Proteomics

Dataset Information

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Characterization of intact proteomic profile of senescent-associated secretory phenotype (SASP) by top-down mass spectrometry.


ABSTRACT: Senescent cells are increasingly recognized as major contributors to age-related diseases, primarily through the secretion of bioactive molecules known as the senescence-associated secretory phenotype (SASP). The SASP plays a crucial role in promoting various age-related conditions, including neurodegeneration and type-2 diabetes. While bottom-up proteomic profiling has been instrumental in elucidating senescence heterogeneity and linking SASP factors to aging and obesity, the complexity of protein modifications in SASP remains underexplored. Notably, proteoform-level analysis has not yet been applied to study SASP profiles in detail. In this study, we employ top-down proteomics to capture proteoform diversity in the secretomes of senescent and healthy lung fibroblasts (IMR90).

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture, Fibroblast

SUBMITTER: Mozhgan Boroumand  

LAB HEAD: Nathan Bassity

PROVIDER: PXD061829 | Pride | 2025-12-29

REPOSITORIES: Pride

Dataset's files

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Figures.pptx Other
Meta_data.xlsx Xlsx
NonSEN1_500ng.raw Raw
NonSEN1_500ng_ms2_toppic_proteoform_single.tsv Tabular
NonSEN2_500ng.raw Raw
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Publications

Characterization of the Intact Proteomic Profile of Senescent-Associated Secretory Phenotype by Top-Down Mass Spectrometry.

Boroumand Mozhgan M   Dey Amit A   Cupp-Sutton Kellye K   Pierce Tomas T   Tsitsipatis Dimitrios D   Herman Allison B AB   Wu Si S   Basisty Nathan N  

Analytical chemistry 20251014 47


Cellular senescence is a stable state of cell-cycle arrest characterized by extensive remodeling of the secretome, known as the senescence-associated secretory phenotype (SASP). The SASP profoundly influences tissue microenvironments and contributes to chronic inflammation and age-related diseases. While previous studies have characterized the SASP using bottom-up proteomics, intact proteoforms' diversity and structural complexity remain poorly understood. In this study, we apply quantitative to  ...[more]

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