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Kruse, M.

Publications and source records attributed to Kruse, M..

3 recordsLinked to original sources

Topological data analysis identifies PURPL as a prognostic gene in breast cancer Luminal A patients

IntroductionLuminal A is the most common breast cancer molecular subtype and is generally associated with a favorable five-year prognosis. However, a substantial subset of patients experience relapse, suggesting that biologically distinct high-risk tumors exist within this subtype. MethodsWe applied Topological Analysis of Array Comparative Genomic Hybridization (TAaCGH) to identify recurrent copy number alterations associated with Luminal A breast cancer. We subsequently evaluated the long non-coding RNA PURPL using copy number, gene expression, and survival data in the independent TCGA, METABRIC, and SCAN-B cohorts. Associations with clinical outcome were examined using multivariable Cox regression and TP53-stratified analyses. ResultsPURPL copy number gain was associated with significantly worse survival in TCGA and METABRIC, while elevated PURPL expression was associated with significantly worse survival in TCGA and SCAN-B. Elevated PURPL expression remained associated with survival after adjustment for clinical covariates. In analyses stratified by TP53 mutation status, high PURPL expression remained associated with worse survival in TP53 wild-type tumors. Although PURPL has previously been implicated in cancer-related mechanisms, its copy number alteration, expression, and association with clinical outcome have not been systematically evaluated in Luminal A breast cancer. ConclusionThese findings identify PURPL as a candidate lncRNA within a recurrent copy number alteration associated with adverse clinical outcome in Luminal A breast cancer and support further mechanistic investigation of its role in this subtype.

cancer biology↗

Tunable DNA Origami Nanosensors for Detection of Multiscale Spatial Ion Concentration Gradients

Ion gradients play a vital role in cellular signaling, mechanobiology, and organ-level homeostasis. Despite their importance, accurately mapping these spatial gradients at biologically relevant length scales remains a challenge due to the limited tunability and spatial resolution of conventional fluorescent sensors. Here, we present a DNA origami-based sensor (NanoDyn) with tunable sensitivity that enables the detection of Na+ ion gradients across micron to millimeter scales. The sensor design leverages programmable DNA base-pairing interactions to control both the detection range and sensitivity of the sensor. Using fluorescence spectroscopy, we show that NanoDyn can exhibit programmable sensing ranges spanning [~]100 - 1675 mM Na+. To validate the ability to quantify ion gradients and investigate its spatial resolution, we use a custom microfluidic gradient generator, showing that NanoDyn can resolve changes in ion gradients across multiple scales and over distances as little as [~]6 {micro}m, which here, is limited by the resolution of the microfluidic device. In highlighting the potential of DNA nanodevices as multiscale tunable ion gradient sensors, together with their biocompatibility, high temporal resolution, and potential for multiplexed functionalization, this work expands on the role that DNA nanodevices can play in spatial sensing to study ion-mediated processes in microenvironments. Overall, this work advances DNA nanotechnology as a versatile foundation for biosensing with capabilities to probe ion-mediated signaling in health and disease.

bioengineering↗

Visualization of individual cell division history in complex tissues

The division potential of individual stem cells and the molecular consequences of successive rounds of proliferation remain largely unknown. We developed an inducible cell division counter (iCOUNT) that reports cell division events in human and mouse tissues in vitro and in vivo. Analysing cell division histories of neural stem/progenitor cells (NSPCs) in the developing and adult brain, we show that iCOUNT allows for novel insights into stem cell behaviour. Further, we used single cell RNA-sequencing (scRNA-seq) of iCOUNT-labelled NSPCs and their progenies from the developing mouse cortex and forebrain-regionalized human organoids to identify molecular pathways that are commonly regulated between mouse and human cells, depending on individual cell division histories. Thus, we developed a novel tool to characterize the molecular consequences of repeated cell divisions of stem cells that allows an analysis of the cellular principles underlying tissue formation, homeostasis, and repair. HighlightsO_LIiCOUNT reports previous cell divisions in mouse and human cells in vitro C_LIO_LIiCOUNT detects cell division biographies in complex mouse tissues in vivo C_LIO_LIiCOUNT allows for the analysis of human neural stem/progenitor cells in human forebrain organoids C_LIO_LISingle cell RNA-sequencing of iCOUNT cells derived from the mouse developing cortex and human forebrain organoids identifies molecular consequences of previous rounds of cell divisions C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/266171v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@144b085org.highwire.dtl.DTLVardef@a10b2forg.highwire.dtl.DTLVardef@e57053org.highwire.dtl.DTLVardef@1316c11_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗