TAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting

Recent Technologies towards Diagnostic and Therapeutic Applications of Circulating Nucleic Acids in Colorectal Cancers

Liquid biopsy has emerged as a promising noninvasive approach for colorectal cancer (CRC) management. This review focuses on technologies detecting circulating nucleic acids, specifically circulating tumor DNA (ctDNA) and circulating RNA (cfRNA), as CRC biomarkers. Recent advancements in molecular technologies have enabled sensitive and specific detection of tumor-derived genetic material in bodily fluids. These include quantitative real-time PCR, digital PCR, next-generation sequencing (NGS), and emerging nanotechnology-based methods. For ctDNA analysis, techniques such as BEAMing and droplet digital PCR offer high sensitivity in detecting rare mutant alleles, while NGS approaches provide comprehensive genomic profiling. cfRNA detection primarily utilizes qRT-PCR arrays, microarray platforms, and RNA sequencing for profiling circulating microRNAs and discovering novel RNA biomarkers. These technologies show potential in early CRC detection, treatment response monitoring, minimal residual disease assessment, and tumor evolution tracking. However, challenges remain in standardizing procedures, optimizing detection limits, and establishing clinical utility across disease stages. This review summarizes current circulating nucleic acid detection technologies, their CRC applications, and discusses future directions for clinical implementation.

The endometrial transcriptome of infertile women with and without implantation failure

INTRODUCTION

Implantation failure after transferring morphologically "good-quality" embryos in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) may be explained by impaired endometrial receptivity. Analyzing the endometrial transcriptome analysis may reveal the underlying processes and could help in guiding prognosis and using targeted interventions for infertility. This exploratory study investigated whether the endometrial transcriptome profile was associated with short-term or long-term implantation outcomes (ie success or failure).

MATERIAL AND METHODS

Mid-luteal phase endometrial biopsies of 107 infertile women with one full failed IVF/ICSI cycle, obtained within an endometrial scratching trial, were subjected to RNA-sequencing and differentially expressed genes analysis with covariate adjustment (age, body mass index, luteinizing hormone [LH]-day). Endometrial transcriptomes were compared between implantation failure and success groups in the short term (after the second fresh IVF/ICSI cycle) and long term (including all fresh and frozen cycles within 12 months). The short-term analysis included 85/107 women (33 ongoing pregnancy vs 52 no pregnancy), excluding 22/107 women. The long-term analysis included 46/107 women (23 'fertile' group, ie infertile women with a live birth after ≤3 embryos transferred vs 23 recurrent implantation failure group, ie no live birth after ≥3 good quality embryos transferred), excluding 61/107 women not fitting these categories. As both analyses drew from the same pool of 107 samples, there was some sample overlap. Additionally, cell type enrichment scores and endometrial receptivity were analyzed, and an endometrial development pseudo-timeline was constructed to estimate transcriptomic deviations from the optimum receptivity day (LH + 7), denoted as ΔWOI (window of implantation).

RESULTS

There were no significantly differentially expressed genes between implantation failure and success groups in either the short-term or long-term analyses. Principal component analysis initially showed two clusters in the long-term analysis, unrelated to clinical phenotype and no longer distinct following covariate adjustment. Cell type enrichment scores did not differ significantly between groups in both analyses. However, endometrial receptivity analysis demonstrated a potentially significant displacement of the WOI in the non-pregnant group compared with the ongoing pregnant group in the short-term analysis.

CONCLUSIONS

No distinct endometrial transcriptome profile was associated with either implantation failure or success in infertile women. However, there may be differences in the extent to which the WOI is displaced.

Integrated small RNA, transcriptome and physiological approaches provide insight into Taxodium hybrid 'Zhongshanshan' roots in acclimation to prolonged flooding

Although Taxodium hybrid 'Zhongshanshan' 406 (Taxodium mucronatum Tenore × Taxodium distichum; Taxodium 406) is an extremely flooding-tolerant woody plant, the physiological and molecular mechanisms underlying acclimation of its roots to long-term flooding remain largely unknown. Thus, we exposed saplings of Taxodium 406 to either non-flooding (control) or flooding for 2 months. Flooding resulted in reduced root biomass, which is in line with lower concentrations of citrate, α-ketoglutaric acid, fumaric acid, malic acid and adenosine triphosphate (ATP) in Taxodium 406 roots. Flooding led to elevated activities of pyruvate decarboxylase, alcohol dehydrogenase and lactate dehydrogenase, which is consistent with higher lactate concentration in the roots of Taxodium 406. Flooding brought about stimulated activities of superoxide dismutase and catalase and elevated reduced glutathione (GSH) concentration and GSH/oxidized glutathione, which is in agreement with reduced concentrations of O2- and H2O2 in Taxodium 406 roots. The levels of starch, soluble protein, indole-3-acetic acid, gibberellin A4 and jasmonate were decreased, whereas the concentrations of glucose, total non-structural carbohydrates, most amino acids and 1-aminocyclopropane-1-carboxylate (ACC) were improved in the roots of flooding-treated Taxodium 406. Underlying these changes in growth and physiological characteristics, 12,420 mRNAs and 42 miRNAs were significantly differentially expressed, and 886 miRNA-mRNA pairs were identified in the roots of flooding-exposed Taxodium 406. For instance, 1-aminocyclopropane-1-carboxylate synthase 8 (ACS8) was a target of Th-miR162-3p and 1-aminocyclopropane-1-carboxylate oxidase 4 (ACO4) was a target of Th-miR166i, and the downregulation of Th-miR162-3p and Th-miR166i results in the upregulation of ACS8 and ACO4, probably bringing about higher ACC content in flooding-treated roots. Overall, these results indicate that differentially expressed mRNA and miRNAs are involved in regulating tricarboxylic acid cycle, ATP production, fermentation, and metabolism of carbohydrates, amino acids and phytohormones, as well as reactive oxygen species detoxification of Taxodium 406 roots. These processes play pivotal roles in acclimation to flooding stress. These results will improve our understanding of the molecular and physiological bases underlying woody plant flooding acclimation and provide valuable insights into breeding-flooding tolerant trees.

Immunotherapy-related biomarkers: Confirmations and uncertainties

Immunotherapy profoundly changed oncology treatment, becoming one of the main therapeutical strategies. Remarkable improvement has been achieved in survival outcomes, but the percentage of patients who benefit from immunotherapy is still limited. Only one-third of patients receiving immune checkpoint inhibitors (ICIs) achieve long-term response. Several patients are not responsive to treatment or relapse after an initial response. To date, programmed death-ligand 1, microsatellite instability, and tumor mutational burden are the three biomarkers validated to predict the ICIs response, but a single variable seems still insufficient in the patient's selection. Considering the substantial and increasing use of these drugs, the identification of new predictive biomarkers of ICI response is of paramount importance. We summarize the state of the art and the clinical use of immune biomarkers in oncology, highlighting the strength and weaknesses of currently approved biomarkers, describing the emerging tissues and circulating biomarkers, and outlining future perspectives.

Single-Nucleus RNA-Seq: Open the Era of Great Navigation for FFPE Tissue

Single-cell sequencing (scRNA-seq) has revolutionized our ability to explore heterogeneity and genetic variations at the single-cell level, opening up new avenues for understanding disease mechanisms and cell-cell interactions. Single-nucleus RNA-sequencing (snRNA-seq) is emerging as a promising solution to scRNA-seq due to its reduced ionized transcription bias and compatibility with richer samples. This approach will provide an exciting opportunity for in-depth exploration of billions of formalin-fixed paraffin-embedded (FFPE) tissues. Recent advancements in single-cell/nucleus gene expression workflows tailored for FFPE tissues have demonstrated their feasibility and provided crucial guidance for future studies utilizing FFPE specimens. In this review, we provide a broad overview of the nuclear preparation strategies, the latest technologies of snRNA-seq applicable to FFPE samples. Finally, the limitations and potential technical developments of snRNA-seq in FFPE samples are summarized. The development of snRNA-seq technologies for FFPE samples will lay a foundation for transcriptomic studies of valuable samples in clinical medicine and human sample banks.

Targeted gene expression profiling for accurate endometrial receptivity testing

Expressional profiling of the endometrium enables the personalised timing of the window of implantation (WOI). This study presents and evaluates a novel analytical pipeline based on a TAC-seq (Targeted Allele Counting by sequencing) method for endometrial dating. The expressional profiles were clustered, and differential expression analysis was performed on the model development group, using 63 endometrial biopsies spanning over proliferative (PE, n = 18), early-secretory (ESE, n = 18), mid-secretory (MSE, n = 17) and late-secretory (LSE, n = 10) endometrial phases of the natural cycle. A quantitative predictor model was trained on the development group and validated on sequenced samples from healthy women, consisting of 52 paired samples taken from ESE and MSE phases and five LSE phase samples from 31 individuals. Finally, the developed test was applied to 44 MSE phase samples from a study group of patients diagnosed with recurrent implantation failure (RIF). In validation samples (n = 57), we detected displaced WOI in 1.8% of the samples from fertile women. In the RIF study group, we detected a significantly higher proportion of the samples with shifted WOI than in the validation set of samples from fertile women, 15.9% and 1.8% (p = 0.012), respectively. The developed model was evaluated with an average cross-validation accuracy of 98.8% and an accuracy of 98.2% in the validation group. The developed beREADY screening model enables sensitive and dynamic detection of selected transcriptome biomarkers, providing a quantitative and accurate prediction of endometrial receptivity status.

PHDs-seq: a large-scale phenotypic screening method for drug discovery through parallel multi-readout quantification

High-throughput phenotypic screening is a cornerstone of drug development and the main technical approach for stem cell research. However, simultaneous detection of activated core factors responsible for cell fate determination and accurate assessment of directional cell transition are difficult using conventional screening methods that focus on changes in only a few biomarkers. The PHDs-seq (Probe Hybridization based Drug screening by sequencing) platform was developed to evaluate compound function based on their transcriptional effects in a wide range of signature biomarkers. In this proof-of-concept demonstration, several sets of markers related to cell fate determination were profiled in adipocyte reprogramming from dermal fibroblasts. After validating the accuracy, sensitivity and reproducibility of PHDs-seq data in molecular and cellular assays, a panel of 128 signalling-related compounds was screened for the ability to induce reprogramming of keloid fibroblasts (KF) into adipocytes. Notably, the potent ATP-competitive VEGFR/PDGFR inhibitor compound, ABT869, was found to promote the transition from fibroblasts to adipocytes. This study highlights the power and accuracy of the PHDs-seq platform for high-throughput drug screening in stem cell research, and supports its use in basic explorations of the molecular mechanisms underlying disease development.

Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.

TORNADO-seq: A Protocol for High-Throughput Targeted RNA-seq-Based Drug Screening in Organoids

Organoids are 3D ex vivo cell aggregates derived from primary tissue and shown to closely recapitulate tissue homeostasis. Organoids deliver certain advantages compared to 2D cell lines and mouse models, especially in drug-screening studies and translational research projects. The application of organoids in the research field is fast-emerging and new techniques for organoid manipulation are constantly developing. Despite recent advances, RNA-seq-based drug-screening platforms in organoids are not yet established. Here, we provide a detailed protocol for performing TORNADO-seq, a targeted RNA-seq-based drug-screening method in organoids. Analyzing complex phenotypes with a large number of carefully selected read-outs allows to directly classify and group drugs even without structural similarity or overlapping mode of actions from prior knowledge. Our assay principle combines cost-effectiveness and sensitive detection of multiple cell identities, signaling pathways, and key drivers of cellular phenotypes and can be applied to many systems where this new form of high-content screening can provide information not obtainable otherwise.

Commercially Available Molecular Approaches to Evaluate Endometrial Receptivity: A Systematic Review and Critical Analysis of the Literature

Despite the advances in the field of reproductive medicine, implantation failure represents a challenging condition affecting 10-30% of patients subjected to in vitro fertilization (IVF). Research has focused on the identification of molecules playing crucial roles in endometrial receptivity, with the aim of designing predictive tools for efficient detection of the implantation window. To that end, novel molecular genomic and transcriptomic approaches have been introduced as promising tools to enable personalized approaches with the aim of optimizing embryo transfer dating. However, the clinical value of these approaches remains unclear. The aim of this study is to provide a systematic review and critical analysis of the existing evidence regarding the employment of commercially available novel approaches to evaluate endometrial receptivity. An Embase and PubMed/Medline search was performed on 1 February 2022. From the 475 articles yielded, only 27 were included and analyzed. The considerable heterogeneity of the included articles indicates the uniqueness of the implantation window, showcasing that the optimal time for embryo transfer varies significantly between women. Moreover, this study provides information regarding the technical aspects of these advanced molecular tools, as well as an analysis of novel possible biomarkers for endometrial receptivity, providing a basis for future research in the field.

Interaction between endometrial microbiota and host gene regulation in recurrent implantation failure

AIM

To learn about the interaction between endometrial microbiota and host gene regulation in recurrent implantation failure.

METHODS

The endometrial microbiota of 111 patients (RIF, 75; CON, 36) was analyzed by using 16 s rRNA sequencing technology. Transcriptome sequencing analysis of the endometrial of 60 patients was performed by using high-throughput sequencing.

RESULTS

We found that the structure and composition of endometrium microbiota community of RIF patients were significantly different from those in control group. The abnormality of microbial structure and composition might interfere with the implantation of embryos by affecting the immune adaptation of the endometrium and the formation of endometrial blood vessels.

CONCLUSIONS

Our research described the host-microbe interaction in RIF. The structure and composition of endometrium microbiota community of RIF patients were significantly different from those in CON group. The abnormality of microbial structure and composition might interfere with the implantation of embryos by affecting the immune adaptation of the endometrium and the formation of endometrial blood vessels.

Transcriptomics of receptive endometrium in women with sonographic features of adenomyosis

BACKGROUND

Women with uterine adenomyosis seeking assisted reproduction have been associated with compromised endometrial receptivity to embryo implantation. To understand the mechanisms involved in this process, we aimed to compare endometrial transcriptome profiles during the window of implantation (WOI) between women with and without adenomyosis.

METHODS

We obtained endometrial biopsies LH-timed to the WOI from women with sonographic features of adenomyosis (n=10) and controls (n=10). Isolated RNA samples were subjected to RNA sequencing (RNA-seq) by the Illumina NovaSeq 6000 platform and endometrial receptivity classification with a molecular tool for menstrual cycle phase dating (beREADY®, CCHT). The program language R and Bioconductor packages were applied to analyse RNA-seq data in the setting of the result of accurate endometrial dating. To suggest robust candidate pathways, the identified differentially expressed genes (DEGs) associated with the adenomyosis group in the receptive phase were further integrated with 151, 173 and 42 extracted genes from published studies that were related to endometrial receptivity in healthy uterus, endometriosis and adenomyosis, respectively. Enrichment analyses were performed using Cytoscape ClueGO and CluePedia apps.

RESULTS

Out of 20 endometrial samples, 2 were dated to the early receptive phase, 13 to the receptive phase and 5 to the late receptive phase. Comparison of the transcriptomics data from all 20 samples provided 909 DEGs (p<0.05; nonsignificant after adjusted p value) in the adenomyosis group but only 4 enriched pathways (Bonferroni p value < 0.05). The analysis of 13 samples only dated to the receptive phase provided suggestive 382 DEGs (p<0.05; nonsignificant after adjusted p value) in the adenomyosis group, leading to 33 enriched pathways (Bonferroni p value < 0.05). These included pathways were already associated with endometrial biology, such as "Expression of interferon (IFN)-induced genes" and "Response to IFN-alpha". Data integration revealed pathways indicating a unique effect of adenomyosis on endometrial molecular organization (e.g., "Expression of IFN-induced genes") and its interference with endometrial receptivity establishment (e.g., "Extracellular matrix organization" and "Tumour necrosis factor production").

CONCLUSIONS

Accurate endometrial dating and RNA-seq analysis resulted in the identification of altered response to IFN signalling as the most promising candidate of impaired uterine receptivity in adenomyosis.

Coupling miR/isomiR and mRNA Expression Signatures Unveils New Molecular Layers of Endometrial Receptivity

Embryo implantation depends on endometrial receptivity (ER). To achieve ER, the preparation of the uterine lining requires controlled priming by ovarian hormones and the expression of numerous genes in the endometrial tissue. microRNAs (miRs) have emerged as critical genetic regulators of ER in fertility and of the diseases that are associated with infertility. With the rapid development of next-generation sequencing technologies, it has become clear that miR genes can produce canonical miRs and variants—isomiRs. Here, we describe miR/isomiR expression dynamics across the four time points of natural chorionic gonadotropin (hCG)-administered cycles. Sequencing of the small RNAs (sRNA-seq) revealed that the most significant expression changes during the transition from the pre-receptive to the receptive phase occurred in the isomiR families of miR-125a, miR-125b, miR-10a, miR-10b, miR-449c, miR-92a, miR-92b, and miR-99a. Pairing the analysis of the differentially expressed (DE) miRs/isomiRs and their predicted DE mRNA targets uncovered 280 negatively correlating pairs. In the receptive endometrium, the 5′3′-isomiRs of miR-449c, which were among the most highly up-regulated isomiRs, showed a negative correlation with their target, transcription factor (TF) MYCN, which was down-regulated. Joint analysis of the miR/isomiR and TF expression identified several regulatory interactions. Based on these data, a regulatory TF-miR/isomiR gene-target circuit including let7g-5p and miR-345; the isomiR families of miR-10a, miR-10b, miR-92a, and miR-449c; and MYCN and TWIST1 was proposed to play a key role in the establishment of ER. Our work uncovers the complexity and dynamics of the endometrial isomiRs that can act cooperatively with miRs to control the functionally important genes that are critical to ER. Further studies of miR/isomiR expression patterns that are paired with those of their target mRNAs may provide a more in-depth picture of the endometrial pathologies that are associated with implantation failure.

Endometrial Expression of Cell Adhesion Genes in Recurrent Implantation Failure Patients in Ongoing IVF Cycle

Recurrent implantation failure (RIF) is one of the major obstacles in IVF. Transcriptomic literature has revealed the various biological processes involved in endometrial receptivity (ER) under different physiological circumstances, especially in natural cycle. We intended to determine the function-specific ER profile under controlled ovarian stimulation (COS) cycle. This can help to back trace the genomic impairment in RIF patients during the IVF cycle and to validate the genes involved in enriched pathways. In our study, retrospective gene expression microarray dataset was reanalysed after the follow-up, in classic non pregnant RIF (cases) vs fertile women (controls) under COS (n = 5/group). Reanalysis of microarray revealed significant downregulation of cell adhesion function (P:3.11E-05) with the maximum gene count. For validation purpose, downregulation of eight genes (COMP, HABP2, ITGAD, CDH3, COL22A1, MFAP4, THBS1and CD300A) involved in enriched cell adhesion pathway having fold change > 3 were assessed by real-time PCR in independent cohorts of cases and controls (n = 24, each). Downregulation of six out of eight genes (COMP, HABP2, ITGAD, CDH3, MFAP4 and THBS1) were confirmed by real-time PCR (P < 0.05) with fold change > 2. This indicates the importance of analysed genes in the ER mechanism under COS, thus mimicking the fresh embryo transfer. The further analysis in larger cohorts would substantiate the study findings in RIF patients undergoing IVF cycle.

High-content, targeted RNA-seq screening in organoids for drug discovery in colorectal cancer

Organoids allow the recapitulation of intestinal homeostasis and cancerogenesis in vitro; however, RNA sequencing (RNA-seq)-based methods for drug screens are missing. We develop targeted organoid sequencing (TORNADO-seq), a high-throughput, high-content drug discovery platform that uses targeted RNA-seq to monitor the expression of large gene signatures for the detailed evaluation of cellular phenotypes in organoids. TORNADO-seq is a fast, highly reproducible time- and cost-effective ($5 per sample) method that can probe cell mixtures and their differentiation state in the intestinal system. We apply this method to isolate drugs that enrich for differentiated cell phenotypes and show that these drugs are highly efficacious against cancer compared to wild-type organoids. Furthermore, TORNADO-seq facilitates in-depth insight into the mode of action of these drugs. Our technology can easily be adapted to many other systems and will allow for more systematic, large-scale, and quantitative approaches to study the biology of complex cellular systems.

Guidelines for biomarker discovery in endometrium: correcting for menstrual cycle bias reveals new genes associated with uterine disorders

Transcriptomic approaches are increasingly used in reproductive medicine to identify candidate endometrial biomarkers. However, it is known that endometrial progression in the molecular biology of the menstrual cycle is a main factor that could affect the discovery of disorder-related genes. Therefore, the aim of this study was to systematically review current practices for considering the menstrual cycle effect and to demonstrate its bias in the identification of potential biomarkers. From the 35 studies meeting the criteria, 31.43% did not register the menstrual cycle phase. We analysed the menstrual cycle effect in 11 papers (including 12 studies) from Gene Expression Omnibus: three evaluating endometriosis, two evaluating recurrent implantation failure, one evaluating recurrent pregnancy loss, one evaluating uterine fibroids and five control studies, which collected endometrial samples throughout menstrual cycle. An average of 44.2% more genes were identified after removing menstrual cycle bias using linear models. This effect was observed even if studies were balanced in the proportion of samples collected at different endometrial stages or only in the mid-secretory phase. Our bias correction method increased the statistical power by retrieving more candidate genes than per-phase independent analyses. Thanks to this practice, we discovered 544 novel candidate genes for eutopic endometriosis, 158 genes for ectopic ovarian endometriosis and 27 genes for recurrent implantation failure. In conclusion, we demonstrate that menstrual cycle progression masks molecular biomarkers, provides new guidelines to unmask them and proposes a new classification that distinguishes between biomarkers of disorder or/and menstrual cycle progression.

Fetal HLA-G mediated immune tolerance and interferon response in preeclampsia

BACKGROUND

Fetal immune tolerance is crucial for pregnancy success. We studied the link between preeclampsia, a severe pregnancy disorder with uncertain pathogenesis, and fetal human leukocyte antigen G (HLA-G) and other genes regulating maternal immune responses.

METHODS

We assessed sex ratios and regulatory HLA-G haplotypes in population cohorts and series of preeclampsia and stillbirth. We studied placental mRNA expression of 136 genes by sequencing and HLA-G and interferon alpha (IFNα) protein expression by immunohistochemistry.

FINDINGS

We found underrepresentation of males in preeclamptic births, especially those delivered preterm or small for gestational age. Balancing selection at HLA-G associated with the sex ratio, stillbirth, and preeclampsia. We observed downregulation of HLA-G, its receptors, and many other tolerogenic genes, and marked upregulation of IFNA1 in preeclamptic placentas.

INTERPRETATION

These findings indicate that an evolutionary trade-off between immune tolerance and protection against infections at the maternal-fetal interface promotes genetic diversity in fetal HLA-G, thereby affecting survival, preeclampsia, and sex ratio. We highlight IFNA1 as a potential mediator of preeclampsia and a target for therapeutic trials.

FUNDING

Finnish Medical Foundation, Päivikki and Sakari Sohlberg Foundation, Karolinska Institutet Research Foundation, Scandinavia-Japan Sasakawa Foundation, Japan Eye Bank Association, Astellas Foundation for Research on Metabolic Disorders, Japan Society for the Promotion of Science, Knut and Alice Wallenberg Foundation, Swedish Research Council, Medical Society Liv och Hälsa, Sigrid Jusélius Foundation, Helsinki University Hospital and University of Helsinki, Jane and Aatos Erkko Foundation, Academy of Finland, Finska Läkaresällskapet, Novo Nordisk Foundation, Finnish Foundation for Pediatric Research, and Emil Aaltonen Foundation.

Digital multiplex ligation assay for highly multiplexed screening of β-lactamase-encoding genes in bacterial isolates

Increasing incidence of antibiotic resistance in clinical and environmental settings calls for increased scalability in their surveillance. Current screening technologies are limited by the number of samples and genes that can easily be screened. We demonstrate here digital multiplex ligation assay (dMLA) as a low-cost targeted genomic detection workflow capable of highly-parallel screening of bacterial isolates for multiple target gene regions simultaneously. Here, dMLA is used for simultaneous detection of 1187 β-lactamase-encoding genes, including extended spectrum β-lactamase (ESBL) genes, in 74 bacterial isolates. We demonstrate dMLA as a light-weight and cost-efficient workflow which provides a highly scalable tool for antimicrobial resistance surveillance and is also adaptable to genetic screening applications beyond antibiotic resistance.

Tamminen et al. develop a digital multiplex ligation assay (dMLA) that enables the detection of bacterial isolates using probe hybridization and ligation-based assays with next-generation sequencing. Their method can be applied in high-throughput and affordable screening for antibiotic resistance.

Prospective evaluation of NGS-based liquid biopsy in untreated late stage non-squamous lung carcinoma in a single institution

Background

NGS from plasma samples in non-squamous cell lung carcinoma (NSCC) can aid in the detection of actionable genomic alterations. However, the absolute clinical value of NGS in liquid biopsy (LB) made at baseline is currently uncertain. We assessed the impact of plasma-based NGS using an in-house test and an outsourced test in comparison to a routine molecular pathology workflow.

Methods

Twenty-four advanced/metastatic treatment-naïve NSCC patients were prospectively included. NGS analyses were conducted both in-house using the Oncomine cfTNA Panel and in an external testing center using the Foundation Liquid assay. NGS analysis and/or specific molecular based assays were conducted in parallel on tissue or cytological samples.

Results

Both LB tests were well correlated. Tissue NGS results were obtained in 67% of patients and demonstrated good correlation with LB assays. Activating EGFR mutations were detected using LB tests in three patients. PD-L1 expression assessed in tissue sections enabled the initiation of pembrolizumab treatment in five patients.

Conclusion

NGS from LB is feasible in routine clinical practice using an in-house or an outsourced test at baseline. However, the impact on therapy selection was limited in this small series of patients and LB was not able to replace tissue-based testing in our hands.

Creating basis for introducing non‐invasive prenatal testing in the Estonian public health setting

OBJECTIVE

The study aimed to validate a whole-genome sequencing-based NIPT laboratory method and our recently developed NIPTmer aneuploidy detection software with the potential to integrate the pipeline into prenatal clinical care in Estonia.

METHOD

In total, 424 maternal blood samples were included. Analysis pipeline involved cell-free DNA extraction, library preparation and massively parallel sequencing on Illumina platform. Aneuploidies were determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from sequencing raw data. SeqFF was implemented to estimate cell-free fetal DNA (cffDNA) fraction.

RESULTS

NIPTmer identified correctly all samples of non-mosaic trisomy 21 (T21, 15/15), T18 (9/9), T13 (4/4) and monosomy X (4/4) cases, with the 100% sensitivity. However, one mosaic T18 remained undetected. Six false-positive (FP) results were observed (FP rate of 1.5%, 6/398), including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). The level of cffDNA of <4% was estimated in eight samples, including one sample with T13 and T18. Despite low cffDNA level, these two samples were determined as aneuploid.

CONCLUSION

We believe that the developed NIPT method can successfully be used as a universal primary screening test in combination with ultrasound scan for the first trimester fetal examination.

Computational framework for targeted high-coverage sequencing based NIPT

Non-invasive prenatal testing (NIPT) enables accurate detection of fetal chromosomal trisomies. The majority of publicly available computational methods for sequencing-based NIPT analyses rely on low-coverage whole-genome sequencing (WGS) data and are not applicable for targeted high-coverage sequencing data from cell-free DNA samples. Here, we present a novel computational framework for a targeted high-coverage sequencing-based NIPT analysis. The developed framework uses a hidden Markov model (HMM) in conjunction with a supplemental machine learning model, such as decision tree (DT) or support vector machine (SVM), to detect fetal trisomy and parental origin of additional fetal chromosomes. These models were developed using simulated datasets covering a wide range of biologically relevant scenarios with various chromosomal quantities, parental origins of extra chromosomes, fetal DNA fractions, and sequencing read depths. Developed models were tested on simulated and experimental targeted sequencing datasets. Consequently, we determined the functional feasibility and limitations of each proposed approach and demonstrated that read count-based HMM achieved the best overall classification accuracy of 0.89 for detecting fetal euploidies and trisomies on simulated dataset. Furthermore, we show that by using the DT and SVM on the HMM classification results, it was possible to increase the final trisomy classification accuracy to 0.98 and 0.99, respectively. We demonstrate that read count and allelic ratio-based models can achieve a high accuracy (up to 0.98) for detecting fetal trisomy even if the fetal fraction is as low as 2%. Currently, existing commercial NIPT analysis requires at least 4% of fetal fraction, which can be possibly a challenge in case of early gestational age (<10 weeks) or high maternal body mass index (>35 kg/m²). More accurate detection can be achieved at higher sequencing depth using HMM in conjunction with supplemental models, which significantly improve the trisomy detection especially in borderline scenarios (e.g., very low fetal fraction) and enables to perform NIPT even earlier than 10 weeks of pregnancy.

Bioinformatics Analysis for Circulating Cell-Free DNA in Cancer

Molecular analysis of cell-free DNA (cfDNA) that circulates in plasma and other body fluids represents a "liquid biopsy" approach for non-invasive cancer screening or monitoring. The rapid development of sequencing technologies has made cfDNA a promising source to study cancer development and progression. Specific genetic and epigenetic alterations have been found in plasma, serum, and urine cfDNA and could potentially be used as diagnostic or prognostic biomarkers in various cancer types. In this review, we will discuss the molecular characteristics of cancer cfDNA and major bioinformatics approaches involved in the analysis of cfDNA sequencing data for detecting genetic mutation, copy number alteration, methylation change, and nucleosome positioning variation. We highlight specific challenges in sensitivity to detect genetic aberrations and robustness of statistical analysis. Finally, we provide perspectives regarding the standard and continuing development of bioinformatics analysis to move this promising screening tool into clinical practice.