Explore the vast range of titles available.

The National Cancer Institute’s Office of Data Sharing is implementing a framework for data sharing and public access policies, which will empower innovation and maximize therapeutic benefits for the cancer community.

Mutations of the KRAS gene are found in human cancers with high frequency and result in the constitutive activation of its protein products. This leads to aberrant regulation of downstream pathways, promoting cell survival, proliferation, and tumorigenesis that drive cancer progression and negatively affect treatment outcomes. Here, we describe a workflow that can detect and quantify mutation-specific consequences of KRAS biochemistry, namely linked changes in posttranslational modifications (PTMs). We combined immunoaffinity enrichment with detection by top-down mass spectrometry to discover and quantify proteoforms with or without the Gly13Asp mutation (G13D) specifically in the KRAS4b isoform. The workflow was applied first to isogenic KRAS colorectal cancer (CRC) cell lines and then to patient CRC tumors with matching KRAS genotypes. In two cellular models, a direct link between the knockout of the mutant G13D allele and the complete nitrosylation of cysteine 118 of the remaining WT KRAS4b was observed. Analysis of tumor samples quantified the percentage of mutant KRAS4b actually present in cancer tissue and identified major differences in the levels of C-terminal carboxymethylation, a modification critical for membrane association. These data from CRC cells and human tumors suggest mechanisms of posttranslational regulation that are highly context-dependent and which lead to preferential production of specific KRAS4b proteoforms.

Vasopressin's action in renal cells to regulate water transport depends on protein phosphorylation. Here we used mass spectrometry-based quantitative phosphoproteomics to identify signaling pathways involved in the short-term V2-receptor-mediated response in cultured collecting duct cells (mpkCCD) from mouse. Using Stable Isotope Labeling by Amino acids in Cell culture (SILAC) with two treatment groups (0.1 nM dDAVP or vehicle for 30 min), we carried out quantification of 2884 phosphopeptides. The majority (82%) of quantified phosphopeptides did not change in abundance in response to dDAVP. Analysis of the 273 phosphopeptides increased by dDAVP showed a predominance of so-called \"basophilic\" motifs consistent with activation of kinases of the AGC family. Increases in phosphorylation of several known protein kinase A targets were found. In addition, increased phosphorylation of targets of the calmodulin-dependent kinase family was seen, including autophosphorylation of calmodulin-dependent kinase 2 at T286. Analysis of the 254 phosphopeptides decreased in abundance by dDAVP showed a predominance of so-called \"proline-directed\" motifs, consistent with down-regulation of mitogen-activated or cyclin-dependent kinases. dDAVP decreased phosphorylation of both JNK1/2 (T183/Y185) and ERK1/2 (T183/Y185; T203/Y205), consistent with a decrease in activation of these proline-directed kinases in response to dDAVP. Both ERK and JNK were able to phosphorylate residue S261of aquaporin-2 in vitro, a site showing a decrease in phosphorylation in response to dDAVP in vivo. The data support roles for multiple vasopressin V2-receptor-dependent signaling pathways in the vasopressin signaling network of collecting duct cells, involving several kinases not generally accepted to regulate collecting duct function.

During the past several decades, the understanding of cancer at the molecular level has been primarily focused on mechanisms on how signaling molecules transform homeostatically balanced cells into malignant ones within an individual pathway. However, it is becoming more apparent that pathways are dynamic and crosstalk at different control points of the signaling cascades, making the traditional linear signaling models inadequate to interpret complex biological systems. Recent technological advances in high throughput, deep sequencing for the human genomes and proteomic technologies to comprehensively characterize the human proteomes in conjunction with multiplexed targeted proteomic assays to measure panels of proteins involved in biologically relevant pathways have made significant progress in understanding cancer at the molecular level. It is undeniable that proteomic profiling of differentially expressed proteins under many perturbation conditions, or between normal and “diseased” states is important to capture a first glance at the overall proteomic landscape, which has been a main focus of proteomics research during the past 15-20 years. However, the research community is gradually shifting its heavy focus from that initial discovery step to protein target verification using multiplexed quantitative proteomic assays, capable of measuring changes in proteins and their interacting partners, isoforms, and post-translational modifications (PTMs) in response to stimuli in the context of signaling pathways and protein networks. With a critical link to genotypes (i.e., high throughput genomics and transcriptomics data), new and complementary information can be gleaned from multi-dimensional omics data to (1) assess the effect of genomic and transcriptomic aberrations on such complex molecular machinery in the context of cell signaling architectures associated with pathological diseases such as cancer (i.e., from genotype to proteotype to phenotype); and (2) target pathway- and network-driven changes and map the fluctuations of these functional units (proteins) responsible for cellular activities in response to perturbation in a spatiotemporal fashion to better understand cancer biology as a whole system.

Background Mass spectrometry-based proteomics has become a powerful tool for the identification and quantification of proteins from a wide variety of biological specimens. To date, the majority of studies utilizing tissue samples have been carried out on prospectively collected fresh frozen or optimal cutting temperature (OCT) embedded specimens. However, such specimens are often difficult to obtain, in limited in supply, and clinical information and outcomes on patients are inherently delayed as compared to banked samples. Annotated formalin fixed, paraffin embedded (FFPE) tumor tissue specimens are available for research use from a variety of tissue banks, such as from the surveillance, epidemiology and end results (SEER) registries’ residual tissue repositories. Given the wealth of outcomes information associated with such samples, the reuse of archived FFPE blocks for deep proteomic characterization with mass spectrometry technologies would provide a valuable resource for population-based cancer studies. Further, due to the widespread availability of FFPE specimens, validation of specimen integrity opens the possibility for thousands of studies that can be conducted worldwide. Methods To examine the suitability of the SEER repository tissues for proteomic and phosphoproteomic analysis, we analyzed 60 SEER patient samples, with time in storage ranging from 7 to 32 years; 60 samples with expression proteomics and 18 with phosphoproteomics, using isobaric labeling. Linear modeling and gene set enrichment analysis was used to evaluate the impacts of collection site and storage time. Results All samples, regardless of age, yielded suitable protein mass after extraction for expression analysis and 18 samples yielded sufficient mass for phosphopeptide analysis. Although peptide, protein, and phosphopeptide identifications were reduced by 50, 20 and 76% respectively, from comparable OCT specimens, we found no statistically significant differences in protein quantitation correlating with collection site or specimen age. GSEA analysis of GO-term level measurements of protein abundance differences between FFPE and OCT embedded specimens suggest that the formalin fixation process may alter representation of protein categories in the resulting dataset. Conclusions These studies demonstrate that residual FFPE tissue specimens, of varying age and collection site, are a promising source of protein for proteomic investigations if paired with rigorously verified mass spectrometry workflows.

Immunotherapies are revolutionizing cancer care, producing durable responses and potentially cures in a subset of patients. However, response rates are low for most tumors, grade 3/4 toxicities are not uncommon, and our current understanding of tumor immunobiology is incomplete. While hundreds of immunomodulatory proteins in the tumor microenvironment shape the anti-tumor response, few of them can be reliably quantified. To address this need, we developed a multiplex panel of targeted proteomic assays targeting 52 peptides representing 46 proteins using peptide immunoaffinity enrichment coupled to multiple reaction monitoring-mass spectrometry. We validated the assays in tissue and plasma matrices, where performance figures of merit showed over 3 orders of dynamic range and median inter-day CVs of 5.2% (tissue) and 21% (plasma). A feasibility study in clinical biospecimens showed detection of 48/52 peptides in frozen tissue and 38/52 peptides in plasma. The assays are publicly available as a resource for the research community.

In the past two decades, our ability to study cellular and molecular systems has been transformed through the development of omics sciences. While unlimited potential lies within massive omics datasets, the success of omics sciences to further our understanding of human disease and/or translating these findings to clinical utility remains elusive due to a number of factors. A significant limiting factor is the integration of different omics datasets (i.e., integromics) for extraction of biological and clinical insights. To this end, the National Cancer Institute (NCI) and the National Heart, Lung and Blood Institute (NHLBI) organized a joint workshop in June 2012 with the focus on integration issues related to multi-omics technologies that needed to be resolved in order to realize the full utility of integrating omics datasets by providing a glimpse into the disease as an integrated “system”. The overarching goals were to (1) identify challenges and roadblocks in omics integration, and (2) facilitate the full maturation of ‘integromics’ in biology and medicine. Participants reached a consensus on the most significant barriers for integrating omics sciences and provided recommendations on viable approaches to overcome each of these barriers within the areas of technology, bioinformatics and clinical medicine.

Clinical proteomics presents great promise in biology and medicine because of its potential for improving our understanding of diseases at the molecular level and for detecting disease-related biomarkers for diagnosis, prognosis, and prediction of therapeutic responses. To realize its full potential to improve clinical outcome for patients, proteomic studies have to be well designed, from biosample cohorts to data and statistical analyses. One key component in the biomarker development pipeline is the understanding of the regulatory science that evaluates diagnostic assay performance through rigorous analytical and clinical review criteria. The National Cancer Institute's Clinical Proteomic Technologies for Cancer (CPTC) initiative has proposed an intermediate preclinical \"verification\" step to close the gap between protein-based biomarker discovery and clinical qualification. In collaboration with the US Food and Drug Administration (FDA), the CPTC network investigators recently published 2 mock submission review documents, first-of-their-kind educational materials that may help the scientific community interested in developing products for the clinic in understanding the likely analytical evaluation requirements for multiplex protein technology-based diagnostic tests. Building on this momentum, the CPTC continues with this report its collaboration with the FDA, as well as its interactions with the AACC and the Centers for Medicare and Medicaid Services, to further the understanding of regulatory requirements for approving multiplex proteomic platform-based tests and analytically validating multiple analytes.

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.

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, \"How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?\" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.