Induction of endoplasmic reticular stress by bortezomib: A novel therapeutic strategy for pancreatic cancer

Bortezomib (VELCADE™, formerly known as PS-341) is a selective and potent inhibitor of the proteasome that was recently FDA-approved for the treatment of multiple myeloma. Despite its success in multiple myeloma and progression into clinical trials for other malignancies, bortezomib's exact mechanism of action remains undefined. The major objective of this study was to evaluate the anticancer activity of this drug using in vitro and in vivo pancreatic cancer models and determine whether bortezomib-induced apoptosis occurs via induction of endoplasmic reticular (ER) stress. The investigation revealed that bortezomib inhibited tumor cell proliferation via abrogation of cdk activity and induced apoptosis in pancreatic cancer cell lines. I hypothesized that bortezomib-induced apoptosis was triggered by a large accumulation ubiquitin-conjugated proteins that resulted in ER stress. My data demonstrated that bortezomib induced a unique type of ER stress in that it inhibited PKR-like ER kinase (PERK) and subsequent phosphorylation of eukaryotic initiation factor 2α (eif2α), a key event in translational suppression. The combined effects of proteasome inhibition and the failure to attenuate translation resulted in an accumulation of aggregated proteins (proteotoxicity), JNK activation, cytochrome c release, caspase-3 activation, and DNA fragmentation. Bortezomib also enhanced apoptosis induced by other agents that stimulated the unfolded protein response (UPR), demonstrating that translational suppression is a critical cytoprotective mechanism during ER stress. Tumor cells attempt to survive bortezomib-induced ER stress by sequestering aggregated proteins into large structures, termed aggresomes. Since histone deacetylase 6 (HDAC6) is essential for aggresome formation, tumor cells may be sensitized to bortezomib-induced apoptosis by blocking HDAC function. My results demonstrated that HDAC inhibitors disrupted aggresome formation and synergized with bortezomib to induce apoptosis in pancreatic cancer or multiple myeloma cells in vitro and in orthotopic pancreatic tumors in vivo. Taken together, my data establish a mechanistic link between bortezomib-induced aggresome formation, ER stress, and apoptosis and identify a novel therapeutic strategy for the treatment of pancreatic cancer and other hematologic and solid malignancies. ^

Measurement of the vascular input function in mice for DCE-MRI

DCE-MRI is an important technique in the study of small animal cancer models because its sensitivity to vascular changes opens the possibility of quantitative assessment of early therapeutic response. However, extraction of physiologically descriptive parameters from DCE-MRI data relies upon measurement of the vascular input function (VIF), which represents the contrast agent concentration time course in the blood plasma. This is difficult in small animal models due to artifacts associated with partial volume, inflow enhancement, and the limited temporal resolution achievable with MR imaging. In this work, the development of a suite of techniques for high temporal resolution, artifact resistant measurement of the VIF in mice is described. One obstacle in VIF measurement is inflow enhancement, which decreases the sensitivity of the MR signal to the presence of contrast agent. Because the traditional techniques used to suppress inflow enhancement degrade the achievable spatiotemporal resolution of the pulse sequence, improvements can be achieved by reducing the time required for the suppression. Thus, a novel RF pulse which provides spatial presaturation contemporaneously with the RF excitation was implemented and evaluated. This maximizes the achievable temporal resolution by removing the additional RF and gradient pulses typically required for suppression of inflow enhancement. A second challenge is achieving the temporal resolution required for accurate characterization of the VIF, which exceeds what can be achieved with conventional imaging techniques while maintaining adequate spatial resolution and tumor coverage. Thus, an anatomically constrained reconstruction strategy was developed that allows for sampling of the VIF at extremely high acceleration factors, permitting capture of the initial pass of the contrast agent in mice. Simulation, phantom, and in vivo validation of all components were performed. Finally, the two components were used to perform VIF measurement in the murine heart. An in vivo study of the VIF reproducibility was performed, and an improvement in the measured injection-to-injection variation was observed. This will lead to improvements in the reliability of quantitative DCE-MRI measurements and increase their sensitivity.

THE ROLE OF MAP KINASES ON THE FUNCTIONAL HETEROGENEITY OF HUMAN CD8+ T CELL MATURATION SUBSETS

While prior studies have focused on naïve (CD45RA+CD27+) and early stage memory (CD45RA-CD27+) CD8+ T cells, late memory CD8+ T cells (CD45RA+CD27) have received less interest because this subset of T cells is generally recognized as effectors, which produce IFNγ (but no IL-2) and perforin. However, multiple studies suggest that late memory CD8+ T cells may provide inadequate protection in infectious diseases and cancer models. To better understand the unique function of late memory CD8+ T cells, I optimized multi-color flow cytometry techniques to assess the cytokine production of each human CD8+ T cell maturation subset. I demonstrated that late memory CD8+ T cells are the predominant producer of CC chemokines (e.g. MIP-1β), but rarely produce IL-2; therefore they do not co-produce IL-2/IFNγ (polyfunctionality), which has been shown to be critical for protective immunity against chronic viral infection. These data suggest that late memory CD8+ T cells are not just cytotoxic effectors, but may have unique functional properties. Determining the molecular signature of each CD8+ T cell maturation subset will help characterize the role of late memory CD8+ T cells. Prior studies suggest that ERK1 and ERK2 play a role in cytokine production including IL-2 in T cells. Therefore, I tested whether differential expression of ERK1 and ERK2 in CD8+ T cell maturation subsets contributes to their functional signature by a novel flow cytometry technique. I found that the expression of total ERK1, but not ERK2, is significantly diminished in late memory CD8+ T cells and that ERK1 expression is strongly associated with IL-2 production and CD28 expression. I also found that IL-2 production is increased in late memory CD8+ T cells by over-expressing ERK1. Collectively, these data suggest that ERK1 is required for IL-2 production in human CD8+ T cells. In summary, this dissertation demonstrated that ERK1 is down-regulated in human late memory CD8+ T cells, leading to decreased production of IL-2. The data in this dissertation also suggested that the functional heterogeneity in human CD8+ T cell maturation subsets results from their differential ERK1 expression.

Chronic stress promotes tumor growth through increased BDNF production and neo-innervation

Background: Activation of the sympathetic nervous system (SNS) in response to chronic biobehavioral stress results in high levels of catecholamines and persistent activation of adrenergic signaling, which promotes tumor growth and progression. However it is unknown how catecholamine levels within the tumor exceed systemic levels in circulation. I hypothesized that neo-innervation of tumors is required for stress-mediated effects on tumor growth. Results: First, I examined whether sympathetic nerves are present in human ovarian cancer samples as well as orthotopic ovarian cancer models. Immunohistochemical (IHC) staining for neurofilament revealed that catecholaminergic neurons are present within tumor tissue. In order to determine whether chronic stress affects the density of nerves in the tumor, I utilized an orthotopic mouse model of ovarian cancer that was exposed to daily restraint stress. IHC analysis revealed that nerve density in tumors increased by more than three-fold in stressed animals versus non-stressed controls. IHC analysis suggested that this results from both recruitment of existing neurons (axonogenesis) as well as new neuron formation (neurogenesis) within the tumor. To determine how tumors are recruiting nerve growth, I utilized a PCR array analysis of 84 nerve growth related genes and their receptors, which showed that stimulation of the SKOV3 ovarian cancer cell line with norepinephrine (NE) leads to increased expression of several neurotrophins, including brain-derived neurotrophic factor (BDNF). Neurite extension assays showed that media conditioned by ovarian cancer cell lines is capable of inducing neurite outgrowth in differentiated neuron-like PC12 cells, and NE treatment of cancer cells potentiates this effect. Norepinephrine-induced neurite extension was abolished after BDNF silencing by siRNA, suggesting that BDNF is critical to tumor cell-induced nerve growth. in vivo BDNF inhibition resulted in complete abrogation of stress-induced increases in tumor weight and nerve density, as well as downstream markers of stress. Discussion: These studies indicate that adrenergic signalling induced by chronic stress promotes neo-innervation in the tumor microenvironment. This results in a mutually beneficial relationship between the tumor cells and neurons. This work is crucial for providing a link between chronic stress and its effects on the tumor and its microenvironment. The data shown here aims to open new venues that can be used in development of therapies designed to block the stress effects on tumor growth.

THE MECHANISM OF TUMORIGENESIS IN THE IMMORTALIZED HUMAN PANCREATIC CELL LINES: CELL CULTURE MODELS OF HUMAN PANCREATIC CANCER

The mechanism of tumorigenesis in the immortalized human pancreatic cell lines: cell culture models of human pancreatic cancer Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer in the world. The most common genetic lesions identified in PDAC include activation of K-ras (90%) and Her2 (70%), loss of p16 (95%) and p14 (40%), inactivation p53 (50-75%) and Smad4 (55%). However, the role of these signature gene alterations in PDAC is still not well understood, especially, how these genetic lesions individually or in combination contribute mechanistically to human pancreatic oncogenesis is still elusive. Moreover, a cell culture transformation model with sequential accumulation of signature genetic alterations in human pancreatic ductal cells that resembles the multiple-step human pancreatic carcinogenesis is still not established. In the present study, through the stepwise introduction of the signature genetic alterations in PDAC into the HPV16-E6E7 immortalized human pancreatic duct epithelial (HPDE) cell line and the hTERT immortalized human pancreatic ductal HPNE cell line, we developed the novel experimental cell culture transformation models with the most frequent gene alterations in PDAC and further dissected the molecular mechanism of transformation. We demonstrated that the combination of activation of K-ras and Her2, inactivation of p16/p14 and Smad4, or K-ras mutation plus p16 inactivation, was sufficient for the tumorigenic transformation of HPDE or HPNE cells respectively. We found that these transformed cells exhibited enhanced cell proliferation, anchorage-independent growth in soft agar, and grew tumors with PDAC histopathological features in orthotopic mouse model. Molecular analysis showed that the activation of K-ras and Her2 downstream effector pathways –MAPK, RalA, FAK, together with upregulation of cyclins and c-myc were involved in the malignant transformation. We discovered that MDM2, BMP7 and Bmi-1 were overexpressed in the tumorigenic HPDE cells, and that Smad4 played important roles in regulation of BMP7 and Bmi-1 gene expression and the tumorigenic transformation of HPDE cells. IPA signaling pathway analysis of microarray data revealed that abnormal signaling pathways are involved in transformation. This study is the first complete transformation model of human pancreatic ductal cells with the most common gene alterations in PDAC. Altogether, these novel transformation models more closely recapitulate the human pancreatic carcinogenesis from the cell origin, gene lesion, and activation of specific signaling pathway and histopathological features.

Logistic regression models for ordinal response: A study of self-efficacy in colorectal cancer screening

The ordinal logistic regression models are used to analyze the dependant variable with multiple outcomes that can be ranked, but have been underutilized. In this study, we describe four logistic regression models for analyzing the ordinal response variable. ^ In this methodological study, the four regression models are proposed. The first model uses the multinomial logistic model. The second is adjacent-category logit model. The third is the proportional odds model and the fourth model is the continuation-ratio model. We illustrate and compare the fit of these models using data from the survey designed by the University of Texas, School of Public Health research project PCCaSO (Promoting Colon Cancer Screening in people 50 and Over), to study the patient’s confidence in the completion colorectal cancer screening (CRCS). ^ The purpose of this study is two fold: first, to provide a synthesized review of models for analyzing data with ordinal response, and second, to evaluate their usefulness in epidemiological research, with particular emphasis on model formulation, interpretation of model coefficients, and their implications. Four ordinal logistic models that are used in this study include (1) Multinomial logistic model, (2) Adjacent-category logistic model [9], (3) Continuation-ratio logistic model [10], (4) Proportional logistic model [11]. We recommend that the analyst performs (1) goodness-of-fit tests, (2) sensitivity analysis by fitting and comparing different models.^

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^

NHERF1 – New Modifier of Colorectal Cancer Progression

Colorectal cancer (CRC) develops from multiple progressive modifications of normal intestinal epithelium into adenocarcinoma. Loss of cell polarity has been implicated as an early event in this process, but the molecular players involved are not well known. NHERF1 (Na+/H+ Exchanger Regulatory Factor 1) is an adaptor protein with apical membrane localization in polarized epithelia. In this study, we tested our hypothesis that NHERF1 plays a role in CRC. We examined surgical CRC resection specimens for changes in NHERF1 expression, and modeled these changes in two- and three-dimensional (2D and 3D) Caco-2 CRC cell systems. NHERF1 had significant alterations from normal to adenoma and carcinoma transitions (2=38.5, d.f.=4, P<0.001), displaying apical membrane localization in normal tissue but loss of expression in adenoma and ectopic overexpression in carcinoma. In Caco-2 cell models, NHERF1 depletion induced epithelial-mesenchymal-transition in 2D cell monolayers and disruption of apical-basal polarity in 3D cyst system. The mesenchymal phenotype of NHERF1-depleted cells was fully restored by re-expression of NHERF1 at the apical membrane. Cytoplasmic and nuclear NHERF1 re-expression not only failed to restore the epithelial phenotype but led to more aggressive phenotypes. Our findings suggest that membrane NHERF1 is an important regulator of epithelial morphogenesis, and that changes in NHERF1 expression correlate with CRC progression. NHERF1 loss and ectopic expression that induce massive disruption of epithelial cell polarity may, thereby, mark important steps in CRC development.

Role and Regulation of EphA2 in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cancer cause of death in the US. Gemcitabine is the first-line therapy for this disease, but unfortunately it shows only very modest benefit. The focus of the current study was to investigate the role and regulation of EphA2, a receptor tyrosine kinase expressed in PDAC, to further understand this disease and identify new therapeutic targets. The role of EphA2 was determined in PDAC by siRNA mediated silencing. In combination with gemcitabine, silencing of EphA2 caused a dramatic increase in apoptosis even in highly resistant cells in vitro. Furthermore, EphA2 silencing was found to be useful in 2 orthotopic models in vivo: 1) shRNA-pretreated Miapaca-2 cells, and 2) in vivo delivery of siRNA to established MPanc96 tumors. Silencing of EphA2 alone reduced tumor growth in Miapaca-2 cells. In MPanc96, only the combination treatment of gemcitabine plus siEphA2 significantly reduced tumor growth, as well as the number of lung and liver metastases. Taken together, these observations support EphA2 as a target for combination therapies for PDAC. The regulation of EphA2 was further explored with a focus on the role of Ras. K-Ras activating mutations are the most important initiating event in PDAC. We demonstrated that Ras regulates EphA2 expression through activation of MEK2 and phosphorylation of ERK. Downstream of ERK, silencing of the transcription factor AP-1 subunit c-Jun or inhibition of the ERK effector RSK caused a decrease in EphA2 expression, supporting their roles in this process. Further examination of Ras/MEK/ERK pathway modulators revealed that PEA-15, a protein that sequesters ERK to the cytoplasm, inhibited expression of EphA2. A significant inverse correlation between EphA2 and PEA-15 levels was observed in mouse models of PDAC. In cells where an EGFR inhibitor reduced phospho-Erk, expression of EphA2 was also reduced, indicating that changes in EphA2 levels may allow monitoring the effectiveness of anti-Ras/MEK/ERK therapies. In conclusion, EphA2 levels may be a good prognostic factor for anti-EGFR/anti-Ras therapies, and EphA2 itself is a relevant target for the development of new therapies.

Risk of Second Malignant Neoplasms Following Proton Arc Therapy and Volumetric Modulated Arc Therapy for Prostate Cancer

The risk of second malignant neoplasms (SMNs) following prostate radiotherapy is a concern due to the large population of survivors and decreasing age at diagnosis. It is known that parallel-opposed beam proton therapy carries a lower risk than photon IMRT. However, a comparison of SMN risk following proton and photon arc therapies has not previously been reported. The purpose of this study was to predict the ratio of excess relative risk (RRR) of SMN incidence following proton arc therapy to that after volumetric modulated arc therapy (VMAT). Additionally, we investigated the impact of margin size and the effect of risk-minimized proton beam weighting on predicted RRR. Physician-approved treatment plans were created for both modalities for three patients. Therapeutic dose was obtained with differential dose-volume histograms from the treatment planning system, and stray dose was estimated from the literature or calculated with Monte Carlo simulations. Then, various risk models were applied to the total dose. Additional treatment plans were also investigated with varying margin size and risk-minimized proton beam weighting. The mean RRR ranged from 0.74 to 0.99, depending on risk model. The additional treatment plans revealed that the RRR remained approximately constant with varying margin size, and that the predicted RRR was reduced by 12% using a risk-minimized proton arc therapy planning technique. In conclusion, proton arc therapy was found to provide an advantage over VMAT in regard to predicted risk of SMN following prostate radiotherapy. This advantage was independent of margin size and was amplified with risk-optimized proton beam weighting.

Cell Cycle Regulatory Roles of Estrogen Receptor alpha (ERα) in Breast Cancer Cells

Previous studies have shown that Estrogen Receptor alpha (ERα) is an important indicator for diagnosis, prognosis and treatment of breast cancers. However, the question remains as to the role of ERα in the cell in the presence versus absence of 17-β estradiol In this dissertation the role of ERα in both its unliganded and liganded state, with respect to the cell cycle will be explored. The cell line models used in this project are ER-positive MCF-7 cells with and without siRNA to ERα and ER-positive MDA-MB-231 cells that have been engineered to express ERα. Cells were synchronized and the cell cycle progression was monitored by flow cytometric analysis. Using these methods, two specific questions were addressed: Does ERα modulate the cell cycle differently under liganded versus unliganded conditions? And, does the presence of ERα regulate cell cycle phase transitions? The results show for the first time that ERα is cell cycle regulated and modulates the progression of cells through S and G2/M phases of the cell cycle. Ligand bound ERα increases progression through S and G2/M phases, whereas unliganded ERα acts as an inhibitor of cell cycle progression. To further investigate the cell cycle regulated effects of liganded ERα, a luciferase assay was performed and showed that the transcription of target genes such as Progestrone Receptor (PgR) and Trefoil protein (pS2) increased duing S and G2/M phases when ERα is bound to ligand. Additionally, complex formation between cyclin B and ER α was shown by immunoprecipitation and led to the discovery that anaphase promoting complex (APC) is the E3 ligase for both cyclin B and ERα at the termination of M phase. Our findings suggest that unliganded ERα has an inhibitory effect on the progression of the cell cycle. Therefore, it is reasonable to speculate that the combination of drugs that lower estrogen level (such as aromatase inhibitors) and preserves ERα from degradation would provide better outcome for breast cancer treatment. We have shown that APC functions as the E3 ligase for ERα and thus might provide a target to design a specific inhibitor of ERα degradation.

Prime-boost vaccination with plasmid and adenovirus gene vaccines control HER2/neu+ metastatic breast cancer in mice.

INTRODUCTION: Once metastasis has occurred, the possibility of completely curing breast cancer is unlikely, particularly for the 30 to 40% of cancers overexpressing the gene for HER2/neu. A vaccine targeting p185, the protein product of the HER2/neu gene, could have therapeutic application by controlling the growth and metastasis of highly aggressive HER2/neu+ cells. The purpose of this study was to determine the effectiveness of two gene vaccines targeting HER2/neu in preventive and therapeutic tumor models. METHODS: The mouse breast cancer cell line A2L2, which expresses the gene for rat HER2/neu and hence p185, was injected into the mammary fat pad of mice as a model of solid tumor growth or was injected intravenously as a model of lung metastasis. SINCP-neu, a plasmid containing Sindbis virus genes and the gene for rat HER2/neu, and Adeno-neu, an E1,E2a-deleted adenovirus also containing the gene for rat HER2/neu, were tested as preventive and therapeutic vaccines. RESULTS: Vaccination with SINCP-neu or Adeno-neu before tumor challenge with A2L2 cells significantly inhibited the growth of the cells injected into the mammary fat or intravenously. Vaccination 2 days after tumor challenge with either vaccine was ineffective in both tumor models. However, therapeutic vaccination in a prime-boost protocol with SINCP-neu followed by Adeno-neu significantly prolonged the overall survival rate of mice injected intravenously with the tumor cells. Naive mice vaccinated using the same prime-boost protocol demonstrated a strong serum immunoglobulin G response and p185-specific cellular immunity, as shown by the results of ELISPOT (enzyme-linked immunospot) analysis for IFNgamma. CONCLUSION: We report herein that vaccination of mice with a plasmid gene vaccine and an adenovirus gene vaccine, each containing the gene for HER2/neu, prevented growth of a HER2/neu-expressing breast cancer cell line injected into the mammary fat pad or intravenously. Sequential administration of the vaccines in a prime-boost protocol was therapeutically effective when tumor cells were injected intravenously before the vaccination. The vaccines induced high levels of both cellular and humoral immunity as determined by in vitro assessment. These findings indicate that clinical evaluation of these vaccines, particularly when used sequentially in a prime-boost protocol, is justified.

Antibodies targeting hepatoma-derived growth factor as a novel strategy in treating lung cancer.

Hepatoma-derived growth factor (HDGF) is overexpressed in lung cancer and the overexpression correlates with aggressive biological behaviors and poor clinical outcomes. We developed anti-HDGF monoclonal antibodies and tested their antitumor activity in lung cancer xenograft models. We also determined biological effects in tumors treated with the antibody alone or in combination with bevacizumab/avastin (an anti-vascular endothelial growth factor antibody) and/or gemcitabine (a chemotherapeutic agent). We found the anti-HDGF was effective to inhibit tumor growth in non-small cell lung cancer xenograft models. In the A549 model, compared with control IgG, tumor growth was substantially inhibited in animals treated with anti-HDGF antibodies, particularly HDGF-C1 (P = 0.002) and HDGF-H3 (P = 0.005). When HDGF-H3 was combined with either bevacizumab or gemcitabine, we observed enhanced tumor growth inhibition, particularly when the three agents were used together. HDGF-H3-treated tumors exhibited significant reduction of microvessel density with a pattern distinctive from the microvessel reduction pattern observed in bevacizumab-treated tumors. HDGF-H3-treated but not bevacizumab-treated tumors also showed a significant increase of apoptosis. Interestingly, many of the apoptotic cells in HDGF-H3-treated tumors are stroma cells, suggesting that the mechanism of the antitumor activity is, at least in part, through disrupting formation of tumor-stroma structures. Our results show that HDGF is a novel therapeutic target for lung cancer and can be effectively targeted by an antibody-based approach.