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Supplementary Table S2 from Data-Driven Computational Modeling Identifies Determinants of Glioblastoma Response to SHP2 Inhibition

NIAID Data Ecosystem2026-04-29 收录

药物响应预测

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https://figshare.com/articles/dataset/Supplementary_Table_S2_from_Data-Driven_Computational_Modeling_Identifies_Determinants_of_Glioblastoma_Response_to_SHP2_Inhibition/22428244 数据链接链接失效反馈

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Supplementary Table S2

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创建时间：

2021-04-15

癌症生物标志物

药物响应预测

Next generation sequencing was used to identify Notch mutations in a large collection of diverse solid tumors. NOTCH1 and NOTCH2 rearrangements leading to constitutive receptor activation were confine

NIAID Data Ecosystem90

Expression data from primary breast tumors

乳腺癌基因表达

药物响应预测

Expression data were used to predict the activity status of diverse pathways, which were compared to Tamoxifen response 20 M1 breast cancer patients were evaluated for the activity of transcriptomic

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Table_7_LncRNA-FAM66C Was Identified as a Key Regulator for Modulating Tumor Microenvironment and Hypoxia-Related Pathways in Glioblastoma.XLSX

胶质母细胞瘤

缺氧相关lncRNA调控

Although the role of hypoxia has been greatly explored and unveiled in glioblastoma (GBM), the mechanism of hypoxia-related long non-coding (lnc) RNAs has not been clearly understood. This study aims

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The RNA m6A reader YTHDF2 maintains oncogene expression and is a targetable dependency in glioblastoma stem cells [m6A RIP-seq]

胶质母细胞瘤

RNAm6A修饰

Glioblastoma is a universally lethal cancer driven by glioblastoma stem cells (GSCs). Here, we interrogated N6-methyladenosine (m6A) mRNA modifications in GSCs by methyl RNA-immunoprecipitation follow

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Uridine-cytidine kinase 2 promotes glycolysis and reprograms glioblastoma stem cell characteristics under hypoxic conditions through the PI3K/Akt/HIF-1α pathway

HIF-1α

胶质母细胞瘤

This study aimed to explore key regulatory molecules involved in metabolic alterations clarify the heterogeneity of glioblastoma and develop novel therapeutic strategies. The microarray dataset GSE451

DataCite Commons2025-12-23 更新40

Supplementary Table S2 from Data-Driven Computational Modeling Identifies Determinants of Glioblastoma Response to SHP2 Inhibition

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