Biomedical applications of terahertz spectra in clinical and molecular pathology of human glioma

Ensemble learning prediction framework for EGFR amplification status of glioma based on terahertz spectral features

Epidermal growth factor receptor (EGFR) plays a pivotal role in the initiation and progression of gliomas. In particular, in glioblastoma, EGFR amplification emerges as a catalyst for invasion, proliferation, and resistance to radiotherapy and chemotherapy. Current approaches are not capable of providing rapid diagnostic results of molecular pathology. In this study, we propose a terahertz spectroscopic approach for predicting the EGFR amplification status of gliomas for the first time. A machine learning model was constructed using the terahertz response of the measured glioma tissues, including the absorption coefficient, refractive index, and dielectric loss tangent. The novelty of our model is the integration of three classical base classifiers, i.e., support vector machine, random forest, and extreme gradient boosting. The ensemble learning method combines the advantages of various base classifiers, this model has more generalization ability. The effectiveness of the proposed method was validated by applying an individual test set. The optimal performance of the integrated algorithm was verified with an area under the curve (AUC) maximum of 85.8 %. This signifies a significant stride toward more effective and rapid diagnostic tools for guiding postoperative therapy in gliomas.

Characteristic fingerprint spectrum of α-synuclein mutants on terahertz time-domain spectroscopy

α-Synuclein, a presynaptic neuronal protein encoded by the SNCA gene, is involved in the pathogenesis of Parkinson's disease. Point mutations and multiplications of α-synuclein (A30P and A53T) are correlated with early-onset Parkinson's disease characterized by rapid progression and poor prognosis. Currently, the clinical identification of SNCA variants, especially disease-related A30P and A53T mutants, remains challenging and also time consuming. This study aimed to develop a novel label-free detection method for distinguishing the SNCA mutants using transmission terahertz (THz) time-domain spectroscopy. The protein was spin-coated onto the quartz to form a thin film, which was measured using THz time-domain spectroscopy. The spectral characteristics of THz broadband pulse waves of α-synuclein protein variants (SNCA wild type, A30P, and A53T) at different frequencies were analyzed via Fourier transform. The amplitude A intensity (AWT, AA30P, and AA53T) and peak occurrence time in THz time-domain spectroscopy sensitively distinguished the three protein variants. The phase φ difference in THz frequency domain followed the trend of φWT > φA30P > φA53T. There was a significant difference in THz frequency amplitude A' corresponding to the frequency ranging from 0.4 to 0.66 THz (A'A53T > A'A30P > A'WT). At a frequency of 0.4-0.6 THz, the transmission T of THz waves distinguished three variants (TA53T > TA30P > TWT), whereas there was no difference in the transmission T at 0.66 THz. The SNCA wild-type protein and two mutant variants (A30P and A53T) had distinct characteristic fingerprint spectra on THz time-domain spectroscopy. This novel label-free detection method has great potential for the differential diagnosis of Parkinson's disease subtypes.

Advances in terahertz metasurface graphene for biosensing and application

Based on the extraordinary electromagnetic properties of terahertz waves, such as broadband, low energy, high permeability, and biometric fingerprint spectra, terahertz sensors show great application prospects in the biochemical field. However, the sensitivity of terahertz sensing technology is increasingly required by modern sensing demands. With the development of terahertz technology and functional materials, graphene-based terahertz metasurface sensors with the advantages of high sensitivity, fingerprint identification, nondestructive and anti-interference are gradually gaining attention. In addition to providing ideas for terahertz biosensors, these devices have attracted in-depth research and development by scientists. An overview of graphene-based terahertz metasurfaces and their applications in the detection of biochemical molecules is presented. This includes sensor mechanism research, graphene metasurface index evaluation, protein and nucleic acid sensors, and other chemical molecule sensing. A comparative analysis of graphene, nanomaterials, silicon, and metals to develop material-integrated metasurfaces. Furthermore, a brief summary of the main performance results of this class of devices is presented, along with suggestions for improvements to the existing shortcoming.

Clinical Theranostics Trademark of Exosome in Glioblastoma Metastasis

Glioblastoma (GBM) is an aggressive type of cancer that has led to the death of a large population. The traditional approach fails to develop a solution for GBM's suffering life. Extensive research into tumor microenvironments (TME) indicates that TME extracellular vesicles (EVs) play a vital role in cancer development and progression. EVs are classified into microvacuoles, apoptotic bodies, and exosomes. Exosomes are the most highlighted domains in cancer research. GBM cell-derived exosomes participate in multiple cancer progression events such as immune suppression, angiogenesis, premetastatic niche formation (PMN), ECM (extracellular matrix), EMT (epithelial-to-mesenchymal transition), metastasis, cancer stem cell development and therapeutic and drug resistance. GBM exosomes also carry the signature of a glioblastoma-related status. The exosome-based GBM examination is part of the new generation of liquid biopsy. It also solved early diagnostic limitations in GBM. Traditional therapeutic approaches do not cross the blood-brain barrier (BBB). Exosomes are a game changer in GBM treatment and it is emerging as a potential platform for effective, efficient, and specific therapeutic development. In this review, we have explored the exosome-GBM interlink, the clinical impact of exosomes on GBM biomarkers, the therapeutics signature of exosomes in GBM, exosome-based research challenges, and future directions in GBM. Therefore, the GBM-derived exosomes offer unique therapeutic opportunities, which are currently under preclinical and clinical testing.