Integrative Bioinformatics Analysis Reveals Potential Long Non-Coding RNA Biomarkers and Analysis of Function in Non-Smoking Females with Lung Cancer

Comprehensive landscape and future perspective of long noncoding RNAs in non-small cell lung cancer: it takes a village

Long noncoding RNAs (lncRNAs) are a distinct subtype of RNA that lack protein-coding capacity but exert significant influence on various cellular processes. In non-small cell lung cancer (NSCLC), dysregulated lncRNAs act as either oncogenes or tumor suppressors, contributing to tumorigenesis and tumor progression. LncRNAs directly modulate gene expression, act as competitive endogenous RNAs by interacting with microRNAs or proteins, and associate with RNA binding proteins. Moreover, lncRNAs can reshape the tumor immune microenvironment and influence cellular metabolism, cancer cell stemness, and angiogenesis by engaging various signaling pathways. Notably, lncRNAs have shown great potential as diagnostic or prognostic biomarkers in liquid biopsies and therapeutic strategies for NSCLC. This comprehensive review elucidates the significant roles and diverse mechanisms of lncRNAs in NSCLC. Furthermore, we provide insights into the clinical relevance, current research progress, limitations, innovative research approaches, and future perspectives for targeting lncRNAs in NSCLC. By summarizing the existing knowledge and advancements, we aim to enhance the understanding of the pivotal roles played by lncRNAs in NSCLC and stimulate further research in this field. Ultimately, unraveling the complex network of lncRNA-mediated regulatory mechanisms in NSCLC could potentially lead to the development of novel diagnostic tools and therapeutic strategies.

LncRNA STK4 antisense RNA 1 (STK4-AS1) promoted osteosarcoma by inhibiting p53 expression

BACKGROUND

LncRNA STK4 antisense RNA 1 (STK4-AS1) has been identified as a potential biomarker associated with multiple cancers. We proposed that STK4-AS1 plays a role in the proliferation of osteosarcoma by regulating the cell cycle.

METHODS

We compared the expression of STK4-AS1, p53, and p21 in osteosarcoma vs normal samples in clinical tissues and cell lines. We determined the effect of overexpression and knockdown of STK4-AS1 in p53 expressing osteosarcoma cells U2OS, p53 muted osteosarcoma cells MG63, and osteoblast cells hFOB on p53 and p21 expression and the cell viability. For U2OS and MG63, the cell cycle was analyzed and the expression of cyclin proteins was determined. We overexpressed p53 or p21 in STK4-AS1 overexpressed cells to explore the association of STK4-AS1 and p53 in U2OS.

RESULTS

The STK4-AS1 expression was higher and p53 and p21 expression were lower in osteosarcoma tissue and cells than in their non-cancer counterparts. The expression of STK4-AS1 was negatively correlated with the expression of p53 or p21. Knockdown of STK4-AS1 in U2OS decreased the cell viability, increased cells in the G0/G1 phase, decreased cells in the S and G2/M phase, decreased expression of cyclin A and B, increased p53 and p21, and had no effect on cyclin D and cyclin E, while overexpression of STK4-AS1 did the opposes. Overexpression of p53 or p21 recovered some changes caused by STK4-AS1 overexpression in U2OS. MG63 expressed no p53 and the expression of p21, cyclin A, and cyclin B, cell viability, and cell cycle were not affected by altered STK4-AS1 levels. In hFOB cells, the expression of p53 and p21 was decreased and the cell viability was increased when STK4-AS1 was overexpressed, but they were not affected when STK4-AS1 was knocked down.

CONCLUSION

LncRNA STK4-AS1 promoted the cell cycle of osteosarcoma cells by inhibiting p53 expression.

Linc00511 Knockdown Inhibited TGF-β1-Induced Epithelial-Mesenchymal Transition of Bronchial Epithelial Cells by Targeting miR-16-5p/Smad3

BACKGROUND

Airway remodeling in patients with asthma was correlated with induced epithelial-mesenchymal transition (EMT) of bronchial epithelial cells.

OBJECTIVE

This study examined the mechanism of Linc00511 on induced EMT of bronchial epithelial cells after transforming growth factor-β1 (TGF-β1) induction.

METHODS

The human bronchial epithelial cell 16HBE was treated with 10 ng/mL TGF-β1 for 12 h, 24 h, or 48 h to induce EMT. Cell proliferation and migration rate were detected using CCK8 and wound healing assays, respectively. The expression of key markers of EMT (E-cadherin, N-cadherin, Small mothers against decapentaplegic family member 3 [Smad3], and slug) was tested by Western blot.

RESULTS

We found that Linc00511 was time dependently increased in TGF-β-treated 16HBE cells. Silencing Linc00511 reduced 16HBE cell proliferation, migration, and EMT progress. In addition, the dual-luciferase reporter assay showed Linc00511 was a molecular sponge for miR-16-5p. MiR-16-5p decreased the expression of Smad3 by targeting its 3'-untranslated region (3'UTR). After TGF-β1 exposure, miR-16-5p silencing counteracted the decreases of 16HBE cell proliferation, migration, and EMT induced by Linc00511 knockdown. And Smad3 overexpression also reversed the inhibitory effect of Linc00511 knockdown on proliferation, migration, and EMT progression in TGF-β1-induced human bronchial epithelial cells.

CONCLUSION

Linc00511 may be a valuable biomarker for asthma therapy.

Identification of genes and pathways associated with sex in Non-smoking lung cancer population

INTRODUCTION

Women represent a higher proportion than men among those with lung cancer in nonsmokers compared to smokers. The reason for this abnormally higher proportion is not yet clear, but sex differences suggest there may be a genetic component at play.

MATERIALS AND METHODS

The gene expression determined by Illumina RNA Sequencing and the relevant clinical information of lung cancer patients was download from TCGA. The differentially expressed genes (DEGs) were screened between males and females in both nonsmoking and smoking populations. The top 50 validated DEGs are represented with heatmaps. Based on the DEGs, GO functional and KEGG pathway enrichment analyses were performed. PPI networks were constructed to further illustrate the direct and indirect associations among the DEGs. Survival analysis was performed to explore whether these genes can affect lung cancer patient prognosis.

RESULTS

In non-smoking patients, there were significantly more females than males (female 73.0% vs male 27.0%, P < 0.001). Such difference was not found in smoking patients (female 50.7% vs male 49.3%, P = 0.770). A total of 898 DEGs were identified in the non-smoking population, while a total of 992 DEGs were identified in the smoking population. Of these, only 122 genes were shared by both populations. Some pathways were enriched specifical in non-smoking population, such as cAMP signaling pathway and ovarian steroidogenesis. Several proteins related to estrogen function and MAPK/PI3K signaling, such as KRT16, ERBB4 and NTF4, showed differential effects on the lung adenocarcinoma progression in non-smoking males or females.

CONCLUSIONS

Some genetic differences between male and female in non-smoking lung adenocarcinoma patients have been identified. Potentially, ER signaling and MAPK/PI3K signaling partially participated in this discrepancy.

The effect of chromosome abnormalities on expression of SnoRNA in radioresistant and radiosensitive cell lines after irradiation

In this paper, we have studied the role of chromosomal abnormalities in the expression of small nucleolar RNAs (snoRNAs) of radioresistant (K562) and radiosensitive (HL-60) leukemia cell line. Cells were exposed to an X-ray dose of 4 Gy. SnoRNA expression was investigated using NGS sequencing. The distribution of expressed snoRNAs on chromosomes has been found to be different for two cell lines. The most significant differences in the expression of snoRNAs were found in the K562 cell line based on the analysis of the dynamics of log2fc values. The type of clustering, the number and type of snoRNAs slightly differed in the chromosomes with trisomy and monosomy and had a pronounced difference in pairs with marker chromosomes in both cell lines. In this study, we have demonstrated that chromosomal abnormalities alter the expression of snoRNA after irradiation. Trisomies and monosomies do not have such a noticeable effect on the expression of snoRNAs as the presence of marker chromosomes.

Gender specific eRNA TBX5-AS1 as the immunological biomarker for male patients with lung squamous cell carcinoma in pan-cancer screening

As an innate feature of human beings, gender differences have an influence on various biological phenotypes, yet it does not attract enough attention in genomics studies. The prognosis of multiple carcinomas usually exhibits a favorable ending for female patients, but the neglect of gender differences can cause serious bias in survival analysis. Enhancer RNAs (eRNAs) are mostly downstream of androgens or estrogen. The present study was aimed to screen eRNAs in patients with non-small-cell lung cancer. The findings revealed that eRNA TBX5-AS1 was expressed differently between female and male patients. Meanwhile, its prognostic significance appeared only in male patients with squamous cell carcinoma (SCC) type. The Gene Set Enrichment Analysis proved that the expression level of TBX5-AS1 increased following the activation of the androgen signaling pathway. In pan-cancer analysis, the prognostic prediction based on gender grouping obtained more meaningful results, and the synergy between TBX5-AS1 and its homologous target was more consistent. Furthermore, immunity variations between sexes prompted us to explore the role that TBX5-AS1 played in tumor microenvironment and immunotherapy. The robust evidence proved that male patients with high expression of TBX5-AS1 possessed a malignant immune microenvironment and urgently needed immune checkpoint inhibitor treatment. In conclusion, TBX5-AS1 may be one of the strongest candidates to predict prognosis for male patients with SCC and provide a reference for immunotherapy.

Identification of Significant Genes in Lung Cancer of Nonsmoking Women via Bioinformatics Analysis

Background

The aim of this study was to identify potential key genes, proteins, and associated interaction networks for the development of lung cancer in nonsmoking women through a bioinformatics approach.

Methods

We used the GSE19804 dataset, which includes 60 lung cancer and corresponding paracancerous tissue samples from nonsmoking women, to perform the work. The GSE19804 microarray was downloaded from the GEO database and differentially expressed genes were identified using the limma package analysis in R software, with the screening criteria of p value < 0.01 and ∣log₂ fold change (FC) | >2.

Results

A total of 169 DEGs including 130 upregulated genes and 39 downregulated were selected. Gene Ontology and KEGG pathway analysis were performed using the DAVID website, and protein-protein interaction (PPI) networks were constructed and the hub gene module was screened through STING and Cytoscape.

Conclusions

We obtained five key genes such as GREM1, MMP11, SPP1, FOSB, and IL33 which were strongly associated with lung cancer in nonsmoking women, which improved understanding and could serve as new therapeutic targets, but their functionality needs further experimental verification.

Long noncoding RNA LINC00968 inhibits proliferation, migration and invasion of lung adenocarcinoma through targeting miR-22-5p/CDC14A axis

Lung adenocarcinoma (LUAD) is a high aggressive human cancer which usually diagnosed at advanced stages. Accumulating evidences indicate that long noncoding RNAs (lncRNAs) are crucial participants in LUAD progression. In the present study, we found that lncRNA LINC00968 was significantly down-regulated in LUAD tissues and cell lines. LINC00968 level was positively correlated to survival rate, and negatively correlated to tumor node metastasis (TNM) stage, tumor size and lymph node metastasis of LUAD patients. We over-expressed LINC00968 in LUAD cells using lentivirus, inhibited proliferation and cell cycle arrest at G1 phase were detected. LINC00968 over-expression also suppressed migration, invasion and epithelial mesenchymal transition. We further validated that LINC00968 localized in cytoplasm and acted as an upstream regulator of microRNA miR-22-5p, which was up-regulated in LUAD tissues and cell lines. Besides, elevated miR-22-5p expression abolished the effect of LINC00968 over-expression on LUAD progression including in vivo tumor growth. In addition, we first validated that cell division cycle 14A (CDC14A), which was down-regulated in LUAD tissues, was a downstream target of miR-22-5p. We over-expressed CDC14A in LUAD cells and miR-22-5p induced LUAD progression was partially reversed. In conclusion, our study demonstrated that LINC00968 inhibited proliferation, migration and invasion of LUAD by sponging miR-22-5p and further restoring CDC14A. This novel regulatory axis might provide us with promising diagnostic and therapeutic target in LUAD treatment.

Low miR-1231 expression predicts poor prognosis in non-small-cell lung cancer and accelerates cell proliferation, migration and invasion

Aim: miRNAs have been found to be involved in the tumor progression. This study aimed to assess the prognostic significance and biological function of miRNA-1231 (miR-1231) in non-small-cell lung cancer (NSCLC). Materials & methods: Expression of miR-1231 was measured by using quantitative real-time PCR. The prognosis value of miR-1231 was evaluated by Kaplan-Meier survival curves and Cox regression analysis. The biological function of miR-1231 was further studied. Results: Expression of miR-1231 in NSCLC patients and NSCLC cell lines were decreased. MiR-1231 was an independent prognostic biomarker. Overexpression of miR-1231 inhibited NSCLC cell proliferation, migration and invasion. Conclusion: Downregulated expression of miR-1231 serves as a prognostic biomarker of NSCLC and may be a potential therapeutic target.

Integrated transcriptomics and epigenomics reveal chamber-specific and species-specific characteristics of human and mouse hearts

DNA methylation, chromatin accessibility, and gene expression represent different levels information in biological process, but a comprehensive multiomics analysis of the mammalian heart is lacking. Here, we applied nucleosome occupancy and methylome sequencing, which detected DNA methylation and chromatin accessibility simultaneously, as well as RNA-seq, for multiomics analysis of the 4 chambers of adult and fetal human hearts, and adult mouse hearts. Our results showed conserved region-specific patterns in the mammalian heart at transcriptome and DNA methylation level. Adult and fetal human hearts showed distinct features in DNA methylome, chromatin accessibility, and transcriptome. Novel long noncoding RNAs were identified in the human heart, and the gene expression profiles of major cardiovascular diseases associated genes were displayed. Furthermore, cross-species comparisons revealed human-specific and mouse-specific differentially expressed genes between the atria and ventricles. We also reported the relationship among multiomics and found there was a bell-shaped relationship between gene-body methylation and expression in the human heart. In general, our study provided comprehensive spatiotemporal and evolutionary insights into the regulation of gene expression in the heart.

Multi-omic analyses of the four chambers of the human and mouse heart, including transcriptome, DNA methylation and chromatin accessibility, reveals characteristic patterns of gene regulation at the level of heart regions.

Advances in Understanding the LncRNA-Mediated Regulation of the Hippo Pathway in Cancer

Long noncoding RNAs (lncRNAs) are a class of RNA molecules that are longer than 200 nucleotides and cannot encode proteins. Over the past decade, lncRNAs have been defined as regulatory elements of multiple biological processes, and their aberrant expression contributes to the development and progression of various malignancies. Recent studies have shown that lncRNAs are involved in key cancer-related signaling pathways, including the Hippo signaling pathway, which plays a prominent role in controlling organ size and tissue homeostasis by regulating cell proliferation, apoptosis, and differentiation. However, dysregulation of this pathway is associated with pathological conditions, especially cancer. Accumulating evidence has revealed that lncRNAs can modulate the Hippo signaling pathway in cancer. In this review, we elaborate on the role of the Hippo signaling pathway and the advances in the understanding of its lncRNA-mediated regulation in cancer. This review provides additional insight into carcinogenesis and will be of great clinical value for developing novel early detection and treatment strategies for this deadly disease.

Cost-Effectiveness Analysis of Nivolumab Plus Ipilimumab vs. Chemotherapy as First-Line Therapy in Advanced Non-Small Cell Lung Cancer

Background: The CheckMate 227 trial has indicated that nivolumab plus ipilimumab compared with chemotherapy significantly increases long-term survival in the first-line setting of advanced non-small-cell lung cancer (NSCLC).

Methods: A Markov model was built to estimate the cost and effectiveness of nivolumab plus ipilimumab vs. chemotherapy as the first-line therapy in patients with advanced NSCLC based on outcomes data from the CheckMate 227 trial. We calculated the cost and health outcomes at a willingness-to-pay (WTP) threshold of $150,000 per quality adjusted life year (QALY) in populations with different programmed death ligand 1 (PD-L1) expression levels (≥50, ≥1, and <1%) or a high tumor mutational burden (TMB) (≥10 mutations per megabase). Sensitivity analysis were used to test the model stability.

Results: The outcomes showed that the incremental costs and QALYs by using nivolumab plus ipilimumab were $124180.76 and 1.16, $70951.42 and 0.53, $144093.63 and 0.83 for the advanced NSCLC patients with a PD-L1 expression ≥50%, ≥1%, and <1%, which led to an incremental cost-effective ratio (ICER) of $107403.72, $133732.20, and $172589.15 per QALY, respectively. For patients with a high TMB, nivolumab plus ipilimumab contributed an extra 2.04 QALYs at a cost of $69182.50 per QALY.

Conclusion: Nivolumab plus ipilimumab as first-line therapy makes a better cost-effective strategy than chemotherapy in advanced NSCLC patients with PD-L1 expression levels ≥50% and ≥1% or a high TMB, at a willingness-to-pay threshold of $150,000 per QALY, but not in the patients with a PD-L1 expression <1%.

[A Literature Review on the Role of TBX5 in Expression and Progression of Lung Cancer: Current Perspectives]

T-box转录因子（T-box transcription factor gene, TBX）基因涉及器官的发生，TBX5在人的正常心脏和肺组织中表达水平最高。TBX5的缺乏可能导致胸廓发育畸形和膈肌发育异常，其异位表达和过表达会诱导细胞凋亡和抑制细胞生长。既往研究发现了TBX5在食管腺癌、胃癌、结肠癌和乳腺癌的发生和发展中的潜在作用。我们对TBX2亚家族的基因表达和预后之间的关系进行了综述，同时探究TBX5在调控肺癌发生发展机制中的研究进展。虽然TBX5和肺癌发生之间的关系尚不明确，不过TBX5可以显著抑制人体内肿瘤生长，其表达水平和肺癌的进展呈现负相关。由此，TBX5的基因表达水平和甲基化程度是潜在的表证肺癌增殖和转移的生物标志物，具有作为肺癌治疗靶点的潜力。

LncRNA TBX5-AS1 Regulates the Tumor Progression Through the PI3K/AKT Pathway in Non-Small Cell Lung Cancer

Purpose

Long non-coding RNAs (lncRNAs) have been reported to play important roles in tumor biology. In this study, we aimed to investigate the effects of T-box transcription factor 5 antisense RNA 1 (TBX5-AS1) on aggressive phenotypes of non-small cell lung cancer (NSCLC) cells and explore its regulatory pathway.

Methods

The expression of TBX5-AS1 in tissues, plasma, and cells was determined by qRT-PCR. Cell viability, proliferation, migration, invasion, and apoptosis were assessed using MTT, colony formation, wound-healing, Transwell, and flow cytometry assay, respectively. Western blot analysis was performed to measure the expression of apoptosis-related proteins. Besides, transfected cells were exposed to PI3K activator (740Y-P) to verify the regulatory pathway.

Results

TBX5-AS1 expression was down-regulated in NSCLC tissues, plasma, and cells, and associated with lymph node metastasis and histological grade. Overexpression of TBX5-AS1 inhibited cell viability, colony formation, migration, and invasion, while it promoted apoptosis. Conversely, knockdown of TBX5-AS1 showed the completely opposite results. Additionally, western blot showed that the phosphorylation of PI3K and AKT was stimulated by TBX5-AS1 knockdown and suppressed by TBX5-AS1 overexpression. The addition of 740Y-P in transfected cells reversed the TBX5-AS1-induced inhibition of PI3K and AKT phosphorylation and effects on aggressive phenotypes of NSCLC cells.

Conclusion

The study confirmed the down-regulation of TBX5-AS1 in patients with NSCLC and its association with the progression. We innovatively proposed a possible model of TBX5-AS1-mediated gene regulation in NSCLC progression that TBX5-AS1 inhibited the aggressive phenotypes of NSCLC cells through inactivating the PI3K/AKT pathway. This finding provided a novel insight into NSCLC pathogenesis.

Identification of lncRNA biomarkers for lung cancer through integrative cross-platform data analyses

This study was designed to identify lncRNA biomarker candidates using lung cancer data from RNA-Seq and microarray platforms separately.

Lung cancer datasets were obtained from the Gene Expression Omnibus (GEO, n = 287) and The Cancer Genome Atlas (TCGA, n = 216) repositories, only common lncRNAs were used. Differentially expressed (DE) lncRNAs in tumors with respect to normal were selected from the Affymetrix and TCGA datasets. A training model consisting of the top 20 DE Affymetrix lncRNAs was used for validation in the TCGA and Agilent datasets. A second similar training model was generated using the TCGA dataset.

First, a model using the top 20 DE lncRNAs from Affymetrix for training and validated using TCGA and Agilent, achieved high prediction accuracy for both training (98.5% AUC for Affymetrix) and validation (99.2% AUC for TCGA and 92.8% AUC for Agilent). A similar model using the top 20 DE lncRNAs from TCGA for training and validated using Affymetrix and Agilent, also achieved high prediction accuracy for both training (97.7% AUC for TCGA) and validation (96.5% AUC for Affymetrix and 80.9% AUC for Agilent). Eight lncRNAs were found to be overlapped from these two lists.

Prediction of Specific Subtypes and Common Markers of Non-Small Cell Lung Cancer Based on Competing Endogenous RNA Network

Background

There are various pathological types of lung cancer, including squamous cell carcinoma and adenocarcinoma. Although both of them are lung cancers, there are significant differences in diagnosis, pathogenesis, location, imaging, metastasis, and treatment. According to the competing endogenous RNA (ceRNA) theory, long non-coding RNAs (lncRNAs) compete with encoding protein genes (mRNAs) to connect with miRNAs, thus affecting the level of mRNA.

Material/Methods

First, using the t test, we identified mRNAs and lncRNAs that have different expressions (fold change >2, P<0.01) in normal samples and in tumor samples. We calculated the significance of the shared miRNAs for mRNAs and lncRNAs by hypergeometric test (P<0.01). Further, mRNA and lncRNA pairs with co-expression relationships in cancer samples were used to establish ceRNA networks. Then, the random walk algorithm was used to optimize the specific ceRNA networks and identify potential prognostic markers of survival. Finally, we built a common ceRNA network to find markers of non-small-cell lung cancer.

Results

We identified some potential key markers, such as PVT1, LINC00472, CDKN2A, and FAM83B, in LUSC and HOXA11-AS, HNF1A-AS1, LINC00511, and HOTAIR in LUAD by analyzing the ceRNA networks. Moreover, a number of common ceRNA pairs, such as CDC25C/CDK1/RRM2-LINC00355, have been found, and they are also significant markers for tumor survival and prognosis.

Conclusions

In summary, the present study provides a comparative analysis in 2 kinds of lung cancer ceRNA networks. Some specific and common markers we predicted that may be of great importance for clinical diagnosis and treatment.

Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma

BACKGROUND

Recent genome-wide association studies (GWASs) have suggested several susceptibility loci of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) by statistical analysis at individual single-nucleotide polymorphisms (SNPs). However, these loci only explain a small fraction of HBV-related HCC heritability. In the present study, we aimed to identify additional susceptibility loci of HBV-related HCC using advanced knowledge-based analysis.

METHODS

We performed knowledge-based analysis (including gene- and gene-set-based association tests) on variant-level association p-values from two existing GWASs of HBV-related HCC. Five different types of gene-sets were collected for the association analysis. A number of SNPs within the gene prioritized by the knowledge-based association tests were selected to replicate genetic associations in an independent sample of 965 cases and 923 controls.

RESULTS

The gene-based association analysis detected four genes significantly or suggestively associated with HBV-related HCC risk: SLC39A8, GOLGA8M, SMIM31, and WHAMMP2. The gene-set-based association analysis prioritized two promising gene sets for HCC, cell cycle G1/S transition and NOTCH1 intracellular domain regulates transcription. Within the gene sets, three promising candidate genes (CDC45, NCOR1 and KAT2A) were further prioritized for HCC. Among genes of liver-specific expression, multiple genes previously implicated in HCC were also highlighted. However, probably due to small sample size, none of the genes prioritized by the knowledge-based association analyses were successfully replicated by variant-level association test in the independent sample.

CONCLUSIONS

This comprehensive knowledge-based association mining study suggested several promising genes and gene-sets associated with HBV-related HCC risks, which would facilitate follow-up functional studies on the pathogenic mechanism of HCC.

Cost-Effectiveness Analysis of Atezolizumab Plus Chemotherapy in the First-Line Treatment of Metastatic Non-Squamous Non-Small Cell Lung Cancer

INTRODUCTION

The purpose of this study was to estimate the cost-effectiveness of atezolizumab plus chemotherapy in patients with metastatic non-squamous non-small cell lung cancer (NSCLC) from the United States (US) payers' perspective in the first-line treatment.

METHODS

A mathematical Markov model was developed to estimate cost and effectiveness of atezolizumab combination therapy versus carboplatin plus nab-paclitaxel alone in the first-line therapy of metastatic non-squamous NSCLC from the data of IMpower130. Costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) were analyzed, and model robustness was assessed by sensitivity analysis. Additional subgroup analyses were performed as well.

RESULTS

Compared to chemotherapy, treatment with atezolizumab plus chemotherapy yields an increase of 0.16 QALYs with an increase in cost of $109,809.13, resulting in an ICER of $670,309.66 per QALY. The most influential factor in this model was the cost of atezolizumab. Probabilistic sensitivity analysis showed that there was 0% probability that atezolizumab plus chemotherapy was cost-effective at willingness-to-pay (WTP) values of $150,000 per QALY. The results of subgroup analyses showed that the ICER remained greater than $150,000/QALY across the all patient subgroups.

CONCLUSION

First-line treatment with atezolizumab in combination with carboplatin plus nab-paclitaxel is not a cost-effective option in patients with metastatic non-squamous NSCLC.

LncRNA LINC01140 Inhibits Glioma Cell Migration and Invasion via Modulation of miR-199a-3p/ZHX1 Axis

PURPOSE

Glioma is an aggressive tumor from the nervous system, which causes more than 70% of primary malignant brain tumors. Considering its severe malignancy, there is an urgent need to investigate more practical markers to understand the pathogenesis of glioma, and potential treatment methods for glioma patients. In the paper, we are focused on examining the roles of LINC01140, miR-199a-3p, and ZHX1 in the progression of gliomas, as well as their inner associations and modulation mechanisms.

METHODS

qRT-PCR was employed to examine the expression levels of LINC01140 and miR-199a-3p. We measured the expressions of ZHX1 via qRT-PCR and Western blotting. CCK8 assays, migration assays, and invasion assays were carried out to determine the cell viabilities and abilities of migration and invasion. We also conducted in vivo tumor growth experiments to investigate the roles of LINC01140 in glioma developments.

RESULTS

The expressions of LINC01140 were promoted in glioma. Silencing LINC01140 could inhibit glioma cell viabilities, migration, and invasion. In our experiments, miR-199a-3p was inhibited in glioma. LINC01140 negatively regulated the expressions of miR-199a-3p in glioma. MiR-199a-3p could target ZHX1 to inhibit its expression in glioma cells.

CONCLUSION

LINC01140 could promote glioma developments by modulating the miR-199a-3p/ZHX1 axis.

A novel prognostic nomogram based on 5 long non-coding RNAs in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common and invasive histological subtype of all kidney malignancies, with high levels of incidence and mortality. In the present study, long non-coding (lnc)RNA expression profiles of patients with ccRCC from The Cancer Genome Atlas database were comprehensively analyzed to identify differentially expressed lncRNAs (DElncRNAs). The patients with ccRCC were then divided into training and validation cohorts. Univariate and LASSO regression analyses were performed to select the most significant survival-associated candidate DElncRNAs in the training cohort. Multivariate Cox regression analysis was then performed to develop a risk score formula and a prognostic nomogram for predicting 3- and 5-year overall survival (OS). The accuracies of the nomogram predictions were evaluated by determining the area under the receiver operating characteristic curve (AUC) and a calibration plot. Finally, functional enrichment analysis and protein-protein interaction network prediction were implemented to predict the functions and molecular mechanisms of the candidate DElncRNAs in ccRCC. A total of 1,553 DElncRNAs were identified, and 5 candidate DElncRNAs (AC026992.2, AC245041.2, LINC00524, LINC01956 and LINC02080) were included in the nomogram. The AUC values for 3- and 5-year overall survival in the training cohort were 0.768 and 0.814, respectively, which were increased compared with that based on the clinical index (0.760 and 0.694, respectively). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the 521 mRNAs highly associated with 5 DElncRNAs were primarily involved in 17 terms and 25 pathways, respectively. Based on the 5 DElncRNAs, a novel and convenient prognostic nomogram for predicting 3- and 5-year OS for patients with ccRCC was developed. The results of the present study may be conducive to the development of a precise predictive tool for the prognosis of ccRCC and may provide information regarding the molecular mechanisms of ccRCC. However, additional experimental in vitro and in vivo studies investigating lncRNAs may be required.

Survival analysis and functional annotation of long non-coding RNAs in lung adenocarcinoma

Long non-coding RNAs (lncRNAs) are a subclass of non-protein coding transcripts that are involved in several regulatory processes and are considered as potential biomarkers for almost all cancer types. This study aims to investigate the prognostic value of lncRNAs for lung adenocarcinoma (LUAD), the most prevalent subtype of lung cancer. To this end, the processed data of The Cancer Genome Atlas LUAD were retrieved from GEPIA and circlncRNAnet databases, matched with each other and integrated with the analysis results of a non-small cell lung cancer plasma RNA-Seq study. Then, the data were filtered in order to separate the differentially expressed lncRNAs that have a prognostic value for LUAD. Finally, the selected lncRNAs were functionally annotated using a bioinformatic and systems biology approach. Accordingly, we identified 19 lncRNAs as the novel LUAD prognostic lncRNAs. Also, based on our results, all 19 lncRNAs might be involved in lung cancer-related biological processes. Overall, we suggested several novel biomarkers and drug targets which could help early diagnosis, prognosis and treatment of LUAD patients.

Differentially Expressed Gene Screening, Biological Function Enrichment, and Correlation with Prognosis in Non-Small Cell Lung Cancer

Background

The aim of this study was to explore the differently expressed genes and pathways in non-small cell lung cancer (NSCLC) and their correlation with the prognosis.

Material/Methods

Gene expression data series of GSE19804, GSE101929, and GSE33532 were downloaded from the Gene Expression Ominibus (GEO) database. The overlaping differently expressed genes (DEGs) were identified form the above 3 data series. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEEG) were used to analyze the biological functions and signal pathways of DEGs. The protein–protein interaction (PPI) was analyzed thorough Search Tool for the Retrieval of Interacting Gens (STRING). The relationship between the expression of hub genes and the prognosis of patients was analyzed by Kaplan-Meier Plotter online software.

Results

Twenty-nine DEGs were identified, with 22 upregulated genes and 7 downregulated genes. The enriched biological processes were mainly related to diet-induced thermogenesis and actin filament binding. The KEGG pathways were enriched in calcium signaling, regulation of lipolysis in adipocytes, and PPAR signaling. Two downregulated genes (MMP1 and SPP1) were identified as hub genes by Cytohubba. Twenty-two dysregulated genes were correlated with patient prognosis.

Conclusions

Differentially expressed genes are common in NSCLC patients and can be used as biomarkers for patient prognosis.

Identification of Key Genes and Pathways in Female Lung Cancer Patients Who Never Smoked by a Bioinformatics Analysis

Smoking is considered the major risk factor for lung cancer, but only a small portion of female lung adenocarcinoma patients are associated with smoking. Thus, identifying crucial genes and pathways related to nonsmoking female lung cancer patients is of great importance. Gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. The R software packages were applied to screen the differentially expressed genes (DEGs). GO term enrichment and KEGG pathway analyses were carried out using DAVID tools. The protein-protein interaction (PPI) network was constructed by Cytoscape software. In total, 487 downregulated and 199 upregulated DEGs were identified. The down-regulated DEGs were mainly enriched for behavior and response to wounding, and the upregulated DEGs were significantly enriched for multicellular organismal metabolic process and cell division. The KEGG pathway analysis revealed that the downregulated DEGs were significantly enriched for cell adhesion molecules and neuroactive ligand-receptor interaction, while the upregulated DEGs were mainly enriched for cell cycle and the p53 signaling pathway. The top 10 hub genes and top 3 gene interaction modules were selected from the PPI network. Of the ten hub genes, a high expression of five genes was related to a poor OS in female lung cancer patients who never smoked, including IL6, CXCR2, FPR2, PPBP and HBA1. However, a low expression of GNG11, LRRK2, CDH5, CAV1 and SELE was associated with a worse OS for the female lung cancer patients who never smoked. In conclusion, our study provides novel insight for a better understanding of the pathogenesis of nonsmoking female lung cancer, and these identified DEGs may serve as biomarkers for diagnostics and treatment.