Bulk DNA Research Articles

FARSB stratifies prognosis and cold tumor microenvironment across different cancer types: an integrated single cell and bulk RNA sequencing analysis

Immunotherapy has brought significant clinical benefits to a subset of patients, but has thus far been disappointing in the treatment of immunologically "cold" tumors. Existing biomarkers that can precisely identify these populations are insufficient. In this context, a potential cold tumor microenvironment (TME) marker FARSB was investigated to reveal its impact on TME and patients' response to immunotherapy across pan-cancer. The expression levels and mutational landscape of FARSB in pan-cancer were investigated. Kaplan-Meier and univariate Cox regression analyses were applied to analyze the prognostic significance of FARSB. Pathways affected by FARSB were investigated by gene set enrichment and variation analysis. The relationship between FARSB expression and immune infiltration was examined using the TIMER2 and R packages. Single-cell RNA sequencing (scRNA-seq) data of several cancer types from GSE72056, GSE131907, GSE132465, GSE125449 and PMID32561858 were analyzed to validate the impact of FARSB on the TME. The predictive effect of FARSB on immunotherapy efficacy was explored in 3 immune checkpoint inhibitors (ICIs)- treated cohorts (PMID32472114, GSE176307, and Riaz2017). FARSB expression was significantly higher in 25 tumor tissues than in normal tissues and was associated with poor prognosis in almost all tumor types. FARSB expression exhibited a strong association with several DNA damage repair pathways and was significantly associated with TP53 mutation in lung adenocarcinoma (P < 0.0001, OR=2.25). FARSB characterized a typical immune desert TME and correlated with impaired expression of chemokines and chemokines receptors. Large-scale scRNA-seq analysis confirmed the immunosuppressive role of FARSB and revealed that FARSB potentially shapes the cold TME by impeding intercellular interactions. In 3 ICI-treated cohorts, FARSB demonstrated predictive value for immunotherapy. This study provides a pan-cancer landscape of the FARSB gene by integrated single-cell and bulk DNA sequencing analysis and elucidates its biological function to promote DNA damage repair and construct the immune desert TME, suggesting the potential value of FARSB as a novel marker for stratifying patients with poor immunotherapeutic benefits and "cold" TME.

Abstract 4363: Monocyte-specific epigenetic age acceleration and cardiomyopathy risk among survivors of childhood cancer

Abstract Our assessment of epigenetic age acceleration (EAA), calculated with DNA methylation (DNAm) data generated from bulk DNA derived from peripheral blood mononuclear cells (PBMC), supports accelerated aging in childhood cancer survivors (CCS). It is challenging to disentangle variation of DNAm at cell-type specific levels from the effects of age-dependent cell type composition, and bulk measurements may obfuscate the links between EAA and age-related outcomes (e.g., cardiomyopathy). Methylation profiling was generated using Infinium EPIC BeadChips on PBMC-derived DNA from CCS in the St. Jude Lifetime Cohort. Tensor composition analysis was employed to deconvolute bulk DNAm and infer DNAm at each leukocyte subtype level, i.e., a single n (individuals) by m (DNAm sites) matrix of observed DNAm data was deconvoluted into multiple n by m matrices of DNAm data. Epigenetic age (EA, using Levine’s clock) and EAA (residuals from the fit of a simple linear regression of EA on chronological age at blood draw) were calculated for bulk PBMCs and each cell subtype (CD4T, CD8T, B, natural killer, and monocyte). Cardiomyopathy (CMP) was assessed by echocardiography, and severity graded (2 = moderate, 3 = severe/disabling, 4 = life-threatening and 5 = fatal) using a modified version of the National Cancer Institute Common Terminology Criteria for Adverse Events. Cumulative doses of anthracyclines and mean heart radiation doses (heart-RT) calculated through radiation dosimetry were abstracted from medical records. Associations between EAA and CMP were evaluated by multivariable Cox regression. Cell-type specific EA was highly correlated with bulk EA with Pearson r2 between 0.63 (CD8T) and 0.79 (CD4T), but the linear regression lines of cell-type specific EA against bulk EA differed in both intercept and slope, suggesting heterogeneity across leukocyte subtypes. Cell-type specific EAA was moderately correlated with bulk EAA with Pearson r2 between 0.23 (monocyte) and 0.29 (CD8T). Among 2,044 CCS (median age = 33.7 years), 104 (5.1%) developed CMP (≥grade 3). Among bulk EAA and five cell-type specific EAAs, monocyte EAA was the only one significantly associated with CMP (hazard ratio per standard deviation increase in EAA = 1.25, 95% CI = 1.04-1.50, P = 0.018). Cell sorting of PBMC followed by DNAm is currently underway for further validation. We showed an in-depth view of the variability of EAA across leukocyte subtypes, and more importantly, demonstrated that monocyte EAA was associated with CMP risk. Our novel finding is plausible and consistent with the literature implicating monocyte-derived cardiac macrophages in cardiac remodeling, which can be induced by cardiotoxic cancer treatment exposures in CCS. Therapeutic strategies that prevent deleterious effects of monocytes contributing to adverse cardiac remodeling, while sparing their essential immune functions, may prevent or ameliorate CMP among CCS. Citation Format: Cheng Chen, Qian Dong, Qin Na, Nan Song, John Easton, Heather L. Mulder, Emily Walker, Geoffrey Neale, Emily R. Finch, Qian Li, Yutaka Yasui, Daniel A. Mulrooney, Melissa M. Hudson, Kirsten K. Ness, Jinghui Zhang, Xiang Chen, Hui Wang, Leslie L. Robison, Zhaoming Wang. Monocyte-specific epigenetic age acceleration and cardiomyopathy risk among survivors of childhood cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4363.

519 Single Nucleus ATAC Sequencing Reveals Increased PPP1R17 Chromatin Accessibility Driving Cushing’s Disease

INTRODUCTION: Epigenetic drivers of pituitary adenomas causing Cushing’s disease (CD) are virtually unknown. Here, we investigate the epigenetic mechanisms underlying gene dysregulation in CD. METHODS: We isolated single nuclei from 3 CD adenoma – normal gland pairs and performed single nucleus RNA sequencing (snRNAseq) and assays for transposase-accessible chromatin (snATACseq, 10x Genomics). We integrated these data with prior paired single cell data (scRNAseq, n = 3) and bulk RNAseq (CD = 3, non-CD = 3). We performed bulk DNA methylation assays on independent adenomas (CD = 3, non-CD = 3; Illumina Infinium MethylationEPIC). CD adenomas were examined by multiplexed immunohistochemistry (mIHC). We generated murine corticotroph (mCort) cell lines stably transfected with lentiviral expression vectors (Origene) and assessed for cell-cycle changes (Click-IT EdU) and cell proliferation (OneGlo). RESULTS: snATACseq and snRNAseq data identified increased chromatin accessibility with upregulated PPP1R17 expression in single nuclei from CD adenomas, in agreement with our prior scRNAseq and bulk RNAseq data (16-fold in paired analysis, FDR &lt; 0.01). DNA methylation failed to identify global or local differential methylation at the PPP1R17 locus. mIHC confirmed PPP1R17 protein overexpression in human CD tumors. PPP1R17 overexpression in mCort cells accelerated the cell cycle with fewer cells accumulating in S-phase (16.4% vs 24.1%, P &lt; 0.01), and increased cell proliferation (two-way ANOVA P &lt; 0.01). CONCLUSIONS: We identified coordinated chromatin accessibility, transcriptional activation and protein expression of PPP1R17 in human CD adenomas compared to surrounding normal tissues, and recapitulated hyperproliferation in-vitro by stable PPP1R17 overexpression. Our findings uncover targetable epigenetic mechanisms in CD pathogenesis.

Ultrathin, High-Lifetime Silicon Nitride Membranes for Nanopore Sensing.

Thin membranes are highly sought-after for nanopore-based single-molecule sensing, and fabrication of such membranes becomes challenging in the ≲10 nm thickness regime where a plethora of useful molecule information can be acquired by nanopore sensing. In this work, we present a scalable and controllable method to fabricate silicon nitride (SixNy) membranes with effective thickness down to ∼1.5 nm using standard silicon processing and chemical etching using hydrofluoric acid (HF). Nanopores were fabricated using the controlled breakdown method with estimated pore diameters down to ∼1.8 nm yielding events >500,000 and >1,800,000 from dsDNA and bovine serum albumin (BSA) protein, respectively, demonstrating the high-performance and extended lifetime of the pores fabricated through our membranes. We used two different compositions of SixNy for membrane fabrication (near-stoichiometric and silicon-rich SixNy) and compared them against commercial membranes. The final thicknesses of the membranes were measured using ellipsometry and were in good agreement with the values calculated from the bulk etch rates and DNA translocation characteristics. The stoichiometry and the density of the membrane layers were characterized with Rutherford backscattering spectrometry while the nanopores were characterized using pH-conductance, conductivity-conductance, and power spectral density (PSD) graphs.

Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing.

Molecular subtyping of brain tissue provides insights into the heterogeneity of common neurodegenerative conditions, such as Alzheimer's disease. However, existing subtyping studies have mostly focused on single data modalities and only those individuals with severe cognitive impairment. To address these gaps, we applied similarity network fusion, a method capable of integrating multiple high-dimensional multi-omic data modalities simultaneously, to an elderly sample spanning the full spectrum of cognitive ageing trajectories. We analyzed human frontal cortex brain samples characterized by five omic modalities: bulk RNA sequencing (18 629 genes), DNA methylation (53 932 CpG sites), histone acetylation (26 384 peaks), proteomics (7737 proteins) and metabolomics (654 metabolites). Similarity network fusion followed by spectral clustering was used for subtype detection, and subtype numbers were determined by Eigen-gap and rotation cost statistics. Normalized mutual information determined the relative contribution of each modality to the fused network. Subtypes were characterized by associations with 13 age-related neuropathologies and cognitive decline. Fusion of all five data modalities (n = 111) yielded two subtypes (n S1 = 53, n S2 = 58), which were nominally associated with diffuse amyloid plaques; however, this effect was not significant after correction for multiple testing. Histone acetylation (normalized mutual information = 0.38), DNA methylation (normalized mutual information = 0.18) and RNA abundance (normalized mutual information = 0.15) contributed most strongly to this network. Secondary analysis integrating only these three modalities in a larger subsample (n = 513) indicated support for both three- and five-subtype solutions, which had significant overlap, but showed varying degrees of internal stability and external validity. One subtype showed marked cognitive decline, which remained significant even after correcting for tests across both three- and five-subtype solutions (p Bonf = 5.9 × 10-3). Comparison to single-modality subtypes demonstrated that the three-modal subtypes were able to uniquely capture cognitive variability. Comprehensive sensitivity analyses explored influences of sample size and cluster number parameters. We identified highly integrative molecular subtypes of ageing derived from multiple high dimensional, multi-omic data modalities simultaneously. Fusing RNA abundance, DNA methylation, and histone acetylation measures generated subtypes that were associated with cognitive decline. This work highlights the potential value and challenges of multi-omic integration in unsupervised subtyping of post-mortem brain.

Development of a cost-effective, morphology-preserving method for DNA isolation from bulk invertebrate trap catches: Tephritid fruit flies as an exemplar.

Insect identification and preservation of voucher specimens is integral to pest diagnostic and surveillance activities; yet bulk-trapped insects are a diagnostic challenge due to high catch numbers and the susceptibility of samples to environmental damage. Many insect trap catches rely on examination of morphological characters for species identifications, which is a time consuming and highly skilled task, hence there is a need for more efficient molecular approaches. Many bulk DNA extraction methods require destructive sampling of specimens, resulting in damaged, or fully destroyed, voucher specimens. We developed an inexpensive, rapid, bulk DNA isolation method that preserves specimens as pinned vouchers to a standard that allows for post-extraction morphological examination and inclusion in insect reference collections. Our protocol was validated using a group of insects that are time-consuming to identify when trapped in large numbers-the dacine fruit flies (Diptera: Tephritidae: Dacinae). In developing our method, we evaluated existing protocols against the following criteria: effect on morphology; suitability for large trap catches; cost; ease of handling; and application to downstream molecular diagnostic analyses such as real-time PCR and metabarcoding. We found that the optimum method for rapid isolation of DNA extraction was immersing flies in a NaOH:TE buffer at 75°C for 10 minutes, without the need for proteinase K or detergents. This HotSOAK method produced sufficient high-quality DNA whilst preserving morphological characters suitable for species-level identification with up to 20,000 flies in a sample. The lysates performed well in down-stream analyses such as loop-mediated isothermal amplification (LAMP) and real-time PCR applications, while for metabarcoding PCR the lysate required an additional column purification step. Development of this method is a key step required for upscaling our capacity to accurately detect insects captured in bulk traps, whether for biodiversity, biosecurity, or pest management objectives.

Application of high-throughput single-nucleus DNA sequencing in pancreatic cancer

Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.

Navigating the seven challenges of taxonomic reference databases in metabarcoding analyses.

Assessment of biodiversity using metabarcoding data, such as from bulk or environmental DNA sampling, is becoming increasingly relevant in ecology, biodiversity sciences and monitoring. Thereby, the taxonomic identification of species from their DNA sequences relies strongly on reference databases that link genetic sequences to taxonomic names. These databases vary in completeness and availability, depending on the taxonomic group studied and the genetic region targeted. The incompleteness of reference databases is an important argument to explain the nondetection by metabarcoding of species supposedly present. However, there exist further and generally overlooked problems with reference databases that can lead to false or inaccurate inferences of taxonomic assignment. Here, we synthesize all possible problems inherent to reference databases. In particular, we identify a complete, mutually nonexclusive list of seven classes of challenges when it comes to selecting, developing and using a reference database for taxonomic assignment. These are: (i) mislabelling, (ii) sequencing errors, (iii) sequence conflict, (iv) taxonomic conflict, (v) low taxonomic resolution, (vi) missing taxa and (vii) missing intraspecific variants. For each problem identified, we provide a description of possible consequences on the taxonomic assignment process. We illustrate the respective problem with examples taken from the literature or obtained by quantitative analyses of public databases, such as GenBank or BOLD. Finally, we discuss possible solutions to the identified problems and how to navigate them. Only by raising users' awareness of the limitations of metabarcoding data and DNA reference databases will adequate interpretations of these data be achieved.

Single-Cell RNA Sequencing for the Detection of Clonotypic V(D)J Rearrangements in Multiple Myeloma.

Multiple myeloma (MM) has a highly heterogeneous genetic background, which complicates its molecular tracking over time. Nevertheless, each MM patient's malignant plasma cells (PCs) share unique V(D)J rearranged sequences at immunoglobulin loci, which represent ideal disease biomarkers. Because the tumor-specific V(D)J sequence is highly expressed in bulk RNA in MM patients, we wondered whether it can be identified by single-cell RNA sequencing (scRNA-seq). To this end we analyzed CD138+ cells purified from bone marrow aspirates of 19 samples with PC dyscrasias by both a standard method based on bulk DNA and by an implementation of the standard 10x Genomics protocol to detect expressed V(D)J sequences. A dominant clonotype was easily identified in each sample, accounting on average for 83.65% of V(D)J-rearranged cells. Compared with standard methods, scRNA-seq analysis proved highly concordant and even more effective in identifying clonal productive rearrangements, by-passing limitations related to the misannealing of consensus primers in hypermutated regions. We next validated its accuracy to track 5 clonal cells with absolute sensitivity in a virtual sample containing 3180 polyclonal cells. This shows that single-cell V(D)J analysis may be used to find rare clonal cells, laying the foundations for functional single-cell dissection of minimal residual disease.

219P Spatial sequencing of T cell repertoire in breast cancer

Analysis of T-cell repertoire (TCR) has been proposed as a new approach to better understand the adaptive immune response in cancer diseases. Next generation sequencing of the TCR has proven to be a powerful approach to characterize this repertoire, with potential applications to select and follow patients who benefit from immunomodulatory therapies. However, current TCR sequencing in tumor tissues is based on bulk RNA or DNA extraction, which does not provide neither the functional information at the clonotype level nor the spatial context.

Single-Cell Transcriptome Reveals Comprehensive Immune Profiles of T Follicular Helper Cell Lymphoma

Background: Angioimmunoblastic T-cell lymphoma and other nodal lymphomas of T follicular helper (TFH) cell origin (TFH lymphoma) have a poor prognosis and are associated with immune dysregulation. However, comprehensive immune profiles of TFH lymphoma have not been fully investigated. The RHOA G17V mutation (G17V) is a disease-specific mutation found in 60-70% of TFH lymphoma and considered to gain a novel function through binding to VAV1 protein. Nevertheless, the prevalence of homozygous (Homo) and heterozygous (Hetero) G17V mutations and the difference in their oncogenicity due to its zygosity have not been elucidated. Here, we performed single-cell transcriptomic analysis to characterize tumor and immune cells of TFH lymphoma. Methods: We performed single-cell RNA sequencing (scRNA-seq) and T-cell/B-cell receptor sequencing (scTCR/BCR-seq) for 9 lymph nodes (LNs) and 16 peripheral blood (PB) from 14 TFH lymphoma patients (9 at initial diagnosis [ID] and 5 at relapsed/refractory diagnosis [RR]), as well as 7 homeostatic LNs (HLNs) from patients with solid cancers (Fig. 1). Whole-exome sequencing (WES) was also performed for genetic mutation analysis using bulk DNA extracted from tumor tissues and PB of the same cohort as scRNA-seq. scRNA-seq and scTCR/BCR-seq libraries were constructed using the Chromium system (10x Genomics). Publicly available scRNA-seq data from 5 healthy donors (HDs) were also integrated as control. scRNA-seq data analysis was performed by Seurat, Scater, and Batchelor for quality control, integration, and clustering; SingleR for annotation; Immunarch for TCR/BCR repertoire analysis; gene set variation analysis (GSVA) for pathway analysis, and CellPhoneDB for cell-cell interaction analysis. Genomon2 pipeline was used for calling somatic mutations in WES data. Subsequently, VarTrix was applied to estimate mutations detected by WES in scRNA-seq data. Results: In total, 68,738 cells from LNs and 98,891 cells from PB were analyzed. Unsupervised clustering and annotation by canonical markers identified 4 major cell types: CD4/CD8+ T, natural killer (NK), B, and myeloid cells. Tumor cells were identified by the expanded TCR clonality and the TFH-like gene expression signatures. Next, using scRNA-seq data, we reanalyzed a total of 393 somatic mutations discovered by WES and identified 15 mutations in more than 5 cells of scRNA-seq data, of which only RHOA G17V was identified in multiple samples. G17V-mutated cells were detected in 4 LN and 6 PB samples, mostly restricted to tumor cells. G17V-Homo and Hetero cells were identified based on frequency of mutant reads. Differentially expression gene (DEG) analysis and GSVA in G17V-mutated tumor cells of LNs revealed that the regulatory signature was significantly activated in Homo, whereas the proliferation signature was up-regulated in Hetero. Additionally, DEG analysis identified three tumor-specific gene candidates and the expression of cell surface protein PLS3 was validated by flow cytometry and immunohistochemistry. Subsequently, we performed sub-clustering and GSVA of immune cells and found that dysfunctional CD8 T cells were significantly increased in LNs and PB of patients compared to controls and exhibited oligoclonal expansion by TCR repertoire analysis. Notably, TREG, complement component 1q positive macrophages (C1Q+ Mφ), and LAMP3+ dendritic cells (DCs) were significantly increased in LNs from patients with RR diseases than HLNs. DEG analysis and GSVA revealed high expression of PD-L1 and regulatory signatures in LAMP3+ DCs. Moreover, genes related to immune suppression were significantly upregulated in TREG of patients compared to those of controls. Finally, cell-cell interaction analysis uncovered that tumor cells and TREG of RR patients strongly interacted with C1Q+ Mφ and LAMP3+ DCs via CXCR3-CXCL9 and CCR4-CCL17 interactions, respectively, indicating that these myeloid cells not only induced TREG into tumor tissues but also actively interacted with tumor cells. Conclusion: Tumor cells of TFH lymphoma acquired the immunosuppressive signature in the clonal evolution process from the G17V Hetero to Homo. Furthermore, comprehensive immune profiling of TFH lymphoma revealed expansion of cells involved in the immune escape. These results unveiled the enrichment of immune evasive phenotypes in TFH lymphoma and suggested their contribution to treatment resistance in RR patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

CSIG-36. NOTCH3 DRIVES MENINGIOMA TUMORIGENESIS AND RESISTANCE TO RADIOTHERAPY

Abstract There are no approved targeted therapies for meningiomas and the cell types underlying meningeal tumorigenesis are incompletely understood. To address these limitations, we performed single-cell RNA sequencing of 57,114 cells from 8 human meningiomas and 54,607 cells from 3 canine meningiomas. Pseudotime, gene ontology, and copy number variant analyses revealed a population of pericyte-like meningioma cells that were conserved across human and canine tumors and were enriched in expression of Notch3 and other cancer stem cell genes. Deconvolution of cell types from bulk RNA sequencing and DNA methylation profiling of 200 human meningiomas integrated with immunohistochemistry (IHC), immunofluorescence (IF), and RNAScope demonstrated Notch3+ pericytes and Notch3 expression were enriched in high grade or Immune-enriched meningiomas, which were distinguished from other meningioma DNA methylation groups by genes driving vasculature development. IHC and IF of human meninges integrated with lineage tracing approaches using Notch3-CreERT2 ROSAmT/mG alleles in mice demonstrated Notch3 expression was restricted to the perivascular stem cell niche during meningeal development and homeostasis. Mice harboring Notch3-CreERT2 Nf2fl/fl alleles developed meningeal hyperproliferation. Overexpression of constitutively activated Notch3 (Notch3AICD) in Immune-enriched human meningioma cells increased the expression of cancer stem cell genes, driving clonogenic growth in vitro, limiting dilution tumor-initiating capacity in vivo, and resistance to radiotherapy in vivo. A selective Notch3 neutralizing antibody (αNRR3) blocked meningioma cell proliferation and expression of Notch3 target genes, inhibiting meningioma xenograft growth and prolonging overall survival. Single-cell RNA sequencing of 187,366 cells from meningioma xenografts after αNRR3 or radiotherapy treatment ± Notch3AICD overexpression revealed distinct meningioma cell-intrinsic or cell-extrinsic mechanisms driving responses to radiotherapy or αNRR3, respectively. Combined treatment with αNRR3 and radiotherapy additively blocked meningioma xenograft growth and extended survival benefit. In sum, these data shed light on a novel cell type, molecular mechanism, and therapeutic vulnerability in the most common primary intracranial tumor.

LTBK-08. Inferring cell type and cell state composition in glioblastoma from bulk DNA methylation profiles using multi-omic single-cell analyses

Abstract OBJECTIVE Cellular heterogeneity determines tumor phenotype and response to therapy. This is particularly pronounced in glioblastoma (GBM), which is characterized by multiple malignant cell states with distinct proliferation potentials, and different cell types of the microenvironment. Ideally, cellular heterogeneity is characterized using single cell genomic profiling techniques. However, these techniques remain challenging to apply in a diagnostic setting and to large retrospective patient cohorts (TCGA, GLASS, DKFZ and clinical trials). Instead, clinicians routinely support their diagnosis with bulk DNA methylation profiling, which generates robust results from low quality material but does not inform on cellular heterogeneity. We have developed a powerful new computational method to deconvolute bulk DNA methylation data and infer cellular heterogeneity within individual tumors, to support prognostic accuracy and personalized treatment decisions. METHODS Using both bulk and single-cell multi-omic datasets, we created a DNA methylation-based reference of cell types (malignant, glial, neuronal, and immune) within GBM tumors, and the state of malignant cells therein (stem-like vs. differentiated-like). Using this reference, our computational approach accurately deconvolutes bulk DNA methylation profiles of individual query samples. RESULTS High deconvolution accuracy of GBM heterogeneity was achieved from frozen and FFPE tissue samples, including those of low quality or purity (Jensen Shannon divergence for composition similarity &amp;lt; 0.05). Our approach eliminates bias derived from the microenvironment, and results in patient stratification that harmonizes the DNA methylation- and RNA-based classifications of GBM. It also reveals the inter- and intra-tumoral links between the genetic, DNA methylation, and transcriptomic components of GBM pathology, and suggests their specific impacts on treatment efficacy. To facilitate clinical translation, we created a public website that allows clinicians to infer the relative abundance of different cell states within a tumor at the click of a button.

A Droplet Digital PCR (ddPCR) Assay to Detect Phthorimaea absoluta (Lepidoptera: Gelechiidae) in Bulk Trap Samples.

The moth species Phthorimaea absoluta (Meyrick) (formerly Tuta absoluta) is serious threat to tomato and other Solanaceous crops worldwide and is invasive throughout Europe, Asia, and Africa. While P. absoluta has not yet been found in the U.S. recent detections in the Caribbean have raised concerns that the species could be introduced to mainland North America. To improve detection capacity, a droplet digital PCR (ddPCR) assay was developed that employs a nondestructive bulk DNA extraction method able to detect one P. absoluta sample among 200 nontargets. Such high-throughput and sensitive molecular assays are essential to preventing introductions through early detection and response. This assay can also be used in areas where P. absoluta is established to monitor outbreaks and track migratory patterns.

Lineage Landscape: a comprehensive database that records lineage commitment across species.

Commitment to specific cell lineages is critical for mammalian embryonic development. Lineage determination, differentiation, maintenance, and organogenesis result in diverse life forms composed of multiple cell types. To understand the formation and maintenance of living individuals, including human beings, a comprehensive database that integrates multi-omic information underlying lineage differentiation across multiple species is urgently needed. Here, we construct Lineage Landscape, a database that compiles, analyzes and visualizes transcriptomic and epigenomic information related to lineage development in a collection of species. This landscape draws together datasets that capture the ongoing changes in cell lineages from classic model organisms to human beings throughout embryonic, fetal, adult, and aged stages, providing comprehensive, open-access information that is useful to researchers of a broad spectrum of life science disciplines. Lineage Landscape contains single-cell gene expression and bulk transcriptomic, DNA methylation, histone modifications, and chromatin accessibility profiles. Using this database, users can explore genes of interest that exhibit dynamic expression patterns at the transcriptional or epigenetic levels at different stages of lineage development. Lineage Landscape currently includes over 6.6 million cells, 15 million differentially expressed genes and 36 million data entries across 10 species and 34 organs. Lineage Landscape is free to access, browse, search, and download at http://data.iscr.ac.cn/lineage/#/home.

Meiotic crossover detection from single-cell DNA sequencing of sperm cells and bulk DNA sequencing of BC1F1 pups

Meiotic crossover detection from single-cell DNA sequencing of sperm cells and bulk DNA sequencing of BC1F1 pups

Prognosis and Immunological Characteristics of PGK1 in Lung Adenocarcinoma: A Systematic Analysis.

Background: Aerobic glycolysis plays a key role in tumor metabolic reprogramming to reshape the immune microenvironment. The phosphoglycerate kinase 1 (PGK1) gene codes a glycolytic enzyme that converts 1,3-diphosphoglycerate to 3-phosphoglycerate. However, in lung adenocarcinoma (LUAD), the role of PGK1 in altering the tumor microenvironment (TME) has not yet been determined. Methods: Raw data, including bulk DNA and mRNA-seq data, methylation modification data, single-cell RNA-seq data, proteomics data, clinical case characteristics survival, immunotherapy data, and so on, were obtained from multiple independent public data sets. These data were reanalyzed to uncover the prognosis and immunological characteristics of PGK1 in LUAD. Results: We found that PGK1 mRNA and protein were considerably over-expressed in LUAD compared to normal tissue and that high PGK1 expression is associated with poorer prognostic outcomes in LUAD. The enrichment analysis of PGK1 co-expressed genes in lung adenocarcinoma revealed that PGK1 may be involved in hypoxia, metabolism, DNA synthesis, cell cycle, PI3K/AKT, and various immune and inflammatory signaling pathways. Furthermore, PGK1 is also linked to the recruitment of numerous immune cells, including aDC (dendritic cells), macrophages, and neutrophils. More importantly, PGK1 was highly expressed in immunosuppressive cells, including M2 macrophages, Tregs, and exhausted T cells, among others. Finally, higher PGK1 expression indicated significant correlations to immune checkpoints, TMB (tumor mutation burden), and high response to immunotherapy. Conclusions: The presented findings imply that PGK1, as a glycolysis core gene, may be important for the modification of the immune microenvironment by interacting with the tumor metabolism. The results of this study provide clues for a potential immunometabolic combination therapy strategy in LUAD, for which more experimental and clinical translational research is needed.

CNAViz: An interactive webtool for user-guided segmentation of tumor DNA sequencing data.

Copy-number aberrations (CNAs) are genetic alterations that amplify or delete the number of copies of large genomic segments. Although they are ubiquitous in cancer and, thus, a critical area of current cancer research, CNA identification from DNA sequencing data is challenging because it requires partitioning of the genome into complex segments with the same copy-number states that may not be contiguous. Existing segmentation algorithms address these challenges either by leveraging the local information among neighboring genomic regions, or by globally grouping genomic regions that are affected by similar CNAs across the entire genome. However, both approaches have limitations: overclustering in the case of local segmentation, or the omission of clusters corresponding to focal CNAs in the case of global segmentation. Importantly, inaccurate segmentation will lead to inaccurate identification of CNAs. For this reason, most pan-cancer research studies rely on manual procedures of quality control and anomaly correction. To improve copy-number segmentation, we introduce CNAViz, a web-based tool that enables the user to simultaneously perform local and global segmentation, thus overcoming the limitations of each approach. Using simulated data, we demonstrate that by several metrics, CNAViz allows the user to obtain more accurate segmentation relative to existing local and global segmentation methods. Moreover, we analyze six bulk DNA sequencing samples from three breast cancer patients. By validating with parallel single-cell DNA sequencing data from the same samples, we show that by using CNAViz, our user was able to obtain more accurate segmentation and improved accuracy in downstream copy-number calling.

Embryo tracking system for high-throughput sequencing-based preimplantation genetic testing

Can the embryo tracking system (ETS) increase safety, efficacy and scalability of massively parallel sequencing-based preimplantation genetic testing (PGT)? Applying ETS-PGT, the chance of sample switching is decreased, while scalability and efficacy could easily be increased substantially. Although state-of-the-art sequencing-based PGT methods made a paradigm shift in PGT, they still require labor intensive library preparation steps that makes PGT cost prohibitive and poses risks of human errors. To increase the quality assurance, efficiency, robustness and throughput of the sequencing-based assays, barcoded DNA fragments have been used in several aspects of next-generation sequencing (NGS) approach. We developed an ETS that substantially alleviates the complexity of the current sequencing-based PGT. With (n = 693) and without (n = 192) ETS, the downstream PGT procedure was performed on both bulk DNA samples (n = 563) and whole-genome amplified (WGAed) few-cell DNA samples (n = 322). Subsequently, we compared full genome haplotype landscapes of both WGAed and bulk DNA samples containing ETS or no ETS. We have devised an ETS to track embryos right after whole-genome amplification (WGA) to full genome haplotype profiles. In this study, we recruited 322 WGAed DNA samples derived from IVF embryos as well as 563 bulk DNA isolated from peripheral blood of prospective parents. To determine possible interference of the ETS in the NGS-based PGT workflow, barcoded DNA fragments were added to DNA samples prior to library preparation and compared to samples without ETS. Coverages and variants were determined. Current PGT protocols are quality sensitive and prone to sample switching. To avoid sample switching and increase throughput of PGT by sequencing-based haplotyping, six control steps should be carried out manually and checked by a second person in a clinical setting. Here, we developed an ETS approach in which one step only in the entire PGT procedure needs the four-eyes principal. We demonstrate that ETS not only precludes error-prone manual checks but also has no effect on the genomic landscape of preimplantation embryos. Importantly, our approach increases efficacy and throughput of the state-of-the-art PGT methods. Even though the ETS simplified sequencing-based PGT by avoiding potential errors in six steps in the protocol, if the initial assignment is not performed correctly, it could lead to cross-contamination. However, this can be detected in silico following downstream ETS analysis. Although we demonstrated an approach to evaluate purity of the ETS fragment, it is recommended to perform a pre-PGT quality control assay of the ETS amplicons with non-human DNA, such that the purity of each ETS molecule can be determined prior to ETS-PGT. The ETS-PGT approach notably increases efficacy and scalability of PGT. ETS-PGT has broad applicative value, as it can be tailored to any single- and few-cell sequencing approach where the starting specimen is scarce, as opposed to other methods that require a large number of cells as the input. Moreover, ETS-PGT could easily be adapted to any sequencing-based diagnostic method, including PGT for structural rearrangements and aneuploidies by low-pass sequencing as well as non-invasive prenatal testing. M.Z.E. is supported by the EVA (Erfelijkheid Voortplanting & Aanleg) specialty program (grant no. KP111513) of Maastricht University Medical Centre (MUMC+), and the Horizon 2020 innovation (ERIN) (grant no. EU952516) of the European Commission. N/A.

TFIIH moonlighting at telomeres.

Although telomeres are essential for chromosome stability, they represent fragile structures in our genome. Telomere shortening occurs during aging in cells lacking telomerase due to the end replication problem. In addition, recent work uncovered that the bulk of telomeric DNA poses severe hurdles for the semiconservative DNA replication machinery, requiring the assistance of an increasing number of specialized factors that prevent accidental telomere loss or damage events. In this issue of Genes & Development, Yang and colleagues (pp. 956-969) discover that TFIIH, a basic component of the PolII transcription initiation and nucleotide excision repair machinery, facilitates telomere replication. TFIIH is recruited to telomeres by the shelterin component TRF1, taking on at telomeres a moonlighting function.