A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis.

BACKGROUND: Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. METHODS: An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. RESULTS: An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. CONCLUSIONS: The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.

The KDM5B and KDM1A lysine demethylases cooperate in regulating androgen receptor expression and signalling in prostate cancer.

Histone H3 lysine 4 (H3K4) methylation is key epigenetic mark associated with active transcription and is a substrate for the KDM1A/LSD1 and KDM5B/JARID1B lysine demethylases. Increased expression of KDM1A and KDM5B is implicated in many cancer types, including prostate cancer (PCa). Both KDM1A and KDM5B interact with AR and promote androgen regulated gene expression. For this reason, there is great interested in the development of new therapies targeting KDM1A and KDM5B, particularly in the context of castrate resistant PCa (CRPC), where conventional androgen deprivation therapies and androgen receptor signalling inhibitors are no longer effective. As there is no curative therapy for CRPC, new approaches are urgently required to suppress androgen signalling that prevent, delay or reverse progression to the castrate resistant state. While the contribution of KDM1A to PCa is well established, the exact contribution of KDM5B to PCa is less well understood. However, there is evidence that KDM5B is implicated in numerous pro-oncogenic mechanisms in many different types of cancer, including the hypoxic response, immune evasion and PI3/AKT signalling. Here we elucidate the individual and cooperative functions of KDM1A and KDM5B in PCa. We show that KDM5B mRNA and protein expression is elevated in localised and advanced PCa. We show that the KDM5 inhibitor, CPI-455, impairs androgen regulated transcription and alternative splicing. Consistent with the established role of KDM1A and KDM5B as AR coregulators, we found that individual pharmacologic inhibition of KDM1A and KDM5 by namoline and CPI-455 respectively, impairs androgen regulated transcription. Notably, combined inhibition of KDM1A and KDM5 downregulates AR expression in CRPC cells. Furthermore, combined KDM1A and KDM5 inhibition impairs PCa cell proliferation and invasion more than individual inhibition of KDM1A and KDM5B. Collectively our study has identified individual and cooperative mechanisms involving KDM1A and KDM5 in androgen signalling in PCa. Our findings support the further development of KDM1A and KDM5B inhibitors to treat advanced PCa. Further work is now required to confirm the therapeutic feasibility of combined inhibition of KDM1A and KDM5B as a novel therapeutic strategy for targeting AR positive CRPC.

Sialyl-Tn Antigen-Imprinted Dual Fluorescent Core-Shell Nanoparticles for Ratiometric Sialyl-Tn Antigen Detection and Dual-Color Labeling of Cancer Cells.

Sialyl-Tn (STn or sialyl-Thomsen-nouveau) is a carbohydrate antigen expressed by more than 80% of human carcinomas. We here report a strategy for ratiometric STn detection and dual-color cancer cell labeling, particularly, by molecularly imprinted polymers (MIPs). Imprinting was based on spectroscopic studies of a urea-containing green-fluorescent monomer 1 and STn-Thr-Na (sodium salt of Neu5Acα2-6GalNAcα-O-Thr). A few-nanometer-thin green-fluorescent polymer shell, in which STn-Thr-Na was imprinted with 1, other comonomers, and a cross-linker, was synthesized from the surface of red-emissive carbon nanodot (R-CND)-doped silica nanoparticles, resulting in dual fluorescent STn-MIPs. Dual-color labeling of cancer cells was achieved since both red and green emissions were detected in two separate channels of the microscope and an improved accuracy was obtained in comparison with single-signal MIPs. The flow cytometric cell analysis showed that the binding of STn-MIPs was significantly higher (p < 0.001) than that of non-imprinted polymer (NIP) control particles within the same cell line, allowing to distinguish populations. Based on the modularity of the luminescent core-fluorescent MIP shell architecture, the concept can be transferred in a straightforward manner to other target analytes.

Bacterial protein MakA causes suppression of tumour cell proliferation via inhibition of PIP5K1α/Akt signalling.

Recently, we demonstrated that a novel bacterial cytotoxin, the protein MakA which is released by Vibrio cholerae, is a virulence factor, causing killing of Caenorhabditis elegans when the worms are grazing on the bacteria. Studies with mammalian cell cultures in vitro indicated that MakA could affect eukaryotic cell signalling pathways involved in lipid biosynthesis. MakA treatment of colon cancer cells in vitro caused inhibition of growth and loss of cell viability. These findings prompted us to investigate possible signalling pathways that could be targets of the MakA-mediated inhibition of tumour cell proliferation. Initial in vivo studies with MakA producing V. cholerae and C. elegans suggested that the MakA protein might target the PIP5K1α phospholipid-signalling pathway in the worms. Intriguingly, MakA was then found to inhibit the PIP5K1α lipid-signalling pathway in cancer cells, resulting in a decrease in PIP5K1α and pAkt expression. Further analyses revealed that MakA inhibited cyclin-dependent kinase 1 (CDK1) and induced p27 expression, resulting in G2/M cell cycle arrest. Moreover, MakA induced downregulation of Ki67 and cyclin D1, which led to inhibition of cell proliferation. This is the first report about a bacterial protein that may target signalling involving the cancer cell lipid modulator PIP5K1α in colon cancer cells, implying an anti-cancer effect.

K-RAS Associated Gene-Mutation-Based Algorithm for Prediction of Treatment Response of Patients with Subtypes of Breast Cancer and Especially Triple-Negative Cancer.

Purpose: There is an urgent need for developing new biomarker tools to accurately predict treatment response of breast cancer, especially the deadly triple-negative breast cancer. We aimed to develop gene-mutation-based machine learning (ML) algorithms as biomarker classifiers to predict treatment response of first-line chemotherapy with high precision. Methods: Random Forest ML was applied to screen the algorithms of various combinations of gene mutation profiles of primary tumors at diagnosis using a TCGA Cohort (n = 399) with up to 150 months follow-up as a training set and validated in a MSK Cohort (n = 807) with up to 220 months follow-up. Subtypes of breast cancer including triple-negative and luminal A (ER+, PR+ and HER2−) were also assessed. The predictive performance of the candidate algorithms as classifiers was further assessed using logistic regression, Kaplan−Meier progression-free survival (PFS) plot, and univariate/multivariate Cox proportional hazard regression analyses. Results: A novel algorithm termed the 12-Gene Algorithm based on mutation profiles of KRAS, PIK3CA, MAP3K1, MAP2K4, PTEN, TP53, CDH1, GATA3, KMT2C, ARID1A, RunX1, and ESR1, was identified. The performance of this algorithm to distinguish non-progressed (responder) vs. progressed (non-responder) to treatment in the TCGA Cohort as determined using AUC was 0.96 (95% CI 0.94−0.98). It predicted progression-free survival (PFS) with hazard ratio (HR) of 21.6 (95% CI 11.3−41.5) (p < 0.0001) in all patients. The algorithm predicted PFS in the triple-negative subgroup with HR of 19.3 (95% CI 3.7−101.3) (n = 42, p = 0.000). The 12-Gene Algorithm was validated in the MSK Cohort with a similar AUC of 0.97 (95% CI 0.96−0.98) to distinguish responder vs. non-responder patients, and had a HR of 18.6 (95% CI 4.4−79.2) to predict PFS in the triple-negative subgroup (n = 75, p < 0.0001). Conclusions: The novel 12-Gene algorithm based on multitude gene-mutation profiles identified through ML has a potential to predict breast cancer treatment response to therapies, especially in triple-negative subgroups patients, which may assist personalized therapies and reduce mortality.

The METTL3 RNA Methyltransferase Regulates Transcriptional Networks in Prostate Cancer.

Prostate cancer (PCa) is a leading cause of cancer-related deaths and is driven by aberrant androgen receptor (AR) signalling. For this reason, androgen deprivation therapies (ADTs) that suppress androgen-induced PCa progression either by preventing androgen biosynthesis or via AR signalling inhibition (ARSi) are common treatments. The N6-methyladenosine (m6A) RNA modification is involved in regulating mRNA expression, translation, and alternative splicing, and through these mechanisms has been implicated in cancer development and progression. RNA-m6A is dynamically regulated by the METTL3 RNA methyltransferase complex and the FTO and ALKBH5 demethylases. While there is evidence supporting a role for aberrant METTL3 in many cancer types, including localised PCa, the wider contribution of METTL3, and by inference m6A, in androgen signalling in PCa remains poorly understood. Therefore, the aim of this study was to investigate the expression of METTL3 in PCa patients and study the clinical and functional relevance of METTL3 in PCa. It was found that METTL3 is aberrantly expressed in PCa patient samples and that siRNA-mediated METTL3 knockdown or METTL3-pharmacological inhibition significantly alters the basal and androgen-regulated transcriptome in PCa, which supports targeting m6A as a novel approach to modulate androgen signalling in PCa.

Exploring anti-androgen therapies in hormone dependent prostate cancer and new therapeutic routes for castration resistant prostate cancer.

Androgen deprivation therapies (ADTs) are important treatments which inhibit androgen-induced prostate cancer (PCa) progression by either preventing androgen biosynthesis (e.g. abiraterone) or by antagonizing androgen receptor (AR) function (e.g. bicalutamide, enzalutamide, darolutamide). A major limitation of current ADTs is they often remain effective for limited durations after which patients commonly progress to a lethal and incurable form of PCa, called castration-resistant prostate cancer (CRPC) where the AR continues to orchestrate pro-oncogenic signalling. Indeed, the increasing numbers of ADT-related treatment-emergent neuroendocrine-like prostate cancers (NePC), which lack AR and are thus insensitive to ADT, represents a major therapeutic challenge. There is therefore an urgent need to better understand the mechanisms of AR action in hormone dependent disease and the progression to CRPC, to enable the development of new approaches to prevent, reverse or delay ADT-resistance. Interestingly the AR regulates distinct transcriptional networks in hormone dependent and CRPC, and this appears to be related to the aberrant function of key AR-epigenetic coregulator enzymes including the lysine demethylase 1 (LSD1/KDM1A). In this review we summarize the current best status of anti-androgen clinical trials, the potential for novel combination therapies and we explore recent advances in the development of novel epigenetic targeted therapies that may be relevant to prevent or reverse disease progression in patients with advanced CRPC.

Fluorescent Molecularly Imprinted Polymer Layers against Sialic Acid on Silica-Coated Polystyrene Cores-Assessment of the Binding Behavior to Cancer Cells.

Sialic acid (SA) is a monosaccharide usually linked to the terminus of glycan chains on the cell surface. It plays a crucial role in many biological processes, and hypersialylation is a common feature in cancer. Lectins are widely used to analyze the cell surface expression of SA. However, these protein molecules are usually expensive and easily denatured, which calls for the development of alternative glycan-specific receptors and cell imaging technologies. In this study, SA-imprinted fluorescent core-shell molecularly imprinted polymer particles (SA-MIPs) were employed to recognize SA on the cell surface of cancer cell lines. The SA-MIPs improved suspensibility and scattering properties compared with previously used core-shell SA-MIPs. Although SA-imprinting was performed using SA without preference for the α2,3- and α2,6-SA forms, we screened the cancer cell lines analyzed using the lectins Maackia Amurensis Lectin I (MAL I, α2,3-SA) and Sambucus Nigra Lectin (SNA, α2,6-SA). Our results show that the selected cancer cell lines in this study presented a varied binding behavior with the SA-MIPs. The binding pattern of the lectins was also demonstrated. Moreover, two different pentavalent SA conjugates were used to inhibit the binding of the SA-MIPs to breast, skin, and lung cancer cell lines, demonstrating the specificity of the SA-MIPs in both flow cytometry and confocal fluorescence microscopy. We concluded that the synthesized SA-MIPs might be a powerful future tool in the diagnostic analysis of various cancer cells.

Gene-Mutation-Based Algorithm for Prediction of Treatment Response in Colorectal Cancer Patients.

Purpose: Despite the high mortality of metastatic colorectal cancer (mCRC), no new biomarker tools are available for predicting treatment response. We developed gene-mutation-based algorithms as a biomarker classifier to predict treatment response with better precision than the current predictive factors. Methods: Random forest machine learning (ML) was applied to identify the candidate algorithms using the MSK Cohort (n = 471) as a training set and validated in the TCGA Cohort (n = 221). Logistic regression, progression-free survival (PFS), and univariate/multivariate Cox proportional hazard analyses were performed and the performance of the candidate algorithms was compared with the established risk parameters. Results: A novel 7-Gene Algorithm based on mutation profiles of seven KRAS-associated genes was identified. The algorithm was able to distinguish non-progressed (responder) vs. progressed (non-responder) patients with AUC of 0.97 and had predictive power for PFS with a hazard ratio (HR) of 16.9 (p < 0.001) in the MSK cohort. The predictive power of this algorithm for PFS was more pronounced in mCRC (HR = 16.9, p < 0.001, n = 388). Similarly, in the TCGA validation cohort, the algorithm had AUC of 0.98 and a significant predictive power for PFS (p < 0.001). Conclusion: The novel 7-Gene Algorithm can be further developed as a biomarker model for prediction of treatment response in mCRC patients to improve personalized therapies.

PIP5K1α is Required for Promoting Tumor Progression in Castration-Resistant Prostate Cancer.

PIP5K1α has emerged as a promising drug target for the treatment of castration-resistant prostate cancer (CRPC), as it acts upstream of the PI3K/AKT signaling pathway to promote prostate cancer (PCa) growth, survival and invasion. However, little is known of the molecular actions of PIP5K1α in this process. Here, we show that siRNA-mediated knockdown of PIP5K1α and blockade of PIP5K1α action using its small molecule inhibitor ISA-2011B suppress growth and invasion of CRPC cells. We demonstrate that targeted deletion of the N-terminal domain of PIP5K1α in CRPC cells results in reduced growth and migratory ability of cancer cells. Further, the xenograft tumors lacking the N-terminal domain of PIP5K1α exhibited reduced tumor growth and aggressiveness in xenograft mice as compared to that of controls. The N-terminal domain of PIP5K1α is required for regulation of mRNA expression and protein stability of PIP5K1α. This suggests that the expression and oncogenic activity of PIP5K1α are in part dependent on its N-terminal domain. We further show that PIP5K1α acts as an upstream regulator of the androgen receptor (AR) and AR target genes including CDK1 and MMP9 that are key factors promoting growth, survival and invasion of PCa cells. ISA-2011B exhibited a significant inhibitory effect on AR target genes including CDK1 and MMP9 in CRPC cells with wild-type PIP5K1α and in CRPC cells lacking the N-terminal domain of PIP5K1α. These results indicate that the growth of PIP5K1α-dependent tumors is in part dependent on the integrity of the N-terminal sequence of this kinase. Our study identifies a novel functional mechanism involving PIP5K1α, confirming that PIP5K1α is an intriguing target for cancer treatment, especially for treatment of CRPC.

Comparative pathology of dog and human prostate cancer.

Though relatively rare in dogs, prostate cancer (PCa) is the most common non-cutaneous cancer in men. Human and canine prostate glands share many functional, anatomical and physiological features. Due to these similarities, canine PCa has been proposed as a model for PCa in men. PCa is typically androgen-dependent at diagnosis in men and for this reason, androgen deprivation therapies (ADT) are important treatments for advanced PCa in men. In contrast, there is some evidence that PCa is diagnosed more commonly in castrate dogs, at which point, limited therapeutic options are available. In men, a major limitation of current ADT is that progression to a lethal and incurable form of PCa, termed castrate-resistant prostate cancer (CRPC), is common. There is, therefore, an urgent need for a better understanding of the mechanism of PCa initiation and progression to CRPC to enable the development of novel therapeutic approaches. This review focuses on the functional, physiological, endocrine and histopathological similarities and differences in the prostate gland of these species. In particular, we focus on common physiological roles for androgen signalling in the prostate of men and dogs, we review the short- and longer-term effects of castration on PCa incidence and progression in the dog and relate how this knowledge may be relevant to understanding the mechanisms of CRPC in men.

FcγRIIIa receptor interacts with androgen receptor and PIP5K1α to promote growth and metastasis of prostate cancer.

Low-affinity immunoglobulin gamma Fc region receptor III-A (FcγRIIIa) is a cell surface protein that belongs to a family of Fc receptors that facilitate the protective function of the immune system against pathogens. However, the role of FcγRIIIa in prostate cancer (PCa) progression remained unknown. In this study, we found that FcγRIIIa expression was present in PCa cells and its level was significantly higher in metastatic lesions than in primary tumors from the PCa cohort (P = 0.006). PCa patients with an elevated level of FcγRIIIa expression had poorer biochemical recurrence (BCR)-free survival compared with those with lower FcγRIIIa expression, suggesting that FcγRIIIa is of clinical importance in PCa. We demonstrated that overexpression of FcγRIIIa increased the proliferative ability of PCa cell line C4-2 cells, which was accompanied by the upregulation of androgen receptor (AR) and phosphatidylinositol-4-phosphate 5-kinase alpha (PIP5Kα), which are the key players in controlling PCa progression. Conversely, targeted inhibition of FcγRIIIa via siRNA-mediated knockdown or using its inhibitory antibody suppressed growth of xenograft PC-3 and PC-3M prostate tumors and reduced distant metastasis in xenograft mouse models. We further showed that elevated expression of AR enhanced FcγRIIIa expression, whereas inhibition of AR activity using enzalutamide led to a significant downregulation of FcγRIIIa protein expression. Similarly, inhibition of PIP5K1α decreased FcγRIIIa expression in PCa cells. FcγRIIIa physically interacted with PIP5K1α and AR via formation of protein-protein complexes, suggesting that FcγRIIIa is functionally associated with AR and PIP5K1α in PCa cells. Our study identified FcγRIIIa as an important factor in promoting PCa growth and invasion. Further, the elevated activation of FcγRIII and AR and PIP5K1α pathways may cooperatively promote PCa growth and invasion. Thus, FcγRIIIa may serve as a potential new target for improved treatment of metastatic and castration-resistant PCa.

Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients.

Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available. Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups. Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892-0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935-0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1-3 cancer subgroups. Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.

JAK3 Is Expressed in the Nucleus of Malignant T Cells in Cutaneous T Cell Lymphoma (CTCL).

Perturbation in JAK-STAT signaling has been reported in the pathogenesis of cutaneous T cell lymphoma (CTCL). JAK3 is predominantly associated with the intra-cytoplasmic part of IL-2Rγc located in the plasma membrane of hematopoietic cells. Here we demonstrate that JAK3 is also ectopically expressed in the nucleus of malignant T cells. We detected nuclear JAK3 in various CTCL cell lines and primary malignant T cells from patients with Sézary syndrome, a leukemic variant of CTCL. Nuclear localization of JAK3 was independent of its kinase activity whereas STAT3 had a modest effect on nuclear JAK3 expression. Moreover, JAK3 nuclear localization was only weakly affected by blockage of nuclear export. An inhibitor of the nuclear export protein CRM1, Leptomycin B, induced an increased expression of SOCS3 in the nucleus, but only a weak increase in nuclear JAK3. Importantly, immunoprecipitation experiments indicated that JAK3 interacts with the nuclear protein POLR2A, the catalytic subunit of RNA Polymerase II. Kinase assays showed tyrosine phosphorylation of recombinant human Histone H3 by JAK3 in vitro-an effect which was blocked by the JAK inhibitor (Tofacitinib citrate). In conclusion, we provide the first evidence of nuclear localization of JAK3 in malignant T cells. Our findings suggest that JAK3 may have a cytokine-receptor independent function in the nucleus of malignant T cells, and thus a novel non-canonical role in CTCL.

Targeted inhibition of ERα signaling and PIP5K1α/Akt pathways in castration-resistant prostate cancer.

Selective ERα modulator, tamoxifen, is well tolerated in a heavily pretreated castration-resistant prostate cancer (PCa) patient cohort. However, its targeted gene network and whether expression of intratumor ERα due to androgen deprivation therapy (ADT) may play a role in PCa progression is unknown. In this study, we examined the inhibitory effect of tamoxifen on castration-resistant PCa in vitro and in vivo. We found that tamoxifen is a potent compound that induced a high degree of apoptosis and significantly suppressed growth of xenograft tumors in mice, at a degree comparable to ISA-2011B, an inhibitor of PIP5K1α that acts upstream of PI3K/AKT survival signaling pathway. Moreover, depletion of tumor-associated macrophages using clodronate in combination with tamoxifen increased inhibitory effect of tamoxifen on aggressive prostate tumors. We showed that both tamoxifen and ISA-2011B exert their on-target effects on prostate cancer cells by targeting cyclin D1 and PIP5K1α/AKT network and the interlinked estrogen signaling. Combination treatment using tamoxifen together with ISA-2011B resulted in tumor regression and had superior inhibitory effect compared with that of tamoxifen or ISA-2011B alone. We have identified sets of genes that are specifically targeted by tamoxifen, ISA-2011B or combination of both agents by RNA-seq. We discovered that alterations in unique gene signatures, in particular estrogen-related marker genes are associated with poor patient disease-free survival. We further showed that ERα interacted with PIP5K1α through formation of protein complexes in the nucleus, suggesting a functional link. Our finding is the first to suggest a new therapeutic potential to inhibit or utilize the mechanisms related to ERα, PIP5K1α/AKT network, and MMP9/VEGF signaling axis, providing a strategy to treat castration-resistant ER-positive subtype of prostate cancer tumors with metastatic potential.

Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification.

One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939-0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964-0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879-0.763) for PSA and 0.860 (95% CI 0.910-0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968-0.878) than PSA [AUC of 0.773 (95% CI 0.852-0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854-0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892-0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706-0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up.

BACKGROUND: Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. METHODS: Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. RESULTS: The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963-0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929-0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956-0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980-0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947-0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. CONCLUSIONS: The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

Establishment of Prostate Tumor Growth and Metastasis Is Supported by Bone Marrow Cells and Is Mediated by PIP5K1α Lipid Kinase.

Cancer cells facilitate growth and metastasis by using multiple signals from the cancer-associated microenvironment. However, it remains poorly understood whether prostate cancer (PCa) cells may recruit and utilize bone marrow cells for their growth and survival. Furthermore, the regulatory mechanisms underlying interactions between PCa cells and bone marrow cells are obscure. In this study, we isolated bone marrow cells that mainly constituted populations that were positive for CD11b and Gr1 antigens from xenograft PC-3 tumor tissues from athymic nu/nu mice. We found that the tumor-infiltrated cells alone were unable to form tumor spheroids, even with increased amounts and time. By contrast, the tumor-infiltrated cells together with PCa cells formed large numbers of tumor spheroids compared with PCa cells alone. We further utilized xenograft athymic nu/nu mice bearing bone metastatic lesions. We demonstrated that PCa cells were unable to survive and give rise to colony-forming units (CFUs) in media that were used for hematopoietic cell colony-formation unit (CFU) assays. By contrast, PC-3M cells survived when bone marrow cells were present and gave rise to CFUs. Our results showed that PCa cells required bone marrow cells to support their growth and survival and establish bone metastasis in the host environment. We showed that PCa cells that were treated with either siRNA for PIP5K1α or its specific inhibitor, ISA-2011B, were unable to survive and produce tumor spheroids, together with bone marrow cells. Given that the elevated expression of PIP5K1α was specific for PCa cells and was associated with the induced expression of VEGF receptor 2 in PCa cells, our findings suggest that cancer cells may utilize PIP5K1α-mediated receptor signaling to recruit growth factors and ligands from the bone marrow-derived cells. Taken together, our study suggests a new mechanism that enables PCa cells to gain proliferative and invasive advantages within their associated host microenvironment. Therapeutic interventions using PIP5K1α inhibitors may not only inhibit tumor invasion and metastasis but also enhance the host immune system.

MicroRNAs in the Pathogenesis, Diagnosis, Prognosis and Targeted Treatment of Cutaneous T-Cell Lymphomas.

Cutaneous T-cell lymphoma (CTCL) represents a heterogeneous group of potentially devastating primary skin malignancies. Despite decades of intense research efforts, the pathogenesis is still not fully understood. In the early stages, both clinical and histopathological diagnosis is often difficult due to the ability of CTCL to masquerade as benign skin inflammatory dermatoses. Due to a lack of reliable biomarkers, it is also difficult to predict which patients will respond to therapy or progress towards severe recalcitrant disease. In this review, we discuss recent discoveries concerning dysregulated microRNA (miR) expression and putative pathological roles of oncogenic and tumor suppressive miRs in CTCL. We also focus on the interplay between miRs, histone deacetylase inhibitors, and oncogenic signaling pathways in malignant T cells as well as the impact of miRs in shaping the inflammatory tumor microenvironment. We highlight the potential use of miRs as diagnostic and prognostic markers, as well as their potential as therapeutic targets. Finally, we propose that the combined use of miR-modulating compounds with epigenetic drugs may provide a novel avenue for boosting the clinical efficacy of existing anti-cancer therapies in CTCL.