Contrast subgraphs allow comparing homogeneous and heterogeneous networks derived from omics data.

Background: Biological networks are often used to describe the relationships between relevant entities, particularly genes and proteins, and are a powerful tool for functional genomics. Many important biological problems can be investigated by comparing biological networks between different conditions or networks obtained with different techniques.

Findings: We show that contrast subgraphs, a recently introduced technique to identify the most important structural differences between 2 networks, provide a versatile tool for comparing gene and protein networks of diverse origin.

Cancer Metabolic Subtypes and Their Association with Molecular and Clinical Features.

The alterations of metabolic pathways in cancer have been investigated for many years, beginning long before the discovery of the role of oncogenes and tumor suppressors, and the last few years have witnessed renewed interest in this topic. Large-scale molecular and clinical data on tens of thousands of samples allow us to tackle the problem from a general point of view. Here, we show that transcriptomic profiles of tumors can be exploited to define metabolic cancer subtypes, which can be systematically investigated for associations with other molecular and clinical data.

The heme synthesis-export system regulates the tricarboxylic acid cycle flux and oxidative phosphorylation.

Heme is an iron-containing porphyrin of vital importance for cell energetic metabolism. High rates of heme synthesis are commonly observed in proliferating cells. Moreover, the cell-surface heme exporter feline leukemia virus subgroup C receptor 1a (FLVCR1a) is overexpressed in several tumor types.