Related Experiment Video

Updated: Feb 9, 2026

Heterotypic Three-dimensional In Vitro Modeling of Stromal-Epithelial Interactions During Ovarian Cancer Initiation and Progression
12:42

Heterotypic Three-dimensional In Vitro Modeling of Stromal-Epithelial Interactions During Ovarian Cancer Initiation and Progression

Published on: August 28, 2012

15.7K

Systematic Identification of Druggable Epithelial-Stromal Crosstalk Signaling Networks in Ovarian Cancer

Tsz-Lun Yeung1, Jianting Sheng2,3, Cecilia S Leung1

  • 1Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX.

Journal of the National Cancer Institute
|June 4, 2018
PubMed
Abstract

Insights

This study used microdissected transcriptomes to identify ovarian cancer-stroma crosstalk networks. Repurposing calcitriol to target cancer-associated fibroblast Smad signaling improved survival in mice, suggesting new treatment strategies.

Area of Science:

  • Oncology
  • Systems Biology
  • Cancer Research

Background:

  • Bulk tumor tissue analysis hinders deciphering of stroma-cancer crosstalk networks.
  • Microdissected transcriptome profiling offers a novel approach to identify prognostic cancer-stroma interactions.
  • This method presents opportunities for developing new ovarian cancer treatment strategies.

Purpose of the Study:

  • To identify cancer-stroma crosstalk networks with prognostic value in ovarian cancer using microdissected transcriptome profiles.
  • To discover new therapeutic indications for existing drugs by analyzing these crosstalk networks.
  • To investigate the potential of targeting cancer-associated fibroblast (CAF) signaling pathways.

Main Methods:

  • Generated transcriptome profiles from microdissected ovarian cancer cells and CAFs from 70 high-grade serous ovarian cancer patients.
  • Utilized the CCCExplorer computational systems biology program to uncover crosstalk networks within the tumor microenvironment.
  • Performed survival analysis in mice treated with calcitriol, targeting Smad signaling, versus a vehicle control.

Main Results:

  • Identified activated TGF-β-dependent and -independent Smad signaling in a CAF subtype, associated with significantly poorer patient survival (15 vs. 26 months median overall survival).
  • Demonstrated that calcitriol effectively suppressed Smad signaling in CAFs.
  • Showed that calcitriol treatment inhibited tumor progression and prolonged median survival in mice from 36 to 48 weeks.

Conclusions:

  • Multicellular systems biology modeling can effectively identify drug targets within cancer-stroma crosstalk networks.
  • Repurposing known drugs, like calcitriol, targeting these networks offers a feasible strategy for cancer treatment.
  • This approach holds promise for accelerating the development of more effective cancer cures.

More Related Videos

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer09:08

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Published on: January 12, 2020

7.2K
Preparation of Mitochondria from Ovarian Cancer Tissues and Control Ovarian Tissues for Quantitative Proteomics Analysis11:51

Preparation of Mitochondria from Ovarian Cancer Tissues and Control Ovarian Tissues for Quantitative Proteomics Analysis

Published on: November 18, 2019

6.3K

Related Concept Videos

mTOR Signaling and Cancer Progression03:03

mTOR Signaling and Cancer Progression

The mammalian target of rapamycin or mTOR protein was discovered in 1994 due to its direct interaction with rapamycin. The protein gets its name from a yeast homolog called TOR. The mTOR protein complex in mammalian cells plays a major role in balancing anabolic processes such as the synthesis of proteins, lipids, and nucleotides and catabolic processes, such as autophagy in response to environmental cues, such as availability of nutrients and growth factors.
The mTOR pathway or the...
4.9K
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,...
4.6K
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
15.2K
Systematic Sampling Method01:17

Systematic Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
13.4K
Network Covalent Solids02:18

Network Covalent Solids

Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.5K