| 1. |
- Chargari, Cyrus, et al.
(författare)
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Brachytherapy for Pediatric Patients at Gustave Roussy Cancer Campus : A Model of International Cooperation for Highly Specialized Treatments
- 2022
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Ingår i: International Journal of Radiation Oncology Biology Physics. - : Elsevier BV. - 0360-3016. ; 113:3, s. 602-613
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Childhood cancer is rare, and treatment is frequently associated with long-term morbidity. Disparities in survival and long-term side effects encourage the establishment of networks to increase access to complex organ-conservative strategies, such as brachytherapy. We report our experience of an international cooperation model in childhood cancers. Methods and Materials: We examined the outcome of all children referred to our center from national or international networks to be treated according to a multimodal organ-conservative approach, including brachytherapy. Results: We identified 305 patients whose median age at diagnosis was 2.2 years (range, 1.4 months to 17.2 years). Among these patients, 99 (32.4%) were treated between 2015 and 2020; 172 (56.4%) were referred from national centers; and 133 (43.6%) were international patients from 31 countries (mainly Europe). Also, 263 patients were referred for primary treatment and 42 patients were referred for salvage treatment. Genitourinary tumors were the most frequent sites, with 56.4% bladder/prostate rhabdomyosarcoma and 28.5% gynecologic tumors. In addition to brachytherapy, local treatment consisted of partial tumor resection in 207 patients (67.9%), and 39 patients (13%) had additional external radiation therapy. Median follow-up was 58 months (range, 1 month to 48 years), 93 months for national patients, and 37 months for international patients (P < .0001). Five-year local control, disease-free survival, and overall survival rates were 90.8% (95% confidence interval [CI], 87.3%-94.4%), 84.4% (95% CI, 80.1%-89.0%), and 93.3% (95% CI, 90.1%-96.5%), respectively. Patients referred for salvage treatment had poorer disease-free survival (P < .01). Implementation of image guided pulse-dose-rate brachytherapy was associated with better local control among patients with rhabdomyosarcoma referred for primary treatment (hazard ratio, 9.72; 95% CI, 1.24-71.0). At last follow-up, 16.7% patients had long-term severe treatment-related complications, and 2 patients (0.7%) had developed second malignancy. Conclusions: This retrospective series shows the feasibility of a multinational referral network for brachytherapy allowing high patient numbers in rare pediatric cancers. High local control probability and acceptable late severe complication probability could be achieved despite very challenging situations. This cooperation model could serve as a basis for generating international reference networks for high-tech radiation such as brachytherapy to increase treatment care opportunities and cure probability.
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| 2. |
- Adhikari, Subash, et al.
(författare)
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A high-stringency blueprint of the human proteome
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Forskningsöversikt (refereegranskat)abstract
- The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP’s tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.
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| 3. |
- Deutsch, Eric W., et al.
(författare)
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p Advances and Utility of the Human Plasma Proteome
- 2021
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 20:12, s. 5241-5263
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Forskningsöversikt (refereegranskat)abstract
- The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.
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| 4. |
- LeDuc, Richard D., et al.
(författare)
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Proteomics Standards Initiative's ProForma 2.0 : Unifying the Encoding of Proteoforms and Peptidoforms br
- 2022
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 21:4, s. 1189-1195
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Tidskriftsartikel (refereegranskat)abstract
- It is important for the proteomics community to have a standardizedmanner to represent all possible variations of a protein or peptide primary sequence,including natural, chemically induced, and artifactual modifications. The HumanProteome Organization Proteomics Standards Initiative in collaboration with severalmembers of the Consortium for Top-Down Proteomics (CTDP) has developed astandard notation called ProForma 2.0, which is a substantial extension of the originalProForma notation developed by the CTDP. ProForma 2.0 aims to unify therepresentation of proteoforms and peptidoforms. ProForma 2.0 supports use casesneeded for bottom-up and middle-/top-down proteomics approaches and allows theencoding of highly modified proteins and peptides using a human- and machine-readable string. ProForma 2.0 can be used to represent protein modifications in a specified or ambiguous location, designated bymass shifts, chemical formulas, or controlled vocabulary terms, including cross-links (natural and chemical) and atomic isotopes.Notational conventions are based on public controlled vocabularies and ontologies. The most up-to-date full specification documentand information about software implementations are available athttp://psidev.info/proforma.
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| 5. |
- Luo, Xiyang, et al.
(författare)
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A Comprehensive Evaluation of Consensus Spectrum Generation Methods in Proteomics
- 2022
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 21:6, s. 1566-1574
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Tidskriftsartikel (refereegranskat)abstract
- Spectrum clustering is a powerful strategy to minimize redundant mass spectra by grouping them based on similarity, with the aim of forming groups of mass spectra from the same repeatedly measured analytes. Each such group of near-identical spectra can be represented by its so-called consensus spectrum for downstream processing. Although several algorithms for spectrum clustering have been adequately benchmarked and tested, the influence of the consensus spectrum generation step is rarely evaluated. Here, we present an implementation and benchmark of common consensus spectrum algorithms, including spectrum averaging, spectrum binning, the most similar spectrum, and the best-identified spectrum. We have analyzed diverse public data sets using two different clustering algorithms (spectra-duster and MaRaCluster) to evaluate how the consensus spectrum generation procedure influences downstream peptide identification. The BEST and BIN methods were found the most reliable methods for consensus spectrum generation, including for data sets with post-translational modifications (PTM) such as phosphorylation. All source code and data of the present study are freely available on GitHub at https://github.com/statisticalbiotechnology/representative-spectra-benchmark.
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| 6. |
- Neely, Benjamin A., et al.
(författare)
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Toward an Integrated Machine Learning Model of a Proteomics Experiment
- 2023
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 22:3, s. 681-696
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Forskningsöversikt (refereegranskat)abstract
- In recent years machine learning has made extensive progress in modeling many aspects of mass spectrometry data. We brought together proteomics data generators, repository managers, and machine learning experts in a workshop with the goals to evaluate and explore machine learning applications for realistic modeling of data from multidimensional mass spectrometry-based proteomics analysis of any sample or organism. Following this sample-to-data roadmap helped identify knowledge gaps and define needs. Being able to generate bespoke and realistic synthetic data has legitimate and important uses in system suitability, method development, and algorithm benchmarking, while also posing critical ethical questions. The interdisciplinary nature of the workshop informed discussions of what is currently possible and future opportunities and challenges. In the following perspective we summarize these discussions in the hope of conveying our excitement about the potential of machine learning in proteomics and to inspire future research.
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| 7. |
- Omenn, Gilbert S., et al.
(författare)
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Progress Identifying and Analyzing the Human Proteome : 2021 Metrics from the HUPO Human Proteome Project
- 2021
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 20:12, s. 5227-5240
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Tidskriftsartikel (refereegranskat)abstract
- The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, MusculoSkeletal, Liver, and Cancers B/D-HPP teams and from the Knowledge-base, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.
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| 8. |
- Omenn, Gilbert S., et al.
(författare)
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Research on the Human Proteome Reaches a Major Milestone : > 90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project
- 2020
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 19:12, s. 4735-4746
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Tidskriftsartikel (refereegranskat)abstract
- According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.
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| 9. |
- Omenn, Gilbert S., et al.
(författare)
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The 2022 Report on the Human Proteome from the HUPO Human Proteome Project
- 2023
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 22:4, s. 1024-1042
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Tidskriftsartikel (refereegranskat)abstract
- The 2022 Metrics of the Human Proteome from the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 407 (93.2%) of the 19 750 predicted proteins coded in the human genome, a net gain of 50 since 2021 from data sets generated around the world and reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 78 from 1421 to 1343. This represents continuing experimental progress on the human proteome parts list across all the chromosomes, as well as significant reclassifications. Meanwhile, applying proteomics in a vast array of biological and clinical studies continues to yield significant findings and growing integration with other omics platforms. We present highlights from the Chromosome-Centric HPP, Biology and Disease-driven HPP, and HPP Resource Pillars, compare features of mass spectrometry and Olink and Somalogic platforms, note the emergence of translation products from ribosome profiling of small open reading frames, and discuss the launch of the initial HPP Grand Challenge Project, “A Function for Each Protein”.
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| 10. |
- Omenn, Gilbert S., et al.
(författare)
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The 2023 Report on the Proteome from the HUPO Human Proteome Project
- 2024
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 23:2, s. 532-549
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Forskningsöversikt (refereegranskat)abstract
- Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1–4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.
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