A review on the role of PCA3 lncRNA in carcinogenesis with an especial focus on prostate cancer

Long non-coding RNAs in cancer: multifaceted roles and potential targets for immunotherapy

Cancer remains a major global health concern with high mortality rates mainly due to late diagnosis and poor prognosis. Long non-coding RNAs (lncRNAs) are emerging as key regulators of gene expression in human cancer, functioning through various mechanisms including as competing endogenous RNAs (ceRNAs) and indirectly regulating miRNA expression. LncRNAs have been found to have both oncogenic and tumor-suppressive roles in cancer, with the former promoting cancer cell proliferation, migration, invasion, and poor prognosis. Recent research has shown that lncRNAs are expressed in various immune cells and are involved in cancer cell immune escape and the modulation of the tumor microenvironment, thus highlighting their potential as targets for cancer immunotherapy. Targeting lncRNAs in cancer or immune cells could enhance the anti-tumor immune response and improve cancer immunotherapy outcomes. However, further research is required to fully understand the functional roles of lncRNAs in cancer and the immune system and their potential as targets for cancer immunotherapy. This review offers a comprehensive examination of the multifaceted roles of lncRNAs in human cancers, with a focus on their potential as targets for cancer immunotherapy. By exploring the intricate mechanisms underlying lncRNA-mediated regulation of cancer cell proliferation, invasion, and immune evasion, we provide insights into the diverse therapeutic applications of these molecules.

Unveiling four axes ADAMTS9-AS2|MEG3/hsa-miR-150/PRKCA|MMP14 within prostate cancer through establishment of the ceRNA network

Prostate cancer is among the most common cancers in males. Recent application of system biology methods has resulted in identification of key genes in the process of carcinogenesis. In the current study, we selected two datasets related to prostate cancer (PCa) and performed bulk RNA-seq analysis by selecting samples with Gleason scores greater than 7 and combining them. Subsequently, using several systems biology approaches, we constructed the ceRNA network and ultimately identified key axes related to PCa. Our analyses revealed importance of ADAMTS9-AS2/miR-150/PRKCA, ADAMTS9-AS2/miR-150/MMP14, MEG3/miR-150/PRKCA and MEG3/miR-150/MMP14 with miR-150 being a central component. Remarkably, miR-150 exhibited strong statistical significance in survival analyses. Further, analyzing expression levels from TCGA datasets, the expression of the identified genes associates significantly with prostate cancer compared to normal tissue confirming the bioinformatic analyses. Therefore, these genes can be regarded as prognostic markers in prostate cancer and the pathways are potential targets for therapeutic interventions.

A comprehensive review on lncRNA LOXL1-AS1: molecular mechanistic pathways of lncRNA LOXL1-AS1 in tumorigenicity of cancer cells

Long non-coding RNAs (lncRNAs) are versatile RNAs that regulate various cellular processes, such as gene regulation, by acting as signals, decoys, guides, and scaffolds. A novel recognized lncRNA, LOXL1-antisense RNA 1 (LOXL1-AS1), is dysregulated in some diseases, including cancer, and acts as an oncogenic lncRNA in many types of cancer cells. Upregulation of LOXL1-AS1 has been involved in proliferation, migration, metastasis, and EMT, as well as inhibiting apoptosis in cancer cells. Most importantly, the malignant promoting activity of LOXL1-AS1 can be mostly mediated by sequestering specific miRNAs and inhibiting their binding to the 3´UTR of their target mRNAs, thereby indirectly regulating gene expression. Additionally, LOXL1-AS1 can decoy transcription factors and proteins and prevent their binding to their regulatory regions, inhibiting their mechanistic activity on the regulation of gene expression and signaling pathways. This review presents the mechanistic pathways of the oncogenic role of LOXL1-AS1 by modulating its target miRNAs and proteins in various cancer cells. Having information about the molecular mechanisms regulated by LOXL1-AS1 in cancer cells can open ways to find out particular prognostic biomarkers, as well as discover novel therapeutic approaches for different types of cancer.

Transcript Markers from Urinary Extracellular Vesicles for Predicting Risk Reclassification of Prostate Cancer Patients on Active Surveillance

Serum prostate-specific antigen (PSA), its derivatives, and magnetic resonance tomography (MRI) lack sufficient specificity and sensitivity for the prediction of risk reclassification of prostate cancer (PCa) patients on active surveillance (AS). We investigated selected transcripts in urinary extracellular vesicles (uEV) from PCa patients on AS to predict PCa risk reclassification (defined by ISUP 1 with PSA > 10 ng/mL or ISUP 2-5 with any PSA level) in control biopsy. Before the control biopsy, urine samples were prospectively collected from 72 patients, of whom 43% were reclassified during AS. Following RNA isolation from uEV, multiplexed reverse transcription, and pre-amplification, 29 PCa-associated transcripts were quantified by quantitative PCR. The predictive ability of the transcripts to indicate PCa risk reclassification was assessed by receiver operating characteristic (ROC) curve analyses via calculation of the area under the curve (AUC) and was then compared to clinical parameters followed by multivariate regression analysis. ROC curve analyses revealed a predictive potential for AMACR, HPN, MALAT1, PCA3, and PCAT29 (AUC = 0.614-0.655, p < 0.1). PSA, PSA density, PSA velocity, and MRI maxPI-RADS showed AUC values of 0.681-0.747 (p < 0.05), with accuracies for indicating a PCa risk reclassification of 64-68%. A model including AMACR, MALAT1, PCAT29, PSA density, and MRI maxPI-RADS resulted in an AUC of 0.867 (p < 0.001) with a sensitivity, specificity, and accuracy of 87%, 83%, and 85%, respectively, thus surpassing the predictive power of the individual markers. These findings highlight the potential of uEV transcripts in combination with clinical parameters as monitoring markers during the AS of PCa.

Predicting prostate cancer progression with a Multi-lncRNA expression-based risk score and nomogram integrating ISUP grading

Prostate cancer is a highly heterogeneous disease; therefore, estimating patient prognosis accurately is challenging due to the lack of biomarkers with sufficient specificity and sensitivity. One of the current challenges lies in integrating genomic and transcriptomic data with clinico-pathological features and in incorporating their application in everyday clinical practice. Therefore, we aimed to model a risk score and nomogram containing long non-coding RNA (lncRNA) expression and clinico-pathological data to better predict the probability of prostate cancer progression. We performed bioinformatics analyses to identify lncRNAs differentially expressed across various prostate cancer stages and associated with progression-free survival. This information was further integrated into a prognostic risk score and nomogram containing transcriptomic and clinico-pathological features to estimate the risk of disease progression. We used RNA-seq data from 5 datasets from public repositories (total n = 178) comprising different stages of prostate cancer: pre-treatment primary prostate adenocarcinomas, post-treatment tumors and metastatic castration resistant prostate cancer. We found 30 lncRNAs with consistent differential expression in all comparisons made using two R-based packages. Multivariate progression-free survival analysis including the ISUP group as covariate, revealed that 7/30 lncRNAs were significantly associated with time-to-progression. Next, we combined the expression of these 7 lncRNAs into a multi-lncRNA score and dichotomized the patients into low- or high-score. Patients with a high-score showed a 4-fold risk of disease progression (HR = 4.30, 95 %CI = 2.66-6.97, p = 3.1e-9). Furthermore, we modelled a combined risk-score containing information on the multi-lncRNA score and ISUP group. We found that patients with a high-risk score had nearly 8-fold risk of progression (HR = 7.65, 95 %CI = 4.05-14.44, p = 3.4e-10). Finally, we created and validated a nomogram to help uro-oncologists to better predict patient's risk of progression at 3- and 5-years post-diagnosis. In conclusion, the integration of lncRNA expression data and clinico-pathological features of prostate tumors into predictive models might aid in tailored disease risk assessment and treatment for patients with prostate cancer.

Cancer risk and male Infertility: Unravelling predictive biomarkers and prognostic indicators

In recent years, there has been a global increase in cases of male infertility. There are about 30 million cases of male infertility worldwide and male reproductive health is showing rapid decline in last few decades. It is now recognized as a potential risk factor for developing certain types of cancer, particularly genitourinary malignancies like testicular and prostate cancer. Male infertility is considered a potential indicator of overall health and an early biomarker for cancer. Cases of unexplained male factor infertility have high levels of oxidative stress and oxidative DNA damage and this induces both denovo germ line mutations and epimutations due to build up of 8-hydroxy 2 deoxygunaosine abase which is highly mutagenic and also induces hypomethylation and genomic instability. Consequently, there is growing evidence to explore the various factors contributing to an increased cancer risk. Currently, the available prognostic and predictive biomarkers associated with semen characteristics and cancer risk are limited but gaining significant attention in clinical research for the diagnosis and treatment of elevated cancer risk in the individual and in offspring. The male germ cell being transcriptionally and translationally inert has a highly truncated repair mechanism and has minimal antioxidants and thus most vulnerable to oxidative injury due to environmental factors and unhealthy lifestyle and social habits. Therefore, advancing our understanding requires a thorough evaluation of the pathophysiologic mechanisms at the DNA, RNA, protein, and metabolite levels to identify key biomarkers that may underlie the pathogenesis of male infertility and associated cancer. Advanced methodologies such as genomics, epigenetics, proteomics, transcriptomics, and metabolomics stand at the forefront of cutting-edge approaches for discovering novel biomarkers, spanning from infertility to associated cancer types. Henceforth, in this review, we aim to assess the role and potential of recently identified predictive and prognostic biomarkers, offering insights into the success of assisted reproductive technologies, causes of azoospermia and idiopathic infertility, the impact of integrated holistic approach and lifestyle modifications, and the monitoring of cancer susceptibility, initiation and progression. Comprehending these biomarkers is crucial for providing comprehensive counselling to infertile men and cancer patients, along with their families.

The interplay between noncoding RNAs and drug resistance in hepatocellular carcinoma: the big impact of little things

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related death in people, and a common primary liver cancer. Lacking early diagnosis and a high recurrence rate after surgical resection, systemic treatment is still an important treatment method for advanced HCC. Different drugs have distinct curative effects, side effects and drug resistance due to different properties. At present, conventional molecular drugs for HCC have displayed some limitations, such as adverse drug reactions, insensitivity to some medicines, and drug resistance. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs), have been well documented to be involved in the occurrence and progression of cancer. Novel biomarkers and therapeutic targets, as well as research into the molecular basis of drug resistance, are urgently needed for the management of HCC. We review current research on ncRNAs and consolidate the known roles regulating drug resistance in HCC and examine the potential clinical applications of ncRNAs in overcoming drug resistance barriers in HCC based on targeted therapy, cell cycle non-specific chemotherapy and cell cycle specific chemotherapy.

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.

Novel PRUNE2 Germline Mutations in Aggressive and Benign Parathyroid Neoplasms

Parathyroid tumors are mostly sporadic but can also occur in familial forms, including different kinds of genetic syndromes with varying phenotypes and penetrance. Recently, somatic mutations of the tumor suppressor gene PRUNE2 were found to be frequent in parathyroid cancer (PC). The germline mutation status of PRUNE2 was investigated in a large cohort of patients with parathyroid tumors from the genetically homogenous Finnish population, 15 of which had PC, 16 atypical parathyroid tumors (APT), and 6 benign parathyroid adenomas (PA). Mutations in previously established hyperparathyroidism-related genes were screened with a targeted gene panel analysis. Nine PRUNE2 germline mutations with a minor allele frequency (MAF) of <0.05 were found in our cohort. Five of these were predicted to be potentially damaging and were identified in two patients with PC, two with APT, and three with PA. The mutational status was not associated with the tumor group nor related to the clinical picture or severity of the disease. Still, the frequent finding of rare germline mutations of PRUNE2 may point to the gene playing a role in the pathogenesis of parathyroid neoplasms.

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.

LncRNA/miRNA/mRNA Network Introduces Novel Biomarkers in Prostate Cancer

The construction of a competing endogenous RNA (ceRNA) network is an important step in the identification of the role of differentially expressed genes in cancers. In the current research, we used a number of bioinformatics tools to construct the ceRNA network in prostate cancer and identify the importance of these modules in predicting the survival of patients with this type of cancer. An assessment of microarray data of prostate cancer and normal samples using the Limma package led to the identification of differential expressed (DE) RNAs that we stratified into mRNA, lncRNA, and miRNAs, resulting in 684 DEmRNAs, including 437 downregulated DEmRNAs (such as TGM4 and SCGB1A1) and 241 upregulated DEmRNAs (such as TDRD1 and CRISP3); 6 DElncRNAs, including 1 downregulated DElncRNA (H19) and 5 upregulated DElncRNAs (such as PCA3 and PCGEM1); and 59 DEmiRNAs, including 30 downregulated DEmiRNAs (such as hsa-miR-1274a and hsa-miR-1274b) and 29 upregulated DEmiRNAs (such as hsa-miR-1268 and hsa-miR-1207-5p). The ceRNA network contained a total of 5 miRNAs, 5 lncRNAs, and 17 mRNAs. We identified hsa-miR-17, hsa-miR-93, hsa-miR-150, hsa-miR-25, PART1, hsa-miR-125b, PCA3, H19, RND3, and ITGB8 as the 10 hub genes in the ceRNA network. According to the ROC analysis, the expression levels of 19 hub genes showed a high diagnostic value. Taken together, we introduce a number of novel promising diagnostic biomarkers for prostate cancer.

Long Non-Coding RNAs, Extracellular Vesicles and Inflammation in Alzheimer's Disease

Alzheimer's Disease (AD) has currently no effective treatment; however, preventive measures have the potential to reduce AD risk. Thus, accurate and early prediction of risk is an important strategy to alleviate the AD burden. Neuroinflammation is a major factor prompting the onset of the disease. Inflammation exerts its toxic effect via multiple mechanisms. Amongst others, it is affecting gene expression via modulation of non-coding RNAs (ncRNAs), such as miRNAs. Recent evidence supports that inflammation can also affect long non-coding RNA (lncRNA) expression. While the association between miRNAs and inflammation in AD has been studied, the role of lncRNAs in neurodegenerative diseases has been less explored. In this review, we focus on lncRNAs and inflammation in the context of AD. Furthermore, since plasma-isolated extracellular vesicles (EVs) are increasingly recognized as an effective monitoring strategy for brain pathologies, we have focused on the studies reporting dysregulated lncRNAs in EVs isolated from AD patients and controls. The revised literature shows a positive association between pro-inflammatory lncRNAs and AD. However, the reports evaluating lncRNA alterations in EVs isolated from the plasma of patients and controls, although still limited, confirm the value of specific lncRNAs associated with AD as reliable biomarkers. This is an emerging field that will open new avenues to improve risk prediction and patient stratification, and may lead to the discovery of potential novel therapeutic targets for AD.

Long Non-Coding RNAs: Tools for Understanding and Targeting Cancer Pathways

The regulatory nature of long non-coding RNAs (lncRNAs) has been well established in various processes of cellular growth, development, and differentiation. Therefore, it is vital to examine their contribution to cancer development. There are ample examples of lncRNAs whose cellular levels are significantly associated with clinical outcomes. However, whether these non-coding molecules can work as either key drivers or barriers to cancer development remains unknown. The current review aims to discuss some well-characterised lncRNAs in the process of oncogenesis and extrapolate the extent of their decisive contribution to tumour development. We ask if these lncRNAs can independently initiate neoplastic lesions or they always need the modulation of well characterized oncogenes or tumour suppressors to exert their functional properties. Finally, we discuss the emerging genetic approaches and appropriate animal and humanised models that can significantly contribute to the functional dissection of lncRNAs in cancer development and progression.

The Role of Long Non-Coding RNAs in Epithelial-Mesenchymal Transition-Related Signaling Pathways in Prostate Cancer

Prostate cancer (PCa) is one of the most common male malignancies with frequent remote invasion and metastasis, leading to high mortality. Epithelial-mesenchymal transition (EMT) is a fundamental process in embryonic development and plays a key role in tumor proliferation, invasion and metastasis. Numerous long non-coding RNAs (lncRNAs) could regulate the occurrence and development of EMT through various complex molecular mechanisms involving multiple signaling pathways in PCa. Given the importance of EMT and lncRNAs in the progression of tumor metastasis, we recapitulate the research progress of EMT-related signaling pathways regulated by lncRNAs in PCa, including AR signaling, STAT3 signaling, Wnt/β-catenin signaling, PTEN/PI3K/AKT signaling, TGF-β/Smad and NF-κB signaling pathways. Furthermore, we summarize four modes of how lncRNAs participate in the EMT process of PCa via regulating relevant signaling pathways.