Myeong Hee Yu

Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins

Multiple reaction monitoring (MRM) mass spectrometry has been successfully applied to monitor targeted proteins in biological specimens, raising the possibility that assays could be configured to measure all human proteins. We report the results of a pilot study designed to test the feasibility of a large-scale, international effort for MRM assay generation. We have configured, validated across three laboratories and made publicly available as a resource to the community 645 novel MRM assays representing 319 proteins expressed in human breast cancer. Assays were multiplexed in groups of >150 peptides and deployed to quantify endogenous analytes in a panel of breast cancer–related cell lines. The median assay precision was 5.4%, with high interlaboratory correlation (R2 > 0.96). Peptide measurements in breast cancer cell lines were able to discriminate among molecular subtypes and identify genome-driven changes in the cancer proteome. These results establish the feasibility of a large-scale effort to develop an MRM assay resource.

Differential profiling of breast cancer plasma proteome by isotope-coded affinity tagging method reveals biotinidase as a breast cancer biomarker

BackgroundBreast cancer is one of the leading causes of womens death worldwide. It is important to discover a reliable biomarker for the detection of breast cancer. Plasma is the most ideal source for cancer biomarker discovery since many cells cross-communicate through the secretion of soluble proteins into blood.MethodsPlasma proteomes obtained from 6 breast cancer patients and 6 normal healthy women were analyzed by using the isotope-coded affinity tag (ICAT) labeling approach and tandem mass spectrometry. All the plasma samples used were depleted of highly abundant 6 plasma proteins by immune-affinity column chromatography before ICAT labeling. Several proteins showing differential abundance level were selected based on literature searches and their specificity to the commercially available antibodies, and then verified by immunoblot assays.ResultsA total of 155 proteins were identified and quantified by ICAT method. Among them, 33 proteins showed abundance changes by more than 1.5-fold between the plasmas of breast cancer patients and healthy women. We chose 5 proteins for the follow-up confirmation in the individual plasma samples using immunoblot assay. Four proteins, α1-acid glycoprotein 2, monocyte differentiation antigen CD14, biotinidase (BTD), and glutathione peroxidase 3, showed similar abundance ratio to ICAT result. Using a blind set of plasmas obtained from 21 breast cancer patients and 21 normal healthy controls, we confirmed that BTD was significantly down-regulated in breast cancer plasma (Wilcoxon rank-sum test, p = 0.002). BTD levels were lowered in all cancer grades (I-IV) except cancer grade zero. The area under the receiver operating characteristic curve of BTD was 0.78. Estrogen receptor status (p = 0.940) and progesterone receptor status (p = 0.440) were not associated with the plasma BTD levels.ConclusionsOur study suggests that BTD is a potential serological biomarker for the detection of breast cancer.

Cavities of α1-antitrypsin that play structural and functional roles

The native form of inhibitory serine protease inhibitors (serpins) is strained, which is critical for their inhibitory activity. Previous studies on stabilizing mutations of α1‐antitrypsin, a prototype of serpins, indicated that cavities provide a structural basis for the native strain of the molecule. We have systematically mapped the cavities of α1‐antitrypsin that play such structural and functional roles by designing cavity‐filling mutations at residues that line the walls of the cavities. Results show that energetically unfavorable cavities are distributed throughout the α1‐antitrypsin molecule, and the cavity‐filling mutations stabilized the native conformation at 8 out of 10 target sites. The stabilization effect of the individual cavity‐filling mutations of α1‐antitrypsin varied (0.2–1.9 kcal/mol for each additional methylene group) and appeared to depend largely on the structural flexibility of the cavity environment. Cavity‐filling mutations that decreased inhibitory activity of α1‐antitrypsin were localized in the loop regions that interact with β‐sheet A distal from the reactive center loop. The results are consistent with the notion that β‐sheet A and the structure around it mobilize when α1‐antitrypsin forms a complex with a target protease.

Gcn4p-mediated transcriptional repression of ribosomal protein genes under amino-acid starvation.

Gcn4p is a well‐characterized bZIP transcription factor that activates more than 500 genes encoding amino acids and purine biosynthesis enzymes, and many stress–response genes under various stress conditions. Under these stresses, it had been shown that transcriptions of ribosomal protein (RP) genes were decreased. However, the detailed mechanism of this downregulation has not been elucidated. In this study, we present a novel mechanistic model for a repressive role of Gcn4p on RP transcription, especially under amino‐acid starvation. It was found that Gcn4p bound directly to Rap1p, which in turn inhibited Esa1p–Rap1p binding. The inhibition of Esa1p recruitment to RP promoters ultimately reduced the level of histone H4 acetylation and RP transcription. These data revealed that Gcn4p has simultaneous dual roles as a repressor for RP genes as well as an activator for amino‐acid biosynthesis genes. Moreover, our results showed evidence of a novel link between general control of amino‐acid biosynthesis and ribosome biogenesis mediated by Gcn4p at an early stage of adaptation to amino‐acid starvation.

A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies.

Proteomic approach reveals FKBP4 and S100A9 as potential prediction markers of therapeutic response to neoadjuvant chemotherapy in patients with breast cancer.

Although doxorubicin (Doxo) and docetaxel (Docet) in combination are widely used in treatment regimens for a broad spectrum of breast cancer patients, a major obstacle has emerged in that some patients are intrinsically resistant to these chemotherapeutics. Our study aimed to discover potential prediction markers of drug resistance in needle-biopsied tissues of breast cancer patients prior to neoadjuvant chemotherapy. Tissues collected before chemotherapy were analyzed by mass spectrometry. A total of 2,331 proteins were identified and comparatively quantified between drug sensitive (DS) and drug resistant (DR) patient groups by spectral count. Of them, 298 proteins were differentially expressed by more than 1.5-fold. Some of the differentially expressed proteins (DEPs) were further confirmed by Western blotting. Bioinformatic analysis revealed that the DEPs were largely associated with drug metabolism, acute phase response signaling, and fatty acid elongation in mitochondria. Clinical validation of two selected proteins by immunohistochemistry found that FKBP4 and S100A9 might be putative prediction markers in discriminating the DR group from the DS group of breast cancer patients. The results demonstrate that a quantitative proteomics/bioinformatics approach is useful for discovering prediction markers of drug resistance, and possibly for the development of a new therapeutic strategy.

Profiling of differentially expressed proteins in stage IV colorectal cancers with good and poor outcomes.

Screening patients at high risk of recurrence of cancer would allow for more accurate and personalized treatment. In this study, we tried to identify the prognosis-related protein profile by applying two different quantitative proteomic techniques, difference in-gel electrophoresis and cleavable isotope-coded affinity tag method. Six tumor tissues were obtained from stage IV colorectal cancer (CRC) patients, of which three have survived more than five years (good prognostic group, GPG) and the other three died within 25 months (poor prognostic group, PPG) after palliative surgery and subsequent chemotherapy treatment. From the two independent quantitative analyses, we identified 175 proteins with abundance ratios greater than 2-fold. Gene ontology analysis revealed that proteins related to cellular assembly/organization and movement were generally increased in the PPG. Twenty-two proteins, including caveolin-1, were chosen for confirmatory studies by Western blot and immunohistochemistry. The Western blot data for each individual protein were analyzed with Mann-Whitney tests, and a multi-marker panel was generated by logistic regression analysis. Five proteins, fatty acid binding protein 1, intelectin 1, transitional endoplasmic reticulum ATPase, transgelin and tropomyosin 2, were significantly different between the two prognostic groups within 95% confidence. No single protein could completely distinguish the two groups from each other. However, a combination of the five proteins effectively distinguished PPG from GPG patients (AUC=1). Our study suggests a multi-marker panel composed of proteome signatures that provide accurate predictive information and potentially assist personalized therapy. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Rpn13p and Rpn14p are involved in the recognition of ubiquitinated Gcn4p by the 26S proteasome.

The 26S proteasome, composed of the 20S core and 19S regulatory complexes, is important for the turnover of polyubiquitinated proteins. Each subunit of the complex plays a special role in proteolytic function, including substrate recruitment, deubiquitination, and structural contribution. To assess the function of some non‐essential subunits in the 26S proteasome, we isolated the 26S proteasome from deletion strains of RPN13 and RPN14 using TAP affinity purification. The stability of Gcn4p and the accumulation of ubiquitinated Gcn4p were significantly increased, but the affinity in the recognition of proteasome was decreased. In addition, the subcomplexes of the isolated 26S proteasomes from deletion mutants were less stable than that of the wild type. Taken together, our findings indicate that Rpn13p and Rpn14p are involved in the efficient recognition of 26S proteasome for the proteolysis of ubiquitinated Gcn4p.

Proteomic analysis of γ-butyrolactone-treated mouse thalamus reveals dysregulated proteins upon absence seizure

Absence seizure has been of interest because the symptom is related to sensory processing. However, the mechanism that causes the disease is not understood yet. To better understand the molecular mechanism related to the disease progress at protein level, we performed proteomic studies using the thalamus of mice for which absence seizure was induced by γ‐butyrolactone (GBL). Differential proteome expression between GBL‐treated mice and control mice was examined by fluorescence 2D difference gel electrophoresis (DIGE) at three different time points (5, 10, and 30u2003min) after GBL‐administration. We identified 16 proteins differentially expressed by >1.4‐fold at any of the three time points. All proteins besides the serine protease inhibitor EIA were down‐regulated in absence seizure‐induced mice. The down‐regulated proteins can be classified into five groups by their biological functions: cytoskeleton rearrangement, neuroprotection, neurotransmitter secretion, calcium binding, and metabolism. The maximum level of change was reached by 10u2003min after GBL‐treatment, with the expression level returning back to the original at 30u2003min when mice were awakened from absence seizure thereby demonstrating the proteomic response is reversible. Our results suggest that absence seizures are associated with restricted functional sets of proteins, whose down‐regulation may interfere with general function of neuronal cells.

Network clustering revealed the systemic alterations of mitochondrial protein expression

The mitochondrial protein repertoire varies depending on the cellular state. Protein component modifications caused by mitochondrial DNA (mtDNA) depletion are related to a wide range of human diseases; however, little is known about how nuclear-encoded mitochondrial proteins (mt proteome) changes under such dysfunctional states. In this study, we investigated the systemic alterations of mtDNA-depleted (ρ0) mitochondria by using network analysis of gene expression data. By modularizing the quantified proteomics data into protein functional networks, systemic properties of mitochondrial dysfunction were analyzed. We discovered that up-regulated and down-regulated proteins were organized into two predominant subnetworks that exhibited distinct biological processes. The down-regulated network modules are involved in typical mitochondrial functions, while up-regulated proteins are responsible for mtDNA repair and regulation of mt protein expression and transport. Furthermore, comparisons of proteome and transcriptome data revealed that ρ0 cells attempted to compensate for mtDNA depletion by modulating the coordinated expression/transport of mt proteins. Our results demonstrate that mt protein composition changed to remodel the functional organization of mitochondrial protein networks in response to dysfunctional cellular states. Human mt protein functional networks provide a framework for understanding how cells respond to mitochondrial dysfunctions.