Plasma cell-free RNA signatures of inflammatory syndromes in children.

Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circulating cell-free RNA (cfRNA) in plasma as an analyte for the differential diagnosis and characterization of pediatric inflammatory syndromes. We profiled cfRNA in 370 plasma samples from pediatric patients with a range of inflammatory conditions, including Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), viral infections, and bacterial infections. We developed machine learning models based on these cfRNA profiles, which effectively differentiated KD from MIS-C-two conditions presenting with overlapping symptoms-with high performance [test area under the curve = 0.98]. We further extended this methodology into a multiclass machine learning framework that achieved 80% accuracy in distinguishing among KD, MIS-C, viral, and bacterial infections. We further demonstrated that cfRNA profiles can be used to quantify injury to specific tissues and organs, including the liver, heart, endothelium, nervous system, and the upper respiratory tract. Overall, this study identified cfRNA as a versatile analyte for the differential diagnosis and characterization of a wide range of pediatric inflammatory syndromes.

Liquid Biopsy Based on Cell-Free DNA and RNA.

This review delves into the rapidly evolving landscape of liquid biopsy technologies based on cell-free DNA (cfDNA) and cell-free RNA (cfRNA) and their increasingly prominent role in precision medicine. With the advent of high-throughput DNA sequencing, the use of cfDNA and cfRNA has revolutionized noninvasive clinical testing. Here, we explore the physical characteristics of cfDNA and cfRNA, present an overview of the essential engineering tools used by the field, and highlight clinical applications, including noninvasive prenatal testing, cancer testing, organ transplantation surveillance, and infectious disease testing. Finally, we discuss emerging technologies and the broadening scope of liquid biopsies to new areas of diagnostic medicine.

Detecting androgen receptor (AR), AR variant 7 (AR-V7), prostate-specific membrane antigen (PSMA), and prostate-specific antigen (PSA) gene expression in CTCs and plasma exosome-derived cfRNA in patients with metastatic castration-resistant prostate cancer (mCRPC) by integrating the VTX-1 CTC isolation system with the QIAGEN AdnaTest.

BACKGROUND: Therapies for metastatic castration-resistant prostate cancer (mCRPC) include targeting the androgen receptor (AR) with androgen receptor inhibitors (ARIs) and prostate-specific membrane antigen (PSMA). Having the ability to detect AR, AR splice variant 7 (AR-V7), or PSMA in circulating tumor cells (CTCs) or circulating exosomal cell-free RNA (cfRNA) could be helpful to guide selection of the appropriate therapy for each individual patient. The Vortex Biosciences VTX-1 system is a label-free CTC isolation system that enables the detection of the expression of multiple genes in both CTCs and exosomal cfRNA from the same blood sample in patients with mCRPC. Detection of both AR-V7 and PSMA gene expression in both CTCs and cfRNA simultaneously has not yet been reported. METHODS: To characterize the combined VTX-1-AdnaDetect workflow, 22Rv1 cancer cells were spiked into blood from healthy donors and processed with the VTX-1 to mimic patient samples and assess performances (capture efficiency, purity, AR and AR-V7 expression). Then, we collected 19 blood samples from 16 patients with mCRPC and therapeutic resistance to androgen receptor inhibitors (ARIs). Plasma was separated and the plasma-depleted blood was processed further with the VTX-1 to collect CTCs. Both plasma exosomal cfRNA and CTCs were subsequently analyzed for AR, AR-V7, PSMA, and prostate-specific antigen (PSA) mRNA expression using the AdnaTest ProstateCancerPanel AR-V7 assay. RESULTS: AR-V7 expression could be detected in 22Rv1 cells spiked into blood from healthy volunteers as well as in CTCs and plasma-derived exosomal cfRNA from patients with mCRPC by processing blood with the VTX-1 CTC isolation system followed by the AdnaTest ProstateCancerPanel AR-V7 assay. 94.7% of patient blood samples (18/19) had detectable AR expression in either CTCs or exosomal cfRNA (16 in CTCs, 12 in cfRNA). 15.8% of the 19 patient blood samples (3/19) were found to have AR-V7-positive (AR-V7+) CTCs, one of which was also AR-V7+ in the exosomal cfRNA analysis. 42.1% of patient blood samples (8/19) were found to be PSMA positive (PSMA+): 26.3% (5/19) were PSMA+ in the CTC analysis and 31.6% (6/19) were PSMA+ in the exosomal cfRNA analysis. Of those 8 PSMA+ samples, 2 had detectable PSMA only in CTCs, and 3 had detectable PSMA only in exosomal cfRNA. CONCLUSION: VTX-1 enables isolation of CTCs and plasma exosomes from a single blood draw and can be used for detecting AR-V7 and PSMA mRNA in both CTCs and cfRNA in patients with mCRPC and resistance to ARIs. This technology facilitates combining RNA measurements in CTCs and exosomal cfRNA for future studies to develop potentially clinically relevant cancer biomarker detection in blood.

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.

Cell-Free Nucleic Acids for Early Prediction of Preeclampsia.

PURPOSE OF REVIEW: This review summarizes the potential of cell-free nucleic acids for predicting preeclampsia, contrasts them with other methods, and discusses these findings' relevance to preeclampsia's pathogenesis and care. RECENT FINDINGS: Recent studies have demonstrated the utility of cell-free nucleic acids in early preeclampsia risk prediction. Encouragingly, nucleic acid measurement exhibits similar or better sensitivity as compared to standard screening assays and furthermore sheds light on preeclampsia's underlying placental biology. Over the past decade, liquid biopsies measuring cell-free nucleic acids have found diverse applications, including in prenatal care. Recent advances have extended their utility to predict preeclampsia, a major cause of maternal mortality. These assays assess methylation patterns in cell-free DNA (cfDNA) or gene levels in cell-free RNA (cfRNA). Currently, preeclampsia care focuses on blood pressure control, seizure prevention, and delivery. If validated, early prediction of preeclampsia through liquid biopsies can improve maternal health and deepen our understanding of its causes.

Phospho-RNA-seq: a modified small RNA-seq method that reveals circulating mRNA and lncRNA fragments as potential biomarkers in human plasma.

Extracellular RNAs (exRNAs) in biofluids have attracted great interest as potential biomarkers. Although extracellular microRNAs in blood plasma are extensively characterized, extracellular messenger RNA (mRNA) and long non-coding RNA (lncRNA) studies are limited. We report that plasma contains fragmented mRNAs and lncRNAs that are missed by standard small RNA-seq protocols due to lack of 5' phosphate or presence of 3' phosphate. These fragments were revealed using a modified protocol ("phospho-RNA-seq") incorporating RNA treatment with T4-polynucleotide kinase, which we compared with standard small RNA-seq for sequencing synthetic RNAs with varied 5' and 3' ends, as well as human plasma exRNA Analyzing phospho-RNA-seq data using a custom, high-stringency bioinformatic pipeline, we identified mRNA/lncRNA transcriptome fingerprints in plasma, including tissue-specific gene sets. In a longitudinal study of hematopoietic stem cell transplant patients, bone marrow- and liver-enriched exRNA genes were tracked with bone marrow recovery and liver injury, respectively, providing proof-of-concept validation as a biomarker approach. By enabling access to an unexplored realm of mRNA and lncRNA fragments, phospho-RNA-seq opens up new possibilities for plasma transcriptomic biomarker development.

Identification of novel cell-free RNAs in maternal plasma as preterm biomarkers in combination with placental RNA profiles.

BACKGROUND: Preterm birth (PTB) is the main driver of newborn deaths. The identification of pregnancies at risk of PTB remains challenging, as the incomplete understanding of molecular mechanisms associated with PTB. Although several transcriptome studies have been done on the placenta and plasma from PTB women, a comprehensive description of the RNA profiles from plasma and placenta associated with PTB remains lacking. METHODS: Candidate markers with consistent trends in the placenta and plasma were identified by implementing differential expression analysis using placental tissue and maternal plasma RNA-seq datasets, and then validated by RT-qPCR in an independent cohort. In combination with bioinformatics analysis tools, we set up two protein-protein interaction networks of the significant PTB-related modules. The support vector machine (SVM) model was used to verify the prediction potential of cell free RNAs (cfRNAs) in plasma for PTB and late PTB. RESULTS: We identified 15 genes with consistent regulatory trends in placenta and plasma of PTB while the full term birth (FTB) acts as a control. Subsequently, we verified seven cfRNAs in an independent cohort by RT-qPCR in maternal plasma. The cfRNA ARHGEF28 showed consistence in the experimental validation and performed excellently in prediction of PTB in the model. The AUC achieved 0.990 for whole PTB and 0.986 for late PTB. CONCLUSIONS: In a comparison of PTB versus FTB, the combined investigation of placental and plasma RNA profiles has shown a further understanding of the mechanism of PTB. Then, the cfRNA identified has the capacity of predicting whole PTB and late PTB.

Digital PCR-based evaluation of nucleic acid extraction kit performance for the co-purification of cell-free DNA and RNA.

BACKGROUND: Blood plasma, one of the most studied liquid biopsies, contains various molecules that have biomarker potential for cancer detection, including cell-free DNA (cfDNA) and cell-free RNA (cfRNA). As the vast majority of cell-free nucleic acids in circulation are non-cancerous, a laboratory workflow with a high detection sensitivity of tumor-derived nucleic acids is a prerequisite for precision oncology. One way to meet this requirement is by the combined analysis of cfDNA and cfRNA from the same liquid biopsy sample. So far, no study has systematically compared the performance of cfDNA and cfRNA co-purification to increase sensitivity. RESULTS: First, we set up a framework using digital PCR (dPCR) technology to quantify cfDNA and cfRNA from human blood plasma in order to compare cfDNA/cfRNA co-purification kit performance. To that end, we optimized two dPCR duplex assays, designed to quantify both cfDNA and cfRNA with the same assays, by ensuring that primers and probes are located within a highly abundant exon. Next, we applied our optimized workflow to evaluate the co-purification performance of two manual and two semi-automated methods over a range of plasma input volumes (0.06-4 mL). Some kits result in higher nucleic acid concentrations in the eluate, while consuming only half of the plasma volume. The combined nucleic acid quantification systematically results in higher nucleic acid concentrations as compared to a parallel quantification of cfDNA and cfRNA in the eluate. CONCLUSIONS: We provide a framework to evaluate the performance of cfDNA/cfRNA co-purification kits and have tested two manual and two semi-automated co-purification kits in function of the available plasma input amount and the intended use of the nucleic acid eluate. We demonstrate that the combined quantification of cfDNA and cfRNA has a benefit compared to separate quantification. We foresee that the results of this study are instrumental for clinical applications to help increase mutation detection sensitivity, allowing improved disease detection and monitoring.

A comprehensive characterization of cell-free RNA in spent blastocyst medium and quality prediction for blastocyst.

The rate of pregnancy can be affected by many factors in assisted reproductive technology (ART), and one of which is the quality of embryos. Therefore, selecting the embryos with high potential is crucial for the outcome. Fifteen spent blastocyst medium (SBM) samples were collected from 14 patients who received in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI), seven from high-grade embryos and eight from low-grade embryos. Cell-free RNA (cf-RNA) profile of SBM samples were analyzed by RNA sequencing in the present study. It was found that a large amount of cf-RNA were released into SBM, including protein-coding genes (68.9%) and long noncoding RNAs (lncRNAs) (17.26%). Furthermore, a high correlation was observed between blastocyst genes and SBM genes. And the cf-mRNAs of SBM were highly fragmented, and coding sequence (CDS) and untranslated (UTR) regions were released equally. Two hundred and thirty-two differentially expressed genes were identified in high-grade SBM (hSBM) and low-grade SBM (lSBM), which could be potential biomarker in distinguishing the embryos with different quality as an alternative or supplementary approach for subjective morphology criteria. Hence, cf-RNAs sequencing revealed the characterization of circulating transcriptomes of embryos with different quality. Based on the results, the genes related to blastocyst quality were screened, including the genes closely related to translation, immune-signaling pathway, and amino acid metabolism. Overall, the present study showed the types of SBM cf-RNAs, and the integrated analysis of cf-RNAs profiling with morphology grading displayed its potential in predicting blastocyst quality. The present study provided valuable scientific basis for noninvasive embryo selection in ART by RNA-profiling analysis.

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.

Blood-based liquid biopsy: insights into early detection, prediction, and treatment monitoring of bladder cancer.

Bladder cancer (BC) is a clinical challenge worldwide with late clinical presentation, poor prognosis, and low survival rates. Traditional cystoscopy and tissue biopsy are routine methods for the diagnosis, prognosis, and monitoring of BC. However, due to the heterogeneity and limitations of tumors, such as aggressiveness, high cost, and limited applicability of longitudinal surveillance, the identification of tumor markers has attracted significant attention in BC. Over the past decade, liquid biopsies (e.g., blood) have proven to be highly efficient methods for the discovery of BC biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into the peripheral circulation and allows serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers are being extensively studied and have shown promising results in clinical applications of BC, including early detection, detection of microscopic residual disease, prediction of recurrence, and response to therapy. Therefore, in this review, we aim to provide an update on various novel blood-based liquid biopsy markers and review the advantages and current limitations of liquid biopsy in BC therapy. The role of blood-based circulating tumor cells, circulating tumor DNA, cell-free RNA, exosomes, metabolomics, and proteomics in diagnosis, prognosis, and treatment monitoring, and their applicability to the personalized management of BC, are highlighted.

Exploring the Role of Circulating Cell-Free RNA in the Development of Colorectal Cancer.

Circulating tumor RNA (ctRNA) has recently emerged as a novel and attractive liquid biomarker. CtRNA is capable of providing important information about the expression of a variety of target genes noninvasively, without the need for biopsies, through the use of circulating RNA sequencing. The overexpression of cancer-specific transcripts increases the tumor-derived RNA signal, which overcomes limitations due to low quantities of circulating tumor DNA (ctDNA). The purpose of this work is to present an up-to-date review of current knowledge regarding ctRNAs and their status as biomarkers to address the diagnosis, prognosis, prediction, and drug resistance of colorectal cancer. The final section of the article discusses the practical aspects involved in analyzing plasma ctRNA, including storage and isolation, detection technologies, and their limitations in clinical applications.

Predictive RNA profiles for early and very early spontaneous preterm birth.

BACKGROUND: Spontaneous preterm birth remains the main driver of childhood morbidity and mortality. Because of an incomplete understanding of the molecular pathways that result in spontaneous preterm birth, accurate predictive markers and target therapeutics remain elusive. OBJECTIVE: This study sought to determine if a cell-free RNA profile could reveal a molecular signature in maternal blood months before the onset of spontaneous preterm birth. STUDY DESIGN: Maternal samples (n=242) were obtained from a prospective cohort of individuals with a singleton pregnancy across 4 clinical sites at 12-24 weeks (nested case-control; n=46 spontaneous preterm birth <35 weeks and n=194 term controls). Plasma was processed via a next-generation sequencing pipeline for cell-free RNA using the Mirvie RNA platform. Transcripts that were differentially expressed in next-generation sequencing cases and controls were identified. Enriched pathways were identified in the Reactome database using overrepresentation analysis. RESULTS: Twenty five transcripts associated with an increased risk of spontaneous preterm birth were identified. A logistic regression model was developed using these transcripts to predict spontaneous preterm birth with an area under the curve =0.80 (95% confidence interval, 0.72-0.87) (sensitivity=0.76, specificity=0.72). The gene discovery and model were validated through leave-one-out cross-validation. A unique set of 39 genes was identified from cases of very early spontaneous preterm birth (<25 weeks, n=14 cases with time to delivery of 2.5±1.8 weeks); a logistic regression classifier on the basis of these genes yielded an area under the curve=0.76 (95% confidence interval, 0.63-0.87) in leave-one-out cross validation. Pathway analysis for the transcripts associated with spontaneous preterm birth revealed enrichment of genes related to collagen or the extracellular matrix in those who ultimately had a spontaneous preterm birth at <35 weeks. Enrichment for genes in insulin-like growth factor transport and amino acid metabolism pathways were associated with spontaneous preterm birth at <25 weeks. CONCLUSION: Second trimester cell-free RNA profiles in maternal blood provide a noninvasive window to future occurrence of spontaneous preterm birth. The systemic finding of changes in collagen and extracellular matrix pathways may serve to identify individuals at risk for premature cervical remodeling, with growth factor and metabolic pathways implicated more often in very early spontaneous preterm birth. The use of cell-free RNA profiles has the potential to accurately identify those at risk for spontaneous preterm birth by revealing the underlying pathophysiology, creating an opportunity for more targeted therapeutics and effective interventions.

RNA-Seq of amniotic fluid cell-free RNA: a discovery phase study of the pathophysiology of congenital cytomegalovirus infection.

BACKGROUND: Congenital cytomegalovirus infection is the most common perinatal infection and a significant cause of sensorineural hearing loss, cerebral palsy, and neurodevelopmental disability. There is a paucity of human gene expression studies examining the pathophysiology of cytomegalovirus infection. OBJECTIVE: This study aimed to perform a whole transcriptomic assessment of amniotic fluid from pregnancies with live fetuses to identify differentially expressed genes and enriched Gene Ontology categories associated with congenital cytomegalovirus infection. STUDY DESIGN: Amniotic fluid supernatant was prospectively collected from pregnant women undergoing amniocentesis for suspected congenital cytomegalovirus infection because of first-trimester maternal primary infection or ultrasound features suggestive of fetal infection. Women who had received therapy to prevent fetal infection were excluded. Congenital cytomegalovirus infection was diagnosed via viral polymerase chain reaction of amniotic fluid; cytomegalovirus-infected fetuses were paired with noninfected controls, matched for gestational age and fetal sex. Paired-end RNA sequencing was performed on amniotic fluid cell-free RNA with the Novaseq 6000 at a depth of 30 million reads per sample. Following quality control and filtering, reads were mapped to the human genome and counts summarized across genes. Differentially expressed genes were identified using 2 approaches: voomWithQualityWeights in conjunction with limma and RUVSeq with edgeR. Genes with a false discovery rate <0.05 were considered statistically significant. Differential exon use was analyzed using DEXSeq. Functional analysis was performed using gene set enrichment analysis and Ingenuity Pathway Analysis. Manual curation of differentially regulated genes was also performed. RESULTS: Amniotic fluid samples were collected from 50 women; 16 (32%) had congenital cytomegalovirus infection confirmed by polymerase chain reaction. After excluding 3 samples without matched controls, 13 cytomegalovirus-infected samples collected at 18 to 23 weeks and 13 cytomegalovirus-negative gestation-matched controls were submitted for RNA sequencing and analysis (N=26). Ten of the 13 pregnancies with cytomegalovirus-infected fetuses had amniocentesis because of serologic evidence of maternal primary infection with normal fetal ultrasound, and 3 had amniocentesis because of ultrasound abnormality suggestive of cytomegalovirus infection. Four cytomegalovirus-infected pregnancies ended in termination (n=3) or fetal death (n=1), and 9 resulted in live births. Pregnancy outcomes were available for 11 of the 13 cytomegalovirus-negative controls; all resulted in live births of clinically-well infants. Differential gene expression analysis revealed 309 up-regulated and 32 down-regulated genes in the cytomegalovirus-infected group compared with the cytomegalovirus-negative group. Gene set enrichment analysis showed significant enrichment of multiple Gene Ontology categories involving the innate immune response to viral infection and interferon signaling. Of the 32 significantly down-regulated genes, 8 were known to be involved in neurodevelopment and preferentially expressed by the brain. Six specific cellular restriction factors involved in host defense to cytomegalovirus infection were up-regulated in the cytomegalovirus-infected group. Ingenuity Pathway Analysis predicted the activation of pathways involved in progressive neurologic disease and inflammatory neurologic disease. CONCLUSION: In this next-generation sequencing study, we revealed new insights into the pathophysiology of congenital cytomegalovirus infection. These data on the up-regulation of the intraamniotic innate immune response to cytomegalovirus infection and the dysregulation of neurodevelopmental genes may inform future approaches to developing prognostic markers and assessing fetal responses to in utero therapy.

[Latest Research Findings on Prediction of Preeclampsia in Pregnant Women Based on Analysis of Cell-Free RNA in Peripheral Blood].

Preeclampsia gravely threatens the health of mothers and infants. At present, treatment based on the relevant mechanisms of pathogenesis is still not available, and there is no independent reliable clinical index for early prediction of preeclampsia. According to recent studies, analysis of the cell-free RNA in the peripheral blood of pregnant women has shown that testing certain cell-free RNA levels can help predict in advance the occurrence of preeclampsia before clinical symptoms appear. In this paper, we described the status of research and progress in using maternal cell-free RNA analysis in predicting preeclampsia. In addition, we stated that cell-free RNA in peripheral blood may become a promising, real-time and non-invasive monitoring method that can be used to explore the mechanisms of pathogenesis and pathophysiology of preeclampsia and to identify different subtypes of preeclampsia.

Cell-free DNA and RNA-measurement and applications in clinical diagnostics with focus on metabolic disorders.

Circulating cell-free DNA (cfDNA) and RNA (cfRNA) hold enormous potential as a new class of biomarkers for the development of noninvasive liquid biopsies in many diseases and conditions. In recent years, cfDNA and cfRNA have been studied intensely as tools for noninvasive prenatal testing, solid organ transplantation, cancer screening, and monitoring of tumors. In obesity, higher cfDNA concentration indicates accelerated cellular turnover of adipocytes during expansion of adipose mass and may be directly involved in the development of adipose tissue insulin resistance by inducing inflammation. Furthermore, cfDNA and cfRNA have promising diagnostic value in a range of obesity-related metabolic disorders, such as nonalcoholic fatty liver disease, type 2 diabetes, and diabetic complications. Here, we review the current and future applications of cfDNA and cfRNA within clinical diagnostics, discuss technical and analytical challenges in the field, and summarize the opportunities of using cfDNA and cfRNA in the diagnostics and prognostics of obesity-related metabolic disorders.

Highly sensitive fusion detection using plasma cell-free RNA in non-small-cell lung cancers.

ALK, ROS1, and RET kinase fusions are important predictive biomarkers of tyrosine kinase inhibitors (TKIs) in non-small-cell lung cancer (NSCLC). Analysis of cell-free DNA (cfDNA) provides a noninvasive method to identify gene changes in tumor cells. The present study sought to use cfRNA and cfDNA for identifying fusion genes. A reliable protocol was established to detect fusion genes using cfRNA and assessed the analytical validity and clinical usefulness in 30 samples from 20 cases of fusion-positive NSCLC. The results of cfRNA-based assays were compared with tissue biopsy and cfDNA-based liquid biopsy (Guardant360 plasma next-generation sequencing [NGS] assay). The overall sensitivity of the cfRNA-based assay was 26.7% (8/30) and that of cfDNA-based assay was 16.7% (3/18). When analysis was limited to the samples collected at chemo-naïve or progressive disease status and available for both assays, the sensitivity of the cfRNA-based assay was 77.8% (7/9) and that of cfDNA-based assay was 33.3% (3/9). Fusion gene identification in cfRNA was correlated with treatment response. These results suggest that the proposed cfRNA assay is a useful diagnostic test for patients with insufficient tissues to facilitate effective administration of first-line treatment and is a useful tool to monitor the progression of NSCLC for consideration of second-line treatments.

Integrative single-cell and cell-free plasma RNA transcriptomics elucidates placental cellular dynamics.

The human placenta is a dynamic and heterogeneous organ critical in the establishment of the fetomaternal interface and the maintenance of gestational well-being. It is also the major source of cell-free fetal nucleic acids in the maternal circulation. Placental dysfunction contributes to significant complications, such as preeclampsia, a potentially lethal hypertensive disorder during pregnancy. Previous studies have identified significant changes in the expression profiles of preeclamptic placentas using whole-tissue analysis. Moreover, studies have shown increased levels of targeted RNA transcripts, overall and placental contributions in maternal cell-free nucleic acids during pregnancy progression and gestational complications, but it remains infeasible to noninvasively delineate placental cellular dynamics and dysfunction at the cellular level using maternal cell-free nucleic acid analysis. In this study, we addressed this issue by first dissecting the cellular heterogeneity of the human placenta and defined individual cell-type-specific gene signatures by analyzing more than 24,000 nonmarker selected cells from full-term and early preeclamptic placentas using large-scale microfluidic single-cell transcriptomic technology. Our dataset identified diverse cellular subtypes in the human placenta and enabled reconstruction of the trophoblast differentiation trajectory. Through integrative analysis with maternal plasma cell-free RNA, we resolved the longitudinal cellular dynamics of hematopoietic and placental cells in pregnancy progression. Furthermore, we were able to noninvasively uncover the cellular dysfunction of extravillous trophoblasts in early preeclamptic placentas. Our work showed the potential of integrating transcriptomic information derived from single cells into the interpretation of cell-free plasma RNA, enabling the noninvasive elucidation of cellular dynamics in complex pathological conditions.

Viral evolution in the cell-associated HIV-1 DNA during early ART can lead to drug resistance and virological failure in children.

Using cell-associated DNA and cell-free RNA of human immunodeficiency virus type-1 (HIV-1), we investigated the role of drug-resistant viral variants that emerged during early antiretroviral therapy (ART) in determining virological outcome. This case-control study compared virologic nonresponder children (two viral loads [VLs] ≥ 200 copies/mL within 2 years of ART) and responder children (two VLs < 200 copies/mL after six months of ART) infected with HIV-1 initiated on nonnucleoside reverse-transcriptase inhibitor (NNRTI)-based ART. The partial reverse-transcriptase gene of HIV-1 in cell-associated DNA was genotyped using next-generation sequencing (NGS; Illumina; threshold 0.5%; at baseline and month six of ART) and in cell-free RNA (concurrently and at virological failure; VL > 1000 copies/mL at ≥ 12 months of ART) using the Sanger method. Among 30 nonresponders and 37 responders, baseline differences were insignificant while adherence, VL, and drug resistance mutations (DRMs) observed at month six differed significantly ( P ≥ 0.05). At month six, NGS estimated a higher number of DRMs compared with Sanger (50% vs 33%; P = 0.001). Among the nonresponders carrying a resistant virus (86.6%) at virological failure, 26% harbored clinically relevant low-frequency DRMs in the cell-associated DNA at month six (0.5%-20%; K103N, G190A, Y181C, and M184I). Plasma VL of > 3 log 10 copies/mL (AOR, 30.4; 95% CI, 3.3-281; P = 0.003) and treatment-relevant DRMs detected in the cell-associated DNA at month six (AOR, 24.2; 95% CI, 2.6-221; P = 0.005) were independently associated with increased risk for early virological failure. Our findings suggest that treatment-relevant DRMs acquired in cell-associated DNA during the first six months of ART can predict virological failure in children initiated on NNRTI-based ART.

Circulating tumor cell and cell-free RNA capture and expression analysis identify platelet-associated genes in metastatic lung cancer.

BACKGROUND: Circulating tumor cells (CTC) and plasma cell-free RNA (cfRNA) can serve as biomarkers for prognosis and treatment response in lung cancer. One barrier to the selected or routine use of CTCs and plasma cfRNA in precision oncology is the limited quantity of both, and CTCs are only seen in metastatic disease. As capture of CTCs and plasma cfRNA presents an opportunity to monitor and assess malignancies without invasive procedures, we compared two methods for CTC capture and identification, and profiled mRNA from CTCs and plasma cfRNA to identify potential tumor-associated biomarkers. METHODS: Peripheral blood was collected from ten patients with small cell lung cancer (SCLC), ten patients with non-small cell lung cancer (NSCLC) and four healthy volunteers. Two methods were used for CTC capture: the standard epithelial cell adhesion molecule (EpCam) CellSearch kit (unicapture) and EpCAM plus HER2, EGFR and MUC-1 specific combined ferrofluid capture (quadcapture). For the quadcapture, anti-cytokeratin 7 (CK7) was additionally used to assist in CTC identification. NanoString analysis was performed on plasma cfRNA and on mRNA from combined ferrofluid isolated CTCs. Expression data was analyzed using STRING and Reactome. RESULTS: Unicapture detected CTCs in 40% of NSCLC and 60% of SCLC; whereas, quadcapture/CK7 identified CTCs in 20% of NSCLC and 80% of SCLC. Bioinformatic analysis of NanoString data identified high expression of a platelet factor 4 (PF4)-related group of transcripts. CONCLUSIONS: Quadcapture ferrofluid reagent did not significantly improve CTC capture efficacy. NanoString analysis based on CTC and plasma cfRNA data highlighted an intriguing PF-4-centric network in patients with metastatic lung cancer.