1. Introduction
Blood is composed of multiple circulating cell populations, with its proper function depending on maintaining the correct cellular composition and functional states [ 1 ]. Blood simultaneously supports oxygen transport, immunity, and hemostasis. As such, the relevant cell types must be reliably identified and distinguished, and in some contexts, selectively targeted. This cellular diversity is not incidental; it is generated by tightly regulated hematopoiesis in the bone marrow, which produces lineages that differ in maturity, abundance, and activation state [ 2 , 3 ]. As a result, even within a single lineage, clinically meaningful phenotypes can reflect shifts in differentiation stage or cell state, rather than the appearance of an entirely new cell type. Disruption of these regulated programs alters both cell identity and function and can manifest as hematologic disease [ 4 , 5 ]. Together, the diversity and dynamic nature of blood cell populations create fundamental challenges for both diagnostic detection and therapeutic targeting.
Blood disorders and diseases describe conditions that interfere with specific proteins, receptors, and/or cellular signaling pathways [ 6 , 7 ]. These conditions can potentially disrupt the production, maturation, and function of blood elements. From a diagnostic and therapeutic perspective, many blood disorders are defined not only by genetic or molecular alterations, but also by changes in cell identity or surface marker expression. To address such conditions, a variety of strategies targeting blood cells and their microenvironment have been developed. These include small molecule inhibitors, stem cell transplantations and antibody therapies [ 8 , 9 , 10 ]. Each of the listed technologies face their own challenges, resulting in several unmet needs within the domain of blood diagnostic and therapeutics. This includes less toxic drugs, faster and less demanding diagnostic strategies, and difficulty in identifying and developing sensors for suitable surface targets [ 11 , 12 , 13 ].
Aptamers have been introduced as a unique tool to address key obstacles and unmet needs in blood diagnostics and therapeutics. Aptamers are short, single-stranded nucleic acids with defined tertiary structures that can be selected to bind molecular or cellular targets. These molecules have been explored for their ability to be highly specific and stable with reduced off-target effects while functioning in complex biological environments [ 14 , 15 ]. This review will highlight the potential of aptamers to fill existing gaps in blood diagnostics and therapeutics by showcasing their advantages and applications in this area. The review will cover relevant publications and will close with a discussion of major challenges and future perspectives for aptamer-based diagnostics and therapeutics in the context of blood and blood cell diseases.
1.1. Hematopoiesis
Hematopoiesis is a vital process that originates from hematopoietic stem cells (HSCs) in the bone marrow. Through tightly regulated differentiation programs, this process generates a wide range of blood cell populations with distinct lineage identities and functional states. As blood cells progress through differentiation, they acquire lineage- and state-specific phenotypes that are reflected in their surface marker expression. For example, leukocytes, which include monocytes, granulocytes and lymphocytes, defend the body against infection and injuries through innate and adaptive immune responses. On the other hand, erythrocytes and platelets represent additional terminally differentiated lineages with specialized biological roles (e.g., oxygen. CO 2 , and nutrient transport) [ 16 ]. All these populations arise through hierarchical differentiation pathways that generate phenotypically related but molecularly distinct cell types ( Figure 1 ). Notably, blood cells also express surface markers during differentiation, several of which have been identified. Consequently, this diversity in antigen presentation amongst different hematopoietic cells offers unique targets for diagnostics and drug development. As such, molecular targeting strategies that can exploit differences in surface marker expression, including aptamer-based approaches, are well positioned to address challenges in blood cell-specific detection and intervention.
1.2. Blood Diseases
Blood diseases, or hematologic disorders, impact blood or blood-forming tissues, disrupting the balance needed for healthy blood production and function [ 17 , 18 ]. These pathologies target specific proteins, receptors, and cellular factors. This often results in abnormal cell identity, differentiation, or abundance within the blood compartment. For example, acute leukemias, such as Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL), cause a rapid and uncontrolled proliferation of immature blood cells that overwhelm the bone marrow and crowd out healthy cells [ 19 , 20 ]. In contrast, chronic leukemias such as Chronic Myeloid Leukemia (CML) and Chronic Lymphocytic Leukemia (CLL) progress more slowly and alter immune cell composition over time [ 21 , 22 ]. Other blood cancers, including Hodgkin’s and non-Hodgkin’s lymphomas, arise from lymphocytes and spread through lymphatic tissues, while multiple myeloma affects plasma cells and compromises immune function through malignant bone marrow infiltration [ 23 , 24 ]. In addition to malignancies, inherited non-cancerous disorders such as sickle cell disease alter red blood cell morphology, reducing oxygen transport and increasing the risk of vascular occlusion [ 25 ]. Despite their diverse etiologies and clinical courses, these conditions share a common feature, namely disruption of the blood’s ability to perform its life-sustaining roles.
The biological and clinical diversity of blood disorders highlights the need for molecular tools that distinguish diseased from healthy blood cells, as well as closely related cell types and functional states within a lineage. In practice, many current treatment strategies rely on targets that are not fully specific, leading to substantial off-target effects and reduced quality of life for patients. As a result, therapeutic intervention often trades efficacy for toxicity, particularly in diseases where malignant and healthy cells share surface features. The same challenge arises in diagnostics, where the accurate identification of rare or phenotypically similar cell populations is essential for early detection and disease monitoring. Therefore, there is a need for new technologies that enable selective cell typing and detection in complex blood samples, not only between different disease types, but also among healthy blood cells for diagnostic and biosensing purposes.
1.3. Challenges in Blood Cell Targeting
Precise molecular targeting of blood cells underpins many of the most impactful modern hematologic technologies. For example, chimeric antigen receptor (CAR)-T cell therapy relies on accurate antigen selection to achieve potent anti-tumor activity, while diagnostic workflows depend on selective isolation of rare cell types from complex blood samples to improve disease detection and classification [ 26 , 27 ]. Beyond clinical settings, selective recognition of blood cell populations is also used in forensics analysis, further underscoring the broad importance of reliable cell-specific targeting [ 28 ]. Across these diverse applications, success depends critically on the ability to selectively recognize specific blood cell populations within highly heterogeneous and dynamic mixtures.
Despite the need for and importance of targeting specific cells, achieving selectivity in the blood compartment is inherently difficult. Many cell surface targets are not unique to a single diseased or healthy population, making the choice of an appropriate antigen a central and non-trivial design constraint [ 29 ]. For example, CD33, CD117, and CD123, which are upregulated in many AML patients, are also expressed on hematopoietic stem and progenitor cells, creating a substantial risk of off-target engagement without careful tuning of the targeting agent [ 30 , 31 , 32 , 33 , 34 ]. Even when a clinically validated receptor is available (for instance, CD19 for many lymphomas), the development of effective and manufacturable targeting agents against new or less-characterized antigens remains challenging [ 35 ]. Together, these factors highlight the need for alternative targeting strategies that can achieve high selectivity in complex blood environments, while minimizing off-target effects and remaining compatible with therapeutic and diagnostic deployment.
1.4. Aptamers
The word aptamer, derived from the Latin words aptus (to fit) and meros (part), describes short, single-stranded oligonucleotides that can be composed of a sequence of ribonucleic acid (RNA) or deoxyribonucleic acid (DNA) [ 36 ]. These highly versatile RNA or DNA oligonucleotides have the capacity to bind to a specific target through intermolecular interactions. This characteristic has earned them the nickname “chemical antibodies”, reflecting functional analogy rather than structural similarity, while boasting several advantages over traditional antibodies ( Table 1 ). Since their introduction in 1990 by Ellington and Szostak [ 37 ] and Tuerk and Gold [ 38 ], aptamers have drawn sustained interest for diagnostics, therapeutics and biosensing because their chemical synthesis enables large-scale production, minimal batch variability, low cost, and ease of modification [ 39 , 40 ]. Beyond these advantages, aptamers usually display low immunogenicity, and their activity can rapidly be reversed by a short complementary antidote oligonucleotide, providing on-demand control on in vitro and in vivo function [ 41 ].
Highly selective functional nucleic acid aptamers can be generated against a broad spectrum of targets from ions and small molecules to proteins and whole cells [ 50 , 51 , 52 , 53 ]. In the field of hematology, numerous aptamers have been selected to recognize surface markers on leukemias and other blood cells, and aptamer–antidote pairs have progressed to clinical trials for coagulation targets illustrating their technical feasibility in blood-related applications [ 54 , 55 ]. Collectively, these properties position aptamers as versatile recognition elements that are well suited for precision therapies and diagnostics.
Several recent reviews have surveyed aptamer applications in hematology, particularly focusing on diagnostics for specific blood cancers, coagulation-related protein targets, or platform-centric biosensing technologies [ 54 , 56 , 57 , 58 , 59 ]. While these studies provide valuable coverage of these domains, they do not address a complementary question, namely how aptamers are being used as targeting reagents for distinct blood cell types, lineages, and functional states. As such, here we present a cell-centric perspective organized around hematopoiesis. Rather than cataloging disease-specific assays or sensing platforms, we focus on aptamers as molecular tools for recognizing and manipulating blood cells across lineages and states, in both healthy and diseased contexts, and use this organization to highlight systematic biases, gaps in coverage, and underexploited opportunities in the current literature.
2. Overview and Key Innovations of SELEX
Currently, aptamer discovery relies almost exclusively on in vitro selection strategies called SELEX (Systematic Evolution of Ligands by EXponential enrichment), which can enrich selected aptamers not only for tight binding affinity, but also target specificity, stability, and suitability for downstream applications [ 60 , 61 , 62 ]. In the context of blood cell targeting, the choice of SELEX methodology is particularly consequential due to the complexity of cell surface architectures, the presence of post-translational modifications, and the challenges associated with validating function in physiologically relevant environments. As a result, adaptations of classical SELEX, including cell-based and in vivo selection strategies, help address the unique constraints of hematologic targets.
2.1. Classical, Cell-Based, and In Vivo SELEX Strategies
In its classical implementation, SELEX is performed against purified molecular targets, with successive rounds of binding, partitioning, amplification, and enrichment used to isolate sequences with measurable affinity and specificity ( Figure 2 ). Although this approach has been widely applied across many target classes, it remains labor-intensive and exhibits a relatively low overall success rate, estimated at approximately 30% [ 63 , 64 ]. These limitations are particularly relevant for blood cell targets, where selections against isolated recombinant proteins often fail to recapitulate the conformational complexity, multimeric organization, and post-translational modifications present on native cell surfaces [ 61 , 65 , 66 ].
To address these constraints, Cell-SELEX enables selection directly against intact, live cells, thereby preserving membrane context, receptor conformation, and glycosylation patterns [ 60 , 61 ]. Importantly, this strategy removes the requirement for prior target identification and has proven especially valuable in hematologic and malignant systems, where suitable surface markers may be difficult to predict [ 65 , 67 ]. An illustrative example is provided by Daniels et al. (2003) in which aptamers selected against a glioma cell line were subsequently shown to bind tenascin-C following affinity-based target identification [ 68 ]. Such studies demonstrate how Cell-SELEX can support both ligand discovery and post hoc identification of relevant molecular targets in complex cellular environments. However, Cell-SELEX, and other in vitro SELEX methodologies, do not fully consider the complex environments in blood, and can lead to poor in vivo functionality.
A related adaptation of Cell-SELEX is ligand-guided selection (LIGS), in which a known high-affinity ligand (e.g., antibody or natural receptor ligand) is used to competitively displace aptamers binding to a specific epitope during selection [ 69 ]. This approach enables enrichment of aptamers directed toward predefined cell-surface targets without requiring prior purification of the protein, thereby combining aspects of classical and cell-based SELEX. LIGS can improve target specificity and facilitate epitope-level selection in complex cellular environments, which may be advantageous for hematologic targets with closely related family members [ 70 ]. However, LIGS requires the availability of a well-characterized competing ligand and may bias selection toward epitopes overlapping with that ligand, potentially limiting discovery of novel binding sites.
Beyond in vitro approaches, in vivo SELEX introduces aptamer libraries directly into living organisms, allowing selection to occur under physiological conditions that incorporate circulation, tissue access, and biological clearance [ 71 ]. Through iterative cycles of administration, recovery, and PCR amplification, aptamers can be enriched against target tissues or circulating cells without prior knowledge of the molecular target. Although this method requires stabilizing modifications (e.g., 2′-fluoro or 2′-O-methyl modifications discussed in Section 2.2 .) and must contend with rapid renal clearance, these constraints can enrich for sequences with favorable pharmacokinetic properties [ 71 , 72 ]. Importantly, this approach enables identification of aptamers that retain function in complex biological environments, which partially addresses the gap between in vitro binding and in vivo performance that remains common in blood cell-targeting studies [ 73 ]. Despite these notable advantages, in vivo SELEX is rarely used due to its limitations, such as extended selection times, labour intensive, low success rate, and the complexity of utilizing live animal subjects.
2.2. Limitations in SELEX for Blood Cell Targeting
The SELEX methodologies (classical, cell, and to a lesser extent in vivo) have been used to generate numerous aptamers across the literature that bind to blood cells [ 54 , 74 ]. However, across these approaches, consistent challenges remain in translating initial binders into robust tools suitable for diagnostic or therapeutic use. In particular, many reported aptamers are characterized primarily under simplified in vitro conditions, with limited evaluation of specificity, stability, or clearance in complex matrices [ 75 ]. For example, characterization of aptamers in complex serum or whole blood and clearance properties is often lacking. Furthermore, the reliance on unmodified DNA or 2′-modified RNA without exploring additional options has greatly limited the exploration of backbone diversity.
In practice, chemical modifications are frequently required when aptamers are intended for use in serum, whole blood, or in vivo settings. Unmodified RNA aptamers are particularly susceptible to rapid nuclease degradation, often limiting their functional half-life to minutes in biological fluids [ 76 ], whereas DNA aptamers exhibit greater intrinsic stability, but remain vulnerable to endonucleases and rapid renal clearance due to their small size [ 76 , 77 ]. Consequently, a range of chemical strategies have been employed, including 2′-fluoro or 2′-O-methyl substitutions, locked nucleic acid (LNA) incorporation, phosphorothioate (PS) backbone modifications, and molecular weight extension approaches such as PEGylation or albumin-binding conjugates [ 78 , 79 , 80 ]. Importantly, not all modifications are introduced solely to increase nuclease resistance; some are intended to prolong circulation time, enhance binding affinity, modulate structural rigidity, or reduce immunogenicity. As highlighted in Table 2 , the extent and type of modification vary considerably depending on the intended application, and while certain clinical candidates require extensive stabilization, others used in short-term or ex vivo applications may function adequately with minimal modification. Thus, the necessity and degree of chemical modification remain context-dependent rather than universally required.
Moreover, there continues to be challenges in standardization in aptamer literature featuring SELEX, with many past publications lacking detailed information on the sequence, modifications, and validation [ 75 , 81 , 82 ]. As a result, much of the field remains focused on the identification of aptamer “hits” or using a small selection of existing aptamers, rather than the development of well-characterized “leads”. Future work that incorporates improved validation strategies, expanded chemical diversity, and greater methodological transparency into SELEX workflows could improve the speed and reliability of discovering not only aptamer “hits”, but also moving towards aptamer “leads”.
Implementing in silico designs into SELEX (i.e., machine learning and predictive modeling) may also be a valuable avenue to explore in guiding library design to improve the success rate [ 83 ]. However, current computational approaches remain limited. Most structural prediction tools were developed for RNA and do not reliably capture the folding behavior of DNA aptamers, and platforms such as AlphaFold are not yet optimized for predicting aptamer–target interactions. In addition, molecular dynamics simulations are often conducted on nanosecond to microsecond timescales, which may be insufficient to fully sample the conformational flexibility of nucleic acid structures. As such, computational methods should not be viewed as replacements for experimental SELEX. Rather, their current potential value lies in narrowing sequence space, biasing initial library composition, and prioritizing candidates for experimental validation. As larger and more diverse datasets become available, predictive performance may improve, but at present these approaches remain complementary to empirical selection strategies rather than superior to them.
Table 2
Examples of reported aptamers targeting blood cell populations: targets, affinities, chemical composition, and sequences. Where applicable, truncated aptamer characterizations were prioritized.
a Functional validation and biological context (e.g., cell line binding, primary patient samples, in vivo models, or diagnostic assay format) are described in the cited primary reports. b Original SELEX paper for the aptamer. c N/A indicates that there was no information on the K D , sequence, or disease from the reference. d Blood cancers include B-ALL, T-ALL, AML, and MM, as well as additional types of leukemia and lymphoma. e Aptamer was discovered for CD30 while selecting for RANK targeting aptamers.
| Example Target | a Reported K D , Measurement Method, and Reference | Relevant Disease | Type | Sequence (5′ → 3′) |
| A1 | 29.5 pM [ 84 ] b , flow cytometry | N/A c | DNA | CATCCATGGGAATTCGTCGACCCGGGCCTGACAACCTTTACACCTTCTCGAGAAGGTGTCTTCCTAAGCTCGATCTCG |
| AML1 | 0.99 ± 0.02 nM [ 85 ] b , SPR, truncation | Leukemia | RNA | GGGAUGGACGACCCACCACGGCGAGGUAUCCCAUCCCA |
| 3.5 ± 0.4 nM [ 86 ] b , SPR, truncation | AML | RNA | GGACCCUGCCACGAUAGCGGCGCGGGAAGUAAAGUAUACACCUAACGGUCCA | |
| BAFF-R | 47.1 ± 7.6 nM [ 87 ] b , gel shift assay | Lymphoma | RNA, 2’fluoro-pyrimidine | GGGAGGACGAUGCGGGAGGCUCAACAAUGAUAGAGCCCGCAAUGUUGAUAGUUGUGCCCAGUCUGCAGACGACUCGCCCGA |
| BCMA | 79.4 nM [ 88 ] b , qRT-PCR, truncation | MM | RNA, 2’fluoro-pyrimidine | AGUGCAAGACGUUCGCAGAUUAGCGAAAAGAGGGUCUCAUUGACUAGUAC |
| CCR5 | 31.3 nM, [ 89 ] b , gel shift assay, truncation | HIV | RNA, 2’fluoro-pyrimidine | GGGAGACAAGACUAGACGCUCAAUGUGGGCCACGCCCGAUUUUACGCUUUUACCCGCACGCGAUUGGUUUGUUUCCC |
| 110 nM [ 90 ] b , flow cytometry | AML | RNA, 2’fluoro-pyrimidine | GGGAGGACGATGCGGGCCUUCGUUUGUUUCGUCCAAGACGACTCGCCCGA | |
| CD3ε | 3 nM [ 91 ] b , flow cytometry, truncation | N/A c | DNA | GCCGCGGGGTGGGTCTAGTGTGGATGTTTAGGGGGCGGC |
| 0.3 nM [ 79 ], flow cytometry, dimer | N/A c | DNA, LNA, 2′-OMe, PEG-linker | ‘+A+GCCGCGGGGTGGGTCTAGTGTGGATGTTTAGGGGGCGGCmUmT- (C42H61N2O10P)4- +A+GCCGCGGGGTGGGTCTAGTGTGGATGTTTAGGGGGCGGCmUmT | |
| 135 nM [ 92 ], flow cytometry | N/A c | DNA, PEG-linker | TGGGCGGGGTGGGTCTAGTGTGGATGTTTAGGGGGCCCA | |
| CD3 (murine) | 37.9 nM [ 93 ] b , SPR | Blood cancer d | RNA, 2’fluoro-pyrimidine | CCTTGCCTGCTTTCACGTGTGATCCCTGCCCGT |
| CD4 | N/A c [ 94 ] | HIV | DNA | GTGACGTCCTGATCGATTGTGCATTCGGTGTGACGATCT |
| 1.59 nM [ 95 ] b , flow cytometry | HIV | DNA | ATCCAGAGTGACGCAGCACCACCACCGTACAATTCGCTTTCTTTTTTCATTACCTACTCTGGC | |
| 2.9 nM [ 96 ] b , qPCR | N/A c | DNA | GCCTGTTGTGAGCCTCCTAACGATGTCGACGTGCAGCTTCCTTGAGCCTTACTGAAAATACTACCCAGTCCATGCTTATTCTTGTCTCCC | |
| CD8 | 10.59 nM [ 97 ] b , flow cytometry | Stevens–Johnson syndrome | DNA | ACGCTCGGATGCCACTACAGCTTGCTATGCTCCCCTTGGGGTACGTAACGATGTCGACGACTCATGGACGTGCTGGTGAC |
| 1.9 nM [ 14 ] b , flow cytometry | Blood cancer d | DNA | ATCCAGAGTGACGCAGCAACAGAGGTGTAGAAGTACACGTGAACAAGCTTGAAATTGTCTCTGACAGAGGACTAAGCCACCGTGTCCA | |
| CD16α | 45 ± 28 nM [ 98 ] b , dot blot, truncation | Blood cancer d | DNA, 15-deoxyadenosine linker, PEG | CACTGCGGGGGTCTATACGTGAGGAAGAAGTGGGCAGGTC |
| CD19 | 85.4 nM [ 99 ] b , flow cytometry | Lymphoma | DNA | TGCGTGTGTAGTGTGTCTGTTCTCCTTTTTTTGGTTGCTGCTCTTAGGGATTTGGGCGG |
| N/A c [ 100 ] b | ALL | DNA, RNA | RNA: UUGAAACUGUAAGGUGGC DNA: TTGAAACTGTAAGGTGGC | |
| 49.9 ± 13 nM [ 101 ] b , BLI, truncation | B-cell neoplasms | RNA, 2’fluoro-pyrimidine | UGAGCCCUGUUCGACAGGAGGCUCA | |
| CD20 | 96.91 nM [ 102 ] b , flow cytometry | Lymphoma | DNA | ATACCAGCTTATTCAATTGGAATAAGGGGGTATTACTGTCTGGTAAACAAACGCTATGCGAGGGGATTCAAGATAGTAAGTGCAATCT |
| CD22 | N/A c [ 103 ] b | B-ALL | RNA, 2’fluoro-pyrimidine | GGGAGGACGAUGCGGGCCAUUCGUCUUUUCGUCCCCAGACGACUCGCCCGA |
| CD28 (murine) | 40 nM [ 104 ] b , filter binding assay, dimer | N/A c | RNA, 2’fluoro-pyrimidine | CAGAGACTTCCAAAATAAAAGACTCCTGAAAGTTGCAAAATAAAAAACTC |
| CD30 | 0.11 Nm e [ 105 ] b , SPR | Blood cancers d | RNA, 2’fluoro-pyrimidine | N/A c |
| 50 nM [ 106 ] b , flow cytometry | Lymphoma | DNA | TACCAGTGCGATGCTCAG ACTGGGCGAAACAAGTCTATTGACTATGAGCCTGACGCATTCGGTTGAC | |
| CD33 | 43 nM [ 107 ] b , flow cytometry | AML | DNA | TACCAGTGCGATGCTCAGCACGCTTATAGGGGCTGGACAAAATTCTACCCAGCCTTTTCTGACGCATTCGGTTGAC |
| CD33/CD34 | N/A c [ 108 ] | AML | DNA | N/a c |
| CD38 | 50.03 nM [ 109 ] b , flow cytometry, truncation | MM | DNA | TCCAGAGTGACGCAGCAGCCAACGTGCTTTCTACCTTATTTTCCGTCACTCTCACTCTGGA |
| 4.8 ± 0.2 nM [ 110 ] b , SPR, truncation | MM | DNA | AGGCGCCCAACCTCCTTTAGTGTCAAGGCAGGGGAAACAAGTCTGGCTTAGGGTGT | |
| CD44 | 187.0 ± 30.6 nM [ 111 ] b , filter binding assay | Blood cancer d | DNA, PS | GAGATTCATCACGCGCATAGTCTTGGGACGGTGTTAAACGAAAGGGGACGACCGACTATGCGATGATGTCTTC |
| 81.3 nM [ 78 ] b , fluorescence | Blood cancer d | RNA, 2’fluoro-pyrimidine, 2′-OMe | GGGAUGGAUCCAAGCUUACUGGCAUCUGGAUUUGCGCGUGCCAGAAUAAAGAGUAUAACGUGUGAAUGGGAAGCUUCGAUAGGAAUUCGG | |
| 238 ± 9 nM [ 112 ] b , MST, truncation | Blood cancer d | DNA | CATGCTTCCCCAGGGAGATGACCGGGCGTACACCGTCGCGGCACATGTCTGAATGCGTTTAGTCTCTGTG | |
| 14.54 nM [ 113 ] b , flow cytometry, truncation | Blood cancer d | DNA | GGGACGCTGAACACTATCATGGGGTGCTATCTCTCTTGGT | |
| 55.5 ± 13.4 nM [ 114 ] | Blood cancer d | DNA, PS | TTAAGATCXGXTAGGGAACCAAGACGACAG | |
| CD71 | 55.02 ± 0.4 nM [ 115 ] b , flow cytometry, truncation | Blood cancer d | DNA | ACTCATAGGGTTAGGGGCTGCTGGCCAGATACTCAGATGGTAGGGTTACTATGAGC |
| 35.2 ± 23.79 nM [ 116 ] b , flow cytometry, toehold | Lymphoma | DNA | GGAGTCACACGCATTAGCGTAAAGGGGGTGTTTGTGCGGTGTGGAGTGCGCGTGCTAATGCTGGAGTGTTTCCCAGGACCC | |
| CD117 | 7.14 nM [ 117 ] b , flow cytometry, truncation | AML | DNA | GGGGCCGGGGCAAGGGGGGGGTACCGTGGTAGGAC |
| 11.75 ± 1.30 nM [ 118 ] b , flow cytometry, truncation | AML | DNA | TCCAGTGACGCAGCATCGAGCGGGGGACCCTATTAGCTGAATGAGATGCAATTACAAGCGTGGACACTGGC | |
| 21.8 nM [ 119 ] b , BLI | AML | DNA | N/A c | |
| CD123 | 29.41 nM [ 52 ] b , flow cytometry | AML | DNA | TGCGTGTGTACTGTGTCTGGTCCCGTAGCTACTAGCGAACTCCCTGCCTCTTAGGGATTTGGGCGG |
| 39.1 nM [ 80 ], flow cytometry | AML | DNA, PS | TGCGTGTGTACTGTGTCTGGTCCCGTAGCTACTAGCGAACTCCCTGCCTCTTAGGGATTTGGGCGG | |
| CD371 | 15.5 nM [ 120 ] b , SPR | AML | DNA | ATTACCAGGGACCGAAGGCAAAACTATGATCGGTGG |
| CTLA-4 | 10 nM [ 121 ] b , double-filter binding assay, truncation | Blood cancer d | RNA, 2’fluoro-pyrimidine | CCGACGTGCCGCAACTTCAACCCTGCACAACCAATCCGCC |
| 11.84 nM [ 122 ] b , flow cytometry | Blood cancer d | DNA | TCCCTACGGCGCTAACGATGGTGAAAATGGGCCTAGGGTGGACGGTGCCACCGTGCTACAAC | |
| DC-SIGN | 21.73 nM [ 123 ] b , LSC | N/A c | DNA | GGCGAAAATTTGTGGATATAGAGGGTTACTCGGAT |
| M0- and M2-like macrophages | 22.81 ± 5.6 nM (M0) and 44.12 ± 8.0 nM (M2) [ 51 ] b , flow cytometry | Blood cancer d | DNA | GAAGAGTAGATGAAACGTTTTTTCGCCCGATAAAAGGGACGTGCGTCAGACA |
| mIgM | N/A c [ 124 ] b | Burkitt’s lymphoma | DNA, 5′-iodo-deoxyuridine, PEG, disulfide bond | ACCGGGAGGATAGTTCGGTGGCTGTTCAGGGTCTCCTCCCGGTG |
| 359 nM [ 125 ], flow cytometry, multimers | Burkitt’s lymphoma | DNA, 5′-iodo-deoxyuridine, LNA, 2′-OMe, PEG | ACCGTGGAGGATAGTTCGGTGGCTGTTCAGGGTCTCCTCCACGGT | |
| N/A c [ 69 ] b , flow cytometry | Burkitt’s lymphoma | DNA | N/A c | |
| MLL-AF9 | 37.5 ± 2.5 nM [ 60 ] b , flow cytometry | AML | DNA | TAGGGAAGAGAAGGACATATGATCGCACACTATTAGAGTGTACGCATGATACATTGACTAGTACATGACCACTTGA |
| Nucleated red blood cells (NRBC) | 38.30 ± 4.99 nM [ 126 ] b , flow cytometry, truncation | Prenatal diagnostics | DNA | GCCAAATACCGGTCTGTCGGTGGGTATTGTGGACACTCTGGC |
| Nucleolin | N/A c [ 127 ] b | Blood cancer d | DNA | TTTGGTGGTGGTGGTTGTGGTGGTGGTGG |
| OFA/iLRP | 101.25 nM [ 128 ] b , flow cytometry | AML | DNA | TGCGTGTGTAGTGTGTCTGTTGTTTGTATTGTTGTCTATCCTCTTAGGGATTTGGGCGG |
| N/A c [ 129 ], truncation | AML | DNA | TTGTTTGTATTGTTGTCTATCCTCTTAGGGATT | |
| Red blood cell (RBC) | N/A c [ 28 ] b | Forensics | DNA | ATCCAGAGTGACGCAGCACGGGTTGGGGCTGGTTGTGTGTTGTTTTTTTGGCTGTATGTGGACACGGTGGCTTAGT |
| RhD | 580.5 ± 142.0 nM [ 130 ] b , flow cytometry | Hemolytic anemia | DNA | GGCCTGGTCTGTTAGCCGGGTAGCAGCCCCGGCACCTATT |
| Siglec-5 | 2.77 nM [ 131 ] b , flow cytometry | AML | DNA | GACGCTTACTCAGGTGTGACTCGGTACGCCGCAAGACGAGTTGTGTATAAGCCGGCCGAAGGACGCAGATGAAGTCTC |
3. Aptamers Targeting Blood Cell Types
Most existing reviews of aptamers in hematology organize the literature around diseases, assay formats, or technological platforms. Here, we instead organize the field explicitly around blood cell types and hematopoietic lineages. This framing reflects the fact that many of the central challenges in blood targeting are biological rather than technological, in particular the difficulty of distinguishing closely related cell types, differentiation stages, and functional states within a highly dynamic system. Accordingly, in this section we survey reported aptamers by lineage (B cells, T cells, NK cells, and red blood cells). We use Table 2 as a reference point, and analyze patterns in target selection, chemical composition, and intended application. This organization makes visible both the uneven distribution of aptamer targets across hematopoiesis and the implicit assumptions that have guided target choice, while highlighting underexplored cell types and functional states that represent opportunities for future development.
3.1. B Cells
B cells are central to humoral immunity, differentiating into plasma cells that secrete antibodies and regulate adaptive responses [ 132 ]. Their relatively well-defined lineage markers and established clinical relevance have made B cells one of the most frequently targeted blood cell types for aptamer development. Accordingly, most reported B-cell aptamers focus on a small set of surface receptors that are already validated in antibody-based diagnostics and therapies [ 133 , 134 ]. This concentration reflects both the accessibility of these targets and a broader tendency to prioritize diseased or malignant B-cell populations over healthy counterparts.
Among reported targets, the bulk of aptamers have been selected against the CD19 receptor. CD19 is a well-known marker for B-cell lineages, but cannot be used to distinguish between healthy and malignant B cells [ 101 ]. To date, major efforts in B-cell aptamer development have concentrated on a small number of clinically established targets rather than expanding into less-characterized surface markers. As summarized in Table 2 , CD19-targeting aptamers span both DNA- and RNA-based chemistries, with reported affinities generally in the nanomolar range. Despite this volume of work, relatively few studies interrogate how aptamer sequence, chemistry, or structure relate to binding performance at the molecular level. Danquah et al. sought to address this limitation by combining aptamer selection with computational modeling to examine predicted interactions between an RNA aptamer and CD19 [ 100 ]. In that study, modeling was used to rationalize an observed improvement in binding affinity upon conversion of the RNA aptamer to a DNA format. Although there is precedent for successful RNA-to-DNA conversion in select aptamers [ 77 , 135 ], such outcomes are not broadly generalizable and likely depend on preservation of key structural motifs rather than simple backbone substitution. However, the proposed binding mechanism was not directly validated experimentally, underscoring a broader limitation in the field, namely the scarcity of structure–function analyses that link aptamer design choices to binding behavior [ 136 ].
Beyond CD19, a smaller set of aptamers has been reported against additional B-cell surface receptors, but this landscape remains narrow and conservative. These targets include B-cell maturation antigen (BCMA), CD20, CD22, B-cell activating factor receptor (BAFF-R), and components of the B-cell receptor (BCR) (see Table 2 ). Notably, the series of studies targeting the membrane-bound B-cell receptor complex stand out as one of the clearest demonstrations of true cell-SELEX against a native, multi-component immune receptor. Moreover, it provides a rare example of aptamer selection guided by biologically grounded receptor architecture rather than by convenience targets. Compared to CD19, aptamers against these targets are fewer in number, despite their established relevance in both normal B-cell biology and B-cell malignancies. Notably, most reported aptamers targeting these receptors exhibit nanomolar affinities and include minimal chemical modifications, reflecting a conservative design space similar to that observed for leukemia-associated targets more broadly. Currently, much of the work on B-cell aptamers has remained focused on therapeutics for diseased lineages. By contrast, aptamer development targeting healthy B cells remains limited, despite their potential utility in biosensing, immune profiling, and diagnostic applications. As a result, most B-cell aptamers have effectively been evaluated in roles closely analogous to antibody reagents, rather than as probes of more subtle distinctions in B-cell state, differentiation, or function. Expanding aptamer selection toward healthy B-cell populations could therefore enable new tools for monitoring immune status and cell composition, while reducing reliance on disease-specific selection paradigms.
3.2. T Cells
T cells are central to adaptive immunity, orchestrating cellular responses through distinct subpopulations. Helper (CD4 + ) T cells engage MHC-II on antigen-presenting cells to recruit and regulate immune effectors, while cytotoxic (CD8 + ) T cells recognize MHC-I and directly kill target cells [ 137 , 138 ]. Because of their central role in immune regulation and their widespread use in immunotherapy, T cells have been a major focus of aptamer development among healthy blood cell populations. Accordingly, reported T-cell aptamers span a broader range of intended applications than those developed for B cells, including cell capture, activation, and targeted delivery (see Table 2 ).
The CD3 receptor, expressed on all T-cell subsets, is a core component of the T-cell receptor (TCR) complex and has been widely studied in SELEX experiments [ 139 ]. However, much of the existing literature has focused on improving binding performance or chemical stability of CD3 aptamers rather than demonstrating functional utility in biologically relevant settings [ 79 ]. Co-stimulatory activation of CD3 and CD28 receptors leads to T cell activation, and a paper by Pastor et al. explored this by designing an anti-CD28 aptamer and found successful activation of T cells [ 104 ]. In that study, however, CD3 engagement relied on an antibody reagent, and the CD28 aptamer was specific to murine targets, limiting direct translational relevance. This highlights a recurring pattern in the T-cell aptamer literature, in which proof-of-concept activity is demonstrated, but integration into fully aptamer-based or human-relevant systems remains incomplete.
Beyond CD3, most T-cell aptamer work has focused on lineage-defining receptors such as CD4 and CD8, a strategy that prioritizes cell-type identification over functional state resolution (see Table 2 ). Unlike B cells, much of the literature has produced aptamers for healthy T cells, and the intended applications have ranged from drug delivery to specific cell capture. Nevertheless, most of these aptamers do not discriminate between functional T-cell states, such as resting, activated, exhausted, or memory phenotypes, nor do they distinguish closely related subpopulations within the CD4 + or CD8 + compartments. Hence, most reported T-cell aptamers distinguish cell types more readily than they distinguish cell states. As a result, aptamer-based tools for dynamic immune monitoring remain underdeveloped. Future work in this area could help to improve in situ biosensing, immune profiling, and diagnostic applications, particularly in contexts requiring longitudinal monitoring of patient immune status, and take advantage of aptamers’ desirable characteristics, including low immunogenicity, reversibility, and chemical tunability.
3.3. Natural Killer (NK) Cells
NK cells are innate lymphoid cells comprising roughly 2% of circulating lymphocytes and function in antiviral and antitumor immunity via cytokine release and cytotoxicity [ 140 , 141 ]. Unlike T cells, NK cells lack CD3, and their effector activity is determined primarily by CD16 and CD56 expression [ 142 ]. Differences in CD16 and CD56 expression define functionally distinct NK-cell subsets with high-CD56 and low-CD16 cells mediating cytokine secretion, but not cytotoxicity. Meanwhile, low-CD56 and high-CD16 cells, which represent approximately 90% of circulating NK cells, mediate both cytotoxicity and cytokine release. Despite growing interest in NK cells for immunotherapy, including CAR-NK strategies, aptamer development targeting NK-cell receptors remains extremely limited.
As summarized in Table 2 , only a small number of aptamers have been reported for NK-cell-associated targets, including a single aptamer against CD16 and none directed toward CD56 as of writing [ 98 ]. This limited coverage contrasts sharply with the clinical importance of NK cells and reflects a broader underrepresentation of innate immune lineages in aptamer discovery efforts. An illustrative example of functional adaptation is provided by an anti-CD30 aptamer initially selected by Parekh et al. and later repurposed by Yang et al. for NK-cell-mediated targeting [ 106 , 143 ]. In this approach, the aptamer was displayed on the surface of NK cells to direct cytotoxic activity toward CD30-positive cancer cells, functioning as a modular alternative to conventional CAR constructs. While challenges remain, including aptamer stability, surface persistence, and in vivo durability, this strategy highlights the potential of aptamers to enable reversible and tunable NK-cell targeting, offering conceptual advantages over permanent genetic modification.
Despite these proof-of-concept demonstrations, aptamer selection against healthy NK cells and NK-cell-specific functional states remains largely unexplored. This appears to reflect not a lack of biological relevance, but rather potentially a tendency to prioritize targets that are already embedded in established therapeutic and diagnostic pipelines. Expanding aptamer discovery toward NK-cell subsets and activation states could enable new diagnostic, biosensing, and therapeutic strategies, particularly in settings where reversible or transient targeting is desirable. The scarcity of NK-cell aptamers therefore represents both a limitation of the current literature and a clear opportunity for future development.
3.4. Red Blood Cells (RBCs)
RBCs are responsible for oxygen transport and play roles in a variety of diseases, including malaria, sickle cell anemia, and sepsis [ 16 , 144 , 145 , 146 ]. Unlike lymphoid cells, RBCs lack nuclei and have limited surface protein diversity, which constrains the number of accessible molecular targets for selective recognition. As a result, aptamer development targeting RBCs has been far more limited than for immune cell lineages and has focused primarily on therapeutic modulation and diagnostic applications rather than immune regulation.
As summarized in Table 2 , only a small number of publications report aptamers that directly target RBC-associated antigens. Most of these efforts have centered on clinically established blood group antigens, including the A and B antigens and the Rhesus (Rh) factor, which play central roles in transfusion compatibility. In particular, DNA aptamers have been developed to bind the RhD antigen and sterically mask RhD epitopes on RhD + RBCs, thereby reducing recognition by alloanti-RhD antibodies [ 130 ]. This strategy illustrates a distinct advantage of aptamers over antibody-based approaches, namely the ability to reversibly modulate immune recognition without permanent alteration of the cell surface.
Beyond blood group antigens, aptamer selection against RBCs has also been explored for forensic identification and prenatal diagnostics, including targeting nucleated red blood cells (NRBCs) ( Table 2 ). Overall, however, target selection in this area appears to have been shaped primarily by practical considerations related to transfusion compatibility and cell identity, rather than by broader exploration of functional or pathological surface features. This focus is understandable given the limited surface proteome of mature RBCs, but it has also meant that aptamer development remains concentrated on a small number of canonical antigens. Expanding aptamer discovery toward additional RBC-associated targets or functional states could enable new diagnostic and transfusion-related applications, particularly where temporary and reversible modulation of RBC recognition is desirable.
3.5. Integrative Perspective
Collectively, publications across B cells, T cells, NK cells, and RBCs illustrate the conceptual versatility of aptamers across diverse hematologic contexts, spanning immune modulation, diagnostics, biosensing, and therapeutic targeting. However, analysis of reported aptamers reveals clear and recurring biases in cell type selection and application focus. As summarized in Table 2 , the majority of aptamers have been developed against diseased or malignant blood cell populations, with comparatively fewer efforts directed toward healthy cells or physiologically relevant cell states. While many of the targets listed can also be present on healthy cells (e.g., CD3 or CD19), existing aptamers are often optimized under disease-specific or non-physiological conditions, making adaptation to alternative contexts challenging [ 75 ]. This limitation is compounded by a general lack of structure–function insight across the aptamer literature. There are currently only a handful of studies that systematically examine how sequence, chemistry, or folding relate to target engagement under biologically relevant conditions [ 147 , 148 ]. As a result, repurposing existing aptamers frequently requires compromise in binding performance or experimental design, rather than rational optimization. Greater integration of structural characterization and functional validation could reduce reliance on repeated, labor-intensive SELEX campaigns, particularly for applications involving healthy blood cells where target epitopes are conserved rather than mutated.
Furthermore, aptamer development has remained heavily skewed toward lymphoid lineages, particularly B and T cells, while innate and non-immune blood cell populations remain underrepresented. Although some studies have explored myeloid targets, these efforts have largely focused on diseased cells, leaving healthy myeloid populations, NK-cell subsets, and RBC-associated targets comparatively unexplored ( Table 2 ). Given the favourable properties of aptamers for reversible binding, low immunogenicity, and chemical tunability, expanding aptamer discovery toward healthy blood cells and functional cell states represents a significant opportunity. Such efforts could enable new tools for immune monitoring, diagnostics, and biosensing that leverage the dynamic and heterogeneous nature of blood rather than treating it solely as a disease target.
4. Applications
The application landscape for blood cell-targeting aptamers reflects both the conceptual strengths of aptamers and the current limitations in their development. In principle, aptamers offer capabilities that are difficult to reproduce with antibodies, including reversible binding via antidotes, programmable multivalency, and precise chemical control over structure and function. In practice, however, most reported applications use aptamers as direct substitutes for antibodies in established workflows, rather than exploiting these distinctive features. As a result, the literature is rich in proof-of-concept demonstrations, but relatively limited in studies that interrogate robustness, physiological performance, or translational viability. In the sections below, we organize applications by use case and discuss, where relevant, the extent to which current implementations exploit or underutilize the distinctive properties of aptamers.
4.1. Selective Isolation of Blood Cells
Isolating specific blood cell populations from mixed samples such as peripheral blood or bone marrow is essential for downstream applications in both clinical and research settings ( Figure 3 ). These techniques are essential for reliable biosensing, diagnostics, and even therapeutics (i.e., CAR-T cell therapy) and therefore require highly selective and minimally disruptive separation of target cells. Aptamer-based capture methods have emerged as promising tools for blood cell isolation, offering comparable performance to antibody-based systems while providing improved reproducibility, lower cost, and the potential for reversible cell release [ 26 , 43 , 149 ]. In this section, we outline the dominant blood cell isolation platforms and discuss how aptamer-specific properties can enhance their performance and flexibility.
Fluorescence-activated cell sorting (FACS) and magnetic-activated cell sorting (MACS) are the two primary techniques used to isolate defined blood cell populations [ 150 , 151 ]. FACS enables multiparametric separation using fluorescent probes and can distinguish closely related immune subsets, such as CD4 + and CD8 + T cells. However, FACS is associated with high equipment costs, specialized technical requirements, and extended processing times, which can limit scalability and clinical translation [ 152 ]. By contrast, MACS relies on magnetic micro- or nanoparticles to capture cells via surface markers (e.g., CD3 for T cells or CD19 for B cells). Although limited to surface antigens and typically restricted to isolating one population per run, MACS offers faster and more cost-effective isolation, with greater compatibility with clinical workflows and good manufacturing practice (GMP) environments. Aptamers have been successfully adapted for both FACS- and MACS-based separation of blood cells, achieving yields and purities comparable to antibody-based systems [ 14 , 153 ]. Their chemical synthesis, reduced batch-to-batch variability, and reversible binding properties make them particularly attractive for isolating diverse hematologic lineages, including T cells, NK cells, and progenitor populations.
Aptamer-mediated separation offers distinct advantages over antibodies for isolating blood cells intended for therapeutic use. Unlike antibodies, aptamers can be designed to release bound cells under mild, non-damaging conditions using complementary “antidote” strands [ 14 , 154 ]. This reversible capture-and-release capability directly addresses a key limitation of antibody-based isolation, namely irreversible receptor occupancy and potential downstream functional perturbation. For example, Kacherovsky et al. selected a DNA aptamer for CD8 + T-cell isolation using a MACS-based workflow [ 14 ]. The authors demonstrated isolation of highly pure and viable CD8 + T cells from peripheral blood mononuclear cells (PBMCs). Excitingly, the performance was comparable to antibody-based capture, while enabling efficient cell release through toehold-mediated strand displacement.
Direct comparisons between aptamers and antibodies are relatively uncommon in the literature. Therefore, antibodies remain the gold standard for blood cell isolation, as well as biosensing, diagnostics, and therapeutics. This is not because aptamers are inferior, but because of entrenched protocols, regulatory familiarity, and decades of infrastructure investment [ 155 ]. Systematic, application-relevant benchmarking studies, particularly in whole blood and clinically realistic workflows, would substantially strengthen the case for aptamer adoption. Furthermore, reversible aptamer-based isolation remains underexplored. Adapting this strategy to existing aptamers against other blood cell markers (e.g., CD3, CD16, or CD19) represents a clear opportunity to improve the precision, safety, and scalability of blood cell purification for both research and therapeutic applications.
4.2. Therapeutic Applications
4.2.1. Drug Delivery
Apart from their classic functions as molecular recognition elements, aptamers have also been applied as programmable delivery vehicles that can interface with several therapeutic platforms, such as nanoparticles, extracellular vesicles, CRISPR liposome complexes, and engineered bispecific or multivalent architectures ( Figure 3 ) [ 118 , 156 , 157 , 158 ]. These strategies rely on aptamers’ high affinity and specificity to achieve cell-selective targeting, while their chemical modularity primarily enables conjugation to therapeutic payloads and integration into more complex delivery architectures. This differs from antibody–drug conjugates (ADCs) where there is efficient drug delivery. For instance, a recent paper by Yu et al. used an anti-CD38 antibody to target multiple myeloma, but the downsides of the antibodies (e.g., limited target selection and payload capacity) can hinder real-world therapeutic outcomes [ 159 , 160 ].
In the most straightforward implementations, aptamers are directly conjugated to therapeutic cargos, creating single-component targeting constructs in which the aptamer serves simultaneously as the recognition element and the delivery scaffold. For example, for delivery to malignant hematopoietic cells, chemotherapeutic drugs can be directly coupled to an aptamer targeting agent. Take an anti-CD123 aptamer developed by Wu et al., where they utilized a targeted drug chain strategy to link doxorubicin to the ends of their aptamers to treat AML ( Figure 4 ) [ 52 ]. Doxorubicin intercalates into GC base pairs, and a GC-rich duplex region was appended to the aptamer to generate a multivalent DNA “drug-train” capable of carrying high drug payloads. In this system, the aptamer serves both as a targeting ligand for CD123 + leukemic cells and as a structural scaffold that enhances intracellular drug accumulation.
Aptamer-mediated delivery has also been extended to RNA-based therapeutics in hematologic and immune contexts. A landmark example is the work by Neff et al., who developed an anti-gp120 RNA aptamer fused to an siRNA payload for targeted delivery to HIV-infected CD4 + T cells in vivo [ 161 ]. In a humanized mouse model with multilineage human hematopoiesis, this aptamer-siRNA chimera selectively entered infected T cells, suppressed viral replication by several orders of magnitude, and protected against CD4 + T cell depletion. Notably, the aptamer itself contributed antiviral activity while simultaneously serving as a cell-specific delivery vehicle for the siRNA, illustrating the dual functional potential of aptamer-based targeting constructs in blood and immune cell populations [ 161 , 162 ].
More broadly, strategies based on direct conjugation of aptamers to small-molecule or nucleic acid payloads share limitations with traditional drug-delivery systems, including limited drug stability, poor control over intracellular release, and inefficient endosomal escape [ 163 ]. To address these challenges, several groups have incorporated aptamers as targeting ligands on liposomal or polymeric nanoparticles. For example, de la Puente et al. developed an anti-CD38 RNA aptamer to functionalize bortezomib-loaded nanoparticles for MM [ 164 ]. Aptamer functionalization significantly enhanced selective nanoparticle accumulation in CD38 + myeloma cells, improving therapeutic efficacy in preclinical models. This work illustrates how aptamers can function as modular targeting elements within established nanomedicine frameworks rather than as standalone delivery agents.
4.2.2. Aptamers as Therapeutics
Beyond drug delivery, aptamers themselves have been explored as active therapeutic agents, including in hematopoietic malignancies. A defining and largely unique advantage of aptamer therapeutics is the ability to externally and rapidly control their activity using the complementary “antidote” oligonucleotides described earlier, enabling reversible, titratable intervention in vivo. This property fundamentally distinguishes aptamers from antibodies and small molecules, whose effects cannot be switched off once administered [ 165 , 166 ]. In parallel, the ability of SELEX to identify high-affinity ligands without prior target engineering provides advantages over protein and small-molecule discovery in terms of cost, speed, and chemical control [ 167 ]. These features, together with long-term storage stability, scalable synthesis, and the capacity to modulate biological activity through relatively simple tertiary structures, make aptamers especially well-suited for applications where safety, controllability, and temporal precision are critical.
While many aptamer-based blood therapies are focused on delivery applications, aptamers can also function as standalone therapeutic agents that directly modulate cell-surface signaling pathways, analogous to antibodies or receptor-targeting biologics. For example, Parekh et al. developed an anti-CD30 aptamer that exploited the pro-apoptotic signaling associated with CD30 engagement in anaplastic large cell lymphoma (ALCL) ( Figure 5 ) [ 106 ]. The aptamer selectively induced apoptosis in CD30 + cell lines while sparing CD30 − controls, demonstrating target-specific cytotoxicity in vitro [ 106 ]. Furthermore, Huang et al. selected a DNA anti-CTLA4 aptamer via cell-SELEX that functioned as an agonist of cytotoxic T-lymphocyte antigen-4 (CTLA4) [ 122 ]. Notably, this study included in vivo validation, demonstrating antitumor efficacy, serum stability, and low toxicity, and directly compared aptamer performance with an anti-CTLA4 monoclonal antibody. Such comparisons remain rare in the aptamer literature and represent an important benchmark for translational relevance [ 122 ].
Beyond oncologic or immune-modulatory applications, aptamers have also been explored as reversible functional blockers in non-malignant blood cell contexts, a niche that particularly highlights their low immunogenicity and programmability. For example, Zhang et al. reported an ssDNA anti-RhD aptamer designed to sterically block RhD antigen recognition to reduce hemolytic anemia risk during transfusion in RhD − patients when compatible blood is scarce [ 130 ]. In vitro studies using mixed peripheral blood mononuclear cell populations demonstrated effective masking of RhD epitopes at optimized concentrations. Although in vivo validation is required, this work highlights a therapeutic niche uniquely suited to aptamers, namely the temporary and reversible modulation of immune recognition on healthy blood cells without permanently altering cell function.
Finally, though this review is primarily focused on cellular targets in hematology, the most mature and clinically advanced applications of aptamer therapeutics in the blood have, in fact, been directed against soluble coagulation proteins. Coagulation represents one of the clearest success stories for aptamer therapeutics, because aptamers can bind large functional protein surfaces (often exosites) to block enzyme or cofactor function and, uniquely, can be rapidly shut off via complementary antidotes, an especially valuable property in settings where bleeding risk must be tightly controlled. Although clinical development of the most advanced early system was ultimately halted due to rare but severe adverse reactions associated with PEG, the factor IXa inhibitory aptamer–antidote platform nevertheless demonstrated the core clinical feasibility of this approach [ 168 , 169 ]. In this work, a PEGylated FIXa aptamer paired with an oligonucleotide antidote (the REG1 system) advanced through multiple clinical studies as a rapidly reversible procedural anticoagulant [ 170 ]. The phase III REGULATE-PCI trial confirmed potent anticoagulant activity and rapid reversal by the complementary antidote in patients. However, the study was terminated due to hypersensitivity reactions later attributed to pre-existing anti-PEG antibodies rather than failure of the aptamer mechanism itself [ 170 , 171 ]. This experience provided several critical lessons for the field: PEGylation, while extending circulation half-life, is not immunologically inert; aptamer pharmacokinetics must be engineered with careful attention to formulation-associated immune responses; and programmable antidote-mediated control of coagulation is clinically achievable in humans. More recently, Sullenger and coworkers introduced an “EXACT” (Exosite–ACTive site) anticoagulant in which a thrombin exosite-binding aptamer was chemically conjugated to dabigatran, a small-molecule active-site inhibitor [ 172 ]. This bivalent construct increased thrombin affinity and inhibitory potency by over three orders of magnitude relative to the aptamer alone and achieved heparin-like anticoagulant activity in vitro, in vivo, and ex vivo, while retaining the programmability and controllability of an aptamer-based system.
4.3. Sensing in Diagnostics and Forensics
Aptamer-based biosensors (“aptasensors”) have emerged as powerful tools for detecting and characterizing blood cells and their surface antigens [ 54 , 173 , 174 ]. By transducing aptamer–target binding events into optical or electrical signals, these systems enable quantitative and often label-free detection of specific blood cell types, in some cases with sensitivities reaching the femtomolar range [ 175 ]. Compared to antibody-based assays, aptasensors benefit from the intrinsic properties of aptamers, including high-affinity and specific target recognition, low immunogenicity, low production cost, high chemical stability, and minimal batch-to-batch variability, which together enable faster response times and improved robustness in blood analysis workflows [ 176 , 177 ].
The chemical modularity of aptamers further allows their straightforward integration into diverse sensing formats, including colorimetric and fluorescence-based platforms, making them attractive for both laboratory diagnostics and point-of-care applications. For instance, Costanzo et al. (2024) demonstrated the potential of using aptamers in forensic science to selectively bind and differentiate between RBCs from different individuals [ 28 ]. Although currently limited to a single proof-of-concept study, this work suggests potential future applications of aptamers in identity verification and sample authentication using blood-based evidence. Nevertheless, despite their conceptual and technical advantages, a substantial gap remains between aptamer discovery by SELEX and successful deployment in clinically robust biosensing systems [ 149 ]. In this section, we highlight representative examples of aptamer-based biosensors for blood cell detection and discuss both their technical promise and their current translational limitations.
A complementary diagnostic use case has also emerged in affinity proteomics, where chemically modified aptamers (“SOMAmers”) enabled high-plex profiling of soluble blood proteins. Shubin et al. (2019) used the SOMAscan platform to quantify 1305 serum proteins from small-volume longitudinal samples and reported a dataset designed to support rejection biomarker discovery in face transplantation [ 178 ]. This study provided one of the most detailed end-to-end examples of aptamer-enabled blood profiling, including sample handling constraints (for example, hemolysis and freeze–thaw control) and an openly deposited dataset for downstream analysis. Such platform-scale studies highlighted a second route to blood “diagnostics”, biomarker discovery from serum proteomes, which complemented cell-surface aptasensors and cell-targeting workflows discussed below.
4.3.1. Colorimetric Aptasensors
Colorimetric aptasensors provide a simple and cost-effective route to visual detection of blood cell biomarkers [ 179 , 180 ]. A common implementation uses gold nanoparticles whose aggregation state, and thus optical properties, change upon aptamer–target binding, producing a visible color shift. Two commonly used colorimetric models are the adsorption–desorption approach and the hybridization approach. In the adsorption–desorption model the aptamer is non-specifically adsorbed to the surface of the AuNP and desorbs in the presence of its target [ 181 ]. This model makes several assumptions: (1) the aptamer has a higher affinity for its target than the surface of the AuNP, (2) the aptamer detaches from the surface of the AuNP, and (3) the colour shift that occurs is from the unprotected AuNPs in the presence of salt. Researchers such as Liu et al. and Chen et al. have challenged of these assumptions and chemical oversimplifications and shown that this model is sometimes prone to artifacts [ 182 , 183 ]. The hybridization model, however, has emerged as a robust option that utilizes predictable interactions. One representative example is the nucleolin-targeting AS1411-based system reported by Borghei et al. in which the aptamer was hybridized to DNA probes immobilized on gold nanoparticles for cancer cell detection ( Figure 6 ) [ 179 ]. The aptasensor showed high specificity and high sensitivity for cancer cells. However, like many colorimetric aptasensors, its performance has not yet been demonstrated in whole blood, where matrix complexity and the strong optical background from hemoglobin pose significant challenges. Despite these limitations, the conceptual simplicity of this approach makes colorimetric aptasensors attractive for rapid screening applications in low-resource or field settings [ 149 ].
4.3.2. Fluorescent Aptasensors
Fluorescent aptasensors are among the most widely used formats for blood cell detection and imaging due to their high sensitivity and compatibility with spatially resolved readouts [ 184 ]. One common design, molecular beacon-type aptasensors, employ fluorophore–quencher pairs attached to aptamers such that target binding induces a conformational change and restores fluorescence. Label-free approaches employing intercalating dyes or nanomaterials have also been reported [ 176 ]. Boykoff et al. developed a bispecific fluorescent aptasensor responsive to the tumor microenvironment by linking ATP- and CD3-binding aptamers ( Figure 7 ) [ 92 ]. Increased ATP levels triggered fluorescence in Jurkat T-cell models. While this work illustrates the conceptual flexibility of fluorescent aptasensor designs, the system was not evaluated in whole blood or in vivo contexts, limiting conclusions about translational utility.
5. Summary, Challenges, and Future Perspectives
Aptamers are versatile molecular tools for blood cell applications spanning selective isolation, drug delivery, biosensing, and therapeutics. Throughout this review, we have highlighted how aptamers can exploit differences in blood cell surface marker expression and cellular state, offering advantages such as chemical synthesis, batch-to-batch consistency, reversibility, and low immunogenicity. These properties position aptamers as attractive alternatives or complements to antibody-based approaches in both diagnostic and therapeutic settings.
Despite this promise, substantial barriers remain to translating blood cell-targeting aptamers from benchtop studies to real-world applications. Across application areas, a recurring limitation is the lack of validation in physiologically relevant environments, particularly whole blood or serum. Aptamer-mediated blood cell isolation illustrates this gap clearly: while reversible capture and release has been demonstrated, relatively few studies systematically evaluate isolation efficiency, target internalization, or functional consequences under clinically realistic conditions. Similar challenges arise in drug delivery, where most aptamer-based systems remain at an early stage, relying on relatively simple conjugation or nanoparticle targeting strategies without fully exploiting the programmable logic and release mechanisms that aptamers can offer. In diagnostics and biosensing, many aptasensor platforms demonstrate excellent performance under simplified conditions, yet lack in vivo or complex-matrix validation, limiting their translational impact [ 185 ].
More broadly, the current aptamer literature remains skewed toward a narrow subset of blood cell targets, particularly B and T lymphocytes, with comparatively limited exploration of healthy cell populations, innate immune cells, and dynamic cell states. This focus constrains the development of aptamer-based biosensors and diagnostics intended for immune monitoring or longitudinal profiling. In parallel, the absence of standardized good manufacturing practice (GMP) guidelines and regulatory pathways for aptamers continues to slow clinical translation, particularly when compared with well-established antibody platforms [ 185 , 186 , 187 ].
Addressing these challenges represents a clear opportunity for the field. Future progress will depend on integrating rigorous validation in complex biological matrices, expanding target selection beyond diseased lymphoid cells, and establishing clearer standards for aptamer characterization, manufacturing, and clinical development. With these advances, aptamers are well positioned to move beyond proof-of-concept studies and realize their potential as practical tools for hematopoietic targeting, diagnostics, and therapy.
Acknowledgments
We thank the McKeague Lab for useful discussions, especially Antoine Moitessier, Olivia Kovecses, and Omar Salam for feedback on the manuscript. During the preparation of this manuscript/study, the author(s) used OpenAI ChatGPT, GPT-5.2 for the purposes of refining sentence structure. The authors have reviewed and edited the output and take full responsibility for the content of this publication.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Author Contributions
Conceptualization, B.A. and M.M.; writing: original draft preparation, B.A., F.E., K.G., X.H., R.N. and M.M.; writing: review and editing, B.A., F.E., K.G., X.H., R.N., S.M. and M.M.; visualization, B.A., F.E. and S.M. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No new data were created or analyzed in this study.
Conflicts of Interest
The authors declare no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript: ALCL Anaplastic large cell lymphoma ALL Acute lymphoblastic leukemia AML Acute myeloid leukemia ATP Adenosine triphosphate AuNPs Gold nanoparticles BAFF-R B-cell activating factor receptor B-ALL B-cell acute lymphoblastic leukemia BCMA B-cell maturation antigen BCR B-cell receptor BLI Bio-layer interferometry CAR Chimeric antigen receptor CCR5 C-C chemokine receptor type 5 CLL Chronic lymphocytic leukemia CML Chronic myeloid leukemia CTLA4 Cytotoxic T-lymphocyte antigen-4 DC-SIGN Dendritic cell-specific intercellular adhesion molecule-3 grabbing non-integrin DNA Deoxyribonucleic acid FACS Fluorescent-activated cell sorting FRET Förster resonance energy transfer GMP Good manufacturing practice HIV Human immunodeficiency virus HSC Hematopoietic stem cell kDa Kilodaltons LNA Locked nucleic acid LSC Liquid scintillation counting MACS Magnetic-activated cell sorting MHC Major histocompatibility complex mIgM Membrane immunoglobulin M MST Microscale thermophoresis MM Multiple myeloma NK Natural killer NRBC Nucleated red blood cell OFA/iLRP Oncofetal antigen-immature laminin receptor protein PCR Polymerase chain reaction PEG Polyethylene glycol PS Phosphorothioate qRT-PCR Quantitative real-time polymerase chain reaction RBC Red blood cell Rh Rhesus factor RNA Ribonucleic acid SELEX Systematic evolution of ligands by exponential enrichment siRNA Small-interfering RNA SPR Surface plasmon resonance T-ALL T-cell lymphoblastic leukemia TCR T-cell receptor
References
1. Kasbekar M. Mitchell C.A. Proven M.A. Passegue E. Hematopoietic stem cells through the ages: A lifetime of adaptation to organismal demands Cell Stem Cell 2023 30 1403 1420 10.1016/j.stem.2023.09.013 37865087 PMC10842631
2. Cosgrove J. Hustin L.S.P. de Boer R.J. Perie L. Hematopoiesis in numbers Trends Immunol. 2021 42 1100 1112 10.1016/j.it.2021.10.006 34742656
3. Cheng H. Zheng Z. Cheng T. New paradigms on hematopoietic stem cell differentiation Protein Cell 2020 11 34 44 10.1007/s13238-019-0633-0 31201709 PMC6949320
4. Asada S. Kitamura T. Clonal hematopoiesis and associated diseases: A review of recent findings Cancer Sci. 2021 112 3962 3971 10.1111/cas.15094 34328684 PMC8486184
5. Pardali E. Dimmeler S. Zeiher A.M. Rieger M.A. Clonal hematopoiesis, aging, and cardiovascular diseases Exp. Hematol. 2020 83 95 104 10.1016/j.exphem.2019.12.006 31891750
6. Desai R.H. Zandvakili N. Bohlander S.K. Dissecting the Genetic and Non-Genetic Heterogeneity of Acute Myeloid Leukemia Using Next-Generation Sequencing and In Vivo Models Cancers 2022 14 2182 10.3390/cancers14092182 35565315 PMC9103951
7. Ozer O. Dogan L. Baysal Z. Basir H. Ciftci A.T. Eroz P. Guclu E.S. Evaluation of peripheral blood inflammatory biomarkers in sickle cell disease with and without retinopathy Graefes Arch. Clin. Exp. Ophthalmol. 2024 262 3787 3796 10.1007/s00417-024-06569-9 38976013 PMC11608169
8. Schroeder P. Fulzele K. Forsyth S. Ribadeneira M.D. Guichard S. Wilker E. Marshall C.G. Drake A. Fessler R. Konstantinidis D.G. Etavopivat, a Pyruvate Kinase Activator in Red Blood Cells, for the Treatment of Sickle Cell Disease J. Pharmacol. Exp. Ther. 2022 380 210 219 10.1124/jpet.121.000743 35031585
9. Spencer Chapman M. Wilk C.M. Boettcher S. Mitchell E. Dawson K. Williams N. Muller J. Kovtonyuk L. Jung H. Caiado F. Clonal dynamics after allogeneic haematopoietic cell transplantation Nature 2024 635 926 934 10.1038/s41586-024-08128-y 39478227 PMC11602715
10. Takeuchi S. Ito Y. Matsuoka S. Abe M. Tsurui H. Horimoto Y. Fukuhara T. Hirano T. Mizutani N. Ito T. Novel anti-ITGA4 monoclonal antibody induces cell death via large pore formation in NK/T-cell lymphoma cells Sci. Rep. 2025 15 45655 10.1038/s41598-025-32892-0 41469420 PMC12753658
11. Ferrara F. Geissler K. Mehta P. Montesinos P. Venditti A. Unmet needs in patients with acute myeloid leukemia ineligible for intensive approaches: Perspectives from a European expert panel Front. Oncol. 2025 15 1642472 10.3389/fonc.2025.1642472 41244920 PMC12616280
12. Chung E. Ewald L. Kassembaum N.J. Noyes T. Gakidou E. Mokdad A.H. Delays in Blood Work and Disease Burden: A Cross-Sectional Analysis of Unmet Blood Work Need and Seven Key Health Conditions Across 21 Countries Int. J. Public Health 2024 69 1607667 10.3389/ijph.2024.1607667 39834604 PMC11742933
13. Mukherjee M.D. Gupta P. Kumari V. Rana I. Jindal D. Sagar N. Singh J. Dhand C. Wearable biosensors in modern healthcare: Emerging trends and practical applications Talanta Open 2025 12 100486 10.1016/j.talo.2025.100486
14. Kacherovsky N. Cardle I.I. Cheng E.L. Yu J.L. Baldwin M.L. Salipante S.J. Jensen M.C. Pun S.H. Traceless aptamer-mediated isolation of CD8(+) T cells for chimeric antigen receptor T-cell therapy Nat. Biomed. Eng. 2019 3 783 795 10.1038/s41551-019-0411-6 31209354 PMC6783348
15. Yan J. Bhadane R. Ran M. Ma X. Li Y. Zheng D. Salo-Ahen O.M.H. Zhang H. Development of Aptamer-DNAzyme based metal-nucleic acid frameworks for gastric cancer therapy Nat. Commun. 2024 15 3684 10.1038/s41467-024-48149-9 38693181 PMC11063048
16. Besedina N.A. Skverchinskaya E.A. Shmakov S.V. Ivanov A.S. Mindukshev I.V. Bukatin A.S. Persistent red blood cells retain their ability to move in microcapillaries under high levels of oxidative stress Commun. Biol. 2022 5 659 10.1038/s42003-022-03620-5 35787676 PMC9253111
17. Pan T. Zhang J. Wang X. Song Y. Global burden and trends of hematologic malignancies based on Global Cancer Observatory 2022 and Global Burden of Disease 2021 Exp. Hematol. Oncol. 2025 14 98 10.1186/s40164-025-00684-x 40676693 PMC12273037
18. Zhang N. Wu J. Wang Q. Liang Y. Li X. Chen G. Ma L. Liu X. Zhou F. Global burden of hematologic malignancies and evolution patterns over the past 30 years Blood Cancer J. 2023 13 82 10.1038/s41408-023-00853-3 37193689 PMC10188596
19. Kovecses O. Sharif-Askari B. Gonzalez-Losada C. Reebye V. Ryan B.M. Luedtke N.W. Mercier F.E. McKeague M. RNA activation of CEBPA improves leukemia treatment Mol. Ther. Nucleic Acids 2025 36 102611 Erratum in Mol. Ther. Nucleic Acids 2025 , 36 , 102643 10.1016/j.omtn.2025.102611 40686853 PMC12271619
20. Quessada J. Nozais M. Grosjean C. Savey C. Pankaew S. Allelova S. Potier D. Loosveld M. Payet-Bornet D. Ectopic expression of BEX genes in T-cell acute lymphoblastic leukemia Blood Adv. 2026 10 452 465 10.1182/bloodadvances.2024015174 40811813 PMC12830129
21. Titcomb C.P. Chronic Myeloid Leukemia—A Review of Current Status J. Insur. Med. 2025 52 137 143 10.17849/insm-52-3-1-7.2 40957652
22. Bottcher M. Reemts L. Hengeveld P.J. Bottcher-Loschinski R. Bhuria V. Lu J. Materna-Reichelt S. Das D. Stojanovic Guzvic N. Bruns H. Immunoglobulin heavy-chain status and stromal interactions shape ferroptosis sensitivity in chronic lymphocytic leukemia Signal Transduct. Target. Ther. 2026 11 3 10.1038/s41392-025-02535-x 41486278 PMC12765864
23. Weniger M.A. Kuppers R. Molecular biology of Hodgkin lymphoma Leukemia 2021 35 968 981 10.1038/s41375-021-01204-6 33686198 PMC8024192
24. Elbahoty M.H. Papineni B. Samant R.S. Multiple myeloma: Clinical characteristics, current therapies and emerging innovative treatments targeting ribosome biogenesis dynamics Clin. Exp. Metastasis 2024 41 829 842 10.1007/s10585-024-10305-2 39162964 PMC11607061
25. Elendu C. Amaechi D.C. Alakwe-Ojimba C.E. Elendu T.C. Elendu R.C. Ayabazu C.P. Aina T.O. Aborisade O. Adenikinju J.S. Understanding Sickle cell disease: Causes, symptoms, and treatment options Medicine 2023 102 e35237 10.1097/md.0000000000035237 37746969 PMC10519513
26. Maru B. Nadeau L. McKeague M. Enhancing CAR-T Cell Therapy with Functional Nucleic Acids ACS Pharmacol. Transl. Sci. 2021 4 1716 1727 10.1021/acsptsci.1c00188 34927006 PMC8669706
27. Rakhshandehroo T. Mantri S.R. Moravej H. Louis B.B.V. Salehi Farid A. Munaretto L. Regan K. Khan R.M.M. Wolff A. Farkash Z. A CAR enhancer increases the activity and persistence of CAR T cells Nat. Biotechnol. 2025 43 948 959 10.1038/s41587-024-02339-4 39079964 PMC11779983
28. Costanzo H. Gooch J. Tungsirisurp S. Frascione N. The Development and Characterisation of ssDNA Aptamers via a Modified Cell-SELEX Methodology for the Detection of Human Red Blood Cells Int. J. Mol. Sci. 2024 25 1814 10.3390/ijms25031814 38339091 PMC10855528
29. Woll P.S. Yoshizato T. Hellstrom-Lindberg E. Fioretos T. Ebert B.L. Jacobsen S.E.W. Targeting stem cells in myelodysplastic syndromes and acute myeloid leukemia J. Intern. Med. 2022 292 262 277 10.1111/joim.13535 35822488 PMC9544124
30. Molica M. Perrone S. Mazzone C. Niscola P. Cesini L. Abruzzese E. de Fabritiis P. CD33 Expression and Gentuzumab Ozogamicin in Acute Myeloid Leukemia: Two Sides of the Same Coin Cancers 2021 13 3214 10.3390/cancers13133214 34203180 PMC8268215
31. Vu H.N. Situ A.J. Dai X. Ulmer T.S. Structure of the CD33 Receptor and Implications for the Siglec Family Biochemistry 2025 64 1450 1462 10.1021/acs.biochem.4c00864 40067740 PMC12002911
32. Thomas R. Ritchey J.K. DiPersio J.F. Kim M.Y. Targeting CD117 on hematopoietic stem and progenitor cells impairs CAR T cell activity Mol. Ther. 2025 33 4584 4599 10.1016/j.ymthe.2025.05.033 40450523 PMC12432900
33. Pelosi E. Castelli G. Testa U. CD123 a Therapeutic Target for Acute Myeloid Leukemia and Blastic Plasmocytoid Dendritic Neoplasm Int. J. Mol. Sci. 2023 24 2718 10.3390/ijms24032718 36769040 PMC9917129
34. El Achi H. Dupont E. Paul S. Khoury J.D. CD123 as a Biomarker in Hematolymphoid Malignancies: Principles of Detection and Targeted Therapies Cancers 2020 12 3087 10.3390/cancers12113087 33113953 PMC7690688
35. Jiang Y. Lin W. Zhu L. Targeted Drug Delivery for the Treatment of Blood Cancers Molecules 2022 27 1310 10.3390/molecules27041310 35209102 PMC8880555
36. McKeague M. Derosa M.C. Challenges and opportunities for small molecule aptamer development J. Nucleic Acids 2012 2012 748913 10.1155/2012/748913 23150810 PMC3488411
37. Ellington A.D. Szostak J.W. In vitro selection of RNA molecules that bind specific ligands Nature 1990 346 818 822 10.1038/346818a0 1697402
38. Tuerk C. Gold L. Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase Science 1990 249 505 510 10.1126/science.2200121 2200121
39. Keefe A.D. Pai S. Ellington A. Aptamers as therapeutics Nat. Rev. Drug Discov. 2010 9 537 550 Erratum in Nat. Rev. Drug Discov. 2010 , 9 , 660 10.1038/nrd3141 20592747 PMC7097324
40. Song K.M. Lee S. Ban C. Aptamers and their biological applications Sensors 2012 12 612 631 10.3390/s120100612 22368488 PMC3279232
41. Yu H. Frederiksen J. Sullenger B.A. Applications and future of aptamers that achieve rapid-onset anticoagulation RNA 2023 29 455 462 10.1261/rna.079503.122 36697262 PMC10019365
42. Xiang D. Zheng C. Zhou S.F. Qiao S. Tran P.H. Pu C. Li Y. Kong L. Kouzani A.Z. Lin J. Superior Performance of Aptamer in Tumor Penetration over Antibody: Implication of Aptamer-Based Theranostics in Solid Tumors Theranostics 2015 5 1083 1097 10.7150/thno.11711 26199647 PMC4508498
43. Zhou J. Rossi J. Aptamers as targeted therapeutics: Current potential and challenges Nat. Rev. Drug Discov. 2017 16 181 202 Erratum in Nat. Rev. Drug Discov. 2017 , 16 , 440 10.1038/nrd.2016.199 27807347 PMC5700751
44. Caruthers M.H. Gene Synthesis Machines: DNA Chemistry and Its Uses Science 1985 230 281 285 10.1126/science.3863253 3863253
45. Domsicova M. Korcekova J. Poturnayova A. Breier A. New Insights into Aptamers: An Alternative to Antibodies in the Detection of Molecular Biomarkers Int. J. Mol. Sci. 2024 25 6833 10.3390/ijms25136833 38999943 PMC11240909
46. Fu Z. Xiang J. Aptamers, the Nucleic Acid Antibodies, in Cancer Therapy Int. J. Mol. Sci. 2020 21 2793 10.3390/ijms21082793 32316469 PMC7215806
47. Bouchard P.R. Hutabarat R.M. Thompson K.M. Discovery and development of therapeutic aptamers Annu. Rev. Pharmacol. Toxicol. 2010 50 237 257 10.1146/annurev.pharmtox.010909.105547 20055704
48. Cesarini V. Appleton S.L. de Franciscis V. Catalucci D. The recent blooming of therapeutic aptamers Mol. Asp. Med. 2025 102 101350 10.1016/j.mam.2025.101350 39933246
49. Zichel R. Chearwae W. Pandey G.S. Golding B. Sauna Z.E. Aptamers as a sensitive tool to detect subtle modifications in therapeutic proteins PLoS ONE 2012 7 e31948 10.1371/journal.pone.0031948 22384109 PMC3288073
50. Yang L.F. Ling M. Kacherovsky N. Pun S.H. Aptamers 101: Aptamer discovery and in vitro applications in biosensors and separations Chem. Sci. 2023 14 4961 4978 10.1039/d3sc00439b 37206388 PMC10189874
51. Sylvestre M. Saxby C.P. Kacherovsky N. Gustafson H. Salipante S.J. Pun S.H. Identification of a DNA Aptamer That Binds to Human Monocytes and Macrophages Bioconjugate Chem. 2020 31 1899 1907 10.1021/acs.bioconjchem.0c00247 32589412
52. Wu H. Wang M. Dai B. Zhang Y. Yang Y. Li Q. Duan M. Zhang X. Wang X. Li A. Novel CD123-aptamer-originated targeted drug trains for selectively delivering cytotoxic agent to tumor cells in acute myeloid leukemia theranostics Drug Deliv. 2017 24 1216 1229 10.1080/10717544.2017.1367976 28845698 PMC8241133
53. Yu H. Luo Y. Alkhamis O. Canoura J. Yu B. Xiao Y. Isolation of Natural DNA Aptamers for Challenging Small-Molecule Targets, Cannabinoids Anal. Chem. 2021 93 3172 3180 10.1021/acs.analchem.0c04592 33528997 PMC7895305
54. Aljohani M.M. Cialla-May D. Popp J. Chinnappan R. Al-Kattan K. Zourob M. Aptamers: Potential Diagnostic and Therapeutic Agents for Blood Diseases Molecules 2022 27 383 10.3390/molecules27020383 35056696 PMC8778139
55. Liu M. Zaman K. Fortenberry Y.M. Overview of the Therapeutic Potential of Aptamers Targeting Coagulation Factors Int. J. Mol. Sci. 2021 22 3897 10.3390/ijms22083897 33918821 PMC8069679
56. Bayani A. Abosaoda M.K. Rizaev J. Nazari M. Jafari Z. Soleimani Samarkhazan H. Aptamer-based approaches in leukemia: A paradigm shift in targeted therapy Clin. Exp. Med. 2025 25 186 10.1007/s10238-025-01724-w 40445231 PMC12125159
57. Yilmaz O. Yilmaz B.N. Kandilcik N.B. Yigit Z.S. Altuntop Yayla M.E. Aptamer-based monitorization and therapeutic applications of blood coagulation cascade disorders: A systematic review Thromb. Res. 2025 258 109566 10.1016/j.thromres.2025.109566 41468844
58. Yousefnia S. Negahdary M. Diagnostic application of aptamers against leukemia, multiple myeloma and lymphoma: A review J. Drug Deliv. Sci. Technol. 2024 100 106103 10.1016/j.jddst.2024.106103
59. Ganguly S.C. Paul R. Mondal B. Kundu M. Chakraborty T. Recent advancements in aptamer-mediated theranostics in the management of hematological disorders Int. J. Pharm. 2026 688 126435 10.1016/j.ijpharm.2025.126435 41325832
60. Earnest K.G. McConnell E.M. Hassan E.M. Wunderlich M. Hosseinpour B. Bono B.S. Chee M.J. Mulloy J.C. Willmore W.G. DeRosa M.C. Development and characterization of a DNA aptamer for MLL-AF9 expressing acute myeloid leukemia cells using whole cell-SELEX Sci. Rep. 2021 11 19174 10.1038/s41598-021-98676-4 34580387 PMC8476576
61. Bing T. Zhang N. Shangguan D. Cell-SELEX, an Effective Way to the Discovery of Biomarkers and Unexpected Molecular Events Adv. Biosyst. 2019 3 e1900193 10.1002/adbi.201900193 32648677
62. Zhang Y. Jiang Y. Kuster D. Ye Q. Huang W. Furbacher S. Zhang J. Doll P. Lin W. Dong S. Single-step discovery of high-affinity RNA ligands by UltraSelex Nat. Chem. Biol. 2025 21 1118 1126 10.1038/s41589-025-01868-6 40164941
63. Darmostuk M. Rimpelova S. Gbelcova H. Ruml T. Current approaches in SELEX: An update to aptamer selection technology Biotechnol. Adv. 2015 33 1141 1161 10.1016/j.biotechadv.2015.02.008 25708387
64. Brown A. Brill J. Amini R. Nurmi C. Li Y. Development of Better Aptamers: Structured Library Approaches, Selection Methods, and Chemical Modifications Angew. Chem. Int. Ed. Engl. 2024 63 e202318665 10.1002/anie.202318665 38253971
65. Zhong Y. Zhao J. Li J. Liao X. Chen F. Advances of aptamers screened by Cell-SELEX in selection procedure, cancer diagnostics and therapeutics Anal. Biochem. 2020 598 113620 10.1016/j.ab.2020.113620 32087127
66. Goto S. Tsukakoshi K. Ikebukuro K. Development of aptamers against unpurified proteins Biotechnol. Bioeng. 2017 114 2706 2716 10.1002/bit.26389 28734049
67. Shigdar S. Agnello L. Fedele M. Camorani S. Cerchia L. Profiling Cancer Cells by Cell-SELEX: Use of Aptamers for Discovery of Actionable Biomarkers and Therapeutic Applications Thereof Pharmaceutics 2021 14 28 10.3390/pharmaceutics14010028 35056924 PMC8781458
68. Daniels D.A. Chen H. Hicke B.J. Swiderek K.M. Gold L. A tenascin-C aptamer identified by tumor cell SELEX: Systematic evolution of ligands by exponential enrichment Proc. Natl. Acad. Sci. USA 2003 100 15416 15421 10.1073/pnas.2136683100 14676325 PMC307582
69. Zumrut H.E. Ara M.N. Fraile M. Maio G. Mallikaratchy P. Ligand-Guided Selection of Target-Specific Aptamers: A Screening Technology for Identifying Specific Aptamers Against Cell-Surface Proteins Nucleic Acid. Ther. 2016 26 190 198 10.1089/nat.2016.0611 27148897 PMC4900185
70. Williams N.B. Batool S. Zumrut H.E. Patel R. Sosa G. Jamal M. Mallikaratchy P. An In Vitro Selection Platform to Identify Multiple Aptamers against Multiple Cell-Surface Markers Using Ligand-Guided Selection Biochemistry 2022 61 1600 1613 10.1021/acs.biochem.2c00105 35829681 PMC10117398
71. Sola M. Menon A.P. Moreno B. Meraviglia-Crivelli D. Soldevilla M.M. Carton-Garcia F. Pastor F. Aptamers Against Live Targets: Is In Vivo SELEX Finally Coming to the Edge? Mol. Ther. Nucleic Acids 2020 21 192 204 10.1016/j.omtn.2020.05.025 32585627 PMC7321788
72. Civit L. Theodorou I. Frey F. Weber H. Lingnau A. Grober C. Blank M. Dambrune C. Stunden J. Beyer M. Targeting hormone refractory prostate cancer by in vivo selected DNA libraries in an orthotopic xenograft mouse model Sci. Rep. 2019 9 4976 10.1038/s41598-019-41460-2 30899039 PMC6428855
73. Wong K.Y. Wong M.S. Lee J.H. Liu J. From cell-SELEX to tissue-SELEX for targeted drug delivery and aptamer nanomedicine Adv. Drug Deliv. Rev. 2025 224 115646 10.1016/j.addr.2025.115646 40618926
74. Liao Y. Xiong S. Ur Rehman Z. He X. Peng H. Liu J. Sun S. The Research Advances of Aptamers in Hematologic Malignancies Cancers 2023 15 300 10.3390/cancers15010300 36612296 PMC9818631
75. Kelly L. Maier K.E. Yan A. Levy M. A comparative analysis of cell surface targeting aptamers Nat. Commun. 2021 12 6275 10.1038/s41467-021-26463-w 34725326 PMC8560833
76. Shigdar S. Macdonald J. O’Connor M. Wang T. Xiang D. Al Shamaileh H. Qiao L. Wei M. Zhou S.F. Zhu Y. Aptamers as theranostic agents: Modifications, serum stability and functionalisation Sensors 2013 13 13624 13637 10.3390/s131013624 24152925 PMC3859083
77. Amero P. Lokesh G.L.R. Chaudhari R.R. Cardenas-Zuniga R. Schubert T. Attia Y.M. Montalvo-Gonzalez E. Elsayed A.M. Ivan C. Wang Z. Conversion of RNA Aptamer into Modified DNA Aptamers Provides for Prolonged Stability and Enhanced Antitumor Activity J. Am. Chem. Soc. 2021 143 7655 7670 10.1021/jacs.9b10460 33988982 PMC12486140
78. Ababneh N. Alshaer W. Allozi O. Mahafzah A. El-Khateeb M. Hillaireau H. Noiray M. Fattal E. Ismail S. In vitro selection of modified RNA aptamers against CD44 cancer stem cell marker Nucleic Acid. Ther. 2013 23 401 407 10.1089/nat.2013.0423 24171482 PMC3868357
79. Freage L. Jamal D. Williams N.B. Mallikaratchy P.R. A Homodimeric Aptamer Variant Generated from Ligand-Guided Selection Activates the T Cell Receptor Cluster of Differentiation 3 Complex Mol. Ther. Nucleic Acids 2020 22 167 178 10.1016/j.omtn.2020.08.016 32920262 PMC7494611
80. Wang M. Wu H. Duan M. Yang Y. Wang G. Che F. Liu B. He W. Li Q. Zhang L. SS30, a novel thioaptamer targeting CD123, inhibits the growth of acute myeloid leukemia cells Life Sci. 2019 232 116663 Erratum in Life Sci. 2019 , 240 , 117111 10.1016/j.lfs.2019.116663 31323275
81. McKeague M. Calzada V. Cerchia L. DeRosa M. Heemstra J.M. Janjic N. Johnson P.E. Kraus L. Limson J. Mayer G. The minimum aptamer publication standards (MAPS guidelines) for de novo aptamer selection Aptamers 2022 6 10 18
82. Miller A.A. Rao A.S. Nelakanti S.R. Kujalowicz C. Shi T. Rodriguez T. Ellington A.D. Stovall G.M. Systematic Review of Aptamer Sequence Reporting in the Literature Reveals Widespread Unexplained Sequence Alterations Anal. Chem. 2022 94 7731 7737 10.1021/acs.analchem.1c04407 35420426 PMC9179646
83. Lee S.J. Cho J. Lee B.H. Hwang D. Park J.W. Design and Prediction of Aptamers Assisted by In Silico Methods Biomedicines 2023 11 356 10.3390/biomedicines11020356 36830893 PMC9953197
84. Hosseini S.M.H. Bassami M.R. Haghparast A. Sankian M. Hashemi Tabar G. Identification of Aptamers that Specifically Bind to A(1) Antigen by Performing Cell-on Human Erythrocytes Galen. Med. J. 2020 9 e1657 10.31661/gmj.v9i0.1657 34466563 PMC8343710
85. Fukunaga J. Nomura Y. Tanaka Y. Amano R. Tanaka T. Nakamura Y. Kawai G. Sakamoto T. Kozu T. The Runt domain of AML1 (RUNX1) binds a sequence-conserved RNA motif that mimics a DNA element RNA 2013 19 927 936 10.1261/rna.037879.112 23709277 PMC3683927
86. Amano R. Takada K. Tanaka Y. Nakamura Y. Kawai G. Kozu T. Sakamoto T. Kinetic and Thermodynamic Analyses of Interaction between a High-Affinity RNA Aptamer and Its Target Protein Biochemistry 2016 55 6221 6229 10.1021/acs.biochem.6b00748 27766833
87. Zhou J. Tiemann K. Chomchan P. Alluin J. Swiderski P. Burnett J. Zhang X. Forman S. Chen R. Rossi J. Dual functional BAFF receptor aptamers inhibit ligand-induced proliferation and deliver siRNAs to NHL cells Nucleic Acids Res. 2013 41 4266 4283 10.1093/nar/gkt125 23470998 PMC3627597
88. Catuogno S. Di Martino M.T. Nuzzo S. Esposito C.L. Tassone P. de Franciscis V. An Anti-BCMA RNA Aptamer for miRNA Intracellular Delivery Mol. Ther. Nucleic Acids 2019 18 981 990 10.1016/j.omtn.2019.10.021 31778956 PMC6889555
89. Dey A.K. Griffiths C. Lea S.M. James W. Structural characterization of an anti-gp120 RNA aptamer that neutralizes R5 strains of HIV-1 RNA 2005 11 873 884 10.1261/rna.7205405 15923374 PMC1370772
90. Zhou J. Satheesan S. Li H. Weinberg M.S. Morris K.V. Burnett J.C. Rossi J.J. Cell-specific RNA aptamer against human CCR5 specifically targets HIV-1 susceptible cells and inhibits HIV-1 infectivity Chem. Biol. 2015 22 379 390 10.1016/j.chembiol.2015.01.005 25754473 PMC4369413
91. Zumrut H.E. Batool S. Argyropoulos K.V. Williams N. Azad R. Mallikaratchy P.R. Integrating Ligand-Receptor Interactions and In Vitro Evolution for Streamlined Discovery of Artificial Nucleic Acid Ligands Mol. Ther. Nucleic Acids 2019 17 150 163 10.1016/j.omtn.2019.05.015 31255977 PMC6606840
92. Boykoff N. Freage L. Lenn J. Mallikaratchy P. Bispecific Aptamer Sensor toward T-Cell Leukemia Detection in the Tumor Microenvironment ACS Omega 2021 6 32563 32570 10.1021/acsomega.1c04125 34901605 PMC8655784
93. Menon A.P. Villanueva H. Meraviglia-Crivelli D. van Santen H.M. Hellmeier J. Zheleva A. Nonateli F. Peters T. Wachsmann T.L.A. Hernandez-Rueda M. CD3 aptamers promote expansion and persistence of tumor-reactive T cells for adoptive T cell therapy in cancer Mol. Ther. Nucleic Acids 2024 35 102198 10.1016/j.omtn.2024.102198 38745854 PMC11091522
94. Zhu Q. Shibata T. Kabashima T. Kai M. Inhibition of HIV-1 protease expression in T cells owing to DNA aptamer-mediated specific delivery of siRNA Eur. J. Med. Chem. 2012 56 396 399 10.1016/j.ejmech.2012.07.045 22907035
95. Zhao N. Pei S.N. Parekh P. Salazar E. Zu Y. Blocking interaction of viral gp120 and CD4-expressing T cells by single-stranded DNA aptamers Int. J. Biochem. Cell Biol. 2014 51 10 18 10.1016/j.biocel.2014.03.008 24661998 PMC4041034
96. Fellows T. Ho L. Flanagan S. Fogel R. Ojo D. Limson J. Gold nanoparticle-streptavidin conjugates for rapid and efficient screening of aptamer function in lateral flow sensors using novel CD4-binding aptamers identified through Crossover-SELEX Analyst 2020 145 5180 5193 10.1039/D0AN00634C 32567629
97. Wang C.W. Chung W.H. Cheng Y.F. Ying N.W. Peck K. Chen Y.T. Hung S.I. A new nucleic acid-based agent inhibits cytotoxic T lymphocyte-mediated immune disorders J. Allergy Clin. Immunol. 2013 132 713 722.e11 10.1016/j.jaci.2013.04.036 23791505
98. Boltz A. Piater B. Toleikis L. Guenther R. Kolmar H. Hock B. Bi-specific aptamers mediating tumor cell lysis J. Biol. Chem. 2011 286 21896 21905 10.1074/jbc.M111.238261 21531729 PMC3122244
99. Hu Y. Li X. An Y. Duan J. Yang X.D. Selection of a novel CD19 aptamer for targeted delivery of doxorubicin to lymphoma cells Oncotarget 2018 9 26605 26615 10.18632/oncotarget.24902 29928472 PMC6003574
100. Danquah M.K. Guo H.B. Tan K.X. Bhakta M. Atomistic probing of aptameric binding of CD19 outer membrane domain reveals an “aptamer walking” mechanism Biotechnol. Prog. 2020 36 e2957 10.1002/btpr.2957 31912987
101. Esposito C.L. Van Roosbroeck K. Santamaria G. Rotoli D. Sandomenico A. Wierda W.G. Ferrajoli A. Ruvo M. Calin G.A. de Franciscis V. Selection of a Nuclease-Resistant RNA Aptamer Targeting CD19 Cancers 2021 13 5220 10.3390/cancers13205220 34680368 PMC8533794
102. Haghighi M. Khanahmad H. Palizban A. Selection and Characterization of Single-Stranded DNA Aptamers Binding Human B-Cell Surface Protein CD20 by Cell-SELEX Molecules 2018 23 715 10.3390/molecules23040715 29561802 PMC6017093
103. Ruiz-Ciancio D. Lin L.H. Veeramani S. Barros M.N. Sanchez D. Di Bartolo A.L. Masone D. Giangrande P.H. Mestre M.B. Thiel W.H. Selection of a novel cell-internalizing RNA aptamer specific for CD22 antigen in B cell acute lymphoblastic leukemia Mol. Ther. Nucleic Acids 2023 33 698 712 10.1016/j.omtn.2023.07.028 37662970 PMC10469072
104. Pastor F. Soldevilla M.M. Villanueva H. Kolonias D. Inoges S. de Cerio A.L. Kandzia R. Klimyuk V. Gleba Y. Gilboa E. CD28 aptamers as powerful immune response modulators Mol. Ther. Nucleic Acids 2013 2 e98 10.1038/mtna.2013.26 23756353 PMC3696906
105. Mori T. Oguro A. Ohtsu T. Nakamura Y. RNA aptamers selected against the receptor activator of NF-kappaB acquire general affinity to proteins of the tumor necrosis factor receptor family Nucleic Acids Res. 2004 32 6120 6128 10.1093/nar/gkh949 15562003 PMC534629
106. Parekh P. Kamble S. Zhao N. Zeng Z. Portier B.P. Zu Y. Immunotherapy of CD30-expressing lymphoma using a highly stable ssDNA aptamer Biomaterials 2013 34 8909 8917 10.1016/j.biomaterials.2013.07.099 23968853 PMC3784013
107. Yang C. Wang Y. Ge M.H. Fu Y.J. Hao R. Islam K. Huang P. Chen F. Sun J. Hong F. Rapid identification of specific DNA aptamers precisely targeting CD33 positive leukemia cells through a paired cell-based approach Biomater. Sci. 2019 7 938 950 10.1039/C8BM01393D 30519686
108. Zaimy M.A. Jebali A. Bazrafshan B. Mehrtashfar S. Shabani S. Tavakoli A. Hekmatimoghaddam S.H. Sarli A. Azizi H. Izadi P. Coinhibition of overexpressed genes in acute myeloid leukemia subtype M2 by gold nanoparticles functionalized with five antisense oligonucleotides and one anti-CD33(+)/CD34(+) aptamer Cancer Gene Ther. 2016 23 315 320 10.1038/cgt.2016.33 27514505
109. Wen J. Tao W. Hao S. Iyer S.P. Zu Y. A unique aptamer-drug conjugate for targeted therapy of multiple myeloma Leukemia 2016 30 987 991 10.1038/leu.2015.216 26242462
110. Jiang D. Wang L. Lin H. Wu X. Zhang M. Xu S. Long Z. Bing T. Selection and characterization of aptamers against CD38 for clinical diagnostics Chin. Chem. Lett. 2026 37 111502 10.1016/j.cclet.2025.111502
111. Somasunderam A. Thiviyanathan V. Tanaka T. Li X. Neerathilingam M. Lokesh G.L. Mann A. Peng Y. Ferrari M. Klostergaard J. Combinatorial selection of DNA thioaptamers targeted to the HA binding domain of human CD44 Biochemistry 2010 49 9106 9112 10.1021/bi1009503 20843027 PMC2981344
112. Pecak A. Skalniak L. Pels K. Ksiazek M. Madej M. Krzemien D. Malicki S. Wladyka B. Dubin A. Holak T.A. Anti-CD44 DNA Aptamers Selectively Target Cancer Cells Nucleic Acid. Ther. 2020 30 289 298 10.1089/nat.2019.0833 32379519
113. Gao T. Li W. Ma J. Chen Y. Wang Z. Sun N. Pei R. Selection of DNA aptamer recognizing CD44 for high-e ffi ciency capture of circulating tumor cells Talanta 2023 262 124728 10.1016/j.talanta.2023.124728 37247446
114. Wang H. He W. Elizondo-Riojas M.A. Zhou X. Lee T.J. Gorenstein D.G. Development and Characterization of CD44-Targeted X-Aptamers with Enhanced Binding Affinity for Cancer Therapeutics Bioengineering 2025 12 113 10.3390/bioengineering12020113 40001633 PMC11852163
115. Wu X. Zhao Z. Bai H. Fu T. Yang C. Hu X. Liu Q. Champanhac C. Teng I.T. Ye M. DNA Aptamer Selected against Pancreatic Ductal Adenocarcinoma for in vivo Imaging and Clinical Tissue Recognition Theranostics 2015 5 985 994 10.7150/thno.11938 26155314 PMC4493536
116. Cheng E.L. Kacherovsky N. Pun S.H. Aptamer-Based Traceless Multiplexed Cell Isolation Systems ACS Appl. Mater. Interfaces 2022 14 44136 44146 10.1021/acsami.2c11783 36149728
117. Zhao N. Pei S.N. Qi J. Zeng Z. Iyer S.P. Lin P. Tung C.H. Zu Y. Oligonucleotide aptamer-drug conjugates for targeted therapy of acute myeloid leukemia Biomaterials 2015 67 42 51 10.1016/j.biomaterials.2015.07.025 26204224 PMC4550516
118. Li X. Dai J. Shi Y. Chen J. Zhou F. Qian X. Wang P. Fu X. Tan W. Bispecific Aptamer-Drug Conjugates Selectively Eliminate Malignant Hematologic Cells for Treating Acute Myeloid Leukemia Langmuir 2025 41 2580 2590 10.1021/acs.langmuir.4c04350 39841114
119. Dwivedy A. Baskaran D. Sharma G. Hong W. Gandavadi D. Krissanaprasit A. Han J. Liu Y. Zimmers Z. Mafokwane T. Engineering Novel DNA Nanoarchitectures for Targeted Drug Delivery and Aptamer mediated Apoptosis in Cancer Therapeutics Adv. Funct. Mater. 2025 35 2425394 10.1002/adfm.202425394 40487293 PMC12143806
120. Chen Y. Li Q. Lou S. Zeng H. Chen S. Design and development of an aptamer targeting C-type lectin-like molecule-1 as a biomarker for acute myeloid leukemia: A SELEX approach Front. Bioeng. Biotechnol. 2025 13 1601453 10.3389/fbioe.2025.1601453 40821668 PMC12354661
121. Santulli-Marotto S. Nair S.K. Rusconi C. Sullenger B. Gilboa E. Multivalent RNA aptamers that inhibit CTLA-4 and enhance tumor immunity Cancer Res. 2003 63 7483 7489 14612549
122. Huang B.T. Lai W.Y. Chang Y.C. Wang J.W. Yeh S.D. Lin E.P. Yang P.C. A CTLA-4 Antagonizing DNA Aptamer with Antitumor Effect Mol. Ther. Nucleic Acids 2017 8 520 528 10.1016/j.omtn.2017.08.006 28918052 PMC5573796
123. Hui Y. Shan L. Lin-Fu Z. Jian-Hua Z. Selection of DNA aptamers against DC-SIGN protein Mol. Cell. Biochem. 2007 306 71 77 10.1007/s11010-007-9555-x 17660953 PMC7089390
124. Mallikaratchy P. Tang Z. Kwame S. Meng L. Shangguan D. Tan W. Aptamer directly evolved from live cells recognizes membrane bound immunoglobin heavy mu chain in Burkitt’s lymphoma cells Mol. Cell. Proteom. 2007 6 2230 2238 10.1074/mcp.M700026-MCP200 17875608
125. Mallikaratchy P.R. Ruggiero A. Gardner J.R. Kuryavyi V. Maguire W.F. Heaney M.L. McDevitt M.R. Patel D.J. Scheinberg D.A. A multivalent DNA aptamer specific for the B-cell receptor on human lymphoma and leukemia Nucleic Acids Res. 2011 39 2458 2469 10.1093/nar/gkq996 21030439 PMC3064813
126. Li X. Wang T. Xie T. Dai J. Zhang Y. Ling N. Guo J. Li C. Sun X. Zhang X. Aptamer-Mediated Enrichment of Rare Circulating Fetal Nucleated Red Blood Cells for Noninvasive Prenatal Diagnosis Anal. Chem. 2023 95 5419 5427 10.1021/acs.analchem.3c00115 36920371
127. Bates P.J. Kahlon J.B. Thomas S.D. Trent J.O. Miller D.M. Antiproliferative activity of G-rich oligonucleotides correlates with protein binding J. Biol. Chem. 1999 274 26369 26377 10.1074/jbc.274.37.26369 10473594
128. An Y. Hu Y. Li X. Li Z. Duan J. Yang X.D. Selection of a novel DNA aptamer against OFA/iLRP for targeted delivery of doxorubicin to AML cells Sci. Rep. 2019 9 7343 10.1038/s41598-019-43910-3 31089250 PMC6517398
129. An Y. Yao F. Li X. Jiang Q. Yang X.-D. Targeted drug delivery to AML by OFA/iLRP aptamer guided DNA nanostructure Sci. Rep. 2026 16 4377 10.1038/s41598-025-34487-1 41501129 PMC12865006
130. Zhang Y. Xu H. Wang X. Wang L. Liu R. Li L. Zhou H. Single-strained DNA aptamers mask RhD antigenic epitopes on human RhD+ red blood cells to escape alloanti-RhD immunological recognition Mol. Med. Rep. 2020 21 1841 1848 10.3892/mmr.2020.10985 32319623 PMC7057830
131. Yang M. Jiang G. Li W. Qiu K. Zhang M. Carter C.M. Al-Quran S.Z. Li Y. Developing aptamer probes for acute myelogenous leukemia detection and surface protein biomarker discovery J. Hematol. Oncol. 2014 7 5 10.1186/1756-8722-7-5 24405684 PMC3895837
132. Martinis E. Tonon S. Colamatteo A. La Cava A. Matarese G. Pucillo C.E.M. B cell immunometabolism in health and disease Nat. Immunol. 2025 26 366 377 10.1038/s41590-025-02102-0 39984733
133. Zaslavsky M.E. Craig E. Michuda J.K. Sehgal N. Ram-Mohan N. Lee J.Y. Nguyen K.D. Hoh R.A. Pham T.D. Roltgen K. Disease diagnostics using machine learning of B cell and T cell receptor sequences Science 2025 387 eadp2407 10.1126/science.adp2407 39977494 PMC12061481
134. Trivedi N. Pitner R.A. Rawlings D.J. James R.G. Engineering B cells to treat and study human disease Nat. Biotechnol. 2025 43 1431 1444 10.1038/s41587-025-02757-y 40764821
135. Walsh R. DeRosa M.C. Retention of function in the DNA homolog of the RNA dopamine aptamer Biochem. Biophys. Res. Commun. 2009 388 732 735 10.1016/j.bbrc.2009.08.084 19699181
136. Fang Z. Feng X. Tang F. Jiang H. Han S. Tao R. Lu C. Aptamer Screening: Current Methods and Future Trend towards Non-SELEX Approach Biosensors 2024 14 350 10.3390/bios14070350 39056626 PMC11274700
137. Kunzli M. Masopust D. CD4(+) T cell memory Nat. Immunol. 2023 24 903 914 10.1038/s41590-023-01510-4 37156885 PMC10343737
138. Koh C.H. Lee S. Kwak M. Kim B.S. Chung Y. CD8 T-cell subsets: Heterogeneity, functions, and therapeutic potential Exp. Mol. Med. 2023 55 2287 2299 10.1038/s12276-023-01105-x 37907738 PMC10689838
139. Shah K. Al-Haidari A. Sun J. Kazi J.U. T cell receptor (TCR) signaling in health and disease Signal Transduct. Target. Ther. 2021 6 412 10.1038/s41392-021-00823-w 34897277 PMC8666445
140. Vivier E. Rebuffet L. Narni-Mancinelli E. Cornen S. Igarashi R.Y. Fantin V.R. Natural killer cell therapies Nature 2024 626 727 736 10.1038/s41586-023-06945-1 38383621
141. Chen S. Zhu H. Jounaidi Y. Comprehensive snapshots of natural killer cells functions, signaling, molecular mechanisms and clinical utilization Signal Transduct. Target. Ther. 2024 9 302 10.1038/s41392-024-02005-w 39511139 PMC11544004
142. Senjor E. Ko M.-W. Kaur K. Chen P.-C. Breznik B. Chovatiya N. Kos J. Jewett A. Multifaceted nature of natural killer cells: Potential mode of interaction and shaping of stem cells NK Cells in Cancer Immunotherapy: Successes and Challenges Academic Press San Diego, CA, USA 2023 3 25
143. Yang S. Wen J. Li H. Xu L. Liu Y. Zhao N. Zeng Z. Qi J. Jiang W. Han W. Aptamer-Engineered Natural Killer Cells for Cell-Specific Adaptive Immunotherapy Small 2019 15 e1900903 10.1002/smll.201900903 31026116 PMC6541510
144. Anastasiadi A.T. Arvaniti V.Z. Hudson K.E. Kriebardis A.G. Stathopoulos C. D’Alessandro A. Spitalnik S.L. Tzounakas V.L. Exploring unconventional attributes of red blood cells and their potential applications in biomedicine Protein Cell 2024 15 315 330 10.1093/procel/pwae001 38270470 PMC11074998
145. Cao H. Antonopoulos A. Henderson S. Wassall H. Brewin J. Masson A. Shepherd J. Konieczny G. Patel B. Williams M.L. Red blood cell mannoses as phagocytic ligands mediating both sickle cell anaemia and malaria resistance Nat. Commun. 2021 12 1792 10.1038/s41467-021-21814-z 33741926 PMC7979802
146. Mithoowani S. Laureano M. Crowther M.A. Hillis C.M. Investigation and management of erythrocytosis Can. Med. Assoc. J. 2020 192 E913 E918 10.1503/cmaj.191587 32778603 PMC7829024
147. Zhang N. Chen Z. Liu D. Jiang H. Zhang Z.K. Lu A. Zhang B.T. Yu Y. Zhang G. Structural Biology for the Molecular Insight between Aptamers and Target Proteins Int. J. Mol. Sci. 2021 22 4093 10.3390/ijms22084093 33920991 PMC8071422
148. Lakhin A.V. Tarantul V.Z. Gening L.V. Aptamers: Problems, Solutions and Prospects Acta Naturae 2013 5 34 43 10.32607/20758251-2013-5-4-34-43 24455181 PMC3890987
149. Davydova A. Vorobyeva M. Aptamer-Based Biosensors for the Colorimetric Detection of Blood Biomarkers: Paving the Way to Clinical Laboratory Testing Biomedicines 2022 10 1606 10.3390/biomedicines10071606 35884911 PMC9313021
150. Pan J. Wan J. Methodological comparison of FACS and MACS isolation of enriched microglia and astrocytes from mouse brain J. Immunol. Methods 2020 486 112834 10.1016/j.jim.2020.112834 32810482
151. Marsman C. Jorritsma T. Ten Brinke A. van Ham S.M. Flow Cytometric Methods for the Detection of Intracellular Signaling Proteins and Transcription Factors Reveal Heterogeneity in Differentiating Human B Cell Subsets Cells 2020 9 2633 10.3390/cells9122633 33302385 PMC7762542
152. Aslam A. Khawaja S. Qazi R.e. Mian A.A. Rehman F.U. Cell Sorting for Biomedical Applications Using Superparamagnetic Iron Oxide Nanoparticles BioNanoScience 2025 15 413 10.1007/s12668-025-02040-z
153. Gray B.P. Requena M.D. Nichols M.D. Sullenger B.A. Aptamers as Reversible Sorting Ligands for Preparation of Cells in Their Native State Cell Chem. Biol. 2020 27 232 244.e7 10.1016/j.chembiol.2019.12.004 31879266 PMC7038790
154. Chen M. Chang P. Zhang Z. Liu D. Hou R. Shi M. Li J. Xu K. Zheng J. Development of a DNA Aptamer-Based Approach to Noninvasively Image CAR-T Cells In Vivo and Traceless Enrichment In Vitro Adv. Sci. 2025 12 e2506746 10.1002/advs.202506746 PMC12302554 40349166
155. Li Y. Zamay T.N. Luzan N.A. Pryakhin E.A. Styazhkina E.V. Osminkina L.A. Kolovskaya O.S. Dymova M.A. Kuligina E.V. Richter V.A. Aptamers as a new frontier in targeted cancer therapy Adv. Drug Deliv. Rev. 2025 226 115692 10.1016/j.addr.2025.115692 41015208
156. Zhu Y. Zhang W. Chen J. Binary Nanodrug-Delivery System Designed for Leukemia Therapy: Aptamer- and Transferrin-Codecorated Daunorubicin- and Luteolin-Coloaded Nanoparticles Drug Des. Dev. Ther. 2023 17 1 13 10.2147/DDDT.S387246 36636745 PMC9830956
157. Chowdhury R. Eslami S. Pham C.V. Rai A. Lin J. Hou Y. Greening D.W. Duan W. Role of aptamer technology in extracellular vesicle biology and therapeutic applications Nanoscale 2024 16 11457 11479 10.1039/D4NR00207E 38856692
158. Gong Y. Tian S. Xuan Y. Zhang S. Lipid and polymer mediated CRISPR/Cas9 gene editing J. Mater. Chem. B 2020 8 4369 4386 10.1039/D0TB00207K 32364557
159. Yu Y.H. Tian W.T. Grauffel C. Lin W.C. Hsieh M.Y. Wu P.W. Lee H.J. Peng C.J. Lin P.H. Chu H.M. An Antibody-Drug Conjugate for Multiple Myeloma Prepared by Multi-Arm Linkers Adv. Sci. 2024 11 e2307852 10.1002/advs.202307852 PMC11132082 38477561
160. Lin C. Hadfield M.J. Santopietro A. Lagos G. Cheng L. El-Deiry W.S. Aggarwal R. Mega A. Hyams E. Carneiro B.A. The evolving landscape of antibody-drug conjugates (ADCs) for treatment of prostate cancer NPJ Precis. Oncol. 2025 9 351 10.1038/s41698-025-01131-0 41238753 PMC12618892
161. Neff C.P. Zhou J. Remling L. Kuruvilla J. Zhang J. Li H. Smith D.D. Swiderski P. Rossi J.J. Akkina R. An aptamer-siRNA chimera suppresses HIV-1 viral loads and protects from helper CD4(+) T cell decline in humanized mice Sci. Transl. Med. 2011 3 66ra66 10.1126/scitranslmed.3001581 PMC3138523 21248316
162. Wheeler L.A. Trifonova R. Vrbanac V. Basar E. McKernan S. Xu Z. Seung E. Deruaz M. Dudek T. Einarsson J.I. Inhibition of HIV transmission in human cervicovaginal explants and humanized mice using CD4 aptamer-siRNA chimeras J. Clin. Investig. 2011 121 2401 2412 10.1172/JCI45876 21576818 PMC3104760
163. Gao F. Yin J. Chen Y. Guo C. Hu H. Su J. Recent advances in aptamer-based targeted drug delivery systems for cancer therapy Front. Bioeng. Biotechnol. 2022 10 972933 10.3389/fbioe.2022.972933 36051580 PMC9424825
164. de la Puente P. Luderer M.J. Federico C. Jin A. Gilson R.C. Egbulefu C. Alhallak K. Shah S. Muz B. Sun J. Enhancing proteasome-inhibitory activity and specificity of bortezomib by CD38 targeted nanoparticles in multiple myeloma J. Control. Release 2018 270 158 176 10.1016/j.jconrel.2017.11.045 29196043 PMC6056271
165. Mayer G. Legen T. Patwari T. Weber A.M. Hunting Cells for Gentle Liberation Cell Chem. Biol. 2020 27 257 258 10.1016/j.chembiol.2020.02.006 32200913
166. Requena M.D. Yan A. Llanga T. Sullenger B.A. Reversible Aptamer Staining, Sorting, and Cleaning of Cells (Clean FACS) with Antidote Oligonucleotide or Nuclease Yields Fully Responsive Cells Nucleic Acid. Ther. 2024 34 12 17 10.1089/nat.2023.0050 38285522 PMC11302193
167. Byun J. Recent Progress and Opportunities for Nucleic Acid Aptamers Life 2021 11 193 10.3390/life11030193 33671039 PMC7997341
168. Du H. Rosbash M. The U1 snRNP protein U1C recognizes the 5′ splice site in the absence of base pairing Nature 2002 419 86 90 10.1038/nature00947 12214237
169. Reed C.R. Bonadonna D. Otto J.C. McDaniel C.G. Chabata C.V. Kuchibhatla M. Frederiksen J. Layzer J.M. Arepally G.M. Sullenger B.A. Aptamer-based factor IXa inhibition preserves hemostasis and prevents thrombosis in a piglet model of ECMO Mol. Ther. Nucleic Acids 2022 27 524 534 10.1016/j.omtn.2021.12.011 35036063 PMC8728519
170. Lincoff A.M. Mehran R. Povsic T.J. Zelenkofske S.L. Huang Z. Armstrong P.W. Steg P.G. Bode C. Cohen M.G. Buller C. Effect of the REG1 anticoagulation system versus bivalirudin on outcomes after percutaneous coronary intervention (REGULATE-PCI): A randomised clinical trial Lancet 2016 387 349 356 Erratum in Lancet 2016 , 387 , 1162 10.1016/s0140-6736(15)00515-2 26547100
171. Povsic T.J. Lawrence M.G. Lincoff A.M. Mehran R. Rusconi C.P. Zelenkofske S.L. Huang Z. Sailstad J. Armstrong P.W. Steg P.G. Pre-existing anti-PEG antibodies are associated with severe immediate allergic reactions to pegnivacogin, a PEGylated aptamer J. Allergy Clin. Immunol. 2016 138 1712 1715 10.1016/j.jaci.2016.04.058 27522158
172. Yu H. Pitoc G. Zhang M. Clancy J. Frederiksen J. Yan A. Francis S. Sullenger R. Rempel R. Gammell S. An Aptamer-Based EXACT Anticoagulant as a Sustainable, Animal-Free Alternative to Unfractionated Heparin Adv. Sci. 2025 13 e09867 10.1002/advs.202509867 PMC12822440 41053535
173. Stangherlin S. Lui N. Lee J.H. Liu J. Aptamer-based biosensors: From SELEX to biomedical diagnostics TrAC Trends Anal. Chem. 2025 191 118349 10.1016/j.trac.2025.118349
174. Nur Y. Gaffar S. Hartati Y.W. Subroto T. Applications of electrochemical biosensor of aptamers-based (APTASENSOR) for the detection of leukemia biomarker Sens. Bio-Sens. Res. 2021 32 100416 10.1016/j.sbsr.2021.100416
175. Zhang M. Gao G. Ding Y. Deng C. Xiang J. Wu H. A fluorescent aptasensor for the femtomolar detection of epidermal growth factor receptor-2 based on the proximity of G-rich sequences to Ag nanoclusters Talanta 2019 199 238 243 10.1016/j.talanta.2019.02.014 30952252
176. Sheraz M. Sun X.-F. Wang Y. Chen J. Sun L. Recent Developments in Aptamer-Based Sensors for Diagnostics Sensors 2024 24 7432 10.3390/s24237432 39685966 PMC11644826
177. Kordasht H.K. Hasanzadeh M. Aptamer based recognition of cancer cells: Recent progress and challenges in bioanalysis Talanta 2020 220 121436 10.1016/j.talanta.2020.121436 32928438
178. Shubin A.V. Kollar B. Dillon S.T. Pomahac B. Libermann T.A. Riella L.V. Blood proteome profiling using aptamer-based technology for rejection biomarker discovery in transplantation Sci. Data 2019 6 314 10.1038/s41597-019-0324-y 31819064 PMC6901551
179. Borghei Y.S. Hosseini M. Dadmehr M. Hosseinkhani S. Ganjali M.R. Sheikhnejad R. Visual detection of cancer cells by colorimetric aptasensor based on aggregation of gold nanoparticles induced by DNA hybridization Anal. Chim. Acta 2016 904 92 97 10.1016/j.aca.2015.11.026 26724767
180. Geleta G.S. A colorimetric aptasensor based on gold nanoparticles for detection of microbial toxins: An alternative approach to conventional methods Anal. Bioanal. Chem. 2022 414 7103 7122 10.1007/s00216-022-04227-9 35902394
181. Ranganathan V. Srinivasan S. Singh A. DeRosa M.C. An aptamer-based colorimetric lateral flow assay for the detection of human epidermal growth factor receptor 2 (HER2) Anal. Biochem. 2020 588 113471 10.1016/j.ab.2019.113471 31614117
182. Zhang F. Liu J. Label-Free Colorimetric Biosensors Based on Aptamers and Gold Nanoparticles: A Critical Review Anal. Sens. 2020 1 30 43 10.1002/anse.202000023
183. Chen Z. Yang Y. Liang Y. Cui X. Chai L. Wang X. Le T. Rethinking the Role of AuNPs in Colorimetric Aptasensors: Dominant Nonspecific Interactions with Antibiotics over Aptamer Recognition ACS Sens. 2026 11 522 532 10.1021/acssensors.5c03309 41276993
184. Lee M. Shin S. Kim S. Park N. Recent Advances in Biological Applications of Aptamer-Based Fluorescent Biosensors Molecules 2023 28 7327 10.3390/molecules28217327 37959747 PMC10647268
185. Tan L.L. Mohamad N.S. Electrochemical Aptamer-Based Biosensors for Sepsis Diagnosis: Recent Advances, Challenges, and Future Perspectives (2020–2025) Biosensors 2025 15 402 10.3390/bios15070402 40710052 PMC12292998
186. Shanaa O.A. Rumyantsev A. Sambuk E. Padkina M. In Vivo Production of RNA Aptamers and Nanoparticles: Problems and Prospects Molecules 2021 26 1422 10.3390/molecules26051422 33800717 PMC7961669
187. Afonin K.A. Dobrovolskaia M.A. Church G. Bathe M. Opportunities, Barriers, and a Strategy for Overcoming Translational Challenges to Therapeutic Nucleic Acid Nanotechnology ACS Nano 2020 14 9221 9227 10.1021/acsnano.0c04753 32706238 PMC7731581