The long non-coding RNA GHSROS reprograms prostate cancer cell lines toward a more aggressive phenotype

Prognostic values of long noncoding RNA in bone metastasis of prostate cancer: A systematic review and meta-analysis

Introduction

Recent studies have shown that long non-coding RNAs are closely related to the occurrence and development of prostate cancer bone metastasis, and can be used as biomarkers to predict the prognosis of patients. Therefore, this study aimed to systematically evaluate the relationship between the expression levels of long non-coding RNAs and the prognosis of patients.

Methods

The studies of lncRNA in prostate cancer bone metastasis from Pubmed, Cochrane library, Embase, Ebsco, Web of science, Scopus, Ovid databases were analyzed, and Stata 15 was used for meta-analysis. Associations between lncRNA expression and patients' overall survival (OS) and bone metastasis-free survival (BMFS) were assessed by correlation analysis with pooled hazard ratios (HR) and 95% confidence intervals (CI). Furthermore, the results were validated using GEPIA2 and UALCAN, online database based on TCGA. Subsequently, the molecular mechanisms of the included lncRNAs were predicted based on the LncACTdb 3.0 database and the lnCAR database. Finally, we used clinical samples to validate lncRNAs that were significantly different in both databases.

Results

A total of 5 published studies involving 474 patients were included in this meta-analysis. The results showed that lncRNA overexpression was significantly associated with lower OS (HR = 2.55, 95% CI: 1.69 - 3.99, p < 0.05) and lower BMFS (OR = 3.16, 95% CI: 1.90 - 5.27, p < 0.05) in patients with prostate cancer bone metastasis. Based on validation from the GEPIA2 and UALCAN online databases, SNHG3 and NEAT1 were significantly up-regulated in prostate cancer. Further functional prediction showed that the lncRNAs included in the study were involved in regulating the occurrence and development of prostate cancer through the ceRNA axis. The result of clinical samples showed that SNHG3 and NEAT1 were expressed in prostate cancer bone metastasis at higher levels than in primary tumors.

Conclusions

LncRNA can be used as a novel predictive biomarker for predicting poor prognosis in patients with prostate cancer bone metastasis, which is worthy of clinical validation.

Cancer-associated fibroblast-derived gene signatures predict radiotherapeutic survival in prostate cancer patients

BACKGROUND

Cancer-associated fibroblasts (CAFs) play multiple roles in regulating tumor metastasis and treatment response. Current clinical indicators are insufficient to accurately assess disease risk and radiotherapy response, emphasizing the urgent need for additional molecular prognostic markers.

METHODS

In order to investigate CAF-related genes associated with radiotherapy and construct prognostic CAF-related gene signatures for prostate cancer, we firstly established a radio-resistant prostate CAF cell subline (referred to as CAFR) from Mus-CAF (referred to as CAF) through fractionated irradiation using X-rays. Transcriptome sequencing for CAF and CAFR was conducted, and 2626 CAF-related differentially expressed genes (DEGs) associated with radiotherapy were identified. Human homologous genes of mouse CAF-related DEGs were then obtained.

RESULTS

Functional enrichment analysis revealed that these CAF-related DEGs were significantly enriched ECM- and immune-related functions and pathways. Based on GSE116918 dataset, 186 CAF-related DEGs were correlated with biochemical recurrence-free survival (BCRFS) of prostate cancer patients, 16 of which were selected to construct a BCRFS-related CAF signature, such as ACPP, THBS2, and KCTD14; 142 CAF-related DEGs were correlated with metastasis-free survival (MFS), 16 of which were used to construct a MFS-related CAF signature, such as HOPX, TMEM132A, and ZNF467. Both Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets confirmed that the two CAF signatures accurately predicted BCRFS and MFS of prostate cancer patients. The risk scores were higher in patients with higher gleason grades and higher clinical T stages. Moreover, the BCRFS-related CAF signature was an independent prognostic factor and a nomogram consisting of BCRFS-related CAF signature and various clinical factors accurately predicted 2-, 3-, and 5-year survival time of prostate cancer patients. Furthermore, the risk score was positively correlated with multiple immune checkpoints.

CONCLUSIONS

Our established CAF signatures could accurately predict BCRFS and MFS in prostate cancer patients undergoing radiotherapy.

Recent Advances in the Genetic of MALT Lymphomas

Simple Summary

Mucosa-associated lymphoid tissue (MALT) lymphoma is the most common subtype of marginal zone lymphomas. These B-cell neoplasms may arise from many organs and usually have an indolent behavior. Recurrent chromosomal translocations and cytogenetic alterations are well characterized, some of them being associated to specific sites. Through next-generation sequencing technologies, the mutational landscape of MALT lymphomas has been explored and available data to date show that there are considerable variations in the incidence and spectrum of mutations among MALT lymphoma of different sites. Interestingly, most of these mutations affect several common pathways and some of them are potentially targetable. Gene expression profile and epigenetic studies have also added new information, potentially useful for diagnosis and treatment. This article provides a comprehensive review of the genetic landscape in MALT lymphomas.

Abstract

Mucosa-associated lymphoid tissue (MALT) lymphomas are a diverse group of lymphoid neoplasms with B-cell origin, occurring in adult patients and usually having an indolent clinical behavior. These lymphomas may arise in different anatomic locations, sharing many clinicopathological characteristics, but also having substantial variances in the aetiology and genetic alterations. Chromosomal translocations are recurrent in MALT lymphomas with different prevalence among different sites, being the 4 most common: t(11;18)(q21;q21), t(1;14)(p22;q32), t(14;18)(q32;q21), and t(3;14)(p14.1;q32). Several chromosomal numerical abnormalities have also been described, but probably represent secondary genetic events. The mutational landscape of MALT lymphomas is wide, and the most frequent mutations are: TNFAIP3, CREBBP, KMT2C, TET2, SPEN, KMT2D, LRP1B, PRDM1, EP300, TNFRSF14, NOTCH1/NOTCH2, and B2M, but many other genes may be involved. Similar to chromosomal translocations, certain mutations are enriched in specific lymphoma types. In the same line, variation in immunoglobulin gene usage is recognized among MALT lymphoma of different anatomic locations. In the last decade, several studies have analyzed the role of microRNA, transcriptomics and epigenetic alterations, further improving our knowledge about the pathogenic mechanisms in MALT lymphoma development. All these advances open the possibility of targeted directed treatment and push forward the concept of precision medicine in MALT lymphomas.

Interaction between Non-Coding RNAs and Androgen Receptor with an Especial Focus on Prostate Cancer

The androgen receptor (AR) is a member of the nuclear receptor superfamily and has three functional domains, namely the N-terminal, DNA binding, and C-terminal domain. The N-terminal domain harbors potent transactivation functions, whereas the C-terminal domain binds to androgens and antiandrogens used to treat prostate cancer. AR has genomic activity being DNA binding-dependent or through interaction with other DNA-bound transcription factors, as well as a number of non-genomic, non-canonical functions, such as the activation of the ERK, AKT, and MAPK pathways. A bulk of evidence indicates that non-coding RNAs have functional interactions with AR. This type of interaction is implicated in the pathogenesis of human malignancies, particularly prostate cancer. In the current review, we summarize the available data on the role of microRNAs, long non-coding RNAs, and circular RNAs on the expression of AR and modulation of AR signaling, as well as the effects of AR on their expression. Recognition of the complicated interaction between non-coding RNAs and AR has practical importance in the design of novel treatment options, as well as modulation of response to conventional therapeutics.