Integrated Next-generation Sequencing Research Articles

The evolving role of interventional cytopathology from thyroid FNA to NGS: Lessons learned at Federico II University of Naples.

Fine-needle aspiration (FNA) guided by ultrasound (US) has emerged as a highly precise diagnostic method for managing thyroid nodules, significantly diminishing unnecessary surgeries. The effectiveness of US-guided FNA is high when a single specialist performs the FNA procedure and the microscopy. This paradigm has paved the way for the evolution of interventional cytopathology, a specialist with a pivotal role in the preoperative diagnostic process, encompassing patient history review, clinical examination, FNA execution under US guidance, preparation, and microscopic interpretation of cytological samples. As the landscape of precision medicine unfolds, molecular testing assumes greater importance in thyroid cytopathology, particularly in refining the risk of malignancy for indeterminate nodules. The updated Bethesda classification system underscores the clinical significance of molecular tests, emphasizing their role in refining diagnostic accuracy. With this evolving landscape, interventional cytopathologists must adapt by acquiring expertise in molecular technologies and addressing ongoing challenges in workflow harmonization and optimization. This paper delves into our decade-long experience as interventional cytopathologists, focusing on recent endeavours to ensure adequate samples not only for microscopic diagnosis but also for molecular testing. Additionally, here we review the challenges of integrating next-generation sequencing (NGS) technology into clinical practice, highlighting the importance of integrating clinically meaningful molecular data into comprehensive molecular cytology reports.

HIV-DRIVES: HIV drug resistance identification, variant evaluation, and surveillance pipeline.

The global prevalence of resistance to antiviral drugs combined with antiretroviral therapy (cART) emphasizes the need for continuous monitoring to better understand the dynamics of drug-resistant mutations to guide treatment optimization and patient management as well as check the spread of resistant viral strains. We have recently integrated next-generation sequencing (NGS) into routine HIV drug resistance (HIVDR) monitoring, with key challenges in the bioinformatic analysis and interpretation of the complex data generated, while ensuring data security and privacy for patient information. To address these challenges, here we present HIV-DRIVES (HIV Drug Resistance Identification, Variant Evaluation, and Surveillance), an NGS-HIVDR bioinformatics pipeline that has been developed and validated using Illumina short reads, FASTA, and Sanger ab1.seq files.

Trial of Electronic Medical Record Integrated Next-Generation Sequencing Ordering in Veterans Affairs Cancer Care.

Previous studies document underuse of next-generation sequencing (NGS). We examined the impact to oncology care for veterans of incorporating NGS ordering into the Veterans Affairs (VA) electronic medical record (EMR) at two New York City VA Medical Centers. We identified patients with non-small cell lung cancer and prostate cancer with oncology clinic visits and NGS testing indications between January and December 2021. Patients were divided into external ordering (EO) with visits before we implemented an EMR ordering system for NGS in July 2021, and internal ordering (IO) with visits after this date. The primary outcome was proportion of NGS testing performed in EO versus IO groups. Secondary outcomes were time between metastatic disease diagnosis to receipt of test by vendor, time of metastatic diagnosis to result, and proportion of testing by race. A total of 168 patients were identified, 116 EO and 52 IO patients. Between IO and EO periods, testing significantly increased from 52% to 87% (P ≤ .01); it was conducted more quickly, with time from metastatic diagnosis to sample receipt by the NGS vendor improving to median 37 days from 299 days (P = .03); and the time from documented metastatic disease to a test result improved to median 56 days from 309 days (P = .03). The proportion of tissue received by the vendor was not significantly different between the two groups. There were no significant differences in testing according to self-reported race. Integration of NGS ordering in the EMR led to increased proportion and speed of testing for a vulnerable patient population served by the country's largest health system.

Unraveling the Significance of MET Focal Amplification in Lung Cancer: Integrative NGS, FISH, and IHC Investigation

MET amplification (METamp) represents a promising therapeutic target in non–small cell lung cancer, but no consensus has been established to identify METamp-dependent tumors that could potentially benefit from MET inhibitors. In this study, an analysis of MET amplification/overexpression status was performed in a retrospectively recruited cohort comprising 231 patients with non–small cell lung cancer from Shanghai Chest Hospital (SCH cohort) using 3 methods: fluorescence in situ hybridization (FISH), hybrid capture-based next-generation sequencing, and immunohistochemistry for c-MET and phospho-MET. The SCH cohort included 130 cases known to be METamp positive by FISH and 101 negative controls. The clinical relevance of these approaches in predicting the efficacy of MET inhibitors was evaluated. Additionally, next-generation sequencing data from another 2 cohorts including 22,010 lung cancer cases were utilized to examine the biological characteristics of different METamp subtypes. Of the 231 cases, 145 showed MET amplification/overexpression using at least 1 method, whereas only half of them could be identified by all 3 methods. METamp can occur as focal amplification or polysomy. Our study revealed that the inconsistency between next-generation sequencing and FISH primarily occurred in the polysomy subtype. Further investigations indicated that compared with polysomy, focal amplification correlated with fewer co-occurring driver mutations, higher protein expressions of c-MET and phospho-MET, and higher incidence in acquired resistance than in de novo setting. Moreover, patients with focal amplification presented a more robust response to MET inhibitors compared with those with polysomy. Notably, a strong correlation was observed between focal amplification and programmed cell death ligand-1 expression, indicating potential therapeutic implications with combined MET inhibitor and immunotherapy for patients with both alterations. Our findings provide insights into the molecular complexity and clinical relevance of METamp in lung cancer, highlighting the role of MET focal amplification as an oncogenic driver and its feasibility as a primary biomarker to further investigate the clinical activity of MET inhibitors in future studies.

Beyond traditional therapies: clinical significance of complex molecular profiling in patients with advanced solid tumours-results from a Turkish multi-centre study.

The objective of this multi-centre, real-world study was to examine the potential influence of comprehensive molecular profiling on the development of treatment decisions or adjustments for patients with advanced solid malignancies. We then evaluated the impact of these informed choices on patient treatment outcomes. The study encompassed 234 adult patients (mean age: 52.7±14.3years, 54.7% women) who were diagnosed with solid tumours at 21 different medical centres in Turkey. Remarkably, 67.9% of the patients exhibited metastasis at the time of diagnosis. We utilized an OncoDNA (Gosselies, Belgium) platform (OncoDEEP) integrating next-generation sequencing with additional tests to harvest complex molecular profiling data. The results were analyzed in relation with two specific outcomes: (i) the impact on therapeutic decisions, including formulation or modifications, and (ii) associated treatment response. Out of the 228 patients with final molecular profiling results, 118 (50.4%) had their treatment modified, whilst the remaining 110 (47.0%) did not. The response rates were comparable, with 3.9 versus 3.4% for complete response, 13.6 versus 29.3% for partial response, 66.9 versus 51.7% for progressive disease and 15.5 versus 15.5% for stable disease for treatments informed and not informed by complex molecular profiling, respectively (P=0.16). Our real-world findings highlight the significant impact of complex molecular profiling on the treatment decisions made by oncologists for a substantial portion of patients with advanced solid tumours. Regrettably, no significant advantage was detected in terms of treatment response or disease control rates.

Genomic DNA-based measurable residual disease monitoring in pediatric acute myeloid leukemia: unselected consecutive cohort study

Measurable residual disease (MRD) monitoring in childhood acute myeloid leukemia (AML) is used to assess response to treatment and for early detection of imminent relapse. In childhood AML, MRD is typically evaluated using flow cytometry, or by quantitative detection of leukemia-specific aberrations at the mRNA level. Both methods, however, have significant limitations. Recently, we demonstrated the feasibility of MRD monitoring in selected subgroups of AML at the genomic DNA (gDNA) level. To evaluate the potential of gDNA-based MRD monitoring across all AML subtypes, we conducted a comprehensive analysis involving 133 consecutively diagnosed children. Integrating next-generation sequencing into the diagnostic process, we identified (presumed) primary genetic aberrations suitable as MRD targets in 97% of patients. We developed patient-specific quantification assays and monitored MRD in 122 children. The gDNA-based MRD monitoring via quantification of primary aberrations with a sensitivity of at least 10−4 was possible in 86% of patients; via quantification with sensitivity of 5 × 10−4, of secondary aberrations, or at the mRNA level in an additional 8%. Importantly, gDNA-based MRD exhibited independent prognostic value at early time-points in patients stratified to intermediate-/high-risk treatment arms. Our study demonstrates the broad applicability, feasibility, and clinical significance of gDNA-based MRD monitoring in childhood AML.

Integrative Placental Multi-Omics Analysis Reveals Perturbed Pathways and Potential Prognostic Biomarkers in Gestational Hypertension

Gestational hypertension (GH) is a severe complication that occurs after 20 weeks of pregnancy; however, its molecular mechanisms are not yet fully understood. Through this case-control discovery phase study, we aimed to find disease-specific candidate placental microRNAs (miRNAs) and metabolite markers for differentiating GH by integrating next-generation sequencing and metabolomics multi-omics analysis of placenta. Using small RNA sequencing and metabolomics of placental tissues of healthy pregnant (HP, n=24) and GH subjects (n=20), the transcriptome and metabolome were characterized in both groups. The study identified a total of 44 downregulated placental miRNAs which includes three novel, three mature and 38 precursor miRNAs. Six miRNAs including three mature (hsa-miR-181a-5p, hsa-miR-498-5p, and hsa-miR-26b-5p) and three novel (NC_000016.10_1061, NC_000005.10_475, and NC_000001.11_53) were considered for final target prediction and functional annotation. Integrative analysis of differentially expressed miRNAs and metabolites yielded five pathways such as purine, glutathione, glycerophospholipid, inositol phosphate and β-alanine to be significantly perturbed in GH. We present fourteen genes (LPCAT1, LPCAT2, DGKH, PISD, GPAT2, PTEN, SACM1L, PGM2, AMPD3, AK7, AK3, CNDP1, IDH2, and ODC1) and eight metabolites (xanthosine, xanthine, spermine, glycine, CDP-Choline, glyceraldehyde 3-phosphate, β-alanine, and histidine) with potential to distinguish GH and HP. The differential expression of miRNAs, their target genes, altered metabolites and metabolic pathways in GH patients were identified for the first time in our study. Further, the altered miRNAs and metabolites were integrated to build their inter-connectivity network. The findings obtained from our study may be used as a valuable source to further unravel the molecular pathways associated with GH and also for the evaluation of prognostic markers.

Integrative mapping of the dog epigenome: Reference annotation for comparative intertissue and cross-species studies

Dogs have become a valuable model in exploring multifaceted diseases and biology relevant to human health. Despite large-scale dog genome projects producing high-quality draft references, a comprehensive annotation of functional elements is still lacking. We addressed this through integrative next-generation sequencing of transcriptomes paired with five histone marks and DNA methylome profiling across 11 tissue types, deciphering the dog’s epigenetic code by defining distinct chromatin states, super-enhancer, and methylome landscapes, and thus showed that these regions are associated with a wide range of biological functions and cell/tissue identity. In addition, we confirmed that the phenotype-associated variants are enriched in tissue-specific regulatory regions and, therefore, the tissue of origin of the variants can be traced. Ultimately, we delineated conserved and dynamic epigenomic changes at the tissue- and species-specific resolutions. Our study provides an epigenomic blueprint of the dog that can be used for comparative biology and medical research.

Rapid and Automated Semiconductor-Based Next-Generation Sequencing for Simultaneous Detection of Somatic DNA and RNA Aberrations in Myeloid Neoplasms

Evaluation of suspected myeloid neoplasms involves testing for recurrent, diagnostically and therapeutically relevant genetic alterations. Current molecular testing requires multiple technologies, different domains of expertise, and unconnected workflows, resulting in variable, lengthy turnaround times that can delay treatment. To address this unmet clinical need, we evaluated the Oncomine Myeloid Assay GX panel on the Ion Torrent Genexus platform, a rapid, integrated nucleic acid to report next-generation sequencing platform for detecting clinically relevant genetic aberrations in myeloid disorders. Specimens included synthetic DNA (101 targets) and RNA (9 targets) controls and real-world nucleic acid material derived from bone marrow or peripheral blood samples (40 patients). Ion Torrent Genexus results and performance indices were compared with those obtained from clinically validated genomic testing workflows in 2 separate clinical laboratories. The Ion Torrent Genexus identified 100% of DNA and RNA control variants. For primary patient specimens, the Ion Torrent Genexus reported 82 of 107 DNA variants and 19 of 19 RNA gene fusions identified on clinically validated assays, yielding an 80% overall detection rate. Reanalysis of exported, unfiltered Ion Torrent Genexus data revealed 15 DNA variants not called by the filtered on-board bioinformatics pipeline, yielding a 92% potential detection rate. These results hold promise for the implementation of an integrated next-generation sequencing system to rapidly detect genetic aberrations, facilitating accurate, genomics-based diagnoses and accelerated time to precision therapies in myeloid neoplasms.

Mini-review: Current and Future Perspectives on Microbially Focused Restoration Strategies in Tallgrass Prairies.

Ecosystem restoration is a critical conservation strategy, especially for increasing resilience and resistance to climate change. Current restoration efforts that convert reclaimed agricultural land to native tallgrass prairies typically focus on aboveground communities, but it can take decades to restore soil microbial biodiversity and function using these strategies, if they recover at all. This incomplete restoration can have detrimental impacts on longer-term restoration goals, such as supporting late-successional plant species and facilitating soil carbon sequestration. Soil microorganisms are key components in determining the fate of organic material that enters the soil. They mediate decomposition rates and contribute to plant-microbe-soil interactions, produce microbial biomass, necromass, and metabolic products, and physically protect soil carbon through aggregation. Interactions with plants and controls over soil carbon vary widely depending on the specific microbial taxa present, their physiology, their functional capabilities, and their responses to environmental stressors. Thus, the ability for new restorations, prairie conservation corridors, and prairies planted in marginal lands to act as carbon sinks and help balance greenhouse gas emissions can depend on the success of microbial restoration. Next-generation sequencing approaches can support novel methods for evaluating existing restoration practices and developing microbially focused management strategies. This review summarizes the growing body of literature describing microbially focused tallgrass prairie restoration and considers when and how integrating next-generation sequencing approaches into management efforts can be beneficial. We provide a roadmap for future restoration efforts where microbial ecologists, restoration ecologists, and land managers can work together to meet their goals to promote climate-ready restored ecosystems.

SWI/SNF complex gene variations are associated with a higher tumor mutational burden and a better response to immune checkpoint inhibitor treatment: a pan-cancer analysis of next-generation sequencing data corresponding to 4591 cases

BackgroundGenes related to the SWItch/sucrose nonfermentable (SWI/SNF) chromatin remodeling complex are frequently mutated across cancers. SWI/SNF-mutant tumors are vulnerable to synthetic lethal inhibitors. However, the landscape of SWI/SNF mutations and their associations with tumor mutational burden (TMB), microsatellite instability (MSI) status, and response to immune checkpoint inhibitors (ICIs) have not been elucidated in large real-world Chinese patient cohorts.MethodsThe mutational rates and variation types of six SWI/SNF complex genes (ARID1A, ARID1B, ARID2, SMARCA4, SMARCB1, and PBRM1) were analyzed retrospectively by integrating next-generation sequencing data of 4591 cases covering 18 cancer types. Thereafter, characteristics of SWI/SNF mutations were depicted and the TMB and MSI status and therapeutic effects of ICIs in the SWI/SNF-mutant and SWI/SNF-non-mutant groups were compared.ResultsSWI/SNF mutations were observed in 21.8% of tumors. Endometrial (54.1%), gallbladder and biliary tract (43.4%), and gastric (33.9%) cancers exhibited remarkably higher SWI/SNF mutational rates than other malignancies. Further, ARID1A was the most frequently mutated SWI/SNF gene, and ARID1A D1850fs was identified as relatively crucial. The TMB value, TMB-high (TMB-H), and MSI-high (MSI-H) proportions corresponding to SWI/SNF-mutant cancers were significantly higher than those corresponding to SWI/SNF-non-mutant cancers (25.8 vs. 5.6 mutations/Mb, 44.3% vs. 10.3%, and 16.0% vs. 0.9%, respectively; all p < 0.0001). Furthermore, these indices were even higher for tumors with co-mutations of SWI/SNF genes and MLL2/3. Regarding immunotherapeutic effects, patients with SWI/SNF variations showed significantly longer progression-free survival (PFS) rates than their SWI/SNF-non-mutant counterparts (hazard ratio [HR], 0.56 [95% confidence interval {CI} 0.44–0.72]; p < 0.0001), and PBRM1 mutations were associated with relatively better ICI treatment outcomes than the other SWI/SNF gene mutations (HR, 0.21 [95% CI 0.12–0.37]; p = 0.0007). Additionally, patients in the SWI/SNF-mutant + TMB-H (HR, 0.48 [95% CI 0.37–0.54]; p < 0.0001) cohorts had longer PFS rates than those in the SWI/SNF-non-mutant + TMB-low cohort.ConclusionsSWI/SNF complex genes are frequently mutated and are closely associated with TMB-H status, MSI-H status, and superior ICI treatment response in several cancers, such as colorectal cancer, gastric cancer, and non-small cell lung cancer. These findings emphasize the necessity and importance of molecular-level detection and interpretation of SWI/SNF complex mutations.

Integrated next-generation sequencing and comparative transcriptomic analysis of leaves provides novel insights into the ethylene pathway of Chrysanthemum morifolium in response to a Chinese isolate of chrysanthemum virus B

BackgroundChrysanthemum virus B (CVB), a key member of the genus Carlavirus, family Betaflexiviridae, causes severe viral diseases in chrysanthemum (Chrysanthemum morifolium) plants worldwide. However, information on the mechanisms underlying the response of chrysanthemum plants to CVB is scant.MethodsHere, an integrated next-generation sequencing and comparative transcriptomic analysis of chrysanthemum leaves was conducted to explore the molecular response mechanisms of plants to a Chinese isolate of CVB (CVB-CN) at the molecular level.ResultsIn total, 4934 significant differentially expressed genes (SDEGs) were identified to respond to CVB-CN, of which 4097 were upregulated and 837 were downregulated. Gene ontology and functional classification showed that the majority of upregulated SDEGs were categorized into gene cohorts involved in plant hormone signal transduction, phenylpropanoid and flavonoid biosynthesis, and ribosome metabolism. Enrichment analysis demonstrated that ethylene pathway-related genes were significantly upregulated following CVB-CN infection, indicating a strong promotion of ethylene biosynthesis and signaling. Furthermore, disruption of the ethylene pathway in Nicotiana benthamiana, a model plant, using virus-induced gene silencing technology rendered them more susceptible to cysteine-rich protein of CVB-CN induced hypersensitive response, suggesting a crucial role of this pathway in response to CVB-CN infection.ConclusionThis study provides evidence that ethylene pathway has an essential role of plant in response to CVB and offers valuable insights into the defense mechanisms of chrysanthemum against Carlavirus.

Integrative genomic and transcriptomic profiling reveals distinct molecular subsets in adult mixed phenotype acute leukemia.

Mixed phenotype acute leukemia (MPAL) is a subtype of leukemia in which lymphoid and myeloid markers are co-expressed. Knowledge regarding the genetic features of MPAL is lacking due to its rarity and heterogeneity. Here, we applied an integrated genomic and transcriptomic approach to explore the molecular characteristics of 176 adult patients with MPAL, including 86 patients with T-lymphoid/myeloid MPAL (T/My MPAL-NOS), 42 with Ph+ MPAL, 36 with B-lymphoid/myeloid MPAL (B/My MPAL-NOS), 4 with t(v;11q23), and 8 with MPAL, NOS, rare types. Genetically, T/My MPAL-NOS was similar to B/T MPAL-NOS but differed from Ph+ MPAL and B/My MPAL-NOS. T/My MPAL-NOS exhibited higher CEBPA, DNMT3A, and NOTCH1 mutations. Ph+ MPAL demonstrated higher RUNX1 mutations. B/T MPAL-NOS showed higher NOTCH1 mutations. By integrating next-generation sequencing and RNA sequencing data of 89 MPAL patients, we defined eight molecular subgroups (G1-G8) with distinct mutational and gene expression characteristics. G1 was associated with CEBPA mutations, G2 and G3 with NOTCH1 mutations, G4 with BCL11B rearrangement and FLT3 mutations, G5 and G8 with BCR::ABL1 fusion, G6 with KMT2A rearrangement/KMT2A rearrangement-like features, and G7 with ZNF384 rearrangement/ZNF384 rearrangement-like characteristics. Subsequently, we analyzed single-cell RNA sequencing data from five patients. Groups G1, G2, G3, and G4 exhibited overexpression of hematopoietic stem cell disease-like and common myeloid progenitor disease-like signatures, G5 and G6 had high expression of granulocyte-monocyte progenitor disease-like and monocyte disease-like signatures, and G7 and G8 had common lymphoid progenitor disease-like signatures. Collectively, our findings indicate that integrative genomic and transcriptomic profiling may facilitate more precise diagnosis and develop better treatment options for MPAL.

An Association between Insulin Resistance and Neurodegeneration in Zebrafish Larval Model (Danio rerio).

Background: Type 2 diabetes mellitus has recently been identified as a mediator of neurodegeneration. However, the molecular mechanisms have not been clearly elucidated. We aimed to investigate insulin resistance associated with neurodegenerative events in zebrafish larvae. Methods: Larvae aged 72 h-post-fertilization (hpf) were induced to insulin resistance by immersion in 250 nM insulin and were then reinduced with 100 nM insulin at 96 hpf. This model was validated by a glucose levels assay, qPCR analysis of selected genes (akt, pepck, zglut3 and claudin-5a) and Oil Red-O (ORO) staining of the yolk sac for lipid distribution. The association of insulin resistance and neurodegeneration was validated by malondialdehyde (MDA), glutathione (GSH) assays, and by integrating next-generation sequencing with database for annotation, visualization and integrated discovery (DAVID). Results: There was a significant increase in glucose levels at 180 min in the insulin-resistant group. However, it decreased at 400 min after the re-challenge. Insulin-signaling mediators, akt and pepck, were showed significantly downregulated up to 400 min after insulin immersion (p < 0.05). Meanwhile, claudin-5a assessed blood–brain barrier (BBB) integrity and showed significant deterioration after 400 min of post-insulin immersion. ORO staining remarked the increase in yolk sac size in the insulin-resistant group. After the confirmation of insulin resistance, MDA levels increased significantly in the insulin-resistant group compared to the control group in the following parameters. Furthermore, dysregulated MAPK- and Wnt/Ca2+-signaling pathways were observed in the insulin-resistant group, disrupting energy metabolism and causing BBB injury. Conclusions: We conclude that the insulin-resistant zebrafish larvae alter the metabolic physiology associated with neurodegeneration.

Exploiting Genomic Features to Improve the Prediction of Transcription Factor-Binding Sites in Plants.

The identification of transcription factor (TF) target genes is central in biology. A popular approach is based on the location by pattern matching of potential cis-regulatory elements (CREs). During the last few years, tools integrating next-generation sequencing data have been developed to improve the performance of pattern matching. However, such tools have not yet been comprehensively evaluated in plants. Hence, we developed a new streamlined method aiming at predicting CREs and target genes of plant TFs in specific organs or conditions. Our approach implements a supervised machine learning strategy, which allows decision rule models to be learnt using TF ChIP-chip/seq experimental data. Different layers of genomic features were integrated in predictive models: the position on the gene, the DNA sequence conservation, the chromatin state and various CRE footprints. Among the tested features, the chromatin features were crucial for improving the accuracy of the method. Furthermore, we evaluated the transferability of predictive models across TFs, organs and species. Finally, we validated our method by correctly inferring the target genes of key TFs controlling metabolite biosynthesis at the organ level in Arabidopsis. We developed a tool-Wimtrap-to reproduce our approach in plant species and conditions/organs for which ChIP-chip/seq data are available. Wimtrap is a user-friendly R package that supports an R Shiny web interface and is provided with pre-built models that can be used to quickly get predictions of CREs and TF gene targets in different organs or conditions in Arabidopsis thaliana, Solanum lycopersicum, Oryza sativa and Zea mays.

Genome-Wide Association Study-Guided Exome Rare Variant Burden Analysis Identifies IL1R1 and CD3E as Potential Autoimmunity Risk Genes for Celiac Disease.

Celiac disease (CeD) is a multifactorial autoimmune enteropathy characterized by the overactivation of the immune system in response to dietary gluten. The molecular etiology of CeD is still not well-understood. Therefore, this study aims to identify potential candidate genes involved in CeD pathogenesis by applying multilayered system biology approaches. Initially, we identified rare coding variants shared between the affected siblings in two rare Arab CeD families by whole-exome sequencing (WES). Then we used the STRING database to construct a protein network of rare variants and genome-wide association study (GWAS) loci to explore their molecular interactions in CeD. Furthermore, the hub genes identified based on network topology parameters were subjected to a series of computational validation analyses like pathway enrichment, gene expression, knockout mouse model, and variant pathogenicity predictions. Our findings have shown the absence of rare variants showing classical Mendelian inheritance in both families. However, interactome analysis of rare WES variants and GWAS loci has identified a total of 11 hub genes. The multidimensional computational analysis of hub genes has prioritized IL1R1 for family A and CD3E for family B as potential genes. These genes were connected to CeD pathogenesis pathways of T-cell selection, cytokine signaling, and adaptive immune response. Future multi-omics studies may uncover the roles of IL1R1 and CD3E in gluten sensitivity. The present investigation lays forth a novel approach integrating next-generation sequencing (NGS) of familial cases, GWAS, and computational analysis for solving the complex genetic architecture of CeD.

Identification and functional validation of novel pharmacogenomic variants using a next-generation sequencing-based approach for clinical pharmacogenomics

Inter-individual variability in pharmacokinetics and drug response is heavily influenced by single-nucleotide variants (SNVs) and copy-number variations (CNVs) in genes with importance for drug disposition. Nowadays, a plethora of studies implement next generation sequencing to capture rare and novel pharmacogenomic (PGx) variants that influence drug response. To address these issues, we present a comprehensive end-to-end analysis workflow, beginning from targeted PGx panel re-sequencing to in silico analysis pipelines and in vitro validation assays. Specifically, we show that novel pharmacogenetic missense variants that are predicted or putatively predicted to be functionally deleterious, significantly alter protein activity levels of CYP2D6 and CYP2C19 proteins. We further demonstrate that variant priorization pipelines tailored with functional in vitro validation assays provide supporting evidence for the deleterious effect of novel PGx variants. The proposed workflow could provide the basis for integrating next-generation sequencing for PGx testing into routine clinical practice.

TAZ-CAMTA1 and YAP-TFE3 alter the TAZ/YAP transcriptome by recruiting the ATAC histone acetyltransferase complex

Epithelioid hemangioendothelioma (EHE) is a vascular sarcoma that metastasizes early in its clinical course and lacks an effective medical therapy. The TAZ-CAMTA1 and YAP-TFE3 fusion proteins are chimeric transcription factors and initiating oncogenic drivers of EHE. A combined proteomic/genetic screen in human cell lines identified YEATS2 and ZZZ3, components of the Ada2a-containing histone acetyltransferase (ATAC) complex, as key interactors of both fusion proteins despite the dissimilarity of the C terminal fusion partners CAMTA1 and TFE3. Integrative next generation sequencing approaches in human and murine cell lines showed that the fusion proteins drive a unique transcriptome by simultaneously hyperactivating a TEAD-based transcriptional program and modulating the chromatin environment via interaction with the ATAC complex. Interaction of the ATAC complex with both fusion proteins indicates that it is a key oncogenic driver and unifying enzymatic therapeutic target for this sarcoma. This study presents an approach to mechanistically dissect how chimeric transcription factors drive the formation of human cancers.

Actionable driver DNA variants and fusion genes can be detected in archived cytological specimens with the Oncomine Dx Target Test Multi-CDx system in lung cancer.

Molecular testing is critical for identifying actionable variants in lung cancer for precision medicine. When tumor tissue samples are unavailable, archived cytological specimens (ACSs) can be used. The authors examined whether oncogenic variants could be accurately detected in ACSs versus paired formalin-fixed, paraffin-embedded (FFPE) tumor tissues with in vitro diagnostic tests. The authors collected 18 ACSs and 15 FFPE tissues from 15 patients with lung cancer and investigated genomic profiles with the Oncomine Dx Target Test Multi-CDx system, which is an integrated next-generation sequencing platform that comprehensively examines 4 companion diagnostic target genes (epidermal growth factor receptor [EGFR]; B-Raf proto-oncogene, serine/threonine kinase [BRAF]; anaplastic lymphoma kinase [ALK]; and ROS proto-oncogene 1, receptor tyrosine kinase [ROS1]). They compared the quantity and quality of extracted nucleic acids, the sequencing quality control (QC), and the detected variants between ACSs and FFPE tissues. The total amount of DNA and RNA obtained from 1 slide was higher in FFPE tissues than ACSs. The RNA integrity number was higher in ACSs. There were no differences in sequencing QC between ACSs and FFPE tissues. A total of 21 variants, including EGFR mutations and ALK and ROS1 fusion genes, were detected in both ACSs and FFPE tissues with 100% concordance. ACSs can be a feasible alternative with which to identify actionable mutations and fusion genes via the Oncomine Dx Target Test Multi-CDx system.

Integrated Genomic Analysis of Chromosomal Alterations and Mutations in B-Cell Acute Lymphoblastic Leukemia Reveals Distinct Genetic Profiles at Relapse.

The clonal basis of relapse in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is complex and not fully understood. Next-generation sequencing (NGS), array comparative genomic hybridization (aCGH), and multiplex ligation-dependent probe amplification (MLPA) were carried out in matched diagnosis–relapse samples from 13 BCP-ALL patients to identify patterns of genetic evolution that could account for the phenotypic changes associated with disease relapse. The integrative genomic analysis of aCGH, MLPA and NGS revealed that 100% of the BCP-ALL patients showed at least one genetic alteration at diagnosis and relapse. In addition, there was a significant increase in the frequency of chromosomal lesions at the time of relapse (p = 0.019). MLPA and aCGH techniques showed that IKZF1 was the most frequently deleted gene. TP53 was the most frequently mutated gene at relapse. Two TP53 mutations were detected only at relapse, whereas the three others showed an increase in their mutational burden at relapse. Clonal evolution patterns were heterogeneous, involving the acquisition, loss and maintenance of lesions at relapse. Therefore, this study provides additional evidence that BCP-ALL is a genetically dynamic disease with distinct genetic profiles at diagnosis and relapse. Integrative NGS, aCGH and MLPA analysis enables better molecular characterization of the genetic profile in BCP-ALL patients during the evolution from diagnosis to relapse.