Non-invasive characterization of human bone marrow stimulation and reconstitution by cell-free messenger RNA sequencing

Cell-free RNA Liquid Biopsy to Monitor Hematopoietic Stem Cell Transplantation

Hematopoietic Stem Cell Transplantation (HSCT) is one of the oldest and most successful immunotherapies. Yet, despite long-standing success in the use of HSCT for the treatment of blood cancers and severe immune disorders, monitoring post-transplant complications remains a challenge due to a lack of informative diagnostic tests. Here, we investigate the utility of cell-free RNA (cfRNA) in plasma as a liquid biopsy to monitor allogeneic HSCT recipients during and after treatment. We assayed longitudinal samples from 92 HSCT recipients by cfRNA sequencing and show that cfRNA provides insight into treatment and recovery trajectories, immune dynamics in response to transplantation, infection, and solid-tissue injury associated with Graft-Versus-Host Disease. Collectively, our results provide support for the use of plasma cfRNA profiling to monitor complications of HSCT.

Decoding bioactive signals of the RNA secretome: the cell-free messenger RNA catalogue

Despite gene-expression profiling being one of the most common methods to evaluate molecular dysregulation in tissues, the utilization of cell-free messenger RNA (cf-mRNA) as a blood-based non-invasive biomarker analyte has been limited compared to other RNA classes. Recent advancements in low-input RNA-sequencing and normalization techniques, however, have enabled characterization as well as accurate quantification of cf-mRNAs allowing direct pathological insights. The molecular profile of the cell-free transcriptome in multiple diseases has subsequently been characterized including, prenatal diseases, neurological disorders, liver diseases and cancers suggesting this biological compartment may serve as a disease agnostic platform. With mRNAs packaged in a myriad of extracellular vesicles and particles, these signals may be used to develop clinically actionable, non-invasive disease biomarkers. Here, we summarize the recent scientific developments of extracellular mRNA, biology of extracellular mRNA carriers, clinical utility of cf-mRNA as disease biomarkers, as well as proposed functions in cell and tissue pathophysiology.

Cell type signatures in cell-free DNA fragmentation profiles reveal disease biology

Circulating cell-free DNA (cfDNA) fragments have characteristics that are specific to the cell types that release them. Current methods for cfDNA deconvolution typically use disease tailored marker selection in a limited number of bulk tissues or cell lines. Here, we utilize single cell transcriptome data as a comprehensive cellular reference set for disease-agnostic cfDNA cell-of-origin analysis. We correlate cfDNA-inferred nucleosome spacing with gene expression to rank the relative contribution of over 490 cell types to plasma cfDNA. In 744 healthy individuals and patients, we uncover cell type signatures in support of emerging disease paradigms in oncology and prenatal care. We train predictive models that can differentiate patients with colorectal cancer (84.7%), early-stage breast cancer (90.1%), multiple myeloma (AUC 95.0%), and preeclampsia (88.3%) from matched controls. Importantly, our approach performs well in ultra-low coverage cfDNA datasets and can be readily transferred to diverse clinical settings for the expansion of liquid biopsy.

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

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

Noninvasive preeclampsia prediction using plasma cell-free RNA signatures

BACKGROUND

Preeclampsia, especially preterm preeclampsia and early-onset preeclampsia, is a life-threating pregnancy disorder, and the heterogeneity and complexity of preeclampsia make it difficult to predict risk and to develop treatments. Plasma cell-free RNA carries unique information from human tissue and may be useful for noninvasive monitoring of maternal, placental, and fetal dynamics during pregnancy.

OBJECTIVE

This study aimed to investigate various RNA biotypes associated with preeclampsia in plasma and to develop classifiers to predict preterm preeclampsia and early-onset preeclampsia before diagnosis.

STUDY DESIGN

We performed a novel, cell-free RNA sequencing method termed polyadenylation ligation-mediated sequencing to investigate the cell-free RNA characteristics of 715 healthy pregnancies and 202 pregnancies affected by preeclampsia before symptom onset. We explored differences in the abundance of different RNA biotypes in plasma between healthy and preeclampsia samples and built preterm preeclampsia and early-onset preeclampsia prediction classifiers using machine learning methods. Furthermore, we validated the performance of the classifiers using the external and internal validation cohorts and assessed the area under the curve and positive predictive value.

RESULTS

We detected 77 genes, including messenger RNA (44%) and microRNA (26%), that were differentially expressed in healthy mothers and mothers with preterm preeclampsia before symptom onset, which could separate participants with preterm preeclampsia from healthy samples and that played critical functional roles in preeclampsia physiology. We developed 2 classifiers for predicting preterm preeclampsia and early-onset preeclampsia before diagnosis based on 13 cell-free RNA signatures and 2 clinical features (in vitro fertilization and mean arterial pressure), respectively. Notably, both classifiers showed enhanced performance when compared with the existing methods. The preterm preeclampsia prediction model achieved 81% area under the curve and 68% positive predictive value in an independent validation cohort (preterm, n=46; control, n=151); the early-onset preeclampsia prediction model had an area under the curve of 88% and a positive predictive value of 73% in an external validation cohort (early-onset preeclampsia, n=28; control, n=234). Furthermore, we demonstrated that downregulation of microRNAs may play vital roles in preeclampsia through the upregulation of preeclampsia-relevant target genes.

CONCLUSION

In this cohort study, a comprehensive transcriptomic landscape of different RNA biotypes in preeclampsia was presented and 2 advanced classifiers with substantial clinical importance for preterm preeclampsia and early-onset preeclampsia prediction before symptom onset were developed. We demonstrated that messenger RNA, microRNA, and long noncoding RNA can simultaneously serve as potential biomarkers of preeclampsia, holding the promise of prevention of preeclampsia in the future. Abnormal cell-free messenger RNA, microRNA, and long noncoding RNA molecular changes may help to elucidate the pathogenic determinants of preeclampsia and open new therapeutic windows to effectively reduce pregnancy complications and fetal morbidity.

Multiomics characterization of cell type repertoires for urine liquid biopsies

Urine is assayed alongside blood in medicine, yet current clinical diagnostic tests utilize only a small fraction of its total biomolecular repertoire, potentially foregoing high-resolution insights into human health and disease. In this work, we characterized the joint landscapes of transcriptomic and metabolomic signals in human urine. We also compared the urine transcriptome to plasma cell-free RNA, identifying a distinct cell type repertoire and enrichment for metabolic signal. Untargeted metabolomic measurements identified a complementary set of pathways to the transcriptomic analysis. Our findings suggest that urine is a promising biofluid yielding prognostic and detailed insights for hard-to-biopsy tissues with low representation in the blood, offering promise for a new generation of liquid biopsies.

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.

Selective enrichment of plasma cell-free messenger RNA in cancer-associated extracellular vesicles

Extracellular vesicles (EVs) have been shown as key mediators of extracellular small RNA transport. However, carriers of cell-free messenger RNA (cf-mRNA) in human biofluids and their association with cancer remain poorly understood. Here, we performed a transcriptomic analysis of size-fractionated plasma from lung cancer, liver cancer, multiple myeloma, and healthy donors. Morphology and size distribution analysis showed the successful separation of large and medium particles from other soluble plasma protein fractions. We developed a strategy to purify and sequence ultra-low amounts of cf-mRNA from particle and protein enriched subpopulations with the implementation of RNA spike-ins to control for technical variability and to normalize for intrinsic drastic differences in cf-mRNA amount carried in each plasma fraction. We found that the majority of cf-mRNA was enriched and protected in EVs with remarkable stability in RNase-rich environments. We observed specific enrichment patterns of cancer-associated cf-mRNA in each particle and protein enriched subpopulation. The EV-enriched differentiating genes were associated with specific biological pathways, such as immune systems, liver function, and toxic substance regulation in lung cancer, liver cancer, and multiple myeloma, respectively. Our results suggest that dissecting the complexity of EV subpopulations illuminates their biological significance and offers a promising liquid biopsy approach.

Comprehensive analysis of circulating cell-free RNAs in blood for diagnosing non-small cell lung cancer

Early screening and detection of non-small cell lung cancer (NSCLC) is crucial due to the significantly low survival rate in advanced stages. Blood-based liquid biopsy is non-invasive test to assistant disease diagnosis, while cell-free RNA is one of the promising biomarkers in blood. However, the disease related signatures have not been explored completely for most cell-free RNA transcriptome sequencing (cfRNA-Seq) datasets. To address this gap, we developed a comprehensive cfRNA-Seq pipeline for data analysis and constructed a machine learning model to facilitate noninvasive early diagnosis of NSCLC. The results of our study have demonstrated the identification of differential mRNA, lncRNAs and miRNAs from cfRNA-Seq, which have exhibited significant association with development and progression of lung cancer. The classifier based on gene expression signatures achieved an impressive area under the curve (AUC) of up to 0.9, indicating high specificity and sensitivity in both cross-validation and independent test. Furthermore, the analysis of T cell and B cell immune repertoire extracted from cfRNA-Seq have provided insights into the immune status of cancer patients, while the microbiome analysis has revealed distinct bacterial and viral profiles between NSCLC and normal samples. In our future work, we aim to validate the existence of cancer associated T cell receptors (TCR)/B cell receptors (BCR) and microorganisms, and subsequently integrate all identified signatures into diagnostic model to improve the prediction accuracy. This study not only provided a comprehensive analysis pipeline for cfRNA-Seq dataset but also highlights the potential of cfRNAs as promising biomarkers and models for early NSCLC diagnosis, emphasizing their importance in clinical settings.

Noninvasive Prenatal Testing Using Circulating DNA and RNA: Advances, Challenges, and Possibilities

Prenatal screening using sequencing of circulating cell-free DNA has transformed obstetric care over the past decade and significantly reduced the number of invasive diagnostic procedures like amniocentesis for genetic disorders. Nonetheless, emergency care remains the only option for complications like preeclampsia and preterm birth, two of the most prevalent obstetrical syndromes. Advances in noninvasive prenatal testing expand the scope of precision medicine in obstetric care. In this review, we discuss advances, challenges, and possibilities toward the goal of providing proactive, personalized prenatal care. The highlighted advances focus mainly on cell-free nucleic acids; however, we also review research that uses signals from metabolomics, proteomics, intact cells, and the microbiome. We discuss ethical challenges in providing care. Finally, we look to future possibilities, including redefining disease taxonomy and moving from biomarker correlation to biological causation.

Nucleic acid biomarkers of immune response and cell and tissue damage in children with COVID-19 and MIS-C

Differential host responses in coronavirus disease 2019 (COVID-19) and multisystem inflammatory syndrome in children (MIS-C) remain poorly characterized. Here, we use next-generation sequencing to longitudinally analyze blood samples from pediatric patients with COVID-19 or MIS-C across three hospitals. Profiling of plasma cell-free nucleic acids uncovers distinct signatures of cell injury and death between COVID-19 and MIS-C, with increased multiorgan involvement in MIS-C encompassing diverse cell types, including endothelial and neuronal cells, and an enrichment of pyroptosis-related genes. Whole-blood RNA profiling reveals upregulation of similar pro-inflammatory pathways in COVID-19 and MIS-C but also MIS-C-specific downregulation of T cell-associated pathways. Profiling of plasma cell-free RNA and whole-blood RNA in paired samples yields different but complementary signatures for each disease state. Our work provides a systems-level view of immune responses and tissue damage in COVID-19 and MIS-C and informs future development of new disease biomarkers.

Liquid biopsy by analysis of circulating myeloma cells and cell-free nucleic acids: a novel noninvasive approach of disease evaluation in multiple myeloma

Multiple myeloma (MM) is an incurable hematological cancer with high spatial- and temporal-heterogeneity. Invasive single-point bone marrow sampling cannot capture the tumor heterogeneity and is difficult to repeat for serial assessments. Liquid biopsy is a technique for identifying and analyzing circulating MM cells and cell products produced by tumors and released into the circulation, allowing for the minimally invasive and comprehensive detection of disease burden and molecular alterations in MM and monitoring treatment response and disease progression. Furthermore, liquid biopsy can provide complementary information to conventional detection approaches and improve their prognostic values. This article reviewed the technologies and applications of liquid biopsy in MM.

Molecular Monitoring of Lymphomas

Molecular monitoring of tumor-derived alterations has an established role in the surveillance of leukemias, and emerging nucleic acid sequencing technologies are likely to similarly transform the clinical management of lymphomas. Lymphomas are well suited for molecular surveillance due to relatively high cell-free DNA and circulating tumor DNA concentrations, high somatic mutational burden, and the existence of stereotyped variants enabling focused interrogation of recurrently altered regions. Here, we review the clinical scenarios and key technologies applicable for the molecular monitoring of lymphomas, summarizing current evidence in the literature regarding molecular subtyping and classification, evaluation of treatment response, the surveillance of active cellular therapies, and emerging clinical trial strategies.

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.

Circulating cell-free messenger RNA enables non-invasive pan-tumour monitoring of melanoma therapy independent of the mutational genotype

BACKGROUND

Plasma-derived tumour-specific cell-free nucleic acids are increasingly utilized as a minimally invasive, real-time biomarker approach in many solid tumours. Circulating tumour DNA of melanoma-specific mutations is currently the best studied liquid biopsy biomarker for melanoma. However, the combination of hotspot genetic alterations covers only around 80% of all melanoma patients. Therefore, alternative approaches are needed to enable the follow-up of all genotypes, including wild-type.

METHODS

We identified KPNA2, DTL, BACE2 and DTYMK messenger RNA (mRNA) upregulated in melanoma versus nevi tissues by unsupervised data mining (N = 175 melanoma, N = 20 normal skin, N = 6 benign nevi) and experimentally confirmed differential mRNA expression in vitro (N = 18 melanoma, N = 8 benign nevi). Circulating cell-free RNA (cfRNA) was analysed in 361 plasma samples (collected before and during therapy) from 100 melanoma patients and 18 healthy donors. Absolute cfRNA copies were quantified on droplet digital PCR.

RESULTS

KPNA2, DTL, BACE2 and DTYMK cfRNA demonstrated high diagnostic accuracy between melanoma patients' and healthy donors' plasma (AUC > 86%, p < .0001). cfRNA copies increased proportionally with increasing tumour burden independently of demographic variables and even remained elevated in individuals with radiological absence of disease. Re-analysis of single-cell transcriptomes revealed a pan-tumour origin of cfRNA, including endothelial, cancer-associated fibroblasts, macrophages and B cells beyond melanoma cells as cellular sources. Low baseline cfRNA levels were associated with significantly longer progression-free survival (PFS) (KPNA2 HR = .54, p = .0362; DTL HR = .60, p = .0349) and overall survival (KPNA2 HR = .52, p = .0237; BACE2 HR = .55, p = .0419; DTYMK HR = .43, p = .0393). Lastly, we found that cfRNA copies significantly increased during therapy in non-responders compared to responders regardless of therapy and mutational subtypes and that the increase of KPNA2 (HR = 1.73, p = .0441) and DTYMK (HR = 1.82, p = .018) cfRNA during therapy was predictive of shorter PFS.

CONCLUSIONS

In sum, we identified a new panel of cfRNAs for a pan-tumour liquid biopsy approach and demonstrated its utility as a prognostic, therapy-monitoring tool independent of the melanoma mutational genotype.

Diagnostic biomolecules and combination therapy for pre-eclampsia

Pre-eclampsia (PE), associated with placental malperfusion, is the primary reason for maternal and perinatal mortality and morbidity that can cause vascular endothelial injury and multi-organ injury. Despite considerable research efforts, no pharmaceutical has been shown to stop disease progression. If women precisely diagnosed with PE can achieve treatment at early gestation, the maternal and fetal outcomes can be maximally optimized by expectant management. Current diagnostic approaches applying maternal characteristics or biophysical markers, including blood test, urine analysis and biophysical profile, possess limitations in the precise diagnosis of PE. Biochemical factor research associated with PE development has generated ambitious diagnostic targets based on PE pathogenesis and dissecting molecular phenotypes. This review focuses on current developments in biochemical prediction of PE and the corresponding interventions to ameliorate disease progression, aiming to provide references for clinical diagnoses and treatments.

Survey of extracellular communication of systemic and organ-specific inflammatory responses through cell free messenger RNA profiling in mice

Background

Inflammatory and immune responses are essential and dynamic biological processes that protect the body against acute and chronic adverse stimuli. While conventional protein markers have been used to evaluate systemic inflammatory response, the immunological response to stimulation is complex and involves modulation of a large set of genes and interacting signalling pathways of innate and adaptive immune systems. There is a need for a non-invasive tool that can comprehensively evaluate and monitor molecular dysregulations associated with inflammatory and immune responses in circulation and in inaccessible solid organs.

Methods

Here we utilized cell-free messenger RNA (cf-mRNA) RNA-Seq whole transcriptome profiling and computational biology to temporally assess lipopolysaccharide (LPS) induced and JAK inhibitor modulated inflammatory and immune responses in mouse plasma samples.

Findings

Cf-mRNA profiling displayed a pattern of systemic immune responses elicited by LPS and dysregulation of associated pathways. Moreover, attenuation of several inflammatory pathways, including STAT and interferon pathways, were observed following the treatment of JAK inhibitor. We further identified the dysregulation of liver-specific transcripts in cf-mRNA which reflected changes in the gene-expression pattern in this generally inaccessible biological compartment.

Interpretation

Using a preclinical mouse model, we demonstrated the potential of plasma cf-mRNA profiling for systemic and organ-specific characterization of drug-induced molecular alterations that are associated with inflammatory and immune responses.

Funding

Molecular Stethoscope.

Evaluating the Effects of Storage Conditions on Multiple Cell-Free RNAs in Plasma by High-Throughput Sequencing

Background: Plasma cell-free RNAs (cfRNAs) can serve as noninvasive biomarkers for the diagnosis and monitoring of diseases. However, the delay in blood processing may lead to unreliable results. Therefore, an unbiased evaluation based on the whole transcriptome under different storage conditions is needed. Methods: Here, blood samples were collected in ethylenediaminetetraacetic acid tubes and processed immediately (0 hour), or stored at room temperature (RT) or 4°C for different time intervals (2, 6, and 24 hours) before plasma separation. High-throughput sequencing was applied to assess the effects of storage conditions on the transcript profiles and fragment characteristics of plasma cell-free mRNA, long noncoding RNA (lncRNA), and small RNAs. Results: More genes changed their expression levels with time when blood was stored at RT compared with those at 4°C. Cell-free mRNA and lncRNA were relatively stable in blood preserved at 4°C for 6 hours, while cell-free microRNA (miRNA) and piwi-interacting RNA (piRNA) remained stable at 4°C for 24 hours. After 24 hours, more contamination of the leukocyte-derived RNAs occurred at RT, possibly due to apoptosis. Meanwhile, significant changes were also observed regarding the characteristics of the RNA fragments, including fragment size, the proportion of intron, and the pyrimidine frequency of the fragmented 3' end. Fifteen tissue-enriched genes were detected in the plasma but not expressed in leukocytes. The expression level and fragment length of these genes gradually decreased during storage, suggesting the degradation of the cfRNA and the dilution of leukocyte-derived RNA with other tissue-derived cfRNA. Conclusions: Our results suggest that the contamination of leukocyte-derived RNA and the degradation of original cfRNA contribute to the changes in the cfRNA expression profiles and the fragment characteristics during short-term storage. The storage of blood at 4°C for 6 hours allows plasma cfRNA to remain relatively stable, which will be useful for further studies or clinical applications where adequate quantification or the fragment signature of cfRNA is required.

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

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

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

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

The clinical utility of cfRNA for disease detection and surveillance: A proof of concept study in non-small cell lung cancer

Background

CT scans are used in routine clinical practice for the diagnosis and treatment surveillance of non‐small cell lung cancer (NSCLC). However, more sensitive methods are desirable. Liquid biopsy analyses of RNA and DNA can offer more sensitive diagnostic approaches. Cell‐free RNA (cfRNA) has been described in several malignancies, but its clinical utility has not previously been explored.

Methods

We evaluated the clinical utility of cfRNA for early detection and surveillance of tumor disease in a proof‐of‐concept study. Using real‐time‐droplet digital polymerase chain reaction we characterized a candidate transcript (MORF4L2) in plasma samples from 41 advanced stage, 38 early stage NSCLC and 39 healthy samples. We compared its diagnostic performance with tumor markers and evaluated its utility for disease monitoring.

Results

MORF4L2 cfRNA was more abundant in patients than in healthy donors (p < 0.0001). Using the Youden index approach (cutoff value of 537 copies/ml was established) with a sensitivity of 0.73 (95% CI: 0.61–0.82) and a specificity of 0.87 (95% CI: 0.73–0.96). Positive and negative predictive values of 0.92 (95% CI: 0.83–0.95) and 0.59 (95% CI: 0.47–0.83) were achieved. Combination of cfRNA and Cyfra21‐1 improved its predictive value from 89.5% to 94.7%. Low baseline MORF4L2 levels were associated with better overall survival (HR:0.25, 95% CI: 0.09–0.7, p = 0.009) and progression‐free survival for patients treated with tyrosine kinase inhibitors (p = 0.011) and chemotherapy (p = 0.019). MORF4L2 profile between baseline and follow‐up mirrored radiological response and tumor dynamics better than tumor markers. cfRNA transcripts allowed monitoring tumor dynamics in patients without tumor‐reported genetic alterations.

Conclusion

Our data support clinical utility of cfRNA for detection and surveillance of NSCLC. Further studies with larger cohorts are required.

Plasma cell-free RNA profiling distinguishes cancers from pre-malignant conditions in solid and hematologic malignancies

Cell-free RNA (cfRNA) in plasma reflects phenotypic alterations of both localized sites of cancer and the systemic host response. Here we report that cfRNA sequencing enables the discovery of messenger RNA (mRNA) biomarkers in plasma with the tissue of origin-specific to cancer types and precancerous conditions in both solid and hematologic malignancies. To explore the diagnostic potential of total cfRNA from blood, we sequenced plasma samples of eight hepatocellular carcinoma (HCC) and ten multiple myeloma (MM) patients, 12 patients of their respective precancerous conditions, and 20 non-cancer (NC) donors. We identified distinct gene sets and built classification models using Random Forest and linear discriminant analysis algorithms that could distinguish cancer patients from premalignant conditions and NC individuals with high accuracy. Plasma cfRNA biomarkers of HCC are liver-specific genes and biomarkers of MM are highly expressed in the bone marrow compared to other tissues and are related to cell cycle processes. The cfRNA level of these biomarkers displayed a gradual transition from noncancerous states through precancerous conditions and cancer. Sequencing data were cross-validated by quantitative reverse transcription PCR and cfRNA biomarkers were validated in an independent sample set (20 HCC, 9 MM, and 10 NC) with AUC greater than 0.86. cfRNA results observed in precancerous conditions require further validation. This work demonstrates a proof of principle for using mRNA transcripts in plasma with a small panel of genes to distinguish between cancers, noncancerous states, and precancerous conditions.

Inferring gene expression from cell-free DNA fragmentation profiles

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

LncRNA Biomarkers of Inflammation and Cancer

Long noncoding RNAs (lncRNAs) are promising candidates as biomarkers of inflammation and cancer. LncRNAs have several properties that make them well-suited as molecular markers of disease: (1) many lncRNAs are expressed in a tissue-specific manner, (2) distinct lncRNAs are upregulated based on different inflammatory or oncogenic stimuli, (3) lncRNAs released from cells are packaged and protected in extracellular vesicles, and (4) circulating lncRNAs in the blood are detectable using various RNA sequencing approaches. Here we focus on the potential for lncRNA biomarkers to detect inflammation and cancer, highlighting key biological, technological, and analytical considerations that will help advance the development of lncRNA-based liquid biopsies.

Cell types of origin of the cell-free transcriptome

Cell-free RNA from liquid biopsies can be analyzed to determine disease tissue of origin. We extend this concept to identify cell types of origin using the Tabula Sapiens transcriptomic cell atlas as well as individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset. We define cell type signature scores, which allow the inference of cell types that contribute to cell-free RNA for a variety of diseases.

Cell types affected by various diseases are inferred from cell-free RNA.

Early prediction of preeclampsia in pregnancy with cell-free RNA

Liquid biopsies that measure circulating cell-free RNA (cfRNA) offer an opportunity to study the development of pregnancy-related complications in a non-invasive manner and to bridge gaps in clinical care1-4. Here we used 404 blood samples from 199 pregnant mothers to identify and validate cfRNA transcriptomic changes that are associated with preeclampsia, a multi-organ syndrome that is the second largest cause of maternal death globally5. We find that changes in cfRNA gene expression between normotensive and preeclamptic mothers are marked and stable early in gestation, well before the onset of symptoms. These changes are enriched for genes specific to neuromuscular, endothelial and immune cell types and tissues that reflect key aspects of preeclampsia physiology6-9, suggest new hypotheses for disease progression and correlate with maternal organ health. This enabled the identification and independent validation of a panel of 18 genes that when measured between 5 and 16 weeks of gestation can form the basis of a liquid biopsy test that would identify mothers at risk of preeclampsia long before clinical symptoms manifest themselves. Tests based on these observations could help predict and manage who is at risk for preeclampsia-an important objective for obstetric care10,11.

Non-Invasive Characterization of the Pancreas During Bariatric Surgery via Circulating Pancreatic Specific Cell-free Messenger RNA

Bariatric surgery results in sustained weight loss and improvement in glucose homeostasis. However, the lack of accessible non-invasive tools to examine molecular alterations occurring in the pancreas limits our understanding of the causes and recovery of glucose homeostasis. Here, we describe the use of a circulating cell free mRNA (cfmRNA) based multiplex qPCR assay to selectively amplify and quantify circulating pancreatic specific transcripts levels within plasma. We applied this assay to a cohort of 58 plasma samples consisting of 10 patients that tracks multiple time points including pre and post-bariatric surgery. In our targeted multiplex screen of 14 selected pancreatic specific circulating transcripts, we identified 13 pancreatic specific transcripts that can be amplified from plasma. Furthermore, when quantifying the amplicons obtained in the short-term post-surgery (2 weeks–1 month) and long-term (3–12 months), we observed a consistent reduction of circulating GCG transcripts during short term post-surgery. Across the cohort, GCG cfmRNA levels correlated significantly with common metrics of improvement following bariatric surgery such as: haemoglobin A1c levels (R: −0.41, p-value: 0.0039) and percentage of excess weight loss (R: 0.29, p-value: 0.046).

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

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

Noninvasive stratification of nonalcoholic fatty liver disease by whole transcriptome cell-free mRNA characterization

Hepatic fibrosis stage is the most important determinant of outcomes in patients with nonalcoholic fatty liver disease (NAFLD). There is an urgent need for noninvasive tests that can accurately stage fibrosis and determine efficacy of interventions. Here, we describe a novel cell-free (cf)-mRNA sequencing approach that can accurately and reproducibly profile low levels of circulating mRNAs and evaluate the feasibility of developing a cf-mRNA-based NAFLD fibrosis classifier. Using separate discovery and validation cohorts with biopsy-confirmed NAFLD (n = 176 and 59, respectively) and healthy subjects (n = 23), we performed serum cf-mRNA RNA-Seq profiling. Differential expression analysis identified 2,498 dysregulated genes between patients with NAFLD and healthy subjects and 134 fibrosis-associated genes in patients with NAFLD. Comparison between cf-mRNA and liver tissue transcripts revealed significant overlap of fibrosis-associated genes and pathways indicating that the circulating cf-mRNA transcriptome reflects molecular changes in the livers of patients with NAFLD. In particular, metabolic and immune pathways reflective of known underlying steatosis and inflammation were highly dysregulated in the cf-mRNA profile of patients with advanced fibrosis. Finally, we used an elastic net ordinal logistic model to develop a classifier that predicts clinically significant fibrosis (F2-F4). In an independent cohort, the cf-mRNA classifier was able to identify 50% of patients with at least 90% probability of clinically significant fibrosis. We demonstrate a novel and robust cf-mRNA-based RNA-Seq platform for noninvasive identification of diverse hepatic molecular disruptions and for fibrosis staging with promising potential for clinical trials and clinical practice.NEW & NOTEWORTHY This work is the first study, to our knowledge, to utilize circulating cell-free mRNA sequencing to develop an NAFLD diagnostic classifier.

Cytokine IP-10 and GM-CSF are prognostic biomarkers for severity in secondary dengue infection

Dengue virus (DENV) infection is mostly prevalent in tropical and sub-tropical regions of the world. Though most DENV infections are self-limiting febrile like-illness, a small proportion of secondary infection is fatal, if untreated symptomatically. Among various factors involved in severe dengue, immune enhancement by cytokine is the major one. The objective of the study is to elucidate serum cytokine expression among primary and secondary infection and determine if any signature cytokine is correlated with disease severity. Seventy-six serum samples at acute time points were collected during the 2017 DENV outbreak in Madurai, Tamil Nadu. Among the 76 serum samples, 49 belong to primary and 27 to secondary DENV infection. Interestingly, a large number of primary infection presented with DHF/DSS symptoms and, children were found prone to DHF and DSS in secondary infection. The serum samples were analysed for inflammatory cytokines, namely IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, IL-17A, IFN-γ, TNF-α, IP-10 and GM-CSF using ELISA assay as well as mRNA analysis using qPCR. Among the 12 inflammatory cytokines analysed IP-10 and GMCSF mRNA and protein shows significant upregulation in secondary infection. Similarly, a strong correlation was observed between GM-CSF and IP-10 with thrombocytopenia, ascites, serous effusion and spontaneous bleeding. Based on the observations, GM-CSF and IP-10 could be a potential prognostic biomarkers for secondary DENV infection.

Data-Driven Modeling of Pregnancy-Related Complications

A healthy pregnancy depends on complex interrelated biological adaptations involving placentation, maternal immune responses, and hormonal homeostasis. Recent advances in high-throughput technologies have provided access to multiomics biological data that, combined with clinical and social data, can provide a deeper understanding of normal and abnormal pregnancies. Integration of these heterogeneous datasets using state-of-the-art machine-learning methods can enable the prediction of short- and long-term health trajectories for a mother and offspring and the development of treatments to prevent or minimize complications. We review advanced machine-learning methods that could: provide deeper biological insights into a pregnancy not yet unveiled by current methodologies; clarify the etiologies and heterogeneity of pathologies that affect a pregnancy; and suggest the best approaches to address disparities in outcomes affecting vulnerable populations.

Territory-wide cohort study of Brugada syndrome in Hong Kong: predictors of long-term outcomes using random survival forests and non-negative matrix factorisation

OBJECTIVES

Brugada syndrome (BrS) is an ion channelopathy that predisposes affected patients to spontaneous ventricular tachycardia/fibrillation (VT/VF) and sudden cardiac death. The aim of this study is to examine the predictive factors of spontaneous VT/VF.

METHODS

This was a territory-wide retrospective cohort study of patients diagnosed with BrS between 1997 and 2019. The primary outcome was spontaneous VT/VF. Cox regression was used to identify significant risk predictors. Non-linear interactions between variables (latent patterns) were extracted using non-negative matrix factorisation (NMF) and used as inputs into the random survival forest (RSF) model.

RESULTS

This study included 516 consecutive BrS patients (mean age of initial presentation=50±16 years, male=92%) with a median follow-up of 86 (IQR: 45-118) months. The cohort was divided into subgroups based on initial disease manifestation: asymptomatic (n=314), syncope (n=159) or VT/VF (n=41). Annualised event rates per person-year were 1.70%, 0.05% and 0.01% for the VT/VF, syncope and asymptomatic subgroups, respectively. Multivariate Cox regression analysis revealed initial presentation of VT/VF (HR=24.0, 95% CI=1.21 to 479, p=0.037) and SD of P-wave duration (HR=1.07, 95% CI=1.00 to 1.13, p=0.044) were significant predictors. The NMF-RSF showed the best predictive performance compared with RSF and Cox regression models (precision: 0.87 vs 0.83 vs. 0.76, recall: 0.89 vs. 0.85 vs 0.73, F1-score: 0.88 vs 0.84 vs 0.74).

CONCLUSIONS

Clinical history, electrocardiographic markers and investigation results provide important information for risk stratification. Machine learning techniques using NMF and RSF significantly improves overall risk stratification performance.

Ethical, Legal and Social Issues (ELSI) Associated with Non-Invasive Prenatal Testing: Reflections on the Evolution of Prenatal Diagnosis and Procreative Choices

New technologies such as non-invasive prenatal testing (NIPT), capable of analyzing cell-free fetal DNA in the maternal bloodstream, have become increasingly widespread and available, which has in turn led to ethical and policy challenges that need addressing. NIPT is not yet a diagnostic tool, but can still provide information about fetal genetic characteristics (including sex) very early in pregnancy, and there is no denying that it offers valuable opportunities for pregnant women, particularly those at high risk of having a child with severe genetic disorders or seeking an alternative to invasive prenatal testing. Nonetheless, the ethical, legal and social implications (ELSI) include multiple aspects of informed decision-making, which can entail risks for the individual right to procreative autonomy, in addition to the potential threats posed by sex-selective termination of pregnancy (in light of the information about fetal sex within the first trimester), and the stigmatization and discrimination of disabled individuals. After taking such daunting challenges into account and addressing NIPT-related medicolegal complexities, the review's authors highlight the need for an ethically and legally sustainable framework for the implementation of NIPT, which seems poised to become a diagnostic tool, as its scope is likely to broaden in the near future.

Investigating Pregnancy and Its Complications Using Circulating Cell-Free RNA in Women's Blood During Gestation

In recent years, there have been major advances in the application of non-invasive techniques to predict pregnancy-related complications, for example by measuring cell-free RNA (cfRNA) in maternal blood. In contrast to cell-free DNA (cfDNA), which is already in clinical use to diagnose fetal aneuploidy, circulating RNA levels can correspond with tissue-specific gene expression and provide a snapshot of prenatal health across gestation. Here, we review the physiologic origins of cfRNA and its novel applications and corresponding challenges to monitor fetal and maternal health and predict pregnancy-related complications.