Feng, Y.-X. | Search bioRxiv

bioRxiv2021

ERK signaling licenses SKN-1A/NRF1 for proteasome production and proteasomal stress resistance

The ubiquitin-proteasome system is vital for cell growth and homeostasis, but for most cancers proteasomal inhibition has not been effective as a therapy. Normal and cancer cells adapt to proteasomal stress through an evolutionarily conserved recovery response, in which the transcription factor NRF1 upregulates proteasome subunit genes. Starting with a C. elegans screen to identify regulators of the recovery response, here we show that this response depends upon phosphorylation of NRF1 on a single residue by the growth factor-activated kinase ERK1/2. Inhibition of this phosphorylation impairs NRF1 nuclear localization and proteasome gene activation, sensitizes C. elegans and cancer cells to proteasomal stress, and synergizes with proteasome inhibition to retard human melanoma growth in vivo in a mouse model. The evolutionarily conserved ERK1/2-NRF1 axis couples proteasome production to growth signaling, and represents a promising new strategy for expanding the range and efficacy of proteasomal inhibition therapy in cancer.

cell biology↗

bioRxiv2018

Small effect size leads to reproducibility failure in resting-state fMRI studies

Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric isorders together with healthy individuals have been analyzed. Parkinsons disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named amplitude of low frequency fluctuation (ALFF) showed that the effect size (Hedges g) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t-maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.

neuroscience↗