Date of Completion


Embargo Period


Major Advisor

Dr. James F. Rusling

Associate Advisor

Dr. John B. Schenkman

Associate Advisor

Dr. Ashis K. Basu

Field of Study



Doctor of Philosophy

Open Access

Open Access


Cancer is the second leading cause of deaths in the United States. This thesis focuses on two research project (1) development of novel LC-MS/MS methodology to screen chemicals and their metabolites for DNA damaging effects which might eventually lead to cancer and (2) development of automated and 3D printed elecrochemical biosensors to detect panels of prostate cancer biomarkers for early diagnosis and to differentiate aggressive and non-aggressive versions of prostate cancer.

Chapter 1 gives a brief introduction and describes goals and significance of the thesis. It also gives an overview of genotoxicity, DNA damaging events, xenobiotics, and cytochrome P450 enzymes and their role in reactive metabolite formation. A brief description of P53 tumor suppressor gene and its role in cancer and organ specific cancer is also included.

Chapter 2 describes the first ever restriction enzyme-assisted LC-MS/MS methodology for sequence specific DNA damage by chemical metabolites on exon 7 fragment of P53 gene. It describes the importance of structural integrity of large ds-DNA vs small ss-DNA for codon specific DNA damage in co-relation tissue specific cancer.

Chapter 3 shows the effect of cytosine methylation on sequence specificity and rate of metabolite adduction on exon 7 fragment of P53 gene. Kinetics of BPDE adduction was validated using both LC-MS/MS methodology and molecular modelling.

Chapter 4 describes the development of magnetic biocolloid technology in a 96 well platform to feed DNA damage products to LC-MS/MS to screen multiple cyt P450 enzymes on bioactivation of drugs or chemicals and resulting DNA damaging events on P53 gene and correlation of results to tissue specific cancer.

Chapter 5 involves brief overview of prostate cancer and the need for automated low cost biosensor in cancer diagnostics. It also describes the developed automated reagent/sample cassette and 3D printed user friendly microfluidic devices for protein-based point of care diagnostics.