DSBSO-Based XL-MS Analysis of Breast Cancer PDX Tissues to Delineate Protein Interaction Network in Clinical Samples.

Protein-protein interactions (PPIs) are fundamental to understanding biological systems as protein complexes are the active molecular modules critical for carrying out cellular functions. Dysfunctional PPIs have been associated with various diseases including cancer. Systems-wide PPI analysis not only sheds light on pathological mechanisms, but also represents a paradigm in identifying potential therapeutic targets.

Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer.

Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above).

Urinary marker panels for aggressive prostate cancer detection.

Majority of patients with indolent prostate cancer (PCa) can be managed with active surveillance. Therefore, finding biomarkers for classifying patients between indolent and aggressive PCa is essential. In this study, we investigated urinary marker panels composed of urinary glycopeptides and/or urinary prostate-specific antigen (PSA) for their clinical utility in distinguishing non-aggressive (Grade Group 1) from aggressive (Grade Group ≥ 2) PCa.

Optimized data-independent acquisition approach for proteomic analysis at single-cell level.

Background: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised.

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.

Comparing Urinary Glycoproteins among Three Urogenital Cancers and Identifying Prostate Cancer-Specific Glycoproteins.

Prostate cancer, bladder cancer, and renal cancers are major urogenital cancers. Of which, prostate cancer is the most commonly diagnosed and second leading cause of cancer death for men in the United States. For urogenital cancers, urine is considered as proximate body fluid to the tumor site for developing non-invasiveness tests.

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.

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.

Development of Parallel Reaction Monitoring Assays for the Detection of Aggressive Prostate Cancer Using Urinary Glycoproteins.

Recently, we have found that two urinary glycoproteins, prostatic acid phosphatase (ACPP) and clusterin (CLU), combined with serum prostate-specific antigen (PSA) can serve as a three-signature panel for detecting aggressive prostate cancer (PCa) based on a quantitative glycoproteomic study. To facilitate the translation of candidates into clinically applicable tests, robust and accurate targeted parallel reaction monitoring (PRM) assays that can be widely adopted in multiple labs were developed in this study. The developed PRM assays for the urinary glycopeptides, FLN*ESYK from ACPP and EDALN*ETR from CLU, demonstrated good repeatability and a sufficient working range covering three to four orders of magnitude, and their performance in differentiating aggressive PCa was assessed by the quantitative analysis of urine specimens collected from 69 nonaggressive (Gleason score = 6) and 73 aggressive (Gleason ≥ 8) PCa patients.

An Integrated Workflow for Global, Glyco-, and Phospho-proteomic Analysis of Tumor Tissues.

Recently, the rapid development and application of mass spectrometry (MS)-based technologies have markedly improved the comprehensive proteomic characterization of global proteome and protein post-translational modifications (PTMs). However, the current conventional approach for global proteomic analysis is often carried out separately from PTM analysis. In our study, we developed an integrated workflow for multiplex analysis of global, glyco-, and phospho-proteomics using breast cancer patient-derived xenograft (PDX) tumor samples.

Development of a glycoproteomic strategy to detect more aggressive prostate cancer using lectin-immunoassays for serum fucosylated PSA.

Background: Prostate-specific antigen (PSA) is commonly used as a serum biomarker for the detection of prostate cancer. However, levels of PSA in serum do not reliably distinguish aggressive prostate cancer from non-aggressive disease. Therefore, there is an urgent need for biomarkers that can differentiate aggressive prostate cancers from non-aggressive phenotypes.

Evaluating the Possibility of Detecting Variants in Shotgun Proteomics via LeTE-Fusion Analysis Pipeline.

In proteogenomic studies, many genome-annotated events, for example, single amino acid variation (SAAV) and short INDEL, are often unobserved in shotgun proteomics. Therefore, we propose an analysis pipeline called LeTE-fusion (Le, peptide length; T, theoretical values; E, experimental data) to first investigate whether peptides with certain lengths are observed more often in mass spectrometry (MS)-based proteomics, which may hinder peptide identification causing difficulty in detecting genome-annotated events. By applying LeTE-fusion on different MS-based proteome data sets, we found peptides within 7-20 amino acids are more frequently identified, possibly attributed to MS-related factors instead of proteases.

Decoding the Effect of Isobaric Substitutions on Identifying Missing Proteins and Variant Peptides in Human Proteome.

To confirm the existence of missing proteins, we need to identify at least two unique peptides with length of 9-40 amino acids of a missing protein in bottom-up mass-spectrometry-based proteomic experiments. However, an identified unique peptide of the missing protein, even identified with high level of confidence, could possibly coincide with a peptide of a commonly observed protein due to isobaric substitutions, mass modifications, alternative splice isoforms, or single amino acid variants (SAAVs). Besides unique peptides of missing proteins, identified variant peptides (SAAV-containing peptides) could also alternatively map to peptides of other proteins due to the aforementioned issues.