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Prioritizing candidate biomarkers for verification remains a formidable obstacle to the translation of protein diagnostics to clinical applications. Whiteaker et al . assemble a multistage, targeted proteomics pipeline to relieve this bottleneck and use a mouse cancer model to demonstrate its analytical performance. High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.

A wealth of proteogenomic data has been generated using cancer samples to deepen our understanding of the mechanisms of cancer and how biological networks are altered in association with somatic mutation of tumor suppressor genes, such as TP53 and PTEN. To generate functional signatures of TP53 or PTEN loss, we profiled the RNA and phosphoproteomes of the MCF10A epithelial cell line, along with its congenic TP53- or PTEN-knockout derivatives, upon perturbation with the monofunctional DNA alkylating agent methyl methanesulfonate (MMS) vs. mock treatment. To enable quantitative and reproducible mass spectrometry data generation, the cell lines were SILAC-labeled (stable isotope labeling with amino acids in cell culture), and the experimental design included label swapping and biological replicates. All data are publicly available and may be used to advance our understanding of the TP53 and PTEN tumor suppressor genes and to provide functional signatures for bioinformatic analyses of proteogenomic datasets.

Introduction Acute myeloid leukemia (AML) remains one of the deadliest hematopoietic malignancies. A better understanding of the molecular biology governing AML may lead to improved risk stratification and facilitate the development of novel therapies. Proteins are responsible for much of the biology of cells. Several studies have examined the global proteome in bulk mononuclear cells (MNCs) from AML specimens, which are comprised a heterogenous population of cells at various stages of differentiation. Methods Given the potential impact of the nonleukemic cells on protein expression profiles, we applied an integrative proteogenomic approach utilizing next‐generation sequencing and mass spectrometry‐based proteomics to identify novel protein biomarkers in unsorted MNCs and viable leukemic blasts (VLBs) isolated from blood and bone marrow specimens obtained at the time of AML diagnosis. Results We identified significant differences in protein expression between VLBs and MNCs. Subsequent studies (N = 27) focused on proteomic profiling of VLBs that identified novel candidate biomarkers associated with mutational genotypes and clinical outcome, some of which were recapitulated in an independent cohort of patients. Using mass spectrometry, we also detected mutated protein products, some of which were predicted via in silico analyses to be potential neoantigens amenable to adoptive immunotherapy. As previously described, analyses comparing transcript and protein expression showed an overall modest correlation between mRNA and protein dataset, but enriching for genes associated with mutations significantly improved the protein–RNA correlation. Conclusion Together, the results provide insight into the biology of VLBs and demonstrate the gains derived from examining the proteome in addition to genome and transcriptome.

In the event of a nuclear incident in a heavily populated area, the surge in demand for medical evaluation will likely overwhelm our emergency care system, compromising our ability to care for victims with life-threatening injuries or exposures. Therefore, there exists a need for a rapidly deployable biological assay for radiation exposure that can be performed in the field by individuals with little to no medical training. Saliva is an attractive biofluid for this purpose, due to the relative ease of its collection and the wide array of biomolecules it contains. To determine whether the human salivary proteome is responsive to ionizing radiation exposure, we characterized the abundances of salivary proteins in humans before and after total body irradiation. Using an assay panel targeting 90 analytes (growth factors, chemokines and cytokines), we identified proteins that were significantly radiation responsive in human saliva. The responses of three proteins (monocyte chemo-attractant protein 1, interleukin 8 and intercellular adhesion molecule 1) were confirmed using independent immunoassay platforms and then verified and further characterized in 130 saliva samples from a completely independent set of 38 patients undergoing total body irradiation. The results demonstrate the potential for detecting radiation exposure based on analysis of human saliva.

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.

The structural maintenance of chromosome 1 (Smc1) protein is a member of the highly conserved cohesin complex and is involved in sister chromatid cohesion. In response to ionizing radiation, Smc1 is phosphorylated at two sites, Ser-957 and Ser-966, and these phosphorylation events are dependent on the ATM protein kinase. In this study, we describe the generation of two novel ELISAs for quantifying phospho-Smc1Ser-957 and phospho-Smc1Ser-966. Using these novel assays, we quantify the kinetic and biodosimetric responses of human cells of hematological origin, including immortalized cells, as well as both quiescent and cycling primary human PBMC. Additionally, we demonstrate a robust in vivo response for phospho-Smc1Ser-957 and phospho-Smc1Ser-966 in lymphocytes of human patients after therapeutic exposure to ionizing radiation, including total-body irradiation, partial-body irradiation, and internal exposure to 131I. These assays are useful for quantifying the DNA damage response in experimental systems and potentially for the identification of individuals exposed to radiation after a radiological incident.