Deep Sequencing Research Articles

Dynamic 3D Point Cloud Sequences as 2D Videos.

Dynamic 3D point cloud sequences serve as one of the most common and practical representation modalities of dynamic real-world environments. However, their unstructured nature in both spatial and temporal domains poses significant challenges to effective and efficient processing. Existing deep point cloud sequence modeling approaches imitate the mature 2D video learning mechanisms by developing complex spatio-temporal point neighbor grouping and feature aggregation schemes, often resulting in methods lacking effectiveness, efficiency, and expressive power. In this paper, we propose a novel generic representation called Structured Point Cloud Videos (SPCVs). Intuitively, by leveraging the fact that 3D geometric shapes are essentially 2D manifolds, SPCV re-organizes a point cloud sequence as a 2D video with spatial smoothness and temporal consistency, where the pixel values correspond to the 3D coordinates of points. The structured nature of our SPCV representation allows for the seamless adaptation of well-established 2D image/video techniques, enabling efficient and effective processing and analysis of 3D point cloud sequences. To achieve such re-organization, we design a self-supervised learning pipeline that is geometrically regularized and driven by self-reconstructive and deformation field learning objectives. Additionally, we construct SPCV-based frameworks for both low-level and high-level 3D point cloud sequence processing and analysis tasks, including action recognition, temporal interpolation, and compression. Extensive experiments demonstrate the versatility and superiority of the proposed SPCV, which has the potential to offer new possibilities for deep learning on unstructured 3D point cloud sequences.

Deep sequencing analysis of chloroplast transcription and splicing in Euglena gracilis

Deep sequencing analysis of chloroplast transcription and splicing in Euglena gracilis

Genetic species concept as applied to multilocus nuclear data

Using the example of multiple species groups and species complexes, it is empirically shown that the resolving power of a set of 10–20 nuclear loci is insufficient for the study of their genetic differentiation. For the adequate analysis of phylogenetic relationships (including reticulation events) and assessment of divergence levels within such groups of closely related species, it is necessary to multiply the number of nuclear loci and transit to high-throughput next-generation deep sequencing. However, the question of the genomic coverage required for the purposes of such study remains open. In other words, exactly how many genes in a set are needed to measure the genetic distance resolving the relationships between branches on the phylogenetic tree reconstruction of a complex of closely related species? We chose protein-coding sequences as a standard set of markers. Distances for 160–180 genes with a combined length of 270 000–300 000 bp were used to estimate the divergence levels of closely related mammalian species. In most cases, the interspecific distances are within the 0.15–0.75% range (median of 0.33%). The range of distances between semi-species is 0.12–0.28% (median of 0.14%). Intraspecific distances are always lower than 0.11%. Rodents show higher values of interspecific distances, 0.25–2.3% (median of 0.72%); distances between half-species range from 0.1 to 0.35%. To determine the number of nuclear loci and their combined length sufficient for the calculation of a genetic distance, we use simulations based on a model that included the following parameters: the average rate of gene evolution, its dispersion, and the level of polymorphism in the modern and ancestral populations. We performed a preliminary analysis of the distribution of loci evolution rates among mammalian taxa based on the data on ~50 thousand nuclear markers. It is shown that a relative error of 10–15%, comparable to the same value for mitochondrial distances between close species based on individual genes (approximately 1000 bp in length), is achieved using approximately 100 loci of 300 bp in length. Based on these data, we propose the following working hypothesis: the threshold of interspecific/intraspecific genetic distance calculated on the basis of the exons most frequently used in mammalian molecular phylogenetics is approximately 0.15%. This hypothesis assumes a species rank for the forms in statu nascendi. It should be noted that not all “good” species have significant genetic distances, since in some cases reproductive barriers form faster than substitutions accumulate in the genome.

MatP local enrichment delays segregation independently of tetramer formation and septal anchoring in Vibrio cholerae.

Vibrio cholerae harbours a primary chromosome derived from the monochromosomal ancestor of the Vibrionales (ChrI) and a secondary chromosome derived from a megaplasmid (ChrII). The coordinated segregation of the replication terminus of both chromosomes (TerI and TerII) determines when and where cell division occurs. ChrI encodes a homologue of Escherichia coli MatP, a protein that binds to a DNA motif (matS) that is overrepresented in replication termini. Here, we use a combination of deep sequencing and fluorescence microscopy techniques to show that V. cholerae MatP structures TerI and TerII into macrodomains, targets them to mid-cell during replication, and delays their segregation, thus supporting that ChrII behaves as a bona fide chromosome. We further show that the extent of the segregation delay mediated by MatP depends on the number and local density of matS sites, and is independent of its assembly into tetramers and any interaction with the divisome, in contrast to what has been previously observed in E. coli.

Enriching the future of public health microbiology with hybridization bait capture.

SUMMARYPublic health microbiology focuses on microorganisms and infectious agents that impact human health. For years, this field has relied on culture or molecular methods to investigate complex samples of public health importance. However, with the increase in accuracy and decrease in sequencing cost over the last decade, there has been a transition to the use of next-generation sequencing in public health microbiology. Nevertheless, many available sequencing methods (e.g., shotgun metagenomics and amplicon sequencing) do not work well in complex sample types, require deep sequencing, or have inherent biases associated with them. Hybridization bait capture, also known as target enrichment, brings in solutions for such limitations. It is an increasingly popular technique to simultaneously characterize many thousands of genetic elements while reducing the amount of sequencing needed (thereby reducing the sequencing costs). Here, we summarize the concept of hybridization bait capture for public health, reviewing a total of 35 bait sets designed in six key topic areas for public health microbiology [i.e., antimicrobial resistance (AMR), bacteria, fungi, parasites, vectors, and viruses], and compare hybridization bait capture to previously relied upon methods. Furthermore, we provide an in-depth comparison of the three most popular bait sets designed for AMR by evaluating each of them against three major AMR databases: Comprehensive Antibiotic Resistance Database, Microbial Ecology Group Antimicrobial Resistance Database, and Pathogenicity Island Database. Thus, this article provides a review of hybridization bait capture for public health microbiologists.

Highly sensitive deep panel sequencing of 27 HPV genotypes in prostate cancer biopsies results in very low detection rates and indicates that HPV is not a major etiological driver of this malignancy.

Human papillomavirus (HPV) has been proposed to contribute to the carcinogenesis of prostate cancer. However, previous studies have yielded conflicting results. This study aims to add useful information to the ongoing discussion concerning the association between HPV infection and prostate cancer. We used two high-throughput next-generation sequencing (NGS) approaches to detect HPV RNA in malignant and adjacent normal (AN) prostate tissue (cohorts 1 and 2) and HPV DNA from carcinogenic and probably/possibly carcinogenic-classified HPV types (cohort 3) in malignant prostate, AN prostate, and benign prostatic hyperplasia (BPH) tissues. In total, 0% (cohort 1: 0/83, cohort 2: 0/16) of the malignant prostate tissue samples and 0% (cohort 1: 0/23, cohort 2: 0/8) of the AN prostate tissue samples were positive for HPV RNA. A total of 8.3% (1/12) of the BPH samples, 0% (0/28) of the AN samples, and 0.8% (1/132) of the malignant prostate samples were positive for HPV16 DNA. However, the normalized read count of the HPV16-positive malignant sample was close to the cut-off. In addition, no other carcinogenic-classified HPV types were detected in any of the BPH, AN, or malignant prostate tissue samples. Our study does not support HPV infection as a major contributor to the etiology of prostate cancer.

Abstract IA025: A DNA methylation atlas of normal human cell types

Abstract DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies. Citation Format: Tommy Kaplan. A DNA methylation atlas of normal human cell types [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr IA025.

Abstract B057: Base-error model (BEM) for improved detection of ctDNA in lymph samples of HPV-negative head and neck cancer patients

Abstract Introduction: Previously we demonstrated that ctDNA present in lymphatic exudate collected via surgical drains (“lymph”) outperformed plasma for detecting minimal residual disease (MRD) in head and neck squamous cell carcinoma (HNSCC) patients through a targeted sequencing (TS) approach. However, artifacts introduced during library preparation and sequencing remain challenges to sensitive low allelic fraction mutation detection. To enhance the performance of the TS approach, we characterized the background noise in lymph samples and developed a base-error model (BEM) that reduces sequencing artifacts and maximizes ctDNA signal. Methods: Lymph and blood were collected from 44 HPV-negative HNSCC patients postoperatively at 24 hours along with resected tumor. Cell-free DNA was extracted from lymph and sequenced using a custom TS panel with unique molecular identifiers (UMI). Somatic mutations were identified by tumor and blood exome sequencing (200x). Five patients had <2 mutations in tumor and were excluded. Two patients were censored due to lack of clinical data, yielding 17 patients with disease recurrence (REC) and 20 with no evidence of disease (NED) with >1 year of follow-up. Tumor-specific variants were force-called in lymph using a custom pipeline. A BEM of each tumor variant was built using a series of high-quality lymph reference samples to quantify the background noise. BEM was fit by Weibull distribution if more than 5 non-zero non-reference alleles were observed at a tumor variant position across the reference samples. Otherwise, Gaussian distribution was used to fit BEM. Force-called variants were considered artifacts if the variant allele fraction (VAF) was not greater than BEM cutoff controlled by false discovery rate. Patients were considered MRD positive if the mean VAF was greater than the estimated limit of detection. The Kaplan-Meier (KM) estimator with log-rank test and Cox proportional-hazards model were used for survival analyses. Results: Background noise was observed in reference lymph samples across all 12 nucleotide substitution classes. Out of 299 single nucleotide variants (SNVs), 94 were determined as artifacts by BEM. Among the artifacts, 77 were C/G to A/T mutations, indicating that the majority of recurrent background artifact in TS is likely the result of oxidative damage. The artifacts had VAFs ranging from 0.004% to 0.12% with median of 0.02%. Incorporation of BEM in lymph TS showed significantly improved specificity (sensitivity (SN) = 71%, specificity (SP) = 65%; p = 0.027, Hazard ratio (HR) = 3.07) compared to the same cohort without BEM (SN = 76%, SP = 30%, p = 0.60, HR = 1.34). Conclusions: BEM is a sensitive and robust method to improve ctDNA detection accuracy in TS. We demonstrated its utility in improving recurrence prediction in a HNSCC cohort. Given its advantages, we envision that BEM will prove useful as a general strategy for deep sequencing applications requiring precise digital quantification of low frequency alleles in TS. Citation Format: Zhuosheng Gu, Maciej Pacula, Seka Lazare, Noah Earland, Marra S. Francis, Adam Harmon, Megan Long, Aadel A. Chaudhuri, Jose P. Zevallos, Wendy Winckler. Base-error model (BEM) for improved detection of ctDNA in lymph samples of HPV-negative head and neck cancer patients [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B057.

Abstract B009: Individualized-tumor-informed panel approach enables ultra-sensitive ctDNA-based minimal residue disease monitoring for high-risk pediatric cancers

Abstract While the use of ctDNA-based minimal residual disease (MRD) monitoring is gaining popularity in adult cancers, this approach is not yet widely adopted in pediatric cancers (PCs). We developed a robust and sensitive assay to monitor ctDNA in PCs, which overcomes PC-specific challenges including low tumor mutational burden, paucity of hotspot mutations and low blood volume. To address these challenges, our innovations include personalized panel design that targets primary tumor mutations from each patient, a fixed panel targeting hotspot mutations, error suppression from duplex deep sequencing and customized pipeline for tumor burden estimation. We retrospectively analyzed 661 blood or cerebrospinal fluid (CSF) samples from 168 patients. We achieved an average detection limit of 0.005% ctDNA purity leading to MRD detected ranging from 0.001% to 100% with brain tumor consistently showing a low MRD. At disease diagnosis, progression and relapse, our assay identified ctDNA in over 93% of extra- cranial solid tumors, 90% of leukemia, 89% of sarcoma, and 90% of neuroblastoma. For brain tumors, we detected MRD in ∼90% of CSF samples, and in ∼60% of blood samples, a major advance over previous approaches. Importantly, we detected MRD in ∼ 20% of cases with a clinically complete response, predicting relapse up to 6 months before clinical confirmation. Overall, these results demonstrate that our monitoring assay for PCs is an important addition to standard of care for precision-guided treatment. Citation Format: Rob Salomon, Wenhan Chen, Charles Shale, Mojgan Toumari, Aileen Lowe, Wenyan Li, Jingwei Chen, Sajad Razavi-Bazaz, Paulette Barahona, Louise Cui, Chelsea Mayoh, Sam El-Kamand, Vanessa Tyrrell, Marie Wong-Erasmus, Loretta MS Lau, Noemi Fuentes-Bolanos, Edwin Cuppen, Dong-Anh Khoung-Quang, Jordan Staunton, Marion K Mateos, Toby Trahair, Michelle Haber, David S Ziegler, Paul Ekert, Peter Priestley, Mark Cowley. Individualized-tumor-informed panel approach enables ultra-sensitive ctDNA-based minimal residue disease monitoring for high-risk pediatric cancers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B009.

Abstract PR003: ctDNA release kinetics and fragmentation to monitor treatment response and resistance in esophageal adenocarcinoma

Abstract Background: Esophageal adenocarcinoma (EAC) has a low 5-year survival rate and limited options for targeted therapies. Circulating tumor (ct)DNA isolated from liquid biopsies could help monitor patients to personalize treatment decisions. However, ctDNA studies in EAC remain sparse, and significant knowledge gaps exist in our understanding of ctDNA emission in response to therapy. The goal of this study was 1) to conduct a multimodal, longitudinal analysis of plasma cell free (cf)DNA in EAC patients and 2) to better understand the biology of ctDNA release during drug treatment. Methods: 1) A total of 189 longitudinal blood samples were collected from 41 EAC patients throughout treatment. cfDNA was isolated from baseline and post-neoadjuvant chemo samples for targeted deep sequencing alongside white blood cell controls. Shallow whole-genome sequencing was conducted on cfDNA for ichorCNA and fragmentomics analysis. 2) To dynamically monitor ctDNA fluctuations during EAC treatment, cfDNA was isolated from all other timepoints for digital (d)PCR quantification of the mutations identified from sequencing. ctDNA release kinetics were studied in vitro using three cell lines (OE19, FLO-1, A549), as well as our newly established cisplatin resistant model of OE19. ctDNA was analyzed by Qubit, dPCR, and Bioanalyzer. Annexin-V/PI flow cytometry was used to assess percentages of apoptotic and necrotic cells to correlate ctDNA to release mechanism. Results: 1) Sequencing has been completed for 21/41 patients and is ongoing for 20/41 patients. In the first 21 patients, somatic mutations were found in potential EAC driver genes, such as KRAS, TP53, ACVR2A, NOTCH1, and APC. Interestingly, in one patient’s cfDNA sample sequenced post neoadjuvant chemo, a novel mutation emerged in FBXW7, representing a potential resistance driver. ichorCNA tumor fraction (TF) values overall were low, and when using the recommended 0.03 TF estimate cutoff, there were significantly larger baseline TF values in metastatic (stage IVB) patients than those with localized disease (stage III) (p<0.05). 2) In vitro viable cancer cell numbers correlated to ctDNA levels, as measured by qubit and dPCR analysis. Additionally, cisplatin and 5-FU chemo treatments led to larger ctDNA release in all cells. ctDNA emission kinetics correlated to cytotoxicity (apoptosis and necrosis as shown through flow cytometry), with higher levels of ctDNA released by cisplatin-sensitive vs. resistant cells (p<0.05). Additionally, cisplatin treatment caused a shift in average ctDNA fragment size, with larger fragments observed during treatment, corresponding to an increased proportion of necrotic cells. Conclusions: This study reveals that multimodal cfDNA analysis can successfully be used in EAC patients to monitor treatment response and potentially identify resistance mechanisms. Moreover, in vitro models demonstrated a correlation of ctDNA emission and fragment length with chemo-cytotoxicity, shedding light on the release kinetics of DNA from cancer cells. Citation Format: Alexandra Bartolomucci, Laura Kienzle, Sarah Tadhg Ferrier, Lisa-Monique Edward, Jeffrey Bruce, Kwang-Bo Joung, Stephenie Prokopec, Wotan Zeng, Abirami Sharma, Kyle Dickinson, Nicholas Bertos, Jonathan Cools-Lartigue, Lorenzo Ferri, Trevor J. Pugh, Julia V. Burnier. ctDNA release kinetics and fragmentation to monitor treatment response and resistance in esophageal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR003.

Abstract 4145859: Clonal Hematopoiesis of Indeterminate Potential Increases Mortality Risk in Coronary Artery Disease

Background: Clonal hematopoiesis of indeterminate potential (CHIP) has been associated with an increased incidence of common late-onset diseases including myocardial infarction. Research Question: Here we examined the impact of CHIP on mortality in patients with coronary artery disease (CAD) and further explored potential underlying mechanisms. Methods: CAD patients were examined for CHIP-defining mutations using deep DNA sequencing. Propensity score matching was used to compare CHIP CAD with non-CHIP CAD patients. Survival was analyzed using Kaplan-Meier curves and Cox proportional hazard models. Functional aspects were investigated at the protein and RNA level in cardiovascular relevant human postmortem tissue from the Munich cardIovaScular StudIes biObaNk (MISSION), in CAD patients from an independent cohort and in in-vitro macrophage models. Results: Within 7,933 CAD patients screened by deep-DNA-sequencing with a 13 gene panel, 2,002 carried at least one CHIP defining mutation with a variant allele frequency ≥2%. After 1:1 matching with non-CHIP carriers we revealed a significantly elevated 3-year mortality in the group of CHIP carriers [HR 1.48 (CI 95% 1.23-1.78); p<0.0001)] as well as in carriers of mutations in one out of seven individual genes – ASXL1 , DNMT3A , PPM1D , SF3B1 , SRSF2 , TET2 , and U2AF1 . In human coronary atherosclerotic plaque we visualized CHIP-mutations within leukocytes. Further, within coronary artery plaque of deceased TET2 mutation carriers (n=26 vs. n=13 controls) we identified by proteomic profiling an upregulation of inflammatory and metabolic pathways, including enhanced lipid metabolism. In an independent cohort of CAD patients undergoing coronary bypass surgery, RNA sequencing data from monocyte-derived macrophages revealed in TET2 CHIP carriers associations with CAD complexity. TET2 -mutated macrophages studied in-vitro revealed an increased uptake of low-density lipoprotein (LDL) and oxidized LDL-cholesterol besides a known upregulation of inflammatory pathways. Conclusion: In summary, this study emphasizes CHIP as a significant prognostic factor in CAD patients, associated with increased complexity of CAD and altered gene expression within human coronary artery plaques. Mechanistically, TET2 mutations modify the behavior of CHIP-affected macrophages, leading to heightened inflammation and increased uptake of LDL-cholesterol.

Saturation profiling of drug-resistant genetic variants using prime editing.

Methods to characterize the functional effects of genetic variants of uncertain significance (VUSs) have been limited by incomplete coverage of the mutational space. In clinical oncology, drug resistance arising from VUSs can prevent optimal treatment. Here we introduce PEER-seq, a high-throughput method based on prime editing that can evaluate the functional effects of single-nucleotide variants (SNVs). PEER-seq introduces both intended SNVs and synonymous marker mutations using prime editing and deep sequences the endogenous target regions to identify the introduced SNVs. We generate and functionally evaluate 2,476 SNVs in the epidermal growth factor receptor gene (EGFR), including 99% of all possible variants in the canonical tyrosine kinase domain. We determined resistance profiles of 95% of all possible EGFR protein variants encoded in the whole tyrosine kinase domain against the common tyrosine kinase inhibitors afatinib, osimertinib and osimertinib in the presence of the co-occurring substitution T790M, in PC-9 cells. Our study has the potential to substantially improve the precision of therapeutic choices in clinical settings.

Novel Differentially Expressed LncRNAs Regulate Artemisinin Biosynthesis in Artemisia annua

Long non-coding RNAs (lncRNAs) are crucial in regulating secondary metabolite production in plants, but their role in artemisinin (ART) biosynthesis, a key anti-malarial compound from Artemisia annua, remains unclear. Here, by investigating high-artemisinin-producing (HAP) and lowartemisinin-producing (LAP) genotypes, we found that the final artemisinin content in A. annua is influenced by the quantity of the precursor compounds. We report on RNA deep sequencing in HAP and LAP genotypes. Based on the application of a stringent pipeline, 1419 novel lncRNAs were identified. Moreover, we identified 256 differentially expressed lncRNAs between HAP and LAP. We then established correlations between lncRNAs and artemisinin biosynthesis genes in order to identify a molecular framework for the differential expression of the pathway between the two genotypes. Three potential lncRNAs (MSTRG.33718.2, MSTRG.30396.1 and MSTRG.2697.4) linked to the key artemisinin biosynthetic genes (ADS: Amorpha-4,11-diene synthase, DXS: 1-deoxy-D-xylulose-5-phosphate synthase, and HMGS: 3-hydroxyl-3-methyglutaryl CoA synthase) were detected. Importantly, we observed that up-regulation of these lncRNAs positively modulates the target artemisinin biosynthetic genes, potentially leading to high artemisinin biosynthesis in HAP. In contrast, BAS (beta-amyrin synthase), which is involved in the artemisinin competing pathway, was strongly down-regulated in HAP compared to LAP, in line with the expression pattern of the linked lncRNA MSTRG.30396.1. By identifying and characterizing lncRNAs that are potentially linked to the regulation of key biosynthetic genes, this work provides new insights into the complex regulatory networks governing artemisinin production in A. annua. Such findings could pave the way for innovative approaches in metabolic engineering, potentially enhancing artemisinin yields and addressing challenges in sustainable production.

STEM-05. SHARED ONCOGENIC MUTATIONS IN THE SUBVENTRICULAR ZONE AND GLIOBLASTOMA: GENETIC AND CLINICAL IMPLICATIONS

Abstract The subventricular zone (SVZ), a neurogenic niche in the adult brain, is suspected to harbor neural stem cells (NSCs) that can acquire cancer-driving mutations and give rise to glioblastoma (GBM). Nevertheless, the corroborating genetic data are restricted to a small patient cohort. This study aimed to validate the presence of low-level oncogenic mutations in the SVZ of GBM patients and assess their clinical implications.. We performed deep hybrid capture sequencing of 15 GBM-associated genes and TERT promoter amplicon sequencing on triple-matched samples from the SVZ, primary tumor, and blood of 60 GBM patients. Approximately 62% of patients (40 of 61 patients) showed shared oncogenic mutations between the tumor and tumor-free SVZ, including TERT promoter, PTEN, and TP53. While shared mutations did not affect overall clinical profiles, TERT promoter mutations were significantly enriched in the shared group (94.9% of patients, p ≤ 0.001). RNA sequencing revealed upregulation of proliferation-related genes in tumors with shared SVZ mutations, and these patients had worse progression-free and overall survival (p = 0.038 and 0.031, respectively). This study provides the largest-scale genetic validation of the SVZ as a potential cellular origin of GBM, highlighting the distinct genetic and clinical features associated with shared oncogenic mutations. These findings warrant further investigation into the role of SVZ mutations in GBM genesis and their potential as therapeutic targets.

STEM-06. DISTANT ORIGIN OF GLIOBLASTOMA RECURRENCE: NEURAL STEM CELLS IN THE SUBVENTRICULAR ZONE SERVE AS A SOURCE OF TUMOR RECONSTRUCTION AFTER PRIMARY RESECTION

Abstract The recurrence of glioblastoma (GBM) remains unavoidable. Neural stem cells (NSCs) in the subventricular zone (SVZ) are considered a treatment target due to their potential role as the cellular origin of GBM. However, it is not yet confirmed whether GBM recurrence also originates from these cells. We first conducted deep sequencing on paired patient samples, including primary tumors (pT), recurrent tumors (rT), and SVZ tissues. The sequencing results revealed that in 5 out of 9 patients, the rT evolved independently from the SVZ rather than directly from the pT. Based on this, we developed a mouse model to simulate the GBM recurrence process by transforming SVZ NSCs into GFP-labeled cells carrying cancer mutations via electroporation. Following the resection of the tdTomato-labeled pT, we observed that 57.1% of the rT consists of a mixture of GFP- and tdTomato-positive tumor cells. To study the behavior of NSCs, we improved the existing mouse model by removing cortical tissue to simulate the complete resection of the pT. Four weeks post-surgical resection, 64.7% of tumors reconstructed in the resection cavity (RC), driven by the migration of OPC lineage cells. Time-course RNA-seq results indicated that the CXCL12-CXCR4 pathway might be responsible for driving the migration of SVZ NSCs to the RC. Further deconvolution and fluorescence staining analysis confirmed that CXCL12 secreted by endothelial cells around the RC could drive CXCR4-positive NSCs to migrate to the area. Additionally, the CXCR4 antagonist AMD3100 significantly reduced tumor recurrence in mice and extended survival. RNA-seq results from both mouse and human paired tumor samples confirmed that the CXCL12-CXCR4 pathway was enriched in locally recurrent tumor specimens and was correlated with shorter patient survival. In summary, our study provides evidence that GBM recurrence originates from SVZ NSCs. Moreover, we identified the CXCL12-CXCR4 pathway as a potential therapeutic target for GBM recurrence.

Genomic profiling of circulating tumor DNA for childhood cancers.

The utility of circulating tumor DNA (ctDNA) analysis has not been well-established for disease detection and monitoring of childhood cancers, especially leukemias. We developed PeCan-Seq, a deep sequencing method targeting diverse somatic genomic variants in cell-free samples in childhood cancer. Plasma samples were collected at diagnosis from 233 children with hematologic, solid and brain tumors. All children with hematologic malignancy (n = 177) had detectable ctDNA at diagnosis. The median ctDNA fraction was 0.77, and 97% of 789 expected tumor variants were identified, including sequence mutations, copy number variations, and structural variations responsible for oncogenic fusions. In contrast, ctDNA was detected in 19 of 38 solid tumor patients and 1 of 18 brain tumor patients. Somatic variants from ctDNA were correlated with minimal residual disease levels as determined by flow cytometry in serial plasma samples from patients with B-cell acute lymphoblastic leukemia (B-ALL). We showcase multi-tumor detection by ctDNA analysis for a patient with concurrent B-ALL and neuroblastoma. In conclusion, PeCan-seq sensitively identified heterogeneous ctDNA alterations from 1 mL plasma for childhood hematologic malignancies and a subset of solid tumors. PeCan-seq provides a robust, non-invasive approach to augment comprehensive genomic profiling at diagnosis and mutation-specific detection during disease monitoring.

Challenges and Prospects of DNA-Encoded Library Data Interpretation.

DNA-encoded library (DEL) technology is a powerful platform for the efficient identification of novel chemical matter in the early drug discovery process enabled by parallel screening of vast libraries of encoded small molecules through affinity selection and deep sequencing. While DEL selections provide rich data sets for computational drug discovery, the underlying technical factors influencing DEL data remain incompletely understood. This review systematically examines the key parameters affecting the chemical information in DEL data and their impact on hit triaging and machine learning integration. The need for rigorous data handling and interpretation is emphasized, with standardized methods being critical for the success of DEL-based approaches. Major challenges include the relationship between sequence counts and binding affinities, frequent hitters, and the influence of factors such as inhomogeneous library composition, DNA damage, and linkers on binding modes. Experimental artifacts, such as those caused by protein immobilization and screening matrix effects, further complicate data interpretation. Recent advancements in using machine learning to denoise DEL data and predict drug candidates are highlighted. This review offers practical guidance on adopting best practices for integrating robust methodologies, comprehensive data analysis, and computational tools to improve the accuracy and efficacy of DEL-driven hit discovery.

Deep RNA sequencing of human dorsal root ganglion neurons reveals somatosensory mechanisms.

Deep RNA sequencing of human dorsal root ganglion neurons reveals somatosensory mechanisms.

Neuroblastoma plasticity during metastatic progression stems from the dynamics of an early sympathetic transcriptomic trajectory.

Despite their indisputable importance in neuroblastoma (NB) pathology, knowledge of the bases of NB plasticity and heterogeneity remains incomplete. They may be rooted in developmental trajectories of their lineage of origin, the sympatho-adrenal neural crest. We find that implanting human NB cells in the neural crest of the avian embryo allows recapitulating the metastatic sequence until bone marrow involvement. Using deep single cell RNA sequencing, we characterize transcriptome states of NB cells and their dynamics over time and space, and compare them to those of fetal sympatho-adrenal tissues and patient tumors and bone marrow samples. Here we report remarkable transcriptomic proximities restricted to an early sympathetic neuroblast branch that co-exist with phenotypical adaptations over disease progression and recapitulate intratumor and interpatient heterogeneity. Combining avian and patient datasets, we identify a list of genes upregulated during bone marrow involvement and associated with growth dependency, validating the relevance of our multimodal approach.

Preliminary assessment of the diagnostic accuracy of cutaneous T-cell lymphoma through deep sequencing of T-cell receptor gamma gene.

The diagnostic challenges in early mycosis fungoides (MF) and other cutaneous T-cell lymphomas (CTCL) persist despite advancements in molecular methods. The study aims to provide a preliminary assessment of next-generation sequencing in analyzing T-cell receptor gamma (TRG) sequences for distinguishing CTCL from benign inflammatory disorders. Skin samples from CTCL and benign inflammatory skin disorders proven clinicopathologically were assessed for TRG by NGS. Our study analyzed skin samples from a total of 36 subjects, comprising 22 cases of CTCL, including 14 MF and 8 other CTCLs, alongside 14 cases of benign inflammatory skin disorders. According to the LymphoTrack criteria, monoclonality was detected in 75.0 % of the overall 24 CTCL patients. Specifically, in MF cases, 10 out of 14 were identified as monoclonality, with all four non-monoclonal cases being in the patch stage. For the other CTCL, 6 out of 8 cases displayed monoclonality. Among the overall 22 CTCL patients, 11 had multiple biopsies, with 9 displaying the same dominant clone across different sites. Among the 14 benign cases, only the case with erythrodermic psoriasis exhibited monoclonality. Our decision tree analysis suggests that a high frequency of the most abundant clone, its ratio to the third most abundant clone, and TRG V-I segment usage are effective markers aiding in diagnosing CTCL. Combination of the clone frequencies, and TRG V segment usage may enhance diagnosis for MF and other CTCLs, aiding in differentiating them from benign conditions. However, molecular diagnosis for patch-stage MF remains challenging.