Graduation Year

2016

Document Type

Thesis

Degree

M.S.B.E.

Degree Name

MS in Biomedical Engineering (M.S.B.E.)

Degree Granting Department

Chemical Engineering

Major Professor

Ariosto Silva, Ph.D.

Co-Major Professor

Robert Frisina, Jr., Ph.D.

Committee Member

William Lee III, Ph.D.

Keywords

cancer, decision support system, drug sensitivity, personalized therapy, precision medicine

Abstract

Multiple Myeloma (MM) is a treatable, yet incurable, malignancy of bone marrow

plasma cells. This cancer affects many patients and many succumb to relapse of tumor burden

despite a large number of available chemotherapeutic agents developed for therapy. This is

because MM tumors are heterogeneous and receive protection from therapeutic agents by the

microenvironment and other mechanisms including homologous MM-MM aggregation.

Therefore, therapy failure and frequent patient relapse is due to the evolution of drug resistance,

not a lack of available drugs. To analyze and understand this problem, the evolution of drug

resistance has been explored and presented herein. We seek to describe the methods through

which MM cells become resistant to therapy, and how this resistance evolves throughout a

patient’s treatment history. We achieve this in five steps.

First we review the patient’s clinical history, including treatments and changes in

tumor burden. Second, we trace the evolutionary tree of sub-clones within the tumor

burden using standard of care fluorescence in situ hybridization (FISH). Thirdly,

immunohistochemistry slides are stained and aligned to quantify the level of environmental

protection received by surrounding cells and plasma in the bone marrow microenvironment

(coined environment mediated drug resistance score [EMDR]). The fourth analysis type is

produced through a novel 384-well plate ex vivo chemosensitivity assay to quantify sensitivity of

primary MM cells to chemotherapeutic agents and extrapolate these findings to 90-day clinical

response predictions. In addition to direct clinical application in the choice of best treatment, this

tool was also used to study changes in sensitivity of patient tumors to other drugs, and it was

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observed that, upon relapse, in addition to developing resistance to the current line of therapy,

tumors become cross-resistant to agents that they were never exposed to. Finally, MM-MM

homologous aggregation is quantified to assess the level of drug resistance contributed by

clustering of patient tumor cells, which causes upregulation of Bcl-2 expression and other

resistance mechanisms1.

The findings of such experimentation improve comprehension of the driving factors that

contribute to drug resistance evolution on a personalized treatment basis. The aforementioned

factors all contribute in varying degrees for unique patient cases, seven of which are presented in

depth for this project. In summary: Environmental protection plays a critical initial role in drug

resistance, which is followed by increase in tumor genetic heterogeneity as a result of mutations

and drug-induced Darwinian selection. Eventually, environment-independent drug resistant subpopulations

emerge, allowing the tumor to spread to unexplored areas of the bone marrow while

maintaining inherited drug resistant phenotype2. It is our hope that these findings will help in

shifting perspective regarding optimal management of MM by finding new therapeutic

procedures that address all aspects of drug resistance to minimize chance of relapse and improve

quality of life for patients.

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