Accurate and reproducible interpretation of somatic variants is fundamental for therapy decision-making in patients with cancer. To harmonize and automate oncogenicity classification, Oncogenicity Variant Interpreter (OncoVI), an open-source, Python-based implementation of the Clinical Genome Resource/Cancer Genomics Consortium/Variant Interpretation for Cancer Consortium oncogenicity guidelines, was developed. For each of the guideline criteria, the textual descriptions were interpreted, and publicly available resources were identified to be used as reference. Starting from the genomic coordinates of a variant, OncoVI automatically performs functional annotation, collects relevant evidence from the integrated resources, evaluates each criterion, and provides a final oncogenicity classification. OncoVI achieved an accuracy of 80% on a gold standard set of 93 somatic variants provided by the guidelines, with a sensitivity of 88% for oncogenic/likely oncogenic variants. When applied to a real-world set of 7802 variants from 557 participants previously evaluated by the Molecular Tumor Board (MTB) Erlangen, OncoVI showed 79% concordance with the prior MTB assessment of variant impact on protein function. In addition, expert reassessment of 135 MTB variants, conducted in accordance with the oncogenicity guidelines, further confirmed both the validity of OncoVI implementation and the appropriateness of the identified resources. Taken together, OncoVI provides significant support for the harmonized and reproducible oncogenicity classification of somatic variants across institutions.

BACKGROUND AND OBJECTIVE:The Food and Drug Administration and the European Medicine Agency approved erdafitinib for patients with FGFR3-altered metastatic urothelial carcinoma (mUC), highlighting the central role of tumor molecular profiling for patients with mUC. Although different studies described the molecular landscape of muscle-invasive bladder cancer (MIBC) using publicly-available data, a dedicated evaluation of real-world actionable alterations, with evidence-based therapeutic recommendations according to current Molecular Tumor Board (MTB) guidelines, is still lacking. DESIGN, SETTING, AND PARTICIPANTS:We characterized actionable genetic alterations in a retrospective cohort of 233 patients with MIBC/mUC (Muscle-Invasive Erlangen [MIER] cohort) using targeted sequencing. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:Clinically relevant variants were assessed through a custom bioinformatics workflow and expert medical review. To validate their clinical relevance in a real-world setting, we examined actionable alterations and associated therapy recommendations in a cohort of 40 patients with MIBC/mUC undergoing routine diagnostics (MTB cohort). RESULTS AND LIMITATIONS:In the MIER cohort, 95% of patients (n = 226/233; 95% confidence interval [CI], 94-99) harbored at least one pathogenic/likely pathogenic variant. Therapeutically relevant FGFR3 alterations were identified in 11% of patients (n = 26/233; 95% CI, 7.4-16). Additionally, 40% of patients (95% CI, 34-47) showed alterations in 24 biomarkers for FDA-approved therapies. In the MTB cohort, 55% of patients received either on-label (5.0%) or off-label (50%) therapy recommendations. Notably, the recommendation was implemented in only one patient, who achieved stable disease for 4 mo with off-label alpelisib. Retrospectively, similar on-label and off-label indications could have applied to 10% and 70% of patients in the MIER cohort, respectively. CONCLUSIONS:Overall, evidence-based indications for on-label and off-label therapies were observed for the majority of patients with MIBC/mUC. However, our results also revealed a significant gap between the high prevalence of actionable findings and the actual implementation of MTB-guided treatments in clinical practice, suggesting a need for enhanced therapy access and physician adherence to MTB recommendations.

Alterations in Homologous Recombination Repair (HRR) Pathway genes have been found to be associated with HR‐Deficiency (HRD), which is an approved biomarker for PARP Inhibitor (PARPi) treatment. The aim of a Molecular Tumor Board (MTB) is to identify molecular alterations in cancer patients with advanced tumors that may suggest off‐label treatment options. So far, few studies have analyzed the presence of HRR gene mutations and their association with HRD outside of clinical studies. Currently, no data on HRD testing in the setting of a MTB have been published. For the present study, a cohort of 237 patients encompassing 24 different tumor entities was collected from the MTB of the Comprehensive Cancer Center Erlangen‐EMN. We show that an elevated Genomic Instability Score (GIS ≥42) can occur in samples with and without mutations in HRR‐related genes. Overall, 38.1% of cancer samples with BRCA1/2 mutations, 10.9% of tumors with alterations in HRR genes other than BRCA1/2 , and 4.3% of cancer samples without HRR gene mutations harbored an elevated GIS. Notably, our data show that various inactivating BRCA1/2 mutations are not associated with an elevated GIS. Taken together, panCancer assessment of HRD in addition to BRCA1/2 and other HRR gene mutational analysis is recommended to guide decisions regarding PARPi treatment. Further studies are needed to establish thresholds for GIS in non‐ovarian cancer entities. Finally, HRD can be observed in 4.3% of BRCA1/2 and other HRR gene wildtype cancer samples, and may emerge as an independent biomarker for PARPi in the future.

Molecular Tumour Boards (MTBs) rely on different bioinformatics tools and knowledgebases for variant annotation, oncogenicity classification, and estimation of complex biomarkers to identify actionable alterations. However, the typical bioinformatics workflow to process raw next-generation sequencing (NGS) data into clinically meaningful variants involves multiple steps and is inherently complex, thus requiring repeated manual intervention and causing delays in providing molecularly informed precision oncology. Here, we aimed at overcoming these limitations by developing a fully-automated integrative workflow to support NGS-based analyses within MTBs. Our workflow was established at the Institute of Pathology, University Hospital Erlangen (Germany), and adapted to the fully digitized Pathology department at Gravina Hospital in Caltagirone (Italy), using the Illumina TruSight Oncology 500 HRD assay as case study. A trigger event initiates all the downstream bioinformatics analyses to support variant interpretation. In Erlangen, the trigger event is the automatic detection of new NGS data on the Illumina Connected Analytics cloud-based platform. In Caltagirone, the analyses are manually triggered from the anatomic pathology laboratory information system (AP-LIS). The workflow automatically: (i) generates an intuitive overview of sequencing quality metrics, (ii) performs variant annotation, (iii) classifies variant oncogenicity through a fully-automated implementation of the ClinGen/CGC/VICC guidelines, and (iv) generates homologous recombination deficiency scores with genomic instability plots. In the digitized pathology department, results can be readily opened from the AP-LIS and visualized in the patient gallery. Taken together, our end-to-end fully-automated workflow streamlines NGS-based analyses within MTBs by integrating variant interpretation, oncogenicity classification, and estimation of clinically relevant biomarkers.

In precision oncology, reliable testing of predictive molecular biomarkers is the prerequisite for optimal patient treatment. Interlaboratory comparisons are a crucial tool to verify diagnostic performance and reproducibility of one's approach. Here, we describe the design and results of the first recurrent, internationally performed PIK3CA Breast Cancer Tissue external quality assessment (EQA), which was organized by German Quality in Pathology (QuIP) GmbH and started in 2021. After the internal pretesting phase performed by the (lead) panel institutes, in both 2021 and 2022, each EQA test set comprised n=10 tissue samples of hormone receptor-positive, human epidermal growth factor receptor 2-negative invasive breast cancer (IBC) that had to be analyzed and reported by the participants. In 2021, the results were evaluated separately for German-speaking countries (part 1) and international laboratories (part 2). In 2022, the EQA was performed across the European Union. The EQA success rates were 84.6% (n=11/13), 88.6% (n=39/44), and 87.9% (n=29/33) for EQA 2021 part 1, EQA 2021 part 2, and EQA 2022, respectively. The most commonly used methodologies were next-generation sequencing and mutation-/allele-specific qualitative polymerase-chain-reaction-based assays. In summary, this recurrent PIK3CA EQA proved to be a suitable approach for quality assessment in predictive molecular biomarker testing, to obtain an international overview of methods used for PIK3CA mutation analysis and to identify the strengths and weaknesses of individual methods.

Meningeal solitary fibrous tumors (SFT) are rare and have a high frequency of local recurrence and distant metastasis. In a cohort of 126 patients (57 female, 69 male; mean age at surgery 53.0 years) with pathologically confirmed meningeal SFTs with extended clinical follow-up (median 9.9 years; range 15 days-43 years), we performed extensive molecular characterization including genome-wide DNA methylation profiling (n = 80) and targeted TERT promoter mutation testing (n = 98). Associations were examined with NAB2::STAT6 fusion status (n = 101 cases; 51 = ex5-7::ex16-17, 26 = ex4::ex2-3; 12 = ex2-3::exANY/other and 12 = no fusion) and placed in the context of 2021 Central Nervous System (CNS) WHO grade. NAB2::STAT6 fusion breakpoints (fusion type) were significantly associated with metastasis-free survival (MFS) (p = 0.03) and, on multivariate analysis, disease-specific survival (DSS) when adjusting for CNS WHO grade (p = 0.03). DNA methylation profiling revealed three distinct clusters: Cluster 1 (n = 38), Cluster 2 (n = 22), and Cluster 3 (n = 20). Methylation clusters were significantly associated with fusion type (p < 0.001), with Cluster 2 harboring ex4::ex2-3 fusion in 16 (of 20; 80.0%), nearly all TERT promoter mutations (7 of 8; 87.5%), and predominantly an "SFT" histologic phenotype (15 of 22; 68.2%). Clusters 1 and 3 were less distinct, both dominated by tumors having ex5-7::ex16-17 fusion (respectively, 25 of 33; 75.8%, and 12 of 18; 66.7%) and with variable histological phenotypes. Methylation clusters were significantly associated with MFS (p = 0.027), but not overall survival (OS). In summary, NAB2::STAT6 fusion type was significantly associated with MFS and DSS, suggesting that tumors with an ex5::ex16-17 fusion may have inferior patient outcomes. Methylation clusters were significantly associated with fusion type, TERT promoter mutation status, histologic phenotype, and MFS.

ABSTRACTPurposeOffering equal Patient Access to Precision Oncology (PO) is a major challenge of clinical oncologists and cancer center representatives. Here, we provide an easily transferable model adopted from strategic management science to assess the geographic impact of a cancer center – in terms of general cancer care and PO participation.MethodsAs members of the German WERA alliance, the cancer centers Würzburg, Erlangen, Regensburg and Augsburg merged care data regarding their geographical impact. Specifically, we examined the provenance of patients from WERA’s molecular tumor boards (MTBs) between 2020 and 2022 (n = 2243). As second dimension, we added the provenance of patients receiving general cancer care (termed Total Cancer Care, TCC) by WERA. Clustering our outreach along these two dimensions allowed us to set up a four-quadrant matrix consisting of postal code areas with referrals towards WERA. These areas were re-identified on a map of the Federal State of Bavaria and surrounding regions.ResultsIn terms of positive MTB and general cancer care referrals, the WERA Matrix overlooked an active screening area of n = 821 postal code areas – representing about 50% of Bavaria’s spatial expansion and more than six million inhabitants. The WERA Matrix identified regions successfully connected to our outreach structures in terms of subsidiarity – with general cancer care mainly performed locally but PO performed in cooperation with WERA. At the same time, we detected postal code areas with a potential PO backlog – characterized by high levels of cancer care performed by WERA and low levels or no MTB representation.ConclusionsThe WERA Matrix provided a transparent portfolio of postal code areas, which helped assessing the geographical impact of our PO program. We believe that its intuitive principle can easily be transferred to other cancer centers.

Small blue round cell sarcomas (SBRCSs) are a heterogeneous group of tumors with overlapping morphologic features but markedly varying prognosis. They are characterized by distinct chromosomal alterations, particularly rearrangements leading to gene fusions, whose detection currently represents the most reliable diagnostic marker. Ewing sarcomas are the most common SBRCSs, defined by gene fusions involving EWSR1 and transcription factors of the ETS family, and the most frequent non-EWSR1-rearranged SBRCSs harbor a CIC rearrangement. Unfortunately, currently the identification of CIC::DUX4 translocation events, the most common CIC rearrangement, is challenging. Here, we present a machine-learning approach to support SBRCS diagnosis that relies on gene expression profiles measured via targeted sequencing. The analyses on a curated cohort of 69 soft-tissue tumors showed markedly distinct expression patterns for SBRCS subgroups. A random forest classifier trained on Ewing sarcoma and CIC-rearranged cases predicted probabilities of being CIC-rearranged >0.9 for CIC-rearranged-like sarcomas and <0.6 for other SBRCSs. Testing on a retrospective cohort of 1335 routine diagnostic cases identified 15 candidate CIC-rearranged tumors with a probability >0.75, all of which were supported by expert histopathologic reassessment. Furthermore, the multigene random forest classifier appeared advantageous over using high ETV4 expression alone, previously proposed as a surrogate to identify CIC rearrangement. Taken together, the expression-based classifier can offer valuable support for SBRCS pathologic diagnosis.

Insertion mutations in exon 20 of the epidermal growth factor receptor gene (EGFR exon20ins) are rare, heterogeneous alterations observed in non-small cell lung cancer (NSCLC). With a few exceptions, they are associated with primary resistance to established EGFR tyrosine kinase inhibitors (TKIs). As patients carrying EGFR exon20ins may be eligible for treatment with novel therapeutics—the bispecific antibody amivantamab, the TKI mobocertinib, or potential future innovations—they need to be identified reliably in clinical practice for which quality-based routine genetic testing is crucial. Spearheaded by the German Quality Assurance Initiative Pathology two international proficiency tests were run, assessing the performance of 104 participating institutes detecting EGFR exon20ins in tissue and/or plasma samples. EGFR exon20ins were most reliably identified using next-generation sequencing (NGS). Interestingly, success rates of institutes using commercially available mutation-/allele-specific quantitative (q)PCR were below 30% for tissue samples and 0% for plasma samples. Most of these mutation-/allele-specific (q)PCR assays are not designed to detect the whole spectrum of EGFR exon20ins mutations leading to false negative results. These data suggest that NGS is a suitable method to detect EGFR exon20ins in various types of patient samples and is superior to the detection spectrum of commercially available assays.

With the increasing use of innovative next generation sequencing (NGS) platforms in routine diagnostic and research settings, the genetic landscape of uterine sarcomas has been dynamically evolving during the last two decades. Notably, the majority of recently recognized genotypes in uterine sarcomas represent gene fusions, while recurrent oncogene mutations of diagnostic and/ or therapeutic value have been rare. Recently, a distinctive aggressive uterine sarcoma expressing S100 and SOX10, but otherwise lacking diagnostic morphological, immunophenotypic and molecular features of other uterine malignancies has been presented in a scientific abstract form (USCAP, 2023), but detailed description and delineation of the entity is still missing. We herein describe two high-grade unclassified uterine sarcomas characterized by spindle to round cell morphology and diffuse expression of S100 and SOX10, originating in the uterine body and cervix of 53- and 45-year-old women and carrying an ERBB3 (p.Glu928Gly) and an ERBB2 (p.Val777Leu) mutation, respectively. Both tumors harbored in addition genomic HER2 amplification, ATRX mutation and CDKN2A deletion. Methylation studies revealed a methylome most similar to MPNST-like tumors, but distinct from melanoma, MPNST, clear cell sarcoma, and endometrial stromal sarcoma. Case 1 died of progressive peritoneal metastases after multiple trials of chemotherapy 47 months after diagnosis. Case 2 is a recent case who presented with a cervical mass, which was biopsied. This study defines a novel heretofore unrecognized aggressive uterine sarcoma with unique phenotypic and genotypic features. Given the potential value of targeting HER2, recognizing this tumor type is mandatory for appropriate therapeutic strategies and for better future delineation of the entity.

Background In precision oncology, the accurate and reproducible classification of variant oncogenicity is fundamental for therapy decision making. In 2022, a set of guidelines for the classification of oncogenicity of somatic variants in cancer were defined by the Clinical Genome Resource, the Cancer Genomics Consortium, and the Variant Interpretation for Cancer Consortium. However, to date an implementation that automates the evaluation of these criteria does not exist. Furthermore, for the majority of the criteria, the interpretation of the criterion-associated textual indication and the choice of publicly available resources to gather criterion-supporting information depends on the user. Thus, the risk of a variant being classified differently by independent laboratories is relevant, with implications for the management of patient care. Methods Here, we developed Oncogenicity Variant Interpreter (OncoVI), a fully-automated Python-based implementation of the oncogenicity guidelines. First, each criterion was interpreted and publicly available resources were identified to be utilised as reference. Then, criteria were implemented in OncoVI and the information reported by the associated resources were integrated. OncoVI is part of a broader Python-framework that, starting from the genomic position of the variant, automatically performs functional annotation, collects the available evidence from the reference resources, and provides a classification of oncogenicity. Results On the set of 93 somatic variants provided by the guidelines OncoVI achieved an overall accuracy of 80%, with a sensitivity of 88% in the classification of Oncogenic/Likely Oncogenic variants. On a real-world data set of 7,802 variants from 557 patients previously evaluated within the Molecular Tumour Board (MTB) Erlangen, an agreement of 79% was observed between the oncogenicity classification of OncoVI and the MTB pathogenicity assessment. In addition, the pathogenicity classification of 135 variants of the MTB data set was re-assessed by expert biologists adhering solely to the oncogenicity guidelines. This re-evaluation confirmed the validity of OncoVI"s interpretation of the resources chosen as reference, but it also underlined the ability of experts in solving conflicting evidence. Conclusions Taken together, OncoVI provides an effective implementation of the oncogenicity guidelines, thus facilitating their adoption and supporting the reproducible and harmonised oncogenicity classification of somatic variants between institutions. ### Competing Interest Statement ArHa obtains honoraria for lectures or consulting/advisory boards for Abbvie, Agilent, AstraZeneca, Biocartis, BMS, Boehringer Ingelheim, Cepheid, Diaceutics, Gilead, Illumina, Ipsen, Janssen, Lilly, Merck, MSD, Nanostring, Novartis, Pfizer, Qiagen, QUIP GmbH, Roche, Sanofi, 3DHistech and other research support from AstraZeneca, Biocartis, Cepheid, Gilead, Illumina, Janssen, Nanostring, Novartis, Owkin, Qiagen, QUIP GmbH, Roche, Sanofi. FH obtains honoraria for lectures or consulting/advisory boards for AstraZeneca, BMS, Boehringer Ingelheim, Novartis and receives research support from Illumina GmbH. The remaining authors have no financial or non-financial competing interests to declare. ### Funding Statement This study was funded by Deutsche Forschungsgemeinschaft (German Research Foundation) grant TRR 305 [projects Z01 (FF) and Z02 (ArHa)]. We express gratitude to patients, clinicians, technicians and institutions who contributed to the Molecular Tumour Board of the CCC Erlangen-EMN (Germany) ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Friedrich-Alexander University Erlangen-Nuremberg (100_17 B from 7 April 2017, addendum from 27 July 2021). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript

In precision oncology, reliable testing of predictive molecular biomarkers is a prerequisite for optimal patient treatment. Interlaboratory comparisons are a crucial tool to verify diagnostic performance and reproducibility of one's approach. Herein is described the design and results of the fi rst recurrent, internationally performed PIK3CA (phosphatidylinositol-4,5-bisphosphate 3 kinase catalytic subunit a ) breast cancer tissue external quality assessment (EQA), organized by German Quality in Pathology GmbH and started in 2021. After the internal pretesting phase performed by the (lead) panel institutes, in both 2021 and 2022, each EQA test set comprised n = 10 tissue samples of hormone receptor- positive, human epidermal growth factor receptor 2- negative invasive breast cancer that had to be analyzed and reported by the participants. In 2021, the results were evaluated separately for German-speaking countries (part 1) and international laboratories (part 2). In 2022, the EQA was performed across the European Union. The EQA success rates were 84.6% (n n = 11/13), 88.6% (n n = 39/ 44), and 87.9% (n n = 29/33) for EQA 2021 part 1, part 2, and EQA 2022, respectively. The most commonly used methods were next-generation sequencing and mutation-/allele-specific fi c qualitative PCR-based assays. In summary, this recurrent PIK3CA EQA proved to be a suitable approach to obtain an international overview of methods used for PIK3CA mutation analysis, to evaluate them qualitatively, and identify the strengths and weaknesses of individual methods. (J Mol Diagn 2024, 26: 624-637;- 637; https://doi.org/10.1016/j.jmoldx.2024.04.003)

OBJECTIVES:The development of desmoid tumors (DT) is associated with trauma, which is an aspect with medicolegal relevance. The objective of this study was to analyze the proportion and type of trauma (surgical, blunt/fracture, implants), its lag time, and mutations of the CTNNB1 gene in patients with sporadic DT. METHODS:We analyzed a prospectively kept database of 381 females and 171 males, median age at disease onset 37.7 years (females) and 39.3 years (males) with a histologically confirmed DT. Patients with germline mutation of the APC gene were excluded. Details of the history particularly of traumatic injuries to the site of DT were provided by 501 patients. RESULTS:In 164 patients (32.7%), a trauma anteceding DT could be verified with a median lag time of 22.9 months (SD, 7.7 months; range, 9-44 months). A prior surgical procedure was relevant in 98 patients, a blunt trauma in 35 patients, a punctuated trauma (injections, trocar) in 18 patients, and site of an implant in 10 patients. In 220 patients, no trauma was reported (43.9%), and 58 females (11.6%) had a postpregnancy DT in the rectus abdominis muscle. In 42 patients (8.4%), data were inconclusive. The distribution of mutations in the CTNNB1 gene (codon 41 vs. 45) was similar in patients with and without a history of trauma before DT development. CONCLUSIONS:A significant subgroup of patients suffers from a trauma-associated DT, predominantly at a prior surgical site including implants to breast or groin, accounting for 77.9% of the cases, whereas blunt trauma was responsible in 22.1%. We found no data to support that trauma-associated DT have different molecular features in the CTNNB1 gene.

Molecular Tumor Boards (MTBs) converge state-of-the-art next-generation sequencing (NGS) methods with the expertise of an interdisciplinary team consisting of clinicians, pathologists, human geneticists, and molecular biologists to provide molecularly informed guidance in clinical decision making to the treating physician. In the present study, we particularly focused on elucidating the factors impacting on the clinical translation of MTB recommendations, utilizing data generated from gene panel mediated comprehensive genomic profiling (CGP) of 554 patients at the MTB of the Comprehensive Cancer Center Erlangen, Germany, during the years 2016 to 2020. A subgroup analysis of cases with available follow-up data (n = 332) revealed 139 cases with a molecularly informed MTB recommendation, which was successfully implemented in the clinic in 44 (31.7%) of these cases. Here, the molecularly matched treatment was applied in 45.4% (n = 20/44) of cases for ≥6 months and in 25% (n = 11/44) of cases for 12 months or longer (median time to treatment failure, TTF: 5 months, min: 1 month, max: 38 months, ongoing at data cut-off). In general, recommendations were preferentially implemented in the clinic when of high (i.e., tier 1) clinical evidence level. In particular, this was the case for MTB recommendations suggesting the application of PARP, PIK3CA, and IDH1/2 inhibitors. The main reason for non-compliance to the MTB recommendation was either the application of non-matched treatment modalities (n = 30)/stable disease (n = 7), or deteriorating patient condition (n = 22)/death of patient (n = 9). In summary, this study provides an insight into the factors affecting the clinical implementation of molecularly informed MTB recommendations, and careful considerations of these factors may guide future processes of clinical decision making.

Ectopic Cushing syndrome is a rare clinical disorder resulting from excessive adrenocorticotrophic hormone (ACTH) produced by non-pituitary neoplasms, mainly neuroendocrine neoplasms (NENs) of the lung, pancreas, and gastrointestinal tract, and other less common sites. The genetic background of ACTH-producing NENs has not been well studied. Inspired by an index case of ACTH-producing pancreatic NEN carrying a gene fusion, we postulated that ACTH-producing NENs might be enriched for gene fusions. We herein examined 21 ACTH-secreting NENs of the pancreas (10), lung (9), thymus (1), and kidney (1) using targeted RNA sequencing. The tumors were classified according to the most recent WHO classification as NET-G1/typical carcinoid (n = 4), NETG-2/atypical carcinoid (n = 14), and NET-G3 (n = 3). Overall, targeted RNA sequencing was successful in 11 cases (4 of 10 pancreatic tumors, 5 of 9 pulmonary tumors, and in the one renal and one thymic tumor). All four successfully tested pancreatic tumors revealed a gene fusion: two had a EWSR1::BEND2 and one case each had a KMT2A::BCOR and a TFG::ADGRG7 fusion, respectively. EWSR1 rearrangements were confirmed in both tumors with a EWSR1::BEND2 by FISH. Gene fusions were mutually exclusive with ATRX, DAXX, and MEN1 mutations (the most frequently mutated genes in NETs) in all four cases. Using RNA-based variant assessment (n = 16) or via the TSO500 panel (n = 5), no pathogenic BCOR mutations were detected in any of the cases. Taken together, gene fusions were detected in 4/4 (100%) pancreatic versus 0/7 (0%) non-pancreatic tumors, respectively. These results suggest a potential role for gene fusions in triggering the ACTH production in pancreatic NENs presenting with ectopic Cushing syndrome. While the exact mechanisms responsible for the ectopic ACTH secretion are beyond the scope of this study, overexpressed fusion proteins might be involved in promoter-mediated overexpression of pre-ACTH precursors in analogy to the mechanisms postulated for EWSR1::CREB1-mediated paraneoplastic phenomena in certain mesenchymal neoplasms. The genetic background of the ACTH-producing non-pancreatic NENs remains to be further studied.