MiRNAs in Lung Adenocarcinoma: Role, Diagnosis, Prognosis, and Therapy.

Lung cancer has emerged as a significant public health challenge and remains the leading cause of cancer-related mortality worldwide. Among various types of lung malignancies, lung adenocarcinoma (LUAD) stands as the most prevalent form. MicroRNAs (miRNAs) play a crucial role in gene regulation, and their involvement in cancer has been extensively explored. While several reviews have been published on miRNAs and lung cancer, there remains a gap in the review regarding miRNAs specifically in LUAD. In this review, we not only highlight the potential diagnostic, prognostic, and therapeutic implications of miRNAs in LUAD, but also present an inclusive overview of the extensive research conducted on miRNAs in this particular context.

Apatinib preferentially inhibits PC9 gefitinib-resistant cancer cells by inducing cell cycle arrest and inhibiting VEGFR signaling pathway.

BACKGROUND: Lung cancer is one of the most common and deadly tumors around the world. Targeted therapy for patients with certain mutations, especially by use of tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR), has provided significant benefit to patients. However, gradually developed resistance to the therapy becomes a major challenge in clinical practice and an alternative to treat such patients is needed. Herein, we report that apatinib, a novel anti-angiogenic drug, effectively inhibits obtained gefitinib-resistant cancer cells but has no much effect on their parental sensitive cells. METHODS: Gefitinib-resistant lung cancer cell line (PC9GR) was established from its parental sensitive line (PC9) with a traditional EGFR mutation after long time exposure to gefitinib. Different concentrations of apatinib were used to treat PC9, PC9GR, and other two lung cancer cell lines for its anti-growth effects. RNA sequencing was performed on PC9, PC9GR, and both after apatinib treatment to detect differentially expressed genes and involved pathways. Protein expression of key cycle regulators p57, p27, CDK2, cyclin E2, and pRb was detected using Western blot. Xenograft mouse model was used to assess the anti-tumor activity of apatinib in vivo. RESULTS: The established PC9GR cells had over 250-fold increased resistance to gefitinib than its sensitive parental PC9 cells (IC50 5.311 ± 0.455 µM vs. 0.020 ± 0.003 µM). The PC9GR resistance cells obtained the well-known T790M mutation. Apatinib demonstrated much stronger ( ~ fivefold) growth inhibition on PC9GR cells than on PC9 and other two lung cancer cell lines, A549 and H460. This inhibition was mostly achieved through cell cycle arrest of PC9GR cells in G1 phase. RNA-seq revealed multiple changed pathways in PC9GR cells compared to the PC9 cells and after apatinib treatment the most changed pathways were cell cycle and DNA replication where most of gene activities were repressed. Consistently, protein expression of p57, CDK2, cyclin E2, and pRb was significantly impacted by apatinib in PC9GR cells. Oral intake of apatinib in mouse model significantly inhibited establishment and growth of PC9GR implanted tumors compared to PC9 established tumors. VEGFR2 phosphorylation in PC9GR tumors after apatinib treatment was significantly reduced along with micro-vessel formation. CONCLUSIONS: Apatinib demonstrated strong anti-proliferation and anti-growth effects on gefitinib resistant lung cancer cells but not its parental sensitive cells. The anti-tumor effect was mostly due to apatinib induced cell cycle arrest and VEGFR signaling pathway inhibition. These data suggested that apatinib may provide a benefit to patients with acquired resistance to EGFR-TKI treatment.

The relationship between single nucleotide polymorphisms and skin cancer susceptibility: A systematic review and network meta-analysis.

Background: Single nucleotide polymorphisms (SNPs) interfere with the function of certain genes and thus may influence the probability of skin cancer. The correlation between SNPs and skin cancer (SC) lacks statistical power, however. Therefore, the purpose of this study was to identify the gene polymorphisms involved in skin cancer susceptibility using network meta-analysis and to determine the relationship between SNPs and SC risk. Methods: PubMed, Embase, and Web of Science were searched for articles including "SNP" and different types of SC as keywords between January 2005 and May 2022. The Newcastle-Ottawa Scale was used to assess bias judgments. The odds ratio (ORs) and their 95% confidence intervals (CIs) were determined to estimate heterogeneity within and between studies. Meta-analysis and network meta-analysis were carried out to identify the SNPs associated with SC. The P-score of each SNP was compared to obtain the rank of probability. Subgroup analyses were performed by cancer type. Results: A total of 275 SNPs from 59 studies were included in the study. Two subgroup SNP networks using the allele model and dominant model were analyzed. The alternative alleles of rs2228570 (FokI) and rs13181 (ERCC2) were the first-ranking SNPs in both subgroups one and two of the allele model, respectively. The homozygous dominant genotype and heterozygous genotype of rs475007 in subgroup one and the homozygous recessive genotype of rs238406 in subgroup two were most likely to be associated with skin cancer based on the dominant model. Conclusions: According to the allele model, SNPs FokI rs2228570 and ERCC2 rs13181 and, according to the dominant model, SNPs MMP1 rs475007 and ERCC2 rs238406 are closely linked to SC risk.

Microarray data analysis to identify miRNA biomarkers and construct the lncRNA-miRNA-mRNA network in lung adenocarcinoma.

MicroRNAs (miRNAs), regulatory noncoding RNAs, are involved in gene regulation and may play a role in cancer development. The aim of this study was to identify miRNAs involved in lung adenocarcinoma (LUAD) using bioinformatics analysis. MiRNA (GSE135918), mRNA (GSE136043) and lncRNA (GSE130779) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed miRNAs (DEMis), mRNAs (DEMs), and lncRNA (DELs) in LUAD. We used DEMs for functional enrichment analysis. MiRNA expression quantification from The Cancer Genome Atlas (TCGA) was used to validate DEMis. LncBase Predicted v.2, Targetscan, and MiRBase were used to predict lncRNAs and mRNAs. The LUAD data in TCGA were used for overall survival (OS) analysis. We screened the downregulation of 8 DEMis and upregulation of 6 DEMis, and found that 70 signal pathways changed. We chose 3 relevant signaling pathways in lung cancer development, WNT, PI3K-Akt, and Notch, and scanned for mRNAs involved in them that are potential targets of these miRNAs. Then a lncRNA-miRNA-mRNA network was constructed. We also found 7 miRNAs that were associated with poor OS in LUAD. Low expression level of hsa-miR-30a was highly associated with poor OS in LUAD (P < .001) and the target genes of hsa-miR-30a-3p were abundant in the Wnt and AKT signaling pathways. In addition, our results reported for the first time that hsa-miR-3944 and hsa-miR-3652 were highly expressed in LUAD. And the high expression level of hsa-miR-3944 was associated with poor OS (P < .05). Hsa-miR-30a-3p may suppress the occurrence and progression of lung cancer through Wnt and AKT signaling pathways and become a good biomarker in LUAD. Hsa-miR-3944 and hsa-miR-3652 may serve as new biomarkers in LUAD.

Transcriptome Profiling of Acquired Gefitinib Resistant Lung Cancer Cells Reveals Dramatically Changed Transcription Programs and New Treatment Targets.

Background: Targeted therapy for lung cancer with epidermal growth factor receptor (EGFR) mutations with tyrosine kinase inhibitors (TKIs) represents one of the major breakthroughs in lung cancer management. However, gradually developed resistance to these drugs prevents sustained clinical benefits and calls for resistant mechanism research and identification of new therapeutic targets. Acquired T790M mutation accounts for the majority of resistance cases, yet transcriptome changes in these cells are less characterized, and it is not known if new treatment targets exist by available drugs. Methods: Transcriptome profiling was performed for lung cancer cell line PC9 and its resistant line PC9GR after long-term exposure to gefitinib through RNA sequencing. Differentially expressed genes and changed pathways were identified along with existing drugs targeting these upregulated genes. Using 144 lung cancer cell lines with both gene expression and drug response data from the cancer cell line encyclopedia (CCLE) and Cancer Therapeutics Response Portal (CTRP), we screened 549 drugs whose response was correlated with these upregulated genes in PC9GR cells, and top drugs were evaluated for their response in both PC9 and PC9GR cells. Results: In addition to the acquired T790M mutation, the resistant PC9GR cells had very different transcription programs from the sensitive PC9 cells. Multiple pathways were changed with the top ones including TNFA signaling, androgen/estrogen response, P53 pathway, MTORC1 signaling, hypoxia, and epithelial mesenchymal transition. Thirty-two upregulated genes had available drugs that can potentially be effective in treating the resistant cells. From the response profiles of CCLE, we found 17 drugs whose responses were associated with at least four of these upregulated genes. Among the four drugs evaluated (dasatinib, KPT-185, trametinib, and pluripotin), all except trametinib demonstrated strong inhibitory effects on the resistant PC9GR cells, among which KPT185 was the most potent. KPT-185 suppressed growth, caused apoptosis, and inhibited migration of the PC9GR cells at similar (or better) rates as the sensitive PC9 cells in a dose-dependent manner. Conclusions: Acquired TKI-resistant lung cancer cells (PC9GR) have dramatically changed transcription and pathway regulation, which expose new treatment targets. Existing drugs may be repurposed to treat those patients with developed resistance to TKIs.

Apatinib Reverses Paclitaxel-resistant Lung Cancer Cells (A549) Through Blocking the Function of ABCB1 Transporter.

BACKGROUND/AIM: Multidrug resistance (MDR) is often associated with overexpression of P-glycoprotein (ABCB1) in cancer cells. Apatinib is a novel Vascular endothelial growth factor receptor-TKI (VEGFR-TKI) which inhibits the function of ABCB1 in certain cancers. This study aimed to investigate the effect of apatinib on the reversal of paclitaxel (PTX) resistance in A549 lung cancer cells (A549/PTX) and related mechanisms. MATERIALS AND METHODS: A549/PTX cells were treated with apatinib alone, PTX alone, or PTX and apatinib. Cell viability was measured by the CCK8 assay. Apoptosis rate, cell-cycle arrest, Rhodamine efflux and reactive oxygen species (ROS) generation were determined by flow cytometry. The intracellular paclitaxel concentration was measured by ultra performance liquid chromatography (UPLC). Protein levels were analyzed by western blotting. RESULTS: A549/PTX cells had significant resistance to PTX and higher expression of ABCB1 compared to A549 cells. Apatinib increased the cytotoxicity of PTX, enhanced PTX-induced apoptosis and cycle arrest, and triggered intracellular ROS generation in A549/PTX cells. In addition, apatinib treatment increased the concentration of intracellular PTX in A549/PTX cells. Apatinib-PTX combination inhibited AKT and ERK pathways. CONCLUSION: Apatinib reverses the drug resistance to PTX in A549 PTX-resistant cells through inhibiting the function of ABCB1 and resumes anti-cancer effects.