Christopher R. Smith

Identification of Five Candidate Lung Cancer Biomarkers by Proteomics Analysis of Conditioned Media of Four Lung Cancer Cell Lines

Detection of lung cancer at an early stage is necessary for successful therapy and improved survival rates. We performed a bottom-up proteomics analysis using a two-dimensional LC-MS/MS strategy on the conditioned media of four lung cancer cell lines of different histological backgrounds (non-small cell lung cancer: H23 (adenocarcinoma), H520 (squamous cell carcinoma), and H460 (large cell carcinoma); small cell lung cancer: H1688) to identify secreted or membrane-bound proteins that could be useful as novel lung cancer biomarkers. Proteomics analysis of the four conditioned media allowed identification of 1,830 different proteins (965, 871, 726, and 847 from H1688, H23, H460, and H520, respectively). All proteins were assigned a subcellular localization, and 38% were classified as extracellular or membrane-bound. We successfully identified the internal control proteins (also detected by ELISA), kallikrein-related peptidases 14 and 11, and IGFBP2. We also identified known or putative lung cancer tumor markers such as squamous cell carcinoma antigen, carcinoembryonic antigen, chromogranin A, creatine kinase BB, progastrin-releasing peptide, neural cell adhesion molecule, and tumor M2-PK. To select the most promising candidates for validation, we performed tissue specificity assays, functional classifications, literature searches for association to cancer, and a comparison of our proteome with the proteome of lung-related diseases and serum. Five novel lung cancer candidates, ADAM-17, osteoprotegerin, pentraxin 3, follistatin, and tumor necrosis factor receptor superfamily member 1A were preliminarily validated in the serum of patients with lung cancer and healthy controls. Our results demonstrate the utility of this cell culture proteomics approach to identify secreted and shed proteins that are potentially useful as serological markers for lung cancer.

Proteomic analysis of seminal plasma from normal volunteers and post-vasectomy patients identifies over 2000 proteins and candidate biomarkers of the urogenital system.

Seminal plasma is a fluid that originates from the testis, epididymis,prostate, and seminal vesicles, and hence, proteomic studies may identify potential markers of infertility and other diseases of the genito-urinary tract. We profiled the proteomes of pooled seminal plasma from fertile Control and post-vasectomy (PV) men. PV seminal plasma samples are void of proteins originating from the testis and the epididymis due to ligation of the vas deferens, and hence, comparative analysis of Control and PV data sets allows for identification of proteins originating from these tissues. Utilizing offline MudPIT and high-resolution mass spectrometry, we were able to identify over 2000 proteins in Control and PV pools each and over 2300 proteins all together. With semiquantitative analysis using spectral counting, we catalogued 32 proteins unique to Control, 49 at lower abundance in PV, 3 unique to PV, and 25 at higher abundance in PV. We believe that proteins unique to Control or at lower abundance in PV have their origin in the testis and the epididymis. Public databases have confirmed that many of these proteins originate from the testis and epididymis and are linked to the reproductive tract. These proteins may serve as candidate biomarkers for future studies of infertility and urogenital diseases.

Integrated Proteomic Profiling of Cell Line Conditioned Media and Pancreatic Juice for the Identification of Pancreatic Cancer Biomarkers

Pancreatic cancer is one of the leading causes of cancer-related deaths, for which serological biomarkers are urgently needed. Most discovery-phase studies focus on the use of one biological source for analysis. The present study details the combined mining of pancreatic cancer-related cell line conditioned media and pancreatic juice for identification of putative diagnostic leads. Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer, we extensively characterized the proteomes of conditioned media from six pancreatic cancer cell lines (BxPc3, MIA-PaCa2, PANC1, CAPAN1, CFPAC1, and SU.86.86), the normal human pancreatic ductal epithelial cell line HPDE, and two pools of six pancreatic juice samples from ductal adenocarcinoma patients. All samples were analyzed in triplicate. Between 1261 and 2171 proteins were identified with two or more peptides in each of the cell lines, and an average of 521 proteins were identified in the pancreatic juice pools. In total, 3479 nonredundant proteins were identified with high confidence, of which ∼40% were extracellular or cell membrane-bound based on Genome Ontology classifications. Three strategies were employed for identification of candidate biomarkers: (1) examination of differential protein expression between the cancer and normal cell lines using label-free protein quantification, (2) integrative analysis, focusing on the overlap of proteins among the multiple biological fluids, and (3) tissue specificity analysis through mining of publically available databases. Preliminary verification of anterior gradient homolog 2, syncollin, olfactomedin-4, polymeric immunoglobulin receptor, and collagen alpha-1(VI) chain in plasma samples from pancreatic cancer patients and healthy controls using ELISA, showed a significant increase (p < 0.01) of these proteins in plasma from pancreatic cancer patients. The combination of these five proteins showed an improved area under the receiver operating characteristic curve to CA19.9 alone. Further validation of these proteins is warranted, as is the investigation of the remaining group of candidates.

Mining the Ovarian Cancer Ascites Proteome for Potential Ovarian Cancer Biomarkers

Current ovarian cancer biomarkers are inadequate because of their relatively low diagnostic sensitivity and specificity. There is a need to discover and validate novel ovarian cancer biomarkers that are suitable for early diagnosis, monitoring, and prediction of therapeutic response. We performed an in-depth proteomics analysis of ovarian cancer ascites fluid. Size exclusion chromatography and ultrafiltration were used to remove high abundance proteins with molecular mass ≥30 kDa. After trypsin digestion, the subproteome (≤30 kDa) of ascites fluid was determined by two-dimensional liquid chromatography-tandem mass spectrometry. Filtering criteria were used to select potential ovarian cancer biomarker candidates. By combining data from different size exclusion and ultrafiltration fractionation protocols, we identified 445 proteins from the soluble ascites fraction using a two-dimensional linear ion trap mass spectrometer. Among these were 25 proteins previously identified as ovarian cancer biomarkers. After applying a set of filtering criteria to reduce the number of potential biomarker candidates, we identified 52 proteins for which further clinical validation is warranted. Our proteomics approach for discovering novel ovarian cancer biomarkers appears to be highly efficient because it was able to identify 25 known biomarkers and 52 new candidate biomarkers that warrant further validation.

Product ion monitoring assay for prostate-specific antigen in serum using a linear ion-trap.

While numerous strategies exist for biomarker discovery, the bottleneck to product development and routine use at the clinic is in the verification phase of candidate biomarkers. The aim of this study was to establish a robust and high-throughput product ion monitoring (PIM) assay that is potentially capable of rapidly verifying candidates from discovery phase experiments. Using prostate-specific antigen (PSA), a model biomarker, and a routinely used mass spectrometer for discovery platforms, an ion trap (LTQ, Thermo), the utility of this instrument to perform PIM was explored. The proteotypic doubly charged intact peptide LSEPAELTDAVK ( m/ z 637) fragmenting to m/ z 943 (PAELTDAVK) was monitored. A limit of detection of 10 attomoles with a coefficient of variation (CV) of <20% was obtained for a purified recombinant PSA digest. Immunoextraction of endogenous PSA from serum using a monoclonal antibody on a 96-well microtiter plate, followed by PIM on the LTQ, enabled quantification of PSA down to less than 1 ng/mL with a limit of detection of 0.1 ng/mL and CVs < 20%. Mascot searching and ion ratio confirmation further supported the conclusion that the quantified moiety in serum was the PSA peptide. We conclude that this methodology could be adapted quickly and easily to other candidates, thus providing a much needed technology to bridge the gap between discovery and validation platforms.

Comprehensive Analysis of Conditioned Media from Ovarian Cancer Cell Lines Identifies Novel Candidate Markers of Epithelial Ovarian Cancer

Ovarian cancer remains a deadly threat to women as the disease is often diagnosed in the late stages when the chance of survival is low. There are no good biomarkers available for early detection and only a few markers have shown clinical utility for prognosis, response to therapy and disease recurrence. We mined conditioned media of four ovarian cancer cell lines (HTB75, TOV-112D, TOV-21G and RMUG-S) by two-dimensional liquid chromatography-mass spectrometry. Each cell line represented one of the major histological types of epithelial ovarian cancer. We identified 2039 proteins from which 228 were extracellular and 192 were plasma membrane proteins. Within the latter list, we identified several known markers of ovarian cancer including three that are well established, namely, CA-125, HE4, and KLK6. The list of 420 extracellular and membrane proteins was cross-referenced with the proteome of ascites fluid to generate a shorter list of 51 potential biomarker candidates. According to Ingenuity Pathway Analysis, two of the top 10 diseases associated with the list of 51 proteins were cancer and reproductive diseases. We selected nine proteins for preliminary validation using 20 serum samples from healthy women and 10 from women with ovarian cancer. Of the nine proteins, clusterin (increase) and IGFBP6 (decrease) showed significant differences between women with or without ovarian cancer. We conclude that in-depth proteomic analysis of cell culture supernatants of ovarian cancer cell lines can identify potential ovarian cancer biomarkers that are worth further clinical validation.

Kallikrein-related Peptidase-8 (KLK8) Is an Active Serine Protease in Human Epidermis and Sweat and Is Involved in a Skin Barrier Proteolytic Cascade

Kallikrein-related peptidase-8 (KLK8) is a relatively uncharacterized epidermal protease. Although proposed to regulate skin-barrier desquamation and recovery, the catalytic activity of KLK8 was never demonstrated in human epidermis, and its regulators and targets remain unknown. Herein, we elucidated for the first time KLK8 activity in human non-palmoplantar stratum corneum and sweat ex vivo. The majority of stratum corneum and sweat KLK8 was catalytically active, displaying optimal activity at pH 8.5 and considerable activity at pH 5. We also showed that KLK8 is a keratinocyte-specific protease, not secreted by human melanocytes or dermal fibroblasts. KLK8 secretion increased significantly upon calcium induction of terminal keratinocyte differentiation, suggesting an active role for this protease in upper epidermis. Potential activators, regulators, and targets of KLK8 activity were identified by in vitro kinetic assays using pro-KLK8 and mature KLK8 recombinant proteins produced in Pichia pastoris. Mature KLK8 activity was enhanced by calcium and magnesium ions and attenuated by zinc ions and by autocleavage after Arg164. Upon screening KLK8 cleavage of a library of FRET-quenched peptides, trypsin-like specificity was observed with the highest preference for (R/K)(S/T)(A/V) at P1-P1′-P2′. We also demonstrated that KLK5 and lysyl endopeptidase activate latent pro-KLK8, whereas active KLK8 targets pro-KLK11, pro-KLK1, and LL-37 antimicrobial peptide activation in vitro. Together, our data identify KLK8 as a new active serine protease in human stratum corneum and sweat, and we propose regulators and targets that augment its involvement in a skin barrier proteolytic cascade. The implications of KLK8 elevation and hyperactivity in desquamatory and inflammatory skin disease conditions remain to be studied.

Differential N-glycosylation of Kallikrein 6 Derived from Ovarian Cancer Cells or the Central Nervous System

Ovarian cancer causes more deaths than any other gynecological disorder. Perturbed glycosylation is one of the hallmarks of this malignancy. Kallikrein 6 (KLK6) elevation in serum is a diagnostic and prognostic indicator in ovarian cancer. The majority of ovarian carcinomas express high levels of KLK6, which diffuses into the circulation. Under physiological conditions, KLK6 is expressed highly in the central nervous system and found at high levels in cerebrospinal fluid from where it enters the circulation. Our aim was to characterize and compare the N-glycosylation status of this protein in ovarian cancer ascites fluid and cerebrospinal fluid. Anion-exchange chromatography was used to reveal different post-translational modifications on the two isoforms. Mobility gel shift Western blot analysis coupled with glycosidase digestion showed that the molecular weight difference between the two isoforms was because of differential glycosylation patterns. The presence of a single N-glycosylation site on KLK6 was confirmed by site-directed mutagenesis. Using a Sambucus nigra agglutinin-monoclonal antibody sandwich enzyme-linked immunosorbent assay approach, it was shown that ovarian cancer-derived KLK6 was modified with α2-6-linked sialic acid. The structure and composition of glycans of both KLK6 isoforms was elucidated by glycopeptide monitoring with electrospray ionization-Orbitrap tandem mass spectrometry. Therefore, the extensive and almost exclusive sialylation of KLK6 from ovarian cancer cells could lead to the development of an improved biomarker for the early diagnosis of ovarian carcinoma.

Platform for Establishing Interlaboratory Reproducibility of Selected Reaction Monitoring-Based Mass Spectrometry Peptide Assays

Mass spectrometry (MS) is an attractive alternative to quantification of proteins by immunoassays, particularly for protein biomarkers of clinical relevance. Reliable quantification requires that the MS-based assays are robust, selective, and reproducible. Thus, the development of standardized protocols is essential to introduce MS into clinical research laboratories. The aim of this study was to establish a complete workflow for assessing the transferability and reproducibility of selected reaction monitoring (SRM) assays between clinical research laboratories. Four independent laboratories in North America, using identical triple-quadrupole mass spectrometers (Quantum Ultra, Thermo), were provided with standard protocols and instrumentation settings to analyze unknown samples and internal standards in a digested plasma matrix to quantify 51 peptides from 39 human proteins using a multiplexed SRM assay. The interlaboratory coefficient of variation (CV) was less than 10% for 25 of 39 peptides quantified (12 peptides were not quantified based upon hydrophobicity) and exhibited CVs less than 20% for the remaining peptides. In this report, we demonstrate that previously developed research platforms for SRM assays can be improved and optimized for deployment in clinical research environments.

Interlaboratory reproducibility of selective reaction monitoring assays using multiple upfront analyte enrichment strategies.

Over the past few years, mass spectrometry has emerged as a technology to complement and potentially replace standard immunoassays in routine clinical core laboratories. Application of mass spectrometry to protein and peptide measurement can provide advantages including high sensitivity, the ability to multiplex analytes, and high specificity at the amino acid sequence level. In our previous study, we demonstrated excellent reproducibility of mass spectrometry-selective reaction monitoring (MS-SRM) assays when applying standardized standard operating procedures (SOPs) to measure synthetic peptides in a complex sample, as lack of reproducibility has been a frequent criticism leveled at the use of mass spectrometers in the clinical laboratory compared to immunoassays. Furthermore, an important caveat of SRM-based assays for proteins is that many low-abundance analytes require some type of enrichment before detection with MS. This adds a level of complexity to the procedure and the potential for irreproducibility increases, especially across different laboratories with different operators. The purpose of this study was to test the interlaboratory reproducibility of SRM assays with various upfront enrichment strategies and different types of clinical samples (representing real-world body fluids commonly encountered in routine clinical laboratories). Three different, previously published enrichment strategies for low-abundance analytes and a no-enrichment strategy for high-abundance analytes were tested across four different laboratories using different liquid chromatography-SRM (LC-SRM) platforms and previously developed SOPs. The results demonstrated that these assays were indeed reproducible with coefficients of variation of less than 30% for the measurement of important clinical proteins across all four laboratories in real world samples.