scholarly journals STAT3 rs3816769 polymorphism correlates with gene expression level and may predispose to nonsmall cell lung cancer: a preliminary study

2013 ◽  
Vol 123 (12) ◽  
pp. 672-679 ◽  
Author(s):  
Daria Domańska ◽  
Adam Antczak ◽  
Dorota Pastuszak‑Lewandoska ◽  
Paweł Górski ◽  
Jacek Kordiak ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Lung Cancer ◽  
Nonsmall Cell Lung Cancer ◽  
Gene Expression Level ◽  
Expression Level ◽  
Preliminary Study

scholarly journals Identification of lung cancer gene markers through kernel maximum mean discrepancy and information entropy

2019 ◽  
Vol 12 (S8) ◽  
Author(s):  
Zhixun Zhao ◽  
Hui Peng ◽  
Xiaocai Zhang ◽  
Yi Zheng ◽  
Fang Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Information Entropy ◽  
Differential Expression Analysis ◽  
Differentially Expressed Gene ◽  
Gene Expression Level ◽  
Expression Level ◽  
Marker Genes ◽  
Gene Markers ◽  
Maximum Mean Discrepancy

Abstract Background The early diagnosis of lung cancer has been a critical problem in clinical practice for a long time and identifying differentially expressed gene as disease marker is a promising solution. However, the most existing gene differential expression analysis (DEA) methods have two main drawbacks: First, these methods are based on fixed statistical hypotheses and not always effective; Second, these methods can not identify a certain expression level boundary when there is no obvious expression level gap between control and experiment groups. Methods This paper proposed a novel approach to identify marker genes and gene expression level boundary for lung cancer. By calculating a kernel maximum mean discrepancy, our method can evaluate the expression differences between normal, normal adjacent to tumor (NAT) and tumor samples. For the potential marker genes, the expression level boundaries among different groups are defined with the information entropy method. Results Compared with two conventional methods t-test and fold change, the top average ranked genes selected by our method can achieve better performance under all metrics in the 10-fold cross-validation. Then GO and KEGG enrichment analysis are conducted to explore the biological function of the top 100 ranked genes. At last, we choose the top 10 average ranked genes as lung cancer markers and their expression boundaries are calculated and reported. Conclusion The proposed approach is effective to identify gene markers for lung cancer diagnosis. It is not only more accurate than conventional DEA methods but also provides a reliable method to identify the gene expression level boundaries.

scholarly journals Preliminary study on the clinical significance of kinesin Kif18a in nonsmall cell lung cancer

Medicine ◽  
2020 ◽  
Vol 99 (4) ◽  
pp. e19011
Author(s):  
Weifeng Guo ◽  
Huiqing Zeng ◽  
Jinyang Zheng ◽  
Yueming He ◽  
Xibin Zhuang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Clinical Significance ◽  
Cell Lung Cancer ◽  
Nonsmall Cell Lung Cancer ◽  
Preliminary Study

Prediction of nonsmall cell lung cancer sensitivity to cisplastin and paclitaxel based on marker gene expression

2011 ◽  
Vol 45 (4) ◽  
pp. 600-607 ◽  
Author(s):  
U. A. Boyarskikh ◽  
Yu. V. Kondrakhin ◽  
I. S. Yevshin ◽  
R. N. Sharipov ◽  
A. V. Komelkov ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Lung Cancer ◽  
Marker Gene ◽  
Nonsmall Cell Lung Cancer ◽  
Marker Gene Expression

Assessing PD-L1 Expression Level by Radiomic Features From PET/CT in Nonsmall Cell Lung Cancer Patients: An Initial Result

2020 ◽  
Vol 27 (2) ◽  
pp. 171-179 ◽  
Author(s):  
Mengmeng Jiang ◽  
Dazhen Sun ◽  
Yinglong Guo ◽  
Yixian Guo ◽  
Jie Xiao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Cell Lung Cancer ◽  
Nonsmall Cell Lung Cancer ◽  
Initial Result ◽  
Expression Level ◽  
Lung Cancer Patients ◽  
Pet Ct

scholarly journals Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer

2010 ◽  
Vol 129 (2) ◽  
pp. 355-364 ◽  
Author(s):  
Abel Sanchez-Palencia ◽  
Mercedes Gomez-Morales ◽  
Jose Antonio Gomez-Capilla ◽  
Vicente Pedraza ◽  
Laura Boyero ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Gene Expression Profiling ◽  
Cell Lung Cancer ◽  
Expression Profiling ◽  
Nonsmall Cell Lung Cancer ◽  
Novel Biomarkers

Interleukin 17A Polymorphism Elevates Gene Expression and Is Associated with Increased Risk of Nonsmall Cell Lung Cancer

2015 ◽  
Vol 34 (1) ◽  
pp. 63-68 ◽  
Author(s):  
Sensen Cheng ◽  
Zhulin Shao ◽  
Xiuchun Liu ◽  
Liangjun Guo ◽  
Xia Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Lung Cancer ◽  
Nonsmall Cell Lung Cancer ◽  
Interleukin 17A ◽  
Increased Risk

scholarly journals Molecular Mechanism of Expression Changes of Immunological Indexes of PD-1/sPD-L1 after Radiotherapy in Nonsmall Cell Lung Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yanli Qu ◽  
Huan Wang ◽  
Hangyu Liu ◽  
Xiaohu Sun ◽  
Ji Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Molecular Mechanism ◽  
Cell Lung Cancer ◽  
Nonsmall Cell Lung Cancer ◽  
Expression Level ◽  
Control Group ◽  
Group A ◽  
Group B ◽  
Nsclc Patients

It is aimed at investigating the changes of serum soluble programmed death-ligand 1 (sPD-L1) expression level in nonsmall cell lung cancer (NSCLC) before and after radiotherapy, the correlation of PD-L1, PD-1, and proteins of Akt (protein kinase B), mTOR, and HIF-1α, and the molecular mechanism of the PD-1/PD-L1 pathway in the development of NSCLS. A total of 126 NSCLC patients receiving radiotherapy in Liaoning Cancer Hospital from September 2018 to September 2019 were selected as the observation group, and another 58 healthy volunteers were selected as the control group. NSCLC patients were divided into group A (stage I-II, stereotactic radiotherapy) and group B (stage III, intensity-modulated radiation therapy) according to the cancer stage. The efficacy of radiotherapy was evaluated, and sPD-L1 expression was detected by ELISA. The immunohistochemical staining was adopted to detect protein expressions of Akt, mTOR, and HIF-1α in NSCLC tissues. The correlation between their expression and expression of PD-L1 and PD-1 was analyzed. The results showed that the overall response rate (ORR) of group A was 89.29%, the clinical benefit response (CBR) was 96.43%, the median survival time (MST) was 25 months, and the survival rate within three years was 72.56%. In group B, the ORR was 70.41%, the CBR was 97.96%, the MST was 18 months, and the survival rate within three years was 34.67%. Comparison of overall serum sPD-L1 expression in the control group, group A, and group B and between groups before radiotherapy was statistically significant ( P < 0.01 ). After radiotherapy, serum sPD-L1 expression in group A and group B decreased compared with that before radiotherapy ( P < 0.01 ). Among NSCLC patients, the positive expression rate of Akt, mTOR, and HIF-1α was 71.32%, 41.26%, and 80.65%, respectively. PD-L1 expression and Akt, mTOR, and HIF-1α expression showed a significant correlation. PD1 expression and Akt, mTOR, and HIF-1α expression also showed a significant correlation. It indicated that the expression level of sPD-L1 in NSCLC patients was higher than that in normal subjects, but the expression level of sPD-L1 was decreased after radiotherapy. PD-1/PD-L1 may play important roles in NSCLC procession through the Akt/mTOR and HIF-1α pathway.

Sign in / Sign up

Export Citation Format

Share Document