Data‐Independent Acquisition‐Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer

Song, Yimeng; Zhong, Liang; Zhou, Juntuo; Lu, Min; Xing, Tianying; Ma, Lulin; Shen, Jing

doi:10.1002/prca.201700066

Cited by 39 publications

(40 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, significant advances have been made in MS‐based proteomics, from sample preparation to liquid chromatography and instrumentation, making the identification of more expressed proteins in cells or tissues possible with good accuracy and reproducibility . Data‐independent acquisition (DIA) has been widely employed in proteomics analysis because of enhanced protein coverage and reliable data acquisition . The present study constructed dynamic network profiles in macrophages treated with LPS for different times using a DIA‐based quantitative proteomics strategy.…”

Section: Introductionmentioning

confidence: 99%

Data‐Independent Acquisition‐Based Quantitative Proteomics Analysis Reveals Dynamic Network Profiles during the Macrophage Inflammatory Response

Chen

et al. 2020

Proteomics

View full text Add to dashboard Cite

Understanding of the molecular regulatory mechanisms underlying the inflammatory response is incomplete. The present study focuses on characterizing the proteome in a model of inflammation in macrophages treated with lipopolysaccharide (LPS). A total of 3597 proteins are identified in macrophages with the data-independent acquisition (DIA) method. Bioinformatic analyses reveal discrete modules and the underlying molecular mechanisms, as well as the signaling network that modulates the development of inflammation. It is found that a total of 87 differentially expressed proteins are shared by all stages of LPS-induced inflammation in macrophages and that 18 of these proteins participate in metabolic processes by forming a tight interaction network. Data support the hypothesis that ribosome proteins play a key role in regulating the macrophage response to LPS. Interestingly, conjoint analyses of the transcriptome and proteome in macrophages treated with LPS reveal that the genes upregulated at both the mRNA and protein levels are mainly involved in inflammation and the immune response, whereas the genes downregulated are significantly enriched in metabolism-related processes. These results not only provide a more comprehensive understanding of the molecular mechanisms of inflammation mediated by bacterial infection but also provide a dynamic proteomic resource for further studies.

show abstract

Section: Introductionmentioning

confidence: 99%

Data‐Independent Acquisition‐Based Quantitative Proteomics Analysis Reveals Dynamic Network Profiles during the Macrophage Inflammatory Response

Chen

et al. 2020

Proteomics

View full text Add to dashboard Cite

show abstract

“…LC-MS/MS has become the preferred method for measuring DNA adducts due to the high selectivity obtained in comparison to, e.g., 32 P-post-labeling technique [27][28][29] . Moreover, recent advances in MS instrumentation providing HRAM data have resulted in gaining more information on the chemical structure of the adduct based on its fragmentation pattern and more accurate elemental composition determination 12,30 .…”

Section: Discussionmentioning

confidence: 99%

“…We employed HRMS in DIA mode that permitted stepwise acquisition for the detection of adducts and is useful for its archival nature as samples that have been analyzed earlier can be re-examined for new adducts. Even with the fragmentation data being limited to MS/MS, DIA approach has made significant progress in proteomics 31,32 and metabolomics 33,34 . Development of bioinformatics tools related to adduct analysis would further enhance the use of this method in adductomics.…”

Section: Discussionmentioning

confidence: 99%

DNA epigenetic marks are linked to reproductive aberrations in amphipods

Gorokhova

Martella

et al. 2019

Preprint

View full text Add to dashboard Cite

Linking exposure to environmental contaminants with diseases is crucial for proposing preventive and regulatory actions. Upon exposure to anthropogenic chemicals, covalent modifications on the genome can drive developmental and reproductive disorders in wild populations, with subsequent effects on the population persistence. Hence, screening of chemical modifications on DNA can be used to provide information on the probability of such disorders in populations of concern. Using a high-resolution mass spectrometry methodology, we identified DNA nucleoside adducts in gravid females of the Baltic amphipods Monoporeia affinis, and linked the adduct profiles to the frequency of embryo malformations in the broods. Twenty-three putative nucleoside adducts were detected in the females and their embryos, and eight modifications were structurally identified using highresolution accurate mass data. To identify which adducts were significantly associated with embryo malformations, partial least squares regression (PLSR) modelling was applied. The PLSR model yielded three adducts as the key predictors: methylation at two different positions of the DNA (5methyl-2'-deoxycytidine and N 6 -methyl-2'-deoxyadenosine) representing epigenetic marks, and a structurally unidentified nucleoside adduct. These adducts predicted the elevated frequency of the malformations with a high classification accuracy (84%). To the best of our knowledge, this is the first application of DNA adductomics for identification of contaminant-induced malformations in field-collected animals. The method can be adapted for a broad range of species and evolve as a new omics tool in environmental health assessment.

show abstract

“…Furthermore, HIF2a hyperactivity in ccRCC cells can promote the expression of the lipid droplet-associated protein perilipin 2 (PLIN2), which facilitates lipid storage and indirectly blunts endoplasmic reticulum (ER) stress pathways (4). It is interesting to note that PLIN2 has been identified as a potential urinary biomarker of advance ccRCC (48,49), providing additional rationale to develop therapeutic strategies to intervene on this HIF2a-PLIN2 pathway. Collectively, all of these recently described lipid metabolic pathways altered in ccRCC provide potential targets for drug discovery.…”

Section: Discussionmentioning

confidence: 99%

MBOAT7-Driven Phosphatidylinositol Remodeling Promotes the Progression of Clear Cell Renal Carcinoma

Neumann

Zhang

Silver

et al. 2019

Preprint

View full text Add to dashboard Cite

The most common kidney cancer, clear cell Renal Cell Carcinoma (ccRCC) is closely associated with obesity. In fact, the "clear cell" variant of RCC is given this name due to large lipid droplets within the tumor cells. Although it is well appreciated that renal lipid metabolism is altered in ccRCC, the mechanisms driving this are not well understood. Leveraging a shotgun lipidomics approach we have identified a lipid signature for ccRCC that includes an increase in arachidonic acid-enriched phosphatidylinositols (AA-PI). In parallel, we found that ccRCC tumors have increased expression of the acyltransferase enzyme membrane bound O-acyltransferase domain containing 7 (MBOAT7) that contributes to AA-PI synthesis. In ccRCC patients, MBOAT7 expression increases with tumor grade, and increased MBOAT7 expression correlates with poor survival. Genetic deletion of MBOAT7 in ccRCC cells decreases proliferation and induces cell cycle arrest, and MBOAT7 -/cells fail to form tumors in vivo. RNAseq of MBOAT7 -/cells identified alterations in cell migration and extracellular matrix organization, which were functionally validated in migration assays. Our work highlights the accumulation of AA-PI in ccRCC and demonstrate a novel way to decrease the AA-PI pool in ccRCC by limiting MBOAT7. Our data reveal that metastatic ccRCC is associated with altered AA-PI metabolism, and identify MBOAT7 as a novel target in advanced ccRCC.

show abstract

Data‐Independent Acquisition‐Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer

Abstract: The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis.

Cited by 39 publications

References 41 publications

Data‐Independent Acquisition‐Based Quantitative Proteomics Analysis Reveals Dynamic Network Profiles during the Macrophage Inflammatory Response

Data‐Independent Acquisition‐Based Quantitative Proteomics Analysis Reveals Dynamic Network Profiles during the Macrophage Inflammatory Response

DNA epigenetic marks are linked to reproductive aberrations in amphipods

MBOAT7-Driven Phosphatidylinositol Remodeling Promotes the Progression of Clear Cell Renal Carcinoma

Contact Info

Product

Resources

About