All ETDs from UAB

Advisory Committee Chair

Sara J Cooper

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) Heersink School of Medicine


With a 5-year survival rate of 7% and only marginal improvements in recent dec-ades, pancreatic adenocarcinoma (PDAC) survival statistics present a disheartening chal-lenge. A majority of the high mortality rate associated with PDAC is due to late-stage diagnosis and limited efficacy of the current chemotherapeutic arsenal. This work is largely focused on the ~20% of tumors detected prior to metastasis for which curative surgical resection can be combined with chemotherapy and radiation therapy, increasing the 5 year survival rate to ~25%. Although a subset of these patients who undergo surgi-cal resection experience sustained remission, a majority of patients still relapse within 2 years making it difficult for even relatively early stage patients and their providers to make value-based decisions on a treatment course. In an effort to improve patient out-comes, multi-drug cocktails such as FOLFIRINOX (fluorouracil, folinic acid, irinotecan and oxaliplatin) are being increasingly used for adjuvant therapy despite their concomi-tant toxicities. The ability to stratify patients likely to respond to single agent therapy from those patients who may benefit from multi-drug therapy or may be refractory to all current therapeutic avenues could provide much needed clarity to the current PDAC ad-juvant therapy decision tree. We have begun to address this need by performing RNA-sequencing on a subset of treatment naïve PDAC tumors from a cohort of patients select-ed to include a wide range of survival times post-resection. We define the key early tran-scriptional characteristics of tumors that predict prognosis by training a regularized re-gression model on our cohort’s transcriptomes. Context is provided to our prognostic model by comparing it to previously described prognostic markers such as the meta-PCNA index, a metric that summarizes the expression of cell proliferation-associated proteins, and to prognostic expression signatures of other cancers. Finally, we identify and experimentally validate new single gene targets, whose expression level may modu-late tumor chemoresistance, using both a candidate gene approach based on expression differences observed in our patient cohort as well as genome-wide CRISPR screening.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.