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Nawaz, U.

Publications and source records attributed to Nawaz, U..

3 recordsLinked to original sources

OnCorr: A pan-cancer mRNA-protein correlation tool for precision oncology

Proteins are ultimately responsible for cellular phenotypes and are targeted by most anticancer drugs. However, beyond immunohistochemistry, proteins are not typically measured in precision oncology, meaning transcriptomics is used as a proxy. To determine how informative mRNA is for guiding personalised treatments, mRNA-protein correlations were analysed in three large pan-cancer datasets and made available in a web portal (https://procan.shinyapps.io/OnCorr/). OnCorr can be integrated into precision medicine programs to augment transcriptomics.

cancer biology↗

Potent synthetic lethality between PLK1 and EYA-family inhibitors in tumours of the central and peripheral nervous system

The Eyes Absent family of protein phosphatases (EYA1-4) are aberrantly expressed and tumour-promoting across many devastating cancers of neurological origin affecting both children and adults. It has recently been demonstrated that EYA1 and EYA4 promote tumour cell survival by increasing the active pool of Polo-like kinase 1 (PLK1) molecules. This discovery provides a rationale for the therapeutic combination of EYA inhibitors with direct, ATP-competitive, PLK1 inhibitors. Here, we demonstrate potent and synergistic effects of EYA and PLK1 inhibition in cancer cell lines that overexpress EYA1 and/or EYA4, including in neuroblastoma and glioblastoma models. We identify decreases in PLK1 activity and RAD51 foci formation, and increases in mitotic arrest and cell death, as mechanistic contributors to combination sensitivity. Combined EYA and PLK1 inhibition is also effective in glioblastoma stem cell models that overexpress EYA1/EYA4 and specifically targets the cancer stem cell state. Finally, through multi-omic correlational analysis, we identify high levels of the NuRD complex and SOX9 as contributors to combination treatment sensitivity. Overall, this work identifies a novel synthetic lethal combination therapy with potential utility across a wide range of neurological cancers.

cancer biology↗

Individual Variation in Brain Network Topology is Linked to Schizophrenia Symptomatology

BackgroundResting state fMRI (rsfMRI) demonstrates that the brain is organized into distributed networks. Numerous studies have examined links between psychiatric symptomatology and network functional connectivity. Traditional rsfMRI analyses assume that the spatial organization of networks is invariant between individuals. This dogma has recently been overturned by the demonstration that networks show significant variation between individuals. We tested the hypothesis that previously observed relationships between schizophrenia negative symptom severity and network connectivity are actually due to individual differences in network spatial organization.\n\nMethods44 participants diagnosed with schizophrenia underwent rsfMRI scans and clinical assessments. A multivariate pattern analysis determined how whole brain functional connectivity correlates with negative symptom severity at the individual voxel level.\n\nResultsBrain connectivity to a region of the right dorso-lateral pre-frontal cortex correlates with negative symptom severity. This finding results from individual differences in the topographic distribution of two networks: the default mode network (DMN) and the task positive network (TPN). Both networks demonstrate strong (r[~]0.49) and significant (p<0.001) relationships between topography and symptom severity. For individuals with low symptom severity, this critical region is part of the DMN. In highly symptomatic individuals, this region is part of the TPN.\n\nConclusionPreviously overlooked individual variation in brain organization is tightly linked to differences in schizophrenia symptom severity. Recognizing critical links between network topography and pathological symptomology may identify key circuits that underlie cognitive and behavioral phenotypes. Individual variation in network topography likely guides different responses to clinical interventions that rely on anatomical targeting (e.g. TMS).

neuroscience↗