Construction of noninvasive prognostic model of bladder cancer patients based on urine proteomics and screening of natural compounds.

ABSTRACT:

Background

Bladder cancer (BCa) has a high incidence and recurrence rate worldwide. So far, there is no noninvasive detection of BCa therapy and prognosis based on urine multi-omics. Therefore, it is necessary to explore noninvasive predictive models and novel treatment modalities for BCa.

Methods

First, we performed protein analysis of urine from five BCa patients and five healthy individuals using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Combining multi-omics data to mine particular and sensitive molecules to predict BCa prognosis. Second, urine proteomics data were combined with TCGA transcriptome data to select differential genes that were specifically highly expressed in urine and tissues. Further, the Lasso equation was used to screen specific molecul

SUBMITTER: Wan S 

PROVIDER: S-EPMC11797276 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature