Identification of proximal SUMO-dependent interactors using SUMO-ID.

The fast dynamics and reversibility of posttranslational modifications by the ubiquitin family pose significant challenges for research. Here we present SUMO-ID, a technology that merges proximity biotinylation by TurboID and protein-fragment complementation to find SUMO-dependent interactors of proteins of interest. We develop an optimized split-TurboID version and show SUMO interaction-dependent labelling of proteins proximal to PML and RANGAP1. SUMO-dependent interactors of PML are involved in transcription, DNA damage, stress response and SUMO modification and are highly enriched in SUMO Interacting Motifs, but may only represent a subset of the total PML proximal proteome. Likewise, SUMO-ID also allow us to identify interactors of SUMOylated SALL1, a less characterized SUMO substrate. Furthermore, using TP53 as a substrate, we identify SUMO1, SUMO2 and Ubiquitin preferential interactors. Thus, SUMO-ID is a powerful tool that allows to study the consequences of SUMO-dependent interactions, and may further unravel the complexity of the ubiquitin code.

Phosphoinositide 3-Kinase-Regulated Pericyte Maturation Governs Vascular Remodeling.

BACKGROUND: Pericytes regulate vessel stabilization and function, and their loss is associated with diseases such as diabetic retinopathy or cancer. Despite their physiological importance, pericyte function and molecular regulation during angiogenesis remain poorly understood. METHODS: To decipher the transcriptomic programs of pericytes during angiogenesis, we crossed Pdgfrb(BAC)-CreERT2 mice into RiboTagflox/flox mice. Pericyte morphological changes were assessed in mural cell-specific R26-mTmG reporter mice, in which low doses of tamoxifen allowed labeling of single-cell pericytes at high resolution. To study the role of phosphoinositide 3-kinase (PI3K) signaling in pericyte biology during angiogenesis, we used genetic mouse models that allow selective inactivation of PI3Kα and PI3Kß isoforms and their negative regulator phosphate and tensin homolog deleted on chromosome 10 (PTEN) in mural cells. RESULTS: At the onset of angiogenesis, pericytes exhibit molecular traits of cell proliferation and activated PI3K signaling, whereas during vascular remodeling, pericytes upregulate genes involved in mature pericyte cell function, together with a remarkable decrease in PI3K signaling. Immature pericytes showed stellate shape and high proliferation, and mature pericytes were quiescent and elongated. Unexpectedly, we demonstrate that PI3Kß, but not PI3Kα, regulates pericyte proliferation and maturation during vessel formation. Genetic PI3Kß inactivation in pericytes triggered early pericyte maturation. Conversely, unleashing PI3K signaling by means of PTEN deletion delayed pericyte maturation. Pericyte maturation was necessary to undergo vessel remodeling during angiogenesis. CONCLUSIONS: Our results identify new molecular and morphological traits associated with pericyte maturation and uncover PI3Kß activity as a checkpoint to ensure appropriate vessel formation. In turn, our results may open new therapeutic opportunities to regulate angiogenesis in pathological processes through the manipulation of pericyte PI3Kß activity.

Targeting PML in triple negative breast cancer elicits growth suppression and senescence.

Oncogene addiction postulates that the survival and growth of certain tumor cells is dependent upon the activity of one oncogene, despite their multiple genetic and epigenetic abnormalities. This phenomenon provides a foundation for molecular targeted therapy and a rationale for oncogene-based stratification. We have previously reported that the Promyelocytic Leukemia protein (PML) is upregulated in triple negative breast cancer (TNBC) and it regulates cancer-initiating cell function, thus suggesting that this protein can be therapeutically targeted in combination with PML-based stratification. However, the effects of PML perturbation on the bulk of tumor cells remained poorly understood. Here we demonstrate that TNBC cells are addicted to the expression of this nuclear protein. PML inhibition led to a remarkable growth arrest combined with features of senescence in vitro and in vivo. Mechanistically, the growth arrest and senescence were associated to a decrease in MYC and PIM1 kinase levels, with the subsequent accumulation of CDKN1B (p27), a trigger of senescence. In line with this notion, we found that PML is associated to the promoter regions of MYC and PIM1, consistent with their direct correlation in breast cancer specimens. Altogether, our results provide a feasible explanation for the functional similarities of MYC, PIM1, and PML in TNBC and encourage further study of PML targeting strategies for the treatment of this breast cancer subtype.

Integrative analysis of transcriptomics and clinical data uncovers the tumor-suppressive activity of MITF in prostate cancer.

The dysregulation of gene expression is an enabling hallmark of cancer. Computational analysis of transcriptomics data from human cancer specimens, complemented with exhaustive clinical annotation, provides an opportunity to identify core regulators of the tumorigenic process. Here we exploit well-annotated clinical datasets of prostate cancer for the discovery of transcriptional regulators relevant to prostate cancer. Following this rationale, we identify Microphthalmia-associated transcription factor (MITF) as a prostate tumor suppressor among a subset of transcription factors. Importantly, we further interrogate transcriptomics and clinical data to refine MITF perturbation-based empirical assays and unveil Crystallin Alpha B (CRYAB) as an unprecedented direct target of the transcription factor that is, at least in part, responsible for its tumor-suppressive activity in prostate cancer. This evidence was supported by the enhanced prognostic potential of a signature based on the concomitant alteration of MITF and CRYAB in prostate cancer patients. In sum, our study provides proof-of-concept evidence of the potential of the bioinformatics screen of publicly available cancer patient databases as discovery platforms, and demonstrates that the MITF-CRYAB axis controls prostate cancer biology.

Cluster Locator, online analysis and visualization of gene clustering.

Summary: Genes sharing functions, expression patterns or quantitative traits are not randomly distributed along eukaryotic genomes. In order to study the distribution of genes that share a given feature, we present Cluster Locator, an online analysis and visualization tool. Cluster Locator determines the number, size and position of all the clusters formed by the protein-coding genes on a list according to a given maximum gap, the percentage of gene clustering of the list and its statistical significance. The output includes a visual representation of the distribution of genes and gene clusters along the reference genome. Availability and implementation: Cluster Locator is freely available at http://clusterlocator.bnd.edu.uy/. Supplementary information: Supplementary data are available at Bioinformatics online.

Erratum: The metabolic co-regulator PGC1α suppresses prostate cancer metastasis.

This corrects the article DOI: 10.1038/ncb3357.

Spatial intratumoural heterogeneity in the expression of GIT1 is associated with poor prognostic outcome in oestrogen receptor positive breast cancer patients with synchronous lymph node metastases.

Background: The outcome for oestrogen receptor positive (ER+) breast cancer patients has improved greatly in recent years largely due to targeted therapy. However, the presence of involved multiple synchronous lymph nodes remains associated with a poor outcome. Consequently, these patients would benefit from the identification of new prognostic biomarkers and therapeutic targets. The expression of G-protein-coupled receptor kinase-interacting protein 1 (GIT1) has recently been shown to be an indicator of advanced stage breast cancer. Therefore, we investigated its expression and prognostic value of GIT1 in a cohort of 140 ER+ breast cancer with synchronous lymph node involvement. Methods: Immunohistochemistry was employed to assess GIT1 expression in a tissue microarray (TMA) containing duplicate non-adjacent cores with matched primary tumour and lymph node tissue (n=140). GIT1 expression in tumour cells was scored and statistical correlation analyses were carried out. Results: The results revealed a sub-group of patients that displayed discordant expression of GIT1 between the primary tumour and the lymph nodes (i.e. spatial intratumoural heterogeneity). We observed that loss of GIT1 expression in the metastasis was associated with a shorter time to recurrence, poorer overall survival, and a shorter median survival time. Moreover, multivariate analysis demonstrated that GIT1 expression was an independent prognostic indicator. Conclusions: GIT1 expression enabled the identification of a sub-class of ER+ patients with lymph node metastasis that have a particularly poor prognostic outcome. We propose that this biomarker could be used to further stratify ER+ breast cancer patients with synchronous lymph node involvement and therefore facilitate adjuvant therapy decision making.

The metabolic co-regulator PGC1α suppresses prostate cancer metastasis.

Cellular transformation and cancer progression is accompanied by changes in the metabolic landscape. Master co-regulators of metabolism orchestrate the modulation of multiple metabolic pathways through transcriptional programs, and hence constitute a probabilistically parsimonious mechanism for general metabolic rewiring. Here we show that the transcriptional co-activator peroxisome proliferator-activated receptor gamma co-activator 1α (PGC1α) suppresses prostate cancer progression and metastasis. A metabolic co-regulator data mining analysis unveiled that PGC1α is downregulated in prostate cancer and associated with disease progression. Using genetically engineered mouse models and xenografts, we demonstrated that PGC1α opposes prostate cancer progression and metastasis. Mechanistically, the use of integrative metabolomics and transcriptomics revealed that PGC1α activates an oestrogen-related receptor alpha (ERRα)-dependent transcriptional program to elicit a catabolic state and metastasis suppression. Importantly, a signature based on the PGC1α-ERRα pathway exhibited prognostic potential in prostate cancer, thus uncovering the relevance of monitoring and manipulating this pathway for prostate cancer stratification and treatment.