P474: FUNCTIONAL (PHOSPHO-)PROTEOMICS OF DRUG RESPONSE IN ACUTE MYELOID LEUKEMIA Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1097/01.hs9.0000968804.83594.27
Background: Acute Myeloid Leukemia (AML) is a particularly heterogeneous malignancy, for which standard care often fails to reach a durable response. Given the high inter-individual diversity, patients could potentially benefit from therapies tailored to an individual’s unique molecular profile, background and physical status. Such efforts are currently pioneered by genomics technologies, yet most therapeutics aim to alter the activity of proteins rather than genes. At the same time, our knowledge about the functional consequences of genetic aberrations and the role of the cellular context remains incomplete. Therefore, directly assessing how therapeutics alter the proteome activity will open new frontiers. Aims: Here, we introduce a functional mass spectrometry-based (phospho-)proteomics approach and demonstrate its application to probe the dynamic molecular response of AML cells to drug treatment. Methods: We build on a state-of-the-art high-resolution mass spectrometry platform to perform multi-modal proteome analyses from 96 well-plate cultures of cell lines. Viable primary peripheral blood mononuclear cells were isolated from patient blood draws. For drug response experiments, human cell lines were incubated with either DMSO or commonly available drugs (e.g. bortezomib, venetoclax) at IC50 concentrations following standard protocols. To quantify protein phosphorylation on a proteome-wide scale, we applied our recently developed µPhos protocol (Oliinyk et al., bioRxiv 2023) that enables straightforward and miniaturized sample processing from 96-well cell culture plates. To delineate drug response signatures, we performed dose-response and time-course experiments and analyzed the proteomics result files statistically in the R or Python programming environments. Results: We demonstrate the application of our µPhos platform to perform functional proteomics and phosphoproteomics of drug response in 96-well format. Using highly sensitive trapped ion mobility mass spectrometry, we quantified >15,000 unique phosphopeptides from 10 µg protein starting material (~50,000 human cancer cells) and generated quantitative profiles of >7,000 proteins within one hour analysis time. This analytical depth widely covers cellular pathways and clinically relevant drug targets. Analysis of primary AML cells revealed a remarkable diversity of phosphoproteomes between patients, indicating potential differences in their proteome activity status. Our cell culture experiments provided insight into the molecular signatures of drug response. For example, incubating the human AML cell line U937 with the proteasome inhibitor bortezomib showed a significant down-regulation of secretory proteins as well as increased phosphorylation of chromatin remodelers and the TGF-β signaling machinery. We are currently performing time-course and dose-response experiments to further deconvolute the complex response signatures. Summary/Conclusion: We conclude that µPhos is a powerful platform to elucidate drug response on the phosphoproteome level. The demonstrated capability to work with small sample amounts makes it also very attractive for the analysis of primary patient samples. Keywords: Bortezomib, Proteomics, Acute myeloid leukemia, Phosphorylation
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1097/01.hs9.0000968804.83594.27
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385667146
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4385667146Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1097/01.hs9.0000968804.83594.27Digital Object Identifier
- Title
-
P474: FUNCTIONAL (PHOSPHO-)PROTEOMICS OF DRUG RESPONSE IN ACUTE MYELOID LEUKEMIAWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-01Full publication date if available
- Authors
-
Denys Oliinyk, Maximilian Fleischmann, Dilfuza Ernafasova, Caroline Tschernjawski, Sebastian Scholl, Andreas Hochhaus, Florian Meier-RosarList of authors in order
- Landing page
-
https://doi.org/10.1097/01.hs9.0000968804.83594.27Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1097/01.hs9.0000968804.83594.27Direct OA link when available
- Concepts
-
Proteome, Proteomics, Myeloid leukemia, Mass cytometry, Computational biology, Drug response, Context (archaeology), Bioinformatics, Drug, Biology, Medicine, Pharmacology, Cancer research, Gene, Phenotype, Genetics, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4385667146 |
|---|---|
| doi | https://doi.org/10.1097/01.hs9.0000968804.83594.27 |
| ids.doi | https://doi.org/10.1097/01.hs9.0000968804.83594.27 |
| ids.openalex | https://openalex.org/W4385667146 |
| fwci | 0.0 |
| type | article |
| title | P474: FUNCTIONAL (PHOSPHO-)PROTEOMICS OF DRUG RESPONSE IN ACUTE MYELOID LEUKEMIA |
| biblio.issue | S3 |
| biblio.volume | 7 |
| biblio.last_page | e8359427 |
| biblio.first_page | e8359427 |
| topics[0].id | https://openalex.org/T10519 |
| topics[0].field.id | https://openalex.org/fields/16 |
| topics[0].field.display_name | Chemistry |
| topics[0].score | 0.9690999984741211 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1607 |
| topics[0].subfield.display_name | Spectroscopy |
| topics[0].display_name | Advanced Proteomics Techniques and Applications |
| topics[1].id | https://openalex.org/T10836 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9495999813079834 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1312 |
| topics[1].subfield.display_name | Molecular Biology |
| topics[1].display_name | Metabolomics and Mass Spectrometry Studies |
| is_xpac | False |
| apc_list.value | 1200 |
| apc_list.currency | USD |
| apc_list.value_usd | 1200 |
| apc_paid.value | 1200 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1200 |
| concepts[0].id | https://openalex.org/C104397665 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6968753337860107 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q860947 |
| concepts[0].display_name | Proteome |
| concepts[1].id | https://openalex.org/C46111723 |
| concepts[1].level | 3 |
| concepts[1].score | 0.6403806805610657 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q471857 |
| concepts[1].display_name | Proteomics |
| concepts[2].id | https://openalex.org/C2778729363 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5624572038650513 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11688946 |
| concepts[2].display_name | Myeloid leukemia |
| concepts[3].id | https://openalex.org/C2778015335 |
| concepts[3].level | 4 |
| concepts[3].score | 0.5547364354133606 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q17051163 |
| concepts[3].display_name | Mass cytometry |
| concepts[4].id | https://openalex.org/C70721500 |
| concepts[4].level | 1 |
| concepts[4].score | 0.5371736884117126 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q177005 |
| concepts[4].display_name | Computational biology |
| concepts[5].id | https://openalex.org/C2994119904 |
| concepts[5].level | 3 |
| concepts[5].score | 0.5277405977249146 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1251001 |
| concepts[5].display_name | Drug response |
| concepts[6].id | https://openalex.org/C2779343474 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4196212589740753 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q3109175 |
| concepts[6].display_name | Context (archaeology) |
| concepts[7].id | https://openalex.org/C60644358 |
| concepts[7].level | 1 |
| concepts[7].score | 0.3895914554595947 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q128570 |
| concepts[7].display_name | Bioinformatics |
| concepts[8].id | https://openalex.org/C2780035454 |
| concepts[8].level | 2 |
| concepts[8].score | 0.35655495524406433 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q8386 |
| concepts[8].display_name | Drug |
| concepts[9].id | https://openalex.org/C86803240 |
| concepts[9].level | 0 |
| concepts[9].score | 0.35283783078193665 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[9].display_name | Biology |
| concepts[10].id | https://openalex.org/C71924100 |
| concepts[10].level | 0 |
| concepts[10].score | 0.32951119542121887 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[10].display_name | Medicine |
| concepts[11].id | https://openalex.org/C98274493 |
| concepts[11].level | 1 |
| concepts[11].score | 0.30494749546051025 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q128406 |
| concepts[11].display_name | Pharmacology |
| concepts[12].id | https://openalex.org/C502942594 |
| concepts[12].level | 1 |
| concepts[12].score | 0.300056517124176 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q3421914 |
| concepts[12].display_name | Cancer research |
| concepts[13].id | https://openalex.org/C104317684 |
| concepts[13].level | 2 |
| concepts[13].score | 0.15508908033370972 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[13].display_name | Gene |
| concepts[14].id | https://openalex.org/C127716648 |
| concepts[14].level | 3 |
| concepts[14].score | 0.12095066905021667 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q104053 |
| concepts[14].display_name | Phenotype |
| concepts[15].id | https://openalex.org/C54355233 |
| concepts[15].level | 1 |
| concepts[15].score | 0.10736989974975586 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q7162 |
| concepts[15].display_name | Genetics |
| concepts[16].id | https://openalex.org/C151730666 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q7205 |
| concepts[16].display_name | Paleontology |
| keywords[0].id | https://openalex.org/keywords/proteome |
| keywords[0].score | 0.6968753337860107 |
| keywords[0].display_name | Proteome |
| keywords[1].id | https://openalex.org/keywords/proteomics |
| keywords[1].score | 0.6403806805610657 |
| keywords[1].display_name | Proteomics |
| keywords[2].id | https://openalex.org/keywords/myeloid-leukemia |
| keywords[2].score | 0.5624572038650513 |
| keywords[2].display_name | Myeloid leukemia |
| keywords[3].id | https://openalex.org/keywords/mass-cytometry |
| keywords[3].score | 0.5547364354133606 |
| keywords[3].display_name | Mass cytometry |
| keywords[4].id | https://openalex.org/keywords/computational-biology |
| keywords[4].score | 0.5371736884117126 |
| keywords[4].display_name | Computational biology |
| keywords[5].id | https://openalex.org/keywords/drug-response |
| keywords[5].score | 0.5277405977249146 |
| keywords[5].display_name | Drug response |
| keywords[6].id | https://openalex.org/keywords/context |
| keywords[6].score | 0.4196212589740753 |
| keywords[6].display_name | Context (archaeology) |
| keywords[7].id | https://openalex.org/keywords/bioinformatics |
| keywords[7].score | 0.3895914554595947 |
| keywords[7].display_name | Bioinformatics |
| keywords[8].id | https://openalex.org/keywords/drug |
| keywords[8].score | 0.35655495524406433 |
| keywords[8].display_name | Drug |
| keywords[9].id | https://openalex.org/keywords/biology |
| keywords[9].score | 0.35283783078193665 |
| keywords[9].display_name | Biology |
| keywords[10].id | https://openalex.org/keywords/medicine |
| keywords[10].score | 0.32951119542121887 |
| keywords[10].display_name | Medicine |
| keywords[11].id | https://openalex.org/keywords/pharmacology |
| keywords[11].score | 0.30494749546051025 |
| keywords[11].display_name | Pharmacology |
| keywords[12].id | https://openalex.org/keywords/cancer-research |
| keywords[12].score | 0.300056517124176 |
| keywords[12].display_name | Cancer research |
| keywords[13].id | https://openalex.org/keywords/gene |
| keywords[13].score | 0.15508908033370972 |
| keywords[13].display_name | Gene |
| keywords[14].id | https://openalex.org/keywords/phenotype |
| keywords[14].score | 0.12095066905021667 |
| keywords[14].display_name | Phenotype |
| keywords[15].id | https://openalex.org/keywords/genetics |
| keywords[15].score | 0.10736989974975586 |
| keywords[15].display_name | Genetics |
| language | en |
| locations[0].id | doi:10.1097/01.hs9.0000968804.83594.27 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210211592 |
| locations[0].source.issn | 2572-9241 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2572-9241 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | HemaSphere |
| locations[0].source.host_organization | https://openalex.org/P4310318547 |
| locations[0].source.host_organization_name | Wolters Kluwer |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310318547 |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | HemaSphere |
| locations[0].landing_page_url | https://doi.org/10.1097/01.hs9.0000968804.83594.27 |
| locations[1].id | pmh:oai:pubmedcentral.nih.gov:10428809 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S2764455111 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed Central |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | cc-by-nc-nd |
| locations[1].pdf_url | https://pmc.ncbi.nlm.nih.gov/articles/PMC10428809/pdf/hs9-7-e8359427.pdf |
| locations[1].version | submittedVersion |
| locations[1].raw_type | Text |
| locations[1].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Hemasphere |
| locations[1].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/10428809 |
| locations[2].id | pmh:oai:doaj.org/article:c981470b46834db7af44b384adfa6ae2 |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].source.host_organization_lineage | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | HemaSphere, Vol 7, p e8359427 (2023) |
| locations[2].landing_page_url | https://doaj.org/article/c981470b46834db7af44b384adfa6ae2 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5113260536 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Denys Oliinyk |
| authorships[0].countries | DE |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210134900 |
| authorships[0].affiliations[0].raw_affiliation_string | Jena University Hospital, Functional Proteomics, Jena, Germany |
| authorships[0].institutions[0].id | https://openalex.org/I4210134900 |
| authorships[0].institutions[0].ror | https://ror.org/035rzkx15 |
| authorships[0].institutions[0].type | healthcare |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210134900 |
| authorships[0].institutions[0].country_code | DE |
| authorships[0].institutions[0].display_name | Jena University Hospital |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Denys Oliinyk |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Jena University Hospital, Functional Proteomics, Jena, Germany |
| authorships[1].author.id | https://openalex.org/A5049210820 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Maximilian Fleischmann |
| authorships[1].countries | DE |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210134900 |
| authorships[1].affiliations[0].raw_affiliation_string | Jena University Hospital, Klinik für Innere Medizin II, Jena, Germany |
| authorships[1].institutions[0].id | https://openalex.org/I4210134900 |
| authorships[1].institutions[0].ror | https://ror.org/035rzkx15 |
| authorships[1].institutions[0].type | healthcare |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210134900 |
| authorships[1].institutions[0].country_code | DE |
| authorships[1].institutions[0].display_name | Jena University Hospital |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Maximilian Fleischmann |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Jena University Hospital, Klinik für Innere Medizin II, Jena, Germany |
| authorships[2].author.id | https://openalex.org/A5092614030 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Dilfuza Ernafasova |
| authorships[2].countries | DE |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210134900 |
| authorships[2].affiliations[0].raw_affiliation_string | Jena University Hospital, Functional Proteomics, Jena, Germany |
| authorships[2].institutions[0].id | https://openalex.org/I4210134900 |
| authorships[2].institutions[0].ror | https://ror.org/035rzkx15 |
| authorships[2].institutions[0].type | healthcare |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210134900 |
| authorships[2].institutions[0].country_code | DE |
| authorships[2].institutions[0].display_name | Jena University Hospital |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Dilfuza Ernafasova |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Jena University Hospital, Functional Proteomics, Jena, Germany |
| authorships[3].author.id | https://openalex.org/A5092614031 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Caroline Tschernjawski |
| authorships[3].countries | DE |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210134900 |
| authorships[3].affiliations[0].raw_affiliation_string | Jena University Hospital, Functional Proteomics, Jena, Germany |
| authorships[3].institutions[0].id | https://openalex.org/I4210134900 |
| authorships[3].institutions[0].ror | https://ror.org/035rzkx15 |
| authorships[3].institutions[0].type | healthcare |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210134900 |
| authorships[3].institutions[0].country_code | DE |
| authorships[3].institutions[0].display_name | Jena University Hospital |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Caroline Tschernjawski |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Jena University Hospital, Functional Proteomics, Jena, Germany |
| authorships[4].author.id | https://openalex.org/A5022644839 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-2893-3630 |
| authorships[4].author.display_name | Sebastian Scholl |
| authorships[4].countries | DE |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210134900 |
| authorships[4].affiliations[0].raw_affiliation_string | Jena University Hospital, Klinik für Innere Medizin II, Jena, Germany |
| authorships[4].institutions[0].id | https://openalex.org/I4210134900 |
| authorships[4].institutions[0].ror | https://ror.org/035rzkx15 |
| authorships[4].institutions[0].type | healthcare |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210134900 |
| authorships[4].institutions[0].country_code | DE |
| authorships[4].institutions[0].display_name | Jena University Hospital |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Sebastian Scholl |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Jena University Hospital, Klinik für Innere Medizin II, Jena, Germany |
| authorships[5].author.id | https://openalex.org/A5035964802 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-0626-0834 |
| authorships[5].author.display_name | Andreas Hochhaus |
| authorships[5].countries | DE |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210134900 |
| authorships[5].affiliations[0].raw_affiliation_string | Jena University Hospital, Klinik für Innere Medizin II, Jena, Germany |
| authorships[5].institutions[0].id | https://openalex.org/I4210134900 |
| authorships[5].institutions[0].ror | https://ror.org/035rzkx15 |
| authorships[5].institutions[0].type | healthcare |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210134900 |
| authorships[5].institutions[0].country_code | DE |
| authorships[5].institutions[0].display_name | Jena University Hospital |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Andreas Hochhaus |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Jena University Hospital, Klinik für Innere Medizin II, Jena, Germany |
| authorships[6].author.id | https://openalex.org/A5092614032 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Florian Meier-Rosar |
| authorships[6].countries | DE |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I4210134900 |
| authorships[6].affiliations[0].raw_affiliation_string | Jena University Hospital, Functional Proteomics, Jena, Germany |
| authorships[6].institutions[0].id | https://openalex.org/I4210134900 |
| authorships[6].institutions[0].ror | https://ror.org/035rzkx15 |
| authorships[6].institutions[0].type | healthcare |
| authorships[6].institutions[0].lineage | https://openalex.org/I4210134900 |
| authorships[6].institutions[0].country_code | DE |
| authorships[6].institutions[0].display_name | Jena University Hospital |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Florian Meier-Rosar |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Jena University Hospital, Functional Proteomics, Jena, Germany |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1097/01.hs9.0000968804.83594.27 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | P474: FUNCTIONAL (PHOSPHO-)PROTEOMICS OF DRUG RESPONSE IN ACUTE MYELOID LEUKEMIA |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10519 |
| primary_topic.field.id | https://openalex.org/fields/16 |
| primary_topic.field.display_name | Chemistry |
| primary_topic.score | 0.9690999984741211 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1607 |
| primary_topic.subfield.display_name | Spectroscopy |
| primary_topic.display_name | Advanced Proteomics Techniques and Applications |
| related_works | https://openalex.org/W1982829397, https://openalex.org/W2106414650, https://openalex.org/W2347437365, https://openalex.org/W1999412725, https://openalex.org/W4390205769, https://openalex.org/W2124137418, https://openalex.org/W2159717395, https://openalex.org/W2391458050, https://openalex.org/W2086860678, https://openalex.org/W3022402204 |
| cited_by_count | 0 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1097/01.hs9.0000968804.83594.27 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210211592 |
| best_oa_location.source.issn | 2572-9241 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2572-9241 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | HemaSphere |
| best_oa_location.source.host_organization | https://openalex.org/P4310318547 |
| best_oa_location.source.host_organization_name | Wolters Kluwer |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310318547 |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | HemaSphere |
| best_oa_location.landing_page_url | https://doi.org/10.1097/01.hs9.0000968804.83594.27 |
| primary_location.id | doi:10.1097/01.hs9.0000968804.83594.27 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210211592 |
| primary_location.source.issn | 2572-9241 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2572-9241 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | HemaSphere |
| primary_location.source.host_organization | https://openalex.org/P4310318547 |
| primary_location.source.host_organization_name | Wolters Kluwer |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310318547 |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | HemaSphere |
| primary_location.landing_page_url | https://doi.org/10.1097/01.hs9.0000968804.83594.27 |
| publication_date | 2023-08-01 |
| publication_year | 2023 |
| referenced_works_count | 0 |
| abstract_inverted_index.R | 236 |
| abstract_inverted_index.a | 6, 18, 103, 129, 189, 315, 358, 398 |
| abstract_inverted_index.10 | 276 |
| abstract_inverted_index.96 | 141 |
| abstract_inverted_index.At | 64 |
| abstract_inverted_index.To | 184, 216 |
| abstract_inverted_index.We | 126, 242, 377, 393 |
| abstract_inverted_index.an | 34 |
| abstract_inverted_index.as | 364, 366 |
| abstract_inverted_index.at | 178 |
| abstract_inverted_index.by | 48 |
| abstract_inverted_index.et | 200 |
| abstract_inverted_index.in | 234, 259, 325 |
| abstract_inverted_index.is | 5, 397 |
| abstract_inverted_index.it | 419 |
| abstract_inverted_index.of | 59, 74, 80, 119, 144, 246, 256, 289, 310, 318, 340, 361, 369, 426 |
| abstract_inverted_index.on | 128, 188, 405 |
| abstract_inverted_index.or | 171, 237 |
| abstract_inverted_index.to | 16, 33, 55, 113, 122, 135, 250, 385, 401, 412 |
| abstract_inverted_index.we | 101, 192, 221, 270 |
| abstract_inverted_index.AML | 120, 312, 348 |
| abstract_inverted_index.For | 159, 343 |
| abstract_inverted_index.Our | 330 |
| abstract_inverted_index.The | 409 |
| abstract_inverted_index.aim | 54 |
| abstract_inverted_index.and | 40, 77, 109, 207, 224, 227, 254, 285, 304, 372, 382 |
| abstract_inverted_index.are | 45, 378 |
| abstract_inverted_index.for | 10, 423 |
| abstract_inverted_index.how | 89 |
| abstract_inverted_index.ion | 266 |
| abstract_inverted_index.its | 111 |
| abstract_inverted_index.new | 97 |
| abstract_inverted_index.one | 293 |
| abstract_inverted_index.our | 68, 194, 247 |
| abstract_inverted_index.the | 22, 57, 65, 71, 78, 81, 92, 115, 229, 235, 244, 337, 346, 353, 373, 388, 406, 424 |
| abstract_inverted_index.yet | 51 |
| abstract_inverted_index.µg | 277 |
| abstract_inverted_index.DMSO | 170 |
| abstract_inverted_index.IC50 | 179 |
| abstract_inverted_index.Such | 43 |
| abstract_inverted_index.This | 297 |
| abstract_inverted_index.U937 | 351 |
| abstract_inverted_index.al., | 201 |
| abstract_inverted_index.also | 420 |
| abstract_inverted_index.care | 13 |
| abstract_inverted_index.cell | 145, 164, 213, 331, 349 |
| abstract_inverted_index.drug | 123, 160, 218, 257, 307, 341, 403 |
| abstract_inverted_index.from | 30, 140, 155, 211, 275 |
| abstract_inverted_index.high | 23 |
| abstract_inverted_index.hour | 294 |
| abstract_inverted_index.into | 336 |
| abstract_inverted_index.line | 350 |
| abstract_inverted_index.mass | 105, 132, 268 |
| abstract_inverted_index.most | 52 |
| abstract_inverted_index.open | 96 |
| abstract_inverted_index.role | 79 |
| abstract_inverted_index.same | 66 |
| abstract_inverted_index.than | 62 |
| abstract_inverted_index.that | 204, 395 |
| abstract_inverted_index.very | 421 |
| abstract_inverted_index.well | 365 |
| abstract_inverted_index.were | 153, 166 |
| abstract_inverted_index.will | 95 |
| abstract_inverted_index.with | 168, 352, 414 |
| abstract_inverted_index.work | 413 |
| abstract_inverted_index.(AML) | 4 |
| abstract_inverted_index.(e.g. | 175 |
| abstract_inverted_index.2023) | 203 |
| abstract_inverted_index.Acute | 1, 433 |
| abstract_inverted_index.Aims: | 99 |
| abstract_inverted_index.Given | 21 |
| abstract_inverted_index.Here, | 100 |
| abstract_inverted_index.Using | 262 |
| abstract_inverted_index.about | 70 |
| abstract_inverted_index.alter | 56, 91 |
| abstract_inverted_index.blood | 150, 157 |
| abstract_inverted_index.build | 127 |
| abstract_inverted_index.cells | 121, 152, 313 |
| abstract_inverted_index.could | 27 |
| abstract_inverted_index.depth | 299 |
| abstract_inverted_index.drugs | 174 |
| abstract_inverted_index.fails | 15 |
| abstract_inverted_index.files | 232 |
| abstract_inverted_index.human | 163, 282, 347 |
| abstract_inverted_index.lines | 165 |
| abstract_inverted_index.makes | 418 |
| abstract_inverted_index.often | 14 |
| abstract_inverted_index.probe | 114 |
| abstract_inverted_index.reach | 17 |
| abstract_inverted_index.small | 415 |
| abstract_inverted_index.their | 326 |
| abstract_inverted_index.time, | 67 |
| abstract_inverted_index.time. | 296 |
| abstract_inverted_index.which | 11 |
| abstract_inverted_index.>7,000 | 290 |
| abstract_inverted_index.Python | 238 |
| abstract_inverted_index.TGF-β | 374 |
| abstract_inverted_index.Viable | 147 |
| abstract_inverted_index.cancer | 283 |
| abstract_inverted_index.cells) | 284 |
| abstract_inverted_index.covers | 301 |
| abstract_inverted_index.draws. | 158 |
| abstract_inverted_index.either | 169 |
| abstract_inverted_index.genes. | 63 |
| abstract_inverted_index.highly | 263 |
| abstract_inverted_index.level. | 408 |
| abstract_inverted_index.lines. | 146 |
| abstract_inverted_index.rather | 61 |
| abstract_inverted_index.result | 231 |
| abstract_inverted_index.sample | 209, 416 |
| abstract_inverted_index.scale, | 191 |
| abstract_inverted_index.showed | 357 |
| abstract_inverted_index.unique | 36, 273 |
| abstract_inverted_index.widely | 300 |
| abstract_inverted_index.within | 292 |
| abstract_inverted_index.µPhos | 197, 248, 396 |
| abstract_inverted_index.96-well | 212, 260 |
| abstract_inverted_index.>15,000 | 272 |
| abstract_inverted_index.Myeloid | 2 |
| abstract_inverted_index.amounts | 417 |
| abstract_inverted_index.applied | 193 |
| abstract_inverted_index.benefit | 29 |
| abstract_inverted_index.between | 320 |
| abstract_inverted_index.bioRxiv | 202 |
| abstract_inverted_index.complex | 389 |
| abstract_inverted_index.context | 83 |
| abstract_inverted_index.culture | 214, 332 |
| abstract_inverted_index.durable | 19 |
| abstract_inverted_index.dynamic | 116 |
| abstract_inverted_index.efforts | 44 |
| abstract_inverted_index.enables | 205 |
| abstract_inverted_index.format. | 261 |
| abstract_inverted_index.further | 386 |
| abstract_inverted_index.genetic | 75 |
| abstract_inverted_index.insight | 335 |
| abstract_inverted_index.myeloid | 434 |
| abstract_inverted_index.patient | 156, 428 |
| abstract_inverted_index.perform | 136, 251 |
| abstract_inverted_index.plates. | 215 |
| abstract_inverted_index.primary | 148, 311, 427 |
| abstract_inverted_index.protein | 186, 278 |
| abstract_inverted_index.remains | 84 |
| abstract_inverted_index.status. | 42, 329 |
| abstract_inverted_index.trapped | 265 |
| abstract_inverted_index.(Oliinyk | 199 |
| abstract_inverted_index.(~50,000 | 281 |
| abstract_inverted_index.Analysis | 309 |
| abstract_inverted_index.Leukemia | 3 |
| abstract_inverted_index.Methods: | 125 |
| abstract_inverted_index.Results: | 241 |
| abstract_inverted_index.activity | 58, 94, 328 |
| abstract_inverted_index.analyses | 139 |
| abstract_inverted_index.analysis | 295, 425 |
| abstract_inverted_index.analyzed | 228 |
| abstract_inverted_index.approach | 108 |
| abstract_inverted_index.cellular | 82, 302 |
| abstract_inverted_index.commonly | 172 |
| abstract_inverted_index.conclude | 394 |
| abstract_inverted_index.cultures | 143 |
| abstract_inverted_index.directly | 87 |
| abstract_inverted_index.example, | 344 |
| abstract_inverted_index.genomics | 49 |
| abstract_inverted_index.isolated | 154 |
| abstract_inverted_index.material | 280 |
| abstract_inverted_index.mobility | 267 |
| abstract_inverted_index.pathways | 303 |
| abstract_inverted_index.patients | 26 |
| abstract_inverted_index.physical | 41 |
| abstract_inverted_index.platform | 134, 249, 400 |
| abstract_inverted_index.powerful | 399 |
| abstract_inverted_index.profile, | 38 |
| abstract_inverted_index.profiles | 288 |
| abstract_inverted_index.proteins | 60, 291, 363 |
| abstract_inverted_index.proteome | 93, 138, 327 |
| abstract_inverted_index.protocol | 198 |
| abstract_inverted_index.provided | 334 |
| abstract_inverted_index.quantify | 185 |
| abstract_inverted_index.recently | 195 |
| abstract_inverted_index.relevant | 306 |
| abstract_inverted_index.response | 118, 161, 219, 258, 390, 404 |
| abstract_inverted_index.revealed | 314 |
| abstract_inverted_index.samples. | 429 |
| abstract_inverted_index.standard | 12, 182 |
| abstract_inverted_index.starting | 279 |
| abstract_inverted_index.tailored | 32 |
| abstract_inverted_index.targets. | 308 |
| abstract_inverted_index.Keywords: | 430 |
| abstract_inverted_index.assessing | 88 |
| abstract_inverted_index.available | 173 |
| abstract_inverted_index.chromatin | 370 |
| abstract_inverted_index.currently | 46, 379 |
| abstract_inverted_index.delineate | 217 |
| abstract_inverted_index.developed | 196 |
| abstract_inverted_index.diversity | 317 |
| abstract_inverted_index.elucidate | 402 |
| abstract_inverted_index.following | 181 |
| abstract_inverted_index.generated | 286 |
| abstract_inverted_index.increased | 367 |
| abstract_inverted_index.incubated | 167 |
| abstract_inverted_index.inhibitor | 355 |
| abstract_inverted_index.introduce | 102 |
| abstract_inverted_index.knowledge | 69 |
| abstract_inverted_index.leukemia, | 435 |
| abstract_inverted_index.molecular | 37, 117, 338 |
| abstract_inverted_index.patients, | 321 |
| abstract_inverted_index.performed | 222 |
| abstract_inverted_index.pioneered | 47 |
| abstract_inverted_index.potential | 323 |
| abstract_inverted_index.response. | 20, 342 |
| abstract_inverted_index.secretory | 362 |
| abstract_inverted_index.sensitive | 264 |
| abstract_inverted_index.signaling | 375 |
| abstract_inverted_index.therapies | 31 |
| abstract_inverted_index.Therefore, | 86 |
| abstract_inverted_index.analytical | 298 |
| abstract_inverted_index.attractive | 422 |
| abstract_inverted_index.background | 39 |
| abstract_inverted_index.bortezomib | 356 |
| abstract_inverted_index.capability | 411 |
| abstract_inverted_index.clinically | 305 |
| abstract_inverted_index.diversity, | 25 |
| abstract_inverted_index.frontiers. | 98 |
| abstract_inverted_index.functional | 72, 104, 252 |
| abstract_inverted_index.incubating | 345 |
| abstract_inverted_index.indicating | 322 |
| abstract_inverted_index.machinery. | 376 |
| abstract_inverted_index.performing | 380 |
| abstract_inverted_index.peripheral | 149 |
| abstract_inverted_index.processing | 210 |
| abstract_inverted_index.proteasome | 354 |
| abstract_inverted_index.proteomics | 230, 253 |
| abstract_inverted_index.protocols. | 183 |
| abstract_inverted_index.quantified | 271 |
| abstract_inverted_index.remarkable | 316 |
| abstract_inverted_index.remodelers | 371 |
| abstract_inverted_index.signatures | 339 |
| abstract_inverted_index.treatment. | 124 |
| abstract_inverted_index.well-plate | 142 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.Bortezomib, | 431 |
| abstract_inverted_index.Proteomics, | 432 |
| abstract_inverted_index.aberrations | 76 |
| abstract_inverted_index.application | 112, 245 |
| abstract_inverted_index.bortezomib, | 176 |
| abstract_inverted_index.deconvolute | 387 |
| abstract_inverted_index.demonstrate | 110, 243 |
| abstract_inverted_index.differences | 324 |
| abstract_inverted_index.experiments | 226, 333, 384 |
| abstract_inverted_index.incomplete. | 85 |
| abstract_inverted_index.malignancy, | 9 |
| abstract_inverted_index.mononuclear | 151 |
| abstract_inverted_index.multi-modal | 137 |
| abstract_inverted_index.potentially | 28 |
| abstract_inverted_index.programming | 239 |
| abstract_inverted_index.signatures, | 220 |
| abstract_inverted_index.signatures. | 391 |
| abstract_inverted_index.significant | 359 |
| abstract_inverted_index.time-course | 225, 381 |
| abstract_inverted_index.venetoclax) | 177 |
| abstract_inverted_index.consequences | 73 |
| abstract_inverted_index.demonstrated | 410 |
| abstract_inverted_index.experiments, | 162 |
| abstract_inverted_index.miniaturized | 208 |
| abstract_inverted_index.particularly | 7 |
| abstract_inverted_index.quantitative | 287 |
| abstract_inverted_index.spectrometry | 133 |
| abstract_inverted_index.therapeutics | 53, 90 |
| abstract_inverted_index.dose-response | 223, 383 |
| abstract_inverted_index.environments. | 240 |
| abstract_inverted_index.heterogeneous | 8 |
| abstract_inverted_index.proteome-wide | 190 |
| abstract_inverted_index.spectrometry, | 269 |
| abstract_inverted_index.statistically | 233 |
| abstract_inverted_index.technologies, | 50 |
| abstract_inverted_index.concentrations | 180 |
| abstract_inverted_index.individual’s | 35 |
| abstract_inverted_index.Phosphorylation | 436 |
| abstract_inverted_index.down-regulation | 360 |
| abstract_inverted_index.high-resolution | 131 |
| abstract_inverted_index.phosphopeptides | 274 |
| abstract_inverted_index.phosphoproteome | 407 |
| abstract_inverted_index.phosphorylation | 187, 368 |
| abstract_inverted_index.straightforward | 206 |
| abstract_inverted_index.inter-individual | 24 |
| abstract_inverted_index.phosphoproteomes | 319 |
| abstract_inverted_index.state-of-the-art | 130 |
| abstract_inverted_index.phosphoproteomics | 255 |
| abstract_inverted_index.spectrometry-based | 106 |
| abstract_inverted_index.Summary/Conclusion: | 392 |
| abstract_inverted_index.(phospho-)proteomics | 107 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.1408518 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |