Laboratory blood test profiling reveals distinct biochemical and hemocyte features of mutated non-small cell lung cancer.

Limin Ou, Xiuyu Cai, Wenchuang Zeng, Liyan Huang, Qiuhua Deng, Hailing Tang, Zhuxing Chen, Huan Zhou, Yongping Lin, Liping Liu, Wenhua Liang
Author Information
  1. Limin Ou: Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.
  2. Xiuyu Cai: Department of VIP Region, Sun Yat-sen University Cancer Center, Guangzhou, China.
  3. Wenchuang Zeng: Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.
  4. Liyan Huang: The Translational Medicine Laboratory, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.
  5. Qiuhua Deng: The Translational Medicine Laboratory, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.
  6. Hailing Tang: The Translational Medicine Laboratory, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.
  7. Zhuxing Chen: Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.
  8. Huan Zhou: Department of Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
  9. Yongping Lin: Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  10. Liping Liu: The Translational Medicine Laboratory, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.
  11. Wenhua Liang: Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou, China.

Abstract

Background: The testing for capability of some routine blood test parameters to reflect the biology of non-small cell lung carcinoma with different driver mutations is of great interest and practice significance. We aim to screen these variables and, if allowed, develop a novel predictive model based on results of these routine blood tests commonly performed in clinical practice to inform which can help doctors assess the patient's genetic mutation status as early as possible before surgery.
Methods: For the exploration cohort, we included 1,595 patients who were diagnosed with non-small cell lung cancer (NSCLC) and genetically profiled by a next-generation sequencing panel in the First Affiliated Hospital of Guangzhou Medical University. The external validation cohort, which consists of 197 NSCLC cancer patients from Sun Yat-sen University Cancer Hospital, was subsequently established.
Results: We analyzed the association between 46 frequently tested laboratory variables and different genetic mutation types. mutation was found to be a unique subtype that exclusively correlated with several blood parameters in our study. Least absolute shrinkage and selection operator (LASSO) regression was performed, and the following parameters were found to be significantly associated with mutation: triglycerides [odds ratio (OR) =1.63], arterial oxygen partial pressure (OR =0.97), uric acid (OR =1.01), basophil count (OR =1.41), eosinophil count (OR =1.146), fibrinogen (OR =1.42), standard bicarbonate (OR =0.85), high-density lipoprotein cholesterol (OR =0.18), alpha-L-fucosidase (OR =1.07). The areas under the receiver-operator characteristic curve in the training set and the external validation set were 0.85 [95% confidence interval (CI): 0.81-0.88] and 0.81 (95% CI: 0.71-0.91), respectively.
Conclusions: We developed a non-invasive, more cost-effective predictive model of NSCLC based on routinely available variables, with practical predictive power. This model can be used as a practical screening tool to guide the use of more specialized and expensive molecular assays for mutation in NSCLC. However, further studies are warranted to investigate the mechanism underlying such association between mutations and the related parameters of blood tests.

Keywords

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