| 1. |
- Aebersold, Ruedi, et al.
(författare)
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How many human proteoforms are there?
- 2018
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Ingår i: Nature Chemical Biology. - : NATURE PUBLISHING GROUP. - 1552-4450 .- 1552-4469. ; 14:3, s. 206-214
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Boja, Emily S., et al.
(författare)
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Analytical Validation Considerations of Multiplex Mass-Spectrometry-Based Proteomic Platforms for Measuring Protein Biomarkers
- 2014
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 13:12, s. 5325-5332
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), staggers to make a significant impact with only an average similar to 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years.
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| 3. |
- Fehniger, Thomas, et al.
(författare)
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Four Areas of Engagement Requiring Strengthening in Modern Proteomics Today.
- 2014
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 13:12, s. 5310-5318
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Tidskriftsartikel (refereegranskat)abstract
- The global human proteomics community in 2014 is fully engaged in projects that aim to create a better understanding of human biology and its complexities and to provide products from this new knowledge that will in some way benefit humanity. Human proteomics, like any other scientific enterprise, needs to identify areas of direction and development, both for the near future in completing current research projects and into the long-term for the engagement with even more complex challenges. In this Editorial we highlight and discuss four important areas that we collectively believe require attention and demand a collective response going forward. These four areas are: (1) Provide high-quality standardized, sensitive, specific, quantitative, and readily accessible protein, peptide, or other biomarkers of health, disease, response to therapy into the approval processes of regulatory agencies (e.g., U.S. Food and Drug Administration; FDA), and obtaining approval from the relevant agencies for their use in a clinical or other testing settings. (2) Implement standard processes for collecting, processing, and storing human clinical samples in biorepositories and enforcement of measures to ensure subject integrity including informed consent for the downstream use of samples and in registrations of subject identities within study databases. (3) Test and validate mass spectrometry technology platforms that hold much promise for creating opportunities for obtaining new important knowledge at levels of detection previously not achievable. (4) Organize clinical discovery operations and activities in an intuitive manner to meet the challenges of increased interests in the science we provide and diminishing levels of centrally financed resource and infrastructure support.
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| 4. |
- Marko-Varga, György, et al.
(författare)
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Biorepository Regulatory Frameworks: Building Parallel Resources That Both Promote Scientific Investigation and Protect Human Subjects
- 2014
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 13:12, s. 5319-5324
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Clinical samples contained in biorepositories represent an important resource for investigating the many factors that drive human biology. The biological and chemical markers contained in clinical samples provide important measures of health and disease that when combined with such medical evaluation data can aid in decision making by physicians. Nearly all disciplines in medicine and every omic depend upon the readouts obtained from such samples, whether the measured analyte is a gene, a protein, a lipid, or a metabolite. There are many steps in sample processing, storage, and management that need to understood by the researchers who utilize biorepositories in their own work. These include not only the preservation of the desired analytes in the sample but also good understanding of the moral and legal framework required for subject protection irrespective of where the samples have been collected. Today there is a great deal of effort in the community to align and standardize both the methodology of sample collection and storage performed in different locations and the necessary frameworks of subject protection including informed consent and institutional review of the studies being performed. There is a growing trend in developing biorepositories around the focus of large population-based studies that address both active and silent nonsymptomatic disease. Logistically these studies generate large numbers of clinical samples and practically place increasing demand upon health care systems to provide uniform sample handling, processing, storage, and documentation of both the sample and the subject as well to ensure that safeguards exist to protect the rights of the study subjects for deciding upon the fates of their samples. Currently the authority to regulate the entire scope of biorepository usage exists as national practice in law in only a few countries. Such legal protection is a necessary component within the framework of biorepositories, both now and in the future. In this brief overview, we provide practical information to the potential users of biorepositories about some of the current developments in both the methodology of sample acquisition and in the regulatory environment governing their use.
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| 5. |
- Olson, Nathan D., et al.
(författare)
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precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regions
- 2020
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new machine-learning approaches combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.
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| 6. |
- Olson, Nathan D., et al.
(författare)
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PrecisionFDA Truth Challenge V2: Calling variants from short and long reads in difficult-to-map regions
- 2022
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Ingår i: Cell Genomics. - : Elsevier BV. - 2666-979X. ; 2:5, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- The precisionFDA Truth Challenge V2 aimed to assess the state of the art of variant calling in challenging genomic regions. Starting with FASTQs, 20 challenge participants applied their variant-calling pipelines and submitted 64 variant call sets for one or more sequencing technologies (Illumina, PacBio HiFi, and Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with updated Genome in a Bottle benchmark sets and genome stratifications. Challenge submissions included numerous innovative methods, with graph-based and machine learning methods scoring best for short-read and long-read datasets, respectively. With machine learning approaches, combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.
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| 7. |
- Yoo, Seungyeul, et al.
(författare)
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A community effort to identify and correct mislabeled samples in proteogenomic studies
- 2021
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Ingår i: Patterns. - : Elsevier BV. - 2666-3899. ; 2:5
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Tidskriftsartikel (refereegranskat)abstract
- Sample mislabeling or misannotation has been a long-standing problem in scientific research, particularly prevalent in large-scale, multi-omic studies due to the complexity of multi-omic workflows. There exists an urgent need for implementing quality controls to automatically screen for and correct sample mislabels or misannotations in multi-omic studies. Here, we describe a crowdsourced precisionFDA NCI-CPTAC Multi-omics Enabled Sample Mislabeling Correction Challenge, which provides a framework for systematic benchmarking and evaluation of mislabel identification and correction methods for integrative proteogenomic studies. The challenge received a large number of submissions from domestic and international data scientists, with highly variable performance observed across the submitted methods. Post-challenge collaboration between the top-performing teams and the challenge organizers has created an open-source software, COSMO, with demonstrated high accuracy and robustness in mislabeling identification and correction in simulated and real multi-omic datasets.
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