From Formulation Quality to Anti-Tumor Immunity: A Multimodal Imaging and Translational Framework for mRNA–Lipid Nanoparticle Cancer Vaccines in Preclinical Tumor Models

mRNA–Lipid nanoparticles (LNPs) for cancer vaccines are often considered a linear progression, in which formulation, biodistribution, innate stimulation, antigen expression, and tumor control form a continuum. They are not. This review connects the manufacturing inputs and lipid composition to particle attributes, innate sensing, organ and cell exposure, cytosolic translation, antigen presentation, therapeutic response, and hepatic safety. This review aims to provide a mechanism-aligned framework from critical quality attributes (CQAs) and critical process parameters (CPPs) to innate sensing, multimodal imaging, and preclinical efficacy and safety that can be used to design and interpret preclinical studies of mRNA-LNP cancer vaccines, with explicit attention to orthotopic pancreatic ductal adenocarcinoma (PDAC) models. Principal findings: (i) total organ signal is an inadequate surrogate for productive delivery; the decisive variable is translation of antigen in a permissive antigen-presenting cell (APC) during a defined inflammatory window; (ii) formulation and process variables including size, PDI, encapsulation, RNA integrity and capping, lipid composition, PEG-lipid architecture, mixing conditions, and storage history alter this conversion; and (iii) multimodal imaging is most informative when carrier or payload tracking is paired with reporter or antigen expression, immune profiling, tumor response, and liver-safety assays. We propose a release-to-response architecture for preclinical studies and identify the evidence required for clinically interpretable pharmacology. We reviewed peer-reviewed studies on mRNA cancer vaccination, quantitative imaging, PDAC models, LNP quality-by-design, and formulation-dependent innate immunology. The total organ signal is an inadequate surrogate for productive delivery; the decisive variable is translating antigen into an antigen-presenting cell during a permissive inflammatory window. Particle size, polydispersity, encapsulation, RNA integrity and capping, lipid composition, PEG-lipid architecture, mixing conditions, and storage history can alter this conversion. Multimodal imaging is most informative when carrier or payload tracking is paired with reporter or antigen expression, immune profiling, tumor response, and liver safety assays. PDAC studies have shown that hepatic or splenic exposure can be either a liability or intentional immune reprogramming. We propose a release-to-response architecture for preclinical studies and identify the evidence required for clinically interpretable pharmacology.

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Journal
Biomolecules
Published
2026-11-01
DOI
https://doi.org/10.3390/biom16111589
Primary Topic
RNA Interference and Gene Delivery
Type
article
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article

From Formulation Quality to Anti-Tumor Immunity: A Multimodal Imaging and Translational Framework for mRNA–Lipid Nanoparticle Cancer Vaccines in Preclinical Tumor Models

Mohammad A. Obeid, Abdelrahim M. Alqudah, Alaa A. A. Aljabali, Esam Y. Qnais et al.
Biomolecules
RNA Interference and Gene Delivery
article

From Formulation Quality to Anti-Tumor Immunity: A Multimodal Imaging and Translational Framework for mRNA–Lipid Nanoparticle Cancer Vaccines in Preclinical Tumor Models

Mohammad A. Obeid, Abdelrahim M. Alqudah, Alaa A. A. Aljabali, Esam Y. Qnais, Omar Gammoh
article en

Abstract

mRNA–Lipid nanoparticles (LNPs) for cancer vaccines are often considered a linear progression, in which formulation, biodistribution, innate stimulation, antigen expression, and tumor control form a continuum. They are not. This review connects the manufacturing inputs and lipid composition to particle attributes, innate sensing, organ and cell exposure, cytosolic translation, antigen presentation, therapeutic response, and hepatic safety. This review aims to provide a mechanism-aligned framework from critical quality attributes (CQAs) and critical process parameters (CPPs) to innate sensing, multimodal imaging, and preclinical efficacy and safety that can be used to design and interpret preclinical studies of mRNA-LNP cancer vaccines, with explicit attention to orthotopic pancreatic ductal adenocarcinoma (PDAC) models. Principal findings: (i) total organ signal is an inadequate surrogate for productive delivery; the decisive variable is translation of antigen in a permissive antigen-presenting cell (APC) during a defined inflammatory window; (ii) formulation and process variables including size, PDI, encapsulation, RNA integrity and capping, lipid composition, PEG-lipid architecture, mixing conditions, and storage history alter this conversion; and (iii) multimodal imaging is most informative when carrier or payload tracking is paired with reporter or antigen expression, immune profiling, tumor response, and liver-safety assays. We propose a release-to-response architecture for preclinical studies and identify the evidence required for clinically interpretable pharmacology. We reviewed peer-reviewed studies on mRNA cancer vaccination, quantitative imaging, PDAC models, LNP quality-by-design, and formulation-dependent innate immunology. The total organ signal is an inadequate surrogate for productive delivery; the decisive variable is translating antigen into an antigen-presenting cell during a permissive inflammatory window. Particle size, polydispersity, encapsulation, RNA integrity and capping, lipid composition, PEG-lipid architecture, mixing conditions, and storage history can alter this conversion. Multimodal imaging is most informative when carrier or payload tracking is paired with reporter or antigen expression, immune profiling, tumor response, and liver safety assays. PDAC studies have shown that hepatic or splenic exposure can be either a liability or intentional immune reprogramming. We propose a release-to-response architecture for preclinical studies and identify the evidence required for clinically interpretable pharmacology.

BiomoleculesVol. 16(11)
Hashemite University (JO), Yarmouk University (JO), Ras al-Khaimah Medical and Health Sciences University (AE)
Openalex Percentile: Top 22%
RNA Interference and Gene Delivery
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