Browsing by Subject "Drug resistance"

Epstein-Barr virus (EBV) is a ubiquitous human herpesvirus that infects over 95% of the adult population. While infection is typically asymptomatic, in some individuals, particularly the immunocompromised, EBV is the causative agent of several cancers including lymphomas and epithelial cancers. Specifically, gastric carcinoma, nasopharyngeal carcinoma, and lymphoepithelioma-like carcinoma which occurs across multiple sites in the body, most notably, in the lung. EBV-associated gastric cancer (EBVaGC) is a unique subset of gastric cancer that makes up 10% of all GCs worldwide. EBVaGCs display an 80% rate of activating PIK3CA mutation and are also the most hypermethylated of any tumor type, displaying what is known as a CpG island hypermethylator phenotype (CIMP). EBV infection of B cells can be easily modeled in vitro using primary B cells and lymphoblastoid cell lines (LCLs). However, epithelial cell infection models have proven much more difficult to develop. Given these difficulties, EBV infection and outgrowth in epithelial cells is comparatively understudied and the process of tumorigenesis in vivo is poorly understood. In this dissertation, I developed methods to generate EBV infected epithelial cell lines derived from both gastric cancer and lung adenocarcinoma using diverse strains of EBV. I used these models to complete a CRISPR/Cas9 whole genome knockout screen to identify cellular restriction factors of infection and outgrowth. Together, these data will provide novel insights into the process of EBV infection and the dynamic interplay between virus and host during tumorigenesis. Furthermore, I have used these models to explore unique therapeutic approaches for EBV+ epithelial cancers. Specifically, I have characterized the lytic reactivation potential to histone deacetylase (HDAC) inhibitors and generated preclinical data supporting the use of HDAC inhibitors and the anti-viral ganciclovir for treatment of EBV+ epithelial tumors. Lastly, I have identified modulators of the response to a PI3Ka inhibitor in PIK3CA mutant gastric cancers. I found that loss of NEDD9 or inhibition of BCL-XL rendered cells hyper-sensitive to the PI3Ka inhibitor BYL719. Additionally, I found that loss of CBFB conferred resistance to BYL719 through up- regulation of the protein kinase PIM1 and defined the clinical utility of our data in the context of PI3K inhibition more broadly. The work outlined in this dissertation contributes to the study of EBV infection and tumorigenesis in the stomach as well as provides mechanistic insights into novel therapeutic approaches for EBV+ epithelial cancers and PIK3CA mutant gastric cancers.

Background: Indonesia has one of the highest TB burdens in the world and is one of ten countries that accounted for 77% of the global gap between treatment enrollment and the estimated number of new cases of MDR/RR-TB in 2019. However, there are knowledge gaps about how the delay of MDR-TB treatment initiation might affect this situation. Therefore, this study aimed to examine challenges of implementing MDR-TB treatment initiation in a Programmatic Management of Drug-Resistant Tuberculosis (PMDT) national referral hospital in Indonesia. Method: This study used mixed methods to collect both quantitative data through hospital records of MDR-TB patients and qualitative data through interviews with patients and health workers. Result: The median time between diagnosis and treatment initiation was 26 days, and was associated with co-morbidities, MDR-TB knowledge, and support assessment. This study also revealed the complex situation of people affected with MDR-TB with lack of social support and health system challenges during the MDR-TB treatment initiation process. Conclusion: The results of this study revealed the challenges of the treatment initiation process from the complex perspectives of the patients, the aspects of the health system that need to be improved, and the importance of social support starting from diagnosis.

Targeted therapeutics are among the most promising approaches for treating diverse forms of malignancies. Indeed, as sequencing prices and technology continue to improve it will be possible to achieve a precise map of each individual cancer’s genomic lesions, providing insights into the best strategies for treatment. However, these approaches will be undermined by cancer’s ability to resist upfront target inhibition (intrinsic resistance) as well as, in cases where tumors are initially sensitive, develop resistance over the course of drug treatment (acquired resistance). The literature to date reveals a problem as complex as the tumor itself; the heterogeneity of cancer as a disease is matched by the myriad ways in which it evades treatment.

Understanding drug resistance as a whole quickly becomes a problem of scale. Not only is there cancer subtype-associated variation to consider, but also intrinsic and acquired resistance profiles can differ based on the type of inhibitor used and at what node the offending pathway is inhibited. Assigning proper treatments to account for these mechanisms adds an additional layer of complexity as the number of FDA-approved and late-stage clinical candidate molecules increases. Here, when applied appropriately, high throughput methods offer the ability to screen thousands of perturbations in parallel, quickly narrowing the search space for a phenotype of interest.

This work applies such methods to the cell-autonomous complexity of drug resistance and seeks to understand (1) mechanisms by which cancer cells evade drug treatment, (2) design concepts for the most effective combinatorial drugging strategies, and (3) how it might be possible to account for resistance-associated heterogeneity by targeting the evolutionary liabilities of resistant cells. Using a combination of open reading frame (ORF), clustered regularly spaced short palindromic repeats (CRISPR), and pharmacologic screening technologies, this work attains the resolution and throughput necessary to address 1-3 above and begins to unravel the complexity of drug resistance.

We have developed a broadly applicable platform that harnesses the power of protein engineering and genetic screening to produce efficacious protein-drug combinations for cancer therapy. For proof-of-concept, we implemented this strategy to engineer targeted pro-apoptotic drug combinations that overcome cancer resistance to protein agonists of death receptor 5 (DR5), a key upregulated marker in colorectal cancer (CRC). Over the past decade, various DR5 agonists have shown poor clinical efficacy, including both engineered antibodies and TRAIL, the natural ligand for this receptor. Comprehensive studies suggest that there are three major obstacles to success of these agents: 1) potency, 2) delivery, and 3) resistance.

We have systematically addressed these challenges by engineering a sustained-release formulation of a highly potent, hexavalent death receptor 5 agonist (DRA), and administering the agonist as a sustained release depot, in combination with rationally nominated targeted drugs that overcome intrinsic resistance to DRAs. To address the need for sustained delivery of therapeutic proteins, we developed injectable depots of DRAs recombinantly fused to thermally responsive elastin-like polypeptide (ELP) biopolymers. The bioactive ELP-DRA fusions undergo temperature-driven phase transition upon subcutaneous injection in vivo, resulting in the formation of a gel-like depot suitable for sustained drug delivery. A single 30 mg/kg injection of the gel-like ELP-DRA depot induced significant tumor regression in Colo205 mouse xenografts. To pinpoint the genetic drivers of CRC resistance to the DRA, we used a gain-of-function ORF screen and a CRISPR/Cas9 knockout screen. The screens identified genes that confer sensitivity to the DRA in resistant CRC cell lines. Over twenty small molecule drugs targeting pathways and proteins identified from the screens were then tested in combination with the DRA to identify highly synergistic combinations using cytotoxicity assays. Clonogenic, time-to-progression, and cell viability assays showed that pharmacological blockade of XIAP, Bcl-XL, and CDK4/6 strongly enhances antitumor activity of DRA in established human CRC cell lines and patient-derived CRC cells. In vivo tumor regression studies demonstrated the potent anti-tumor efficacy of combining inhibitors of XIAP and Bcl-XL with the sustained release formulation of ELP-DRA.

By addressing both delivery and resistance issues with our protein engineering and genomics platform, we have overcome the key obstacles to DRA translation as a successful drug in the clinic. Our rational approach elegantly provides optimal protein-small molecule drug combinations that elicit a robust anticancer response, exhibit minimal toxicity, and combat drug resistance.