Abstract LB-006: Proteogenomic characterization of human colon cancer reveals new therapeutic opportunities

We prospectively collected matched tumor specimens, adjacent non-tumor tissues, and blood samples from 110 colon cancer patients and analyzed the samples using seven omics platforms, including whole-exome sequencing, copy number arrays, RNA-Seq, miRNA-Seq, label-free global proteomics, isobaric tandem mass tag (TMT) labeling-based global proteomics, and TMT-based phosphoproteomics. Comparative proteomic and phosphoproteomic analysis of paired tumor and adjacent normal samples produced the first comprehensive catalogue of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers and drug targets. These cancer-associated proteins and phosphosites had very little overlap with known cancer genes in the Cancer Gene Census, providing a novel information layer to our knowledge about colon cancer. One notable finding in differential proteome analysis is the identification of several cancer/testis antigens that were recurrently over-expressed in tumors compared to adjacent normal tissue, including IGF2BP3 (51%), SPAG1 (14%), and ATAD2 (8%). Through integrative analysis of the whole-exome sequencing, RNA-Seq, and proteomics data, we further predicted personalized neoantigens for 38% of the patients. In total, we found proteomics-supported neoantigens or cancer/testis antigens for 78% of the tumors in this cohort, demonstrating the potential of proteogenomics in identifying tumor antigens for cancer vaccine development. Proteomics data complemented somatic copy number analysis results and showed that multiple somatic copy number deletion events converge to repress the endocytosis pathway, suggesting its tumor suppressor role in colon cancer. In addition to reinforcing or complementing genomic findings, proteogenomic integration may also contradict genomics data-based inferences and lead to unexpected discoveries and therapeutic opportunities. Proteomics data identified SOX9 as an oncogene in colon cancer, whereas it was predicted to be a tumor suppressor based on somatic mutation data in the TCGA study. Phosphoproteomics data revealed a dual role of Rb phosphorylation in promoting proliferation and repressing apoptosis in colon cancer, clarifying the long-standing puzzle of colon cancer-specific amplification of this tumor suppressor and highlighting a unique opportunity for targeting Rb phosphorylation in colon cancer. Microsatellite instability status has been approved by the FDA as a biomarker for selecting patients for checkpoint inhibitor therapy in colorectal and other solid tumors. However, many MSI-high tumors fail to respond to checkpoint inhibition. Our proteogenomic analysis identified a subtype-specific association between increased glycolysis and decreased CD8 T cell infiltration in MSI-high colon tumors, suggesting glycolysis as a target for overcoming immune evasion in this MSI-H tumors. We make the primary and processed datasets available in publicly accessible data repositories and portals to allow broad use of these datasets for new biological discoveries and therapeutic hypothesis generation.

Citation Format: Bing Zhang, Suhas Vasaikar, Chen Huang, Xiaojing Wang, Vladislav A. Petyuk, Sara R. Savage, Bo Wen, Yongchao Dou, Yun Zhang, Zhiao Shi, Osama A. Arshad, Marina A. Gritsenko, Lisa J. Zimmerman, Jason E. McDermott, Therese R. Clauss, Ronald J. Moore, Rui Zhao, Matthew E. Monroe, Yi-Ting Wang, Matthew C. Chambers, Robbert J. Slebos, Ken S. Lau, Qianxing Mo, Li Ding, Matthew Ellis, Mathangi Thiagarajan, Christopher R. Kinsinger, Henry Rodriguez, Richard D. Smith, Karin D. Rodland, Daniel C. Liebler, Tao Liu, CPTAC Investigators. Proteogenomic characterization of human colon cancer reveals new therapeutic opportunities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-006.

Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities

We performed the first proteogenomic study on a prospectively collected colon cancer cohort. Comparative proteomic and phosphoproteomic analysis of paired tumor and normal adjacent tissues produced a catalog of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers, drug targets, and cancer/testis antigens. Proteogenomic integration not only prioritized genomically inferred targets, such as copy-number drivers and mutation-derived neoantigens, but also yielded novel findings. Phosphoproteomics data associated Rb phosphorylation with increased proliferation and decreased apoptosis in colon cancer, which explains why this classical tumor suppressor is amplified in colon tumors and suggests a rationale for targeting Rb phosphorylation in colon cancer. Proteomics identified an association between decreased CD8 T cell infiltration and increased glycolysis in microsatellite instability-high (MSI-H) tumors, suggesting glycolysis as a potential target to overcome the resistance of MSI-H tumors to immune checkpoint blockade. Proteogenomics presents new avenues for biological discoveries and therapeutic development.

Reassessment of Exosome Composition

The heterogeneity of small extracellular vesicles and presence of non-vesicular extracellular matter have led to debate about contents and functional properties of exosomes. Here, we employ high-resolution density gradient fractionation and direct immunoaffinity capture to precisely characterize the RNA, DNA, and protein constituents of exosomes and other non-vesicle material. Extracellular RNA, RNA-binding proteins, and other cellular proteins are differentially expressed in exosomes and non-vesicle compartments. Argonaute 1-4, glycolytic enzymes, and cytoskeletal proteins were not detected in exosomes. We identify annexin A1 as a specific marker for microvesicles that are shed directly from the plasma membrane. We further show that small extracellular vesicles are not vehicles of active DNA release. Instead, we propose a new model for active secretion of extracellular DNA through an autophagy- and multivesicular-endosome-dependent but exosome-independent mechanism. This study demonstrates the need for a reassessment of exosome composition and offers a framework for a clearer understanding of extracellular vesicle heterogeneity.

Abstract 2398: Tumor cell-adipocyte gap junctions activate lipolysis in breast cancer

During mammary tumorigenesis, a cell-cell interface exists between adipocytes and cancer cells. Several studies have demonstrated that breast tumor cells can secrete cytokines that induce lipolysis in adjacent adipocytes. However, evidence of tumor-adjacent lipolysis in clinical samples has been lacking. We therefore assayed for lipolysis in normal tissue adjacent to breast tumors (NAT) using (1) the three-component breast composition measure, a radiographic imaging method derived from dual-energy mammography that allows lipid content of a tissue to be quantified, on breast tumors and NAT from 46 patients, (2) a publically available dataset of gene expression in primary breast tumors and NAT from 9 patients, (3) laser capture microdissection and proteomics on primary breast tumors, stroma and NAT from 75 patients, and (4) immunoblot analysis of NAT from several patient-derived and transgenic mouse models of breast cancer. We found strong evidence in all cases that lipolysis is activated in breast cancer-adjacent adipose tissue. We next set out to model the breast cancer-adipocyte interface and determine the contribution of cell-cell contact to induced lipolysis. Gap junctions are cell-cell junctions formed by proteins called connexins, which are known to transport a variety of small molecules (<1kD) including cAMP, a critical pro-lipolytic signaling molecule. Using established dye transfer assays, we determined that gap junctions form between breast cancer cells, and between breast cancer cells and adipocytes. Using biochemical assays, we demonstrated that cAMP is a substrate of breast cancer cell gap junctions, that transfer of cAMP from breast cancer cells to adipocytes occurs, and that breast cancer cells activate lipolytic signaling, all in a gap junction-dependent manner. Finally, we found that gap junction communication in this context is dependent upon connexin 31 (Cx31), and we establish the importance of Cx31 for breast tumor growth and activation of lipolysis in tumor-adjacent adipose tissue in vivo.

Citation Format: Roman Camarda, Jeremy Williams, Serghei Malkov, Lisa J. Zimmerman, Suzanne Manning, Dvir Aran, Andrew Beardsley, Daniel Van de Mark, Jeffrey van Haren, Yong Chen, Charles Berdan, Sharon Louie, Celine Mahieu, Juliane Winkler, Elizabeth Willey, John D. Gagnon, Kosaku Shinoda, K. Mark Ansel, Zena Werb, Daniel C. Nomura, Shingo Kajimura, Torsten Wittmann, Atul J. Butte, Melinda E. Sanders, Daniel C. Liebler, Gregor Krings, John A. Shepherd, Andrei Goga. Tumor cell-adipocyte gap junctions activate lipolysis in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2398.

Quantitative Mass Spectrometry Analysis of PD-L1 Protein Expression, N-glycosylation and Expression Stoichiometry with PD-1 and PD-L2 in Human Melanoma

Quantitative assessment of key proteins that control the tumor-immune interface is one of the most formidable analytical challenges in immunotherapeutics. We developed a targeted MS platform to quantify programmed cell death-1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2) at fmol/microgram protein levels in formalin fixed, paraffin-embedded sections from 22 human melanomas. PD-L1 abundance ranged 50-fold, from ∼0.03 to 1.5 fmol/microgram protein and the parallel reaction monitoring (PRM) data were largely concordant with total PD-L1-positive cell content, as analyzed by immunohistochemistry (IHC) with the E1L3N antibody. PD-1 was measured at levels up to 20-fold lower than PD-L1, but the abundances were not significantly correlated (r² = 0.062, p = 0.264). PD-1 abundance was weakly correlated (r² = 0.3057, p = 0.009) with the fraction of lymphocytes and histiocytes in sections. PD-L2 was measured from 0.03 to 1.90 fmol/microgram protein and the ratio of PD-L2 to PD-L1 abundance ranged from 0.03 to 2.58. In 10 samples, PD-L2 was present at more than half the level of PD-L1, which suggests that PD-L2, a higher affinity PD-1 ligand, is sufficiently abundant to contribute to T-cell downregulation. We also identified five branched mannose and N-acetylglucosamine glycans at PD-L1 position N192 in all 22 samples. Extent of PD-L1 glycan modification varied by ∼10-fold and the melanoma with the highest PD-L1 protein abundance and most abundant glycan modification yielded a very low PD-L1 IHC estimate, thus suggesting that N-glycosylation may affect IHC measurement and PD-L1 function. Additional PRM analyses quantified immune checkpoint/co-regulator proteins LAG3, IDO1, TIM-3, VISTA, and CD40, which all displayed distinct expression independent of PD-1, PD-L1, and PD-L2. Targeted MS can provide a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics.

Colorectal Cancer Cell Line Proteomes Are Representative of Primary Tumors and Predict Drug Sensitivity

BACKGROUND AND AIMS

Proteomics holds promise for individualizing cancer treatment. We analyzed to what extent the proteomic landscape of human colorectal cancer (CRC) is maintained in established CRC cell lines and the utility of proteomics for predicting therapeutic responses.

METHODS

Proteomic and transcriptomic analyses were performed on 44 CRC cell lines, compared against primary CRCs (n=95) and normal tissues (n=60), and integrated with genomic and drug sensitivity data.

RESULTS

Cell lines mirrored the proteomic aberrations of primary tumors, in particular for intrinsic programs. Tumor relationships of protein expression with DNA copy number aberrations and signatures of post-transcriptional regulation were recapitulated in cell lines. The 5 proteomic subtypes previously identified in tumors were represented among cell lines. Nonetheless, systematic differences between cell line and tumor proteomes were apparent, attributable to stroma, extrinsic signaling, and growth conditions. Contribution of tumor stroma obscured signatures of DNA mismatch repair identified in cell lines with a hypermutation phenotype. Global proteomic data showed improved utility for predicting both known drug-target relationships and overall drug sensitivity as compared with genomic or transcriptomic measurements. Inhibition of targetable proteins associated with drug responses further identified corresponding synergistic or antagonistic drug combinations. Our data provide evidence for CRC proteomic subtype-specific drug responses.

CONCLUSIONS

Proteomes of established CRC cell line are representative of primary tumors. Proteomic data tend to exhibit improved prediction of drug sensitivity as compared with genomic and transcriptomic profiles. Our integrative proteogenomic analysis highlights the potential of proteome profiling to inform personalized cancer medicine.

Identification of Proteomic Features To Distinguish Benign Pulmonary Nodules from Lung Adenocarcinoma

We hypothesized that distinct protein expression features of benign and malignant pulmonary nodules may reveal novel candidate biomarkers for the early detection of lung cancer. We performed proteome profiling by liquid chromatography-tandem mass spectrometry to characterize 34 resected benign lung nodules, 24 untreated lung adenocarcinomas (ADCs), and biopsies of bronchial epithelium. Group comparisons identified 65 proteins that differentiate nodules from ADCs and normal bronchial epithelium and 66 proteins that differentiate ADCs from nodules and normal bronchial epithelium. We developed a multiplexed parallel reaction monitoring (PRM) assay to quantify a subset of 43 of these candidate biomarkers in an independent cohort of 20 benign nodules, 21 ADCs, and 20 normal bronchial biopsies. PRM analyses confirmed significant nodule-specific abundance of 10 proteins including ALOX5, ALOX5AP, CCL19, CILP1, COL5A2, ITGB2, ITGAX, PTPRE, S100A12, and SLC2A3 and significant ADC-specific abundance of CEACAM6, CRABP2, LAD1, PLOD2, and TMEM110-MUSTN1. Immunohistochemistry analyses for seven selected proteins performed on an independent set of tissue microarrays confirmed nodule-specific expression of ALOX5, ALOX5AP, ITGAX, and SLC2A3 and cancer-specific expression of CEACAM6. These studies illustrate the value of global and targeted proteomics in a systematic process to identify and qualify candidate biomarkers for noninvasive molecular diagnosis of lung cancer.

Abstract LB-056: Quantitative mass spectrometry analysis of immune checkpoint protein expression and N-glycosylation in human melanoma

Quantitative assessment of key proteins that control the tumor-immune interface is one of the most formidable analytical challenges in immunotherapeutics. We developed an targeted mass spectrometry (MS) platform to quantify programmed cell death-1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2) at fmol/microgram protein levels in formalin fixed, paraffin-embedded sections from 22 human melanomas. PD-L1 abundance ranged 50-fold, from approximately 0.03 to 1.5 fmol/microgram protein and the PRM data were largely concordant with total PD-L1-positive cell content, as analyzed by immunohistochemistry (IHC) with the E1L3N antibody. PD-1 was measured at levels up to 20-fold lower than PD-L1, but the abundances were not significantly correlated (r2 = 0.062, p = 0.264). PD-1 abundance was weakly correlated (r2 = 0.3057, p = 0.009) with the fraction of lymphocytes/histiocytes in sections. PD-L2 was measured from 0.03 to 1.90 fmol/microgram protein and the ratio of PD-L2 to PD-L1 abundance ranged from 0.03 to 2.58. In 8 samples, PD-L2 was present at more than half the level of PD-L1, which suggests that PD-L2, a higher affinity PD-1 ligand, is sufficiently abundant to contribute to T-cell downregulation. We also identified five branched mannose and N-acetylglucosamine glycans at PD-L1 position N192 in all 22 samples. Extent of PD-L1 glycan modification varied by approximately 10-fold and the melanoma with the highest PD-L1 protein abundance and most abundant glycan modification yielded a very low PD-L1 IHC estimate, thus suggesting that N-glycosylation may affect IHC measurement and PD-L1 function. Additional PRM analyses quantified immune checkpoint/co-regulator proteins LAG3, IDO1, TIM-3, VISTA and CD40, which all displayed distinct expression independent of PD-1, PD-L1 and PD-L2. Targeted MS can provide a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics. (Supported by NIH grant U24CA159988)

Citation Format: Carlos Morales Betanzos, Hyoungjoo Lee, Paula I. Gonzalez Ericsson, Justin M. Balko, Douglas B. Johnson, Lisa J. Zimmerman, Daniel C. Liebler. Quantitative mass spectrometry analysis of immune checkpoint protein expression and N-glycosylation in human melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-056. doi:10.1158/1538-7445.AM2017-LB-056

WITHDRAWN: Quantitative mass spectrometry analysis of PD-L1 protein expression, N-glycosylation and expression stoichiometry with PD-1 and PD-L2 in human melanoma

This article has been withdrawn by the authors. We discovered an error after this manuscript was published as a Paper in Press. Specifically, we learned that the structures of glycans presented for the PD-L1 peptide were drawn and labeled incorrectly. We wish to withdraw this article and submit a corrected version for review.

The airway epithelium undergoes metabolic reprogramming in individuals at high risk for lung cancer

The molecular determinants of lung cancer risk remain largely unknown. Airway epithelial cells are prone to assault by risk factors and are considered to be the primary cell type involved in the field of cancerization. To investigate risk-associated changes in the bronchial epithelium proteome that may offer new insights into the molecular pathogenesis of lung cancer, proteins were identified in the airway epithelial cells of bronchial brushing specimens from risk-stratified individuals by shotgun proteomics. Differential expression of selected proteins was validated by parallel reaction monitoring mass spectrometry in an independent set of individual bronchial brushings. We identified 2,869 proteins, of which 312 proteins demonstrated a trend in expression. Pathway analysis revealed enrichment of carbohydrate metabolic enzymes in high-risk individuals. Glucose consumption and lactate production were increased in human bronchial epithelial BEAS2B cells treated with cigarette smoke condensate for 7 months. Increased lipid biosynthetic capacity and net reductive carboxylation were revealed by metabolic flux analyses of [U-¹³C₅] glutamine in this in vitro model, suggesting profound metabolic reprogramming in the airway epithelium of high-risk individuals. These results provide a rationale for the development of potentially new chemopreventive strategies and selection of patients for surveillance programs.

Oncogenic KRAS and BRAF Drive Metabolic Reprogramming in Colorectal Cancer

Metabolic reprogramming, in which altered utilization of glucose and glutamine supports rapid growth, is a hallmark of most cancers. Mutations in the oncogenes KRAS and BRAF drive metabolic reprogramming through enhanced glucose uptake, but the broader impact of these mutations on pathways of carbon metabolism is unknown. Global shotgun proteomic analysis of isogenic DLD-1 and RKO colon cancer cell lines expressing mutant and wild type KRAS or BRAF, respectively, failed to identify significant differences (at least 2-fold) in metabolic protein abundance. However, a multiplexed parallel reaction monitoring (PRM) strategy targeting 73 metabolic proteins identified significant protein abundance increases of 1.25-twofold in glycolysis, the nonoxidative pentose phosphate pathway, glutamine metabolism, and the phosphoserine biosynthetic pathway in cells with KRAS G13D mutations or BRAF V600E mutations. These alterations corresponded to mutant KRAS and BRAF-dependent increases in glucose uptake and lactate production. Metabolic reprogramming and glucose conversion to lactate in RKO cells were proportional to levels of BRAF V600E protein. In DLD-1 cells, these effects were independent of the ratio of KRAS G13D to KRAS wild type protein. A study of 8 KRAS wild type and 8 KRAS mutant human colon tumors confirmed the association of increased expression of glycolytic and glutamine metabolic proteins with KRAS mutant status. Metabolic reprogramming is driven largely by modest (<2-fold) alterations in protein expression, which are not readily detected by the global profiling methods most commonly employed in proteomic studies. The results indicate the superiority of more precise, multiplexed, pathway-targeted analyses to study functional proteome systems. Data are available through MassIVE Accession MSV000079486 at ftp://MSV000079486@massive.ucsd.edu.

Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays

BACKGROUND

For many years, basic and clinical researchers have taken advantage of the analytical sensitivity and specificity afforded by mass spectrometry in the measurement of proteins. Clinical laboratories are now beginning to deploy these work flows as well. For assays that use proteolysis to generate peptides for protein quantification and characterization, synthetic stable isotope-labeled internal standard peptides are of central importance. No general recommendations are currently available surrounding the use of peptides in protein mass spectrometric assays.

CONTENT

The Clinical Proteomic Tumor Analysis Consortium of the National Cancer Institute has collaborated with clinical laboratorians, peptide manufacturers, metrologists, representatives of the pharmaceutical industry, and other professionals to develop a consensus set of recommendations for peptide procurement, characterization, storage, and handling, as well as approaches to the interpretation of the data generated by mass spectrometric protein assays. Additionally, the importance of carefully characterized reference materials-in particular, peptide standards for the improved concordance of amino acid analysis methods across the industry-is highlighted. The alignment of practices around the use of peptides and the transparency of sample preparation protocols should allow for the harmonization of peptide and protein quantification in research and clinical care.

Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Comprehensive Characterization of Glycosylation and Hydroxylation of Basement Membrane Collagen IV by High-Resolution Mass Spectrometry

Collagen IV is the main structural protein that provides a scaffold for assembly of basement membrane proteins. Posttranslational modifications such as hydroxylation of proline and lysine and glycosylation of lysine are essential for the functioning of collagen IV triple-helical molecules. These modifications are highly abundant posing a difficult challenge for in-depth characterization of collagen IV using conventional proteomics approaches. Herein, we implemented an integrated pipeline combining high-resolution mass spectrometry with different fragmentation techniques and an optimized bioinformatics workflow to study posttranslational modifications in mouse collagen IV. We achieved 82% sequence coverage for the α1 chain, mapping 39 glycosylated hydroxylysine, 148 4-hydroxyproline, and seven 3-hydroxyproline residues. Further, we employed our pipeline to map the modifications on human collagen IV and achieved 85% sequence coverage for the α1 chain, mapping 35 glycosylated hydroxylysine, 163 4-hydroxyproline, and 14 3-hydroxyproline residues. Although lysine glycosylation heterogeneity was observed in both mouse and human, 21 conserved sites were identified. Likewise, five 3-hydroxyproline residues were conserved between mouse and human, suggesting that these modification sites are important for collagen IV function. Collectively, these are the first comprehensive maps of hydroxylation and glycosylation sites in collagen IV, which lay the foundation for dissecting the key role of these modifications in health and disease.

Abstract 2000: Proteomic features of histological compartments in colorectal carcinoma

Proteomic analysis of cancer tissues by mass spectrometry (MS) is complicated by the fact that histological context is lost in the analysis. Knowledge on the abundance of key proteins for the different histological compartments may allow an assessment of the contribution of each of these components to the proteomic profile obtained. We studied 18 colorectal carcinoma specimens and isolated carcinoma, necrosis, normal epithelium, stroma, smooth muscle, and lymphoid infiltrate compartments using laser capture microdissection (LCM). Proteins extracted from 60 LCM caps were subjected to short-stack, gel electrophoresis, in-gel trypsin digestion and analyzed on a Thermo-Fisher QExactive Orbitrap MS instrument. Data were searched using myrimatch and MS-GF+ on a RefSeq protein database and identified proteins were assembled using IDpicker 3. The analysis identified about 2,000 non-redundant proteins at a protein FDR&lt;5%. Unsupervised cluster analysis of the most abundant proteins clustered each of the compartments together with few exceptions. Surprisingly, the necrotic compartment was almost identical from the carcinoma compartment, indicating the stability of the small peptides used for MS sequence identifications. Comparisons of spectral count data between each of the compartments and the remainder of the dataset by protein enrichment analyses was performed using the online tool www.webgestalt.org. The carcinoma compartment was enriched for proteins involved in nucleic acid and general metabolism processes. Smooth muscle was enriched for proteins involved in muscle contraction and cell adhesion. The lymphoid infiltrates were enriched for chromatin and nucleosome proteins, possibly indicating the relative contribution of nuclear proteins from these small cells. The stromal component was enriched for extracellular matrix proteins and proteins involved in glycosylation processes. Using data from ProteinAtlas.org, we confirmed histological associations of the most prominent protein markers with their respective histological component. For instance, COL12A1 was highly expressed in the stromal compartment, while SMTN was highly specific for smooth muscle. Expression levels characterizing each of the histological components can thus be described in protein signatures that can serve as a measure of the relative contribution of each of the components in the complex composition of a colorectal carcinoma sample.

Supported by NIH/NCI grant U24CA159988.

Citation Format: Robbert JC Slebos, Lisa J. Zimmerman, Suzanne Manning, Melinda E. Sanders, Chanjuan Shi, M Kay Washington, Daniel C. Liebler. Proteomic features of histological compartments in colorectal carcinoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2000. doi:10.1158/1538-7445.AM2015-2000

Activating PIK3CA Mutations Induce an Epidermal Growth Factor Receptor (EGFR)/Extracellular Signal-regulated Kinase (ERK) Paracrine Signaling Axis in Basal-like Breast Cancer

Mutations in PIK3CA, the gene encoding the p110α catalytic subunit of phosphoinositide 3-kinase (PI3K) have been shown to transform human mammary epithelial cells (MECs). These mutations are present in all breast cancer subtypes, including basal-like breast cancer (BLBC). Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified 72 protein expression changes in human basal-like MECs with knock-in E545K or H1047R PIK3CA mutations versus isogenic MECs with wild-type PIK3CA. Several of these were secreted proteins, cell surface receptors or ECM interacting molecules and were required for growth of PIK3CA mutant cells as well as adjacent cells with wild-type PIK3CA. The proteins identified by MS were enriched among human BLBC cell lines and pointed to a PI3K-dependent amphiregulin/EGFR/ERK signaling axis that is activated in BLBC. Proteins induced by PIK3CA mutations correlated with EGFR signaling and reduced relapse-free survival in BLBC. Treatment with EGFR inhibitors reduced growth of PIK3CA mutant BLBC cell lines and murine mammary tumors driven by a PIK3CA mutant transgene, all together suggesting that PIK3CA mutations promote tumor growth in part by inducing protein changes that activate EGFR.

Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

Wavelet-based peak detection and a new charge inference procedure for MS/MS implemented in ProteoWizard's msConvert

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1–100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets.

Abstract B015: Knock-in of PIK3CA mutations in MCF10A mammary epithelial cells modifies their proteomic profile to resemble basal-like breast cancer and stimulate EGFR-dependent cell proliferation

PIK3CA, the gene encoding the p110α catalytic subunit of phosphatidylinositol-3 kinase (PI3K), is frequently mutated in breast cancer. Activating mutations in PIK3CA are known to transform mammary epithelial cells (MECs). Genomic knock-in of the two most frequent hot-spot PIK3CA mutations (E545K or H1047R) into MCF10A MECs resulted in growth factor-independent proliferation. Shotgun LC-MS/MS mass spectrometry analysis of wild type, E545K and H1047R MCF10A cell lysates revealed 73 proteins uniquely altered in the both mutant cell lines compared to wild type cells. KEGG pathway analysis demonstrated that PIK3CA mutant cells have elevated levels of proteins involved in focal adhesion, ECM-receptor interactions and actin cytoskeleton regulation. Nearly half the proteins upregulated in the mutant cells are secreted or involved in extracellular matrix (ECM) processing or signaling. The EGFR ligand amphiregulin was five-fold higher in the conditioned media harvested from PIK3CA mutant cells as compared to wild type cells. The conditioned media of PIK3CA mutant cells, but not that of wild-type cells, was sufficient to stimulate proliferation and EGFR phosphorylation in wild type MCF10A cells. Proliferation and EGFR activation were inhibited with an amphiregulin-neutralizing antibody or with EGFR neutralizing antibodies and kinase inhibitors. PIK3CA mutant cells downregulated PTPRF, a receptor tyrosine phosphatase. EGFR signaling and proliferation were stimulated in wild type cells when PTPRF was downregulated with siRNA, suggesting that PIK3CA mutant MCF10A cells activate EGFR-dependent proliferation by suppression of a negative regulatory phosphatase and increased secretion of amphiregulin.

The expression of transglutaminase 2, peroxidasin, fibronectin, integrin α5, laminin β3, laminin γ2, thrombospondin and EphA2, eight proteins upregulated in PIK3CA mutant MCF10A cells, was evaluated in a panel of breast cancer cell lines. All eight proteins were more highly expressed in basal-like compared to luminal-like breast cancer cell lines. The expression of PTPRF, which is decreased in PIK3CA mutant MCF10A cells, was lower in basal-like cell lines. Interrogation of microarray data demonstrated that the RNA signal of proteins upregulated in mutant PIK3CA MCF10A cells correlated with decreased relapse-free survival in basal-like, but not in luminal-like breast cancer. siRNA-mediated silencing of peroxidasin, laminin γ2, EphA2, integrin β1 or amphiregulin reduced the proliferation of PIK3CA mutant MCF10A cells, suggesting that these proteins are necessary for maintenance of the transformed phenotype. siRNA-mediated silencing of peroxidasin and EphA2 proteins also reduces the proliferation of basal-like breast cancer cells. Our proteomic analysis of PIK3CA mutant MCF10A cells revealed mechanisms of autocrine and paracrine induced proliferation and alterations mostly limited to basal-like breast cancer cells. These may serve as therapeutic targets in this subtype of breast cancer.

Citation Format: Christian D. Young, Lisa J. Zimmerman, Corbin A. Whitwell, Ariella B. Hanker, Thomas Stricker, Dana M. Brantley-Sieders, Ben Ho Park, Daniel C. Liebler, Rebecca S. Cook, Carlos L. Arteaga. Knock-in of PIK3CA mutations in MCF10A mammary epithelial cells modifies their proteomic profile to resemble basal-like breast cancer and stimulate EGFR-dependent cell proliferation. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr B015.

Analysis of the Staphylococcus aureus abscess proteome identifies antimicrobial host proteins and bacterial stress responses at the host-pathogen interface

Abscesses are a hallmark of invasive staphylococcal infections and the site of a dynamic struggle between pathogen and host. However, the precise host and bacterial factors that contribute to abscess formation and maintenance have not been completely described. In this work, we define the Staphylococcus aureus abscess proteome from both wild-type and neutropenic mice to elucidate the host response to staphylococcal infection and uncover novel S. aureus virulence factors. Among the proteins identified, the mouse protein histone H4 was enriched in the abscesses of wild-type compared with neutropenic animals. Histone H4 inhibits staphylococcal growth in vitro demonstrating a role for this protein in the innate immune response to staphylococcal infection. These analyses also identified staphylococcal proteins within the abscess, including known virulence factors and proteins with previously unrecognized roles in pathogenesis. Within the latter group was the universal stress protein Usp2, which was enriched in kidney lesions from neutropenic mice and required for the S. aureus response to stringent stress. Taken together, these data describe the S. aureus abscess proteome and lay the foundation for the identification of contributors to innate immunity and bacterial pathogenesis.

Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS)

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

Targeted quantitation of proteins by mass spectrometry

Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement.

In-depth proteomic analysis of nonsmall cell lung cancer to discover molecular targets and candidate biomarkers

Advances in proteomic analysis of human samples are driving critical aspects of biomarker discovery and the identification of molecular pathways involved in disease etiology. Toward that end, in this report we are the first to use a standardized shotgun proteomic analysis method for in-depth tissue protein profiling of the two major subtypes of nonsmall cell lung cancer and normal lung tissues. We identified 3621 proteins from the analysis of pooled human samples of squamous cell carcinoma, adenocarcinoma, and control specimens. In addition to proteins previously shown to be implicated in lung cancer, we have identified new pathways and multiple new differentially expressed proteins of potential interest as therapeutic targets or diagnostic biomarkers, including some that were not identified by transcriptome profiling. Up-regulation of these proteins was confirmed by multiple reaction monitoring mass spectrometry. A subset of these proteins was found to be detectable and differentially present in the peripheral blood of cases and matched controls. Label-free shotgun proteomic analysis allows definition of lung tumor proteomes, identification of biomarker candidates, and potential targets for therapy.

Global stability of plasma proteomes for mass spectrometry-based analyses

Peptide-based mass spectrometry approaches, such as multiple reaction monitoring, provide a powerful means to measure candidate protein biomarkers in plasma. A potential confounding problem is the effect of preanalytical variables, which may affect the integrity of proteins and peptides. Although some blood proteins undergo rapid physiological proteolysis ex vivo, the stability of most plasma proteins to preanalytical variables remains largely unexplored. We applied liquid chromatography-tandem mass spectrometry shotgun proteomics and multiple reaction monitoring analyses to characterize the stability of proteins at the peptide level in plasma. We systematically evaluated the effects of delay in plasma preparation at different temperatures, multiple freeze-thaw cycles and erythocyte hemolysis on peptide and protein inventories in prospectively collected human plasma. Time course studies indicated few significant changes in peptide and protein identifications, semitryptic peptides and methionine-oxidized peptides in plasma from blood collected in EDTA plasma tubes and stored for up to a week at 4 °C or room temperature prior to plasma isolation. Similarly, few significant changes were observed in similar analyses of plasma subjected to up to 25 freeze-thaw cycles. Hemolyzed samples produced no significant differences beyond the presence of hemoglobin proteins. Finally, paired comparisons of plasma and serum samples prepared from the same patients also yielded few significant differences, except for the depletion of fibrinogen in serum. Blood proteins thus are broadly stable to preanalytical variables when analyzed at the peptide level. Collection protocols to generate plasma for multiple reaction monitoring-based analyses may have different requirements than for other analyses directed at intact proteins.

Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells

Because MYC plays a causal role in many human cancers, including those with hypoxic and nutrient-poor tumor microenvironments, we have determined the metabolic responses of a MYC-inducible human Burkitt lymphoma model P493 cell line to aerobic and hypoxic conditions, and to glucose deprivation, using stable isotope-resolved metabolomics. Using [U-(13)C]-glucose as the tracer, both glucose consumption and lactate production were increased by MYC expression and hypoxia. Using [U-(13)C,(15)N]-glutamine as the tracer, glutamine import and metabolism through the TCA cycle persisted under hypoxia, and glutamine contributed significantly to citrate carbons. Under glucose deprivation, glutamine-derived fumarate, malate, and citrate were significantly increased. Their (13)C-labeling patterns demonstrate an alternative energy-generating glutaminolysis pathway involving a glucose-independent TCA cycle. The essential role of glutamine metabolism in cell survival and proliferation under hypoxia and glucose deficiency makes them susceptible to the glutaminase inhibitor BPTES and hence could be targeted for cancer therapy.

Chemoresistant colorectal cancer cells and cancer stem cells mediate growth and survival of bystander cells

BACKGROUND

Recent studies suggest that cancer stem cells (CSCs) mediate chemoresistance, but interestingly, only a small percentage of cells in a resistant tumour are CSCs; this suggests that non-CSCs survive by other means. We hypothesised that chemoresistant colorectal cancer (CRC) cells generate soluble factors that enhance survival of chemonaive tumour cells.

METHODS

Chemoresistant CRC cells were generated by serial passage in oxaliplatin (Ox cells). Conditioned media (CM) was collected from parental and oxaliplatin-resistant (OxR) cells. CRC cells were treated with CM and growth and survival were assessed. Tumour growth rates were determined in nude mice after cells were treated with CM. Mass spectrometry (MS) identified proteins in CM. Reverse phase protein microarray assays determined signalling effects of CM in parental cells.

RESULTS

Oxaliplatin-resistant CM increased survival of chemo-naive cells. CSC CM also increased growth of parental cells. Parental and OxR mixed tumours grew larger than tumours composed of parental or OxR cells alone. Mass spectrometry detected unique survival-promoting factors in OxR CM compared with parental CM. Cells treated with OxR CM demonstrated early phosphorylation of EGFR and MEK1, with later upregulation of total Akt .We identified progranulin as a potential mediator of chemoresistance.

CONCLUSION

Chemoresistant tumour cells and CSCs may promote resistance through soluble factors that mediate survival in otherwise chemosensitive tumour cells.

Lung cancer diagnosis from proteomic analysis of preinvasive lesions

Early detection may help improve survival from lung cancer. In this study, our goal was to derive and validate a signature from the proteomic analysis of bronchial lesions that could predict the diagnosis of lung cancer. Using previously published studies of bronchial tissues, we selected a signature of nine matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) mass-to-charge ratio features to build a prediction model diagnostic of lung cancer. The model was based on MALDI MS signal intensity (MALDI score) from bronchial tissue specimens from our 2005 published cohort of 51 patients. The performance of the prediction model in identifying lung cancer was tested in an independent cohort of bronchial specimens from 60 patients. The probability of having lung cancer based on the proteomic analysis of the bronchial specimens was characterized by an area under the receiver operating characteristic curve of 0.77 (95% CI 0.66-0.88) in this validation cohort. Eight of the nine features were identified and validated by Western blotting and immunohistochemistry. These results show that proteomic analysis of endobronchial lesions may facilitate the diagnosis of lung cancer and the monitoring of high-risk individuals for lung cancer in surveillance and chemoprevention trials.

Abstract 2799: Unexpected sustained hypoxic glutamine metabolism and therapeutic opportunities

Rationale: As the result of genetic alterations and tumor hypoxia, cancer cells re-program metabolism to meet increased energy demand for enhanced anabolism, cell proliferation, and protection from oxidative damage and cell death signals. Whereas glycolysis and its regulation by the MYC oncogene product (Myc) have been intensively studied, glutaminolysis and anapleurosis, especially under hypoxia, have not been defined.

Objectives: We sought to determine whether glutamine, a key source of nitrogen and anabolic carbon skeleton for mammalian cells, is still utilized under hypoxic condition and how it is regulated by MYC.

Methods: We used NMR and FT-ICR-MS to resolve 13C and 15N labeling patterns of metabolites derived from labeled glutamine or glucose in the P493 human B lymphoma model that bear a tetracycline-repressible MYC, under normoxic and hypoxic conditions. Levels of specific enzymes, which are involved in glucose and glutamine metabolism, were determined by immunoblotting and LC-MRM-MS and compared with the metabolomic profiles.

Measurements and Main Results: Myc regulates almost the entire glycolytic pathway. As expected for hypoxia, many glycolytic enzymes levels and lactate production were elevated, and 13C- glucose catabolism by the TCA cycle was significantly diminished. Myc elevated glutaminase (GLS, which converts glutamine to glutamate and NH4+), the glutamine transporter SLC1A5, and the transaminases GOT1 and GPT2, suggesting that transamination is favored with Myc activation. While GLS-mediated NH4+ release persisted under hypoxia, the Myc-induced transaminases favor the production of α-ketoglutarate without additional NH4+ production. The 13C labeling pattern of Ala is consistent with active mitochondrial GPT2 that transaminates 13C-pyruvate derived from 13C- glucose. Given that mitochondrial function is generally believed to be diminished by hypoxia, glutamine metabolism unexpectedly persisted in hypoxia with continued oxidation of glutamine carbons by the TCA cycle. The key enzymes and main products of 13C labeled glutamine were not decreased by hypoxia, and glutamine contributed to substantial de novo glutathione production in hypoxia. Because glutamine metabolism is sustained in hypoxia, which is pervasive in the tumor microenvironment, we sought to target glutaminase in vivo. We found that small molecule inhibition of glutaminase could diminish lymphoma and pancreatic cancer xenograft growth in vivo.

Conclusions: Our studies reveal a previously unsuspected sustained glutamine metabolism in hypoxia. Glutamine contributes to TCA cycle carbons as well as enhances glutathione synthesis in hypoxia, suggesting that cancer cells reprogram metabolism via both glucose and glutamine to adapt to the tumor microenvironment. Our findings indicate that key nodal points in glutamine metabolism in addition to those in glycolysis could be targeted for therapy.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2799. doi:10.1158/1538-7445.AM2011-2799

Methods for peptide and protein quantitation by liquid chromatography-multiple reaction monitoring mass spectrometry

Liquid chromatography-multiple reaction monitoring mass spectrometry of peptides using stable isotope dilution (SID) provides a powerful tool for targeted protein quantitation. However, the high cost of labeled peptide standards for SID poses an obstacle to multiple reaction monitoring studies. We compared SID to a labeled reference peptide (LRP) method, which uses a single labeled peptide as a reference standard for all measured peptides, and a label-free (LF) approach, in which quantitation is based on analysis of un-normalized peak areas for detected MRM transitions. We analyzed peptides from the Escherichia coli proteins alkaline phosphatase and β-galactosidase spiked into lysates from human colon adenocarcinoma RKO cells. We also analyzed liquid chromatography-multiple reaction monitoring mass spectrometry data from a recently published interlaboratory study by the National Cancer Institute Clinical Proteomic Technology Assessment for Cancer network (Addona et al. (2009) Nat. Biotechnol. 27: 633-641), in which unlabeled and isotopically labeled synthetic peptides or their corresponding proteins were spiked into human plasma. SID displayed the highest correlation coefficients and lowest coefficient of variation in regression analyses of both peptide and protein spike studies. In protein spike experiments, median coefficient of variation values were about 10% for SID and 20-30% for LRP and LF methods. Power calculations indicated that differences in measurement error between the methods have much less impact on measured protein expression differences than biological variation. All three methods detected significant (p < 0.05) differential expression of three endogenous proteins in a test set of 10 pairs of human lung tumor and control tissues. Further, the LRP and LF methods both detected significant differences (p < 0.05) in levels of seven biomarker candidates between tumors and controls in the same set of lung tissue samples. The data indicate that the LRP and LF methods provide cost-effective alternatives to SID for many quantitative liquid chromatography-multiple reaction monitoring mass spectrometry applications.

TagRecon: high-throughput mutation identification through sequence tagging

Shotgun proteomics produces collections of tandem mass spectra that contain all the data needed to identify mutated peptides from clinical samples. Identifying these sequence variations, however, has not been feasible with conventional database search strategies, which require exact matches between observed and expected sequences. Searching for mutations as mass shifts on specified residues through database search can incur significant performance penalties and generate substantial false positive rates. Here we describe TagRecon, an algorithm that leverages inferred sequence tags to identify unanticipated mutations in clinical proteomic data sets. TagRecon identifies unmodified peptides as sensitively as the related MyriMatch database search engine. In both LTQ and Orbitrap data sets, TagRecon outperformed state of the art software in recognizing sequence mismatches from data sets with known variants. We developed guidelines for filtering putative mutations from clinical samples, and we applied them in an analysis of cancer cell lines and an examination of colon tissue. Mutations were found in up to 6% of identified peptides, and only a small fraction corresponded to dbSNP entries. The RKO cell line, which is DNA mismatch repair deficient, yielded more mutant peptides than the mismatch repair proficient SW480 line. Analysis of colon cancer tumor and adjacent tissue revealed hydroxyproline modifications associated with extracellular matrix degradation. These results demonstrate the value of using sequence tagging algorithms to fully interrogate clinical proteomic data sets.

Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.

Abstract 2727: Predicting lung cancer risk based on a novel proteomic signature of bronchial lesions

A biomarker signature to identify individuals at-risk for lung cancer would be of great clinical value. We hypothesized that the bronchial epithelium expresses a subset of proteins that once increased confer an elevated risk for lung cancer. We have therefore developed a proteomic approach to assess the risk for lung cancer. From our previous studies, we selected 11 matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) features to distinguish normal bronchial epithelium and low grade preinvasive lesions from high grade preinvasive lesions and invasive lung tumors. We tested this signature in an independent validation set consisting of bronchial specimens from 60 patients. The prediction accuracy was 78% with 73% sensitivity and 81% specificity. There was a 19-fold increased risk of having lung cancer for individuals with a signature intensity above the third quartile (95% CI, 5.65-64.81). We identified 10 of the 11 features corresponding to 7 proteins, thymosin ß4, ubiquitin, acyl-coA binding protein, cystatin A, S100A11, cytochrome c and macrophage migration inhibitory factor. The identity of these proteins was validated by immunohistochemistry, Western blotting and MALDI imaging mass spectrometry (IMS). MALDI IMS localized the candidate biomarker proteins specifically to high grade preinvasive lesions and invasive tumors. This novel proteomic signature may facilitate the selection and monitoring of high risk individuals for lung cancer early detection and chemoprevention strategies.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2727.

Abstract 3746: Proteomic analysis of laser capture microdissected cells from basal, Her 2 positive and luminal A human breast tumors

The analysis of tissue is often confounded by the heterogenous nature, small size of biopsies, and focal presence of tumors. The use of laser capture microdissection (LCM) allows for isolation of nearly pure cell populations enhancing specificity of subsequent analyses. A method developed in our laboratory facilitating the removal of adhered cells utilizing SDS-PAGE followed by in-gel digestion and tandem mass spectrometry was applied to LCM-acquired cells from Basal, Her 2 positive and Luminal A breast tumor tissues. Cells were LCM-acquired from frozen tissue sections corresponding to Basal, Her 2 positive or Luminal A human breast tumor tissue. The sample set consisted of 3 tumors per subgroup with 3 caps per tumor, for a total of 27 caps each containing approximately 10,000 cells corresponding to 3-5 μg protein. The thermoplastic membranes containing the captured cells were peeled from the cap and suspended in SDS loading buffer and gently heated for 10 minutes. The solubilized proteins were electrophoresed 2 cm into a 10-20% Tricine gel followed by in-gel trypsin digestion and peptide extraction. Tryptic peptides were analyzed by reversed-phase (RP) liquid chromatography-tandem mass spectrometry (LC-MS-MS) on a Thermo Orbitrap instrument. Following LC/MS/MS analysis of the LCM digests, tandem spectra were searched against the human IPI database using the search algorithm, Myrimatch, and the search results filtered using IDPicker. A spectral counting approach was applied to the data-dependent data to compare quantitative differences of proteins identified. A total of 91646 spectra were confidently identified which corresponded to 1671 protein groups across all biological and technical replicates. An average of 545, 543, and 610 protein groups were identified in the basal, Her 2 positive, and Luminal A subtypes, respectively, from an equivalent of roughly 800 cells. Spectral count differences between datasets between normal and tumor samples were analyzed using both a Quasi-likelihood Poisson regression model, developed in-house, in addition to using the Limma package in Bioconductor. Using the criteria of a False Discovery Rate (FDR) &lt; 0.05, a total of 90 proteins showed statistically significant differences in expression among the breast tumor subtypes. A hierarchical clustering of these proteins was performed, creating a heat map representing the gene expression patterns of these proteins. As expected, ERBB2 was identified in the Her 2 positive tumor tissue samples; however, this protein was not identified in either the Basal or Luminal A samples. The proteins identified which were found to distinguish each tissue subtype are currently being investigated for their biological relevance in breast cancer pathways and as possible prognostic and predictive biomarkers.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3746.

Interlaboratory study characterizing a yeast performance standard for benchmarking LC-MS platform performance

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize pre-analytical and analytical variation in comparative proteomics experiments.

Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.

IDPicker 2.0: Improved protein assembly with high discrimination peptide identification filtering

Tandem mass spectrometry-based shotgun proteomics has become a widespread technology for analyzing complex protein mixtures. A number of database searching algorithms have been developed to assign peptide sequences to tandem mass spectra. Assembling the peptide identifications to proteins, however, is a challenging issue because many peptides are shared among multiple proteins. IDPicker is an open-source protein assembly tool that derives a minimum protein list from peptide identifications filtered to a specified False Discovery Rate. Here, we update IDPicker to increase confident peptide identifications by combining multiple scores produced by database search tools. By segregating peptide identifications for thresholding using both the precursor charge state and the number of tryptic termini, IDPicker retrieves more peptides for protein assembly. The new version is more robust against false positive proteins, especially in searches using multispecies databases, by requiring additional novel peptides in the parsimony process. IDPicker has been designed for incorporation in many identification workflows by the addition of a graphical user interface and the ability to read identifications from the pepXML format. These advances position IDPicker for high peptide discrimination and reliable protein assembly in large-scale proteomics studies. The source code and binaries for the latest version of IDPicker are available from http://fenchurch.mc.vanderbilt.edu/ .

Network-assisted protein identification and data interpretation in shotgun proteomics

Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence, that is, confident proteins, are reported, whereas many possible proteins of biological interest are eliminated. We have developed a clique-enrichment approach (CEA) to rescue eliminated proteins by incorporating the relationship among proteins as embedded in a protein interaction network. In several data sets tested, CEA increased protein identification by 8–23% with an estimated accuracy of 85%. Rescued proteins were supported by existing literature or transcriptome profiling studies at similar levels as confident proteins and at a significantly higher level than abandoned ones. Applying CEA on a breast cancer data set, rescued proteins coded by well-known breast cancer genes. In addition, CEA generated a network view of the proteins and helped show the modular organization of proteins that may underpin the molecular mechanisms of the disease.

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low mug/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.

Evaluation of strong cation exchange versus isoelectric focusing of peptides for multidimensional liquid chromatography-tandem mass spectrometry

Shotgun proteome analysis platforms based on multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a powerful means to discover biomarker candidates in tissue specimens. Analysis platforms must balance sensitivity for peptide detection, reproducibility of detected peptide inventories and analytical throughput for protein amounts commonly present in tissue biospecimens (< 100 microg), such that platform stability is sufficient to detect modest changes in complex proteomes. We compared shotgun proteomics platforms by analyzing tryptic digests of whole cell and tissue proteomes using strong cation exchange (SCX) and isoelectric focusing (IEF) separations of peptides prior to LC-MS/MS analysis on a LTQ-Orbitrap hybrid instrument. IEF separations provided superior reproducibility and resolution for peptide fractionation from samples corresponding to both large (100 microg) and small (10 microg) protein inputs. SCX generated more peptide and protein identifications than did IEF with small (10 microg) samples, whereas the two platforms yielded similar numbers of identifications with large (100 microg) samples. In nine replicate analyses of tryptic peptides from 50 microg colon adenocarcinoma protein, overlap in protein detection by the two platforms was 77% of all proteins detected by both methods combined. IEF more quickly approached maximal detection, with 90% of IEF-detectable medium abundance proteins (those detected with a total of 3-4 peptides) detected within three replicate analyses. In contrast, the SCX platform required six replicates to detect 90% of SCX-detectable medium abundance proteins. High reproducibility and efficient resolution of IEF peptide separations make the IEF platform superior to the SCX platform for biomarker discovery via shotgun proteomic analyses of tissue specimens.

Diagnostic accuracy of MALDI mass spectrometric analysis of unfractionated serum in lung cancer

PURPOSE

There is a critical need for improvements in the noninvasive diagnosis of lung cancer. We hypothesized that matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) analysis of the most abundant peptides in the serum may distinguish lung cancer cases from matched controls.

PATIENTS AND METHODS

We used MALDI MS to analyze unfractionated serum from a total of 288 cases and matched controls split into training (n = 182) and test sets (n = 106). We used a training-testing paradigm with application of the model profile defined in a training set to a blinded test cohort.

RESULTS

Reproducibility and lack of analytical bias was confirmed in quality-control studies. A serum proteomic signature of seven features in the training set reached an overall accuracy of 78%, a sensitivity of 67.4%, and a specificity of 88.9%. In the blinded test set, this signature reached an overall accuracy of 72.6 %, a sensitivity of 58%, and a specificity of 85.7%. The serum signature was associated with the diagnosis of lung cancer independently of gender, smoking status, smoking pack-years, and C-reactive protein levels. From this signature, we identified three discriminatory features as members of a cluster of truncated forms of serum amyloid A.

CONCLUSIONS

We found a serum proteomic profile that discriminates lung cancer from matched controls. Proteomic analysis of unfractionated serum may have a role in the noninvasive diagnosis of lung cancer and will require methodological refinements and prospective validation to achieve clinical utility.

Covalent adduction of human serum albumin by 4-hydroxy-2-nonenal: kinetic analysis of competing alkylation reactions

The electrophilic lipid oxidation product 4-hydroxy-2-nonenal (HNE) reacts with proteins to form covalent adducts, and this damage has been implicated in pathologies associated with oxidative stress. HNE adduction of blood proteins, such as human serum albumin (HSA), yields adducts that may serve as markers of oxidative stress in vivo. We used liquid chromatography-tandem mass spectrometry (LC-MS-MS) and the P-Mod algorithm to map the sites of 10 adducts formed by reaction of HNE with HSA in vitro. The detected adducts included Michael adducts formed at histidine and lysine residues. The selectivity of HNE in competing adduction reactions was evaluated by analysis of kinetics for HNE Michael adduction at six targeted HSA histidine residues. Reaction kinetics were analyzed by selected reaction monitoring in LC-MS-MS using stable isotope tagging with phenyl isocyanate. Rate constants ranged over 4 orders of magnitude, with the order of reactivity being H242 > H510 > H67 > H367 > H247 approximately K233. The most reactive target, H242, is located in a fatty acid- and drug binding cavity in subdomain IIa of HSA and appears to be a hot-spot for HNE modification. Analysis of adduction kinetics together with HSA structure and target residue pK(a) values suggest that location in the hydrophobic binding cavity and low predicted pK(a) of H242 account for its high reactivity toward HNE. H242 adducts may be preferred products of adduction by lipophilic electrophiles and may comprise a family of biomarkers for oxidative stress.

Selectively increased oxidative modifications mapped to detergent‐insoluble forms of Aβ and β‐III tubulin in Alzheimer's disease

Deleterious post-translational modifications (PTMs) to the neuronal cytoskeleton are a proposed mechanistic link between accumulation of amyloid (A) beta peptides and subsequent abnormalities of tau and neurodegeneration in Alzheimer's disease (AD). Here we tested the hypothesis that PTMs on neuronal tubulins selectively accumulate in a pathological protein fraction in AD. We used new software, P-MOD, to identify comprehensively and map PTMs using mass spectral data from soluble (normal) and detergent-insoluble (pathological) protein fractions from AD, as well as total extracts from controls, for selected proteins: Abeta, tau, apolipoprotein (apo) E, glial fibrillary acidic protein (GFAP), alpha-III tubulin, and beta-III tubulin. Our results confirmed direct observations of others by identifying methionine (M) sulfoxides at Abeta position 35 and numerous sites of tau phosphorylation in detergent-insoluble protein from AD, while no PTMs were enriched on primarily astrocyte-derived apoE or GFAP in this fraction. P-MOD mapped several abundant M sulfoxides to neuron-enriched beta-III tubulin but not its heterodimeric partner, neuron-enriched alpha-III tubulin, a result confirmed by selective suppression of CNBr-mediated cleavage of beta-III tubulin. These findings are the first comprehensive assessment of PTMs in AD and point to oxidative modification of beta-III tubulin as a potential contributor to the neuronal cytoskeletal disruption that is characteristic of AD.

Identification of protein fragments as pattern features in MALDI-MS analyses of serum

The use of matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) to acquire spectral profiles has become a common approach to detect proteomic biomarkers of disease. MALDI-MS signals may represent both intact proteins as well as proteolysis products. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis can tentatively identify the corresponding proteins Here, we describe the application of a data analysis utility called FragMint, which combines MALDI-MS spectral data with LC-MS/MS based protein identifications to generate candidate protein fragments consistent with both types of data. This approach was used to identify protein fragments corresponding to spectral signals in MALDI-MS analyses of unfractionated human serum. The serum also was analyzed by one-dimensional SDS-PAGE and bands corresponding to the MALDI-MS signal masses were excised and subjected to in-gel digestion and LC-MS/MS analysis. Database searches mapped all of the identified peptides to abundant blood proteins larger than the observed MALDI-MS signals. FragMint identified fragments of these proteins that contained the MS/MS identified sequences and were consistent with the observed MALDI-MS signals. This approach should be generally applicable to identify protein species corresponding to MALDI-MS signals.

Characterization of S-(N,N-Dialkylaminocarbonyl)cysteine Adducts and Enzyme Inhibition Produced by Thiocarbamate Herbicides in the Rat

Thiocarbamates are a major class of herbicides used extensively in the agricultural industry. It has been shown that thiocarbamates can form reactive sulfoxide and sulfone intermediates, which may be involved in the toxicity of thiocarbamates through covalent modification of cysteine and serine active sites of enzymes. Molinate has been shown to generate an S-hexahydro-1H-azepine-1-carbonyl adduct on the Cys-125 residue of the beta2- and beta3-chains of rat globin analogous to that reported for disulfiram and to inhibit aldehyde dehydrogenase and nonspecific esterase activity. The present study examined whether other thiocarbamate herbicides produce similar covalent protein modifications and enzyme inhibition to that reported for molinate and whether S-(N,N-dialkylaminocarbonyl)cysteine adduct levels are correlated to enzyme inhibition or the structure of thiocarbamate herbicides. Additionally, the potential of molinate to act as a peripheral demyelinating agent similar to disulfiram was evaluated. To address these aims, rats were exposed ip to molinate, vernolate, ethiolate, EPTC, or butylate for 5 days after which hemogloblin was isolated and analyzed for protein adducts using HPLC and matrix-assisted laser desorption ionization time-of-flight mass spectrometry. In addition, brain, liver, and testes mitochondrial and microsomal fractions were assayed for nonspecific esterase, low Km ALDH, or total ALDH activities, and S-(N,N-dialkylaminocarbonyl)cysteine adducts were measured by LC/MS/MS. For the neurotoxicity assessments, rats were administered molinate parenterally for subchronic periods and morphological evaluations performed on peripheral nerves. All of the thiocarbamates except butylate produced S-(N,N-dialkylaminocarbonyl)cysteine adducts on globin and the quantity of adducts detected decreased with increasing size of the nitrogen substituents. In contrast, a clear relationship between cysteine modification in mitochondrial and microsomal samples to nitrogen substituents was not evident, and although molinate produced relatively high levels of adducts and esterase inhibition and butylate low levels of adducts and esterase inhibition for most samples, in general, the level of S-(N,N-dialkylaminocarbonyl)cysteine adducts did not appear to be related to enzyme inhibition. Molinate did not produce segmental demyelination in peripheral nerve, suggesting that molinate and possibly other thiocarbamates do not share the neurotoxic potential of dithiocarbamates.