Multiplexed, Scheduled, High-Resolution Parallel Reaction Monitoring on a Full Scan QqTOF Instrument with Integrated Data-Dependent and Targeted Mass Spectrometric Workflows

Recent advances in commercial mass spectrometers with higher resolving power and faster scanning capabilities have expanded their functionality beyond traditional data-dependent acquisition (DDA) to targeted proteomics with higher precision and multiplexing. Using an orthogonal quadrupole time-of flight (QqTOF) LC-MS system, we investigated the feasibility of implementing large-scale targeted quantitative assays using scheduled, high resolution multiple reaction monitoring (sMRM-HR), also referred to as parallel reaction monitoring (sPRM). We assessed the selectivity and reproducibility of PRM, also referred to as parallel reaction monitoring, by measuring standard peptide concentration curves and system suitability assays. By evaluating up to 500 peptides in a single assay, the robustness and accuracy of PRM assays were compared to traditional SRM workflows on triple quadrupole instruments. The high resolution and high mass accuracy of the full scan MS/MS spectra resulted in sufficient selectivity to monitor 6–10 MS/MS fragment ions per target precursor, providing flexibility in postacquisition assay refinement and optimization. The general applicability of the sPRM workflow was assessed in complex biological samples by first targeting 532 peptide precursor ions in a yeast lysate, and then 466 peptide precursors from a previously generated candidate list of differentially expressed proteins in whole cell lysates from <i>E. coli</i>. Lastly, we found that sPRM assays could be rapidly and efficiently developed in Skyline from DDA libraries when acquired on the same QqTOF platform, greatly facilitating their successful implementation. These results establish a robust sPRM workflow on a QqTOF platform to rapidly transition from discovery analysis to highly multiplexed, targeted peptide quantitation

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype

Lectin Chromatography/Mass Spectrometry Discovery Workflow Identifies Putative Biomarkers of Aggressive Breast Cancers

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (<i>n</i> = 5/subtype). The samples were fractionated using the lectins <i>Aleuria aurantia</i> (AAL) and <i>Sambucus nigra</i> agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically <i>N</i>-deglycosylated and analyzed by LC–MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype