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

DNA Damage Can Stall the Cell Cycle02:36

DNA Damage Can Stall the Cell Cycle

In response to DNA damage, cells can pause the cell cycle to assess and repair the breaks. However, the cell must check the DNA at certain critical stages during the cell cycle. If the cell cycle pauses before DNA replication, the cells will contain twice the amount of DNA. On the other hand, if cells arrest after DNA replication but before mitosis, they will contain four times the normal amount of DNA. With a host of specialized proteins at their disposal,cells must use the right protein at...
DNA Damage can Stall the Cell Cycle02:36

DNA Damage can Stall the Cell Cycle

In response to DNA damage, cells can pause the cell cycle to assess and repair the breaks. However, the cell must check the DNA at certain critical stages during the cell cycle. If the cell cycle pauses before DNA replication, the cells will contain twice the amount of DNA. On the other hand, if cells arrest after DNA replication but before mitosis, they will contain four times the normal amount of DNA. With a host of specialized proteins at their disposal,cells must use the right protein at...
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.
Cytotoxic T Cells-mediated Immune Response01:27

Cytotoxic T Cells-mediated Immune Response

Cytotoxic T cells are a vital component of the immune system. They have the remarkable ability to identify and target antigens on infected or abnormal cells. These antigens often originate from intracellular pathogens such as viruses or abnormal proteins cancer cells produce.
Immunological surveillance is the ability of immune cells to monitor and eliminate infected cells with intracellular pathogens, neoplastically transformed cells, and cells with non-self antigens. Cytotoxic T cells and NK...
The Intrinsic Apoptotic Pathway01:31

The Intrinsic Apoptotic Pathway

Internal cellular stress, such as cellular injury or hypoxia, triggers intrinsic apoptosis. The B-cell lymphoma 2 (Bcl-2) family of proteins are the primary regulators of the intrinsic apoptotic pathway. For example, during DNA damage, checkpoint proteins, such as Ataxia Telangiectasia Mutated (ATM protein) and Checkpoints Factor-2 (Chk2) proteins, are activated. These proteins phosphorylate p53 which further activates pro-apoptotic proteins, such as Bax, Bak, PUMA, and Noxa, and inhibits...
Treatment Resistant Cancers02:56

Treatment Resistant Cancers

Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...

You might also read

Related Articles

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

Sort by
Same author

Identifying four distinct prognostic trajectories using latent class growth analysis in moderate-severe TBI: a 10-year retrospective cohort study.

Neurosurgical review·2026
Same author

SREBP1-mediated lipogenesis promotes dedifferentiation and senescence of vascular smooth muscle cells through epigenetic remodeling.

Nature communications·2025
Same author

Activation of the RSAD2-YTHDF1 axis in smooth muscle causes inflammatory bowel disease via intercellular mitochondrial transfer.

Nature communications·2025
Same author

DNA methylation variations of DNA damage response in glioblastoma: NSUN5 modulates tumor-intrinsic cytosolic DNA-sensing and microglial behavior.

Journal of translational medicine·2025
Same author

DNA methylation variations of DNA damage response correlate survival and local immune status in melanomas.

Immunity, inflammation and disease·2024
Same author

Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.

European journal of trauma and emergency surgery : official publication of the European Trauma Society·2024

Related Experiment Video

Updated: Jul 1, 2026

Identifying PD-1/PD-L1 Inhibitors with Surface Plasmon Resonance Technology
07:04

Identifying PD-1/PD-L1 Inhibitors with Surface Plasmon Resonance Technology

Published on: May 2, 2025

DNA Damage Response Alterations and Immune Checkpoint Blockade Outcomes Across Multiple Cancers.

Tian-Chi Ma1,2, Wen-Heng Guo1,2, De-Min Liu3,4

  • 1The Department of Aviation Medicine, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China.

JCO Precision Oncology
|June 29, 2026
PubMed
Summary

DNA damage response (DDR) alterations can predict immune checkpoint blockade (ICB) efficacy in specific cancers. A machine learning model using DDR mutations offers a context-aware biomarker for precision oncology, outperforming tumor mutational burden.

More Related Videos

Analysis of Human T Cell Activity in an Allogeneic Co-Culture Setting of Pre-Treated Tumor Cells
09:04

Analysis of Human T Cell Activity in an Allogeneic Co-Culture Setting of Pre-Treated Tumor Cells

Published on: March 7, 2025

Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood
06:07

Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood

Published on: February 5, 2020

Related Experiment Videos

Last Updated: Jul 1, 2026

Identifying PD-1/PD-L1 Inhibitors with Surface Plasmon Resonance Technology
07:04

Identifying PD-1/PD-L1 Inhibitors with Surface Plasmon Resonance Technology

Published on: May 2, 2025

Analysis of Human T Cell Activity in an Allogeneic Co-Culture Setting of Pre-Treated Tumor Cells
09:04

Analysis of Human T Cell Activity in an Allogeneic Co-Culture Setting of Pre-Treated Tumor Cells

Published on: March 7, 2025

Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood
06:07

Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood

Published on: February 5, 2020

Area of Science:

  • Genomics
  • Cancer Biology
  • Immunotherapy

Background:

  • Alterations in DNA damage response (DDR) pathways are increasingly recognized for their role in predicting patient responses to cancer immunotherapies.
  • However, the pan-cancer utility of DDR alterations as biomarkers for immune checkpoint blockade (ICB) efficacy is not well-established.

Purpose of the Study:

  • To comprehensively characterize DDR mutational landscapes across various cancer types.
  • To evaluate the predictive capability of DDR alterations for ICB treatment outcomes.

Main Methods:

  • Integrated multiomics data from The Cancer Genome Atlas (TCGA) and independent ICB-treated cohorts.
  • Employed unsupervised clustering and machine learning to stratify patients based on DDR mutation patterns.
  • Conducted survival analyses and multivariable Cox models, assessing independence from tumor mutational burden (TMB).
  • Utilized bioinformatic analyses to explore immune-related features associated with DDR-defined subtypes.

Main Results:

  • Pan-cancer DDR clustering showed limited prognostic value outside of ICB treatment.
  • Four DDR mutation-based subtypes significantly predicted overall survival in ICB-treated melanoma, non-small cell lung cancer, and gastrointestinal cancers.
  • These DDR subtypes demonstrated treatment-specific predictive relevance, not predicting survival in non-ICB cohorts.
  • A DDR-defined high-risk subgroup in melanoma showed poor survival independent of TMB, which lacked independent predictive value.
  • DDR subtypes correlated with distinct transcriptional programs in immune signaling and DNA damage repair.

Conclusions:

  • DDR mutational landscapes serve as context-dependent biomarkers for ICB efficacy.
  • A DDR-based machine learning model predicts ICB outcomes, offering advantages over TMB.
  • Supports a framework for developing context-aware biomarkers in precision oncology.