Proteogenomic data and resources for pan-cancer analysis.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma.

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of ß-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

Maintenance regimen of GM-CSF with rituximab and lenalidomide improves survival in high-risk B-cell lymphoma by modulating natural killer cells.

BACKGROUND: The treatment of high-risk B-cell lymphoma (BCL) remains a challenge, especially in the elderly. METHODS: A total of 83 patients (median age 65 years), who have achieved a complete response after induction therapy, were divided into two groups: R2 + GM-CSF regimen (lenalidomide, rituximab, granulocyte-macrophage colony-stimulating factor [GM-CSF]) as maintenance therapy (n = 39) and observation (n = 44). The efficacy of the R2 + GM-CSF regimen as maintenance in patient with high-risk BCL was analyzed and compared with observation. RESULTS: The number of natural killer cells in patients increased after R2 + GM-CSF regimen administration (0.131 × 109 /L vs. 0.061 × 109 /L, p = 0.0244). Patients receiving the R2 + GM-CSF regimen as maintenance therapy had longer remission (duration of response: 18.9 vs. 11.3 months, p = 0.001), and longer progression-free survival (not reached (NR) vs. 31.7 months, p = 0.037), and overall survival (OS) (NR vs. NR, p = 0.015). The R2 + GM-CSF regimen was safe and well tolerated. High international prognostic index score (p = 0.012), and high tumor burden (p = 0.005) appeared to be independent prognostic factors for worse PFS. CONCLUSIONS: The maintenance therapy of R2 + GM-CSF regimen may improve survival in high-risk BCL patients, which might be modulated by amplification of natural killer cells. The efficacy of the R2 + GM-CSF maintenance regimen has to be further validated in prospective random clinical trials.

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.

Neoplastic cell enrichment of tumor tissues using coring and laser microdissection for proteomic and genomic analyses of pancreatic ductal adenocarcinoma.

BACKGROUND: The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses. METHODS: Three fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations. RESULTS: The neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity. CONCLUSIONS: In addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique.

Characterization of core fucosylation via sequential enzymatic treatments of intact glycopeptides and mass spectrometry analysis.

Core fucosylation of N-linked glycoproteins has been linked to the functions of glycoproteins in physiological and pathological processes. However, quantitative characterization of core fucosylation remains challenging due to the complexity and heterogeneity of N-linked glycosylation. Here we report a mass spectrometry-based method that employs sequential treatment of intact glycopeptides with enzymes (STAGE) to analyze site-specific core fucosylation of glycoproteins. The STAGE method utilizes Endo F3 followed by PNGase F treatment to generate mass signatures for glycosites that are formerly modified by core fucosylated N-linked glycans. We benchmark the STAGE method and use it to characterize site specific core fucosylation of glycoproteins from human hepatocellular carcinoma and pancreatic ductal adenocarcinoma, resulting in the identification of 1130 and 782 core fucosylated glycosites, respectively. These results indicate that our STAGE method enables quantitative characterization of core fucosylation events from complex protein mixtures, which may benefit our understanding of core fucosylation functions in various diseases.

Improving the detection of aggressive prostate cancer using immunohistochemical staining of protein marker panels.

Prostate cancer (PCa) is a heterogeneous group of tumors, including non-aggressive (NAG) and aggressive (AG) cancer, with variable clinical outcomes. Clinically, in order to assess the aggressiveness of a PCa, a core needle biopsy of a tumor is usually obtained to evaluate the Gleason pattern and score of the tumor. However, it may be difficult to assign on a small biopsy sample using histology. Therefore, additional tool is needed to aid in the assessment. We studied the diagnostic utility of 12 protein markers to identify AG tumors using immunohistochemistry (IHC) and tumor tissue microarray (TMA), including 215 cores of PCa and 111 cores of tumor-matched normal adjacent tissue (NAT). Protein markers were evaluated for their potential utility as single or combined panels for identification of AG. Of 12 proteins, PSMA, phospho-EGFR, AR and P16 were over-expressed in AG. Galectin-3, DPP4 and MAN1B1 revealed stronger staining patterns in NAG. The sensitivity and specificity of individual marker varied widely. Based on AUC values of individual marker, we constructed two- and three-marker panels. In two-marker panels, especially in the panel of DPP4 and PSMA, the AUC value reached 0.83 (ranging from 0.76 to 0.83). In three-marker panels, containing both DPP4 and PSMA with either Galectin-3 or phospho-EGFR, the AUC value reached 0.86 (ranging from 0.83 to 0.86). The specificities at 95% sensitivity of three-marker panels were also significantly improved. In addition to Gleason score, our IHC panels provide a practical tool to assess the aggressiveness of PCa.

Characterization of In Vivo Protein Complexes via Chemical Cross-Linking and Mass Spectrometry.

Cells perform various functions by proteins via protein complexes. Characterization of protein complexes is critical to understanding their biological and clinical significance and has been one of the major efforts of functional proteomics. To date, most protein complexes are characterized by the in vitro system from protein extracts after the cells or tissues are lysed, and it has been challenging to determine which of these protein complexes are formed in intact cells. Herein, we report an approach to preserve protein complexes using in vivo cross-linking, followed by size exclusion chromatography and data-independent acquisition mass spectrometry. This approach enables the characterization of in vivo protein complexes from cells or tissues, which allows the determination of protein complexes in clinical research. More importantly, the described approach can identify protein complexes that are not detected by the in vitro system, which provide unique protein function information.

OmicsOne: associate omics data with phenotypes in one-click.

BACKGROUND: The rapid advancements of high throughput "omics" technologies have brought a massive amount of data to process during and after experiments. Multi-omic analysis facilitates a deeper interrogation of a dataset and the discovery of interesting genes, proteins, lipids, glycans, metabolites, or pathways related to the corresponding phenotypes in a study. Many individual software tools have been developed for data analysis and visualization. However, it still lacks an efficient way to investigate the phenotypes with multiple omics data. Here, we present OmicsOne as an interactive web-based framework for rapid phenotype association analysis of multi-omic data by integrating quality control, statistical analysis, and interactive data visualization on 'one-click'. MATERIALS AND METHODS: OmicsOne was applied on the previously published proteomic and glycoproteomic data sets of high-grade serous ovarian carcinoma (HGSOC) and the published proteome data set of lung squamous cell carcinoma (LSCC) to confirm its performance. The data was analyzed through six main functional modules implemented in OmicsOne: (1) phenotype profiling, (2) data preprocessing and quality control, (3) knowledge annotation, (4) phenotype associated features discovery, (5) correlation and regression model analysis for phenotype association analysis on individual features, and (6) enrichment analysis for phenotype association analysis on interested feature sets. RESULTS: We developed an integrated software solution, OmicsOne, for the phenotype association analysis on multi-omics data sets. The application of OmicsOne on the public data set of ovarian cancer data showed that the software could confirm the previous observations consistently and discover new evidence for HNRNPU and a glycopeptide of HYOU1 as potential biomarkers for HGSOC data sets. The performance of OmicsOne was further demonstrated in the Tumor and NAT comparison study on the proteome data set of LSCC. CONCLUSIONS: OmicsOne can effectively simplify data analysis and reveal the significant associations between phenotypes and potential biomarkers, including genes, proteins, and glycopeptides, in minutes to assist users to understand aberrant biological processes.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Data-Independent Acquisition-Based Mass Spectrometry (DIA-MS) for Quantitative Analysis of Intact N-Linked Glycopeptides.

N-linked protein glycosylation is a key regulator in various biological functions. Previous studies have shown that aberrant glycosylation is associated with many diseases. Therefore, it is essential to elucidate protein modifications of glycosylation by quantitatively profiling intact N-linked glycopeptides. Data-independent acquisition (DIA) mass spectrometry (MS) is a cost-effective, flexible, and high-throughput method for global proteomics. However, substantial challenges are still present in the quantitative analysis of intact glycopeptides with high accuracy at high throughput. In this study, we have established a novel integrated platform for the DIA analysis of intact glycopeptides isolated from complex samples. The established analysis platform utilizes a well-designed DIA-MS method for raw data collection, a spectral library constructed specifically for intact glycopeptide quantification providing accurate results by the inclusion of Y ions for quantification and filtering of quantified intact glycopeptides with low-quality MS2 spectra automatically using a set of criteria. Intact glycopeptides isolated from human serum were used to evaluate the performance of the integrated platform. By utilizing 100 isolation windows for DIA data acquisition, a well-constructed human serum spectral library containing 1123 nonredundant intact glycopeptides with Y ions, and automated data inspection, 620 intact glycopeptides were quantified with high confidence from DIA-MS. In summary, our integrated platform can serve as a reliable quantitative tool for characterizing intact glycopeptides isolated from complex biological samples to assist our understanding of biological functions of N-linked glycosylation.

Proteomic characterization of primary and metastatic prostate cancer reveals reduced proteinase activity in aggressive tumors.

Prostate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. In order to improve patient outcomes, it is critical to clinically separate aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with aggressive PCa, it is still challenging to separate AG from NAG. To better understand the functional consequences of PCa progression and the unique features of the AG subtype, we studied the proteomic signatures of primary AG, NAG and metastatic PCa. 39 PCa and 10 benign prostate controls in a discovery cohort and 57 PCa in a validation cohort were analyzed using a data-independent acquisition (DIA) SWATH-MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using a validation cohort; and was also compared with a TCGA mRNA expression dataset and confirmed by immunohistochemistry (IHC) using PCa tissue microarray (TMA). 4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed reduced expressions of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates and the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using an independently-collected tumor cohort, correlated with a TCGA mRNA dataset, and confirmed by immunohistochemical stains of PCa tumor microarray (TMA). Our study is the first large-scale proteomics analysis of PCa tissue using a DIA SWATH-MS platform. It provides not only an interrogative proteomic signature of PCa subtypes, but also indicates the critical roles played by certain proteinases during tumor progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in PCa and for the development of a clinical assay to distinguish aggressive from indolent PCa.

Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

18F-fluorodeoxyglucose positron emission tomography-based prediction for splenectomy in patients with suspected splenic lymphoma.

BACKGROUND: Diagnostic splenectomy is often performed on patients with suspected splenic lymphoma. However, unnecessary splenectomy entails more harm than benefit for patients. Therefore, a preliminary screening method for patients with suspected splenic lymphoma that has high sensitivity and specificity is urgently needed. METHODS: From the pathology database at Huadong and Huashan Hospital, we retrospectively identified 60 patients of suspected splenic lymphoma who underwent fluorodeoxyglucose (FDG)-positron emission tomography (PET) before receiving a splenectomy and did not show any increase in FDG uptake except in the spleen. We compared the indicators of PET-CT, such as the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and the SUVmax of 18F-FDG uptake ratios between the spleen/liver, spleen/bone marrow, and liver/bone marrow. RESULTS: No significant differences were detected in SUVmax, TLG, MTV, or the SUVmax ratio of the liver/bone marrow between the lymphoma and benign groups. However, the SUVmax ratios of the spleen/liver and spleen/bone marrow were significantly higher in the lymphoma group than in the benign group (P=0.001; P=0.001). Receiver operating characteristic (ROC) curve analysis determined a spleen/liver SUVmax ratio of >2.42 and a spleen/bone marrow SUVmax ratio of >1.45 to be the indications for requiring a diagnostic splenectomy for lymphoma. Parallel testing increased the specificity and sensitivity of the test. CONCLUSIONS: Patients whose PET-CT results are inconclusive regarding the need for splenectomy may benefit from our prediction model. Future large-scale prospective clinical trials are required to verify these findings.

Survival Benefit and Efficiency of Low Dose Decitabine With CEG Regimen Compared to Decitabine Alone in the Elderly MDS - A Multicenter, Retrospective Study.

BACKGROUND: Decitabine are used in the treatment of myelodysplastic syndrome (MDS), but none trials reported overall survival improvement. METHODS: High-risk MDS and MDS transformed AML (sAML) patients (IPSS-R > 4.5, age above 60 years) in 6 medical centers of China were treated and compared a new regimen (decitabine with CEG) consisted of low dose decitabine (15 mg/m2, days 1-3), low dose etoposide (30 mg/m2, days 4,6,8,10,12), cytarabine (10 mg/m2 per day, days 4-12) and granulocyte colony-stimulating factor (G-CSF, 5ug/kg, adjusted by patients' WBC level, 12 hours prior to decitabine administration) with decitabine alone. The endpoints were death and disease progression. RESULTS: The baseline characteristics of these 2 groups were equivalent and none patients received prior chemotherapy. The treatment response rate (P= .048) and progression free survival (PFS, P = .030) all demonstrated significant improvement compared with decitabine alone. Decitabine with CEG regimen had attained a CR rate of 45.7%, a median OS of 36 (19-53) months and a median PFS of 34 (16.7-51.3) months in high-risk MDS patients, a CR rate of 40% in sAML. While decitabine alone only attained a median OS of 26 (24.5-27.5) months and a CR rate of 18.2% as well as a median progression free survival of 20 (17.6-22.4) months in MDS patients. Treatment response to CR or PR and TP53 mutation were 2 prognostic factor for OS and PFS in decitabine with CEG regimen. CONCLUSION: Decitabine with CEG regimen showed some promising advantage in elderly, high-risk MDS.

Proteomics Landscape of Host-Pathogen Interaction in Acinetobacter baumannii Infected Mouse Lung.

Acinetobacter baumannii is an important pathogen of nosocomial infection worldwide, which can primarily cause pneumonia, bloodstream infection, and urinary tract infection. The increasing drug resistance rate of A. baumannii and the slow development of new antibacterial drugs brought great challenges for clinical treatment. Host immunity is crucial to the defense of A. baumannii infection, and understanding the mechanisms of immune response can facilitate the development of new therapeutic strategies. To characterize the system-level changes of host proteome in immune response, we used tandem mass tag (TMT) labeling quantitative proteomics to compare the proteome changes of lungs from A. baumannii infected mice with control mice 6 h after infection. A total of 6,218 proteins were identified in which 6,172 could be quantified. With threshold p < 0.05 and relative expression fold change > 1.2 or < 0.83, we found 120 differentially expressed proteins. Bioinformatics analysis showed that differentially expressed proteins after infection were associated with receptor recognition, NADPH oxidase (NOX) activation and antimicrobial peptides. These differentially expressed proteins were involved in the pathways including leukocyte transendothelial migration, phagocyte, neutrophil degranulation, and antimicrobial peptides. In conclusion, our study showed proteome changes in mouse lung tissue due to A. baumannii infection and suggested the important roles of NOX, neutrophils, and antimicrobial peptides in host response. Our results provide a potential list of protein candidates for the further study of host-bacteria interaction in A. baumannii infection. Data are available via ProteomeXchange with identifier PXD020640.