Lynn A. Beer

Systematic Discovery of Ectopic Pregnancy Serum Biomarkers Using 3-D Protein Profiling Coupled with Label-free Quantitation

Ectopic pregnancy (EP) and normal intrauterine pregnancy (IUP) serum proteomes were quantitatively compared to systematically identify candidate biomarkers. A 3-D biomarker discovery strategy consisting of abundant protein immunodepletion, SDS gels, LC-MS/MS, and label-free quantitation of MS signal intensities identified 70 candidate biomarkers with differences between groups greater than 2.5-fold. Further statistical analyses of peptide quantities were used to select the most promising 12 biomarkers for further study, which included known EP biomarkers, novel EP biomarkers (ADAM12 and ISM2), and five specific isoforms of the pregnancy specific beta-1-glycoprotein family. Technical replicates showed good reproducibility and protein intensities from the label-free discovery analysis compared favorably with reported abundance levels of several known reference serum proteins over at least 3 orders of magnitude. Similarly, relative abundances of candidate biomarkers from the label-free discovery analysis were consistent with relative abundances from pilot validation assays performed for five of the 12 most promising biomarkers using label-free multiple reaction monitoring of both the patient serum pools used for discovery and the individual samples that constituted these pools. These results demonstrate robust, reproducible, in-depth 3-D serum proteome discovery, and subsequent pilot-scale validation studies can be achieved readily using label-free quantitation strategies.

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer

UNLABELLED New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity. BIOLOGICAL SIGNIFICANCE This manuscript addresses the importance of distinguishing between protein homologs and isoforms when identifying and validating cancer biomarkers in plasma or serum. Specifically, it describes the use of targeted in-depth LC-MS/MS analysis to determine the members of two protein families, chloride intracellular channel (CLIC) and tropomyosin (TPM) proteins that are detectable in sera of ovarian cancer patients. It then establishes a multiplexed isoform- and homology-specific MRM assay to quantify all observed gene products in these two protein families as well as many of the closely related tropomyosin isoforms. Using this assay, levels of all detected CLICs and TPMs were quantified in ovarian cancer patient and control subject sera. These results demonstrate that in addition to the previously known CLIC1, multiple tropomyosins and CLIC4 are promising new ovarian cancer biomarkers. Based on these initial validation studies, these new ovarian cancer biomarkers appear to be superior to most previously known ovarian cancer biomarkers.

A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer

Proteomics discovery of novel cancer serum biomarkers is hindered by the great complexity of serum, patient-to-patient variability, and triggering by the tumor of an acute-phase inflammatory reaction. This host response alters many serum protein levels in cancer patients, but these changes have low specificity as they can be triggered by diverse causes. We addressed these hurdles by utilizing a xenograft mouse model coupled with an in-depth 4-D protein profiling method to identify human proteins in the mouse serum. This strategy ensures that identified putative biomarkers are shed by the tumor, and detection of low-abundance proteins shed by the tumor is enhanced because the mouse blood volume is more than a thousand times smaller than that of a human. Using TOV-112D ovarian tumors, more than 200 human proteins were identified in the mouse serum, including novel candidate biomarkers and proteins previously reported to be elevated in either ovarian tumors or the blood of ovarian cancer patients. Subsequent quantitation of selected putative biomarkers in human sera using label-free multiple reaction monitoring (MRM) mass spectrometry (MS) showed that chloride intracellular channel 1, the mature form of cathepsin D, and peroxiredoxin 6 were elevated significantly in sera from ovarian carcinoma patients.

Rapid Verification of Candidate Serological Biomarkers Using Gel-based, Label-free Multiple Reaction Monitoring

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μL of serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.

A disintegrin and metalloprotease protein-12 as a novel marker for the diagnosis of ectopic pregnancy

OBJECTIVE To evaluate the performance of a novel biomarker, a disintegrin and metalloprotease-12 (ADAM-12), to differentiate an ectopic pregnancy (EP) from normal intrauterine pregnancies (IUPs). DESIGN Case-control study. SETTING Three urban academic centers. PATIENT(S) Women who were seen in the emergency department with pain or bleeding in the first trimester of pregnancy. INTERVENTION(S) Sera from women with diagnosed EP or IUP were evaluated via proteomics and an ADAM-12 dissociation-enhanced lanthanide fluoroimmunoassay. MAIN OUTCOME MEASURE(S) Differences between groups, area under the receiver operating curve, sensitivity, and specificity. RESULT(S) Via a proteomics evaluation, we found a statistically significant decrease in ADAM-12 in the sera of patients with EP, which we confirmed in a larger group of 199 patients (median IUP 18.6 ng/mL versus median EP 2.5 ng/mL with good discrimination between the groups as assessed by receiver operating characteristics [area under the curve = 0.82]). At a low cut-point, the sensitivity was 70% and specificity 84%, but, at a higher cut-point optimizing sensitivity, the ADAM-12 test demonstrated a sensitivity of 97%. CONCLUSION(S) ADAM-12 is a promising marker for the diagnosis of EP in women with symptoms in the first trimester, validating the proteomics findings. Further studies in additional patient populations and in combination with other biomarkers are needed.

In-Depth Analysis of a Plasma or Serum Proteome Using a 4D Protein Profiling Method

Comprehensive proteomic analysis of human plasma or serum has been a major strategy used to identify biomarkers that serve as indicators of disease. However, such in-depth proteomic analyses are challenging due to the complexity and extremely large dynamic range of protein concentrations in plasma. Therefore, reduction in sample complexity through multidimensional pre-fractionation strategies is critical, particularly for the detection of low-abundance proteins that have the potential to be the most specific disease biomarkers. We describe here a 4D protein profiling method that we developed for comprehensive proteomic analyses of both plasma and serum. Our method consists of abundant protein depletion coupled with separation strategies - microscale solution isoelectrofocusing and 1D SDS-PAGE - followed by reversed-phase separation of tryptic peptides prior to LC-MS/MS. Using this profiling strategy, we routinely identify a large number of proteins over nine orders of magnitude, including a substantial number of proteins at the low ng/mL or lower levels from approximately 300 μL of plasma sample.

Identification of Multiple Novel Protein Biomarkers Shed by Human Serous Ovarian Tumors into the Blood of Immunocompromised Mice and Verified in Patient Sera

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples.

A systems biology analysis of metastatic melanoma using in-depth three-dimensional protein profiling.

Melanoma is an excellent model to study molecular mechanisms of tumor progression because melanoma usually develops through a series of architecturally and phenotypically distinct stages that are progressively more aggressive, culminating in highly metastatic cells. In this study, we used an in‐depth, 3‐D protein level, comparative proteome analysis of two genetically, very closely related melanoma cell lines with low‐ and high‐metastatic potentials to identify proteins and key pathways involved in tumor progression. This proteome comparison utilized fluorescent tagging of cell lysates followed by microscale solution IEF prefractionation and subsequent analysis of each fraction on narrow‐range 2‐D gels. LC‐MS/MS analysis of gel spots exhibiting significant abundance changes identified 110 unique proteins. The majority of observed abundance changes closely correlate with biological processes central to cancer progression, such as cell death and growth and tumorigenesis. In addition, the vast majority of protein changes mapped to six cellular networks, which included known oncogenes (JNK, c‐myc, and N‐myc) and tumor suppressor genes (p53 and transforming growth factor‐β) as critical components. These six networks showed substantial connectivity, and most of the major biological functions associated with these pathways are involved in tumor progression. These results provide novel insights into cellular pathways implicated in melanoma metastasis.

Baseline Immunoglobulin E Levels as a Marker of Doxorubicin- and Trastuzumab-Associated Cardiac Dysfunction

RATIONALE There is a critical need to develop robust, mechanistic strategies to identify patients at increased risk of cancer therapeutics-related cardiac dysfunction (CTRCD). OBJECTIVE We aimed to discover new biomarkers associated with doxorubicin- and trastuzumab-induced CTRCD using high-throughput proteomic profiling. METHODS AND RESULTS Plasma, echocardiograms, and clinical outcomes were collected at standardized intervals in breast cancer patients undergoing doxorubicin and trastuzumab cancer therapy. Thirty-one longitudinal plasma samples from 3 cases with CTRCD and 4 age- and cancer-matched controls without CTRCD were processed and analyzed using label-free liquid chromatography-mass spectrometry. From these analyses, 862 proteins were identified from case/control pairs 1 and 2 and 1360 proteins from case/control pair 3. Proteins with a >1.5-fold change in cases compared with controls with a P<0.05 either at the time of CTRCD diagnosis or across all time points were considered candidate diagnostic or predictive biomarkers, respectively. The protein that demonstrated the largest differences between cases and controls was immunoglobulin E, with higher levels detected at baseline and across all time points in controls without CTRCD as compared with matched CTRCD cases (P<0.05). Similarly, in a validation study of 35 participants treated with doxorubicin and trastuzumab, high baseline immunoglobulin E levels were associated with a significantly lower risk of CTRCD (P=0.018). CONCLUSIONS In patients receiving doxorubicin and trastuzumab, high baseline immunoglobulin E levels are associated with a lower risk of CTRCD. These novel findings suggest a new paradigm in cardio-oncology, implicating the immune system as a potential mediator of doxorubicin- and trastuzumab-induced cardiac dysfunction.

Quantitative Comparisons of Large Numbers of Human Plasma Samples Using TMT10plex Labeling

One strategy for improving the throughput of human plasma proteomic discovery analysis while maintaining good depth of analysis is to multiplex using isobaric tags. At present, the greatest multiplexing that is commercially available uses the TMT10plex kit. As an example of this approach, we describe efficient shotgun discovery proteomics of large numbers of human plasma to identify potential biomarkers. In the analysis strategy, a common pooled reference was used to enable comparisons across multiple experiments. Duplicate samples showed excellent overall reproducibility across different TMT experiments. Data filters that improved the quality of individual peptide and protein quantitation included using a filter for purity of the targeted precursor ion in the isolation window and using only unique peptides.