Amitriptyline down-regulates coenzyme Q10 biosynthesis in lung cancer cells

Ortiz, T.; Paz, Marina Villanueva; Díaz-Parrado, Eduardo; Illanes, Matilde; Fernández-Rodríguez, Ana; Sánchez-Alcázar, José A.; Miguel, Manuel de

doi:10.1016/j.ejphar.2017.01.017

Cited by 8 publications

(5 citation statements)

References 46 publications

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“…Besides, it can affect the production of reactive oxygen species by affecting the synthesis of coenzyme Q10. This result has been verified in lung cancer cell lines [ 67 ]. Other tricyclic antidepressants were confirmed to induce autophagic cell death by affecting PI3K/AKT/mTOR signaling pathway in GBM cell line U-87MG [ 68 ].…”

Section: Discussionsupporting

confidence: 52%

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

Wang

Yang

et al. 2021

Briefings in Bioinformatics

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Glioblastoma (GBM) is the most malignant and lethal intracranial tumor, with extremely limited treatment options. Immunotherapy has been widely studied in GBM, but none can significantly prolong the overall survival (OS) of patients without selection. Considering that GBM cancer stem cells (CSCs) play a non-negligible role in tumorigenesis and chemoradiotherapy resistance, we proposed a novel stemness-based classification of GBM and screened out certain population more responsive to immunotherapy. The one-class logistic regression algorithm was used to calculate the stemness index (mRNAsi) of 518 GBM patients from The Cancer Genome Atlas (TCGA) database based on transcriptomics of GBM and pluripotent stem cells. Based on their stemness signature, GBM patients were divided into two subtypes via consensus clustering, and patients in Stemness Subtype I presented significantly better OS but poorer progression-free survival than Stemness Subtype II. Genomic variations revealed patients in Stemness Subtype I had higher somatic mutation loads and copy number alteration burdens. Additionally, two stemness subtypes had distinct tumor immune microenvironment patterns. Tumor Immune Dysfunction and Exclusion and subclass mapping analysis further demonstrated patients in Stemness Subtype I were more likely to respond to immunotherapy, especially anti-PD1 treatment. The pRRophetic algorithm also indicated patients in Stemness Subtype I were more resistant to temozolomide therapy. Finally, multiple machine learning algorithms were used to develop a 7-gene Stemness Subtype Predictor, which were further validated in two external independent GBM cohorts. This novel stemness-based classification could provide a promising prognostic predictor for GBM and may guide physicians in selecting potential responders for preferential use of immunotherapy.

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Section: Discussionsupporting

confidence: 52%

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

Wang

Yang

et al. 2021

Briefings in Bioinformatics

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“…[ 30 ] MAOIs inhibit the differentiation of acute myeloid leukemia cells to exert an antitumor effect. [ 31 ] TcAs inhibit the occurrence and development of malignant tumors, including lung cancer, [ 32 , 33 ] glioma, [ 34 , 35 ] liver cancer, [ 36 ] lymphoma, [ 27 ] and melanoma. [ 37 ] SSRIs induce apoptosis of lymphoma cells, [ 38 ] inhibit the proliferation of colon cancer cells, [ 39 ] and enhance the antitumor immunity of melanoma.…”

Section: Discussionmentioning

confidence: 99%

HTR1A Inhibits the Progression of Triple‐Negative Breast Cancer via TGF‐β Canonical and Noncanonical Pathways

et al. 2022

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Triple‐negative breast cancer is the most aggressive subtype of breast cancer and the incidence of depression in breast cancer patients is high, which leading to worse survival and increased risk of recurrence. The effect of antidepressants on breast cancer patients remains contradictory, which might be due to variations in antidepression targets. Therefore, there is significant value to explore the antitumor potential of antidepressants and discover new therapeutic targets for breast patients. The authors screen antidepressant‐related oncogenes or suppressors by using siRNAs. After combining functional experiments with online database analysis, 5‐hydroxytryptamine receptor 1A (HTR1A is selected with antitumor potential in breast cancer cells in vivo and in vitro. RNA‐seq analysis and coimmunoprecipitation assays indicate that HTR1A interacts with TRIM21 and PSMD7 to inhibit the degradation of T β RII through the ubiquitin‐proteasome pathway, thereby inhibiting the transforming growth factor‐ β (TGF‐β) canonical and noncanonical pathway. In addition, HTR1A is an independent predictive factor for breast cancer patients. The combined treatment of HTR1A agonists with demethylation drugs may significantly improve patient survival. It is of great significance to clarify the function and mechanism of the depression‐related gene HTR1A in breast cancer, which might provide a new approach for triple‐negative breast cancer patients.

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“…Some other NMRGs, such as LRPPRC [ 21 ], DARS2 [ 12 ], GARS [ 22 ], ATAD3 [ 23 ], TRMU [ 24 ], and PDSS1 [ 25 ] had been identified to be correlated with the carcinogenesis and progression in HCC. Moreover, the aberrant expression of COX15 [ 26 ], LARS [ 27 ], PARS2 [ 28 ], MRPL3 [ 29 ], ISCU [ 30 ], COQ7 [ 31 ], SPG7 [ 32 ], TRMT10C [ 33 ], and COQ6 [ 34 ] were found to have certain influence on the tumor invasions in many other cancer types. However, in the present study, it was the first time that the expressions of these NMRGs, including HARS2 , MPV17 , MTFMT, C12ORF65 , FRDA , CARS2 , VARS2 , and CABC1 , were found to have influence on the progression of HCC patients.…”

Section: Discussionmentioning

confidence: 99%

Mitochondrial-Related Transcriptome Feature Correlates with Prognosis, Vascular Invasion, Tumor Microenvironment, and Treatment Response in Hepatocellular Carcinoma

Wang

Song

Zhang

et al. 2022

Oxidative Medicine and Cellular Longevity

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Background. Hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, which was highly correlated with metabolic dysfunction. Nevertheless, the association between nuclear mitochondrial-related transcriptome and HCC remained unclear. Materials and Methods. A total of 147 nuclear mitochondrial-related genes (NMRGs) were downloaded from the MITOMAP: A Human Mitochondrial Genome Database. The training dataset was downloaded from The Cancer Genome Atlas (TCGA), while validation datasets were retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). The univariate and multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were applied to construct a NMRG signature, and the value of area under receiver operating characteristic curve (AUC) was utilized to assess the signature and nomogram. Then, data from the Genomics of Drug Sensitivity in Cancer (GDSC) were used for the evaluation of chemotherapy response in HCC. Results. Functional enrichment of differentially expressed genes (DEGs) between HCC and paired normal tissue samples demonstrated that mitochondrial dysfunction was significantly associated with HCC development. Survival analysis showed a total of 35 NMRGs were significantly correlated with overall survival (OS) of HCC, and the LASSO Cox regression analysis further identified a 25-NMRG signature and corresponding prognosis score based on their transcriptional profiling. HCC patients were divided into high- and low-risk groups according to the median prognosis score, and high-risk patients had significantly worse OS (median OS: 27.50 vs. 83.18 months, P < 0.0001 ). The AUC values for OS at 1, 3, and 5 years were 0.79, 0.77, and 0.77, respectively. The prognostic capacity of NMRG signature was verified in the GSE14520 dataset and ICGC-HCC cohort. Besides, the NMRG signature outperformed each NMRG and clinical features in prognosis prediction and could also differentiate whether patients presented with vascular invasions (VIs) or not. Subsequently, a prognostic nomogram (C-index: 0.753, 95% CI: 0.703~0.804) by the integration of age, tumor metastasis, and NMRG prognosis score was constructed with the AUC values for OS at 1, 3, and 5 years were 0.82, 0.81, and 0.82, respectively. Notably, significant enrichment of regulatory and follicular helper T cells in high-risk group indicated the potential treatment of immune checkpoint inhibitors for these patients. Interestingly, the NMRG signature could also identify the potential responders of sorafenib or transcatheter arterial chemoembolization (TACE) treatment. Additionally, HCC patients in high-risk group appeared to be more sensitive to cisplatin, vorinostat, and methotrexate, reversely, patients in low-risk group had significantly higher sensitivity to paclitaxel and bleomycin instead. Conclusions. In summary, the development of NMRG signature provided a more comprehensive understanding of mitochondrial dysfunction in HCC, helped predict prognosis and tumor microenvironment, and provided potential targeted therapies for HCC patients with different NMRG prognosis scores.

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Amitriptyline down-regulates coenzyme Q10 biosynthesis in lung cancer cells

Cited by 8 publications

References 46 publications

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

HTR1A Inhibits the Progression of Triple‐Negative Breast Cancer via TGF‐β Canonical and Noncanonical Pathways

Mitochondrial-Related Transcriptome Feature Correlates with Prognosis, Vascular Invasion, Tumor Microenvironment, and Treatment Response in Hepatocellular Carcinoma

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