Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Integrative pharmacogenomic approaches to study and overcome drug resistance in cancer

Wang, Yue (2023) Integrative pharmacogenomic approaches to study and overcome drug resistance in cancer. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

[img] PDF (ETD)
Updated Version
Restricted to University of Pittsburgh users only until 9 May 2025.

Download (10MB) | Request a Copy

Abstract

Drug resistance is a major challenge in obtaining durable and long-lasting responses in either chemo-/targeted therapies or immunotherapies in cancer. For decades, great efforts have been made to address two essential questions: (1) what makes drug resistance, and (2) how to overcome drug resistance. In this thesis, we integrated multi-dimensional pharmacogenomic data from cancer cell lines and patients to systematically identify novel master regulators that contribute to chemo-/immunotherapy resistance (Chapter 2 and Chapter 3), as well as chemo-immunotherapy synergisms to overcome immunotherapy resistance (Chapter 4). Specifically, in Chapter 2, we established a knowledgebase of long non-coding RNAs (lncRNAs) associated with multi-drug resistance through integrating expression profile of 11,950 lncRNAs and response profile of 265 anti-cancer drugs in 1,005 cancer cell lines. We identified a novel lncRNA named ERINA, who is an estrogen responsive oncogenic lncRNA, can regulate multi-drug resistance and is associated with poor survival of estrogen receptor positive breast cancer patients. In Chapter 3, through an integrative analysis of lncRNA expression and tumor immune response in 9,626 tumor samples across 32 cancer types, we developed a lncRNA-based immune response (LIMER) score that can predict the immune cells infiltration and patient prognosis in multiple cancer types. By further integrating the lncRNA DNA methylation data, we identified tumor-specific lncRNAs that can potentially regulate tumor immune response in multiple cancer types. We validated that lncRNA EPIC1 can induce tumor immune evasion and immunotherapy resistance by suppressing tumor cell antigen presentation and interferon signaling. In Chapter 4, we integrated the expression profiles from patients received immunotherapy and half million post-treatment cancer cell line expression profiles, through which we characterized the first comprehensive landscape and mechanism for chemo-immunotherapy synergism. We validated a P21-activated kinase inhibitor (PAKi) and showed the compound can synergize with anti-PD-1 treatment via inducing mitophagy, which triggers the tumor secretion of CXCL10 through a mitochondrial double strand RNA and type I interferon dependent mechanism. Together, these three studies presented in this thesis will facilitate the ongoing pre-clinical efforts on establishing strategies to reverse chemotherapy and immunotherapy resistance.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Wang, Yueyuw90@pitt.eduyuw90
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairLi, Ssol4@pitt.eduSOL4
Committee MemberXie, Wwex6@pitt.eduWEX6
Committee MemberLu, Bbinfeng.lu@hmh-cdi.orgBINFENG
Committee MemberZhang, Mmiz45@pitt.eduMIZ45
Committee MemberLi, Bbo.li@utsouthwestern.edu
Date: 9 May 2023
Date Type: Publication
Defense Date: 18 January 2023
Approval Date: 9 May 2023
Submission Date: 27 March 2023
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 181
Institution: University of Pittsburgh
Schools and Programs: School of Pharmacy > Pharmaceutical Sciences
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Chemoimmunotherapy Drug resistance Pharmacogenomics Computational Modeling Cancer genomics
Date Deposited: 09 May 2023 17:44
Last Modified: 09 May 2023 17:44
URI: http://d-scholarship.pitt.edu/id/eprint/44316

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item