Lung adenocarcinoma is the most common pathological pattern of lung cancer. During the past decades, a number of targeted agents have been explored to treat advanced lung adenocarcinoma. In the present clinical practice, antagonists of the epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF)-directed therapies are widely used. In the former category, the agent erlotinib (tyrosine kinase inhibitor) has shown obvious advantages over cytotoxic therapy. Anti-VEGF therapy bevacizumab used for lung adenocarcinoma was recommended in NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) as first-line therapy. Similarly, apatinib is speculated to response by selectively inhibiting the vascular endothelial growth factor receptor-2. The patient with unknown EGFR status benefited 5-month progressive free survival (PFS) from erlotinib, and then another 5.1-month PFS with combined treatment of apatinib, which suggested a new option for lung adenocarcinoma. However, when dabigatran was used to cancer-related venous thromboembolism during apatinib therapy, extensive subcutaneous bleeding occurred, warning us against the risks of bleeding. Besides, hypertension and anorexia were observed, causing dosage adjustment.
Background Patients with advanced clear cell renal cell carcinoma (ccRCC) have a poor prognosis and lack effective prognostic biomarkers. N6‐methyladenosine‐related lncRNAs (m6A‐related long noncoding RNAs [lncRNAs]) have been confirmed to be associated with the development of multiple tumors, but its role in ccRCC is not clear. Methods Gene expression data and clinical information of ccRCC patients were extracted from The Cancer Genome Atlas Database. The prognostic m6A‐related lncRNAs were obtained by Pearson's correlation analysis and univariate Cox regression analysis. Afterward, the cluster classification and its correlation with prognosis, clinical characteristics, and immunity were analyzed. LASSO regression was used to establish the prognostic risk model. The predictive performance of the prognostic model was evaluated and validated by survival analysis and receiver operating characteristic curve analysis, et al. The expression of immune checkpoints and immune cell infiltration in patients with different risks were systematically analyzed. Results A total of 27 prognostic m6A‐related lncRNAs were identified. These m6A‐related lncRNAs were differentially expressed between tumor and normal tissues. Among them, 24 high‐risk m6A‐related lncRNAs were overexpressed in Cluster 2 and correlated with poor prognosis, low stromal score, high expression of immune checkpoints, and immunosuppressive cells infiltration. Based upon, a prognostic risk model composed of seven m6A‐related lncRNAs was constructed. After a series of analyses, it was proved that this model had good sensitivity and specificity, and could predict the prognosis of patients with different clinical stratification. The expression of PD‐1, PD‐L1, CTLA‐4, LAG‐3, TIM‐3, and TIGIT were significantly increased in the high‐risk patients, and there was a correlation between the risk score and immune cell infiltration. Conclusions The seven m6A‐related lncRNAs prognostic risk signature showed reliable prognostic predictive power for ccRCC and was associated with the expression of immune checkpoints and immune cell infiltration. This seven m6A‐related lncRNAs signature will be helpful in managing ccRCC and guiding individualized immunotherapy.
Background. The heat shock protein 90 (HSP90s) family is composed of molecular chaperones composed of four isoforms in humans, which has been widely reported as unregulated in various kinds of cancers. Nevertheless, the role of each HSP90s isoform in prognosis and immune infiltration in distinct subtypes of breast cancer (BRAC) remains unclear. Methods. Public online databases including the Oncomine, UALCAN, Kaplan-Meier Plotter, Tumor IMmune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), GeneMANIA, and Database for Annotation, Visualization, and Integrated Discovery (DAVID) were integrated to perform bioinformatic analyses and to explore the possible associations among HSP90s gene expression, prognosis, and immune infiltration in BRAC. Results. The mRNA expression of all HSP90s members was elevated in distinct clinical stages and subtypes of BRAC, compared with the normal breast tissue ( P < 0.05 ). Overexpressed HSP90AA1 was associated with poor prognosis, particularly, both short overall survival (OS) and release-free survival (RFS) in Basal-like BRAC patients; overexpressed HSP90AB1 and HSP90B1 were both associated with poor RFS in Luminal A BRAC patients, while overexpressed TRAP1 was associated with favorable RFS in Luminal A BRAC patients. Moreover, HSP90s gene expression in BRAC showed correlations with the infiltration of CD8+ T cells, neutrophils, macrophages, and dendritic cells (DCs), as well as the activation of tumor-associated macrophages (TAMs), DCs, and CD4+ helper T (Th) cells. The underlying mechanisms of HSP90s modulating tumor-infiltrating immune cells (TIICs) might be related with their functions in antigen processing and presentation, major histocompatibility complex (MHC) binding, and assisting client proteins. Conclusion. This study demonstrated that HSP90s family genes were overexpressed and might be serve as prognostic biomarkers in subtypes of BRAC. It might be a novel breakthrough point of BRAC treatment to regulate immune infiltration in BRAC microenvironment for more effective anticancer immunity through pharmacological intervention of HSP90s.
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