| Revision as of 12:33, 15 January 2025 editTimtrent (talk | contribs)Autopatrolled, Extended confirmed users, Page movers, New page reviewers, Pending changes reviewers132,198 editsm clean up (DraftCleaner)← Previous edit | Revision as of 12:35, 15 January 2025 edit undoTimtrent (talk | contribs)Autopatrolled, Extended confirmed users, Page movers, New page reviewers, Pending changes reviewers132,198 edits Filled in 10 bare reference(s) with reFill 2Next edit → | ||
| Line 3: | Line 3: | ||
| {{AfC topic|other}} | {{AfC topic|other}} | ||
| {{AfC submission|||ts=20250115111902|u=Hira Imran|ns=2}} | {{AfC submission|||ts=20250115111902|u=Hira Imran|ns=2}} | ||
| A ] Profile may be employed to discover or diagnose disease/condition, which can monitor responses to therapeutic measures. Sometimes also referred to as ] profile and protein signature.<ref>https://www.cancer.gov/publications/dictionaries/cancer-terms/def/proteomic-profile</ref> Proteome ] analysis is the analysis of the entire proteome from complex samples such as complete cells, tissues, and body fluids. It is most used for identifying as many ] and proteins as possible. Proteome profiling analysis based on ] can provide reference information for high-throughput quantitative proteomics and protein modification analysis.<ref>https://www.bgi.com/global/service/proteome-profiling</ref> Proteomic profiling is the large-scale analysis of proteins, which is essential for understanding biological processes and disease mechanisms. Recent studies have compared various platforms, such as SomaScan and Olink, and highlighted differences in precision, accuracy, and phenotypic associations across diverse ].<ref>https://www.science.org/doi/10.1126/sciadv.abm5164</ref> | A ] Profile may be employed to discover or diagnose disease/condition, which can monitor responses to therapeutic measures. Sometimes also referred to as ] profile and protein signature.<ref>https://www.cancer.gov/publications/dictionaries/cancer-terms/def/proteomic-profile</ref> Proteome ] analysis is the analysis of the entire proteome from complex samples such as complete cells, tissues, and body fluids. It is most used for identifying as many ] and proteins as possible. Proteome profiling analysis based on ] can provide reference information for high-throughput quantitative proteomics and protein modification analysis.<ref>{{Cite web|url=https://www.bgi.com/global/service/proteome-profiling|title=Proteome Profiling - BGI Mass Spec, NGS, Multi-omics, Proteomics|website=www.bgi.com}}</ref> Proteomic profiling is the large-scale analysis of proteins, which is essential for understanding biological processes and disease mechanisms. Recent studies have compared various platforms, such as SomaScan and Olink, and highlighted differences in precision, accuracy, and phenotypic associations across diverse ].<ref>{{Cite journal|url=https://www.science.org/doi/10.1126/sciadv.abm5164|title=Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods|first1=Daniel H.|last1=Katz|first2=Jeremy M.|last2=Robbins|first3=Shuliang|last3=Deng|first4=Usman A.|last4=Tahir|first5=Alexander G.|last5=Bick|first6=Akhil|last6=Pampana|first7=Zhi|last7=Yu|first8=Debby|last8=Ngo|first9=Mark D.|last9=Benson|first10=Zsu-Zsu|last10=Chen|first11=Daniel E.|last11=Cruz|first12=Dongxiao|last12=Shen|first13=Yan|last13=Gao|first14=Claude|last14=Bouchard|first15=Mark A.|last15=Sarzynski|first16=Adolfo|last16=Correa|first17=Pradeep|last17=Natarajan|first18=James G.|last18=Wilson|first19=Robert E.|last19=Gerszten|date=August 19, 2022|journal=Science Advances|volume=8|issue=33|pages=eabm5164|via=science.org (Atypon)|doi=10.1126/sciadv.abm5164|pmid=35984888|pmc=PMC9390994}}</ref> | ||
| === Key Techniques and Innovations === | === Key Techniques and Innovations === | ||
| Advanced emerging technologies in proteomics profiling are revolutionizing sensitivity, speed, and ] capabilities. Some key milestones in advances have been: | Advanced emerging technologies in proteomics profiling are revolutionizing sensitivity, speed, and ] capabilities. Some key milestones in advances have been: | ||
| '''''Single-Cell Proteomics''':'' Techniques of SCOPE-MS and prioritized Single Cell ProtEomics (pSCoPE) allow for deep analysis of individual cells and thus increase the proteome depth and resolution.<ref>https://www.technologynetworks.com/proteomics/articles/trends-and-advancements-in-proteomics-377815</ref> | '''''Single-Cell Proteomics''':'' Techniques of SCOPE-MS and prioritized Single Cell ProtEomics (pSCoPE) allow for deep analysis of individual cells and thus increase the proteome depth and resolution.<ref>{{Cite web|url=https://www.technologynetworks.com/proteomics/articles/trends-and-advancements-in-proteomics-377815|title=Trends and Advancements in Proteomics|website=Proteomics & Metabolomics from Technology Networks}}</ref> | ||
| '''''Mass Spectrometry Innovations''':'' ] enables the measurement of thousands of proteins from minimal samples in under 20 minutes. | '''''Mass Spectrometry Innovations''':'' ] enables the measurement of thousands of proteins from minimal samples in under 20 minutes. | ||
| Line 14: | Line 14: | ||
| '''''Machine Learning Integration''':'' AI is being used to predict and validate ] results, thereby improving accuracy and efficiency in ] | '''''Machine Learning Integration''':'' AI is being used to predict and validate ] results, thereby improving accuracy and efficiency in ] | ||
| '''''Immuno-ligation Methods''':'' High-throughput ] allow for the simultaneous detection of multiple proteins and thus improve profiling capabilities. This is opening up avenues to even more clinical applications with increased precision and biology.<ref>https://www.imec-int.com/en/articles/moonshot-reality-progress-proteomics</ref> | '''''Immuno-ligation Methods''':'' High-throughput ] allow for the simultaneous detection of multiple proteins and thus improve profiling capabilities. This is opening up avenues to even more clinical applications with increased precision and biology.<ref>{{Cite web|url=https://www.imec-int.com/en/articles/moonshot-reality-progress-proteomics|title=Progress in proteomics|website=imec}}</ref> | ||
| === Proteomic Profiling in Disease Detection === | === Proteomic Profiling in Disease Detection === | ||
| Line 20: | Line 20: | ||
| === Techniques for Data Analysis === | === Techniques for Data Analysis === | ||
| Global proteome profiling is the direct representation of the protein set in an organism, organ, tissues, or an organelle. Among the primary goals of proteomic analysis is to compare and determine the relative quantities of proteins under a defined set of conditions. Over the last 4 decades, ]s has gained popularity because it successfully helped differential ] provide visual proof of changes in protein abundance that cannot be predicted from genome analysis. Each protein spot on a 2-DE gel can be analyzed based on its abundance, location, or even presence and absence. This flexible gel-based method combines and makes use of the best principle for separation of protein complexes based on their charge and mass, visual mapping coupled with successful mass spectrometric identification of individual proteins.<ref>https://pubmed.ncbi.nlm.nih.gov/28735397/</ref> | Global proteome profiling is the direct representation of the protein set in an organism, organ, tissues, or an organelle. Among the primary goals of proteomic analysis is to compare and determine the relative quantities of proteins under a defined set of conditions. Over the last 4 decades, ]s has gained popularity because it successfully helped differential ] provide visual proof of changes in protein abundance that cannot be predicted from genome analysis. Each protein spot on a 2-DE gel can be analyzed based on its abundance, location, or even presence and absence. This flexible gel-based method combines and makes use of the best principle for separation of protein complexes based on their charge and mass, visual mapping coupled with successful mass spectrometric identification of individual proteins.<ref>{{Cite journal|url=https://pubmed.ncbi.nlm.nih.gov/28735397/|title=Global Proteomic Profiling and Identification of Stress-Responsive Proteins Using Two-Dimensional Gel Electrophoresis|first1=Pragya|last1=Barua|first2=Dipak|last2=Gayen|first3=Nilesh Vikram|last3=Lande|first4=Subhra|last4=Chakraborty|first5=Niranjan|last5=Chakraborty|date=January 15, 2017|journal=Methods in Molecular Biology (Clifton, N.J.)|volume=1631|pages=163–179|via=PubMed|doi=10.1007/978-1-4939-7136-7_10|pmid=28735397}}</ref> | ||
| Latest developments in proteomics have paved the way for the discovery of techniques such as ] analysis (COLA), which detects protein–protein co-localizations at a global scale. This helps map ] dynamics under various conditions, making it possible to understand protein interactions and functions.<ref>https://pmc.ncbi.nlm.nih.gov/articles/PMC5315029/</ref> Proteomic profiling relates to each individual's physiological changes by the monitoring of protein expression variations according to factors such as aging, exercise, and environmental conditions. For example, in aging muscle, proteomic analysis showed changes in ] and altered ] that indicate adaptations in muscle functions and energy metabolism.<ref>https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2011.00105/full</ref> | Latest developments in proteomics have paved the way for the discovery of techniques such as ] analysis (COLA), which detects protein–protein co-localizations at a global scale. This helps map ] dynamics under various conditions, making it possible to understand protein interactions and functions.<ref>{{Cite web|url=https://pmc.ncbi.nlm.nih.gov/articles/PMC5315029/|title=Proteomics profiling of interactome dynamics by colocalisation analysis (COLA) - PMC}}</ref> Proteomic profiling relates to each individual's physiological changes by the monitoring of protein expression variations according to factors such as aging, exercise, and environmental conditions. For example, in aging muscle, proteomic analysis showed changes in ] and altered ] that indicate adaptations in muscle functions and energy metabolism.<ref>{{Cite journal|url=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2011.00105/full|title=Proteomic Profiling of Fast-To-Slow Muscle Transitions during Aging|first=Kay|last=Ohlendieck|date=December 26, 2011|journal=Frontiers in Physiology|volume=2|via=Frontiers|doi=10.3389/fphys.2011.00105}}</ref> | ||
| === Proteomics in Cancer and Tumor Microenvironment === | === Proteomics in Cancer and Tumor Microenvironment === | ||
| In addition, proteomic approaches are very useful in characterizing ], which show how populations of cells influence cancer progression through protein interactions. Proteomics is especially well suited to the analysis of the microenvironment, considering that the origin of many components of the microenvironment is host tissue, with no appreciable genomic alteration detectable, and that the release and shedding of proteins from the surface of cancer cells contribute significantly, all of which cannot be predicted strictly from ]. It especially helped advance proteomic analysis toward a better understanding of how ] manipulate their microenvironment by producing structural proteins of ECM, modifying proteins of ECM, and proteases. Proteomics has also further advanced the global identification of ].<ref>https://pmc.ncbi.nlm.nih.gov/articles/PMC3978437/</ref> | In addition, proteomic approaches are very useful in characterizing ], which show how populations of cells influence cancer progression through protein interactions. Proteomics is especially well suited to the analysis of the microenvironment, considering that the origin of many components of the microenvironment is host tissue, with no appreciable genomic alteration detectable, and that the release and shedding of proteins from the surface of cancer cells contribute significantly, all of which cannot be predicted strictly from ]. It especially helped advance proteomic analysis toward a better understanding of how ] manipulate their microenvironment by producing structural proteins of ECM, modifying proteins of ECM, and proteases. Proteomics has also further advanced the global identification of ].<ref>{{Cite journal|url=https://pmc.ncbi.nlm.nih.gov/articles/PMC3978437/|title=Proteomic profiling of the tumor microenvironment: recent insights and the search for biomarkers|first1=Sam|last1=Hanash|first2=Mark|last2=Schliekelman|date=February 27, 2014|journal=Genome Medicine|volume=6|issue=2|doi=10.1186/gm529}}</ref> | ||
| === Importance === | === Importance === | ||
| '''Proteomic profiling''' is important in the advancement of our understanding of biological processes and mechanisms of disease. It helps in ], thereby enhancing diagnostics and vaccine development by revealing protein interactions and functions related to ].<ref>https://pubmed.ncbi.nlm.nih.gov/36601329/</ref> Protein profiling has greatly helped in the early detection of cancers by using specific proteins found in the blood plasma. Recent studies have developed proteome-based tests with a high degree of accuracy in the detection of early stage cancers, using panels of proteins that distinguish cancerous from normal samples. For example, it has recently been demonstrated that using panels of ten sex-specific proteins, early-stage cancer could be identified with up to 93% accuracy in males and 84% in females at high specificity levels.<ref>https://bmjoncology.bmj.com/content/3/1/e000073</ref> | '''Proteomic profiling''' is important in the advancement of our understanding of biological processes and mechanisms of disease. It helps in ], thereby enhancing diagnostics and vaccine development by revealing protein interactions and functions related to ].<ref>{{Cite journal|url=https://pubmed.ncbi.nlm.nih.gov/36601329/|title=Proteomics approaches: A review regarding an importance of proteome analyses in understanding the pathogens and diseases|first1=Muhammad|last1=Zubair|first2=Jia|last2=Wang|first3=Yanfei|last3=Yu|first4=Muhammad|last4=Faisal|first5=Mingpu|last5=Qi|first6=Abid Ullah|last6=Shah|first7=Zhixin|last7=Feng|first8=Guoqing|last8=Shao|first9=Yu|last9=Wang|first10=Qiyan|last10=Xiong|date=January 15, 2022|journal=Frontiers in Veterinary Science|volume=9|pages=1079359|via=PubMed|doi=10.3389/fvets.2022.1079359|pmid=36601329|pmc=9806867}}</ref> Protein profiling has greatly helped in the early detection of cancers by using specific proteins found in the blood plasma. Recent studies have developed proteome-based tests with a high degree of accuracy in the detection of early stage cancers, using panels of proteins that distinguish cancerous from normal samples. For example, it has recently been demonstrated that using panels of ten sex-specific proteins, early-stage cancer could be identified with up to 93% accuracy in males and 84% in females at high specificity levels.<ref>{{Cite journal|url=https://bmjoncology.bmj.com/content/3/1/e000073|title=Novel proteomics-based plasma test for early detection of multiple cancers in the general population|first1=Bogdan|last1=Budnik|first2=Hossein|last2=Amirkhani|first3=Mohammad H.|last3=Forouzanfar|first4=Ashkan|last4=Afshin|date=January 9, 2024|journal=BMJ Oncology|volume=3|issue=1|via=bmjoncology.bmj.com|doi=10.1136/bmjonc-2023-000073|pmid=10.1136/bmjonc-2023-000073}}</ref> | ||
| == References == | == References == | ||
Revision as of 12:35, 15 January 2025
Proteomic Profiling | This article, Proteomic Profiling, has recently been created via the Articles for creation process. Please check to see if the reviewer has accidentally left this template after accepting the draft and take appropriate action as necessary.
Reviewer tools: Inform author |
A Proteomic Profile may be employed to discover or diagnose disease/condition, which can monitor responses to therapeutic measures. Sometimes also referred to as protein expression profile and protein signature. Proteome profiling analysis is the analysis of the entire proteome from complex samples such as complete cells, tissues, and body fluids. It is most used for identifying as many peptides and proteins as possible. Proteome profiling analysis based on mass spectrometry (MS) can provide reference information for high-throughput quantitative proteomics and protein modification analysis. Proteomic profiling is the large-scale analysis of proteins, which is essential for understanding biological processes and disease mechanisms. Recent studies have compared various platforms, such as SomaScan and Olink, and highlighted differences in precision, accuracy, and phenotypic associations across diverse cohorts.
Key Techniques and Innovations
Advanced emerging technologies in proteomics profiling are revolutionizing sensitivity, speed, and data analysis capabilities. Some key milestones in advances have been:
Single-Cell Proteomics: Techniques of SCOPE-MS and prioritized Single Cell ProtEomics (pSCoPE) allow for deep analysis of individual cells and thus increase the proteome depth and resolution.
Mass Spectrometry Innovations: Thermo Fisher's Orbitrap Astral enables the measurement of thousands of proteins from minimal samples in under 20 minutes.
Machine Learning Integration: AI is being used to predict and validate mass spectrometry results, thereby improving accuracy and efficiency in data interpretation.
Immuno-ligation Methods: High-throughput multiplex assays allow for the simultaneous detection of multiple proteins and thus improve profiling capabilities. This is opening up avenues to even more clinical applications with increased precision and biology.
Proteomic Profiling in Disease Detection
Proteomics profiling has been used in the discovery of biomarkers for diseases. A study conducted with the use of the Olink Proteomics Platform found that patients with glaucoma had differently expressed metabolic proteins, thus the potential of proteomics in early disease detection and development of a therapeutic strategy.
Techniques for Data Analysis
Global proteome profiling is the direct representation of the protein set in an organism, organ, tissues, or an organelle. Among the primary goals of proteomic analysis is to compare and determine the relative quantities of proteins under a defined set of conditions. Over the last 4 decades, two-dimensional gel electrophoresis has gained popularity because it successfully helped differential proteomics provide visual proof of changes in protein abundance that cannot be predicted from genome analysis. Each protein spot on a 2-DE gel can be analyzed based on its abundance, location, or even presence and absence. This flexible gel-based method combines and makes use of the best principle for separation of protein complexes based on their charge and mass, visual mapping coupled with successful mass spectrometric identification of individual proteins.
Latest developments in proteomics have paved the way for the discovery of techniques such as colocalization analysis (COLA), which detects protein–protein co-localizations at a global scale. This helps map interactome dynamics under various conditions, making it possible to understand protein interactions and functions. Proteomic profiling relates to each individual's physiological changes by the monitoring of protein expression variations according to factors such as aging, exercise, and environmental conditions. For example, in aging muscle, proteomic analysis showed changes in protein isoforms and altered metabolic pathways that indicate adaptations in muscle functions and energy metabolism.
Proteomics in Cancer and Tumor Microenvironment
In addition, proteomic approaches are very useful in characterizing tumor microenvironments, which show how populations of cells influence cancer progression through protein interactions. Proteomics is especially well suited to the analysis of the microenvironment, considering that the origin of many components of the microenvironment is host tissue, with no appreciable genomic alteration detectable, and that the release and shedding of proteins from the surface of cancer cells contribute significantly, all of which cannot be predicted strictly from genomic analysis. It especially helped advance proteomic analysis toward a better understanding of how tumor cells manipulate their microenvironment by producing structural proteins of ECM, modifying proteins of ECM, and proteases. Proteomics has also further advanced the global identification of protease targets.
Importance
Proteomic profiling is important in the advancement of our understanding of biological processes and mechanisms of disease. It helps in pathogen identification, thereby enhancing diagnostics and vaccine development by revealing protein interactions and functions related to virulence. Protein profiling has greatly helped in the early detection of cancers by using specific proteins found in the blood plasma. Recent studies have developed proteome-based tests with a high degree of accuracy in the detection of early stage cancers, using panels of proteins that distinguish cancerous from normal samples. For example, it has recently been demonstrated that using panels of ten sex-specific proteins, early-stage cancer could be identified with up to 93% accuracy in males and 84% in females at high specificity levels.
References
- https://www.cancer.gov/publications/dictionaries/cancer-terms/def/proteomic-profile
- "Proteome Profiling - BGI Mass Spec, NGS, Multi-omics, Proteomics". www.bgi.com.
- Katz, Daniel H.; Robbins, Jeremy M.; Deng, Shuliang; Tahir, Usman A.; Bick, Alexander G.; Pampana, Akhil; Yu, Zhi; Ngo, Debby; Benson, Mark D.; Chen, Zsu-Zsu; Cruz, Daniel E.; Shen, Dongxiao; Gao, Yan; Bouchard, Claude; Sarzynski, Mark A.; Correa, Adolfo; Natarajan, Pradeep; Wilson, James G.; Gerszten, Robert E. (August 19, 2022). "Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods". Science Advances. 8 (33): eabm5164. doi:10.1126/sciadv.abm5164. PMC 9390994. PMID 35984888 – via science.org (Atypon).
{{cite journal}}: CS1 maint: PMC format (link) - "Trends and Advancements in Proteomics". Proteomics & Metabolomics from Technology Networks.
- "Progress in proteomics". imec.
- https://pubs.acs.org/doi/10.1021/acs.jproteome.4c00593#:~:text=In%20this%20study%2C%20we%20used,glaucoma%20and%20the%20cataract%20group.
- Barua, Pragya; Gayen, Dipak; Lande, Nilesh Vikram; Chakraborty, Subhra; Chakraborty, Niranjan (January 15, 2017). "Global Proteomic Profiling and Identification of Stress-Responsive Proteins Using Two-Dimensional Gel Electrophoresis". Methods in Molecular Biology (Clifton, N.J.). 1631: 163–179. doi:10.1007/978-1-4939-7136-7_10. PMID 28735397 – via PubMed.
- "Proteomics profiling of interactome dynamics by colocalisation analysis (COLA) - PMC".
- Ohlendieck, Kay (December 26, 2011). "Proteomic Profiling of Fast-To-Slow Muscle Transitions during Aging". Frontiers in Physiology. 2. doi:10.3389/fphys.2011.00105 – via Frontiers.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - Hanash, Sam; Schliekelman, Mark (February 27, 2014). "Proteomic profiling of the tumor microenvironment: recent insights and the search for biomarkers". Genome Medicine. 6 (2). doi:10.1186/gm529.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - Zubair, Muhammad; Wang, Jia; Yu, Yanfei; Faisal, Muhammad; Qi, Mingpu; Shah, Abid Ullah; Feng, Zhixin; Shao, Guoqing; Wang, Yu; Xiong, Qiyan (January 15, 2022). "Proteomics approaches: A review regarding an importance of proteome analyses in understanding the pathogens and diseases". Frontiers in Veterinary Science. 9: 1079359. doi:10.3389/fvets.2022.1079359. PMC 9806867. PMID 36601329 – via PubMed.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - Budnik, Bogdan; Amirkhani, Hossein; Forouzanfar, Mohammad H.; Afshin, Ashkan (January 9, 2024). "Novel proteomics-based plasma test for early detection of multiple cancers in the general population". BMJ Oncology. 3 (1). doi:10.1136/bmjonc-2023-000073. PMID 10.1136/bmjonc-2023-000073 – via bmjoncology.bmj.com.
{{cite journal}}: Check|pmid=value (help)