Antisense RNAs are ubiquitous in human cells, yet their role is largely unexplored. Here we profiled antisense RNAs in the MDA-MB-231 breast cancer cell line and its highly lung metastatic derivative. We identified one antisense RNA that drives cancer progression by upregulating the redox enzyme NADPH quinone dehydrogenase 1 (NQO1), and named it NQO1-AS. Knockdown of either NQO1 or NQO1-AS reduced lung colonization in a mouse model, and investigation into the role of NQO1 indicated that it is broadly protective against oxidative damage and ferroptosis. Breast cancer cells in the lung are dependent on this pathway, and this dependence can be exploited therapeutically by inducing ferroptosis while inhibiting NQO1. Together, our findings establish a role for NQO1-AS in the progression of breast cancer by regulating its sense mRNA post-transcriptionally. Because breast cancer predominantly affects females, the disease models used in this study are of female origin and the results are primarily applicable to females.

RNA structural switches are key regulators of gene expression in bacteria, but their characterization in Metazoa remains limited. Here, we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3' untranslated region of the RORC (RAR-related orphan receptor C) transcript. In vivo dimethyl sulfate (DMS) mutational profiling with sequencing (DMS-MaPseq), coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identify trans factors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated messenger RNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.

In our cells, a limited number of RNA binding proteins (RBPs) are responsible for all aspects of RNA metabolism across the entire transcriptome. To accomplish this, RBPs form regulatory units that act on specific target regulons. However, the landscape of RBP combinatorial interactions remains poorly explored. Here, we perform a systematic annotation of RBP combinatorial interactions via multimodal data integration. We build a large-scale map of RBP protein neighborhoods by generating in vivo proximity-dependent biotinylation datasets of 50 human RBPs. In parallel, we use CRISPR interference with single-cell readout to capture transcriptomic changes upon RBP knockdowns. By combining these physical and functional interaction readouts, along with the atlas of RBP mRNA targets from eCLIP assays, we generate an integrated map of functional RBP interactions. We then use this map to match RBPs to their context-specific functions and validate the predicted functions biochemically for four RBPs. This study provides a detailed map of RBP interactions and deconvolves them into distinct regulatory modules with annotated functions and target regulons. This multimodal and integrative framework provides a principled approach for studying post-transcriptional regulatory processes and enriches our understanding of their underlying mechanisms.