Evidence map›Paper›PMID 42395543›Full record

ArticlebioRxiv : the preprint server for biology2026

Engineering nanoparticle surface chemistry for antigen-presenting cell targeting improves specificity and safety of TLR3 agonist cancer immunotherapy.

Victoria F Gomerdinger, Cassandra Parada, Andrea Li, Aidan Kindopp, Justin A Kaskow, Eva Cai, Julia B Treese, Ivan S Pires, Apoorv Shanker, Gil Covarrubias and 3 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Victoria F GomerdingerDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0003-1122-0482
Cassandra ParadaDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Andrea LiDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Aidan KindoppDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Justin A KaskowDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-9046-4383
Eva CaiDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Julia B TreeseDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Ivan S PiresDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Apoorv ShankerDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Gil CovarrubiasDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Alexander D StonemanDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Magalie BoucherDivision of Comparative Medicine, Massachusetts Institute of Technology, Cambridge, MA, USA.
Paula T HammondDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Funding

VIRUS PRODUCTION COREP30CA014051 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Jacqueline A. Lees · 1985 to 2026
$93.9M
NCI NIH HHS P30 CA014051
6 · The paper itself

Abstract

Innate immune agonists are promising therapeutic agents to induce immune responses against cancer. However, these agents have been limited by toxicity associated with systemic accumulation and activity in off-target cells. In this work, a targeted nanoparticle (NP) platform to encapsulate and protect the Toll-like receptor 3 (TLR3) agonist polyinosinic-polycytidylic acid (poly(I:C)) and promote its specific delivery to antigen presenting cells (APCs), macrophages and dendritic cells, for activation of this cell population was designed. To determine NP physiochemical properties that promote APC delivery, we developed a library of NP surface chemistries formed by electrostatic adsorption of polyanion coatings onto liposomes using layer-by-layer (LbL) assembly and screened the particles on APCs and off-target cells. Dextran sulfate was identified as a promising coating to enhance specific APC delivery. We applied these design parameters to develop a poly(I:C)-loaded NP for an APC-targeted immunotherapy. In a model of metastatic ovarian cancer, the LbL NP prolonged poly(I:C) retention in the peritoneal space-with 2-fold remaining 24-48hr after administration compared to free poly(I:C)-ultimately reducing systemic accumulation and associated toxicities. Compared to free drug, the NP reduced the increase in serum levels of TNFα, IL-6, and CXCL10 by 9-, 4-, and 31-fold respectively. NP-treated mice experienced lower weight loss and recovered more quickly at a higher poly(I:C) dose, indicating a widening of the therapeutic window. The NP formulation enhanced accumulation of poly(I:C) in the tumor 2-fold and activation of the target APC population compared to free drug, and ultimately slowed tumor growth and extended survival in combination with doxorubicin chemotherapy. Overall, this work demonstrates a modular NP delivery strategy to improve the delivery, safety, and therapeutic window of a TLR3 agonist.

Indexed as

Antigen presenting cellsCancer therapyImmune agonistLayer-by-LayerOvarian cancerTargeted nanomedicineTherapeutic safety

Identifiers

PMID42395543
PMCPMC13320797

What Socratic holds

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Registered trials

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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.