P-107PATHOLOGICAL INVASIVE COMPONENT SIZE IS ASSOCIATED WITH LYMPH NODE METASTASIS AND PROGNOSIS IN LUNG ADENOCARCINOMA

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.

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Identification of lymph node metastasis-related microRNAs in lung adenocarcinoma and analysis of the underlying mechanisms using a bioinformatics approach

Experimental Biology and Medicine ◽

10.1177/1535370216677353 ◽

2016 ◽

Vol 242 (7) ◽

pp. 709-717 ◽

Cited By ~ 16

Author(s):

Li Yan ◽

Demin Jiao ◽

Huizhen Hu ◽

Jian Wang ◽

Xiali Tang ◽

...

Keyword(s):

Transcription Factors ◽

Lymph Node ◽

Lymph Node Metastasis ◽

Lung Adenocarcinoma ◽

Lymphatic Metastasis ◽

Target Genes ◽

Bioinformatics Analyses ◽

Node Metastasis ◽

Primary Lung Adenocarcinoma ◽

Underlying Mechanisms

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.

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