Evidence map›Paper›PMID 39286218›Full record

ReviewHeliyon2024

Eliminating a barrier: Aiming at VISTA, reversing MDSC-mediated T cell suppression in the tumor microenvironment.

Yayuan Deng, Mengjia Shi, Lin Yi, Muhammad Naveed Khan, Zhijia Xia, Xiaosong Li

Abstract readReview
In one paragraph

Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
–field-weighted citation impact
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

67 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

7 more citing papers are in PubMed but not listed here.

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

6 authors.

Yayuan DengThe First College of Clinical Medicine, Chongqing Medical University, Chongqing, China.
Mengjia ShiClinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Lin YiThe First College of Clinical Medicine, Chongqing Medical University, Chongqing, China.
Muhammad Naveed KhanClinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Zhijia XiaDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, 81377, Germany.
Xiaosong LiClinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment by producing remarkable clinical outcomes for patients with various cancer types. However, only a subset of patients benefits from immunotherapeutic interventions due to the primary and acquired resistance to ICIs. Myeloid-derived suppressor cells (MDSCs) play a crucial role in creating an immunosuppressive tumor microenvironment (TME) and contribute to resistance to immunotherapy. V-domain Ig suppressor of T cell activation (VISTA), a negative immune checkpoint protein highly expressed on MDSCs, presents a promising target for overcoming resistance to current ICIs. This article provides an overview of the evidence supporting VISTA's role in regulating MDSCs in shaping the TME, thus offering insights into how to overcome immunotherapy resistance.

Indexed as

ICIsImmunotherapy resistanceMDSCTumor microenvironmentVISTA

Identifiers

PMID39286218
PMCPMC11402941

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.