Browsing by Subject "Cancer"

The advent of new genomic approaches, particularly next generation sequencing (NGS) has resulted in explosive growth of biological data. As the size of biological data keeps growing at exponential rates, new methods for data management and data processing are becoming essential in bioinformatics and computational biology. Indeed, data analysis has now become the central challenge in genomics.

NGS has provided rich tools for defining genomic alterations that cause cancer. The processing time and computing requirements have now become a serious bottleneck to the characterization and analysis of these genomic alterations. Moreover, as the adoption of NGS continues to increase, the computing power required often exceeds what any single institution can provide, leading to major restraints in the type and number of analyses that can be performed.

Cloud computing represents a potential solution to this problem. On a cloud platform, computing resources can be available on-demand, thus allowing users to implement scalable and highly parallel methods. However, few centralized frameworks exist to allow the average researcher the ability to apply bioinformatics workflows using cloud resources. Moreover, bioinformatics approaches are associated with multiple processing challenges, such as the variability in the methods or data used and the reproducibility requirements of the research analysis.

Here, we present CloudConductor, a software system that is specifically designed to harness the power of cloud computing to perform complex analysis pipelines on large biological datasets. CloudConductor was designed with five central features in mind: scalability, modularity, parallelism, reproducibility and platform agnosticism.

We demonstrate the processing power afforded by CloudConductor on a real-world genomics problem. Using CloudConductor, we processed and analyzed 101 whole genome tumor-normal paired samples from Burkitt lymphoma subtypes to identify novel genomic alterations. We identified a total of 72 driver genes associated with the disease. Somatic events were identified in both coding and non-coding regions of nearly all driver genes, notably in genes IGLL5, BACH2, SIN3A, and DNMT1. We have developed the analysis framework by implementing a graphical user interface, a back-end database system, a data loader and a workflow management system.

In this thesis, we develop the concepts and describe an implementation of automated cloud-based infrastructure to analyze genomics data, creating a fast and efficient analysis resource for genomics researchers.

Controlled breathing techniques are widely used to help people manage pain, and there is growing interest in using these approaches during painful outpatient medical procedures. The outpatient MRI-guided breast biopsy is one setting where patients may particularly benefit from breathing interventions for pain. To date, however, no studies have examined interventions for pain reduction in this setting. This randomized controlled pilot study assessed the feasibility, acceptability, and efficacy of a novel audio-recorded controlled breathing intervention for reducing breast and body pain in women undergoing MRI-guided breast biopsy. Fifty-eight women undergoing MRI-guided breast biopsy were randomized to a 1) controlled breathing intervention or 2) usual care condition. Assessments of pain, anxiety, distraction from pain, relaxation, blood pressure, heart rate, pain catastrophizing, and self-efficacy for managing pain and anxiety were administered. Participants were assessed at baseline, during biopsy, immediately post-biopsy, and 24 hours post-biopsy. Results demonstrated that the intervention was feasible and acceptable. However, when compared to usual care, controlled breathing did not significantly reduce pain, increase distraction from pain or relaxation during biopsy, decrease physiological reactivity, reduce pain catastrophizing, or increase self-efficacy for pain and anxiety from pre- to post-biopsy. These findings could be used to revise the controlled breathing intervention.

Purpose: Ensuring that tumor motion is within the radiation field for high-dose and high-precision radiosurgery in areas greatly influenced by respiratory motion. Therefore tracking the target or gating the radiation beam by using real-time imaging and surrogate motion monitoring methods are employed. However, these methods cannot be used to depict the effect of respiratory motion on tumor deviation. Therefore, an investigation of parameters for method predicting the tumor motion induced by respiratory motion multiple steps ahead of real time is performed. Currently, algorithms exist to make predictions about future real-time events, however these methods are tedious or unable to predict far enough in advance.

Methods and Materials: The algorithm takes data collected from the Varian RPM$ System, which is a one-dimensional (1D) surrogate signal of amplitude versus time. After the 1D surrogate signal is obtained, the algorithm determines on average what an approximate respiratory cycle is over the entire signal using a rising edge function. The signal is further dividing it into three components: (a) training component is the core portion of the data set which is further divided into subcomponents of length equal to the input component; (b) input component serves as the parameter searched for throughout the training component, (c) analysis component used as a validation against the prediction. The prediction algorithm consists of three major steps: (1) extracting top-ranked subcomponents from training component which best-match the input component; (2) calculating weighting factors from these best-matched subcomponents; (3) collecting the proceeding optimal subcomponent and fusing them with assigned weighting factors to form prediction. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation and root mean square error (RMSE) between prediction and known output.

Results: Respiratory motion data was simulated for 30 cases and 555 patients and phantoms using the RPM system. Simulations were used to optimize prediction algorithm parameters. The simulation cases were used to determine optimal filters for smoothing and number of top-ranked subcomponents to determine optimal subcomponents for prediction. Summed difference results in a value of 0.4770 for the 15 Point Savitzky-Golay filter.

After determining the proper filter for data preprocessing the number of required top-ranked subcomponents for each method was determine. Equal Weighting has a maximum average correlation, c=0.997 when using 1 Subcomponent, Relative Weighting has a maximum average correlation, c=0.997 when using 2 Subcomponents, Pattern Weighting has a maximum average correlation c=0.915 when using 1 subcomponent, Derivative Equal Weighting has a maximum average correlation c=0.976 when using 2 Subcomponents, and Derivative Relative Weighting has a maximum average correlation of c=0.976 when using 5 Subcomponents.

The correlation coefficient and RMSE of prediction versus analysis component distributions demonstrate an improvement during optimization for simulations. This is true for both the full and half cycle prediction. However, when moving to the clinical data the distribution of prediction data, both correlation coefficient and RMSE, there is not an improvement as the optimization occurs. Therefore, a comparison of the clinical data using the 5 Pt moving filter and arbitrarily chosen number of subcomponents was performed. In the clinical data, average correlation coefficient between prediction and analysis component 0.721+/-0.390, 0.727+/-0.383, 0.535+/-0.454, 0.725+/-0.397, and 0.725+/-0.398 for full respiratory cycle prediction and 0.789+/-0.398, 0.800+/-0.385, 0.426+/-0.562, 0.784+/-0.389, and 0.784+/-0.389 for half respiratory cycle prediction for equal weighting, relative weighting, pattern, derivative equal and derivative relative weighting methods, respectively. Additionally, the clinical data average RMSE between prediction and analysis component 0.196+/-0.174, 0.189+/-0.161, 0.302+/-0.162, 0.200+/-0.169, and 0.202+/-0.181 for full respiratory cycle prediction and 0.155+/-0.171, 0.149+/-0.138, 0.528+/-0.179, 0.174+/-0.150, and 0.173+/-0.149 for half respiratory cycle prediction for equal weighting, relative weighting, pattern, derivative equal and derivative relative weighting methods, respectively. The half cycle prediction displays higher accuracy over the full cycle prediction. Wilcoxon signed-rank test reveals statistically highly significant values (p<0.1%) for 4 out of 5 algorithms favoring the half cycle prediction (Equal, Relative, Derivative Equal, and Derivative Relative Weighting Methods). In this method, the relative weighting method has the most correlations coefficients with values greater than 0.9 and also yields the largest number of highest correlations over other prediction methods.

Conclusions: In conclusion, the number of subcomponents used for prediction may be better determined based on individual breathing pattern. The prediction accuracy using patient data is better using half cycle prediction over full cycle prediction for all algorithms for the majority of methods tested. Finally, relative weighting method performed better than other methods.

An estimated 10% of people worldwide have an enteric nervous system (ENS) related illness including irritable bowel syndrome (IBS), diabetes, colorectal cancer, fecal incontinence, and chronic constipation or diarrhea. Current drug treatments have severe side effects and often do not adequately address symptoms; a new approach is needed. ENS stimulation is a promising therapy for these patients, but a major limitation to this approach is our lack of knowledge. The human ENS is comprised of 5 million neurons and drives the digestive system, but its normal function and connections to the central nervous system (CNS) remain poorly understood. One of the major canonical signaling pathways between the ENS and the CNS is the vagus nerve, but the neural circuits involved are still under investigation. Better understanding of these circuits would provide a potential method of treatment for ENS related illness, with neurostimulation serving as an alternative to pharmaceutical treatments. Herein I describe a project which addresses these needs via development of new imaging tools to better understand the gut-brain axis, as well as demonstrating its utility as a target for treatment of gastrointestinal (GI) illness, specifically cancer-associated cachexia. Leaders in enteric neuroscience note that the continued inconsistencies in GI electrotherapies are driven by a fundamental lack of understanding of gut innervation and circuitry. New tools to directly observe colonic innervation and neuronal response, as well as a map of the whole peripheral nervous system, will reveal crucial targets for stimulation and enable more efficient targeting selection for neurostimulation or other local interventions, which will reduce off target effects and improve efficacy. To address these issues, I have developed an intravital window for direct imaging of the colon, enabling observation of colonic ENS response to stimulation in vivo for the first time. Additionally, I have developed an embryonic window, allowing visualization of embryonic GI development from E9.5 through birth. Finally, I have generated a mouse peripheral nerve map based on Diffusion Tensor Magnetic Resonance Imaging (DT MRI). Using novel scan parameters and post-processing algorithms, I identified nerve fibers throughout the body and generated quantitative tractography which specifically highlights GI innervation via the vagus nerve. Cachexia is a multi-systemic syndrome which produces weight loss, muscle atrophy, adipose wasting, fatigue, and anorexia. Affecting an estimated 1% of the global population and up to 80% of all cancer patients, cachexia is fatal in roughly 30% of cases and is incurable. Cancer-associated cachexia (CAC) is particularly devastating as in addition to resulting in decreased quality of life, CAC reduces tolerance and efficacy of cancer treatments and higher overall mortality. As many as half of all cancer deaths are attributed to CAC. There are currently no clinically meaningful treatments for CAC, despite attempts to employ dietary support, physical therapy, anti-inflammatory medication, appetite stimulants, and other supportive therapies. Herein I describe potential therapeutic approach for treatment of CAC via vagal perturbation – either by vagotomy or ultra-low frequency vagal block with an implanted stimulator. This intervention significantly attenuates weight loss, skeletal muscle atrophy, anorexia, urea cycle dysregulation, and circulating inflammatory cytokine elevation. Most importantly, it increases survival time in mice injected with tumor cells, suggesting this could be a clinically meaningful approach for treatment of CAC.

Current standard cancer treatments such as chemotherapeutics, and radiation therapy are nearly as likely to kill the patient as cure the cancer. Therapies that have such a narrow window of efficacy are necessary for the treatment of aggressive diseases, but safer alternatives must be created. By discovering novel therapeutics that target specific disease processes within specific diseased cells, while leaving healthy cells unaltered, we can improve the lives of millions of cancer sufferers and their families. A therapeutic's window of efficacy can be measured by the therapeutic index. For many anti-cancer therapeutics, the therapeutic index is very small, the dose of treatment that kills cancer cells and shrinks tumors is nearly the dose that causes toxicity. In cancer patients, this toxicity causes many serious conditions such as gastrointestinal distress, organ damage, and death.

Recently, the model of cancer treatment has evolved from non-specific cytotoxic agents to more selective therapeutics that target cellular processes necessary for cancer cell survival. If a therapy can be targeted to selectively bind and internalize targeted cells, its toxicity would only impact the targeted cells and healthy cells in the immediate vicinity, which would greatly reduce the toxic effects on the rest of the body. Targeting cancer cells can be done through cancer biomarkers, which are cell surface proteins, expressed exclusively, or are much more abundant on the surface of cancer cells than on somatic cells.

Advances in antibody and aptamer technology have enabled researchers to design those molecules to bind specifically to cancer cells, and deliver drugs that alter specific cellular processes. An aptamer designed to bind PSMA, a prostate cancer biomarker, only bound to a specific subset of cancer cells, and delivered a therapeutic siRNA that prevented a specific survival process from occurring. While this technology is promising, it is currently limited to targeting small subsets of cancer types. To generate an aptamer therapeutic that would have greater utility and efficacy, I have examined the properties of a nucleolin aptamer-mediated delivery system that targets multiple types of cancer cells, and delivers various oligonucleotide therapeutics.

The nucleolin aptamer targeted cancer cells by binding to membrane–associated nucleolin. Nucleolin, a conserved protein found in all eukaryotes, shuttles from the nucleus, through the cytoplasm to the cell membrane. Cancer cells express a far greater amount of membrane–associated nucleolin than somatic cells, making nucleolin an ideal cancer biomarker. The shuttling, and oligonucleotide binding attributes of the protein enable it to deliver aptamer chimeras from the cell surface to the nucleus. Therefore the nucleolin aptamer has unique access to the nuclei of cancer cells, and can deliver therapeutic oligonucleotide cargoes through nucleolin binding.

The nucleolin aptamer delivered splice–switching oligonucleotides, a form of antisense technology, improving their efficacy, and potentially increasing their therapeutic viability. The ability to deliver antisense oligonucleotides to the nuclei of cancer cells has the potential for other therapeutic possibilities including the inhibition of transcription with antisense triplexes.

The nucleolin aptamer can also deliver therapeutic aptamers. The nucleolin aptamer–β–arrestin aptamer chimera prevented the stem cell renewal phenotype necessary for leukemia progression in human patient tissue samples. The ability to effectively deliver therapeutic aptamers may lead to clinical applications for many of the aptamers that have been selected against intracellular targets including transcriptional activators.

Oligonucleotide research continues to advance our understanding of potentially therapeutic oligonucleotides. Long non–coding RNAs for example, may impact epigenetics, and transcription. Additionally, locked nucleic acids have been developed to improve binding affinity, thus increasing the efficacy of antisense oligonucleotides. In order to bring these discoveries into the clinic, they must be safely and specifically delivered to their target cells.

This work demonstrated that the nucleolin aptamer could deliver oligonucleotide therapeutics to specific cancer cells. Nucleolin aptamer chimeras have the potential to develop into safe and effective cancer therapies, thus improving the treatment options for cancer sufferers.

Background: The Cataldo Cancer Stigma Scale (CASS) was developed to measure patient experienced and perceived stigma and was further modified for use in the pediatric patient population. This study aimed to adapt and translate a Swahili version of the CASS for use in the Tanzanian pediatric patient population to measure cancer stigma and identify the types of stigma pediatric cancer patients face. Methods: Approximately 40 items were extracted from two prior developmental and validation studies of the CASS that assessed stigma in adult patients and non-patient cohorts. The survey items, developed initially in English, underwent translation into Swahili, back-translated, reconciled, and screened for duplications. The translated items were refined using concurrent cognitive interviewing. Results: After three rounds of cognitive interviews with 15 respondents, comprehension of the survey questions was assessed and improved with all items reaching at least 80% comprehension. Additional reviews included grammar and specific Swahili word selection changes to clarify the question’s meaning. Duplications or repetition of sentences were also considered to remove questions from the survey. The final survey comprised 25 survey items with 7 stigma sub-categories. Conclusions: This study sheds light on the complex nature of cancer-related stigma in pediatric patients. For future purposes, research is needed to validate the CASS survey with a larger sample of the population, including a comparison stigma assessment to establish validity.

Antivascular targeting is a promising strategy for tumor therapy. This strategy overcomes many of the transport barriers and has shown efficacy in many preclinical models, but targeting epitopes on tumor vasculature can also promote accumulation in healthy tissues. We used Elastin-like Polypeptide (ELP) to form block copolymers (BCs) consisting of two separate ELP blocks seamlessly fused at the genetic level. ELPBCs self-assemble into spherical micelles at a critical micelle temperature (CMT), allowing external control over monovalent unimer and multivalent micelle forms. We hypothesized that thermal self-assembly could trigger specific binding of ligand-ELPBC to target receptors via the multivalency effect as a method to spatially restrict high-avidity interactions. We termed this approach Dynamic Affinity Modulation (DAM). The objectives of this study were to design, identify, and evaluate protein-based drug carriers that specifically bind to target receptors through static or dynamic multivalent ligand presentation.

ELPBCs were modified to include a low-affinity GRGDS or GNGRG ligand and a unique conjugation site for hydrophobic compounds. This addition did not disrupt micelle self-assembly and facilitated thermally-controlled multivalency. The ability of ligand-ELPBC to specifically interact with isolated AvB3 or CD13 was tested using an in vitro binding assay incorporating an engineered cell line. RGD-ELPBC promoted specific receptor binding in response to multivalent presentation but NGR-ELPBC did not. Enhanced binding with multivalent presentation was also observed only with constructs exhibiting CMT < body temperature. This study establishes proof-of-principle of DAM, but ELPBC requires thermal optimization for use with applied hyperthermia. Static affinity targeting of fluorescent ligand-ELPBC was then analyzed in vivo using intravital microscopy (IM), immunohistochemistry (IHC), and custom image processing algorithms. IM showed increased accumulation of NGR-ELPBC in tumor tissue relative to normal tissue while RGD-ELPBC and non-ligand ELPBC did not, and IHC verified these observations. This study shows (1) multivalent NGR presentation is suitable for static multivalent targeting of tumors and tumor vasculature, (2) multivalent RGD presentation may be suitable for DAM with thermal optimization, and (3) ELPBC micelles may selectively target proteins at the tumor margin.

Three-dimensional (3D) tumor models aim to reduce the need for animal models for drug and gene delivery studies. However, many models are not conducive to environmental manipulation and may not be easily adapted for in situ microscopic analysis of transport phenomena. One goal of this study was to develop a 3D tumor model that can mimic 3D cell-cell interactions to mimic native tumor tissues.

To this end, a novel 3D microfluidics-based tumor model was created which allowed the overnight culture of a high density of tumor cells and could be used for small molecule penetration studies. This microfluidic device facilitated the loading of B16.F10 tumor cells in a densely-packed three-dimensional arrangement in a micro-channel which was accessible for nutrient supply via channels on either side through which culture media was continuously infused. Cell volume fraction in the micro-channel was determined via nuclear staining and counting of cells immediately after loading and after a 12-hr culture period. The average volume fraction of cells in this model was 0.32 immediately after loading and 0.26 after 12-hr culture. The values are comparable to cell volume fractions of the in vivo B16.F10 tumor previously measured in our lab. The reduction in cell volume fraction after overnight culture was due to the change in cell morphology to become more elongated after time in culture. Cell-cell adhesions appeared to have formed during culture, resulting in more uniform packing.

Sodium fluorescein dye was used as a drug analog and the extent of penetration of this fluorescent molecule through the cell compartment was assessed through microscopy. The dye was introduced on one side of the cell micro-channel and fluorescence images were captured for generation of concentration profiles in the cell compartment. Results showed that dye penetration through the cell chamber was greatly limited by the presence of the 3D cell culture and a linear concentration profile was achieved across the cell compartment. Also, the concentration of sodium fluorescein in the cell compartment of the 12-hr microfluidic cell culture was appreciably lower than the concentration in the cell compartment when the dye was introduced immediately after loading cells. These results suggest that the proposed tumor model shows significant resistance to dye penetration and could prove to be extremely useful for mimicking tumor tissue resistance to drug penetration via diffusion.

There are many barriers to gene delivery to tumors which highlight the importance of selecting an effective gene carrier system. Some pathogenic bacteria have been investigated as gene delivery vectors because of their innate ability to selectively proliferate in tumor environments. However, pathogenicity concerns arise when trying to achieve therapeutic levels of gene expression. It has been shown that non-pathogenic bacteria such as E. coli can be engineered to invade mammalian cells and participate as gene delivery vehicles. Hence, the second part of this research project involved the use of the newly developed microfluidic 3D tumor model previously described to visualize the transport behavior of invasive (inv+) and non-invasive (inv-) E. coli. The inv+ bacteria harbored a plasmid containing the inv gene encoding the protein invasin that binds to &beta₁ integrin receptors on the surface of mammalian cells resulting in the phagocytosis of invasin-expressing bacteria by normally non-phaogcytotic cells. Two tumor cells lines were used: B16.F10 and EMT6, which have been shown to differ in expression of &beta₁ integrins. The bacteria were also engineered to express mCherry for fluorescent detection.

A suspension of tumor cells and bacteria was loaded into the microfluidic device and cultured for 12 hrs before imaging bacteria distribution throughout the cell culture. Proliferation of inv+ bacteria was generally uniform throughout the cell compartment in the B16.F10 model and bacterial cells were primarily concentrated outside of cells. Bacteria that were internalized did not appear to migrate far from the plasma membrane of the tumor cell. The non-invasive bacteria proliferated to a much greater extent than the invasive form and this proliferation was also generally uniform throughout the cell compartment. Proliferation of both invasive and non-invasive bacteria in the EMT6 model was less uniform than in the B16.F10 model. Overall bacterial concentration appeared to be lower in the EMT6 model. Viability staining after bacterial infection showed that tumor cells in the 3D model were able to maintain viability despite bacterial cell proliferation.

An additional assay was conducted in culture plate wells to determine the effect of chemical factors secreted by tumor cells on bacterial cell proliferation. The results of this assay revealed that tumor cells may be secreting anti-microbial factors that inhibit the proliferation of bacteria and that the binding of invasin-expressing E. coli to tumor cells may further promote the release of these factors.

The results of this study suggest that tumor cell type plays a major role in the distribution and proliferation of bacteria in a 3D environment. The ability to visualize bacterial spread throughout a 3D tumor model will prove to be useful for observing the effect of various genetic modifications on the transport and gene delivery efficiency of E. coli.

Dendritic cells (DC) have been the key elements in developing cancer vaccines to induce potent T cell responses to eradicate tumors. However, the common approach adopted in clinical trials using ex vivo generated DC loaded with tumor antigens (Ag) has been challenged by its limited clinical response, complexity, and quality of the manufacturing process. Alternative efforts focused on in vivo Ag loading on endogenous primary DC have not yet been well validated in their efficacy for cancer treatment, suggesting the efficiency of in vivo Ag transfer to endogenous DC from currently available Ag-delivering vehicles needs to be further improved. Here, I aim to develop an alternative cellular vaccine platform that can circumvent the aforementioned problems. I reason that classical Ly-6Chi monocytes (i.e. monocytes hereafter) can be a promising candidate to be loaded with tumor Ag and induce effective T cell responses. With advantages including easy-purification from human peripheral blood, monocytes evidently can present antigens directly via in vivo differentiation into bona fide DC or indirectly via antigen transfer to lymphoid resident DC to induce strong Th1 or cytotoxic T lymphocyte (CTL) responses. However, whether monocytes exploit favorably direct or indirect pathway to present the same Ag they are carrying to trigger effective immune responses remains unclear. Furthermore, how exactly monocytes or monocyte-derived cells transfer antigens to lymphoid resident DC has yet to be elucidated. I hypothesized that Ag-loaded monocytes can induce strong anti-tumor immunity and began the research by investigating the immune responses that can be induced by Ag-loaded monocytes. I then went on to determine the mechanisms that mediate monocyte-induced immune responses and evaluate anti-tumor efficacy of this monocyte vaccine.

In the first part of this study, I characterized the immune responses induced by Ag-loaded monocytes. By using negative selection via magnetic-activated cell sorting (MACS) columns, I was able to purify monocytes from bone marrow (BM) cells and determined that these monocytes could be successfully loaded with Ag in the forms of proteins, peptides and mRNA. I found that intravenously (IV) injected Ag-loaded monocytes induced robust Ag-specific CD4+ and CD8+ T cell responses in mice without triggering antibody responses. This vaccine activity of Ag-loaded monocytes appeared to be dose-dependent and required live monocytes with no need of ex vivo stimulation. I found that Ag-specific CD8+ T cells induced by Ag-loaded monocytes were functionally more robust than those induced by protein Ag emulsified in a traditional adjuvant CFA.

In the second part of this study, I investigated how IV injected Ag-loaded monocytes stimulate T cell responses. I identified that the spleen is the primary immune niche for Ag-loaded monocytes to induce T cell responses. I found that Ag-loaded monocytes mainly retain in the spleen where they begin to differentiate into phenotypic DC. Surprisingly, major histocompatibility complex (MHC)-deficient monocytes maintain full capacity to stimulate T cell responses, suggesting that Ag-loaded monocytes do not present Ag by themselves. I determined that endogenous splenic DC is absolutely required for monocyte-induced T cell responses. Therefore, Ag-loaded monocytes induce T cell responses indirectly via transferring Ag to splenic DC even they do differentiate into phenotypic DC in the spleen. I elucidated that this monocyte-to-DC Ag transfer occurs via gap junctions for CD8+ T cell responses and via macrophages for CD4+ T cell responses.

In the final part of this study, I demonstrated that IV injected Ag-loaded monocytes have robust anti-tumor efficacy targeting both model and validated tumor Ag in prophylactic, memory and therapeutic murine SQ melanoma models. The anti-tumor efficacy is superior to that seen with traditional adjuvants or RNA-pulsed DC vaccines, and can be combined with checkpoint blockade to increase their efficacy. Furthermore, I demonstrated that Ag-loaded monocytes have a clear anti-tumor efficacy in an intracranial glioblastoma (GBM) model targeting against mutant isocitrate dehydrogenase 1-R132H (mIDH1-R132H), a validated tumor Ag of GBM.

In conclusion, IV injection of unactivated Ag-loaded monocytes without adjuvants induces highly efficacious anti-tumor T cell responses via dual independent and efficient Ag transfer pathways to splenic DC. These findings revise the paradigm that monocytes have to be activated ex vivo to achieve optimal vaccine efficacy and reveal unappreciated cell-associated Ag acquiring pathways of splenic DCs that can be specifically manipulated for future vaccine design in the treatment of human cancers.

Fluorescence Activated Cell Sorting (FACS) and Magnetic Activated Cell Sorting (MACS) are two essential tools for cell separation in research and medicine. Antibodies, the gold standard in both of these methods, are effective ligands for cell-surface biomarkers, but their irreversible binding precludes a wide variety of downstream medical and experimental applications. Aptamers – nucleic acid ligands with a defined three-dimensional structure that enables them to bind a molecular target with a high degree of specificity – offer a viable alternative for this particular obstacle because their RNA- or DNA-based chemistry enables their removal from cellular targets. In these studies, we present examples of successful sorting of cells and removal of the targeting aptamers with MACS and FACS using both the previously-published antisense-based method of post-sorting aptamer removal and a more general approach using nuclease-based digestion of targeting aptamers on the cell surface after cell isolation. We believe this work can be used in a number of potential post-sorting applications where targeting ligands or attached magnetic or fluorescent moieties could interfere with experimental or clinical results.

Tissue homeostasis is controlled by the availability of growth factors, which sustain exogenous nutrient uptake and prevent apoptosis. Cancer cells, however, can express constitutively active oncogenic kinases such as BCR-Abl that promote these processes independent of extrinsic growth factors. When cells are deprived sufficient growth signals or when oncogenic kinases are inhibited, glucose metabolism decreases and cells activate the self-digestive process of autophagy, which clears damaged organelles and provides degradation products as an alternate fuel to support mitochondrial metabolism. Importantly, loss of growth signals can also lead to apoptosis mediated through Bcl-2 family proteins, and Bcl-2 has been reported to interfere with autophagy, potentially disrupting a key nutrient source just as glucose uptake becomes limiting. Since autophagy may support survival or lead to death depending on context, the role of this pathway in apoptosis-competent growth factor deprived cells remains unclear.

In this thesis, I examine the interactions of autophagy with Bcl-2 family proteins and apoptosis upon inhibition of growth signals in hematopoietic cells. In contrast to other studies, I found autophagy was rapidly induced in growth factor deprived cells regardless of Bcl-2 or Bcl-xL expression, and this led to increased production of fatty acids and amino acids for metabolism. While these data suggested autophagy may play a key role to support metabolism of growth factor deprived cells, provision of exogenous pyruvate or lipids as alternate fuel had little affect on cell survival. Instead, I found that autophagy modulated cell stress pathways and Bcl-2 family protein expression in a context specific fashion to impact cell fate.

My results show that autophagy's effect on cell survival is dependent on its level of induction within a cell. I observed that partial suppression of autophagy protects cells from stress and induction of pro-apoptotic Bcl-2 family expression, while complete inhibition of autophagy enhances stress and is pro-apoptotic. In experiments using shRNAi to partially suppress autophagy, I found increased survival upon growth factor deprivation in several different types of cells expressing anti-apoptotic Bcl-2 or Bcl-xL, indicating that autophagy promoted cell death in these instances. Cell death was not autophagic, but apoptotic, and relied on direct Chop-dependent transcriptional induction of the pro-apoptotic Bcl-2 family protein Bim. In contrast, complete acute disruption of autophagy through conditional Cre-mediated excision of the autophagy-essential gene Atg3 led to p53 phosphorylation, upregulation of p21 and the pro-apoptotic Bcl-2 family protein Puma, and rapid cell death of cells the presence or absence of growth factor. Importantly, transformed BCR-Abl-expressing cells had low basal levels of autophagy but were highly dependent on this process. Deletion of Atg3 or treatment with chemical autophagy inhibitors led to rapid apoptosis, and BCR-Abl expressing cells were unable to form leukemia in mice in without autophagy. Together, my data demonstrate a dual role for autophagy in cell survival or cell death and suggest that the level of autophagy in a cell is critical in determining its role in apoptosis and cell fate. Ultimately, these results may help to determine future approaches to modulate autophagy in cancer therapy.

The bone morphogenetic protein (BMP) signaling pathways have important roles in embryonic development and homeostasis. BMPs have been shown to pattern the dorsoventral axis in zebrafish (Danio rerio) early during embryonic development by establishing a dorsal-to-­ventral ligand gradient. During tumorigenesis, BMPs primarily function as tumor promoters, as an increase in BMP expression is associated with an increase in invasion, migration, epithelial-­to-­mesenchymal transition (EMT), proliferation and angiogenesis.

Although it is clear that BMPs play multiple roles in these biological events, the precise mechanism by which BMPs mediate these functions is not fully understood. Canonically, BMP ligands signal through cell surface receptor complexes that phosphorylate transcription factors, Smad1, Smad5 and Smad8, which mediate BMP-­ specific gene transcription. While studying BMP signaling during cancer progression, we determined that BMPs unexpectedly signal through the canonical TGF-β-­responsive transcription factors, Smad2 and Smad3.

We determined that BMP-­induced Smad2/3 signaling occurs preferentially in embryonic cells and transformed cells. BMPs signal to Smad2/3 by stimulating complex formation between the BMP binding TGF-­β superfamily receptors, ALK3/6, and the Smad2/3 phosphorylating receptors, ALK5/7. BMP signaling through Smad1/5/8 induces MET, while Smad1/5 and Smad2 mediate dorsoventral axis patterning in zebrafish embryos and Smad3 facilitates invasion.

Taken together, our data provides evidence that BMP-­induced Smad2 and Smad3 phosphorylation occurs through a non-­canonical signaling mechanism to mediate multiple biological events. Thus, the signaling mechanisms utilized by BMPs and TGF-­β superfamily receptors are broader than previously appreciated.

Glioblastoma (GBM) is the most common and deadly primary malignant brain tumor. Despite an aggressive multimodal standard of care, prognoses and patient quality of life remain exceptionally poor, due in part to the non-specific and toxic nature of conventional treatment options. By contrast, adoptive cell transfer of T cells genetically modified to express tumor-specific chimeric antigen receptors (CARs) has emerged as a promising approach to targeting brain tumors, given that T cells have migratory capacity within the brain parenchyma, a mechanism to discriminate between normal and neoplastic tissue, and can develop immunological memory. This work spans the development of an effective CAR T-cell immunotherapy strategy targeting the tumor-specific driver mutation, EGFRvIII, which is expressed exclusively by GBM and other cancers but not normal tissue.

Chapters 1 and 2 provide an overview of GBM and the current clinical standard of care, the role of the immune system as it relates to the development and eradication of cancer, and an introduction to various immunotherapy platforms under active preclinical and clinical investigation. Chapter 3 details the historical context of adoptive T-cell immunotherapy and its evolution to present day, detailing our early proof-of-principle studies that led to the inception of the original research described herein. Data presented in Chapter 4 summarizes our translational objectives in implementing CAR T-cell immunotherapy clinically for patients with newly-diagnosed GBM. Chapter 5 addresses a perennial limitation to the immunotherapy of solid tumors by demonstrating an ability of modified CARs to circumvent intratumoral immunosuppression mediated by regulatory T cells. In Chapter 6, we present data that demonstrate, for the first time, a novel role for host lymphodepletion in cellular immunotherapy delivered directly into the brain. Lastly, Chapter 7 contains concluding remarks on the current state of CAR technology and important future directions.

In summary, our work here demonstrates that CAR T cell immunotherapy 1) has curative potential against highly established, orthotopic and syngeneic murine GBM, 2) can be strategically implemented within the current clinical treatment paradigm for GBM, and 3) can overcome a major mechanism of immunosuppression, demonstrating the versatility of gene-modified T cells for the treatment of malignant brain tumors. Together, these studies have paved way for the rationale design of two phase I clinical trials in patients with newly-diagnosed and recurrent EGFRvIII-positive GBM at Duke University.

In this dissertation, I reported several cellular reprogramming mechanisms in response to different factors, such as viral infection and oncogenic transformation, by utilizing molecular biology and high-throughput sequencing tools. In the first part of the dissertation, I investigated how hepatocytes contain HBV replication and promote their own survival by orchestrating a translational defense mechanism via the stress-sensitive SUMO-2/3-specific peptidase SENP3. We found that SENP3 expression level decreased in HBV-infected hepatocytes in various models including HepG2-NTCP cell lines and a humanized mouse model. Downregulation of SENP3 reduced HBV replication and boosted host protein translation. We also discovered that IQGAP2, a Ras GTPase-activating-like protein, is a key substrate for SENP3-mediated de-SUMOylation. Downregulation of SENP3 in HBV infected cells facilitated IQGAP2 SUMOylation and degradation, which leads to suppression of HBV gene expression and restoration of global translation of host genes via modulation of AKT phosphorylation. In the second part, I showed that, in Kras-mutant alveolar type II cells (AEC2), FOSL1-based AP-1 factor guides mSWI/SNF complex to increase chromatin accessibility at genomic loci controlling the expression of genes necessary for neoplastic transformation. I identified two orthogonal processes in Kras-mutant distal airway club cells. The first process was step-like in behavior and promoted their trans-differentiation into an AEC2-like state through NKX2.1. The second was linear and controlled oncogenic transformation through the AP-1 complex. Our results suggest that the chromatin state of the cell influences its response to oncogenic Kras. Other than the cell-type-specific effects, a cross-tissue conserved AP-1-dependent chromatin remodeling program regulates carcinogenesis.

Heat Shock transcription Factor 1 (HSF1) has long been recognized as the master regulator and signal integrator in the eukaryotic proteotoxic stress response. Revealed by recent discoveries in cancer, the functions of HSF1 have extended far beyond its canonical role in protein folding, further encompassing critical functions in anti-apoptosis, invasion and metastasis, energy metabolism, DNA damage repair, and evasion of host immune surveillance. Meanwhile, both our understanding of the molecular basis of HSF1 regulation as well as available biochemical tools to investigate such details are lacking. Based on an in vitro ligand binding approach, the studies presented in this thesis were dedicated to the identification, validation, and characterization of a direct, first-in-class, small-molecule HSF1 inhibitor. The pharmacological inhibition of HSF1 occurs through small-molecule stimulation of nuclear, but not cytoplasmic HSF1 degradation, which attenuated prostate cancer cell proliferation, inhibited the HSF1 cancer gene signature and arrested tumor progression in multiple therapy-resistant animal models of prostate cancer. The identification of a direct small-molecule HSF1 inhibitor provides a unique pharmacological tool for future HSF1 research and serves as a significant proof-of-concept for pharmacologically targeting HSF1 for anti-cancer treatment approaches.