| Literature DB >> 29928493 |
Ricardo L Pereira1, Isis C Nascimento1, Ana P Santos1, Isabella E Y Ogusuku1, Claudiana Lameu1, Günter Mayer2,3, Henning Ulrich1.
Abstract
Although the term 'cancer' was still over two thousand years away of being coined, the first known cases of the disease date back to about 3000BC, in ancient Egypt. Five thousand years later, still lacking a cure, it has become one of the leading causes of death, killing over half a dozen million people yearly. So far, monoclonal antibodies are the most successful immune-therapy tools when it comes to fighting cancer. The number of clinical trials that use them has been increasing steadily during the past few years, especially since the Food and Drug Administration greenlit the use of the first immune-checkpoint blockade antibodies. However, albeit successful, this approach does come with the cost of auto-inflammatory toxicity. Taking this into account, the development of new therapeutic reagents with low toxicity becomes evident, particularly ones acting in tandem with the tools currently at our disposal. Ever since its discovery in the early nineties, aptamer technology has been used for a wide range of diagnostic and therapeutic applications. With similar properties to those of monoclonal antibodies, such as high-specificity of recognition and high-affinity binding, and the advantages of being developed using in vitro selection procedures, aptamers quickly became convenient building blocks for the generation of multifunctional constructs. In this review, we discuss the steps involved in the in vitro selection process that leads to functional aptamers - known as Systematic Evolution of Ligands by Exponential Enrichment - as well as the most recent applications of this technology in diagnostic and treatment of oncological illnesses. Moreover, we also suggest ways to improve such use.Entities:
Keywords: Cell-SELEX; aptamers; cancer; clinical application
Year: 2018 PMID: 29928493 PMCID: PMC6003562 DOI: 10.18632/oncotarget.25260
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1Depiction of the aptamer structure and its interaction with the target
(A) The ssDNA is subjected to a set of conditions that enable it to fold and adopt a secondary structure. (B) The ssDNA base pairs in the linear parts of the molecule interact via hydrogen bonds, (C) in the loops, however, the bases are free to interact with the targets and do so via hydrogen bonds and/or dipolar interactions.
Figure 2Schematic representation of the SELEX process
(A) Not only is the process iterative, but also (B) with each round, the stringency is increased, thus resulting in higher affinity and specificity. This increase is achieved by increasing both the number of washes and non-specific competitors, and decreasing the number of target molecules within every cycle.
Aptamers selected using the cell-SELEX procedure
| Aptamer | Cancer types | Target | Subtractive selection | Cycles of selection | Suggested function/application | Reference |
|---|---|---|---|---|---|---|
| GBI-10 | Glioblastoma | U251 cells line | 21 | identification of targets | Daniels et al., 2003 [ | |
| - | Glioblastoma Multiforme | A-172 cell line | - | 18 | Diagnosis, targeted drug delivery, and discovery of molecular marker | Bayrac et al., 2011 [ |
| GBM128 and GBM131 | Glioblastoma | U118-MG cell line | SVGp12 cells | 30 | Identification of glioblastoma biomarkers | Kang et al., 2012 [ |
| - | Glioblastoma | Tumor-initiating Cells (CD133+) | Non-stem glioma cells and neural progenitors cells | 8 | Aptamer-based therapies combined with conventional or targeted therapies | Kim et al., 2013 [ |
| U2, U8, U19 and U31 | Glioblastoma | U87 overexpressing EGFRvIII | U87MG cell line | 11 | molecular imaging probe | Wu et al., 2014 [ |
| WQY-9-B | Gliosarcoma | K308 | SVGp12 | 16 | molecular probe for diagnosis | Wu et al., 2016 [ |
| Glioma | U87MG glioma cells | T98G cells | 14 | Discovery of new molecular targets | Cerchia et al., 2009 [ | |
| KMF2-1a | Breast cancer | MCF-10AT1 | MCF-10A1 | Cell type-specific intracellular delivery | Zhang et al., 2012 [ | |
| MS03 | Breast cancer | MCF-7 cells | MCF-10A and MCF-7sal cells | 13 | Diagnostic and therapeutic applications | Lu et al., 2015 [ |
| - | Breast cancer | TUBO cell line | CT26 cell line | 12 | Targeted breast cancer therapy | Moosavian et al., 2015 [ |
| KW16-13 | breast ductal carcinoma | MCF10CA1h | MCF10A | 18 | development as novel anti-tumor therapeutics | Chandrasekaran et al., 2016 [ |
| TD05 | B-cell lymphoma | Ramos cells | - | 23 | Tang et al., 2007 [ | |
| S3, S5, S12 and S27 | Nasopharyngeal carcinoma | NPC 5-8F cell line | NP69 cell line | 22 | Identification of biomarker for early diagnosis and targeted therapy | Jia et al., 2016 [ |
| - | Lung cancer | NCI-H69 SCLC cell line | NCIH661 NSCLC cell line | 25 | lung cancer subtyping during screening and appropriate treatment planning | Chen et al., 2008 [ |
| small cell lung cancer | SBC3 | RERF-LC-MA | 16 | Specific detection probes | Kunii et al., 2011 [ | |
| TLS1, TLS3, TLS4, TLS6, TLS7, TLS9, and TLS11 | Liver cancers | BNL 1ME A.7R.1 cell line | BNL CL.2 cell line | 16 | Development of molecular probe | Shangguan et al., 2008 [ |
| Liver cancer | HepG2 | THLE-2 | 19 | targeted therapies, and imaging probe | Xu et al., 2015 [ | |
| - | Hepatocarcinoma | HepG2 cells | Primary normal human liver hepatocyte cells, | 11 | Selective delivery of anticancer drugs | Ninomiya et al., 2013 [ |
| LY-1, 13, 46, 32, 27/45, and 7/43 | Hepatocellular carcinoma | HCCLM9 cell line | MHCC97L cell line | 10 | Identification of new diagnostic targets and developing new targeted therapeutics | Wang et al., 2013 [ |
| LY-1 | Liver cancers | HCCLM9 | MHCC97L | 9 | Development of molecular probe and chemotherapy for metastatic hepatocellular carcinoma | Rong et al., 2016 [ |
| - | Cholangiocarcinoma | QBC-939 cells | SMMC-7721 | 13 | early diagnosis and therapeutics | Wan et al., 2015 [ |
| - | Gastric carcinoma | AGS cell line | GES-1 cell line | 12 | Identify biomarkers for gastric cancer diagnosis and targeting therapy. | Cao et al., 2014 [ |
| PL1-8 | Pancreatic ductal adenocarcinoma | PL45 cell line | TOV-21G cell line | 23 | Biomarkers identification and drug delivery | Champanhac et al., 2015 [ |
| XQ-2d | Pancreatic ductal adenocarcinoma | PL45 cell line | hTERT-HPNE cell line | 15 | Wu et al., 2015 [ | |
| Aptamers 1 and 146 | Pancreatic cancer | HPAC cell line | HPDE cell line | 16 | CSCs targeting drug delivery, or circulating tumor cell detection | Kim et al., 2017 [ |
| Ovarian cancer | TOV-21G | HeLa | 22 | Identification of biomarkers | Van Simaeys et al., 2010 [ | |
| RLA01, RLA02, and RLA03 | Ovarian cancer | Caov-3 cell | HOSE 6-3 cells | 15 | Diagnostic and drug delivery | Benedetto et al., 2015 [ |
| - | Colorectal Cancer | DLD-1, Dukes’ type C colorectal adenocarcinoma | HCT 116 | 16 | Identify specific biomarkers | Sefah et al., 2010 [ |
| - | Metastatic colorectal cancer | LoVo cells | HCT-8 cells | 22 | multi-target cell imaging/ multi-target drug therapy | Li et al., 2014 [ |
| - | Colorectal cancer | CR-CSC x HCT-8 CRC line | HCT-8 CRC line x CR-CSC | 5 | colorectal cancer cells and stem cells | Hung et al., 2015 [ |
| XL-33-1 | Colon cancer | SW620 cells | SW480 cells | 14 | metastatic cancer diagnosis and treatment | Li et al., 2015 [ |
| - | Prostate cancer | PC3 | HeLa and SMMC-7721 cells | 17 | Diagnosis and target therapy | Wang et al., 2014 [ |
| - | Prostate adenocarcinoma | LNCaP cells | PC-3 cell line | 10 | Diagnostic and targeted drug delivery | Almasi et al., 2016 [ |
| - | Prostate cancer | PC-3 cell line | RWPE-1 | 9 | Identification of biomarker | Souza et al., 2016 [ |
| - | Osteosarcoma | U-2 OS cell line | SGC7901, MCF-7 and HT-1080 | 13 | specific diagnosis and developing probe-carrier-antitumor drug complexes and targeted therapies | Wang et al., 2015 [ |
Over the past few years, the number of cancer-related aptamers selected using cell-SELEX has increased significantly. Their applications are, clearly, diverse - from in vivo imaging to drug delivery, all the way to identification of new diagnostic targets.
Figure 3Strategies to enhance bio-therapeutic therapies in cancer using aptamers
Aptamer-siRNA chimeras can be used to stimulate receptor internalization, which leads to siRNA delivery within the cytoplasm. Aptamers can also be used to induce cellular uptake of therapeutic agents (drugs, other aptamers, nanoparticles, polymers) which can act in different ways by apoptosis induction, lower RNA expression, tumor regression, and other mechanisms.
Clinical trials undertaken with aptamers targeting cancer
| Trial number | Cancer type | Study phase | Primary purpose |
|---|---|---|---|
| NCT02957370 | Bladder | Observational | Discover biomarker |
| NCT03385148 | Colorectal | Phase 1 | Diagnostic |
| NCT01830244 | Breast | Phase 2 | Treatment* |
| NCT00056199 | Retinal | Phase 1 | Treatment |
| NCT01034410 | Acute myeloid leukemia | Phase 2 | Treatment |
*The aptamer is not the focus of the study. Samples of patients who agree will be used to isolate cancer initiating cells generate breast cancer models and using aptamers to target tumors.
The number of known cancer-targeting aptamers in clinical trials corresponds to, approximately, 5% of the total number of aptamers known to be in that development stage. This content is of public domain (https://clinicaltrials.gov).