Lymphatic microvessel density combined with CT used in the diagnosis of mediastinal and hilar lymph node metastasis of non-small cell lung cancer. Arch Med Res. 2012;43:132-138. [PMID: 22386563 DOI: 10.1016/j.arcmed.2012.02.002]

Identification and validation of the model consisting of DDX49, EGFR, and T-stage as a possible risk factor for lymph node metastasis in patients with lung cancer

INTRODUCTION

The lymph node metastasis stage of lung cancer is an important decisive factor in the need for postoperative adjuvant treatment and the difference between stage IIIa and stage IIIB that is the necessary information to distinguish whether surgery can be performed or not. The specificity of the clinical diagnosis of lung cancer with lymph node metastasis cannot meet the requirements of preoperative evaluation of surgical indications and prediction of surgical removal range in lung cancer.

METHODS

This was an early experimental laboratory trial. The model identification data included the RNA sequence data of 10 patients from our clinical data and 188 patients with lung cancer from The Cancer Genome Atlas dataset. The model development and validation data consisted of RNA sequence data for 537 cases from the Gene Expression Omnibus dataset. We explore the predictive value of the model on two independent clinical data.

RESULTS

A higher specificity of diagnostic model for patients with lung cancer with lymph node metastases consisted of DDX49, EGFR, and tumor stage (T-stage), which were the independent predictive factors. The area under the curve value, specificity, and sensitivity for predicting lymph node metastases were 0.835, 70.4%, and 78.9% at RNA expression level in the training group, and 0.681, 73.2%, and 75.7% at RNA expression level in the validation group as shown as in result part. To verify the predictive performance of the combined model for lymph node metastases, we downloaded the GSE30219 data set (n = 291) and the GSE31210 data set (n = 246) from the Gene Expression Omnibus (GEO) database as the training group and validation group, respectively. In addition, the model had a higher specificity for predicting lymph node metastases in independent tissue samples.

CONCLUSIONS

Determination of DDX49, EGFR, and T-stage could form a novel prediction model to improve the diagnostic efficacy of lymph node metastasis in clinical application.

BDH1 promotes lung cancer cell proliferation and metastases by PARP1-mediated autophagy

Lymph node metastases and distant metastases were the important limiting factor for therapy of unresectable locally advanced (IIIB stage) and oligotransduction (IVa stage) lung cancer. This study was undertaken to identify a novel predictive biomarker for predicting lymph node metastases of lung cancer. A total of 364 patients with lung cancer which comprised of 198 patients with transcriptome sequencing data, 110 cases with immunohistochemistry data and 66 patients with serum samples were included to identify and validate the candidate gene. Autophagy was measured by western blots, immunofluorescence and electron microscope. We found that 3-hydroxybutyrate dehydrogenase 1 (BDH1) was associated with proliferation and metastases of lung cancer. BDH1 expression in both tissue and serum samples was associated with lung cancer metastases. Mechanical studies revealed that the AMPK-mTOR signalling pathway mediated by PARP1 played an important role in BDH1-induced autophagy. Activation of mTOR pathway markedly increased the effect of BDH1 in cell proliferation and metastases. These results were verified by the knockdown of PARP1. Furthermore, in vivo administration of BDH1 effectively promoted tumour growth in H460 xenografts mice. Our finding not only suggested that BDH1 might be useful as a novel biomarker and therapeutic target for lung cancer metastases, but also imply that PARP1-mediated AMPK-mTOR signalling pathway might play a critical role in BDH1-induced autophagy and lung cancer proliferation and metastases.

DDX49 is a novel biomarker and therapeutic target for lung cancer metastases

The identification of lymph node metastases is important for the diagnosis, treatment and prognosis of patients with lung cancer. We found DDX49 was associated with the lymph node metastases in lung cancer by the Akt/β-catenin pathway. Transcriptome sequencing, bioinformatics analysis, quantitative RT-PCR, cell transfection and the Cancer Genome Atlas (TCGA) data set were used to identify DDX49 responsible for lymph node metastases. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to explore the possible molecular mechanism in experimental cell. The DDX49 gene was correlated significantly with lymph node metastases of lung cancer. The knockdown of DDX49 inhibited the cell proliferation and migration in PC-9 and H460 cells. The mechanism research found downexpression of DDX49 decreased the Akt/β-catenin pathway in lung cancer cell. In vivo experiments showed that DDX49 promoted the proliferation and metastases of lung cancer cells by increasing the Akt/β-catenin pathway. These findings suggested that DDX49 may be useful as a novel biomarker of lymph node metastases and therapeutic target for lung cancer metastasis.

CT perfusion imaging in the diagnosis of esophageal cancer

Esophageal cancer is one of the most common malignant tumors in China. The symptoms of early esophageal cancer often tend to be unspecific and are easily ignored. Diagnosis of esophageal cancer at early stage can improve its therapy and prognosis. Currently, there are still limitations for the application of digestive barium meal examination and endoscopic pathological biopsy in diagnosis of esophageal cancer. CT perfusion imaging, a technique developed in recent years, can assess tissue microcirculation quickly, conveniently, and non-invasively. These unique advantages have led to its gradual application to tumor diagnosis and prognosis evaluation. In this article, we review the application of CT perfusion imaging in the diagnosis of esophageal cancer.