The miRNAs involved in prostate cancer chemotherapy response as chemoresistance and chemosensitivity predictors

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq revealed key genes for bone metastasis and chemoresistance in prostate cancer

BACKGROUND

Prostate cancer (PCa) is a serious malignancy. The main causes of PCa aggravation and death are unexplained resistance to chemotherapy and bone metastases.

OBJECTIVE

This study aimed to investigate the molecular mechanisms associated with the dynamic processes of progression, bone metastasis, and chemoresistance in PCa.

METHODS

Through comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data, Gene Expression Omnibus (GEO) tumor progression and metastasis-related genes were identified. These genes were subjected to lasso regression modeling using the Cancer Genome Atlas (TCGA) database. Tartrate-resistant acid phosphatase (TRAP) staining and real-time quantitative PCR (RT-qPCR) were used to evaluate osteoclast differentiation. CellMiner was used to confirm the effect of LDHA on chemoresistance. Finally, the relationship between LDHA and chemoresistance was verified using doxorubicin-resistant PCa cell lines.

RESULTS

7928 genes were identified as genes related to tumor progression and metastasis. Of these, 7 genes were found to be associated with PCa prognosis. The scRNA-seq and TCGA data showed that the expression of LDHA was higher in tumors and associated with poor prognosis of PCa. In addition, upregulation of LDHA in PCa cells induces osteoclast differentiation. Additionally, high LDHA expression was associated with resistance to Epirubicin, Elliptinium acetate, and doxorubicin. Cellular experiments demonstrated that LDHA knockdown inhibited doxorubicin resistance in PCa cells.

CONCLUSIONS

LDHA may play a potential contributory role in PCa initiation and development, bone metastasis, and chemoresistance. LDHA is a key target for the treatment of PCa.

Prostate cancer therapy outcome prediction: are miRNAs a suitable guide for therapeutic decisions?

BACKGROUND

Radical prostatectomy, radiotherapy, chemotherapy, and androgen-deprivation therapy are among the most common treatment options for different forms of prostate cancer (PCa). However, making therapeutic decisions is difficult due to the lack of reliable prediction markers indicating therapy outcomes in clinical practice. The involvement of miRNAs in all mechanisms of the PCa development and their easy detection characterize them as attractive PCa biomarkers. Although there are extensive data on the role of miRNAs in PCa therapy resistance and sensitivity development, the issues of whether they could be used as a guide for therapy choice and, if so, how we can progress toward this goal, remain unclear. Thus, generalizable reviews and studies which summarize, compare, and analyze data on miRNA involvement in responses to different types of PCa therapies are required.

OBJECTIVES

Data on the involvement of miRNAs in therapy responses, on the role of cross-miRNA expression in different therapies, and on miRNA targets were analyzed in order to determine the miRNA-related factors which can lend perspective to the future development of personalized predictors of PCa sensitivity/resistance to therapies.

MATERIALS AND METHODS

The data available on the miRNAs associated with different PCa therapies (resistance and sensitivity therapies) are summarized and analyzed in this study, including analyses using bioinformatics resources. Special attention was dedicated to the mechanisms of the development of therapy resistance.

RESULTS AND DISCUSSION

A comprehensive combined analysis of the current data revealed a panel of miRNAs that were shown to be most closely associated with the PCa therapy response and were found to regulate the genes involved in PCa development via cell proliferation regulation, epithelial-mesenchymal transition (EMT), apoptosis, cell-cycle progression, angiogenesis, metastasis and invasion regulation, androgen-independent development, and colony formation.

CONCLUSION

The selected miRNA-based panel has the potential to be a guide for therapeutic decision making in the effective treatment of PCa.

Overcoming chemoresistance and radio resistance in prostate cancer: The emergent role of non-coding RNAs

Prostate cancer (PCa) continues to be a major health concern worldwide, with its resistance to chemotherapy and radiation therapy presenting major hurdles in successful treatment. While patients with localized prostate cancer generally have a good survival rate, those with metastatic prostate cancer often face a grim prognosis, even with aggressive treatments using various methods. The high mortality rate in severe cases is largely due to the lack of treatment options that can offer lasting results, especially considering the significant genetic diversity found in tumors at the genomic level. This comprehensive review examines the intricate molecular mechanisms governing resistance in PCa, emphasising the pivotal contributions of non-coding RNAs (ncRNAs). We delve into the diverse roles of microRNAs, long ncRNAs, and other non-coding elements as critical regulators of key cellular processes involved in CR & RR. The review emphasizes the diagnostic potential of ncRNAs as predictive biomarkers for treatment response, offering insights into patient stratification and personalized therapeutic approaches. Additionally, we explore the therapeutic implications of targeting ncRNAs to overcome CR & RR, highlighting innovative strategies to restore treatment sensitivity. By synthesizing current knowledge, this review not only provides a comprehension of the chemical basis of resistance in PCa but also identifies gaps in knowledge, paving the way for future research directions. Ultimately, this exploration of ncRNA perspectives offers a roadmap for advancing precision medicine in PCa, potentially transforming therapeutic paradigms and improving outcomes for patients facing the challenges of treatment resistance.

Evidence-based procedures to improve the reliability of circulating miRNA biomarker assays

Circulating cell-free microRNAs (cfmiRNA) are an emerging class of biomarkers that have shown great promise in the clinical diagnosis, treatment, and monitoring of several pathological conditions, including cancer. However, validation and clinical implementation of cfmiRNA biomarkers has been hindered by the variability introduced during different or suboptimal specimen collection and handling practices. To address the need for standardization and evidence-based guidance, the National Cancer Institute (NCI) developed a new Biospecimen Evidenced-Based Practices (BEBP) document, entitled "Cell-free miRNA (cfmiRNA): Blood Collection and Processing". The BEBP, the fourth in the document series, contains step-by-step procedural guidelines on blood collection, processing, storage, extraction, and quality assessment that are tailored specifically for cfmiRNA analysis of plasma and serum. The workflow outlined in the BEBP is based on the available literature and recommendations of an expert panel. The BEBP contains the level of detail required for development of evidence-based standard operating procedures (SOPs) as well as the flexibility needed to accomodate (i) discovery- and inquiry-based studies and (ii) the different constraints faced by research labs, industry, clinical and academic institutions to foster widespread implementation. Guidance from the expert panel also included recommendations on study design, validating changes in workflow, and suggested quality thresholds to delineate meaningful changes in cfmiRNA levels. The NCI cfmiRNA: Blood Collection and Processing BEBP is available here as supplementary information as well as through the NCI Biorepositories and Biospecimen Research Branch (BBRB) (https://biospecimens.cancer.gov/resources/bebp.asp).

MicroRNAs as biomarkers for early diagnosis, targeting and prognosis of prostate cancer

Globally, prostate cancer (PC) is leading cause of cancer-related mortality in men worldwide. Despite significant advances in the treatment and management of this disease, the cure rates for PC remains low, largely due to late detection. PC detection is mostly reliant on prostate-specific antigen (PSA) and digital rectal examination (DRE); however, due to the low positive predictive value of current diagnostics, there is an urgent need to identify new accurate biomarkers. Recent studies support the biological role of microRNAs (miRNAs) in the initiation and progression of PC, as well as their potential as novel biomarkers for patients' diagnosis, prognosis, and disease relapse. In the advanced stages, cancer-cell-derived small extracellular vesicles (SEVs) may constitute a significant part of circulating vesicles and cause detectable changes in the plasma vesicular miRNA profile. Recent computational model for the identification of miRNA biomarkers discussed. In addition, accumulating evidence indicates that miRNAs can be utilized to target PC cells. In this article, the current understanding of the role of microRNAs and exosomes in the pathogenesis and their significance in PC prognosis, early diagnosis, chemoresistance, and treatment are reviewed.

MicroRNAs as Predictors of Lung-Cancer Resistance and Sensitivity to Cisplatin

BACKGROUND

Platinum-based chemotherapy, cisplatin (DDP) specifically, is the main strategy for treating lung cancer (LC). However, currently, there is a lack of predictive drug-resistance markers, and there is increased interest in the development of a reliable and sensitive panels of markers for DDP chemotherapy-effectiveness prediction. MicroRNAs represent a perspective pool of markers for chemotherapy effectiveness.

OBJECTIVES

Data on miRNAs associated with LC DDP chemotherapy response are summarized and analyzed.

MATERIALS AND METHODS

A comprehensive review of the data in the literature and an analysis of bioinformatics resources were performed. The gene targets of miRNAs, as well as their reciprocal relationships with miRNAs, were studied using several databases.

RESULTS AND DISCUSSION

The complex analysis of bioinformatics resources and the literature indicated that the expressions of 12 miRNAs have a high predictive potential for LC DDP chemotherapy responses. The obtained information was discussed from the point of view of the main mechanisms of LC chemoresistance.

CONCLUSIONS

An overview of the published data and bioinformatics resources, with respect to the predictive microRNA markers of chemotherapy response, is presented in this review. The selected microRNAs and gene panel have a high potential for predicting LC DDP sensitiveness or DDP resistance as well as for the development of a DDP co-therapy.