Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

Biomedical applications of magnetic nanoparticles under the influence of a magnetic field have been proved useful beyond expectations in cancer therapy. Magnetic nanoparticles are effective heat mediators, drug nanocarriers, and contrast agents; various strategies have been suggested to selectively target tumor cancer cells. Our study presents magnetodynamic nanotherapy using DNA aptamer-functionalized 50 nm gold-coated magnetic nanoparticles exposed to a low frequency alternating magnetic field for selective elimination of tumor cells in vivo. The cell specific DNA aptamer AS-14 binds to the fibronectin protein in Ehrlich carcinoma hence helps deliver the gold-coated magnetic nanoparticles to the mouse tumor. Applying an alternating magnetic field of 50 Hz at the tumor site causes the nanoparticles to oscillate and pull the fibronectin proteins and integrins to the surface of the cell membrane. This results in apoptosis followed by necrosis of tumor cells without heating the tumor, adjacent healthy cells and tissues. The aptamer-guided nanoparticles and the low frequency alternating magnetic field demonstrates a unique non-invasive nanoscalpel technology for precise cancer surgery at the single cell level.

Current advances in targeted magnetic nanotheranostics are summarized in this review. Unique structural, optical, electronic and thermal properties of magnetic materials in nanometer scale are attractive in the field of biomedicine. Magnetic nanoparticles functionalized with therapeutic molecules, ligands for targeted delivery, fluorescent and other chemical agents can be used for cancer diagnostic and therapeutic purposes. High selectivity, small size, and low immunogenicity of synthetic nucleic acid aptamers make them attractive delivery agents for therapeutic purposes. Properties, production and functionalization of magnetic nanoparticles and aptamers as ligands for targeted delivery are discussed herein. In recent years, magnetic nanoparticles have been widely used in diagnostic methods, such as scintigraphy, single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), and Raman spectroscopy. Therapeutic purposes of magnetic nanoconstructions are also promising. They are used for effective drug delivery, magnetic mediated hypertermia, and megnetodynamic triggering of apoptosis. Thus, magnetic nanotheranostics opens a new venue for complex differential diagnostics, and therapy of metastatic cancer.

Aptamer-based approaches are very promising tools in nanomedicine. These small single-stranded DNA or RNA molecules are often used for the effective delivery and increasing biocompatibility of various therapeutic agents. Recently, magnetic nanoparticles (MNPs) have begun to be successfully applied in various fields of biomedicine. The use of MNPs is limited by their potential toxicity, which depends on their biocompatibility. The functionalization of MNPs by ligands increases biocompatibility by changing the charge and shape of MNPs, preventing opsonization, increasing the circulation time of MNPs in the blood, thus shielding iron ions and leading to the accumulation of MNPs only in the necessary organs. Among various ligands, aptamers, which are synthetic analogs of antibodies, turned out to be the most promising for the functionalization of MNPs. This review describes the factors that determine MNPs’ biocompatibility and affect their circulation time in the bloodstream, biodistribution in organs and tissues, and biodegradation. The work also covers the role of the aptamers in increasing MNPs’ biocompatibility and reducing toxicity.

Nanotechnologies involving physical methods of tumor destruction using functional oligonucleotides are promising for targeted cancer therapy. Our study presents magnetodynamic therapy for selective elimination of tumor cells in vivo using DNA aptamer-functionalized magnetic nanoparticles exposed to a low frequency alternating magnetic field. We developed an enhanced targeting approach of cancer cells with aptamers and arabinogalactan. Aptamers to fibronectin (AS-14) and heat shock cognate 71 kDa protein (AS-42) facilitated the delivery of the nanoparticles to Ehrlich carcinoma cells, and arabinogalactan (AG) promoted internalization through asialoglycoprotein receptors. Specific delivery of the aptamer-modified FeAG nanoparticles to the tumor site was confirmed by magnetic resonance imaging (MRI). After the following treatment with a low frequency alternating magnetic field, AS-FeAG caused cancer cell death in vitro and tumor reduction in vivo. Histological analyses showed mechanical disruption of tumor tissues, total necrosis, cell lysis, and disruption of the extracellular matrix. The enhanced targeted magnetic theranostics with the aptamer conjugated superparamagnetic ferroarabinogalactans opens up a new venue for making biocompatible contrasting agents for MRI imaging and performing non-invasive anti-cancer therapies with a deep penetrated magnetic field.

Diabetic nephropathy, hypertension, and glomerulonephritis are the most common causes of chronic kidney diseases (CKD). Since CKD of various origins may not become apparent until kidney function is significantly impaired, a differential diagnosis and an appropriate treatment are needed at the very early stages. Conventional biomarkers may not have sufficient separation capabilities, while a full-proteomic approach may be used for these purposes. In the current study, several machine learning algorithms were examined for the differential diagnosis of CKD of three origins. The tested dataset was based on whole proteomic data obtained after the mass spectrometric analysis of plasma and urine samples of 34 CKD patients and the use of label-free quantification approach. The k-nearest-neighbors algorithm showed the possibility of separation of a healthy group from renal patients in general by proteomics data of plasma with high confidence (97.8%). This algorithm has also be proven to be the best of the three tested for distinguishing the groups of patients with diabetic nephropathy and glomerulonephritis according to proteomics data of plasma (96.3% of correct decisions). The group of hypertensive nephropathy could not be reliably separated according to plasma data, whereas analysis of entire proteomics data of urine did not allow differentiating the three diseases. Nevertheless, the group of hypertensive nephropathy was reliably separated from all other renal patients using the k-nearest-neighbors classifier “one against all” with 100% of accuracy by urine proteome data. The tested algorithms show good abilities to differentiate the various groups across proteomic data sets, which may help to avoid invasive intervention for the verification of the glomerulonephritis subtypes, as well as to differentiate hypertensive and diabetic nephropathy in the early stages based not on individual biomarkers, but on the whole proteomic composition of urine and blood.