A systematic comparison of pan-Trk immunohistochemistry assays among multiple cancer types

AIMS NTRK rearranged tumours are rare but can be successfully treated using anti-TRK-targeted therapies, making NTRK testing important for treatment choices in patients with advanced cancers. Pan-Trk immunohistochemistry (IHC) has become a valuable and affordable screening tool in many laboratories. Unfortunately, the choice of antibodies and IHC protocols to investigate biomarkers is not standardised. In this study, we compared the performance of four pan-Trk IHC methods, using three different clones, primarily in NTRK fusion-positive tumours. METHODS AND RESULTS We studied the performance of four pan-Trk IHC methods using three different clones: EPR17341 (Abcam and Ventana), EP1058Y (Abcam) and A7H6R (Cell Signaling) in 22 molecularly confirmed NTRK rearranged tumours. Additionally, selected NTRK fusion-negative tumours were further included: NTRK mutated (n = 8) and amplified (n = 15) tumours as well as NTRK fusion-negative tumours driven by other gene fusions, such as ALK, ROS1 and BCOR (n = 20), as well as salivary gland tumours (n = 16). Inter-rater agreement of three pathologists was additionally calculated, including H-score. With clone EPR17341 (Abcam in-house and ready-to-use Ventana protocol), all molecularly confirmed NTRK1-3 rearranged tumours were positively detected by immunohistochemistry, while the other clones missed NTRK2-3 rearranged tumours. For the fusion-negative cohort we found the best performance (least false-positive cases) using the clone A7H6R (Cell Signalling). CONCLUSION Given the therapeutic importance, testing for NTRK rearrangements in daily practice has become necessary and, despite IHC being a fast and affordable tool, using it in routine diagnostics is complicated and requires a high level of expertise

Conservative surgical treatment with fertility preservation in a young adult with NTRK rearranged spindle cell neoplasm of the uterine cervix

In depth molecular studies are constantly expanding our understanding and refining the classification of gynecological neoplasms. NTRK rearranged spindle cell neoplasms of the lower genital tract are an emerging entity, of particular interest due to possible targeted treatment with selective kinase inhibitors. Nonetheless, surgery remains the initial treatment of choice. We present the case of a 24-year-old patient suffering from a NTRK rearranged spindle cell neoplasm of the uterine cervix which was treated with a fertility preserving conservative surgical approach

DDoS: A Graph Neural Network based Drug Synergy Prediction Algorithm

Background: Drug synergy occurs when the combined effect of two drugs is greater than the sum of the individual drugs' effect. While cell line data measuring the effect of single drugs are readily available, there is relatively less comparable data on drug synergy given the vast amount of possible drug combinations. Thus, there is interest to use computational approaches to predict drug synergy for untested pairs of drugs. Methods: We introduce a Graph Neural Network (GNN) based model for drug synergy prediction, which utilizes drug chemical structures and cell line gene expression data. We use information from the largest drug combination database available (DrugComb), combining drug synergy scores in order to construct high confidence benchmark datasets. Results: Our proposed solution for drug synergy predictions offers a number of benefits: 1) It utilizes a combination of 34 distinct drug synergy datasets to learn on a wide variety of drugs and cell lines representations. 2) It is trained on constructed high confidence benchmark datasets. 3) It learns task-specific drug representations, instead of relying on generalized and pre-computed chemical drug features. 4) It achieves similar or better prediction performance (AUPR scores ranging from 0.777 to 0.964) compared to state-of-the-art baseline models when tested on various benchmark datasets. Conclusions: We demonstrate that a GNN based model can provide state-of-the-art drug synergy predictions by learning task-specific representations of drugs

Establishment and functional testing of a novel ex vivo extraskeletal osteosarcoma cell model (USZ20-ESOS1)

Extraskeletal osteosarcoma (ESOS) is a rare malignant mesenchymal tumor that originates in the soft tissue. ESOS accounts for less than 1% of all soft tissue sarcomas and exhibits an aggressive behavior with a high propensity for local recurrence and distant metastasis. Despite advances in treatment, the prognosis for ESOS remains poor, with a five-year survival rate of less than 50% and 27% for metastatic patients. Ex vivo models derived from patient samples are critical tools for studying rare diseases with poor prognoses, such as ESOS, and identifying potential new treatment strategies. In this work, we established a novel ESOS ex vivo sarco-sphere model from a metastatic lesion to the dermis for research and functional testing purposes. The ex vivo cell model accurately recapitulated the native tumor, as evidenced by histomorphology and molecular profiles. Through a functional screening approach, we were able to identify novel individual anti-cancer drug sensitivities for different drugs such as romidepsin, miverbresib and to multiple kinase inhibitors. Overall, our new ESOS ex vivo cell model represents a valuable tool for investigating disease mechanisms and answering basic and translational research questions

Establishment, characterization and functional testing of two novel ex vivo extraskeletal myxoid chondrosarcoma (EMC) cell models

Extraskeletal myxoid chondrosarcoma (EMC) is a malignant mesenchymal neoplasm of uncertain differentiation as classified by the WHO Classification of Tumours 2020. Although often associated with pronlonged survival, EMC has high rates of distant recurrences and disease-associated death. EMCs are translocation sarcomas and harbor in > 90% of the cases an NR4A3 rearrangement. The molecular consequences of the NR4A3 gene fusions are not yet fully elucidated as well-characterized ex vivo cell models for EMC are lacking. Patient-derived ex vivo models are important and essential tools for investigating disease mechanisms associated with diseases that are rare, that exhibit poor prognosis and for the identification of potential novel treatment options. We established two novel EMC ex vivo models (USZ20-EMC1 and USZ22-EMC2) for functional testing and research purposes. USZ20-EMC1 and USZ22-EMC2 were established and maintained as sarco-sphere cell models for several months in culture. The cells were molecularly characterized using DNA sequencing and methylation profiling. Both cell models represent their native tumor tissue as confirmed by histomorphology and their molecular profiles, suggesting that native tumor cell function can be recapitulated in the ex vivo models. Using a functional screening approach, novel anti-cancer drug sensitivities including potential synergistic combinations were identified. In conclusion, two novel EMC ex vivo cell models (USZ20-EMC1 and USZ22-EMC2) were successfully established and characterized from native tumor tissues. Both cell models will be useful tools for further investigating disease mechanisms and for answering basic and translational research questions. Keywords: Ex vivo cell model; Extraskeletal myxoid chondrosarcoma; Functional testing; Molecular profiling; Sarco-spher

MTPpilot: An Interactive Software for Visualization of Next-Generation Sequencing Results in Molecular Tumor Boards

PURPOSE Comprehensive targeted next-generation sequencing (NGS) panels are routinely used in modern molecular cancer diagnostics. In molecular tumor boards, the detected genomic alterations are often discussed to decide the next treatment options for patients with cancer. With the increasing size and complexity of NGS panels, the discussion of these results becomes increasingly complex, especially if they are reported in a text-based form, as it is the standard in current molecular pathology. METHODS We have developed the Molecular Tumor Profiling pilot (MTPpilot) webservice using HTML, PHP, JavaScript, and MySQL to support the clinical discussion of NGS results at molecular tumor boards. RESULTS MTPpilot integrates various public genome, network, and cancer mutation databases with interactive visualization tools to assess the functional impact of mutations and support clinical decision making at tumor boards. CONCLUSION MTPpilot is tailored for discussion of NGS gene panel results at molecular tumor boards. It is freely available as a webservice at MTPpilot

On-site Cytology for Development of Patient-Derived Three-dimensional Organoid Cultures - A Pilot Study

BACKGROUND/AIM Development of patient-derived three-dimensional (3D) organoid cultures is an emerging technique in the field of precision oncology. We aimed to integrate on-site adequacy evaluation using cytology into the tumor organoid development workflow to ensure precise characterization and growth of these cultures. PATIENTS AND METHODS Cancer patients were consented to a Precision Medicine trial. Fresh tissue was procured for genomic analyses as well as organoid development. Fresh tissue destined for organoid development was evaluated by preparing on-site cytology smears to ensure that only lesional tissue would be submitted for further cell culture work. RESULTS Cytology preparations were made from 64 different tumor samples and evaluated prior to tissue submission for organoid development. In 53 (82.2%) of those tumor samples, the cytology preparation was diagnostic, thus providing adequate material for organoid development. CONCLUSION Characterizing the tissue prior to submission for organoid development ensures submission of lesional tissue only. Furthermore, it is a cost-effective method that can help document patient diagnosis. This can be of importance in biopsies, since the tissue submitted for organoid development cannot be retrieved for clinical diagnosis afterwards. Our findings in this pilot study led to the implementation of on-site cytological evaluation in the tumor organoid development workflow at the Englander Institute for Precision Medicine, NY, USA

Inhibition of FGF receptor blocks adaptive resistance to RET inhibition in CCDC6-RET-rearranged thyroid cancer

Genetic alterations in RET lead to activation of ERK and AKT signaling and are associated with hereditary and sporadic thyroid cancer and lung cancer. Highly selective RET inhibitors have recently entered clinical use after demonstrating efficacy in treating patients with diverse tumor types harboring RET gene rearrangements or activating mutations. In order to understand resistance mechanisms arising after treatment with RET inhibitors, we performed a comprehensive molecular and genomic analysis of a patient with RET-rearranged thyroid cancer. Using a combination of drug screening and proteomic and biochemical profiling, we identified an adaptive resistance to RET inhibitors that reactivates ERK signaling within hours of drug exposure. We found that activation of FGFR signaling is a mechanism of adaptive resistance to RET inhibitors that activates ERK signaling. Combined inhibition of FGFR and RET prevented the development of adaptive resistance to RET inhibitors, reduced cell viability, and decreased tumor growth in cellular and animal models of CCDC6-RET-rearranged thyroid cancer

Molecular and immunophenotypic characterization of SMARCB1 (INI1) - deficient intrathoracic Neoplasms

The switch/sucrose-non-fermenting (SWI/SNF) complex is an ATP-dependent chromatin remodeling complex that plays important roles in DNA repair, transcription and cell differentiation. This complex consists of multiple subunits and is of particular interest in thoracic malignancies due to frequent subunit alteration of SMARCA4 (BRG1). Much less is known about SMARCB1 (INI1) deficient intrathoracic neoplasms, which are rare, often misclassified and understudied. In a retrospective analysis of 1479 intrathoracic malignant neoplasms using immunohistochemistry for INI1 (SMARCB1) on tissue micro arrays (TMA) and a search through our hospital sarcoma database, we identified in total nine intrathoracic, INI1 deficient cases (n = 9). We characterized these cases further by additional immunohistochemistry, broad targeted genomic analysis, methylation profiling and correlated them with clinical and radiological data. This showed that genomic SMARCB1 together with tumor suppressor alterations drive tumorigenesis in some of these cases, rather than epigenetic changes such as DNA methylation. A proper diagnostic classification, however, remains challenging. Intrathoracic tumors with loss or alteration of SMARCB1 (INI1) are highly aggressive and remain often underdiagnosed due to their rarity, which leads to false diagnostic interpretations. A better understanding of these tumors and proper diagnosis is important for better patient care as clinical trials and more targeted therapeutic options are emerging