Cancer Diagnostics and Early Detection Using Electrochemical Aptasensors

Omage, Joel Imoukhuede; Easterday, Ethan; Rumph, Jelonia T.; Brula, Imamulhaq; Hill, Braxton; Kristensen, Jeffrey; Ha, Dat Thinh; Galindo, Cristi L.; Danquah, Michael K.; Sims, Naiya; Nguyen, Van Thuan

doi:10.3390/mi13040522

Cited by 14 publications

(3 citation statements)

References 123 publications

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“…Aptamer-based biosensors have been widely used in various fields, such as environmental monitoring [ 1 ], food quality and safety [ 2 ], and medical diagnostics and therapy [ 3 ], due to the physical and chemical features of aptamers for detection and small binding substances [ 4 ]. Moreover, the advancement in nanostructured materials has attracted much attention in recent years due to their potential applications and unique properties, including high reactivity, high functionalization, large surface-area-to-volume ratio, and small size [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

et al. 2022

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Nanomaterial-based aptasensors are useful devices capable of detecting small biological species. Determining suitable signal processing methods can improve the identification and quantification of target analytes detected by the biosensor and consequently improve the biosensor’s performance. In this work, we propose a data augmentation method to overcome the insufficient amount of available original data and long short-term memory (LSTM) to automatically predict the analyte concentration from part of a signal registered by three electrochemical aptasensors, with differences in bioreceptors, analytes, and the signals’ lengths for specific concentrations. To find the optimal network, we altered the following variables: the LSTM layer structure (unidirectional LSTM (LSTM) and bidirectional LSTM (BLSTM)), optimizers (Adam, RMSPROP, SGDM), number of hidden units, and amount of augmented data. Then, the evaluation of the networks revealed that the highest original data accuracy increased from 50% to 92% by exploiting the data augmentation method. In addition, the SGDM optimizer showed a lower performance prediction than that of the ADAM and RMSPROP algorithms, and the number of hidden units was ineffective in improving the networks’ performances. Moreover, the BLSTM nets showed more accurate predictions than those of the ULSTM nets on lengthier signals. These results demonstrate that this method can automatically detect the analyte concentration from the sensor signals.

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Section: Introductionmentioning

confidence: 99%

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

et al. 2022

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“…Aptamers have been successfully used as multifunctional tools in various fields, such as tumor diagnosis, targeted therapy, food detection, and analysis, as well as bioimaging. More specifically, as recognition elements, aptamers can be used not only to make different types of aptasensors [ 58 , 59 , 60 , 61 ] to detect and diagnose diseases but also to modify them to immune cells [ 29 , 62 , 63 , 64 , 65 ], which can impart targeting functions on immune cells.…”

Section: Discussionmentioning

confidence: 99%

Selection and Identification of an ssDNA Aptamer for Fibroblast Activation Protein

et al. 2023

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As a type II transmembrane serine protease, fibroblast activation protein (FAP) is specifically expressed on the surface of fibroblasts associated with a variety of epithelial-derived malignancies such as pancreatic cancer, breast cancer, and colon cancer. It participates in the processes of tumorigenesis, progression, and immunosuppression. FAP constitutes an important target for tumor treatment; however, the current studies on FAP are mainly related to structural characteristics, enzymatic properties, and biological functions, and aptamers of FAP have not been investigated. In this work, by using recombinant human FAP as the target, five candidate aptamers, which are AptFAP-A1, AptFAP-A2, AptFAP-A3, AptFAP-A4, and AptFAP-A5, were selected by capillary electrophoresis–systematic evolution of ligands by exponential enrichment (CE-SELEX), and their secondary structures were predicted to be mainly stem-loop. Moreover, the CE-laser-induced fluorescence (LIF) method was used to determine the equilibrium dissociation constant KD values between the FAP protein and candidate aptamers, and the KD value was in the low molar range. Finally, Cy5-labeled aptamers were co-incubated with human pancreatic cancer-associated fibroblasts highly expressing FAP protein, and confocal microscopy imaging showed that aptamer AptFAP-A4 had the highest affinities with the cells. The FAP aptamers screened in this study provide a promising direction for the development of rapid tumor diagnosis and targeted therapy.

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“…Although this immunoassay has high sensitivity and efficiency, the need for complicated washing steps and heterogeneous responses in this assay cause diverse antibody (Ab)-antigen interactions and diminished Ab performance [ 52 , 53 ], which affect detection sensitivity and experimental reusability [ 53 ]. Aptamers, on the other hand, have different significant advantages over antibodies, including their small size, low cost, increased chemical stability, and feasible design [ 54 , 55 ]. These characteristics have received widespread attention and have shown promise in addressing the aforementioned immunoassay concerns [ 56 ].…”

Section: Introductionmentioning

confidence: 99%

Electrochemical aptasensor based on the engineered core-shell MOF nanostructures for the detection of tumor antigens

et al. 2023

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It is essential to develop ultrasensitive biosensors for cancer detection and treatment monitoring. In the development of sensing platforms, metal-organic frameworks (MOFs) have received considerable attention as potential porous crystalline nanostructures. Core-shell MOF nanoparticles (NPs) have shown different diversities, complexities, and biological functionalities, as well as significant electrochemical (EC) properties and potential bio-affinity to aptamers. As a result, the developed core-shell MOF-based aptasensors serve as highly sensitive platforms for sensing cancer biomarkers with an extremely low limit of detection (LOD). This paper aimed to provide an overview of different strategies for improving selectivity, sensitivity, and signal strength of MOF nanostructures. Then, aptamers and aptamers-modified core-shell MOFs were reviewed to address their functionalization and application in biosensing platforms. Additionally, the application of core-shell MOF-assisted EC aptasensors for detection of several tumor antigens such as prostate-specific antigen (PSA), carbohydrate antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), human epidermal growth factor receptor-2 (HER2), cancer antigen 125 (CA-125), cytokeratin 19 fragment (CYFRA21-1), and other tumor markers were discussed. In conclusion, the present article reviews the advancement of potential biosensing platforms toward the detection of specific cancer biomarkers through the development of core-shell MOFs-based EC aptasensors.

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Cancer Diagnostics and Early Detection Using Electrochemical Aptasensors

Cited by 14 publications

References 123 publications

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

Selection and Identification of an ssDNA Aptamer for Fibroblast Activation Protein

Electrochemical aptasensor based on the engineered core-shell MOF nanostructures for the detection of tumor antigens

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