WHO Glioma Classification Update and Genomics: What Radiologists Need to Know

Bai, James; Varghese, Jerrin Thadathil; Jain, Rajan

doi:10.26226/morressier.5e5e709500701ceba4a26ab8

“…Based on certain pathological characteristics, gliomas are classified into four grades (WHO grades I, II, III and IV). Grade I or II tumors are low grade astrocytomas, grade III tumors are anaplastic astrocytomas, and grade IV tumors are glioblastomas multiforme (21,22). To determine the correlation between GASC1 expression levels and clinicopathological parameters in glioma tissues, fresh glioma samples were collected from 18 patients undergoing resection in Neurosurgery Department.…”

Section: Resultsmentioning

confidence: 99%

GASC1 promotes glioma progression by enhancing NOTCH1 signaling

Zhang

¹

,

Yang

²

,

Liu

³

et al. 2021

View full text Add to dashboard Cite

Recent studies have reported that gene amplified in squamous cell carcinoma 1 (GASC1) is involved in the progression of several types of cancer. However, whether GASC1 promotes glioma progression remains unknown. Therefore, the present study aimed to investigate the effect of GASC1 exposure on glioma tumorigenesis. The western blot demonstrated that grade III and IV glioma tissues exhibited a higher mRNA and protein expression of GASC1. Moreover, CD133 + U87 or U251 cells from magnetic cell separation exhibited a higher GASC1 expression. Invasion Transwell assay, clonogenic assay and wound healing assay have shown that GASC1 inhibition using a pharmacological inhibitor and specific short hairpin (sh)RNA suppressed the invasive, migratory and tumorsphere forming abilities of primary culture human glioma cells. Furthermore, GASC1-knockdown decreased notch receptor (Notch) responsive protein hes family bHLH transcription factor 1 (Hes1) signaling. GASC1 inhibition reduced notch receptor 1 (NOTCH1) expression, and a NOTCH1 inhibitor enhanced the effects of GASC1 inhibition on the CD133 + U87 or U251 cell tumorsphere forming ability, while NOTCH1 overexpression abrogated these effects. In addition, the GASC1 inhibitor caffeic acid and/or the NOTCH1 inhibitor DAPT (a γ-Secretase Inhibitor), efficiently suppressed the human glioma xenograft tumors. Thus, the present results demonstrated the importance of GASC1 in the progression of glioma and identified that GASC1 promotes glioma progression, at least in part, by enhancing NOTCH signaling, suggesting that GASC1/NOTCH1 signaling may be a potential therapeutic target for glioma treatment.

show abstract

“…e main observation indicators of the lesion image included the location of the lesion, the number of lesions, the size of the lesion, the shape of the lesion, the signal intensity, the edema around the tumor, and the degree of enhancement [16]. After the original MRI image was transmitted to the workstation, it was processed by the Function tool (2) software to obtain the ADC map and FA map, with the FA value and ADC value measured. Subsequently, the rFA and rADC values were obtained according to the ratio of the tumor body part and the tumor edema zone to the contralateral white matter area, respectively.…”

Section: E Deep Learning Model Based On Multimodal Featurementioning

confidence: 99%

“…Brain glioma (BG) originates from glial cells and is the most common brain tumor. It is characterized by infiltrating growth, especially high-grade BG [2]. As a result, it is difficult to distinguish it from normal brain tissue, leading to a great risk for surgical resection.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Magnetic Resonance Imaging Image Feature Analysis for Pathological Classification of Brain Glioma

Wei

¹

,

Thomas

²

2021

Scientific Programming

View full text Add to dashboard Cite

To explore the application value of MRI in the diagnosis of brain glioma (BG), in the study, a deep learning-based multimodal feature fusion model was established, which was then applied in BG classification. 60 BG patients who came to our hospital for treatment were selected as research subjects. They all accepted the MRI scan and the enhanced scan, and the MRI results were compared with the pathological results. The results showed that the sensitivity of the algorithm was above 90%, and the sensitivity to diagnose grade IV glioma was as high as 98.28%; the specificity was above 78%, and the specificity to diagnose grade IV glioma was as high as 95.85%; the detection accuracy was above 95%. The relative fractional anisotropy (rFA) values of the tumor body were smaller than those of peritumoral edema in both the high-grade group and low-grade group, and the difference was notable P < 0.05 ; the relative apparent diffusion coefficients (rADC) values of the peritumoral edema were greater than those of tumor bodies of the same grade in both the high-grade group and the low-grade group, and the difference was notable P < 0.05 ; notable differences were noted in the rADC values of tumor bodies between the high-grade group and the low-grade group P < 0.05 and in the rADC values of the glioma peritumoral edema between the high-grade group and the low-grade group P < 0.05 . In summary, MRI based on deep learning raises the sensitivity, specificity, and accuracy to diagnose BG and can more accurately classify BG pathologically, providing reference for clinical treatment of BG.

show abstract

“…The organic phase was dried, and concentration of the solvent under reduced pressure gave ethyl 2-azidoacetate (12, 1.16 g, 100%) as a colorless oil. 1…”

Section: -(2-azidoethoxy)benzaldehyde (10)mentioning

confidence: 99%

“…Gliomas can be classified on the basis of their histological subtypes: the astrocytoma, which is the most common, the oligodendroglioma and the ependymoma. They can be further divided into Low-Grade Gliomas (LGGs) and into High-Grade Gliomas (HGGs), based on their malignancy 1 HGGs are the most invasive and are associated with a high ability to metastasize, with an extremely fast cell growth, a marked chemoresistance and a poor clinical outcome 2 . Their marked drug resistance is related to the presence of a high density of cancer stem cells (CSCs) that possess self-renewal ability and an unlimited proliferative potential, just like their physiological counterparts 3,4 .…”

Section: Introductionmentioning

confidence: 99%

Curcumin-based-fluorescent probes targeting ALDH1A3 as a promising tool for glioblastoma precision surgery and early diagnosis

Gelardi

¹

,

Caprioglio

²

,

Colombo

³

et al. 2021

Preprint

View full text Add to dashboard Cite

High Grade Glioma (HGG) is the most aggressive primary brain tumour for which both effective treatments and efficient tools for an early-stage diagnosis are lacking. Herein, we present two curcumin-based fluorescent probes that are able to bind to aldehyde dehydrogenase 1A3 (ALDH1A3), an enzyme overexpressed in glioma stem cells (GSCs) and associated with stemness and invasiveness of HGG. Both compounds are selective versus ALDH1A3, without showing any appreciable interaction with other ALDH1A isoenzymes. Indeed, their fluorescent signal is detectable only in our positive controls in vitro and absent in cells that lack ALDH1A3. Remarkably, in vivo, they selectively accumulate in glioblastoma cells, allowing the identification of the growing tumour mass. The significant specificity of our compounds is the necessary premise for their further development into glioblastoma cells detecting probes to be possibly used during neurosurgical operations.

show abstract

WHO Glioma Classification Update and Genomics: What Radiologists Need to Know

Cited by 9 publications

References 0 publications

GASC1 promotes glioma progression by enhancing NOTCH1 signaling

GASC1 promotes glioma progression by enhancing NOTCH1 signaling

Deep Learning-Based Magnetic Resonance Imaging Image Feature Analysis for Pathological Classification of Brain Glioma

Curcumin-based-fluorescent probes targeting ALDH1A3 as a promising tool for glioblastoma precision surgery and early diagnosis

Contact Info

Product

Resources

About