Biology subjects

Nielsen, M. M.

Publications and source records attributed to Nielsen, M. M..

11 recordsLinked to original sources

bioRxiv2025

LRP2 expression in melanoma is associated with a transitory cell state, increased T cell infiltration, and is upregulated by IFNγ signaling

Low density lipoprotein receptor-related protein 2 (LRP2) is a 600 kilodalton multi-ligand endocytic membrane receptor expressed in several cell types during fetal development, including neuroepithelial cells, and in select absorptive epithelial cells in the adult. In epithelial cancers, LRP2 expression is associated with a differentiated tumor cell state and better prognosis. In previous work, we found that while LRP2 is not expressed in benign naevi, it is frequently acquired in melanoma. However, the molecular drivers of LRP2 expression in melanoma and characteristics of LRP2-expressing melanoma have yet to be described. Here, we show that LRP2 expression is related to a transitory melanoma cell state defined by co-expression of melanocyte lineage and neural crest transcriptional programs. Further, we reveal that melanoma LRP2 expression is increased in T cell-inflamed tumors, and is directly upregulated through interferon-gamma signaling. Correlation of melanoma LRP2 expression with clinicopathological variables demonstrates that LRP2 expression is associated with low Breslow thickness and low clinical stage in primary melanomas. Taken together, the present study describes the characteristics of LRP2-expressing melanoma and reveals interferon gamma signaling as a novel strong positive regulator of LRP2 expression in melanoma. SignificanceMelanoma cells often acquire LRP2 expression but the drivers of LRP2 expression in this setting and characteristics of LRP2-expressing melanoma remain unclear. Here, we show that LRP2 expression is related to a transitory melanoma differentiation cell state. Further, LRP2 expression in melanoma correlates with a T cell-inflamed tumor microenvironment and LRP2 expression in melanoma cells can be directly increased by interferon-gamma. In addition, LRP2 expression is associated with less advanced histopathological characteristics of melanoma. These findings encourage future studies on LRP2 in settings with increased interferon signaling, in particular in melanoma metastases following immunotherapy.

cancer biology↗

bioRxiv2024

Temporally resolved single-cell RNA sequencing reveals protective and pathological responses during herpes simplex virus 1 CNS infection

Herpes Simplex Virus 1 (HSV-1) is a common human neurotropic virus with the majority of adults harboring latent-recurrent infections. In rare cases, HSV-1 infection can access the central nervous system through the neuronal route and develop into life-threatening encephalitis. Here, we used a mouse model for HSV-1 infection to describe the transcriptomic profile of the infected brain stem at the single-cell level and with temporal resolution. Among resident brain cells, microglia increased in proportion during the course of infection, while astrocytes, pericytes, and endothelial cell levels decrease. At the levels of peripheral immune cells, we found notably monocytes to strongly influx the infected brain. Large dynamic changes were found in the abundance of subpopulations of the different cell types following virus infection. For instance, we identify one subpopulation of microglia exhibiting very high type I interferon and chemokine expression early during infection. This population was also enriched for viral transcripts, suggesting localization at foci of infection, and orchestrating recruitment of other immune cells. In contrast, for the infiltrating monocytes, we identified a larger panel of unique subpopulations with antiviral and inflammatory phenotypes, and found not all of these being highly positive for viral transcripts, thus indicating monocyte activities beyond the infected brain areas. Finally, investigation of endothelial cell cross-talk with other cell types revealed that cytokines derived from microglia and monocyte, but also T cells, contribute to disturbance of the blood brain barrier. Our work thus reveals for the first time the complex nature of the cellular response in the virus-infected brain, which seeks to eliminate infection but can also prime for pathological changes.

immunology↗

bioRxiv2023

circHIPK3 nucleates IGF2BP2 and functions as a competing endogenous RNA

Circular RNAs (circRNAs) represent a class of widespread endogenous RNAs that regulate gene expression and thereby influence cell biological decisions with implications for the pathogenesis of several diseases. Here, we disclose a novel gene-regulatory role of circHIPK3 by combining analyses of large genomics datasets and mechanistic cell biological follow-up experiments. Specifically, we use temporal depletion of circHIPK3 or specific RNA binding proteins (RBPs) and identify several perturbed genes by RNA sequencing analyses. Using expression-coupled motif analyses of mRNA expression data from various knockdown experiments, we identify an 11-mer motif within circHIPK3, which is also enriched in genes that become downregulated upon circHIPK3 depletion. By mining eCLIP datasets, we find that the 11-mer motif constitutes a strong binding site for IGF2BP2 and validate this circHIPK3-IGF2BP2 interaction experimentally using RNA-immunoprecipitation and competition assays in bladder cancer cell lines. Our results suggest that circHIPK3 and IGF2BP2 mRNA targets compete for binding. Since the identified 11-mer motif found in circHIPK3 is enriched in upregulated genes following IGF2BP2 knockdown, and since IGF2BP2 depletion conversely globally antagonizes the effect of circHIPK3 knockdown on target genes, our results suggest that circHIPK3 can sequester IGF2BP2 as a competing endogenous RNA (ceRNA), leading to target mRNA stabilization. As an example of a circHIPK3-regulated gene, we focus on the STAT3 mRNA as a specific substrate of IGF2BP2 and validate that manipulation of circHIPK3 regulates IGF2BP2-STAT3 mRNA binding and thereby STAT3 mRNA levels. However, absolute copy number quantifications demonstrate that IGF2BP2 outnumbers circHIPK3 by orders of magnitude, which is inconsistent with a simple 1:1 ceRNA hypothesis. Instead, we show that circHIPK3 can nucleate multiple copies of IGF2BP2, potentially via phase separation, to produce IGF2BP2 condensates. Finally, we show that circHIPK3 expression correlates with overall survival of patients with bladder cancer. Our results are consistent with a model where relatively few cellular circHIPK3 molecules function as inducers of IGF2BP2 condensation thereby regulating STAT3 and other key factors for cell proliferation and potentially cancer progression.

molecular biology↗

bioRxiv2021

Sequence dependencies and mutation rates of localized mutational processes in cancer

BackgroundCancer mutations accumulate through replication errors and DNA damage coupled with incomplete repair. Individual mutational processes often show strong sequence and regional preferences. As a result, some sequence contexts mutate at much higher rates than others. Mutational hotspots, with recurrent mutations across cancer samples, represent genomic positions with elevated mutation rates, often caused by highly localized mutational processes. ResultsWe analyze the mutation rates of all 11-mer genomic sequence contexts using the PCAWG set of 2,583 pan-cancer whole genomes. We further associate individual mutations and contexts to mutational signatures and estimate their relative mutation rates. We show that hotspots generally identify highly mutable sequence contexts. Using these, we show that some mutational signatures are enriched in hotspot sequence contexts, corresponding to well-defined sequence preferences for the underlying localized mutational processes. This includes signature 17b (of unknown etiology) and signatures 62 (POLE), 7a (UV), and 72 (linked to lymphomas). In some cases, the mutation rate increases further when focusing on certain genomic regions, such as signature 62 in poised promoters, where the mutation is increased several thousand folds over the overall data set average. ConclusionWe summarize our findings in a catalog of localized mutational processes, their sequence preferences, and their estimated mutation rates.

cancer biology↗

bioRxiv2021

Public T-cell epitopes shared among SARS-CoV-2 variants are presented on prevalent HLA class I alleles

T-cell epitopes with broad population coverage may form the basis for a new generation of SARS-CoV-2 vaccines. However, published studies on immunoprevalence are limited by small test cohorts, low frequencies of antigen-specific cells and lack of data correlating eluted HLA ligands with T-cell responsiveness. As the protective role of pre-existing cross-reactivity to homologous peptides is unclear, we aimed to identify SARS-CoV-2-specific minimal epitopes recognized by CD8 T-cells among 48 peptides eluted from prevalent HLA alleles, and an additional 84 predicted binders, in a large cohort of convalescents (n=83) and pre-pandemic control samples (n=19). We identified nine conserved SARS-CoV-2-specific epitopes restricted by four of the most prevalent HLA class I alleles in the Norwegian study cohort, to which responding CD8 T cells were detected in 70-100% of convalescents expressing the relevant HLA allele. Only two of these were derived from the Spike protein, included in current vaccines. We found a strong correlation between immunoprevalence and immunodominance. Thus, the CD8 T-cell response to SARS-CoV-2 is more focused than previously believed. Using a new algorithm, we predict that a vaccine including these epitopes could induce a T-cell response in 83% of Caucasians.

immunology↗

bioRxiv2020

miRNA activity inferred from single cell mRNA expression

High throughput single-cell RNA sequencing (scRNAseq) can provide mRNA expression profiles for thousands of cells. However, miRNAs cannot currently be studied at the same scale. By exploiting that miRNAs bind well-defined sequence motifs and typically down-regulate target genes, we show that motif enrichment analysis can be used to derive miRNA activity estimates from scRNAseq data. Motif enrichment analyses have traditionally been used to derive binding motifs for regulatory factors, such as miRNAs or transcription factors, that have an effect on gene expression. Here we reverse its use. By starting from the miRNA seed site, we derive a measure of activity for miRNAs in single cells. We first establish the approach on a comprehensive set of bulk TCGA cancer samples (n=9,679), with paired mRNA and miRNA expression profiles, where many miRNAs show a strong correlation with measured expression. By downsampling we show that the method can be used to estimate miRNA activity in sparse data comparable to scRNAseq experiments. We then analyze a human and a mouse scRNAseq data set, and show that for several miRNA candidates, including liver specific miR-122 and muscle specific miR-1 and miR-133a, we obtain activity measures supported by the literature. The methods are implemented and made available in the miReact software. Our results demonstrate that miRNA activities can be estimated at the single cell level. This allows insights into the dynamics of miRNA activity across a range of fields where scRNAseq is applied.

bioinformatics↗

bioRxiv2020

Transcriptome-wide profiles of circular RNA and RNA binding protein interactions reveal effects on circular RNA biogenesis and cancer pathway expression

Circular RNAs (circRNAs) are stable, often highly expressed RNA transcripts with potential to modulate other regulatory RNAs. A few circRNAs have been shown to bind RNA binding proteins (RBPs), however, little is known about the prevalence and strength of these interactions in different biological contexts. Here, we comprehensively evaluate the interplay between circRNAs and RBPs in the ENCODE cell lines, HepG2 and K562, by profiling the expression of circRNAs in fractionated total RNA-sequencing samples and analyzing binding sites of 150 RBPs in large eCLIP data sets. We show that KHSRP binding sites are enriched in flanking introns of circRNAs in both HepG2 and K562 cells, and that KHSRP depletion affects circRNA biogenesis. Additionally, we show that exons forming circRNAs are generally enriched with RBP binding sites compared to non-circularizing exons. To detect individual circRNAs with regulatory potency, we computationally identify circRNAs that are highly covered by RBP binding sites and experimentally validate circRNA-RBP interactions by RNA immunoprecipitations. We characterize circCDYL, a highly expressed circRNA with clinical and functional implications in bladder cancer, which is covered with GRWD1 binding sites. We confirm that circCDYL binds GRWD1 in vivo and functionally characterizes the effect of circCDYL-GRWD1 interactions on target genes in HepG2. Furthermore, we confirm interactions between circCDYL and RBPs in bladder cancer cells and demonstrate that circCDYL depletion affects hallmarks of cancer and perturbs the expression of key cancer genes, e.g. TP53 and MYC. Finally, we show that elevated levels of highly RBP-covered circRNAs, including circCDYL, are associated with overall survival of bladder cancer patients. Our study demonstrates transcriptome-wide and cell-type-specific circRNA-RBP interactions that could play important regulatory roles in tumorigenesis.

genomics↗

bioRxiv2017

Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes

Discovery of cancer drivers has traditionally focused on the identification of protein-coding genes. Here we present a comprehensive analysis of putative cancer driver mutations in both protein-coding and non-coding genomic regions across >2,500 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We developed a statistically rigorous strategy for combining significance levels from multiple driver discovery methods and demonstrate that the integrated results overcome limitations of individual methods. We combined this strategy with careful filtering and applied it to protein-coding genes, promoters, untranslated regions (UTRs), distal enhancers and non-coding RNAs. These analyses redefine the landscape of non-coding driver mutations in cancer genomes, confirming a few previously reported elements and raising doubts about others, while identifying novel candidate elements across 27 cancer types. Novel recurrent events were found in the promoters or 5UTRs of TP53, RFTN1, RNF34, and MTG2, in the 3UTRs of NFKBIZ and TOB1, and in the non-coding RNA RMRP. We provide evidence that the previously reported non-coding RNAs NEAT1 and MALAT1 may be subject to a localized mutational process. Perhaps the most striking finding is the relative paucity of point mutations driving cancer in non-coding genes and regulatory elements. Though we have limited power to discover infrequent non-coding drivers in individual cohorts, combined analysis of promoters of known cancer genes show little excess of mutations beyond TERT.

genomics↗

bioRxiv2017

Pan-cancer study of heterogeneous RNA aberrations

We present the most comprehensive catalogue of cancer-associated gene alterations through characterization of tumor transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes project. Using matched whole-genome sequencing data, we attributed RNA alterations to germline and somatic DNA alterations, revealing likely genetic mechanisms. We identified 444 associations of gene expression with somatic non-coding single-nucleotide variants. We found 1,872 splicing alterations associated with somatic mutation in intronic regions, including novel exonization events associated with Alu elements. Somatic copy number alterations were the major driver of total gene and allele-specific expression (ASE) variation. Additionally, 82% of gene fusions had structural variant support, including 75 of a novel class called \"bridged\" fusions, in which a third genomic location bridged two different genes. Globally, we observe transcriptomic alteration signatures that differ between cancer types and have associations with DNA mutational signatures. Given this unique dataset of RNA alterations, we also identified 1,012 genes significantly altered through both DNA and RNA mechanisms. Our study represents an extensive catalog of RNA alterations and reveals new insights into the heterogeneous molecular mechanisms of cancer gene alterations.

genomics↗

bioRxiv2017

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival

Cancer develops by accumulation of somatic driver mutations, which impact cellular function. Non-coding mutations in non-coding regulatory regions can now be studied genome-wide and further characterized by correlation with gene expression and clinical outcome to identify driver candidates. Using a new two-stage procedure, called ncDriver, we first screened 507 ICGC whole-genomes from ten cancer types for non-coding elements, in which mutations are both recurrent and have elevated conservation or cancer specificity. This identified 160 significant non-coding elements, including the TERT promoter, a well-known non-coding driver element, as well as elements associated with known cancer genes and regulatory genes (e.g., PAX5, TOX3, PCF11, MAPRE3). However, in some significant elements, mutations appear to stem from localized mutational processes rather than recurrent positive selection in some cases. To further characterize the driver potential of the identified elements and shortlist candidates, we identified elements where presence of mutations correlated significantly with expression levels (e.g. TERT and CDH10) and survival (e.g. CDH9 and CDH10) in an independent set of 505 TCGA whole-genome samples. In a larger pan-cancer set of 4,128 TCGA exomes with expression profiling, we identified mutational correlation with expression for additional elements (e.g., near GATA3, CDC6, ZNF217 and CTCF transcription factor binding sites). Survival analysis further pointed to MIR122, a known marker of poor prognosis in liver cancer. This screen for significant mutation patterns followed by correlative mutational analysis identified new individual driver candidates and suggest that some non-coding mutations recurrently affect expression and play a role in cancer development.

cancer biology↗

bioRxiv2017

A Site Specific Model And Analysis Of The Neutral Somatic Mutation Rate In Whole-Genome Cancer Data

BackgroundDetailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration.\n\nResultsTo take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures.\n\nConclusionWe find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

bioinformatics↗