Biology subjects

Brendler-Spaeth, T.

Publications and source records attributed to Brendler-Spaeth, T..

3 recordsLinked to original sources

bioRxiv2026

Novel Methylation Markers in a Prostate Cancer Cohort are Associated with Disease Development and Relapse

Prostate cancer remains one of the most common cancers among men globally. While significant strides have been made in diagnosis and treatment, understanding the complex genetic and epigenetic underpinnings of the disease remains crucial for guiding intervention and developing more personalized and effective therapies. The importance of DNA methylation in prostate cancer has been known for some time, but important facets of the modulation of the epigenome during carcinogenesis remain obscure, partly because the bulk of cancer methylation data have been produced using microarray technologies. Here we utilise the TruSeq methyl capture method (EPICseq) to profile the, previously defined, UK Prostate ICGC cohort of well-annotated primary prostate cancers. To this we add methylation sequencing of benign tissue from the same men. These data allow us to identify differentially methylated regions distinguishing cancerous and non-cancerous prostate tissue, while identifying numerous genes whose methylation profiles can perform that task as well as distinguishing between classes of prostate cancer. We describe a describe a methylation-based control mechanism for prostate-cancer-associated SNPs, and show that this seems a likely mechanism of action for a SNP near the MMP7 gene. We describe three novel molecular signatures that arise from different aspects of the biology of prostate cancer revealed by sequencing. Each is shown to be an independent classifier of cancers into groups with different expected times to relapse. These consist of patterns in driver gene methylation, strand-specific methylation, and signal arising in mitochondrial reads. We show that these signatures, combined with existing molecular tools, provide a powerful predictor of time to recurrence. By substantially enhancing understanding of prostate cancer risk, detection, and prognosis, we pave the way for the development of clinical practices that will benefit patients and improve outcomes.

cancer biology↗

bioRxiv2026

SELECT-seq allows Pre-Sequencing Enrichment of SNP Edits in One-Pot Single-Cell Whole-Transcriptome Sequencing

Advances in high-throughput sequencing have associated millions of putative genetic variants with disease. However, scalable experimental methods to establish causal relationships between genetic variants and downstream transcriptional outcomes remain a major challenge. Single-cell methods that integrate genotyping with transcriptomic profiling provide a way to address this, but do not enable pre-sequencing enrichment of correctly edited cells, limiting scale. We present SELECT-seq (SNP Enrichment Leveraging Cas12a Targeting), a rapid method that allows SNP-specific PCR amplification and Cas12a-mediated fluorescence detection simultaneously with whole-transcriptome amplification. This one-pot workflow enables identification and enrichment of SNP-bearing single cells, making a rapid and scalable methodology for analysis of genotype-phenotype linkage avoiding laborious single cell cloning steps. As a proof of principle we show that SELECT-seq distinguishes U-2 OS and T-47D cell lines based on a PIK3CA (NM_006218.4:c.3463A>G) mutation while preserving transcriptome integrity. It physically enriches a rare NRF2 T80K (NM_006164.5:c.390C>A) mutant cells (6.7%) from a prime-edited pool, achieving 86% genotype accuracy, and shows 87.5% directional concordance in the transcriptomic effects compared with a clonal NRF2 T80K cell line. SELECT-seq thus provides a rapid, scalable and widely accessible approach for mapping genotype-phenotype relationships at single-cell resolution.

molecular biology↗

bioRxiv2026

Saturation-seq integrates single-cell saturation genome editing and RNA-seq to quantify NFE2L2 (NRF2) variant effects

Interpreting the functional consequences of variants remains one of the central unsolved problems in genomics and clinical genetics. Compounding this, most existing approaches rely on reductive, one-dimensional proxies such as cell growth to score variant effects, which can be a poor substitute for the rich, multidimensional phenotyping that is ultimately needed to understand how variants alter biology. This is especially true for variants known to act through gain-of-function/neomorphic mechanisms. We developed Saturation-seq, a high-throughput platform that combines saturation genome editing with single-cell DNA and RNA profiling to systematically map variant effects. Using CRISPR-based editing in a barcoded haploid cell line, we install hundreds of variants directly into endogenous genomic loci, testing them in multiplex and preserving the native coding and regulatory context. Single-cell amplicon and transcriptome sequencing enables direct linkage of each genomic edit to its transcriptional impact. We apply Saturation-seq to comprehensively characterize 230 variants in the recurrently mutated N-terminal region of NFE2L2 (NRF2), a master regulator of oxidative stress and an oncogene mutated in lung cancer. We define variant function with disruption scores computed from misregulation of known NRF2 targets in single-cell transcriptomes; scores separate pathogenic/benign truthset variants with >90% accuracy and enabled interpretation of TCGA and TRACERx patient tumor data, as well as a rare NFE2L2 germline variant linked to a developmental syndrome. Thus, we establish a broadly applicable high-resolution single-cell variant-to-function platform with a rich phenotypic readout.

genomics↗