Biology subjects

Heilig, C. E.

Publications and source records attributed to Heilig, C. E..

4 recordsLinked to original sources

bioRxiv2026

Prospective pan-cancer phosphoproteomics at clinical scale extends therapeutic options in precision oncology

Genomics-guided precision oncology has improved survival in cancer entities with actionable mutations but cannot capture oncogenic signaling that manifests at the protein level. Here, we report a prospective, real-world pan-cancer study profiling proteomes and phosphoproteomes of 1,998 tumor samples from adults and children with rare or advanced cancers enrolled in the German precision oncology programs DKFZ/NCT/DKTK MASTER, CATCH and INFORM and their molecular tumor boards (MTBs). We developed tumor proteome activity status (TOPAS) scores for 46 clinically relevant kinases, an immune activity score capturing antigen presentation and T-cell activation and identified therapeutically targetable cell-surface proteins for 94% of patients. These readouts enhance MTB recommendations by exposing actionable non-genomic kinase activity, refining interpretation of oncogenic genome alterations, and highlighting cell-surface treatment options. Three proof-of-concept analyses indicate clinical utility including kinase activity-stratified pazopanib response in sarcoma, immune activity score-tracked checkpoint-inhibitor outcomes pan-cancer, and a phosphoproteomic biomarker distinguishing EGFR-inhibitor response in chordoma.

cancer biology↗

bioRxiv2026

Systematic functional drug testing in patient-derived models reveals ex vivo sensitivities associated with clinical outcome in rare solid tumors

Rare cancers are individually uncommon but collectively represent a substantial share of cancer burden, with limited systemic treatment options for many entities. Molecular profiling identifies targetable alterations, but actionable findings are limited and responses can vary despite a matched target. This motivates complementary approaches that directly assess tumor drug response. Here, we establish a biopsy-compatible ex vivo drug sensitivity testing platform optimized for low input and reproducibility. Patient-derived material was tested either directly or following ex vivo expansion. Functional profiling was performed within clinically relevant timelines across models from 126 patients with rare advanced solid tumors. Drug responses were consistent between model types. In most samples, we identified at least one potentially active compound, supporting feasibility at biopsy-scale. High in vitro sensitivity was associated with clinical benefit and progression-free survival. These findings support functional drug sensitivity testing as a complementary component in precision oncology for adults with rare cancers. Statement of SignificanceThis study presents a biopsy-compatible drug sensitivity testing platform for phenotype-based therapy stratification in rare cancers. It identifies actionable ex vivo drug responses and shows associations with clinical outcome in patients treated with screened therapies. These findings support functional testing as a complementary additional layer of stratification for therapeutic prioritization.

cancer biology↗

bioRxiv2023

ZygosityPredictor

SummaryZygosityPredictor provides functionality to evaluate how many copies of a gene are affected by mutations in next generation sequencing data. In cancer samples, the tool processes both somatic and germline mutations. In particular, ZygosityPredictor computes the number of affected copies for single nucleotide variants and small insertions and deletions (Indels). In addition, the tool integrates information at gene level via phasing of several variants and subsequent logic to derive how strongly a gene is affected by mutations and provides a measure of confidence. This information is of particular interest in precision oncology, e.g. when assessing whether unmutated copies of tumor-suppressor genes remain. Availability and implementationZygosityPredictor was implemented as an R-package and is available via Bioconductor at https://bioconductor.org/packages/ZygosityPredictor. Detailed documentation is provided in the vignette including application to an example genome.

bioinformatics↗

bioRxiv2023

Multidimensional Characterization of Soft-Tissue Sarcomas with FUS-TFCP2 or EWSR1-TFCP2 Fusions

Linking clinical multi-omics analyses with mechanistic studies provides opportunities to explore the pathogenesis of rare cancers. We leveraged two precision oncology programs to investigate rhabdomyosarcoma with FUS/EWSR1-TFCP2 fusions, an orphan malignancy without effective systemic therapies. All tumors exhibited outlier expression of the ALK receptor tyrosine kinase, which was partly accompanied by intragenic deletions and aberrant splicing, resulting in truncated ALK variants that were oncogenic and sensitive to ALK inhibitors. Additional recurrent alterations included CKDN2A/MTAP co-deletions, providing a rationale for therapies targeting CDK4/6 and PRMT5. Functional studies showed that FUS-TFCP2 blocks myogenic differentiation and induces transcription of ALK and a truncated form of TERT through binding outside their regular promoters. Furthermore, FUS-TFCP2 inhibited DNA double-strand break repair. Consistent with this, and unlike other fusion-driven sarcomas, TFCP2-rearranged tumors exhibited marked genomic instability and signs of defective homologous recombination. DNA methylation profiling indicated a close relationship with undifferentiated sarcomas rather than rhabdomyosarcoma. Finally, we identified patients in whom overt disease was preceded by benign lesions carrying TFCP2 fusions, providing insight into stepwise sarcomagenesis and suggesting new approaches to early detection and interception. SIGNIFICANCEMost rare cancers are poorly understood, and pathogenesis-directed therapies are often lacking, resulting in poor patient outcomes. This study illustrates the potential of linking precision oncology programs with preclinical research to gain insight into the classification, pathogenesis, and therapeutic vulnerabilities of rare cancers that could improve the clinical management of such diseases.

cancer biology↗