Biology subjects

Roehrig, A.

Publications and source records attributed to Roehrig, A..

4 recordsLinked to original sources

bioRxiv2026

Routine FFPE sections support clinically compatible single-nucleus transcriptomics across six human cancer types

Tumor cellular composition--including malignant cell states, immune populations, and stromal populations--is increasingly recognized as a determinant of therapeutic response and resistance to anti-cancer agents, yet comprehensive cellular profiling remains largely confined to research settings. Here, we present a clinically compatible sample-to-report workflow for tumor composition profiling from routine formalin-fixed paraffin-embedded (FFPE) clinical specimens. By combining low-input single-nucleus RNA sequencing with foundation model- based automated cell annotation, this workflow enables prospective sample-by-sample analysis without dedicated research material or cohort-based processing. Across 116 clinical specimens representing six cancer types, we generated reproducible measurements of cellular composition and cell-type-specific gene expression, demonstrated high technical reproducibility, and showed concordance with pathological assessment of immune infiltration. The workflow was similarly applicable to archival FFPE material and ultra-low-input biopsy specimens. Together, these findings establish a practical framework for routine single-cell profiling from standard pathology specimens and open the perspective of prospective evaluation of cellular composition as a clinical biomarker in precision oncology.

cancer biology↗

bioRxiv2026

Single-cell trajectories in metastatic urothelial carcinoma reveal tumor-immune reprogramming and macrophage-driven resistance to PD-(L)1 blockade

Immune checkpoint inhibitors (ICI) improved outcomes in metastatic urothelial carcinoma (mUC), but primary and acquired resistance remain poorly understood. We performed single-nuclei RNA sequencing on sequential metastatic biopsies from ICI-treated mUC patients. Tumor cells showed transcriptomic heterogeneity within individual lesions, basal cells being associated with increased immune infiltration and response. Myeloid and lymphoid compartments exhibited features of immune dysfunction in non-responders. Longitudinal analyses revealed convergent adaptive resistance mechanisms, dominated by polarization toward pro-tumoral macrophage states, but also including downregulation of the antigen presentation machinery in tumor cells, increased checkpoint expression with loss of cytotoxicity in T cells. Individual trajectories point to distinct evolutionary routes under ICI pressure. Across pivotal ICI trials, bulk expression of the M2-like macrophage marker HES1 predicted ICI resistance. Our study provides the first single-cell longitudinal atlas of ICI-treated mUC, revealing macrophage reprogramming as a dominant driver of resistance, establishing a framework for individualized immunotherapy strategies.

cancer biology↗

bioRxiv2025

A single-nucleus multimodal framework reveals epigenomic priming of chemoresistant states in ovarian cancer

Non-genetic intratumor heterogeneity (ITH) drives therapeutic failure in cancer, yet its clinical monitoring remains challenging. We develop a multimodal single-nucleus framework that simultaneously profiles transcriptional and histone modification landscapes from frozen biopsies. Applied to longitudinal samples from 16 patients with high-grade serous ovarian cancer (HGSOC), this approach reveals reproducible tumor evolution under chemotherapy: proliferative and interferon-responsive states are lost, while those associated with TNF- and epithelial-mesenchymal transition (EMT) expand. Chromatin profiling shows that these chemoresistant programs are epigenetically primed through H3K4me1 marks before treatment and nominates transcription-factor drivers, including ZBTB7A. Non-genetic baseline tumor composition predicts survival, and fibroblast remodeling parallels malignant adaptation. These findings establish a clinically scalable strategy for mapping functional ITH and identify epigenomic priming as a determinant of therapeutic failure. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=181 HEIGHT=200 SRC="FIGDIR/small/692102v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@432524org.highwire.dtl.DTLVardef@3b7843org.highwire.dtl.DTLVardef@54a2eforg.highwire.dtl.DTLVardef@95273d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

ultraID: a compact and efficient enzyme for proximity-dependent biotinylation in living cells

Proximity-dependent biotinylation (PDB) combined with mass spectrometry analysis has established itself as a key technology to study protein-protein interactions in living cells. A widespread approach, BioID, uses an abortive variant of the E. coli BirA biotin protein ligase, a quite bulky enzyme with slow labeling kinetics. To improve PDB versatility and speed, various enzymes have been developed by different approaches. Here we present a novel small-size engineered enzyme: ultraID. We show its practical use to probe the interactome of Argonaute-2 after a 10 min labeling pulse and expression at physiological levels. Moreover, using ultraID, we provide a membrane-associated interactome of coatomer, the coat protein complex of COPI vesicles. To date, ultraID is the smallest and most efficient biotin ligase available for PDB and offers the possibility of investigating interactomes at a high temporal resolution.

biochemistry↗