2022 World Conference on Lung Cancer (ePosters)-EP16.02-020. Lung Cancer Cell Dynamics Significantly Depended on Blood Cell Circuit, Biochemical Factors, Hemostasis System, Cancer Characteristics

EP16.02-020. Lung Cancer Cell Dynamics Significantly Depended on Blood Cell Circuit, Biochemical Factors, Hemostasis System, Cancer Characteristics

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The objective of this study was to examine the factors that significantly affect the dynamics of lung cancer (LC) cells. The researchers analyzed data from 768 non-small cell LC patients who underwent surgery and were monitored between 1985 and 2022. The patients had a median age of 57.6 years and a median tumor size of 4.1 cm. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap, and neural network computing were used to determine significant dependencies.<br /><br />The overall life span of the patients was 2,244.9 days, and the cumulative 5-year survival rate was 72.9%. The 10-year and 20-year survival rates were 64.3% and 43.1% respectively. The researchers found that LC cell dynamics significantly depended on various factors including the phase transition from early to invasive LC, lymph node status, histology, tumor size, and the ratio between cancer cells and blood cell subpopulations. Neural network simulation further revealed the relationships between LC cell dynamics and parameters such as segmented neutrophils, lymphocytes, and various blood cell subpopulations.<br /><br />The study also showed that the level of certain blood parameters, such as ESS, glucose, and bilirubin, played a significant role in LC cell dynamics. The researchers used neural network computing to predict LC cell dynamics with an accuracy of 92-95%.<br /><br />Overall, the findings suggest that lung cancer cell dynamics are significantly influenced by factors related to the blood cell circuit, biochemical factors, the hemostasis system, cancer characteristics, and anthropometric data. Understanding these factors can potentially help improve the diagnosis, treatment, and prognosis of lung cancer patients.

Asset Subtitle

Oleg Kshivets

Meta Tag

Speaker Oleg Kshivets

Topic Tumour Biology and Biomarkers - Minimally Invasive Biomarkers

Keywords

lung cancer cells

factors

dynamics

tumor size

lymph node status

histology

blood cell subpopulations

neural network simulation

blood parameters

diagnosis