<i><scp>SNCA</scp></i>, a novel biomarker for Group 4 medulloblastomas, can inhibit tumor invasion and induce apoptosis

Li, Yong-Xiao; Yu, Zhenwei; Jiang, Tao; Shao, Liwei; Liu, Yan; Li, Na; Wu, Yufeng; Zheng, Chen; Wu, Xiaoyu; Zhang, Ming; Zheng, Danfeng; Qi, Xueling; Min, Di; Zhang, Jing; Chang, Qing

doi:10.1111/cas.13515

Cited by 26 publications

(18 citation statements)

References 41 publications

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“…Nonetheless, the assignment of molecular subgroups of MB in routine clinical situation is still a challenge for many institutions with limited resources (8,17). The NanoString assay demonstrated by Northcott et al is an accurate, reproducible, and rapid method for the molecular subgrouping of MB (17), but this method is only recently available for research use in a few medical centers in China, India, and Brazil (26)(27)(28). Therefore, it is of great clinical and social significance to be able to predict the molecular subgroups of MB with the information provided in routine examinations conducted in daily medical practice.…”

Section: Discussionmentioning

confidence: 99%

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

et al. 2020

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The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to develop machine learning models for predicting MB molecular subgroups based on multi-parameter magnetic resonance imaging (MRI) radiomics, tumor locations, and clinical factors. A total of 122 MB patients were enrolled retrospectively. After selecting robust, non-redundant, and relevant features from 5,529 extracted radiomics features, a random forest model was constructed based on a training cohort ( n = 92) and evaluated on a testing cohort ( n = 30). By combining radiographic features and clinical parameters, two combined prediction models were also built. The subgroup can be classified using an 11-feature radiomics model with a high area under the curve (AUC) of 0.8264 for WNT and modest AUCs of 0.6683, 0.6004, and 0.6979 for SHH, Group 3, and Group 4 in the testing cohort, respectively. Incorporating location and hydrocephalus into the radiomics model resulted in improved AUCs of 0.8403 and 0.8317 for WNT and SHH, respectively. After adding gender and age, the AUCs for WNT and SHH were further improved to 0.9097 and 0.8654, while the accuracies were 70 and 86.67% for Group 3 and Group 4, respectively. Prediction performance was excellent for WNT and SHH, while that for Group 3 and Group 4 needs further improvements. Machine learning algorithms offer potentials to non-invasively predict the molecular subgroups of MB.

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Section: Discussionmentioning

confidence: 99%

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

et al. 2020

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“…Parkinson’s signaling is one of the enriched pathways for the downregulated genes in this comparison, which include the pro-apoptotic genes CYCC , UCHL1 , and SNCA [36]. Of note, the abnormal expression of genes involved in cell proliferation and its regulation, such as MAPK, suggests that suicides with SUD may have an increased cell proliferation, which could lead to structural abnormalities in the prefrontal cortex of suicides with SUD and lead to an impaired function of this brain area.…”

Section: Discussionmentioning

confidence: 99%

Brain Gene Expression Pattern of Subjects with Completed Suicide and Comorbid Substance Use Disorder

et al. 2018

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Background/Aim: Although individuals with substance use disorder (SUD) are at high risk of committing suicide, most studies of postmortem gene expression exclude subjects with SUD due to the potential confounding effect of drugs in the transcriptome. Thus, little is known about the gene expression profile in suicides with SUD. The identification of altered biological processes in suicides with SUD is crucial in the comprehension of the interaction between both pathologies. Methods: We evaluated the gene expression profile in the dorsolateral prefrontal area of suicides and nonsuicides with and without SUD by microarrays. Results: We identified 222 differentially expressed genes, predominately enriched in cell proliferation in the comparison between suicides with and without SUD. When comparing the transcriptome of suicides with SUD to nonsuicides with SUD, we identified 550 differentially expressed genes, mainly enriched in oxidative phosphorylation. Differentially expressed genes (1,417) between suicides and nonsuicides without SUD were detected. Most of them were related to mitochondrial function. Conclusion: Interaction between suicide and SUD seems to influence the expression of genes involved in glial proliferation and glutamatergic neurotransmission. These results highlight, for the first time, that suicides with SUD have a gene expression profile distinct from that of subjects with only one of these disorders.

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“…SNX2 expression is reduced in human colorectal carcinoma and has been identified as a fusion partner of ABL1 in B-cell acute lymphoblastic leukemia; meanwhile, SNCAIP has been only reported in medulloblastoma studies. On the other hand, MARCKS has been widely studied for its role in invasion, proliferation, and drug resistance within different types of cancers [ 28 , 43 , 44 , 45 ]. Another study using data recovered from the Genome Expression Omnibus (GEO) from 1804 DLBCL patients and performed a guilt-by-association analysis of only the 500 top-ranked CD20-associated gene probes.…”

Section: Gwas In B-cell Nhlmentioning

confidence: 99%

Tracking the Genetic Susceptibility Background of B-Cell Non-Hodgkin’s Lymphomas from Genome-Wide Association Studies

Hernández-Verdin¹,

Labreche²,

Benazra

et al. 2020

IJMS

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B-cell non-Hodgkin’s lymphoma (NHL) risk associations had been mainly attributed to family history of the disease, inflammation, and immune components including human leukocyte antigen (HLA) genetic variations. Nevertheless, a broad range of genome-wide association studies (GWAS) have shed light into the identification of several genetic variants presumptively associated with B-cell NHL etiologies, survival or shared genetic risk with other diseases. The present review aims to overview HLA structure and diversity and summarize the evidence of genetic variations, by GWAS, on five NHL subtypes (diffuse large B-cell lymphoma DLBCL, follicular lymphoma FL, chronic lymphocytic leukemia CLL, marginal zone lymphoma MZL, and primary central nervous system lymphoma PCNSL). Evidence indicates that the HLA zygosity status in B-cell NHL might promote immune escape and that genome-wide significance variants can give biological insight but also potential therapeutic markers such as WEE1 in DLBCL. However, additional studies are needed, especially for non-DLBCL, to replicate the associations found to date.

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SNCA, a novel biomarker for Group 4 medulloblastomas, can inhibit tumor invasion and induce apoptosis

Cited by 26 publications

References 41 publications

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

Brain Gene Expression Pattern of Subjects with Completed Suicide and Comorbid Substance Use Disorder

Tracking the Genetic Susceptibility Background of B-Cell Non-Hodgkin’s Lymphomas from Genome-Wide Association Studies

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