Identification of MicroRNAs as Viable Aggressiveness Biomarkers for Prostate Cancer

Integrating multi-cohort machine learning and clinical sample validation to explore peripheral blood mRNA diagnostic biomarkers for prostate cancer

BACKGROUND

The global incidence of prostate cancer (PCa) has been rising annually, and early diagnosis and treatment remain pivotal for improving therapeutic outcomes and patient prognosis. Concurrently, advancements in liquid biopsy technology have facilitated disease diagnosis and monitoring, with its minimally invasive nature and low heterogeneity positioning it as a promising approach for predicting disease progression. However, current liquid biopsy strategies for PCa predominantly rely on prostate-specific antigen (PSA), which lacks specificity and compromises diagnostic accuracy. Thus, there is an urgent need to identify novel liquid biopsy biomarkers to enable early and precise PCa diagnosis.

METHODS

We integrated 12 machine learning algorithms to construct 113 combinatorial models, screening and validating an optimal PCa diagnostic panel across five datasets from TCGA and GEO databases. Subsequently, the biological feasibility of the selected predictive model was verified in one prostate epithelial cell line and five PCa cell lines. Robust RNA diagnostic targets were further validated for their expression in plasma samples to establish an RNA-based liquid biopsy strategy for PCa. Finally, plasma samples from PCa and benign prostatic hyperplasia (BPH) patients at Wuhan Tongji Hospital were collected to evaluate the strategy's clinical significance.

RESULTS

Differential analysis identified 1,071 candidate mRNAs, which were input into the integrated machine learning framework. Among the 113 combinatorial models, the 9-gene diagnostic panel selected by the Stepglm[both] and Enet[alpha = 0.4] algorithms demonstrated the highest diagnostic efficacy (mean AUC = 0.91), including JPH4, RASL12, AOX1, SLC18A2, PDZRN4, P2RY2, B3GNT8, KCNQ5, and APOBEC3C. Cell line experiments further validated AOX1 and B3GNT8 as robust RNA biomarkers, both exhibiting consistent PCa-specific expression in human plasma samples. In liquid biopsy analyses, AOX1 and B3GNT8 outperformed PSA in diagnostic accuracy, achieving a combined AUC of 0.91. Notably, these biomarkers also demonstrated diagnostic utility in patients with ISUP ≤ 2.

CONCLUSIONS

Through an integrated machine learning approach and clinical validation, we developed an RNA-based diagnostic panel for PCa. Specifically, we identified AOX1 and B3GNT8 as novel liquid biopsy biomarkers with promising clinical diagnostic value. These findings provide new targets and insights for early and precise PCa diagnosis.

Unveiling hotspots of emerging research in the miRNA-related mechanism underlying cancer through comprehensive bibliometric analysis with implications for precision medicine and non-invasive diagnostics

Background and objective

MicroRNAs (miRNAs) are implicated in cancer by exerting roles in tumor growth, metastasis, and even drug resistance. The general trends of miRNA research in diverse cancers are not fully understood. In this work, miRNA-related research in colorectal cancer, prostate cancer, leukemia, and brain tumors was analyzed in search of key research trends with clinical potential.

Methods

A bibliometric analysis of articles, spanning from 2014 to 2024, was carried out with the major focus laid on four types of cancers. The Co-citation network analysis, keyword bursts, and the collaborative pattern were done in VOSviewer and CiteSpace, respectively.

Results

Colorectal cancer had the highest publication volume, with research primarily focusing on gene expression, extracellular vesicles, and non-coding RNAs. Prostate cancer showed a shift toward clinical applications, while leukemia and brain tumor research, though less extensive, highlighted miRNA's potential in early diagnosis and treatment. Co-citation analysis identified emerging research collaborations and key contributors.

Conclusion

miRNA plays a pivotal role in cancer diagnosis, biomarker development, and therapeutic interventions. With advancements in non-invasive diagnostics and personalized medicine, miRNA offers significant potential for clinical applications. Future research should focus on miRNA's role in drug resistance and combination therapies to accelerate its clinical translation.

Oncogenic MicroRNAs: Key players in human prostate cancer pathogenesis, a narrative review

Prostate cancer (PC) is a leading cause of cancer-related mortality in men worldwide, and identifying key molecular players in its pathogenesis is essential for advancing effective diagnosis and therapy. MicroRNAs (miRNAs) have recently emerged as significant molecules involved in the progression of various cancers. As noncoding RNAs, miRNAs play a vital role in regulating gene expression and are implicated in several aspects of cancer pathogenesis. In the context of human PC, growing evidence suggests that certain miRNAs with oncogenic properties are key players in the initiation, progression, and metastasis of the disease. In conclusion, dysregulated miRNAs are critical in prostate cancer progression, influencing key cellular processes. Oncogenic miRNAs exhibit diagnostic and therapeutic potential in PC. Targeting these miRNAs presents novel treatment avenues, but further research is needed to fully understand their clinical utility. Additional investigation into the mechanisms of miRNA regulation and their interactions with other signaling pathways is necessary to comprehensively understand the role of oncogenic miRNAs in PC and to develop effective treatments for this disease. Overall, substantiating the role of oncogenic miRNAs in PC pathogenesis provides valuable insights into the mechanisms underlying the disease and may lead to the development of novel targeted therapies for improved patient outcomes.

Osteo-immunomodulatory effects of macrophage-derived extracellular vesicles treated with biphasic calcium phosphate ceramics on bone regeneration

Literature on osteoimmunology has demonstrated that macrophages have a great influence on biomaterial-induced bone formation. However, there are almost no reports clarifying the osteo-immunomodulatory capacity of macrophage-derived extracellular vesicles (EVs). This study comprehensively investigated the effects of EVs derived from macrophages treated with biphasic calcium phosphate (BCP) ceramics (BEVs) on vital events associated with BCP-induced bone formation such as immune response, angiogenesis, and osteogenesis. It was found that compared with EVs derived from macrophages alone (control, CEVs), BEVs preferentially promoted macrophage polarization towards a wound-healing M2 phenotype, enhanced migration, angiogenic differentiation, and tube formation of human umbilical vein endothelial cells, and induced osteogenic differentiation of mesenchymal stem cells. Analysis of 15 differentially expressed microRNAs (DEMs) related to immune, angiogenesis, and osteogenesis suggested that BEVs exhibited good immunomodulatory, pro-angiogenic, and pro-osteogenic abilities, which might be attributed to their specific miRNA cargos. These findings not only deepen our understanding of biomaterial-mediated osteoinduction, but also suggest that EVs derived from biomaterial-treated macrophages hold great promise as therapeutic agents with desired immunomodulatory capacity for bone regeneration.

Biomarkers for Pre-Treatment Risk Stratification of Prostate Cancer Patients: A Systematic Review

BACKGROUND

Prostate cancer (PCa) is one of the most frequently occurring malignancies. Although most cases are not life-threatening, approximately 20% endure an unfavorable outcome. PSA-based screening reduced mortality but at the cost of an increased overdiagnosis/overtreatment of low-risk (lrPCa) and favorable intermediate-risk (firPCa) PCa. PCa risk-groups are usually identified based on serum Prostate-Specific Antigen (PSA), the Gleason score, and clinical T stage, which have consistent although variable specificity or subjectivity. Thus, more effective and specific tools for risk assessment are needed, ideally making use of minimally invasive methods such as liquid biopsies. In this systematic review we assessed the clinical potential and analytical performance of liquid biopsy-based biomarkers for pre-treatment risk stratification of PCa patients.

METHODS

Studies that assessed PCa pre-treatment risk were retrieved from PubMed, Scopus, and MedLine. PCa risk biomarkers were analyzed, and the studies' quality was assessed using the QUADAS-2 tool.

RESULTS

The final analysis comprised 24 full-text articles, in which case-control studies predominated, mostly reporting urine-based biomarkers (54.2%) and biomarker quantification by qPCR (41.7%). Categorization into risk groups was heterogeneous, predominantly making use of the Gleason score.

CONCLUSION

This systematic review unveils the substantial clinical promise of using circulating biomarkers in assessing the risk for prostate cancer patients. However, the standardization of groups, categories, and biomarker validation are mandatory before this technique can be implemented. Circulating biomarkers might represent a viable alternative to currently available tools, obviating the need for tissue biopsies, and allowing for faster and more cost-effective testing, with superior analytical performance, specificity, and reproducibility.

Diagnostic and Prognostic Value of miR-93 in Prostate Cancer: A Meta-Analysis and Bioinformatics Analysis

Background

Accurate and non-invasive diagnostic and prognostic markers are necessary to improve patient outcomes. MicroRNAs have been proposed as relatively non-invasive and pertinent biomarkers. miR-93 has been studied for its potential as a diagnostic and prognostic marker in prostate cancer (PCa), but findings from individual studies are inconsistent. We conducted a meta-analysis of its overall differential expression in 13 PCa studies and a bioinformatics analysis to provide a comprehensive appraisal of its diagnostic and prognostic role.

Methods

We searched all published papers on miR-93 expression in PCa up to Nov 30, 2022 using PubMed, Science Direct, Web of Science, Cochrane Central Register of Controlled Trials databases. We used RevMan software to Meta-analyze the included literature. A bioinformatics analysis of genes and pathways that might be target to the effect of the mature miR-93-5p was carried out.

Results

The pooled standardized mean difference (SMD) of miR-93 expression in PCa, its area under the curve (AUC) and hazard ratio (HR) were 1.26, 95% CI [-0.34-2.86], 0.84, 95% CI [0.76 -0.93] and 1.67, 95% CI [0.98, 2.84] respectively. Bioinformatics analysis revealed that mature miR-93-5p may regulate genes such as SMAD1, SMAD7 and MAPK and the PI3K-Akt signaling pathways.

Conclusion

miR-93 has significant diagnostic and prognostic value in PCa. These findings highlight the potential of miR-93 as a non-invasive biomarker for PCa and may contribute to earlier detection and prognostic assessment. The target genes and signaling pathways regulated by miR-93 may provide insights into the underlying molecular mechanisms of PCa.

Novel Siglec-15-Sia axis inhibitor leads to colorectal cancer cell death by targeting miR-6715b-3p and oncogenes

Siglecs are well known immunotherapeutic targets in cancer. Current checkpoint inhibitors have exhibited limited efficacy, prompting a need for novel therapeutics for targets such as Siglec-15. Presently, small molecule inhibitors targeting Siglec-15 are not explored alongside characterised regulatory mechanisms involving microRNAs in CRC progression. Therefore, a small molecule inhibitor to target Siglec-15 was elucidated in vitro and microRNA mediated inhibitor effects were investigated. Our research findings demonstrated that the SHG-8 molecule exerted significant cytotoxicity on cell viability, migration, and colony formation, with an IC50 value of approximately 20µM. SHG-8 exposure induced late apoptosis in vitro in SW480 CRC cells. Notably, miR-6715b-3p was the most upregulated miRNA in high-throughput sequencing, which was also validated via RT-qPCR. MiR-6715b-3p may regulate PTTG1IP, a potential oncogene which was validated via RT-qPCR and in silico analysis. Additionally, molecular docking studies revealed SHG-8 interactions with the Siglec-15 binding pocket with the binding affinity of -5.4 kcal/mol, highlighting its role as a small molecule inhibitor. Importantly, Siglec-15 and PD-L1 are expressed on mutually exclusive cancer cell populations, suggesting the potential for combination therapies with PD-L1 antagonists.

Explainable artificial intelligence to predict and identify prostate cancer tissue by gene expression

BACKGROUND AND OBJECTIVE

Prostate cancer is one of the most prevalent forms of cancer in men worldwide. Traditional screening strategies such as serum PSA levels, which are not necessarily cancer-specific, or digital rectal exams, which are often inconclusive, are still the screening methods used for the disease. Some studies have focused on identifying biomarkers of the disease but none have been reported for diagnosis in routine clinical practice and few studies have provided tools to assist the pathologist in the decision-making process when analyzing prostate tissue. Therefore, a classifier is proposed to predict the occurrence of PCa that provides physicians with accurate predictions and understandable explanations.

METHODS

A selection of 47 genes was made based on differential expression between PCa and normal tissue, GO gene ontology as well as the literature to be used as input predictors for different machine learning methods based on eXplainable Artificial Intelligence. These methods were trained using different class-balancing strategies to build accurate classifiers using gene expression data from 550 samples from 'The Cancer Genome Atlas'. Our model was validated in four external cohorts with different ancestries, totaling 463 samples. In addition, a set of SHapley Additive exPlanations was provided to help clinicians understand the underlying reasons for each decision.

RESULTS

An in-depth analysis showed that the Random Forest algorithm combined with majority class downsampling was the best performing approach with robust statistical significance. Our method achieved an average sensitivity and specificity of 0.90 and 0.8 with an AUC of 0.84 across all databases. The relevance of DLX1, MYL9 and FGFR genes for PCa screening was demonstrated in addition to the important role of novel genes such as CAV2 and MYLK.

CONCLUSIONS

This model has shown good performance in 4 independent external cohorts of different ancestries and the explanations provided are consistent with each other and with the literature, opening a horizon for its application in clinical practice. In the near future, these genes, in combination with our model, could be applied to liquid biopsy to improve PCa screening.

ER Negative Breast Cancer and miRNA: There Is More to Decipher Than What the Pathologist Can See!

Breast cancer (BC), the most prevalent cancer in women, is a heterogenous disease. Despite advancements in BC diagnosis, prognosis, and therapeutics, survival rates have drastically decreased in the metastatic setting. Therefore, BC still remains a medical challenge. The evolution of high-throughput technology has highlighted gaps in the classification system of BCs. Of particular interest is the notorious triple negative BC, which was recounted as being heterogenous itself and it overlaps with distinct subtypes, namely molecular apocrine (MA) and luminal androgen (LAR) BCs. These subtypes are, even today, still misdiagnosed and poorly treated. As such, researchers and clinicians have been looking for ways through which to refine BC classification in order to properly understand the initiation, development, progression, and the responses to the treatment of BCs. One tool is biomarkers and, specifically, microRNA (miRNA), which are highly reported as associated with BC carcinogenesis. In this review, the diverse roles of miRNA in estrogen receptor negative (ER-) and androgen receptor positive (AR+) BC are depicted. While highlighting their oncogenic and tumor suppressor functions in tumor progression, we will discuss their diagnostic, prognostic, and predictive biomarker potentials, as well as their drug sensitivity/resistance activity. The association of several miRNAs in the KEGG-reported pathways that are related to ER-BC carcinogenesis is presented. The identification and verification of accurate miRNA panels is a cornerstone for tackling BC classification setbacks, as is also the deciphering of the carcinogenesis regulators of ER - AR + BC.

The clinical diagnostic value of plasma miR-592 and miR-217-3p levels in retinoblastoma

BACKGROUND

This study was designed to investigate the abnormal expression of plasma miR-592 and miR-217-3p in retinoblastoma (Rb) and explore the clinical diagnostic value of their expression levels for Rb.

METHODS

The 100 Rb patients who came to Nanchang Hongdu Hospital of Traditional Chinese Medicine from January 2018 to January 2019 were selected as the Rb group, and 100 healthy patients who came to the physical examination centre during the same period were selected as the control group. Real-time fluorescence quantitative PCR (qRT-PCR) was used to detect the expression levels of plasma miR-592 and miR-217-3p in all subjects; analyse the relationship between plasma miR-592 and miR-217-3p levels and the clinicopathological characteristics of Rb. Pearson correlation analysis evaluated the relationship between plasma miR-592 and miR-217-3p levels and overall survival.

RESULTS

Plasma levels of miR-592 and miR-217-3p in the Rb group were significantly higher than those in the control group (p<0.0001), and the expression of miR-592 was significantly correlated with family genetic history (p 0.0001), tumour bias (p=0.0081), lymph node metastasis (p=0.0048) and pathological grade (p=0.0025), and the expression of miR-217-3p was significantly related to family genetic history (p 0.0001), optic nerve infiltration (p 0.0001), lymph node metastasis (p=0.0090), and pathological grade (p 0.0001). The high expression of miR-592 and miR-217-3p presents a more serious pathological manifestation of Rb, and the overall survival of patients is significantly shortened with the increase of miR-592 (r=-0.2276, p=0.0052) and miR-217-3p levels (r=-0.6461, p 0.0001).

CONCLUSIONS

and miR-217-3p are highly expressed in the plasma of Rb patients, and their elevated levels present severe pathological manifestations of Rb and shortened overall survival, which is expected to become biomarkers for clinical diagnosis of Rb.

m6A Methylation Regulators Are Predictive Biomarkers for Tumour Metastasis in Prostate Cancer

Simple Summary

Recurrence and metastatic progression always lead to dismal outcomes in prostate cancer (PCa). There is no reliable biomarker for the prediction of recurrence and metastasis other than the Prostate Cancer Antigen (PCA). N6-methyladenosine (m⁶A) is the most common post-transcriptional mRNA modification and is regulated by m⁶A regulators dynamically. Since m⁶A modification is associated with cancer development and outgrowth, we performed a consensus clustering on PCa with regard to the gene expression of all m⁶A regulators. We identified three subtypes of Pca with distinct m⁶A expression patterns and enriched biological pathways. We also established an m⁶A score for metastasis prediction based on our clustering, which is potentially a predictive biomarker for Pca metastasis.

Abstract

Prostate cancer (PCa) is one of the most common cancers in men. Usually, most PCas at initial diagnosis are localized and hormone-dependent, and grow slowly. Patients with localized PCas have a nearly 100% 5-year survival rate; however, the 5-year survival rate of metastatic or progressive PCa is still dismal. N6-methyladenosine (m⁶A) is the most common post-transcriptional mRNA modification and is dynamically regulated by m⁶A regulators. A few studies have shown that the abnormal expression of m⁶A regulators is significantly associated with cancer progression and immune cell infiltration, but the roles of these regulators in PCa remain unclear. Here, we examined the expression profiles and methylation levels of 21 m⁶A regulators across the Cancer Genome Atlas (TCGA), 495 PCas by consensus clustering, and correlated the expression of m⁶A regulators with PCa progression and immune cell infiltration. Consensus clustering was applied for subtyping Pca samples into clusters based on the expression profiles of m⁶A regulators. Each subtype’s signature genes were obtained by a pairwise differential expression analysis. Featured pathways of m⁶A subtypes were predicted by Gene Ontology. The m⁶A score was developed to predict m⁶A activation. The association of the m⁶A score with patients’ survival, metastasis and immune cell infiltration was also investigated. We identified three distinct clusters in PCa based on the expression profiles of 21 m⁶A regulators by consensus clustering. The differential expression and pathway analyses on the three clusters uncovered the m⁶A regulators involved in metabolic processes and immune responses in PCa. Moreover, we developed an m⁶A score to evaluate the m⁶A regulator activation for PCa. The m⁶A score is significantly associated with Gleason scores and metastasis in PCa. The predictive capacity of the m⁶A score on PCa metastasis was also validated in another independent cohort with an area under the curve of 89.5%. Hence, our study revealed the critical role of m⁶A regulators in PCa progression and the m⁶A score is a promising predictive biomarker for PCa metastasis.

Integrative Analysis and Experimental Validation Indicated That SNHG17 Is a Prognostic Marker in Prostate Cancer and a Modulator of the Tumor Microenvironment via a Competitive Endogenous RNA Regulatory Network

The incidence of prostate cancer (PC) is growing rapidly worldwide, and studies uncovering the molecular mechanisms driving the progression and modulating the immune infiltration and antitumor immunity of PC are urgently needed. The long noncoding RNA SNHG family has been recognized as a prognostic marker in cancers and contributes to the progression of multiple cancers, including PC. In this study, we aimed to clarify the prognostic values and underlying mechanisms of SNHGs in promoting the progression and modulating the tumor microenvironment of PC through data mining based on The Cancer Genome Atlas (TCGA) database. We identified that within the SNHG family, SNHG17 was most correlated with the overall survival of PC patients and could act as an independent predictor. Moreover, we constructed a competitive endogenous RNA (ceRNA) network by which SNHG17 promotes progression and potentially inhibits the immune infiltration and immune response of prostate cancer. By interacting with miR-23a-3p/23b-3p/23c, SNHG17 upregulates the expression of UBE2M and OTUB1, which have been demonstrated to play critical roles in the tumorigenesis of human cancers, more importantly promoting cancer cell immunosuppression and resistance to cytotoxic stimulation. Finally, we examined the correlation between SNHG17 expression and the clinical progression of PC patients based on our cohort of 52 PC patients. We also verified the SNHG17/miR-23a/OTUB1 axis in RV-1 and PC-3 cells by dual luciferase and RIP assays, and we further identified that SNHG17 promoted cellular invasive capacity by modulating OTUB1. In summary, the current study conducted a ceRNA-based SNHG17-UBE2M/OTUB1 axis and indicated that SNHG17 might be a novel prognostic factor associated with the progression, immunosuppression, and cytotoxic resistance of PC.

The Role of Androgen Receptor and microRNA Interactions in Androgen-Dependent Diseases

The androgen receptor (AR) is a member of the steroid hormone receptor family of nuclear transcription factors. It is present in the primary/secondary sexual organs, kidneys, skeletal muscles, adrenal glands, skin, nervous system, and breast. Abnormal AR functioning has been identified in numerous diseases, specifically in prostate cancer (PCa). Interestingly, recent studies have indicated a relationship between the AR and microRNA (miRNA) crosstalk and cancer progression. MiRNAs are small, endogenous, non-coding molecules that are involved in crucial cellular processes, such as proliferation, apoptosis, or differentiation. On the one hand, AR may be responsible for the downregulation or upregulation of specific miRNA, while on the other hand, AR is often a target of miRNAs due to their regulatory function on AR gene expression. A deeper understanding of the AR–miRNA interactions may contribute to the development of better diagnostic tools as well as to providing new therapeutic approaches. While most studies usually focus on the role of miRNAs and AR in PCa, in this review, we go beyond PCa and provide insight into the most recent discoveries about the interplay between AR and miRNAs, as well as about other AR-associated and AR-independent diseases.

Regulation of Neuroendocrine-like Differentiation in Prostate Cancer by Non-Coding RNAs

Neuroendocrine prostate cancer (NEPC) represents a variant of prostate cancer that occurs in response to treatment resistance or, to a much lesser extent, de novo. Unravelling the molecular mechanisms behind transdifferentiation of cancer cells to neuroendocrine-like cancer cells is essential for development of new treatment opportunities. This review focuses on summarizing the role of small molecules, predominantly microRNAs, in this phenomenon. A published literature search was performed to identify microRNAs, which are reported and experimentally validated to modulate neuroendocrine markers and/or regulators and to affect the complex neuroendocrine phenotype. Next, available patients’ expression datasets were surveyed to identify deregulated microRNAs, and their effect on NEPC and prostate cancer progression is summarized. Finally, possibilities of miRNA detection and quantification in body fluids of prostate cancer patients and their possible use as liquid biopsy in prostate cancer monitoring are discussed. All the addressed clinical and experimental contexts point to an association of NEPC with upregulation of miR-375 and downregulation of miR-34a and miR-19b-3p. Together, this review provides an overview of different roles of non-coding RNAs in the emergence of neuroendocrine prostate cancer.

miR-145-5p: A Potential Biomarker in Predicting Gleason Upgrading of Prostate Biopsy Samples Scored 3+3=6

Background

The Gleason grading system is a major tool used for prediction of prostate cancer (PCa) behavior. Because of heterogeneity and sampling errors, prognosis is variable even among patients with the same Gleason score (GS). Therefore, more accurate biomarkers that complement the Gleason system are needed to improve the clinical management of PCa.

Methods

Formalin-fixed, paraffin embedded tissue samples were obtained from radical prostatectomy (RP) (patient set 1, n=53) and needle biopsy (patient set 2, n=107; patient set 3, n=119). Cancer tissues from pure regions of each Gleason pattern (GP) were separately collected using laser-captured microdissection, followed by Real-time-PCR to determine the relative expression of miRNAs, including miR-1-5p, miR-21-5p, miR-30d-5p, miR-100-5p, miR-145-5p, miR-224-5p, and miR-708-5p. miRNA’s association with Gleason upgrading (GU) was evaluated using receiver operator characteristics (ROC) curve and multivariate logistic regression analysis. The integrated miRNA targets prediction and enrichment analyses were performed to determine the potential functions of miRNA.

Results

It was found that miR-145-5p in GP3 from radical prostatectomy (RP) were overexpressed in patients with GS6 PCa compared with GS7 patients, which was further confirmed in a larger biopsy cohort. ROC curve analysis revealed that miR-145-5p in biopsy was significantly associated with GU upon RP. In multivariate analyses, miR-145-5p was an independent predictor of GU.

Conclusion

Our study indicated that differential expression of miRNAs existed in GP3 from pure GS6 and GS7 PCa, highlighting a path toward the clinical use of miRNAs in predicting GU and assisting in treatment modality selection.