Insomnia score: predictive ability of insomnia, high-diagnostic and prognostic value for cancer.

Objective This study utilized bioinformatics methods to investigate the association between insomnia and cancer. Methods We identified key insomnia-related genes and constructed an insomnia score (riskScore = ∑ Expression gene * Coefficient) based on an insomnia dataset using differential analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and Least Absolute Shrinkage and Selection Operator (LASSO) regression. The predictive ability of the insomnia score was validated in the insomnia dataset using Receiver Operating Characteristic (ROC) analysis. Finally, the diagnostic and prognostic value of the insomnia score was assessed in a pan-cancer cohort. Results Differential analysis, WGCNA, and LASSO screening of the insomnia dataset yielded three key insomnia-related genes (PTMA, NLRP8, and CCBE1). An insomnia score was then constructed using the formula: riskScore = -0.8039667 * Expression PTMA + - 3.1975230 * Expression NLRP8 + -0.4957560 * Expression CCBE1 . The ROC analysis demonstrated that the insomnia score has excellent predictive ability for insomnia. Furthermore, pan-cancer analysis illustrated the diagnostic and prognostic value of the insomnia score across various cancers. Conclusion We successfully constructed an insomnia score and demonstrated its diagnostic and prognostic value in multiple cancers.