A single-cell transcriptomic comparison between small intestinal neuroendocrine tumors and their progenitor

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Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results A single-cell transcriptomic comparison between small intestinal neuroendocrine tumors and their progenitor View ORCID Profile Fredrik Axling , View ORCID Profile Elham Barazeghi , View ORCID Profile Per Hellman , View ORCID Profile Olov Norlén , View ORCID Profile Samuel Backman , View ORCID Profile Peter Stålberg doi: https://doi.org/10.1101/2025.02.10.637596 Fredrik Axling 1 Department of Surgical Sciences, Uppsala University , Uppsala, Sweden, Rudbeck Laboratory, SE-751 85 Uppsala, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Fredrik Axling For correspondence: Fredrik.axling{at}uu.se Peter.stalberg{at}uu.se Elham Barazeghi 1 Department of Surgical Sciences, Uppsala University , Uppsala, Sweden, Rudbeck Laboratory, SE-751 85 Uppsala, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Elham Barazeghi Per Hellman 1 Department of Surgical Sciences, Uppsala University , Uppsala, Sweden, Rudbeck Laboratory, SE-751 85 Uppsala, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Per Hellman Olov Norlén 1 Department of Surgical Sciences, Uppsala University , Uppsala, Sweden, Rudbeck Laboratory, SE-751 85 Uppsala, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Olov Norlén Samuel Backman 1 Department of Surgical Sciences, Uppsala University , Uppsala, Sweden, Rudbeck Laboratory, SE-751 85 Uppsala, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Samuel Backman Peter Stålberg 1 Department of Surgical Sciences, Uppsala University , Uppsala, Sweden, Rudbeck Laboratory, SE-751 85 Uppsala, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Peter Stålberg For correspondence: Fredrik.axling{at}uu.se Peter.stalberg{at}uu.se Abstract Full Text Info/History Metrics Preview PDF Abstract Several studies have attempted to find the initiating drivers of small intestinal neuroendocrine tumors (SI-NET) development and the molecular mechanisms driving progression and metastatic spread. For gene expression studies using bulk microarrays and RNA sequencing, researchers commonly use normal intestinal mucosa as a control. The intestine is made up of several different cell types, and using bulk RNA-seq may generate findings that reflect factors other than the tumor transformation. This could potentially contribute to the lack of discoverable treatments and prevention strategies for SI-NETs. We performed scRNA-seq on tissue from two patients that had tumor resection surgery and separated the EC cells from the normal intestinal mucosa and used specific markers to compare them against SI-NET tumors cells. We pinpointed new genes associated with chr18 haploinsufficiency but also others with loss or gain of expression that have not previously been associated with SI-NETs, and which could be potential targets for further functional genomic studies. Introduction Small intestinal neuroendocrine tumors (SI-NETs), which are believed to originate from enterochromaffin (EC) cells in the gastrointestinal tract ( de Herder 2005 ; Sei et al. 2016 ; Yao et al. 2008 ), are often slow-growing and small in size, with an annual incidence of 1 per 100,000. Most patients are diagnosed as stage IV with distant metastases ( Modlin et al. 2014 ). Results from studies on epigenetic and genetic alterations in SI-NETs are scarce, and extensive DNA analysis using short-read sequencing and array-based methods has revealed a stable tumor genome, with frequent loss of chromosome 18 but no recurrent small mutations ( Banck et al. 2013 ), with the exception of CDKN1B , which is only found mutated in 8% of cases ( Crona et al. 2015 ; Francis et al. 2013 ). Several studies ( Clift et al. 2019 ) have attempted to find the pathological origin of SI-NET upregulation and the underlying molecular mechanisms important for their progression and metastatic spread. For this purpose, normal intestinal mucosa is commonly used as a control for gene expression studies using bulk microarrays and RNA sequencing. Bulk analyses have become a mainstay of molecular biology research but are limited by the heterogeneity of tissues, which consist of multiple cell types, whose average gene expression is measured in bulk sequencing experiments ( Li and Wang 2021 ). Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to study the gene expression patterns of individual constituent cells and has been successfully used to clarify the cellular origins of different forms of adult and pediatric kidney cancer ( Young et al. 2018 ). Such an approach is highly useful for SI-NETs, which are thought to arise from a rare cell population in the intestinal epithelium, as the intestinal epithelium is made up of several different cell types ( Elmentaite et al. 2021 ; Hickey et al. 2023 ), not only the SI-NET progenitor EC cell. Using bulk RNA-sequencing will generate results that are not specific to the SI-NET phenotype but rather reflect, e.g., the differences between enterochromaffin cells and healthy enterocytes. The paucity of relevant control samples may be one of the causes of the lack of translatable discoveries for targeted treatment strategies for SI-NETs. To overcome this limitation, we have applied scRNA-seq to isolate the EC cells in the normal intestinal mucosa using specific cell markers and compare these against surgically resected SI-NET tumors. Initial efforts were focused on the development of protocols for obtaining viable suspensions of single cells from surgical specimens and required well-timed coordination between the operating team, the pathology lab, the research lab, and the core facility. In the present study, we aimed to compare the transcriptomes of SI-NET cells to the normal EC cell in order to identify driver genes and gene modules with aberrant expression specific to the SI-NET malignancy. Materials and methods Ethics statement Informed written consent was obtained from all patients for tissue use and disease study, and ethical approval was secured from the Regional Ethical Review Board in Uppsala (EPN 2011/375). This research was carried out in compliance with the Declaration of Helsinki. Sample preparation, library construction and scRNA sequencing During the gross pathological examination of surgical specimens from two patients undergoing surgical resection of SI-NETs, a representative piece of tumor tissue and a portion of adjacent normal bowel mucosa were taken for analysis. The tissue was minced, washed with Ham’s F-10 medium, and centrifuged to separate cells from the medium. Cells were transferred to a collagenase solution, followed by incubation at 37 °C for 2 hours, and filtered through a sterile stainless steel or nylon mesh to separate the dispersed cells and tissue fragments from the larger pieces ( Birch 1989 ). Cells were then centrifuged and washed with EGTA solution, followed by Percoll treatment (Smedsrød and Pertoft 1985) to obtain a single-cell suspension. Sequencing libraries were prepared using the Chromium Single Cell 3’ Reagent Kit v3 ( Zheng et al. 2017 ) (10X Genomics) in accordance with the manufacturer’s instructions. The resulting libraries were sequenced on one NovaSeq 6000 SP flow cell. The Cell Ranger Single-Cell Suite 7.2.0 was used to demultiplex and identify the assigned barcodes for each of the primary tumors and healthy adjacent tissue. External datasets for validation A validation scRNA-seq dataset was in silico created using data from two different published studies: “Healthy small intestine from single-cell transcriptome analysis reveals differential nutrient absorption functions in the human intestine” ( Wang et al. 2020 ) and primary SI-NET sample from “Comparative single-cell RNA sequencing (scRNA-seq) reveals liver metastasis-specific targets in a patient with small intestinal neuroendocrine cancer” ( Rao et al. 2020 ). For bulk gene expression validation, two gene array expression datasets consisting of primary SI-NET tumor and normal mucosa tissue ( Andersson et al. 2016 ; Leja et al. 2009 ) were merged using ComBat ( Johnson, Li, and Rabinovic 2007 ) for batch correction. Followed by a logistic regression model applied to the remaining batches with a forward stepwise selection (FSS) algorithm to classify the batch-corrected samples. A Kolmogorov-Smirnov test was used for assessing distribution, and a Wilcoxon rank-sum test was used for differential expression. Overlapping enteroendocrine specificity was performed using the human protein atlas single-cell type transcriptomics map dataset ( Karlsson et al. 2021 ). Bioinformatics processing and data analysis Cell Ranger 7.2.0 (10x Genomics) was used with transcriptome reference 2020-A Human GRCh38 (GENCODE v32/Ensembl 98) to process raw sequencing samples from both the internal and external scRNA-seq datasets to generate count matrices, which were used as input for Seurat v5 ( Butler et al. 2018 ) for downstream processing and analysis. The internal samples were quality controlled by discarding cells that contained less than 200 or more than 9000 features and had >90% mitochondrial gene expression. The external primary SI-NET sample was filtered by cells containing less than 250 or more than 5000 features with >10% mitochondrial gene content, and cells in the external small intestine samples were discarded if they contained less than 250 or more than 5000 features with >30% mitochondrial genes. EC and SI-NET cells were then isolated in both the internal and external samples using unsupervised clustering and specific cell markers, derived from the combination of the following markers: CHGB, CHGA , and ADGRG4 . Other cell types were identified using the following markers: Fibroblast: COL1A1, PDGFRA, and ACTA2 . Enterocyte: APOA1, FABP6, ALPI, SI , and KRT20 . Leukocyte: CD4, CD8A, CD3G , and KLRD1 . B cell: CD79A and MS4A1 . Mast cell: CPA3 . Monocyte: CD14 . Foveolar cell: IL33 . Goblet cell: FCGBP, SPINK4, REP15 , and MUC2 . Tuft cell: AVIL, POU2F3, GFI1B , and TRPM5 . Stem cell: LGR5, RGMB, SMOC2 , and ASCL2 . Paneth cell: LYZ . Transit-amplifying cell: PCNA, TOP2A , and MCM5 . NormalizeData and ScaleData, followed by IntegrateLayers, were used to merge cells derived from EC and SI-NET origins in each healthy and tumor sample into an internal discovery and an external validation dataset. Differential gene expression (DGE) between EC and SI-NET cells was then investigated in the discovery and validation datasets using FindMarkers with the Mann–Whitney U-test with Bonferroni correction (p-value) for multiple testing, and genes not overlapping between the two datasets were discarded. The STRING Database ( Szklarczyk et al. 2023 ) with Cytoscape ( Shannon et al. 2003 ) was used for producing interaction networks between differentially expressed genes. Functional gene enrichment analysis was performed using g:Profiler (Reimand et al. 2007). Results Cell type identification and specific gene expression differences We performed single-cell RNA sequencing on tumor tissue and adjacent normal intestinal mucosa derived from two patients extracted during surgical resection of SI-NETs using the 10X Genomics Single Cell 3’ v3 chromium platform, yielding single-cell transcriptomes of 13086 cells. Unsupervised clustering and cell marker profiles were used for characterizing cells in the tumor and normal mucosa samples, followed by statistical comparison. By comparing EC cells with SI-NET cells, our analysis revealed 741 significant (p ≤ 0.05) differentially expressed genes. To validate our novel scRNA-seq dataset, we in silico generated an external validation dataset. This was done using two datasets consisting of scRNA-sequenced normal intestine and a SI-NET tumor, applying the same approach as previously described. EC and SI-NET cells were isolated in the same manner from the external validation dataset and statistically compared with the resulting 1921 (p ≤ 0.05) significantly differentially expressed genes. Significant genes between the discovery and validation datasets were then compared, and genes without overlap were excluded from further analyses, resulting in a final comparison of 457 significant genes. Out of the 457 significant genes, 115 genes were upregulated and 342 were downregulated in tumor samples. Cells in the discovery and validation datasets can be distinguished in the Uniform Manifold Approximation and Projection (UMAP) plots in figure 1 . Download figure Open in new tab Figure 1: UMAP plots represent cells from the internal discovery dataset and the external validation dataset. A: Discovery SI-NET resected tumor cells (n = 4249), B: Discovery Ileum resected tissue cells (n = 6688), C: Discovery Enterochromaffin (EC) (n = 84) and SI-NET isolated cells (n = 69). D: Validation SI-NET resected tumor cells (n = 1373), E: Validation Ileum resected tissue cells (n = 7843), and F: Validation Enterochromaffin (EC) (n = 87) and SI-NET isolated cells (n = 660). Cell types: Enterocyte, Goblet, Fibroblast, Transit-amplifying, Stem, Tuft, Paneth, Enterochromaffin (EC), Small Intestinal Neuroendocrine Tumor (SI-NET), Foveolar, Monocyte, Mast, and B-cell. Gene expression methodology comparison We compared overlap for our significant genes against earlier gene array expression data consisting of primary SI-NET and normal intestinal mucosa ( Andersson et al. 2016 ; Leja et al. 2009 ). Re-analyzing the gene array datasets revealed 6685 significant genes between primary SI-NET and normal mucosa, but only 216 genes (67 tumor-upregulated and 149 tumor-downregulated genes) preserved the same trajectory of expression between the scRNA-seq and bulk gene array dataset. Gene interaction network We proceeded to cluster the significant genes that passed validation using a gene expression network approach with a minimum required interaction score of 0.9 and isolated 103 interconnected neighboring genes. In tumor cells, 16 of the 103 connected genes showed upregulation, while 87 displayed downregulation ( Figure 2 ). Download figure Open in new tab Figure 2: The gene expression network inputs from 457 significant genes with a minimum required interaction score of 0.9 and at least one connected neighboring gene, resulting in 103 genes with neighboring interactions. We conducted a gene enrichment analysis of the genes involved in the network, and the top driver terms revealed for the SI-NET upregulated genes were AMPA glutamate receptor activity, amyloid-beta binding, monoatomic ion channel complex, AMPA glutamate receptor complex, and neuron projection, and the SI-NET downregulated terms can be observed in figure 3 . We linked the Reactome pathway results to TP53 signaling and tyrosine kinase receptor (ERRB4) signaling. Download figure Open in new tab Figure 3: Gene ontology (GO) analysis of the 87 SI-NET downregulated genes. The black line indicates p-value threshold (adj. p-value = 0.05). Loss of chromosome 18 heterozygosity As loss of heterozygosity on chromosome 18 is a common mutational event in SI-NETs, we also examined genes located on chromosome 18. We found 13 genes with a significant downregulation of expression in tumor cells ( Table 1 ). View this table: View inline View popup Download powerpoint Table 1: Genes located on chromosome 18 with downregulation of expression in SI-NET cells. SI-NET tumorigenesis impact on gene expression differentiation We proceeded to investigate genes with major downregulation in tumor cells, and in total, we could detect 20 genes that had abolished expression (expressed in <1.5% of cells). However, only ISL1, ONECUT3, PPP1R1C, LCN15, NTS , and PLXNA4 had specificity for enteroendocrine expression in the small intestine when compared against single-cell expression data in the human protein atlas single-cell type transcriptomics map. The expression of these six downregulated genes can be observed in figure 4 . Download figure Open in new tab Figure 4: Expression patterns of the six genes with verified expression in enteroendocrine cells were revealed to be downregulated in the SI-NET tumor cells. In contrast, 32 genes with no expression in EC cells but with presence in SI-NET cells could be confirmed in the human protein atlas database to lack enteroendocrine expression. ADAMTS9-AS2, NPSR1-AS1, LINC02388 , and LINC02484 could not be verified due to their lack of presence in the human protein atlas database. Further experiments will be needed to investigate the possible role of these dysregulated genes ( Table 2 ). View this table: View inline View popup Download powerpoint Table 2: Human protein atlas-verified genes (n = 38) with gain or loss of expression in SI-NET cells. LoE = loss of expression; GoE = gain of expression. Discussion Until now, EC-related studies have mainly been focused on their role and function in the gastrointestinal tract ( Anon 2017 ; Beumer et al. 2020 ; Singh et al. 2024 ). While their comparison against SI-NETs has been conducted using bulk-tissue methodologies ( Samsom et al. 2019 ), others have focused on the comparison between primary and metastatic lesions ( Rao et al. 2020 ) and intertumoral differences ( Hoffman et al. 2023 ) using single-cell technologies. Here we present the first single-cell sequencing study comparison between the small intestinal neuroendocrine tumor cell and its progenitor enterochromaffin cell. Until 10x Genomics released their 10X Chromium FLEX platform, applications of single-cell techniques required fresh viable cells, and this proved to be a challenge to obtain from surgically resected SI-NET specimens, which is evident in the comparatively low cell number and relatively high degree of mitochondrial gene expression. This had a significant impact on the number and quality of the tumor cells included in the analysis; in order to mitigate this and to decrease the risk of false-positive findings, we performed a two-step validation where we first compared our results for overlapping expression against an external validation dataset. This resulted in a final list of 457 overlapping significant genes, and we proceeded to pinpoint enriched differences using gene interaction networks and gene ontology analysis for expression differences between EC and SI-NET. This showed numerous enriched differences between the two cell types, revealing functions associated with tumor relevance in the receptor tyrosine kinase and TP53 pathways, as well as effects corresponding to cellular respiratory mechanisms. We also observed numerous cell morphology associations, including cell junctions, cell adhesion, plasma membrane, and cytoskeleton. However, this enrichment is not unexpected in a tumor versus normal cell comparison, but an interesting observation is that the majority of the genes associated with these pathways are downregulated in the tumor cells. SI-NETs experience recurrent loss of chromosome 18 heterozygosity affecting the transcription capabilities of its tumor suppressor gene SMAD4 ( Banck et al. 2013 ), and thus inducing SMAD4-haploinsufficiency ( Hofving et al. 2021 ). We could distinguish 13 genes located on chromosome 18 with downregulated expression in the tumor cells. The long, non-coding RNA (lncRNA) LINC00907 was the most downregulated, but also the adenylyl cyclase inhibitor GALR1 (Galaninreceptor 1) and GRB2-associated and regulator of MAPK protein 1, GAREM1 , are noteworthy. LncRNAs possess tissue-specific expression and exhibit phenotypic regulated expression ( Guttman et al. 2009 ) with a number of lncRNAs transcriptionally controlled by important oncogenes or tumor suppressors ( Huarte et al. 2010 ; Zheng et al. 2014 ). LINC00907’s function is not clear, but it is associated with adenosquamous prostate carcinoma and chromosome 18q deletion syndrome ( Rappaport et al. 2017 ). We summarized a subset of 38 genes that passed overlapping validation with either abolished or initiated expression in SI-NET cells and had been second-step validated for the presence of enteroendocrine expression in the human protein atlas database. We compared the expression of these 38 genes in our GOT1 and CNDT2.5 xenografts (unpublished data), as these cell lines can be valuable for conducting functional genomic studies in SI-NETs. The following genes had no or very low expression in both cell line xenografts: NTS, LCN15, ONECUT3, ZMAT4, HS3ST4, HPN, UBE2QL1, TCEAL2, ADAM19, MICU3, NMNAT2 , and DACH2 . Out of the 38 genes, six genes with loss of expression in tumor cells; a subset of these was shown to be of particular interest, with ISL1 (encoding for LIM Homeobox 1, an insulin gene enhancer region binder protein, among other targets) already being reported in earlier studies as lacking expression by immunohistochemistry analysis in SI-NETs. ( Tran, Sherman, and Howe 2020 ; Xiang, Malik, and Zhang 2023 ). On the other hand, little is known about LCN15 , which encodes lipocalin 15. Our results showed that NTS exhibited the strongest expression differences, with 15 log2 fold changes, a difference that is also evident in our bulk gene expression comparison. NTS expression comparison in our CNDT2.5 and GOT1 xenografts revealed no or very little expression of NTS, and these results demonstrate that NTS expressions are downregulated in SI-NETs. Thanks to non-cancerous tissue investigations, NTS has been shown to display a vital role in the promotion of wound healing ( Mouritzen et al. 2018 ). Its receptors have been linked to the Wnt/β-catenin signaling pathway in pancreatic NETs, glioblastoma, and hepatocellular carcinoma, and upregulation leads to tumor growth (Kim, Liu, et al. 2015; Xiao et al. 2017 ; Ye et al. 2016 ). Most likely, the same biological mechanisms upregulating wound healing also promote tumor growth ( Liu et al. 2022 ; Whyte, Smith, and Helms 2012 ). NTS and its high-affinity receptor NTSR1 are most extensively characterized in the context of gastrointestinal cancers. Both are overexpressed in gastric and colon cancer, and this overexpression correlates well with poor prognosis ( Christou et al. 2020 ). Four different non- intestinal NET cell lines have been shown to express neurotensin ( NTS ) on both the transcript and protein levels (Kim, Li, et al. 2015), and when upregulated, stimulate cell proliferation and growth (Kim, Liu, et al. 2015). However, more research is needed to find out what role NTS might play in SI-NETs and how its role in tumor growth and cell proliferation differs from those seen in colorectal and stomach cancer. We used a very low cut-off (expressed in less than 1.5% of cells) to decide which genes are either losing or gaining expression in SI-NETs. This means that there are probably more genes that should be looked into among the differentially expressed genes. Moreover, relative changes in gene expression, in addition to the upregulation of silenced genes and the complete silencing of expressed genes, may play a crucial role in tumor development. Therefore, we urge further screening for associations of tumor relevance in our significant genes to possibly cull more candidates for functional studies. This study provided us with a glimpse of potential genes responsible for or being affected during the tumorigenesis and growth of small intestinal neuroendocrine tumors and which would be of interest to investigate by functional genomic studies in SI-NET cells. In conclusion, by using single-cell RNA sequencing, we were able to distinguish unexplored differences between SI-NET and its progenitor cell, and we identified a few important genes for future studies. Data We obtained gene array expression data for bulk expression comparison from GEO accession no. GSE9576 and GSM1591697. Single-cell transcriptome data for the external validation dataset was obtained from GSE125970 for the ileum and GSE140312 for the primary small intestine neuroendocrine tumor. Declaration of interests The authors declare no competing interests. Acknowledgments This study was funded by grants from the Swedish Cancer Foundation and governmental funding of clinical research within the Swedish National Health Service (ALF). The authors are grateful to the Endocrine Surgical Unit at the Uppsala University Hospital for assistance. Single-cell sequencing was performed by the SNP&SEQ Technology Platform in Uppsala. The facility is part of the National Genomics Infrastructure (NGI) Sweden and Science for Life Laboratory. The SNP&SEQ Platform is also supported by the Swedish Research Council and the Knut and Alice Wallenberg Foundation. Footnotes elham.barazeghi{at}uu.se ; per.hellman{at}uu.se ; olov.norlen{at}uu.se ; samuel.backman{at}uu.se References ↵ Andersson , Ellinor , Yvonne Arvidsson , Christina Swärd , Tobias Hofving , B. Wängberg , Erik Kristiansson , and Ola Nilsson . 2016 . “ Expression Profiling of Small Intestinal Neuroendocrine Tumors Identifies Subgroups with Clinical Relevance, Prognostic Markers and Therapeutic Targets .” Modern Pathology: An Official Journal of the United States and Canadian Academy of Pathology, Inc 29 ( 6 ): 616 – 29 . doi: 10.1038/modpathol.2016.48 . OpenUrl CrossRef PubMed ↵ Anon . 2017 . “Enterochromaffin Cells Are Gut Chemosensors That Couple to Sensory Neural Pathways | Articles | Nature Index.” Retrieved February 7, 2025 ( https://www.nature.com/nature-index/article/10.1016/j.cell.2017.05.034 ). ↵ Banck , Michaela S. , Rahul Kanwar , Amit A. Kulkarni , Ganesh K. Boora , Franziska Metge , Benjamin R. Kipp , Lizhi Zhang , Erik C. Thorland , Kay T. Minn , Ramesh Tentu , Bruce W. Eckloff , Eric D. Wieben , Yanhong Wu , Julie M. Cunningham , David M. Nagorney , Judith A. Gilbert , Matthew M. Ames , and Andreas S. Beutler . 2013 . “ The Genomic Landscape of Small Intestine Neuroendocrine Tumors .” The Journal of Clinical Investigation 123 ( 6 ): 2502 – 8 . doi: 10.1172/JCI67963 . OpenUrl CrossRef PubMed Web of Science ↵ Beumer , Joep , Jens Puschhof , Julia Bauzá-Martinez , Adriana Martínez-Silgado , Rasa Elmentaite , Kylie R. James , Alexander Ross , Delilah Hendriks , Benedetta Artegiani , Georg A. Busslinger , Bas Ponsioen , Amanda Andersson-Rolf , Aurelia Saftien , Charelle Boot , Kai Kretzschmar , Maarten H. Geurts , Yotam E. Bar-Ephraim , Cayetano Pleguezuelos-Manzano , Yorick Post , Harry Begthel , Franka van der Linden , Carmen Lopez-Iglesias , Willine J. van de Wetering , Reinier van der Linden , Peter J. Peters , Albert J. R. Heck , Joachim Goedhart , Hugo Snippert , Matthias Zilbauer , Sarah A. Teichmann , Wei Wu , and Hans Clevers . 2020 . “ High-Resolution mRNA and Secretome Atlas of Human Enteroendocrine Cells .” Cell 181 ( 6 ): 1291 - 1306.e19 . doi: 10.1016/j.cell.2020.04.036 . OpenUrl CrossRef ↵ Birch , J. R. 1989 . “ Culture of Animal Cells: A Manual of Basic Technique: By R. I. Freshney, Alan R. Liss, Inc., New York, 1987. Pp. Xviii + 397, Price $59.50. ISBN 0-8451-4241-0 .” Journal of Chemical Technology & Biotechnology 45 ( 4 ): 330 – 330 . doi: 10.1002/jctb.280450414 . OpenUrl CrossRef ↵ Butler , Andrew , Paul Hoffman , Peter Smibert , Efthymia Papalexi , and Rahul Satija . 2018 . “ Integrating Single-Cell Transcriptomic Data across Different Conditions, Technologies, and Species .” Nature Biotechnology 36 ( 5 ): 411 – 20 . doi: 10.1038/nbt.4096 . OpenUrl CrossRef PubMed ↵ Christou , Niki , Sabrina Blondy , Valentin David , Mireille Verdier , Fabrice Lalloué , Marie-Odile Jauberteau , Muriel Mathonnet , and Aurélie Perraud . 2020 . “ Neurotensin Pathway in Digestive Cancers and Clinical Applications: An Overview .” Cell Death & Disease 11 ( 12 ): 1 – 12 . doi: 10.1038/s41419-020-03245-8 . OpenUrl CrossRef ↵ Clift , Ashley Kieran , Mark Kidd , Lisa Bodei , Christos Toumpanakis , Richard P. Baum , Kjell Oberg , Irvin M. Modlin , and Andrea Frilling . 2019 . “ Neuroendocrine Neoplasms of the Small Bowel and Pancreas .” Neuroendocrinology 110 ( 6 ): 444 – 76 . doi: 10.1159/000503721 . OpenUrl CrossRef PubMed ↵ Crona , Joakim , Tobias Gustavsson , Olov Norlén , Katarina Edfeldt , Tobias Åkerström , Gunnar Westin , Per Hellman , Peyman Björklund , and Peter Stålberg . 2015 . “ Somatic Mutations and Genetic Heterogeneity at the CDKN1B Locus in Small Intestinal Neuroendocrine Tumors .” Annals of Surgical Oncology 22 Suppl 3 : S1428 – 1435 . doi: 10.1245/s10434-014-4351-9 . OpenUrl CrossRef PubMed ↵ Elmentaite , Rasa , Natsuhiko Kumasaka , Kenny Roberts , Aaron Fleming , Emma Dann , Hamish W. King , Vitalii Kleshchevnikov , Monika Dabrowska , Sophie Pritchard , Liam Bolt , Sara F. Vieira , Lira Mamanova , Ni Huang , Francesca Perrone , Issac Goh Kai’En , Steven N. Lisgo , Matilda Katan , Steven Leonard , Thomas R. W. Oliver , C. Elizabeth Hook , Komal Nayak , Lia S. Campos , Cecilia Domínguez Conde , Emily Stephenson , Justin Engelbert , Rachel A. Botting , Krzysztof Polanski , Stijn van Dongen , Minal Patel , Michael D. Morgan , John C. Marioni , Omer Ali Bayraktar , Kerstin B. Meyer , Xiaoling He , Roger A. Barker , Holm H. Uhlig , Krishnaa T. Mahbubani , Kourosh Saeb-Parsy , Matthias Zilbauer , Menna R. Clatworthy , Muzlifah Haniffa , Kylie R. James , and Sarah A. Teichmann . 2021 . “ Cells of the Human Intestinal Tract Mapped across Space and Time .” Nature 597 ( 7875 ): 250 – 55 . doi: 10.1038/s41586-021-03852-1 . OpenUrl CrossRef PubMed ↵ Francis , Joshua M. , Adam Kiezun , Alex H. Ramos , Stefano Serra , Chandra Sekhar Pedamallu , Zhi Rong Qian , Michaela S. Banck , Rahul Kanwar , Amit A. Kulkarni , Anna Karpathakis , Veronica Manzo , Tanupriya Contractor , Juliet Philips , Elizabeth Nickerson , Nam Pho , Susanne M. Hooshmand , Lauren K. Brais , Michael S. Lawrence , Trevor Pugh , Aaron McKenna , Andrey Sivachenko , Kristian Cibulskis , Scott L. Carter , Akinyemi I. Ojesina , Samuel Freeman , Robert T. Jones , Douglas Voet , Gordon Saksena , Daniel Auclair , Robert Onofrio , Erica Shefler , Carrie Sougnez , Jonna Grimsby , Lisa Green , Niall Lennon , Tim Meyer , Martyn Caplin , Daniel C. Chung , Andreas S. Beutler , Shuji Ogino , Christina Thirlwell , Ramesh Shivdasani , Sylvia L. Asa , Chris R. Harris , Gad Getz , Matthew Kulke , and Matthew Meyerson . 2013 . “ Somatic Mutation of CDKN1B in Small Intestine Neuroendocrine Tumors .” Nature Genetics 45 ( 12 ): 1483 – 86 . doi: 10.1038/ng.2821 . OpenUrl CrossRef PubMed ↵ Guttman , Mitchell , Ido Amit , Manuel Garber , Courtney French , Michael F. Lin , David Feldser , Maite Huarte , Or Zuk , Bryce W. Carey , John P. Cassady , Moran N. Cabili , Rudolf Jaenisch , Tarjei S. Mikkelsen , Tyler Jacks , Nir Hacohen , Bradley E. Bernstein , Manolis Kellis , Aviv Regev , John L. Rinn , and Eric S. Lander . 2009 . “ Chromatin Signature Reveals over a Thousand Highly Conserved Large Non-Coding RNAs in Mammals .” Nature 458 ( 7235 ): 223 – 27 . doi: 10.1038/nature07672 . OpenUrl CrossRef PubMed Web of Science ↵ de Herder , W. W. 2005 . “ Tumours of the Midgut (Jejunum, Ileum and Ascending Colon, Including Carcinoid Syndrome) .” Best Practice & Research. Clinical Gastroenterology 19 ( 5 ): 705 – 15 . doi: 10.1016/j.bpg.2005.05.007 . OpenUrl CrossRef PubMed ↵ Hickey , John W. , Winston R. Becker , Stephanie A. Nevins , Aaron Horning , Almudena Espin Perez , Chenchen Zhu , Bokai Zhu , Bei Wei , Roxanne Chiu , Derek C. Chen , Daniel L. Cotter , Edward D. Esplin , Annika K. Weimer , Chiara Caraccio , Vishal Venkataraaman , Christian M. Schürch , Sarah Black , Maria Brbić , Kaidi Cao , Shuxiao Chen , Weiruo Zhang , Emma Monte , Nancy R. Zhang , Zongming Ma , Jure Leskovec , Zhengyan Zhang , Shin Lin , Teri Longacre , Sylvia K. Plevritis , Yiing Lin , Garry P. Nolan , William J. Greenleaf , and Michael Snyder . 2023 . “ Organization of the Human Intestine at Single-Cell Resolution .” Nature 619 ( 7970 ): 572 – 84 . doi: 10.1038/s41586-023-05915-x . OpenUrl CrossRef PubMed ↵ Hoffman , Samantha E. , Todd W. Dowrey , Carlos Villacorta Martin , Kevin Bi , Breanna Titchen , Shreya Johri , Laura DelloStritto , Miraj Patel , Colin Mackichan , Stephanie Inga , Judy Chen , Grace Grimaldi , Sara Napolitano , Isaac Wakiro , Jingyi Wu , Jason Yeung , Asaf Rotem , Ewa Sicinska , Erin Shannon , Thomas Clancy , Jiping Wang , Sarah Denning , Lauren Brais , Naomi R. Besson , Kathleen L. Pfaff , Ying Huang , Katrina Z. Kao , Scott Rodig , Jason L. Hornick , Sebastien Vigneau , Jihye Park , Matthew H. Kulke , Jennifer Chan , Eliezer M. Van Allen , and George J. Murphy . 2023 . “ Intertumoral Lineage Diversity and Immunosuppressive Transcriptional Programs in Well-Differentiated Gastroenteropancreatic Neuroendocrine Tumors .” Science Advances 9 ( 39 ): eadd9668 . doi: 10.1126/sciadv.add9668 . OpenUrl CrossRef PubMed ↵ Hofving , Tobias , Erik Elias , Anna Rehammar , Linda Inge , Gülay Altiparmak , Marta Persson , Erik Kristiansson , Martin E. Johansson , Ola Nilsson , and Yvonne Arvidsson . 2021 . “ SMAD4 Haploinsufficiency in Small Intestinal Neuroendocrine Tumors .” BMC Cancer 21 : 101 . doi: 10.1186/s12885-021-07786-9 . OpenUrl CrossRef PubMed ↵ Huarte , Maite , Mitchell Guttman , David Feldser , Manuel Garber , Magdalena J. Koziol , Daniela Kenzelmann-Broz , Ahmad M. Khalil , Or Zuk , Ido Amit , Michal Rabani , Laura D. Attardi , Aviv Regev , Eric S. Lander , Tyler Jacks , and John L. Rinn . 2010 . “ A Large Intergenic Noncoding RNA Induced by P53 Mediates Global Gene Repression in the P53 Response .” Cell 142 ( 3 ): 409 – 19 . doi: 10.1016/j.cell.2010.06.040 . OpenUrl CrossRef PubMed Web of Science ↵ Johnson , W. Evan , Cheng Li , and Ariel Rabinovic . 2007 . “ Adjusting Batch Effects in Microarray Expression Data Using Empirical Bayes Methods .” Biostatistics (Oxford, England) 8 ( 1 ): 118 – 27 . doi: 10.1093/biostatistics/kxj037 . OpenUrl CrossRef PubMed Web of Science ↵ Karlsson , Max , Cheng Zhang , Loren Méar , Wen Zhong , Andreas Digre , Borbala Katona , Evelina Sjöstedt , Lynn Butler , Jacob Odeberg , Philip Dusart , Fredrik Edfors , Per Oksvold , Kalle von Feilitzen , Martin Zwahlen , Muhammad Arif , Ozlem Altay , Xiangyu Li , Mehmet Ozcan , Adil Mardinoglu , Linn Fagerberg , Jan Mulder , Yonglun Luo , Fredrik Ponten , Mathias Uhlén , and Cecilia Lindskog . 2021 . “ A Single-Cell Type Transcriptomics Map of Human Tissues .” Science Advances 7 ( 31 ): eabh2169 . doi: 10.1126/sciadv.abh2169 . OpenUrl FREE Full Text Kim , Ji Tae , Jing Li , Jun Song , Eun Y. Lee , Heidi L. Weiss , Courtney M. Townsend , and B. Mark Evers . 2015 . “ Differential Expression and Tumorigenic Function of Neurotensin Receptor 1 in Neuroendocrine Tumor Cells .” Oncotarget 6 ( 29 ): 26960 – 70 . OpenUrl CrossRef PubMed Kim , Ji Tae , Chunming Liu , Yekaterina Y. Zaytseva , Heidi L. Weiss , Courtney M. Townsend , and B. Mark Evers . 2015 . “ Neurotensin, a Novel Target of Wnt/β-Catenin Pathway, Promotes Growth of Neuroendocrine Tumor Cells .” International Journal of Cancer. Journal International Du Cancer 136 ( 6 ): 1475 – 81 . doi: 10.1002/ijc.29123 . OpenUrl CrossRef PubMed ↵ Leja , Justyna , Ahmed Essaghir , Magnus Essand , Kenneth Wester , Kjell Oberg , Thomas H. Tötterman , Ricardo Lloyd , George Vasmatzis , Jean-Baptiste Demoulin , and Valeria Giandomenico . 2009 . “ Novel Markers for Enterochromaffin Cells and Gastrointestinal Neuroendocrine Carcinomas .” Modern Pathology: An Official Journal of the United States and Canadian Academy of Pathology, Inc 22 ( 2 ): 261 – 72 . doi: 10.1038/modpathol.2008.174 . OpenUrl CrossRef PubMed Web of Science ↵ Li , Xinmin , and Cun-Yu Wang . 2021 . “ From Bulk, Single-Cell to Spatial RNA Sequencing .” International Journal of Oral Science 13 ( 1 ): 1 – 6 . doi: 10.1038/s41368-021-00146-0 . OpenUrl CrossRef PubMed ↵ Liu , Jiaqi , Qing Xiao , Jiani Xiao , Chenxi Niu , Yuanyuan Li , Xiaojun Zhang , Zhengwei Zhou , Guang Shu , and Gang Yin . 2022 . “ Wnt/β-Catenin Signalling: Function, Biological Mechanisms, and Therapeutic Opportunities .” Signal Transduction and Targeted Therapy 7 ( 1 ): 1 – 23 . doi: 10.1038/s41392-021-00762-6 . OpenUrl CrossRef ↵ Modlin , Irvin M. , Kjell Oberg , Andrew Taylor , Ignat Drozdov , Lisa Bodei , and Mark Kidd . 2014 . “ Neuroendocrine Tumor Biomarkers: Current Status and Perspectives .” Neuroendocrinology 100 ( 4 ): 265 – 77 . doi: 10.1159/000368363 . OpenUrl CrossRef PubMed ↵ Mouritzen , Michelle V. , Sali Abourayale , Rooshanie Ejaz , Christine B. Ardon , Eugenia Carvalho , Louise T. Dalgaard , Martin Roursgaard , and Håvard Jenssen . 2018 . “ Neurotensin, Substance P, and Insulin Enhance Cell Migration .” Journal of Peptide Science: An Official Publication of the European Peptide Society 24 ( 7 ): e3093 . doi: 10.1002/psc.3093 . OpenUrl CrossRef ↵ Rao , Manisha , Ki Oh , Richard Moffitt , Patricia Thompson , Jinyu Li , Jingxuan Liu , Aaron Sasson , George Georgakis , Joseph Kim , Minsig Choi , and Scott Powers . 2020 . “ Comparative Single-Cell RNA Sequencing (scRNA-Seq) Reveals Liver Metastasis-Specific Targets in a Patient with Small Intestinal Neuroendocrine Cancer .” Cold Spring Harbor Molecular Case Studies 6 ( 2 ): a004978 . doi: 10.1101/mcs.a004978 . OpenUrl Abstract / FREE Full Text ↵ Rappaport , Noa , Michal Twik , Inbar Plaschkes , Ron Nudel , Tsippi Iny Stein , Jacob Levitt , Moran Gershoni , C. Paul Morrey , Marilyn Safran , and Doron Lancet . 2017 . “ MalaCards: An Amalgamated Human Disease Compendium with Diverse Clinical and Genetic Annotation and Structured Search .” Nucleic Acids Research 45 ( D1 ): D877 – 87 . doi: 10.1093/nar/gkw1012 . OpenUrl CrossRef PubMed Reimand , Jüri , Meelis Kull , Hedi Peterson , Jaanus Hansen , and Jaak Vilo . 2007 . “ G:Profiler—a Web-Based Toolset for Functional Profiling of Gene Lists from Large-Scale Experiments .” Nucleic Acids Research 35 ( Web Server issue ): W193 – 200 . doi: 10.1093/nar/gkm226 . OpenUrl CrossRef PubMed Web of Science ↵ Samsom , K. G. , L. M. van Veenendaal , G. D. Valk , M. R. Vriens , M. E. T. Tesselaar , and J. G. van den Berg . 2019 . “ Molecular Prognostic Factors in Small-Intestinal Neuroendocrine Tumours .” Endocrine Connections 8 ( 7 ): 906 – 22 . doi: 10.1530/EC-19-0206 . OpenUrl CrossRef PubMed ↵ Sei , Yoshitatsu , Jianying Feng , Xilin Zhao , Joanne Forbes , Derek Tang , Kunio Nagashima , Jeffrey Hanson , Martha M. Quezado , Marybeth S. Hughes , and Stephen A. Wank . 2016 . “ Polyclonal Crypt Genesis and Development of Familial Small Intestinal Neuroendocrine Tumors .” Gastroenterology 151 ( 1 ): 140 – 51 . doi: 10.1053/j.gastro.2016.03.007 . OpenUrl CrossRef PubMed ↵ Shannon , Paul , Andrew Markiel , Owen Ozier , Nitin S. Baliga , Jonathan T. Wang , Daniel Ramage , Nada Amin , Benno Schwikowski , and Trey Ideker . 2003 . “ Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks .” Genome Research 13 ( 11 ): 2498 – 2504 . doi: 10.1101/gr.1239303 . OpenUrl Abstract / FREE Full Text ↵ Singh , Pratik N. P. , Wei Gu , Shariq Madha , Allen W. Lynch , Paloma Cejas , Ruiyang He , Swarnabh Bhattacharya , Miguel Muñoz Gomez , Matthew G. Oser , Myles Brown , Henry W. Long , Clifford A. Meyer , Qiao Zhou , and Ramesh A. Shivdasani . 2024 . “ Transcription Factor Dynamics, Oscillation, and Functions in Human Enteroendocrine Cell Differentiation .” Cell Stem Cell 31 ( 7 ): 1038 - 1057.e11 . doi: 10.1016/j.stem.2024.04.015 . OpenUrl CrossRef PubMed Smedsrød , Bård , and Håkan Pertoft . 1985 . “ Preparation of Pure Hepatocytes and Reticuloendothelial Cells in High Yield From a Single Rat Liver by Means of Percoll Centrifugation and Selective Adherence .” Journal of Leukocyte Biology 38 ( 2 ): 213 – 30 . doi: 10.1002/jlb.38.2.213 . OpenUrl CrossRef PubMed Web of Science ↵ Szklarczyk , Damian , Rebecca Kirsch , Mikaela Koutrouli , Katerina Nastou , Farrokh Mehryary , Radja Hachilif , Annika L. Gable , Tao Fang , Nadezhda T. Doncheva , Sampo Pyysalo , Peer Bork , Lars J. Jensen , and Christian von Mering . 2023 . “ The STRING Database in 2023: Protein-Protein Association Networks and Functional Enrichment Analyses for Any Sequenced Genome of Interest .” Nucleic Acids Research 51 ( D1 ): D638 – 46 . doi: 10.1093/nar/gkac1000 . OpenUrl CrossRef PubMed ↵ Tran , Catherine G. , Scott K. Sherman , and James R. Howe . 2020 . “ Small Bowel Neuroendocrine Tumors .” Current Problems in Surgery 57 ( 12 ): 100823 . doi: 10.1016/j.cpsurg.2020.100823 . OpenUrl CrossRef PubMed ↵ Wang , Yalong , Wanlu Song , Jilian Wang , Ting Wang , Xiaochen Xiong , Zhen Qi , Wei Fu , Xuerui Yang , and Ye-Guang Chen . 2020 . “ Single-Cell Transcriptome Analysis Reveals Differential Nutrient Absorption Functions in Human Intestine .” The Journal of Experimental Medicine 217 ( 2 ): e20191130 . doi: 10.1084/jem.20191130 . OpenUrl CrossRef PubMed ↵ Whyte , Jemima L. , Andrew A. Smith , and Jill A. Helms . 2012 . “ Wnt Signaling and Injury Repair .” Cold Spring Harbor Perspectives in Biology 4 ( 8 ): a008078 . doi: 10.1101/cshperspect.a008078 . OpenUrl Abstract / FREE Full Text ↵ Xiang , Yan , Faizan Malik , and Paul J. Zhang . 2023 . “ Islet-1 Is Differentially Expressed Among Neuroendocrine and Non-Neuroendocrine Tumors and Its Potential Diagnostic Implication .” International Journal of Surgical Pathology 31 ( 7 ): 1294 – 1301 . doi: 10.1177/10668969231157319 . OpenUrl CrossRef PubMed ↵ Xiao , Hualiang , Ying Zeng , Qiushi Wang , Shirong Wei , and Xiangfeng Zhu . 2017 . “ A Novel Positive Feedback Loop Between NTSR1 and Wnt/β-Catenin Contributes to Tumor Growth of Glioblastoma .” Cellular Physiology and Biochemistry 43 ( 5 ): 2133 – 42 . doi: 10.1159/000484232 . OpenUrl CrossRef PubMed ↵ Yao , James C. , Manal Hassan , Alexandria Phan , Cecile Dagohoy , Colleen Leary , Jeannette E. Mares , Eddie K. Abdalla , Jason B. Fleming , Jean-Nicolas Vauthey , Asif Rashid , and Douglas B. Evans . 2008 . “ One Hundred Years after ‘Carcinoid’: Epidemiology of and Prognostic Factors for Neuroendocrine Tumors in 35,825 Cases in the United States .” Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology 26 ( 18 ): 3063 – 72 . doi: 10.1200/JCO.2007.15.4377 . OpenUrl Abstract / FREE Full Text ↵ Ye , Yingnan , Xinxin Long , Lijie Zhang , Jieying Chen , Pengpeng Liu , Hui Li , Feng Wei , Wenwen Yu , Xiubao Ren , and Jinpu Yu . 2016 . “ NTS/NTR1 Co-Expression Enhances Epithelial-to-Mesenchymal Transition and Promotes Tumor Metastasis by Activating the Wnt/β-Catenin Signaling Pathway in Hepatocellular Carcinoma .” Oncotarget 7 ( 43 ): 70303 – 22 . doi: 10.18632/oncotarget.11854 . OpenUrl CrossRef PubMed ↵ Young , Matthew D. , Thomas J. Mitchell , Felipe A. Vieira Braga , Maxine G. B. Tran , Benjamin J. Stewart , John R. Ferdinand , Grace Collord , Rachel A. Botting , Dorin-Mirel Popescu , Kevin W. Loudon , Roser Vento-Tormo , Emily Stephenson , Alex Cagan , Sarah J. Farndon , Martin Del Castillo Velasco-Herrera , Charlotte Guzzo , Nathan Richoz , Lira Mamanova , Tevita Aho , James N. Armitage , Antony C. P. Riddick , Imran Mushtaq , Stephen Farrell , Dyanne Rampling , James Nicholson , Andrew Filby , Johanna Burge , Steven Lisgo , Patrick H. Maxwell , Susan Lindsay , Anne Y. Warren , Grant D. Stewart , Neil Sebire , Nicholas Coleman , Muzlifah Haniffa , Sarah A. Teichmann , Menna Clatworthy , and Sam Behjati . 2018 . “ Single-Cell Transcriptomes from Human Kidneys Reveal the Cellular Identity of Renal Tumors .” Science (New York, N.Y .) 361 ( 6402 ): 594 – 99 . doi: 10.1126/science.aat1699 . OpenUrl Abstract / FREE Full Text ↵ Zheng , Grace X. Y. , Brian T. Do , Dan E. Webster , Paul A. Khavari , and Howard Y. Chang . 2014 . “ Dicer-microRNA-Myc Circuit Promotes Transcription of Hundreds of Long Noncoding RNAs .” Nature Structural & Molecular Biology 21 ( 7 ): 585 – 90 . doi: 10.1038/nsmb.2842 . OpenUrl CrossRef PubMed ↵ Zheng , Grace X. Y. , Jessica M. Terry , Phillip Belgrader , Paul Ryvkin , Zachary W. Bent , Ryan Wilson , Solongo B. Ziraldo , Tobias D. Wheeler , Geoff P. McDermott , Junjie Zhu , Mark T. Gregory , Joe Shuga , Luz Montesclaros , Jason G. Underwood , Donald A. Masquelier , Stefanie Y. Nishimura , Michael Schnall-Levin , Paul W. Wyatt , Christopher M. Hindson , Rajiv Bharadwaj , Alexander Wong , Kevin D. Ness , Lan W. Beppu , H. Joachim Deeg , Christopher McFarland , Keith R. Loeb , William J. Valente , Nolan G. Ericson , Emily A. Stevens , Jerald P. Radich , Tarjei S. Mikkelsen , Benjamin J. Hindson , and Jason H. Bielas . 2017 . “ Massively Parallel Digital Transcriptional Profiling of Single Cells .” Nature Communications 8 ( 1 ): 14049 . doi: 10.1038/ncomms14049 . 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Share A single-cell transcriptomic comparison between small intestinal neuroendocrine tumors and their progenitor Fredrik Axling , Elham Barazeghi , Per Hellman , Olov Norlén , Samuel Backman , Peter Stålberg bioRxiv 2025.02.10.637596; doi: https://doi.org/10.1101/2025.02.10.637596 Share This Article: Copy Citation Tools A single-cell transcriptomic comparison between small intestinal neuroendocrine tumors and their progenitor Fredrik Axling , Elham Barazeghi , Per Hellman , Olov Norlén , Samuel Backman , Peter Stålberg bioRxiv 2025.02.10.637596; doi: https://doi.org/10.1101/2025.02.10.637596 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Cancer Biology Subject Areas All Articles Animal Behavior and Cognition (7622) Biochemistry (17648) Bioengineering (13870) Bioinformatics (41880) Biophysics (21423) Cancer Biology (18553) Cell Biology (25458) Clinical Trials (138) Developmental Biology (13364) Ecology (19866) Epidemiology (2067) Evolutionary Biology (24290) Genetics (15589) Genomics (22475) Immunology (17711) Microbiology (40326) Molecular Biology (17145) Neuroscience (88471) Paleontology (666) Pathology (2826) Pharmacology and Toxicology (4815) Physiology (7635) Plant Biology (15114) Scientific Communication and Education (2044) Synthetic Biology (4286) Systems Biology (9815) Zoology (2268)