Dysregulated FOXM1 signaling in the regulation of cancer stem cells

Sher, Gulab; Masoodi, Tariq; Patil, Kalyani; Akhtar, Sabah; Kuttikrishnan, Shilpa; Ahmad, Aamir; Uddin, Shahab

doi:10.1016/j.semcancer.2022.07.009

Cited by 56 publications

(24 citation statements)

References 170 publications

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“…Based on normalized enrichment scores (NES) and P values, we selected the four most important enriched signaling pathways ( Figure 8D ), with lower CM scores associated with immune-related signaling pathways. The tumor stem cell index is an index to assess the similarity of tumor cells to stem cells and is associated with biological processes active in tumor cells ( 34 ). Therefore, we assessed the correlation between the RNA stemness score (RNAss) and the CM risks score.…”

Section: Resultsmentioning

confidence: 99%

Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer

et al. 2023

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BackgroundOvarian cancer (OC) is one of the most common and most malignant gynecological malignancies in gynecology. On the other hand, dysregulation of copper metabolism (CM) is closely associated with tumourigenesis and progression. Here, we investigated the impact of genes associated with copper metabolism (CMRGs) on the prognosis of OC, discovered various CM clusters, and built a risk model to evaluate patient prognosis, immunological features, and therapy response.Methods15 CMRGs affecting the prognosis of OC patients were identified in The Cancer Genome Atlas (TCGA). Consensus Clustering was used to identify two CM clusters. lasso-cox methods were used to establish the copper metabolism-related gene prognostic signature (CMRGPS) based on differentially expressed genes in the two clusters. The GSE63885 cohort was used as an external validation cohort. Expression of CM risk score-associated genes was verified by single-cell sequencing and quantitative real-time PCR (qRT-PCR). Nomograms were used to visually depict the clinical value of CMRGPS. Differences in clinical traits, immune cell infiltration, and tumor mutational load (TMB) between risk groups were also extensively examined. Tumour Immune Dysfunction and Rejection (TIDE) and Immune Phenotype Score (IPS) were used to validate whether CMRGPS could predict response to immunotherapy in OC patients.ResultsIn the TCGA and GSE63885 cohorts, we identified two CM clusters that differed significantly in terms of overall survival (OS) and tumor microenvironment. We then created a CMRGPS containing 11 genes to predict overall survival and confirmed its reliable predictive power for OC patients. The expression of CM risk score-related genes was validated by qRT-PCR. Patients with OC were divided into low-risk (LR) and high-risk (HR) groups based on the median CM risk score, with better survival in the LR group. The 5-year AUC value reached 0.74. Enrichment analysis showed that the LR group was associated with tumor immune-related pathways. The results of TIDE and IPS showed a better response to immunotherapy in the LR group.ConclusionOur study, therefore, provides a valuable tool to further guide clinical management and tailor the treatment of patients with OC, offering new insights into individualized treatment.

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Section: Resultsmentioning

confidence: 99%

Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer

et al. 2023

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“…In addition, we also evaluated the TME scores in both two risk groups, not surprisingly, stromal score, immune score, and ESTIMATE score were higher in the high-risk group than in the low-risk group ( Figure 7D ). Tumor stemness index is an index to assess the similarity between tumor cells and stem cells, which is related to active biological processes in tumor cells, such as cancer recurrence, tumor proliferation and drug resistance ( 28 ). Therefore, we evaluated the correlation between DNA stemness score (DNAss) along with RNA stemness score (RNAss) and risk score.…”

Section: Resultsmentioning

confidence: 99%

Crosstalk of angiogenesis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in colorectal adenocarcinoma

Cui

Liu²,

Wang³

et al. 2022

Front. Immunol.

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BackgroundColorectal adenocarcinoma (COAD) is one of the most common malignancies and angiogenesis is vital to the development of cancer. Here, we explored the roles of angiogenesis-related genes (ARGs) that affect the prognosis of COAD and constructed risk models to assess patient prognosis, immune characteristics, and treatment outcomes.MethodsWe comprehensively characterized the transcriptional and genetic modifications of 48 ARGs in COAD and evaluated the expression patterns. We identified two ARG subgroups using the consensus clustering algorithm. Based on the differentially expressed genes (DEGs) of two ARG subtypes, we calculated risk score, namely ARG_scores, and calssified COAD patients into different risk groups. To investigate the expression of ARG_score-related genes, qRT-PCR was performed. Subsequently, we mapped the nomogram to visually and accurately describe the value of the application of ARG_score. Finally, the correlation between ARG_score and clinical features, immune infiltration along with drug sensitivity were explored.ResultsWe identified two ARG related subgroups and there were great differences in overall survival (OS) and tumor microenvironment. Then, we created an ARG_score for predicting overall survival based on eight DEGs and confirmed its reliable predictive power in COAD patients, with higher ARG_score associated with worse prognosis. Furthermore, eight ARG_score-related genes expression was investigated by qRT-PCR. To make the ARG_score clinically feasible, we created a highly reliable nomogram. We also found a higher proportion of microsatellite instability-high (MSI-H) and higher tumor mutational burden (TMB) in the high-risk group. In addition, ARG_score was notably correlated with cancer stem cell indices and drug sensitivity.ConclusionThis scoring model has potential clinical application value in the prognosis, immune microenvironment and therapeutic drug sensitivity of COAD, which provides new insights for personalized treatment.

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“…Various studies have highlighted that the alterations arise in FOXM1 during post-transcriptional and post-translational modifications, which leads to its deregulation and overexpression in cancer cells ( 55 , 57 ). The role of FOXM1 in tumor cells is its participation in the self–renewal and proliferation of cancer stem cells through Wnt signaling, the MAPK-ERK pathway, and the PI3K-mTOR pathway ( 58 ). Studies conducted on patients suffering from Osteosarcoma have revealed that the upregulation of miR-370 suppressed the expression of FOXMI.…”

Section: Discussionmentioning

confidence: 99%

Integrated gene network analysis sheds light on understanding the progression of Osteosarcoma

Dey

Vasudevan

et al. 2023

Front. Med.

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IntroductionOsteosarcoma is a rare disorder among cancer, but the most frequently occurring among sarcomas in children and adolescents. It has been reported to possess the relapsing capability as well as accompanying collateral adverse effects which hinder the development process of an effective treatment plan. Using networks of omics data to identify cancer biomarkers could revolutionize the field in understanding the cancer. Cancer biomarkers and the molecular mechanisms behind it can both be understood by studying the biological networks underpinning the etiology of the disease.MethodsIn our study, we aimed to highlight the hub genes involved in gene-gene interaction network to understand their interaction and how they affect the various biological processes and signaling pathways involved in Osteosarcoma. Gene interaction network provides a comprehensive overview of functional gene analysis by providing insight into how genes cooperatively interact to elicit a response. Because gene interaction networks serve as a nexus to many biological problems, their employment of it to identify the hub genes that can serve as potential biomarkers remain widely unexplored. A dynamic framework provides a clear understanding of biological complexity and a pathway from the gene level to interaction networks.ResultsOur study revealed various hub genes viz. TP53, CCND1, CDK4, STAT3, and VEGFA by analyzing various topological parameters of the network, such as highest number of interactions, average shortest path length, high cluster density, etc. Their involvement in key signaling pathways, such as the FOXM1 transcription factor network, FAK-mediated signaling events, and the ATM pathway, makes them significant candidates for studying the disease. The study also highlighted significant enrichment in GO terms (Biological Processes, Molecular Function, and Cellular Processes), such as cell cycle signal transduction, cell communication, kinase binding, transcription factor activity, nucleoplasm, PML body, nuclear body, etc.ConclusionTo develop better therapeutics, a specific approach toward the disease targeting the hub genes involved in various signaling pathways must have opted to unravel the complexity of the disease. Our study has highlighted the candidate hub genes viz. TP53, CCND1 CDK4, STAT3, VEGFA. Their involvement in the major signaling pathways of Osteosarcoma makes them potential candidates to be targeted for drug development. The highly enriched signaling pathways include FOXM1 transcription pathway, ATM signal-ling pathway, FAK mediated signaling events, Arf6 signaling events, mTOR signaling pathway, and Integrin family cell surface interactions. Targeting the hub genes and their associated functional partners which we have reported in our studies may be efficacious in developing novel therapeutic targets.

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Dysregulated FOXM1 signaling in the regulation of cancer stem cells

Cited by 56 publications

References 170 publications

Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer

Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer

Crosstalk of angiogenesis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in colorectal adenocarcinoma

Integrated gene network analysis sheds light on understanding the progression of Osteosarcoma

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