The ERG-Regulated LINC00920 Promotes Prostate Cancer Cell Survival via the 14-3-3ε-FOXO Pathway

N6-methyladenosine modified lncRNAs signature for stratification of biochemical recurrence in prostate cancer

Nonmutational epigenetic reprogramming is a crucial mechanism contributing to the pronounced heterogeneity of prostate cancer (PCa). Among these mechanisms, N6-methyladenosine (m6A)-modified long non-coding RNAs (lncRNAs) have emerged as key players. However, the precise roles of m6A-modified lncRNAs in PCa remain to be elucidated. In this study, methylated RNA immunoprecipitation sequencing (MeRIP-seq) was conducted on primary and metastatic PCa samples, leading to the identification of 21 lncRNAs exhibiting differential methylation and expression patterns. We further established a PCa prognostic signature, named m6A-modified lncRNA score (mLs), based on 9 differential methylated lncRNAs in 4 multicenter cohorts. The high mLs score cohort exhibited a tendency for earlier biochemical recurrence (BCR) compared to the low mLs score cohort. Remarkably, the predictive performance of the mLs score surpassed that of five previously reported lncRNA-based signatures. Functional enrichment analysis underscored a negative correlation between the mLs score and lipid metabolism. Additionally, through MeRIP-qPCR, we pinpointed a hub gene, MIR210HG, which was validated through in vitro and in vivo experiments. These findings collectively illuminate the landscape of m6A-methylated lncRNAs in PCa tissue via MeRIP-seq and harness this information to prognosticate PCa outcomes using the mLs score. Furthermore, our study validates, both experimentally and mechanistically, the facilitative role of MIR210HG in driving PCa progression.

14-3-3ε: a protein with complex physiology function but promising therapeutic potential in cancer

Over the past decade, the role of the 14-3-3 protein has received increasing interest. Seven subtypes of 14-3-3 proteins exhibit high homology; however, each subtype maintains its specificity. The 14-3-3ε protein is involved in various physiological processes, including signal transduction, cell proliferation, apoptosis, autophagy, cell cycle regulation, repolarization of cardiac action, cardiac development, intracellular electrolyte homeostasis, neurodevelopment, and innate immunity. It also plays a significant role in the development and progression of various diseases, such as cardiovascular diseases, inflammatory diseases, neurodegenerative disorders, and cancer. These immense and various involvements of 14-3-3ε in diverse processes makes it a promising target for drug development. Although extensive research has been conducted on 14-3-3 dimers, studies on 14-3-3 monomers are limited. This review aimed to provide an overview of recent reports on the molecular mechanisms involved in the regulation of binding partners by 14-3-3ε, focusing on issues that could help advance the frontiers of this field. Video Abstract.

Histone methyltransferase SUV39H2 regulates apoptosis and chemosensitivity in prostate cancer through AKT/FOXO signaling pathway

Prostate cancer (PCa) is one of the most common malignant tumors that exhibit both chemoresistance and recurrence. SUV39H2 is highly expressed in many types of human tumors, but its role in the development and progression of PCa has never been clarified. The aim of this study is to elucidate the role of SUV39H2 in the development and progression of PCa, its association with the AKT/FOXO signaling pathway, and its potential implications for PCa diagnosis and treatment. SUV39H2 expression was analyzed in The Cancer Genome Atlas (TCGA) and genotype tissue expression pan-cancer data. The TCGA database was evaluated for SUV39H2 enrichment and its correlation to immune cell infiltration. SUV39H2 levels in PCa tissues and control tissues were determined in 30 patients using qPCR and IHC. Clinical relevance was assessed via The Cancer Genome Atlas (TCGA). In vitro assessments including colony formation assays, Western Blot analysis, CCK-8 assays, and flow cytometry were utilized to establish SUV39H2's contribution to PCa cell growth. The influence of SUV39H2 on PC3 and DU145 cell proliferation was assessed through a cell line-derived xenograft model. Sphere formation assays and qPCR were employed to delineate SUV39H2's role in PCa stemness and chemosensitivity. In vitro macrophage polarization assays provided insights into SUV39H2's association with M2 macrophages, while enrichment analysis shed light on its role in FOXO signaling. PCa tissues expressed higher levels of SUV39H2 than normal tissues. By knocking down SUV39H2, PCa cells were made more chemosensitive to docetaxel and cell proliferation and stemness were inhibited. Additionally, SUV39H2 knockdown significantly inhibited in vivo PCa cell growth and inhibited the polarization of macrophages. Furthermore, SUV39H2 was found to regulate AKT/FOXO signaling by increasing Akt and FOXO3a phosphorylation. Our findings highlight SUV39H2's role in PCa cell apoptosis and chemosensitivity mainly by regulating the AKT/FOXO signaling pathway and suggest that SUV39H2 could be a potential target for PCa diagnosis and treatment.

Importance of long non-coding RNAs in the pathogenesis, diagnosis, and treatment of prostate cancer

Long non-coding RNAs (lncRNAs) are regulatory transcripts with essential roles in the pathogenesis of almost all types of cancers, including prostate cancer. They can act as either oncogenic lncRNAs or tumor suppressor ones in prostate cancer. Small nucleolar RNA host genes are among the mostly assessed oncogenic lncRNAs in this cancer. PCA3 is an example of oncogenic lncRNAs that has been approved as a diagnostic marker in prostate cancer. A number of well-known oncogenic lncRNAs in other cancers such as DANCR, MALAT1, CCAT1, PVT1, TUG1 and NEAT1 have also been shown to act as oncogenes in prostate cancer. On the other hand, LINC00893, LINC01679, MIR22HG, RP1-59D14.5, MAGI2-AS3, NXTAR, FGF14-AS2 and ADAMTS9-AS1 are among lncRNAs that act as tumor suppressors in prostate cancer. LncRNAs can contribute to the pathogenesis of prostate cancer via modulation of androgen receptor (AR) signaling, ubiquitin-proteasome degradation process of AR or other important signaling pathways. The current review summarizes the role of lncRNAs in the evolution of prostate cancer with an especial focus on their importance in design of novel biomarker panels and therapeutic targets.

Interactions between 14-3-3 Proteins and Actin Cytoskeleton and Its Regulation by microRNAs and Long Non-Coding RNAs in Cancer

14-3-3s are a family of structurally similar proteins that bind to phosphoserine or phosphothreonine residues, forming the central signaling hub that coordinates or integrates various cellular functions, thereby controlling many pathways important in cancer, cell motility, cell death, cytoskeletal remodeling, neuro-degenerative disorders and many more. Their targets are present in all cellular compartments, and when they bind to proteins they alter their subcellular localization, stability, and molecular interactions with other proteins. Changes in environmental conditions that result in altered homeostasis trigger the interaction between 14-3-3 and other proteins to retrieve or rescue homeostasis. In circumstances where these regulatory proteins are dysregulated, it leads to pathological conditions. Therefore, deeper understanding is needed on how 14-3-3 proteins bind, and how these proteins are regulated or modified. This will help to detect disease in early stages or design inhibitors to block certain pathways. Recently, more research has been devoted to identifying the role of MicroRNAs, and long non-coding RNAs, which play an important role in regulating gene expression. Although there are many reviews on the role of 14-3-3 proteins in cancer, they do not provide a holistic view of the changes in the cell, which is the focus of this review. The unique feature of the review is that it not only focuses on how the 14-3-3 subunits associate and dissociate with their binding and regulatory proteins, but also includes the role of micro-RNAs and long non-coding RNAs and how they regulate 14-3-3 isoforms. The highlight of the review is that it focuses on the role of 14-3-3, actin, actin binding proteins and Rho GTPases in cancer, and how this complex is important for cell migration and invasion. Finally, the reader is provided with super-resolution high-clarity images of each subunit of the 14-3-3 protein family, further depicting their distribution in HeLa cells to illustrate their interactions in a cancer cell.

Long Noncoding RNAs and Circular RNAs Regulate AKT and Its Effectors to Control Cell Functions of Cancer Cells

AKT serine-threonine kinase (AKT) and its effectors are essential for maintaining cell proliferation, apoptosis, autophagy, endoplasmic reticulum (ER) stress, mitochondrial morphogenesis (fission/fusion), ferroptosis, necroptosis, DNA damage response (damage and repair), senescence, and migration of cancer cells. Several lncRNAs and circRNAs also regulate the expression of these functions by numerous pathways. However, the impact on cell functions by lncRNAs and circRNAs regulating AKT and its effectors is poorly understood. This review provides comprehensive information about the relationship of lncRNAs and circRNAs with AKT on the cell functions of cancer cells. the roles of several lncRNAs and circRNAs acting on AKT effectors, such as FOXO, mTORC1/2, S6K1/2, 4EBP1, SREBP, and HIF are explored. To further validate the relationship between AKT, AKT effectors, lncRNAs, and circRNAs, more predicted AKT- and AKT effector-targeting lncRNAs and circRNAs were retrieved from the LncTarD and circBase databases. Consistently, using an in-depth literature survey, these AKT- and AKT effector-targeting database lncRNAs and circRNAs were related to cell functions. Therefore, some lncRNAs and circRNAs can regulate several cell functions through modulating AKT and AKT effectors. This review provides insights into a comprehensive network of AKT and AKT effectors connecting to lncRNAs and circRNAs in the regulation of cancer cell functions.

Annotation and functional characterization of long noncoding RNAs deregulated in pancreatic adenocarcinoma

PURPOSE

Transcriptome analysis of pancreatic ductal adenocarcinoma (PDAC) has been useful to identify gene expression changes that sustain malignant phenotypes. Yet, most studies examined only tumor tissues and focused on protein-coding genes, leaving long non-coding RNAs (lncRNAs) largely underexplored.

METHODS

We generated total RNA-Seq data from patient-matched tumor and nonmalignant pancreatic tissues and implemented a computational pipeline to survey known and novel lncRNAs. siRNA-mediated knockdown in tumor cell lines was performed to assess the contribution of PDAC-associated lncRNAs to malignant phenotypes. Gene co-expression network and functional enrichment analyses were used to assign deregulated lncRNAs to biological processes and molecular pathways.

RESULTS

We detected 9,032 GENCODE lncRNAs as well as 523 unannotated lncRNAs, including transcripts significantly associated with patient outcome. Aberrant expression of a subset of novel and known lncRNAs was confirmed in patient samples and cell lines. siRNA-mediated knockdown of a subset of these lncRNAs (LINC01559, LINC01133, CCAT1, LINC00920 and UCA1) reduced cell proliferation, migration and invasion. Gene co-expression network analysis associated PDAC-deregulated lncRNAs with diverse biological processes, such as cell adhesion, protein glycosylation and DNA repair. Furthermore, UCA1 knockdown was shown to specifically deregulate co-expressed genes involved in DNA repair and to negatively impact DNA repair following damage induced by ionizing radiation.

CONCLUSIONS

Our study expands the repertoire of lncRNAs deregulated in PDAC, thereby revealing novel candidate biomarkers for patient risk stratification. It also provides a roadmap for functional assays aimed to characterize novel mechanisms of action of lncRNAs in pancreatic cancer, which could be explored for therapeutic development.

Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.

miR-449a Repression Leads to Enhanced NOTCH Signaling in TMPRSS2:ERG Fusion Positive Prostate Cancer Cells

About 50% of prostate cancer (PCa) tumors are TMPRSS2:ERG (T2E) fusion-positive (T2E+), but the role of T2E in PCa progression is not fully understood. We were interested in investigating epigenomic alterations associated with T2E+ PCa. Using different sequencing cohorts, we found several transcripts of the miR-449 cluster to be repressed in T2E+ PCa. This repression correlated strongly with enhanced expression of NOTCH and several of its target genes in TCGA and ICGC PCa RNA-seq data. We corroborated these findings using a cellular model with inducible T2E expression. Overexpression of miR-449a in vitro led to silencing of genes associated with NOTCH signaling (NOTCH1, HES1) and HDAC1. Interestingly, HDAC1 overexpression led to the repression of HES6, a negative regulator of the transcription factor HES1, the primary effector of NOTCH signaling, and promoted cell proliferation by repressing the cell cycle inhibitor p21. Inhibition of NOTCH as well as knockdown of HES1 reduced the oncogenic properties of PCa cell lines. Using tissue microarray analysis encompassing 533 human PCa cores, ERG-positive areas exhibited significantly increased HES1 expression. Taken together, our data suggest that an epigenomic regulatory network enhances NOTCH signaling and thereby contributes to the oncogenic properties of T2E+ PCa.

Long Non-Coding RNA Landscape in Prostate Cancer Molecular Subtypes: A Feature Selection Approach

Prostate cancer is one of the most common malignancies in men. It is characterized by a high molecular genomic heterogeneity and, thus, molecular subtypes, that, to date, have not been used in clinical practice. In the present paper, we aimed to better stratify prostate cancer patients through the selection of robust long non-coding RNAs. To fulfill the purpose of the study, a bioinformatic approach focused on feature selection applied to a TCGA dataset was used. In such a way, LINC00668 and long non-coding(lnc)-SAYSD1-1, able to discriminate ERG/not-ERG subtypes, were demonstrated to be positive prognostic biomarkers in ERG-positive patients. Furthermore, we performed a comparison between mutated prostate cancer, identified as "classified", and a group of patients with no peculiar genomic alteration, named "not-classified". Moreover, LINC00920 lncRNA overexpression has been linked to a better outcome of the hormone regimen. Through the feature selection approach, it was found that the overexpression of lnc-ZMAT3-3 is related to low-grade patients, and three lncRNAs: lnc-SNX10-87, lnc-AP1S2-2, and ADPGK-AS1 showed, through a co-expression analysis, significant correlation values with potentially druggable pathways. In conclusion, the data mining of publicly available data and robust bioinformatic analyses are able to explore the unknown biology of malignancies.