NSE, positively regulated by LINC00657-miR-93-5p axis, promotes small cell lung cancer (SCLC) invasion and epithelial-mesenchymal transition (EMT) process

Lü, Lin; Zha, Zhiqiang; Zhang, Peiling; Li, Dailing; Liu, Guolong

doi:10.7150/ijms.58415

Cited by 11 publications

(5 citation statements)

References 55 publications

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“…As shown in the results of the present study, serum tumor biomarkers, including CEA and NSE, were significant predictors in patients with PSCLC. In patients with an abnormal NSE level, a higher NSE level would indicate an increased likelihood of SCLC diagnosis, while the CEA level was higher in ADC than that in SCLC, which is consistent with previous studies ( 25 ). This study not only included serum tumor markers to explore the predictive markers but also considered the impact of other clinical factors such as smoking history, gender, and age on SCLC.…”

Section: Discussionsupporting

confidence: 92%

CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma

et al. 2023

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PurposeExploring a non-invasive method to accurately differentiate peripheral small cell lung cancer (PSCLC) and peripheral lung adenocarcinoma (PADC) could improve clinical decision-making and prognosis.MethodsThis retrospective study reviewed the clinicopathological and imaging data of lung cancer patients between October 2017 and March 2022. A total of 240 patients were enrolled in this study, including 80 cases diagnosed with PSCLC and 160 with PADC. All patients were randomized in a seven-to-three ratio into the training and validation datasets (170 vs. 70, respectively). The least absolute shrinkage and selection operator regression was employed to generate radiomics features and univariate analysis, followed by multivariate logistic regression to select significant clinical and radiographic factors to generate four models: clinical, radiomics, clinical-radiographic, and clinical-radiographic-radiomics (comprehensive). The Delong test was to compare areas under the receiver operating characteristic curves (AUCs) in the models.ResultsFive clinical-radiographic features and twenty-three selected radiomics features differed significantly in the identification of PSCLC and PADC. The clinical, radiomics, clinical-radiographic and comprehensive models demonstrated AUCs of 0.8960, 0.8356, 0.9396, and 0.9671 in the validation set, with the comprehensive model having better discernment than the clinical model (P=0.036), the radiomics model (P=0.006) and the clinical–radiographic model (P=0.049).ConclusionsThe proposed model combining clinical data, radiographic characteristics and radiomics features could accurately distinguish PSCLC from PADC, thus providing a potential non-invasive method to help clinicians improve treatment decisions.

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Section: Discussionsupporting

confidence: 92%

CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma

et al. 2023

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“…According to Zhang et al, the lncRNA NORAD promotes NSCLC progression by regulating the miR-26b-5p/COMMD8 axis, providing a potential novel target in NSCLC therapy [41]. LncRNA NORAD also promotes SCLC invasion and EMT by targeting the miR-93-5p/NSE axis [42]. Recently, Han et al suggested that lncRNA NORAD could be used as a core marker of COPD [43].…”

Section: Discussionmentioning

confidence: 99%

Systematic analysis of various RNA transcripts and construction of biological regulatory networks at the post-transcriptional level for chronic obstructive pulmonary disease

Li,

Zhang,

Dong

et al. 2023

J Transl Med

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Background Although chronic inflammation, oxidative stress, airway remodeling, and protease-antiprotease imbalance have been implicated in chronic obstructive pulmonary disease (COPD), the exact pathogenesis is still obscure. Gene transcription and post-transcriptional regulation have been taken into account as key regulators of COPD occurrence and development. Identifying the hub genes and constructing biological regulatory networks at the post-transcriptional level will help extend current knowledge on COPD pathogenesis and develop potential drugs. Methods All lung tissues from non-smokers (n = 6), smokers without COPD (smokers, n = 7), and smokers with COPD (COPD, n = 7) were collected to detect messenger RNA (mRNA), microRNA (miRNA), circular RNA (circRNA), and long non-coding RNA (lncRNA) expression and identify the hub genes. Biological regulatory networks were constructed at the post-transcriptional level, including the RNA-binding protein (RBP)-hub gene interaction network and the competitive endogenous RNA (ceRNA) network. In addition, we assessed the composition and abundance of immune cells in COPD lung tissue and predicted potential therapeutic drugs for COPD. Finally, the hub genes were confirmed at both the RNA and protein levels. Results Among the 20 participants, a total of 121169 mRNA transcripts, 1871 miRNA transcripts, 4244 circRNA transcripts, and 122130 lncRNA transcripts were detected. There were differences in the expression of 1561 mRNAs, 48 miRNAs, 33 circRNAs, and 545 lncRNAs between smokers and non-smokers, as well as 1289 mRNAs, 69 miRNAs, 32 circRNAs, and 433 lncRNAs between smokers and COPD patients. 18 hub genes were identified in COPD. TGF-β signaling and Wnt/β-catenin signaling may be involved in the development of COPD. Furthermore, the circRNA/lncRNA-miRNA-mRNA ceRNA networks and the RBP-hub gene interaction network were also constructed. Analysis of the immune cell infiltration level revealed that M2 macrophages and activated NK cells were increased in COPD lung tissues. Finally, we identified that the ITK inhibitor and oxybutynin chloride may be effective in treating COPD. Conclusions We identified several novel hub genes involved in COPD pathogenesis. TGF-β signaling and Wnt/β-catenin signaling were the most dysregulated pathways in COPD patients. Our study constructed post-transcriptional biological regulatory networks and predicted small-molecule drugs for the treatment of COPD, which enhanced the existing understanding of COPD pathogenesis and suggested an innovative direction for the therapeutic intervention of the disease.

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“…14 In recent years, many studies have shown that NSE is related to the diagnosis and staging of LC. 15 However, single tumor marker detection possesses lower sensitivity and specificity in the early diagnosis of LC, which has little application value in the early screening and diagnosis of LC, and the combined detection of multiple markers can make up for these defects. 16,17 So, it is important to find a better screening method to improve diagnostic rate of LC.…”

Section: Lc Have Recently Become Clearmentioning

confidence: 99%

“… 14 In recent years, many studies have shown that NSE is related to the diagnosis and staging of LC. 15 …”

Section: Introductionmentioning

confidence: 99%

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Efficacy of autoantibodies combined with tumor markers in the detection of lung cancer

Jing

Xie

et al. 2022

Clinical Laboratory Analysis

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Background The purpose of this study was to explore the detection value of seven autoantibodies (TAAbs): p53, PGP9.5, SOX2, GBU4‐5, MAGE A1, CAGE, and GAGE7 and three tumor markers: CYFRA21‐1, NSE, and SCCA in the diagnosis of lung cancer. Methods ELISA was used to detect the levels of the TAAbs, and chemiluminescence immunoassay was used to test the levels of the tumor markers. The diagnostic efficacy of the TAAbs combined with the tumor markers for lung cancer was evaluated by receiver operating characteristic (ROC) curves. Results The positive rate of the combined detection of seven TAAbs and three tumor markers in lung cancer (37.8%) was higher than that in other three groups. The positive rates of SOX2, GAGE7, MAGE A1, CAGE, CYFRA21‐1, and SCCA had differences among the four groups. Compared with the benign lung disease group, only GAGE7, CYFRA21‐1, and SCCA differed among the groups. The combined sensitivity of the TAAbs was 29.07% (AUC, 0.594), the combined sensitivity of all the markers was 37.76% (AUC, 0.660 [p < 0.05]), and Youden's index was 0.196. In the lung cancer group, CYFRA21‐1 had a significant difference in age and sex, and SOX2, MAGE A1, CYFRA21‐1, NSE, and SCCA were significantly different in pathological type and TNM. In contrast, p53 and GBU4‐5 showed no significant differences in age, sex, pathological type, and TNM. Conclusions The combined detection of seven TAAbs and three tumor markers could be useful in early diagnosis of lung cancer.

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NSE, positively regulated by LINC00657-miR-93-5p axis, promotes small cell lung cancer (SCLC) invasion and epithelial-mesenchymal transition (EMT) process

Cited by 11 publications

References 55 publications

CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma

CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma

Systematic analysis of various RNA transcripts and construction of biological regulatory networks at the post-transcriptional level for chronic obstructive pulmonary disease

Efficacy of autoantibodies combined with tumor markers in the detection of lung cancer

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