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

Emerging role of circulating cell-free RNA as a non-invasive biomarker for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a severe neoplastic disease associated with high morbidity and mortality rates. HCC is often detected at advanced stages leading to ineffective curative treatments. Recently, liquid biopsy has emerged as a non-invasive method to identify highly specific HCC biomarkers in bodily fluids such as blood, serum, urine, and saliva. Circulating cell-free nucleic acids (cfNAs), particularly cell-free DNA (cfDNA) and cell-free RNA (cfRNA), have become promising candidates for biomarkers in liquid biopsy applications. While cfDNA presented significant challenges, researchers have turned their attention to cfRNA, which can be efficiently identified through various methods and is considered a potential biomarker for cancer diagnosis and prognosis. This review primarily focuses on studies related to detecting various cfRNA in body fluids as biomarkers. The aim is to provide a summary of available information to assist researchers in their investigations and the development of new diagnostic and prognostic tools.

A review on cell-free RNA profiling: Insights into metabolic diseases and predictive value for bariatric surgery outcomes

BACKGROUND

The advent of liquid biopsies presents a novel, minimally invasive methodology for the detection of disease biomarkers, offering a significant advantage over traditional biopsy techniques. Particularly, the analysis of cell-free RNA (cfRNA) has garnered interest due to its dynamic expression profiles and the capability to study various RNA species, including messenger RNA (mRNA) and long non-coding RNA (lncRNA). These attributes position cfRNA as a versatile biomarker with broad potential applications in clinical research and diagnostics.

SCOPE OF REVIEW

This review delves into the utility of cfRNA biomarkers as prognostic tools for obesity-related comorbidities, such as diabetes, dyslipidemia, and non-alcoholic fatty liver disease.

MAJOR CONCLUSIONS

We evaluate the efficacy of cfRNA in forecasting metabolic outcomes associated with obesity and in identifying patients likely to experience favorable clinical outcomes following bariatric surgery. Additionally, this review synthesizes evidence from studies examining circulating cfRNA across different physiological and pathological states, with a focus on its role in diabetes, including disease progression monitoring and treatment efficacy assessment. Through this exploration, we underscore the emerging relevance of cfRNA signatures in the context of obesity and its comorbidities, setting the stage for future investigative efforts in this rapidly advancing domain.

Depletion-assisted multiplexed cell-free RNA sequencing reveals distinct human and microbial signatures in plasma versus extracellular vesicles

BACKGROUND

Cell-free long RNAs in human plasma and extracellular vesicles (EVs) have shown promise as biomarkers in liquid biopsy, despite their fragmented nature.

METHODS

To investigate these fragmented cell-free RNAs (cfRNAs), we developed a cost-effective cfRNA sequencing method called DETECTOR-seq (depletion-assisted multiplexed cell-free total RNA sequencing). DETECTOR-seq utilised a meticulously tailored set of customised guide RNAs to remove large amounts of unwanted RNAs (i.e., fragmented ribosomal and mitochondrial RNAs) in human plasma. Early barcoding strategy was implemented to reduce costs and minimise plasma requirements.

RESULTS

Using DETECTOR-seq, we conducted a comprehensive analysis of cell-free transcriptomes in both whole human plasma and EVs. Our analysis revealed discernible distributions of RNA types in plasma and EVs. Plasma exhibited pronounced enrichment in structured circular RNAs, tRNAs, Y RNAs and viral RNAs, while EVs showed enrichment in messenger RNAs (mRNAs) and signal recognition particle RNAs (srpRNAs). Functional pathway analysis highlighted RNA splicing-related ribonucleoproteins (RNPs) and antimicrobial humoral response genes in plasma, while EVs demonstrated enrichment in transcriptional activity, cell migration and antigen receptor-mediated immune signals. Our study indicates the comparable potential of cfRNAs from whole plasma and EVs in distinguishing cancer patients (i.e., colorectal and lung cancer) from healthy donors. And microbial cfRNAs in plasma showed potential in classifying specific cancer types.

CONCLUSIONS

Our comprehensive analysis of total and EV cfRNAs in paired plasma samples provides valuable insights for determining the need for EV purification in cfRNA-based studies. We envision the cost effectiveness and efficiency of DETECTOR-seq will empower transcriptome-wide investigations in the fields of cfRNAs and liquid biopsy.

KEYPOINTS

DETECTOR-seq (depletion-assisted multiplexed cell-free total RNA sequencing) enabled efficient and specific depletion of sequences derived from fragmented ribosomal and mitochondrial RNAs in plasma. Distinct human and microbial cell-free RNA (cfRNA) signatures in whole Plasma versus extracellular vesicles (EVs) were revealed. Both Plasma and EV cfRNAs were capable of distinguishing cancer patients from normal individuals, while microbial RNAs in Plasma cfRNAs enabled better classification of cancer types than EV cfRNAs.

Leveraging Cancer Phenotypic Plasticity for Novel Treatment Strategies

Cancer cells, like all other organisms, are adept at switching their phenotype to adjust to the changes in their environment. Thus, phenotypic plasticity is a quantitative trait that confers a fitness advantage to the cancer cell by altering its phenotype to suit environmental circumstances. Until recently, new traits, especially in cancer, were thought to arise due to genetic factors; however, it is now amply evident that such traits could also emerge non-genetically due to phenotypic plasticity. Furthermore, phenotypic plasticity of cancer cells contributes to phenotypic heterogeneity in the population, which is a major impediment in treating the disease. Finally, plasticity also impacts the group behavior of cancer cells, since competition and cooperation among multiple clonal groups within the population and the interactions they have with the tumor microenvironment also contribute to the evolution of drug resistance. Thus, understanding the mechanisms that cancer cells exploit to tailor their phenotypes at a systems level can aid the development of novel cancer therapeutics and treatment strategies. Here, we present our perspective on a team medicine-based approach to gain a deeper understanding of the phenomenon to develop new therapeutic strategies.

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

An overview of challenges associated with exosomal miRNA isolation toward liquid biopsy-based ovarian cancer detection

As one of the deadliest gynaecological cancers, ovarian cancer has been on the list. With lesser-known symptoms and lack of an accurate detection method, it is still difficult to catch it early. In terms of both the diagnosis and outlook for cancer, liquid biopsy has come a long way with significant advancements. Exosomes, extracellular components commonly shed by cancerous cells, are nucleic acid-rich particles floating in almost all body fluids and hold enormous promise, leading to minimallyinvasive molecular diagnostics. They have been shown as potential biomarkers in liquid biopsy, being implicated in tumour growth and metastasis. In order to address the drawbacks of ovarian cancer tumor heterogeneity, a liquid biopsy-based approach is being investigated by detecting cell-free nucleic acids, particularly non-coding RNAs, having the advantage of being less invasive and more prominent in nature. microRNAs are known to actively contribute to cancer development and their existence inside exosomes has also been made quite apparent which can be leveraged to diagnose and treat the disease. Extraction of miRNAs and exosomes is an arduous execution, and while other approaches have been investigated, none have produced results that are as encouraging due to limits in time commitment, yield, and, most significantly, damage to the exosomal structure resulting discrepancies in miRNA-based expression profiling for disease diagnosis. We have briefly outlined and reviewed the difficulties with exosome isolation techniques and the need for their standardization. The several widely used procedures and their drawbacks in terms of the exosomal purity they may produce have also been outlined.

Extracellular Vesicles for Childhood Cancer Liquid Biopsy

Liquid biopsy involves the utilization of minimally invasive or noninvasive techniques to detect biomarkers in biofluids for disease diagnosis, monitoring, or guiding treatments. This approach is promising for the early diagnosis of childhood cancer, especially for brain tumors, where tissue biopsies are more challenging and cause late detection. Extracellular vesicles offer several characteristics that make them ideal resources for childhood cancer liquid biopsy. Extracellular vesicles are nanosized particles, primarily secreted by all cell types into body fluids such as blood and urine, and contain molecular cargos, i.e., lipids, proteins, and nucleic acids of original cells. Notably, the lipid bilayer-enclosed structure of extracellular vesicles protects their cargos from enzymatic degradation in the extracellular milieu. Proteins and nucleic acids of extracellular vesicles represent genetic alterations and molecular profiles of childhood cancer, thus serving as promising resources for precision medicine in cancer diagnosis, treatment monitoring, and prognosis prediction. This review evaluates the recent progress of extracellular vesicles as a liquid biopsy platform for various types of childhood cancer, discusses the mechanistic roles of molecular cargos in carcinogenesis and metastasis, and provides perspectives on extracellular vesicle-guided therapeutic intervention. Extracellular vesicle-based liquid biopsy for childhood cancer may ultimately contribute to improving patient outcomes.

CRISPR/Cas detection with nanodevices: moving deeper into liquid biopsy

The emerging field of liquid biopsy has garnered significant interest in precision diagnostics, offering a non-invasive and repetitive method for analyzing bodily fluids to procure real-time diagnostic data. The precision and accuracy offered by the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (CRISPR/Cas) technology have advanced and broadened the applications of liquid biopsy. Significantly, when combined with swiftly advancing nanotechnology, CRISPR/Cas-mediated nanodevices show vast potential in precise liquid biopsy applications. However, persistent challenges are still associated with off-target effects, and the current platforms also constrain the performance of the assays. In this review, we highlight the merits of CRISPR/Cas systems in liquid biopsy, tracing the development of CRISPR/Cas systems and their current applications in disease diagnosis particularly in liquid biopsies. We also outline ongoing efforts to design nanoscale devices with improved sensing and readout capabilities, aiming to enhance the performance of CRISPR/Cas detectors in liquid biopsy. Finally, we identify the critical obstacles hindering the widespread adoption of CRISPR/Cas liquid biopsy and explore potential solutions. This feature article presents a comprehensive overview of CRISPR/Cas-mediated liquid biopsies, emphasizing the progress in integrating nanodevices to improve specificity and sensitivity. It also sheds light on future research directions in employing nanodevices for CRISPR/Cas-based liquid biopsies in the realm of precision medicine.

Blood-based liquid biopsy in advanced prostate cancer

Prostate cancer is characterized by several genetic alterations which could impact prognosis and therapeutic decisions in the advanced disease. Tissue biopsy is still considered the gold standard approach for molecular characterization in prostate cancer, but it has several limitations, including the possibility of insufficient/inadequate tumor tissue to be analyzed. Blood-based liquid biopsy is a non-invasive method to investigate tumor cell derivatives in the bloodstream, being a valid alternative to tissue biopsy for molecular characterization but also for predictive and/or prognostic purposes. In this review, we analyze the most relevant evidence in this field, focusing on clinically relevant targets such as HRD genetic alterations and also focusing on the differences between tissue and liquid biopsy in light of the data from the latest clinical trials.

Terminal modifications independent cell-free RNA sequencing enables sensitive early cancer detection and classification

Cell-free RNAs (cfRNAs) offer an opportunity to detect diseases from a transcriptomic perspective, however, existing techniques have fallen short in generating a comprehensive cell-free transcriptome profile. We develop a sensitive library preparation method that is robust down to 100 µl input plasma to analyze cfRNAs independent of their 5'-end modifications. We show that it outperforms adapter ligation-based method in detecting a greater number of cfRNA species. We perform transcriptome-wide characterizations in 165 lung cancer, 30 breast cancer, 37 colorectal cancer, 55 gastric cancer, 15 liver cancer, and 133 cancer-free participants and demonstrate its ability to identify transcriptomic changes occurring in early-stage tumors. We also leverage machine learning analyses on the differentially expressed cfRNA signatures and reveal their robust performance in cancer detection and classification. Our work sets the stage for in-depth study of the cfRNA repertoire and highlights the value of cfRNAs as cancer biomarkers in clinical applications.

A Simple, Rapid, and Effective Heparinase Protocol to Enable Nucleic Acid Study from Frozen Heparinized Plasma

Cell-free RNAs (cfRNAs) are promising analytes as non-invasive biomarkers and have even greater potential if tied in with metabolomics. Plasma is an optimal source for cfRNAs but is often derived from a variety of anticoagulants. Plasma obtained in heparin is suitable for metabolomics but is difficult to utilize for qPCR-based downstream analysis. In the present study, we aimed to develop a simple, time-efficient, and cost-effective heparinase protocol, followed by library preparation and sequencing of human plasma cfRNAs drawn and stored in heparin at -80 °C for several years. Blood was collected in CPT™ sodium heparin tubes from patients with chronic HCV infection (NCT02400216) at the National Institutes of Health (NIH) Clinical Center. Plasma cfRNAs were treated with heparinase I and used for library preparation and next-generation sequencing (NGS). Heparinase treatment maintained RNA integrity and allowed for successful library preparation for all the study subjects even with 7 ng of cfRNAs as starting material. The classification report derived from Pavian R package v1.2.0 showed no artificial reads. The abundance of chordate over microbial reads suggests no addition of experimental error through heparinase I treatment. We report a novel and practical approach to heparinase treatment for human plasma collected and frozen in sodium heparin for several years. This is an effective demonstration of utilizing heparin plasma for NGS and downstream transcriptomic research, which could then be integrated with metabolomics from the same samples, maximizing efficiency and minimizing blood draws.

Cell free ACE2 RNA: A potential biomarker of COVID-19 severity

Despite the downward trend of COVID-19 pandemic and increased immunity of the general population, COVID-19 is still an elusive disease with risks due to emerging variants. Fast and reliable diagnosis of COVID-19 disease would allow better therapeutic interventions for patients at risk to develop more severe outcomes. Cell-free RNAs (cfRNAs) have been proven to be an effective biomarker in cancer and infectious diseases. It has been reported that cfRNAs are amplified in the bloodstream of these patients and at earlier stages of the disease, reflecting tissue damage. Hence, we hypothesize that cfRNAs may serve as a potential indicator of COVID-19 disease severity. To our knowledge, this is the first report to display a significant link between COVID-19 severity and cfRNA of angiotensin converting enzyme-2 (ACE2), the receptor for SARS-CoV-2 virus. qRT-PCR analysis of liquid biopsies from COVID-19 patients (n = 82) displayed a significant increase in ACE2-cfRNA levels in patients with severe manifestations. This finding correlated with blood biomarkers (ANC, WBC, and Creatinine) that were also significantly increased in these patients. We previously showed that bronchial cells from obese subjects express higher ACE2 levels, hence, we further analysed the involvement of obesity as a main contributor to severe outcomes. We confirm a significant increase of ACE2-cfRNA in the plasma of obese/overweight (Ob/Ov) COVID-19 patients compared to lean subjects, with no observed significant change in blood biomarkers. These findings suggest that monitoring ACE2-cfRNAs, as a biomarker, during COVID-19 infection may allow for better disease management, specifically for severe-COVID-19 patients.

Liquid biopsy: creating opportunities in brain space

In recent years, liquid biopsy has emerged as an alternative method to diagnose and monitor tumors. Compared to classical tissue biopsy procedures, liquid biopsy facilitates the repetitive collection of diverse cellular and acellular analytes from various biofluids in a non/minimally invasive manner. This strategy is of greater significance for high-grade brain malignancies such as glioblastoma as the quantity and accessibility of tumors are limited, and there are collateral risks of compromised life quality coupled with surgical interventions. Currently, blood and cerebrospinal fluid (CSF) are the most common biofluids used to collect circulating cells and biomolecules of tumor origin. These liquid biopsy analytes have created opportunities for real-time investigations of distinct genetic, epigenetic, transcriptomics, proteomics, and metabolomics alterations associated with brain tumors. This review describes different classes of liquid biopsy biomarkers present in the biofluids of brain tumor patients. Moreover, an overview of the liquid biopsy applications, challenges, recent technological advances, and clinical trials in the brain have also been provided.

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.

Identification of novel first-trimester serum biomarkers for early prediction of preeclampsia

BACKGROUND

Preeclampsia (PE) is a leading cause of maternal and perinatal mortality and morbidity worldwide, but effective early prediction remains a challenge due to the lack of reliable biomarkers.

METHODS

Based on the extensive human biobank of our large-scale assisted reproductive cohort platform, the first-trimester serum levels of 48 cytokines, total immunoglobulins (Igs), anti-phosphatidylserine (aPS) antibodies, and several previously reported PE biomarkers [including placental growth factor (PlGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and activin A] were measured in 34 women diagnosed with PE and 34 matched normotensive controls.

RESULTS

The PE group has significantly higher first-trimester serum levels of interleukin (IL)-2Rα, IL-9, tumor necrosis factor-β (TNF-β), RANTES, hepatocyte growth factor (HGF), total IgM, and total IgG, and aPS IgG optical density (OD) value, as well as lower first-trimester serum levels of PlGF and total IgA and aPS-IgG immune complexes (IC) OD value than the control group. Combining top five first-trimester serum biomarkers (total IgM, total IgG, PlGF, aPS IgG, and total IgA) achieved superior predictive value [area under the curve (AUC) and 95% confidence interval (CI) 0.983 (0.952-1.000), with a sensitivity of 100% and a specificity of 94.1%] for PE development compared to PlGF and PlGF/sFlt-1 independently [AUC and 95% CI 0.825 (0.726-0.924) and 0.670 (0.539-0.800), respectively].

CONCLUSION

We identified novel first-trimester serum biomarkers and developed an effective first-trimester prediction model using immune-related factors and PlGF for PE, which could facilitate the development of early diagnostic strategies and provide immunological insight into the further mechanistic exploration of PE.

Liquid Biopsy in Lung Cancer: Biomarkers for the Management of Recurrence and Metastasis

Liquid biopsies have emerged as a promising tool for the detection of metastases as well as local and regional recurrence in lung cancer. Liquid biopsy tests involve analyzing a patient's blood, urine, or other body fluids for the detection of biomarkers, including circulating tumor cells or tumor-derived DNA/RNA that have been shed into the bloodstream. Studies have shown that liquid biopsies can detect lung cancer metastases with high accuracy and sensitivity, even before they are visible on imaging scans. Such tests are valuable for early intervention and personalized treatment, aiming to improve patient outcomes. Liquid biopsies are also minimally invasive compared to traditional tissue biopsies, which require the removal of a sample of the tumor for further analysis. This makes liquid biopsies a more convenient and less risky option for patients, particularly those who are not good candidates for invasive procedures due to other medical conditions. While liquid biopsies for lung cancer metastases and relapse are still being developed and validated, they hold great promise for improving the detection and treatment of this deadly disease. Herein, we summarize available and novel approaches to liquid biopsy tests for lung cancer metastases and recurrence detection and describe their applications in clinical practice.

Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer

Lung cancer detection and monitoring are hampered by a lack of sensitive biomarkers, which results in diagnosis at late stages and difficulty in tracking response to treatment. Recent developments have established liquid biopsies as promising non-invasive methods for detecting biomarkers in lung cancer patients. With concurrent advances in high-throughput sequencing technologies and bioinformatics tools, new approaches for biomarker discovery have emerged. In this article, we survey established and emerging biomarker discovery methods using nucleic acid materials derived from bodily fluids in the context of lung cancer. We introduce nucleic acid biomarkers extracted from liquid biopsies and outline biological sources and methods of isolation. We discuss next-generation sequencing (NGS) platforms commonly used to identify novel biomarkers and describe how these have been applied to liquid biopsy. We highlight emerging biomarker discovery methods, including applications of long-read sequencing, fragmentomics, whole-genome amplification methods for single-cell analysis, and whole-genome methylation assays. Finally, we discuss advanced bioinformatics tools, describing methods for processing NGS data, as well as recently developed software tailored for liquid biopsy biomarker detection, which holds promise for early diagnosis of lung cancer.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. “Classical” tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

Integrated analysis of circulating cell free nucleic acids for cancer genotyping and immune phenotyping of tumor microenvironment

The circulating cell-free nucleic acids (ccfNAs) consist of a heterogenous cocktail of both single (ssNA) and double-stranded (dsNA) nucleic acids. These ccfNAs are secreted into the blood circulation by both healthy and malignant cells via various mechanisms including apoptosis, necrosis, and active secretion. The major source of ccfNAs are the cells of hematopoietic system under healthy conditions. These ccfNAs include fragmented circulating cell free DNA (ccfDNA), coding or messenger RNA (mRNA), long non-coding RNA (lncRNA), microRNA (miRNA), and mitochondrial DNA/RNA (mtDNA and mtRNA), that serve as prospective biomarkers in assessment of various clinical conditions. For, e.g., free fetal DNA and RNA migrate into the maternal plasma, whereas circulating tumor DNA (ctDNA) has clinical relevance in diagnostic, prognostic, therapeutic targeting, and disease progression monitoring to improve precision medicine in cancer. The epigenetic modifications of ccfDNA as well as circulating cell-free RNA (ccfRNA) such as miRNA and lncRNA show disease-related variations and hold potential as epigenetic biomarkers. The messenger RNA present in the circulation or the circulating cell free mRNA (ccf-mRNA) and long non-coding RNA (ccf-lncRNA) have gradually become substantial in liquid biopsy by acting as effective biomarkers to assess various aspects of disease diagnosis and prognosis. Conversely, the simultaneous characterization of coding and non-coding RNAs in human biofluids still poses a significant hurdle. Moreover, a comprehensive assessment of ccfRNA that may reflect the tumor microenvironment is being explored. In this review, we focus on the novel approaches for exploring ccfDNA and ccfRNAs, specifically ccf-mRNA as biomarkers in clinical diagnosis and prognosis of cancer. Integrating the detection of circulating tumor DNA (ctDNA) for cancer genotyping in conjunction with ccfRNA both quantitatively and qualitatively, may potentially hold immense promise towards precision medicine. The current challenges and future directions in deciphering the complexity of cancer networks based on the dynamic state of ccfNAs will be discussed.

Systematic Investigation of the Diagnostic and Prognostic Impact of LINC01087 in Human Cancers

(1) Background: Long non-coding RNAs may constitute epigenetic biomarkers for the diagnosis, prognosis, and therapeutic response of a variety of tumors. In this context, we aimed at assessing the diagnostic and prognostic value of the recently described long intergenic non-coding RNA 01087 (LINC01087) in human cancers. (2) Methods: We studied the expression of LINC01087 across 30 oncological indications by interrogating public resources. Data extracted from the TCGA and GTEx databases were exploited to plot receiver operating characteristic curves (ROC) and determine the diagnostic performance of LINC01087. Survival data from TCGA and KM-Plotter directories allowed us to graph Kaplan-Meier curves and evaluate the prognostic value of LINC01087. To investigate the function of LINC01087, gene ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed. Furthermore, interactions between LINC01087 and both miRNA and mRNA were studied by means of bioinformatics tools. (3) Results: LINC01087 was significantly deregulated in 7 out of 30 cancers, showing a predominant upregulation. Notably, it was overexpressed in breast (BC), esophageal (ESCA), and ovarian (OV) cancers, as well as lung squamous cell carcinoma (LUSC), stomach adenocarcinoma (STAD), and uterine carcinosarcoma (UCS). By contrast, LINC01087 displayed downregulation in testicular germ cell tumors (TGCT). ROC curve analyses identified LINC01087 as a potential diagnostic indicator in BC, ESCA, OV, STAD, and TGCT. Moreover, high and low expression of LINC01087 predicted a favorable prognosis in BC and papillary cell carcinoma, respectively. In silico analyses indicated that deregulation of LINC01087 in cancer was associated with a modulation of genes related to ion channel, transporter, and peptide receptor activity. (4) Conclusions: the quantification of an altered abundance of LINC01087 in tissue specimens might be clinically useful for the diagnosis and prognosis of some hormone-related tumors, including BC, OV, and TGCT, as well as other cancer types such as ESCA and STAD. Moreover, our study revealed the potential of LINC01087 (and perhaps other lncRNAs) to regulate neuroactive molecules in cancer.