Cancer Stemness Online: A Resource for Investigating Cancer Stemness and Associations with Immune Response.

ABSTRACT: Cancer progression involves the gradual loss of a differentiated phenotype and the acquisition of progenitor and stem cell-like features, which are potential culprits of immunotherapy resistance. Although the state-of-the-art predictive computational methods have facilitated the prediction of cancer stemness, there remains a lack of efficient resources to accommodate various usage requirements. Here, we present the Cancer Stemness Online, an integrated resource for efficiently scoring cancer stemness potential at both bulk and single-cell levels. This resource integrates eight robust predictive algorithms as well as 27 signature gene sets associated with cancer stemness for predicting stemness scores. Downstream analyses were performed from five distinct aspects: identifying the signature

SUBMITTER: Zhou W 

PROVIDER: S-EPMC11522875 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature