Radiation-Induced Alterations in Proliferation, Migration, and Adhesion in Lens Epithelial Cells and Implications for Cataract Development

The lens of the eye is one of the most radiosensitive tissues. Although the exact mechanism of radiation-induced cataract development remains unknown, altered proliferation, migration, and adhesion have been proposed as factors. Lens epithelial cells were exposed to X-rays (0.1–2 Gy) and radiation effects were examined after 12 h and 7 day. Proliferation was quantified using an MTT assay, migration was measured using a Boyden chamber and wound-healing assay, and adhesion was assessed on three extracellular matrices. Transcriptional changes were also examined using RT-qPCR for a panel of genes related to these processes. In general, a nonlinear radiation response was observed, with the greatest effects occurring at a dose of 0.25 Gy. At this dose, a reduction in proliferation occurred 12 h post irradiation (82.06 ± 2.66%), followed by an increase at 7 day (116.16 ± 3.64%). Cell migration was increased at 0.25 Gy, with rates 121.66 ± 6.49% and 232.78 ± 22.22% greater than controls at 12 h and 7 day respectively. Cell adhesion was consistently reduced above doses of 0.25 Gy. Transcriptional alterations were identified at these same doses in multiple genes related to proliferation, migration, and adhesion. Overall, this research began to elucidate the functional changes that occur in lens cells following radiation exposure, thereby providing a better mechanistic understanding of radiation-induced cataract development.

Transcriptomic and Metabolomic Profiling in Helicobacter pylori–Induced Gastric Cancer Identified Prognosis- and Immunotherapy-Relevant Gene Signatures

Background: Chronic Helicobacter pylori (HP) infection is considered the major cause of non-cardia gastric cancer (GC). However, how HP infection influences the metabolism and further regulates the progression of GC remains unknown.Methods: We comprehensively evaluated the metabolic pattern of HP-positive (HP+) GC samples using transcriptomic data and correlated these patterns with tumor microenvironment (TME)–infiltrating characteristics. The metabolic score was constructed to quantify metabolic patterns of individual tumors using principal component analysis (PCA) algorithms. The expression alterations of key metabolism-related genes (MRGs) and downstream metabolites were validated by PCR and untargeted metabolomics analysis.Results: Two distinct metabolic patterns and differential metabolic scores were identified in HP+ GC, which had various biological pathways in common and were associated with clinical outcomes. TME-infiltrating profiles under both patterns were highly consistent with the immunophenotype. Furthermore, the analysis indicated that a low metabolic score was correlated with an increased EMT subtype, immunosuppression status, and worse survival. Importantly, we identified that the expression of five MRGs, GSS, GMPPA, OGDH, SGPP2, and PIK3CA, was remarkably correlated with HP infection, patient survival, and therapy response. Furthermore, the carbohydrate metabolism and citric acid may be downstream regulators of the function of metabolic genes in HP-induced GC.Conclusion: Our findings suggest that there is cross talk between metabolism and immune promotion during HP infection. MRG-specific transcriptional alterations may serve as predictive biomarkers of survival outcomes and potential targets for treatment of patients with HP-induced GC.

Transcription Regulation and Genome Rewiring Governing Sensitivity and Resistance to FOXM1 Inhibition in Breast Cancer

Forkhead box M1 (FOXM1), an oncogenic transcription factor associated with aggressiveness and highly expressed in many cancers, is an emerging therapeutic target. Using novel 1,1-diarylethylene-diammonium small molecule FOXM1 inhibitors, we undertook transcriptomic, protein, and functional analyses to identify mechanisms by which these compounds impact breast cancer growth and survival, and the changes that occur in estrogen receptor (ERα)-positive and triple negative breast cancer cells that acquire resistance upon long-term treatment with the inhibitors. In sensitive cells, these compounds regulated FOXM1 gene networks controlling cell cycle progression, DNA damage repair, and apoptosis. Resistant cells showed transcriptional alterations that reversed the expression of many genes in the FOXM1 network and rewiring that enhanced inflammatory signaling and upregulated HER2 or EGFR growth factor pathways. ERα-positive breast cancer cells that developed resistance showed greatly reduced ERα levels and responsiveness to fulvestrant and a 10-fold increased sensitivity to lapatinib, suggesting that targeting rewired processes in the resistant state may provide benefits and prolong anticancer effectiveness. Improved understanding of how FOXM1 inhibitors suppress breast cancer and how cancer cells can defeat their effectiveness and acquire resistance should be helpful in directing further studies to move these agents towards translation into the clinic.

The Perspectives of Early Diagnosis of Schizophrenia Through the Detection of Epigenomics-Based Biomarkers in iPSC-Derived Neurons

The lack of early diagnostic biomarkers for schizophrenia greatly limits treatment options that deliver therapeutic agents to affected cells at a timely manner. While previous schizophrenia biomarker research has identified various biological signals that are correlated with certain diseases, their reliability and practicality as an early diagnostic tool remains unclear. In this article, we discuss the use of atypical epigenetic and/or consequent transcriptional alterations (ETAs) as biomarkers of early-stage schizophrenia. Furthermore, we review the viability of discovering and applying these biomarkers through the use of cutting-edge technologies such as human induced pluripotent stem cell (iPSC)-derived neurons, brain models, and single-cell level analyses.

Gene-corrected p.A30P SNCA patient-derived isogenic neurons rescue neuronal branching and function

Parkinson’s disease (PD) is characterised by the degeneration of A9 dopaminergic neurons and the pathological accumulation of alpha-synuclein. The p.A30P SNCA mutation generates the pathogenic form of the alpha-synuclein protein causing an autosomal-dominant form of PD. There are limited studies assessing pathogenic SNCA mutations in patient-derived isogenic cell models. Here we provide a functional assessment of dopaminergic neurons derived from a patient harbouring the p.A30P SNCA mutation. Using two clonal gene-corrected isogenic cell lines we identified image-based phenotypes showing impaired neuritic processes. The pathological neurons displayed impaired neuronal activity, reduced mitochondrial respiration, an energy deficit, vulnerability to rotenone, and transcriptional alterations in lipid metabolism. Our data describes for the first time the mutation-only effect of the p.A30P SNCA mutation on neuronal function, supporting the use of isogenic cell lines in identifying image-based pathological phenotypes that can serve as an entry point for future disease-modifying compound screenings and drug discovery strategies.

Single-Cell Transcriptomics Study of Human Hematopoietic Progenitors Reveals Alterations Associated with Aging and Myeloid Malignancies

Hematopoietic stem and progenitor cells (HSPCs) comprise a continuum of cells with varying differentiation potential and priming toward specific lineages. During both healthy aging and myeloid malignancies, changes occur in the composition and regulation of HSPCs. In this study, we evaluated human HSPCs obtained from young and elderly healthy donors using single-cell RNA sequencing to identify the transcriptional and regulatory alterations associated with aging at single cell resolution. We then applied this knowledge to the study of specific perturbations associated with the development of myeloid pathologies. We isolated >90,000 bone marrow CD34+ cells from 5 young (18-20 y/o), 3 elderly (>65 y/o) healthy donors, 1 patient with myelodysplastic syndrome (MDS) and 1 patient with acute myeloid leukemia (AML), using fluorescence-activated cell sorting. scRNA libraries were prepared with the 10X chromium platform and sequenced. Finally, bioinformatic analysis was performed using available R and Python algorithms such as Seurat, Palantir and Scenic. First, we characterized HSPC subpopulations in young donors by unsupervised clustering and manual annotation. Taking the previous findings as reference, we then classified the elderly and pathological HSPC using elastic-net regularization prediction models (Figure 1A). Comparison of subpopulations in young and elderly donors confirmed the age-related increase in HSC, as well as reduction of lymphoid progenitors and myelomonocytic compartments. Next, we performed differential expression and pathways analysis to uncover age-associated alterations in the transcriptional profile of cells with the same identity. We found a generalized enrichment in elderly HSPC of pathways activated upon stress and inflammation, such as p53, hypoxia and TNF alpha response. This suggests an age-related increased response to the more inflammatory microenvironment of elderly individuals. On the other hand, young HSPC were enriched for cell cycle activation and proliferation pathways, as well as metabolic processes (Figure 1B). Using trajectory analysis, we recovered 6 differentiation paths present in our young donor's data. When compared to the elderly, the greatest changes occurred along the monocytic trajectory. For some genes, expression differed through the whole trajectory, indicating the existence of original transcriptional alterations already at the HSC compartment. On the other hand, expression of myelomonocytic differentiation markers, such as MPO and CD74, reached lower levels in our elderly HSPC data, pointing towards a loss of capacity for monocytic differentiation in progenitors from elderly individuals. Finally, to identify key transcription factors regulating the progression of differentiation routes, we built gene regulatory networks. Overall, we found lower activation levels for transcriptional programs in the early progenitors from elderly donors. In addition, gene ontology enrichment analysis showed that the active networks in the young were enriched for differentiation-related terms, while networks from the elderly were not. These results also indicate an age-associated loss of differentiation capability. We then applied the same computational tools to analyze aberrant hematopoiesis in samples from 2 patients suffering from myeloid malignancies (MDS and AML). On one hand, we subjected the MDS sample to trajectory analysis, focusing on the erythroid lineage. We observed perturbations in the expression dynamics of genes playing a role in erythropoiesis. In the AML sample, we encountered a significant expansion of the most immature cell compartments (HSC, LMPP and MEP). In addition, GRN reconstruction showed up the specific activity of transcription programs activated by factors deregulated during leukemia, such as ZSCAN18 and GFI1. In conclusion, our work described the transcriptional alterations that occur in early hematopoiesis, both during healthy aging and myeloid pathology. We used multiple approaches, such as the study cellular proportions, differentiation trajectories and GRNs. The inclusion of samples from patients with myeloid pathology provided insights into the potential role of single-cell technologies for understanding and treating hematological malignancies. Figure 1 Figure 1. Disclosures Sanchez-Guijo: Gilead: Consultancy, Honoraria; Celgene/Bristol-Myers-Squibb,: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Takeda: Honoraria, Research Funding; Roche: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding. Diez-Campelo: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Valcarcel: BMS: Consultancy, Honoraria, Speakers Bureau; CELGENE: Consultancy, Honoraria, Speakers Bureau; ASTELLAS: Consultancy, Honoraria, Speakers Bureau; AMGEN: Consultancy, Honoraria, Speakers Bureau; NOVARTIS: Consultancy, Honoraria, Speakers Bureau; TAKEDA: Consultancy, Honoraria, Speakers Bureau; JAZZ: Consultancy, Honoraria, Speakers Bureau; SOBI: Consultancy, Honoraria, Speakers Bureau; SANOFI: Consultancy, Honoraria, Speakers Bureau. Romero: 10X Genomics: Current Employment. Prosper: Janssen: Honoraria; Oryzon: Honoraria; BMS-Celgene: Honoraria, Research Funding.

673 (Re-) Solving the biology of colorectal cancer onset and progression to improve treatment and prevention

BackgroundColorectal cancer (CRC) development is accompanied by the gradual accumulation of genetic alterations in epithelial cells of the colon and rectum.1 2 The paradigm of the adenoma-carcinoma sequence was originally centered around cancer cells; however, it is now clear that the tumor microenvironment plays a substantial role in cancer progression and patient outcome.3 In recent years, technologies have evolved rapidly, allowing the multiplexed quantification of gene expression while preserving spatial context.4 Furthermore, some spatial transcriptomic technologies also allow the parallel interrogation of different cell populations in the tumor microenvironment. Here, we performed digital spatial profiling on early-stage CRC samples to elucidate the biological processes that are at the basis of malignant transformation and to identify novel therapeutic targets and (immune) biomarkers.MethodsEndoscopically resected early-stage CRC samples were obtained at Leiden University Medical Center. In total, 144 areas of illumination were interrogated with GeoMx digital spatial profiling using the Cancer Transcriptome Atlas (>1,800 genes). In each of eight samples, nine regions of interest with different levels of cancer progression were selected, including normal epithelium, transition areas, low-, and high-grade dysplasia, and invasive carcinoma (figure 1A). We segmented each region based on cytokeratin and vimentin protein expression (figure 1B). Immunohistochemical detection was performed on these samples and 26 additional samples to validate targets associated with disease progression.ResultsDigital spatial profiling allowed us to dissect transcriptional alterations in epithelial and stromal fractions between different regions from healthy tissue, different degrees of dysplasia, and cancer. Gene expression data revealed a clear separation of profiled areas by histologic category. Interestingly, gene expression features in the stromal compartment provided a better data-driven separation of histologic categories than the epithelial fraction (figure 1C). Substantial changes in immune-related pathways were identified, including differential expression of specific immunomodulators. We validated the expression of several candidate biomarkers/targets that demonstrated consistent alterations from normal tissue to cancer by immunohistochemistry. Several proteins were identified that could clearly discriminate benign from malignant tissue.ConclusionsWe here demonstrated the unique biological insights that are provided by spatial examination of early-stage CRC by digital spatial profiling. We identified specific genes that were altered during CRC tumorigenesis, in epithelial and stromal/immune fractions. Furthermore, our results indicate an essential role for innate immunity in colorectal cancer onset and progression. The genes identified by this approach could potentially serve as novel biomarkers and targets for early interception or prevention of CRC development.AcknowledgementsThis work was supported by the European Research Council (ERC) Starting grant awarded to Dr. Noel F. de Miranda and the Stichting Management Apothekers en de Gezondheidszorg (STIMAG) Research grant awarded to Jessica Roelands.Trial RegistrationN/AReferencesFearon ER, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell 1990;61(5):759–767. doi: 10.1016/0092-8674(90)90186-I.Nowell PC. The clonal evolution of tumor cell populations. Science 1976;194(4260):23–28. doi: 10.1126/science.959840.Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011;144(5):646–674. doi: 10.1016/j.cell.2011.02.013.Merritt CR, et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat Biotechnol 2020;38(5):586–599. doi: 10.1038/s41587-020-0472-9.Ethics ApprovalThis study was approved by the METC Leiden-Den Haag-Delft (protocol B20.039). Patient samples were anonymised and handled according to the medical ethical guidelines described in the Code of Conduct for Proper Secondary Use of Human Tissue of the Dutch Federation of Biomedical Scientific Societies.Abstract 673 Figure 1Transcriptional alterations in early-stage colorectal cancer. Digital spatial profiling defines transcriptional alterations in early-stage colorectal cancer. (A) Schematic representation of an early-stage CRC sample containing regions with different levels of cancer progression, including normal epithelium, transition areas, low-, and high-grade dysplasia, and invasive carcinoma. (B) Segmentation based immunofluorescent labelling with antibodies directed against PanCK and Vimentin in one of the early-stage CRC samples. Artificial overlay of implemented segmentation is indicated for each ROI, visualizing Vimentin+ (pink) and PanCK+ (orange) segments. Inset: higher magnification of an individual ROI. (C) Dimension reduction of expression of all quantified genes by t-Distributed Stochastic Neighbor Embedding (tSNE). tSNE plots are annotated by segment (left), and histological region (right).

Transcriptional alterations of protein coding and noncoding RNAs in triple negative breast cancer in response to DNA methyltransferases inhibition

Background DNA methylation plays a crucial role in multiple cellular processes such as gene regulation, chromatin stability, and genetic imprinting. In mammals, DNA methylation is achieved by DNA methyltransferases (DNMTs). A number of studies have associated alterations in DNMT activity to tumorigenesis; however, the exact role of DNMTs in shaping the genome in triple negative breast cancer (TNBC) is still being unraveled. Methods In the current study, we employed two DNMT inhibitors (Decitabine and 5-Azacytidine), two TNBC models (MDA-MB-231 and BT-549) and whole transcriptome RNA-Seq and characterized the transcriptional alterations associated with DNMT inhibition. Colony forming unit (CFU), flow cytometry, and fluorescent microscopy were used to assess cell proliferation, cell cycle distribution, and cell death, respectively. Ingenuity pathway analysis (IPA) was used for network and pathway analyses. Results Remarkably, DNMT inhibition induced the expression of genes involved in endoplasmic reticulum response to stress, response to unfolder protein, as well as cobalamin metabolic processes. In contrast, suppression of cellular processes related to cell cycle and mitosis were hallmarks of DNMT inhibition. Concordantly, DNMT inhibition led to significant inhibition of TNBC cell proliferation, G2-M cell cycle arrest and induction of cell death. Mechanistically, DNMT inhibition activated TP53, NUPR1, and NFkB (complex) networks, while RARA, RABL6, ESR1, FOXM1, and ERBB2 networks were suppressed. Our data also identified the long noncoding RNA (lncRNA) transcriptional portrait associated with DNMT inhibition and identified 25 commonly upregulated and 60 commonly downregulated lncRNAs in response to Decitabine and 5-Azacytidinec treatment in both TNBC models. TPT1-AS1 was the most highly induced (6.3 FC), while MALAT1 was the most highly suppressed (− 7.0 FC) lncRNA in response to DNMT inhibition. Conclusions Taken together, our data provides a comprehensive view of transcriptome alterations in the coding and noncoding transcriptome in TNBC in response to DNMT inhibition.