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Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...

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Related Experiment Video

Updated: Jun 25, 2026

Two-dimensional Gel Electrophoresis Coupled with Mass Spectrometry Methods for an Analysis of Human Pituitary Adenoma Tissue Proteome
12:34

Two-dimensional Gel Electrophoresis Coupled with Mass Spectrometry Methods for an Analysis of Human Pituitary Adenoma Tissue Proteome

Published on: April 2, 2018

Exploring epigenome-proteome interactions underlying post-surgical progression of non-functioning pituitary adenomas

Medha Suman1,2, Tobias Hallén3,4, Terence Garner5

  • 1Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, SU Sahlgrenska, Göteborg, 41345, Sweden. medha.suman@gu.se.

Journal of Translational Medicine
|June 24, 2026
PubMed
Summary
This summary is machine-generated.

This study reveals distinct epigenetic and protein network differences between progressive and indolent non-functioning pituitary adenomas (NFPAs). These findings offer a new framework for identifying markers to predict tumor progression risk.

Keywords:
DNA methylationHypernetworkNon-functioning pituitary adenomaProtein expressionTumor progression

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Related Experiment Videos

Last Updated: Jun 25, 2026

Two-dimensional Gel Electrophoresis Coupled with Mass Spectrometry Methods for an Analysis of Human Pituitary Adenoma Tissue Proteome
12:34

Two-dimensional Gel Electrophoresis Coupled with Mass Spectrometry Methods for an Analysis of Human Pituitary Adenoma Tissue Proteome

Published on: April 2, 2018

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Area of Science:

  • Endocrinology
  • Molecular Biology
  • Genomics

Background:

  • Non-functioning pituitary adenomas (NFPAs) pose clinical challenges due to invasive growth and frequent post-surgical progression.
  • Understanding the molecular drivers of NFPA progression is crucial for risk stratification and treatment.
  • Current methods lack reliability in predicting tumor recurrence after surgery.

Purpose of the Study:

  • To comprehensively characterize molecular alterations and their interactions in progressive versus indolent NFPAs.
  • To identify biological processes driving post-surgical tumor progression.
  • To uncover potential network-informed candidate markers for NFPA progression.

Main Methods:

  • Integrated analysis of genome-wide DNA methylation and proteomics in 25 progressive and 15 indolent NFPAs.
  • Utilized hypernetwork modeling to link CpG sites with differentially expressed proteins.
  • Investigated cis-regulatory relationships to assess DNA methylation's direct impact on protein expression.

Main Results:

  • Hypernetwork analysis revealed distinct epigenetic-proteomic networks in progressive and indolent NFPAs.
  • Progressive NFPAs showed interconnected networks involving DNA replication, transcription, and cytoskeleton organization (e.g., MCM6, HDGFL2, AJM1, SYNE2).
  • Indolent NFPAs exhibited broader networks related to protein processing, extracellular matrix, and oxidative stress response (e.g., PSMD6, LAMB2, CISD2).

Conclusions:

  • Distinct epigenetic-proteomic regulatory mechanisms underlie NFPA tumor behavior.
  • Hypernetwork analysis provides insights beyond direct regulation, identifying key network alterations.
  • This integrative approach offers a framework for discovering mechanistically relevant markers for tumor progression.