Evidence map›Paper›PMID 38592744›Full record

ReviewNanoscale2024

Genetically engineered cell-derived nanovesicles for cancer immunotherapy.

Shan He, Zongmin Zhao

Open access · bronzeAbstract readReview
In one paragraph

Review in Nanoscale, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Effect of gut bacterial extracellular vesicles on angiogenic potential and vascular integrity: positive and negative aspects.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Review
  3. Review
  4. Article
  5. 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

2 authors at 1 institution in 1 country.

Shan HeDepartment of Pharmaceutical Sciences, College of Pharmacy, University of Illinois Chicago, Chicago, IL 60612, USA. zhaozm@uic.edu.
Zongmin ZhaoDepartment of Pharmaceutical Sciences, College of Pharmacy, University of Illinois Chicago, Chicago, IL 60612, USA. zhaozm@uic.edu.ORCID http://orcid.org/0000-0001-8979-844X
University of Illinois Chicago · US

Funding

Multiscale approaches to engineering living cells for nanotherapeutic deliveryR35GM150507 · NIGMS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI Zongmin Zhao · 2023 to 2026
$1.6M
NIGMS NIH HHS R35 GM150507
6 · The paper itself

Abstract

The emergence of immunotherapy has marked a new epoch in cancer treatment, presenting substantial clinical benefits. Extracellular vesicles (EVs), as natural nanocarriers, can deliver biologically active agents in cancer therapy with their inherent biocompatibility and negligible immunogenicity. However, natural EVs have limitations such as inadequate targeting capability, low loading efficacy, and unpredictable side effects. Through progress in genetic engineering, EVs have been modified for enhanced delivery of immunomodulatory agents and antigen presentation with specific cancer targeting ability, deepening the role of EVs in cancer immunotherapy. This review briefly describes typical EV sources, isolation methods, and adjustable targeting of EVs. Furthermore, this review highlights the genetic engineering strategies developed for delivering immunomodulatory agents and antigen presentation in EV-based systems. The prospects and challenges of genetically engineered EVs as cancer immunotherapy in clinical translation are also discussed.

Indexed as

Extracellular VesiclesGenetic EngineeringImmunotherapyNeoplasmsAnimalsAntigen PresentationHumans

Identifiers

PMID38592744
PMCPMC11075450
OpenAlexW4393145216

What OpenQuestion holds

Textmetadata
LicenceTDM
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.