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Aptamers are short DNA/RNA oligonucleotides capable of binding to target molecules with high affinity and specificity. The process of selecting an aptamer is called Systematic Evolution of Ligands by Exponential Enrichment (SELEX). Thanks to the inherit merits, aptamers have been used in a wide range of applications, including disease diagnosis, targeted delivery agents and therapeutic uses. To date, great achievements regarding the selection, modifications and application of aptamers have been made. However, few aptamer-based products have already successfully entered into clinical and industrial use. Besides, it is still a challenge to obtain aptamers with high affinity in a more efficient way. Thus, it is important to comprehensively review the current shortage and achievement of aptamer-related technology. In this review, we first present the limitations and notable advances of aptamer selection. Then, we compare the different methods used in the kinetic characterization of aptamers. We also discuss the impetus and developments of the clinical application of aptamers.

RNA modification plays a crucial role in many biological functions, and its abnormal regulation is associated with the progression of cancer. Among them, N 6 -methyladenine (m 6 A) is the most abundant RNA modification. Methyltransferase-like 14 (METTL14) is the central component of the m 6 A methylated transferase complex, which is involved in the dynamic reversible process of m 6 A modification.  METTL14 acts as both an oncogene and tumor suppressor gene to regulate the occurrence and development of various cancers. The abnormal m 6 A level induced by METTL14 is related to tumorigenesis, proliferation, metastasis, and invasion. To date, the molecular mechanism of METTL14 in various malignant tumors has not been fully studied. In this paper, we systematically summarize the latest research progress on METTL14 as a new biomarker for cancer diagnosis and its biological function in human tumors and discuss its potential clinical application. This study aims to provide new ideas for targeted therapy and improved prognoses in cancer.

Sclerostin negatively regulates bone formation by antagonizing Wnt signalling. An antibody targeting sclerostin for the treatment of postmenopausal osteoporosis was approved by the U.S. Food and Drug Administration, with a boxed warning for cardiovascular risk. Here we demonstrate that sclerostin participates in protecting cardiovascular system and inhibiting bone formation via different loops. Loop3 deficiency by genetic truncation could maintain sclerostin’s protective effect on the cardiovascular system while attenuating its inhibitory effect on bone formation. We identify an aptamer, named aptscl56, which specifically targets sclerostin loop3 and use a modified aptscl56 version, called Apc001PE, as specific in vivo pharmacologic tool to validate the above effect of loop3. Apc001PE has no effect on aortic aneurysm and atherosclerotic development in ApoE −/− mice and hSOST ki .ApoE −/− mice with angiotensin II infusion. Apc001PE can promote bone formation in hSOST ki mice and ovariectomy-induced osteoporotic rats. In summary, sclerostin loop3 cannot participate in protecting the cardiovascular system, but participates in inhibiting bone formation. Antibodies targeting sclerostin can ameliorate postmenopausal osteoporosis but present some cardiovascular risk. Here the authors show that the cardiovascular and skeletal effects of sclerostin are mediated by different loops, suggesting ways to preserve the positive effects on bone formation while avoiding the negative cardiovascular consequences.

Background Skeletal muscle atrophy induced by either aging (sarcopenia) or mechanical unloading is associated with serious health consequences. Long non‐coding RNAs (lncRNAs) are implicated as important regulators in numerous physiological and pathological processes. Methods Microarray analysis was performed to identify the differentially expressed lncRNAs in skeletal muscle between adult and aged mice. The most decreased lncRNA in aged skeletal muscle was identified. The C2C12 mouse myoblast cells were used to assess the biological function of the lncRNA in vitro. The target microRNA of lncRNA and the target protein of microRNA were predicted by bioinformatics analysis and validated in vitro. Furthermore, the biology function of the lncRNA in vivo was investigated by local overexpression or knockdown the lncRNA in skeletal muscle. The therapeutic effect of the lncRNA overexpression in age‐related or mechanical unloading‐induced muscle atrophy was also evaluated. Results We identified a novel lncRNA (muscle anabolic regulator 1, MAR1) which was highly expressed in mice skeletal muscle and positively correlated with muscle differentiation and growth in vitro and in vivo. We predicted and validated that microRNA‐487b (miR‐487b) was a direct target of MAR1. We also predicted and validated that Wnt5a, an important regulator during myogenesis, was a target of miR‐487b in C2C12 cells. Our findings further demonstrated that enforced MAR1 expression in myoblasts led to derepression of Wnt5a. Moreover, MAR1 promoted skeletal muscle mass/strength and Wnt5a protein level in mice. Enforced MAR1 expression in mice attenuated muscle atrophy induced by either aging or unloading. Conclusions The newly identified lncRNA MAR1 acts as a miR‐487b sponge to regulate Wnt5a protein, resulting in promoting muscle differentiation and regeneration. MAR1 could be a novel therapeutic target for treating muscle atrophy induced by either aging or mechanical unloading.

Several virtual screening models are proposed to screen small molecules only targeting primary miRNAs without selectivity. Few attempts have been made to develop virtual screening strategies for discovering small molecules targeting mature miRNAs. Mature miRNAs and their specific target mRNA can form unique functional loops during argonaute (AGO)‐mediated miRNA–mRNA interactions, which may serve as potential targets for small‐molecule drug discovery. Thus, a loop‐based and AGO‐incorporated virtual screening model is constructed for targeting the loops. The previously published studies have found that miR‐214 can target ATF4 to inhibit osteoblastic bone formation, whereas miR‐214 can target TRAF3 to promote osteoclast activity. By using the virtual model, the top ten candidate small molecules targeting miR‐214‐ATF4 mRNA interactions and top ten candidate small molecules targeting miR‐214‐TRAF3 mRNA interactions are selected, respectively. Based on both in vitro and in vivo data, one small molecule can target miR‐214‐ATF4 mRNA to promote ATF4 protein expression and enhance osteogenic potential, whereas one small molecule can target miR‐214‐TRAF3 mRNA to promote TRAF3 protein expression and inhibit osteoclast activity. These data indicate that the loop‐based and AGO‐incorporated virtual screening model can help to obtain small molecules specifically targeting miRNA–mRNA interactions to rescue bone phenotype in genetically modified mice. It is found that mature miRNA and their specific target mRNA can form unique functional loops during argonaute (AGO)‐mediated miRNA–mRNA interactions. Thus, a loop‐based and AGO‐incorporated virtual screening model is constructed for screening small molecules targeting the loops. By using the virtual model, two small molecules are obtained that can specifically target miR‐214‐ATF4 mRNA interactions and miR‐214‐TRAF3 mRNA interactions, respectively.

Neuroblastoma ranks as the most commonly seen and deadly solid tumour in infancy. The aberrant activity of m6A‐RNA methyltransferase METTL3 is involved in human cancers. Therefore, functional genetic variants in the METTL3 gene may contribute to neuroblastoma risk. In the current nine‐centre case‐control study, we aimed to analyse the association between the METTL3 gene single nucleotide polymorphisms (SNPs) and neuroblastoma susceptibility. We genotyped four METTL3 gene SNPs (rs1061026 T>G, rs1061027 C>A, rs1139130 A>G, and rs1263801 G>C) in 968 neuroblastoma patients and 1814 controls in China. We found significant associations between these SNPs and neuroblastoma risk in neither single‐locus nor combined analyses. Interestingly, in the stratified analysis, we observed a significant risk association with rs1061027 AA in subgroups of children ≤ 18 months of age (adjusted OR = 1.87, 95% CI = 1.03‐3.41, P = .040) and females (adjusted OR = 1.86, 95% CI = 1.07‐3.24, P = .028). Overall, we identified a significant association between METTL3 gene rs1061027 C>A polymorphism and neuroblastoma risk in children ≤18 months of age and females. Our findings provide novel insights into the genetic determinants of neuroblastoma.

Rationale: Sclerostin inhibition demonstrated bone anabolic potential in osteogenesis imperfecta (OI) mice, whereas humanized therapeutic sclerostin antibody romosozumab for postmenopausal osteoporosis imposed clinically severe cardiac ischemic events. Therefore, it is desirable to develop the next generation sclerostin inhibitors to promote bone formation without increasing cardiovascular risk for OI. Methods and Results: Our data showed that sclerostin suppressed inflammatory responses, prevented aortic aneurysm (AA) and atherosclerosis progression in hSOSTki.Col1a2+/G610C.ApoE-/- mice. Either loop2&3 deficiency or inhibition attenuated sclerostin's suppressive effects on expression of inflammatory cytokines and chemokines in vitro, whilst loop3 deficiency maintained the protective effect of sclerostin on cardiovascular system both in vitro and in vivo. Moreover, loop3 was critical for sclerostin's antagonistic effect on bone formation in Col1a2+/G610C mice. Accordingly, a sclerostin loop3-specific aptamer aptscl56 was identified by our lab. It could recognize both recombinant sclerostin and sclerostin in the serum of OI patients via targeting loop3. PEG40k conjugated aptscl56 (Apc001PE) demonstrated to promote bone formation, increase bone mass and improve bone microarchitecture integrity in Col1a2+/G610C mice via targeting loop3, while did not show influence in inflammatory response, AA and atherosclerosis progression in Col1a2+/G610C.ApoE-/- mice with Angiotensin II infusion. Further, Apc001PE had no influence in the protective effect of sclerostin on cardiovascular system in hSOSTki.Col1a2+/G610C.ApoE-/- mice, while it inhibited the antagonistic effect of sclerostin on bone formation in hSOSTki.Col1a2+/G610C mice via targeting loop3. Apc001PE was non-toxic to healthy rodents, even at ultrahigh dose. Apc001PE for OI was granted orphan drug designation by US-FDA in 2019 (DRU-2019-6966). Conclusion: Sclerostin loop3-specific aptamer Apc001PE promoted bone formation without increasing cardiovascular risk in OI mice.

Biomarkers are detectable molecules that can reflect specific physiological states of cells, organs, and organisms and therefore be regarded as indicators for specific diseases. And the discovery of biomarkers plays an essential role in cancer management from the initial diagnosis to the final treatment regime. Practically, reliable clinical biomarkers are still limited, restricted by the suboptimal methods in biomarker discovery. Nucleic acid aptamers nowadays could be used as a powerful tool in the discovery of protein biomarkers. Nucleic acid aptamers are single-strand oligonucleotides that can specifically bind to various targets with high affinity. As artificial ssDNA or RNA, aptamers possess unique advantages compared to conventional antibodies. They can be flexible in design, low immunogenicity, relative chemical/thermos stability, as well as modifying convenience. Several SELEX (Systematic Evolution of Ligands by Exponential Enrichment) based methods have been generated recently to construct aptamers for discovering new biomarkers in different cell locations. Secretome SELEX-based aptamers selection can facilitate the identification of secreted protein biomarkers. The aptamers developed by cell-SELEX can be used to unveil those biomarkers presented on the cell surface. The aptamers from tissue-SELEX could target intracellular biomarkers. And as a multiplexed protein biomarker detection technology, aptamer-based SOMAScan can analyze thousands of proteins in a single run. In this review, we will introduce the principle and workflow of variations of SELEX-based methods, including secretome SELEX, ADAPT, Cell-SELEX and tissue SELEX. Another powerful proteome analyzing tool, SOMAScan, will also be covered. In the second half of this review, how these methods accelerate biomarker discovery in various diseases, including cardiovascular diseases, cancer and neurodegenerative diseases, will be discussed.

[...]we found that four SNPs had potential functions, namely, three SNPs of ERCC1, which are rs2298881, rs11615, and rs3212986, and one SNP of XPF (rs2276466). Logistic regression analysis was also performed to calculate the age- and gender-adjusted odds ratio (ORs) values and 95% confidence interval (CIs) to quantify the degree of association. Genotype Cases (n = 314) Controls (n = 380) P value∗ Crude OR (95% CI) P value Adjusted OR (95% CI)† P value† ERCC1 rs2298881 C > A (HWE = 0.353)  CC 132 (42.04) 139 (36.58) 1.00 1.00  CA 138 (43.95) 171 (45.00) 0.85 (0.61–1.18) 0.330 0.87 (0.63–1.21) 0.408  AA 44 (14.01) 70 (18.42) 0.66 (0.42–1.03) 0.070 0.67 (0.43–1.05) 0.081  Additive 0.069 0.82 (0.66–1.02) 0.069 0.83 (0.67–1.03) 0.086  Dominant 182 (57.96) 241 (63.42) 0.142 0.80 (0.59–1.08) 0.143 0.81 (0.60–1.11) 0.185  Recessive 270 (85.99) 310 (81.58) 0.119 0.72 (0.48–1.09) 0.120 0.72 (0.48–1.09) 0.122 ERCC1 rs11615 G > A (HWE = 0.034)  GG 171 (54.46) 231 (60.79) 1.00 1.00  GA 126 (40.13) 121 (31.84) 1.41 (1.02–1.93) 0.036 1.39 (1.01–1.91) 0.045  AA 17 (5.41) 28 (7.37) 0.82 (0.44–1.55) 0.540 0.81 (0.43–1.53) 0.515  Additive 0.352 1.12 (0.88–1.43) 0.352 1.11 (0.87–1.42) 0.400  Dominant 143 (45.54) 149 (39.21) 0.093 1.30 (0.96–1.76) 0.093 1.28 (0.94–1.73) 0.114  Recessive 297 (94.59) 352 (92.63) 0.298 0.72 (0.39–1.34) 0.300 0.71 (0.38–1.33) 0.290 ERCC1 rs3212986 C > A (HWE = 0.474)  CC 132 (42.04) 162 (42.63) 1.00 1.00  CA 146 (46.50) 177 (46.58) 1.01 (0.74–1.39) 0.940 1.01 (0.73–1.39) 0.951  AA 36 (11.46) 41 (10.79) 1.08 (0.65–1.78) 0.771 1.08 (0.65–1.79) 0.761  Additive 0.801 1.03 (0.82–1.29) 0.801 1.03 (0.82–1.29) 0.798  Dominant 182 (57.96) 218 (57.37) 0.875 1.03 (0.76–1.39) 0.875 1.02 (0.76–1.39) 0.881  Recessive 278 (88.54) 339 (89.21) 0.778 1.07 (0.67–1.72) 0.778 1.08 (0.67–1.73) 0.763 XPF rs2276466 C > G (HWE = 0.633)  CC 179 (57.74) 223 (58.68) 1.00 1.00  CG 117 (37.74) 134 (35.26) 1.09 (0.79–1.49) 0.603 1.13 (0.82–1.56) 0.457  GG 14 (4.52) 23 (6.05) 0.76 (0.38–1.52) 0.434 0.75 (0.37–1.51) 0.420  Additive 0.897 0.98 (0.77–1.27) 0.897 1.00 (0.78–1.29) 1.000  Dominant 131 (42.26) 157 (41.32) 0.803 1.04 (0.77–1.41) 0.803 1.07 (0.79–1.46) 0.662  Recessive 296 (95.48) 357 (93.95) 0.373 0.73 (0.37–1.45) 0.375 0.72 (0.36–1.42) 0.343 Combined effect of risk genotypes‡  0–1 61 (19.43) 96 (25.26) 1.00 1.00  2–3 253 (80.57) 284 (74.74) 0.067 1.40 (0.98–2.02) 0.068 1.41 (0.98–2.02) 0.066 Data are presented as n (%). ∗χ2 -test for genotype distributions between glioma patients and cancer-free controls. † Adjusted for age and gender. ‡ Risk genotypes were carriers with rs2298881 CC/CA, rs11615 GG/GA, rs3212986 CA/AA genotypes. [5,6] Variations in some alleles of ERCC1 gene polymorphisms may attenuate the capacity of DNA repair, and these mutations are mainly concentrated in the 3′ UTR while there are several polymorphisms in the coding region of XPF that bring about possible genetic instability. [...]some ERCC1/XPF genes SNPs may have effects on glioma. [...]the chosen SNPs have potential functions. [...]we lack functional experiments and need to understand how SNPs affect gliomas. [...]more attention should be paid to the interactions between environmental and genetic factors.

The recurrence and metastasis of children with mediastinal neuroblastoma (NB) are also occurred after surgery, chemotherapy, or radiotherapy. Strategies targeting the tumor microenvironment have been reported to improve survival; however, thorough investigations of monocytes and tumor-associated macrophages (Mϕs) with specialized functions in NB are still lacking. Our data first demonstrated polypyrimidine tract binding protein 2 (PTBP2) as a possible identifier in patients with mediastinal NB screened by proteomic profiling and that PTBP2 predicted good outcomes. Functional studies revealed that PTBP2 in NB cells induced the chemotactic activity and repolarization of tumor-associated monocytes and Mϕs, which, in turn, inhibited NB growth and dissemination. Mechanistically, PTBP2 prevents interferon regulatory factor 9 alternative splicing and upregulates signal transducers and activators of transcription 1 to stimulate C-C motif chemokine ligand 5 (CCL5) and interferon-stimulated gene factor-dependent type I interferon secretion, to induce monocyte/Mϕs chemotaxis, and to sustain monocytes in a proinflammatory phenotype. Our study defined a critical event of PTBP2-induced monocytes/Mϕs in NB progression and revealed that RNA splicing occurred by PTBP2 benefits immune compartmentalization between NB cells and monocytes. This work revealed the pathological and biological role of PTBP2 in NB development and indicates that PTBP2-induced RNA splicing benefits immune compartmentalization and predicted a favorable prognosis in mediastinal NB.