In vivo genome-wide CRISPR screening identifies CITED2 as a driver of prostate cancer bone metastasis

Most cancer deaths are due to metastatic dissemination to distant organs. Bone is the most frequently affected organ in metastatic prostate cancer and a major cause of prostate cancer deaths. Yet, our partial understanding of the molecular factors that drive bone metastasis has been a limiting factor for developing preventative and therapeutic strategies to improve patient survival and well-being. Although recent studies have uncovered molecular alterations that occur in prostate cancer metastasis, their functional relevance for bone metastasis is not well understood. Using genome-wide CRISPR activation and inhibition screens we have identified multiple drivers and suppressors of prostate cancer metastasis. Through functional validation, including an innovative organ-on-a-chip invasion platform for studying bone tropism, our study identifies the transcriptional modulator CITED2 as a novel driver of prostate cancer bone metastasis and uncovers multiple new potential molecular targets for bone metastatic disease.

Distinct mesenchymal cell states mediate prostate cancer progression

In the complex tumor microenvironment (TME), mesenchymal cells are key players, yet their specific roles in prostate cancer (PCa) progression remain to be fully deciphered. This study employs single-cell RNA sequencing to delineate molecular changes in tumor stroma that influence PCa progression and metastasis. Analyzing mesenchymal cells from four genetically engineered mouse models (GEMMs) and correlating these findings with human tumors, we identify eight stromal cell populations with distinct transcriptional identities consistent across both species. Notably, stromal signatures in advanced mouse disease reflect those in human bone metastases, highlighting periostin's role in invasion and differentiation. From these insights, we derive a gene signature that predicts metastatic progression in localized disease beyond traditional Gleason scores. Our results illuminate the critical influence of stromal dynamics on PCa progression, suggesting new prognostic tools and therapeutic targets.

Distinct mesenchymal cell states mediate prostate cancer progression

Alterations in tumor stroma influence prostate cancer progression and metastatic potential. However, the molecular underpinnings of this stromal-epithelial crosstalk are largely unknown. Here, we compare mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for common and GEMM-specific transcriptional programs. We show that stromal responses are conserved in mouse models and human prostate cancers with the same genomic alterations. We noted striking similarities between the transcriptional profiles of the stroma of murine models of advanced disease and those of of human prostate cancer bone metastases. These profiles were then used to build a robust gene signature that can predict metastatic progression in prostate cancer patients with localized disease and is also associated with progression-free survival independent of Gleason score. Taken together, this offers new evidence that stromal microenvironment mediates prostate cancer progression, further identifying tissue-based biomarkers and potential therapeutic targets of aggressive and metastatic disease.

Distinct mesenchymal cell states mediate prostate cancer progression

Alterations in tumor stroma influence prostate cancer progression and metastatic potential. However, the molecular underpinnings of this stromal-epithelial crosstalk are largely unknown. Here, we compare mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for common and GEMM-specific transcriptional programs. We show that stromal responses are conserved in mouse models and human prostate cancers with the same genomic alterations. We noted striking similarities between the transcriptional profiles of the stroma of murine models of advanced disease and those of of human prostate cancer bone metastases. These profiles were then used to build a robust gene signature that can predict metastatic progression in prostate cancer patients with localized disease and is also associated with progression-free survival independent of Gleason score. Taken together, this offers new evidence that stromal microenvironment mediates prostate cancer progression, further identifying tissue-based biomarkers and potential therapeutic targets of aggressive and metastatic disease.

OncoLoop: A Network-Based Precision Cancer Medicine Framework

Prioritizing treatments for individual patients with cancer remains challenging, and performing coclinical studies using patient-derived models in real time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity (cognate) model(s) by leveraging drug perturbation profiles. As a proof of concept, we applied OncoLoop to prostate cancer using genetically engineered mouse models (GEMM) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of human prostate cancer cohorts by Master Regulator (MR) conservation analysis revealed that most patients with advanced prostate cancer were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated in allograft, syngeneic, and patient-derived xenograft (PDX) models of tumors and metastasis. Furthermore, OncoLoop-predicted drugs enhanced the efficacy of clinically relevant drugs, namely, the PD-1 inhibitor nivolumab and the AR inhibitor enzalutamide.

SIGNIFICANCE

OncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround coclinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. This article is highlighted in the In This Issue feature, p. 247.

Abstract 1905: Accelerating clinically-translatable discoveries using a network- and RNA-based precision-oncology framework

Despite recent advances, prioritizing therapy at the individual patient level remains challenging. In fact, inter-patient tumor heterogeneity remains one of the major challenges in cancer therapy, making it difficult to optimize available treatments on an individual patient basis. Likewise, the systematic prediction of drug sensitivity in vivo is still a major challenge in translational research, where targeted therapeutics are currently selected based on the presence of either actionable oncogene dependencies or aberrant cellular mechanisms. A further challenge is the limited availability of models that faithfully recapitulate the biology, complexity, and heterogeneity of human tumors, including their interaction with a conserved microenvironment and a competent immune system.

To address these challenges, we introduce OncoLoop, a highly-generalizable, network-based precision medicine framework to triangulate between available mouse models, human tumors, and large-scale drug perturbational assays with in vivo validation to predict personalized treatment. OncoLoop requires only transcriptomic data (i.e., RNA-seq profiles) and leverages regulatory network analysis to (a) identify cognate models based on conservation of patient-specific Master Regulator (MR) proteins and (b) prioritize drugs based on their ability to invert the activity of MR proteins (MR-inverters), using drug perturbation profiles in cognate cell lines. As proof-of-concept, we applied OncoLoop to prostate cancer using a series of genetically engineered mouse models (GEMMs) that capture a broad range of phenotypes, including metastatic, castration-resistant and neuroendocrine disease. Indeed, >70% of patients in published cohorts had at least one high-fidelity matched GEMM. Drugs targeting shared Master Regulator dependencies of a patient and its cognate GEMM(s) were predicted using perturbational profiles of >300 drugs in MR-matched cell lines, resulting in an 80% validation rate in GEMM allografts and human xenografts. This network-based approach is highly generalized and can be applied to both cancer and non-cancer-related contexts.

Citation Format: Alessandro Vasciaveo, Min Zou, Juan M. Arriaga, Francisca Nunes de Almeida, Eugene F. Douglass, Michael Shen, Andrea Califano, Cory Abate-Shen. Accelerating clinically-translatable discoveries using a network- and RNA-based precision-oncology framework [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1905.

Establishment of the LNCaP Cell Line - The Dawn of an Era for Prostate Cancer Research

Among the relatively few established human prostate cancer cell lines, LNCaP cells are unique in their ability to model key stages of prostate cancer progression. Analyses of LNCaP cells and their derivatives have been invaluable for elucidating important translational aspects of prostate tumorigenesis, metastasis, and drug response, particularly in the context of androgen receptor signaling. Here, we present major highlights from a wealth of literature that has exploited LNCaP cells and their derivatives to inform on prostate cancer progression and androgen response for improving the treatment of patients with prostate cancer. See related article by Horoszewicz and colleagues, Cancer Res 1983;43:1809-18.

Abstract LB247: A forward genetic screen to identify drivers of neuroendocrine prostate cancer

Neuroendocrine prostate cancer (NEPC) is a deadly variant of prostate cancer for which no cure is yet available. Up to 20 percent of the patients with castration resistant prostate cancer (CRPC), will progress to NEPC after treatment with standard-of-care therapies, such as abiraterone and enzalutamide, that target the androgen receptor (AR) pathway. However, the molecular mechanisms that drive the emergence of NEPC are largely unknown, contributing to a lack of treatment options for patients with NEPC. We implemented a forward genetic approach to identify novel drivers of NEPC, by using the Sleeping Beauty (SB) transposon-based forward genetic mutagenesis screening system in our Pten-, Trp53-deficient mouse model that is primed to develop NEPC at a low frequency. We generated a mouse strain (NPp53SBT2Onc) in which the Nkx3.1 promoter regulates the expression of tamoxifen-inducible Cre specifically in the mouse prostate epithelium, resulting in transposition of the T2Onc2 transposable element and conditional deletion of Pten and Trp53 in mouse prostate epithelium. We observed an increased NEPC incidence in our NPp53SBT2Onc mouse model compared to control mice without the transposon T2Onc2, suggesting that the SB-mediated insertional mutagenesis events are driving the development of NEPC. To elucidate the genetic events that are driving the observed NEPC phenotype, we identified the common insertion sites (CISs) of the transposon insertions, which revealed a total of 330 CIS-associated genes. We further performed an integrative analysis using RNA-seq data from our SB cohort, a second mouse dataset and a metastatic CRPC patient cohort, which allowed us to identify the Master Regulator (MR) proteins that are associated with NEPC, as well as the upstream genomic events that modulate these MRs and the emergence of NEPC. Altogether, our approach resulted in the identification of CIS-associated genes that are upstream of these MRs associated to NEPC and that are likely to drive this lethal subtype of prostate cancer. We will further validate and elucidate the role of these candidate genes in prostate cancer progression to NEPC, in both mouse and human using CRISPR technology. In summary, we have developed a Sleeping Beauty forward genetic screen in our mouse model of CRPC, which not only accelerates disease progression, but also increases the incidence of NEPC. Our integrative analysis identified a panel of CIS-associated genes that are likely to be functionally involved in progression to NEPC. Validation of candidate drivers resulting from our analysis will shed light on mechanisms that this aggressive disease uses to evade treatments and may inform the development of novel therapies.

Citation Format: Francisca Nunes de Almeida, Alessandro Vasciaveo, Min Zou, Matteo Di Bernardo, Andrea Califano, Cory Abate-Shen. A forward genetic screen to identify drivers of neuroendocrine prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB247.

Abstract 2: Addressing treatment resistance in models of lethal prostate cancer

Prostate cancer (PC) is the malignancy with the highest incidence worldwide in males. Although localized disease can be effectively treated and usually has a favorable prognosis, progression to metastasis results in high mortality rates as current treatment modalities are not yet curative. The standard of care for advanced PC is hormonal therapy, termed Androgen Deprivation Therapy (ADT). Unfortunately, ADT typically elicits the emergence of a lethal phenotype, termed Castration Resistant PC (CRPC), which is treatment-resistant and frequently gives rise to a highly aggressive variant with features of neuroendocrine differentiation, known as Neuroendocrine PC (NEPC). We used Genetically-Engineered Mouse Models (GEMMs) of CRPC to perform a forward genetic screening using the Sleeping Beauty (SB) transposon system. Specifically, we selected a GEMM with loss of function of both Pten and Trp53, since we previously demonstrated that this model is able to transdifferentiate to NEPC tumors under ADT pressure. Then, we generated a mouse strain in which the SB transposase expression is under the control of a tamoxifen-inducible Cre allele driven by the prostate-specific Nkx3.1 promoter. SB activation generated tumors with an accelerated growth phenotype, when compared to non-activated controls, that present histological features of NEPC. To elucidate these tumors' regulatory program, we harvested SB-barcoded DNA-Seq and RNA-Seq and performed an integrative analysis that links genomic alterations to downstream regulatory programs. Specifically, we used DNA data to recover genes in the proximity of integration patterns generated by SB-transposase random insertions, candidate to be initiator events that fostered the accelerated phenotype and the acquisition of NEPC features. We used RNA-Seq data to identify Master Regulator (MR) proteins responsible of NEPC cell identity. Next, we analyzed molecular data from cohorts of CRPC patients to reverse-engineer both regulatory network of Transcription Factors (TFs) and regulatory dependencies between signaling proteins and TFs activity. This analysis resulted in an NEPC regulatory network of candidate MR proteins and their upstream genomic events, that are likely to be responsible for this treatment-resistant phenotype. Notably, top hits from this analysis are known to be involved in the DNA repair machinery and the WNT pathway, but are not yet associated with lethal prostate cancer. Cross-species computational analysis of patient-specific MRs activity conservation between patients and our mice cohorts, aligned NEPC patients to mice tumors with NE differentiation features, corroborating our study's clinical relevance. In summary, we used in vivo models of prostate cancer to elucidate molecular drivers of NEPC, a lethal variant that is treatment-resistant. We are in the process of validating these results in vitro using the latest CRISPR technology.

Citation Format: Alessandro Vasciaveo, Francisca Nunes de Almeida, Min Zou, Matteo Di Bernardo, Andrea Califano, Cory Abate-Shen. Addressing treatment resistance in models of lethal prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2.

Cdc42 defines apical identity and regulates epithelial morphogenesis by promoting apical recruitment of Par6-aPKC and Crumbs

Cdc42 regulates epithelial morphogenesis together with the Par complex (Baz/Par3-Par6-aPKC), Crumbs (Crb/CRB3) and Stardust (Sdt/PALS1). However, how these proteins work together and interact during epithelial morphogenesis is not well understood. To address this issue, we used the genetically amenable Drosophila pupal photoreceptor and follicular epithelium. We show that during epithelial morphogenesis active Cdc42 accumulates at the developing apical membrane and cell-cell contacts, independently of the Par complex and Crb. However, membrane localization of Baz, Par6-aPKC and Crb all depend on Cdc42. We find that although binding of Cdc42 to Par6 is not essential for the recruitment of Par6 and aPKC to the membrane, it is required for their apical localization and accumulation, which we find also depends on Par6 retention by Crb. In the pupal photoreceptor, membrane recruitment of Par6-aPKC also depends on Baz. Our work shows that Cdc42 is required for this recruitment and suggests that this factor promotes the handover of Par6-aPKC from Baz onto Crb. Altogether, we propose that Cdc42 drives morphogenesis by conferring apical identity, Par-complex assembly and apical accumulation of Crb.

Regulation of Cdc42 and its effectors in epithelial morphogenesis

Cdc42 - a member of the small Rho GTPase family - regulates cell polarity across organisms from yeast to humans. It is an essential regulator of polarized morphogenesis in epithelial cells, through coordination of apical membrane morphogenesis, lumen formation and junction maturation. In parallel, work in yeast and Caenorhabditis elegans has provided important clues as to how this molecular switch can generate and regulate polarity through localized activation or inhibition, and cytoskeleton regulation. Recent studies have revealed how important and complex these regulations can be during epithelial morphogenesis. This complexity is mirrored by the fact that Cdc42 can exert its function through many effector proteins. In epithelial cells, these include atypical PKC (aPKC, also known as PKC-3), the P21-activated kinase (PAK) family, myotonic dystrophy-related Cdc42 binding kinase beta (MRCKβ, also known as CDC42BPB) and neural Wiskott-Aldrich syndrome protein (N-WASp, also known as WASL). Here, we review how the spatial regulation of Cdc42 promotes polarity and polarized morphogenesis of the plasma membrane, with a focus on the epithelial cell type.

Open data set of live cyanobacterial cells imaged using an X-ray laser

Structural studies on living cells by conventional methods are limited to low resolution because radiation damage kills cells long before the necessary dose for high resolution can be delivered. X-ray free-electron lasers circumvent this problem by outrunning key damage processes with an ultra-short and extremely bright coherent X-ray pulse. Diffraction-before-destruction experiments provide high-resolution data from cells that are alive when the femtosecond X-ray pulse traverses the sample. This paper presents two data sets from micron-sized cyanobacteria obtained at the Linac Coherent Light Source, containing a total of 199,000 diffraction patterns. Utilizing this type of diffraction data will require the development of new analysis methods and algorithms for studying structure and structural variability in large populations of cells and to create abstract models. Such studies will allow us to understand living cells and populations of cells in new ways. New X-ray lasers, like the European XFEL, will produce billions of pulses per day, and could open new areas in structural sciences.

Profilin connects actin assembly with microtubule dynamics

Profilin is a well-known regulator of actin filament formation. It indirectly associates with microtubules and influences their growth rate. Formins are the linker molecules, and the turnover of the actin microfilament system balances profilin association with the microtubules.

Profilin controls actin nucleation and assembly processes in eukaryotic cells. Actin nucleation and elongation promoting factors (NEPFs) such as Ena/VASP, formins, and WASP-family proteins recruit profilin:actin for filament formation. Some of these are found to be microtubule associated, making actin polymerization from microtubule-associated platforms possible. Microtubules are implicated in focal adhesion turnover, cell polarity establishment, and migration, illustrating the coupling between actin and microtubule systems. Here we demonstrate that profilin is functionally linked to microtubules with formins and point to formins as major mediators of this association. To reach this conclusion, we combined different fluorescence microscopy techniques, including superresolution microscopy, with siRNA modulation of profilin expression and drug treatments to interfere with actin dynamics. Our studies show that profilin dynamically associates with microtubules and this fraction of profilin contributes to balance actin assembly during homeostatic cell growth and affects micro­tubule dynamics. Hence profilin functions as a regulator of microtubule (+)-end turnover in addition to being an actin control element.