AMBRA1 phosphorylation by CDK1 and PLK1 regulates mitotic spindle orientation.

AMBRA1 is a crucial factor for nervous system development, and its function has been mainly associated with autophagy. It has been also linked to cell proliferation control, through its ability to regulate c-Myc and D-type cyclins protein levels, thus regulating G1-S transition. However, it remains still unknown whether AMBRA1 is differentially regulated during the cell cycle, and if this pro-autophagy protein exerts a direct role in controlling mitosis too. Here we show that AMBRA1 is phosphorylated during mitosis on multiple sites by CDK1 and PLK1, two mitotic kinases. Moreover, we demonstrate that AMBRA1 phosphorylation at mitosis is required for a proper spindle function and orientation, driven by NUMA1 protein. Indeed, we show that the localization and/or dynamics of NUMA1 are strictly dependent on AMBRA1 presence, phosphorylation and binding ability. Since spindle orientation is critical for tissue morphogenesis and differentiation, our findings could account for an additional role of AMBRA1 in development and cancer ontogenesis.

Acquisition of docetaxel resistance in breast cancer cells reveals upregulation of ABCB1 expression as a key mediator of resistance accompanied by discrete upregulation of other specific genes and pathways.

The microtubule-targeting taxanes are important in breast cancer therapy, but no predictive biomarkers have yet been identified with sufficient scientific evidence to allow clinical routine use. The purposes of the present study were to develop a cell-culture-based discovery platform for docetaxel resistance and thereby identify key molecular mechanisms and predictive molecular characteristics to docetaxel resistance. Two docetaxel-resistant cell lines, MCF7RES and MDARES, were generated from their respective parental cell lines MCF-7 and MDA-MB-231 by stepwise selection in docetaxel dose increments over 15 months. The cell lines were characterized regarding sensitivity to docetaxel and other chemotherapeutics and subjected to transcriptome-wide mRNA microarray profiling. MCF7RES and MDARES exhibited a biphasic growth inhibition pattern at increasing docetaxel concentrations. Gene expression analysis singled out ABCB1, which encodes permeability glycoprotein (Pgp), as the top upregulated gene in both MCF7RES and MDARES. Functional validation revealed Pgp as a key resistance mediator at low docetaxel concentrations (first-phase response), whereas additional resistance mechanisms appeared to be prominent at higher docetaxel concentrations (second-phase response). Additional resistance mechanisms were indicated by gene expression profiling, including genes in the interferon-inducible protein family in MCF7RES and cancer testis antigen family in MDARES. Also, upregulated expression of various ABC transporters, ECM-associated proteins, and lysosomal proteins was identified in both resistant cell lines. Finally, MCF7RES and MDARES presented with cross-resistance to epirubicin, but only MDARES showed cross-resistance to oxaliplatin. In conclusion, Pgp was identified as a key mediator of resistance to low docetaxel concentrations with other resistance mechanisms prominent at higher docetaxel concentrations. Supporting Pgp upregulation as one major mechanism of taxane resistance and cell-line-specific alterations as another, both MCF7RES and MDARES were cross-resistant to epirubicin (Pgp substrate), but only MDARES was cross-resistant to oxaliplatin (non-Pgp substrate).

The invariant chain CD74 protein is a cell surface binding partner of TIMP-1 in breast cancer cells.

Tissue inhibitor of metalloproteinases-1 (TIMP-1) regulates the proteolytic activity of matrix metalloproteinases (MMPs), playing an important role in the homeostasis of the extracellular matrix. Beyond its well-known role in tissue maintenance, TIMP-1 has been associated with multiple MMP-independent cytokine-like functions. The protein structure of TIMP-1, with two distinct domains, one interacting with MMPs and another able to bind multiple partners, provides a rationale for this multifunctionality. The identification of CD63 as a cell surface receptor for TIMP-1, able to mediate intracellular signaling through the Erk/MAPK axis, provided a molecular basis for the role of TIMP-1 in cellular signaling. However, several lines of evidence suggest that TIMP-1 may be able to associate with many interaction partners, thus attaining multiple functions. To enable the identification of previously unknown interaction partners that may underpin the core cellular functions of TIMP-1, known as well as unknown, we performed a yeast two-hybrid screening using a mammary gland complementary DNA (cDNA) library. We report here the identification of multiple interactors, including MHC class II-associated invariant chain γ (CD74). We verified that CD74 interacts with TIMP-1 in breast cancer cells and that this interaction contributes to cellular internalization of TIMP-1 and mediates intracellular signaling through the Akt signaling axis in breast cancer cells. These data provide new insights into the complex nature of the functions of TIMP-1 and their potential mechanistic basis.

The Cancermuts software package for the prioritization of missense cancer variants: a case study of AMBRA1 in melanoma.

Cancer genomics and cancer mutation databases have made an available wealth of information about missense mutations found in cancer patient samples. Contextualizing by means of annotation and predicting the effect of amino acid change help identify which ones are more likely to have a pathogenic impact. Those can be validated by means of experimental approaches that assess the impact of protein mutations on the cellular functions or their tumorigenic potential. Here, we propose the integrative bioinformatic approach Cancermuts, implemented as a Python package. Cancermuts is able to gather known missense cancer mutations from databases such as cBioPortal and COSMIC, and annotate them with the pathogenicity score REVEL as well as information on their source. It is also able to add annotations about the protein context these mutations are found in, such as post-translational modification sites, structured/unstructured regions, presence of short linear motifs, and more. We applied Cancermuts to the intrinsically disordered protein AMBRA1, a key regulator of many cellular processes frequently deregulated in cancer. By these means, we classified mutations of AMBRA1 in melanoma, where AMBRA1 is highly mutated and displays a tumor-suppressive role. Next, based on REVEL score, position along the sequence, and their local context, we applied cellular and molecular approaches to validate the predicted pathogenicity of a subset of mutations in an in vitro melanoma model. By doing so, we have identified two AMBRA1 mutations which show enhanced tumorigenic potential and are worth further investigation, highlighting the usefulness of the tool. Cancermuts can be used on any protein targets starting from minimal information, and it is available at https://www.github.com/ELELAB/cancermuts as free software.

The Mutational Landscape of the Oncogenic MZF1 SCAN Domain in Cancer.

SCAN domains in zinc-finger transcription factors are crucial mediators of protein-protein interactions. Up to 240 SCAN-domain encoding genes have been identified throughout the human genome. These include cancer-related genes, such as the myeloid zinc finger 1 (MZF1), an oncogenic transcription factor involved in the progression of many solid cancers. The mechanisms by which SCAN homo- and heterodimers assemble and how they alter the transcriptional activity of zinc-finger transcription factors in cancer and other diseases remain to be investigated. Here, we provide the first description of the conformational ensemble of the MZF1 SCAN domain cross-validated against NMR experimental data, which are probes of structure and dynamics on different timescales. We investigated the protein-protein interaction network of MZF1 and how it is perturbed in different cancer types by the analyses of high-throughput proteomics and RNASeq data. Collectively, we integrated many computational approaches, ranging from simple empirical energy functions to all-atom microsecond molecular dynamics simulations and network analyses to unravel the effects of cancer-related substitutions in relation to MZF1 structure and interactions.