Dataset Information

Identifying Predictive Gene Expression and Signature Related to Temozolomide Sensitivity of Glioblastomas.

ABSTRACT: Temozolomide (TMZ) is considered a standard chemotherapeutic agent for glioblastoma (GBM). Characterizing the biological molecules and signaling pathways involved in TMZ sensitivity would be helpful for selecting therapeutic schemes and evaluating prognosis for GBM. Thus, in the present study, we selected 34 glioma cell lines paired with specific IC50 values of TMZ obtained from CancerRxGene and RNA-seq data downloaded from the Cancer Cell Line Encyclopedia to identify genes related to TMZ sensitivity. The results showed that 1,373 genes were related to the response of GBM cells to TMZ. Biological function analysis indicated that epithelial-mesenchymal transition, Wnt signaling, and immune response were the most significantly activated functions in TMZ-resistant cell lines. Additionally, negative regulation of telomere maintenance via telomerase was enriched in TMZ-sensitive glioma cell lines. We also preliminarily observed a synergistic effect of combination treatment comprising TMZ and a telomerase inhibitor in vitro. We identified six genes (MROH8, BET1, PTPRN2, STC1, NKX3-1, and ARMC10) using the random survival forests variable hunting algorithm based on the minimum error rate of the gene combination and constructed a gene expression signature. The signature was strongly related to GBM clinical characteristics and exhibited good prognosis accuracy for both The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Patients in the high score group had a shorter survival time than those in the low score group (11.2 vs. 22.2 months, hazard ratio = 7.31, p = 4.59e-11) of the TCGA dataset. The CGGA dataset was selected as a validation group with 40 patients in the high score set and 43 patients in the low score set (12.5 vs. 28.8 months, hazard ratio = 3.42, p = 8.61e-5). Moreover, the signature showed a better prognostic value than MGMT promoter methylation in both datasets. We also developed a nomogram for clinical use that integrated the TMZ response signature and four other risk factors to individually predict patient survival after TMZ chemotherapy. Overall, our study provides promising therapeutic targets and potential guidance for adjuvant therapy of GBM.

SUBMITTER: Cai HQ

PROVIDER: S-EPMC7258082 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identifying Predictive Gene Expression and Signature Related to Temozolomide Sensitivity of Glioblastomas.

Cai Hong-Qing HQ Liu Ang-Si AS Zhang Min-Jie MJ Liu Hou-Jie HJ Meng Xiao-Li XL Qian Hai-Peng HP Wan Jing-Hai JH

Frontiers in oncology 20200522

Temozolomide (TMZ) is considered a standard chemotherapeutic agent for glioblastoma (GBM). Characterizing the biological molecules and signaling pathways involved in TMZ sensitivity would be helpful for selecting therapeutic schemes and evaluating prognosis for GBM. Thus, in the present study, we selected 34 glioma cell lines paired with specific IC<sub>50</sub> values of TMZ obtained from CancerRxGene and RNA-seq data downloaded from the Cancer Cell Line Encyclopedia to identify genes related t ...[more]

PMID: 32528873

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Project description:ObjectiveTo identify novel epigenetic signatures that could provide predictive information that is complementary to promoter methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) gene for predicting temozolomide (TMZ) response, among glioblastomas (GBMs) without glioma-CpGs island methylator phenotype (G-CIMP) METHODS: Different cohorts of primary non-G-CIMP GBMs with genome-wide DNA methylation microarray data were included for discovery and validation of a multimarker signature, combined using a RISK score model. Different statistical analyses and functional experiments were performed for clinical and biological validation.ResultsBy employing discovery cohorts with radiotherapy (RT) and TMZ versus RT alone and a strict multistep selection strategy, we identified seven CpGs, each of which was significantly correlated with overall survival (OS) of non-G-CIMP GBMs with RT/TMZ, independent of age, MGMT promoter methylation status, and other identified CpGs. A RISK score signature of the 7 CpGs was developed and validated to distinguish non-G-CIMP GBMs with differential survival outcomes to RT/TMZ, but not to RT alone. The interaction analyses also showed differential outcomes to RT/TMZ versus RT alone within the RISK score-based subgroups. The signature could also improve the risk classification by age and MGMT promoter methylation status. Functional experiments showed that HSBP2 appeared to be epigenetically regulated by one identified CpG and was associated with TMZ resistance, but it was not associated with cell proliferation or apoptosis in GBM cell lines. The predictive value of the single CpG methylation of HSBP2 by pyrosequencing was observed in a local cohort of isocitrate dehydrogenase 1 (IDH1) R132H wild-type GBMs.ConclusionsThis novel epigenetic signature might be a promising predictive (but not a general prognostic) biomarker and be helpful for refining the MGMT-based guiding approach to TMZ usage in non-G-CIMP GBMs.

Project description:BackgroundAPOBEC family play an important role in cancer mutagenesis and tumor development. The role of APOBEC family in lung adenocarcinoma (LUAD) has not been studied comprehensively.Materials and methodsThe expression data of pan-cancer as well as LUAD was obtained from public databases. The expression level of APOBEC family genes was analyzed in different normal and cancer tissues. APOBEC mutagenesis enrichment score (AMES) was utilized to evaluate the APOBEC-induced mutations and the relation of APOBEC with genomic instability. Gene set enrichment analysis was used to identify differentially enriched pathways. Univariate Cox regression and Lasso regression were applied to screen key prognostic genes. The immune cell infiltration was estimated by CIBERSORT. RT-qPCR assay, CCK-8 and Transwell assay were conducted to explore gene expression and lung cancer cell invasion.ResultsCancer tissues had significantly altered expression of APOBEC family genes and the expression patterns of APOBEC family were different in different cancer types. APOBEC3B was the most aberrantly expressed in most cancer types. In LUAD, we observed a significantly positive correlation of AMES with intratumor heterogeneity (ITH), tumor neoantigen burden (TNB), and tumor mutation burden (TMB). High AMES group had high mutation counts of DNA damage repair pathways, and high enrichment of cell cycle and DNA repair pathways. We identified four prognostic genes (LYPD3, ANLN, MUC5B, and FOSL1) based on AMES, and constructed an AMES-related gene signature. The expressions of four genes were enhanced and accelerated the invasion ability and viability of lung cancer cells. Furthermore, we found that high group increased oxidative stress level.ConclusionsAPOBEC family was associated with genomic instability, DNA damage-related pathways, and cell cycle in LUAD. The AMES-related gene signature had a great potential to indicate the prognosis and guide immunotherapy/chemotherapy for patients suffering from LUAD.

Project description:Glioblastoma (GBM) is the most malignant glioma, with a median overall survival (OS) of 14-16 months. Temozolomide (TMZ) is the first-line chemotherapy drug for glioma, but whether TMZ should be withheld from patients with GBMs that lack O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is still under debate. DNA methylation profiling holds great promise for further stratifying the responses of MGMT promoter unmethylated GBMs to TMZ. In this study, we studied 147 TMZ-treated MGMT promoter unmethylated GBM, whose methylation information was obtained from the HumanMethylation27 (HM-27K) BeadChips (n = 107) and the HumanMethylation450 (HM-450K) BeadChips (n = 40) for training and validation, respectively. In the training set, we performed univariate Cox regression and identified that 3,565 CpGs were significantly associated with the OS of the TMZ-treated MGMT promoter unmethylated GBMs. Functional analysis indicated that the genes corresponding to these CpGs were enriched in the biological processes or pathways of mitochondrial translation, cell cycle, and DNA repair. Based on these CpGs, we developed a 31-CpGs methylation signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm. In both training and validation datasets, the signature identified the TMZ-sensitive GBMs in the MGMT promoter unmethylated GBMs, and only the patients in the low-risk group appear to benefit from the TMZ treatment. Furthermore, these identified TMZ-sensitive MGMT promoter unmethylated GBMs have a similar OS when compared with the MGMT promoter methylated GBMs after TMZ treatment in both two datasets. Multivariate Cox regression demonstrated the independent prognostic value of the signature in TMZ-treated MGMT promoter unmethylated GBMs. Moreover, we also noticed that the hallmark of epithelial-mesenchymal transition, ECM related biological processes and pathways were highly enriched in the MGMT unmethylated GBMs with the high-risk score, indicating that enhanced ECM activities could be involved in the TMZ-resistance of GBM. In conclusion, our findings promote our understanding of the roles of DNA methylation in MGMT umethylated GBMs and offer a very promising TMZ-sensitivity predictive signature for these GBMs that could be tested prospectively.

Dataset Information

Identifying Predictive Gene Expression and Signature Related to Temozolomide Sensitivity of Glioblastomas.

Publications

Identifying Predictive Gene Expression and Signature Related to Temozolomide Sensitivity of Glioblastomas.

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