Transcriptome and single-cell RNA sequencing analysis with 101 machine learning combinations and experimental verification reveals the mechanism of action of mannose metabolism in bladder cancer
Anhong Li, Kaile Zhao, Tianjiao Wang, Guangyue Shi

TL;DR
This study identifies key genes and macrophages linked to mannose metabolism in bladder cancer, offering new insights for prognosis and treatment.
Contribution
The study introduces a novel risk model based on four mannose metabolism-related genes and highlights macrophage subtypes in bladder cancer prognosis.
Findings
CALR, SLMAP, PFKFB4, and TMTC1 are identified as prognostic genes in bladder cancer.
Macrophages are confirmed as critical cells in bladder cancer, with five subtypes identified.
The risk model stratifies patients into high- and low-risk groups with distinct survival outcomes.
Abstract
Bladder cancer (BLCA) is a prevalent genitourinary malignancy characterized by high recurrence and mortality rates. While mannose metabolism has demonstrated anti-tumor potential across various cancers, its role in BLCA remains underexplored. This study examines the influence of mannose metabolism on BLCA prognosis. BLCA-related datasets and genes associated with mannose metabolism (MMRGs) were obtained from public databases. Candidate genes were identified by overlapping differentially expressed genes with MMRGs. Prognostic genes were pinpointed using ten machine learning algorithms and regression analysis to develop a risk model, which was subsequently validated. A nomogram was constructed by integrating the risk score with clinical features, and its predictive accuracy was assessed. We performed functional enrichment, drug sensitivity, reverse transcription-quantitative polymerase…
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Taxonomy
TopicsBladder and Urothelial Cancer Treatments · Single-cell and spatial transcriptomics · Ferroptosis and cancer prognosis
