Biology subjects

Horst, J.

Publications and source records attributed to Horst, J..

4 recordsLinked to original sources

bioRxiv2025

Detection and monitoring of translocation renal cell carcinoma via plasma cell-free epigenomic profiling

TFE3 translocation renal cell carcinoma (tRCC), an aggressive kidney cancer driven by TFE3 gene fusions, is frequently misdiagnosed owing to morphologic overlap with other kidney cancer subtypes. Conventional liquid biopsy assays that detect tumor DNA via somatic mutations or copy number alterations are unsuitable for tRCC, since it often lacks recurrent genetic alterations and because fusion breakpoints are highly variable between patients. We reasoned that epigenomic profiling could more effectively detect tRCC, because the driver fusion constitutes an oncogenic transcription factor that alters gene regulation. By defining a TFE3-driven epigenomic signature in tRCC cell lines and detecting it in patient plasma using chromatin immunoprecipitation and sequencing, we distinguished tRCC from clear cell RCC (AUC=0.87) and healthy controls (AUC=0.91) at low tumor fractions (<1%). This work establishes a framework for non-invasive epigenomic detection, diagnosis and monitoring of tRCC, with implications for other mutationally quiet, fusion-driven cancers. SIGNIFICANCETranslocation renal cell carcinoma (tRCC) is an aggressive fusion-driven subtype of kidney cancer that is frequently misdiagnosed due to morphologic overlap with other kidney cancer subtypes. Conventional liquid biopsy assays targeting DNA alterations are suboptimal for use in tRCC due to its paucity of genomic changes. We demonstrate the utility of cell-free chromatin profiling to noninvasively detect and monitor tRCC with high accuracy, a method that could have applicability to other genomically quiet cancers.

genomics↗

bioRxiv2025

Fusion-driven oncogenic programs shape the immune landscape in translocation renal cell carcinoma

Renal cell carcinomas comprise multiple molecularly distinct cancers but most are treated empirically with therapies designed for clear cell RCC (ccRCC), the most common subtype, due to incomplete understanding of subtype-specific biology. We analyzed single-cell transcriptomes and chromatin accessibility profiles from translocation renal cell carcinoma (tRCC), an aggressive RCC defined by oncogenic TFE3 gene fusions. Unexpectedly, despite arising from a proximal tubule cell of origin similar to ccRCC, tRCCs display markedly distinct oncogenic programs and an immunosuppressive tumor microenvironment. tRCCs exhibit six conserved tumor meta-programs, including epithelial-mesenchymal transition and proximal tubule identity programs whose balance is regulated by TFE3 fusion activity. The fusion-driven EMT program drives a suppressive TME marked by progenitor-exhausted CD8+ T cells, anti-inflammatory SPP1+ macrophages, and matrix-associated fibroblasts (mCAFs). Our findings highlight unique TFE3 fusion-driven biology in tRCC, explaining its reduced immunotherapy responsiveness relative to ccRCC, and suggesting strategies for targeting fusion-driven oncogenic programs and TME reprogramming.

genomics↗

bioRxiv2024

Single-cell epigenetic profiling reveals an interferon response-high program associated with BAP1 deficiency in kidney cancer

Renal cell carcinoma (RCC) is characterized by recurrent somatic mutations in epigenetic regulators, which stratify patients into clinically significant subgroups with distinct prognoses and treatment responses. However, the cell type-specific epigenetic landscape of RCC--broadly and in the context of these mutations--is incompletely understood. To investigate these open questions, we integrated single nucleus ATAC sequencing data from RCC tumors across four independent cohorts. In clear cell RCC tumors, we identified four shared malignant epigenetic programs related to angiogenesis, proximal tubule-like features, interferon (IFN) signaling, and one that lacked distinct genomic regions with increased accessibility. Among the mutated epigenetic regulators, BAP1 mutation exhibited the most significant impact on chromatin accessibility in tumor cells, and the associated epigenetic changes were linked to IFN response. We identify multiple potential sources of elevated IFN signaling in these lesions, such as increased immune infiltration and increased accessibility and expression of an IFN-associated ERV, ERV3-16A3_LTR. We find that the expression of ERV3-16A3_LTR may itself be a negative prognostic biomarker in ccRCC. Our findings highlight the convergence of malignant epigenetic programs across ccRCC tumors and suggest that BAP1 loss, potentially through ERV3-16A3_LTR dysregulation, is associated with an IFN response-high epigenetic program.

cancer biology↗

bioRxiv2017

MinorityReport, software for generalized analysis of causal genetic variants

BackgroundThe widespread availability of next generation genome sequencing technologies has enabled a wide range of variant detection applications, especially in cancer and inborn genetic disorders. For model systems and microorganisms, the same technology may be used to discover the causative mutations for any phenotype, including those generated in response to chemical perturbation. In the case of pathogenic organisms, these approaches have allowed the determination of drug targets by means of resistance selection followed by genome sequencing.\n\nResultsHere, we present open source software written in python, MinorityReport, to facilitate the comparison of any two sets of genome alignments for the purpose of rapidly identifying the spectrum of nonsynonymous changes, insertions or deletions, and copy number variations in a presumed mutant relative to its parent. Specifically, MinorityReport relates mapped sequence reads in SAM format output from any alignment tool for both the mutant and parent genome, relative to a reference genome, and produces the set of variants that distinguishes the mutant from the parent, all presented in an intuitive, straightforward report format. MinorityReport features tunable parameters for evaluating evidence and a scoring system that prioritizes reported variants based on relative proportions of read counts supporting the variant in the mutant versus parent data sets. We demonstrate the utility of MinorityReport using publicly available data sets that we previously published to find the determinants of resistance for novel anti-malarial drugs.\n\nConclusionsMinorityReport is readily available (github: xxxxxxx) to identify the genetic mechanisms of drug resistance in plasmodium, genotype-phenotype relationships in human diads, or genomic variations between any two related organisms.

bioinformatics↗