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The crumbs cell polarity complex plays a crucial role in apical-basal epithelial polarity, cellular adhesion, and morphogenesis. Homozygous variants in human CRB1 result in autosomal recessive Leber congenital amaurosis (LCA) and retinitis pigmentosa (RP), with no established genotype-phenotype correlation. The associated protein complexes have key functions in developmental pathways; however the underlying disease mechanism remains unclear. Using the oko meduzym289/m289 (crb2a-/- ) zebrafish, we performed integrative transcriptomic (RNA-seq data) and methylomic (reduced representation bisulphite sequencing, RRBS) analysis of whole retina to identify dysregulated genes and pathways. Delayed retinal cell specification was identified in both the crb2a-/- zebrafish and CRB1 patient-derived retinal organoids, highlighting dysfunction of cell cycle modulation and epigenetic transcriptional control. Differential DNA methylation analysis revealed novel hypermethylated pathways involving biological adhesion, Hippo and transforming growth factor β (TGFβ) signalling. By integrating gene expression with DNA methylation using functional epigenetic modules (FEM), we identified 6 key modules involving cell cycle control and disturbance of TGFβ, BMP, Hippo, and SMAD protein signal transduction pathways, revealing significant interactome hotspots relevant to crb2a function, confirming the epigenetic control of gene regulation in early retinal development and points to a novel mechanism underlying CRB1-retinopathies. This article is protected by copyright. All rights reserved.

Gains and losses of DNA are prevalent in cancer and emerge as a consequence of inter-related processes of replication stress, mitotic errors, spindle multipolarity and breakage–fusion–bridge cycles, among others, which may lead to chromosomal instability and aneuploidy1,2. These copy number alterations contribute to cancer initiation, progression and therapeutic resistance3–5. Here we present a conceptual framework to examine the patterns of copy number alterations in human cancer that is widely applicable to diverse data types, including whole-genome sequencing, whole-exome sequencing, reduced representation bisulfite sequencing, single-cell DNA sequencing and SNP6 microarray data. Deploying this framework to 9,873 cancers representing 33 human cancer types from The Cancer Genome Atlas6 revealed a set of 21 copy number signatures that explain the copy number patterns of 97% of samples. Seventeen copy number signatures were attributed to biological phenomena of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, chromothripsis and haploidization. The aetiologies of four copy number signatures remain unexplained. Some cancer types harbour amplicon signatures associated with extrachromosomal DNA, disease-specific survival and proto-oncogene gains such as MDM2. In contrast to base-scale mutational signatures, no copy number signature was associated with many known exogenous cancer risk factors. Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations.

Supplementary Table from Systematic Evaluation of the Immune Environment of Small Intestinal Neuroendocrine Tumors

Supplementary Data from Systematic Evaluation of the Immune Environment of Small Intestinal Neuroendocrine Tumors

Purpose:The immune tumor microenvironment and the potential therapeutic opportunities for immunotherapy in small intestinal neuroendocrine tumors (siNET) have not been fully defined.Experimental Design:Herein, we studied 40 patients with primary and synchronous metastatic siNETs, and matched blood and normal tissue obtained during surgery. We interrogated the immune checkpoint landscape using multi-parametric flow cytometry. In addition, matched FFPE tissue was obtained for multi-parametric IHC to determine the relative abundance and distribution of T-cell infiltrate. Tumor mutational burden (TMB) was also assessed and correlated with immune infiltration.Results:Effector tumor-infiltrating lymphocytes (TIL) had a higher expression of PD-1 in the tumor microenvironment compared with the periphery. In addition, CD8+ TILs had a significantly higher co-expression of PD-1/ICOS and PD-1/CTLA-4 (cytotoxic T lymphocyte antigen-4) and higher levels of PD-1 expression compared with normal tissue. IHC revealed that the majority of cases have ≤10% intra-tumoral T cells but a higher number of peri-tumoral T cells, demonstrating an “exclusion” phenotype. Finally, we confirmed that siNETs have a low TMB compared with other tumor types in the TCGA database but did not find a correlation between TMB and CD8/Treg ratio.Conclusions:Taken together, these results suggest that a combination therapy approach will be required to enhance the immune response, using PD-1 as a checkpoint immunomodulator backbone in combination with other checkpoint targeting molecules (CTLA-4 or ICOS), or with drugs targeting other pathways to recruit “excluded” T cells into the tumor microenvironment to treat patients with siNETs.

The interplay among different cells in a tissue is essential for maintaining homeostasis. Although, disease states have been traditionally attributed to individual cell types, increasing evidence and new therapeutic options have demonstrated the primary role of multicellular functions to understand health and disease, opening new avenues to understand pathogenesis and develop new treatment strategies. We recently described the cellular composition and dynamics of the human oral mucosa; however, the spatial arrangement of cells is needed to better understand a morphologically complex tissue. Here, we link single-cell RNA sequencing, spatial transcriptomics, and high-resolution multiplex fluorescence in situ hybridisation to characterise human oral mucosa in health and oral chronic inflammatory disease. We deconvolved expression for resolution enhancement of spatial transcriptomic data and defined highly specialised epithelial and stromal compartments describing location-specific immune programs. Furthermore, we spatially mapped a rare pathogenic fibroblast population localised in a highly immunogenic region, responsible for lymphocyte recruitment through CXCL8 and CXCL10 and with a possible role in pathological angiogenesis through ALOX5AP. Collectively, our study provides a comprehensive reference for the study of oral chronic disease pathogenesis.

Liquid biopsies in the form of cell-free circulating tumor DNA (ctDNA) isolated from blood plasma or serum have shown great promise to be used as minimally-invasive markers in cancer patients providing an insight into the composition of both primary tumor and metastases, and an opportunity to assess clonal dynamics throughout the course of disease. CtDNA carries not only tumor- specific changes in its sequence but also distinctive epigenetic marks, namely DNA methylation patterns similar to the patterns in the primary tumor. Deregulation of tissue-specific DNA methylation patterns is an early event in carcinogenesis holding great promise to be exploited for early detection of cancer. However, in contrast to mutation detection, targeted DNA methylation sequencing of cfDNA remains a challenge due to low concentration and heavy fragmentation. The limiting step in detection of any analyte is the recovery of the DNA molecules. The pre-analytical steps in the DNA methylation detection pipeline include extraction of cfDNA molecules and their conversion using sodium bisulfite. Bisulfite conversion is a harsh chemical reaction that induces further fragmentation and degradation of already scarce cfDNA. In this study we compared commercial methods for cfDNA extraction and for bisulfite conversion to evaluate the yield, degradation and procedural loss. We compared five commercial kits for cfDNA extraction from blood plasma, three column-based (Qiagen’s QIAamp Circulating nucleic acids kit, Norgen’s Plasma/Serum Cell-Free Circulating DNA Purification and Macherey-Nagel’s NucleoSpin® Plasma XS) and two based on magnetic beads cleanup (Bioo Scientific’s Next Prep magnetic Cell-Free Circulating DNA isolation kitand Applied Biosystems’ Magmax Cell-Free Circulating DNA isolation kit. The kits used for bisulfite conversion were Zymo EZ DNA Methylation Lightning with column based purification and with magnetic beads purification, Zymo EZ DNA Methylation Direct with column based purification and with magnetic bead purification, Qiagen Epitect Fast DNA Bisulfite and Diagenode Premium Bisulfite kits. Same samples were processed by each of the kits, Sample degradation was determined using Agilent Bioanalyzer dsDNA kit. Yield was evaluated by Picogreen, absolute qPCR for single-copy gene and for contamination of gDNA by a B-cell specific assay, while procedural loss was determined based on the recovery of a synthetic spike-in. Citation Format: Miljana Tanic, Oluwadunni Emiloju, Pawan Dhami, Stephan Beck. Comparison of pre-analytical methods for DNA methylation analysis of cfDNA. [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 6012.

B cells generate antibodies that are essential for immune protection, but their subgroups are poorly defined. Here, we perform undirected deep profiling of B cells in matched human lymphoid tissues from deceased transplant organ donors and blood. In addition to identifying unanticipated features of tissue-based B cell differentiation, we resolve two subsets of marginal zone B (MZB) cells differing in cell surface and transcriptomic profiles, clonal relationships to other subsets, enrichment of genes in the NOTCH pathway, distribution bias within splenic marginal zone microenvironment, and immunoglobulin repertoire diversity and hypermutation frequency. Each subset is present in spleen, gut-associated lymphoid tissue, mesenteric lymph nodes, and blood. MZB cells and the lineage from which they are derived are depleted in lupus nephritis. Here, we show that this depletion is of only one MZB subset. The other remains unchanged as a proportion of total B cells compared with health. Thus, it is important to factor MZB cell heterogeneity into studies of human B cell responses and pathology.

Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies. While this is an effective treatment, it can result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier that could be used in donor selection in HCT to reduce the incidence of aGVHD.The discovery cohort of the study consisted of 288 donors from a population receiving HLA-A, -B, -C and -DRB1 matched unrelated donor HCT with T cell replete peripheral blood stem cell grafts for treatment of acute leukaemia or myelodysplastic syndromes after myeloablative conditioning. Donors were selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD that survived at least 100 days post-HCT matched for sex, age, disease and GVHD prophylaxis.Genome-wide DNA methylation was assessed using the Infinium Methylation EPIC BeadChip (Illumina), measuring CpG methylation at >850,000 sites across the genome. Following quality control, pre-processing and exploratory analyses, we applied a machine learning algorithm (Random Forest) to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91.To test this classifier, we used an independent validation cohort (n=288) selected using the same criteria as the discovery cohort. Different attempts to validate the classifier using the independent validation cohort failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort.Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.

The progress made in directed differentiation of stem cells has shown that understanding human pancreas development can provide cues for generating unlimited amounts of insulin-producing beta cells for transplantation therapy in diabetes. However, current differentiation protocols have not been successful in reproducibly generating functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single cell RNA sequencing with spatial transcriptomics at multiple developmental timepoints and revealed distinct temporal-spatial gene cascades in the developing human pancreas. Cell trajectory inference identified endocrine progenitor populations and novel branch-specific genes as the progenitors differentiate towards alpha or beta cells, indicating that transcriptional maturation occurred over this developmental timeframe. Spatial differentiation trajectories indicated that immature Schwann cells are spatially co-located with endocrine progenitors and contribute to beta cell maturation via the L1CAM-EPHB2 pathway. Our integrated approach enabled us to identify heterogeneity and multiple lineage dynamics within the mesenchyme, showing that it contributed to the exocrine acinar cell state. Finally, we have generated an interactive web resource for interrogating human pancreas development for the research community.

Current differentiation protocols have not been successful in reproducibly generating fully functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single-cell RNA sequencing with spatial transcriptomics at multiple developmental time points and revealed distinct temporal-spatial gene cascades. Cell trajectory inference identified endocrine progenitor populations and branch-specific genes as the progenitors differentiate toward alpha or beta cells. Spatial differentiation trajectories indicated that Schwann cells are spatially co-located with endocrine progenitors, and cell-cell connectivity analysis predicted that they may interact via L1CAM-EPHB2 signaling. Our integrated approach enabled us to identify heterogeneity and multiple lineage dynamics within the mesenchyme, showing that it contributed to the exocrine acinar cell state. Finally, we have generated an interactive web resource for investigating human pancreas development for the research community.

Introduction: Lung TRACERx is a prominent study employing multi-region and longitudinal multi-omics sequencing to unravel the evolutionary trajectories of lung cancer. Aberrant DNA methylation patterns have been widely described in nearly all human cancers, yet their interplay with DNA mutations in lung cancer is not well understood. Incorporating the contribution of epigenetic modifications to cancer evolution trajectories within TRACERx could improve our understanding of the intricate relationship between genetic and epigenetic changes in non-small cell lung cancer (NSCLC) evolution. Methods: Multi-region sampling from 38 TRACERx patients including 112 tumor regions and 37 matched normal adjacent tissue samples was performed. Reduced representation bisulfite sequencing (RRBS) was performed to assess DNA methylation and the CAMDAC (Larose-Cadieux et al, 2020) was applied to estimate purified tumor methylation rates and correct for copy number changes. Whole exome sequencing and somatic copy number alterations (SCNAs) were inferred using the ASCAT tool (Van Loo et al, 2010) and Methsig (Pan et al, 2021) was performed to discover new methylation driver genes. Results: Using multi-region sequencing, we identified ubiquitous hypermethylation of 29 known driver genes in both lung adenocarcinoma (LUAD) and squamous cell lung cancer (LUSC), together with an additional 9 and 27 genes exclusive to LUSC and LUAD, respectively. We also identified 13 and 7 driver genes non-ubiquitously hypermethylated exclusively in LUSC and LUAD, respectively. Using a differential methylation based approach, we describe a method to determine the extent of intra-tumor methylation heterogeneity akin to established ITH scores based on genomics data. In addition, we report the identification of novel subtype-specific methylation driver genes enriched in HOX family members which are related to cancer progression. Through integration of DNA methylation and genomic sequencing data, we identify parallel mechanisms contributing towards ubiquitous tumor suppressor gene alterations. At the patient level, multiple driver genes such as NSD1, GATA3 and MGA were subject to repression by both copy number loss and DNA hypermethylation. Finally, we describe dosage-compensation of genes such as the Notch ligands JAG2 and DLK1 that are proximal to amplified oncogenes and hypermethylated during tumor evolution. Conclusion: We describe the contribution of DNA methylation and genomic alterations to altering the landscape of NSCLC. Leveraging DNA methylation, we can determine the extent of convergent repression mechanisms in different regions of the same tumor, assess DNA methylation heterogeneity, and discover DNA methylation-based driver genes in NSCLC. Citation Format: Francisco Gimeno-Valiente, Carla Castignani, Elizabeth Larose-Cadieux, Kezhong Chen, Nana Mensah, Olga Chervova, Thomas Watkins, Pawan Dhami, Heli Vaikkinen, Andrew Feber, TRACERx Consortium, Jonas Demeulemeester, Miljana Tanic, Stephan Beck, Peter Van Loo, Charles Swanton, Nnennaya Kanu. Identification of convergent gene repression mechanisms through integrative genomic and DNA methylation analysis in TRACERx [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5710.