Despite significant advances in gene medicine, translating the results from research to the clinic to treat both genetic disorders and acquired diseases by introducing nucleic acids is still a challenging task (Wang et al., 2019). To date, more than 900,000 articles on the topic of gene therapy can be retrieved from the Web of Science; meanwhile, only around 3,180 gene therapy clinical trials have been approved, ongoing or completed worldwide, and 56.4% of these are in phase I ¹ . Suitable vectors prevent naked nucleic acids introduced into the body from ubiquitous nucleases and renal elimination, and facilitate the process of targeted delivery and efficient internalization (Ren et al., 2021). Nonviral carriers, especially nanoparticles, have demonstrated tremendous potential in the targeted delivery of genetic material in treating hereditary transthyretin amyloidosis, pancreatic cancer, and other diseases with lower immunogenicity, with larger loading capacity, and being free from unexpected gene integration when compared to viral vectors (Ohno et al., 2013; Kamerkar et al., 2017; Adams et al., 2018; Yan et al., 2019; Cheng et al., 2020; Li et al., 2021). Nanotechnology is widely used in the medical industry and forms an important class of drug and nucleic acid delivery systems to accelerate the effect of drugs in the human body (Ravindran et al., 2018). Although various nanoparticles, such as lipid complexes, gold nanoparticles, and extracellular vesicles, have been extensively developed in recent years, low delivery efficiency, potential cytotoxicity, and immaturity for their application limit the steps to translation (Liu et al., 2017; Amreddy et al., 2018). Therefore, nano-delivery systems for nucleic acid are worthy of further research to meet the growing demands in nano-medicine and gene therapy translations.

Bibliometrics is a branch of informatics that evaluates the current situation and future research development trends, and professional software mapping knowledge domains may form an intuitive result. Before visualizing the map, data must be retrieved from the database, processed to transform, clustered to reduce dimensions, and organized as a network that contains nodes and links. Depending on the different items of interest and their relationships, networks are divided into co-occurrence networks, co-citation networks, and collaboration networks, which allow keyword–keyword, reference–reference, or author–author connections to uncover clues in the research field. Keywords in the same article tend to have a relationship in certain discipline and thus can be connected with links to form a co-occurrence network; analogously, references cited by the same article are connected for a co-citation network. CiteSpace is a software famous for excellently performing co-citation analysis and displaying the trends and developments in scientific domains (Chen, 2006; Chen, 2013). In addition, the density view provided by VOSviewer has a fantastic visualization in the co-occurrence network (Moral-Munoz et al., 2020). The alluvial flow diagram, presented by the MapEquation—a web-based application, shows the change of the network over time, which intuitively indicates the tendency of fields. By combining bibliometrics with data visualization, the intellectual structure of a specific domain can be established quantitatively and graphically for evaluating literature performance, detecting central issues, and breaking discipline dilemmas.

We researched and analyzed the intellectual structure of the nanoparticles targeted to deliver nucleic acids, summarized the hotspots of nanoparticles for gene therapy, and identified research trends to provide clues, ideas, and information for researchers and decision-makers interested in this field.

The data were retrieved from the Web of Science Core Collection (SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI, CCR-EXPANDED, and IC) with Retrieval Strategy 1 (see the Retrieval Strategy 1 section at the end of article) and dated from 1 January 2011 to 29 August 2021. A total of 1,232 full records and cited references were exported to CiteSpace 5.8.R2 (64-bit) to remove the duplicates, editorials, and proceedings papers; only 1,221 articles and reviews remained for further analysis according to the CiteSpace manual (Chen, 2014). Time slicing was performed from January 2011 to December 2021 for 1 year per slice, which meant that the data were sliced by year from 2011 to 2021 to generate 11 networks. The top 50 most frequently cited or occurring items were selected each year, the Pathfinder Algorithm was used to prune unnecessary links, then the 11 pruned networks were merged into a final network (Chen and Morris, 2003). The networks were viewed in CiteSpace, and the network information was exported to Microsoft Excel 2019 or other software when necessary. Modularity was used to evaluate the quality of the networks. Considering that a network contains several communities (clusters), modularity investigates the connection between them. High modularity means that the communities are well distinguished from one another (Chen, 2012). The modularity (Q) of an exemplary network varies from 0.3 to 0.7 or higher (Newman and Girvan, 2004).

A crucial characteristic to discover the landmarks of a network in VOSviewer is high density, which depends on the quantity and quality of the neighboring nodes (van Eck, 2021). This algorithm detects hub nodes, namely, keywords those co-occurred with more different words. As shown in one of the high-density cores in Figure 2, the low transfection efficiency of the nanoparticle-targeted delivery systems has puzzled scientists for a long time (Wilhelm et al., 2016; Chernousova and Epple, 2017). Although no nanoparticles have been presented as a desirable solution for clinical use even to date, several delivery systems are undergoing phase II/III clinical trials, and the SVA of our study has also revealed efforts on the modifications based on polycations, polymers, gold nanoparticles, and lipids regarding the delivery efficiency of siRNA and pDNA (Xue et al., 2013; Ganbold et al., 2017; Herrera et al., 2018; Kwon et al., 2020; Pedziwiatr-Werbicka et al., 2021).

The factors those form an efficient transfection include but are not limited to high stability in circulation, easy escape from endosomes, and rapid release of the cargo (into the nucleus or cytoplasm). The high positive charge density of the polycations promises their affinity to nucleic acids, allows relative success in the endosomal escape likely through the proton sponge effect, but also leads to poor stability for interacting with the serum components and cytotoxicity. Our SVA result highlighted the research in modifying the cationic nano vectors by crosslinking the primary amines of branched polyethylenimine using dimethyl suberimidate. The primary amines were then converted to amidine functions, which were supposed to imitate the arginine-rich motifs of the protein transduction domain to improve internalization efficiency, disperse the charge to reduce toxicity, and expedite intracellular release. The hydrophobicity of the C-8 linker also formed a synergetic membrane penetration effect. All of these possible mechanisms were adequately embodied in the improvement of transfection efficiency both in vivo and in vitro and the shift of safety in contrast to the native branched polyethylenimine and commercial reagents for transfection (Tripathi et al., 2013).

For the electrically neutral polymers, the clearance effect of the negatively charged glomerular basement membrane and aggregation caused by charged proteins in the blood were no longer the main concerning issues, but slow unpacking of cargo and entrapment in the endosomes made them uncompetitive (Yin et al., 2014). The SVA also detected several remodels in such nanoparticles, typically, the peptide spiders presented with a high MCR (Table 2). The polyethylene glycol (PEG) acted as an octo-valent backbone and was functionalized by the tumor-targeted peptide iRGD and membrane-active peptide transportan in reducible or non-reducible linkages. The hydrophilic shielding effect of PEG maintained the stability of nanocarriers, specifically binding between iRGD and α_vβ₃ integrins, an upregulated marker on neoplastic tissues, achieved an accurate delivery toward tumor cells and stroma, and transportan, of which the mechanism remained unclear, was speculated to interact with the cell surface by electrostatic/hydrophobic ions or hydrogen bonding upon their structure, hence triggering internalization via endocytosis or/and direct translocation (Kwon et al., 2020; Langel, 2021). The microscopic images presented endosomal escape of siRNA in the peptide spiders with reducible linkages intuitively, and the peptide spiders showed an efficiency of ∼50% in silencing the targeted gene, lower than commercial reagents, but successfully maintaining a higher cell viability (>80%) in vitro (Kwon et al., 2020). The peptide spiders linked with iRGD and transportan might be a solution to the PEG dilemma, and other researchers have highlighted similar modifications to PEG (Fang et al., 2011).

To further understand the mechanism of the nanoparticles delivery system, special detection methods focusing on different transfection steps are urgently needed, and there have been some exciting attempts recently (Verrneulen et al., 2018; Jiang et al., 2020; Kim et al., 2021).

The keywords tumor cell, nanotechnology, and membrane antigen constitute another core of the density map. 67.4% of the gene therapy clinical trials addresses cancer diseases as their indication ³ . Tumors feature an abnormal growth of cells, and malignant tumors are still a common cause of disease-related deaths. In order to fight cancer, patients receive surgery, radiotherapy, chemotherapy and other treatments, at the cost of aesthetic changes, systemic derangement and functional loss. Comparatively, targeted gene therapy offers a competitive choice to repair mutated genes or eliminate the influence, and the permeability and retention effect makes solid tumors a perfect target in drug delivery systems of nanoparticles (Maeda, 2012). Nanotechnology is widely used to deliver hereditary substances against serum endonucleases, immune detection, and renal clearance, and there were significant achievements in which the aptamers stood out from the others in targeting delivery (Yin et al., 2014; Pereira-Silva et al., 2020). Aptamers are oligonucleotides with specific three-dimensional structures that bind to targeted receptors (Zhou and Rossi, 2017). In the co-citation network, clusters #4 and #10 (aptamer) were close to the #16 RNA-bioconjugates (Figure 3), which indicates that the aptamers have been widely used in coupling with RNA for targeted delivery. SELEX (systematic evolution of ligands by exponential enrichment) is a technology to select high-affinity aptamers in vitro (Zhou and Rossi, 2017). Different SELEX approaches have been developed for higher aptamer specificity and a faster selection cycle (Zhang et al., 2019). In the density map, SELEX was in close quarters with the keyword membrane antigen (Figure 2). Cell-specific membrane antigens are ideal binding sites to realize the targeted delivery of the aptamer-conjugated nanoparticles, although adjustments of carriers are required to improve targeting efficiency, loading ability, the half-lifespan, and binding kinetics (Zhou and Rossi, 2011). The introduction of locked nucleic acid enhanced aptamer’s serum stability and this hybrid has been applied in research of delivering therapeutics targeting colon cancer (Roy et al., 2015a; Roy et al., 2015b).

An abnormal citation sometimes announces change in the domain of science, and unusually, it is in cluster #17 (genome editing) for mismatching in early publishing and delayed citing (Table 1). Unlike RNA, the delivery of genome editing therapeutics involves large cargo capacity, off-target toxicity, and immune reaction, and the non-virus vector might be a good answer (van Haasteren et al., 2020). Genome editing operations were greatly simplified by the targeted specificity formed from CRISPR–Cas9 (clustered regularly interspaced short palindromic repeats- CRISPR-associated protein 9) through a very short RNA coding region since its discovery in 1987. CRISPRs are repeated segments of DNA found initially in prokaryotic organisms, and the Cas proteins are endonucleases that use single guide RNA (sgRNA) to form a complementary base pair with the target DNA and then cut the DNA at a specific site (Ishino et al., 1987; Liu et al., 2017). Among them, Cas9 has been widely used because of its efficiency and simplicity (Liu et al., 2017). In recent years, the safety and efficiency shown in clinical trials reduced the concerns about gene therapy, which was sufficiently certified by citing the events of cluster #17 (Naldini, 2015). Therefore, CRISPR–Cas9 may open new avenues for cancer research and treatment, and further exploration of the nanocarriers to introduce CRISPR–Cas9 for both in vivo and in vitro gene therapy is needed.

Depending on the purpose of gene editing, CRISPR-Cas9 is used to mediate gene knockout via nonhomologous end joining, or precisely editing genes by homology-directed repair, and the requisite elements in the former situation are Cas9 protein and sgRNA, while for precise editing, a supernumerary donor template is also required (Cong et al., 2013). The cargo of this system can be: 1) pDNA that expresses both sgRNA and Cas9 protein; 2) sgRNA and mRNA of Cas9 protein; 3) sgRNA and Cas9 protein; or 4) donor DNA when necessary. The deliberate design of the nanocarriers for different loadings is critical to effective delivery and appropriate unpacking in certain subcellular localization (Liu et al., 2017).

Remarkably, in both the mean publication year (2015) and citing year (2020), our research suggested that the exosomes were likely another hotspot of nanomedicine in the targeted delivery of nucleic acids, which made cluster #1 exosomes look “young” as shown in Figure 3 (Di et al., 2018). Exosomes, a family of extracellular vesicles, with diameters ranging from 40 to 130 nm, are communicators of intercellular information. As shown in Figures 4, 5, studies related to the extracellular vesicles can be traced back to 2011 in the co-occurrence network but did not form a cluster until 2017 (Alvarez-Erviti et al., 2011). Using the exosomes to deliver siRNA has been an attractive choice for their natural ability to load, sort, and package biomacromolecules, cross physical barriers (especially the blood–brain barrier), and safety (Elsharkasy et al., 2020). Several ways to functionalize the exosomes with aptamers have been achieved to inhibit the growth of cancer cells; in addition, aptamers can also mediate selective DNA assembly on the membrane surface of the exosomes (Wan et al., 2017; Pi et al., 2018; Tran et al., 2020). As the exosomes derived from autologous breast cancer cells had a high affinity to the lungs, the exosomes’ membrane helped nanoparticles load therapeutic siRNA targeted to the pre-metastatic niche of the lungs, thus restraining the metastasis of breast cancer (Zhao et al., 2020). Despite low yield, instability, and unclear mechanism cramping the progress of translation, a series of proposals on standardized manufacture make the exosomes viable nanoparticles in nucleic acid delivery (Buschmann et al., 2021; Butreddy et al., 2021).

There are also limitations in our study. First, on account of the best performance CiteSpace, choosing the Web of Science as the only source of our research implied possible bias in the absence of literature that were only included by other databases. Besides, applying different computation models in bibliometrics may slightly affect the outcomes, although we have made our best effort to optimize software selection and interpret the results. In addition, our purpose was to detect deeply into the science domain of nanomedicine on the targeted delivering of nucleic acids. Thus, the collaboration networks were not presented in this study. In fact, defining impactive authors, institutions, and countries in this field matters a lot in allocating research finance. Furthermore, since its significant advantage in contrast to viral vector is safety, the efficiency of the nanocarrier is emphasized more in this bibliometric study based on existing materials, although effectiveness and safety share equivalent significance virtually. Last but not least, the limitation of our topic resulted in the absence of presenting research advances on the viral delivery platform in our study; in fact, experiences in translating viral vectors to the clinic in gene therapy are worth studying.

In summary, our study depicted the landscape in the scientific domain of nanoparticles targeted delivering of nucleic acids by co-occurrence and co-citation networks, where the low transfection efficiency was a major task to overcome. The SVA revealed representative modifications on polycations, polymers, gold nanoparticles, and lipids, but special detection methods for transfection are urgently needed. SELEX-enriched aptamers play an essential role in RNA targeted delivery. Specially, the co-citation analysis highlighted the exosome as a promising vector. Besides, integrating nano vectors with gene editing platforms has become an exciting research tendency. Through the above analysis, we aimed to establish a general knowledge system for biologists, chemists, and pharmacists interested in this field and offer visualized and valuable information for policy decisions to promote translations.

TS = (“Nanoparticles” OR “Nanoparticle” OR “Nanocrystalline” OR “Nanocrystalline Material” OR “Nanocrystal” OR “nanoparticles” OR “nano particle” OR “nano particles”) AND TS = (“Nucleic Acids” OR “Nucleic Acid” OR “Nucleotide” OR “Nucleotides”) AND TS = (“Targeted” OR “Targeting” OR “target”) AND TS = (“Therapeutic” OR “Therapy” OR “Therapies”).