MSACL 2024 Abstract

Identification of the Protein Expression of Androgen Receptor Variants Using Targeted Proteomics in Clinical Castration Resistant Prostate Cancer Models Sychev, Zoi E.(1), Larson, Gabrienne (2), Shiba, Seie (1,3), Dehm, Scott M.(1), Seegmiller, Jesse C. (1,3,4), Drake, Justin M.(2) (1)Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis MN, USA (2)Department of Pharmacology University of Minnesota, Minneapolis MN, USA (3)Advanced Research and Diagnostic Laboratory, University of Minnesota, Minneapolis MN, USA (4) M Health Fairview, Minneapolis MN, USA Zoi Sychev, PhD (Presenter) University of Minnesota, Twin Cities >> POSTER (PDF)

Presenter Bio: Cancer Biologist with over 10 years of experience focused on developing strategies to characterize and identify molecular mechanisms constituting effective cancer immunotherapies. Lead investigator in all aspects of experimental design, execution, and data analyses for mass spectrometry based proteomics. My greatest motivation is to develop technologies that could be applicable across multiple fields working with multidisciplinary teams to culminate successful products and to improve healthcare by developing novel diagnostic platform, enhancing test-utilization, clinical toxicology, and data-driven clinical laboratory processes optimization.

Introduction
Castration Resistant Prostate Cancer (CRPC) is a treatment resistant form of prostate cancer (PCa). Currently, there is not a way to identify which patients will develop this resistance before full blown CRPC develops. Therefore, all PCa treatment approaches are similar yet this results in tumor regression in some cases and progression in others. Targeting the androgen receptor (AR) is still the main focus of current therapies even in CRPC. Emergence of AR splice variants (AR-vs) after initial treatment is thought to be one of the primary mechanisms of resistance. AR-vs lack the ligand binding domain rendering Androgen Deprivation Therapy (ADT) ineffective in tumors expressing these variants. Recent work has identified the DNA and RNA species of ARVs in CRPC but investigation into whether the protein is translated are unknown. One exception is the approval of an antibody test that detects a specific AR-v, AR-v7, from the blood of PC patients and predicts ADT response. However, there are instances where a patient may not express ARv7 and are still resistant to ADT. This may suggest that other AR-vs, not currently detected at the protein level, are important predictors for ADT response. The primary goal of this work is to expand the protein identification of known and unknown AR-Vs that may predict response to ADT using targeted liquid chromatography tandem mass spectrometry (LC-MS/MS). Targeted LC-MS/MS can provide accurate, precise, sensitive, and reproducible detection of a pre-determined set of peptides in specimens without the need for antibody enrichment.

Objective:
The goal of this work is to generate a robust set of unique peptides that behave as surrogates for AR-v proteins and then evaluate them via targeted LC-MS/MS.

Method:
We developed the AR-v targeted LC-MS/MS assay by first designing AR splice variants from unique splice regions via RNA-guided sequences translated to amino acid sequences. The AR-variants full amino acid sequences were then in-silico trypsin digested using Expasy software tool that generated tryptic peptides. Blast analysis of the AR-v peptides was performed where no overlap with other human proteins was observed. These AR-v peptide sequences were commercially synthesized along with heavy isotopically analogs to be used as internal standards in the LC-MS/MS method. The LC-MS/MS system consisted of a XR HPLC system (Shimadzu) with a QTRAP 6500 triple quadrupole mass spectrometer (SCIEX) using electrospray ionization and multiple reaction monitoring (MRM) for analysis. Experiments were conducted under high-flow conditions with a flow rate of 0.700 mL/min and a 7-minute run time employing gradient chromatography. Mobile phase solutions consisted of 0.1% formic acid in water (mobile phase A) and 0.1% formic acid in acetonitrile (mobile phase B). A Kinetex (Phenomenex) 2.6 um C-18 100 A 50 x 3 mm column was used for all chromatographic runs. The method examined 9 peptides and included 2 to 3 MRM transitions per peptide. Calibration curves were constructed using unlabeled peptides over 0.10 pmol/uL to 1 pmol/uL. Specimens examined consisted of a panel of prostate cancer cell lines (n= 6), CRPC patient derived xenografts tumors (n=4) and a negative control cell line (no androgen receptor expression), Cos-1, which served with a dual function and was used as matrix for peptide MRM optimization experiments. Cell line and patient derived xenografts tumor specimens were processed using lysis buffer containing 7 M of urea, 2 M thiourea, 0.4 M Tris pH 8.0, 20% acetonitrile (ACN), 10 mM TCEP and 25 mM chloroacetamide. Protease inhibitor HALT was added to the lysis buffer at 1x concentration immediately before addition to the specimens. Viscous specimens, likely due to chromatin release, were sonicated using a probe sonicator set at 30% amplitude, for 5 seconds while samples were on ice. The specimens then underwent proteolysis using LysC at pH 8.2 and incubated at 37 C for 4 hours and then trypsin at pH 8.2 was added and incubated at 37C in a warm air incubator overnight (~16 hrs). After incubation, the samples were acidified with trifluoroacetic acid to pH 3 (final concentration of 0.3-0.6%) or less to stop further enzymatic activity. Specimens were desalted using reverse phase HLB columns and the elutions were dried down using a speed vacuum. Samples were re-suspended with 0.1% formic acid. Internal standard solution was spiked-in to each calibrator and cell line specimen and then added to a 2 mL autosampler vials with 300 µL glass inserts. Linearity and sensitivity for each peptide included in the method was examined using calibration curves. Data analysis was conducted using Multiquant (SCIEX) software.

Results:
The targeted MRM approached was successfully achieved for quantification of 9 peptides from 8 proteins in 6 prostate cancer cell lines and 4 patient derived xenografts tumor specimens. Out of the 8 proteins evaluated, we observed 3 known targets (AR-exon1, AR-v7 and AR-v12) and 4 novel AR-vs in 22Rv1 PCa cell lines. Additionally, CRPC patient derived xenografts were assessed where 3 novel AR-vs were detected.

Conclusions:
These preliminary results using a LC-MS/MS platform show promising identification and quantification of novel AR-vs that have not been measured before at the protein level. Subsequent analysis of larger cohorts will further elucidate AR-vs role in PCa treatment resistance mechanisms and possibly assist in future treatment approaches.