Proteomics

Dataset Information

0

Characterizing the secretome of EGFR mutant lung adenocarcinoma


ABSTRACT: Lung cancer is the leading cause of cancer related death worldwide, mainly due to the late stage of disease at the time of diagnosis. Non-invasive biomarkers are needed to supplement existing screening methods to enable earlier detection and increased patient survival. This is critical to EGFR-driven lung adenocarcinoma as it commonly occurs in individuals who have never smoked and do not qualify for current screening protocols. Methods: In this study, we performed mass spectrometry analysis of the secretome of cultured lung cells representing different stages of mutant EGFR driven transformation, from normal to fully malignant. Identified secreted proteins specific to the malignant state were validated using orthogonal methods and their clinical activity assessed in lung adenocarcinoma patient cohorts. Results: We quantified 1020 secreted proteins, which were compared for differential expression between stages of transformation. We validated differentially expressed proteins at the transcriptional level in clinical tumor specimens, association with patient survival, and absolute concentration to yield three biomarker candidates: MDK, GDF15, and SPINT2. These candidates were validated using ELISA and increased levels were associated with poor patient survival specifically in EGFR mutant lung adenocarcinoma patients. Conclusions: Our study provides insight into changes in secreted proteins during EGFR driven lung adenocarcinoma transformation that may play a role in the processes that promote tumor progression. The specific candidates identified can harnessed for biomarker use to identify high risk individuals for early detection screening programs and disease management for this molecular subgroup of lung adenocarcinoma patients.

INSTRUMENT(S): Orbitrap Eclipse

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung Adenocarcinoma Cell Line

SUBMITTER: Gian Luca Negri  

LAB HEAD: Gregg Morin

PROVIDER: PXD045328 | Pride | 2024-01-03

REPOSITORIES: Pride

Dataset's files

Source:

Similar Datasets

2023-07-12 | GSE237072 | GEO
2023-07-12 | GSE237071 | GEO
2024-09-02 | BIOMD0000000827 | BioModels
2022-04-04 | GSE101399 | GEO
2024-06-20 | GSE269746 | GEO
2024-10-30 | GSE274293 | GEO
2014-03-10 | E-GEOD-48414 | biostudies-arrayexpress
2015-02-03 | E-GEOD-65420 | biostudies-arrayexpress
2015-11-01 | E-GEOD-70046 | biostudies-arrayexpress
2022-12-21 | GSE198672 | GEO