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.

mRNA Capture Sequencing and RT-qPCR for the Detection of Pathognomonic, Novel, and Secondary Fusion Transcripts in FFPE Tissue: A Sarcoma Showcase.

We assess the performance of mRNA capture sequencing to identify fusion transcripts in FFPE tissue of different sarcoma types, followed by RT-qPCR confirmation. To validate our workflow, six positive control tumors with a specific chromosomal rearrangement were analyzed using the TruSight RNA Pan-Cancer Panel. Fusion transcript calling by FusionCatcher confirmed these aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole-transcriptome TruSeq RNA Exome sequencing was applied to 17 fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS) tumors, for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. For six patients, a pathognomonic fusion transcript was readily detected, i.e., PAX3-FOXO1 in two ARMS patients, and EWSR1-FLI1, EWSR1-ERG, or EWSR1-NFATC2 in four URCS patients. For the 11 remaining patients, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2, and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53, and UBE2F-ALS2). In conclusion, this study shows that mRNA capture sequencing enhances the detection rate of pathognomonic fusions and enables the identification of novel and secondary fusion transcripts in sarcomas.

Long noncoding RNA expression profiling in cancer: Challenges and opportunities.

In recent years, technological advances in transcriptome profiling revealed that the repertoire of human RNA molecules is more diverse and extended than originally thought. This diversity and complexity mainly derive from a large ensemble of noncoding RNAs. Because of their key roles in cellular processes important for normal development and physiology, disruption of noncoding RNA expression is intrinsically linked to human disease, including cancer. Therefore, studying the noncoding portion of the transcriptome offers the prospect of identifying novel therapeutic and diagnostic targets. Although evidence of the relevance of noncoding RNAs in cancer is accumulating, we still face many challenges when it comes to accurately profiling their expression levels. Some of these challenges are inherent to the technologies employed, whereas others are associated with characteristics of the noncoding RNAs themselves. In this review, we discuss the challenges related to long noncoding RNA expression profiling, highlight how cancer long noncoding RNAs provide new opportunities for cancer diagnosis and treatment, and reflect on future developments.

Subpar reporting of pre-analytical variables in RNA-focused blood plasma studies.

Extracellular RNA (cell-free RNA; exRNA) from blood-derived liquid biopsies is an appealing, minimally invasive source of disease biomarkers. As pre-analytical variables strongly influence exRNA measurements, their reporting is essential for meaningful interpretation and replication of results. The aim of this review was to chart to what extent pre-analytical variables are documented, to pinpoint shortcomings and to improve future reporting. In total, 200 blood plasma exRNA studies published in 2018 or 2023 were reviewed for annotation of 22 variables associated with blood collection, plasma preparation, and RNA purification. Our results show that pre-analytical variables are poorly documented, with only three out of 22 variables described in over half of the publications. The percentage of variables reported ranged from 4.6% to 54.6% (mean 24.84%) in 2023 and from 4.6% to 57.1% (mean 28.60%) in 2018. Recommendations and guidelines (i.e., BRISQ, ASCO-CAP, BloodPAC, PPMPT, and CEN standards) have currently not resulted in improved reporting. In conclusion, our results highlight the lack of reporting pre-analytical variables in exRNA studies and advocate for a consistent use of available standards, endorsed by funders and journals.

Benchmarking blood collection tubes and processing intervals for extracellular vesicle performance metrics.

The analysis of extracellular vesicles (EV) in blood samples is under intense investigation and holds the potential to deliver clinically meaningful biomarkers for health and disease. Technical variation must be minimized to confidently assess EV-associated biomarkers, but the impact of pre-analytics on EV characteristics in blood samples remains minimally explored. We present the results from the first large-scale EV Blood Benchmarking (EVBB) study in which we systematically compared 11 blood collection tubes (BCT; six preservation and five non-preservation) and three blood processing intervals (BPI; 1, 8 and 72 h) on defined performance metrics (n = 9). The EVBB study identifies a significant impact of multiple BCT and BPI on a diverse set of metrics reflecting blood sample quality, ex-vivo generation of blood-cell derived EV, EV recovery and EV-associated molecular signatures. The results assist the informed selection of the optimal BCT and BPI for EV analysis. The proposed metrics serve as a framework to guide future research on pre-analytics and further support methodological standardization of EV studies.

Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models enables specific monitoring of tumour-derived extracellular RNA.

While cell-free DNA (cfDNA) is widely being investigated, free circulating RNA (extracellular RNA, exRNA) has the potential to improve cancer therapy response monitoring and detection due to its dynamic nature. However, it remains unclear in which blood subcompartment tumour-derived exRNAs primarily reside. We developed a host-xenograft deconvolution framework, exRNAxeno, with mapping strategies to either a combined human-mouse reference genome or both species genomes in parallel, applicable to exRNA sequencing data from liquid biopsies of human xenograft mouse models. The tool enables to distinguish (human) tumoural RNA from (murine) host RNA, to specifically analyse tumour-derived exRNA. We applied the combined pipeline to total exRNA sequencing data from 95 blood-derived liquid biopsy samples from 30 mice, xenografted with 11 different tumours. Tumoural exRNA concentrations are not determined by plasma platelet levels, while host exRNA concentrations increase with platelet content. Furthermore, a large variability in exRNA abundance and transcript content across individual mice is observed. The tumoural gene detectability in plasma is largely correlated with the RNA expression levels in the tumour tissue or cell line. These findings unravel new aspects of tumour-derived exRNA biology in xenograft models and open new avenues to further investigate the role of exRNA in cancer.

Messenger RNA capture sequencing of extracellular RNA from human biofluids using a comprehensive set of spike-in controls.

Comprehensive transcriptome analysis of extracellular RNA (exRNA) purified from human biofluids is challenging because of the low RNA concentration and compromised RNA integrity. Here, we describe an optimized workflow to (1) isolate exRNA from different types of biofluids and (2) to prepare messenger RNA (mRNA)-enriched sequencing libraries using complementary hybridization probes. Importantly, the workflow includes 2 sets of synthetic spike-in RNA molecules as processing controls for RNA purification and sequencing library preparation and as an alternative data normalization strategy. For complete details on the use and execution of this protocol, please refer to Hulstaert et al. (2020).

Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles.

RNA profiling has emerged as a powerful tool to investigate the biomarker potential of human biofluids. However, despite enormous interest in extracellular nucleic acids, RNA sequencing methods to quantify the total RNA content outside cells are rare. Here, we evaluate the performance of the SMARTer Stranded Total RNA-Seq method in human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. We found the method to be accurate, precise, compatible with low-input volumes and able to quantify a few thousand genes. We picked up distinct classes of RNA molecules, including mRNA, lncRNA, circRNA, miscRNA and pseudogenes. Notably, the read distribution and gene content drastically differ among biofluids. In conclusion, we are the first to show that the SMARTer method can be used for unbiased unraveling of the complete transcriptome of a wide range of biofluids and their extracellular vesicles.

Circulating microRNA biomarkers for metastatic disease in neuroblastoma patients.

In this study, the circulating miRNome from diagnostic neuroblastoma serum was assessed for identification of noninvasive biomarkers with potential in monitoring metastatic disease. After determining the circulating neuroblastoma miRNome, 743 miRNAs were screened in 2 independent cohorts of 131 and 54 patients. Evaluation of serum miRNA variance in a model testing for tumor stage, MYCN status, age at diagnosis, and overall survival revealed tumor stage as the most significant factor impacting miRNA abundance in neuroblastoma serum. Differential abundance analysis between patients with metastatic and localized disease revealed 9 miRNAs strongly associated with metastatic stage 4 disease in both patient cohorts. Increasing levels of these miRNAs were also observed in serum from xenografted mice bearing human neuroblastoma tumors. Moreover, murine serum miRNA levels were strongly associated with tumor volume. These findings were validated in longitudinal serum samples from metastatic neuroblastoma patients, where the 9 miRNAs were associated with disease burden and treatment response.

DNA methylation profiling of primary neuroblastoma tumors using methyl-CpG-binding domain sequencing.

Comprehensive genome-wide DNA methylation studies in neuroblastoma (NB), a childhood tumor that originates from precursor cells of the sympathetic nervous system, are scarce. Recently, we profiled the DNA methylome of 102 well-annotated primary NB tumors by methyl-CpG-binding domain (MBD) sequencing, in order to identify prognostic biomarker candidates. In this data descriptor, we give details on how this data set was generated and which bioinformatics analyses were applied during data processing. Through a series of technical validations, we illustrate that the data are of high quality and that the sequenced fragments represent methylated genomic regions. Furthermore, genes previously described to be methylated in NB are confirmed. As such, these MBD sequencing data are a valuable resource to further study the association of NB risk factors with the NB methylome, and offer the opportunity to integrate methylome data with other -omic data sets on the same tumor samples such as gene copy number and gene expression, also publically available.

Stage 4S neuroblastoma tumors show a characteristic DNA methylation portrait.

Stage 4S neuroblastoma (NB) is a special type of NB found in infants with metastases at diagnosis and is associated with an excellent outcome due to its remarkable capacity to undergo spontaneous regression. As genomics have not been able to explain this intriguing clinical presentation, we here aimed at profiling the DNA methylome of stage 4S NB to better understand this phenomenon. To this purpose, differential methylation analyses between International Neuroblastoma Staging System (INSS) stage 4S, stage 4 and stage 1/2 were performed, using methyl-CpG-binding domain (MBD) sequencing data of 14 stage 4S, 14 stage 4, and 13 stage 1/2 primary NB tumors (all MYCN non-amplified in order not to confound results). Stage 4S-specific hyper- and hypomethylated promoters were determined and further characterized for genomic localization and function by cytogenetic band enrichment, gene set enrichment, transcription factor target enrichment and differential RNA expression analyses. We show that specific chromosomal locations are enriched for stage 4S differentially methylated promoters and that stage 4S tumors show characteristic hypermethylation of specific subtelomeric promoters. Furthermore, genes involved in important oncogenic pathways, in neural crest development and differentiation, and in epigenetic processes are differentially methylated and expressed in stage 4S tumors. Based on these findings, we describe new biological mechanisms possibly contributing to the stage 4S-specific tumor biology and spontaneous regression. In conclusion, this study is the first to describe the highly characteristic stage 4S DNA methylome. These findings will open new avenues to further unravel the NB pathology in general and stage 4S disease specifically.

Methyl-CpG-binding domain sequencing reveals a prognostic methylation signature in neuroblastoma.

Accurate assessment of neuroblastoma outcome prediction remains challenging. Therefore, this study aims at establishing novel prognostic tumor DNA methylation biomarkers. In total, 396 low- and high-risk primary tumors were analyzed, of which 87 were profiled using methyl-CpG-binding domain (MBD) sequencing for differential methylation analysis between prognostic patient groups. Subsequently, methylation-specific PCR (MSP) assays were developed for 78 top-ranking differentially methylated regions and tested on two independent cohorts of 132 and 177 samples, respectively. Further, a new statistical framework was used to identify a robust set of MSP assays of which the methylation score (i.e. the percentage of methylated assays) allows accurate outcome prediction. Survival analyses were performed on the individual target level, as well as on the combined multimarker signature. As a result of the differential DNA methylation assessment by MBD sequencing, 58 of the 78 MSP assays were designed in regions previously unexplored in neuroblastoma, and 36 are located in non-promoter or non-coding regions. In total, 5 individual MSP assays (located in CCDC177, NXPH1, lnc-MRPL3-2, lnc-TREX1-1 and one on a region from chromosome 8 with no further annotation) predict event-free survival and 4 additional assays (located in SPRED3, TNFAIP2, NPM2 and CYYR1) also predict overall survival. Furthermore, a robust 58-marker methylation signature predicting overall and event-free survival was established. In conclusion, this study encompasses the largest DNA methylation biomarker study in neuroblastoma so far. We identified and independently validated several novel prognostic biomarkers, as well as a prognostic 58-marker methylation signature.

MYCN and HDAC5 transcriptionally repress CD9 to trigger invasion and metastasis in neuroblastoma.

The systemic and resistant nature of metastatic neuroblastoma renders it largely incurable with current multimodal treatment. Clinical progression stems mainly from the increasing burden of metastatic colonization. Therapeutically inhibiting the migration-invasion-metastasis cascade would be of great benefit, but the mechanisms driving this cycle are as yet poorly understood. In-depth transcriptome analyses and ChIP-qPCR identified the cell surface glycoprotein, CD9, as a major downstream player and direct target of the recently described GRHL1 tumor suppressor. CD9 is known to block or facilitate cancer cell motility and metastasis dependent upon entity. High-level CD9 expression in primary neuroblastomas correlated with patient survival and established markers for favorable disease. Low-level CD9 expression was an independent risk factor for adverse outcome. MYCN and HDAC5 colocalized to the CD9 promoter and repressed transcription. CD9 expression diminished with progressive tumor development in the TH-MYCN transgenic mouse model for neuroblastoma, and CD9 expression in neuroblastic tumors was far below that in ganglia from wildtype mice. Primary neuroblastomas lacking MYCN amplifications displayed differential CD9 promoter methylation in methyl-CpG-binding domain sequencing analyses, and high-level methylation was associated with advanced stage disease, supporting epigenetic regulation. Inducing CD9 expression in a SH-EP cell model inhibited migration and invasion in Boyden chamber assays. Enforced CD9 expression in neuroblastoma cells transplanted onto chicken chorioallantoic membranes strongly reduced metastasis to embryonic bone marrow. Combined treatment of neuroblastoma cells with HDAC/DNA methyltransferase inhibitors synergistically induced CD9 expression despite hypoxic, metabolic or cytotoxic stress. Our results show CD9 is a critical and indirectly druggable suppressor of the invasion-metastasis cycle in neuroblastoma.

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers.

BACKGROUND: Accurate outcome prediction in neuroblastoma, which is necessary to enable the optimal choice of risk-related therapy, remains a challenge. To improve neuroblastoma patient stratification, this study aimed to identify prognostic tumor DNA methylation biomarkers. RESULTS: To identify genes silenced by promoter methylation, we first applied two independent genome-wide methylation screening methodologies to eight neuroblastoma cell lines. Specifically, we used re-expression profiling upon 5-aza-2'-deoxycytidine (DAC) treatment and massively parallel sequencing after capturing with a methyl-CpG-binding domain (MBD-seq). Putative methylation markers were selected from DAC-upregulated genes through a literature search and an upfront methylation-specific PCR on 20 primary neuroblastoma tumors, as well as through MBD- seq in combination with publicly available neuroblastoma tumor gene expression data. This yielded 43 candidate biomarkers that were subsequently tested by high-throughput methylation-specific PCR on an independent cohort of 89 primary neuroblastoma tumors that had been selected for risk classification and survival. Based on this analysis, methylation of KRT19, FAS, PRPH, CNR1, QPCT, HIST1H3C, ACSS3 and GRB10 was found to be associated with at least one of the classical risk factors, namely age, stage or MYCN status. Importantly, HIST1H3C and GNAS methylation was associated with overall and/or event-free survival. CONCLUSIONS: This study combines two genome-wide methylation discovery methodologies and is the most extensive validation study in neuroblastoma performed thus far. We identified several novel prognostic DNA methylation markers and provide a basis for the development of a DNA methylation-based prognostic classifier in neuroblastoma.

Neuroblastoma epigenetics: from candidate gene approaches to genome-wide screenings.

Neuroblastoma (NB) is a childhood tumor originating from sympathetic nervous system cells. Although recently new insights into genes involved in NB have emerged, the molecular basis of neuroblastoma development and progression still remains poorly understood. The best-characterized genetic alterations include amplification of the proto-oncogene MYCN, ALK activating mutations or amplification, gain of chromosome arm 17q and losses of 1p, 3p, and 11q. Epigenetic alterations have been described as well: caspase-8 (CASP8) and RAS-association domain family 1 isoform A (RASSF1A) DNA-methylation are important events for the development and progression of neuroblastoma. In total, there are about 75 genes described as epigenetically affected in NB cell lines and/or NB primary samples. These epigenetic alterations were either found using a candidate gene approach or based on the analysis of genome-wide screening techniques. This review gives an extensive overview of all epigenetic changes described in NB as of today, with a main focus on both prognostic use and the potential of genome-wide techniques to find epigenetic prognostic biomarkers in NB. We summarize the key findings so far and the state-of-the-art of the upcoming methods at a unique time frame in the transition towards combined genome wide chromatin immune-precipitation (ChIP) and DNA sequencing techniques.