From oxygen sensing to angiogenesis: Targeting the hypoxia signaling pathway in metastatic kidney cancer

Prognostic Analysis of a Hypoxia-Associated lncRNA Signature in Glioblastoma and its Pan-Cancer Landscape

BACKGROUND

 Hypoxia is an important clinical feature of glioblastoma (GBM), which regulates a variety of tumor processes and is inseparable from radiotherapy. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) are strongly associated with survival outcomes in GBM patients and modulate hypoxia-induced tumor processes. Therefore, the aim of this study was to establish a hypoxia-associated lncRNAs (HALs) prognostic model to predict survival outcomes in GBM patients.

METHODS

 LncRNAs in GBM samples were extracted from The Cancer Genome Atlas database. Hypoxia-related genes were downloaded from the Molecular Signature Database. Co-expression analysis of differentially expressed lncRNAs and hypoxia-related genes in GBM samples was performed to determine HALs. Six optimal lncRNAs were selected for building HALs models by univariate Cox regression analysis.

RESULTS

 The prediction model has a good predictive effect on the prognosis of GBM patients. Meanwhile, LINC00957 among the six lncRNAs was selected and subjected to pan-cancer landscape analysis.

CONCLUSION

 Taken together, our findings suggest that the HALs assessment model can be used to predict the prognosis of GBM patients. In addition, LINC00957 included in the model may be a useful target to study the mechanism of cancer development and design individualized treatment strategies.

Rationale for immune checkpoint inhibitors plus targeted therapy for advanced renal cell carcinoma

Renal cell carcinoma (RCC) is a frequent urological malignancy characterized by a high rate of metastasis and lethality. The treatment strategy for advanced RCC has moved through multiple iterations over the past three decades. Initially, cytokine treatment was the only systemic treatment option for patients with RCC. With the development of medicine, antiangiogenic agents targeting vascular endothelial growth factor and mammalian target of rapamycin and immunotherapy, immune checkpoint inhibitors (ICIs) have emerged and received several achievements in the therapeutics of advanced RCC. However, ICIs have still not brought completely satisfactory results due to drug resistance and undesirable side effects. For the past years, the interests form researchers have been attracted by the combination of ICIs and targeted therapy for advanced RCC and the angiogenesis and immunogenic tumor microenvironmental variations in RCC. Therefore, we emphasize the potential principle and the clinical progress of ICIs combined with targeted treatment of advanced RCC, and summarize the future direction.

Catalase-gold nanoaggregates manipulate the tumor microenvironment and enhance the effect of low-dose radiation therapy by reducing hypoxia

Radiotherapy as a standard method for cancer treatment faces tumor recurrence and antitumoral unresponsiveness. Suppressive tumor microenvironment (TME) and hypoxia are significant challenges affecting efficacy of radiotherapy. Herein, a versatile method is introduced for the preparation of pH-sensitive catalase-gold cross-linked nanoaggregate (Au@CAT) having acceptable stability and selective activity in tumor microenvironment. Combining Au@CAT with low-dose radiotherapy enhanced radiotherapy effects via polarizing protumoral immune cells to the antitumoral landscape. This therapeutic approach also attenuated hypoxia, confirmed by downregulating hypoxia hallmarks, such as hypoxia-inducible factor α-subunits (HIF-α), vascular endothelial growth factor (VEGF), and EGF. Catalase stability against protease digestion was improved significantly in Au@CAT compared to the free catalase. Moreover, minimal toxicity of Au@CAT on normal cells and increased reactive oxygen species (ROS) were confirmed in vitro compared with radiotherapy. Using the nanoaggregates combined with radiotherapy led to a significant reduction of immunosuppressive infiltrating cells such as myeloid-derived suppressor cells (MDSCs) and regulatory T cells (T-regs) compared to the other groups. While, this combined therapy could significantly increase the frequency of CD8+ cells as well as M1 to M2 macrophages (MQs) ratio. The combination therapy also reduced the tumor size and increased survival rate in mice models of colorectal cancer (CRC). Our results indicate that this innovative nanocomposite could be an excellent system for catalase delivery, manipulating the TME and providing a potential therapeutic strategy for treating CRC.

The Role of Epithelial Mesenchymal Transition (EMT) in Pathogenesis of Cardiotoxicity: Diagnostic & Prognostic Approach

Cancer is one of the diseases, which it is not still completely curable; the existing treatments are associated with many complications, that double its complexity. One of the causes of cancer cell metastasis is Epithelial Mesenchymal Transition (EMT). Recently study demonstrated that EMT cause cardiotoxicity and heart diseases such as heart failure, hypertrophy and fibrosis. This study evaluated molecular and signaling pathway, which lead to cardiotoxicity via EMT. It was demonstrated that the processes of inflammation, oxidative stress and angiogenesis were involved in EMT and cardiotoxicity. The pathways related to these processes act as a double-edged sword. In relation to inflammation and oxidative stress, molecular pathways caused apoptosis of cardiomyocytes and cardiotoxicity induction. While the angiogenesis process inhibits cardiotoxicity despite the progression of EMT. On the other hand, some molecular pathways such as PI3K/mTOR despite causing the progression of EMT lead to the proliferation of cardiomyocytes and prevent cardiotoxicity. Therefore, it was concluded that the identification of molecular pathways can help in designing therapeutic and preventive strategies to increase patients' survival.

Belzutifan (MK-6482): Biology and Clinical Development in Solid Tumors

PURPOSE OF REVIEW

To review the biology, drug development, and clinical data regarding the efficacy and safety of belzutifan (MK-6482), a small molecule inhibitor of HIF-2α.

RECENT FINDINGS

Belzutifan, a second-generation HIF-2α inhibitor, was shown to provide clinically meaningful benefit in the treatment of VHL-associated tumors (including ccRCC, pancreatic lesions as well as neuroendocrine tumor, and CNS hemangioblastomas). The recommended dose of belzutifan is 120 mg orally daily and half-life is 14 h. In pretreated ccRCC, belzutifan achieved disease control rate of 80% in phase I trial. The most common side effects include anemia and hypoxia related symptoms. Investigation into the important role HIF-2α plays in the expression of genes associated with angiogenesis, erythropoiesis, carcinogenesis, and progression of tumors and the discovery of structural vulnerability within HIF-2α have resulted in the development of a new therapy that has demonstrated efficacy and safety in recent clinical trials. Further research is ongoing to optimize therapeutic benefits from this new exciting therapeutic modality and to improve the outcome of HIF-2α-driven tumors.

Dynamic Predictive Models with Visualized Machine Learning for Assessing the Risk of Lung Metastasis in Kidney Cancer Patients

Objective

To establish and verify the clinical prediction model of lung metastasis in renal cancer patients.

Method

Kidney cancer patients from January 1, 2010, to December 31, 2017, in the SEER database were enrolled in this study. In the first section, LASSO method was adopted to select variables. Independent influencing factors were identified after multivariate logistic regression analysis. In the second section, machine learning (ML) algorithms were implemented to establish models and 10-foldcross-validation was used to train the models. Finally, receiver operating characteristic curves, probability density functions, and clinical utility curve were applied to estimate model's performance. The final model was shown by a website calculator.

Result

Lung metastasis was confirmed in 7.43% (3171 out of 42650) of study population. In multivariate logistic regression, bone metastasis, brain metastasis, grade, liver metastasis, N stage, T stage, and tumor size were independent risk factors of lung metastasis in renal cancer patients. Primary site and sequence number were independent protection factors of LM in renal cancer patients. The above 9 impact factors were used to develop the prediction models, which included random forest (RF), naive Bayes classifier (NBC), decision tree (DT), xgboost (XGB), gradient boosting machine (GBM), and logistic regression (LR). In 10-foldcross-validation, the average area under curve (AUC) ranked from 0.907 to 0.934. In ROC curve analysis, AUC ranged from 0.879–0.922. We found that the XGB model performed best, and a Web-based calculator was done according to XGB model.

Conclusion

This study provided preliminary evidence that the ML algorithm can be used to predict lung metastases in patients with kidney cancer. This low cost, noninvasive and easy to implement diagnostic method is useful for clinical work. Of course this model still needs to undergo more real-world validation.

Belzutifan: First Approval

Belzutifan (Welireg™) is an oral small molecule inhibitor of hypoxia-inducible factor (HIF)-2α being developed by Peloton Therapeutics for the treatment of solid tumours, including renal cell carcinoma (RCC) with clear cell histology (ccRCC) and von Hippel-Lindau (VHL) disease-associated RCC. In August 2021, belzutifan received its first approval in the USA for the treatment of patients with VHL disease who require therapy for associated RCC, central nervous system (CNS) haemangioblastomas or pancreatic neuroendocrine tumours (pNET), not requiring immediate surgery. Clinical studies of belzutifan (as monotherapy or combination therapy) in other indications, including ccRCC, pNET and phaeochromocytoma/paraganglioma, are also underway in various countries. This article summarizes the milestones in the development of belzutifan leading to this first approval for certain VHL disease-associated tumours.

The antitumor mechanisms of aerobic exercise: A review of recent preclinical studies

Aerobic exercise is an important non‐pharmacological means of antitumor intervention, but related mechanisms are poorly understood. In this review, previous studies are summarized from the aspects of tumor oxygenation, autophagy versus apoptosis, and organismal immunity. Current findings on the antitumor effects of aerobic exercise involve AMPK signaling, PI3K/Akt signaling, Th1/Th2 cytokine balance related to immunity, PD‐1/PD‐L1 immunosuppressive signaling, and related cytokine pathways. Several directions for further research are proposed, including whether newly discovered subgroups of cytokines influence the effects of aerobic exercise on tumors, tailoring corresponding exercise prescriptions based on the bidirectional effects of certain cytokines at different stages, identifying the potential effects of exercise time and intensity, and elucidating details of the unclear mechanisms. Through the discussion of the existing data, we hope to provide new ideas for the future research of exercise therapy.

An Effective Hypoxia-Related Long Non-Coding RNAs Assessment Model for Prognosis of Clear Cell Renal Carcinoma

Hypoxia is a significant clinical feature and regulates various tumor processes in clear cell renal carcinoma (ccRCC). Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) are closely associated with the survival outcomes of ccRCC patients and regulates hypoxia-induced tumor processes. Thus, this study aimed to develop a hypoxia-related lncRNA (HRL) prognostic model for predicting the survival outcomes in ccRCC. LncRNAs in ccRCC samples were extracted from The Cancer Genome Atlas database. Hypoxia-related genes were downloaded from the Molecular Signatures Database. A co-expression analysis between differentially expressed lncRNAs and hypoxia-related genes in ccRCC samples was performed to identify HRLs. Univariate and multivariate Cox regression analyses were performed to select nine optimal lncRNAs for developing the HRL model. The prognostic model showed good performance in predicting prognosis among patients with ccRCC, and the validation sets reached consistent results. The model was also found to be related to the clinicopathologic parameters of tumor grade and tumor stage and to tumor immune infiltration. In conclusion, our findings indicate that the hypoxia-lncRNA assessment model may be useful for prognostication in ccRCC cases. Furthermore, the nine HRLs included in the model might be useful targets for investigating the tumorigenesis of ccRCC and designing individualized treatment strategies.