Robert Rivers

Proteogenomic characterization of human colon and rectal cancer

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Integrated proteogenomic characterization of human high-grade serous ovarian cancer

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

Evolution of Clinical Proteomics and its Role in Medicine

Significant progress has been made in characterizing and sequencing genomic alterations of biospecimens from several types of cancer. Understanding the functional changes in the human proteome that arise from the genomic alterations or other factors is the next logical step in the development of high-value protein biomarkers that can be transitioned to clinical studies for biomarker qualification. Linking advances in genomic analysis to proteomic analysis will provide a pathway for qualified biomarkers which can drive the rational development of new diagnostics and therapies. The availability of these multidimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions.

Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective.

Proteomics holds great promise in personalized medicine for cancer in the post‐genomic era. In the past decade, clinical proteomics has significantly evolved in terms of technology development, optimization and standardization, as well as in advanced bioinformatics data integration and analysis. Great strides have been made for characterizing a large number of proteins qualitatively and quantitatively in a proteome, including the use of sample fractionation, protein microarrays and MS. It is believed that differential proteomic analysis of high‐quality clinical biospecimen (tissue and biofluids) can potentially reveal protein/peptide biomarkers responsible for cancer by means of their altered levels of expression and/or PTMs. Multiple reaction monitoring, a multiplexed platform using stable isotope dilution‐MS with sensitivity and reproducibility approaching that of traditional ELISAs commonly used in the clinical setting, has emerged as a potentially promising technique for next‐generation high‐throughput protein biomarker measurements for diagnostics and therapeutics.

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective and robust analytical platform for comprehensive analyses of tissue peptidomes, which is suitable for high-throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with postexcision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Moreover, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. Peptidomics complements results obtainable from conventional bottom-up proteomics and provides insights not readily obtainable from such approaches.

Recommendations for Mass Spectrometry Data Quality Metrics for Open Access Data (Corollary to the Amsterdam Principles)

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the United States National Cancer Institute convened the “International Workshop on Proteomic Data Quality Metrics” in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: 1) an evolving list of comprehensive quality metrics and 2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.

Linking cancer genome to proteome: NCI's investment into proteogenomics

Advances in both targeted and unbiased MS‐based proteomics are now at a mature stage for comprehensively and reproducibly characterizing a large part of the cancer proteome. These developments combined with the extensive genomic characterization of several cancer types by large‐scale initiatives such as the International Cancer Genome Consortium and Cancer Genome Atlas Project have paved the way for proteogenomic analysis of omics datasets and integration methods. The advances serve as the basis for the National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium and this article highlights its current work and future steps in the area of proteogenomics.

Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

Realizing individualized medicine: the road to translating proteomics from the laboratory to the clinic

The sequencing of the human genome has brought great promise and potential for the future of medicine, as well as providing a strong momentum for the burgeoning field of individualized medicine. Tests based on genetic information can be used to allow physicians to target therapies for those patients most likely to benefit from specific therapies and identify potential risk before the onset of disease. While advances in genomics-based molecular diagnostics are progressing, producing some useful US FDA-approved/-cleared diagnostic tests, protein-based molecular diagnostics have not met its promised potential. This article will provide an overview of protein-based analysis technologies, identify their strengths and limitations, discuss barriers to protein-based biomarker development and identify issues which must be addressed in order to successfully transfer the field of proteomics from the laboratory to the clinic.

Development of open-access mock 510(k) regulatory documents on multiplex proteomic technologies.

99 Background: Proteome-based biomarker science is progressing slowly for a variety of factors, including a lack of dialogue early in the discovery/development process with regulatory agencies such as the Food and Drug Administration (FDA). Although high-throughput multiplex proteomic-based technologies have the potential to accurately measure proteins of clinical significance in complex human matrices, regulatory approval for these analytical technologies have not been explored. METHODS To address this gap, investigators from the National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium (CPTAC) held a forward-thinking workshop, involving clinical laboratories, instrument manufacturers, researchers, and FDA representatives in order to streamline the regulatory approval of protein-based multiplex platforms. RESULTS Outcomes included a peer-reviewed workshop report published in special proteomics issue of Clinical Chemistry, and first-of-its-kind open access mock 510(k) regulatory documents (based on two most commonly applied quantitative proteomic technologies: multiplex mass spectrometry-based and multiplex affinity-based platforms) as public community resources (also published in Clinical Chemistry). CONCLUSIONS These open-access documents provide a glimpse of the FDAs perspective of novel approaches to in vitro diagnostics of multiplex protein assays and the process of premarket review. Therefore, these resources should enable others to focus on aspects of the process carefully monitored by the FDA, observe a format that is acceptable to the agency, and understand the iterative nature of review.