Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

MicroRNAs01:22

MicroRNAs

3.1K
MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
3.1K
Induced Pluripotent Stem Cells01:06

Induced Pluripotent Stem Cells

4.4K
Stem cells are undifferentiated cells that divide and produce different cell types. Ordinarily, cells that have differentiated into a specific cell type are terminally differentiated; however, scientists have found a way to reprogram these mature cells so that they dedifferentiate and return to an unspecialized, proliferative state. These cells are pluripotent like embryonic stem cells—able to produce all cell types—and are called induced pluripotent stem cells (iPSCs).
Somatic...
4.4K
Pleiotropy01:33

Pleiotropy

41.2K
Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
41.2K
mTOR Signaling and Cancer Progression03:03

mTOR Signaling and Cancer Progression

3.9K
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...
3.9K
Somatic to iPS Cell Reprogramming01:29

Somatic to iPS Cell Reprogramming

2.3K
Reprogramming alters the gene expression in somatic cells, transforming them into induced pluripotent stem (iPS) cells over several generations. Scientists can reprogram cells by introducing genes for four transcription factors—Oct4, Sox2, Klf4, and c-Myc (OSKM) by viral or non-viral methods. These factors are also known as Yamanaka factors after Shinya Yamanaka, who first generated iPS cells using mouse skin cells. Yamanaka was awarded the Nobel Prize in Physiology or Medicine in 2012...
2.3K
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

6.0K
Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
6.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Comprehensive analysis of phenotypes and transcriptome characteristics reveal  important contribution of chronic stress and  inflammation in the pathogenesis of acne.

Bioscience reports·2026
Same author

Organ Involvement and Treatment Response across Cutaneous Sarcoidosis Subtypes.

Acta dermato-venereologica·2026
Same author

Management of Facial Immune Checkpoint Inhibitor-Induced Vitiligo with Topical Ruxolitinib: Quantitative Assessment Using a Semi-Automatic Tool.

Current oncology (Toronto, Ont.)·2026
Same author

Deep phenotyping of skin tissue remodeling in patients with systemic sclerosis treated with CD19-CAR T cells.

Nature communications·2026
Same author

Network-based analysis reveals potential microRNA regulation of oncogenic pathways in SOX10-depleted uveal melanoma.

Cellular and molecular life sciences : CMLS·2026
Same author

Selective internal radiotherapy and chemosaturation show equivalent survival in metastatic uveal melanoma: a retrospective multicenter study.

The oncologist·2026

Related Experiment Video

Updated: Sep 19, 2025

Feeder-free Derivation of Melanocytes from Human Pluripotent Stem Cells
12:21

Feeder-free Derivation of Melanocytes from Human Pluripotent Stem Cells

Published on: March 3, 2016

10.5K

SOX10, MITF, and microRNAs: Decoding their interplay in regulating melanoma plasticity.

Xin Lai1,2,3, Chunyan Luan3, Zhesi Zhang1

  • 1Biomedicine Unit, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.

International Journal of Cancer
|June 3, 2025
PubMed
Summary

Dysregulation of SOX10 transcription factor is key in melanoma. MicroRNAs (miRNAs) interact with SOX10, forming networks that control melanoma cell plasticity and therapy response.

Keywords:
dynamic systemnetwork biologynetwork motifsphenotypic plasticitysystems biology

More Related Videos

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
07:41

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

Published on: March 8, 2022

2.6K
Spatial and Temporal Control of Murine Melanoma Initiation from Mutant Melanocyte Stem Cells
06:09

Spatial and Temporal Control of Murine Melanoma Initiation from Mutant Melanocyte Stem Cells

Published on: June 7, 2019

9.0K

Related Experiment Videos

Last Updated: Sep 19, 2025

Feeder-free Derivation of Melanocytes from Human Pluripotent Stem Cells
12:21

Feeder-free Derivation of Melanocytes from Human Pluripotent Stem Cells

Published on: March 3, 2016

10.5K
A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
07:41

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

Published on: March 8, 2022

2.6K
Spatial and Temporal Control of Murine Melanoma Initiation from Mutant Melanocyte Stem Cells
06:09

Spatial and Temporal Control of Murine Melanoma Initiation from Mutant Melanocyte Stem Cells

Published on: June 7, 2019

9.0K

Area of Science:

  • Molecular Biology
  • Cancer Biology
  • Network Biology

Background:

  • SOX10 transcription factor dysregulation drives melanoma development and progression.
  • MicroRNAs (miRNAs) regulate gene expression post-transcriptionally, influencing transcription factor activity.
  • Interactions between SOX10 and miRNAs form regulatory network motifs crucial for melanoma biology.

Purpose of the Study:

  • To review and discuss the interplay between SOX10 and miRNAs in melanoma.
  • To investigate gene regulatory interactions and network motifs involving SOX10, MITF, and miRNAs in melanoma.
  • To explain the link between these dynamics and melanoma cell phenotypic plasticity using control theory.

Main Methods:

  • Literature review and discussion of SOX10-miRNA interactions in melanoma.
  • Investigation of gene regulatory networks in melanoma, identifying key motifs.
  • Analysis of component expression levels within identified motifs.
  • Application of control theory to explain phenotypic plasticity.

Main Results:

  • SOX10 and miRNA interactions form network motifs (feedforward/feedback loops) influencing melanoma.
  • These motifs drive nonlinear dynamics in gene expression, impacting tumor proliferation, metastasis, and therapy response.
  • Identified crucial network motifs involving SOX10, MITF, and miRNAs, with analyzed expression levels.

Conclusions:

  • A data-driven network biology approach is essential for understanding melanoma regulatory mechanisms.
  • Elucidating SOX10 and MITF regulation by miRNAs in melanoma offers insights into phenotypic plasticity.
  • Findings may contribute to developing novel miRNA-based melanoma treatments.