Galgo: a bi-objective evolutionary meta-heuristic identifies robust transcriptomic classifiers associated with patient outcome across multiple cancer types.

MOTIVATION: Statistical and machine-learning analyses of tumor transcriptomic profiles offer a powerful resource to gain deeper understanding of tumor subtypes and disease prognosis. Currently, prognostic gene-expression signatures do not exist for all cancer types, and most developed to date have been optimized for individual tumor types. In Galgo, we implement a bi-objective optimization approach that prioritizes gene signature cohesiveness and patient survival in parallel, which provides greater power to identify tumor transcriptomic phenotypes strongly associated with patient survival. RESULTS: To compare the predictive power of the signatures obtained by Galgo with previously studied subtyping methods, we used a meta-analytic approach testing a total of 35 large population-based transcriptomic biobanks of four different cancer types. Galgo-generated colorectal and lung adenocarcinoma signatures were stronger predictors of patient survival compared to published molecular classification schemes. One Galgo-generated breast cancer signature outperformed PAM50, AIMS, SCMGENE and IntClust subtyping predictors. In high-grade serous ovarian cancer, Galgo signatures obtained similar predictive power to a consensus classification method. In all cases, Galgo subtypes reflected enrichment of gene sets related to the hallmarks of the disease, which highlights the biological relevance of the partitions found. AVAILABILITY AND IMPLEMENTATION: The open-source R package is available on www.github.com/harpomaxx/galgo. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Kinetics of human sperm acrosomal exocytosis.

The acrosome reaction is a unique event in the lifespan of sperm characterized by the exocytosis of the acrosomal content and the release of hybrid vesicles formed by patches of the outer acrosomal membrane and the plasma membrane. This unique regulated exocytosis is mediated by essentially the same membrane fusion machinery present in neuroendocrine cells. However, whereas secretion in neuroendocrine cells occurs in less than a second, the acrosome reaction is normally assessed after several minutes of incubation with inducers. In this report, we measured the kinetics of human sperm exocytosis triggered by two stimuli (calcium ionophore and progesterone) by using electron microscopy and three different approaches based on the incorporation of fluorescent Pisum sativum agglutinin into the acrosome upon opening of fusion pores connecting the extracellular medium with the acrosomal lumen. The results with the different methods are consistent with a slow kinetics (t½ = 14 min). We also manipulated the system to measure different steps of the process. We observed that cytosolic calcium increased with a relatively fast kinetics (t½ = 0.1 min). In contrast, the swelling of the acrosomal granule that precedes exocytosis was a slow process (t½ = 13 min). When swelling was completed, the fusion pore opening was fast (t½ = 0.2 min). The results indicate that acrosomal swelling is the slowest step and it determines the kinetics of the acrosome reaction. After the swelling is completed, the efflux of calcium from intracellular stores triggers fusion pores opening and the release of hybrid vesicles in seconds.