Investigator
University Hospital Regensburg
Supplementary biomarker testing in molecular tumor boards increases actionable therapy recommendations: a prospective real-world study of 658 patients
Abstract Background Molecular tumor boards (MTBs) are essential for selecting therapies for patients with rare and advanced cancers. We hypothesized that integrating biomarkers beyond targeted DNA/RNA next-generation sequencing (NGS) could increase actionable findings. Human epidermal growth factor receptor 2 (HER2)-low status has emerged as a critical biomarker in breast cancer, with potential relevance across other tumor types. Homologous recombination deficiency (HRD) is pivotal for the application of Poly(ADP-Ribose)-Polymerase (PARP) inhibitors in ovarian and breast cancer, although its role in other malignancies remains unclear. Antibody–drug conjugates (ADCs) are expanding precision oncology, with promising biomarkers like Trop-2, Nectin-4, and folate receptor alpha (FRα) showing potential across multiple tumor entities. Methods Tumors were analyzed using the TSO500® panel, enabling tumor mutational burden (TMB) readout. HER2 status was assessed via immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH), alongside antibody–drug conjugate (ADC) IHC, microsatellite instability (MSI) polymerase chain reaction (PCR), mismatch repair (MMR) IHC, programmed death-ligand 1 (PD-L1) IHC, and HRD analysis. Cases were discussed weekly, and outcomes were systematically tracked. Data analysis evaluated the benefit of additional biomarker assessments. Results Among 658 patients, 329 received therapy recommendations, 182 based on supplementary biomarker analyses. One hundred recommendations were implemented, with 37% attributed to supplementary diagnostics. Among 64 response-evaluable patients, the clinical benefit rate (complete response + partial response + stable disease) was 45.3%. HER2-low status notably expanded targeted therapy options across tumor types, with similar implementation rates for HER2-low and HER2-amplified tumors. HRD analysis refined stratification in tumors with mutations in homologous recombination repair (HRR) genes beyond BRCA1/2, including PALB2, ATM, and CHEK2. ADC IHC supported 20 recommendations and two therapy implementations. Conclusions The integration of additional biomarker assessments into MTB workflows enhances precision oncology by expanding the pool of patients eligible for targeted therapies.
Development and Validation of a Novel 11-Gene Prognostic Model for Serous Ovarian Carcinomas Based on Lipid Metabolism Expression Profile
(1) Background: Biomarkers might play a significant role in predicting the clinical outcomes of patients with ovarian cancer. By analyzing lipid metabolism genes, future perspectives may be uncovered; (2) Methods: RNA-seq data for serous ovarian cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The non-negative matrix factorization package in programming language R was used to classify molecular subtypes of lipid metabolism genes and the limma package in R was performed for functional enrichment analysis. Through lasso regression, we constructed a multi-gene prognosis model; (3) Results: Two molecular subtypes were obtained and an 11-gene signature was constructed (PI3, RGS, ADORA3, CH25H, CCDC80, PTGER3, MATK, KLRB1, CCL19, CXCL9 and CXCL10). Our prognostic model shows a good independent prognostic ability in ovarian cancer. In a nomogram, the predictive efficiency was notably superior to that of traditional clinical features. Related to known models in ovarian cancer with a comparable amount of genes, ours has the highest concordance index; (4) Conclusions: We propose an 11-gene signature prognosis prediction model based on lipid metabolism genes in serous ovarian cancer.
Potential of platinum-resensitization by Wnt signaling modulators as treatment approach for epithelial ovarian cancer
Abstract Purpose Canonical Wnt/ β-catenin pathway is one mechanism being activated in platinum-resistant epithelial ovarian cancer (EOC). Detecting potential targets for Wnt pathway modulation as a putative future therapeutic approach was the aim of this study. Methods Biological effects of different Wnt modulators (SB216763, XAV939 and triptolide) on the EOC cell lines A2780 and its platinum-resistant clone A2780cis were investigated via multiple functional tests. Immunohistochemistry (IHC) was carried out to compare the expression levels of Wnt marker proteins (β-catenin, snail/ slug, E-cadherin) in patient specimens and to correlate them with lifetime data. Results We could show that activated Wnt signaling of the platinum-resistant EOC cell line A2780cis can be reversed by Wnt manipulators through SB216763 or XAV939. All Wnt manipulators tested consecutively decreased cell proliferation and cell viability. Apoptosis of A2780 and A2780cis was enhanced by triptolide in a dose-dependent manner, whereas cell migration was inhibited by SB216763 and triptolide. IHC analyses elucidated significantly different expression patterns for Wnt markers in the serous subtype. Herein, higher plasmatic snail/ slug expression is associated with improved progression-free (PFS) and overall survival (OS). Conclusion According to the described effects on EOC biology, all three Wnt manipulators seem to have the potential to augment the impact of a platinum-based chemotherapy in EOC. This is promising as a dominance of this pathway was confirmed in serous histology.
Trace Amine-Associated Receptor 1 (TAAR1) Is a Positive Prognosticator for Epithelial Ovarian Cancer
Trace amine-associated receptor 1 (TAAR1) is a Gαs- protein coupled receptor that plays an important role in the regulation of the immune system and neurotransmission in the CNS. In ovarian cancer cell lines, stimulation of TAAR1 via 3-iodothyronamine (T1AM) reduces cell viability and induces cell death and DNA damage. Aim of this study was to evaluate the prognostic value of TAAR1 on overall survival of ovarian carcinoma patients and the correlation of TAAR1 expression with clinical parameters. Ovarian cancer tissue of n = 156 patients who were diagnosed with epithelial ovarian cancer (serous, n = 110 (high-grade, n = 80; low-grade, n = 24; unknown, n = 6); clear cell, n = 12; endometrioid, n = 21; mucinous, n = 13), and who underwent surgery at the Department of Obstetrics and Gynecology, University Hospital of the Ludwig-Maximilians University Munich, Germany between 1990 and 2002, were analyzed. The tissue was stained immunohistochemically with anti-TAAR1 and evaluated with the semiquantitative immunoreactive score (IRS). TAAR1 expression was correlated with grading, FIGO and TNM-classification, and analyzed via the Spearman’s rank correlation coefficient. Further statistical analysis was obtained using nonparametric Kruskal-Wallis rank-sum test and Mann-Whitney-U-test. This study shows that high TAAR1 expression is a positive prognosticator for overall survival in ovarian cancer patients and is significantly enhanced in low-grade serous carcinomas compared to high-grade serous carcinomas. The influence of TAAR1 as a positive prognosticator on overall survival indicates a potential prognostic relevance of signal transduction of thyroid hormone derivatives in epithelial ovarian cancer. Further studies are required to evaluate TAAR1 and its role in the development of ovarian cancer.
Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients
Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.
