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Summary: Background: Epithelioid haemangioma (EH) arising from the skin is a benign vascular tumour with marked inflammatory cell infiltration, which exhibits a high tendency to persist and frequently recurs after resection. So far, the underlying pathogenesis is largely elusive. Objectives: To identify genetic alterations by next‐generation sequencing and/or droplet digital polymerase chain reaction (ddPCR) in cutaneous EH. Methods: DNA and RNA from an EH lesion of an index patient were subjected to whole‐genome and RNA sequencing. Multiplex PCR‐based panel sequencing of genomic DNA isolated from archival formalin‐fixed paraffin‐embedded tissue of 18 patients with cutaneous EH was performed. ddPCR was used to confirm mutations. Results: We identified somatic mutations in genes of the mitogen‐activated protein kinase (MAPK) pathway (MAP2K1 and KRAS) in cutaneous EH biopsies. By ddPCR we could confirm the recurrent presence of activating, low‐frequency mutations affecting MAP2K1. In total, nine out of 18 patients analysed showed activating MAPK pathway mutations, which were mutually exclusive. Comparative analysis of tissue areas enriched for lymphatic infiltrate or aberrant endothelial cells, respectively, revealed an association of these mutations with the presence of endothelial cells. Conclusions: Taken together, our data suggest that EH shows somatic mutations in genes of the MAPK pathway which might contribute to the formation of this benign tumour. What is already known about this topic?Epithelioid haemangioma (EH) arising from the skin is a benign vascular tumour of unknown aetiology.Cutaneous EH often shows a marked inflammatory infiltrate indicating a reactive origin. What does this study add?Half of the samples from cutaneous EH in this study showed activating mutations in the mitogen‐activated protein kinase pathway (MAP2K1 and KRAS).Mutations were mutually exclusive. What is the translational message?Somatic mutations seem to contribute to the formation of a significant proportion of cutaneous EH.The molecular alterations found might be sensitive for targeted therapies. Linked Comment: W. Tan and J.S. Nelson. Br J Dermatol 2022; 186:393–394. [ABSTRACT FROM AUTHOR]

Summary: Background: Eccrine porocarcinoma (EPC) is a rare skin cancer arising from the eccrine sweat glands. Due to the lack of effective therapies, metastasis is associated with a high mortality rate. Objectives: To investigate the drivers of EPC progression. Methods: We carried out genomic and transcriptomic profiling of metastatic EPC (mEPC), validation of the observed alterations in an EPC patient‐derived cell line, confirmation of relevant observations in a large patient cohort of 30 tumour tissues, and successful treatment of a patient with mEPC under the identified treatment regimens. Results: mEPC was characterized by a high tumour mutational burden (TMB) with an ultraviolet signature, widespread copy number alterations and gene expression changes that affected cancer‐relevant cellular processes such as cell cycle regulation and proliferation, including a pathogenic TP53 (tumour protein 53) mutation, a copy number deletion in the CDKN2A (cyclin dependent kinase inhibitor 2A) region and a CTNND1/PAK1 [catenin delta 1/p21 (RAC1) activated kinase 1] gene fusion. The overexpression of EGFR (epidermal growth factor receptor), PAK1 and MAP2K1 (mitogen‐activated protein kinase kinase 1; also known as MEK1) genes translated into strong protein expression and respective pathway activation in the tumour tissue. Furthermore, a patient‐derived cell line was sensitive to EGFR and MEK inhibition, confirming the functional relevance of the pathway activation. Immunohistochemistry analyses in a large patient cohort showed the relevance of the observed changes to the pathogenesis of EPC. Our results indicate that mEPC should respond to immune or kinase inhibitor therapy. Indeed, the advanced disease of our index patient was controlled by EGFR‐directed therapy and immune checkpoint inhibition for more than 2 years. Conclusions: Molecular profiling demonstrated high TMB and EGFR/MAPK pathway activation to be novel therapeutic targets in mEPC. Whatis already known about this topic?Eccrine porocarcinoma (EPC) is a rare skin cancer with a largely unknown aetiology and molecular makeup.In cases not amendable by surgery, no effective treatment is available. Whatdoes this study add?Using comprehensive genomic and transcriptomic profiling, aberrations in cancer‐relevant signalling pathways were identified that could not only be validated functionally in a newly established patient‐derived culture model but could also be confirmed in a larger series of retrospective cases.Importantly, these observations were translated into treatment regimens resulting in substantial clinical benefit in a patient with metastatic EPC. Whatis the translational message?Here, we provide an excellent example of how from‐bedside‐to‐bench and back can work.We not only detected relevant genetic aberrations in EPC, but also confirmed their functional relevance and their transferability to additional cases, culminating in effective treatment of the patient.We thus provide new therapeutic options for EPC and possibly other adnexal carcinomas with similar molecular makeup. Plain language summary available online [ABSTRACT FROM AUTHOR]

Purpose: The pathognomonic FUS::DDIT3 fusion protein drives myxoid liposarcoma (MLS) tumorigenesis via aberrant transcriptional activation of oncogenic signaling. As FUS::DDIT3 has so far not been pharmacologically tractable to selectively target MLS cells, this study investigated the functional role of the cell cycle regulator WEE1 as novel FUS::DDIT3-dependent therapeutic vulnerability in MLS., Experimental Design: Immunohistochemical evaluation of the cell cycle regulator WEE1 was performed in a large cohort of MLS specimens. FUS::DDIT3 dependency and biological function of the G1/S cell cycle checkpoint were analyzed in a mesenchymal stem cell model and liposarcoma cell lines in vitro. WEE1 activity was modulated by RNAi-mediated knockdown and the small molecule inhibitor MK-1775 (adavosertib). An established MLS cell line-based chicken chorioallantoic membrane model was employed for in vivo confirmation., Results: We demonstrate that enhanced WEE1 pathway activity represents a hallmark of FUS::DDIT3-expressing cell lines as well as MLS tissue specimens and that WEE1 is required for MLS cellular survival in vitro and in vivo. Pharmacologic inhibition of WEE1 activity results in DNA damage accumulation and cell cycle progression forcing cells to undergo apoptotic cell death. In addition, our results uncover FUS::DDIT3-dependent WEE1 expression as an oncogenic survival mechanism to tolerate high proliferation and resulting replication stress in MLS. Fusion protein-driven G1/S cell cycle checkpoint deregulation via overactive Cyclin E/CDK2 complexes thereby contributes to enhanced WEE1 inhibitor sensitivity in MLS., Conclusions: Our preclinical study identifies WEE1-mediated replication stress tolerance as molecular vulnerability in FUS::DDIT3-driven MLS tumorigenesis that could represent a novel target for therapeutic intervention., (©2024 American Association for Cancer Research.)

Background and Aims: Cholangiocarcinoma (CCA) is an aggressive malignancy arising from the intrahepatic (iCCA) or extrahepatic (eCCA) bile ducts with poor prognosis and limited treatment options. Prior evidence highlighted a significant contribution of the non-canonical NF-κB signalling pathway in initiation and aggressiveness of different tumour types. Lymphotoxin-β (LTβ) stimulates the NF-κB-inducing kinase (NIK), resulting in the activation of the transcription factor RelB. However, the functional contribution of the non-canonical NF-κB signalling pathway via the LTβ/NIK/RelB axis in CCA carcinogenesis and progression has not been established., Methods: Human CCA-derived cell lines and organoids were examined to determine the expression of NF-κB pathway components upon activation or inhibition. Proliferation and cell death were analysed using real-time impedance measurement and flow cytometry. Immunoblot, qRT-PCR, RNA sequencing and in situ hybridization were employed to analyse gene and protein expression. Four in vivo models of iCCA were used to probe the activation and regulation of the non-canonical NF-κB pathway., Results: Exposure to LTα1/β2 activates the LTβ/NIK/RelB axis and promotes proliferation in CCA. Inhibition of NIK with the small molecule inhibitor B022 efficiently suppresses RelB expression in patient-derived CCA organoids and nuclear co-translocation of RelB and p52 stimulated by LTα1/β2 in CCA cell lines. In murine CCA, RelB expression is significantly increased and LTβ is the predominant ligand of the non-canonical NF-κB signalling pathway., Conclusions: Our study confirms that the non-canonical NF-κB axis LTβ/NIK/RelB drives cholangiocarcinogenesis and represents a candidate therapeutic target., (© 2024 The Author(s). Liver International published by John Wiley & Sons Ltd.)

Precision cancer medicine is widely established, and numerous molecularly targeted drugs for various tumor entities are approved or in development. Personalized pharmacotherapy in oncology has so far been based primarily on tumor characteristics, e.g., somatic mutations. However, the response to drug treatment also depends on pharmacological processes summarized under the term ADME (absorption, distribution, metabolism, and excretion). Variations in ADME genes have been the subject of intensive research for more than five decades, considering individual patients' genetic makeup, referred to as pharmacogenomics (PGx). The combined impact of a patient's tumor and germline genome is only partially understood and often not adequately considered in cancer therapy. This may be attributed, in part, to the lack of methods for combined analysis of both data layers. Optimized personalized cancer therapies should, therefore, aim to integrate molecular information about the tumor and the germline, taking into account existing PGx guidelines for drug therapy. Moreover, such strategies should provide the opportunity to consider genetic variants of previously unknown functional significance. Bioinformatic analysis methods and corresponding algorithms for data interpretation need to be developed to consider PGx data in interdisciplinary molecular tumor boards, where cancer patients are discussed to provide evidence-based recommendations for clinical management based on individual tumor profiles. Significance Statement The era of personalized oncology has seen the emergence of drugs tailored to genetic variants associated with cancer biology. However, full potential of targeted therapy remains untapped due to the predominant focus on acquired tumor-specific alterations. Optimized cancer care must integrate tumor and patient genomes, guided by pharmacogenomic principles. An essential prerequisite for realizing truly personalized drug treatment of cancer patients is the development of bioinformatic tools for comprehensive analysis of all data layers generated in modern precision oncology programs.

Drug sensitivity profiling in patient-derived tumor models offers new hope for improving outcomes in cancers lacking effective therapies. Al Shihabi et al. 1 demonstrate that short-term cultures from bone and soft tissue sarcomas enable clinically meaningful screening of multiple drugs and combinations, marking a significant advance in personalized care for these high-risk diseases., Competing Interests: Declaration of interests C.R.B. received research funding from PreComb Therapeutics., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 10 6  cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic., Competing Interests: Conflicts of interest The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: To reduce smoking uptake in adolescents, the medical students' network Education Against Tobacco (EAT) has developed a school-based intervention involving a face-aging mobile app (Smokerface)., Methods: A two-arm cluster-randomized controlled trial was conducted, evaluating the 2016 EAT intervention, which employed the mobile app Smokerface and which was delivered by medical students. Schools were randomized to intervention or control group. Surveys were conducted at baseline (pre-intervention) and at 9, 16, and 24 months post-intervention via paper & pencil questionnaires. The primary outcome was the difference in within-group changes in smoking prevalence between intervention and control group at 24 months., Results: Overall, 144 German secondary schools comprising 11,286 pupils participated in the baseline survey, of which 100 schools participated in the baseline and at least one of the follow-up surveys, yielding 7437 pupils in the analysis sample. After 24 months, smoking prevalence was numerically lower in the intervention group compared to control group (12.9 % vs. 14.3 %); however, between-group differences in change in smoking prevalence between baseline and 24-months follow-up (OR=0.83, 95 %-CI: 0.64-1.09) were not statistically significant (p = 0.176). Intention to start smoking among baseline non-smokers declined non-significantly in the intervention group (p = 0.064), and remained essentially unchanged in the control group, but between-group differences in changes at the 24-months follow-up (OR=0.88, 0.64-1.21) were not statistically significant (p = 0.417)., Conclusion: While a trend towards beneficial effects of the intervention regarding smoking prevalence as well as intention to start smoking among baseline non-smokers was observed, our smoking prevention trial demonstrated no significant effect of the intervention., Competing Interests: Declaration of Competing Interest TJB programmed the Smokerface App and is therefore formally the owner/rights holder. In 2017, he was offered and accepted 500 Euro per year from another German tobacco prevention charity (ginko Stiftung für Prävention, Germany) to license the Smokerface App for their school-based prevention efforts,with no influence to this study. TJB is also the owner of Smart Health Heidelberg GmbH, a software company which develops digital utehealth apps. Werner Seeger received consulting fees from United Therapeutics, Tiakis Biotech AG, Liquidia, Pieris Pharmaceuticals, Abivax, Pfizer, Medspray BV, outside the submitted work. The other authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Competing Interests: Conflicts of interest Dr Utikal is on the advisory board or has received honoraria from Amgen, Bristol Myers Squibb, GSK, Immunocore, LeoPharma, Merck Sharp and Dohme, Novartis, Pierre Fabre, Roche, and Sanofi outside the submitted work. Dr Meier has received speaker's fees or/and advisor's honoraria from Novartis, Roche, BMS, MSD, and Pierre Fabre. Dr Hobelsberger reports speaker's honoraria from Almirall, UCB, and AbbVie. Dr Gellrich has received speaker's fees or/and advisor's honoraria by Sun Pharma, Sanofi, and Merck. Dr Hauschild reports speaker's honoraria or consultancy fees from the following companies: Agenus, Amgen, BMS, Dermagnostix, Highlight Therapeutics, Immunocore, Incyte, IO Biotech, MerckPfizer, MSD, NercaCare, Novartis, Philogen, Pierre Fabre, Regeneron, Roche, Sanofi-Genzyme, Seagen, Sun Pharma, and Xenthera, outside the submitted work. Dr French is on the advisory board or has received consulting/speaker honoraria from for Galderma, Janssen, Leo Pharma, Eli Lilly, Almirall, Union Therapeutics, Regeneron, Novartis, Amgen, Abbvie, UCB, Biotest, and InflaRx. Dr Schlaak has received consultant or speaker fees or travel grants from BMS, MSD, Roche, Kyowa Kirin, Novartis, Sanofi Genzyme, Pierre Fabre, Sun Pharma, and Immunocore. Dr Erdmann declares honoraria from Bristol-Meyers Squibb, Immunocore, and Novartis outside the submitted work. Dr Haferkamp reports advisory roles for or has received honoraria from Pierre Fabre Pharmaceuticals, Novartis, Roche, BMS, Amgen, and MSD outside the submitted work. Dr Drexler has received honoraria from Pierre Fabre Pharmaceuticals and Novartis outside the submitted work. Dr Sondermann reports grants, speaker's honoraria, or consultancy fees from medi GmbH Bayreuth, Abbvie, Almirall, Amgen, Bristol-Myers Squibb, Celgene, GSK, Janssen, LEO Pharma, Lilly, MSD, Novartis, Pfizer, Roche, Sanofi Genzyme, and UCB outside the submitted work. Dr Schilling reports advisory roles for or has received honoraria from Pierre Fabre Pharmaceuticals, Incyte, Novartis, Roche, BMS, and MSD. Dr Goebeler has received speaker's honoraria and/or has served as a consultant and/or member of advisory boards for Almirall, Argenx, Biotest, Eli Lilly, Janssen Cilag, Leo Pharma, Novartis, and UCB, outside the submitted work. Dr Kather reports consulting services for Owkin, France, Panakeia, UK, and DoMore Diagnostics, Norway and has received honoraria for lectures by MSD, Eisai, and Fresenius. Dr Brinker reports owning a company that develops mobile apps (Smart Health Heidelberg GmbH, Handschuhsheimer Landstr. 9/1, 69120 Heidelberg). Author Haggenmüller, Author Maron, Author Hekler, Dr Krieghoff-Henning, Dr Gaiser, Dr Müller, Dr Fabian, Dr Sergon, Dr Weichenthal, Dr Heinzerling, Dr Schlager, Dr Ghoreschi, Dr Hilke, Dr Pochi, Dr Korsing, Dr Berking, Dr Heppt, Dr Schadendorf, Dr Fröhling, Author Kaminski, Author Doppler, and Author Bucher have no conflicts of interest to declare.

Background and Aims: HCC is the most common primary liver tumor, with an increasing incidence worldwide. HCC is a heterogeneous malignancy and usually develops in a chronically injured liver. The NF-κB signaling network consists of a canonical and a noncanonical branch. Activation of canonical NF-κB in HCC is documented. However, a functional and clinically relevant role of noncanonical NF-κB and its downstream effectors is not established., Approach and Results: Four human HCC cohorts (total n = 1462) and 4 mouse HCC models were assessed for expression and localization of NF-κB signaling components and activating ligands. In vitro , NF-κB signaling, proliferation, and cell death were measured, proving a pro-proliferative role of v-rel avian reticuloendotheliosis viral oncogene homolog B (RELB) activated by means of NF-κB-inducing kinase. In vivo , lymphotoxin beta was identified as the predominant inducer of RELB activation. Importantly, hepatocyte-specific RELB knockout in a murine HCC model led to a lower incidence compared to controls and lower maximal tumor diameters. In silico , RELB activity and RELB-directed transcriptomics were validated on the The Cancer Genome Atlas HCC cohort using inferred protein activity and Gene Set Enrichment Analysis. In RELB-active HCC, pathways mediating proliferation were significantly activated. In contrast to v-rel avian reticuloendotheliosis viral oncogene homolog A, nuclear enrichment of noncanonical RELB expression identified patients with a poor prognosis in an etiology-independent manner. Moreover, RELB activation was associated with malignant features metastasis and recurrence., Conclusions: This study demonstrates a prognostically relevant, etiology-independent, and cross-species consistent activation of a lymphotoxin beta/LTβR/RELB axis in hepatocarcinogenesis. These observations may harbor broad implications for HCC, including possible clinical exploitation., (Copyright © 2023 American Association for the Study of Liver Diseases.)

Cancer Core Europe brings together the expertise, resources, and interests of seven leading cancer institutes committed to leveraging collective innovation and collaboration in precision oncology. Through targeted efforts addressing key medical challenges in cancer and partnerships with multiple stakeholders, the consortium seeks to advance cancer research and enhance equitable patient care., (©2024 American Association for Cancer Research.)

Targeted tumor only sequencing has become a standard practice in cancer diagnostics. This study aims to develop an approach for robust copy number variant calling in tumor samples using only off-target region (OTR) reads. We also established a clinical use case for homologous recombination deficiency (HRD) score estimation (HRDest) using the sum of telomeric-allelic imbalance and large-scale state transition scores without the need for loss of heterozygosity information. A strong correlation was found between HRD score and the sum of telomeric-allelic imbalance + large-scale state transition in The Cancer Genome Atlas cohort (ρ = 0.99, P < 2.2 × 10 -16 ) and in a clinical in-house cohort of 34 tumors (ρ = 0.9, P = 5.1 × 10 -13 ) comparing whole-exome sequencing and targeted sequencing data. HRDest scores from 1086 clinical cases were compared with The Cancer Genome Atlas data set. There were no significant differences in HRD score distribution within the analyzed tumor types. As a control, commercially available HRD standards were also sequenced, and the HRDest scores obtained from the OTR reads were well within the HRD reference range provided by the manufacturer. In conclusion, OTR reads of tumor-only panel sequencing can be used to determine genome-wide copy number variant profiles and to approximate HRD scores., Competing Interests: Disclosure Statement O.N. reports personal fees from Novartis outside the submitted work. A.-L.V. reports personal fees from Astra Zeneca outside the submitted work. J.B. reports a grant from the German Cancer Aid outside the submitted work. S.F. reports consulting or advisory board membership for Bayer, Illumina, and Roche; honoraria from Amgen, Eli Lilly, PharmaMar, and Roche; research funding from AstraZeneca, Pfizer, PharmaMar, and Roche; and travel or accommodation expenses from Amgen, Eli Lilly, Illumina, PharmaMar, and Roche. P.S. reports personal fees from Bristol Myers Squibb, Merck Sharp & Dohme (MSD), Incyte, Janssen, Amgen, Novartis, Roche, and AstraZeneca outside the submitted work. A.S. reports grants and personal fees from Bayer and Bristol Myers Squibb; grants from Chugai; and personal fees from AstraZeneca, MSD, Takeda, Seattle Genetics, Novartis, Illumina, Thermo Fisher, Eli Lilly, and Takeda outside the submitted work. D.K. reports personal fees from AstraZeneca, Bristol Myers Squibb, Pfizer, Lilly, Agilent, and Takeda outside the submitted work. The remaining authors declare no conflict of interest., (Copyright © 2024 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Precision oncology is a field of personalized medicine in which tumor biology forms the basis for tailored treatments. The preferred approach currently applied in clinical practice is based on the concept of malignant tumors as genetic diseases that are caused by mutations in oncogenes and tumor suppressors. On the one hand, these can be targeted by molecular drugs, while on the other hand, next-generation sequencing allows for comprehensive analysis of all relevant aberrations, thus enabling the matching of appropriate treatments across entities based on molecular information. Rational molecular therapies are developed and annotated with supporting evidence by molecular tumor boards, which have been established at various academic centers in recent years. Advancing precision oncology to a new standard of care requires improved applicability of personalized molecular therapies and thorough scientific evaluation of precision oncology programs., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Understanding the molecular and cellular processes involved in lung epithelial regeneration may fuel the development of therapeutic approaches for lung diseases. We combine mouse models allowing diphtheria toxin-mediated damage of specific epithelial cell types and parallel GFP-labeling of functionally dividing cells with single-cell transcriptomics to characterize the regeneration of the distal lung. We uncover cell types, including Krt13 + basal and Krt15 + club cells, detect an intermediate cell state between basal and goblet cells, reveal goblet cells as actively dividing progenitor cells, and provide evidence that adventitial fibroblasts act as supporting cells in epithelial regeneration. We also show that diphtheria toxin-expressing cells can persist in the lung, express specific inflammatory factors, and transcriptionally resemble a previously undescribed population in the lungs of COVID-19 patients. Our study provides a comprehensive single-cell atlas of the distal lung that characterizes early transcriptional and cellular responses to concise epithelial injury, encompassing proliferation, differentiation, and cell-to-cell interactions., (© 2024. The Author(s).)

Importance: The development of artificial intelligence (AI)-based melanoma classifiers typically calls for large, centralized datasets, requiring hospitals to give away their patient data, which raises serious privacy concerns. To address this concern, decentralized federated learning has been proposed, where classifier development is distributed across hospitals., Objective: To investigate whether a more privacy-preserving federated learning approach can achieve comparable diagnostic performance to a classical centralized (ie, single-model) and ensemble learning approach for AI-based melanoma diagnostics., Design, Setting, and Participants: This multicentric, single-arm diagnostic study developed a federated model for melanoma-nevus classification using histopathological whole-slide images prospectively acquired at 6 German university hospitals between April 2021 and February 2023 and benchmarked it using both a holdout and an external test dataset. Data analysis was performed from February to April 2023., Exposures: All whole-slide images were retrospectively analyzed by an AI-based classifier without influencing routine clinical care., Main Outcomes and Measures: The area under the receiver operating characteristic curve (AUROC) served as the primary end point for evaluating the diagnostic performance. Secondary end points included balanced accuracy, sensitivity, and specificity., Results: The study included 1025 whole-slide images of clinically melanoma-suspicious skin lesions from 923 patients, consisting of 388 histopathologically confirmed invasive melanomas and 637 nevi. The median (range) age at diagnosis was 58 (18-95) years for the training set, 57 (18-93) years for the holdout test dataset, and 61 (18-95) years for the external test dataset; the median (range) Breslow thickness was 0.70 (0.10-34.00) mm, 0.70 (0.20-14.40) mm, and 0.80 (0.30-20.00) mm, respectively. The federated approach (0.8579; 95% CI, 0.7693-0.9299) performed significantly worse than the classical centralized approach (0.9024; 95% CI, 0.8379-0.9565) in terms of AUROC on a holdout test dataset (pairwise Wilcoxon signed-rank, P < .001) but performed significantly better (0.9126; 95% CI, 0.8810-0.9412) than the classical centralized approach (0.9045; 95% CI, 0.8701-0.9331) on an external test dataset (pairwise Wilcoxon signed-rank, P < .001). Notably, the federated approach performed significantly worse than the ensemble approach on both the holdout (0.8867; 95% CI, 0.8103-0.9481) and external test dataset (0.9227; 95% CI, 0.8941-0.9479)., Conclusions and Relevance: The findings of this diagnostic study suggest that federated learning is a viable approach for the binary classification of invasive melanomas and nevi on a clinically representative distributed dataset. Federated learning can improve privacy protection in AI-based melanoma diagnostics while simultaneously promoting collaboration across institutions and countries. Moreover, it may have the potential to be extended to other image classification tasks in digital cancer histopathology and beyond.

Summary: ZygosityPredictor 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 Implementation: ZygosityPredictor 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., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press.)

Fibroblast activation protein α (FAPα) is expressed at high levels in several types of tumors. Here, we report the expression pattern of FAPα in solitary fibrous tumor (SFT) and its potential use as a radiotheranostic target. Methods: We analyzed FAPα messenger RNA and protein expression in biopsy samples from SFT patients using immunohistochemistry and multiplexed immunofluorescence. Tracer uptake and detection efficacy were assessed in patients undergoing clinical 68 Ga-FAPα inhibitor (FAPI)-46 PET, 18 F-FDG PET, and contrast-enhanced CT. 90 Y-FAPI-46 radioligand therapy was offered to eligible patients with progressive SFT. Results: Among 813 patients and 126 tumor entities analyzed from the prospective observational MASTER program of the German Cancer Consortium, SFT ( n = 34) had the highest median FAPα messenger RNA expression. Protein expression was confirmed in tumor biopsies from 29 of 38 SFT patients (76%) in an independent cohort. Most cases showed intermediate to high FAPα expression by immunohistochemistry (24/38 samples, 63%), which was located primarily on the tumor cell surface. Nineteen patients who underwent 68 Ga-FAPI-46 PET imaging demonstrated significantly increased tumor uptake, with an SUV max of 13.2 (interquartile range [IQR], 10.2), and an improved mean detection efficacy of 94.5% (SEM, 4.2%), as compared with 18 F-FDG PET (SUV max , 3.2 [IQR, 3.1]; detection efficacy, 77.3% [SEM, 5.5%]). Eleven patients received a total of 34 cycles (median, 3 cycles [IQR, 2 cycles]) of 90 Y-FAPI-46 radioligand therapy, which resulted in disease control in 9 patients (82%). Median progression-free survival was 227 d (IQR, 220 d). Conclusion: FAPα is highly expressed by SFT and may serve as a target for imaging and therapy. Further studies are warranted to define the role of FAPα-directed theranostics in the care of SFT patients., (© 2024 by the Society of Nuclear Medicine and Molecular Imaging.)

Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists' decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists' diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists' confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists' willingness to adopt such XAI systems, promoting future use in the clinic., (© 2024. The Author(s).)