A 10-gene expression signature of Notch pathway predicts recurrence in ovarian carcinoma

Chen, Fang; Liu, Naifu

doi:10.3892/ol.2015.3382

Cited by 15 publications

(18 citation statements)

References 17 publications

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“…Put together, these strongly suggest that while stem-like properties are most likely to be associated with a hybrid E/M phenotype, in accordance with our modeling prediction, the possibility of epithelial or mesenchymal subsets of CSCs is not ruled out. We further compared the level of Notch signaling in the CSCs with the non-stem cells (control) as quantified by a 10-genes ‘Notch signature’ [ 38 ]. In 7 out of 8 cases, with the exclusion of human glioblastoma cells (GSE20736), Notch signaling was more active in CSCs subpopulation, hence confirming that Notch activation may foster stem-like traits ( Supplementary Figure 5 ).…”

Section: Resultsmentioning

confidence: 99%

A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling

et al. 2018

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Epithelial-mesenchymal transition (EMT) and cancer stem cell (CSCs) formation are two fundamental and well-studied processes contributing to cancer metastasis and tumor relapse. Cells can undergo a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype or a complete EMT to attain a mesenchymal one. Similarly, cells can reversibly gain or lose 'stemness'. This plasticity in cell states is modulated by signaling pathways such as Notch. However, the interconnections among the cell states enabled by EMT, CSCs and Notch signaling remain elusive. Here, we devise a computational model to investigate the coupling among the core decision-making circuits for EMT, CSCs and Notch. Our model predicts that hybrid E/M cells are most likely to associate with stem-like traits and enhanced Notch-Jagged signaling – a pathway implicated in therapeutic resistance. Further, we show that the position of the 'stemness window' on the 'EMT axis' is varied by altering the coupling strength between EMT and CSC circuits, and/or modulating Notch signaling. Finally, we analyze the gene expression profile of CSCs from several cancer types and observe a heterogeneous distribution along the 'EMT axis', suggesting that different subsets of CSCs may exist with varying phenotypes along the epithelial-mesenchymal axis. We further investigate therapeutic perturbations such as treatment with metformin, a drug associated with decreased cancer incidence and increased lifespan of patients. Our mechanism-based model explains how metformin can both inhibit EMT and blunt the aggressive potential of CSCs simultaneously, by driving the cells out of a hybrid E/M stem-like state with enhanced Notch-Jagged signaling.

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Section: Resultsmentioning

confidence: 99%

A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling

et al. 2018

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“…Some of the genes in the 97-gene signature have been reported to play critical roles in biological processes, including angiogenesis, metastasis, and proliferation in ovarian cancer. These genes include: CLIP, COL3A1, COL10A1, LAMB1, INHBA, NBL, F3, PDGFRA, PDGFRB, PLAU, ROR2, SCG2, and ZFHX4 30 ; COL11A1, COL5A2, THBS2, TIMP3 and SINAI2 31 ; EGR2 32 , 33 and FOS 34 . Moreover, we investigated transcription factors included in the 97-gene signature.…”

Section: Discussionmentioning

confidence: 99%

The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer

Matondo

Shahid

et al. 2017

Sci Rep

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Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66–5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57–5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.

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“…Models integrating multiple genes spring up in OC and other cancers as the global gene expression data becomes more feasible to use. So far, autophagy, DNA repair pathway, and the Notch pathway-related prognostic signatures have been developed for OC [14][15][16]. Gene methylation panel, miRNAs-based signature, miRNA-lncRNA signature were established because of the vital role of epigenetics in OC prognosis [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Development of a novel transcription factors-related prognostic signature for serous ovarian cancer

Liu

et al. 2020

Preprint

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BackgroundOvarian cancer (OC) is one of the most lethal gynecological cancer globally. Serous ovarian cancer (SOC) is most common pathological type of ovarian cancer. Growing evidence suggests that transcription factors (TFs) play vital roles in serous ovarian cancer (SOC). In the present study, we aimed to develop a transcription factors-related prognostic signature to better predict the survival in patients with SOC.Materials and methodsThe TFs mRNA expression profiles of 564 SOC subjects in the TCGA database, and 70 SOC subjects in the GEO database were screened. Lasso cox regression and consensus clustering analysis were utilized to construct a novel TFs related signature and cluster model, respectively. Genomic alternative analysis was used to elaborate on the association between the TFs related prognostic signature and genomic aberrations. GSEA analysis was applied to identify the biological functional difference between high risk-score group and low-risk score group.ResultsA 17-TFs related prognostic signature was constructed using lasso cox regression and validated in the TCGA and GEO cohorts. Consensus clustering analysis was applied to establish a cluster model. The 17-TFs related prognostic signature, risk score, and cluster models were effective at accurately distinguishing the prognosis of SOC. The GSEA assay results suggested that there was a significant difference in the inflammatory and immune response pathways between the high-risk and low-risk score groups. Immune infiltration, immunotherapy, and chemotherapy responses were analyzed due to the significant difference in the regulation of lymphocyte migration and T cell-mediated cytotoxicity between the two groups; indicating that patients with low-risk score were more likely to respond anti-PD-1, etoposide, paclitaxel, and veliparib but not to gemcitabine, doxorubicin, docetaxel, and cisplatin. Also, the prognostic nomogram model revealed that the risk score was a good prognostic indicator for SOC patients.ConclusionsIn conclusion, we explored the prognostic values of TFs in SOC and developed a 17-TFs related prognostic signature to predict the survival of SOC patients.

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A 10-gene expression signature of Notch pathway predicts recurrence in ovarian carcinoma

Cited by 15 publications

References 17 publications

A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling

A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling

The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer

Development of a novel transcription factors-related prognostic signature for serous ovarian cancer

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