A toolbox of immunoprecipitation-grade monoclonal antibodies to human transcription factors.

A key component of efforts to address the reproducibility crisis in biomedical research is the development of rigorously validated and renewable protein-affinity reagents. As part of the US National Institutes of Health (NIH) Protein Capture Reagents Program (PCRP), we have generated a collection of 1,406 highly validated immunoprecipitation- and/or immunoblotting-grade mouse monoclonal antibodies (mAbs) to 737 human transcription factors, using an integrated production and validation pipeline. We used HuProt human protein microarrays as a primary validation tool to identify mAbs with high specificity for their cognate targets. We further validated PCRP mAbs by means of multiple experimental applications, including immunoprecipitation, immunoblotting, chromatin immunoprecipitation followed by sequencing (ChIP-seq), and immunohistochemistry. We also conducted a meta-analysis that identified critical variables that contribute to the generation of high-quality mAbs. All validation data, protocols, and links to PCRP mAb suppliers are available at http://proteincapture.org.

Anti-peptide monoclonal antibodies generated for immuno-multiple reaction monitoring-mass spectrometry assays have a high probability of supporting Western blot and ELISA.

Immunoaffinity enrichment of peptides coupled to targeted, multiple reaction monitoring-mass spectrometry (immuno-MRM) has recently been developed for quantitative analysis of peptide and protein expression. As part of this technology, antibodies are generated to short, linear, tryptic peptides that are well-suited for detection by mass spectrometry. Despite its favorable analytical performance, a major obstacle to widespread adoption of immuno-MRM is a lack of validated affinity reagents because commercial antibody suppliers are reluctant to commit resources to producing anti-peptide antibodies for immuno-MRM while the market is much larger for conventional technologies, especially Western blotting and ELISA. Part of this reluctance has been the concern that affinity reagents generated to short, linear, tryptic peptide sequences may not perform well in traditional assays that detect full-length proteins. In this study, we test the feasibility and success rates of generating immuno-MRM monoclonal antibodies (mAbs) (targeting tryptic peptide antigens) that are also compatible with conventional, protein-based immuno-affinity technologies. We generated 40 novel, peptide immuno-MRM assays and determined that the cross-over success rates for using immuno-MRM monoclonals for Western blotting is 58% and for ELISA is 43%, which compare favorably to cross-over success rates amongst conventional immunoassay technologies. These success rates could most likely be increased if conventional and immuno-MRM antigen design strategies were combined, and we suggest a workflow for such a comprehensive approach. Additionally, the 40 novel immuno-MRM assays underwent fit-for-purpose analytical validation, and all mAbs and assays have been made available as a resource to the community via the Clinical Proteomic Tumor Analysis Consortium's (CPTAC) Antibody (http://antibodies.cancer.gov) and Assay Portals (http://assays.cancer.gov), respectively. This study also represents the first determination of the success rate (92%) for generating mAbs for immuno-MRM using a recombinant B cell cloning approach, which is considerably faster than the traditional hybridoma approach.

Comparative microsomal proteomics of a model lung cancer cell line NCI-H23 reveals distinct differences between molecular profiles of 3D and 2D cultured cells.

Lung cancer is the leading cause of cancer-related deaths in the USA and worldwide. Yet, about 95% of new drug candidates validated in preclinical phase eventually fail in clinical trials. Such a high attrition rate is attributed mostly to the inability of conventional two-dimensionally (2D) cultured cancer cells to mimic native three-dimensional (3D) growth of malignant cells in human tumors. To ascertain phenotypical differences between these two distinct culture conditions, we carried out a comparative proteomic analysis of a membrane fraction obtained from 3D- and 2D-cultured NSCLC model cell line NCI-H23. This analysis revealed a map of 1,166 (24%) protein species regulated in culture dependent manner, including differential regulation of a subset of cell surface-based CD molecules. We confirmed exclusive expression of CD99, CD146 and CD239 in 3D culture. Furthermore, label-free quantitation, targeting KRas proteoform-specific peptides, revealed upregulation of both wild type and monoallelic KRas4BG12C mutant at the surface of 3D cultured cells. In order to reduce the high attrition rate of new drug candidates, the results of this study strongly suggests exploiting base-line molecular profiling of a large number of patient-derived NSCLC cell lines grown in 2D and 3D culture, prior to actual drug candidate testing.

A dataset describing a suite of novel antibody reagents for the RAS signaling network.

RAS genes are frequently mutated in cancer and have for decades eluded effective therapeutic attack. The National Cancer Institute's RAS Initiative has a focus on understanding pathways and discovering therapies for RAS-driven cancers. Part of these efforts is the generation of novel reagents to enable the quantification of RAS network proteins. Here we present a dataset describing the development, validation (following consensus principles developed by the broader research community), and distribution of 104 monoclonal antibodies (mAbs) enabling detection of 27 phosphopeptides and 69 unmodified peptides from 20 proteins in the RAS network. The dataset characterizes the utility of the antibodies in a variety of applications, including Western blotting, immunoprecipitation, protein array, immunohistochemistry, and targeted mass spectrometry. All antibodies and characterization data are publicly available through the CPTAC Antibody Portal, Panorama Public Repository, and/or PRIDE databases. These reagents will aid researchers in discerning pathways and measuring expression changes in the RAS signaling network.

Generation and characterization of monoclonal antibodies that recognize human and murine supervillin protein isoforms.

Supervillin isoforms have been implicated in cell proliferation, actin filament-based motile processes, vesicle trafficking, and signal transduction. However, an understanding of the roles of these proteins in cancer metastasis and physiological processes has been limited by the difficulty of obtaining specific antibodies against these highly conserved membrane-associated proteins. To facilitate research into the biological functions of supervillin, monoclonal antibodies were generated against the bacterially expressed human supervillin N-terminus. Two chimeric monoclonal antibodies with rabbit Fc domains (clones 1E2/CPTC-SVIL-1; 4A8/CPTC-SVIL-2) and two mouse monoclonal antibodies (clones 5A8/CPTC-SVIL-3; 5G3/CPTC-SVIL-4) were characterized with respect to their binding sites, affinities, and for efficacy in immunoblotting, immunoprecipitation, immunofluorescence microscopy and immunohistochemical staining. Two antibodies (1E2, 5G3) recognize a sequence found only in primate supervillins, whereas the other two antibodies (4A8, 5A8) are specific for a more broadly conserved conformational epitope(s). All antibodies function in immunoblotting, immunoprecipitation and in immunofluorescence microscopy under the fixation conditions identified here. We also show that the 5A8 antibody works on immunohistological sections. These antibodies should provide useful tools for the study of mammalian supervillins.

Direct molecular dissection of tumor parenchyma from tumor stroma in tumor xenograft using mass spectrometry-based glycoproteomics.

The most widely used cancer animal model is the human-murine tumor xenograft. Unbiased molecular dissection of tumor parenchyma versus stroma in human-murine xenografts is critical for elucidating dysregulated protein networks/pathways and developing therapeutics that may target these two functionally codependent compartments. Although antibody-reliant technologies (e.g., immunohistochemistry, imaging mass cytometry) are capable of distinguishing tumor-proper versus stromal proteins, the breadth or extent of targets is limited. Here, we report an antibody-free targeted cross-species glycoproteomic (TCSG) approach that enables direct dissection of human tumor parenchyma from murine tumor stroma at the molecular/protein level in tumor xenografts at a selectivity rate presently unattainable by other means. This approach was used to segment/dissect and obtain the protein complement phenotype of the tumor stroma and parenchyma of the metastatic human lung adenocarcinoma A549 xenograft, with no need for tissue microdissection prior to mass-spectrometry analysis. An extensive molecular map of the tumor proper and the associated microenvironment was generated along with the top functional N-glycosylated protein networks enriched in each compartment. Importantly, immunohistochemistry-based cross-validation of selected parenchymal and stromal targets applied on human tissue samples of lung adenocarcinoma and normal adjacent tissue is indicative of a noteworthy translational capacity for this unique approach that may facilitate identifications of novel targets for next generation antibody therapies and development of real time preclinical tumor models.

Novel antibody reagents for characterization of drug- and tumor microenvironment-induced changes in epithelial-mesenchymal transition and cancer stem cells.

The presence of cancer stem cells (CSCs) and the induction of epithelial-to-mesenchymal transition (EMT) in tumors are associated with tumor aggressiveness, metastasis, drug resistance, and poor prognosis, necessitating the development of reagents for unambiguous detection of CSC- and EMT-associated proteins in tumor specimens. To this end, we generated novel antibodies to EMT- and CSC-associated proteins, including Goosecoid, Sox9, Slug, Snail, and CD133. Importantly, unlike several widely used antibodies to CD133, the anti-CD133 antibodies we generated recognize epitopes distal to known glycosylation sites, enabling analyses that are not confounded by differences in CD133 glycosylation. For all target proteins, we selected antibodies that yielded the expected target protein molecular weights by Western analysis and the correct subcellular localization patterns by immunofluorescence microscopy assay (IFA); binding selectivity was verified by immunoprecipitation-mass spectrometry and by immunohistochemistry and IFA peptide blocking experiments. Finally, we applied these reagents to assess modulation of the respective markers of EMT and CSCs in xenograft tumor models by IFA. We observed that the constitutive presence of human hepatocyte growth factor (hHGF) in the tumor microenvironment of H596 non-small cell lung cancer tumors implanted in homozygous hHGF knock-in transgenic mice induced a more mesenchymal-like tumor state (relative to the epithelial-like state when implanted in control SCID mice), as evidenced by the elevated expression of EMT-associated transcription factors detected by our novel antibodies. Similarly, our new anti-CD133 antibody enabled detection and quantitation of drug-induced reductions in CD133-positive tumor cells following treatment of SUM149PT triple-negative breast cancer xenograft models with the CSC/focal adhesion kinase (FAK) inhibitor VS-6063. Thus, our novel antibodies to CSC- and EMT-associated factors exhibit sufficient sensitivity and selectivity for immunofluorescence microscopy studies of these processes in preclinical xenograft tumor specimens and the potential for application with clinical samples.

Analytical considerations for mass spectrometry profiling in serum biomarker discovery.

The potential of using mass spectrometry profiling as a diagnostic tool has been demonstrated for a wide variety of diseases. Various cancers and cancer-related diseases have been the focus of much of this work because of both the paucity of good diagnostic markers and the knowledge that early diagnosis is the most powerful weapon in treating cancer. The implementation of mass spectrometry as a routine diagnostic tool has proved to be difficult, however, primarily because of the stringent controls that are required for the method to be reproducible. The method is evolving as a powerful guide to the discovery of biomarkers that could, in turn, be used either individually or in an array or panel of tests for early disease detection. Using proteomic patterns to guide biomarker discovery and the possibility of deployment in the clinical laboratory environment on current instrumentation or in a hybrid technology has the possibility of being the early diagnosis tool that is needed.

Proteomic patterns for classification of ovarian cancer and CTCL serum samples utilizing peak pairs indicative of post-translational modifications.

Proteomic patterns as a potential diagnostic technology has been well established for several cancer conditions and other diseases. The use of machine learning techniques such as decision trees, neural networks, genetic algorithms, and other methods has been the basis for pattern determination. Cancer is known to involve signaling pathways that are regulated through PTM of proteins. These modifications are also detectable with high confidence using high-resolution MS. We generated data using a prOTOF mass spectrometer on two sets of patient samples: ovarian cancer and cutaneous t-cell lymphoma (CTCL) with matched normal samples for each disease. Using the knowledge of mass shifts caused by common modifications, we built models using peak pairs and compared this to a conventional technique using individual peaks. The results for each disease showed that a small number of peak pairs gave classification equal to or better than the conventional technique that used multiple individual peaks. This simple peak picking technique could be used to guide identification of important peak pairs involved in the disease process.