D. Iannitti

Discovery of putative pancreatic cancer biomarkers using subcellular proteomics

Pancreatic cancer (PC) is a highly aggressive disease that frequently remains undetected until it has progressed to an advanced, systemic stage. Successful treatment of PC is hindered by the lack of early detection. The application of proteomic analysis to PC combined with subcellular fractionation has introduced new possibilities in the field of biomarker discovery. We utilized matched pairs of pancreas tumor and non-tumor pancreas from patients undergoing tumor resection. The tissues were treated to obtain cellular protein fractions corresponding to cytosol, membrane, nucleus and cytoskeleton. The fractions were then separated by molecular weight and digested with trypsin, followed by liquid chromatography and tandem mass spectrometry. The spectra obtained were searched using Sequest engine and combined into a single analysis file to obtain a semi-quantitative number, spectral count, using Scaffold software. We identified 2393 unique proteins in non-tumor and cancer pancreas. Utilizing PLGEM statistical analysis we determined 104 proteins were significantly changed in cancer. From these, we further validated four secreted proteins that are up-regulated in cancer and have potential for development as minimally-invasive diagnostic markers. We conclude that subcellular fractionation followed by gel electrophoresis and tandem mass spectrometry is a powerful strategy for identification of differentially expressed proteins in pancreatic cancer.

Subcellular tissue proteomics of hepatocellular carcinoma for molecular signature discovery.

Hepatocellular carcinoma (HCC) is one of the leading causes of mortality from solid organ malignancy worldwide. Because of the complexity of proteins within liver cells and tissues, the discovery of therapeutic targets of HCC has been difficult. To investigate strategies for decreasing the complexity of tissue samples for detecting meaningful protein mediators of HCC, we employed subcellular fractionation combined with 1D-gel electrophoresis and liquid chromatography-tandem mass spectrometry analysis. Moreover, we utilized a statistical method, namely, the Power Law Global Error Model (PLGEM), to distinguish differentially expressed proteins in a duplicate proteomic data set. Mass spectrometric analysis identified 3045 proteins in nontumor and HCC from cytosolic, membrane, nuclear, and cytoskeletal fractions. The final lists of highly differentiated proteins from the targeted fractions were searched for potentially translocated proteins in HCC from soluble compartments to the nuclear or cytoskeletal compartments. This analysis refined our targets of interest to include 21 potential targets of HCC from these fractions. Furthermore, we validated the potential molecular targets of HCC, MATR3, LETM1, ILF2, and IQGAP2 by Western blotting, immunohistochemisty, and immunofluorescent microscopy. Here we demonstrate an efficient strategy of subcellular tissue proteomics toward molecular target discovery of one of the most complicated human disease, HCC.

Robotic-assisted completion Cholecystectomy: a safe and effective minimally invasive approach to a challenging surgical scenario

Average LOS 1.1 days TP20-02 ROBOTIC-ASSISTED COMPLETION CHOLECYSTECTOMY: A SAFE AND EFFECTIVE MINIMALLY INVASIVE APPROACH TO A CHALLENGING SURGICAL SCENARIO W. Lyman, M. Passeri, A. Sastry, D. Iannitti, D. Vrochides, E. Baker and J. Martinie Department of General Surgery, and Division of HPB Surgery, Carolinas Medical Center, United States Background: Subtotal cholecystectomy remains a viable and safe option when intraoperative conditions preclude visualization of the Critical View of Safety. 1.8% of these patients eventually require a reoperation. Traditionally, completion cholecystectomy following subtotal cholecystectomy required an open approach. In this study, we present our institutional experience with 16 robotic-assisted completion cholecystectomies following previous subtotal cholecystectomy. Methods: Operating room logs were reviewed from 20102017 to identify all robotic cholecystectomies performed at our institution. Review of all operative reports identified 16 completion cholecystectomies following a previous subtotal cholecystectomy. All additional variables including demographics, operative variables, and postoperative outcomes were collected from EMR records. Results: Median time from previous subtotal cholecystectomy to robotic completion cholecystectomy was 84 months (7 years). 58.3% of patients previously underwent an open subtotal cholecystectomy. The remaining patients underwent a laparoscopic subtotal cholecystectomy. Additional demographics and outcomes can be seen in Table 1. One patient required oral antibiotics for incisional site erythema. No patients required a conversion to an open procedure and average length of stay was 1.1 days. Conclusions: Although traditionally performed with an open approach, we have had success in recent years at our institution with a robotic-assisted approach to completion