Pan-Cancer analysis of TERT and Validation in Osteosarcoma Cell Lines

Xie, Long; Yin, Wei; Tang, Fuxing; He, Maolin

doi:10.1016/j.bbrc.2022.11.068

Cited by 3 publications

(4 citation statements)

References 37 publications

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“…In addition, TERT was a potential prognostic biomarker in diagnosis and prognosis of cancer, including breast cancer, thyroid cancer, and bladder cancer 40 – 42 . Moreover, the suppression of TERT expression decreased osteosarcoma cell metastasis, motility, and proliferation 39 . At present, the role of Coiled-coil domain containing (CCDC26) in cancer prognosis remains unexplored.…”

Section: Discussionmentioning

confidence: 97%

“…TERT gene exerted carcinogenic effect, targeting TERT was an effective therapy in the treatment of non-small cell lung cancer 38 . TERT could potentially function as a valuable genomic indicator for detecting and forecasting various types of cancer, while also holding promise as a potential target for therapeutic interventions in the case of OS 39 . In addition, TERT was a potential prognostic biomarker in diagnosis and prognosis of cancer, including breast cancer, thyroid cancer, and bladder cancer 40 – 42 .…”

Section: Discussionmentioning

confidence: 99%

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The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients

Liu,

Wang

et al. 2024

Sci Rep

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Host immune dysregulation involves in the initiation and development of osteosarcoma (OS). However, the exact role of immune cells in OS remains unknown. We aimed to distinguish the molecular subtypes and establish a prognostic model in OS patients based on immunocyte infiltration. The gene expression profile and corresponding clinical feature of OS patients were obtained from TARGET and GSE21257 datasets. MCP-counter and univariate Cox regression analyses were applied to identify immune cell infiltration-related molecular subgroups. Functional enrichment analysis and immunocyte infiltration analysis were performed between two subgroups. Furthermore, Cox regression and LASSO analyses were performed to establish the prognostic model for the prediction of prognosis and metastasis in OS patients. The subgroup with low infiltration of monocytic lineage (ML) was related to bad prognosis in OS patients. 435 DEGs were screened between the two subgroups. Functional enrichment analysis revealed these DEGs were involved in immune- and inflammation-related pathways. Three important genes (including TERT, CCDC26, and IL2RA) were identified to establish the prognostic model. The risk model had good prognostic performance for the prediction of metastasis and overall survival in OS patients. A novel stratification system was established based on ML-related signature. The risk model could predict the metastasis and prognosis in OS patients. Our findings offered a novel sight for the prognosis and development of OS.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients

Liu,

Wang

et al. 2024

Sci Rep

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“…TERT is an enzyme with a role in maintaining the length of telomeres, comprising protective caps at the ends of chromosomes 23 . TERT is often upregulated in osteosarcoma, producing it at higher levels than normal 24 . This upregulation of TERT allows cancer cells to divide and grow continuously because it helps to prevent the shortening of telomeres that would normally occur during each round of cell division.…”

Section: Discussionmentioning

confidence: 99%

“…23 TERT is often upregulated in osteosarcoma, producing it at higher levels than normal. 24 This upregulation of TERT allows cancer cells to divide and grow continuously because it helps to prevent the shortening of telomeres that would normally occur during each round of cell division. By maintaining the length of telomeres, TERT promotes the immortality of cancer cells and contributes to the development and progression of osteosarcoma.…”

Section: In Vitro Validation Of Tertmentioning

confidence: 99%

Diverse cell death patterns‐related signature for predicting prognosis and drug sensitivity of osteosarcoma patients

Shi,

Wu,

Zhang

et al. 2023

The Journal of Gene Medicine

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BackgroundProgrammed cell death (PCD) is a natural process in which cells undergo controlled self‐destruction, which plays a crucial role in maintaining tissue homeostasis and eliminating damaged or unnecessary cells. The connection between PCD and osteosarcoma was explored in the present study.MethodsTwelve types of PCD were collected for developing a prognostic signature in osteosarcoma using machine learning algorithms. The prognostic value, pathway annotation and drug prediction of the signature were explored.ResultsTelomerase reverse transcriptase (TERT) was found to be a potent hazardous marker in osteosarcoma and could facilitate the proliferation and migration of osteosarcoma.ConclusionsIn summary, the present study has developed a prognostic signature for osteosarcoma and identifies TERT as a potent hazardous gene. The study suggests that further research is needed to address the underlying mechanism of how TERT affects the immune response in osteosarcoma.

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EMT-related gene classifications predict the prognosis, immune infiltration, and therapeutic response of osteosarcoma

Li,

Long,

Liu

et al. 2024

Front. Pharmacol.

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BackgroundOsteosarcoma (OS), a bone tumor with high ability of invasion and metastasis, has seriously affected the health of children and adolescents. Many studies have suggested a connection between OS and the epithelial-mesenchymal transition (EMT). We aimed to integrate EMT-Related genes (EMT-RGs) to predict the prognosis, immune infiltration, and therapeutic response of patients with OS.MethodsWe used consensus clustering to identify potential EMT-Related OS molecular subtypes. Somatic mutation, tumor immune microenvironment, and functional enrichment analyses were performed for each subtype. We next constructed an EMT-Related risk signature and evaluated it by Kaplan-Meier (K-M) analysis survival and receiver operating characteristic (ROC) curves. Moreover, we constructed a nomogram to more accurately predict OS patients’ clinical outcomes. Response effects of immunotherapy in OS patients was analyzed by Tumor Immune Dysfunction and Exclusion (TIDE) analysis, while sensitivity for chemotherapeutic agents was analyzed using oncoPredict. Finally, the expression patterns of hub genes were investigated by single-cell RNA sequencing (scRNA-seq) data analysis.ResultsA total of 53 EMT-RDGs related to prognosis were identified, separating OS samples into two separate subgroups. The EMT-high subgroup showed favourable overall survival and more active immune response. Significant correlations were found between EMT-Related DEGs and functions as well as pathways linked to the development of OS. Additionally, a risk signature was established and OS patients were divided into two categories based on the risk scores. The signature presented a good predictive performance and could be recognized as an independent predictive factor for OS. Furthermore, patients with higher risk scores exhibited better sensitivity for five drugs, while no significant difference existed in immunotherapy response between the two risk subgroups. scRNA-seq data analysis displayed different expression patterns of the hub genes.ConclusionWe developed a novel EMT-Related risk signature that can be considered as an independent predictor for OS, which may help improve clinical outcome prediction and guide personalized treatments for patients with OS.

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Pan-Cancer analysis of TERT and Validation in Osteosarcoma Cell Lines

Cited by 3 publications

References 37 publications

The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients

The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients

Diverse cell death patterns‐related signature for predicting prognosis and drug sensitivity of osteosarcoma patients

EMT-related gene classifications predict the prognosis, immune infiltration, and therapeutic response of osteosarcoma

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