Identification of Gene Regulatory Networks Associated with Breast Cancer Patient Survival Using an Interpretable Deep Neural Network Model.

Artificial neural networks have recently gained significant attention in biomedical research. However, their utility in survival analysis still faces many challenges. In addition to designing models for high accuracy, it is essential to optimize models that provide biologically meaningful insights.

Functional variant rs9344 at 11q13.3 regulates CCND1 expression in multiple myeloma with t(11;14).

Multiple myeloma (MM) is a plasma cell (PC) malignancy characterized by cytogenetic abnormalities, such as t(11;14)(q13;q32), resulting in CCND1 overexpression. The rs9344 G allele within CCND1 is the most significant susceptibility allele for t(11;14). Sequencing data from 2 independent cohorts, CoMMpass (n = 698) and Mayo Clinic (n = 661), confirm the positive association between the G allele and t(11;14).

Molecular markers of proliferation, DNA repair, and immune infiltration defines high-risk subset of resectable retroperitoneal sarcomas.

Introduction: For retroperitoneal sarcomas (RPS), aggressive surgical resection offers the only chance for a cure; however, 5-year survival remains below 65%. Therefore, there is a critical need to identify drivers of poor clinical outcomes.

Materials And Methods: To identify biomarkers of tumors likely to recur following curative intent resection, we performed genomic and transcriptomic sequencing for 47 and 34 patients, respectively, with non-metastatic RPS at a single, high-volume sarcoma center.

Cell-specific cross-talk proteomics reveals cathepsin B signaling as a driver of glioblastoma malignancy near the subventricular zone.

Glioblastoma (GBM) is the most prevalent and aggressive malignant primary brain tumor. GBM proximal to the lateral ventricles (LVs) is more aggressive, potentially because of subventricular zone contact. Despite this, cross-talk between GBM and neural stem/progenitor cells (NSC/NPCs) is not well understood.