Related Experiment Video

Updated: Oct 7, 2025

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

Multi-omics prediction in melanoma immunotherapy: A new brick in the wall

Caroline Robert1, Daniel Gautheret2

  • 1Gustave Roussy, Université Paris-Saclay, 114 rue Edouard Vaillant, Villejuif, France; INSERM U 981, Université Paris-Saclay, 114 rue Edouard Vaillant, Villejuif, France.

Cancer Cell
|January 11, 2022
PubMed

Insights

New research analyzes whole-genome and methylome data for melanoma immunotherapy. While genome breaks indicate resistance, mutation burden and interferon-gamma signature best predict response, requiring more data for clinical use.

Area of Science:

  • Oncology
  • Genomics
  • Immunotherapy

Background:

  • Melanoma immunotherapy response varies significantly among patients.
  • Understanding the genomic and epigenomic factors influencing treatment efficacy is crucial.

Purpose of the Study:

  • To investigate the utility of whole-genome and methylome data in predicting response to melanoma immunotherapy.
  • To identify reliable biomarkers for treatment success.

Main Methods:

  • Analysis of whole-genome sequencing data from melanoma patients.
  • Methylome profiling to assess epigenetic modifications.
  • Correlation of genomic and methylomic features with immunotherapy response.

Main Results:

  • Increased frequency of genome breaks observed in tumors resistant to immunotherapy.
  • Mutation burden and interferon-gamma signature identified as the most effective classifiers for treatment response.
  • Specific genomic and methylomic patterns associated with differential treatment outcomes.

Conclusions:

  • Whole-genome and methylome data provide valuable insights into melanoma immunotherapy response.
  • Mutation burden and interferon-gamma signature are key predictive biomarkers.
  • Clinical application necessitates the aggregation and analysis of larger, diverse datasets.

More Related Videos

Predictive Immune Modeling of Solid Tumors08:50

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

7.2K
Author Spotlight: Recreating Melanoma Complexity with Patient-Derived Organoids for Immunotherapy Evaluation05:33

Author Spotlight: Recreating Melanoma Complexity with Patient-Derived Organoids for Immunotherapy Evaluation

Published on: September 6, 2024

1.8K

Related Concept Videos

Tumor Immunotherapy01:27

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
712
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
5.2K