Combination of body mass index and oxidized low density lipoprotein receptor 1 in prognosis prediction of patients with squamous non-small cell lung cancer

Abstract

// Long Jiang 1,2,3,4,* , Shanshan Jiang 1,* , Yongbin Lin 1,2,3 , Han Yang 1,2,3 , Zerui Zhao 1,2,3 , Zehua Xie 1,2,3 , Yaobin Lin 1,2,3 and Hao Long 1,2,3 1 Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China 2 Lung Cancer Institute of Sun Yat-Sen University, Guangzhou, China 3 Department of Thoracic Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China 4 University of California, San Francisco, San Francisco, USA * These authors have contributed equally to this work Correspondence to: Hao Long, email: // Keywords : squamous non-small cell lung cancer, oxidized low density lipoprotein receptor 1, body mass index, prediction model Received : April 04, 2015 Accepted : May 22, 2015 Published : May 27, 2015 Abstract Lung cancer, especially non-small cell lung cancer (NSCLC), represents enormous challenges in continuously achieving treatment improvements. Besides cancer, obesity is becoming ever more prevalent. Obesity is increasingly acknowledged as a major risk factor for several types of common cancers. Significant mechanisms overlap in the pathobiology of obesity and tumorigenesis. One of these mechanisms involves oxidized low density lipoprotein receptor 1 (OLR1), as a link between obesity and cancer. Additionally, body mass index (BMI) has been widely used in exploiting the role of obesity on a series of diseases, including cancer. Significantly, squamous NSCLC revealed to be divergent clinical and molecular phenotypes compared with non-squamous NSCLC. Consequently, OLR1 immunostaining score and BMI were assessed by Fisher’s linear discriminant analysis to discriminate if progression-free survival (PFS) would exceed 2 years. In addition, the final model was utilized to calculate the discriminant score in each study participant. Finally, 131 patients with squamous NCSLC were eligible for analysis. And a prediction model was established for PFS based on these 2 markers and validated in a second set of squamous NCSLC patients. The model offers a novel tool for survival prediction and could establish a framework for future individualized therapy for patients with squamous NCSLC.