MLSP: A bioinformatics tool for predicting molecular subtypes and prognosis in patients with breast cancer.

ABSTRACT: The molecular landscape in breast cancer is characterized by large biological heterogeneity and variable clinical outcomes. Here, we performed an integrative multi-omics analysis of patients diagnosed with breast cancer. Using transcriptomic analysis, we identified three subtypes (cluster A, cluster B and cluster C) of breast cancer with distinct prognosis, clinical features, and genomic alterations: Cluster A was associated with higher genomic instability, immune suppression and worst prognosis outcome; cluster B was associated with high activation of immune-pathway, increased mutations and middle prognosis outcome; cluster C was linked to Luminal A subtype patients, moderate immune cell infiltration and best prognosis outcome. Combination of the three newly identified clusters with PAM50

SUBMITTER: Zhu J 

PROVIDER: S-EPMC9685393 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature