Integrated glycoproteomic characterization of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC), a common form of RCC, is responsible for the high mortality rate of kidney cancer. Dysregulations of glycoproteins have been shown to associate with ccRCC. However, the molecular mechanism has not been well characterized. Here, a comprehensive glycoproteomic analysis is conducted using 103 tumors and 80 paired normal adjacent tissues. Altered glycosylation enzymes and corresponding protein glycosylation are observed, while two of the major ccRCC mutations, BAP1 and PBRM1, show distinct glycosylation profiles. Additionally, inter-tumor heterogeneity and cross-correlation between glycosylation and phosphorylation are observed. The relation of glycoproteomic features to genomic, transcriptomic, proteomic, and phosphoproteomic changes shows the role of glycosylation in ccRCC development with potential for therapeutic interventions. This study reports a large-scale tandem mass tag (TMT)-based quantitative glycoproteomic analysis of ccRCC that can serve as a valuable resource for the community.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

FCH domain only 1 (FCHo1), a potential new biomarker for lung cancer.

Lung carcinoma is the main reason for cancer-associated deaths in the world. In a previous study, FCH domain only 1 (FCHo1) which is managed by protein kinase B (AKT), was shown to be activated in lung cancer. FCHo1 knockdown has previously been shown to cause cell death in lung cancer. However, the specific roles of FCHo1 in lung carcinoma remain elusive. Herein, we propose that FCHo1's intracellular mechanism targets the G1 to S phase transition, following the M phase. We demonstrated that F-BAR and mu homology domains exist separately in human lung tissues and that one truncated form is not detected in patients with lung cancer. Furthermore, quantitative global proteome analysis of FCHo1 indicated that the inhibition of G1/S phase transition and FCHo1 RNAi led to the death of cells in the G1/S phase. Noninvasive viral aerosol-mediated delivery of FCHo1 shRNA suppressed cancer progression in mice with non-small-cell lung cancer (NSCLC), suggesting that the delivery of FCHo1 shRNA could be a meaningful therapeutic strategy in lung cancer. Additional studies are needed to make clear the detailed mechanism of action of FCHo1.

Evaluation of the Sensitivity and Reproducibility of Targeted Proteomic Analysis Using Data-Independent Acquisition for Serum and Cerebrospinal Fluid Proteins.

There is a need for targeted analysis of biological fluids for diagnosis, prognosis, or monitoring the progression of diseases. Cerebrospinal fluid (CSF) and serum have been widely used for the development of protein analysis for neurodegenerative diseases and other diseases, respectively. Recently, data-independent acquisition (DIA) mass spectrometry (MS) has been developed to increase the throughput over data-dependent acquisition (DDA) on screening of a large number of samples and discovery of candidate targets. When it comes to target validation, the analytical performance of targeted analysis is critical. However, the inter- and intralaboratory analytical performances of the DIA-MS for targeted proteomic analysis of CSF and serum samples have not yet been investigated. In this study, we showed that the DIA-MS approach allowed us to identify and quantify 1732 CSF and 424 serum proteins, with 90% of proteins identified and quantified in at least 50% of DIA-MS runs. To evaluate the sensitivity, linearity, and dynamic range of the DIA approach, we included the stable isotope-labeled (SI) peptides into CSF and serum samples with serial dilutions. The lower limit of quantification (LLOQ) of peptides was 0.1-0.5 fmol, and the dynamic range was over 3.53 orders of magnitude, with excellent linearity (r2 < 0.978) in CSF and serum samples. Finally, the reproducibility of the DIA-MS approach was evaluated using entire proteins identified in CSF and serum samples. The intralaboratory three replicate results showed reliable reproducibility with 12.5 and 17.3% of the median coefficient of variation (CV) in both CSF and serum matrices, whereas the median CVs of interlaboratory three replicates were 23.8 and 32.0% in CSF and serum samples, respectively. The comparison of the quantitative result between replicates showed close similarity at intra- and interlaboratories with a median Pearson correlation value of >0.98 in CSF and serum, respectively. In conclusion, we demonstrate the capability of the DIA approach as a targeted proteomic analysis for candidate proteins from CSF and serum samples.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma.

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Proteomic signatures of 16 major types of human cancer reveal universal and cancer-type-specific proteins for the identification of potential therapeutic targets.

BACKGROUND: Proteomic characterization of cancers is essential for a comprehensive understanding of key molecular aberrations. However, proteomic profiling of a large cohort of cancer tissues is often limited by the conventional approaches. METHODS: We present a proteomic landscape of 16 major types of human cancer, based on the analysis of 126 treatment-naïve primary tumor tissues, 94 tumor-matched normal adjacent tissues, and 12 normal tissues, using mass spectrometry-based data-independent acquisition approach. RESULTS: In our study, a total of 8527 proteins were mapped to brain, head and neck, breast, lung (both small cell and non-small cell lung cancers), esophagus, stomach, pancreas, liver, colon, kidney, bladder, prostate, uterus and ovary cancers, including 2458 tissue-enriched proteins. Our DIA-based proteomic approach has characterized major human cancers and identified universally expressed proteins as well as tissue-type-specific and cancer-type-specific proteins. In addition, 1139 therapeutic targetable proteins and 21 cancer/testis (CT) antigens were observed. CONCLUSIONS: Our discoveries not only advance our understanding of human cancers, but also have implications for the design of future large-scale cancer proteomic studies to assist the development of diagnostic and/or therapeutic targets in multiple cancers.

Urinary glycoproteins associated with aggressive prostate cancer.

Background: There is an urgent need for the detection of aggressive prostate cancer. Glycoproteins play essential roles in cancer development, while urine is a noninvasive and easily obtainable biological fluid that contains secretory glycoproteins from the urogenital system. Therefore, here we aimed to identify urinary glycoproteins that are capable of differentiating aggressive from non-aggressive prostate cancer. Methods: Quantitative mass spectrometry data of glycopeptides from a discovery cohort comprised of 74 aggressive (Gleason score ≥8) and 68 non-aggressive (Gleason score = 6) prostate cancer urine specimens were acquired via a data independent acquisition approach. The glycopeptides showing distinct expression profiles in aggressive relative to non-aggressive prostate cancer were further evaluated for their performance in distinguishing the two groups either individually or in combination with others using repeated 5-fold cross validation with logistic regression to build predictive models. Predictive models showing good performance from the discovery cohort were further evaluated using a validation cohort. Results: Among the 20 candidate glycoproteins, urinary ACPP outperformed the other candidates. Urinary ACPP can also serve as an adjunct to serum PSA to further improve the discrimination power for aggressive prostate cancer (AUC= 0.82, 95% confidence interval 0.75 to 0.89). A three-signature panel including urinary ACPP, urinary CLU, and serum PSA displayed the ability to distinguish aggressive prostate cancer from non-aggressive prostate cancer with an AUC of 0.86 (95% confidence interval 0.8 to 0.92). Another three-signature panel containing urinary ACPP, urinary LOX, and serum PSA also demonstrated its ability in recognizing aggressive prostate cancer (AUC=0.82, 95% confidence interval 0.75 to 0.9). Moreover, consistent performance was observed from each panel when evaluated using a validation cohort. Conclusion: We have identified glycopeptides of urinary glycoproteins associated with aggressive prostate cancer using a quantitative mass spectrometry-based glycoproteomic approach and demonstrated their potential to serve as noninvasive urinary glycoprotein biomarkers worthy of further validation by a multi-center study.

An Electrophilic Deguelin Analogue Inhibits STAT3 Signaling in H-Ras-Transformed Human Mammary Epithelial Cells: The Cysteine 259 Residue as a Potential Target.

Signal transducer and activator of transcription 3 (STAT3) is a point of convergence for numerous oncogenic signals that are often constitutively activated in many cancerous or transformed cells and some stromal cells in the tumor microenvironment. Persistent STAT3 activation in malignant cells stimulates proliferation, survival, angiogenesis, invasion, and tumor-promoting inflammation. STAT3 undergoes activation through phosphorylation on tyrosine 705, which facilitates its dimerization. Dimeric STAT3 translocates to the nucleus, where it regulates the transcription of genes involved in cell proliferation, survival, etc. In the present study, a synthetic deguelin analogue SH48, discovered by virtual screening, inhibited the phosphorylation, nuclear translocation, and transcriptional activity of STAT3 in H-ras transformed human mammary epithelial MCF-10A cells (MCF10A-ras). We speculated that SH48 bearing an α,ß-unsaturated carbonyl group could interact with a thiol residue of STAT3, thereby inactivating this transcription factor. Non-electrophilic analogues of SH48 failed to inhibit STAT3 activation, lending support to the above supposition. By utilizing a biotinylated SH48, we were able to demonstrate the complex formation between SH48 and STAT3. SH48 treatment to MCF10A-ras cells induced autophagy, which was verified by staining with a fluorescent acidotropic probe, LysoTracker Red, as well as upregulating the expression of LC3II and p62. In conclusion, the electrophilic analogue of deguelin interacts with STAT3 and inhibits its activation in MCF10A-ras cells, which may account for its induction of autophagic death.

Cell Line-, Protein-, and Sialoglycosite-Specific Control of Flux-Based Sialylation in Human Breast Cells: Implications for Cancer Progression.

Sialylation, a post-translational modification that impacts the structure, activity, and longevity of glycoproteins has been thought to be controlled primarily by the expression of sialyltransferases (STs). In this report we explore the complementary impact of metabolic flux on sialylation using a glycoengineering approach. Specifically, we treated three human breast cell lines (MCF10A, T-47D, and MDA-MB-231) with 1,3,4-O-Bu3ManNAc, a "high flux" metabolic precursor for the sialic acid biosynthetic pathway. We then analyzed N-glycan sialylation using solid phase extraction of glycopeptides (SPEG) mass spectrometry-based proteomics under conditions that selectively captured sialic acid-containing glycopeptides, referred to as "sialoglycosites." Gene ontology (GO) analysis showed that flux-based changes to sialylation were broadly distributed across classes of proteins in 1,3,4-O-Bu3ManNAc-treated cells. Only three categories of proteins, however, were "highly responsive" to flux (defined as two or more sialylation changes of 10-fold or greater). Two of these categories were cell signaling and cell adhesion, which reflect well-known roles of sialic acid in oncogenesis. A third category-protein folding chaperones-was unexpected because little precedent exists for the role of glycosylation in the activity of these proteins. The highly flux-responsive proteins were all linked to cancer but sometimes as tumor suppressors, other times as proto-oncogenes, or sometimes both depending on sialylation status. A notable aspect of our analysis of metabolically glycoengineered breast cells was decreased sialylation of a subset of glycosites, which was unexpected because of the increased intracellular levels of sialometabolite "building blocks" in the 1,3,4-O-Bu3ManNAc-treated cells. Sites of decreased sialylation were minor in the MCF10A (<25% of all glycosites) and T-47D (<15%) cells but dominated in the MDA-MB-231 line (~60%) suggesting that excess sialic acid could be detrimental in advanced cancer and cancer cells can evolve mechanisms to guard against hypersialylation. In summary, flux-driven changes to sialylation offer an intriguing and novel mechanism to switch between context-dependent pro- or anti-cancer activities of the several oncoproteins identified in this study. These findings illustrate how metabolic glycoengineering can uncover novel roles of sialic acid in oncogenesis.

Deep Proteomics Using Two Dimensional Data Independent Acquisition Mass Spectrometry.

Methodologies that facilitate high-throughput proteomic analysis are a key step toward moving proteome investigations into clinical translation. Data independent acquisition (DIA) has potential as a high-throughput analytical method due to the reduced time needed for sample analysis, as well as its highly quantitative accuracy. However, a limiting feature of DIA methods is the sensitivity of detection of low abundant proteins and depth of coverage, which other mass spectrometry approaches address by two-dimensional fractionation (2D) to reduce sample complexity during data acquisition. In this study, we developed a 2D-DIA method intended for rapid- and deeper-proteome analysis compared to conventional 1D-DIA analysis. First, we characterized 96 individual fractions obtained from the protein standard, NCI-7, using a data-dependent approach (DDA), identifying a total of 151,366 unique peptides from 11,273 protein groups. We observed that the majority of the proteins can be identified from just a few selected fractions. By performing an optimization analysis, we identified six fractions with high peptide number and uniqueness that can account for 80% of the proteins identified in the entire experiment. These selected fractions were combined into a single sample which was then subjected to DIA (referred to as 2D-DIA) quantitative analysis. Furthermore, improved DIA quantification was achieved using a hybrid spectral library, obtained by combining peptides identified from DDA data with peptides identified directly from the DIA runs with the help of DIA-Umpire. The optimized 2D-DIA method allowed for improved identification and quantification of low abundant proteins compared to conventional unfractionated DIA analysis (1D-DIA). We then applied the 2D-DIA method to profile the proteomes of two breast cancer patient-derived xenograft (PDX) models, quantifying 6,217 and 6,167 unique proteins in basal- and luminal- tumors, respectively. Overall, this study demonstrates the potential of high-throughput quantitative proteomics using a novel 2D-DIA method.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Developing Workflow for Simultaneous Analyses of Phosphopeptides and Glycopeptides.

Enrichment of modified peptides from global peptides is inevitable in mass spectrometric analysis protein modifications because of their importance in the study of cellular functions and low abundance in the global proteomic analysis. Recent advances in enrichment methods for modified peptides such as phosphopeptides and intact glycopeptides (IGPs) show that the methods for proteomic analyses of both protein modifications are robust. We have recently observed and reported a large number of IGPs from phosphoproteomic analysis using IMAC-based phosphopeptides enrichment procedure. To determine whether phosphorylated peptides could be specifically isolated from coenriched IGPs in IMAC experiments with different pH, IMAC procedures were performed at different pH conditions, and we found that the enrichment of phosphopeptides at pH 2.0 was the optimal condition for having the highest number of phosphopeptide identifications; however, coenrichment of phosphopeptides and glycopeptides was inevitable in the entire pH range. The hydrophilic enrichments of IGPs performed before or after IMAC enrichment were evaluated subsequently to determine the optimal workflow for simultaneous analyses of phosphopeptides and glycopeptides, and IMAC enrichment followed by hydrophilic enrichment was chosen as the optimized workflow. Applying the workflow to the TMT-labeled peptides from luminal and basal-like type of breast cancer patient-derived xenograft (PDX) models allowed quantitative analyses of phospho- and glycoproteomics with 17582 phosphopeptides and 3468 glycopeptides identified, and 1237 phosphopeptides and 236 glycopeptides showed significant expression differences between luminal and basal-like, respectively. This method allows simultaneous analyses of phosphoprotein and glycoprotein modifications, extending our understanding of roles of glycosylation and phosphorylation in biology and diseases.

Curcumin interacts directly with the Cysteine 259 residue of STAT3 and induces apoptosis in H-Ras transformed human mammary epithelial cells.

Signal transducer and activator of transcription 3 (STAT3) is a transcription factor that is latent but constitutively activated in many types of cancers. It is well known that STAT3 plays a key role in inflammation-associated tumorigenesis. Curcumin is an anti-inflammatory natural compound isolated from the turmeric (Curcuma longa L., Zingiberaceae) that has been extensively used in a traditional medicine over the centuries. In the present study, we have found that curcumin inhibits STAT3 signaling that is persistently overactivated in H-Ras transformed breast epithelial cells (H-Ras MCF10A). Specific cysteine residues present in STAT3 appear to be critical for the activity as well as conformation of this transcription factor. We identified the cysteine residue 259 of STAT3 as a putative site for curcumin binding. Site-directed mutation of this cysteine residue abolished curcumin-induced inactivation of STAT3 and apoptosis in H-Ras MCF10A cells. The α,ß-unsaturated carbonyl moiety of curcumin appears to be essential in its binding to STAT3 in H-Ras MCF10A cells. Tetrahydrocurcumin that lacks such electrophilic moiety failed to interact with STAT3 and to induce apoptosis in the same cell line. Taken together, our findings suggest that curcumin can abrogate aberrant activation of STAT3 through direct interaction, thereby inhibiting STAT3-mediated mammary carcinogenesis.

Proteomic analysis of human follicular fluid in poor ovarian responders during in vitro fertilization.

Poor ovarian response (POR) in controlled ovarian stimulation is often observed during in vitro fertilization and embryo transfer cycles and it is a major problem. A POR has been found to be related to several factors, including advanced age, high body mass index, and history of ovarian or pelvic surgery. However, it is difficult to predict POR, as there are no specific biomarkers known. In this study, we used quantitative proteomic analyses to investigate potential biomarkers that can predict poor response during in vitro fertilization based on follicular fluid samples. A total of 1079 proteins were identified using a high-resolution orbitrap mass spectrometer coupled online to a nanoflow-LC system. It is notable that 65 upregulated and 66 downregulated proteins were found to be functionally enriched in poor responders. We also validated these differentially expressed proteins using a triple-quadrupole mass spectrometer for quantification of targeted proteins. Of the differentially expressed proteins, three proteins (pregnancy zone protein, renin, and sushi repeat-containing protein SRPX) were regarded as statistically significant (p < 0.05).

Endoplasmic reticulum-Golgi intermediate compartment protein 3 knockdown suppresses lung cancer through endoplasmic reticulum stress-induced autophagy.

Trafficking from the endoplasmic reticulum (ER) to the Golgi apparatus is elevated in cancer cells. Therefore, proteins of the ER-Golgi intermediate compartment (ERGIC) attract significant attention as targets for cancer treatment. Enhanced cancer cell growth and epithelial-mesenchymal transition by ERGICs correlates with poor-prognosis of lung cancer. This prompted us to assess whether knockdown of ERGIC3 may decrease lung cancer growth. To test the hypothesis, the effects of ERGIC3 short hairpin RNA (shERGIC3) on ER stress-induced cell death and lung tumorigenesis were investigated both in vitro and in vivo. Knockdown of ERGIC3 led to ER stress-induced autophagic cell death and suppression of proliferation in the A549 human lung cancer cell-line. Moreover, non-invasive aerosol-delivery of shERGIC3 using the biocompatible carrier glycerol propoxylate triacrylate and spermine (GPT-SPE) inhibited lung tumorigenesis in the K-rasLA1 murine model of lung cancer. Our data suggest that suppression of ERGIC3 could provide a framework for the development of effective lung cancer therapies.

Effects of peptide acetylation and dimethylation on electrospray ionization efficiency.

Peptide acetylation and dimethylation have been widely used to derivatize primary amino groups (peptide N-termini and the ε-amino group of lysines) for chemical isotope labeling of quantitative proteomics or for affinity tag labeling for selection and enrichment of labeled peptides. However, peptide acetylation results in signal suppression during electrospray ionization (ESI) due to charge neutralization. In contrast, dimethylated peptides show increased ionization efficiency after derivatization, since dimethylation increases hydrophobicity and maintains a positive charge on the peptide under common LC conditions. In this study, we quantitatively compared the ESI efficiencies of acetylated and dimethylated model peptides and tryptic peptides of BSA. Dimethylated peptides showed higher ionization efficiency than acetylated peptides for both model peptides and tryptic BSA peptides. At the proteome level, peptide dimethylation led to better protein identification than peptide acetylation when tryptic peptides of mouse brain lysate were analyzed with LC-ESI-MS/MS. These results demonstrate that dimethylation of tryptic peptides enhanced ESI efficiency and provided up to two-fold improved protein identification sensitivity in comparison with acetylation.

Proteomic analysis of the aqueous humor in age-related macular degeneration (AMD) patients.

Age-related macular degeneration (AMD) can lead to irreversible central vision loss in the elderly. Although large number of growth factor pathways, including the vascular endothelial growth factor (VEGF), has been implicated in the pathogenesis of AMD, no study has directly assessed the whole proteomic composition in the aqueous humor (AH) among AMD patients. The AH contains proteins secreted from the anterior segment tissue, and these proteins may play an important role in the pathogenesis of AMD. Thus, comparisons between the AH proteomic profiles of AMD patients and non-AMD controls may lead to the verification of novel pathogenic proteins useful as potential clinical biomarkers. In this study, we used discovery-based proteomics and Multiple Reaction Monitoring Mass Spectrometry (MRM-MS) to analyze AH from AMD patients and AH from controls who underwent cataract surgery. A total of 154 proteins with at least two unique peptides were identified in the AH. Of these 154 proteins identified by discovery-based proteomics, 10 AH proteins were novel identifications. The protein composition in the AH was different between AMD patients and non-AMD controls. Subsequently, a systematic MRM-MS assay was performed in seven highly abundant differentially expressed proteins from these groups. Differential expression of three proteins was observed in the AH of AMD patients compared with that of cataract controls (p<0.0312). Elucidation of the aqueous proteome will establish a foundation for protein function analysis and identify differentially expressed markers associated with AMD. This study demonstrates that integrated proteomic technologies can yield novel biomarkers to detect exudative AMD.