scholarly journals Identification and Validation of Immune-Related Gene Signature for Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Ran Jia ◽  
Zhilin Sui ◽  
Hongdian Zhang ◽  
Zhentao Yu

Lung cancer is a serious malignancy, and lung adenocarcinoma (LUAD) is the most common pathological subtype. Immune-related factors play an important role in lymph node metastasis. In this study, we obtained gene expression profile data for LUAD and normal tissues from the TCGA database and analyzed their immune-related genes (IRGs), and observed that 459 IRGs were differentially expressed. Further analysis of the correlation between differentially expressed IRGs and lymph node metastasis revealed 18 lymph node metastasis-associated IRGs. In addition, we analyzed the mutations status, function and pathway enrichment of these IRGs, and regulatory networks established through TF genes. We then identified eight IRGs (IKBKB, LTBR, MIF, PPARD, PPIA, PSME3, S100A6, SEMA4B) as the best predictors by LASSO Logistic analysis and used these IRGs to construct a model to predict lymph node metastasis in patients with LUAD (AUC 0.75; 95% CI: 0.7064–0.7978), and survival analysis showed that the risk score independently affected patient survival. We validated the predictive effect of risk scores on lymph node metastasis and survival using the GEO database as a validation cohort and the results showed good agreement. In addition, the risk score was highly correlated with infiltration of immune cells (mast cells activated, macrophages M2, macrophages M0 and B cells naïve), immune and stromal scores, and immune checkpoint genes (LTBR, CD40LG, EDA2R, and TNFRSF19). We identified key IRGs associated with lymph node metastasis in LUAD and constructed a reliable risk score model, which may provide valuable biomarkers for LUAD patients and further reveal the mechanism of its occurrence.

2017 ◽  
Vol 26 (1) ◽  
pp. 4-11 ◽  
Author(s):  
Wei Zhao ◽  
Hui Wang ◽  
Jun Xie ◽  
Bo Tian

Background. The aim of this study was to assess the prognostic significance of the newly proposed 2015 World Health Organization (WHO) lung adenocarcinoma classification for patients undergoing resection for small (≤1 cm) lung adenocarcinoma. We also investigated whether lobectomy offers prognostic advantage over limited resection for this category of tumors. Methods. A retrospective study of resected pulmonary adenocarcinomas (n = 83) in sizes 1 cm or less was carried out in which comprehensive histologic subtyping was assessed according to the 2015 WHO classification on all consecutive patients who underwent lobectomy or limited resection between 1998 and 2012. Correlation between clinicopathologic parameters and the difference in recurrence between lobectomy and limited resection group was evaluated. Results. Our data show that the proposed 2015 WHO classification identifies histological subsets of small lung adenocarcinomas with significant differences in prognosis. No recurrence was noted for patients with adenocarcinoma in situ and minimally invasive adenocarcinoma. Invasive adenocarcinomas displayed high heterogeneity and the presence of micropapillary component of 5% or greater in adenocarcinomas was significantly related to lymph node involvement and recurrence ( P < .001). Stage IA patients who underwent limited resection had a higher risk of recurrence than did those treated by lobectomy ( P < .05). Conclusions. Application of the 2015 WHO classification identifies patients with adenocarcinoma in situ and minimally invasive adenocarcinoma had excellent prognosis. Micropapillary pattern was associated with high risk of lymph node metastasis and recurrence.


2016 ◽  
Vol 242 (7) ◽  
pp. 709-717 ◽  
Author(s):  
Li Yan ◽  
Demin Jiao ◽  
Huizhen Hu ◽  
Jian Wang ◽  
Xiali Tang ◽  
...  

This study aimed to screen lymphatic metastasis-related microRNAs (miRNAs) in lung adenocarcinoma and explore their underlying mechanisms using bioinformatics. The miRNA expression in primary lung adenocarcinoma, matched adjacent non-tumorigenic and lymph node metastasis tissues of patients were profiled via microarray. The screened metastasis-related miRNAs were then validated using quantitative real-time PCR in a second cohort of lung adenocarcinoma patients with lymphatic metastasis. Significance was determined using a paired t-test. Target genes of the metastasis-related miRNAs were predicted using TargetScan, and transcription factors (TFs) were predicted based on the TRANSFAC and ENCODE databases. Furthermore, the related long non-coding RNAs (lncRNAs) were screened with starBase v2.0. The miRNA-TF-mRNA and lncRNA-miRNA-mRNA networks were constructed to determine the key interactions associated with lung adenocarcinoma metastasis. According to the miRNA microarray results, there were 10 miRNAs that were differentially expressed in metastatic tissues compared with primary tumor and adjacent non-tumorigenic tissues. Among them were increased levels of miR-146a-5p, miR-342-3p, and miR-150-5p, which were validated in the second cohort. Based on the miRNA-TF-mRNA network, vascular endothelial growth factor A and transcription factors (TFs) including TP53, SMAD4, and EP300 were recognized as critical targets of the three miRNAs. Interactions involving SNHG16–miR-146a-5p–SMAD4 and RP6-24A23.7–miR-342-3p/miR-150-5p–EP300 were highlighted according to the lncRNA-miRNA-mRNA network. miR-146a-5p, miR-342-3p, and miR-150-5p are lymphatic metastasis-related miRNAs in lung adenocarcinoma. Bioinformatics analyses demonstrated that SNHG16 might inhibit the interaction between miR-146a-5p and SMAD4, while RP6-24A23.7 might weaken miR-342-3p–EP300 and miR-150-5p–EP300 interactions in metastasis.


2017 ◽  
Vol 35 (3) ◽  
pp. 109-115 ◽  
Author(s):  
Hideyuki Hayashi ◽  
Kazuto Ashizawa ◽  
Yukihiro Ogihara ◽  
Akifumi Nishida ◽  
Keitaro Matsumoto ◽  
...  

2020 ◽  
Vol 70 (5) ◽  
pp. 295-299
Author(s):  
Takuo Hayashi ◽  
Kazuya Takamochi ◽  
Shinji Kohsaka ◽  
Satsuki Kishikawa ◽  
Yoshiyuki Suehara ◽  
...  

2017 ◽  
Vol 23 (4) ◽  
pp. 181-187 ◽  
Author(s):  
Tomohiro Haruki ◽  
Makoto Wakahara ◽  
Yuki Matsuoka ◽  
Ken Miwa ◽  
Kunio Araki ◽  
...  

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