Antonina Mitrofanova

Lineage analysis of basal epithelial cells reveals their unexpected plasticity and supports a cell-of-origin model for prostate cancer heterogeneity

A key issue in cancer biology is whether oncogenic transformation of different cell types of origin within an adult tissue gives rise to distinct tumour subtypes that differ in their prognosis and/or treatment response. We now show that initiation of prostate tumours in basal or luminal epithelial cells in mouse models results in tumours with distinct molecular signatures that are predictive of human patient outcomes. Furthermore, our analysis of untransformed basal cells reveals an unexpected assay dependence of their stem cell properties in sphere formation and transplantation assays versus genetic lineage tracing during prostate regeneration and adult tissue homeostasis. Although oncogenic transformation of basal cells gives rise to tumours with luminal phenotypes, cross-species bioinformatic analyses indicate that tumours of luminal origin are more aggressive than tumours of basal origin, and identify a molecular signature associated with patient outcome. Our results reveal the inherent plasticity of basal cells, and support a model in which different cells of origin generate distinct molecular subtypes of prostate cancer.

Cross-Species Regulatory Network Analysis Identifies a Synergistic Interaction between FOXM1 and CENPF that Drives Prostate Cancer Malignancy

To identify regulatory drivers of prostate cancer malignancy, we have assembled genome-wide regulatory networks (interactomes) for human and mouse prostate cancer from expression profiles of human tumors and of genetically engineered mouse models, respectively. Cross-species computational analysis of these interactomes has identified FOXM1 and CENPF as synergistic master regulators of prostate cancer malignancy. Experimental validation shows that FOXM1 and CENPF function synergistically to promote tumor growth by coordinated regulation of target gene expression and activation of key signaling pathways associated with prostate cancer malignancy. Furthermore, co-expression of FOXM1 and CENPF is a robust prognostic indicator of poor survival and metastasis. Thus, genome-wide cross-species interrogation of regulatory networks represents a valuable strategy to identify causal mechanisms of human cancer.

B-Raf Activation Cooperates with PTEN Loss to Drive c-Myc Expression in Advanced Prostate Cancer

Both the PI3K → Akt → mTOR and mitogen-activated protein kinase (MAPK) signaling pathways are often deregulated in prostate tumors with poor prognosis. Here we describe a new genetically engineered mouse model of prostate cancer in which PI3K-Akt-mTOR signaling is activated by inducible disruption of PTEN, and extracellular signal-regulated kinase 1/2 (ERK1/2) MAPK signaling is activated by inducible expression of a BRAF(V600E) oncogene. These tissue-specific compound mutant mice develop lethal prostate tumors that are inherently resistant to castration. These tumors bypass cellular senescence and disseminate to lymph nodes, bone marrow, and lungs where they form overt metastases in approximately 30% of the cases. Activation of PI3K → Akt → mTOR and MAPK signaling pathways in these prostate tumors cooperate to upregulate c-Myc. Accordingly, therapeutic treatments with rapamycin and PD0325901 to target these pathways, respectively, attenuate c-Myc levels and reduce tumor and metastatic burden. Together, our findings suggest a generalized therapeutic approach to target c-Myc activation in prostate cancer by combinatorial targeting of the PI3K → Akt → mTOR and ERK1/2 MAPK signaling pathways.

ETV4 promotes metastasis in response to activation of PI3-kinase and Ras signaling in a mouse model of advanced prostate cancer

Significance Although locally invasive prostate cancer is nearly always curable, metastatic prostate cancer usually results in lethality. Our study investigates the temporal progression and molecular mechanisms underlying prostate cancer metastasis using a new genetically engineered mouse model. Using lineage-tracing analyses, we show that dissemination of tumor cells occurs early in cancer progression, and well before the occurrence of metastases. We further show that metastasis is temporally coincident with expression of the oncogenic ETS gene Etv4, and that Etv4 promotes prostate cancer metastasis in vivo. Our findings suggest that Etv4 may be a target for therapeutic intervention in metastatic prostate cancer. Combinatorial activation of PI3-kinase and RAS signaling occurs frequently in advanced prostate cancer and is associated with adverse patient outcome. We now report that the oncogenic Ets variant 4 (Etv4) promotes prostate cancer metastasis in response to coactivation of PI3-kinase and Ras signaling pathways in a genetically engineered mouse model of highly penetrant, metastatic prostate cancer. Using an inducible Cre driver to simultaneously inactivate Pten while activating oncogenic Kras and a fluorescent reporter allele in the prostate epithelium, we performed lineage tracing in vivo to define the temporal and spatial occurrence of prostate tumors, disseminated tumor cells, and metastases. These analyses revealed that though disseminated tumors cells arise early following the initial occurrence of prostate tumors, there is a significant temporal lag in metastasis, which is temporally coincident with the up-regulation of Etv4 expression in primary tumors. Functional studies showed that knockdown of Etv4 in a metastatic cell line derived from the mouse model abrogates the metastatic phenotype but does not affect tumor growth. Notably, expression and activation of ETV4, but not other oncogenic ETS genes, is correlated with activation of both PI3-kinase and Ras signaling in human prostate tumors and metastases. Our findings indicate that ETV4 promotes metastasis in prostate tumors that have activation of PI3-kinase and Ras signaling, and therefore, ETV4 represents a potential target of therapeutic intervention for metastatic prostate cancer.

Dual targeting of the Akt/mTOR signaling pathway inhibits castration-resistant prostate cancer in a genetically engineered mouse model

Although the prognosis for clinically localized prostate cancer is now favorable, there are still no curative treatments for castration-resistant prostate cancer (CRPC) and, therefore, it remains fatal. In this study, we investigate a new therapeutic approach for treatment of CRPC, which involves dual targeting of a major signaling pathway that is frequently deregulated in the disease. We found that dual targeting of the Akt and mTOR signaling pathways with their respective inhibitors, MK-2206 and ridaforolimus (MK-8669), is highly effective for inhibiting CRPC in preclinical studies in vivo using a refined genetically engineered mouse model of the disease. The efficacy of the combination treatment contrasts with their limited efficacy as single agents, since delivery of MK-2206 or MK-8669 individually had a modest impact in vivo on the overall tumor phenotype. In human prostate cancer cell lines, although not in the mouse model, the synergistic actions of MK-2206 and ridaforolimus (MK-8669) are due in part to limiting the mTORC2 feedback activation of Akt. Moreover, the effects of these drugs are mediated by inhibition of cellular proliferation via the retinoblastoma (Rb) pathway. Our findings suggest that dual targeting of the Akt and mTOR signaling pathways using MK-2206 and ridaforolimus (MK-8669) may be effective for treatment of CRPC, particularly for patients with deregulated Rb pathway activity.

Testing disjointness of private datasets

Two parties, say Alice and Bob, possess two sets of elements that belong to a universe of possible values and wish to test whether these sets are disjoint or not. In this paper we consider the above problem in the setting where Alice and Bob wish to disclose no information to each other about their sets beyond the single bit: “whether the intersection is empty or not.” This problem has many applications in commercial settings where two mutually distrustful parties wish to decide with minimum possible disclosure whether there is any overlap between their private datasets. We present three protocols that solve the above problem that meet different efficiency and security objectives and data representation scenarios. Our protocols are based on Homomorphic encryption and in our security analysis, we consider the semi-honest setting as well as the malicious setting. Our most efficient construction for a large universe in terms of overall communication complexity uses a new encryption primitive that we introduce called “superposed encryption.” We formalize this notion and provide a construction that may be of independent interest. For dealing with the malicious adversarial setting we take advantage of recent efficient constructions of Universally-Composable commitments based on verifiable encryption as well as zero-knowledge proofs of language membership.

Transdifferentiation as a Mechanism of Treatment Resistance in a Mouse Model of Castration-resistant Prostate Cancer

Current treatments for castration-resistant prostate cancer (CRPC) that target androgen receptor (AR) signaling improve patient survival, yet ultimately fail. Here, we provide novel insights into treatment response for the antiandrogen abiraterone by analyses of a genetically engineered mouse (GEM) model with combined inactivation of Trp53 and Pten, which are frequently comutated in human CRPC. These NPp53 mice fail to respond to abiraterone and display accelerated progression to tumors resembling treatment-related CRPC with neuroendocrine differentiation (CRPC-NE) in humans. Cross-species computational analyses identify master regulators of adverse response that are conserved with human CRPC-NE, including the neural differentiation factor SOX11, which promotes neuroendocrine differentiation in cells derived from NPp53 tumors. Furthermore, abiraterone-treated NPp53 prostate tumors contain regions of focal and/or overt neuroendocrine differentiation, distinguished by their proliferative potential. Notably, lineage tracing in vivo provides definitive and quantitative evidence that focal and overt neuroendocrine regions arise by transdifferentiation of luminal adenocarcinoma cells. These findings underscore principal roles for TP53 and PTEN inactivation in abiraterone resistance and progression from adenocarcinoma to CRPC-NE by transdifferentiation.Significance: Understanding adverse treatment response and identifying patients likely to fail treatment represent fundamental clinical challenges. By integrating analyses of GEM models and human clinical data, we provide direct genetic evidence for transdifferentiation as a mechanism of drug resistance as well as for stratifying patients for treatment with antiandrogens. Cancer Discov; 7(7); 736-49. ©2017 AACR.See related commentary by Sinha and Nelson, p. 673This article is highlighted in the In This Issue feature, p. 653.

Identification of an NKX3.1-G9a-UTY transcriptional regulatory network that controls prostate differentiation

Clues to cancer from an identity change The prostate and seminal vesicle have closely related developmental histories and both are regulated by the same androgenic hormones. A better understanding of the molecular mechanisms controlling the development of the two tissues could help solve why cancer arises frequently in the prostate but only rarely in seminal vesicles. Working with cell and mouse models, Dutta et al. show that forced expression of a single gene, the homeobox gene NKX3.1, causes seminal vesicle epithelium to differentiate into prostate. NKX3.1 regulates the expression of a gene program associated with prostate differentiation by interacting with the G9a histone methyltransferase. Disruption of this regulatory network probably contributes to prostate cancer development. Science, this issue p. 1576 A single gene can convert seminal vesicle epithelium into prostate tissue, a finding that may yield clues to prostate cancer. The NKX3.1 homeobox gene plays essential roles in prostate differentiation and prostate cancer. We show that loss of function of Nkx3.1 in mouse prostate results in down-regulation of genes that are essential for prostate differentiation, as well as up-regulation of genes that are not normally expressed in prostate. Conversely, gain of function of Nkx3.1 in an otherwise fully differentiated nonprostatic mouse epithelium (seminal vesicle) is sufficient for respecification to prostate in renal grafts in vivo. In human prostate cells, these activities require the interaction of NKX3.1 with the G9a histone methyltransferase via the homeodomain and are mediated by activation of target genes such as UTY (KDM6c), the male-specific paralog of UTX (KDM6a). We propose that an NKX3.1-G9a-UTY transcriptional regulatory network is essential for prostate differentiation, and we speculate that disruption of such a network predisposes to prostate cancer.

Efficient and robust prediction algorithms for protein complexes using Gomory-Hu trees.

Two-Hybrid (Y2H) Protein-Protein interaction (PPI) data suffer from high False Positive and False Negative rates, thus making searching for protein complexes in PPI networks a challenge. To overcome these limitations, we propose an efficient approach which measures connectivity between proteins not by edges, but by edge-disjoint paths. We model the number of edge-disjoint paths as a network flow and efficiently represent it in a Gomory-Hu tree. By manipulating the tree, we are able to isolate groups of nodes sharing more edge-disjoint paths with each other than with the rest of the network, which are our putative protein complexes. We examine the performance of our algorithm with Variation of Information and Separation measures and show that it belongs to a group of techniques which are robust against increased false positive and false negative rates. We apply our approach to yeast , mouse, worm, and human Y2H PPI networks, where it shows promising results. On yeast network, we identify 38 statistically significant protein clusters, 20 of which correspond to protein complexes and 16 to functional modules.

Syntax-Driven private evaluation of quantified membership queries

Membership queries are basic predicate operations that apply to datasets. Quantifications of such queries express global properties between datasets, including subset inclusion and disjointness. These operations are basic tools in set-theoretic data-mining procedures such as frequent-itemset-mining. In this work we formalize a family of such queries syntactically and we consider how they can be evaluated in a privacy-preserving fashion. We present a syntax-driven compiler that produces a protocol for each query and we show that semantically such queries correspond to basic set operation predicates between datasets. Using our compiler and based on the fact that it is syntax-driven, two parties can generate various privacy-preserving protocols with different complexity behavior that allow them to efficiently and securely evaluate the predicate of interest without sharing information about the datasets they possess. Our compiler sheds new light on the complexity of privacy-preserving evaluation of predicates such as disjointness and subset-inclusion and achieves substantial complexity improvements compared to previous works in terms of round as well as communication complexity. In particular, among others, we present protocols for both predicates that require one-round of interaction and have communication less than the size of the universe, while previously the only one round protocols known had communication proportional to the size of the universe.