The high-grade glioma is characterized by cell heterogeneity, gene mutations, and poor prognosis. The deletions and mutations of the tumor suppressor gene PTEN (5%-40%) in glioma patients are associated with worse survival and therapeutic resistance. Characterization of unique prognosis molecular signatures by PTEN status in glioma is still unclear. This study established a novel risk model, screened optimal prognostic signatures, and calculated the risk score for the individual glioma patients with different PTEN status. Screening results revealed fourteen independent prognostic gene signatures in PTEN-wt and three in the -50PTEN-mut subgroup. Moreover, we verified risk score as an independent prognostic factor significantly correlated with tumor malignancy. Due to the higher malignancy of the PTEN-mut gliomas, we explored the independent prognostic signatures (CLCF1, AEBP1, and OS9) for a potential therapeutic target in PTEN-mut glioma. We further separated IDH wild-type glioma patients into GBM and LGG to verify the therapeutic target along with PTEN status, notably, the above screened therapeutic targets are also significant prognostic genes in both IDH-wt/PTEN-mut GBM and LGG patients. We further identified the small molecule compound (+)-JQ1 binds to all three targets, indicating a potential therapy for PTEN-mut glioma. In sum, gene signatures and risk scores in the novel risk model facilitate glioma diagnosis, prognosis prediction, and treatment.
Optical-matter interactions and photon scattering in a sub-wavelength space are of great interest in many applications, such as nanopore-based gene sequencing and molecule characterization. Previous studies show that spatial distribution features of the scattering photon states are highly sensitive to the dielectric and structural properties of the nanopore array and matter contained on or within them, as a result of the complex optical-matter interaction in a confined system. In this paper, we report a method for shape characterization of subwavelength nanowells using photon state spatial distribution spectra in the scattering near field. Far-field parametric images of the near-field optical scattering from sub-wavelength nanowell arrays on a SiN substrate were obtained experimentally. Finite-difference time-domain simulations were used to interpret the experimental results. The rich features of the parametric images originating from the interaction of the photons and the nanowells were analyzed to recover the size of the nanowells. Experiments on nanoholes modified with Shp2 proteins were also performed. Results show that the scattering distribution of modified nanoholes exhibits significant differences compared to empty nanoholes. This work highlights the potential of utilizing the photon status scattering of nanowells for molecular characterization or other virus detection applications.
The polarization states of scattered photons can be used to map or image the anisotropic features of a nanostructure. However, the scattering strength depends heavily on the refractivity contrast in the near field under measurement, which limits the imaging sensitivity for viral particles which have little refractivity contrast with their nano-ambientes. In this paper, we show the photon scattering signal strength can be magnified by introducing a more abrupt change of refractivity at the virus particle using antibody-conjugated gold nanoparticles (AuNPs), allowing the presence of such viruses to be detected. Using two different deep learning methods to minimize scattering noise, the photon states scattering signal of a AuNPs ligated virus is enhanced significantly compared to that of a bare virus particle. This is confirmed by Finite Difference Time Domain (FDTD) numerical simulations. The sensitivity of the polarization state scattering spectra from a virus-gold particle doublet is 5.4 times higher than that of a conventional microscope image.
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