Extrahepatic Tropism Is Built From the Corona, Not Bolted On

Question: How are lipid nanoparticles targeted to extrahepatic tissues?

Answer

Across these papers, extrahepatic targeting is treated as a two-step problem rather than a single modification. First, the dominant hepatic sink must be suppressed: liver accumulation is an active apolipoprotein E (ApoE)–LDLR uptake process, and blocking it is a prerequisite for any dose reaching another organ. Second, a new recognition determinant must be supplied. The retrieved work supports a division of labour between two routes. Route one is formulation-intrinsic: changing the ionizable lipid chemotype, adding a fifth lipid component, or swapping the stabilizer/PEG lipid shifts organ-level biodistribution — plausibly by changing which serum proteins integrate into the particle — and does so without any targeting ligand. Route two is ligand installation: antibodies, bispecific antibodies, DNA-hybridization anchors and fusion proteins confer cell-type specificity, but on their own they leave the liver dominant. Taken together, the papers argue that organ-level tropism is set by the lipid composition and its resulting corona, while cell-level specificity is set by the ligand, and the most convincing extrahepatic results combine hepatic de-targeting with ligand retargeting.

Hepatic accumulation is an active ApoE–LDLR process, so extrahepatic targeting begins with blocking it

Liver tropism of intravenously dosed LNPs is attributed specifically to ApoE adsorption and LDLR binding on hepatocytes, and engineered "dead" ApoE mutants carrying five receptor-binding-domain substitutions retain lipid binding while disrupting the ApoE–LDLR interaction, markedly inhibiting LDLR-mediated uptake in culture [22]. The same interaction can be attacked from the particle side: a modular fusion protein platform (NanoPilot) presents antibodies together with anchors that occupy the LDLR ApoE binding site, blocking hepatic uptake and redirecting particles to chosen cells [1]. The physical basis for this vulnerability is that LNP membranes do not simply accumulate a shell of protein — cryo-EM and competitive assays indicate localized membrane thickening and electron-dense remodelling consistent with lipoprotein fusion into the bilayer, with apolipoproteins the dominant associated proteins [9]. The therapeutic identity of an LNP is therefore partly a lipoprotein identity, which is why manipulating it changes where the particle goes.

Removing liver uptake does not by itself create new tropism

The decisive negative result is that both dead-ApoE coating and hyperactive PCSK9 pretreatment substantially reduced liver LNP transduction in vivo without inducing redistribution to other major organs [22]. Only when antibody conjugation was layered on top of de-targeting did the platform achieve engineered tropism to T cells, brain and lung, with reported pilot delivery to megakaryocytes, haematopoietic progenitors and cardiac tissue, and CD5-targeted particles producing CAR+ T cells while cutting hepatocyte transduction by 90% [22]. NanoPilot reaches the same conclusion by a different route: coating gives 30–40% splenic and hepatic T-cell transfection with a threefold reduction in bulk liver accumulation, i.e. cell specificity improved without the organ becoming liver-free [1]. Non-covalent antibody docking reproduces the pattern — a bispecific antibody bridging an HA epitope embedded in the PEG component to PD-L1, CD4, CD5 or SunTag produced a fourfold increase in in vivo transfection of PD-L1-expressing cancer cells and a 26-fold increase ex vivo in quiescent primary human T cells [5].

Ionizable-lipid chemotype can set organ tropism with no targeting ligand at all

A parallel body of work achieves extrahepatic expression purely compositionally. Cyclam-based macrocyclic ionizable lipids conferred selective lung tropism after intravenous dosing, reaching approximately 30% lung editing in Ai9 reporter mice with minimal off-organ activity, and increasing lipophilicity and aromatic content correlated inversely with particle size [12]. Triazine-based ionizable lipids with identical headgroups but different tail lengths all produced pulmonary expression, with the C14 variant doing so without in vitro or in vivo signs of thrombosis [11]. Adding an endogenous ligand as a fifth component had an even sharper effect: screening 100 LNPs in which cholecalciferol (vitamin D3) partially replaced the ionizable lipid identified formulations reported to give >99% pancreas-selective delivery with expression sustained for three days and pancreas-specific gene editing in Ai14 mice [10]. Spleen tropism was obtained by varying ionizable lipid and stabilizer identity and formulation parameters, explicitly without altering particle charge [4]. Spleen accumulation also arises through a mechanistically distinct route: an oxidized-lipid LNP library optimized for macrophages is taken up by ApoE-independent macropinocytosis and shows potent extrahepatic spleen tropism in vivo [14]. Notably, most ionizable-lipid redesign still does not escape the reticuloendothelial system — unsaturated thioether lipids improved in vivo potency more than 200-fold yet retained strong liver and spleen tropism [6].

The operative variable is the adsorbed protein corona, not net charge or bulk pKa

The clearest mechanistic evidence comes from an HDL-inspired library of 112 LNPs built to deliberately program corona composition, in which elevated apolipoprotein A-I/ApoE and vitronectin/ApoE ratios correlated with enhanced blood–brain barrier transport and yielded neuron- and microglia-preferring particles with functional outcomes in traumatic brain injury and neuroinflammation models [16]. That LNPs integrate lipoproteins into their membranes rather than adsorbing a discrete protein shell provides a structural explanation for why corona composition is programmable by lipid chemistry [9]. Consistent with corona rather than electrostatics being causal, splenic over hepatic delivery was achieved without any change in LNP charge [4]. Bulk physicochemical descriptors are poor proxies more generally: simulation work argues that heterogeneous local protonation states, rather than the ensemble apparent pKa, govern biocorona formation and tissue-selective biodistribution [8], and two LNPs with identical TNS-measured pKa (6.6) engaged endosomal membranes maximally at different pH values, with cargo release occurring only on complete membrane lysis [7].

Modular, non-covalent ligand docking buys cell-type specificity inside whichever organ the particle reaches

The chemistry of ligand attachment is converging on reversible docking rather than covalent conjugation, because it preserves particle structure while allowing combinatorial screening. A DNA-tethering method enabled rapid antibody modification and systematic comparison of bispecific LNPs, with bispecific formulations outperforming monotargeted ones for T-cell transfection and, importantly, with targeting molecules themselves altering biodistribution to spleen and liver [13]. The bispecific-antibody/HA-epitope dock achieved the same modularity without DNA, and a universal anti-rat IgG2 arm allowed tethering of off-the-shelf CD4, CD8, CD20, CD45 and CD3 antibodies [5]. DNA can serve double duty: LipiGo integrates short single-stranded DNA into the particle to redirect mRNA to lymphoid organs and antigen-presenting cells, then exploits DNA hybridization to attach ligands for white-adipocyte delivery [2]. How much ligand is enough is non-obvious — for targeted placental LNPs, higher-avidity ligands achieved more effective delivery despite greater polydispersity, and only SAXS-resolved subpopulations, not ensemble metrics, correlated with targeted transfection in vivo [19]. Dual display is also being used to broaden rather than narrow tropism, with anti-CD222 co-displayed with anti-CD5 on LNPs to generate CAR-monocytes and CAR-T cells from the same particle [15].

Conflicts and gaps

Pooled screening and individual validation disagree in ways that matter. A barcoded pooled screen of 25 C14120-based formulations identified organ-specific candidates, but individual validation confirmed high specificity only for the lung candidate and was inconclusive for the spleen candidate [21]; the NanoSTAMP platform was built precisely because pooled LNP screens lack spatial information on localization, uptake and multicellular response within intact tissue [20]. Whether composition-driven tropism is genuinely corona-mediated is largely inferred rather than demonstrated causally — de-targeting liver by ApoE blockade did not redistribute particles to other organs [22], and hepatic de-targeting efficiency was itself reported to depend on the immune status of the recipient [4], so host state is an uncontrolled confounder across studies. Brain delivery is the sharpest unresolved case: ionic-liquid coating extended circulation and increased routing to brain alongside reduced hepatic uptake [3], yet focused-ultrasound BBB opening delivered LNP-packaged mRNA to cerebellum with no detectable protein expression or therapeutic benefit in a Niemann-Pick type C model despite success in wild-type mice [18]. Skeletal muscle, arguably the largest extrahepatic opportunity, has no convincing LNP route in this set; the muscle result that does exist comes from conjugate chemistry, where pH-dependent anti-TfR1 nanobody–siRNA conjugates produced up to 60% transcript knockdown in skeletal muscle two weeks after a single intravenous dose [17]. Nearly all quantitative tropism claims here rest on mouse data.

What would change the answer

A shared barcoded LNP library distributed across laboratories and read out with spatial, cell-resolved barcoding — the NanoSTAMP design applied to a common formulation set — would settle whether composition-driven tropism replicates and whether pooled hits survive individual validation [20]. Corona causality requires swapping rather than correlating: fixing lipid composition while deliberately exchanging corona proteins, as done with HDL-inspired particles and dead-ApoE coatings, and measuring organ distribution of the same particle with different coronas [16] [22]. An LDLR- or ApoE-null or haPCSK9-pretreated host dosed with a fixed library would quantify the ceiling on extrahepatic delivery once hepatic uptake is removed, and would test directly whether the "no redistribution" result generalizes [22]. Finally, head-to-head benchmarking of ligand-only, composition-only and combined particles in the same organ and model — the comparison the de-targeting-plus-retargeting work approximates but does not systematize — plus non-human primate or perfused human organ confirmation, is what would convert the current two-step heuristic into a design rule [22] [13].

References

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[8] Kyle J. Colston, Santiago C. Monsalve, Severin T. Schneebeli. "Structure-Based Modeling of Environment-dependent Protonation States Across LNP Formulations with Atomistic CpHMD". chemrxiv. 2025-03-20T09:02:26.000Z. URL: https://doi.org/10.26434/chemrxiv-2025-psmd3

[9] Grumelot, S., Mohammed, N., Yerima, G., Colonrosado, J., Sadeghi, S. A., Fang, F., Hilsen, K., Shango, B., Saei, A. A., Murray, A. M., Mitchell, M. J., Borhan, B., Sun, L., Vali, H., Mofrad, M., Whitehead, K., Mahmoudi, M.. "Lipid nanoparticle protein coronas arise through lipoprotein fusion rather than shell-like adsorption". bioRxiv. 2026-06-23T00:00:00.000Z. URL: https://doi.org/10.64898/2025.12.21.695162

[10] Isaac, I., Patel, L., Tran, N., Singam, A., Guha, P., Park, S., Bhattacharya, C.. "Reengineering mRNA lipid nanoparticles for systemic delivery to pancreas". bioRxiv. 2024-11-03T00:00:00.000Z. URL: https://doi.org/10.1101/2024.10.30.621163

[11] Ibnat, N., Masud, A. A., Mory, J., Funk, T., Mahmood, D. F., Wood, J., Venditto, V. J.. "Tail length of triazine-based lipids influences blood clotting risk in vitro and in vivo". bioRxiv. 2026-08-26T00:00:00.000Z. URL: https://doi.org/10.64898/2026.08.25.747137

[12] David Oupicky, Kasturi Siddhanta, Neha Kumari, Rahul Singh, Braeden Pinkerton, Aditya Sundar, Ling Ding. "Macrocyclic Ionizable Lipids for Selective Lung Delivery of mRNA and Gene Recombination". chemrxiv. 2025-12-12T01:59:08.000Z. URL: https://doi.org/10.26434/chemrxiv-2025-hpf87

[13] Kelly, M. D., Vu, T. Q., Iyer, A. U., Luo, Y., Linderman, A. P., Cline, L., Sanchez, C., Kamat, N. P.. "DNA-Directed Assembly of Multivalent Lipid Nanoparticles for Targeted T Cell Gene Delivery". bioRxiv. 2025-09-09T00:00:00.000Z. URL: https://doi.org/10.1101/2025.09.04.674323

[14] Mukalel, A. J., Tylek, T., O'Brien, E., Frazee, C., Geisler, H. C., Li, J., Thatte, A. S., Safford, H. C., Figueroa-Espada, C. G., Alameh, M.-G., Hamilton, A. G., Mai, D., Sheppard, N. C., June, C. H., Weissman, D., Spiller, K. L., Mitchell, M. J.. "Bioinspired Oxidized mRNA Lipid Nanoparticles for Ex Vivo Engineering of Chimeric Antigen Receptor Macrophages Targeting Solid Tumors". bioRxiv. 2025-06-11T00:00:00.000Z. URL: https://doi.org/10.1101/2025.06.07.658363

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[16] Xu, Z., Shalin, K., Do, V., Yan, A., Gao, J.. "High-density Lipoprotein Inspired Lipid Nanoparticles for Systemic RNA delivery to the Brain". bioRxiv. 2026-06-01T00:00:00.000Z. URL: https://doi.org/10.64898/2026.05.29.728695

[17] Hoyt, E. A., Moonens, K., Rapisarda, C., Salvador, A. M., Hammond, T. R., Kharade, S., Mondragon Gonzalez, R., Moran, F., Ramkumar, S., Thummapudi, J., Zhou, S., Haussy, G., Capdevila, C., Maillard, F., Ismail, A., Avery, L., Sardi, P., Nonne, C., Cornelis, S., Leksa, N.. "pH-dependent anti-TfR1 NANOBODY(R) molecules deliver efficacious oligonucleotide payloads to muscle and CNS tissues". bioRxiv. 2026-08-03T00:00:00.000Z. URL: https://doi.org/10.64898/2026.07.29.741483

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How this survey was made

This survey answers one question: “How are lipid nanoparticles targeted to extrahepatic tissues?”

We keep our own collection of recent preprints and refresh it every day from bioRxiv, medRxiv, arXiv, PsyArXiv, SocArXiv and ChemRxiv. For each survey, we search that collection for recent work and keep the strongest matches: papers that use the same terms as the question, and papers on the same topic in different words.

The text was written from the titles and abstracts of those papers; the full texts were not read. Statements that draw on a particular paper are marked with a number in brackets. The reference list just above is the 22 papers whose work this text draws on, chosen from the 143 papers those searches returned; the rest of the shortlist is not printed. It is not a complete review of everything published on the question.

Treat this as a starting point and a reading list, not a peer-reviewed review. The searches behind this survey ran on October 21, 2026 and covered work from the previous two years.