PSIP1/p75 promotes tumorigenicity in breast cancer cells by promoting the transcription of cell cycle genes.

Breast cancer (BC) is a highly heterogeneous disease, both at the pathological and molecular level, and several chromatin-associated proteins play crucial roles in BC initiation and progression. Here, we demonstrate the role of PSIP1 (PC4 and SF2 interacting protein)/p75 (LEDGF) in BC progression. PSIP1/p75, previously identified as a chromatin-adaptor protein, is found to be upregulated in basal-like/triple negative breast cancer (TNBC) patient samples and cell lines. Immunohistochemistry in tissue arrays showed elevated levels of PSIP1 in metastatic invasive ductal carcinoma. Survival data analyses revealed that the levels of PSIP1 showed a negative association with TNBC patient survival. Depletion of PSIP1/p75 significantly reduced the tumorigenicity and metastatic properties of TNBC cell lines while its over-expression promoted tumorigenicity. Further, gene expression studies revealed that PSIP1 regulates the expression of genes controlling cell-cycle progression, cell migration and invasion. Finally, by interacting with RNA polymerase II, PSIP1/p75 facilitates the association of RNA pol II to the promoter of cell cycle genes and thereby regulates their transcription. Our findings demonstrate an important role of PSIP1/p75 in TNBC tumorigenicity by promoting the expression of genes that control the cell cycle and tumor metastasis.

ADAR2 regulates RNA stability by modifying access of decay-promoting RNA-binding proteins.

Adenosine deaminases acting on RNA (ADARs) catalyze the editing of adenosine residues to inosine (A-to-I) within RNA sequences, mostly in the introns and UTRs (un-translated regions). The significance of editing within non-coding regions of RNA is poorly understood. Here, we demonstrate that association of ADAR2 with RNA stabilizes a subset of transcripts. ADAR2 interacts with and edits the 3΄UTR of nuclear-retained Cat2 transcribed nuclear RNA (Ctn RNA). In absence of ADAR2, the abundance and half-life of Ctn RNA are significantly reduced. Furthermore, ADAR2-mediated stabilization of Ctn RNA occurred in an editing-independent manner. Unedited Ctn RNA shows enhanced interaction with the RNA-binding proteins HuR and PARN [Poly(A) specific ribonuclease deadenylase]. HuR and PARN destabilize Ctn RNA in absence of ADAR2, indicating that ADAR2 stabilizes Ctn RNA by antagonizing its degradation by PARN and HuR. Transcriptomic analysis identified other RNAs that are regulated by a similar mechanism. In summary, we identify a regulatory mechanism whereby ADAR2 enhances target RNA stability by limiting the interaction of RNA-destabilizing proteins with their cognate substrates.

Navigating 3D electron microscopy maps with EM-SURFER.

BACKGROUND: The Electron Microscopy DataBank (EMDB) is growing rapidly, accumulating biological structural data obtained mainly by electron microscopy and tomography, which are emerging techniques for determining large biomolecular complex and subcellular structures. Together with the Protein Data Bank (PDB), EMDB is becoming a fundamental resource of the tertiary structures of biological macromolecules. To take full advantage of this indispensable resource, the ability to search the database by structural similarity is essential. However, unlike high-resolution structures stored in PDB, methods for comparing low-resolution electron microscopy (EM) density maps in EMDB are not well established. RESULTS: We developed a computational method for efficiently searching low-resolution EM maps. The method uses a compact fingerprint representation of EM maps based on the 3D Zernike descriptor, which is derived from a mathematical series expansion for EM maps that are considered as 3D functions. The method is implemented in a web server named EM-SURFER, which allows users to search against the entire EMDB in real-time. EM-SURFER compares the global shapes of EM maps. Examples of search results from different types of query structures are discussed. CONCLUSIONS: We developed EM-SURFER, which retrieves structurally relevant matches for query EM maps from EMDB within seconds. The unique capability of EM-SURFER to detect 3D shape similarity of low-resolution EM maps should prove invaluable in structural biology.