Evidence map›Paper›PMID 39301248›Full record

ReviewBiomaterials research2024

Strategies to Overcome Hurdles in Cancer Immunotherapy.

Jihyun Kim, Byung Joon Lee, Sehoon Moon, Hojeong Lee, Juyong Lee, Byung-Soo Kim, Keehoon Jung, Hyungseok Seo, Yeonseok Chung

Abstract readReview
In one paragraph

Review in Biomaterials research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. From Bench to Bedside: Emerging Paradigms in CAR-T Cell Therapy for Solid Malignancies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  8. Article
  9. Review
  10. Transforming TGF-β suppression into IL-15 stimulation: Advancing engineered CAR-T therapy for solid tumors.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Article
  11. 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

9 authors.

Jihyun KimResearch Institute for Pharmaceutical Sciences, College of Pharmacy, College of Pharmacy,Seoul National University, Seoul 08826, Republic of Korea.
Byung Joon LeeInterdisciplinary Program for Bioengineering, Seoul National University, Seoul 08826, Republic of Korea.
Sehoon MoonResearch Institute for Pharmaceutical Sciences, College of Pharmacy, College of Pharmacy,Seoul National University, Seoul 08826, Republic of Korea.
Hojeong LeeDepartment of Anatomy and Cell Biology, Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
Juyong LeeResearch Institute for Pharmaceutical Sciences, College of Pharmacy, College of Pharmacy,Seoul National University, Seoul 08826, Republic of Korea.
Byung-Soo KimInterdisciplinary Program for Bioengineering, Seoul National University, Seoul 08826, Republic of Korea.
Keehoon JungDepartment of Anatomy and Cell Biology, Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
Hyungseok SeoResearch Institute for Pharmaceutical Sciences, College of Pharmacy, College of Pharmacy,Seoul National University, Seoul 08826, Republic of Korea.
Yeonseok ChungResearch Institute for Pharmaceutical Sciences, College of Pharmacy, College of Pharmacy,Seoul National University, Seoul 08826, Republic of Korea.ORCID https://orcid.org/0000-0001-5780-4841

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite marked advancements in cancer immunotherapy over the past few decades, there remains an urgent need to develop more effective treatments in humans. This review explores strategies to overcome hurdles in cancer immunotherapy, leveraging innovative technologies including multi-specific antibodies, chimeric antigen receptor (CAR) T cells, myeloid cells, cancer-associated fibroblasts, artificial intelligence (AI)-predicted neoantigens, autologous vaccines, and mRNA vaccines. These approaches aim to address the diverse facets and interactions of tumors' immune evasion mechanisms. Specifically, multi-specific antibodies and CAR T cells enhance interactions with tumor cells, bolstering immune responses to facilitate tumor infiltration and destruction. Modulation of myeloid cells and cancer-associated fibroblasts targets the tumor's immunosuppressive microenvironment, enhancing immunotherapy efficacy. AI-predicted neoantigens swiftly and accurately identify antigen targets, which can facilitate the development of personalized anticancer vaccines. Additionally, autologous and mRNA vaccines activate individuals' immune systems, fostering sustained immune responses against cancer neoantigens as therapeutic vaccines. Collectively, these strategies are expected to enhance efficacy of cancer immunotherapy, opening new horizons in anticancer treatment.

Identifiers

PMID39301248
PMCPMC11411167

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.