhabdomyosarcoma Study (IRS) IV, D9502 and D9803, with 12-year follow-up. High phosphorylation levels were associated with poor overall and poor disease-free survival: Akt Ser(473) (overall survival P < 0.001, recurrence-free survival P < 0.0009), 4EBP1 Thr(37/46) (overall survival P < 0.0110, recurrence-free survival P < 0.0106), eIF4G Ser(1108) (overall survival P < 0.0017, recurrence-free survival P < 0.0072), and p70S6 Thr(389) (overall survival P < 0.0085, recurrence-free survival P < 0.0296). Moreover, the findings support an altered interrelationship between the insulin receptor substrate (IRS-1) and Akt/mTOR pathway proteins (P < 0.0027) for tumors from patients with poor survival. The functional significance of this pathway was tested using CCI-779 in a mouse xenograft model. CCI-779 suppressed phosphorylation of mTOR downstream proteins and greatly reduced the growth of two different rhabdomyosarcoma (RD embryonal P = 0.00008; Rh30 alveolar P = 0.0002) cell lines compared with controls. These results suggest that phosphoprotein mapping of the Akt/mTOR pathway should be studied further as a means to select patients to receive mTOR/IRS pathway inhibitors before administration of chemotherapy.     

巨噬细胞迁移抑制因子通过CC趋化因子配体2诱导巨噬细胞聚集

巨噬细胞迁移抑制因子最初是由于能抑制体外巨噬细胞随机迁移而被发现,现在它作为一种重要的调节因子参与一系列炎症性疾病过程.我们最近发现,巨噬细胞迁移抑制因子的缺失使一些由炎症介质诱发的白细胞-内皮细胞相互作用减弱,提示巨噬细胞迁移抑制因子在炎症反应中起作用的机制之一是促进白细胞聚集.……