SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data.

Background: In Diffuse Large B-Cell Lymphoma (DLBCL), several methodologies are emerging to derive novel biomarkers to be incorporated in the risk assessment. We realized a pipeline that relies on autoencoders (AE) and Explainable Artificial Intelligence (XAI) to stratify prognosis and derive a gene-based signature.

Methods: AE was exploited to learn an unsupervised representation of the gene expression (GE) from three publicly available datasets, each with its own technology.

Alteration of Na/H exchange regulatory factor-1 protein levels in anogenital lesions positive for mucosal high-risk human papillomavirus type 16.

Mucosal high-risk (HR) human papillomaviruses (HPV) are associated with anogenital carcinogenesis. The products of two early genes, E6 and E7, act as major viral oncoproteins. Functional studies in experimental models showed that HPV16 E6 induces degradation of the PDZ protein, the Na+/H+ exchanger regulatory factor-1 (NHERF-1).