Sorafenib as a second-line treatment in metastatic renal cell carcinoma in Mexico: a prospective cohort study

Martin-Aguilar, Ana Elena; Núñez-López, Haidé Nayeli; Ramirez‐Sandoval, Juan C.

doi:10.1186/s12885-020-07720-5

Cited by 7 publications

(4 citation statements)

References 33 publications

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“…In topic seven, key text features such as kidney neoplasms, carcinoma, renal cell, and Wilms tumor implied the relationship between topic seven and kidney cancer. Inhibitors for kidney cancer, such as sorafenib and everolimus, were also identified ( Martín-Aguilar et al, 2021 ; Ren et al, 2021 ). The hypoxia pathway enriched by VHL , VEGFA , and PBRM1 ( p = 5.41e-11) played a crucial role in the governance of cancer stem cells of renal cancer ( Myszczyszyn et al, 2015 ) ( Figure 7B ).…”

Section: Resultsmentioning

confidence: 99%

Contextualizing Genes by Using Text-Mined Co-Occurrence Features for Cancer Gene Panel Discovery

et al. 2021

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Developing a biomedical-explainable and validatable text mining pipeline can help in cancer gene panel discovery. We create a pipeline that can contextualize genes by using text-mined co-occurrence features. We apply Biomedical Natural Language Processing (BioNLP) techniques for literature mining in the cancer gene panel. A literature-derived 4,679 × 4,630 gene term-feature matrix was built. The EGFR L858R and T790M, and BRAF V600E genetic variants are important mutation term features in text mining and are frequently mutated in cancer. We validate the cancer gene panel by the mutational landscape of different cancer types. The cosine similarity of gene frequency between text mining and a statistical result from clinical sequencing data is 80.8%. In different machine learning models, the best accuracy for the prediction of two different gene panels, including MSK-IMPACT (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets), and Oncomine cancer gene panel, is 0.959, and 0.989, respectively. The receiver operating characteristic (ROC) curve analysis confirmed that the neural net model has a better prediction performance (Area under the ROC curve (AUC) = 0.992). The use of text-mined co-occurrence features can contextualize each gene. We believe the approach is to evaluate several existing gene panels, and show that we can use part of the gene panel set to predict the remaining genes for cancer discovery.

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Section: Resultsmentioning

confidence: 99%

Contextualizing Genes by Using Text-Mined Co-Occurrence Features for Cancer Gene Panel Discovery

et al. 2021

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“…In contrast, others have attested to better results with axitinib, instead of sorafenib, as a second line option [ 7 , 15 ]. Both Schmidinger et al and Géczi et al have recommended second-line axitinib post sunitinib [ 16 , 17 ], whereas sorafenib as a second-line treatment (following sunitinib failure) has been favored by other investigators [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Antiangiogenic Properties of Axitinib versus Sorafenib Following Sunitinib Resistance in Human Endothelial Cells—A View towards Second Line Renal Cell Carcinoma Treatment

et al. 2021

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Tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors predominate as first-line therapy options for renal cell carcinoma. When first-line TKI therapy fails due to resistance development, an optimal second-line therapy has not yet been established. The present investigation is directed towards comparing the anti-angiogenic properties of the TKIs, sorafenib and axitinib on human endothelial cells (HUVECs) with acquired resistance towards the TKI sunitinib. HUVECs were driven to resistance by continuously exposing them to sunitinib for six weeks. They were then switched to a 24 h or further six weeks treatment with sorafenib or axitinib. HUVEC growth, as well as angiogenesis (tube formation and scratch wound assay), were evaluated. Cell cycle proteins of the CDK-cyclin axis (CDK1 and 2, total and phosphorylated, cyclin A and B) and the mTOR pathway (AKT, total and phosphorylated) were also assessed. Axitinib (but not sorafenib) significantly suppressed growth of sunitinib-resistant HUVECs when they were exposed for six weeks. This axinitib-associated growth reduction was accompanied by a cell cycle block at the G0/G1-phase. Both axitinib and sorafenib reduced HUVEC tube length and prevented wound closure (sorafenib > axitinib) when applied to sunitinib-resistant HUVECs for six weeks. Protein analysis revealed diminished phosphorylation of CDK1, CDK2 and pAKT, accompanied by a suppression of cyclin A and B. Both drugs modulated CDK-cyclin and AKT-dependent signaling, associated either with both HUVEC growth and angiogenesis (axitinib) or angiogenesis alone (sorafenib). Axitinib and sorafenib may be equally applicable as second line treatment options, following sunitinib resistance.

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“…In addition, higher GPX4 expression is correlated with a higher IC50 value of sorafenib; however, higher ACSL4 expression corresponds to a lower IC50 value of sorafenib in RCC patients, indicating that these ferroptosis-related genes are closely related to drug sensitivity (Fig. 3D) [281][282][283]. In fact, the effect of sorafenib on ferroptosis induction is still controversial.…”

Section: Ferroptosis and Nephrolithiasismentioning

confidence: 99%

Emerging significance and therapeutic targets of ferroptosis: a potential avenue for human kidney diseases

Li,

Zheng,

Fan

et al. 2023

Cell Death Dis

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Kidney diseases remain one of the leading causes of human death and have placed a heavy burden on the medical system. Regulated cell death contributes to the pathology of a plethora of renal diseases. Recently, with in-depth studies into kidney diseases and cell death, a new iron-dependent cell death modality, known as ferroptosis, has been identified and has attracted considerable attention among researchers in the pathogenesis of kidney diseases and therapeutics to treat them. The majority of studies suggest that ferroptosis plays an important role in the pathologies of multiple kidney diseases, such as acute kidney injury (AKI), chronic kidney disease, and renal cell carcinoma. In this review, we summarize recently identified regulatory molecular mechanisms of ferroptosis, discuss ferroptosis pathways and mechanisms of action in various kidney diseases, and describe the protective effect of ferroptosis inhibitors against kidney diseases, especially AKI. By summarizing the prominent roles of ferroptosis in different kidney diseases and the progress made in studying ferroptosis, we provide new directions and strategies for future research on kidney diseases. In summary, ferroptotic factors are potential targets for therapeutic intervention to alleviate different kidney diseases, and targeting them may lead to new treatments for patients with kidney diseases.

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Sorafenib as a second-line treatment in metastatic renal cell carcinoma in Mexico: a prospective cohort study

Cited by 7 publications

References 33 publications

Contextualizing Genes by Using Text-Mined Co-Occurrence Features for Cancer Gene Panel Discovery

Contextualizing Genes by Using Text-Mined Co-Occurrence Features for Cancer Gene Panel Discovery

Antiangiogenic Properties of Axitinib versus Sorafenib Following Sunitinib Resistance in Human Endothelial Cells—A View towards Second Line Renal Cell Carcinoma Treatment

Emerging significance and therapeutic targets of ferroptosis: a potential avenue for human kidney diseases

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