Developing a mass spectrometry–based assay for the ovarian cancer biomarker CA125 (MUC16) using suspension trapping (STrap)

Immunoaffinity-free chromatographic purification of ovarian cancer biomarker CA125 (MUC16) from blood serum enables mass spectrometry characterization

The enrichment of trace proteins from human fluid samples is of great importance in diverse clinical and industrial applications. In clinical diagnostics, such enrichment may enable detection of trace proteins that serve as biomarkers of disease. Affinity-based approaches, such as immunoaffinity pulldown, are widely used to enrich trace proteins, but this strategy relies on the availability and performance of antibodies that act on all proteoforms in an unbiased manner. Our prior work to characterize MUC16 (the mucin protein that carries the ovarian cancer biomarker CA125) by mass spectrometry successfully overcame the reliance on affinity-based enrichment and was used to enrich this biomarker from ascites of individual ovarian cancer patients, however, this strategy was not demonstrated on clinically relevant volumes of serum, a biofluid that is more accessible than ascites. The present work developed a non-affinity-based chromatographic method to enrich MUC16 from serum. The enriched MUC16 sample was further processed using a Midi Top 14 abundant protein depletion column. Peptides identified using bottom-up proteomics yielded 1-8% coverage of MUC16. Additionally, MUC16 was detected in samples containing less than the clinical cut-off level of CA125 (35 U mL-1), suggesting that this strategy of enrichment and bottom-up proteomics can enable analysis of CA125 from the serum of individuals with early-stage ovarian cancer and those whose tumors express CA125 (MUC16) at low levels.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies

BACKGROUND

Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker - located on the mucin protein MUC16 - is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes.

OBJECTIVE

The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test.

METHODS

Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies - OC125, M11, "OC125-like," and "M11-like" - to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy.

RESULTS

Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies.

CONCLUSIONS

Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies

BACKGROUND

Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker-located on the mucin protein MUC16-is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes.

OBJECTIVE

The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test.

METHODS

Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies-OC125, M11, "OC125-like," and "M11-like"-to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy.

RESULTS

Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies.

CONCLUSIONS

Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Simultaneous N-Deglycosylation and Digestion of Complex Samples on S-Traps Enables Efficient Glycosite Hypothesis Generation

N-linked glycosylation is an important post-translational modification that is difficult to identify and quantify in traditional bottom-up proteomics experiments. Enzymatic deglycosylation of proteins by peptide:N-glycosidase F (PNGase F) prior to digestion and subsequent mass spectrometry analysis has been shown to improve coverage of various N-linked glycopeptides, but the inclusion of this step may add up to a day to an already lengthy sample preparation process. An efficient way to integrate deglycosylation with bottom-up proteomics would be a valuable contribution to the glycoproteomics field. Here, we demonstrate a proteomics workflow in which deglycosylation and proteolytic digestion of samples occur simultaneously using suspension trapping (S-Trap). This approach adds no time to standard digestion protocols. Applying this sample preparation strategy to a human serum sample, we demonstrate improved identification of potential N-glycosylated peptides in deglycosylated samples compared with non-deglycosylated samples, identifying 156 unique peptides that contain the N-glycosylation motif (asparagine-X-serine/threonine), the deamidation modification characteristic of PNGase F, and an increase in peptide intensity over a control sample. We expect that this rapid sample preparation strategy will assist in the identification and quantification of both known and potential glycoproteins. Data are available via ProteomeXchange with the identifier PXD037921.

Improved profiling of low molecular weight serum proteome for gastric carcinoma by data-independent acquisition

Low molecular weight proteins (LMWPs) in the bloodstream participate in various biological processes and are closely associated with disease status, whereas identification of serous LMWPs remains a great technical challenge due to the wide dynamic range of protein components. In this study, we constructed an integrated LMWP library by combining the LMWPs obtained by three enrichment methods (50% ACN, 20% ACN + 20 mM ABC, and 30 kDa) and their fractions identified by the data-dependent acquisition method. With this newly constructed library, we comprehensively profiled LMWPs in serum using data-independent acquisition and reliably achieved quantitative results for 75% serous LMWPs. When applying this strategy to quantify LMWPs in human serum samples, we could identify 405 proteins on average per sample, of which 136 proteins were with a MW less than 30 kDa and 293 proteins were with a MW less than 65 kDa. Of note, pre- and post-operative gastric carcinoma (GC) patients showed differentially expressed serous LWMPs, which was also different from the pattern of LWMP expression in healthy controls. In conclusion, our results showed that LMWPs could efficiently distinguish GC patients from healthy controls as well as between pre- and post-operative statuses, and more importantly, our newly developed LMWP profiling platform could be used to discover candidate LMWP biomarkers for disease diagnosis and status monitoring.

Preparative capillary electrophoresis (CE) fractionation of protein digests improves protein and peptide identification in bottom-up proteomics

Reversed-phase liquid chromatography (RPLC) is widely used to reduce sample complexity prior to mass spectrometry (MS) analysis in bottom-up proteomics. Improving peptide separation in complex samples enables lower-abundance proteins to be identified. Multidimensional separations that combine orthogonal separation modes improve protein and peptide identifications over RPLC alone. Here we report a preparative capillary electrophoresis (CE) fractionation method that combines CE and RPLC separations. Using this method, we demonstrate improved protein and peptide identification in a tryptic digest of E. coli cell lysate, with 132 ± 33% more protein identifications and 185 ± 65% more peptide identifications over non-fractionated samples. Fractionation enables detection of lower-abundance proteins in this complex sample. We demonstrate improved coverage of ovarian cancer biomarker MUC16 isolated from conditioned cell media, with 6.73% sequence coverage using CE fractionation compared to 2.74% coverage without preparative fractionation. This new method will allow researchers performing bottom-up proteomics to harness the advantages of CE separations while using widely available LC-MS/MS instrumentation.

Mucinomics as the Next Frontier of Mass Spectrometry

Mucin-domain glycoproteins comprise a class of proteins whose densely O-glycosylated mucin domains adopt a secondary structure with unique biophysical and biochemical properties. The canonical family of mucins is well-known to be involved in various diseases, especially cancer. Despite this, very little is known about the site-specific molecular structures and biological activities of mucins, in part because they are extremely challenging to study by mass spectrometry (MS). Here, we summarize recent advancements toward this goal, with a particular focus on mucin-domain glycoproteins as opposed to general O-glycoproteins. We summarize proteolytic digestion techniques, enrichment strategies, MS fragmentation, and intact analysis, as well as new bioinformatic platforms. In particular, we highlight mucin directed technologies such as mucin-selective proteases, tunable mucin platforms, and a mucinomics strategy to enrich mucin-domain glycoproteins from complex samples. Finally, we provide examples of targeted mucin-domain glycoproteomics that combine these techniques in comprehensive site-specific analyses of proteins. Overall, this Review summarizes the methods, challenges, and new opportunities associated with studying enigmatic mucin domains.

Affinity-free enrichment and mass spectrometry analysis of the ovarian cancer biomarker CA125 (MUC16) from patient-derived ascites

Developing a mass spectrometry-based assay for the ovarian cancer biomarker CA125 (MUC16) is a desirable goal, because it may enable detection of molecular regions that are not recognized by antibodies and are therefore analytically silent in the current immunoassay. Additionally, the ability to characterize the CA125 proteoforms expressed by individuals may offer clinical insight. Enrichment of CA125 from malignant ascites may provide a high-quality source of this important ovarian cancer biomarker, but a reliable strategy for such enrichment is currently lacking. Beginning with crude ascites isolated from three individual patients with high grade serous ovarian cancer, we enriched for MUC16 using filtration, ion exchange, and size exclusion chromatography and then performed bottom-up proteomics on the isolated proteins. This approach of enrichment and analysis reveals that the peptides detected via mass spectrometry map to the SEA domain and C-loop regions within the tandem repeat domains of CA125 and that peptide abundance correlates with clinical CA125 counts.