Prognostic Roles of mRNA Expression of S100 in Non-Small-Cell Lung Cancer

نویسندگان

  • Ying Liu
  • Jian Cui
  • Yun-Liang Tang
  • Liang Huang
  • Cong-Yang Zhou
  • Ji-Xiong Xu
چکیده

The S100 protein family is involved in cancer cell invasion and metastasis, but its prognostic value in non-small-cell lung cancer (NSCLC) has not been elucidated. In the present study we investigated the prognostic role of mRNA expression of each individual S100 in NSCLC patients through the Kaplan-Meier plotter (KM plotter) database. Expression of 14 members of the S100 family correlated with overall survival (OS) for all NSCLC patients; 18 members were associated with OS in adenocarcinoma, but none were associated with OS in squamous cell carcinoma. In particular, high mRNA expression level of S100B was associated with better OS in NSCLC patients. The prognostic value of S100 according to smoking status, pathological grades, clinical stages, and chemotherapeutic treatment of NSCLC was further assessed. Although the results should be further verified in clinical trials our findings provide new insights into the prognostic roles of S100 proteins in NSCLC and might promote development of S100-targeted inhibitors for the treatment of NSCLC.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Expression of Two Basic mRNA Biomarkers in Peripheral Blood of Patients with Non-Small Cell Lung Cancer Detected by Real-Time RT-PCR, Individually and Simultaneously

Introduction: Although extensive research has been conducted on lung cancer markers, a singular clinically applicable marker has not been found yet. The objective of this study was to evaluate the sensitivity and the specificity of carcinoembryonic antigen (CEA) mRNA and lung-specific X protein (LUNX) mRNA biomarkers in peripheral blood to detect lung cancer individually and simultaneously. Met...

متن کامل

Expression of Epidermal Growth Factor Receptor and the association with Demographic and Prognostic Factors in Patients with Non-small Cell Lung Cancer

Introduction: Growth, proliferation, survival, and differentiation are the prominent characteristics of cells, which are affected by cancer. Epidermal growth factor receptor (EGFR) plays a pivotal role in the effective control of these features. Given the significance of EGFR signaling pathway in non-small cell lung cancer (NSCLC), EGFR expression is influential on these cell characteristics. I...

متن کامل

The Effect of Time-dependent Prognostic Factors on Survival of Non-Small Cell Lung Cancer using Bayesian Extended Cox Model

  Abstract Background: Lung cancer is one of the most common cancers around the world. The aim of this study was to use Extended Cox Model (ECM) with Bayesian approach to survey the behavior of potential time-varying prognostic factors of Non-small cell lung cancer. Materials and Methods: Survival status of all 190 patients diagnosed with Non-Small Cell lung cancer referring to hospitals in ...

متن کامل

Prognostic value of various metabolic parameters on pre-treatment 18-F-FDG PET/CT in patients with stage I-III non-small cell lung cancer

Background: the aim of this study was to investigate the prognostic value of 18Fluorine-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) parameters in both overall survival and progression-free survival in Stage I-III non-small cell lung cancer (NSCLC). Materials and Methods: In this retrospective study, 267 patients who were diagnosed as Stage I-III non-smal...

متن کامل

Study of Antimetastatic Effect of Genistein Through Inhibition of Expression of Matrix Metalloproteinase in A-549 Cell Line

The lung cancer is one of the most dangerous cancers and is also the leading cause of cancer death worldwide, accounting for about 1.3 million deaths annually. However in clinical practice, lung cancer therapies commonly do with chemotherapy, although it is hard because the lung cancer may progress to metastasis stage. The metastasis of lung cancer is highly dependent of expression of matrix me...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 2018  شماره 

صفحات  -

تاریخ انتشار 2018