Evidence map›Paper›PMID 41366795›Full record

SynthesisJournal of translational medicine2025

Synergistic innovations of nanomedicine in lymphoma treatment: a systematic review.

Yingying Zhang, Yunjin Li, Ke Yang, Weiping Liu, Sha Zhao, Yuan Tang, Zihang Chen

Abstract readSystematic ReviewReview
In one paragraph

Synthesis in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. In Vivo T-Cell Engineering: Revolution in Delivery Strategies and Clinical Translation.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026
    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

7 authors.

Yingying Zhang *Department of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China.
Yunjin Li *Department of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China.
Ke YangDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China.
Weiping LiuDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China.
Sha ZhaoDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China.
Yuan TangDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China.
Zihang ChenDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China. ianchan_0704@hotmail.com.ORCID 0000-0002-8903-0171

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lymphoma therapy faces persistent challenges, including tumor heterogeneity, drug resistance, and immunosuppressive microenvironments, particularly in relapsed or refractory cases. Current treatments, such as chemotherapy, targeted therapy, and cell-based therapies, are limited by suboptimal targeting, systemic toxicity, and manufacturing complexities, highlighting the urgent need for innovative solutions. Nanomedicine has emerged as a transformative approach, integrating material design with therapeutic strategies to address these barriers. This review of 133 preclinical studies highlights key advancements: the dominance of lipid- and polymer-based nanoparticles, increasing use of natural materials, and the combination of passive EPR-based targeting with active strategies like CD20-mediated approaches. Stimuli-responsive systems, particularly pH-sensitive platforms, further enhance precision drug delivery, improving efficacy while reducing toxicity. Artificial intelligence accelerates progress by integrating multi-omics data and utilizing machine learning to optimize nanoparticle design, enhancing precision and personalization. Additionally, nanotechnology has advanced imaging, minimized chemotherapy-induced toxicity, and enabled in vivo CAR-T generation, offering safer and scalable therapeutic options. However, clinical translation faces hurdles, including scalable manufacturing, single-cell omics-guided nanoparticle design, and humanized models to validate immune microenvironment interactions. Addressing these challenges is essential to fully realize the potential of nanomedicine and AI integration, driving next-generation platforms for precision lymphoma therapy.

Indexed as

LymphomaNanomedicineAnimalsDrug Delivery SystemsHumansNanoparticlesDrug delivery systemLymphomaNanomedicinePrecision oncologyTumor microenvironment remodeling

Identifiers

PMID41366795
PMCPMC12690820

What OpenQuestion 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 OpenQuestion graph.