Biology subjects

Aure, M. R.

Publications and source records attributed to Aure, M. R..

5 recordsLinked to original sources

bioRxiv2025

CLONAL SELECTION SUPPORTED BY SINGLE CELL DNA SEQUENCING REVEALS HORMONAL ADAPTATION AND RESISTANCE IN LOCALLY ADVANCED BREAST CANCER DURING NEOADJUVANT AROMATASE INHIBITION

BackgroundThe aromatase inhibitors (AI) letrozole and exemestane, are often used in sequence in targeting ER+ breast cancers. However resistance to AI poses a major barrier to sustained clinical benefit, while the biological mechanisms underlying the phenomenon remain largely unknown. In this study, we build on our clinical NeoLetExe trial, with the aim to investigate the molecular basis of resistance to AI, by analysing subclonal evolutionary dynamics during sequential treatment. MethodsWe use whole-exome sequencing (WES) data from 11 ER+ breast cancer patients and 3 timepoints of the Neoletexe trial to reconstruct cancer cell fraction-based subclonal composition. Single-cell DNA sequencing from matched tumour samples is used for validating identified clones and variants. Subclonal variants were annotated to genes by integrating evidence from public data and ExpectoSc. Pathway enrichment analysis using Human Base was conducted. ResultsHigher cancer cell fraction clone trajectories were significantly associated with reduced treatment response (p = 0.023). Clones reconstructed by WES were validated at 81% using single-cell DNA sequencing. Clones resistant to both letrozole and exemestane demonstrated PIK3CA/AKT/mTOR signaling activation, KRAS pathway dysregulation, hedgehog signaling, and androgen receptor pathways, alongside extensive immune activation and metabolic reprogramming. Drug-specific resistance patterns showed exemestane-resistant clones enriched for epigenetic control and miRNA-mediated silencing, while letrozole-resistant clones displayed metabolic dysregulation but notably lacked immune pathway activation. In contrast, treatment-sensitive clones maintained coordinated cell cycle control, preserved DNA damage responses, and retained immune signaling capacity. Analysis of FDA-approved breast cancer targets identified actionable alterations in PIK3CA (4 patients) and AKT1 (1 patient) that persisted through AI treatment, with RNA expression analysis revealing 48 additional therapeutic targets spanning PI3K/AKT/mTOR, CDK4/6, DNA repair (BRCA1/2, ATM), and immune checkpoint pathways. ConclusionWES-based cancer cell fraction analysis successfully captured subclonal evolutionary trajectories during AI treatment, revealing drug-specific mechanisms and identifying key molecular players in endocrine therapy resistance. This work establishes a framework for precision oncology approaches by providing actionable therapeutic targets and advancing our understanding of resistance mechanisms to improve clinical outcomes in sequential AI therapy.

cancer biology↗

bioRxiv2021

Epigenetic alterations at distal enhancers are linked to proliferation in human breast cancer

Breast cancer is a highly heterogeneous disease driven by multiple factors including genetic and epigenetic alterations. DNA methylation patterns have been shown to be altered on a genome-wide scale and previous studies have highlighted the critical role of aberrant DNA methylation on gene expression and breast cancer pathogenesis. Here, we perform genome-wide expression-methylation Quantitative Trait Loci (emQTL), a method for integration of CpG methylation and gene expression to identify disease-driving genes under epigenetic control. By grouping these emQTLs by biclustering we identify associations representing important biological processes associated with breast cancer pathogenesis such as proliferation and tumor infiltrating fibroblasts. We report hypomethylation at enhancers carrying transcription factor binding sites of key proliferation-driving transcription factors such as CEBP-{beta}, FOSL1, and FOSL2, with concomitant high expression of cell cycle- and proliferation-related genes in aggressive breast tumors. The identified CpGs and genes were found to be connected through chromatin loops, together indicating that proliferation in aggressive breast tumors is under epigenetic regulation by DNA methylation. Interestingly, there was a significant correlation between proliferation-related DNA methylation and gene expression also within subtypes of breast cancer, thereby showing that varying proliferation may be explained by epigenetic profiles across breast cancer subtypes. Indeed, the identified proliferation gene signature was prognostic both in the Luminal A and Luminal B subtypes. Taken together, we show that proliferation in breast cancer is linked to hypomethylation at specific enhancers and transcription factor binding mediated through chromatin loops.

cancer biology↗

bioRxiv2020

Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of the gene regulatory program in cancers

BackgroundMost cancer alterations occur in the noncoding portion of the human genome, which contains important regulatory regions acting as genetic switches to ensure gene expression occurs at correct times and intensities in correct tissues. However, large scale discovery of noncoding events altering the gene expression regulatory program has been limited to a few examples with high recurrence or high functional impact. ResultsWe focused on transcription factor binding sites (TFBSs) that show similar mutation loads than what is observed in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluated the combined effects of transcriptional and post-transcriptional alteration on the dysregulation of the regulatory programs in cancer. The analysis of seven cancer cohorts culminated with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that were associated with a cascading trans-effect deregulation on the cells regulatory program. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predicted 17 miRNAs as pan-cancer-associated through deregulation of their target gene networks. Overall, our predictions were enriched for protein-coding and miRNA genes previously annotated as cancer drivers. Functional enrichment analyses highlighted that cis-regulatory mutations are associated with the dysregulation of key pathways associated with carcinogenesis ConclusionsThese pan-cancer results suggest that our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients. It highlights how the gene regulatory program is disrupted in cancer cells by combining transcriptional and post-transcriptional regulation of gene expression.

genomics↗

bioRxiv2020

Crosstalk between microRNA expression and DNA methylation drive the hormone-dependent phenotype of breast cancer

BackgroundAbnormal DNA methylation is observed as an early event in breast carcinogenesis. However, how such alterations arise is still poorly understood. microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and have been shown to play key roles in various biological processes. Here, we integrate miRNA expression and DNA methylation at CpGs to study how miRNAs may affect the breast cancer methylome and how DNA methylation may regulate miRNA expression. ResultsmiRNA expression and DNA methylation data from two breast cancer cohorts were subjected to genome-wide correlation analysis. Clustering of the miRNA expression-DNA methylation association pairs significant in both cohorts identified distinct clusters of miRNAs and CpGs. These clusters recapitulated important biological processes associated with breast cancer pathogenesis. Notably, two major clusters were related to immune or fibroblast infiltration, hence identifying miRNAs associated with cells of the tumor microenvironment, while another large cluster was related to estrogen receptor (ER) signaling. Studying the chromatin landscape surrounding the CpGs associated with the estrogen-signaling cluster, we found that miRNAs from this cluster are likely to be regulated through DNA methylation of enhancers bound by FOXA1, GATA2 and ER-alpha. Further, at the hub of the estrogen-cluster, we identified hsa-miR-29c-5p as negatively correlated with the mRNA and protein expression of the DNA methyltransferase DNMT3A, a key enzyme regulating DNA methylation. We found deregulation of hsa-miR-29c-5p already in pre-invasive breast lesions and postulate that hsa-miR-29c-5p may trigger early event abnormal DNA methylation in ER positive breast cancer. ConclusionsWe describe how miRNA expression and DNA methylation interact and associate with distinct breast cancer phenotypes.

cancer biology↗

bioRxiv2019

Copy number motifs expose genome instability type and predict driver events and disease outcome in breast cancer

Tumor evolution is dependent on and constrained by the genotypes emerging from genome instability. We hypothesized that non-site-specific copy number motifs would correlate with underlying replication defects and also with tumor and patient fate. Six feature detectors were defined to characterize and score the local spatial behaviour of a copy number profile. By accumulating scores across genomic regions, a low-dimensional representation of the tumor genome was obtained. The proposed Copy Aberration Regional Mapping Analysis (CARMA) algorithm was applied to 2384 breast tumors from three breast cancer cohorts, revealing distinct copy number motifs in established molecular subtypes. A prognostic index combining the features predicted breast cancer specific survival better than both the genomic instability index (GII) and all commonly used clinical stratifications. CARMA offers effective comparison of tumor subgroups and extracts biologically and clinically relevant features from allele-specific copy number profiles.

bioinformatics↗