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Article ; Online: Recent advances and opportunities in proteomic analyses of tumour heterogeneity.

Bateman, Nicholas W / Conrads, Thomas P

2018 Volume 244, Issue 5, Page(s) 628–637

Abstract: Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with ... ...

Abstract	Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
MeSH term(s)	Animals ; Biomarkers, Tumor/metabolism ; Diffusion of Innovation ; Forecasting ; Humans ; Laser Capture Microdissection ; Mass Spectrometry ; Neoplasms/metabolism ; Neoplasms/pathology ; Pre-Analytical Phase ; Predictive Value of Tests ; Proteomics/methods ; Proteomics/trends ; Single-Cell Analysis ; Tumor Microenvironment
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2018-02-14
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Review
ZDB-ID	3119-7
ISSN	1096-9896 ; 0022-3417
ISSN (online)	1096-9896
ISSN	0022-3417
DOI	10.1002/path.5036
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Article ; Online: ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data.

iScience

2024 Volume 27, Issue 3, Page(s) 109198

Abstract: Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and ... ...

Abstract	Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or Consensus
Language	English
Publishing date	2024-02-12
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2024.109198
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Article ; Online: Brain proteomic atlas of alcohol use disorder in adult males.

Teng, Pang-Ning / Barakat, Waleed / Tran, Sophie M / Tran, Zoe M / Bateman, Nicholas W / Conrads, Kelly A / Wilson, Katlin N / Oliver, Julie / Gist, Glenn / Hood, Brian L / Zhou, Ming / Maxwell, G Larry / Leggio, Lorenzo / Conrads, Thomas P / Lee, Mary R

Translational psychiatry

2023 Volume 13, Issue 1, Page(s) 318

Abstract: ... expressed proteins between groups (fold change > 1.5 and LIMMA p < 0.01) were analyzed by Ingenuity Pathway ...

Abstract	Alcohol use disorder (AUD) affects transcriptomic, epigenetic and proteomic expression in several organs, including the brain. There has not been a comprehensive analysis of altered protein abundance focusing on the multiple brain regions that undergo neuroadaptations occurring in AUD. We performed a quantitative proteomic analysis using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of human postmortem tissue from brain regions that play key roles in the development and maintenance of AUD, the amygdala (AMG), hippocampus (HIPP), hypothalamus (HYP), nucleus accumbens (NAc), prefrontal cortex (PFC) and ventral tegmental area (VTA). Brain tissues were from adult males with AUD (n = 11) and matched controls (n = 16). Across the two groups, there were >6000 proteins quantified with differential protein abundance in AUD compared to controls in each of the six brain regions. The region with the greatest number of differentially expressed proteins was the AMG, followed by the HYP. Pathways associated with differentially expressed proteins between groups (fold change > 1.5 and LIMMA p < 0.01) were analyzed by Ingenuity Pathway Analysis (IPA). In the AMG, adrenergic, opioid, oxytocin, GABA receptor and cytokine pathways were among the most enriched. In the HYP, dopaminergic signaling pathways were the most enriched. Proteins with differential abundance in AUD highlight potential therapeutic targets such as oxytocin, CSNK1D (PF-670462), GABA
MeSH term(s)	Male ; Adult ; Humans ; Alcoholism/metabolism ; Oxytocin ; Proteomics ; Chromatography, Liquid ; Tandem Mass Spectrometry ; Brain/metabolism ; Proteins
Chemical Substances	Oxytocin (50-56-6) ; Proteins
Language	English
Publishing date	2023-10-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	2609311-X
ISSN	2158-3188 ; 2158-3188
ISSN (online)	2158-3188
ISSN	2158-3188
DOI	10.1038/s41398-023-02605-0
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Article ; Online: Author Correction: Automated imaging and identification of proteoforms directly from ovarian cancer tissue.

McGee, John P / Su, Pei / Durbin, Kenneth R / Hollas, Michael A R / Bateman, Nicholas W / Maxwell, G Larry / Conrads, Thomas P / Fellers, Ryan T / Melani, Rafael D / Camarillo, Jeannie M / Kafader, Jared O / Kelleher, Neil L

Nature communications

2023 Volume 14, Issue 1, Page(s) 7946

Language	English
Publishing date	2023-12-01
Publishing country	England
Document type	Published Erratum
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-43898-5
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Article ; Online: CARD19 Interacts with Mitochondrial Contact Site and Cristae Organizing System Constituent Proteins and Regulates Cristae Morphology.

Rios, Kariana E / Zhou, Ming / Lott, Nathaniel M / Beauregard, Chelsi R / McDaniel, Dennis P / Conrads, Thomas P / Schaefer, Brian C

Cells

2022 Volume 11, Issue 7

Abstract: CARD19 is a mitochondrial protein of unknown function. While CARD19 was originally reported to regulate TCR-dependent NF-κB activation via interaction with BCL10, this function is not recapitulated ex vivo in primary murine ... ...

Abstract	CARD19 is a mitochondrial protein of unknown function. While CARD19 was originally reported to regulate TCR-dependent NF-κB activation via interaction with BCL10, this function is not recapitulated ex vivo in primary murine CD8
MeSH term(s)	Animals ; CARD Signaling Adaptor Proteins/metabolism ; CD8-Positive T-Lymphocytes/metabolism ; Gene Expression Regulation ; Mice ; Mitochondria/metabolism ; Mitochondrial Membranes/metabolism ; Mitochondrial Proteins/metabolism
Chemical Substances	CARD Signaling Adaptor Proteins ; Mitochondrial Proteins
Language	English
Publishing date	2022-03-31
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2661518-6
ISSN	2073-4409 ; 2073-4409
ISSN (online)	2073-4409
ISSN	2073-4409
DOI	10.3390/cells11071175
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Article: The Obama Administration's Cancer Moonshot: A Call for Proteomics.

Conrads, Thomas P / Petricoin, Emanuel F

Clinical cancer research : an official journal of the American Association for Cancer Research

2016 Volume 22, Issue 18, Page(s) 4556–4558

Abstract: The Cancer Moonshot Program has been launched and represents a potentially paradigm-shifting initiative with the goal to implement a focused national effort to double the rate of progress against cancer. The placement of precision medicine, immunotherapy, ...

Abstract	The Cancer Moonshot Program has been launched and represents a potentially paradigm-shifting initiative with the goal to implement a focused national effort to double the rate of progress against cancer. The placement of precision medicine, immunotherapy, genomics, and combination therapies was placed at the central nexus of this initiative. Although we are extremely enthusiastic about the goals of the program, it is time we meet this revolutionary project with equally bold and cutting-edge ideas: it is time we move firmly into the postgenome era and provide the necessary resources to propel and seize on innovative recent gains in the field of proteomics required for it to stand on equal footing in this narrative as a combined, synergistic engine for molecular profiling. After all, although the genome is the information archive, it is the proteins that actually do the work of the cell and represent the structural cellular machinery. It is the proteins that comprise most of the biomarkers that are measured to detect cancers, constitute the antigens that drive immune response and inter- and intracellular communications, and it is the proteins that are the drug targets for nearly every targeted therapy that is being evaluated in cancer trials today. We believe that a combined systems biology view of the tumor microenvironment that orients cancer studies back to the functional proteome, phosphoproteome, and biochemistry of the cell will be essential to deliver on the promise of the Cancer Moonshot Program. Clin Cancer Res; 22(18); 4556-8. ©2016 AACR.
Language	English
Publishing date	2016-09-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	1225457-5
ISSN	1557-3265 ; 1078-0432
ISSN (online)	1557-3265
ISSN	1078-0432
DOI	10.1158/1078-0432.CCR-16-0688
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Article ; Online: Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment.

Mitchell, Dave / Hunt, Allison L / Conrads, Kelly A / Hood, Brian L / Makohon-Moore, Sasha C / Rojas, Christine / Maxwell, G Larry / Bateman, Nicholas W / Conrads, Thomas P

Journal of visualized experiments : JoVE

2022 , Issue 184

Abstract: The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell populations. To characterize proteome-level variation and tumor heterogeneity at scale, high-throughput ... ...

Abstract	The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell populations. To characterize proteome-level variation and tumor heterogeneity at scale, high-throughput methods are needed to selectively isolate discrete cellular populations in solid tumor malignancies. This protocol describes a high-throughput workflow, enabled by artificial intelligence (AI), that segments images of hematoxylin and eosin (H&E)-stained, thin tissue sections into pathology-confirmed regions of interest for selective harvest of histology-resolved cell populations using laser microdissection (LMD). This strategy includes a novel algorithm enabling the transfer of regions denoting cell populations of interest, annotated using digital image software, directly to laser microscopes, thus enabling more facile collections. Successful implementation of this workflow was performed, demonstrating the utility of this harmonized method to selectively harvest tumor cell populations from the TME for quantitative, multiplexed proteomic analysis by high-resolution mass spectrometry. This strategy fully integrates with routine histopathology review, leveraging digital image analysis to support enrichment of cellular populations of interest and is fully generalizable, enabling harmonized harvests of cell populations from the TME for multiomic analyses.
MeSH term(s)	Artificial Intelligence ; Ecosystem ; Humans ; Laser Capture Microdissection/methods ; Lasers ; Neoplasms/metabolism ; Proteomics/methods ; Tumor Microenvironment
Language	English
Publishing date	2022-06-03
Publishing country	United States
Document type	Journal Article ; Video-Audio Media ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2259946-0
ISSN	1940-087X ; 1940-087X
ISSN (online)	1940-087X
ISSN	1940-087X
DOI	10.3791/64171
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Article ; Online: Automated imaging and identification of proteoforms directly from ovarian cancer tissue.

Nature communications

2023 Volume 14, Issue 1, Page(s) 6478

Abstract: The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS ( ... ...

Abstract	The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS
MeSH term(s)	Humans ; Female ; Proteome/analysis ; Ovarian Neoplasms/diagnostic imaging ; Tandem Mass Spectrometry/methods ; Software ; Tumor Microenvironment
Chemical Substances	Proteome
Language	English
Publishing date	2023-10-14
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-42208-3
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Article: Quantitative proteomic analysis of HER2 protein expression in PDAC tumors.

Randall, Jamie / Hunt, Allison L / Nutcharoen, Aratara / Johnston, Laura / Chouraichi, Safae / Wang, Hongkun / Winer, Arthur / Wadlow, Raymond / Huynh, Jasmine / Davis, Justin / Corgiat, Brian / Bateman, Nicholas W / Deeken, John F / Petricoin, Emanuel F / Conrads, Thomas P / Cannon, Timothy L

Clinical proteomics

2024 Volume 21, Issue 1, Page(s) 24

Abstract: Metastatic pancreatic adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States, with a 5-year survival rate of only 11%, necessitating identification of novel treatment paradigms. Tumor tissue specimens from patients ... ...

Abstract	Metastatic pancreatic adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States, with a 5-year survival rate of only 11%, necessitating identification of novel treatment paradigms. Tumor tissue specimens from patients with PDAC, breast cancer, and other solid tumor malignancies were collected and tumor cells were enriched using laser microdissection (LMD). Reverse phase protein array (RPPA) analysis was performed on enriched tumor cell lysates to quantify a 32-protein/phosphoprotein biomarker panel comprising known anticancer drug targets and/or cancer-related total and phosphorylated proteins, including HER2
Language	English
Publishing date	2024-03-20
Publishing country	England
Document type	Letter
ZDB-ID	2205154-5
ISSN	1542-6416
ISSN	1542-6416
DOI	10.1186/s12014-024-09476-7
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Article: Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling.

Hunt, Allison L / Bateman, Nicholas W / Barakat, Waleed / Makohon-Moore, Sasha C / Abulez, Tamara / Driscoll, Jordan A / Schaaf, Joshua P / Hood, Brian L / Conrads, Kelly A / Zhou, Ming / Calvert, Valerie / Pierobon, Mariaelena / Loffredo, Jeremy / Wilson, Katlin N / Litzi, Tracy J / Teng, Pang-Ning / Oliver, Julie / Mitchell, Dave / Gist, Glenn /

Rojas, Christine / Blanton, Brian / Darcy, Kathleen M / Rao, Uma N M / Petricoin, Emanuel F / Phippen, Neil T / Maxwell, G Larry / Conrads, Thomas P

Clinical proteomics

2024 Volume 21, Issue 1, Page(s) 4

Abstract: Background: Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in ... ...

Abstract	Background: Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics. Methods: Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor. Results: LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ). Conclusions: Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.
Language	English
Publishing date	2024-01-22
Publishing country	England
Document type	Journal Article
ZDB-ID	2205154-5
ISSN	1542-6416
ISSN	1542-6416
DOI	10.1186/s12014-024-09451-2
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