Biology subjects

Montemurro, M.

Publications and source records attributed to Montemurro, M..

3 recordsLinked to original sources

bioRxiv2024

Mechanical state of pre-tumoral epithelia dictates subsequent tumour aggressiveness

Tumours evolve through the acquisition of increasingly aggressive traits associated with dysplasia. This progression is accompanied by the alteration of tumour mechanical properties, especially through extracellular matrix remodelling. However, the contribution of intrinsic tumour cells mechanics to tumour aggressiveness remains unknown in vivo. Here we show that adherens junction tension in pre-tumoral tissues dictates subsequent tumour evolution. Increased cell contractility, observed in aggressive tumours before any sign of tissue overgrowth, proved sufficient to trigger dysplasia in normally hyperplastic tumours. Unexpectedly, high contractility contributes to tumour evolution through cell death induction which favours cell-cell junctions weakening. Overall, our results highlight the need to re-evaluate the roles of tumoral cell death, and identify pre-tumour cell mechanics as an unsuspected early marker and key trigger of tumour aggressiveness. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/594669v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1a677edorg.highwire.dtl.DTLVardef@b8940org.highwire.dtl.DTLVardef@15feebaorg.highwire.dtl.DTLVardef@13213ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

Identifying the oncogenic potential of gene fusions exploiting miRNAs

BackgroundIt is estimated that oncogenic gene fusions cause about 20% of human cancer morbidity. Identifying potentially oncogenic gene fusions may improve affected patients diagnosis and treatment. Previous approaches to this issue included exploiting specific gene-related information, such as gene function and regulation. Here we propose a model that profits from the previous findings and includes the microRNAs in the oncogenic assessment. We present a classifier called ChimerDriver for the classification of gene fusions as oncogenic or not oncogenic. ChimerDriver is based on a specifically designed neural network and trained on genetic and post-transcriptional information to obtain a reliable classification. Results and discussionThe designed neural network integrates information related to transcription factors, gene ontologies, microRNAs and other detailed information related to the functions of the genes involved in the fusion and the gene fusion structure. As a result, the performances on the test set reached 0.83 f1-score and 96% recall. The comparison with state-of-the-art tools returned comparable or higher results. Moreover, ChimerDriver performed well in a real-world case where 21 out of 24 validated gene fusion samples were detected by the gene fusion detection tool Starfusion. ConclusionsChimerDriver integrated transcriptional and post-transcriptional information in an ad-hoc designed neural network to effectively discriminate oncogenic gene fusions from passenger ones.

bioinformatics↗

bioRxiv2019

Computational modelling of hippocampal sensitivity to expectation violation

Pattern separation and completion are fundamental hippocampal computations supporting memory encoding and retrieval. However, despite extensive exploration of these processes, it remains unclear whether they are modulated by top-down processes. We used a neural network model to examine how unexpected information is represented by the hippocampus. During training the network learned a contingency between a cue and a category, which the target object belongs to. At test, we presented the network with congruous and incongruous cues, as well as perceptually similar foils. We used representational similarity analysis to examine how the top-down expectation modulation interacts with bottom-up perceptual input, in each layer. All subfields showed an interaction between the two, with DG and CA3 being more sensitive to expectation violation than CA1. A further multivariate analysis revealed that representational differences between expected and unexpected inputs were prominent for moderate to high levels of perceptual overlap in DG/CA3. This effect diminished when inputs from DG and CA3 into CA1 were lesioned. Overall, our findings suggest pattern separation in DG and CA3 underlies the effect that violation of expectation exerts on memory.

neuroscience↗