The potential of circulating cell-free RNA as a cancer biomarker: challenges and opportunities

Influence of radical prostatectomy on miRNA dynamics in urine extracellular vesicles

PURPOSE

Cancer statistics demonstrate leading growth of prostate cancer. As a rule, radical prostatectomy (RP) is a mandatory option in the treatment of localized prostate cancer (PCa). Over 30% of patients develop biochemical resistance after the surgery and over 30% of these patients experience prostate cancer recurrence and metastasis. Currently used PCa patient's diagnostic features fail to identify PCa recurrence. To identify the risk group of PCa patients after RP we attempt to apply miRNAs which were shown as promising liquid biopsy markers for PCa diagnosis and prognosis.

MATERIALS AND METHODS

Expression of 14 miRNAs closely involved in the development of prostate cancer from urine extracellular vesicles (uEV) of PCa patients before as well as 3, 6 and 12 months after radical prostatectomy was assessed using RT PCR and compared with their expression from uEV of healthy donors in the current study.

RESULTS

It was shown that 22 miRNA pairs prognostic ratios (MPPRs) significantly changed after radical prostatectomy. MPPRs the most promising in terms of evaluating the effectiveness of radical prostatectomy have been identified. These include two groups: MPPRs significantly changed after surgery towards that in healthy donors; and MPPRs, which divided PCa patients into two significantly different subgroups 3 or 6 months after radical prostatectomy.

CONCLUSIONS

The obtained data indicate that urine EVs represent a valuable source of both MPDR and MPPR for prostate cancer.

Prognostic value of CMTM6 protein in hepatocellular carcinoma involving the regulation of the immune microenvironment

There have been notable irregularities in CMTM6 expression observed in hepatocellular carcinoma (HCC), with an evident correlation between CMTM6 dysregulation and patient prognosis. The cell cycle progression came to a halt at the G2/M phase. In-depth RNA-sequencing analysis of CMTM6 knockdown Hep3B cells revealed that the most prominent effect of CMTM6 perturbation was on the expression of CXCL8, a chemokine involved in immune responses, particularly through the interleukin-17F (IL-17F) signaling pathway. By carefully examining the RNA-sequencing data obtained from CMTM6 knockdown Hep3B cells and cross-referencing it with the TCGA-LIHC database, we were able to discern that CMTM6 and programmed death-ligand 1 (PD-L1) collaboratively partake in immune regulation within T cells. Furthermore, CMTM6 exerted an influential role in modulating the infiltration of CD4+ and CD8+ T cells in the HCC microenvironment, thereby impacting the overall immune response. Our investigation found that HCC cases characterized by an elevated co-expression of CMTM6 and PD-L1, along with augmented CD4+ T cell infiltration, demonstrated comparatively longer overall and progression-free survival rates when contrasted with those displaying lower CD4+ T cell infiltration.

Utilizing nullomers in cell-free RNA for early cancer detection

Early detection of cancer can significantly improve patient outcomes; however, sensitive and highly specific biomarkers for cancer detection are currently missing. Nullomers are the shortest sequences that are absent from the human genome but can emerge due to somatic mutations in cancer. We examine over 10,000 whole exome sequencing matched tumor-normal samples to characterize nullomer emergence across exonic regions of the genome. We also identify nullomer emerging mutational hotspots within tumor genes. Finally, we provide evidence for the identification of nullomers in cell-free RNA from peripheral blood samples, enabling detection of multiple tumor types. We show multiple tumor classification models with an AUC greater than 0.9, including a hepatocellular carcinoma classifier with an AUC greater than 0.99.

Identification of candidate plasma miRNA biomarkers for the diagnosis of head and neck squamous cell carcinoma

Aim: Current head and neck squamous cell carcinoma (HNSCC) diagnostic tools are limited, so this study aimed to identify diagnostic microRNA (miRNA) biomarkers from plasma. Materials & methods: A total of 76 HNSCC and 76 noncancerous control (NC) plasma samples underwent microarray analysis and quantitative reverse transcription PCR to screen for diagnostic plasma miRNAs. The diagnostic potential of the miRNAs was evaluated by the receiver operating characteristic curve. Results: miR-95-3p and miR-579-5p expression was shown to be significantly upregulated, and that of miR-1298-3p to be downregulated in HNSCC patients compared with controls. The final diagnostic panel included miR-95-3p, miR-579-5p and miR-1298-3p with an area under the curve of 0.83. Conclusion: This three-miRNA panel has potential for the diagnosis of HNSCC.

Detection of Naturally occurring abortive transcripts by Base-Stacking Hybridization Assisted Ligation and PCR amplification

Abortive transcripts (ATs) refer to nascent 2-10 nucleotides (nt) RNAs released by RNA polymerases before synthesizing productive RNAs. The quantitative detection of ATs is important for studying transcription initiation and the biological function of ATs; however, no method is available for the qualitative and quantitative assessment of such ultra-short oligonucleotides (typically shorter than 11 nt) in vivo at present, even with the LNA probes, the detection limit can only reach 11 nt. Here, we demonstrated the base stacking hybridization assisted ligation (BSHAL) technique, combined with TaqMan-MGB qPCR, can detect 4-10 nt ATs with a specificity of nucleotide resolution and a sensitivity of approximately 10 pM. By this technique, we detected endogenous ATs in cell lines, mice plasmas, and mice liver tissues, respectively, and proved that naturally occurring ATs do exist. We found that the 8 nt ATs of HMSB and Gapdh could be used as reference ATs for data normalization in Homo and mouse respectively, and 8 nt ATs of Afp and Gpc3 were suitable for use as plasma biomarkers of Hepatocellular carcinoma in mouse, indicate ATs are promising biomarkers. This study offers opportunities to study ATs and other ultra-short oligonucleotides in biological samples.

Opportunity in Complexity: Harnessing Molecular Biomarkers and Liquid Biopsies for Personalized Sarcoma Care

Due to their rarity and complexity, sarcomas represent a substantial therapeutic challenge. However, the incredible diversity within and across sarcoma subtypes presents an opportunity for personalized care to maximize efficacy and limit toxicity. A deeper understanding of the molecular alterations that drive sarcoma development and treatment response has paved the way for molecular biomarkers to shape sarcoma treatment. Genetic, transcriptomic, and protein biomarkers have become critical tools for diagnosis, prognostication, and treatment selection in patients with sarcomas. In the future, emerging biomarkers like circulating tumor DNA analysis offer the potential to improve early detection, monitoring response to treatment, and identifying mechanisms of resistance to personalize sarcoma treatment. Here, we review the current state of molecular biomarkers for sarcomas and highlight opportunities and challenges for the implementation of new technologies in the future.

Diagnostic liquid biopsy biomarkers in renal cell cancer

The clinical presentation of renal cell cancer (RCC) is shifting towards incidental and early detection, creating new challenges in RCC diagnosis. Overtreatment might be reduced with the development of new diagnostic biomarkers to distinguish benign from malignant small renal masses (SRMs). Differently from tissue biopsies, liquid biopsies are obtained from a patient's blood or urine and, therefore, are minimally invasive and suitable for longitudinal monitoring. The most promising types of liquid biopsy biomarkers for RCC diagnosis are circulating tumour cells, extracellular vesicles (EVs) and cell-free DNA. Circulating tumour cell assays have the highest specificity, with low processing time and costs. However, the biological characteristics and low sensitivity limit the use of these markers in SRM diagnostics. Cell-free DNA might complement the diagnosis of high-volume RCC, but the potential for clinical application in SRMs is limited. EVs have the highest biological abundance and the highest sensitivity in identifying low-volume disease; moreover, the molecular characteristics of these markers make EVs suitable for multiple analytical applications. Thus, currently, EV assays have the greatest potential for diagnostic application in RCC (including identification of SRMs). All these liquid biomarkers have potential in clinical practice, pending validation studies. Biomarker implementation will be needed to also improve characterization of RCC subtypes. Last, diagnostic biomarkers might be extended to prognostic or predictive applications.

Peptide absent sequences emerging in human cancers

Early diagnosis of cancer can significantly improve survival of cancer patients; however sensitive and highly specific biomarkers for cancer detection are currently lacking for most cancer types. Nullpeptides are short peptides that are absent from the human proteome. Here, we examined the emergence of nullpeptides during cancer development. We analyzed 3,600,964 somatic mutations across 10,064 whole exome sequencing tumor samples spanning 32 cancer types. We analyze RNA-seq data from primary tumor samples to identify the subset of nullpeptides that emerge in highly expresed genes. We show that nullpeptides, and particularly the subset that is highly recurrent across cancer patients, can be identified in tumor biopsy samples. We find that cancer genes show an excess of nullpeptides and detect nullpeptide hotspots in specific loci of oncogenes and tumor suppressors. We also observe that recurrent nullpeptides are more likely to be found in neoantigens, which have been shown to be effective targets for immunotherapy, suggesting that they can be used to prioritize candidates. Our findings provide evidence for the utility of nullpeptides as cancer detection and therapeutic biomarkers.

Method for the extraction of circulating nucleic acids based on MOF reveals cell-free RNA signatures in liver cancer

Cell-free RNA (cfRNA) allows assessment of health, status, and phenotype of a variety of human organs and is a potential biomarker to non-invasively diagnose numerous diseases. Nevertheless, there is a lack of highly efficient and bias-free cfRNA isolation technologies due to the low abundance and instability of cfRNA. Here, we developed a reproducible and high-efficiency isolation technology for different types of cell-free nucleic acids (containing cfRNA and viral RNA) in serum/plasma based on the inclusion of nucleic acids by metal-organic framework (MOF) materials, which greatly improved the isolation efficiency and was able to preserve RNA integrity compared with the most widely used research kit method. Importantly, the quality of cfRNA extracted by the MOF method is about 10-fold that of the kit method, and the MOF method isolates more than three times as many different RNA types as the kit method. The whole transcriptome mapping characteristics of cfRNA in serum from patients with liver cancer was described and a cfRNA signature with six cfRNAs was identified to diagnose liver cancer with high diagnostic efficiency (area under curve = 0.905 in the independent validation cohort) using this MOF method. Thus, this new MOF isolation technique will advance the field of liquid biopsy, with the potential to diagnose liver cancer.

Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer

BACKGROUND

Liquid biopsy, particularly cell-free RNA (cfRNA), has emerged as a promising non-invasive diagnostic tool for various diseases, including cancer, due to its accessibility and the wealth of information it provides. A key area of interest is the composition and cellular origin of cfRNA in the blood and the alterations in the cfRNA transcriptomic landscape during carcinogenesis. Investigating these changes can offer insights into the manifestations of tissue alterations in the blood, potentially leading to more effective diagnostic strategies. However, the consistency of these findings across different studies and their clinical utility remains to be fully elucidated, highlighting the need for further research in this area.

RESULTS

In this study, we analyzed over 350 blood samples from four distinct studies, investigating the cell type contributions to the cfRNA transcriptomic landscape in liver cancer. We found that an increase in hepatocyte proportions in the blood is a consistent feature across most studies and can be effectively utilized for classifying cancer and healthy samples. Moreover, our analysis revealed that in addition to hepatocytes, liver endothelial cell signatures are also prominent in the observed changes. By comparing the classification performance of cellular proportions to established markers, we demonstrated that cellular proportions could distinguish cancer from healthy samples as effectively as existing markers and can even enhance classification when used in combination with these markers.

CONCLUSIONS

Our comprehensive analysis of liver cell-type composition changes in blood revealed robust effects that help classify cancer from healthy samples. This is especially noteworthy, considering the heterogeneous nature of datasets and the etiological distinctions of samples. Furthermore, the observed differences in results across studies underscore the importance of integrative and comparative approaches in the future research to determine the consistency and robustness of findings. This study contributes to the understanding of cfRNA composition in liver cancer and highlights the potential of cellular deconvolution in liquid biopsy.

MiR-320a Acts as a Tumor Suppressor in Somatotroph Pituitary Neuroendocrine Tumors by Targeting BCAT1

INTRODUCTION

Aberrant miR-320a has been reported to be involved in the tumorigenesis of several cancers. In our previous study, we identified the low expression of circulating miR-320a in patients with somatotroph pituitary neuroendocrine tumor (PitNET); however, the role of miR-320a in somatotroph PitNET proliferation is still unclear.

METHODS

Cell viability and colony formation assays were used to detect the effect of miR-320a and BCAT1 on GH3 cells. TargetScan was used to identify the target genes of miR-320a. Dual-luciferase reporter gene assay was used to explore the relation between miR-320a and BCAT1. Transcriptome and proteome analyses were performed between somatotroph PitNETs and healthy controls. The expression level of miR-320a in somatotroph PitNETs were detected by RT-qPCR and Western blot.

RESULTS

miR-320a mimics inhibit cell proliferation, while miR-320a inhibitors promote cell proliferation in GH3 cells. An overlap analysis using a Venn diagram revealed that BCAT1 is the only target gene of miR-320a overexpressed in somatotroph PitNETs compared to healthy controls, as revealed by both microarray and proteomics results. A dual-luciferase reporter gene assay showed that miR-320a may bind to the BCAT1-3'UTR. The transfection of miR-320a mimics downregulated the expression and miR-320a inhibitors and upregulated the expression of BCAT1 in GH3 cells. The interference of BCAT1 expression in GH3 cells downregulated cell proliferation and growth. Pan-cancer analyses demonstrated that high BCAT1 expression often indicates a poor prognosis.

CONCLUSION

Our findings illustrate that miR-320a may function as a tumor suppressor and BCAT1 may promote tumor progression. miR-320a may inhibit the growth of somatotroph PitNETs by targeting BCAT1.

Liquid biopsy on the horizon in immunotherapy of non-small cell lung cancer: current status, challenges, and perspectives

Non-small cell lung cancer (NSCLC) is one of the most threatening malignancies to human health and life. In most cases, patients with NSCLC are already at an advanced stage when they are diagnosed. In recent years, lung cancer has made great progress in precision therapy, but the efficacy of immunotherapy is unstable, and its response rate varies from patient to patient. Several biomarkers have been proposed to predict the outcomes of immunotherapy, such as programmed cell death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB). Nevertheless, the detection assays are invasive and demanding on tumor tissue. To effectively predict the outcomes of immunotherapy, novel biomarkers are needed to improve the performance of conventional biomarkers. Liquid biopsy is to capture and detect circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) and exosomes in body fluids, such as blood, saliva, urine, pleural fluid and cerebrospinal fluid as samples from patients, so as to make analysis and diagnosis of cancer and other diseases. The application of liquid biopsy provides a new possible solution, as it has several advantages such as non-invasive, real-time dynamic monitoring, and overcoming tumor heterogeneity. Liquid biopsy has shown predictive value in immunotherapy, significantly improving the precision treatment of lung cancer patients. Herein, we review the application of liquid biopsy in predicting the outcomes of immunotherapy in NSCLC patients, and discuss the challenges and future directions in this field.

Liquid Biopsies, Novel Approaches and Future Directions

Cancer is among the leading causes of death worldwide. Early diagnosis and prognosis are vital to improve patients' outcomes. The gold standard of tumor characterization leading to tumor diagnosis and prognosis is tissue biopsy. Amongst the constraints of tissue biopsy collection is the sampling frequency and the incomplete representation of the entire tumor bulk. Liquid biopsy approaches, including the analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), circulating miRNAs, and tumor-derived extracellular vesicles (EVs), as well as certain protein signatures that are released in the circulation from primary tumors and their metastatic sites, present a promising and more potent candidate for patient diagnosis and follow up monitoring. The minimally invasive nature of liquid biopsies, allowing frequent collection, can be used in the monitoring of therapy response in real time, allowing the development of novel approaches in the therapeutic management of cancer patients. In this review we will describe recent advances in the field of liquid biopsy markers focusing on their advantages and disadvantages.

Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application

Renal cell carcinoma (RCC) is a major pathological type of kidney cancer and is one of the most common malignancies worldwide. The unremarkable symptoms of early stages, proneness to postoperative metastasis or recurrence, and low sensitivity to radiotherapy and chemotherapy pose a challenge for the diagnosis and treatment of RCC. Liquid biopsy is an emerging test that measures patient biomarkers, including circulating tumor cells, cell-free DNA/cell-free tumor DNA, cell-free RNA, exosomes, and tumor-derived metabolites and proteins. Owing to its non-invasiveness, liquid biopsy enables continuous and real-time collection of patient information for diagnosis, prognostic assessment, treatment monitoring, and response evaluation. Therefore, the selection of appropriate biomarkers for liquid biopsy is crucial for identifying high-risk patients, developing personalized therapeutic plans, and practicing precision medicine. In recent years, owing to the rapid development and iteration of extraction and analysis technologies, liquid biopsy has emerged as a low cost, high efficiency, and high accuracy clinical detection method. Here, we comprehensively review liquid biopsy components and their clinical applications over the past 5 years. Additionally, we discuss its limitations and predict its future prospects.

Expression of Epithelial and Mesenchymal Markers in Plasmatic Extracellular Vesicles as a Diagnostic Tool for Neoplastic Processes

Tumor-derived extracellular vesicles (TD-EVs) have active roles as cancer hallmark enablers. EVs RNA of epithelial and stromal cells carry information that facilitates the communication processes that contribute to oncological progression, so the objective of this work was to validate by RT-PCR the presence of epithelial (KRT19; CEA) and stromal (COL1A2; COL11A1) markers in RNA of plasmatic EVs in healthy and diverse-malignancy patients for the development of a non-invasive cancer diagnosis system using liquid biopsy. Ten asymptomatic controls and 20 cancer patients were included in the study, and results showed that the isolated plasmatic EVs by scanning transmission electron microscopy (STEM) andBiomedical Research Institute A Coruña nanoparticle tracking analysis (NTA) contained most exosome structures with also a considerable percentage of microvesicles. No differences were found in concentration and size distribution between the two cohorts of patients, but significant gene expression in epithelial and mesenchymal markers between healthy donors and patients with active oncological disease was shown. Results of quantitative RT-PCR are solid and reliable for KRT19, COL1A2, and COL11A1, so the analysis of RNA extracted from TD-EVs could be a correct approach to develop a diagnostic tool in oncological processes.

Integrative analysis of multi-omics data for liquid biopsy

The innovation of liquid biopsy holds great potential to revolutionise cancer management through early diagnosis and timely treatment of cancer. Integrative analysis of different tumour-derived omics data (such as genomics, epigenetics, fragmentomics, and proteomics) from body fluids for cancer detection and monitoring could outperform the analysis of single modality data alone. In this review, we focussed on the discussion of early cancer detection and molecular residual disease surveillance based on multi-omics data of blood. We summarised diverse types of tumour-derived components, current popular platforms for profiling cancer-associated signals, machine learning approaches for joint analysis of liquid biopsy data, as well as multi-omics-based early detection of cancers, molecular residual disease monitoring, and treatment response surveillance. We also discussed the challenges and future directions of multi-omics-based liquid biopsy. With the development of both experimental protocols and computational methods dedicated to liquid biopsy, the implementation of multi-omics strategies into the clinical workflow will likely benefit the clinical management of cancers including decision-making guidance and patient outcome improvement.

Predicting the Likelihood of Colorectal Cancer with Artificial Intelligence Tools Using Fourier Transform Infrared Signals Obtained from Tumor Samples

The early and accurate detection of colorectal cancer (CRC) significantly affects its prognosis and clinical management. However, current standard diagnostic procedures for CRC often lack sensitivity and specificity since most rely on visual examination. Hence, there is a need to develop more accurate methods for its diagnosis. Support vector machine (SVM) and feedforward neural network (FNN) models were designed using the Fourier transform infrared (FT-IR) spectral data of several colorectal tissues that were unanimously identified as either benign or malignant by different unrelated pathologists. The set of samples in which the pathologists had discordant readings were then analyzed using the AI models described above. Between the SVM and NN models, the NN model was able to outperform the SVM model based on their prediction confidence scores. Using the spectral data of the concordant samples as training set, the FNN was able to predict the histologically diagnosed malignant tissues (n = 118) at 59.9-99.9% confidence (average = 93.5%). Of the 118 samples, 84 (71.18%) were classified with an above average confidence score, 34 (28.81%) classified below the average confidence score, and none was misclassified. Moreover, it was able to correctly identify the histologically confirmed benign samples (n = 83) at 51.5-99.7% confidence (average = 91.64%). Of the 83 samples, 60 (72.29%) were classified with an above average confidence score, 22 (26.51%) classified below the average confidence score, and only 1 sample (1.20%) was misclassified. The study provides additional proof of the ability of attenuated total reflection (ATR) FT-IR enhanced by AI tools to predict the likelihood of CRC without dependence on morphological changes in tissues.

Circular RNAs in peripheral blood mononuclear cells are more stable than linear RNAs upon sample processing delay

Circular RNAs (circRNAs) are a novel class of RNAs with closed loop structure. Blood circRNAs are widely acknowledged to be more stable than linear mRNAs, which show promising prospect to be liquid biopsy biomarkers for clinical applications. However, accumulating studies have demonstrated that sample processing delays have profound effects on blood transcriptome expression profiles, wherein knowledge remains elusive about the impacts of prolonged sample processing on blood expression profiles of circRNAs. We collected whole blood samples from three donors and isolated peripheral blood mononuclear cells (PBMCs) at six different incubation time points. We measured total RNA expression profiles using RNA sequencing (RNA‐seq) and investigated the differentially expressed circRNAs, mRNAs and lncRNAs upon blood processing delay. Meanwhile, we explored the underlying inducement of aberrant expression of circRNAs against their corresponding mRNA transcripts. Finally, we utilized rMATS‐turbo and CIRI‐AS, respectively, to screen out differential alternative splicing (AS) events in linear mRNAs and circRNAs. Sample incubation at 4°C lasting to 48 hours (h) led to minimal effects to circRNAs' expression. However, it induced extensive alterations for mRNAs and lncRNAs when the incubation time was beyond 12 h. Additionally, only 2 h processing delays may result in profound impacts on AS events of linear mRNAs, while less impact on the equivalence of circRNAs. Our results suggested that PBMC circRNAs are stable upon sample processing delay, which are more suitable to be liquid biopsy biomarkers.

Diagnostic and Therapeutic Potential of Circulating-Free DNA and Cell-Free RNA in Cancer Management

Over time, molecular biology and genomics techniques have been developed to speed up the early diagnosis and clinical management of cancer. These therapies are often most effective when administered to the subset of malignancies harboring the target identified by molecular testing. Important advances in applying molecular testing involve circulating-free DNA (cfDNA)- and cell-free RNA (cfRNA)-based liquid biopsies for the diagnosis, prognosis, prediction, and treatment of cancer. Both cfDNA and cfRNA are sensitive and specific biomarkers for cancer detection, which have been clinically proven through multiple randomized and prospective trials. These help in cancer management based on the noninvasive evaluation of size, quantity, and point mutations, as well as copy number alterations at the tumor site. Moreover, personalized detection of ctDNA helps in adjuvant therapeutics and predicts the chances of recurrence of cancer and resistance to cancer therapy. Despite the controversial diagnostic values of cfDNA and cfRNA, many clinical trials have been completed, and the Food and Drug Administration has approved many multigene assays to detect genetic alterations in the cfDNA of cancer patients. In this review, we underpin the recent advances in the physiological roles of cfDNA and cfRNA, as well as their roles in cancer detection by highlighting recent clinical trials and their roles as prognostic and predictive markers in cancer management.

Current challenges and best practices for cell-free long RNA biomarker discovery

The analysis of biomarkers in biological fluids, also known as liquid biopsies, is seen with great potential to diagnose complex diseases such as cancer with a high sensitivity and minimal invasiveness. Although it can target any biomolecule, most liquid biopsy studies have focused on circulating nucleic acids. Historically, studies have aimed at the detection of specific mutations on cell-free DNA (cfDNA), but recently, the study of cell-free RNA (cfRNA) has gained traction. Since 2020, a handful of cfDNA tests have been approved for therapy selection by the FDA, however, no cfRNA tests are approved to date. One of the main drawbacks in the field of RNA-based liquid biopsies is the low reproducibility of the results, often caused by technical and biological variability, a lack of standardized protocols and insufficient cohorts. In this review, we will identify the main challenges and biases introduced during the different stages of biomarker discovery in liquid biopsies with cfRNA and propose solutions to minimize them.

microRNAs in Subarachnoid Hemorrhage (Review of Literature)

Recently, many studies have shown that microRNAs (miRNAs) in extracellular bioliquids are strongly associated with subarachnoid hemorrhage (SAH) and its complications. The article presents issues related to the occurrence of subarachnoid hemorrhage (epidemiology, symptoms, differential diagnosis, examination, and treatment of the patient) and a review of current research on the correlation between miRNAs and the complications of SAH. The potential use of miRNAs as biomarkers in the treatment of SAH is presented.

Extracellular Vesicles and Their Associated miRNAs as Potential Biomarkers in Intracranial Aneurysm

Intracranial aneurysms (IA) are abnormal expansions of the intracranial arteries. Once it ruptures, the mortality and disability rate are high. The cost of imaging examinations is high, and rupture risk cannot be predicted, making it difficult for high-risk groups to be screened and prevented. Thus, clinically effective biomarkers are required to screen high-risk groups, estimate the risk of rupture, and determine the appropriate early intervention step. This article introduces the current research and application of exosome-derived microRNA (miRNA) as biomarkers of intracranial aneurysms and their limitations, which can give researchers a general overview of the research in this field. It can also serve as a reference point for selecting related research directions.

Physical exercise and the functions of microRNAs

MicroRNAs (miRNAs) control RNA translation and are a class of small, tissue-specific, non-protein-coding RNAs that maintain cellular homeostasis through negative gene regulation. Maintenance of the physiological environment depends on the proper control of miRNA expression, as these molecules influence almost all genetic pathways, from the cell cycle checkpoint to cell proliferation and apoptosis, with a wide range of target genes. Dysregulation of the expression of miRNAs is correlated with several types of diseases, acting as regulators of cardiovascular functions, myogenesis, adipogenesis, osteogenesis, hepatic lipogenesis, and important brain functions. miRNAs can be modulated by environmental factors or external stimuli, such as physical exercise, and can eventually induce specific and adjusted changes in the transcriptional response. Physical exercise is used as a preventive and non-pharmacological treatment for many diseases. It is well established that physical exercise promotes various benefits in the human body such as muscle hypertrophy, mental health improvement, cellular apoptosis, weight loss, and inhibition of cell proliferation. This review highlights the current knowledge on the main miRNAs altered by exercise in the skeletal muscle, cardiac muscle, bone, adipose tissue, liver, brain, and body fluids. In addition, knowing the modifications induced by miRNAs and relating them to the results of prescribed physical exercise with different protocols and intensities can serve as markers of physical adaptation to training and responses to the effects of physical exercise for some types of chronic diseases. This narrative review consists of randomized exercise training experiments with humans and/or animals, combined with analyses of miRNA modulation.

Saliva Based Liquid Biopsies in Head and Neck Cancer: How Far Are We From the Clinic?

Head and neck cancer (HNC) remains to be a major cause of mortality worldwide because of confounding factors such as late-stage tumor diagnosis, loco-regional aggressiveness and distant metastasis. The current standardized diagnostic regime for HNC is tissue biopsy which fails to determine the thorough tumor dynamics. Therefore, due to the ease of collection, recent studies have focused on the utility of saliva based liquid biopsy approach for serial sampling, early diagnosis, prognosis, longitudinal monitoring of disease progression and treatment response in HNC patients. Saliva collection is convenient, non-invasive, and pain-free and offers repetitive sampling along with real time monitoring of the disease. Moreover, the detection, isolation and analysis of tumor-derived components such as Circulating Tumor Nucleic Acids (CTNAs), Extracellular Vesicles (EVs), Circulating Tumor Cells (CTCs) and metabolites from saliva can be used for genomic and proteomic examination of HNC patients. Although, these circulatory biomarkers have a wide range of applications in clinical settings, no validated data has yet been established for their usage in clinical practice for HNC. Improvements in isolation and detection technologies and next-generation sequencing analysis have resolved many technological hurdles, allowing a wide range of saliva based liquid biopsy application in clinical backgrounds. Thus, in this review, we discussed the rationality of saliva as plausible biofluid and clinical sample for diagnosis, prognosis and therapeutics of HNC. We have described the molecular components of saliva that could mirror the disease status, recent outcomes of salivaomics associated with HNC and current technologies which have the potential to improve the clinical value of saliva in HNC.

Integrative Analyses of Circulating mRNA and lncRNA Expression Profile in Plasma of Lung Cancer Patients

Circulating-free RNAs (cfRNAs) have been regarded as potential biomarkers for “liquid biopsy” in cancers. However, the circulating messenger RNA (mRNA) and long noncoding RNA (lncRNA) profiles of lung cancer have not been fully characterized. In this study, we profiled circulating mRNA and lncRNA profiles of 16 lung cancer patients and 4 patients with benign pulmonary nodules. Compared with benign pulmonary nodules, 806 mRNAs and 1,762 lncRNAs were differentially expressed in plasma of lung adenocarcinoma patients. For lung squamous cell carcinomas, 256 mRNAs and 946 lncRNAs were differentially expressed. A total of 231 mRNAs and 298 lncRNAs were differentially expressed in small cell lung cancer. Eleven mRNAs, 51 lncRNAs, and 207 canonical pathways were differentially expressed in lung cancer in total. Forty-five blood samples were collected to verify our findings via performing qPCR. There are plenty of meaningful mRNAs and lncRNAs that were found. MYC, a transcription regulator associated with the stemness of cancer cells, is overexpressed in lung adenocarcinoma. Transforming growth factor beta (TGFB1), which plays pleiotropic roles in cancer progression, was found to be upregulated in lung squamous carcinoma. MALAT1, a well-known oncogenic lncRNA, was also found to be upregulated in lung squamous carcinoma. Thus, this study provided a systematic resource of mRNA and lncRNA expression profiles in lung cancer plasma.

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Tumor-Derived circRNAs as Circulating Biomarkers for Breast Cancer

Early diagnosis is the key to improving the prognosis of breast cancer (BC) patients; however, there are currently no circulating biomarkers that demonstrate good sensitivity and specificity. This study applied circular RNA (circRNA) microarray analysis, screening, and verification in BC plasma samples to identify three tumor-derived differentially expressed circRNAs: hsa_circ_0000091, hsa_circ_0067772, and hsa_circ_0000512. We constructed a diagnostic model using logistic regression analysis in the training set and established an optimal diagnostic model based on the three circRNAs, which showed sensitivity, specificity, and area under the curve (AUC) values of .971, .902, and .974, respectively. We then verified the diagnostic model in the test set which showed satisfactory stability for BC diagnosis. Additionally, the expression of hsa_circ_0000091 in plasma correlated with axillary lymph node (ALN) metastasis, TNM stage, and prognosis of BC patients. Furthermore, hsa_circ_0000091 combined with ultrasound showed predictive ability for ALN metastasis, with an AUC of .808. These findings suggested that the three identified circRNAs can be used as circulating biomarkers for BC diagnosis, with hsa_circ_0000091 potentially representing a prognostic biomarker for BC and novel approach for predicting ALN metastasis.

Serum RNAs can predict lung cancer up to 10 years prior to diagnosis

Lung cancer (LC) prognosis is closely linked to the stage of disease when diagnosed. We investigated the biomarker potential of serum RNAs for the early detection of LC in smokers at different prediagnostic time intervals and histological subtypes. In total, 1061 samples from 925 individuals were analyzed. RNA sequencing with an average of 18 million reads per sample was performed. We generated machine learning models using normalized serum RNA levels and found that smokers later diagnosed with LC in 10 years can be robustly separated from healthy controls regardless of histology with an average area under the ROC curve (AUC) of 0.76 (95% CI, 0.68-0.83). Furthermore, the strongest models that took both time to diagnosis and histology into account successfully predicted non-small cell LC (NSCLC) between 6 and 8 years, with an AUC of 0.82 (95% CI, 0.76-0.88), and SCLC between 2 and 5 years, with an AUC of 0.89 (95% CI, 0.77-1.0), before diagnosis. The most important separators were microRNAs, miscellaneous RNAs, isomiRs, and tRNA-derived fragments. We have shown that LC can be detected years before diagnosis and manifestation of disease symptoms independently of histological subtype. However, the highest AUCs were achieved for specific subtypes and time intervals before diagnosis. The collection of models may therefore also predict the severity of cancer development and its histology. Our study demonstrates that serum RNAs can be promising prediagnostic biomarkers in an LC screening setting, from early detection to risk assessment.

Irreversible alteration of extracellular vesicle and cell-free messenger RNA profiles in human plasma associated with blood processing and storage

The discovery and utility of clinically relevant circulating biomarkers depend on standardized methods that minimize preanalytical errors. Despite growing interest in studying extracellular vesicles (EVs) and cell-free messenger RNA (cf-mRNA) as potential biomarkers, how blood processing and freeze/thaw impacts the profiles of these analytes in plasma was not thoroughly understood. We utilized flow cytometric analysis to examine the effect of differential centrifugation and a freeze/thaw cycle on EV profiles. Utilizing flow cytometry postacquisition analysis software (FCMpass) to calibrate light scattering and fluorescence, we revealed how differential centrifugation and post-freeze/thaw processing removes and retains EV subpopulations. Additionally, cf-mRNA levels measured by RT-qPCR profiles from a panel of housekeeping, platelet, and tissue-specific genes were preferentially affected by differential centrifugation and post-freeze/thaw processing. Critically, freezing plasma containing residual platelets yielded irreversible ex vivo generation of EV subpopulations and cf-mRNA transcripts, which were not removable by additional processing after freeze/thaw. Our findings suggest the importance of minimizing confounding variation attributed to plasma processing and platelet contamination.

Detection of breast cancer by ATR-FTIR spectroscopy using artificial neural networks

In this study, three (3) neural networks (NN) were designed to discriminate between malignant (n = 78) and benign (n = 88) breast tumors using their respective attenuated total reflection Fourier transform infrared (ATR-FTIR) spectral data. A proposed NN-based sensitivity analysis was performed to determine the most significant IR regions that distinguished benign from malignant samples. The result of the NN-based sensitivity analysis was compared to the obtained results from FTIR visual peak identification. In training each NN models, a 10-fold cross validation was performed and the performance metrics-area under the curve (AUC), accuracy, positive predictive value (PPV), specificity rate (SR), negative predictive value (NPV), and recall rate (RR)-were averaged for comparison. The NN models were compared to six (6) machine learning models-logistic regression (LR), Naïve Bayes (NB), decision trees (DT), random forest (RF), support vector machine (SVM) and linear discriminant analysis (LDA)-for benchmarking. The NN models were able to outperform the LR, NB, DT, RF, and LDA for all metrics; while only surpassing the SVM in accuracy, NPV and SR. The best performance metric among the NN models was 90.48% ± 10.30% for AUC, 96.06% ± 7.07% for ACC, 92.18 ± 11.88% for PPV, 94.19 ± 10.57% for NPV, 89.04% ± 16.75% for SR, and 94.34% ± 10.54% for RR. Results from the proposed sensitivity analysis were consistent with the visual peak identification. However, unlike the FTIR visual peak identification method, the NN-based method identified the IR region associated with C-OH C-OH group carbohydrates as significant. IR regions associated with amino acids and amide proteins were also determined as possible sources of variability. In conclusion, results show that ATR-FTIR via NN is a potential diagnostic tool. This study also suggests a possible more specific method in determining relevant regions within a sample's spectrum using NN.

Transposons: Unexpected players in cancer

Transposons are repetitive DNA sequences encompassing about half of the human genome. They play a vital role in genome stability maintenance and contribute to genomic diversity and evolution. Their activity is regulated by various mechanisms considering the deleterious effects of these mobile elements. Various genetic risk factors and environmental stress conditions affect the regulatory pathways causing alteration of transposon expression. Our knowledge of the biological role of transposons is limited especially in various types of cancers. Retrotransposons of different types (LTR-retrotransposons, LINEs and SINEs) regulate a plethora of genes that have a role in cell reprogramming, tumor suppression, cell cycle, apoptosis, cell adhesion and migration, and DNA repair. The regulatory mechanisms of transposons, their deregulation and different mechanisms underlying transposon-mediated carcinogenesis in humans focusing on the three most prevalent types, lung, breast and colorectal cancers, were reviewed. The modes of regulation employed include alternative splicing, deletion, insertion, duplication in genes and promoters resulting in upregulation, downregulation or silencing of genes.

Identification of Combinations of Plasma lncRNAs and mRNAs as Potential Biomarkers for Precursor Lesions and Early Gastric Cancer

Patients with gastric cancer (GC) are usually first diagnosed at an advanced stage due to the absence of obvious symptoms at an early GC (EGC) stage. Therefore, it is necessary to identify an effective screening method to detect precursor lesions of GC (PLGC) and EGC to increase the 5-year survival rate of patients. Cell-free RNA, as a biomarker, has shown potential in early diagnosis, personalised treatment, and prognosis of cancer. In this study, six RNAs (CEBPA-AS1, INHBA-AS1, AK001058, UCA1, PPBP, and RGS18) were analysed via real-time quantitative polymerase chain reaction (RT-qPCR) using the plasma of patients with EGC and PLGC to identify diagnostic biomarkers. The receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic accuracy. Among the six RNAs, four lncRNAs (CEBPA-AS1, INHBA-AS1, AK001058, and UCA1) were upregulated and two mRNAs (PPBP and RGS18) were downregulated in the plasma of patients with PLGC and EGC. According to the findings of the ROC analysis, the four-RNA combination of INHBA-AS1, AK001058, UCA1, and RGS18 had the highest area under the curve (AUC) value for determining risk of GC in patients with PLGC and the six-RNA combination including CEBPA-AS1, INHBA-AS1, AK001058, UCA1, PPBP, and RGS18 had the highest AUC value for determining the risk of GC in patients with EGC. The results suggest the potential usefulness of noninvasive biomarkers for the molecular diagnosis of GC at earlier stages.

Circulating RNAs in prostate cancer patients

Growing bodies of evidence have demonstrated that the identification of prostate cancer (PCa) biomarkers in the patients' blood and urine may remarkably improve PCa diagnosis and progression monitoring. Among diverse cancer-derived circulating materials, extracellular RNA molecules (exRNAs) represent a compelling component to investigate cancer-related alterations. Once outside the intracellular environment, exRNAs circulate in biofluids either in association with protein complexes or encapsulated inside extracellular vesicles (EVs). Notably, EV-associated RNAs (EV-RNAs) were used for the development of several assays (such as the FDA-approved Progensa Prostate Cancer Antigen 3 (PCA3 test) aiming at improving early PCa detection. EV-RNAs encompass a mixture of species, including small non-coding RNAs (e.g. miRNA and circRNA), lncRNAs and mRNAs. Several methods have been proposed to isolate EVs and relevant RNAs, and to perform RNA-Seq studies to identify potential cancer biomarkers. However, EVs in the circulation of a cancer patient include a multitude of diverse populations that are released by both cancer and normal cells from different tissues, thereby leading to a heterogeneous EV-RNA-associated transcriptional signal. Decrypting the complexity of such a composite signal is nowadays the major challenge faced in the identification of specific tumor-associated RNAs. Multiple deconvolution algorithms have been proposed so far to infer the enrichment of cancer-specific signals from gene expression data. However, novel strategies for EVs sorting and sequencing of RNA associated to single EVs populations will remarkably facilitate the identification of cancer-related molecules. Altogether, the studies summarized here demonstrate the high potential of using EV-RNA biomarkers in PCa and highlight the urgent need of improving technologies and computational approaches to characterize specific EVs populations and their relevant RNA cargo.

Application of third-generation sequencing in cancer research

In the past several years, nanopore sequencing technology from Oxford Nanopore Technologies (ONT) and single-molecule real-time (SMRT) sequencing technology from Pacific BioSciences (PacBio) have become available to researchers and are currently being tested for cancer research. These methods offer many advantages over most widely used high-throughput short-read sequencing approaches and allow the comprehensive analysis of transcriptomes by identifying full-length splice isoforms and several other posttranscriptional events. In addition, these platforms enable structural variation characterization at a previously unparalleled resolution and direct detection of epigenetic marks in native DNA and RNA. Here, we present a comprehensive summary of important applications of these technologies in cancer research, including the identification of complex structure variants, alternatively spliced isoforms, fusion transcript events, and exogenous RNA. Furthermore, we discuss the impact of the newly developed nanopore direct RNA sequencing (RNA-Seq) approach in advancing epitranscriptome research in cancer. Although the unique challenges still present for these new single-molecule long-read methods, they will unravel many aspects of cancer genome complexity in unprecedented ways and present an encouraging outlook for continued application in an increasing number of different cancer research settings.

The potential of using blood circular RNA as liquid biopsy biomarker for human diseases

Circular RNA (circRNA) is a novel class of single-stranded RNAs with a closed loop structure. The majority of circRNAs are formed by a back-splicing process in pre-mRNA splicing. Their expression is dynamically regulated and shows spatiotemporal patterns among cell types, tissues and developmental stages. CircRNAs have important biological functions in many physiological processes, and their aberrant expression is implicated in many human diseases. Due to their high stability, circRNAs are becoming promising biomarkers in many human diseases, such as cardiovascular diseases, autoimmune diseases and human cancers. In this review, we focus on the translational potential of using human blood circRNAs as liquid biopsy biomarkers for human diseases. We highlight their abundant expression, essential biological functions and significant correlations to human diseases in various components of peripheral blood, including whole blood, blood cells and extracellular vesicles. In addition, we summarize the current knowledge of blood circRNA biomarkers for disease diagnosis or prognosis.

The Value of Circulating Circular RNA in Cancer Diagnosis, Monitoring, Prognosis, and Guiding Treatment

Liquid biopsy includes non-invasive analysis of circulating tumor-derived substances. It is a novel, innovative cancer screening tool that overcomes the limitations of current invasive tissue examinations in precision oncology. Circular RNA (circRNA) is a recent, novel, and attractive liquid biomarker showing stability, abundance, and high specificity in various diseases, especially in human cancers. This review focused on the emerging potential of human circRNA in body fluids as the liquid biopsy biomarkers for cancers and the methods used to detect the circRNA expression and summarized the construction of circRNA biomarkers in body fluids for treating human cancers and their limitations before they become part of routine clinical medicine. Furthermore, the future opportunities and challenges of translating circRNAs in liquid biopsy into clinical practices were explored.

Circulating non-coding RNAs as a diagnostic and management biomarker for breast cancer: current insights

Cancer biomarkers can be used to determine the molecular status of a tumor or its metastases, which either release them directly into body fluids or indirectly through disruption of tumor/metastatic tissue. New minimally invasive and repeatable sample collection methods, such as liquid biopsy, have been developed in the last decade to apply cancer knowledge and track its progression. Circulating non-coding RNAs, which include microRNAs, long non-coding RNAs, and PIWI-interacting RNAs, are increasingly being recognized as potential cancer biomarkers. The growing understanding of cancer's molecular pathogenesis, combined with the rapid development of new molecular techniques, encourages the study of early molecular alterations associated with cancer development in body fluids. Specific genetic and epigenetic changes in circulating free RNA (cf-RNA) in plasma, serum, and urine could be used as diagnostic biomarkers for a variety of cancers. Only a subset of these cf-RNAs have been studied in breast cancer, with the most extensive research focusing on cf-miRNA in plasma. These findings pave the way for immediate use of selected cf-RNAs as biomarkers in breast cancer liquid biopsy, as well as additional research into other cf-RNAs to advance.

Liquid Biopsies for Molecular Biology-Based Radiotherapy

Molecular alterations drive cancer initiation and evolution during development and in response to therapy. Radiotherapy is one of the most commonly employed cancer treatment modalities, but radiobiologic approaches for personalizing therapy based on tumor biology and individual risks remain to be defined. In recent years, analysis of circulating nucleic acids has emerged as a non-invasive approach to leverage tumor molecular abnormalities as biomarkers of prognosis and treatment response. Here, we evaluate the roles of circulating tumor DNA and related analyses as powerful tools for precision radiotherapy. We highlight emerging work advancing liquid biopsies beyond biomarker studies into translational research investigating tumor clonal evolution and acquired resistance.

A systematic review of extracellular vesicles as non-invasive biomarkers in glioma diagnosis, prognosis, and treatment response monitoring

The present systematic review was done to investigate the possible application of Extracellular vesicles (EVs) in the diagnosis, prognosis, and treatment response monitoring of gliomas using available literature to wrap up the final applicable conclusion in this regard. we searched PubMed/MEDLINE, Scopus, and ISI Web of Science databases. Authors evaluated the quality of the included studies by the QUADAS-2 tool. In total, 2037 published datasets were retrieved through systematic search. Upon screening for eligibility, 35 datasets were determined as eligible. Exosome was the EV-subtype described in the majority of studies, and most datasets used serum as the primary EVs isolation source. EVs isolation was primarily conducted by ultracentrifugation. 31 datasets reported that EVs hold considerable potential for being used in diagnostics, with the majority reporting different types of miRNAs as biomarkers. Besides, 8 datasets reported that EVs could be a potential source of prognostic biomarkers. And finally, 3 datasets reported that EVs might be a reliable strategy for monitoring therapy response in glioma patients. According to the findings of the current systematic review, it seems that miR-301, miR-21, and HOTAIR had the highest diagnostic accuracy. However, heterogeneous and limited evidence regarding prognosis and treatment response monitoring precludes us from drawing a practical conclusion regarding EVs.

Liquid Biopsy, ctDNA Diagnosis through NGS

Liquid biopsy with circulating tumor DNA (ctDNA) profiling by next-generation sequencing holds great promise to revolutionize clinical oncology. It relies on the basis that ctDNA represents the real-time status of the tumor genome which contains information of genetic alterations. Compared to tissue biopsy, liquid biopsy possesses great advantages such as a less demanding procedure, minimal invasion, ease of frequent sampling, and less sampling bias. Next-generation sequencing (NGS) methods have come to a point that both the cost and performance are suitable for clinical diagnosis. Thus, profiling ctDNA by NGS technologies is becoming more and more popular since it can be applied in the whole process of cancer diagnosis and management. Further developments of liquid biopsy ctDNA testing will be beneficial for cancer patients, paving the way for precision medicine. In conclusion, profiling ctDNA with NGS for cancer diagnosis is both biologically sound and technically convenient.

Assessment of Circulating Nucleic Acids in Cancer: From Current Status to Future Perspectives and Potential Clinical Applications

Current approaches for cancer detection and characterization are based on radiological procedures coupled with tissue biopsies, despite relevant limitations in terms of overall accuracy and feasibility, including relevant patients' discomfort. Liquid biopsies enable the minimally invasive collection and analysis of circulating biomarkers released from cancer cells and stroma, representing therefore a promising candidate for the substitution or integration in the current standard of care. Despite the potential, the current clinical applications of liquid biopsies are limited to a few specific purposes. The lack of standardized procedures for the pre-analytical management of body fluids samples and the detection of circulating biomarkers is one of the main factors impacting the effective advancement in the applicability of liquid biopsies to clinical practice. The aim of this work, besides depicting current methods for samples collection, storage, quality check and biomarker extraction, is to review the current techniques aimed at analyzing one of the main circulating biomarkers assessed through liquid biopsy, namely cell-free nucleic acids, with particular regard to circulating tumor DNA (ctDNA). ctDNA current and potential applications are reviewed as well.

Liquid biomarkers for the management of paediatric neuroblastoma: an approach to personalised and targeted cancer therapy

Background:

Neuroblastoma is the most common extracranial solid tumour of infancy and accounts for about 6–10% of paediatric cancers. It has a biologically and clinically heterogeneous behaviour that ranges from spontaneous regression to cases of highly aggressive metastatic disease that could be unresponsive to standard therapy. In recent years, there have been several investigations into the development of various diagnostic, predictive and prognostic biomarkers towards personalised and targeted management of the disease.

Materials and Methods:

This paper reports on the review of current clinical and emerging biomarkers used in risk assessment, screening for early detection and diagnosis, prognostication and monitoring of the response of treatment of neuroblastoma in paediatric patients.

Conclusions:

Tumour markers can significantly improve diagnosis; however, the invasive, unpleasant and inconvenient nature of current tissue biopsies limits their applications, especially in paediatric patients. Therefore, the development of a non-invasive, reliable high accurate and personalised diagnostic tool capable of early detection and rapid response is the most promising step towards advanced cancer management from tumour diagnosis, therapy to patient monitoring and represents an important step towards the promise of precision, personalised and targeted medicine. Liquid biopsy assay with wide ranges of clinical applications is emerging to hold incredible potential for advancing cancer treatment and has greater promise for diagnostic purposes, identification and tracking of tumour-specific alterations during the course of the disease and to guide therapeutic decisions.

Liquid biopsy for therapy monitoring in early-stage non-small cell lung cancer

Liquid biopsy is now considered a valuable diagnostic tool for advanced metastatic non-small cell lung cancer (NSCLC). In NSCLC, circulating tumor DNA (ctDNA) analysis has been shown to increase the chances of identifying the presence of targetable mutations and has been adopted by many clinicians owing to its low risk. Serial monitoring of ctDNA may also help assess the treatment response or for monitoring relapse. As the presence of detectable plasma ctDNA post-surgery likely indicates residual tumor burden, studies have been performed to quantify plasma ctDNA to assess minimal residual disease (MRD) in early-stage resected NSCLC. Most data on utilizing liquid biopsy for monitoring MRD in early-stage NSCLC are from small-scale studies using ctDNA. Here, we review the recent research on liquid biopsy in NSCLC, not limited to ctDNA, and focus on novel methods such as micro RNAs (miRNA) and long non-coding (lncRNA).

Liquid biopsy in cholangiocarcinoma: Current status and future perspectives

Cholangiocarcinoma (CCA) are a heterogeneous group of tumors in terms of aetiology, natural history, morphological subtypes, molecular alterations and management, but all sharing complex diagnosis, management, and poor prognosis. Several mutated genes and epigenetic changes have been detected in CCA, with the potential to identify diagnostic and prognostic biomarkers and therapeutic targets. Accessing tumoral components and genetic material is therefore crucial for the diagnosis, management and selection of targeted therapies; but sampling tumor tissue, when possible, is often risky and difficult to be repeated at different time points. Liquid biopsy (LB) represents a way to overcome these issues and comprises a diverse group of methodologies centering around detection of tumor biomarkers from fluid samples. Compared to the traditional tissue sampling methods LB is less invasive and can be serially repeated, allowing a real-time monitoring of the tumor genetic profile or the response to therapy. In this review, we analysis the current evidence on the possible roles of LB (circulating DNA, circulating RNA, exosomes, cytokines) in the diagnosis and management of patients affected by CCA.

Urinary microRNA and mRNA in Tumors

Liquid biopsy is gaining importance in the context of analysis of circulating subcellular components, such as exosomes and nucleic acids, and the investigation of biological fluids is increasing because they express features common to the tissue of origin. Particularly, urine has become one of the most attractive biofluids in clinical practice due to its easy collection approach, its availability of large quantities, and its noninvasiveness. Furthermore, a peculiarity is that, compared to serum or plasma, urine is characterized by a simpler composition that improves isolation and identification of biomarkers. Recent studies have been associated with the investigation of mRNAs and microRNAs as potential noninvasive cancer biomarkers in urine, and to date, several approaches for isolating and measuring urinary nucleic acids have been established, despite still developing. This chapter aims at giving some main published evidences on urinary microRNAs and mRNAs, with the intent to consider their potential translational use in clinical practice.

Circulating miR-320a Acts as a Tumor Suppressor and Prognostic Factor in Non-small Cell Lung Cancer

Dysregulated expression profiles of microRNAs (miRNAs) have been observed in several types of cancer, including non-small cell lung cancer (NSCLC); however, the diagnostic and prognostic potential of circulating miRNAs in NSCLC remains largely undefined. Here we found that circulating miR-320a was significantly down-regulated (~5.87-fold; p < 0.0001) in NSCLC patients (n = 80) compared to matched control plasma samples from healthy subjects (n = 80). Kaplan-Meier survival analysis revealed that NSCLC patients with lower levels of circulating miR-320a had overall poorer prognosis and survival rates compared to patients with higher levels (p < 0.0001). Moreover, the diagnostic and prognostic potential of miR-320a correlated with clinicopathological characteristics such as tumor size, tumor node metastasis (TNM) stage, and lymph node metastasis. Functionally, depletion of miR-320a in human A549 lung adenocarcinoma cells induced their metastatic potential and reduced apoptosis, which was reversed by exogenous re-expression of miR-320a mimics, indicating that miR-320a has a tumor-suppressive role in NSCLC. These results were further supported by high levels of epithelial-mesenchymal transition (EMT) marker proteins (e.g., Beta-catenin, MMP9, and E-cadherin) in lung cancer cells and tissues via immunoblot and immunohistochemistry experiments. Moreover, through bioinformatics and dual-luciferase reporter assays, we demonstrated that AKT3 was a direct target of miR-320a. In addition, AKT3-associated PI3K/AKT/mTOR protein-signaling pathways were elevated with down-regulated miR-320a levels in NSCLC. These composite data indicate that circulating miR-320a may function as a tumor-suppressor miRNA with potential as a prognostic marker for NSCLC patients.

Role of cell-free DNA in haematological malignancies

Cell-free DNA (cfDNA) consists of fragments of double stranded DNA that are found in the circulation. They are released from the apoptosis of both normal haemopoietic cells and malignant cells. The use of cfDNA from easily accessible peripheral blood samples has created a new strategy in studying molecular genomics in haematological malignancies. Its use in diagnosis, prognosis and monitoring potentially precludes the need for repeated tissue samples, i.e., bone marrow biopsy or primary tissue biopsy. It also potentially provides a more comprehensive analysis of the disease as cfDNA are released from tumours from multiple sites of the body. While cfDNA research is still in its infancy, given its potential and the expansion in next generation sequencing (NGS) it has attracted a lot of attention in recent years. This review will focus on acute leukaemia, multiple myeloma and lymphoma and the potential diagnostic and prognostic implications of cfDNA, its role in response assessment and in detection of disease relapse.

The Role of Nucleases and Nucleic Acid Editing Enzymes in the Regulation of Self-Nucleic Acid Sensing

Detection of microbial nucleic acids by the innate immune system is mediated by numerous intracellular nucleic acids sensors. Upon the detection of nucleic acids these sensors induce the production of inflammatory cytokines, and thus play a crucial role in the activation of anti-microbial immunity. In addition to microbial genetic material, nucleic acid sensors can also recognize self-nucleic acids exposed extracellularly during turn-over of cells, inefficient efferocytosis, or intracellularly upon mislocalization. Safeguard mechanisms have evolved to dispose of such self-nucleic acids to impede the development of autoinflammatory and autoimmune responses. These safeguard mechanisms involve nucleases that are either specific to DNA (DNases) or RNA (RNases) as well as nucleic acid editing enzymes, whose biochemical properties, expression profiles, functions and mechanisms of action will be detailed in this review. Fully elucidating the role of these enzymes in degrading and/or processing of self-nucleic acids to thwart their immunostimulatory potential is of utmost importance to develop novel therapeutic strategies for patients affected by inflammatory and autoimmune diseases.

Diagnostic accuracy of cerebrospinal fluid and serum-isolated extracellular vesicles for glioblastoma: a systematic review and meta-analysis

BACKGROUND

Glioblastoma (GBM) is the most malignant brain cancer because there are no available biopsy-free methods for the diagnosis or the preoperative early detection. In this regard, the development of a non- or minimally invasive methods for early detection could increase the survival rate of GBM patients.

METHODS

The present study aimed to assess the diagnostic accuracy of extracellular vesicles (EVs) derived RNAs, isolated from patients' CSF or serum for GBM diagnosis. For this purpose, we searched all literature databases and performed a backward and forward reference checking procedure to retrieve appropriate studies. We conducted a meta-analysis on EVs derived biomarkers as well as sensitivity analysis and meta-regression.

RESULTS

We identified EVs-derived 24 RNAs, which can diagnose GBM. The analyzed pooled data showed 76% sensitivity, 80% specificity, and 0.85 AUC, for 16 biomarkers. Besides, the pooled PLR, NLR, and DOR were 3.7, 0.30, and 12, respectively. Subgroup analysis did not show a significant difference between serum and CSF.

CONCLUSIONS

According to the pooled sensitivity, specificity, and AUC for EVs derived biomarkers, we suggest that EVs-derived biomarkers might serve as a high potential and noninvasive diagnostic tool for GBM detection using serum and CSF samples.

Diagnostic and prognostic potential of circulating miRNAs for intracranial aneurysms

Intracranial aneurysm (IA) is an abnormal focal dilation of an artery in the brain that results from a weakening of the inner muscular layer of a blood vessel wall. IAs represent the most common etiology of nontraumatic subarachnoid hemorrhage (SAH). Despite technological advances in the treatment and use of new diagnostic methods for IAs, they continue to pose a significant risk of mortality and disability. Thus, early recognition of IA with a high risk of rupture is crucial for the stratification of patients with such a formidable disease. MicroRNAs (miRNA) are endogenous noncoding RNAs of 18-22 nucleotides that regulate gene expression at the post-transcriptional level through interaction with 3'-untranslated regions (3'UTRs) of the target mRNAs. MiRNAs are involved in the pathogenesis of IAs, including in the mechanisms of formation, growth, and rupture. It is known that in many biological fluids of the human body, such as blood or cerebrospinal fluid (CSF), numerous miRNAs, called circulating miRNAs, have been detected. The expression profile of circulating miRNAs represents a certain part of the cells in which they are modified and secreted in accordance with the physiological or pathological conditions of these cells. Circulating miRNAs can be secreted from cells into human biological fluids in extracellular vesicles or can be bound to Ago2 protein, which makes them resistant to the effects of RNAse. Therefore, circulating miRNAs are considered as new potential biomarkers of interest in many diseases, including IA.