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.

Lung adenocarcinomas without driver genes converge to common adaptive strategies through diverse genetic, epigenetic, and niche construction evolutionary pathways.

Somatic evolution selects cancer cell phenotypes that maximize survival and proliferation in dynamic environments. Although cancer cells are molecularly heterogeneous, we hypothesized convergent adaptive strategies to common host selection forces can be inferred from patterns of epigenetic and genetic evolutionary selection in similar tumors. We systematically investigated gene mutations and expression changes in lung adenocarcinomas with no common driver genes (n = 313). Although 13,461 genes were mutated in at least one sample, only 376 non-synonymous mutations evidenced positive evolutionary selection with conservation of 224 genes, while 1736 and 2430 genes exhibited ≥ two-fold increased and ≥ 50% decreased expression, respectively. Mutations under positive selection are more frequent in genes with significantly altered expression suggesting they often "hardwire" pre-existing epigenetically driven adaptations. Conserved genes averaged 16-fold higher expression in normal lung tissue compared to those with selected mutations demonstrating pathways necessary for both normal cell function and optimal cancer cell fitness. The convergent LUAD phenotype exhibits loss of differentiated functions and cell-cell interactions governing tissue organization. Conservation with increased expression is found in genes associated with cell cycle, DNA repair, p53 pathway, epigenetic modifiers, and glucose metabolism. No canonical driver gene pathways exhibit strong positive selection, but extensive down-regulation of membrane ion channels suggests decreased transmembrane potential may generate persistent proliferative signals. NCD LUADs perform niche construction generating a stiff, immunosuppressive microenvironment through selection of specific collagens and proteases. NCD LUADs evolve to a convergent phenotype through a network of interconnected genetic, epigenetic, and ecological pathways.

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.

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.

Exploration of drug resistance mechanisms in triple negative breast cancer cells using a microfluidic device and patient tissues.

Chemoresistance is a major cause of treatment failure in many cancers. However, the life cycle of cancer cells as they respond to and survive environmental and therapeutic stress is understudied. In this study, we utilized a microfluidic device to induce the development of doxorubicin-resistant (DOXR) cells from triple negative breast cancer (TNBC) cells within 11 days by generating gradients of DOX and medium. In vivo chemoresistant xenograft models, an unbiased genome-wide transcriptome analysis, and a patient data/tissue analysis all showed that chemoresistance arose from failed epigenetic control of the nuclear protein-1 (NUPR1)/histone deacetylase 11 (HDAC11) axis, and high NUPR1 expression correlated with poor clinical outcomes. These results suggest that the chip can rapidly induce resistant cells that increase tumor heterogeneity and chemoresistance, highlighting the need for further studies on the epigenetic control of the NUPR1/HDAC11 axis in TNBC.

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.

Drug-resilient Cancer Cell Phenotype Is Acquired via Polyploidization Associated with Early Stress Response Coupled to HIF2α Transcriptional Regulation.

Therapeutic resistance and recurrence remain core challenges in cancer therapy. How therapy resistance arises is currently not fully understood with tumors surviving via multiple alternative routes. Here, we demonstrate that a subset of cancer cells survives therapeutic stress by entering a transient state characterized by whole-genome doubling. At the onset of the polyploidization program, we identified an upregulation of key transcriptional regulators, including the early stress-response protein AP-1 and normoxic stabilization of HIF2α. We found altered chromatin accessibility, ablated expression of retinoblastoma protein (RB1), and enrichment of AP-1 motif accessibility. We demonstrate that AP-1 and HIF2α regulate a therapy resilient and survivor phenotype in cancer cells. Consistent with this, genetic or pharmacologic targeting of AP-1 and HIF2α reduced the number of surviving cells following chemotherapy treatment. The role of AP-1 and HIF2α in stress response by polyploidy suggests a novel avenue for tackling chemotherapy-induced resistance in cancer. SIGNIFICANCE: In response to cisplatin treatment, some surviving cancer cells undergo whole-genome duplications without mitosis, which represents a mechanism of drug resistance. This study presents mechanistic data to implicate AP-1 and HIF2α signaling in the formation of this surviving cell phenotype. The results open a new avenue for targeting drug-resistant cells.

Tumour tissue-derived small extracellular vesicles reflect molecular subtypes of bladder cancer.

mRNA-based molecular subtypes have implications for bladder cancer prognosis and clinical benefit from certain therapies. Whether small extracellular vesicles (sEVs) can reflect bladder cancer molecular subtypes is unknown. We performed whole transcriptome RNA sequencing for formalin fixed paraffin embedded (FFPE) tumour tissues and sEVs separated from matched tissue explants, urine and plasma in patients with bladder cancer. sEVs were separated using size-exclusion chromatography, and characterized by transmission electron microscopy, nano flow cytometry and western blots, respectively. High yield of sEVs were obtained using approximately 1 g of tissue, incubated with media for 30 min. FFPE tumour tissue and tumour tissue-derived sEVs demonstrated good concordance in molecular subtype classification. All urinary sEVs were classified as luminal subtype, while all plasma sEVs were classified as Ba/Sq subtype, regardless of the molecular subtypes indicated by their matched FFPE tumour tissue. The comparison within urine sEVs, which may exclude the sample type specific background, could pick up the different biology between NMIBC and MIBC, as well as the signature genes related to molecular subtypes. Four candidate sEV-related bladder cancer-specific mRNA biomarkers, FAM71E2, OR4K5, FAM138F and KRTAP26-1, were identified by analysing matched urine sEVs, tumour tissue derived sEVs, and adjacent normal tissue derived sEVs. Compared to sEVs separated from biofluids, tissue-derived sEVs may reflect more tissue- or disease-specific biological features. Urine sEVs are promising biomarkers to be used for liquid biopsy-based molecular subtype classification, but the current algorithm needs to be modified/adjusted. Future work is needed to validate the four new bladder cancer-specific biomarkers in large cohorts.

The contribution of evolvability to the eco-evolutionary dynamics of competing species.

Evolvability is the capacity of a population to generate heritable variation that can be acted upon by natural selection. This ability influences the adaptations and fitness of individual organisms. By viewing this capacity as a trait, evolvability is subject to natural selection and thus plays a critical role in eco-evolutionary dynamics. Understanding this role provides insight into how species respond to changes in their environment and how species coexistence can arise and be maintained. Here, we create a G-function model of competing species, each with a different evolvability. We analyze population and strategy (= heritable phenotype) dynamics of the two populations under clade initiation (when species are introduced into a population), evolutionary tracking (constant, small changes in the environment), adaptive radiation (availability of multiple ecological niches), and evolutionary rescue (extreme environmental disturbances). We find that when species are far from an eco-evolutionary equilibrium, faster-evolving species reach higher population sizes, and when species are close to an equilibrium, slower-evolving species are more successful. Frequent, minor environmental changes promote the extinction of species with small population sizes, regardless of their evolvability. When several niches are available for a species to occupy, coexistence is possible, though slower-evolving species perform slightly better than faster-evolving ones due to the well-recognized inherent cost of evolvability. Finally, disrupting the environment at intermediate frequencies can result in coexistence with cyclical population dynamics of species with different rates of evolution.

A mathematical investigation of polyaneuploid cancer cell memory and cross-resistance in state-structured cancer populations.

The polyaneuploid cancer cell (PACC) state promotes cancer lethality by contributing to survival in extreme conditions and metastasis. Recent experimental evidence suggests that post-therapy PACC-derived recurrent populations display cross-resistance to classes of therapies with independent mechanisms of action. We hypothesize that this can occur through PACC memory, whereby cancer cells that have undergone a polyaneuploid transition (PAT) reenter the PACC state more quickly or have higher levels of innate resistance. In this paper, we build on our prior mathematical models of the eco-evolutionary dynamics of cells in the 2N+ and PACC states to investigate these two hypotheses. We show that although an increase in innate resistance is more effective at promoting cross-resistance, this trend can also be produced via PACC memory. We also find that resensitization of cells that acquire increased innate resistance through the PAT have a considerable impact on eco-evolutionary dynamics and extinction probabilities. This study, though theoretical in nature, can help inspire future experimentation to tease apart hypotheses surrounding how cross-resistance in structured cancer populations arises.

Escherichia coli survival in response to ciprofloxacin antibiotic stress correlates with increased nucleoid length and effective misfolded protein management.

The evolution of antibiotic resistance is a fundamental problem in disease management but is rarely quantified on a single-cell level owing to challenges associated with capturing the spatial and temporal variation across a population. To evaluate cell biological phenotypic responses, we tracked the single-cell dynamics of filamentous bacteria through time in response to ciprofloxacin antibiotic stress. We measured the degree of phenotypic variation in nucleoid length and the accumulation of protein damage under ciprofloxacin antibiotic and quantified the impact on bacterial survival. Increased survival was correlated with increased nucleoid length and the variation in this response was inversely correlated with antibiotic concentration. Survival time was also increased through clearance of misfolded proteins, an unexpected mechanism of stress relief deployed by the filamentous bacteria. Our results reveal a diverse range of survival tactics employed by bacteria in response to ciprofloxacin and suggest potential evolutionary routes to resistance.

Targeting MerTK decreases efferocytosis and increases anti-tumor immune infiltrate in prostate cancer.

The prostate cancer tumor microenvironment (TME) is comprised of many cell types that can contribute to and influence tumor progression. Some of the most abundant prostate cancer TME cells are macrophages, which can be modeled on a continuous spectrum of M1-like (anti-tumor macrophages) to M2-like (pro-tumor macrophages). A function of M2-like macrophages is efferocytosis, the phagocytosis of apoptotic cells. Based on literature from other models and contexts, efferocytosis further supports the M2-like macrophage phenotype. MerTK is a receptor tyrosine kinase that mediates efferocytosis by binding phosphatidylserine on apoptotic cells. We hypothesize efferocytosis in the prostate cancer TME is a tumor-promoting function of macrophages and that targeting MerTK-mediated efferocytosis will slow prostate cancer growth and promote an anti-tumor immune infiltrate. The aims of this study are to measure efferocytosis of prostate cancer cells by in vitro human M1/M2 macrophage models and assess changes in the M2-like, pro-tumor macrophage phenotype following prostate cancer efferocytosis. Additionally, this study aims to demonstrate that targeting MerTK decreases prostate cancer efferocytosis and promotes an anti-tumor immune infiltrate. We have developed methodology using flow cytometry to quantify efferocytosis of human prostate cancer cells using the LNCaP cell line. We observed that M2 macrophages efferocytose the LNCaP cell line more than M1 macrophages. Following efferocytosis of LNCaP cells by M2 human monocyte-derived macrophages (HMDMs), we observed an increase in the M2-like, pro-tumor phenotype by flow cytometry cell surface marker analysis. By qRT-PCR, flow cytometry, and Western blot, we detected greater MerTK expression in M2 than M1 macrophages. Targeting MerTK with antibody Mer590 decreased LNCaP efferocytosis by M2 HMDMs, establishing the role of MerTK in prostate cancer efferocytosis. In the prostate cancer mouse model hi-myc, Mertk KO increased anti-tumor immune infiltrate including CD8 T cells. These findings support targeting MerTK-mediated efferocytosis as a novel therapy for prostate cancer.

Updating the Definition of Cancer.

Most definitions of cancer broadly conform to the current NCI definition: "Cancer is a disease in which some of the body's cells grow uncontrollably and spread to other parts of the body." These definitions tend to describe what cancer "looks like" or "does" but do not describe what cancer "is" or "has become." While reflecting past insights, current definitions have not kept pace with the understanding that the cancer cell is itself transformed and evolving. We propose a revised definition of cancer: Cancer is a disease of uncontrolled proliferation by transformed cells subject to evolution by natural selection. We believe this definition captures the essence of the majority of previous and current definitions. To the simplest definition of cancer as a disease of uncontrolled proliferation of cells, our definition adds in the adjective "transformed" to capture the many tumorigenic processes that cancer cells adopt to metastasize. To the concept of uncontrolled proliferation of transformed cells, our proposed definition then adds "subject to evolution by natural selection." The subject to evolution by natural selection modernizes the definition to include the genetic and epigenetic changes that accumulate within a population of cancer cells that lead to the lethal phenotype. Cancer is a disease of uncontrolled proliferation by transformed cells subject to evolution by natural selection.

Cells in the polyaneuploid cancer cell (PACC) state have increased metastatic potential.

Although metastasis is the leading cause of cancer deaths, it is quite rare at the cellular level. Only a rare subset of cancer cells (~ 1 in 1.5 billion) can complete the entire metastatic cascade: invasion, intravasation, survival in the circulation, extravasation, and colonization (i.e. are metastasis competent). We propose that cells engaging a Polyaneuploid Cancer Cell (PACC) phenotype are metastasis competent. Cells in the PACC state are enlarged, endocycling (i.e. non-dividing) cells with increased genomic content that form in response to stress. Single-cell tracking using time lapse microscopy reveals that PACC state cells have increased motility. Additionally, cells in the PACC state exhibit increased capacity for environment-sensing and directional migration in chemotactic environments, predicting successful invasion. Magnetic Twisting Cytometry and Atomic Force Microscopy reveal that cells in the PACC state display hyper-elastic properties like increased peripheral deformability and maintained peri-nuclear cortical integrity that predict successful intravasation and extravasation. Furthermore, four orthogonal methods reveal that cells in the PACC state have increased expression of vimentin, a hyper-elastic biomolecule known to modulate biomechanical properties and induce mesenchymal-like motility. Taken together, these data indicate that cells in the PACC state have increased metastatic potential and are worthy of further in vivo analysis.

Nuclear morphology predicts cell survival to cisplatin chemotherapy.

The emergence of chemotherapy resistance drives cancer lethality in cancer patients, with treatment initially reducing overall tumor burden followed by resistant recurrent disease. While molecular mechanisms underlying resistance phenotypes have been explored, less is known about the cell biological characteristics of cancer cells that survive to eventually seed the recurrence. To identify the unique phenotypic characteristics associated with survival upon chemotherapy exposure, we characterized nuclear morphology and function as prostate cancer cells recovered following cisplatin treatment. Cells that survived in the days and weeks after treatment and resisted therapy-induced cell death showed increasing cell size and nuclear size, enabled by continuous endocycling resulting in repeated whole genome doubling. We further found that cells that survive after therapy release were predominantly mononucleated and likely employ more efficient DNA damage repair. Finally, we show that surviving cancer cells exhibit a distinct nucleolar phenotype and increased rRNA levels. These data support a paradigm where soon after therapy release, the treated population mostly contains cells with a high level of widespread and catastrophic DNA damage that leads to apoptosis, while the minority of cells that have successful DDR are more likely to access a pro-survival state. These findings are consistent with accession of the polyaneuploid cancer cell (PACC) state, a recently described mechanism of therapy resistance and tumor recurrence. Our findings demonstrate the fate of cancer cells following cisplatin treatment and define key cell phenotypic characteristics of the PACC state. This work is essential for understanding and, ultimately, targeting cancer resistance and recurrence.

Novel urinary tract obstruction marker discovery by multi-marker profiling of urinary extracellular vesicles derived from a rat UTO model.

INTRODUCTION: Congenital urinary obstruction is a common cause of end-stage renal disease in the pediatric population. However, non-invasive diagnostics to predict which patients will benefit from early intervention are lacking. METHODS: Using a rat model of upper and lower urinary tract partial obstruction and the Nanostring nCounter Fibrosis V2 Panel, we evaluated the mRNA cargo of urinary small extracellular vesicles (sEVs) and mRNA expression patterns of kidney and bladder tissues from rats with lower tract urinary obstruction and upper tract urinary obstruction. RESULTS: While mRNA hierarchical clustering of urinary sEVs was unable to differentiate upper compared to lower tract urinary obstruction, clustering was able to detect overall disease state (UUTO or LUTO) versus healthy controls. Further, urinary sEVs carried genes unique to each treatment group (UUTO: 59 genes, LUTO: 17 genes), while only one gene was uniquely carried in the control group. Notable genes of interest found in urinary sEVs were VCAM-1 and NOS1 for UUTO, Egfr for LUTO, and Pck1 for healthy controls. CONCLUSION: This study provides support that differential gene expression of urinary sEV mRNA has potential to act as biomarkers in the diagnosis and prognosis of UTO. Urinary sEVs demonstrated higher numbers of unique genes representative of injury to the kidney than that of injury to the bladder. Importantly, there were genes unique to UUTO sEVs, indicating the extent and reversibility of renal damage can be independent of the function, damage, and architecture of the bladder.

Modeling cancer's ecological and evolutionary dynamics.

In this didactic paper, we present a theoretical modeling framework, called the G-function, that integrates both the ecology and evolution of cancer to understand oncogenesis. The G-function has been used in evolutionary ecology, but has not been widely applied to problems in cancer. Here, we build the G-function framework from fundamental Darwinian principles and discuss how cancer can be seen through the lens of ecology, evolution, and game theory. We begin with a simple model of cancer growth and add on components of cancer cell competition and drug resistance. To aid in exploration of eco-evolutionary modeling with this approach, we also present a user-friendly software tool. By the end of this paper, we hope that readers will be able to construct basic G function models and grasp the usefulness of the framework to understand the games cancer plays in a biologically mechanistic fashion.

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.

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.

RNA profiling of circulating tumor cells systemically captured from diagnostic leukapheresis products in prostate cancer patients.

The application of circulating tumor cells (CTCs) in both clinical practice and research has been continuously limited by the rare number of targets that can be found in a tube of peripheral blood. Diagnostic leukapheresis (DLA) was used to increase the sampling volume. AdnaTest was used to process the whole leukopak, and the RNAs of captured CTCs was then profiled by NanoString nCounter platform. Spike-in experiments and leukopaks from patients with metastatic prostate cancer were used to validate this new strategy. The whole leukopak was further concentrated five times to reduce the total volume from 150 â€‹mL to 30 â€‹mL, which enabled it to be processed by 3 separate AdnaTest kits. The spike-in experiment demonstrated a reliable capture when there were more than 100 cancer cells/10 â€‹mL of concentrated leukopak. In 1 out of 5 real patient samples, CTCs were only detected in the leukopak, but not in peripheral blood. The RNA profiling of DLA CTCs indicated a more aggressive phenotype of CTCs occurred when the patient was experiencing a disease relapse, even when the serum prostate specific antigen (PSA) level was still relatively low and CTCs in peripheral blood were not detectable. We established a new protocol, integrating DLA, AdnaTest and NanoString nCounter technology, to profile RNAs from CTCs captured from a large blood screening volume. The new protocol can process the whole leukopak with sensitive CTC capture. The RNA profiling of CTCs can provide valuable information for disease monitoring.