Oncotarget

Research Papers:

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

Long Jiang, Shanshan Jiang, Yongbin Lin, Han Yang, Zerui Zhao, Zehua Xie, Yaobin Lin and Hao Long _

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Oncotarget. 2015; 6:22072-22080. https://doi.org/10.18632/oncotarget.4299

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Abstract

Long Jiang1,2,3,4,*, Shanshan Jiang1,*, Yongbin Lin1,2,3, Han Yang1,2,3, Zerui Zhao1,2,3, Zehua Xie1,2,3, Yaobin Lin1,2,3 and Hao Long1,2,3

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.


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