News by Subject Biology

Researchers at CeMM have developed knowledge-primed neural networks (KPNNs), a new method that combines the power of deep learning with the interpretability of biological network models. KPNNs learn multiple layers of protein signaling and gene regulation from single-cell RNA-seq data, thereby providing a much-needed boost in our ability to convert massive single-cell atlas data into biological insights. These findings have now been published in the renowned scientific journal Genome Biology.

The mechanism unveiled triggers a mutation fog, causing hundreds of mutations in each tumor, which spread through the genome of lung, head-and-neck and breast cancers. Researchers from the Genome Data Science Lab have identified the antiviral APOBEC3A enzyme as the major cause of this new type of hypermutation. Published in Nature Genetics, the study shows how the mutation fog process generates many oncogenic "cancer driver" mutations, thus accelerating tumour development.

* Patients with glioma - a very common type of tumour originating in the brain - see improvement in survival rates with combined treatment of radiotherapy plus temozolomide * Researchers found a novel mechanism on how tumours evade chemotherapy through genomic rearrangements of the MGMT DNA repair gene * This finding is potentially relevant for updating the methods used to monitor temozolomide efficacy. Genomic rearrangement could be a marker to be detected in blood samples and help make therapeutic decisions

Researchers have correlated information on drugs, genes and diseases to identify potential candidates for psychiatric and neurological treatment. The methodology they developed will be used to search for drugs against COVID-19.

A test which detects changing levels of tumour fragments in the blood may be an easy, non-invasive and quick way to predict who will benefit from immunotherapy, a treatment option for advanced cancers.