Evidence map›Paper›PMID 38590525›Full record

ReviewFrontiers in immunology2024

Aging-related biomarker discovery in the era of immune checkpoint inhibitors for cancer patients.

Abdullah Al-Danakh, Mohammed Safi, Yuli Jian, Linlin Yang, Xinqing Zhu, Qiwei Chen, Kangkang Yang, Shujing Wang, Jianjun Zhang, Deyong Yang

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
8.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Life Factors and Melanoma: From the Macroscopic State to the Molecular Mechanism.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  9. Ageing, immune fitness and cancer.Nature reviews. Cancer · 2025
    Review
  10. Article
  11. Review
  12. Review
  13. Impact of comorbidity on survival in cancer patients receiving immune checkpoint inhibitors.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Abdullah Al-Danakh *Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Mohammed Safi *Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Yuli Jian *Department of Biochemistry and Molecular Biology, Institute of Glycobiology, Dalian Medical University, Dalian, China.
Linlin Yang *Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Xinqing ZhuDepartment of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Qiwei ChenDepartment of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Kangkang YangInstitute for Genome Engineered Animal Models of Human Diseases, National Center of Genetically Engineered Animal Models for International Research, Dalian Medical University, Dalian, Liaoning, China.
Shujing WangDepartment of Biochemistry and Molecular Biology, Institute of Glycobiology, Dalian Medical University, Dalian, China.
Jianjun ZhangDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Deyong YangDepartment of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Dalian Medical University · CNFirst Affiliated Hospital of Dalian Medical University · CNThe University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.

Indexed as

Biomedical ResearchDrug-Related Side Effects and Adverse ReactionsNeoplasmsAgedAgingHumansImmune Checkpoint InhibitorsImmune Checkpoint Inhibitorsagingimmune biomarkersimmune checkpoint inhibitorsimmunosenescenceneoplasm

Identifiers

PMID38590525
PMCPMC11000233
OpenAlexW4392861304

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.