Multi-institutional Analysis Shows that Low PCAT-14 Expression Associates with Poor Outcomes in Prostate Cancer

A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

Retracted: Long noncoding RNA RHPN1-AS1, induced by KDM5B, is involved in breast cancer via sponging miR-6884-5p

The above article, published online in Journal of Cellular Biochemistry on 31 January 2020 in Wiley Online Library (https://doi.org/10.1002/jcb.29645), has been retracted by agreement between the authors, the journal's Editor in Chief, Prof. Dr. Christian Behl, and Wiley Periodicals LLC. The authors asked to retract their article after substantial mistakes in experimental data were found, thus the results are considered to be invalid.

Molecular predictors of metastasis in patients with prostate cancer

INTRODUCTION

Prostate cancer is a serious threat to the health of older adults worldwide. The quality of life and survival time of patients sharply decline once metastasis occurs. Thus, early screening for prostate cancer is very advanced in developed countries. The detection methods used include Prostate-specific antigen (PSA) detection and digital rectal examination. However, the lack of universal access to early screening in some developing countries has resulted in an increased number of patients presenting with metastatic prostate cancer. In addition, the treatment methods for metastatic and localized prostate cancer are considerably different. In many patients, early-stage prostate cancer cells often metastasize due to delayed observation, negative PSA results, and delay in treatment time. Therefore, the identification of patients who are prone to metastasis is important for future clinical studies.

AREAS COVERED

this review introduced a large number of predictive molecules related to prostate cancer metastasis. These molecules involve the mutation and regulation of tumor cell genes, changes in the tumor microenvironment, and the liquid biopsy.

EXPERT OPINION

In next decade, PSMA PET/CT and liquid biopsy will be the excellent predicting tools, while ¹⁷⁷ Lu- PSMA-RLT will be showed excellent anti-tumor efficacy in mPCa patients.

Identification and validation of the pyroptosis-related long noncoding rna signature to predict the prognosis of patients with bladder cancer

Bladder cancer ranked the second most frequent tumor among urological malignancies. This work investigated bladder cancer prognosis, including the relevance of pyroptosis-related long noncoding RNA (lncRNA) in it and its potential roles. The Cancer Genome Atlas database offered statistics on lncRNAs and clinical data from 411 bladder cancer patients. Pearson correlation analysis was used to evaluate pyroptosis-related lncRNAs. To explore prognosis-associated lncRNAs, we performed univariate Cox regression, least absolute shrinkage and selection operator regression analyses, as well as the Kaplan-Meier method. Multivariate Cox analysis was leveraged to establish the risk score model. Afterward, a nomogram was constructed according to the risk score and clinical variables. Finally, to investigate the potential functions of pyroptosis-related lncRNAs, gene set enrichment analysis was employed. Eleven pyroptosis-related lncRNAs were screened to be closely associated with patients prognosis. On this foundation, a risk score model was created to classify patients into high and low risk groups. The signature was shown to be an independent prognostic factor (P < .001) with an area under the curve of 0.730. Then a nomogram was established including risk scores and clinical characteristics. The nomogram prediction effect is excellent, with a concordance index of 0.86. The 11-lncRNAs signature was associated with the supervision of oxidative stress, epithelial-mesenchymal transition, cell adhesion, TGF-β, and Wingless and INT-1 signaling pathway, according to the gene set enrichment analysis. Our findings indicate that pyroptosis-related lncRNAs, which may affect tumor pathogenesis in many ways, might be exploited to assess the prognosis of bladder cancer patients.

LINC01146/F11R facilitates growth and metastasis of prostate cancer under the regulation of TGF-β

The effect of long intergenic non-protein coding RNAs (lncRNAs) was verified in prostate cancer (PCa), but the mechanism of LINC01146 in PCa is unclear. Bioinformatics was applied to analyze LINC01146 expression in PCa and predict target genes of LINC01146, followed by the verification of qRT-PCR, RNA pull-down and co-immunoprecipitation (Co-IP). The correlation between LINC01146 expression and clinicopathological characteristics was investigated. The location of LINC01146 in PCa cells was detected by fluorescence in situ hybridization (FISH). After interference with LINC01146 or/and F11 receptor (F11R) or treated with transforming growth factor beta 1 (TGF-β1), the function of LINC01146 in PCa in vitro or in vivo was determined by CCK-8, colony formation, flow cytometry, scratch test, transwell assay, xenograft experiment and western blot. LINC01146 and F11R were over-expressed in PCa and positively correlated with poor prognosis. LINC01146 located in the cytoplasm and combined with F11R. LINC01146 overexpression impeded apoptosis, facilitated viability, proliferation, migration and invasion in PCa cells in vitro, promoted tumor growth in vivo, downregulated E-cadherin, Bax and Cleaved caspase-3, and upregulated N-cadherin, Vimentin and PCNA, but LINC01146 silencing did the opposite. F11R was positively regulated by LINC01146 and F11R depletion negated the effect of LINC01146 overexpression on malignant phenotypes of PCa cells. The expression of LINC01146 and F11R was regulated by TGF-β1. The promoting role of TGF-β1 in migration, invasion and F11R in PCa cells was reversed by LINC01146 silencing. LINC01146 upregulated F11R to facilitate malignant phenotypes of PCa cells, which was regulated by TGF-β.

LncRNA weighted gene co-expression network analysis reveals novel biomarkers related to prostate cancer metastasis

BACKGROUND

Most prostate cancer patients die from metastasis and lack accurate efficacious biomarkers to monitor the disease behavior, optimize treatment and assess prognosis. Herein, we aimed to identify meaningful lncRNA biomarkers associated with prostate cancer metastatic progression.

METHODS

By repurposing microarray probes, 11,624 lncRNAs in prostate cancer were obtained from Gene Expression Omnibus  database (GSE46691, N = 545; GSE29079, N = 235; GSE94767, N = 130). Weighted gene co-expression network analysis was applied to determine the co-expression lncRNA network pertinent to metastasis. Hub lncRNAs were screened. RNA-seq and clinical data from the Cancer Genome Atlas prostate cancer (TCGA-PRAD) cohort (N = 531) were analyzed. Transwell assay and bioinformatic analysis were performed for mechanism research.

RESULTS

The high expression levels of nine hub lncRNAs (FTX, AC005261.1, NORAD, LINC01578, AC004542.2, ZFAS1, EBLN3P, THUMPD3-AS1, GAS5) were significantly associated with Gleason score and increased probability of metastatic progression. Among these lncRNAs, ZFAS1 had the consistent trends of expression in all of the analysis from different cohorts, and the Kaplan-Meier survival analyses showed higher expression of ZFAS1 was associated with shorter relapse free survival. In-vitro studies confirmed that downregulation of ZFAS1 decreased prostate cancer cell migration.

CONCLUSION

We offered some new insights into discovering lncRNA markers correlated with metastatic progression of prostate cancer using the WGCNA. Some may serve as potential prognostic biomarkers and therapeutic targets for advanced metastatic prostate cancer.

Identification of a 5-lncRNA-Based Signature for Immune Characteristics and Prognosis of Lung Squamous Cell Carcinoma and Verification of the Function of lncRNA SPATA41

Lung squamous cell carcinoma (LUSC) is one of the most lethal cancers worldwide. Traditional tumor-node-metastasis (TNM) staging system has many insufficiencies in predicting immune characteristics, overall survival (OS), and prognosis of LUSC. LncRNA is currently found involved in tumor development and effectively predicts tumor prognosis. We screened potential tumor-related lncRNAs for immune characteristics and constructed a nomogram combining lncRNA and traditional clinical indicators for prognosis prediction. We obtained the large-scale gene expression profiles of samples from 492 LUSC patients in The Cancer Genome Atlas database. SPATA41, AL034550.2, AP003721.2, AC106786.1, and AC078889.1 were finally screened to construct a 5-lncRNA-based signature. The risk score of the signature divided patients into subgroups of high-risk and low-risk with significant differences in OS. Their area under the curve (AUC) reached more than 0.70 in 1, 3, and 5 years. In addition, compared with the high-risk subgroup, the low-risk subgroup exhibited a remarkably favorable prognosis and TME score, along with a higher immune infiltration score and lower TIDE score. The signature also significantly related to chemotherapy response, especially in cisplatin, vinorelbine, and paclitaxel. Importantly, the nomogram we constructed had good reliability with the assessment of the calibration chart and consistency index (c-index). GO and KEGG enrichment analysis indicated that co-expression mRNAs of the 5 lncRNAs were mainly focused on RNA splicing, DNA replication, and protein serine/threonine kinase activity. Functional assays demonstrated that SPATA41, one of the five OS-related lncRNAs, regulated invasion, migration, proliferation, and programmed death in vitro. In summary, our 5-lncRNA-based signature has a good performance in predicting immune characteristics and prognosis of LUSC patients.

Evaluation and multi-institutional validation of a novel urine biomarker lncRNA546 to improve the diagnostic specificity of prostate cancer in PSA gray-zone

Background and objectives

Prostate specific antigen (PSA) is currently the most commonly used biomarker for prostate cancer diagnosis. However, when PSA is in the gray area of 4-10 ng/ml, the diagnostic specificity of prostate cancer is extremely low, leading to overdiagnosis in many clinically false-positive patients. This study was trying to discover and evaluate a novel urine biomarker long non-coding RNA (lncRNA546) to improve the diagnostic accuracy of prostate cancer in PSA gray-zone.

Methods

A cohort study including consecutive 440 participants with suspected prostate cancer was retrospectively conducted in multi-urology centers. LncRNA546 scores were calculated with quantitative real-time polymerase chain reaction. The area under the receiver operating characteristic curve (AUROC), decision curve analysis (DCA) and a biopsy-specific nomogram were utilized to evaluate the potential for clinical application. Logistic regression model was constructed to confirm the predictive power of lncRNA546.

Results

LncRNA546 scores were sufficient to discriminate positive and negative biopsies. ROC analysis showed a higher AUC for lncRNA546 scores than prostate cancer antigen 3 (PCA3) scores (0.78 vs. 0.66, p<0.01) in the overall cohort. More importantly, the AUC of lncRNA546 (0.80) was significantly higher than the AUCs of total PSA (0.57, p=0.02), percentage of free PSA (%fPSA) (0.64, p=0.04) and PCA3 (0.63, p<0.01) in the PSA 4-10 ng/ml cohort. A base model constructed by multiple logistic regression analysis plus lncRNA546 scores improved the predictive accuracy (PA) from 79.8% to 86.3% and improved AUC results from 0.862 to 0.915. DCA showed that the base model plus lncRNA546 displayed greater net benefit at threshold probabilities beyond 15% in the PSA 4-10 ng/ml cohort.

Conclusion

LncRNA546 is a promising novel biomarker for the early detection of prostate cancer, especially in the PSA 4-10 ng/ml cohort.

Mutator-Derived lncRNA Landscape: A Novel Insight Into the Genomic Instability of Prostate Cancer

Background

Increasing evidence has emerged to reveal the correlation between genomic instability and long non-coding RNAs (lncRNAs). The genomic instability-derived lncRNA landscape of prostate cancer (PCa) and its critical clinical implications remain to be understood.

Methods

Patients diagnosed with PCa were recruited from The Cancer Genome Atlas (TCGA) program. Genomic instability-associated lncRNAs were identified by a mutator hypothesis-originated calculative approach. A signature (GILncSig) was derived from genomic instability-associated lncRNAs to classify PCa patients into high-risk and low-risk groups. The biochemical recurrence (BCR) model of a genomic instability-derived lncRNA signature (GILncSig) was established by Cox regression and stratified analysis in the train set. Then its prognostic value and association with clinical features were verified by Kaplan–Meier (K-M) analysis and receiver operating characteristic (ROC) curve in the test set and the total patient set. The regulatory network of transcription factors (TFs) and lncRNAs was established to evaluate TF–lncRNA interactions.

Results

A total of 95 genomic instability-associated lncRNAs of PCa were identified. We constructed the GILncSig based on 10 lncRNAs with independent prognostic value. GILncSig separated patients into the high-risk (n = 121) group and the low-risk (n = 121) group in the train set. Patients with high GILncSig score suffered from more frequent BCR than those with low GILncSig score. The results were further validated in the test set, the whole TCGA cohort, and different subgroups stratified by age and Gleason score (GS). A high GILncSig risk score was significantly associated with a high mutation burden and a low critical gene expression (PTEN and CDK12) in PCa. The predictive performance of our BCR model based on GILncSig outperformed other existing BCR models of PCa based on lncRNAs. The GILncSig also showed a remarkable ability to predict BCR in the subgroup of patients with TP53 mutation or wild type. Transcription factors, such as FOXA1, JUND, and SRF, were found to participate in the regulation of lncRNAs with prognostic value.

Conclusion

In summary, we developed a prognostic signature of BCR based on genomic instability-associated lncRNAs for PCa, which may provide new insights into the epigenetic mechanism of BCR.

LINC00355 regulates p27KIP expression by binding to MENIN to induce proliferation in late-stage relapse breast cancer

Late-stage relapse (LSR) in patients with breast cancer (BC) occurs more than five years and up to 10 years after initial treatment and has less than 30% 5-year relative survival rate. Long non-coding RNAs (lncRNAs) play important roles in BC yet have not been studied in LSR BC. Here, we identify 1127 lncRNAs differentially expressed in LSR BC via transcriptome sequencing and analysis of 72 early-stage and 24 LSR BC patient tumors. Decreasing expression of the most up-regulated lncRNA, LINC00355, in BC and MCF7 long-term estrogen deprived cell lines decreases cellular invasion and proliferation. Subsequent mechanistic studies show that LINC00355 binds to MENIN and changes occupancy at the CDKN1B promoter to decrease p27Kip. In summary, this is a key study discovering lncRNAs in LSR BC and LINC00355 association with epigenetic regulation and proliferation in BC.

Noncoding RNAs in tumor metastasis: molecular and clinical perspectives

Metastasis is the main culprit of cancer-associated mortality and involves a complex and multistage process termed the metastatic cascade, which requires tumor cells to detach from the primary site, intravasate, disseminate in the circulation, extravasate, adapt to the foreign microenvironment, and form organ-specific colonization. Each of these processes has been already studied extensively for molecular mechanisms focused mainly on protein-coding genes. Recently, increasing evidence is pointing towards RNAs without coding potential for proteins, referred to as non-coding RNAs, as regulators in shaping cellular activity. Since those first reports, the detection and characterization of non-coding RNA have explosively thrived and greatly enriched the understanding of the molecular regulatory networks in metastasis. Moreover, a comprehensive description of ncRNA dysregulation will provide new insights into novel tools for the early detection and treatment of metastatic cancer. In this review, we focus on discussion of the emerging role of ncRNAs in governing cancer metastasis and describe step by step how ncRNAs impinge on cancer metastasis. In particular, we highlight the diagnostic and therapeutic applications of ncRNAs in metastatic cancer.

m6 A modification of lncRNA PCAT6 promotes bone metastasis in prostate cancer through IGF2BP2-mediated IGF1R mRNA stabilization

BACKGROUND

Bone metastasis is the leading cause of tumor-related death in prostate cancer (PCa) patients. Long noncoding RNAs (lncRNAs) have been well documented to be involved in the progression of multiple cancers. Nevertheless, the role of lncRNAs in PCa bone metastasis remains largely unclear.

METHODS

The expression of prostate cancer-associated transcripts was analyzed in published datasets and further verified in clinical samples and cell lines by RT-qPCR and in situ hybridization assays. Colony formation assay, MTT assay, cell cycle analysis, EdU assay, Transwell migration and invasion assays, wound healing assay, and in vivo experiments were carried out to investigate the function of prostate cancer-associated transcript 6 (PCAT6) in bone metastasis and tumor growth of PCa. Bioinformatic analysis, RNA pull-down, and RIP assays were conducted to identify the proteins binding to PCAT6 and the potential targets of PCAT6. The therapeutic potential of targeting PCAT6 by antisense oligonucleotides (ASO) was further explored in vivo.

RESULTS

PCAT6 was upregulated in PCa tissues with bone metastasis and increased PCAT6 expression predicted poor prognosis in PCa patients. Functional experiments found that PCAT6 knockdown significantly inhibited PCa cell invasion, migration, and proliferation in vitro, as well as bone metastasis and tumor growth in vivo. Mechanistically, METTL3-mediated m6 A modification contributed to PCAT6 upregulation in an IGF2BP2-dependent manner. Furthermore, PCAT6 upregulated IGF1R expression by enhancing IGF1R mRNA stability through the PCAT6/IGF2BP2/IGF1R RNA-protein three-dimensional complex. Importantly, PCAT6 inhibition by ASO in vivo showed therapeutic potential against bone metastasis in PCa. Finally, the clinical correlation of METTL3, IGF2BP2, IGF1R, and PCAT6 was further demonstrated in PCa tissues and cells.

CONCLUSIONS

Our study uncovers a novel molecular mechanism by which the m6 A-induced PCAT6/IGF2BP2/IGF1R axis promotes PCa bone metastasis and tumor growth, suggesting that PCAT6 may serve as a promising prognostic marker and therapeutic target against bone-metastatic PCa.

CDC20 and PTTG1 are Important Biomarkers and Potential Therapeutic Targets for Metastatic Prostate Cancer

INTRODUCTION

Metastatic prostate cancer (mPCa) is responsible for most prostate cancer (PCa) deaths worldwide. The present study aims to explore the molecular differences between mPCa and PCa.

METHODS

The authors downloaded GSE6752, GSE6919, and GSE32269 from the Gene Expression Omnibus and employed integrated analysis to identify differentially expressed genes (DEGs) between mPCa and PCa. Functional and pathway-enrichment analyses were performed, and a protein-protein interaction (PPI) network and modules were constructed. Clinical mPCa specimens were collected to verify the results by performing RT-qPCR. The Cancer Genome Atlas database was used to conduct a survival analysis, and an immunohistochemical assay was performed. The invasion ability of PCa cells was verified by Transwell assay.

RESULTS

One-hundred six consistently DEGs were found in mPCa compared with PCa. DEGs significantly enriched the positive regulation of cell proliferation, cell division, and cell adhesion in small cell lung cancer and PCa. Cell division, nucleoplasm, and cell cycle were selected from the PPI network, and the top 10 hub genes were selected. CDC20 and PTTG1 with genetic alterations were significantly associated with poorer disease-free survival. Immunohistochemical assay results showed that the expression levels of CDC20 and PTTG1 in mPCa were higher than those in PCa. The results of the migration assay indicated that CDC20 and PTTG1 could enhance the migration ability of PCa cells.

CONCLUSION

The present study revealed that CDC20 and PTTG1 contribute more to migration, progression, and poorer prognoses in mPCa compared with PCa. CDC20 and PTTG1 could represent therapeutic targets in mPCa medical research and clinical studies.

Standardized Uptake Value for 18F-Fluorodeoxyglucose Is a Marker of Inflammatory State and Immune Infiltrate in Cervical Cancer

PURPOSE

Chemoradiotherapy for locally advanced cervical cancer fails in over a third of patients. Biomarkers with therapeutic implications are therefore needed. We investigated the relationship between an established prognostic marker, maximum standardized uptake value (SUV_max) on ¹⁸F-fluorodeoxyglucose positron emission tomography, and the inflammatory and immune state of cervical cancers.

EXPERIMENTAL DESIGN

An SUV_max most prognostic for freedom from progression (FFP) was identified and compared with known prognostic clinical variables in a cohort of 318 patients treated with definitive radiation with prospectively collected clinical data. Gene set enrichment analysis (GSEA) and CIBERSORT of whole-transcriptome data from 68 patients were used to identify biological pathways and immune cell subpopulations associated with high SUV_max. IHC using a tissue microarray (TMA, N = 82) was used to validate the CIBERSORT findings. The impact of macrophages on cervical cancer glucose metabolism was investigated in coculture experiments.

RESULTS

SUV_max <11.4 was most prognostic for FFP (P = 0.001). The GSEA showed that high SUV_max is associated with increased gene expression of inflammatory pathways, including JAK/STAT3 signaling. CIBERSORT and CD68 staining of the TMA showed high SUV_max tumors are characterized by a monocyte-predominant immune infiltrate. Coculture of cervical cancer cells with macrophages or macrophage-conditioned media altered glucose uptake, and IL6 and JAK/STAT3 signaling contribute to this effect.

CONCLUSIONS

SUV_max is a prognostic marker in cervical cancer that is associated with activation of inflammatory pathways and tumor infiltration of myeloid-derived immune cells, particularly macrophages. Macrophages contribute to changes in cervical cancer glucose metabolism.See related commentary by Williamson et al., p. 4136.

Differential CircRNA Expression Signatures May Serve as Potential Novel Biomarkers in Prostate Cancer

Circular RNAs (circRNAs), a recently discovered non-coding RNA, have a number of functions including the regulation of miRNA expression. They have been detected in a number of malignancies including prostate cancer (PCa). The differential expression pattern of circRNAs associated with PCa and androgen receptor (AR) status was investigated in this study. circRNA profiling was performed using a high throughout microarray assay on a panel of prostate cell lines, which consisted of normal, benign, and malignant cells (n = 9). circRNAs were more commonly significantly up-regulated (p < 0.05) than downregulated in malignant cell lines (n = 3,409) vs. benign cell lines (n = 2,949). In a grouped analysis based on AR status, there were 2,127 down-regulated circRNAs in androgen independent cell lines compared to 2,236 in androgen dependent cell lines, thus identifying a potential circRNA signature reflective of androgen dependency. Through a bioinformatics approach, the parental genes associated with the top 10 differentially expressed circRNAs were identified such as hsa_circ_0064644, whose predicted parental gene target is RBMS3, and hsa_circ_0060539, whose predicted gene target is SDC4. Furthermore, we identified three circRNAs associated with the parental gene Caprin1 (hsa_circ_0021652, hsa_circ_0000288, and hsa_circ_0021647). Other studies have shown the importance of Caprin1 in PCa cell survival and drug resistance. Given the modified circRNA expression signatures identified here, these hypothesis generating results suggest that circRNAs may serve as potential putative diagnostic and predictive markers in PCa. However, further validation studies are required to assess the true potential of these markers in the clinical setting.

Unraveling the dark matter, long non-coding RNAs, in male reproductive diseases: A narrative review

Recent advances in human transcriptome have revealed the fundamental and functional roles of long non-coding RNA in the susceptibility to diverse diseases and pathological conditions. They participate in wide range of biological processes such as the modulating of chromatin structure, transcription, translation, and post-translation modification. In addition, based on their unique expression profiles and their association with clinical abnormalities such as those of related to male reproductive diseases, they can be used to develop therapeutic methods and biomarkers for screening of the diseases. In this study, we will review the identified lncRNAs and their molecular functions in the pathogenesis of male reproductive diseases such as prostate cancer, benign prostatic hyperplasia, prostatitis, testicular cancer, varicocele, and sperm abnormalities.

Antibody profiling of patients with prostate cancer reveals differences in antibody signatures among disease stages

BACKGROUND

Previous studies of prostate cancer autoantibodies have largely focused on diagnostic applications. So far, there have been no reports attempting to more comprehensively profile the landscape of prostate cancer-associated antibodies. Specifically, it is unknown whether the quantity of antibodies or the types of proteins recognized change with disease progression.

METHODS

A peptide microarray spanning the amino acid sequences of the gene products of 1611 prostate cancer-associated genes was synthesized. Serum samples from healthy male volunteers (n=15) and patients with prostate cancer (n=85) were used to probe the array. These samples included patients with various clinical stages of disease: newly diagnosed localized prostate cancer (n=15), castration-sensitive non-metastatic prostate cancer (nmCSPC, n=40), castration-resistant non-metastatic prostate cancer (n=15) and castration-resistant metastatic disease (n=15). The patients with nmCSPC received treatment with either standard androgen deprivation therapy (ADT) or an antitumor DNA vaccine encoding prostatic acid phosphatase. Serial sera samples from these individuals were also used to probe the array, to secondarily determine whether this approach could be used to detect treatment-related changes.

RESULTS

We demonstrated that this peptide array yielded highly reproducible measurements of serum IgG levels. We found that the overall number of antibody responses did not increase with disease burden. However, the composition of recognized proteins shifted with clinical stage of disease. Our analysis revealed that the largest difference was between patients with castration-sensitive and castration-resistant disease. Patients with castration-resistant disease recognized more proteins associated with nucleic acid binding and gene regulation compared with men in other groups. Our longitudinal data showed that treatments can elicit antibodies detectable by this array, and notably vaccine-treated patients developed increased responses to more proteins over the course of treatment than did ADT-treated patients.

CONCLUSIONS

This study represents the largest survey of prostate cancer-associated antibodies to date. We have been able to characterize the classes of proteins recognized by patients and determine how they change with disease burden. Our findings further demonstrate the potential of this platform for measuring antigen spread and studying responses to immunomodulatory therapies.

Xenograft-based, platform-independent gene signatures to predict response to alkylating chemotherapy, radiation, and combination therapy for glioblastoma

BACKGROUND

Predictive molecular biomarkers to select optimal treatment for patients with glioblastoma and other cancers are lacking. New strategies are needed when large randomized trials with correlative molecular data are not feasible.

METHODS

Gene signatures (GS) were developed from 31 orthotopic glioblastoma patient-derived xenografts (PDXs), treated with standard therapies, to predict benefit from radiotherapy (RT-GS), temozolomide (Chemo-GS), or the combination (ChemoRT-GS). Independent validation was performed in a heterogeneously treated clinical cohort of 502 glioblastoma patients with overall survival as the primary endpoint. Multivariate Cox analysis was used to adjust for confounding variables and evaluate interactions between signatures and treatment.

RESULTS

PDX models recapitulated the clinical heterogeneity of glioblastoma patients. RT-GS, Chemo-GS, and ChemoRT-GS were correlated with benefit from treatment in the PDX models. In independent clinical validation, higher RT-GS scores were associated with increased survival only in patients receiving RT (P = 0.0031, hazard ratio [HR] = 0.78 [0.66-0.92]), higher Chemo-GS scores were associated with increased survival only in patients receiving chemotherapy (P < 0.0001, HR = 0.66 [0.55-0.8]), and higher ChemoRT-GS scores were associated with increased survival only in patients receiving ChemoRT (P = 0.0001, HR = 0.54 [0.4-0.74]). RT-GS and ChemoRT-GS had significant interactions with treatment on multivariate analysis (P = 0.0009 and 0.02, respectively), indicating that they are bona fide predictive biomarkers.

CONCLUSIONS

Using a novel PDX-driven methodology, we developed and validated 3 platform-independent molecular signatures that predict benefit from standard of care therapies for glioblastoma. These signatures may be useful to personalize glioblastoma treatment in the clinic and this approach may be a generalizable method to identify predictive biomarkers without resource-intensive randomized trials.

Characterization and validation of long noncoding RNAs as new candidates in prostate cancer

Background

Long noncoding RNAs (lncRNAs) have been proved to be an important regulator in gene expression. In almost all kinds of cancers, lncRNAs participated in the process of pathogenesis, invasion, and metastasis. Meanwhile, compared with the large amounts of patients, there is rare knowledge about the role of lncRNAs in prostate cancer (PCa).

Material/Method

In this study, lncRNA expression profiles of prostate cancer were detected by Agilent microarray chip, 5 pairs of case and control specimens were involved in. Differentially expressed lncRNAs were screened out by volcano plot for constructing lncRNA-miRNA-mRNA central network. Then, the top ten up-regulated and down-regulated lncRNAs were validated by qRT-PCR in another 5 tumor specimens and 7 para-cancerous/benign contrasts. Furthermore, we searched for the survival curve of the top 10 upregulated and downregulated lncRNAs.

Results

A total of 817 differentially expressed lncRNAs were filtered out by the criteria of fold change (FC) and t-test p < 0.05. Among them, 422 were upregulated, whereas 395 were downregulated in PCa tissues. Gene ontology and KEGG pathway analyses showed that many lncRNAs were implicated in carcinogenesis. lnc-MYL2-4:1 (FC = 0.00141, p = 0.01909) and NR_125857 (FC = 59.27658, p = 0.00128) had the highest magnitude of change. The subsequent qPCR confirmed the expression of NR_125857 was in accordance with the clinical samples. High expression of PCA3, PCAT14 and AP001610.9 led to high hazard ratio while low expression of RP11-279F6.2 led to high hazard ratio.

Conclusions

Our study detected a relatively novel complicated map of lncRNAs in PCa, which may have the potential to investigate for diagnosis, treatment and follow-up in PCa. Our study revealed the expression of NR_125857 in human PCa tissues was most up-regulated. Further studies are needed to investigate to figure out the mechanisms in PCa.

Omics Derived Biomarkers and Novel Drug Targets for Improved Intervention in Advanced Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed malignancies, and the fifth leading cause of cancer related mortality in men. For advanced PCa, radical prostatectomy, radiotherapy, and/or long-term androgen deprivation therapy are the recommended treatment options. However, subsequent progression to metastatic disease after initial therapy results in low 5-year survival rates (29%). Omics technologies enable the acquisition of high-resolution large datasets that can provide insights into molecular mechanisms underlying PCa pathology. For the purpose of this article, a systematic literature search was conducted through the Web of Science Database to critically evaluate recent omics-driven studies that were performed towards: (a) Biomarker development and (b) characterization of novel molecular-based therapeutic targets. The results indicate that multiple omics-based biomarkers with prognostic and predictive value have been validated in the context of PCa, with several of those being also available for commercial use. At the same time, omics-driven potential drug targets have been investigated in pre-clinical settings and even in clinical trials, holding the promise for improved clinical management of advanced PCa, as part of personalized medicine pipelines.

Pan-cancer proteogenomic analysis reveals long and circular noncoding RNAs encoding peptides

Recent studies show that annotated long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) encode for stable, functional peptides that contribute to human development and disease. To systematically discover lncRNAs and circRNAs encoding peptides, we performed a comprehensive integrative analysis of mass spectrometry-based proteomic and transcriptomic sequencing data from >900 patients across nine cancer types. This enabled us to identify 19,871 novel peptides derived from 8,903 lncRNAs. Further, we exploited open reading frames overlapping the backspliced region of circRNAs to identify 3,238 peptides that are uniquely derived from 2,834 circRNAs and not their corresponding linear RNAs. Collectively, our pan-cancer proteogenomic analysis will serve as a resource for evaluating the coding potential of lncRNAs and circRNAs that could aid future mechanistic studies exploring their function in cancer.

The DNA methylation landscape of advanced prostate cancer

Although DNA methylation is a key regulator of gene expression, the comprehensive methylation landscape of metastatic cancer has never been defined. Through whole-genome bisulfite sequencing paired with deep whole-genome and transcriptome sequencing of 100 castration-resistant prostate metastases, we discovered alterations affecting driver genes only detectable with integrated whole-genome approaches. Notably, we observed that 22% of tumors exhibited a novel epigenomic subtype associated with hyper-methylation and somatic mutations in TET2, DNMT3B, IDH1, and BRAF. We also identified intergenic regions where methylation is associated with RNA expression of the oncogenic driver genes AR, MYC and ERG. Finally, we showed that differential methylation during progression preferentially occurs at somatic mutational hotspots and putative regulatory regions. This study is a large integrated study of whole-genome, whole-methylome and whole-transcriptome sequencing in metastatic cancer and provides a comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer.

Recent scenario of long non-coding RNAs as a diagnostic and prognostic biomarkers of prostate cancer

Prostate cancer (CaP) is a leading cause of cancer deaths in the worldwide with broad range of clinical manifestations ranging from relatively indolent to aggressive metastasis. Altered expression of many circulating long non-coding RNAs (lncRNAs), known to have role in tumorigenesis and metastasis, have already been reported in CaP patients. These lncRNAs modulate CaP pathogenesis by modulating multiple genes and thus altering metabolic pathways. Sustained androgen receptor (AR) signaling is one such key feature of castration-resistant prostate cancer, a CaP stage that has unmet need of accurate diagnostic and prognostic tools, that is affected by lncRNAs. In this review, we have discussed the emerging functions and associations of AR lncRNAs in CaP and highlighted their potential implications in cancer diagnostics and therapeutics. Further, extensive literature analysis in this article indicates that there is an immediate unmet need in the translational approach toward the hitherto identified AR lncRNAs. The characterization of AR lncRNAs involved in CaP is not exhaustive and adequate validation studies are still required to corroborate the present results that would be the impending future of basic research setting into clinical practice.

AR and ERG drive the expression of prostate cancer specific long noncoding RNAs

Long noncoding RNAs (lncRNAs) play pivotal roles in cancer development and progression, and some function in a highly cancer-specific manner. However, whether the cause of their expression is an outcome of a specific regulatory mechanism or nonspecific transcription induced by genome reorganization in cancer remains largely unknown. Here, we investigated a group of lncRNAs that we previously identified to be aberrantly expressed in prostate cancer (PC), called TPCATs. Our high-throughput real-time PCR experiments were integrated with publicly available RNA-seq and ChIP-seq data and revealed that the expression of a subset of TPCATs is driven by PC-specific transcription factors (TFs), especially androgen receptor (AR) and ETS-related gene (ERG). Our in vitro validations confirmed that AR and ERG regulated a subset of TPCATs, most notably for EPCART. Knockout of EPCART was found to reduce migration and proliferation of the PC cells in vitro. The high expression of EPCART and two other TPCATs (TPCAT-3-174133 and TPCAT-18-31849) were also associated with the biochemical recurrence of PC in prostatectomy patients and were independent prognostic markers. Our findings suggest that the expression of numerous PC-associated lncRNAs is driven by PC-specific mechanisms and not by random cellular events that occur during cancer development. Furthermore, we report three prospective prognostic markers for the early detection of advanced PC and show EPCART to be a functionally relevant lncRNA in PC.

The Role of Non-coding RNAs in Oncology

For decades, research into cancer biology focused on the involvement of protein-coding genes. Only recently was it discovered that an entire class of molecules, termed non-coding RNA (ncRNA), plays key regulatory roles in shaping cellular activity. An explosion of studies into ncRNA biology has since shown that they represent a diverse and prevalent group of RNAs, including both oncogenic molecules and those that work in a tumor suppressive manner. As a result, hundreds of cancer-focused clinical trials involving ncRNAs as novel biomarkers or therapies have begun and these are likely just the beginning.

SMAD3/SP1 complex-mediated constitutive active loop between lncRNA PCAT7 and TGF-β signaling promotes prostate cancer bone metastasis

Bone metastasis is associated with cancer-related death in patients with prostate cancer (PCa). Long noncoding RNAs (lncRNAs) play critical roles in tumor progression of PCa. Nevertheless, the biological function of lncRNAs in PCa bone metastasis remains unclear. PCAT7 was identified as a bone metastasis-related lncRNA via analyzing TCGA dataset. Meanwhile, PCAT7 was found to be elevated in primary PCa tissues with bone metastasis and associated with bone metastasis status and poor prognosis of patients with PCa. Functionally, our results reveal that PCAT7 overexpression promotes PCa bone metastasis in vivo, as well as migration, invasion, and EMT of PCa cells in vitro; on the contrary, PCAT7 knockdown has an inverse effect. Mechanistically, PCAT7 activates TGF-β/SMAD signaling by upregulating TGFBR1 expression via sponging miR-324-5p. In turn, TGF-β signaling forms a positive feedback loop with PCAT7 via SMAD3/SP1 complex-induced PCAT7 upregulation. Finally, the clinical positive correlation between PCAT7 and TGFBR1 and TGF-β signaling activity, and the negative association with miR-324-5p are further demonstrated in PCa tissues and clinical primary PCa cells. This study reveals a novel mechanism that is responsible for the constitutive activation of TGF-β signaling in PCa bone metastasis, implying that PCAT7 can act as a potential therapeutic target against bone metastasis of PCa via disrupting the constitutive active loop between PCAT7 and TGF-β signaling.

The Immune Landscape of Prostate Cancer and Nomination of PD-L2 as a Potential Therapeutic Target

BACKGROUND

Immunotherapy has been less successful in treating prostate cancer than other solid tumors. We sought to better understand the immune landscape in prostate cancer and identify immune-related biomarkers and potential therapeutic targets.

METHODS

We analyzed gene expression data from 7826 prospectively collected prostatectomy samples (2013-2016), and 1567 retrospective samples with long-term clinical outcomes, for a total of 9393 samples, all profiled on the same commercial clinical platform in a CLIA-certified lab. The primary outcome was distant metastasis-free survival (DMFS). Secondary outcomes included biochemical recurrence-free survival (bRFS), prostate cancer-specific survival (PCSS), and overall survival (OS). All statistical tests were two-sided.

RESULTS

Unsupervised hierarchical clustering of hallmark pathways demonstrated an immune-related tumor cluster. Increased estimated immune content scores based on immune-specific genes from the literature were associated with worse bRFS (hazard ratio [HR] = 1.26 [95% confidence interval [CI] = 1.12 to 1.42]; P < .001), DMFS (HR = 1.34 [95% CI = 1.13 to 1.58]; P < .001), PCSS (HR = 1.53 [95% CI = 1.21 to 1.92]; P < .001), and OS (HR = 1.27 [95% CI = 1.07 to 1.50]; P = .006). Deconvolution using Cibersort revealed that mast cells, natural killer cells, and dendritic cells conferred improved DMFS, whereas macrophages and T-cells conferred worse DMFS. Interestingly, while PD-L1 was not prognostic, consistent with its low expression in prostate cancer, PD-L2 was expressed at statistically significantly higher levels (P < .001) and was associated with worse bRFS (HR = 1.17 [95% CI = 1.03 to 1.33]; P = .01), DMFS (HR = 1.25 [95% CI = 1.05 to 1.49]; P = .01), and PCSS (HR = 1.45 [95% CI = 1.13 to 1.86]; P = .003). PD-L2 was strongly associated with immune-related pathways on gene set enrichment analysis suggesting that it is playing an important role in immune modulation in clinical prostate cancer samples. Furthermore, PD-L2 was correlated with radiation response pathways, and also predicted response to postoperative radiation therapy (PORT) on multivariable interaction analysis (P = .03).

CONCLUSION

In the largest study of its kind to date, these results illustrate the complex relationship between the tumor-immune interaction, prognosis, and response to radiotherapy, and nominate PD-L2 as a potential novel therapeutic target in prostate cancer, potentially in combination with radiotherapy.

Long non-coding RNA LCAL62 / LINC00261 is associated with lung adenocarcinoma prognosis

Background

More than half of non-small cell lung cancer (NSCLC) patients present with metastatic disease at initial diagnosis with an estimated five-year survival rate of ~5%. Despite advances in understanding primary lung cancer oncogenesis metastatic disease remains poorly characterized. Recent studies demonstrate important roles of long non-coding RNAs (lncRNAs) in tumor physiology and as prognostic markers. Therefore, we present the first transcriptome analysis to identify lncRNAs altered in metastatic lung adenocarcinoma leading to the discovery and characterization of the lncRNA LCAL62 as a prognostic biomarker.

Patients and methods

RNA-Seq, microarray, nanoString expression, and clinical data from 1,116 LUAD patients across six independent cohorts and 83 LUAD cell lines were used to discover and evaluate the survival association of metastasis associated lncRNAs. Coexpression and gene set enrichment analyses were used to establish gene regulatory networks and implicate metastasis associated lncRNAs in specific biological processes.

Results

Our integrative analysis discovered LCAL62 as the most down-regulated lncRNA in metastasis. Further low LCAL62 expression promoted aggressive phenotypes and regulated genes associated with metastasis (such as metastasis repressor FOXA2). Low LCAL62 expression corresponded to poor overall patient survival across five independent lung adenocarcinoma cohorts (n = 881) including our own nanoString validation cohort.

Conclusion

We discovered that LCAL62 was down-regulated in lung cancer progression to promote invasive phenotypes, and lower expression was significantly associated with poor patient outcome and aggressive lung adenocarcinoma.

Prognostic impact of lncRNA-ATB expression in malignant solid tumors: A meta-analysis

PURPOSE

Numerous studies have reported the prognostic role of lncRNA-ATB high expression in solid tumours, but its prognostic effect is still uncertain. Therefore, the purpose of this meta-analysis was to further comprehensively verify the prognostic role of the lncRNA-ATB high expression in solid tumours.

METHODS

A literature search was performed using the electronic platforms to obtain relevant research studies published up to 31 May 2019. Confidence intervals of research endpoints in each study were extracted and merged. All data analysis was performed using Stata12.0 software.

RESULTS

A total of 2120 patients with solid cancers in 14 studies were enrolled in our meta-analysis eventually. The analysis results revealed that high expression of lncRNA-ATB was related to lower OS (HR:1.46, P < 0.001), shorter DFS(HR:1.73, P < 0.001), and earlier RFS (HR:2.67, P < 0.001). Besides, the high expression of lncRNA-ATB has a considerable risk of lymph node metastasis (OR:2.13, P = 0.017)and perineural invasion (OR:1.58, P = 0.018).

CONCLUSIONS

Meta-analysis showed that the high lncRNA-ATB expression was a poor prognostic marker in multiple cancer types. The high expression of lncRNA-ATB symbolizes the high risk of lymph node metastasis and perineural invasion in cancer patients.

A nomogram combining long non-coding RNA expression profiles and clinical factors predicts survival in patients with bladder cancer

Bladder cancer (BCa) is a heterogeneous disease with various tumorigenic mechanisms and clinical behaviors. The current tumor-node-metastasis (TNM) staging system is inadequate to predict overall survival (OS) in BCa patients. We developed a BCa-specific, long-non-coding-RNA (lncRNA)-based nomogram to improve survival prediction in BCa. We obtained the large-scale gene expression profiles of samples from 414 BCa patients in The Cancer Genome Atlas database. Using an lncRNA-mining computational framework, we identified three OS-related lncRNAs among 826 lncRNAs that were differentially expressed between BCa and normal samples. We then constructed a three-lncRNA signature, which efficiently distinguished high-risk from low-risk patients and was even viable in the TNM stage-II, TNM stage-III and ≥65-year-old subgroups (all P<0.05). Using clinical risk factors, we developed a signature-based nomogram, which performed better than the molecular signature or clinical factors alone for prognostic prediction. A bioinformatical analysis revealed that the three OS-related lncRNAs were co-expressed with genes involved in extracellular matrix organization. Functional assays demonstrated that RNF144A-AS1, one of the three OS-related lncRNAs, promoted BCa cell migration and invasion in vitro. Our three-lncRNA signature-based nomogram effectively predicts the prognosis of BCa patients, and could potentially be used for individualized management of such patients.

ZBTB7A Mediates the Transcriptional Repression Activity of the Androgen Receptor in Prostate Cancer

Loss of expression of context-specific tumor suppressors is a critical event that facilitates the development of prostate cancer. Zinc finger and BTB domain containing transcriptional repressors, such as ZBTB7A and ZBTB16, have been recently identified as tumor suppressors that play important roles in preventing prostate cancer progression. In this study, we used combined ChIP-seq and RNA-seq analyses of prostate cancer cells to identify direct ZBTB7A-repressed genes, which are enriched for transcriptional targets of E2F, and identified that the androgen receptor (AR) played a critical role in the transcriptional suppression of these E2F targets. AR recruitment of the retinoblastoma protein (Rb) was required to strengthen the E2F-Rb transcriptional repression complex. In addition, ZBTB7A was rapidly recruited to the E2F-Rb binding sites by AR and negatively regulated the transcriptional activity of E2F1 on DNA replication genes. Finally, ZBTB7A suppressed the growth of castration-resistant prostate cancer (CRPC) in vitro and in vivo, and overexpression of ZBTB7A acted in synergy with high-dose testosterone treatment to effectively prevent the recurrence of CRPC. Overall, this study provides novel molecular insights of the role of ZBTB7A in CRPC cells and demonstrates globally its critical role in mediating the transcriptional repression activity of AR. SIGNIFICANCE: ZBTB7A is recruited to the E2F-Rb binding sites by AR and negatively regulates the transcriptional activity of E2F1 on DNA replication genes.

Assessment of biochemical recurrence of prostate cancer (Review)

The assessment of the risk of biochemical recurrence (BCR) is critical in the management of males with prostate cancer (PC). Over the past decades, a comprehensive effort has been focusing on improving risk stratification; a variety of models have been constructed using PC-associated pathological features and molecular alterations occurring at the genome, protein and RNA level. Alterations in RNA expression (lncRNA, miRNA and mRNA) constitute the largest proportion of the biomarkers of BCR. In this article, we systemically review RNA-based BCR biomarkers reported in PubMed according to the PRISMA guidelines. Individual miRNAs, mRNAs, lncRNAs and multi-gene panels, including the commercially available signatures, Oncotype DX and Prolaris, will be discussed; details related to cohort size, hazard ratio and 95% confidence intervals will be provided. Mechanistically, these individual biomarkers affect multiple pathways critical to tumorigenesis and progression, including epithelial-mesenchymal transition (EMT), phosphatase and tensin homolog (PTEN), Wnt, growth factor receptor, cell proliferation, immune checkpoints and others. This variety in the mechanisms involved not only validates their associations with BCR, but also highlights the need for the coverage of multiple pathways in order to effectively stratify the risk of BCR. Updates of novel biomarkers and their mechanistic insights are considered, which suggests new avenues to pursue in the prediction of BCR. Additionally, the management of patients with BCR and the potential utility of the stratification of the risk of BCR in salvage treatment decision making for these patients are briefly covered. Limitations will also be discussed.

The novel long noncoding RNA LOC283070 is involved in the transition of LNCaP cells into androgen-independent cells via its interaction with PHB2

We sought to investigate the underlying mechanism of action of the long noncoding RNA (lncRNA) LOC283070 in the development of androgen independence in prostate cancer. The interactions between LOC283070 and target proteins were investigated by RNA pull-down and RNA-binding protein immunoprecipitation (RIP) assays. Subcellular fractionation and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) were used to detect the subcellular localization of LOC283070. Western blotting was performed to detect the expression of prohibitin 2 (PHB2). Luciferase activity assays were performed to evaluate the effects of LOC283070 and PHB2 on the androgen receptor (AR) signaling pathway. A methyl thiazolyl tetrazolium (MTT) assay and a growth curve assay were used to test cell viability. Flow cytometry was performed to analyze cell cycles. A transwell assay was employed to test cell migration. We identified PHB2 as an interaction partner of LOC283070 in the pull-down and RIP experiments. Furthermore, we confirmed that the enrichment of LOC283070 with PHB2 in androgen-independent LNCaP (LNCaP-AI) cells was much greater than that in LNCaP cells. Moreover, the expression of PHB2 was not significantly different between the two cell lines, and the expression of LOC283070 in the nuclei of the LNCaP-AI cells was significantly greater than that in the LNCaP cells. In vitro data revealed that PHB2 overexpression significantly inhibited AR activity and cell proliferation and migration and induced accumulation of prostate cancer cells in G0/G1 phase. Moreover, the overexpression of LOC283070 fully abrogated the effects of PHB2 overexpression. In conclusion, we found that LOC283070 can bind to PHB2 located in the nucleus and inhibit its effect, and this is one of the mechanisms by which LOC283070 is involved in the transition of LNCaP cells into androgen-independent cells.

The evolution of long noncoding RNA acceptance in prostate cancer initiation, progression, and its clinical utility in disease management

CONTEXT

It is increasingly evident that non-protein-coding regions of the genome can give rise to transcripts that form functional layers of the cancer genome. One of most abundant classes in these regions is long noncoding RNAs (lncRNAs). They have gained increasing attention in prostate cancer (PCa) and paved the way for a greater understanding of these cryptic regulators in cancer.

OBJECTIVE

To review current research exploring the functional biology of lncRNAs in PCa over the past three decades.

EVIDENCE ACQUISITION

A systematic review was performed using PubMed to search for reports with terms "long noncoding RNA", "prostate", and "cancer" over the past 30 yr (1988-2018).

EVIDENCE SYNTHESIS

We comprehensively surveyed the literature collected and summarise experiments leading to the characterisation of lncRNAs in PCa. A historical timeline of lncRNA identification is described, where each lncRNA is categorised mechanistically and within the primary areas of carcinogenesis: tumour risk and initiation, tumour promotion, tumour suppression, and tumour treatment resistance. We describe select lncRNAs that exemplify these areas. We also review whether these lncRNAs have a clinical utility in PCa diagnosis, prognosis, and prediction, and as therapeutic targets.

CONCLUSIONS

The biology of lncRNA is multifaceted, demonstrating a complex array of molecular and cellular functions. These studies reveal that lncRNAs are involved in every stage of PCa. Their clinical utility for diagnosis, prognosis, and prediction of PCa is well supported, but further evaluation for their therapeutic candidacy is needed. We provide a detailed resource and view inside the lncRNA landscape for other cancer biologists, oncologists, and clinicians.

PATIENT SUMMARY

In this study, we review current knowledge of the non-protein-coding genome in prostate cancer (PCa). We conclude that many of these regions are functional and a source of accurate biomarkers in PCa. With a strong research foundation, they hold promise as future therapeutic targets, yet clinical trials are necessary to determine their intrinsic value to PCa disease management.

Long noncoding RNA LINC02418 regulates MELK expression by acting as a ceRNA and may serve as a diagnostic marker for colorectal cancer

Some types of long noncoding RNAs (lncRNAs) are aberrantly expressed in human diseases, including cancer. However, the overall biological roles and clinical significances of most lncRNAs in colorectal cancer (CRC) are not fully understood. First, The Cancer Genome Atlas (TCGA) was analyzed to identify differentially expressed lncRNAs between CRC tissues and noncancerous tissues. We identified that LINC02418 was highly expressed in CRC tissues and cell lines. Next, we evaluated the effect of LINC02418 on CRC tumorigenesis and its regulatory functions of absorbing microRNA and indirectly stimulating protein expression by acting as a ceRNA. Mechanistically, LINC02418 acted as a ceRNA to upregulate MELK expression by absorbing miR-1273g-3p. In addition, the diagnostic performance of cell-free LINC02418 and exosomal LINC02418 were both evaluated by the receiver operating characteristic curve and the area under the curve (AUC). Exosomal LINC02418 could distinguish the patients with CRC from the healthy controls (AUC = 0.8978, 95% confidence interval = 0.8644–0.9351) better than cell-free LINC02418 (AUC = 0.6784, 95% confidence interval = 0.6116–0.7452). Collectively, we determined that LINC02418 was significantly overexpressed in CRC and that the LINC02418–miR-1273g-3p–MELK axis played a critical role in CRC tumorigenesis. Finally, exosomal LINC02418 is a promising, novel biomarker that can be used for the clinical diagnosis of CRC.

The previously uncharacterized lncRNA APP promotes prostate cancer progression by acting as a competing endogenous RNA

Long noncoding RNAs (lncRNAs) promote cell proliferation, migration, invasion and castration resistance in prostate cancer (PCa). Understanding the inherited molecular mechanisms by which lncRNAs contribute to the progression of PCa to a lethal disease could have an important impact on cancer detection, diagnosis and prognosis. In our study, PCa-associated lncRNA transcripts from RNA-seq data were identified and screened via bioinformatics analysis, NCBI annotations and literature review. We identified a novel lncRNA, lncAPP (lncRNA activated in PCa progression), which activates in PCa progression and is expressed in primary tumor tissues and urine samples of patients with localized or advanced PCa. Urinary-based lncAPP is a promising biomarker for predicting PCa progression. In vitro and in vivo studies demonstrated that lncAPP enhanced cell proliferation and promoted migration and invasion. The underlying mechanism of lncRNA was investigated by RNA immunoprecipitation, dual-luciferase reporter system assay, etc. Upregulation of lncAPP promoted cell migration and invasion via competitively binding miR218 to facilitate ZEB2/CDH2 expression. In addition, in vivo subcutaneous tumor xenograft models and tail intravenously injection metastatic models were constructed to evaluate lncRNA function. Targeting lncAPP/miR218 axis in cell lines and tumor xenografts restrained tumor progression properties both in vitro and in vivo. These results establish that lncAPP/miR218 axis plays a critical role in PCa progression, and they also suggest new strategies to prevent tumor progression for therapeutic purposes.

Long non-coding RNAs in prostate cancer: Biological and clinical implications

Prostate cancer (PCa) is a major health issue in the Western world. Current clinical imperatives for this disease include better stratification of indolent versus aggressive disease to enable improved patient management, as well as the identification of more effective therapies for the prevention and treatment of metastatic and therapy-resistant PCa. The advent of next-generation transcriptomics led to the identification of an important class of molecules, long non-coding RNAs (lncRNAs). LncRNAs have critical functions in normal physiology, but their dysregulation has also been implicated in the development and progression of a variety of cancers, including PCa. Importantly, a subset of lncRNAs are highly prostate-specific, suggesting potential for utility as both biomarkers and therapeutic targets. In this review, we summarise the biology of lncRNAs and their mechanisms of action in the development and progression of prostate cancer. Additionally, we cast a critical eye over the potential for this class of molecules to impact on clinical practice.

STAT3-induced upregulation of lncRNA CASC11 promotes the cell migration, invasion and epithelial-mesenchymal transition in hepatocellular carcinoma by epigenetically silencing PTEN and activating PI3K/AKT signaling pathway

Accumulating evidence suggest that long noncoding RNAs (lncRNAs) are dysregulated in various tumors and serve as crucial regulators in biological processes. Based on The Cancer Genome Atlas (TCGA) database, upregulation of CASC11 was associated with the low overall survival rate of patients with Hepatocellular carcinoma (HCC). However, the function and mechanism of lncRNA CASC11 in the progression of HCC remain unclear. Therefore, we further analyzed the expression pattern and biological role of CASC11 in HCC. CASC11 was found to be overexpressed in HCC tissues and cell lines and predicted a poor prognosis. Loss of CASC11 function efficiently suppressed cell migration, invasion and epithelial-mesenchymal transition (EMT). The mechanism which led to the upregulation of CASC11 was investigated. CASC11 was found to be activated by the transcription factor STAT3. Mechanically, the enhancer of zeste homolog 2 (EZH2) was found to be a binding partner of CASC11. Moreover, CASC11 epigenetically silenced PTEN by binding with EZH2. Finally, rescue assays were conducted to make confirmation. The present results revealed that CASC11 may be potential therapeutic target in HCC.

Dysregulated gene expression predicts tumor aggressiveness in African-American prostate cancer patients

Molecular mechanisms underlying the health disparity of prostate cancer (PCa) have not been fully determined. In this study, we applied bioinformatic approach to identify and validate dysregulated genes associated with tumor aggressiveness in African American (AA) compared to Caucasian American (CA) men with PCa. We retrieved and analyzed microarray data from 619 PCa patients, 412 AA and 207 CA, and we validated these genes in tumor tissues and cell lines by Real-Time PCR, Western blot, immunocytochemistry (ICC) and immunohistochemistry (IHC) analyses. We identified 362 differentially expressed genes in AA men and involved in regulating signaling pathways associated with tumor aggressiveness. In PCa tissues and cells, NKX3.1, APPL2, TPD52, LTC4S, ALDH1A3 and AMD1 transcripts were significantly upregulated (p < 0.05) compared to normal cells. IHC confirmed the overexpression of TPD52 (p = 0.0098) and LTC4S (p < 0.0005) in AA compared to CA men. ICC and Western blot analyses additionally corroborated this observation in PCa cells. These findings suggest that dysregulation of transcripts in PCa may drive the disparity of PCa outcomes and provide new insights into development of new therapeutic agents against aggressive tumors. More studies are warranted to investigate the clinical significance of these dysregulated genes in promoting the oncogenic pathways in AA men.

Transcriptomic heterogeneity in multifocal prostate cancer

BACKGROUND

Commercial gene expression assays are guiding clinical decision making in patients with prostate cancer, particularly when considering active surveillance. Given heterogeneity and multifocality of primary prostate cancer, such assays should ideally be robust to the coexistence of unsampled higher grade disease elsewhere in the prostate in order to have clinical utility. Herein, we comprehensively evaluated transcriptomic profiles of primary multifocal prostate cancer to assess robustness to clinically relevant multifocality.

METHODS

We designed a comprehensive, multiplexed targeted RNA-sequencing assay capable of assessing multiple transcriptional classes and deriving commercially available prognostic signatures, including the Myriad Prolaris Cell Cycle Progression score, the Oncotype DX Genomic Prostate Score, and the GenomeDX Decipher Genomic Classifier. We applied this assay to a retrospective, multi-institutional cohort of 156 prostate cancer samples. Derived commercial biomarker scores for 120 informative primary prostate cancer samples from 44 cases were determined and compared.

RESULTS

Derived expression scores were positively correlated with tumor grade (rS = 0.53-0.73; all P < 0.001), both within the same case and across the entire cohort. In cases of extreme grade-discordant multifocality (co-occurrence of grade group 1 [GG1] and ≥GG4 foci], gene expression scores were significantly lower in low- (GG1) versus high-grade (≥GG4) foci (all P < 0.001). No significant differences in expression scores, however, were observed between GG1 foci from prostates with and without coexisting higher grade cancer (all P > 0.05).

CONCLUSIONS

Multifocal, low-grade and high-grade prostate cancer foci exhibit distinct prognostic expression signatures. These findings demonstrate that prognostic RNA expression assays performed on low-grade prostate cancer biopsy tissue may not provide meaningful information on the presence of coexisting unsampled aggressive disease.

FUNDING

Prostate Cancer Foundation, National Institutes of Health (U01 CA214170, R01 CA183857, University of Michigan Prostate Specialized Program of Research Excellence [S.P.O.R.E.] P50 CA186786-05, Weill Cornell Medicine S.P.O.R.E. P50 CA211024-01A1), Men of Michigan Prostate Cancer Research Fund, University of Michigan Comprehensive Cancer Center core grant (2-P30-CA-046592-24), A. Alfred Taubman Biomedical Research Institute, and Department of Defense.

Pathological bases and clinical impact of long noncoding RNAs in prostate cancer: a new budding star

Long non-coding RNAs (lncRNAs) are functional RNAs longer than 200 nucleotides. Recent advances in the non-protein coding part of human genome analysis have discovered extensive transcription of large RNA transcripts that lack coding protein function, termed non-coding RNA (ncRNA). It is becoming evident that lncRNAs may be an important class of pervasive genes involved in carcinogenesis and metastasis. However, the biological and molecular mechanisms of lncRNAs in diverse diseases are not yet fully understood. Thus, it is anticipated that more efforts should be made to clarify the lncRNA world. Moreover, accumulating evidence has demonstrated that many lncRNAs are dysregulated in prostate cancer (PC) and closely related to tumorigenesis, metastasis, and prognosis or diagnosis. In this review, we will briefly outline the regulation and functional role of lncRNAs in PC. Finally, we discussed the potential of lncRNAs as prospective novel targets in PC treatment and biomarkers for PC diagnosis.

The use of long non-coding RNAs as prognostic biomarkers and therapeutic targets in prostate cancer

Prostate cancer is the most common cancer in men and the second leading cause of cancer-related deaths. The most used biomarker to detect prostate cancer is Prostate Specific Antigen (PSA), whose levels are measured in serum. However, it has been recently established that molecular markers of cancer should not be based solely on genes and proteins but should also reflect other genomic traits; long non-coding RNAs (lncRNAs) serve this purpose. lncRNAs are transcripts of >200 bases that do not encode proteins and that have been shown to display abnormal expression profiles in different types of cancer. Experimental studies have highlighted lncRNAs as potential biomarkers for prognoses and treatments in patients with different types of cancer, including prostate cancer, where the PCA3 lncRNA is currently used as a diagnostic tool and management strategy. With the development of genomic technologies, particularly next-generation sequencing (NGS), several other lncRNAs have been linked to prostate cancer and are currently under validation for their medical use. In this review, we will discuss different strategies for the discovery of novel lncRNAs that can be evaluated as prognostic biomarkers, the clinical impact of these lncRNAs and how lncRNAs can be used as potential therapeutic targets.

Long noncoding RNA PCAT-14 induces proliferation and invasion by hepatocellular carcinoma cells by inducing methylation of miR-372

Long non-coding RNAs (lncRNAs) regulate oncogenesis by inducing methylation of CpG islands to silence target genes. Here we show that the lncRNA PCAT-14 is overexpressed in patients with hepatocellular carcinoma (HCC), and is associated with a poor prognosis after surgery. Our results demonstrate that PCAT-14 promotes proliferation, invasion, and cell cycle arrest in HCC cells. In addition, PCAT-14 inhibits miR-372 expression by inducing methylation of the miR-372 promoter. Simultaneously, miR-372 eliminates the effects of PCAT-14 on proliferation, invasion, and cell cycle in HCC cells. Moreover, PCAT-14 regulates expression of ATAD2 and activation of the Hedgehog pathway via miR-372. These findings indicate that PCAT-14 plays an important role in HCC, and may serve as a novel prognostic factor and therapeutic target.

Carcinogenesis in prostate cancer: The role of long non-coding RNAs

LncRNAs appear to play a considerable role in tumourigenesis through regulating key processes in cancer cells such as proliferative signalling, replicative immortality, invasion and metastasis, evasion of growth suppressors, induction of angiogenesis and resistance to apoptosis. LncRNAs have been reported to play a role in prostate cancer, particularly in regulating the androgen receptor signalling pathway. In this review article, we summarise the role of 34 lncRNAs in prostate cancer with a particular focus on their role in the androgen receptor signalling pathway and the epithelial to mesenchymal transition pathway.

Long non-coding RNA GAS5 and ZFAS1 are prognostic markers involved in translation targeted by miR-940 in prostate cancer

Identification of prognostic biomarkers helps facilitate the prediction of patient outcomes as well as guide treatments. Accumulating evidence now suggests that long non-coding RNAs (lncRNAs) play key roles in tumor progression with diagnostic and prognostic values. However, little is known about the biological functions of lncRNAs and how they contribute to the pathogenesis of cancer. Herein, we performed weighted correlation network analysis (WGCNA) on 380 RNA-seq samples from prostate cancer patients to create networks comprising of microRNAs, lncRNAs, and protein-coding genes. Our analysis revealed expression modules that associated with pathological parameters. More importantly, we identified a gene module that is involved in protein translation and is associated with patient survival. In this gene module, we explored the regulation axis involving GAS5, ZFAS1, and miR-940. We show that GAS5, ZFAS1, and miR-940 are up-regulated in tumors relative to normal prostate tissues, and high expression of either lncRNA is an indicator of poor patient outcome. Finally, we constructed a co-expression network involving GAS5, ZFAS1, and miR-940, as well as the targets of miR-940. Our results show that GAS5 and ZFAS1 are targeted by miR-940 via NAA10 and RPL28. Taken together, co-expression analysis of gene expression profiling from RNA-seq can accelerate the identification and functional characterization of novel prognostic markers in prostate cancer.

The prognostic value of abnormally expressed lncRNAs in prostatic carcinoma: A systematic review and meta-analysis

BACKGROUND

Several long noncoding RNAs (lncRNAs) are abnormally expressed in prostate cancer (PCa), suggesting that they could serve as novel prognostic markers. The current meta-analysis was undertaken to better define the prognostic value of various lncRNAs in PCa.

METHODS

The PubMed, Embase, Medline, and Cochrane Library databases were systematically searched up to February 19, 2017, to retrieve eligible articles. Outcomes analyzed were biochemical recurrence-free survival (BRFS), overall survival (OS), metastasis-free survival (MFS), and prostate cancer-specific survival (PCSS). Pooled hazard ratios (HRs) and 95% confidence intervals (95%CIs) were calculated using fixed-effects or random-effects models.

RESULTS

A total of 10 studies, evaluating 11 PCa-related lncRNAs, were included in the meta-analysis. Pooled results indicate that the abnormal expression of candidate lncRNAs in PCa samples predicted poor BRFS (HR: 1.67, 95%CI: 1.37-2.04, P < .05), without significant heterogeneity among studies (I = 44%, P = .06). Low PCAT14 expression was negatively associated with OS (HR: 0.66, 95%CI: 0.54-0.79, P < .05), MFS (HR: 0.59, 95%CI: 0.48-0.72, P < .05), and PCSS (HR: 0.50, 95%CI: 0.38-0.66, P < .05). Again, there was no significant heterogeneity among studies. The robustness of our results was confirmed by sensitivity and publication bias analyses.

CONCLUSION

We conclude that expression analysis of selected lncRNAs may be of prognostic value in PCa patients.