Dataset Information

Analysis of ECM-enriched samples using different methods

ABSTRACT: Using LC-MS/MS, we analyzed ECM-enriched samples obtained from 1) human triple-negative breast cancer samples and matched adjacent normal mammary gland tissues, and 2) disease-free omentum from patient with non-metastatic ovarian cancer and high-grade- serous-ovarian- cancer-derived omental metastasis samples. We conducted the LC-MS/MS analysis on peptides obtained after solubilizing ECM-enriched samples using different methods (crude ECM extract, urea-soluble extract, urea-insoluble extract) and submitted to basic-reversed- phase separation or not.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Mammary Gland, Epithelial Ovarian Cancer Cell

DISEASE(S): Ovarian Cancer,Breast Cancer

SUBMITTER: Amanda Del Rosario

LAB HEAD: Amanda Del Rosario

PROVIDER: PXD005554 | Pride | 2017-07-11

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	150324_121_AN_G42_C1_2h.mgf	Mgf
	150324_121_AN_G42_C1_2h.mzid.gz	Mzid
	150324_121_AN_G42_C1_2h.pride.mgf.gz	Mgf
	150324_121_AN_G42_C1_2h.pride.mztab.gz	Mztab
	150324_121_AN_G42_C1_2h.raw	Raw

Items per page:

1 - 5 of 709

Publications

Characterization of the Extracellular Matrix of Normal and Diseased Tissues Using Proteomics.

Naba Alexandra A Pearce Oliver M T OMT Del Rosario Amanda A Ma Duanduan D Ding Huiming H Rajeeve Vinothini V Cutillas Pedro R PR Balkwill Frances R FR Hynes Richard O RO

Journal of proteome research 20170719 8

The extracellular matrix (ECM) is a complex meshwork of insoluble fibrillar proteins and signaling factors interacting together to provide architectural and instructional cues to the surrounding cells. Alterations in ECM organization or composition and excessive ECM deposition have been observed in diseases such as fibrosis, cardiovascular diseases, and cancer. We provide here optimized protocols to solubilize ECM proteins from normal or tumor tissues, digest the proteins into peptides, analyze ...[more]

PMID: 28675934

Similar Datasets

Project description:Our modern era is witnessing an increasing infertility rate worldwide. Although some of the causes can be attributed to our modern lifestyle (eg. persistent organic polluants, late pregnancy), our knowledge of the human ovarian tissue has remained limited and insufficient to reverse the infertility statistics. Indeed, all efforts have been focused on the endocrine and cellular function in support of the cell theory that dates back to the 18th century, while the human ovarian matrisome is still under-described. Therefore, hereby we provide the first systematic study focusing on the human ovarian matrisome and its remodeling during a woman lifetime, from prepuberty til menopause. We apply our matrisome tailored fractionation method, the DC-MaP strategy and mass spectrometry-based quantitative proteomics using TMT pro 16-plex isobaric labeling to delineate proteome-wide and ECM-specific shifts between prepubertal, reproductive-age and menopausal stages. Post-translational modifications, namely proline hydroxylation and advanced glycation ends products have also been detected at different intensities according to age. Matrisome age-biomarkers have been validated with lightsheet microscopy-based-3D imaging, following immunofluorescence and tissue clearing with an ovary-tailored protocol. We used machine learning and statistics to build a neural network that can predict predict the probability of a specific ovarian tissue matrisome to resemble to prepubertal, reproductive-age or menopausal tissue and potentially conclude its fertility potency or evaluate in the future the efficiency of ovarian rejuvenation treatments. We also used NLP medscan technology for advanced literature text-mining to predict all possible-connections between the extra- and intra-cellular compartments and how chemo-radiotherapy, known for its gonadotoxicity can also affect key matrisome proteins.This comprehensive proteomics analysis represents the ovarian proteomic codex and contributes to an improved understanding of the critical roles that ECM plays throughout ovarian life span. By publishing our proteomic data, we hope to open new avenues in fertility restoration, ovarian rejuvenation and reproductive tissue engineering