RNA Biomarkers: Frontier of Precision Medicine for Cancer

Contact lenses as novel tear fluid sampling vehicles for total RNA isolation, precipitation, and amplification

The tear fluid is a readily accessible, potential source for biomarkers of disease and could be used to monitor the ocular response to contact lens (CL) wear or ophthalmic pathologies treated by therapeutic CLs. However, the tear fluid remains largely unexplored as a biomarker source for RNA-based molecular analyses. Using a rabbit model, this study sought to determine whether RNA could be collected from commercial CLs and whether the duration of CL wear would impact RNA recovery. The results were referenced to standardized strips of filtered paper (e.g., Shirmer Strips) placed in the inferior fornix. By performing total RNA isolation, precipitation, and amplification with commercial kits and RT-PCR methods, CLs were found to have no significant differences in RNA concentration and purity compared to Schirmer Strips. The study also identified genes that could be used to normalize RNA levels between tear samples. Of the potential control genes or housekeeping genes, GAPDH was the most stable. This study, which to our knowledge has never been done before, provides a methodology for the detection of RNA and gene expression changes from tear fluid that could be used to monitor or study eye diseases.

Detection and quantification of TIMP1 and miR-141 through RT-LAMP and TT-LAMP in serum samples during estrous cycle in buffalo

Estrus identification is a common problem in the reproductive management of farm animals. Hence, several studies have been conducted to explore biomarkers for estrus detection. One of our previous studies identified the abundance of RNA biomarkers such as TIMP1 and miR-141 in buffalo saliva during the estrus stage. However, the level of these RNA biomarkers in buffalo serum during estrous cycle is undetected. Therefore, the present study was designed to quantify TIMP1 and miR-141 in serum during buffalo estrous cycle. Blood samples were collected in different stages of estrous cycle from four healthy cyclic buffaloes. The quantification of TIMP1 and miR-141 was performed with direct serum using RT-LAMP and TT-LAMP technologies, respectively. The LAMP amplification was confirmed by agarose gel electrophoresis and the color change was quantified in comparison to a non-template control using ImageJ software. A decreased abundance of TIMP1 at the diestrus stage and a decreasing trend of miR-141 from proestrus to diestrus stages were observed, which was further reinforced by simulated random populations generated with R programming. Specifically, TIMP1 was found significantly (P < 0.0001) abundant at estrus and metestrus stages as compared to the diestrus stage, whereas miR-141 was significantly (P < 0.001) higher during the proestrus stage as compared to the other stages of estrous cycle. The ROC curve analysis showed miR-141 to be a better biomarker than TIMP1 as it distinguished the proestrus stage from diestrus with a sensitivity and specificity of 83 % and 98 %. This study also marked the first use of TT-LAMP technology for rapid miRNA detection in livestock.

CanISO: a database of genomic and transcriptomic variations in domestic dog (Canis lupus familiaris)

BACKGROUND

The domestic dog, Canis lupus familiaris, is a companion animal for humans as well as an animal model in cancer research due to similar spontaneous occurrence of cancers as humans. Despite the social and biological importance of dogs, the catalogue of genomic variations and transcripts for dogs is relatively incomplete.

RESULTS

We developed CanISO, a new database to hold a large collection of transcriptome profiles and genomic variations for domestic dogs. CanISO provides 87,692 novel transcript isoforms and 60,992 known isoforms from whole transcriptome sequencing of canine tumors (N = 157) and their matched normal tissues (N = 64). CanISO also provides genomic variation information for 210,444 unique germline single nucleotide polymorphisms (SNPs) from the whole exome sequencing of 183 dogs, with a query system that searches gene- and transcript-level information as well as covered SNPs. Transcriptome profiles can be compared with corresponding human transcript isoforms at a tissue level, or between sample groups to identify tumor-specific gene expression and alternative splicing patterns.

CONCLUSIONS

CanISO is expected to increase understanding of the dog genome and transcriptome, as well as its functional associations with humans, such as shared/distinct mechanisms of cancer. CanISO is publicly available at https://www.kobic.re.kr/caniso/ .

Cell-free RNA for the liquid biopsy of gastrointestinal cancer

Gastrointestinal (GI) cancer includes many cancer types, such as esophageal, liver, gastric, pancreatic, and colorectal cancer. As the cornerstone of personalized medicine for GI cancer, liquid biopsy based on noninvasive biomarkers provides promising opportunities for early diagnosis and dynamic treatment management. Recently, a growing number of studies have demonstrated the potential of cell-free RNA (cfRNA) as a new type of noninvasive biomarker in body fluids, such as blood, saliva, and urine. Meanwhile, transcriptomes based on high-throughput RNA detection technologies keep discovering new cfRNA biomarkers. In this review, we introduce the origins and applications of cfRNA, describe its detection and qualification methods in liquid biopsy, and summarize a comprehensive list of cfRNA biomarkers in different GI cancer types. Moreover, we also discuss perspective studies of cfRNA to overcome its current limitations in clinical applications. This article is categorized under: RNA in Disease and Development > RNA in Disease.

Genome-Wide Analysis of Kidney Renal Cell Carcinoma: Exploring Differentially Expressed Genes for Diagnostic and Therapeutic Targets

Kidney renal cell carcinoma (KIRC) is the most common type of renal cancer. Kidney malignancies have been ranked in the top 10 most frequently occurring cancers. KIRC is a prevalent malignancy with a poor prognosis. The disease has risen for the last 40 years, and robust biomarkers for KIRC are needed for precision/personalized medicine. In this bioinformatics study, we utilized genomic data of KIRC patients from The Cancer Genome Atlas for biomarker discovery. A total of 314 samples were used in this study. We identified many differentially expressed genes (DEGs) categorized as upregulated or downregulated. A protein-protein interaction network for the DEGs was then generated and analyzed using the Search Tool for the Retrieval of Interacting Genes plugin of Cytoscape. A set of 10 hub genes was selected based on the Maximum Clique Centrality score defined by the CytoHubba plugin. The elucidated set of genes, that is, CALCA, CRH, TH, CHAT, SLC18A3, FSHB, MYH6, CAV3, KCNA4, and GBX2, were then categorized as potential candidates to be explored as KIRC biomarkers. The survival analysis plots for each gene suggested that alterations in CHAT, CAV3, CRH, MYH6, SLC18A3, and FSHB resulted in decreased survival of KIRC patients. In all, the results suggest that genomic alterations in selected genes can be explored to inform biomarker discovery and for therapeutic predictions in KIRC.

Exploring new prognostic biomarkers in Mantle Cell Lymphoma: a comparison of the circSCORE and the MCL35 score

Mantle cell lymphoma (MCL) is a biologically and clinically heterogeneous disease, emphasizing the need for prognostic biomarkers. In this study we aimed at comparing the prognostic value of two RNA-based risk scores, circSCORE and MCL35, in 149 patients from the MCL2 (ISRCTN87866680) and MCL3 (NCT00514475) patient cohorts. Both risk scores provided significant stratification of high versus low risk for progression free survival (PFS) and overall survival (OS). The circSCORE retained significant prognostic value in adjusted multivariable Cox regressions for PFS, but not for OS. Furthermore, circSCORE added significant prognostic value to MIPI in the pooled cohort (MCL2 and MCL3) for PFS and OS, and for PFS in MCL3 alone, outperforming Ki67 and MCL35. We suggest a new, combined MIPI-circSCORE with improved prognostic value, and with potential for future clinical implementation, if validated in a larger, independent cohort.

Towards Understanding the Key Signature Pathways Associated from Differentially Expressed Gene Analysis in an Indian Prostate Cancer Cohort

Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with genetics, genomics, and the environmental influence in the causality of PCa, not many studies employing the Next Generation Sequencing (NGS) approaches of PCa have been carried out. In our previous study, we identified some causal genes and mutations specific to Indian PCa using Whole Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify differentially expressed genes (DEGs) including long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using the RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened six patients who underwent prostatectomy; we performed whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz., GeneMANIA, Stringdb, Cytoscape-Cytohubba, and cbioportal, to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa, such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, and HN1L, and some other important genes known to be involved in different cancer pathways, such as COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1, etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, ENSG00000287903, and ENST00000647843.1 that need to be characterized further. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which perhaps have not been reported. This has set a precedent for us to validate candidates further experimentally, and we firmly believe this will pave a way toward the discovery of biomarkers and the development of novel therapies.

The Clinical Utility of lncRNAs and Their Application as Molecular Biomarkers in Breast Cancer

Given their tumor-specific and stage-specific gene expression, long non-coding RNAs (lncRNAs) have demonstrated to be potential molecular biomarkers for diagnosis, prognosis, and treatment response. Particularly, the lncRNAs DSCAM-AS1 and GATA3-AS1 serve as examples of this because of their high subtype-specific expression profile in luminal B-like breast cancer. This makes them candidates to use as molecular biomarkers in clinical practice. However, lncRNA studies in breast cancer are limited in sample size and are restricted to the determination of their biological function, which represents an obstacle for its inclusion as molecular biomarkers of clinical utility. Nevertheless, due to their expression specificity among diseases, such as cancer, and their stability in body fluids, lncRNAs are promising molecular biomarkers that could improve the reliability, sensitivity, and specificity of molecular techniques used in clinical diagnosis. The development of lncRNA-based diagnostics and lncRNA-based therapeutics will be useful in routine medical practice to improve patient clinical management and quality of life.

Application of sequence semantic and integrated cellular geography approach to study alternative biogenesis of exonic circular RNA

BACKGROUND

Concurrent existence of lncRNA and circular RNA at both nucleus and cytosol within a cell at different proportions is well reported. Previous studies showed that circular RNAs are synthesized in nucleus followed by transportation across the nuclear membrane and the export is primarily defined by their length. lncRNAs primarily originated through inefficient splicing and seem to use NXF1 for cytoplasm export. However, it is not clear whether circularization of lncRNA happens only in nucleus or it also occurs in cytoplasm. Studies indicate that circular RNAs arise when the splicing apparatus undergoes a phenomenon of back splicing. Minor spliceosome (U12 type) mediated splicing occurs in cytoplasm and is responsible for the splicing of 0.5% of introns of human cells. Therefore, possibility of cRNA biogenesis mediated by minor spliceosome at cytoplasm cannot be ruled out. Secondly, information on genes transcribing both circular and lncRNAs along with total number of RBP binding sites for both of these RNA types is extractable from databases. This study showed how these apparently unconnected pieces of reports could be put together to build a model for exploring biogenesis of circular RNA.

RESULTS

As a result of this study, a model was built under the premises that, sequences with special semantics were molecular precursors in biogenesis of circular RNA which occurred through catalytic role of some specific RBPs. The model outcome was further strengthened by fulfillment of three logical lemmas which were extracted and assimilated in this work using a novel data analytic approach, Integrated Cellular Geography. Result of the study was found to be in well agreement with proposed model. Furthermore this study also indicated that biogenesis of circular RNA was a post-transcriptional event.

CONCLUSIONS

Overall, this study provides a novel systems biology based model under the paradigm of Integrated Cellular Geography which can assimilate independently performed experimental results and data published by global researchers on RNA biology to provide important information on biogenesis of circular RNAs considering lncRNAs as precursor molecule. This study also suggests the possible RBP-mediated circularization of RNA in the cytoplasm through back-splicing using minor spliceosome.

Molecular Diagnosis and Cancer Prognosis-A Concise Review

Cancer is a complicated disease. Globally, it is one of the major causes for morbidity and mortality. A critical challenge associated with it is the difficulty to accurately diagnose it at an early stage. The malignancy due to multistage and heterogeneity that result from genetic and epigenetic modifications poses critical challenge to diagnose and monitor the progress at an early stage. Current diagnostic techniques normally suggest invasive biopsy procedure that can cause further infections and bleeding. Therefore, noninvasive diagnostic methods with high accuracy, safety and earliest detection are the needs of the hour. Herein, we provide a detailed review on the advanced methodologies and protocols developed for the detection of cancer biomarkers based on proteins, nucleic acids and extracellular vesicles. Furthermore, existing challenges and the improvements essential for the rapid, sensitive and noninvasive detection have also been discussed.

Through the Looking Glass: Updated Insights on Ovarian Cancer Diagnostics

Epithelial ovarian cancer (EOC) is the deadliest gynaecological malignancy and the eighth most prevalent cancer in women, with an abysmal mortality rate of two million worldwide. The existence of multiple overlapping symptoms with other gastrointestinal, genitourinary, and gynaecological maladies often leads to late-stage diagnosis and extensive extra-ovarian metastasis. Due to the absence of any clear early-stage symptoms, current tools only aid in the diagnosis of advanced-stage patients, wherein the 5-year survival plummets further to less than 30%. Therefore, there is a dire need for the identification of novel approaches that not only allow early diagnosis of the disease but also have a greater prognostic value. Toward this, biomarkers provide a gamut of powerful and dynamic tools to allow the identification of a spectrum of different malignancies. Both serum cancer antigen 125 (CA-125) and human epididymis 4 (HE4) are currently being used in clinics not only for EOC but also peritoneal and GI tract cancers. Screening of multiple biomarkers is gradually emerging as a beneficial strategy for early-stage diagnosis, proving instrumental in administration of first-line chemotherapy. These novel biomarkers seem to exhibit an enhanced potential as a diagnostic tool. This review summarizes existing knowledge of the ever-growing field of biomarker identification along with potential future ones, especially for ovarian cancer.

Tear Film MicroRNAs as Potential Biomarkers: A Review

MicroRNAs are non-coding RNAs that serve as regulatory molecules in a variety of pathways such as inflammation, metabolism, homeostasis, cell machinery, and development. With the progression of sequencing methods and modern bioinformatics tools, novel roles of microRNAs in regulatory mechanisms and pathophysiological states continue to expand. Advances in detection methods have further enabled larger adoption of studies utilizing minimal sample volumes, allowing the analysis of microRNAs in low-volume biofluids, such as the aqueous humor and tear fluid. The reported abundance of extracellular microRNAs in these biofluids has prompted studies to explore their biomarker potential. This review compiles the current literature reporting microRNAs in human tear fluid and their association with ocular diseases including dry eye disease, Sjögren's syndrome, keratitis, vernal keratoconjunctivitis, glaucoma, diabetic macular edema, and diabetic retinopathy, as well as non-ocular diseases, including Alzheimer's and breast cancer. We also summarize the known roles of these microRNAs and shed light on the future progression of this field.

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.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Size-Controllable and Self-Assembled DNA Nanosphere for Amplified MicroRNA Imaging through ATP-Fueled Cyclic Dissociation

Visualizing intracellular microRNA (miRNA) is of great importance for revealing its roles in the development of disease. However, cell membrane barrier, complex intracellular environment and low abundance of target miRNA are three main challenges for efficient imaging of intracellular miRNA. Here, we report a size-controllable and self-assembled DNA nanosphere with ATP-fueled dissociation property for amplified miRNA imaging in live cells and mice. The DNA nanosphere was self-assembled from Y-shaped DNA (Y-DNA) monomers through predesigned base pair hybridization, and the size could be easily controlled by varying the concentration of Y-DNA. Once the nanosphere was internalized into cells, the intracellular specific target miRNA would trigger the cyclic dissociation of the DNA nanosphere driven by ATP, resulting in amplified FRET signal. The programmable DNA nanosphere has been proven to work well for detecting the expression of miRNA in cancer cells and in mice, which demonstrates its fairish cell penetration, stability and sensitivity.

Sensitive Imaging of Cellular RNA via Cascaded Proximity-Induced Fluorogenic Reactions

Owing to its important biological functions, RNA has become a promising molecular biomarker of various diseases. With a dynamic change in its expression level and a relatively low amount within the complicated biological matrix, signal amplification detection based on DNA probes has been put forward, which is helpful for early diagnosis and prognostic prediction. However, conventional methods are confined to cell lysates or dead cells and are not only time-consuming in sample preparation but also inaccessible to the spatial-temporal information of target RNAs. To achieve live-cell imaging of specific RNAs, both the detection sensitivity and intracellular delivery issues should be addressed. Herein, a new cascaded fluorogenic system based on the combination of hybridization chain reactions (HCRs) and proximity-induced bioorthogonal chemistry is developed, in which a bioorthogonal reaction pair (a tetrazine-quenched dye and its complementary dienophile) is brought into spatial proximity upon target RNA triggering the HCR to turn on and amplify the fluorescence in one step, sensitively indicating the cellular distribution of RNA with minimal false positive results caused by unspecific degradation. Facilitated by a biodegradable carrier based on black phosphorus with high loading capacity and excellent biocompatibility, the resulting imaging platform allows wash-free tracking of target RNAs inside living cells.

The Future of Biomarkers in Veterinary Medicine: Emerging Approaches and Associated Challenges

Simple Summary

In this review we seek to outline the role of new technologies in biomarker discovery, particularly within the veterinary field and with an emphasis on ‘omics’, as well as to examine why many biomarkers-despite much excitement-have not yet made it to clinical practice. Further we emphasise the critical need for close collaboration between clinicians, researchers and funding bodies and the need to set clear goals for biomarker requirements and realistic application in the clinical setting, ensuring that biomarker type, method of detection and clinical utility are compatible, and adequate funding, time and sample size are available for all phases of development.

Abstract

New biomarkers promise to transform veterinary practice through rapid diagnosis of diseases, effective monitoring of animal health and improved welfare and production efficiency. However, the road from biomarker discovery to translation is not always straightforward. This review focuses on molecular biomarkers under development in the veterinary field, introduces the emerging technological approaches transforming this space and the role of ‘omics platforms in novel biomarker discovery. The vast majority of veterinary biomarkers are at preliminary stages of development and not yet ready to be deployed into clinical translation. Hence, we examine the major challenges encountered in the process of biomarker development from discovery, through validation and translation to clinical practice, including the hurdles specific to veterinary practice and to each of the ‘omics platforms–transcriptomics, proteomics, lipidomics and metabolomics. Finally, recommendations are made for the planning and execution of biomarker studies with a view to assisting the success of novel biomarkers in reaching their full potential.

Quantifying telomeric lncRNAs using PNA-labelled RNA-Flow FISH (RNA-Flow)

Here we present a method to detect and quantify long non-coding RNAs, in particular those related to telomeres. By coupling the specificity of a peptide nucleic acid (PNA) probe with flow cytometry we have quantified cellular levels of TERRA and TERC lncRNAs in culture cell lines and PBMCs. This easy-to-use method appointed RNA-Flow allows reliable lncRNA quantification with broad applications in basic research and clinical diagnostics. In addition, the staining protocol presented here was proven useful for the detection and quantification of such lncRNAs on unfixed cells using confocal microscopy.

Telomeric-associated long non-coding RNAs TERRA and TERC can be quantified in culture cell lines and human PBMCs using peptide nucleic acid probes with flow cytometry (RNA-Flow).

Novel Diagnostic Value of Driver Gene Transcription Signatures to Characterise Clear Cell Renal Cell Carcinoma, ccRCC

Routine molecular tumour diagnostics are augmented by DNA-based qualitative and quantitative molecular techniques detecting mutations of DNA. However, in the past decade, it has been unravelled that the phenotype of cancer, as it’s an extremely complex disease, cannot be fully described and explained by single or multiple genetic variants affecting only the coding regions of the genes. Moreover, studying the manifestation of these somatic mutations and the altered transcription programming—driven by genomic rearrangements, dysregulation of DNA methylation and epigenetic landscape—standing behind the tumorigenesis and detecting these changes could provide a more detailed characterisation of the tumour phenotype. Consequently, novel comparative cancer diagnostic pipelines, including DNA- and RNA-based approaches, are needed for a global assessment of cancer patients. Here we report, that by monitoring the expression patterns of key tumour driver genes by qPCR, the normal and the tumorous samples can be separated into distinct categories. Furthermore, we also prove that by examining the transcription signatures of frequently affected genes at 3p25, 3p21 and 9p21.3 genomic regions, the ccRCC (clear cell renal cell carcinoma) and non-tumorous kidney tissues can be distinguished based on the mRNA level of the selected genes. Our results open new diagnostics possibilities where the mRNA signatures of tumour drivers can supplement the DNA-based approaches providing a more precise diagnostics opportunity leading to determine more precise therapeutic protocols.

RNAscope for VEGF-A Detection in Human Tumor Bioptic Specimens

Different pro-angiogenic factors, such as vascular endothelial growth factor-A (VEGF-A), have been related to microvascular density, clinicopathologic factors, and poor prognosis in many tumors. VEGF-A binds its receptor 2 (VEGFR2) to induce neo-angiogenesis, a constant hallmark of tumor initiation and progression. Based on VEGF-A/VEGFR2 relevance in tumor angiogenesis, several inhibitors were developed. However, the clinical benefits of anti-angiogenic therapies are limited because tumors activate different mechanisms of drug resistance.The need for understanding tumor biology, limitation or failure of anti-angiogenic therapies, and the demand for a personalized therapeutic approach has boosted the search for robust biomarkers for patient stratification as responder or non-responder to anti-VEGF therapies.This chapter presents a detailed protocol to perform chromogenic VEGF-A mRNA detection and quantification in human tumor bioptic specimens using RNAscope technology and RNA-in situ hybridization (ISH) algorithm. RNAscope for VEGF-A detection, even for small amounts, is compatible with precious clinical samples and diagnostic laboratory workflows.

Obtaining Reliable RT-qPCR Results in Molecular Diagnostics—MIQE Goals and Pitfalls for Transcriptional Biomarker Discovery

In this review, we discuss the development pipeline for transcriptional biomarkers in molecular diagnostics and stress the importance of a reliable gene transcript quantification strategy. Hence, a further focus is put on the MIQE guidelines and how to adapt them for biomarker discovery, from signature validation up to routine diagnostic applications. First, the advantages and pitfalls of the holistic RNA sequencing for biomarker development will be described to establish a candidate biomarker signature. Sequentially, the RT-qPCR confirmation process will be discussed to validate the discovered biomarker signature. Examples for the successful application of RT-qPCR as a fast and reproducible quantification method in routinemolecular diagnostics are provided. Based on the MIQE guidelines, the importance of “key steps” in RT-qPCR is accurately described, e.g., reverse transcription, proper reference gene selection and, finally, the application of automated RT-qPCR data analysis software. In conclusion, RT-qPCR proves to be a valuable tool in the establishment of a disease-specific transcriptional biomarker signature and will have a great future in molecular diagnostics or personalized medicine.

MiR-378a inhibits glucose metabolism by suppressing GLUT1 in prostate cancer

Prostate cancer (PCa) is the fifth leading cause of cancer related deaths worldwide, in part due to a lack of molecular stratification tools that can distinguish primary tumours that will remain indolent from those that will metastasise. Amongst potential molecular biomarkers, microRNAs (miRs) have attracted particular interest because of their high stability in body fluids and fixed tissues. These small non-coding RNAs modulate several physiological and pathological processes, including cancer progression. Herein we explore the prognostic potential and the functional role of miRs in localised PCa and their relation to nodal metastasis. We define a 7-miR signature that is associated with poor survival independently of age, Gleason score, pathological T state, N stage and surgical margin status and that is also prognostic for disease-free survival in patients with intermediate-risk localised disease. Within our 7-miR signature, we show that miR-378a-3p (hereafter miR-378a) levels are low in primary tumours compared to benign prostate tissue, and also lower in Gleason score 8-9 compared to Gleason 6-7 PCa. We demonstrate that miR-378a impairs glucose metabolism and reduces proliferation in PCa cells through independent mechanisms, and we identify glucose transporter 1 (GLUT1) messenger RNA as a direct target of miR-378a. We show that GLUT1 inhibition hampers glycolysis, leading to cell death. Our data provides a rational for a new PCa stratification strategy based on miR expression, and it reveals that miR-378a and GLUT1 are potential therapeutic targets in highly aggressive glycolytic PCa.

Human disease biomarker panels through systems biology

As more uses for biomarkers are sought after for an increasing number of disease targets, single-target biomarkers are slowly giving way for biomarker panels. These panels incorporate various sources of biomolecular and clinical data to guarantee a higher robustness and power of separation for a clinical test. Multifactorial diseases such as psychiatric disorders show great potential for clinical use, assisting medical professionals during the analysis of risk and predisposition, disease diagnosis and prognosis, and treatment applicability and efficacy. More specific tests are also being developed to assist in ruling out, distinguishing between, and confirming suspicions of multifactorial diseases, as well as to predict which therapy option may be the best option for a given patient's biochemical profile. As more complex datasets are entering the field, involving multi-omic approaches, systems biology has stepped in to facilitate the discovery and validation steps during biomarker panel generation. Filtering biomolecules and clinical data, pre-validating and cross-validating potential biomarkers, generating final biomarker panels, and testing the robustness and applicability of those panels are all beginning to rely on machine learning and systems biology and research in this area will only benefit from advances in these approaches.

DNA Logic Circuits for Multiple Tumor Cells Identification Using Intracellular MicroRNA Molecular Bispecific Recognition

The aberrant expression level of intracellular microRNAs (miRNAs) holds great promise for differentiating cell types at the molecular level. However, cell subtype discrimination based on a single miRNA molecular level is not sufficient and reliable. Herein, multiple identifiable and reporting modules are integrated into a single DNA circuit for multiple cancer cell subtypes identification based on miRNAs bispecific recognition. The DNA three-dimensional (3D) logic gate nano-hexahedron framework extends three recognition modules and three reporting modules to form three "AND" logic gates. Each Boolean operator "AND" returns an "ON" signal in the presence of bispecific miRNAs, simultaneously enabling three types of cell subtype identification. It not only enables the discrimination of cancer cells A549 and MCF-7 from normal cells NHDF but also successfully distinguishes different types of cancer cells. The bispecific intracellular miRNA controllable DNA circuit, with low signal-to-noise ratio, easily extends to various cell type discrimination by adjusting the miRNA species, provides huge opportunities for accurately differentiating multiple cell types at the molecular level.

Functional and Clinical Significance of Dysregulated microRNAs in Liver Cancer

Simple Summary

Liver cancer has a high mortality rate. Here, we retrospectively discuss the current progress and dilemmas in the clinical research and treatment of liver cancer. We primarily focus on microRNAs because of their extremely high value in applications and research. We discuss whether microRNAs can be used for the development of better biomarkers and/or therapeutic drugs, and address the difficulties, requirements for improved diagnostic technologies, and side effects related to microRNA-based drugs.

Abstract

Liver cancer is the leading cause of cancer-related mortality in the world. This mainly reflects the lack of early diagnosis tools and effective treatment methods. MicroRNAs (miRNAs) are a class of non-transcribed RNAs, some of which play important regulatory roles in liver cancer. Here, we discuss microRNAs with key impacts on liver cancer, such as miR-122, miR-21, miR-214, and miR-199. These microRNAs participate in various physiological regulatory pathways of liver cancer cells, and their modulation can have non-negligible effects in the treatment of liver cancer. We discuss whether these microRNAs can be used for better clinical diagnosis and/or drug development. With the advent of novel technologies, fast, inexpensive, and non-invasive RNA-based biomarker research has become a new mainstream approach. However, the clinical application of microRNA-based markers has been limited by the high sequence similarity among them and the potential for off-target problems. Therefore, researchers particularly value microRNAs that are specific to or have special functions in liver cancer. These include miR-122, which is specifically expressed in the liver, and miR-34, which is necessary for the replication of the hepatitis C virus in liver cancer. Clinical treatment drugs have been developed based on miR-34 and miR-122 (MRX34 and Miravirsen, respectively), but their side effects have not yet been overcome. Future research is needed to address these weaknesses and establish a feasible microRNA-based treatment strategy for liver cancer.

Potential Biomarkers of miR-371-373 Gene Cluster in Tumorigenesis

microRNAs (miRNAs) are small non-coding RNA transcripts (20–24 nucleotides) that bind to their complementary sequences in the 3′-untranslated regions (3′-UTR) of targeted genes to negatively or positively regulate their expression. miRNAs affect the expression of genes in cells, thereby contributing to several important biological processes, including tumorigenesis. Identifying the miRNA cluster as a human embryonic stem cell (hESC)-specific miRNAs initially led to the identification of miR-371, miR-372, miR-373, and miR-373*, which can ultimately be translated into mature miRNAs. Recent evidence suggests that miR-371–373 genes are abnormally expressed in various cancers and act either as oncogenes or tumor suppressors, indicating they may be suitable as molecular biomarkers for cancer diagnosis and prevention. In this article, we summarize recent studies linking miR-371–373 functions to tumorigenesis and speculate on the potential applications of miR-371–373 as biomarkers for cancer diagnosis and treatment.

mRBioM: An Algorithm for the Identification of Potential mRNA Biomarkers From Complete Transcriptomic Profiles of Gastric Adenocarcinoma

Purpose

In this work, an algorithm named mRBioM was developed for the identification of potential mRNA biomarkers (PmBs) from complete transcriptomic RNA profiles of gastric adenocarcinoma (GA).

Methods

mRBioM initially extracts differentially expressed (DE) RNAs (mRNAs, miRNAs, and lncRNAs). Next, mRBioM calculates the total information amount of each DE mRNA based on the coexpression network, including three types of RNAs and the protein-protein interaction network encoded by DE mRNAs. Finally, PmBs were identified according to the variation trend of total information amount of all DE mRNAs. Four PmB-based classifiers without learning and with learning were designed to discriminate the sample types to confirm the reliability of PmBs identified by mRBioM. PmB-based survival analysis was performed. Finally, three other cancer datasets were used to confirm the generalization ability of mRBioM.

Results

mRBioM identified 55 PmBs (41 upregulated and 14 downregulated) related to GA. The list included thirteen PmBs that have been verified as biomarkers or potential therapeutic targets of gastric cancer, and some PmBs were newly identified. Most PmBs were primarily enriched in the pathways closely related to the occurrence and development of gastric cancer. Cancer-related factors without learning achieved sensitivity, specificity, and accuracy of 0.90, 1, and 0.90, respectively, in the classification of the GA and control samples. Average accuracy, sensitivity, and specificity of the three classifiers with machine learning ranged within 0.94–0.98, 0.94–0.97, and 0.97–1, respectively. The prognostic risk score model constructed by 4 PmBs was able to correctly and significantly (^∗∗∗p < 0.001) classify 269 GA patients into the high-risk (n = 134) and low-risk (n = 135) groups. GA equivalent classification performance was achieved using the complete transcriptomic RNA profiles of colon adenocarcinoma, lung adenocarcinoma, and hepatocellular carcinoma using PmBs identified by mRBioM.

Conclusions

GA-related PmBs have high specificity and sensitivity and strong prognostic risk prediction. MRBioM has also good generalization. These PmBs may have good application prospects for early diagnosis of GA and may help to elucidate the mechanism governing the occurrence and development of GA. Additionally, mRBioM is expected to be applied for the identification of other cancer-related biomarkers.

Kmerator Suite: design of specific k-mer signatures and automatic metadata discovery in large RNA-seq datasets

The huge body of publicly available RNA-sequencing (RNA-seq) libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large dataset characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor gene-specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualized through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non-coding RNAs for human health applications.

Photoelectrochemical Sensing of α-Synuclein Based on a AuNPs/Graphdiyne-Modified Electrode Coupled with a Nanoprobe

We developed a method for photoelectrochemical (PEC) sensing based on a AuNPs/graphdiyne, as a low background signal composite material, modified electrode coupled with a nanoprobe (probe DNA/DA/MBA/WSe₂) for sensitive α-synuclein (α-Syn) detection. A tungsten selenide (WSe₂) nanoflower was first produced with a one-pot solvothermal method and employed as a signal amplification element and the modified substrate of the nanoprobe. The synergy effect between the WSe₂ nanoflower and graphdiyne (GDY) can reduce the photoinduced electron-hole recombination and expedite the spatial charge separation. Due to the synergistic effect of AuNPs/GDY and WSe₂, this detection strategy provides a high signal-to-noise ratio and good performance. The signal indicator, dopamine/4-mercaptophenyl boronic acid/WSe₂ (DA/MBA/WSe₂), was generated with the recognition of boron-diol. In the presence of the α-Syn oligomer, the target triggered cycle I strand displacement amplification and achieved the conversion of the α-Syn oligomer to a massive output of false-target DNA (FT). The output FT was used for the cycle II catalytic hairpin assembly onto the electrode which was modified with AuNPs/GDY and triple-stranded DNA (TsDNA); thereby, plenty of PEC nanoprobes which are composed of probe DNA and the signal indicator are captured, and the photocurrent response is produced correspondingly. This PEC biosensor generated a strong photocurrent with low blank (27.6 nA) and was sensitive to α-Syn oligomer. The limit of detection was 3.3 aM, and the relative standard deviation (RSD) was 3.7% at 100 aM. Moreover, it also has good selectivity, indicating promising potential in clinical diagnostics.

Overexpression of DDIT4 and TPTEP1 are associated with metastasis and advanced stages in colorectal cancer patients: a study utilizing bioinformatics prediction and experimental validation

BACKGROUND

Various diagnostic and prognostic tools exist in colorectal cancer (CRC) due to multiple genetic and epigenetic alterations causing the disease. Today, the expression of RNAs is being used as prognostic markers for cancer.

METHODS

In the current study, various dysregulated RNAs in CRC were identified via bioinformatics prediction. Expression of several of these RNAs were measured by RT-qPCR in 48 tissues from CRC patients as well as in colorectal cancer stem cell-enriched spheroids derived from the HT-29 cell line. The relationships between the expression levels of these RNAs and clinicopathological features were analyzed.

RESULTS

Our bioinformatics analysis determined 11 key mRNAs, 9 hub miRNAs, and 18 lncRNAs which among them 2 coding RNA genes including DDIT4 and SULF1 as well as 3 non-coding RNA genes including TPTEP1, miR-181d-5p, and miR-148b-3p were selected for the further investigations. Expression of DDIT4, TPTEP1, and miR-181d-5p showed significantly increased levels while SULF1 and miR-148b-3p showed decreased levels in CRC tissues compared to the adjacent normal tissues. Positive relationships between DDIT4, SULF1, and TPTEP1 expression and metastasis and advanced stages of CRC were observed. Additionally, our results showed significant correlations between expression of TPTEP1 with DDIT4 and SULF1.

CONCLUSIONS

Our findings demonstrated increased expression levels of DDIT4 and TPTEP1 in CRC were associated with more aggressive tumor behavior and more advanced stages of the disease. The positive correlations between TPTEP1 as non-coding RNA and both DDIT4 and SULF1 suggest a regulatory effect of TPTEP1 on these genes.

Current updates on precision therapy for breast cancer associated brain metastasis: Emphasis on combination therapy

Cancer therapies have undergone a tremendous progress over the past decade. Precision medicine provides a more tailored approach, making the combination of existing therapies more precise. Different types of cancers are characterized by unique biomarkers that are targeted using various genomic approaches by clinicians and companies worldwide to achieve efficient treatment with minimal side effects. Precision medicine has two broad approaches namely stratified and personalized medicine. The driver mutations could vary within a subtype while the same driver mutations could be found across different subtypes. Precision medicine has recently gained a lot of importance for breast cancer therapy. Various kinds of mutations like hotspot mutations, gene alterations, gene amplification mutations are targeted to design a more specific therapy. Apart from these known gene mutations there are various unknown mutations. Thus, tumor heterogeneity can pose a challenge to precision medicine. For breast cancer, one of the most successful models developed in case of precision medicine is the anti-HER2 therapies as HER2 was considered to have the worst prognosis being highly malignant. But now due to the advent of HER2 receptor targeted therapies, it has a good prognosis. Moreover, precision medicine helps in identifying if the drug molecules being used for the treatment of one kind of cancer can be beneficial in the treatment of another kind of cancer as well, considering the signaling pathways and machinery is similar in most of the cancers. This reduces the time for new drug development and is economically more feasible. Precision medicine will prove to be very advantageous in case of brain metastasis.

Reverse transcription lesion-induced DNA amplification: An instrument-free isothermal method to detect RNA

One challenge in point-of-care (POC) diagnostics is the lack of room-temperature methods for RNA detection based on enzymatic amplification and visualization steps. Here we perform reverse transcription lesion-induced DNA amplification (RT-LIDA), an isothermal amplification method that only requires T4 DNA ligase. RT-LIDA involves the RNA-templated ligation of DNA primers to form complementary DNA (cDNA) followed by toehold-mediated strand displacement of the cDNA and its exponential amplification via our isothermal ligase chain reaction LIDA. Each step is tuned to proceed at 28 °C, which falls within the range of global room temperatures. Using RT-LIDA, we can detect as little as ∼100 amol target RNA and can distinguish RNA target from total cellular RNA. Finally, we demonstrate that the resulting DNA amplicons can be detected colorimetrically, also at room temperature, by rapid, target-triggered disassembly of DNA-modified gold nanoparticles. This integrated amplification/detection platform requires no heating or visualization instrumentation, which is an important step towards realizing instrument-free POC testing.

Precision Oncology, Signaling and Anticancer Agents in Cancer Therapeutics

BACKGROUND

The global alliance for genomics and healthcare facilities provides innovational solutions to expedite research and clinical practices for complex and incurable health conditions. Precision oncology is an emerging field explicitly tailored to facilitate cancer diagnosis, prevention and treatment based on patients' genetic profile. Advancements in "omics" techniques, next-generation sequencing, artificial intelligence and clinical trial designs provide a platform for assessing the efficacy and safety of combination therapies and diagnostic procedures.

METHOD

Data were collected from Pubmed and Google scholar using keywords: "Precision medicine", "precision medicine and cancer", "anticancer agents in precision medicine" and reviewed comprehensively.

RESULTS

Personalized therapeutics including immunotherapy, cancer vaccines, serve as a groundbreaking solution for cancer treatment. Herein, we take a measurable view of precision therapies and novel diagnostic approaches targeting cancer treatment. The contemporary applications of precision medicine have also been described along with various hurdles identified in the successful establishment of precision therapeutics.

CONCLUSION

This review highlights the key breakthroughs related to immunotherapies, targeted anticancer agents, and target interventions related to cancer signaling mechanisms. The success story of this field in context to drug resistance, safety, patient survival and in improving quality of life is yet to be elucidated. We conclude that, in the near future, the field of individualized treatments may truly revolutionize the nature of cancer patient care.

Clinical Trial in a Dish: Using Patient-Derived Induced Pluripotent Stem Cells to Identify Risks of Drug-Induced Cardiotoxicity

Drug-induced cardiotoxicity is a significant clinical issue, with many drugs in the market being labeled with warnings on cardiovascular adverse effects. Treatments are often prematurely halted when cardiotoxicity is observed, which limits their therapeutic potential. Moreover, cardiotoxicity is a major reason for abandonment during drug development, reducing available treatment options for diseases and creating a significant financial burden and disincentive for drug developers. Thus, it is important to minimize the cardiotoxic effects of medications that are in use or in development. To this end, identifying patients at a higher risk of developing cardiovascular adverse effects for the drug of interest may be an effective strategy. The discovery of human induced pluripotent stem cells has enabled researchers to generate relevant cell types that retain a patient's own genome and examine patient-specific disease mechanisms, paving the way for precision medicine. Combined with the rapid development of pharmacogenomic analysis, the ability of induced pluripotent stem cell-derivatives to recapitulate patient-specific drug responses provides a powerful platform to identify subsets of patients who are particularly vulnerable to drug-induced cardiotoxicity. In this review, we will discuss the current use of patient-specific induced pluripotent stem cells in identifying populations who are at risk to drug-induced cardiotoxicity and their potential applications in future precision medicine practice. Graphic Abstract: A graphic abstract is available for this article.

Polymerization and isomerization cyclic amplification for nucleic acid detection with attomolar sensitivity

DNA amplification is one of the most valuable tools for the clinical diagnosis of nucleic acid-related diseases, but current techniques for DNA amplification are based on intermolecular polymerization reactions, resulting in the risk of errors in the intermolecular reaction pattern. In this article, we introduce the concept of intramolecular polymerization and isomerization cyclic amplification (PICA), which extends a short DNA strand to a long strand containing periodic repeats of a sequence through cyclic alternating polymerization and isomerization. To the best of our knowledge, this is the first time that a real ssDNA self-extension method without any additional auxiliary oligonucleotides has been reported. By interfacing PICA with external molecular elements, it can be programmed to respond to different targets. Herein, we designed two distinct types of amplified nucleic acid detection platforms that can be implemented with PICA, including cyclic reverse transcription (CRT) and cyclic replication (CR). We experimentally demonstrate the mechanisms of CRT-PICA and CR-PICA using mammalian miRNA and virus DNA. The results showed that this proposed detection platform has excellent sensitivity, selectivity, and reliability. The detection level could reach the aM level, that is, several copies of target molecules can be detected if a small volume is taken into account.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

Oncological Ligand-Target Binding Systems and Developmental Approaches for Cancer Theranostics

Targeted treatment of cancer hinges on the identification of specific intracellular molecular receptors on cancer cells to stimulate apoptosis for eventually inhibiting growth; the development of novel ligands to target biomarkers expressed by the cancer cells; and the creation of novel multifunctional carrier systems for targeted delivery of anticancer drugs to specific malignant sites. There are numerous receptors, antigens, and biomarkers that have been discovered as oncological targets (oncotargets) for cancer diagnosis and treatment applications. Oncotargets are critically important to navigate active anticancer drug ingredients to specific disease sites with no/minimal effect on surrounding normal cells. In silico techniques relating to genomics, proteomics, and bioinformatics have catalyzed the discovery of oncotargets for various cancer types. Effective oncotargeting requires high-affinity probes engineered for specific binding of receptors associated with the malignancy. Computational methods such as structural modeling and molecular dynamic (MD) simulations offer opportunities to structurally design novel ligands and optimize binding affinity for specific oncotargets. This article proposes a streamlined approach for the development of ligand-oncotarget bioaffinity systems via integrated structural modeling and MD simulations, making use of proteomics, genomic, and X-ray crystallographic resources, to support targeted diagnosis and treatment of cancers and tumors.

Photonic technologies for liquid biopsies: recent advances and open research challenges

The recent development of sophisticated techniques capable of detecting extremely low concentrations of circulating tumor biomarkers in accessible body fluids, such as blood or urine, could contribute to a paradigm shift in cancer diagnosis and treatment. By applying such techniques, clinicians can carry out liquid biopsies, providing information on tumor presence, evolution, and response to therapy. The implementation of biosensing platforms for liquid biopsies is particularly complex because this application domain demands high selectivity/specificity and challenging limit-of-detection (LoD) values. The interest in photonics as an enabling technology for liquid biopsies is growing owing to the well-known advantages of photonic biosensors over competing technologies in terms of compactness, immunity to external disturbance, and ultra-high spatial resolution. Some encouraging experimental results in the field of photonic devices and systems for liquid biopsy have already been achieved by using fluorescent labels and label-free techniques and by exploiting super-resolution microscopy, surface plasmon resonance, surface-enhanced Raman scattering, and whispering gallery mode resonators. This paper critically reviews the current state-of-the-art, starting from the requirements imposed by the detection of the most common circulating biomarkers. Open research challenges are considered together with competing technologies, and the most promising paths of improvement are discussed for future applications.

Integrative analysis of long extracellular RNAs reveals a detection panel of noncoding RNAs for liver cancer

Rationale: Long extracellular RNAs (exRNAs) in plasma can be profiled by new sequencing technologies, even with low abundance. However, cancer-related exRNAs and their variations remain understudied. Methods: We investigated different variations (i.e. differential expression, alternative splicing, alternative polyadenylation, and differential editing) in diverse long exRNA species (e.g. long noncoding RNAs and circular RNAs) using 79 plasma exosomal RNA-seq (exoRNA-seq) datasets of multiple cancer types. We then integrated 53 exoRNA-seq datasets and 65 self-profiled cell-free RNA-seq (cfRNA-seq) datasets to identify recurrent variations in liver cancer patients. We further combined TCGA tissue RNA-seq datasets and validated biomarker candidates by RT-qPCR in an individual cohort of more than 100 plasma samples. Finally, we used machine learning models to identify a signature of 3 noncoding RNAs for the detection of liver cancer. Results: We found that different types of RNA variations identified from exoRNA-seq data were enriched in pathways related to tumorigenesis and metastasis, immune, and metabolism, suggesting that cancer signals can be detected from long exRNAs. Subsequently, we identified more than 100 recurrent variations in plasma from liver cancer patients by integrating exoRNA-seq and cfRNA-seq datasets. From these datasets, 5 significantly up-regulated long exRNAs were confirmed by TCGA data and validated by RT-qPCR in an independent cohort. When using machine learning models to combine two of these validated circular and structured RNAs (SNORD3B-1, circ-0080695) with a miRNA (miR-122) as a panel to classify liver cancer patients from healthy donors, the average AUROC of the cross-validation was 89.4%. The selected 3-RNA panel successfully detected 79.2% AFP-negative samples and 77.1% early-stage liver cancer samples in the testing and validation sets. Conclusions: Our study revealed that different types of RNA variations related to cancer can be detected in plasma and identified a 3-RNA detection panel for liver cancer, especially for AFP-negative and early-stage patients.

Towards establishing extracellular vesicle-associated RNAs as biomarkers for HER2+ breast cancer

Extracellular vesicles (EVs) are emerging as key players in breast cancer progression and hold immense promise as cancer biomarkers. However, difficulties in obtaining sufficient quantities of EVs for the identification of potential biomarkers hampers progress in this area. To circumvent this obstacle, we cultured BT-474 breast cancer cells in a two-chambered bioreactor with CDM-HD serum replacement to significantly improve the yield of cancer cell-associated EVs and eliminate bovine EV contamination. Cancer-relevant mRNAs BIRC5 (Survivin) and YBX1, as well as long-noncoding RNAs HOTAIR, ZFAS1, and AGAP2-AS1 were detected in BT-474 EVs by quantitative RT-PCR. Bioinformatics meta-analyses showed that BIRC5 and HOTAIR RNAs were substantially upregulated in breast tumours compared to non-tumour breast tissue, warranting further studies to explore their usefulness as biomarkers in patient EV samples. We envision this effective procedure for obtaining large amounts of cancer-specific EVs will accelerate discovery of EV-associated RNA biomarkers for cancers including HER2+ breast cancer.

Towards establishing extracellular vesicle-associated RNAs as biomarkers for HER2+ breast cancer

Extracellular vesicles (EVs) are emerging as key players in breast cancer progression and hold immense promise as cancer biomarkers. However, difficulties in obtaining sufficient quantities of EVs for the identification of potential biomarkers hampers progress in this area. To circumvent this obstacle, we cultured BT-474 breast cancer cells in a two-chambered bioreactor with CDM-HD serum replacement to significantly improve the yield of cancer cell-associated EVs and eliminate bovine EV contamination. Cancer-relevant mRNAs BIRC5 (Survivin) and YBX1, as well as long-noncoding RNAs HOTAIR, ZFAS1, and AGAP2-AS1 were detected in BT-474 EVs by quantitative RT-PCR. Bioinformatics meta-analyses showed that BIRC5 and HOTAIR RNAs were substantially upregulated in breast tumours compared to non-tumour breast tissue, warranting further studies to explore their usefulness as biomarkers in patient EV samples. We envision this effective procedure for obtaining large amounts of cancer-specific EVs will accelerate discovery of EV-associated RNA biomarkers for cancers including HER2+ breast cancer.

A Qualitative Transcriptional Signature for Predicting CpG Island Methylator Phenotype Status of the Right-Sided Colon Cancer

A part of colorectal cancer which is characterized by simultaneous numerous hypermethylation CpG islands sites is defined as CpG island methylator phenotype (CIMP) status. Stage II and III CIMP−positive (CIMP+) right-sided colon cancer (RCC) patients have a better prognosis than CIMP−negative (CIMP−) RCC treated with surgery alone. However, there is no gold standard available in defining CIMP status. In this work, we selected the gene pairs whose relative expression orderings (REOs) were associated with the CIMP status, to develop a qualitative transcriptional signature to individually predict CIMP status for stage II and III RCC. Based on the REOs of gene pairs, a signature composed of 19 gene pairs was developed to predict the CIMP status of RCC through a feature selection process. A sample is predicted as CIMP+ when the gene expression orderings of at least 12 gene pairs vote for CIMP+; otherwise the CIMP−. The difference of prognosis between the predicted CIMP+ and CIMP− groups was more significantly different than the original CIMP status groups. There were more differential methylation and expression characteristics between the two predicted groups. The hierarchical clustering analysis showed that the signature could perform better for predicting CIMP status of RCC than current methods. In conclusion, the qualitative transcriptional signature for classifying CIMP status at the individualized level can predict outcome and guide therapy for RCC patients.

MET canonical transcript expression is a predictive biomarker for chemo-sensitivity to MET-inhibitors in hepatocellular carcinoma cell lines

PURPOSE

Long interspersed nuclear element 1 (LINE-1 or L1) is a dominant non-long terminal repeat (non-LTR) retrotransposon in the human genome that has been implicated in the overexpression of MET. Both the canonical MET and L1-MET transcripts are considered to play a role in hepatocellular carcinoma (HCC) development. The aim of this study was to assess the utility of canonical MET, L1-MET, and MET protein expressions as predictive biomarkers for chemo-sensitivity to MET-inhibitors in HCC cell lines in vitro. Additionally, we assessed their expression in tumour tissues from Egyptian HCC patients.

METHODS

MET and L1-MET expressions were assessed by qRT-PCR in six liver cancer cell lines (SNU-387, SNU-475, SK-HEP-1, PLC/PRF/5, SNU-449 and SNU-423) and 47 HCC tumour tissues. MET protein expression was measured by western blot in cell lines and immunohistochemistry in the tumours. Cell proliferation assay was used to assess the effect of crizotinib and tivantinib on the six liver cancer cell lines in correlation with the expression of MET, L1-MET and MET.

RESULTS

The antitumor effect of crizotinib and tivantinib correlated with MET gene expression but not with L1-MET transcript or MET protein expressions. No significant difference was observed between HCC tumours and non-tumour samples in MET and L1-MET transcripts expression. There were no significant correlations between the 2-year overall survival rate and the MET, L1-MET transcripts and the MET protein expression.

CONCLUSION

MET RNA expression could be useful biomarker for tivantinib and crizotinib targeted therapy in HCC. The value of assessment of MET protein expression is limited.

Urinary exosomal mRNA detection using novel isothermal gene amplification method based on three-way junction

Exosomal messenger RNA (mRNA) has emerged as a valuable biomarker for liquid biopsy-based disease diagnosis and prognosis due to its stability in body fluids and its biological regulatory function. Here, we report a rapid one-step isothermal gene amplification reaction based on three-way junction (3WJ) formation and the successful detection of urinary exosomal mRNA from tumor-bearing mice. The 3WJ structure can be formed by the association of 3WJ probes (3WJ-template and 3WJ-primer) in the presence of target RNA. After 3WJ structure formation, the 3WJ primer is repeatedly extended and cleaved by a combination of DNA polymerase and nicking endonuclease, producing multiple signal primers. Subsequently, the signal primers promote a specially designed network reaction pathway to produce G-quadruplex probes under isothermal conditions. Finally, G-quadruplex structure produces highly enhanced fluorescence signal upon binding to thioflavin T. This method provides a detection limit of 1.23 pM (24.6 amol) with high selectivity for the target RNA. More importantly, this method can be useful for the sensing of various kinds of mRNA, including breast cancer cellular mRNA, breast cancer exosomal mRNA, and even urinary exosomal mRNA from breast cancer mice. We anticipate that the developed RNA detection assay can be used for various biomedical applications, such as disease diagnosis, prognosis, and treatment monitoring.

Differentially expressed lncRNAs, miRNAs and mRNAs with associated ceRNA networks in a mouse model of myocardial ischemia/reperfusion injury

Non‑coding RNAs, including long non‑coding RNAs (lncRNAs) and microRNAs (miRNAs/miRs), have significant regulatory effects on a number of biological processes in myocardial ischemia/reperfusion (I/R) injury, including cell differentiation, proliferation and apoptosis. In the present study, the expression levels of lncRNAs, miRNAs and mRNAs were evaluated in a mouse model of myocardial I/R injury. The potential functions of these differentially expressed genes were then analyzed via Gene Ontology and pathway analyses. Additionally, the interactions between lncRNA‑miRNA‑mRNA were predicted by constructing a competing endogenous RNA regulatory network. It was found that 14,366 lncRNAs, 151 miRNAs and 9,377 mRNAs were differentially expressed in mice hearts after I/R compared with the Sham group (fold change >2; P<0.05). The results indicated that these differentially expressed genes were involved in multiple molecular functions, including 'guanosine diphosphate binding', 'RNA polymerase II carboxy‑terminal domain kinase activity', 'TATA‑binding protein‑class protein binding', 'nicotinamide adenine dinucleotide binding' and 'protein phosphatase type 2A regulator activity'. The interactions between lncRNA‑miRNA‑mRNA, including five lncRNAs, 38 miRNAs and 196 mRNAs, were predicted, specifically Gm12040‑mmu‑miR‑125a‑5p‑decapping mRNA 1B, Rpl7l1‑ps1‑mmu‑miR‑124‑3p‑G protein‑coupled receptor 146, Gm11407‑mmu‑miR‑190a‑5p‑homeobox and leucine zipper encoding (HOMEZ), 1600029O15Rik‑mmu‑miR‑132‑3p‑HOMEZ and AK155692‑mmu‑miR‑1224‑3p‑activating transcription factor 6β. Collectively, these findings provided novel insights for future research on lncRNAs, miRNAs and mRNAs in myocardial I/R injury.

Focused ultrasound for safe and effective release of brain tumor biomarkers into the peripheral circulation

The development of noninvasive approaches for brain tumor diagnosis and monitoring continues to be a major medical challenge. Although blood-based liquid biopsy has received considerable attention in various cancers, limited progress has been made for brain tumors, at least partly due to the hindrance of tumor biomarker release into the peripheral circulation by the blood-brain barrier. Focused ultrasound (FUS) combined with microbubbles induced BBB disruption has been established as a promising technique for noninvasive and localized brain drug delivery. Building on this established technique, we propose to develop FUS-enabled liquid biopsy technique (FUS-LBx) to enhance the release of brain tumor biomarkers (e.g., DNA, RNA, and proteins) into the circulation. The objective of this study was to demonstrate that FUS-LBx could sufficiently increase plasma levels of brain tumor biomarkers without causing hemorrhage in the brain. Mice with orthotopic implantation of enhanced green fluorescent protein (eGFP)-transfected murine glioma cells were treated using magnetic resonance (MR)-guided FUS system in the presence of systemically injected microbubbles at three peak negative pressure levels (0.59, 1.29, and 1.58 MPa). Plasma eGFP mRNA levels were quantified with the quantitative polymerase chain reaction (qPCR). Contrast-enhanced MR images were acquired before and after the FUS sonication. FUS at 0.59 MPa resulted in an increased plasma eGFP mRNA level, comparable to those at higher acoustic pressures (1.29 MPa and 1.58 MPa). Microhemorrhage density associated with FUS at 0.59 MPa was significantly lower than that at higher acoustic pressures and not significantly different from the control group. MRI analysis revealed that post-sonication intratumoral and peritumoral hyperenhancement had strong correlations with the level of FUS-induced biomarker release and the extent of hemorrhage. This study suggests that FUS-LBx could be a safe and effective brain-tumor biomarker release technique, and MRI could be used to develop image-guided FUS-LBx.

Selection of Endogenous Control Reference Genes for Studies on Type 1 or Type 2 Endometrial Cancer

A panel of 32 candidate reference genes was used to identify the most stable genes for gene normalisation in quantitative RT-PCR studies using endometrial biopsies obtained from women with endometrial cancer (type 1 or type 2) and without cancer (controls). RNA from the biopsies was isolated, examined for purity and quality, and then reverse transcribed into cDNA before being subjected to real-time qRT-PCR analysis in triplicate within the TaqMan gene Expression Assay kit. The most 'stable' endogenous control genes were then identified using the geNorm qbase + 2 and NormFinder software packages. PSMC4, PUM1 and IPO8 were identified as the best reference genes combination for type 1 endometrial cancer (grades 1, 2 and 3), whereas for type 2 endometrial cancer (serous and carcinosarcoma), UBC, MRPL19, PGK1 and PPIA were the best reference genes combination. We conclude that the use of these normaliser combinations should provide accurate interpretation of gene expression at the transcript level in endometrial cancer studies especially for types 1 and 2 cancers.

The 31-nucleotide Y4-RNA fragment in plasma is a potential novel biomarker

The 31- and 32-nt 5′-fragment of Y4-RNA (Y4RNAfr) exists abundantly in human peripheral blood plasma. Although physiological roles of the plasma Y4RNAfr are not well established, its potential utility as a diagnostic/prognostic marker for acute coronary syndrome was suggested. In this paper, to establish a normal range of the Y4RNAfr level in plasma, we measured plasma Y4RNAfr levels of 40 healthy persons using the method we have developed, and compared them with other blood test data. From the obtained data, we tentatively regarded <0.1 fmol/ng as normal for the Y4RNAfr level in peripheral blood plasma. And the white blood cell count (WBC) and the C-reactive protein (CRP) level showed moderate positive correlations with the Y4RNAfr level, suggesting that Y4RNAfr could be a potential novel inflammatory marker. We also measured the Y4RNAfr level in peripheral blood plasma from four multiple myeloma patients. The plasma Y4RNAfr level was abnormal in all four myeloma patients, and the levels for two patients were far beyond the normal level. The WBC for each patient was normal and the CRP levels for two patients were normal. These observations together suggest that a high level of Y4RNAfr in peripheral blood plasma and a normal WBC could be indicative of multiple myeloma.