Robots as models of evolving systems.

Experimental robobiological physics can bring insights into biological evolution. We present a development of hybrid analog/digital autonomous robots with mutable diploid dominant/recessive 6-byte genomes. The robots are capable of death, rebirth, and breeding. We map the quasi-steady-state surviving local density of the robots onto a multidimensional abstract "survival landscape." We show that robot death in complex, self-adaptive stress landscapes proceeds by a general lowering of the robotic genetic diversity, and that stochastically changing landscapes are the most difficult to survive.

Dormant cancer cells: programmed quiescence, senescence, or both?

Metastasis is the overwhelming driver of cancer mortality, accounting for the majority of cancer deaths. Many patients present with metastatic relapse years after eradication of the primary lesion. Disseminated cancer cells can undergo a durable proliferative arrest and lie dormant in secondary tissues before reentering the cell cycle to seed these lethal relapses. This process of cancer cell dormancy remains poorly understood, largely due to difficulties in studying these dormant cells. In the face of these challenges, the application of knowledge from the cellular senescence and quiescence fields may help to guide future thinking on the study of dormant cancer cells. Both senescence and quiescence are common programs of proliferative arrest that are integral to tissue development and homeostasis. Despite phenotypic differences, these two states also share common characteristics, and both likely play a role in cancer dormancy and delayed metastatic relapse. Understanding the cell biology behind these states, their overlaps and unique characteristics is critical to our future understanding of dormant cancer cells, as these cells likely employ some of the same molecular programs to promote survival and dissemination. In this review, we highlight the biology underlying these non-proliferative states, relate this knowledge to what we currently know about dormant cancer cells, and discuss implications for future work toward targeting these elusive metastatic seeds.

Cancer cells employ lipid droplets to survive toxic stress.

BACKGROUND: Lipid reprogramming is a known mechanism to increase the energetic demands of proliferating cancer cells to drive and support tumorigenesis and progression. Elevated lipid droplets (LDs) are a well-known alteration of lipid reprogramming in many cancers, including prostate cancer (PCa), and are associated with high tumor aggressiveness as well as therapy resistance. The mechanism of LD accumulation and specific LD functions are still not well understood; however, it has been shown that LDs can form as a protective mechanism against lipotoxicity and lipid peroxidation in the cell. METHODS: This study investigated the significance of LDs in PCa. This was done by staining, imaging, image quantification, and flow cytometry analysis of LDs in PCa cells. Additionally, lipidomics and metabolomics experiments were performed to assess the difference of metabolites and lipids in control and treatment surviving cancer cells. Lastly, to assess clinical significance, multiple publicly available datasets were mined for LD-related data. RESULTS: Our study demonstrated that prostate and breast cancer cells that survive 72 h of chemotherapy treatment have elevated LDs. These LDs formed in tandem with elevated reactive oxygen species levels to sequester damaged and excess lipids created by oxidative stress, which promoted cell survival. Additionally, by inhibiting diacylglycerol O-acyltransferase 1 (DGAT1) (which catalyzes triglyceride synthesis into LDs) and treating with chemotherapy simultaneously, we were able to decrease the overall amount of LDs and increase cancer cell death compared to treating with chemotherapy alone. CONCLUSIONS: Overall, our study proposes a potential combination therapy of DGAT1 inhibitors and chemotherapy to increase cancer cell death.

Presence of cells in the polyaneuploid cancer cell (PACC) state predicts the risk of recurrence in prostate cancer.

BACKGROUND: The nonproliferating polyaneuploid cancer cell (PACC) state is associated with therapeutic resistance in cancer. A subset of cancer cells enters the PACC state by polyploidization and acts as cancer stem cells by undergoing depolyploidization and repopulating the tumor cell population after the therapeutic stress is relieved. Our aim was to systematically assess the presence and importance of this entity in men who underwent radical prostatectomy with curative intent to treat their presumed localized prostate cancer (PCa). MATERIALS AND METHODS: Men with National Comprehensive Cancer Network intermediate- or high-risk PCa who underwent radical prostatectomy l from 2007 to 2015 and who did not receive neoadjuvant treatment were included. From the cohort of 2159 patients, the analysis focused on a subcohort of 209 patients and 38 cases. Prostate tissue microarrays (TMAs) were prepared from formalin-fixed, paraffin-embedded blocks of the radical prostatectomy specimens. A total of 2807 tissue samples of matched normal/benign and cancer were arrayed in nine TMA blocks. The presence of PACCs and the number of PACCs on each core were noted. RESULTS: The total number of cells in the PACC state and the total number of cores with PACCs were significantly correlated with increasing Gleason score (p = 0.0004) and increasing Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) (p = 0.004), but no other variables. In univariate proportional hazards models of metastasis-free survival, year of surgery, Gleason score (9-10 vs. 7-8), pathology stage, CAPRA-S, total PACCs, and cores positive for PACCs were all statistically significant. The multivariable models with PACCs that gave the best fit included CAPRA-S. Adding either total PACCs or cores positive for PACCs to CAPRA-S both significantly improved model fit compared to CAPRA-S alone. CONCLUSION: Our findings show that the number of PACCs and the number of cores positive for PACCs are statistically significant prognostic factors for metastasis-free survival, after adjusting for CAPRA-S, in a case-cohort of intermediate- or high-risk men who underwent radical prostatectomy. In addition, despite the small number of men with complete data to evaluate time to metastatic castration-resistant PCa (mCRPC), the total number of PACCs was a statistically significant predictor of mCRPC in univariate analysis and suggested a prognostic effect even after adjusting for CAPRA-S.

Optimized data-independent acquisition approach for proteomic analysis at single-cell level.

BACKGROUND: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. METHODS: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. RESULTS: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. CONCLUSIONS: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

Interplay between Cell Death and Cell Proliferation Reveals New Strategies for Cancer Therapy.

Cell division and cell death are fundamental processes governing growth and development across the tree of life. This relationship represents an evolutionary link between cell cycle and cell death programs that is present in all cells. Cancer is characterized by aberrant regulation of both, leading to unchecked proliferation and replicative immortality. Conventional anti-cancer therapeutic strategies take advantage of the proliferative dependency of cancer yet, in doing so, are triggering apoptosis, a death pathway to which cancer is inherently resistant. A thorough understanding of how therapeutics kill cancer cells is needed to develop novel, more durable treatment strategies. While cancer evolves cell-intrinsic resistance to physiological cell death pathways, there are opportunities for cell cycle agnostic forms of cell death, for example, necroptosis or ferroptosis. Furthermore, cell cycle independent death programs are immunogenic, potentially licensing host immunity for additional antitumor activity. Identifying cell cycle independent vulnerabilities of cancer is critical for developing alternative strategies that can overcome therapeutic resistance.

Characterization of tumor-associated macrophages in prostate cancer transgenic mouse models.

BACKGROUND: Tumor-associated macrophages (TAMs) are critical components of the tumor microenvironment (TME) in prostate cancer. Commonly used orthotopic models do not accurately reflect the complete TME of a human patient or the natural initiation and progression of a tumor. Therefore, genetically engineered mouse models are essential for studying the TME as well as advancing TAM-targeted therapies. Two common transgenic (TG) models of prostate cancer are Hi-Myc and transgenic adenocarcinoma of the mouse prostate (TRAMP), but the TME and TAM characteristics of these models have not been well characterized. METHODS: To advance the Hi-Myc and TRAMP models as tools for TAM studies, macrophage infiltration and characteristics were assessed using histopathologic, flow cytometric, and expression analyses in these models at various timepoints during tumor development and progression. RESULTS: In both Hi-Myc and TRAMP models, macrophages adopt a more pro-tumor phenotype in higher histological grade tumors and in older prostate tissue. However, the Hi-Myc and TRAMP prostates differ in their macrophage density, with Hi-Myc tumors exhibiting increased macrophage density and TRAMP tumors exhibiting decreased macrophage density compared to age-matched wild type mice. CONCLUSIONS: The macrophage density and the adenocarcinoma cancer subtype of Hi-Myc appear to better mirror patient tumors, suggesting that the Hi-Myc model is the more appropriate in vivo TG model for studying TAMs and TME-targeted therapies.

High-Throughput Simultaneous mRNA Profiling Using nCounter Technology Demonstrates That Extracellular Vesicles Contain Different mRNA Transcripts Than Their Parental Prostate Cancer Cells.

Extracellular vesicles (EVs) are nano-sized lipid bilayer encapsulated particles with a molecular cargo that appears to play important roles within the human body, such as in cell-to-cell communication. Unraveling the composition of EV cargos remains one of the most fundamental steps toward understanding the role of EVs in intercellular communication and the discovery of new biomarkers. One of the unmet needs in this field is the lack of a robust, sensitive, and multiplexed method for EV mRNA profiling. We established a new protocol using the NanoString low RNA input nCounter assay by which the targeted mRNA transcripts in EVs can be efficiently and specifically amplified and then assayed for 770 mRNAs in one reaction. Prostate cancer cells with epithelial (PC3-Epi) or mesenchymal (PC3-EMT) phenotypes and their progeny EVs were analyzed by the same panel. Among these mRNAs, 157 were detected in PC3-Epi EVs and 564 were detected in PC3-EMT EVs. NOTCH1 was the most significantly abundant mRNA transcripts in PC3-EMT EVs compared to PC3-Epi EVs. Our results demonstrated that when cells undergo epithelial-to-mesenchymal transition (EMT), a more active loading of cancer progression-related mRNA transcripts may occur. The mRNA cargos of EVs derived from mesenchymal prostate cancer cells may contribute to the pro-EMT function. We found that mRNA transcripts are different in progeny EVs compared to parental cells. EV cargos are not completely reflective of their cell origin, and the underlying mechanism of cargo sorting is complicated and needs to be further elucidated.

It doesn't always pay to be fit: success landscapes.

Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.

The combination of size-based separation and selection-free technology provides higher circulating tumour cells detection sensitivity than either method alone in patients with metastatic prostate cancer.

OBJECTIVE: To investigate the circulating tumour cells (CTCs) capture abilities of two technologies that are not dependent on cell-surface marker expression: a selection-free platform [AccuCyte® -CyteFinder® system (Rarecyte)] and a size-based platform [fluid-assisted separation technology (FAST)]. In addition, the combination of the two systems to more completely assess CTCs was investigated. PATIENTS AND METHODS: In all, 28 patients with metastatic prostate cancer were included. Two 6 mL peripheral blood samples were taken from each patient at the same time-point. The samples were then subjected to the two different technology platforms in parallel. An additional group of samples was acquired by applying the waste chamber material from the FAST-group tests (flow-through that goes through the FAST filter membrane) to the Rarecyte system for the detection any CTCs that were not captured by FAST. RESULTS: The three groups had significantly different putative CTC-positive tests, with positive rates of 29% for Rarecyte, 57% for FAST, and 79% for the combination. We also assessed CTC phenotype: 56.6% of the CTCs were cytokeratin (CK)+/epithelial cell adhesion molecule (EpCAM)-, 3.1% were CK-/EpCAM+, and 40.3% were CK+/EPCAM+. The captured CTCs diameter ranged from 5.2 to 16.9 µm. The mean CTC size from the FAST waste chamber was significantly smaller. The diameters for each of the phenotypic groups were significantly different. CONCLUSIONS: These data highlight disparities in the positive rates and enumerated CTC numbers detected by the two techniques. Notably, the combination of the two technologies resulted in the highest CTC-capture rates. Smaller CTCs were more likely to be missed by the FAST as they passed through the filter system. Sizes of CTCs varied with different cell surface marker phenotypes.

Cancer Cells and M2 Macrophages: Cooperative Invasive Ecosystem Engineers.

Many aspects of cancer can be explained utilizing well-defined ecological principles. Applying these principles to cancer, cancer cells are an invasive species to a healthy organ ecosystem. In their capacity as ecosystem engineers, cancer cells release cytokines that recruit monocytes to the tumor and polarize them to M2-like protumor macrophages. Macrophages, recruited by the cancer cells, act as a secondary invasive species. The ecosystem engineering functions of M2-macrophages in turn support and stimulate cancer cell survival and proliferation. The cooperative ecosystem engineering of both the primary invasive species of the cancer cell and the secondary invasive species of the M2-macrophage thus creates a vicious cycle of tumor promotion. Targeting a specific aspect of this tumor-promoting ecosystem engineering, such as blocking efferocytosis by M2-like macrophages, may improve the response to standard-of-care anticancer therapies. This strategy has the potential to redirect cooperative protumor ecosystem engineering toward an antitumor ecosystem engineering strategy.

Analysis of the Circulating Tumor Cell Capture Ability of a Slit Filter-Based Method in Comparison to a Selection-Free Method in Multiple Cancer Types.

Circulating tumor cells (CTCs) are a promising biomarker for cancer liquid biopsy. To evaluate the CTC capture bias and detection capability of the slit filter-based CTC isolation platform (CTC-FIND), we prospectively compared it head to head to a selection-free platform (AccuCyte®-CyteFinder® system). We used the two methods to determine the CTC counts, CTC positive rates, CTC size distributions, and CTC phenotypes in 36 patients with metastatic cancer. Between the two methods, the median CTC counts were not significantly different and the total counts were correlated (r = 0.63, p < 0.0001). The CTC positive rate by CTC-FIND was significantly higher than that by AccuCyte®-CyteFinder® system (91.7% vs. 66.7%, p < 0.05). The median diameter of CTCs collected by CTC-FIND was significantly larger (13.0 µm, range 5.2-52.0 vs. 10.4 µm, range 5.2-44.2, p < 0.0001). The distributions of CTC phenotypes (CK+EpCAM+, CK+EpCAM- or CK-EpCAM+) detected by both methods were similar. These results suggested that CTC-FIND can detect more CTC-positive cases but with a bias toward large size of CTCs.

Optimization of prostate cancer cell detection using multiplex tyramide signal amplification.

Approximately 29 000 men die of prostate cancer (PCa) each year in the United States, and 90% to 100% of them are due to incurable bone metastasis. It is difficult to determine (1) when PCa disseminates in the natural history of the disease; (2) where cancer cell disseminates before becoming overt metastatic lesions; and (3) which tumors are aggressive and which are indolent. Tumor tissue and liquid (blood and bone marrow) biopsies provide important information to answer these questions, but significant limitations exist for immunostaining strategies that assess protein expression in these tissues. Classic immunohistochemistry (IHC) assays can typically assess expression of one or two proteins per tissue section. We have developed a novel immunofluorescence staining protocol to detect a panel of seven proteins on PCa tissue from primary tumor biopsies and metastatic lesion autopsy tissue, as well as cancer cells from liquid biopsies. We used a tyramide-based system to amplify the true signal and optimized the protocol to reduce background signal, thereby boosting the signal-to-noise ratio. Any protein-specific antibody in this protocol can be exchanged for a different validated antibody. This protocol therefore, represents a highly informative and flexible assay that can be used to provide important information about cancer tissue for the purpose of improving detection, diagnosis, and treatment.

Targeting Tyro3, Axl and MerTK (TAM receptors): implications for macrophages in the tumor microenvironment.

Tumor-associated macrophages are an abundant cell type in the tumor microenvironment. These macrophages serve as a promising target for treatment of cancer due to their roles in promoting cancer progression and simultaneous immunosuppression. The TAM receptors (Tyro3, Axl and MerTK) are promising therapeutic targets on tumor-associated macrophages. The TAM receptors are a family of receptor tyrosine kinases with shared ligands Gas6 and Protein S that skew macrophage polarization towards a pro-tumor M2-like phenotype. In macrophages, the TAM receptors also promote apoptotic cell clearance, a tumor-promoting process called efferocytosis. The TAM receptors bind the "eat-me" signal phosphatidylserine on apoptotic cell membranes using Gas6 and Protein S as bridging ligands. Post-efferocytosis, macrophages are further polarized to a pro-tumor M2-like phenotype and secrete increased levels of immunosuppressive cytokines. Since M2 polarization and efferocytosis are tumor-promoting processes, the TAM receptors on macrophages serve as exciting targets for cancer therapy. Current TAM receptor-directed therapies in preclinical development and clinical trials may have anti-cancer effects though impacting macrophage phenotype and function in addition to the cancer cells.

Polyploid giant cancer cells: Unrecognized actuators of tumorigenesis, metastasis, and resistance.

Cancer led to the deaths of more than 9 million people worldwide in 2018, and most of these deaths were due to metastatic tumor burden. While in most cases, we still do not know why cancer is lethal, we know that a total tumor burden of 1 kg-equivalent to one trillion cells-is not compatible with life. While localized disease is curable through surgical removal or radiation, once cancer has spread, it is largely incurable. The inability to cure metastatic cancer lies, at least in part, to the fact that cancer is resistant to all known compounds and anticancer drugs. The source of this resistance remains undefined. In fact, the vast majority of metastatic cancers are resistant to all currently available anticancer therapies, including chemotherapy, hormone therapy, immunotherapy, and systemic radiation. Thus, despite decades-even centuries-of research, metastatic cancer remains lethal and incurable. We present historical and contemporary evidence that the key actuators of this process-of tumorigenesis, metastasis, and therapy resistance-are polyploid giant cancer cells.

Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration.

BACKGROUND: Epithelial to mesenchymal transition (EMT) is the process by which stationary epithelial cells transdifferentiate to mesenchymal cells with increased motility. EMT is integral in early stages of development and wound healing. Studies have shown that EMT could be a critical early event in tumor metastasis that is involved in acquisition of migratory and invasive properties in multiple carcinomas. METHODS: In this study, we used 15 published gene expression microarray datasets from Gene Expression Omnibus (GEO) that represent 12 cell lines from 6 cancer types across 95 observations (45 unique samples and 50 replicates) with different modes of induction of EMT or the reverse transition, mesenchymal to epithelial transition (MET). We integrated multiple gene expression datasets while considering study differences, batch effects, and noise in gene expression measurements. A universal differential EMT gene list was obtained by normalizing and correcting the data using four approaches, computing differential expression from each, and identifying a consensus ranking. We confirmed our discovery of novel EMT genes at mRNA and protein levels in an in vitro EMT model of prostate cancer - PC3 epi, EMT and Taxol resistant cell lines. We validate our discovery of C1orf116 as a novel EMT regulator by siRNA knockdown of C1orf116 in PC3 epithelial cells. RESULTS: Among differentially expressed genes, we found known epithelial and mesenchymal marker genes such as CDH1 and ZEB1. Additionally, we discovered genes known in a subset of carcinomas that were unknown in prostate cancer. This included epithelial specific LSR and S100A14 and mesenchymal specific DPYSL3. Furthermore, we also discovered novel EMT genes including a poorly-characterized gene C1orf116. We show that decreased expression of C1orf116 is associated with poor prognosis in lung and prostate cancer patients. We demonstrate that knockdown of C1orf116 expression induced expression of mesenchymal genes in epithelial prostate cancer cell line PC3-epi cells, suggesting it as a candidate driver of the epithelial phenotype. CONCLUSIONS: This comprehensive approach of statistical analysis and functional validation identified global expression patterns in EMT and candidate regulatory genes, thereby both extending current knowledge and identifying novel drivers of EMT.

Punctuational evolution is pervasive in distal site metastatic colonization.

The evolution of metastasis represents a lethal stage of cancer progression. Yet, the evolutionary kinetics of metastatic disease remain unresolved. Here, using single cell CRISPR-Cas9 lineage tracing data, we show that in metastatic disease, gradual molecular evolution is punctuated by episodes of rapid evolutionary change associated with lineage divergence. By measuring punctuational effects across the metastatic cascade, we show that punctuational effects contribute more to the molecular diversity at distal site metastases compared to the paired primary tumor, suggesting qualitatively different modes of evolution may drive primary and metastatic tumor progression. This is the first empirical evidence for distinct patterns of molecular evolution at early and late stages of metastasis and demonstrates the complex interplay of cell intrinsic and extrinsic factors that shape lethal cancer.

Multiparameter flow cytometric detection and analysis of rare cells in in vivo models of cancer metastasis.

Rapid and reliable circulating tumor cell (CTC) and disseminated tumor cell (DTC) detection are critical for rigorous evaluation of in vivo metastasis models. Clinical data show that each step of the metastatic cascade presents increasing barriers to success, limiting the number of successful metastatic cells to fewer than 1 in 1,500,000,000. As such, it is critical for scientists to employ approaches that allow for the evaluation of metastatic competency at each step of the cascade. Here, we present a flow cytometry-based method that enables swift and simultaneous comparison of both CTCs and DTCs from single animals, enabling evaluation of multiple metastatic steps within a single model system. We present the necessary gating strategy and optimized sample preparation conditions necessary to capture CTCs and DTCs using this approach. We also provide proof-of-concept experiments emphasizing the appropriate limits of detection of these conditions. Most importantly, we successfully recover CTCs and DTCs from murine blood and bone marrow. In Supplemental materials, we expand the applicability of our method to lung tissue and exemplify a potential multi-plexing strategy to further characterize recovered CTCs and DTCs. This approach to multiparameter flow cytometric detection and analysis of rare cells in in vivo models of metastasis is reproducible, high throughput, broadly applicable, and highly adaptable to a wide range of scientific inquiries. Most notably, it simplifies the recovery and analysis of CTCs and DTCs from the same animal, allowing for a rapid first look at the comparative metastatic competency of various model systems throughout multiple steps of the metastatic cascade.

Oncogenic signaling in the adult Drosophila prostate-like accessory gland leads to activation of a conserved pro-tumorigenic program, in the absence of proliferation.

Drosophila models for tumorigenesis and metastasis have revealed conserved mechanisms of signaling that are also involved in mammalian cancer. Many of these models use the proliferating tissues of the larval stages of Drosophila development, when tissues are highly mitotically active, or stem cells are abundant. Fewer Drosophila tumorigenesis models use adult animals to initiate tumor formation when many tissues are largely terminally differentiated and postmitotic. The Drosophila accessory glands are prostate-like tissues and a model for some aspects of prostate tumorigenesis using this tissue has been explored. In this model, oncogenic signaling was induced during the proliferative stage of accessory gland development, raising the question of how oncogenic activity would impact the terminally differentiated and postmitotic adult tissue. Here, we show that oncogenic signaling in the adult Drosophila accessory gland leads to activation of a conserved pro-tumorigenic program, similar to that observed in mitotic larval tissues, but in the absence of proliferation. Oncogenic signaling in the adult postmitotic gland leads to tissue hyperplasia with nuclear anaplasia and aneuploidy through endoreduplication, which increases polyploidy and occasionally results in non-mitotic neoplastic-like extrusions. We compare gene expression changes in our Drosophila model with that of endocycling prostate cancer cells induced by chemotherapy, which potentially mediate tumor recurrence after treatment. Similar signaling pathways are activated in the Drosophila gland and endocycling cancer cells, suggesting the adult accessory glands provide a useful model for aspects of prostate cancer progression that do not involve cellular proliferation.

Urinary extracellular vesicle-derived miR-126-3p predicts lymph node invasion in patients with high-risk prostate cancer.

To investigate extracellular vesicles (EVs) biomarkers for predicting lymph node invasion (LNI) in patients with high-risk prostate cancer (HRPCa), plasma and/or urine samples were prospectively collected from 45 patients with prostate cancer (PCa) and five with benign prostatic hyperplasia (BPH). Small RNA sequencing was performed to identify miRNAs in the EVs. All patients with PCa underwent radical prostatectomy and extended pelvic lymph node dissection. Differentially-expressed miRNAs were identified in patients with and without pathologically-verified LNI. The candidate miRNAs were validated in low-risk prostate cancer (LRPCa) and BPH. Four miRNA species (e.g. miR-126-3p) and three miRNA species (e.g. miR-27a-3p) were more abundant in urinary and plasma EVs, respectively, of patients with PCa. None of these miRNA species were shared between urinary and plasma EVs. miR-126-3p was significantly more abundant in patients with HR PCa with LNI than in those without (P = 0.018). miR-126-3p was significantly more abundant in the urinary EVs of patients with HRPCa than in those with LRPCa (P = 0.017) and BPH (P = 0.011). In conclusion, urinary EVs-derived miR-126-3p may serve as a good biomarker for predicting LNI in patients with HRPCa.