Biology subjects

Svalina, M. N.

Publications and source records attributed to Svalina, M. N..

3 recordsLinked to original sources

bioRxiv2020

Hyperexcitability and loss of feedforward inhibition in the Fmr1KO lateral amygdala.

Fragile X Syndrome (FXS) is a neurodevelopmental disorder characterized by intellectual disability, autism spectrum disorders (ASDs), and anxiety disorders. The disruption in the function of the FMR1 gene results in a range of alterations in cellular and synaptic function. Previous studies have identified dynamic alterations in inhibitory neurotransmission in early postnatal development in the amygdala of the mouse model of FXS. Yet little is known how these changes alter microcircuit development and plasticity in the lateral amygdala (LA). Using whole-cell patch clamp electrophysiology, we demonstrate that principal neurons (PNs) in the LA exhibit hyperexcitability with a concomitant increase in the synaptic strength of excitatory synapses in the BLA. Further, reduced feed-forward inhibition appears to enhance synaptic plasticity in the FXS amygdala. These results demonstrate that plasticity is enhanced in the amygdala of the juvenile Fmr1 KO mouse and that E/I imbalance may underpin anxiety disorders commonly seen in FXS and ASDs.

neuroscience↗

bioRxiv2019

MEK1/2 in Rhabdomyosarcoma

Alveolar and embryonal rhabdomyosarcoma (RMS) are soft-tissue cancers that affect children, adolescents, and young adults. Sometimes referred to as muscle cancer, RMS is a cancer of muscle and non-muscle origin that phenocopies incompletely differentiated myoblasts or activated satellite (muscle stem) cells. Interestingly, embryonal RMS (ERMS) has been observed to undergo terminal myogenic differentiation in response to stress induced by chemotherapy and radiation therapy4, 9, 24. Given the propensity of rhabdomyosarcoma to differentiation, in this report we explore the use of differentiation therapy combining MEK inhibitor (MEKi) cobimetinib and chemotherapy as a strategy to halt RMS growth. We evaluated a representative panel of RMS cell lines with cobimetinib and chemotherapy in two dosing schedules that mimic clinical use followed by cell growth evaluation and high content analysis (differentiation) assays. We uncovered that cobimetinib does not have significant additive or synergistic effects on cell differentiation or cell growth with chemotherapy in RMS and can have unanticipated antagonistic effects; specifically, pre-exposure of cobimetinib to cells can decrease the effectiveness of chemotherapy-mediated cell growth inhibition in vitro. Although differentiation-therapy is still a potential viable strategy in RMS, our data do not support MEKi/chemotherapy co-treatment in this context.

cancer biology↗

bioRxiv2018

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. This computational modeling approach addresses three major challenges in personalized cancer therapy, which we validate across multiple species via computationally-designed personalized synergistic drug combination predictions, identification of unifying therapeutic targets to overcome intra-tumor heterogeneity, and mitigation of cancer cell resistance and rewiring mechanisms. These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

bioinformatics↗