Systematic bioinformatic approaches reveal novel gene expression signatures associated with acquired resistance to EGFR targeted therapy in lung cancer

ITGAM is a critical gene in ischemic stroke

BACKGROUND

Globally, ischemic stroke (IS) is ranked as the second most prevailing cause of mortality and is considered lethal to human health. This study aimed to identify genes and pathways involved in the onset and progression of IS.

METHODS

GSE16561 and GSE22255 were downloaded from the Gene Expression Omnibus (GEO) database, merged, and subjected to batch effect removal using the ComBat method. The limma package was employed to identify the differentially expressed genes (DEGs), followed by enrichment analysis and protein-protein interaction (PPI) network construction. Afterward, the cytoHubba plugin was utilized to screen the hub genes. Finally, a ROC curve was generated to investigate the diagnostic value of hub genes. Validation analysis through a series of experiments including qPCR, Western blotting, TUNEL, and flow cytometry was performed.

RESULTS

The analysis incorporated 59 IS samples and 44 control samples, revealing 226 DEGs, of which 152 were up-regulated and 74 were down-regulated. These DEGs were revealed to be linked with the inflammatory and immune responses through enrichment analyses. Overall, the ROC analysis revealed the remarkable diagnostic potential of ITGAM and MMP9 for IS. Quantitative assessment of these genes showed significant overexpression in IS patients. ITGAM modulation influenced the secretion of critical inflammatory cytokines, such as IL-1β, IL-6, and TNF-α, and had a distinct impact on neuronal apoptosis.

CONCLUSIONS

The inflammation and immune response were identified as potential pathological mechanisms of IS by bioinformatics and experiments. In addition, ITGAM may be considered a potential therapeutic target for IS.

Gene Expression Profiling as a Potential Tool for Precision Oncology in Non-Small Cell Lung Cancer

Recent technological advances and the application of high-throughput mutation and transcriptome analyses have improved our understanding of cancer diseases, including non-small cell lung cancer. For instance, genomic profiling has allowed the identification of mutational events which can be treated with specific agents. However, detection of DNA alterations does not fully recapitulate the complexity of the disease and it does not allow selection of patients that benefit from chemo- or immunotherapy. In this context, transcriptional profiling has emerged as a promising tool for patient stratification and treatment guidance. For instance, transcriptional profiling has proven to be especially useful in the context of acquired resistance to targeted therapies and patients lacking targetable genomic alterations. Moreover, the comprehensive characterization of the expression level of the different pathways and genes involved in tumor progression is likely to better predict clinical benefit from different treatments than single biomarkers such as PD-L1 or tumor mutational burden in the case of immunotherapy. However, intrinsic technical and analytical limitations have hindered the use of these expression signatures in the clinical setting. In this review, we will focus on the data reported on molecular classification of non-small cell lung cancer and discuss the potential of transcriptional profiling as a predictor of survival and as a patient stratification tool to further personalize treatments.

VPS34 suppression reverses osimertinib resistance via simultaneously inhibiting glycolysis and autophagy

Autophagy and glycolysis are associated with osimertinib resistance. The energy complement and dynamic balance between these two processes make it difficult to block the process of drug resistance; breaking the complementary relationship between them may effectively overcome drug resistance. However, the exact mechanisms and the key players for regulating autophagy and glycolysis remain unclear. In this study, we demonstrate that autophagy and glycolysis levels in osimertinib-resistant cells were markedly higher than parental cells, and a dynamic balance existed between them. Inhibition of the class III phosphoinositide 3-kinase vacuolar protein sorting 34 (VPS34) with 3-methyladenine or small interfering RNA can not only inhibit abnormally enhanced autophagy but also inhibit glycolysis by inhibiting the location of epidermal growth factor receptor (EGFR) and the expression of hexokinase II. By demonstrating that VPS34 is the key player controlling autophagy and glycolysis simultaneously, our study may provide a new strategy for overcoming osimertinib resistance for treatment of EGFR-mutant non-small cell lung cancer patients.

Expression and prognostic value of E2F3 transcription factor in non-small cell lung cancer

E2F transcription factor 3 (E2F3) plays a vital role in the development of various types of cancer. To verify whether E2F3 is a suitable biomarker for the prognosis of lung cancer, bioinformatics analysis was performed to determine the differential expression level of E2F3 in lung cancer and the surrounding non-tumor tissues, and the results were confirmed in a NSCLC cell line and a tissue microarray (TMA). The relevance of E2F3 in non-small cell lung cancer (NSCLC) was investigated in 19 studies from the Oncomine database and confirmed in The Cancer Genome Atlas database. In the lung cancer cell line A549, the inhibition of E2F3 mRNA expression level led to decreased tumor cell viability and cell migration, which was determined by a Cell Counting Kit-8 and wound healing assays, respectively. Immunohistochemistry analyses of E2F3, Bcl-2, Bax and caspase-3 were performed in the NSCLC TMA (n=50). The assessment of TMA detected the increase of E2F3 protein expression level in the tumor tissues, as compared with that in the non-tumor tissues, which was also correlated with the increase in expression of Bcl-2 in tumors. Analysis of the clinical data from patients with NSCLC revealed that the overexpression of E2F3 was associated with early lymphatic spreading, and poor patient survival time. The OncomiR website was used to predict the E2F3 upstream microRNAs and determine their prognostic value in patients with NSCLC. The results from the present study revealed that E2F3 was overexpressed at both the transcriptional and translational levels in NSCLC tissues, as compared with that in non-tumor tissues. The overexpression of E2F3 was associated with the upregulation of the anti-apoptotic factor, Bcl-2, which may contribute to uncontrolled tumor growth. Thus, E2F3 was shown to have important oncogenic properties in the development of NSCLC, and it may become a potential biomarker for patients with NSCLC.

Safety and Tolerability of Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitors in Oncology

Tyrosine kinase inhibitors (TKIs) that target epidermal growth factor receptor (EGFR) have dramatically improved progression-free survival in non-small-cell lung cancer (NSCLC) patients who carry sensitizing EGFR-activating mutations and in patients with breast and pancreatic cancers. However, EGFR-TKIs are associated with significant and disabling undesirable effects that adversely impact on quality of life and compliance. These effects include dermatological reactions, diarrhoea, hepatotoxicity, stomatitis, interstitial lung disease and ocular toxicity. Each individual EGFR-TKI is also associated with additional adverse effect(s) that are not shared widely by the other members of its class. Often, these effects call for dose reduction, treatment discontinuation or pharmacotherapeutic intervention. Since dermatological effects result from on-target effects on wild-type EGFR, rash is often considered to be a biomarker of efficacy. A number of studies have reported better outcomes in patients with skin reactions compared with those without. This has led to a 'dosing-to-rash' strategy to optimize therapeutic outcomes. Although conceptually attractive, there is currently insufficient evidence-based support for this strategy. While skin reactions following EGFR-TKIs are believed to result from an effect on wild-type EGFR, their efficacy is related to effects on mutant variants of EGFR. It is noteworthy that newer EGFR-TKIs that spare wild-type EGFR are associated with fewer dermatological reactions. Furthermore, secondary mutations such as T790M in exon 20 often lead to development of resistance to the clinical activity and efficacy of first- and second-generation EGFR-TKIs. This has stimulated the search for later-generations of EGFR-TKIs with the ability to overcome this resistance and with greater target selectivity to spare wild-type EGFR in expectations of an improved safety profile. However, available data reviewed herein indicate that not only are these newer agents associated with the aforementioned adverse effects typical of earlier agents, but they are also susceptible to resistance due to tertiary mutations, most frequently C797S. At least three later-generation EGFR-TKIs, canertinib, naquotinib and rociletinib, have been discontinued from further development in NSCLC following concerns about their safety and risk/benefit.

Integrative analyses of genes associated with idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF), characterized by irreversible scarring and progressive destruction of the lung tissue, is one of the most common types of idiopathic interstitial pneumonia worldwide. However, there are no reliable candidates for curative therapies. Hence, elucidation of the mechanisms of IPF genesis and exploration of potential biomarkers and prognostic indicators are essential for accurate diagnosis and treatment of IPF. Recently, efficient microarray and bioinformatics analyses have promoted an understanding of the molecular mechanisms of disease occurrence and development, which is necessary to explore genetic alternations and identify potential diagnostic biomarkers. However, high false-positive rates results have been observed based on single microarray datasets. In the current study, we performed a comprehensive analysis of the differential expression, biological functions, and interactions of IPF-related genes. Three publicly available microarray datasets including 54 IPF samples and 34 normal samples were integrated by performing gene set enrichment analysis and analyzing differentially expressed genes (DEGs). Our results identified 350 DEGs genetically associated with IPF. Gene ontology analyses revealed that the changes in the modules were mostly enriched in the positive regulation of smooth muscle cell proliferation, positive regulation of inflammatory responses, and the extracellular space. Kyoto encyclopedia of genes and genomes enrichment analysis of DEGs revealed that IPF involves the TNF signaling pathway, NOD-like receptor signaling pathway, and PPAR signaling pathway. To identify key genes related to IPF in the protein-protein interaction network, 20 hub genes were screened out with highest scores. Our results provided a framework for developing new pathological molecular networks related to specific diseases in silico.