Frontiers of Medicine 2022;16(4):618-626

doi:10.1007/s11684-021-0867-0

Four-protein model for predicting prognostic risk of lung cancer.

Xiang WANG 1 ; Minghui WANG 1 ; Lin FENG 1 ; Jie SONG 1 ; Xin DONG 2 3 ; Ting XIAO 4 ; Shujun CHENG 5

Affiliations

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Keywords

HSP90β; decision tree model; lung cancer; prognosis

Country

China

Language

English

Abstract

Patients with lung cancer at the same stage may have markedly different overall outcome and a lack of specific biomarker to predict lung cancer outcome. Heat-shock protein 90 β (HSP90β) is overexpressed in various tumor cells. In this study, the ELISA results of HSP90β combined with CEA, CA125, and CYFRA21-1 were used to construct a recursive partitioning decision tree model to establish a four-protein diagnostic model and predict the survival of patients with lung cancer. Survival analysis showed that the recursive partitioning decision tree could distinguish the prognosis between high- and low-risk groups. Results suggested that the joint detection of HSP90β, CEA, CA125, and CYFRA21-1 in the peripheral blood of patients with lung cancer is plausible for early diagnosis and prognosis prediction of lung cancer.