Differential protein expression and basal lamina remodeling in human heart failure.

PURPOSE: A goal of this study was to identify and investigate previously unrecognized components of the remodeling process in the progression to heart failure by comparing protein expression in ischemic failing (F) and nonfailing (NF) human hearts. EXPERIMENTAL DESIGN: Protein expression differences were investigated using multidimensional protein identification and validated by Western analysis. This approach detected basal lamina (BL) remodeling, and further studies analyzed samples for evidence of structural BL remodeling. A rat model of pressure overload (PO) was studied to determine whether nonischemic stressors also produce BL remodeling and impact cellular adhesion. RESULTS: Differential protein expression of collagen IV, laminin α2, and nidogen-1 indicated BL remodeling develops in F versus NF hearts Periodic disruption of cardiac myocyte BL accompanied this process in F, but not NF heart. The rat PO myocardium also developed BL remodeling and compromised myocyte adhesion compared to sham controls. CONCLUSIONS AND CLINICAL RELEVANCE: Differential protein expression and evidence of structural and functional BL alterations develop during heart failure. The compromised adhesion associated with this remodeling indicates a high potential for dysfunctional cellular integrity and tethering in failing myocytes. Therapeutically targeting BL remodeling could slow or prevent the progression of heart disease.

ATDC (Ataxia Telangiectasia Group D Complementing) Promotes Radioresistance through an Interaction with the RNF8 Ubiquitin Ligase.

Induction of DNA damage by ionizing radiation (IR) and/or cytotoxic chemotherapy is an essential component of cancer therapy. The ataxia telangiectasia group D complementing gene (ATDC, also called TRIM29) is highly expressed in many malignancies. It participates in the DNA damage response downstream of ataxia telangiectasia-mutated (ATM) and p38/MK2 and promotes cell survival after IR. To elucidate the downstream mechanisms of ATDC-induced IR protection, we performed a mass spectrometry screen to identify ATDC binding partners. We identified a direct physical interaction between ATDC and the E3 ubiquitin ligase and DNA damage response protein, RNF8, which is required for ATDC-induced radioresistance. This interaction was refined to the C-terminal portion (amino acids 348-588) of ATDC and the RING domain of RNF8 and was disrupted by mutation of ATDC Ser-550 to alanine. Mutations disrupting this interaction abrogated ATDC-induced radioresistance. The interaction between RNF8 and ATDC, which was increased by IR, also promoted downstream DNA damage responses such as IR-induced γ-H2AX ubiquitination, 53BP1 phosphorylation, and subsequent resolution of the DNA damage foci. These studies define a novel function for ATDC in the RNF8-mediated DNA damage response and implicate RNF8 binding as a key determinant of the radioprotective function of ATDC.

Protein biomarkers for the early detection of breast cancer.

Advances in breast cancer control will be greatly aided by early detection so as to diagnose and treat breast cancer in its preinvasive state prior to metastasis. For breast cancer, the second leading cause of cancer-related death among women in the United States, early detection does allow for increased treatment options, including surgical resection, with a corresponding better patient response. Unfortunately, however, many patients' tumors are diagnosed following metastasis, thus making it more difficult to successfully treat the malignancy. There are, at present, no existing validated plasma/serum biomarkers for breast cancer. Only a few biomarkers (such as HER-2/neu, estrogen receptor, and progesterone receptor) have utility for diagnosis and prognosis. Thus, there is a great need for new biomarkers for breast cancer. This paper will focus on the identification of new serum protein biomarkers with utility for the early detection of breast cancer.

Glycoproteomics-based identification of cancer biomarkers.

Protein glycosylation is one of the most common posttranslational modifications in mammalian cells. It is involved in many biological pathways and molecular functions and is well suited for proteomics-based disease investigations. Aberrant protein glycosylation may be associated with disease processes. Specific glycoforms of glycoproteins may serve as potential biomarkers for the early detection of disease or as biomarkers for the evaluation of therapeutic efficacy for treatment of cancer, diabetes, and other diseases. Recent technological developments, including lectin affinity chromatography and mass spectrometry, have provided researchers the ability to obtain detailed information concerning protein glycosylation. These in-depth investigations, including profiling and quantifying glycoprotein expression, as well as comprehensive glycan structural analyses may provide important information leading to the development of disease-related biomarkers. This paper describes methodologies for the detection of cancer-related glycoprotein and glycan structural alterations and briefly summarizes several current cancer-related findings.

Comprehensive proteomic profiling of aldehyde dehydrogenases in lung adenocarcinoma cell lines.

We have explored the potential of proteomic profiling to contribute to the delineation of the range of expression and subcellular localization of aldehyde dehydrogenases (ALDHs) in lung adenocarcinoma. In-depth quantitative proteomics was applied to 40 lung adenocarcinoma cell lines resulting in the identification of the known members of the ALDH family. Substantial heterogeneity in the level and occurrence of ALDHs in total lysates and on the cell surface and in their release into the culture media was observed based on mass spectrometry counts. A distinct pattern of expression of ALDHs was observed in cells exhibiting epithelial features relative to cells exhibiting mesenchymal features. Strikingly elevated levels of ALDH1A1 were observed in two cell lines. We also report on the occurrence of an immune response to ALDH1A1 in lung cancer.

Gene expression patterns in mismatch repair-deficient colorectal cancers highlight the potential therapeutic role of inhibitors of the phosphatidylinositol 3-kinase-AKT-mammalian target of rapamycin pathway.

PURPOSE: High-frequency microsatellite-instable (MSI-H) tumors account for approximately 15% of colorectal cancers. Therapeutic decisions for colorectal cancer are empirically based and currently do not emphasize molecular subclassification despite an increasing collection of gene expression information. Our objective was to identify low molecular weight compounds with preferential activity against MSI colorectal cancers using combined gene expression data sets. EXPERIMENTAL DESIGN: Three expression/query signatures (discovery data set) characterizing MSI-H colorectal cancer were matched with information derived from changes induced in cell lines by 164 compounds using the systems biology tool "Connectivity Map." A series of sequential filtering and ranking algorithms were used to select the candidate compounds. Compounds were validated using two additional expression/query signatures (validation data set). Cytotoxic, cell cycle, and apoptosis effects of validated compounds were evaluated in a panel of cell lines. RESULTS: Fourteen of the 164 compounds were validated as targeting MSI-H cell lines using the bioinformatics approach; rapamycin, LY-294002, 17-(allylamino)-17-demethoxygeldanamycin, and trichostatin A were the most robust candidate compounds. In vitro results showed that MSI-H cell lines due to hypermethylation of MLH1 are preferentially targeted by rapamycin (18.3 versus 4.4 mumol/L; P = 0.0824) and LY-294002 (15.02 versus 10.37 mumol/L; P = 0.0385) when compared with microsatellite-stable cells. Preferential activity was also observed in MSH2 and MSH6 mutant cells. CONCLUSION: Our study shows that the phosphatidylinositol 3-kinase-AKT-mammalian target of rapamycin pathway is of special relevance in mismatch repair-deficient colorectal cancer. In addition, we show that amalgamation of gene expression information across studies provides a robust approach for selection of potential therapies corresponding to specific groups of patients.

Comparative proteomic study of two closely related ovarian endometrioid adenocarcinoma cell lines using cIEF fractionation and pathway analysis.

The proteomic profiles from two distinct ovarian endometrioid tumor-derived cell lines, (MDAH-2774 and TOV-112D) each with different morphological characteristics and genetic mutations, have been studied. Characterization of the differential global protein expression between these two cell lines has important implications for the understanding of the pathogenesis of ovarian endometrioid carcinoma. In this comparative proteomic study, extensive fractionation of peptides generated from whole-cell trypsin digestion was achieved by coupling cIEF in the first-dimensional separation with capillary LC (RP-HPLC) in the second dimensional separation. Online analysis was performed using tandem mass spectra acquired by a linear ion trap mass spectrometer from triplicate runs. A total of 1749 and 1955 proteins with protein probability above 0.95 were identified from MDAH-2774 and TOV-112D after filtering through Peptide Prophet/Protein Prophet software. Differentially expressed proteins were further investigated by ingenuity pathway analysis (IPA) to reveal the association with important biological functions. Canonical pathway analysis using IPA demonstrates that important signaling pathways are highly associated with one of these two cell lines versus the other, such as the PI3K/AKT pathway, which is found to be significantly predominant in MDAH-2774 but not in TOV-112D. Also, protein network analysis using IPA highlights p53 as a central hub relating to other proteins from the connectivity map. These results illustrate the utility of high throughput proteomics methods using large-scale proteome profiling combined with bioinformatics tools to identify differential signaling pathways, thus contributing to the understanding of mechanisms of deregulation in neoplastic cells.

Differential protein mapping of ovarian serous adenocarcinomas: identification of potential markers for distinct tumor stage.

Ovarian serous carcinomas (OSCs) comprise over half of all ovarian carcinomas and account for the majority of ovarian cancer-related deaths. We used a 2-dimensional liquid-based protein mapping strategy to characterize global protein expression patterns in 19 OSC tumor samples from 15 different patients to facilitate molecular classification of tumor stage. Protein expression profiles were produced, using pI-based separation in the first dimension and hydrophobicity-based separation in the second dimension, over a pH range of 4.0-7.0. Hierarchical clustering was applied to protein maps to indicate the tumor interrelationships. The 19 tumor samples could be classified into two different groups, one group associated with low stage (Stage 1) tumors and the other group associated with high stage (Stages 3/4) tumors. Proteins that were differentially expressed in different groups were selected for identification by LTQ-ESI-MS/MS. Fourteen of the selected proteins were overexpressed in the low stage tumors; 46 of the proteins were overexpressed in the high stage tumors. These proteins are known to play an important role in cellular functions such as glycolysis, protein biosynthesis, and cytoskeleton rearrangement and may serve as markers associated with different stages of OSCs. To further confirm the stage-dependent protein identifications, Lamin A/C and Vimentin expression in ovarian serous carcinomas was assessed by immunohistochemistry using ovarian tumor tissue microarrays for 66 samples.

A biomarker panel for acute graft-versus-host disease.

No validated biomarkers exist for acute graft-versus-host disease (GVHD). We screened plasma with antibody microarrays for 120 proteins in a discovery set of 42 patients who underwent transplantation that revealed 8 potential biomarkers for diagnostic of GVHD. We then measured by enzyme-linked immunosorbent assay (ELISA) the levels of these biomarkers in samples from 424 patients who underwent transplantation randomly divided into training (n = 282) and validation (n = 142) sets. Logistic regression analysis of these 8 proteins determined a composite biomarker panel of 4 proteins (interleukin-2-receptor-alpha, tumor-necrosis-factor-receptor-1, interleukin-8, and hepatocyte growth factor) that optimally discriminated patients with and without GVHD. The area under the receiver operating characteristic curve distinguishing these 2 groups in the training set was 0.91 (95% confidence interval, 0.87-0.94) and 0.86 (95% confidence interval, 0.79-0.92) in the validation set. In patients with GVHD, Cox regression analysis revealed that the biomarker panel predicted survival independently of GVHD severity. A panel of 4 biomarkers can confirm the diagnosis of GVHD in patients at onset of clinical symptoms of GVHD and provide prognostic information independent of GVHD severity.

Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study.

Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.

Plasma glycoprotein profiling for colorectal cancer biomarker identification by lectin glycoarray and lectin blot.

Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient; hence, the need for simple blood tests that could be used for the early detection of CRC. In this work, we have developed methods for glycoproteomics analysis to identify plasma markers with utility to assist in the detection of colorectal cancer (CRC). Following immunodepletion of the most abundant plasma proteins, the plasma N -linked glycoproteins were enriched using lectin affinity chromatography and subsequently further separated by nonporous silica reversed-phase (NPS-RP)-HPLC. Individual RP-HPLC fractions were printed on nitrocellulose coated slides which were then probed with lectins to determine glycan patterns in plasma samples from 9 normal, 5 adenoma, and 6 colorectal cancer patients. Statistical tools, including principal component analysis, hierarchical clustering, and Z-statistics analysis, were employed to identify distinctive glycosylation patterns. Patients diagnosed with colorectal cancer or adenomas were shown to have dramatically higher levels of sialylation and fucosylation as compared to normal controls. Plasma glycoproteins with aberrant glycosylation were identified by nano-LC-MS/MS, while a lectin blotting methodology was used to validate proteins with significantly altered glycosylation as a function of cancer progression. The potential markers identified in this study for diagnosis to distinguish colorectal cancer from adenoma and normal include elevated sialylation and fucosylation in complement C3, histidine-rich glycoprotein, and kininogen-1. These potential markers of colorectal cancer were subsequently validated by lectin blotting in an independent set of plasma samples obtained from 10 CRC patients, 10 patients with adenomas, and 10 normal subjects. These results demonstrate the utility of this strategy for the identification of N -linked glycan patterns as potential markers of CRC in human plasma, and may have the utility to distinguish different disease states.

Comparative proteomic analysis of low stage and high stage endometrioid ovarian adenocarcinomas.

Ovarian cancer, the second most common gynecological malignancy, accounts for 3% of all cancers among women in the United States, and has a high mortality rate, largely because existing therapies for widespread disease are rarely curative. Ovarian endometrioid adenocarcinoma (OEA) accounts for about 20% of the overall incidence of all ovarian cancer. We have used proteomics profiling to characterize low stage (FIGO stage 1 or 2) versus high stage (FIGO stage 3 or 4) human OEAs. In general, the low stage tumors lacked p53 mutations and had frequent CTNNB1, PTEN, and/or PIK3CA mutations. The high stage tumors had mutant p53, were usually high grade, and lacked mutations predicted to deregulate Wnt/ß-catenin and PI3K/Pten/Akt signaling. We utilized 2-D liquid-based separation/mass mapping techniques to elucidate molecular weight and pI measurements of the differentially expressed intact proteins. We generated 2-D protein mass maps to facilitate the analysis of protein expression between both the low stage and high stage tumors. These mass maps (over a pI range of 5.6-4.6) revealed that the low stage OEAs demonstrated protein over-expression at the lower pI ranges (pI 4.8-4.6) in comparison to the high stage tumors, which demonstrated protein over-expression in the higher pI ranges (pI 5.4-5.2). These data suggest that both low and high stage OEAs have characteristic pI signatures of abundant protein expression probably reflecting, at least in part, the different signaling pathway defects that characterize each group. In this study, the low stage OEAs were distinguishable from high stage tumors based upon the proteomic profiles. Interestingly, when only high-grade (grade 2 or 3) OEAs were included in the analysis, the tumors still tended to cluster according to stage, suggesting that the altered protein expression was not solely dependent upon tumor cell differentiation. Further, these protein profiles clearly distinguish OEA from other types of ovarian cancer at the protein level.

Integral protein microarrays for the identification of lung cancer antigens in sera that induce a humoral immune response.

The identification of biomarkers (both molecules and profiles) in patient sera offers enormous interest for the diagnosis of cancers. In this context, the detection of antibodies to tumor cell autologous antigens possesses great potential. The humoral immune response represents a form of biological amplification of signals that are otherwise weak because of very low concentrations of antigen, especially in the early stages of cancers. Herein we present the use of integral microarrays spotted with tumor-derived proteins to investigate the antibody repertoire in the sera of lung cancer patients and controls. The use of two-dimensional liquid chromatography allowed us to separate proteins from the lung adenocarcinoma cell line A549 into 1760 fractions, which were printed in duplicate, along with various controls, onto nitrocellulose coated slides. The sensitivity and specificity of the microarrays to detect singular antibodies in fluids were first validated through the recognition of fractions containing a lung marker antigen by antibody probing. Twenty fractions were initially selected as highly reactive against the anti-PGP9.5 antibody, and subsequent mass spectrometry analyses confirmed the identity of PGP9.5 protein in four of them. As a result, the importance of neighboring fractions in microarray detection was revealed due to the spreading of proteins during the separation process. Next, the microarrays were individually incubated with 14 serum samples from patients with lung cancer patients, 14 sera from colon cancer patients, and 14 control sera from normal subjects. The reactivity of the selected fractions was analyzed, and the level of immunoglobulin bound to each fraction by each serum sample was quantified. Eight of the 20 fractions offered p values < 0.01 and were recognized by an average of four reacting patients, whereas no serum from normal individuals was positive for those fractions. Protein microarrays from tumor-derived fractions hold the diagnostic potential of uncovering antigens that induce an immune response in patients with certain types of cancers.

Identification of 14-3-3 theta as an antigen that induces a humoral response in lung cancer.

We have implemented a strategy to identify tumor antigens that induce a humoral immune response in lung cancer based on the analysis of tumor cell proteins. Chromatographically fractionated protein extracts from three lung cancer cell lines were subjected to Western blotting and hybridization with individual sera to determine serum antibody binding. Two sets of sera were initially investigated. One set consisted of sera from 19 newly diagnosed subjects with lung adenocarcinoma and 19 matched controls. A second independent set consisted of sera from 26 newly diagnosed subjects with lung adenocarcinoma and 24 controls matched for age, gender, and smoking history. One protein that exhibited significant reactivity with both sets of cancer sera (P = 0.0008) was confidently identified by mass spectrometry as 14-3-3 theta. Remarkably, significant autoantibody reactivity against 14-3-3 theta was also observed in an analysis of a third set consisting of 18 prediagnostic lung cancer sera collected as part of the Beta-Carotene and Retinol Efficacy Trial cohort study, relative to 19 matched controls (P = 0.0042). A receiver operating characteristic curve constructed with a panel of three proteins consisting of 14-3-3 theta identified in this study, plus annexin 1 and protein gene product 9.5 proteins previously identified as associated with autoantibodies in lung cancer, gave a sensitivity of 55% at 95% specificity (area under the curve, 0.838) in discriminating lung cancer at the preclinical stage from matched controls.

Early detection and biomarkers in pancreatic cancer.

Major advances in cancer control will be greatly aided by early detection for diagnosing and treating cancer in its preinvasive state before metastasis. Unfortunately, for pancreatic ductal adenocarcinoma (PDAC), which is the fourth leading cause of cancer-related death in the United States, effective early detection and screening are currently not available and tumors are typically diagnosed at a late stage, frequently after metastasis. Partly because of low sensitivity/specificity, existing biomarkers such as CA19-9 are not adequate as early detection markers of pancreatic cancer. Thus, a great need exists for new biomarkers for pancreatic cancer. This article focuses on recent developments in the identification of new serum protein biomarkers that are useful in the early detection of PDAC.

Glycoprotein microarrays with multi-lectin detection: unique lectin binding patterns as a tool for classifying normal, chronic pancreatitis and pancreatic cancer sera.

Pancreatic cancer is the fourth leading cause of cancer-related death in the United States, with a 5-year survival rate of less than 4%. Effective early detection and screening are currently not available, and tumors are typically diagnosed at a late stage, frequently after metastasis. Existing clinical markers of pancreatic cancer lack specificity, as they are also found in inflammatory diseases of the pancreas and biliary tract. In the work described here, naturally occurring glycoproteins were enriched by using lectin affinity chromatography and then further resolved by nonporous reversed-phase chromatography. Glycoprotein microarrays were then printed and probed with a variety of lectins to screen glycosylation patterns in sera from normal, chronic pancreatitis, and pancreatic cancer patients. Ten normal, 8 chronic pancreatitis, and 6 pancreatic cancer sera were investigated. Data from the glycoprotein microarrays were analyzed using bioinformatics approaches including principal component analysis (PCA) and hierarchical clustering (HC). Both normal and chronic pancreatitis sera were found to cluster close together, although in two distinct groups, whereas pancreatic cancer sera were significantly different from the other two groups. Both sialylation and fucosylation increased as a function of cancer on several proteins including Hemopexin, Kininogen-1, Antithrombin-III, and Haptoglobin-related protein, whereas decreased sialylation was detected on plasma protease C1 inhibitor. Target alterations on glycosylations were verified by lectin blotting experiments and peptide mapping experiments using microLC-ESI-TOF. These altered glycan structures may have utility for the differential diagnosis of pancreatic cancer and chronic pancreatitis and identify critical differences between biological samples from patients with different clinical conditions.

Characterization of apolipoprotein and apolipoprotein precursors in pancreatic cancer serum samples via two-dimensional liquid chromatography and mass spectrometry.

Major advances in cancer control depend upon early detection, early diagnosis and efficacious treatment modalities. Current existing markers of pancreatic ductal adenocarcinoma, generally incurable by available treatment modalities, are inadequate for early diagnosis or for distinguishing between pancreatic cancer and chronic pancreatitis. We have used a proteomic approach to identify proteins that are differentially expressed in sera from pancreatic cancer patients, as compared to control. Normal, chronic pancreatitis and pancreatic cancer serum samples were depleted of high molecular weight proteins by acetonitrile precipitation. Each sample was separated by chromatofocusing, and then further resolved by reversed-phase (RP)-HPLC. Effluent from the RP-HPLC column was split into two streams with one directly interfaced to an electrospray time-of-flight (ESI-TOF) mass spectrometer for molecular weight (MW) determination of the intact proteins. The remainder went through a UV detector with the corresponding peaks collected with a fraction collector, subsequently used for MS/MS analysis. The ion intensities of proteins with the same MW obtained from ESI-TOF-MS analysis were compared, with the differentially expressed proteins determined. An 8915 Da protein was found to be up-regulated while a 9422 Da protein was down-regulated in the pancreatic cancer sera. Both proteins were identified by MS and MS/MS as proapolipoprotein C-II and apolipoprotein C-III(1), respectively. The MS/MS data of proapolipoprotein C-II was searched using "semi-trypsin" as the search enzyme, thus confirming that the protein at 8915 Da was proapolipoprotein C-II. In order to confirm the identity of the protein at 9422 Da, we initially identified a protein of 8765 Da with a similar mass spectral pattern. Based on MS and MS/MS, its intact molecular weight and "semi-trypsin" database search, the protein at 8765 Da was identified as apolipoprotein C-III(0). The MS and MS/MS data of the proteins at 8765 Da and 942 Da were similar, thus confirming the protein at 9422 Da as being apolipoprotein C-III(1). The detection of differentially expressed proapolipoprotein C-II and apolipoprotein C-III(1) in the sera of pancreatic cancer patients may have utility for detection of this deadly malignancy.

Mouse model of human ovarian endometrioid adenocarcinoma based on somatic defects in the Wnt/beta-catenin and PI3K/Pten signaling pathways.

One histologic subtype of ovarian carcinoma, ovarian endometrioid adenocarcinoma (OEA), frequently harbors mutations that constitutively activate Wnt/beta-catenin-dependent signaling. We now show that defects in the PI3K/Pten and Wnt/beta-catenin signaling pathways often occur together in a subset of human OEAs, suggesting their cooperation during OEA pathogenesis. Deregulation of these two pathways in the murine ovarian surface epithelium by conditional inactivation of the Pten and Apc tumor suppressor genes results in the formation of adenocarcinomas morphologically similar to human OEAs with 100% penetrance, short latency, and rapid progression to metastatic disease in upwards of 75% of mice. The biological behavior and gene expression patterns of the murine cancers resemble those of human OEAs with defects in the Wnt/beta-catenin and PI3K/Pten pathways.

Discovery of cancer biomarkers through the use of mouse models.

Although our understanding of the molecular pathogenesis of common types of cancer has improved considerably, the development of effective strategies for cancer diagnosis and treatment have lagged behind. Mouse models of cancer potentially represent an efficient means for uncovering diagnostic markers as genetic alterations associated with human tumors can be engineered in mice. In addition, defined stages of tumor development, breeding conditions, and blood sampling can all be controlled and standardized to limit heterogeneity. Alternatively human cancer cells can be injected into mice and tumor development monitored in xenotransplants. Mouse-based studies promise to elucidate a repertoire of protein changes that occur in blood and biological fluids during tumor development. This is illustrated in a study in which we have applied a three-dimensional intact protein analysis system (IPAS) to elucidate detectable protein changes in serum from immunodeficient mice with lung xenografts from orthotopically implanted human A549 lung adenocarcinoma cells. With sufficiently detailed protein sequence identifications, the observed protein changes can be attributed to either the host mouse or the human tumor cells. It is noteworthy that the majority of increases identified have corresponded to relatively abundant serum proteins, some of which have previously been reported as increased in the sera of cancer patients. Proteomic studies of mouse models of cancer allow assessment of the range of changes in plasma proteins that occur with tumor development and may lead to the identification of potential cancer markers applicable to humans.