Erlotinib is a highly specific and reversible epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), but resistance inevitably develops as the disease progresses. Erlotinib resistance and cancer stem cells (CSCs) are poor factors hindering the prognosis of patients with lung adenocarcinoma (LUAD). Although studies have shown that erlotinib resistance and CSCs can jointly promote cancer development, the mechanism is currently unclear. Here, we investigated the potential biomarker and molecular mechanism of erlotinib resistance and cancer stemness in LUAD. An erlotinib resistance model based on four genes was constructed from The Cancer Genome Atlas (TCGA), the GEO database, the Cancer Cell Line Encyclopedia (CCLE), and the Genomics of Drug Sensitivity in Cancer (GDSC). Through multiple bioinformatic analyses, NCAPG2 was identified as a key gene for erlotinib resistance and stemness in LUAD. Further in vitro experiments demonstrated that NCAPG2 maintains stemness and contributes to erlotinib resistance in LUAD. In summary, NCAPG2 plays a vital role in stemness and erlotinib resistance in LUAD.
Glioblastoma is classified as an immunocompromised tumor. The immune pattern beneath the cold tumor surface, however, has yet to be confirmed. Understanding the immune pattern of glioblastoma will aid in the development of effective treatment strategies. We performed weighted gene co-expression network analysis on all immune-related genes in TCGA-GBM transcriptional data and screened 35 prognosis-related immune genes. Unsupervised consistent clustering of these genes was used to analyze the immunological pattern of GBM. A glioblastoma immune prognostic score was developed by using 13 genes discovered by cox regression methods and verified with the GEO dataset to assess the immune profile, prognosis, and immunotherapy effects in individual patients. Glioblastoma has two immune modalities, immune tolerance and immunodeficiency, with distinct immune microenvironments, tumor-associated macrophages being one of the most promising new therapeutic targets. GIPS is a promising biomarker for assessing immune evasion mechanisms, immunotherapy responses, and prognosis in patients.
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