Biology subjects

Schlosser, P.

Publications and source records attributed to Schlosser, P..

7 recordsLinked to original sources

bioRxiv2026

Loss of the Y chromosome is transcriptionally silent in clear cell renal cell carcinoma and across cancer entities

Tumors in men often lose the Y chromosome. In some tumor types, this is predictive of poor outcome. Given the male predominance and high LOY frequency in clear cell renal cell carcinoma (ccRCC), we asked whether LOY might impact the transcriptome of ccRCC. We determined somatic Y chromosome status and performed differential expression analysis on tumor RNA-sequencing samples of two human ccRCC cohorts (TCGA-KIRC, CPTAC-ccRCC) and in an autochthonous murine ccRCC model with renal epithelium-specific deletion of Vhl, Trp53 and Rb1. We additionally derived five isogenic Y-deficient and five Y chromosome-retaining clones of the human ccRCC cell line 786-O. Across all three settings, transcriptional changes were largely restricted to the expected gene dosage effects of male-specific Y (MSY) and pseudoautosomal region (PAR) genes, without large effects on autosomal genes. At the pathway level, we identified a modest but reproducible response in the human cohorts, converging on cell cycle, ribosomal biogenesis and DNA repair genes. A pan-cancer meta-analysis across TCGA entities recovered the same pattern, with no autosomal gene showing a large consistent effect. In some entities, but not in ccRCC, cancer/testis antigen expression was higher in LOY tumors. We conclude that, apart from direct gene dosage, modest pathway-level shifts and altered silencing of cancer/testis antigens, LOY is transcriptionally silent in adult humans and mice. Y-chromosomal genes are therefore unlikely to act as transcriptional drivers of ccRCC and other cancer entities.

cancer biology↗

bioRxiv2026

Sexually dimorphic effects of mutations in ccRCC driver genes in renal proximal tubule cells

Clear cell renal cell carcinoma (ccRCC) arises more frequently in men than in women, but it remains unclear why this is the case. Mouse models that mimic the truncal mutation of the two most commonly affected tumor suppressor genes in human ccRCC revealed that the transcriptional effects of Vhl or Vhl/Pbrm1 mutation in male and female proximal tubule cells only partially overlap. Cellular responses to mutations in these genes were also sex-specific. Vhl and Vhl/Pbrm1 mutation in females, but only Vhl/Pbrm1 mutation in males, induced the accumulation of PLIN2-coated lipid droplets. The accumulation of optically-clear lipid droplets, reflecting the hallmark clear-cell histological feature of ccRCC, only arose in Vhl/Pbrm1 mutant male mice. Consistent with lipotoxic tubular damage, markers of tubular repair and ongoing epithelial cell proliferation correlated with the lipid accumulation phenotypes. Vhl/Pbrm1 mutation caused stronger clonal expansion than Vhl mutation in males, but not in females. These findings suggest that there are likely to be sexual dimorphisms at the very earliest stages of ccRCC evolution that result from the interplay of intrinsic and mutation-induced transcriptional differences between male and female proximal tubule cells.

cancer biology↗

bioRxiv2026

Transcriptome-based cell type assignment for kidney cell culture models

BackgroundKidney cell lines are widely used to model kidney physiology and disease; however, their gene expression profiles may differ from primary cells due to immortalization, culture conditions, or experimental treatments. Determining whether a cell line resembles its native cell type is critical for interpreting in vitro findings. We developed a transcriptome-based approach that matches bulk RNA-seq data from kidney cell lines, primary cells, or tissues to reference cell types derived from single-cell RNA-seq (scRNA-seq) datasets. MethodsReference transcriptomic profiles were generated from two human and two murine kidney scRNA-seq datasets by pseudobulk aggregation. Bulk RNA-seq data from microdissected kidney tissue, non-kidney negative controls, and kidney cell lines were matched to these references using three statistical similarity measures (Spearman correlation, Euclidean distance, Poisson distance) and three machine learning classifiers (Random Forest, XGBoost, TabPFN). Each was assessed with global gene expression, curated kidney marker gene lists, and the most variable genes. Matching accuracy was evaluated through a three-step validation strategy: within-dataset matching, cross-reference comparison, and validation against primary kidney tissue and negative controls. ResultsGene expression rank-based Spearman correlation and TabPFN, a foundation model for tabular data, emerged as the most accurate and specific approaches, particularly with curated kidney marker gene lists. Both methods correctly identified microdissected kidney tubule segments and were robust against non-kidney negative controls. Applied to commonly used kidney cell lines, OK cells retained proximal tubule identity, particularly under shear stress, while other proximal tubule lines (HK-2, HKC-8, HKC-11) showed inconsistent matching. Collecting duct-derived mIMCD-3 maintained stable similarity across passages, culture conditions, and genetic modifications. ConclusionWe provide two complementary implementations: CellMatchR, an accessible web-based tool using Spearman correlation for routine use, and comprehensive scripts for TabPFN-based matching (link will be added after peer reviewed publication). Together, these resources enable researchers to make informed decisions about kidney cell culture model selection, interpretation, and stability. Translational StatementKidney cell lines are fundamental tools in nephrology research, yet their transcriptomic similarity to native cell types is rarely validated systematically. We demonstrate that combining bulk RNA-seq data with single-cell reference datasets enables robust assessment of cell line identity using gene expression-rank-based correlation and machine learning approaches. By providing a comprehensive evaluation of matching methods, curated kidney marker gene lists, and reference datasets, our study serves as both a practical resource and a methodological framework for the kidney research community, facilitating informed selection of cell culture models, quality control of experimental conditions, developing new experimental cell culture models, and more reliable translation of in vitro findings to kidney physiology and disease.

bioinformatics↗

bioRxiv2024

SLC17 transporters mediate renal excretion of Lac-Phe in mice and humans

N-lactoyl-phenylalanine (Lac-Phe) is a lactate-derived metabolite that suppresses food intake and body weight. Little is known about the mechanisms that mediate Lac-Phe transport across cell membranes. Here we identify SLC17A1 and SLC17A3, two kidney-restricted plasma membrane-localized solute carriers, as physiologic urine Lac-Phe transporters. In cell culture, SLC17A1/3 exhibit high Lac-Phe efflux activity. In humans, levels of Lac-Phe in urine exhibit a strong genetic association with the SLC17A1-4 locus. Urine Lac-Phe levels are also increased following a Wingate sprint test. In mice, genetic ablation of either SLC17A1 or SLC17A3 reduces urine Lac-Phe levels. Despite these differences, both knockout strains have normal blood Lac-Phe and body weights, demonstrating that urine and plasma Lac-Phe pools are functionally and biochemically de-coupled. Together, these data establish SLC17 family members as the physiologic urine transporters for Lac-Phe and uncover a biochemical pathway for the renal excretion of this signaling metabolite.

biochemistry↗

bioRxiv2024

metaGWASmanager: A toolbox for an automated workflow from phenotypes to meta-analysis in GWAS consortia

SummaryThis paper introduces the metaGWASmanager, which streamlines genome-wide association studies within large-scale meta-analysis consortia. It is a toolbox for both the central consortium analysis group and participating studies to generate homogeneous phenotypes, minimize variance from inconsistent methodologies, ensure high-quality association results, and implement time-efficient quality control workflows. The toolbox features a plug-in-based approach for customization. ResultsThe metaGWASmanager toolbox has been successfully deployed in both the CKDGen and MetalGWAS Initiative consortia across hundreds of participating studies, demonstrating its effectiveness in improving the efficiency of GWAS analysis by automating routine tasks and ensuring the value and reliability of association results, thus, ultimately promoting scientific discovery. AvailabilityGitHub: https://github.com/genepi-freiburg/metaGWASmanager Contactpschlos3@jhu.edu, matthias.wuttke@uniklinik-freiburg.de

genetics↗

bioRxiv2021

Large Bi-Ethnic Study of Plasma Proteome Leads to Comprehensive Mapping of cis-pQTL and Models for Proteome-wide Association Studies

Improved understanding of genetic regulation of proteome can facilitate the identification of causal mechanisms for complex traits. We analyzed data on 4,657 plasma proteins from 7,213 European American (EA) and 1,871 African American (AA) individuals from the ARIC study, and further replicated findings on 467 AA individuals from the AASK study. Here we identified 2,004 proteins in EA and 1,618 in AA, with majority overlapping, which showed associations with common variants in cis-regions. Availability of AA samples led to smaller credible sets and significant number of population-specific cis-pQTLs. Elastic-net produced powerful models for protein prediction in both populations. An application of proteome-wide association studies (PWAS) to serum urate and gout, implicated several proteins, including IL1RN, revealing the promise of the drug anakinra to treat acute gout flares. Our study demonstrates the value of large and diverse ancestry study for genetic mechanisms of molecular phenotypes and their relationship with complex traits.

genetics↗

bioRxiv2020

CRISPR/Cas9 targeting Ttc30a mimics ciliary chondrodysplasia with polycystic kidney disease.

Skeletal ciliopathies (e.g. Jeune syndrome, short rib polydactyly syndrome, Sensenbrenner syndrome) are frequently associated with cystic kidney disease and other organ manifestations, but a common molecular mechanism has remained elusive. We established two models for skeletal ciliopathies (ift80 and ift172) in Xenopus tropicalis, which exhibited severe limb deformities, polydactyly, cystic kidneys, and ciliogenesis defects, closely matching the phenotype of affected patients. Employing data-mining and an in silico screen we identified candidate genes with similar molecular properties to genetically validated skeletal ciliopathy genes. Among four genes experimentally validated, CRISPR/Cas9 targeting of ttc30a replicated all aspects of the phenotypes observed in the models of genetically confirmed disease genes, including ciliary defects, limb deformations and cystic kidney disease. Our findings establish three new models for skeletal ciliopathies (ift80, ift172, ttc30a) and identify TTC30A/B as an essential node in the network of ciliary chondrodysplasia and nephronophthisis-like disease proteins implicating post-translational tubulin modifications in its pathogenesis.

developmental biology↗