Clinical Theragnostic Potential of Diverse miRNA Expressions in Prostate Cancer: A Systematic Review and Meta-Analysis

Cancer research in Lebanon: Scope of the most recent publications of an academic institution (Review)

Cancer may be considered one of the most interesting areas of study, and although oncology research has grown markedly over the last decade, there is as yet no known cure for cancer. The objective of the present review is to examine various approaches to cancer research from a single institution, summarize their key conclusions and offer recommendations for future evaluations. The review examined 72 cancer-associated studies that were published within six years from 2017 to 2022. Published works in the subject fields of 'cancer' or 'oncology' and 'research' that were indexed in Scopus and Web of Science were retrieved and sorted according to article title, author names, author count, citation count and key words. After screening, a total of 28 in vitro/animal studies and 46 patient-associated published studies were obtained. A large proportion of these studies comprised literature reviews (20/72), while 20 studies were observational in nature. The 72 publications included 23 in which various types of cancer were examined, while the remaining studies focused on specific types of cancer, including lung, breast, colon and brain cancer. These studies aimed to investigate the incidence, prevalence, treatment and prevention mechanisms associated with cancer. Despite the existence of extensive cancer research, scientists seldom contemplate an ultimate cure for cancer. However, it is crucial to continuously pursue research on cancer prevention and treatment in order to enhance the effectiveness and minimize potential side effects of cancer therapy.

XRCC1: a potential prognostic and immunological biomarker in LGG based on systematic pan-cancer analysis

X-ray repair cross-complementation group 1 (XRCC1) is a pivotal contributor to base excision repair, and its dysregulation has been implicated in the oncogenicity of various human malignancies. However, a comprehensive pan-cancer analysis investigating the prognostic value, immunological functions, and epigenetic associations of XRCC1 remains lacking. To address this knowledge gap, we conducted a systematic investigation employing bioinformatics techniques across 33 cancer types. Our analysis encompassed XRCC1 expression levels, prognostic and diagnostic implications, epigenetic profiles, immune and molecular subtypes, Tumor Mutation Burden (TMB), Microsatellite Instability (MSI), immune checkpoints, and immune infiltration, leveraging data from TCGA, GTEx, CELL, Human Protein Atlas, Ualcan, and cBioPortal databases. Notably, XRCC1 displayed both positive and negative correlations with prognosis across different tumors. Epigenetic analysis revealed associations between XRCC1 expression and DNA methylation patterns in 10 cancer types, as well as enhanced phosphorylation. Furthermore, XRCC1 expression demonstrated associations with TMB and MSI in the majority of tumors. Interestingly, XRCC1 gene expression exhibited a negative correlation with immune cell infiltration levels, except for a positive correlation with M1 and M2 macrophages and monocytes in most cancers. Additionally, we observed significant correlations between XRCC1 and immune checkpoint gene expression levels. Lastly, our findings implicated XRCC1 in DNA replication and repair processes, shedding light on the precise mechanisms underlying its oncogenic effects. Overall, our study highlights the potential of XRCC1 as a prognostic and immunological pan-cancer biomarker, thereby offering a novel target for tumor immunotherapy.

Function and biomedical implications of exosomal microRNAs delivered by parenchymal and nonparenchymal cells in hepatocellular carcinoma

Small extracellular vesicles (exosomes) are important components of the tumor microenvironment. They are small membrane-bound vesicles derived from almost all cell types and play an important role in intercellular communication. Exosomes transmit biological molecules obtained from parent cells, such as proteins, lipids, and nucleic acids, and are involved in cancer development. MicroRNAs (miRNAs), the most abundant contents in exosomes, are selectively packaged into exosomes to carry out their biological functions. Recent studies have revealed that exosome-delivered miRNAs play crucial roles in the tumorigenesis, progression, and drug resistance of hepatocellular carcinoma (HCC). In addition, exosomes have great industrial prospects in the diagnosis, treatment, and prognosis of patients with HCC. This review summarized the composition and function of exosomal miRNAs of different cell origins in HCC and highlighted the association between exosomal miRNAs from stromal cells and immune cells in the tumor microenvironment and the progression of HCC. Finally, we described the potential applicability of exosomal miRNAs derived from mesenchymal stem cells in the treatment of HCC.

Clinical Significance of Extracellular Vesicles in Prostate and Renal Cancer

Extracellular vesicles (EVs)-including apoptotic bodies, microvesicles, and exosomes-are released by almost all cell types and contain molecular footprints from their cell of origin, including lipids, proteins, metabolites, RNA, and DNA. They have been successfully isolated from blood, urine, semen, and other body fluids. In this review, we discuss the current understanding of the predictive value of EVs in prostate and renal cancer. We also describe the findings supporting the use of EVs from liquid biopsies in stratifying high-risk prostate/kidney cancer and advanced disease, such as castration-resistant (CRPC) and neuroendocrine prostate cancer (NEPC) as well as metastatic renal cell carcinoma (RCC). Assays based on EVs isolated from urine and blood have the potential to serve as highly sensitive diagnostic studies as well as predictive measures of tumor recurrence in patients with prostate and renal cancers. Overall, we discuss the biogenesis, isolation, liquid-biopsy, and therapeutic applications of EVs in CRPC, NEPC, and RCC.

GelMA Hydrogel as a Promising Delivery System for Osthole in the Treatment of Rheumatoid Arthritis: Targeting the miR-1224-3p/AGO1 Axis

Rheumatoid arthritis (RA) is a multifaceted, chronic, progressive autoimmune disease. This study aims to explore the potential benefits of an enhanced drug delivery system utilizing optimized Gelatin Methacryloyl (GelMA) vectors in RA management. We evaluated the levels of miR-1124-3p and AGO1 in RA tissues and cell lines using qPCR, WB, and immunofluorescence. The effects of osthole on inflammatory response and joint morphology were determined by qPCR, H&E staining, and micro-CT. The data showed that miR-1224-3p was downregulated in RA tissues and HUM-iCell-s010RA cells, while the overexpression of miR-1224-3p in HUM-iCell-s010RA cells reduced the expression of IL-6 and IL-1β. Luciferase assay demonstrated that AGO1 was a direct target gene of miR-1224-3p. Additionally, osthole treatment increased miR-1224-3p levels and decreased AGO1 expression. The release data showed that osthole loaded on GelMA was released at a slower rate than free osthole. Further studies in a mouse model of CIA confirmed that osthole-loaded GelMA was more effective in attenuating osteopenia in RA as well as alleviating autoimmune arthritis. These findings suggest that osthole can regulate the miR-1224-3p/AGO1 axis in RASFs cells and has the potential to be developed as a clinical anti-RA drug. GelMA could provide a new approach to long-term RA treatment.

Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing

BACKGROUND

Prostate cancer is a significant clinical issue, particularly for high Gleason score (GS) malignancy patients. Our study aimed to engineer and validate a risk model based on the profiles of high-GS PCa patients for early identification and the prediction of prognosis.

METHODS

We conducted differential gene expression analysis on patient samples from The Cancer Genome Atlas (TCGA) and enriched our understanding of gene functions. Using the least absolute selection and shrinkage operator (LASSO) regression, we established a risk model and validated it using an independent dataset from the International Cancer Genome Consortium (ICGC). Clinical variables were incorporated into a nomogram to predict overall survival (OS), and machine learning was used to explore the risk factor characteristics' impact on PCa prognosis. Our prognostic model was confirmed using various databases, including single-cell RNA-sequencing datasets (scRNA-seq), the Cancer Cell Line Encyclopedia (CCLE), PCa cell lines, and tumor tissues.

RESULTS

We identified 83 differentially expressed genes (DEGs). Furthermore, WASIR1, KRTAP5-1, TLX1, KIF4A, and IQGAP3 were determined to be significant risk factors for OS and progression-free survival (PFS). Based on these five risk factors, we developed a risk model and nomogram for predicting OS and PFS, with a C-index of 0.823 (95% CI, 0.766-0.881) and a 10-year area under the curve (AUC) value of 0.788 (95% CI, 0.633-0.943). Additionally, the 3-year AUC was 0.759 when validating using ICGC. KRTAP5-1 and WASIR1 were found to be the most influential prognosis factors when using the optimized machine learning model. Finally, the established model was interrelated with immune cell infiltration, and the signals were found to be differentially expressed in PCa cells when using scRNA-seq datasets and tissues.

CONCLUSIONS

We engineered an original and novel prognostic model based on five gene signatures through TCGA and machine learning, providing new insights into the risk of scarification and survival prediction for PCa patients in clinical practice.

Clinical Investigation of Chemotherapeutic Resistance and miRNA Expressions in Head and Neck Cancers: A Thorough PRISMA Compliant Systematic Review and Comprehensive Meta-Analysis

Background: Chemoresistance is a significant barrier to combating head and neck cancer, and decoding this resistance can widen the therapeutic application of such chemotherapeutic drugs. This systematic review and meta-analysis explores the influence of microRNA (miRNA) expressions on chemoresistance in head and neck cancers (HNC). The objective is to evaluate the theragnostic effects of microRNA expressions on chemoresistance in HNC patients and investigate the utility of miRNAs as biomarkers and avenues for new therapeutic targets. Methods: We performed a comprehensive bibliographic search that included the SCOPUS, PubMed, and Science Direct bibliographic databases. These searches conformed to a predefined set of search strategies. Following the PRISMA guidelines, inclusion and exclusion criteria were framed upon completing the literature search. The data items extracted were tabulated and collated in MS Excel. This spreadsheet was used to determine the effect size estimation for the theragnostic effects of miRNA expressions on chemoresistance in HNC, the hazard ratio (HR), and 95% confidence intervals (95% CI). The comprehensive meta-analysis was performed using the random effects model. Heterogeneity among the data collected was assessed using the Q test, Tau², I², and Z measures. Publication bias of the included studies was checked using the Egger's bias indicator test, Orwin and classic fail-safe N test, Begg and Mazumdar rank collection test, and Duval and Tweedie's trim and fill methods. Results: After collating the data from 23 studies, dysregulation of 34 miRNAs was observed in 2189 people. These data were gathered from 23 studies. Out of the 34 miRNAs considered, 22 were up-regulated, while 12 were down-regulated. The TaqMan transcription kits were the most used miRNA profiling platform, and miR-200c was seen to have a mixed dysregulation. We measured the overall pooled effect estimate of HR to be 1.516 for the various analyzed miRNA at a 95% confidence interval of 1.303-1.765, with a significant p-value. The null hypothesis test's Z value was 5.377, and the p-value was correspondingly noted to be less than 0.0001. This outcome indicates that the risk of death is determined to be higher in up-regulated groups than in down-regulated groups. Among the 34 miRNAs that were investigated, seven miRNAs were associated with an improved prognosis, especially with the overexpression of these seven miRNAs (miR15b-5p, miR-548b, miR-519d, miR-1278, miR-145, miR-200c, Hsa- miR139-3p). Discussion: The findings reveal that intricate relationships between miRNAs' expression and chemotherapeutic resistance in HNC are more likely to exist and can be potential therapeutic targets. This review suggests the involvement of specific miRNAs as predictors of chemoresistance and sensitivity in HNC. The examination of the current study results illustrates the significance of miRNA expression as a theragnostic biomarker in medical oncology.

Liquid Biopsy in Diagnosis and Prognosis of Non-Metastatic Prostate Cancer

Currently, sensitive and specific methods for the detection and prognosis of early stage PCa are lacking. To establish the diagnosis and further identify an appropriate treatment strategy, prostate specific antigen (PSA) blood test followed by tissue biopsy have to be performed. The combination of tests is justified by the lack of a highly sensitive, specific, and safe single test. Tissue biopsy is specific but invasive and may have severe side effects, and therefore is inappropriate for screening of the disease. At the same time, the PSA blood test, which is conventionally used for PCa screening, has low specificity and may be elevated in the case of noncancerous prostate tumors and inflammatory conditions, including benign prostatic hyperplasia and prostatitis. Thus, diverse techniques of liquid biopsy have been investigated to supplement or replace the existing tests of prostate cancer early diagnosis and prognostics. Here, we provide a review on the advances in diagnosis and prognostics of non-metastatic prostate cancer by means of various biomarkers extracted via liquid biopsy, including circulating tumor cells, exosomal miRNAs, and circulating DNAs.

Using Machine Learning to Detect Theranostic Biomarkers Predicting Respiratory Treatment Response

Background: Theranostic approaches—the use of diagnostics for developing targeted therapies—are gaining popularity in the field of precision medicine. They are predominately used in cancer research, whereas there is little evidence of their use in respiratory medicine. This study aims to detect theranostic biomarkers associated with respiratory-treatment responses. This will advance theory and practice on the use of biomarkers in the diagnosis of respiratory diseases and contribute to developing targeted treatments. Methods: We performed a cross-sectional analysis on a sample of 13,102 adults from the UK household longitudinal study ‘Understanding Society’. We used recursive feature selection to identify 16 biomarkers associated with respiratory treatment responses. We then implemented several machine learning algorithms using the identified biomarkers as well as age, sex, body mass index, and lung function to predict treatment response. Results: Our analysis shows that subjects with increased levels of alkaline phosphatase, glycated haemoglobin, high-density lipoprotein cholesterol, c-reactive protein, triglycerides, hemoglobin, and Clauss fibrinogen are more likely to receive respiratory treatments, adjusting for age, sex, body mass index, and lung function. Conclusions: These findings offer a valuable blueprint on why and how the use of biomarkers as diagnostic tools can prove beneficial in guiding treatment management in respiratory diseases.

A Clinical Investigation on the Theragnostic Effect of MicroRNA Biomarkers for Survival Outcome in Cervical Cancer: A PRISMA-P Compliant Protocol for Systematic Review and Comprehensive Meta-Analysis

Background: The most often diagnosed malignancy in women worldwide is cancer of the cervix. It is also the most prevalent kind of gynecological cancer in women. This cancer originates in the opening of the cervix and spreads through sexual contact. Even though human papillomavirus (HPV) may not cause cancer immediately, it does develop over time as a result of the virus’s lengthy persistence to cause dysplastic changes overtime, particularly in high-risk kinds. The primary objective of this research is to see if miRNAs are dysregulated as a result of treatment resistance in cervical cancer (CC). The aim is to see if these microRNAs may be utilized as biomarkers for detecting chemoresistance in CC, particularly for clinical applications. Methods: The recommended protocol for comprehensive study and meta-analysis (PRISMA-P) standards will be utilized for the analysis and data interpretation. The bibliographic databases will be methodically searched using a combination of search keywords. Based on established inclusion and exclusion criteria, the acquired findings will be reviewed, and data retrieved from the selected scientific papers for systematic review. We will then construct a forest from the pooled Hazard ratio (HR) and 95% C.I. values, data obtained using the random-effects model. Discussion: The focus of this study is to identify the function of miRNAs as a chemoresistance regulator and determine if they have the potential scope to be considered as biomarkers for cervical cancer. Through this systematic review and meta-analysis, the goal is to collect, compare, and analyze the data pertaining to the role of miRNAs in cervical cancer, thereby, enabling us to understand the role they play in chemosensitivity.

Mapping Research on miRNAs in Cancer: A Global DataAnalysis and Bibliometric Profiling Analysis

miRNAs biomarkers are emerging as an essential part of clinical oncology. Their oncogenic and tumour suppressor properties playing a role in malignancy has generated interest in their potential for use in disease prognosis. While several studies on miRNA have been carried out across the globe, evaluating the clinical implications of miRNAs in cancer diagnosis and prognosis research has currently not been attempted. A study delineating the area of miRNA research, including the topics presently being focused on, the seminal papers in this field, and the direction of research interest, does not exist. This study aims to conduct a large-scale, global data analysis and bibliometric profiling analysis of studies to evaluate the research output of clinical implications of miRNAs in cancer diagnosis and prognosis listed in the SCOPUS database. A systematic search strategy was followed to identify and extract all relevant studies, subsequently analysed to generate a bibliometric map. SPSS software (version 27) was used to calculate bibliometric indicators or parameters for analysis, such as year and country of affiliation with leading authors, journals, and institutions. It is also used to analyse annual research outputs, including total citations and the number of times it has been cited with productive nations and H-index. The number of global research articles retrieved for miRNA-Cancer research over the study period 2003 to 2019 was 18,636. Between 2012 and 2019, the growth rate of global publications is six times (n = 15,959; 90.71 percent articles) that of 2003 to 2011. (2704; 9.29 per cent articles). China published the most publications in the field of miRNA in cancer (n = 7782; 41%), while the United States had the most citations (n = 327,538; 48%) during the time span. Of these journals, Oncotarget has the highest percentage of article publications. The journal Cancer Research had the most citations (n = 41,876), with 6.20 per cent (n = 41,876). This study revealed a wide variety of journals in which miRNA-Cancer research are published; these bibliometric parameters exhibit crucial clinical information on performance assessment of research productivity and quality of research output. Therefore, this study provides a helpful reference for clinical oncologists, cancer scientists, policy decision-makers and clinical data researchers.

miR-206 Inhibits Laryngeal Carcinoma Cell Multiplication, Migration, and Invasion

Laryngeal carcinoma (LC) is one of the common human cancer types. MicroRNAs (miRNAs) were reported to be the essential regulators in cancer diagnosis, treatment, and prognosis. It was reported that miR-206 expression was reduced in various neoplastic diseases. However, the role and functional mechanism of miR-206 in LC progression remain unclear. In this research, miR-206 was found to be associated with tumor-node-metastasis (TNM) staging. In addition, the area under the curve (AUC) of miR-206 was 0.902 for diagnosis of LC and 0.854 for differential diagnosis of stage I-II and stage III-IV patients. Low expression of miR-206 was associated with poor prognosis of LC patients. miR-206 expression was an independent factor affecting the prognosis of LC patients, as revealed by the Cox regression analysis. In vitro experiments demonstrated that miR-206 overexpression reduced cell multiplication, invasion, and migration and increased cell apoptosis in LC cells. Moreover, SOX9 was a target of miR-206, and miR-206 negatively regulated SOX9 expression. Collectively, miR-206 might be a promising biomarker with diagnostic and prognostic value for LC, and the miR-206/SOX9 axis might be a candidate target for LC therapy.

Vulnerability Rating of Source Code with Token Embedding and Combinatorial Algorithms

We present an empirical analysis of the source code of the Fluoride Bluetooth module, which is a part of standard Android OS distribution, by exhibiting a novel approach for classifying and scoring source code and vulnerability rating. Our workflow combines deep learning, combinatorial optimization, heuristics and machine learning. A combination of heuristics and deep learning is used to embed function (and method) labels into a low-dimensional Euclidean space. Because the corpus of the Fluoride source code is rather limited (containing approximately 12,000 functions), a straightforward embedding (using, e.g. code2vec) is untenable. To overcome the challenge of dearth of data, it is necessary to go through an intermediate step of Byte-Pair Encoding. Subsequently, we embed the tokens from which we assemble an embedding of function/method labels. Long short-term memory network (LSTM) is used to embed tokens. The next step is to form a distance matrix consisting of the cosines between every pairs of vectors (function embedding) which in turn is interpreted as a (combinatorial) graph whose vertices represent functions, and edges correspond to entries whose value exceed some given threshold. Cluster-Editing is then applied to partition the vertex set of the graph into subsets representing “dense graphs,” that are nearly complete subgraphs. Finally, the vectors representing the components, plus additional heuristic-based features are used as features to model the components for vulnerability risk.

Melatonin and regulation of miRNAs: novel targeted therapy for cancerous and noncancerous disease

miRNAs, small noncoding RNAs with crucial diagnostic and prognostic capabilities, play essential therapeutic roles in different human diseases. These biomarkers are involved in several biological mechanisms and are responsible for the regulation of multiple genes expressions in cells. miRNA-based therapy has shown a very bright future in the case of clinical interventions. Melatonin, the main product of the pineal gland, is a multifunctional neurohormone with numerous therapeutic potentials in human diseases. Melatonin is able to regulate miRNAs in different pathologies such as malignant and nonmalignant diseases, which can be considered as a novel kind of targeted therapy. Herein, this review discusses possible therapeutic utility of melatonin for the regulation of miRNAs in various pathological conditions.

Interventional Techniques for Bone and Musculoskeletal Soft Tissue Tumors: Current Practices and Future Directions - Part II. Stabilization

Percutaneous image-guided oncologic interventions have rapidly evolved over the last two decades as an independent strategy or used within a first-, second-, or even third-line strategy in the treatment of musculoskeletal (MSK) tumors. Abundant mostly nonrandomized publications have described the safety, efficacy, and reproducibility of implementing percutaneous therapies both with curative and palliative intent. In this article, we continue to share our experience in bone and MSK soft tissue interventions focusing on stabilization and combined ablation and stabilization. We propose a pathway and explore future directions of image-guided interventional oncology related to skeletal disease. We reflect on the advantages and limitations of each technique and offer guidance and pearls to improve outcomes. Representing patterns from our practices, we demonstrate the role of collaborative working within a multidisciplinary team, ideally within a dedicated tumor treatment center, to deliver patient-specific therapy plans that are value based and favored by patients when given the choice.

miRNA as promising theragnostic biomarkers for predicting radioresistance in cancer: A systematic review and meta-analysis

Radioresistance remains as an obstacle in cancer treatment. This systematic review and meta-analysis aimed to evaluate the association between the expression of miRNAs and responses to radiotherapy and the prognosis of different tumors. In total, 77 miRNAs in 19 cancer types were studied, in which 24 miRNAs were upregulated and 58 miRNAs were downregulated in cancer patients. Five miRNAs were differentially expressed. Moreover, 75 miRNAs were found to be related to radioresistance, while 5 were observed to be related to radiosensitivity. The pooled HR and 95 % confidence interval for the combined studies was 1.135 (0.819-1.574; P-value = 0.4). The HR values of the subgroup analysis for miR-21 (HR = 2.344; 95 % CI: 1.927-2.850; P-value = 0.000), nasopharyngeal carcinoma (HR = 0.448; 95 % CI: 0.265-0.760; P = 0.003) and breast cancer (HR = 1.131; 95 % CI: 0.311-4.109; P = .85) were obtained. Our results highlighted that across the published literature, miRNAs can modulate tumor radioresistance or sensitivity by affecting radiation-related signaling pathways. It seems that miRNAs could be considered as a theragnostic biomarker to predict and monitor clinical response to radiotherapy. Thus, the prediction of radioresistance in malignant patients will improve radiotherapy outcomes and radiotherapeutic resistance.