Evidence map›Paper›PMID 39745117›Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2025

Engineering CAR-T Therapeutics for Enhanced Solid Tumor Targeting.

Danqing Zhu, Won Joon Kim, Hyunjin Lee, Xiaoping Bao, Pilnam Kim

Abstract readReview
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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  5. Review
  6. Review
  7. Engineering CAR-T Therapeutics for Enhanced Solid Tumor Targeting.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  8. Review
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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

5 authors.

Danqing ZhuDepartment of Chemical and Biological Engineering, School of Engineering, The Hong Kong University of Science and Technology (HKUST), Kowloon, Hong Kong SAR, 999077, China.ORCID https://orcid.org/0000-0003-3916-3192
Won Joon KimDepartment of Chemical and Biological Engineering, School of Engineering, The Hong Kong University of Science and Technology (HKUST), Kowloon, Hong Kong SAR, 999077, China.
Hyunjin LeeDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science Technology (KAIST), Daejeon, 34141, Republic of Korea.
Xiaoping BaoDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, 47906, USA.
Pilnam KimDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science Technology (KAIST), Daejeon, 34141, Republic of Korea.

Funding

Engineer Biomimetic Microfluidic Models to Investigate and Reprogram Tumor Associated Neutrophils for Cancer TherapyR37CA265926 · NCI · PURDUE UNIVERSITY · PI Xiaoping Bao · 2022 to 2026
$1.7M
ASPIRE League Seed FundBai Xian Asia Institute Asian Future Leaders Scholarship Program - BXAI AFLSPInnovation and Technology Commission - Hong Kong ITCPD/17-9National Research Foundation of Korea RS-2024-00338828NCI NIH HHS R37 CA265926
6 · The paper itself

Abstract

Cancer immunotherapy, specifically Chimeric Antigen Receptor (CAR)-T cell therapy, represents a significant breakthrough in treating cancers. Despite its success in hematological cancers, CAR-T exhibits limited efficacy in solid tumors, which account for more than 90% of all cancers. Solid tumors commonly present unique challenges, including antigen heterogeneity and complex tumor microenvironment (TME). To address these, efforts are being made through improvements in CAR design and the development of advanced validation platforms. While efficacy is limited, some solid tumor types, such as neuroblastoma and gastrointestinal cancers, have shown responsiveness to CAR-T therapy in recent clinical trials. In this review, it is first examined both experimental and computational strategies, such as protein engineering coupled with machine learning, developed to enhance T cell specificity. The challenges and methods associated with T cell delivery and in vivo reprogramming in solid tumors is discussed. It is also explored the advancements in engineered organoid systems, which are emerging as high-fidelity in vitro models that closely mimic the complex human TME and serve as a validation platform for CAR discovery. Collectively, these innovative engineering strategies offer the potential to revolutionize the next generation of CAR-T therapy, ultimately paving the way for more effective treatments in solid tumors.

Indexed as

Immunotherapy, AdoptiveNeoplasmsReceptors, Chimeric AntigenAnimalsHumansMachine LearningProtein EngineeringReceptors, Antigen, T-CellT-LymphocytesTumor MicroenvironmentReceptors, Antigen, T-CellReceptors, Chimeric Antigencancer immunotherapyChimeric antigen receptor (CAR)drug deliverynanoparticle

Identifiers

PMID39745117
PMCPMC12160681

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.