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We present the rare case of a 51-year-old male diagnosed with a solitary fibrous tumor (SFT) of the prostate, along with a concurrent low-grade prostate adenocarcinoma (Gleason score 3 + 3, Grade Group 1). The diagnosis was confirmed by positive immunohistochemical markers, including CD34, BCL2, and STAT6, and molecular analysis showing a NAB2-STAT6 fusion. Following successful surgical management and the simultaneous diagnosis of a pulmonary relapse from a prior thyroid carcinoma, the patient remains under clinical surveillance. This is particularly significant given the patient's history of multiple tumors, including Hodgkin's lymphoma, papillary thyroid carcinoma, prostate cancer, and SFT., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper{Citation}, (© 2024 The Authors.)

A patient with gastrointestinal stroma tumor (GIST) and KIT p.V559D and BRAF p.G469A alterations was referred to our institutional molecular tumor board (MTB) to discuss therapeutic implications. The patient had been diagnosed with B-cell chronic lymphocytic leukemia (CLL) years prior to the MTB presentation. GIST had been diagnosed 1 month earlier. After structured clinical annotation of the molecular alterations and interdisciplinary discussion, we considered BRAF/KIT co-mutation unlikely in a treatment-naïve GIST. Discordant variant allele frequencies furthermore suggested a second malignancy. NGS of a CLL sample revealed the identical class 2 BRAF alteration, thus supporting admixture of CLL cells in the paragastric mass, leading to the detection of 2 alterations. Following the MTB recommendation, the patient received imatinib and had a radiographic response. Structured annotation and interdisciplinary discussion in specialized tumor boards facilitate the clinical management of complex molecular findings. Coexisting malignancies and clonal hematopoiesis warrant consideration in case of complex and uncommon molecular findings., (© The Author(s) 2024. Published by Oxford University Press.)

Systemic mastocytosis is defined by the clonal proliferation of abnormal mast cells. The clinical course can range from indolent forms with normal life expectancy to advanced mast cell leukemia with dismal prognosis. An association with other diseases, including myeloproliferative neoplasia, has been described. We present a case of a 75-year patient with a history of cutaneous mastocytosis who was diagnosed with mast cell leukemia more than 9 years ago and did not receive treatment. The patient presented to our clinic with acute kidney failure because of renal extramedullary hematopoiesis. Bone marrow histopathology revealed extensive fibrosis and 50% infiltration by mast cells with a c -KIT D816V mutation. No mutations supporting primary myelofibrosis were identified. Treatment with midostaurin was started, and the patient was discharged after improvement of renal function. Here, we discuss diagnostic challenges between different forms of mast cell leukemia and overlaps with other hematological malignancies., Competing Interests: The authors declare that there are no conflicts of interest with regard to this manuscript., (Copyright © 2024 Damian T. Rieke et al.)

Background: The national Network Genomic Medicine (nNGM) Lung Cancer provides comprehensive and high-quality multiplex molecular diagnostics and standardized personalized treatment recommendation for patients with advanced non-small cell lung cancer (aNSCLC) in Germany. The primary aim of this study was to investigate the effectiveness of the nNGM precision medicine program in terms of overall survival (OS) using real-world data (RWD)., Methods: A historical nationwide cohort analysis of patients with aNSCLC and initial diagnosis between 04/2019 and 06/2020 was conducted to compare treatment and OS of patients with and without nNGM-participation. Patients participating within the nNGM (nNGM group) were selected based on a prospective nNGM database. The electronic health records (EHR) of the prospective nNGM database were case-specifically linked to claims data (AOK, German health insurance). The control group was selected from claims data of patients receiving usual care without nNGM-participation (non-nNGM group). The minimum follow-up period was six months., Findings: Overall, n = 509 patients in the nNGM group and n = 7213 patients in the non-nNGM group met the inclusion criteria. Patients participating in the nNGM had a significantly improved OS compared to the non-nNGM group (median OS: 10.5 months vs. 8.7 months, p  = 0.008, HR = 0.84, 95% CI: 0.74-0.95). The 1-year survival rates were 46.8% (nNGM) and 41.3% (non-nNGM). The use of approved tyrosine kinase inhibitors (TKI) in the first-line setting was significantly higher in the nNGM group than in the non-nNGM group (nNGM: 8.4% (43/509) vs. non-nNGM: 5.1% (366/7213), p  = 0.001). Overall, patients receiving first-line TKI treatment had significantly higher 1-year OS rates than patients treated with PD-1/PD-L1 inhibitors and/or chemotherapy (67.2% vs. 40.2%, p  < 0.001)., Interpretation: This is the first study to demonstrate a significant survival benefit and higher utilization of targeted therapies for aNSCLC patients participating within nNGM. Our data indicate that precision medicine programs can enhance collaborative personalized lung cancer care and promote the implementation of treatment innovations and the latest scientific knowledge into clinical routine care., Funding: The study was funded by the AOK Federal Association Germany., Competing Interests: AKä, nvdB, KM, and WH declare financial support from the Federal Association of the AOK, Berlin, Germany (e.g., for performing the analyses and writing the manuscript), as stated in the manuscript. MSche received institutional grants from Amgen, Bristol Myers Squibb, Dracen Pharmaceuticals Inc., Janssen, Novartis, Siemens Healthineers, personal consulting fees from Amgen, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Janssen, Novartis, Pfizer, Roche, Sanofi-Aventis, Siemens Healthineers and Takeda, honoraria or payment for educational events from Amgen, AstraZeneca, Bristol Myers Squibb, Novartis, Pfizer, Sanofi-Aventis and Takeda; received support for attending meetings and/or travel from Boehringer Ingelheim, Janssen, Pfizer, AstraZeneca; and reports participation on a Data Safety Monitoring Board at Boehringer Ingelheim, a leadership or fiduciary role (unpaid) at the ESMO Lung Cancer Faculty, ESMO Climate Change Task Force and the EORTC Lung Cancer group. DTR received payment or honoraria from Roche (Bristol Myers Squibb), Bayer and Lilly for lectures, presentations, speakers’ bureaus, manuscript writing or educational events and support for attending meetings and/or travel from Bayer. MSchu received institutional grants from AstraZeneca and Bristol Myers Squibb, consulting fees from Amgen, AstraZeneca, Blueprint Medicines, Boehringer Ingelheim, Bristol Myers Squibb, GlaxoSmithKline, Janssen, Merck Serono, Novartis, Roche, Sanofi-Aventis and Takeda, payment or honoraria from Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Janssen, Merck Sharp & Dohme, Novartis, Roche, Sanofi-Aventis for lectures, presentations, speakers’ bureaus, manuscript writing or educational events; received support for attending meetings and/or travel from Janssen, Bristol Myers Squibb, Roche, Boehringer Ingelheim, Novartis, Amgen; and participated in Data Safety Monitoring Boards or Advisory Boards at Amgen, Bristol-Myers Squibb, Novartis, Sanofi-Aventis, Janssen, Tacalyx, Abalos and GlaxoSmithKline. MW received institutional grants from Roche, personal consulting fees from Bristol Myers Squibb, Novartis, Lilly, Boehringer Ingelheim, Amgen, Immatics, Bayer and ImCheck Therapeutics, payment or honoraria for educational events from Lilly, Boehringer Ingelheim, SYNLAB, Janssen, Merck Serono, GWT-TUD GmbH, Amgen and Novartis; he received support for attending meetings and/or travel from Pfizer, Bristol Myers Squibb, AstraZeneca, Janssen, Amgen, GEMoaB, Sanofi-Aventis, Immatics, Merck Serono and Daiichi Sankyo and honoraria for participation in a Data Safety Monitoring Board or Advisory Board of ISA Pharmaceuticals. FK received payment or honoraria from Bristol-Myers Squibb, Merck Sharp & Dohme, Novartis, Roche, Lilly, Agilent, Bayer, Merck and Trillium for lectures, presentations, speakers’ bureaus, manuscript writing or educational events and is a board member at the National Pathologists’ Association Germany; and received personal honoraria for lectures by AstraZeneca and Novartis and participated in an advisory board by AstraZeneca. MSe received grants from AstraZeneca and consulting fees from AstraZeneca, Bristol Myers Squibb, Merck Sharp & Dohme, Novartis, Lilly, Roche, Boehringer Ingelheim, Amgen, Takeda, Johnson, Merck-Serono and GSK; received payment or honoraria from AstraZeneca, Bristol Myers Squibb, Merck Sharp & Dohme, Novartis, Lilly, Roche, Boehringer Ingelheim, Amgen, Takeda, Johnson, CureVac, BioNTech, Merck-Serono, GSK, Daiichi and Pfizer for lectures, presentations, speakers’ bureaus, manuscript writing or educational events; and received support for attending meetings and/or travel from Pfizer, Bristol-Myers Squibb and participated in a Data Safety Monitoring Board at Amgen. CB received consulting fees from the AOK NRW-Hamburg, and honoraria for participation in a Data Safety Monitoring Board or Advisory Board of AstraZeneca, Bayer Healthcare, Bristol Myers Squibb, Janssen-Cilag, Merck Serono and Sanofi-Aventis; received payment or honoraria for lectures given for Bristol Myers Squibb, Roche Pharma and Sanofi-Aventis; and received support for attending meetings and/or travel from Sanofi-Aventis, Janssen-Cilag and has an unpaid leadership or fiduciary role at DGHO, DKG-Zertifizierungskommission and CCC Netzwerk. RB received payment or honoraria for lectures and participation in advisory boards for AbbVie, Amgen, AstraZeneca, Bayer, Bristol-Myers Squibb, Boehringer Ingelheim, Illumina, Janssen, Lilly, Merck Serono, Merck Sharp & Dohme, Novartis, Qiagen, Pfizer, Roche and Targos MP Inc.; and reports a leadership or fiduciary role as co-founder and co-owner of Gnothis Inc (SE) and Timer Therapeutics Inc (GE). JW received funding from Amgen, AstraZeneca, Bayer, Blueprint, Bristol-Myers Squibb, Boehringer Ingelheim, Chugai, Daiichi Sankyo, Janssen, Lilly, Loxo, Merck, Mirati, Merck Sharp & Dohme, Novartis, Nuvalent, Pfizer, Pierre-Fabre, Roche, Seattle Genetics, Takeda and Turning Point. The remaining authors declare no conflict of interest., (© 2023 The Author(s).)

Importance: Clinical interpretation of complex biomarkers for precision oncology currently requires manual investigations of previous studies and databases. Conversational large language models (LLMs) might be beneficial as automated tools for assisting clinical decision-making., Objective: To assess performance and define their role using 4 recent LLMs as support tools for precision oncology., Design, Setting, and Participants: This diagnostic study examined 10 fictional cases of patients with advanced cancer with genetic alterations. Each case was submitted to 4 different LLMs (ChatGPT, Galactica, Perplexity, and BioMedLM) and 1 expert physician to identify personalized treatment options in 2023. Treatment options were masked and presented to a molecular tumor board (MTB), whose members rated the likelihood of a treatment option coming from an LLM on a scale from 0 to 10 (0, extremely unlikely; 10, extremely likely) and decided whether the treatment option was clinically useful., Main Outcomes and Measures: Number of treatment options, precision, recall, F1 score of LLMs compared with human experts, recognizability, and usefulness of recommendations., Results: For 10 fictional cancer patients (4 with lung cancer, 6 with other; median [IQR] 3.5 [3.0-4.8] molecular alterations per patient), a median (IQR) number of 4.0 (4.0-4.0) compared with 3.0 (3.0-5.0), 7.5 (4.3-9.8), 11.5 (7.8-13.0), and 13.0 (11.3-21.5) treatment options each was identified by the human expert and 4 LLMs, respectively. When considering the expert as a criterion standard, LLM-proposed treatment options reached F1 scores of 0.04, 0.17, 0.14, and 0.19 across all patients combined. Combining treatment options from different LLMs allowed a precision of 0.29 and a recall of 0.29 for an F1 score of 0.29. LLM-generated treatment options were recognized as AI-generated with a median (IQR) 7.5 (5.3-9.0) points in contrast to 2.0 (1.0-3.0) points for manually annotated cases. A crucial reason for identifying AI-generated treatment options was insufficient accompanying evidence. For each patient, at least 1 LLM generated a treatment option that was considered helpful by MTB members. Two unique useful treatment options (including 1 unique treatment strategy) were identified only by LLM., Conclusions and Relevance: In this diagnostic study, treatment options of LLMs in precision oncology did not reach the quality and credibility of human experts; however, they generated helpful ideas that might have complemented established procedures. Considering technological progress, LLMs could play an increasingly important role in assisting with screening and selecting relevant biomedical literature to support evidence-based, personalized treatment decisions.

Objectives: To identify prognostic factors for evidence-based risk stratification in malignant salivary gland tumors., Methods: This retrospective study identified 162 patients who presented with malignant salivary gland tumors between 2010 and 2020. Final analysis included 91 patients who underwent surgical treatment at our institution and were followed-up for ≥ 1 year. Medical records were reviewed and patients were categorized according to their risk profile., Results: This study included 91 patients (51 males, 40 females, mean age 61 years). The most frequent entities were adenoid cystic carcinoma (n = 13, 14.3%) and mucoepidermoid carcinoma (n = 12, 13.2%). Kaplan-Meier analysis demonstrated a five-year overall survival (OS) of 66.2% and a recurrence-free survival (RFS) of 50.5%. Age > 60 years (p = 0.011), categorization into high-risk group (p = 0.011), UICC stage (p = 0.020), T stage (p = 0.032), grading (p = 0.045) and vascular invasion (p < 0.001) were significantly associated with OS; age > 60 years (p = 0.014), categorization into high-risk group (p < 0.001), UICC stage (p = 0.021), T stage (p = 0.017), grading (p = 0.011), vascular invasion (p = 0.012) and lymphovascular invasion (p < 0.001) were significantly associated with RFS. Multivariate Cox regression with backward elimination identified T stage (HR 1.835; 95% CI 1.187-2.836; p = 0.006) and grading (HR 2.233; 95% CI 1.113-4.480; p = 0.024) as significant factors for OS. Grading (HR 2.499; 95% CI 1.344-4.648; p = 0.004) was confirmed as a significant factor for RFS., Conclusion: Considering the risk of recurrence and distant metastasis in malignant salivary gland tumors, locoregional surgical control may not be sufficient and adjuvant therapies such as radiotherapy and/or systemic therapies should be considered., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: The impact of tumour mutational burden (TMB) on outcome with molecularly matched therapy is unknown. Higher TMB could predict resistance to molecularly matched therapy through co-occurring driver mutations., Methods: One hundred and four patients with advanced cancers underwent molecular profiling in the DKTK-MASTER program. Fifty-five patients received systemic therapy excluding immunotherapy. Patients with molecularly matched (n = 35) or non-molecularly informed therapy (n = 20) were analysed for TMB and survival. Results were validated in an independent cohort of patients receiving molecularly matched (n = 68) or non-molecularly informed therapy (n = 40). Co-occurring driver mutations and TMB were analysed in the exploratory cohort and The Cancer Genome Atlas (TCGA) datasets., Results: Patients were stratified by the median TMB of 1.67 mutations per Megabase (mut/Mb) of 35 patients receiving molecularly matched therapy into TMB-high or TMB-low groups. Median overall survival (4 months [95% CI, 3.3-7.6] versus 12.8 months [95% CI, 10-not reached], p < 0.001) and progression-free survival (1.8 months [95% CI, 1.1-3.7] versus 7.9 months [95% CI, 2.8-17.0], p = 0.003) were significantly shorter in the TMB-high group compared to the TMB-low group. In the validation cohort, shorter OS and PFS were identified in the TMB-high group (TMB cut-off of 4 mut/Mb) treated with molecularly matched therapy. No differences were observed in patients receiving non-molecularly informed systemic therapy. A significant correlation between co-occurring driver mutations and TMB (n = 104, r = 0.78 [95% CI, 0.68-0.85], p < 0.001) was found in the exploratory cohort as well as the majority (24/33) of TCGA studies., Conclusion: A high TMB was associated with unfavourable outcome in patients receiving molecularly matched therapy, indicating untargeted resistance pathways. Therefore, TMB should be further investigated as a predictive biomarker in precision oncology programs., Competing Interests: Declaration of Competing Interest Till de Bortoli, Manuela Benary, Mario Lamping, Reinhold Schäfer and Frederick Klauschen report no potential conflicts of interest. Peter Horak reported consulting or advisory board membership for Platomics and honoraria from Platomics, Roche. Sebastian Stintzing has received honoraria/consulting or advisory role from Amgen, Bayer, Lilly, Merck KGaA, MSD, Pierre Fabre, Roche, Sanofi, Servier, Taiho Pharmaceuticals, Takeda, Boehringer Ingelheim, research funding from Merck Serono, Pierre Fabre, Roche Molecular Diagnostics, travel, accommodation and expenses support from Amgen, Bayer, Lilly, Merck KgaA, Pierre Fabre, Roche, Sanofi, Sirtex Medical and Takeda. Inge Tinhofer reports honoraria/consulting or advisory role for Merck KgaA and MerckSerono. Serge Leyvraz reports consulting or advisory role and travel expenses support from Bayer. Ulrich Keller reports a consulting role for Roche, Janssen-Cilag, Takeda, BMS, Gilead, Hexal, Pfizer, Astra-Zeneca, Pentixapharm and honoraria from Gilead, Amgen, Novartis, BMS, Roche, Takeda, MSD, as well as research funding from Celgene, Takeda, BMS, Roche, Astra-Zeneka, Novartis, MSD, Janssen-Cilag, Pfizer. Other support was declared from Roche, BMS, Gilead, Takeda, Janssen-Cilag and Celgene. Albrecht Stenzinger reported Advisory Board/Speaker’s Bureau from Aignostics, Astra Zeneca, AGCT, Bayer, BMS, Eli Lilly, Illumina, Incyte, Janssen, MSD, Novartis, Pfizer, Roche, Seattle Genetics, Takeda, Thermo Fisher and research grants from Bayer, BMS, Chugai, Incyte. Stefan Fröhling reported consulting or advisory board membership from Bayer, Illumina, Roche; honoraria: Amgen, Eli Lilly, PharmaMar, Roche and research funding from AstraZeneca, Pfizer, PharmaMar, Roche, as well as travel or accommodation expenses support from Amgen, Eli Lilly, Illumina, PharmaMar, Roche. Razelle Kurzrock has received research funding from Biological Dynamics, Boehringer Ingelheim, Debiopharm, Foundation Medicine, Genentech, Grifols, Guardant, Incyte, Konica Minolta, Medimmune, Merck Serono, Omniseq, Pfizer, Sequenom, Takeda, and TopAlliance; as well as consultant and/or speaker fees and/or advisory board for Actuate Therapeutics, AstraZeneca, Bicara Therapeutics, Biological Dynamics, EISAI, EOM Pharmaceuticals, Iylon, Merck, NeoGenomics, Neomed, Pfizer, Prosperdtx, Roche, TD2/Volastra, Turning Point Therapeutics, X-Biotech and has an equity interest in CureMatch Inc., CureMetrix, and IDbyDNA; She also serves on the Board of CureMatch and CureMetrix,and is a co-founder of CureMatch. Ulrich Keilholz has received advisory board/speaker bureau, trial support, research collaboration or research support from Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Glycotope, Innate, Lilly, Medimmune, MerckSerono, MSD/Merck, Novartis, Pfizer, Roche/Genentech and Sirtex. Damian Rieke has received consultant and/or advisory board and/or speaker fees from Bayer, Bristol-Myers Squibb and Lilly. Ivan Jelas has received consultant and/or advisory board and/or speaker fees from Bristol-Myers Squibb, Merck and Roche., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background and Purpose: A subgroup of salivary duct carcinoma (SDC) harbor overexpression of the androgen receptor (AR), and co-occurring mutations in the HRAS - and PIK3CA -genes. The impact of genomic complexity on targeted treatment strategies in advanced cancer is unknown., Materials and Methods: We analyzed molecular and clinical data from an institutional molecular tumor board (MTB) to identify AR+, HRAS / PIK3CA co-mutated SDC. Follow-up was performed within the MTB registrational study or retrospective chart review after approval by the local ethics committee. Response was assessed by the investigator. A systematic literature search was performed in MEDLINE to identify additional clinically annotated cases., Results: 4 patients with AR+ HRAS / PIK3CA co-mutated SDC and clinical follow-up data were identified from the MTB. An additional 9 patients with clinical follow-up were identified from the literature. In addition to AR overexpression and HRAS and PIK3CA -alterations, PD-L1 expression and Tumor Mutational Burden > 10 Mutations per Megabase were identified as additional potentially targetable alterations. Among evaluable patients, androgen deprivation therapy (ADT) was initiated in 7 patients (1 Partial Response (PR), 2 Stable Disease (SD), 3 Progressive Disease (PD), 2 not evaluable), tipifarnib was initiated in 6 patients (1 PR, 4 SD, 1 PD). One patient each was treated with immune checkpoint inhibition (Mixed Response) and combination therapies of tipifarnib and ADT (SD) and alpelisib and ADT (PR)., Conclusion: Available data further support comprehensive molecular profiling of SDC. Combination therapies, PI3K-inhibitors and immune therapy warrant further investigation, ideally in clinical trials. Future research should consider this rare subgroup of SDC., Competing Interests: DR has received consultant and/or advisory board and/or speaker fees from Roche, Bayer, Bristol-Myers Squibb and Lilly. PS has received honoraria personal from BMS, MSD, Incyte, SOBI, AOP, Novartis, Alexion, AstraZeneca, BPM, and ROCHE and travel support from BMS, SOBI, AOP, and Novartis. UK 8th Author reports a consulting role for Roche, Janssen-Cilag, Takeda, BMS, Gilead, Hexal, Pfizer, Astra-Zeneca, Pentixapharm and honoraria from Gilead, Amgen, Novartis, BMS, Roche, Takeda, MSD, as well as research funding from Celgene, Takeda, BMS, Roche, Astra-Zeneca, Novartis, MSD, Janssen-Cilag, Pfizer. Other support was declared from Roche, BMS, Gilead, Takeda, Janssen-Cilag and Celgene. UK 9th Author has received advisory board/speaker bureau, trial support, research collaboration or research support from Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Glycotope, Innate, Lilly, Medimmune, MerckSerono, MSD/Merck, Novartis, Pfizer, Roche/Genentech and Sirtex. KK: Advisory Boards, travel grants and speaker’s fees: MSD, BMS, Merck, Novartis, Bayer. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Rieke, Schröder, Schafhausen, Blanc, Zuljan, von der Emde, Beule, Keller, Keilholz and Klinghammer.)

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC's functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: Structured and harmonized implementation of molecular tumor boards (MTB) for the clinical interpretation of molecular data presents a current challenge for precision oncology. Heterogeneity in the interpretation of molecular data was shown for patients even with a limited number of molecular alterations. Integration of high-dimensional molecular data, including RNA- (RNA-Seq) and whole-exome sequencing (WES), is expected to further complicate clinical application. To analyze challenges for MTB harmonization based on complex molecular datasets, we retrospectively compared clinical interpretation of WES and RNA-Seq data by two independent molecular tumor boards., Methods: High-dimensional molecular cancer profiling including WES and RNA-Seq was performed for patients with advanced solid tumors, no available standard therapy, ECOG performance status of 0-1, and available fresh-frozen tissue within the DKTK-MASTER Program from 2016 to 2018. Identical molecular profiling data of 40 patients were independently discussed by two molecular tumor boards (MTB) after prior annotation by specialized physicians, following independent, but similar workflows. Identified biomarkers and resulting treatment options were compared between the MTBs and patients were followed up clinically., Results: A median of 309 molecular aberrations from WES and RNA-Seq (n = 38) and 82 molecular aberrations from WES only (n = 3) were considered for clinical interpretation for 40 patients (one patient sequenced twice). A median of 3 and 2 targeted treatment options were identified per patient, respectively. Most treatment options were identified for receptor tyrosine kinase, PARP, and mTOR inhibitors, as well as immunotherapy. The mean overlap coefficient between both MTB was 66%. Highest agreement rates were observed with the interpretation of single nucleotide variants, clinical evidence levels 1 and 2, and monotherapy whereas the interpretation of gene expression changes, preclinical evidence levels 3 and 4, and combination therapy yielded lower agreement rates. Patients receiving treatment following concordant MTB recommendations had significantly longer overall survival than patients receiving treatment following discrepant recommendations or physician's choice., Conclusions: Reproducible clinical interpretation of high-dimensional molecular data is feasible and agreement rates are encouraging, when compared to previous reports. The interpretation of molecular aberrations beyond single nucleotide variants and preclinically validated biomarkers as well as combination therapies were identified as additional difficulties for ongoing harmonization efforts., (© 2022. The Author(s).)

Background: Targeted therapies for metastatic uveal melanoma have shown limited benefit in biomarker-unselected populations. The Treat20 Plus study prospectively evaluated the feasibility of a precision oncology strategy in routine clinical practice., Patients and Methods: Fresh biopsies were analyzed by high-throughput genomics (whole-genome, whole-exome, and RNA sequencing). A multidisciplinary molecular and immunologic tumor board (MiTB) made individualized treatment recommendations based on identified molecular aberrations, patient situation, drug, and clinical trial availability. Therapy selection was at the discretion of the treating physician. The primary endpoint was the feasibility of the precision oncology clinical program., Results: Molecular analyses were available for 39/45 patients (87%). The MiTB provided treatment recommendations for 40/45 patients (89%), of whom 27/45 (60%) received ≥1 matched therapy. First-line matched therapies included MEK inhibitors (n = 15), MET inhibitors (n = 10), sorafenib (n = 1), and nivolumab (n = 1). The best response to first-line matched therapy was partial response in one patient (nivolumab based on tumor mutational burden), mixed response in two patients, and stable disease in 12 patients for a clinical benefit of 56%. The matched therapy population had a median progression-free survival and overall survival of 3.3 and 13.9 months, respectively. The growth modulation index with matched therapy was >1.33 in 6/17 patients (35%) with prior systemic therapy, suggesting clinical benefit., Conclusions: A precision oncology approach was feasible for patients with metastatic uveal melanoma, with 60% receiving a therapy matched to identify molecular aberrations. The clinical benefit after checkpoint inhibitors highlights the value of tumor mutational burden testing., Competing Interests: Conflict of interest statement SL reports travel and advisory board support from Immunocore and Bayer. CP reports speaker honoraria from Bristol-Myers Squibb, Novartis, Daiichi-Sankyo, EUSA Pharma and Sirtex Medical and advisory honoraria from EUSA Pharma. MS is employee of Alacris Theranostics. TK is employee of Alacris Theranostics. SO reports consultancy fees from Astra Zeneca, Bristol-Myers Squibb, Janssen Biotech, Merck. DTR reports Honoraria from Lilly, Bristol-Myers Squibb and Advisory Honoraria from Bayer and Alacris Theranostics. KK reports advisory board and conference honoraria from Merck, Sanofi, Merck Sharp & Dohme, Glycotope, Roche, Novartis and Bristol-Myers Squibb. CU reports consulting fees from Sanofi, grant for educational activities form Galderma, Beiresdorf and Almirall. GP reports consulting fees and grant for educational activities from Amgen. Novartis, Sun Pharma. Bristol-Myers Squibb, Merck Sharp & Dohme. FK is co-founder of Aignostics GmbH and has received consulting support from Roche, Novartis, Bristol-Myers Squibb, Lilly, Agilent and Iomedico. AJ reports Consultant fees from Novartis, Roche, Boehringer, Allergan, Bayer. MLY is an employee and shareholder of Alacris Theranostics. UK reports consulting fees for Merck Sharp & Dohme, travel support from Merck Serono, Pfizer, grant for educational activities from Merck Serono, Bristol-Myers Squibb, Pierre-Fabre. FK, MD, ES, GD, ML, SB, RS have no conflict of interest., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objective: We present the Berlin-Tübingen-Oncology corpus (BRONCO), a large and freely available corpus of shuffled sentences from German oncological discharge summaries annotated with diagnosis, treatments, medications, and further attributes including negation and speculation. The aim of BRONCO is to foster reproducible and openly available research on Information Extraction from German medical texts., Materials and Methods: BRONCO consists of 200 manually deidentified discharge summaries of cancer patients. Annotation followed a structured and quality-controlled process involving 2 groups of medical experts to ensure consistency, comprehensiveness, and high quality of annotations. We present results of several state-of-the-art techniques for different IE tasks as baselines for subsequent research., Results: The annotated corpus consists of 11 434 sentences and 89 942 tokens, annotated with 11 124 annotations for medical entities and 3118 annotations of related attributes. We publish 75% of the corpus as a set of shuffled sentences, and keep 25% as held-out data set for unbiased evaluation of future IE tools. On this held-out dataset, our baselines reach depending on the specific entity types F1-scores of 0.72-0.90 for named entity recognition, 0.10-0.68 for entity normalization, 0.55 for negation detection, and 0.33 for speculation detection., Discussion: Medical corpus annotation is a complex and time-consuming task. This makes sharing of such resources even more important., Conclusion: To our knowledge, BRONCO is the first sizable and freely available German medical corpus. Our baseline results show that more research efforts are necessary to lift the quality of information extraction in German medical texts to the level already possible for English., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Immune checkpoint inhibition leads to response in some patients with head and neck squamous cell carcinoma (HNSCC). Robust biomarkers are lacking to date. We analyzed viral status, gene expression signatures, mutational load and mutational signatures in whole exome and RNA-sequencing data of the HNSCC TCGA dataset (n = 496) and a validation set (DKTK MASTER cohort, n = 10). Public single-cell gene expression data from 17 HPV-negative HNSCC were separately reanalyzed. APOBEC3-associated TCW motif mutations but not total single nucleotide variant burden were significantly associated with inflammation. This association was restricted to HPV-negative HNSCC samples. An APOBEC-enriched, HPV-negative subgroup was identified, that showed higher T-cell inflammation and immune checkpoint expression, as well as expression of APOBEC3 genes. Mutations in immune-evasion pathways were also enriched in these tumors. Analysis of single-cell sequencing data identified expression of APOBEC3B and 3C genes in malignant cells. We identified an APOBEC-enriched subgroup of HPV-negative HNSCC with a distinct immunogenic phenotype, potentially mediating response to immunotherapy., (© 2020 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

Background: Reliable and reproducible interpretation of molecular aberrations constitutes a bottleneck of precision medicine. Evidence-based decision management systems may improve rational therapy recommendations. To cope with an increasing amount of complex molecular data in the clinical care of patients with cancer, we established a workflow for the interpretation of molecular analyses., Methods: A specialized physician screened results from molecular analyses for potential biomarkers, irrespective of the diagnostic modality. Best available evidence was retrieved and categorized through establishment of an in-house database and interrogation of publicly available databases. Annotated biomarkers were ranked using predefined evidence levels and subsequently discussed at a molecular tumour board (MTB), which generated treatment recommendations. Subsequent translation into patient treatment and clinical outcomes were followed up., Results: One hundred patients were discussed in the MTB between January 2016 and May 2017. Molecular data were obtained for 70 of 100 patients (50 whole exome/RNA sequencing, 18 panel sequencing, 2 immunohistochemistry (IHC)/microsatellite instability analysis). The MTB generated a median of two treatment recommendations each for 63 patients. Thirty-nine patients were treated: 6 partial responses and 12 stable diseases were achieved as best responses. Genetic counselling for germline events was recommended for seven patients., Conclusion: The development of an evidence-based workflow allowed for the clinical interpretation of complex molecular data and facilitated the translation of personalized treatment strategies into routine clinical care. The high number of treatment recommendations in patients with comprehensive genomic data and promising responses in patients treated with combination therapy warrant larger clinical studies., Competing Interests: Conflict of interest statement M.L., M.B., C.M., E.B., K.J., S.B., K.K., S.O., R.S., and F.K. reported no conflicts of interest. S.L. received support and consulting compensation from Bayer. M.L.Y., T.K. and M.S. are employees of Alacris Theranostics. D.L. is currently an employee of AstraZeneca and reported employment, stock ownership and patents/royalties/intellectual property for her spouse at Bayer. C.S. received honoraria from Merck Serono, I.T. took part in an advisory board by Merck Serono. D.B. is a shareholder of MicroDiscovery GmbH. U.K. reported research funding from Merck Sharp & Dohme, Novartis, Bristol-Myers Squibb, Roche, GlaxoSmithKline, AstraZeneca and Merck Serono and served as a consultant or as a member of the advisory board with Merck Sharp & Dohme, Bristol-Myers Squibb, AstraZeneca, Merck Serono and GlaxoSmithKline. D.T.R. received payments as a consultant for Alacris Theranostics and honoraria from Bristol-Myers Squibb., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Purpose: Rapidly evolving genomics technologies, in particular comprehensive next-generation sequencing (NGS), have led to exponential growth in the understanding of cancer biology, shifting oncology toward personalized treatment strategies. However, comprehensive NGS approaches, such as whole-exome sequencing, have limitations that are related to the technology itself as well as to the input source. Hence, clinical implementation of comprehensive NGS in a quality-controlled diagnostic workflow requires both the standardization of sequencing procedures and continuous validation of sequencing results by orthogonal methods in an ongoing program to enable the determination of key test parameters and continuous improvement of NGS and bioinformatics pipelines., Patients and Methods: We present validation data on 220 patients who were enrolled between 2013 and 2016 in a multi-institutional, genomics-guided precision oncology program (Molecularly Aided Stratification for Tumor Eradication Research) of the National Center for Tumor Diseases Heidelberg and the German Cancer Consortium., Results: More than 90% of clinically actionable genomic alterations identified by combined whole-exome sequencing and transcriptome sequencing were successfully validated, with varying frequencies of discordant results across different types of alterations (fusions, 3.7%; single-nucleotide variants, 2.6%; amplifications, 1.1%; overexpression, 0.9%; deletions, 0.6%). The implementation of new computational methods for NGS data analysis led to a substantial improvement of gene fusion calling over time., Conclusion: Collectively, these data demonstrate the value of a rigorous validation program that partners with comprehensive NGS to successfully implement and continuously improve cancer precision medicine in a clinical setting.

Purpose: Precision oncology holds the promise of improving patient outcome. It is based on the idea that the testing of genomic biomarkers can lead to the recommendation of a treatment option tailored to the specific patient. To derive treatment recommendations from molecular profiles, interdisciplinary molecular tumor boards (MTBs) have been established recently in many academic institutions. The recommendation process in MTBs, however, has not been well defined, which limits applicability to larger clinical trials and patient populations., Methods: We created four fictional patients on the basis of recent real cases with genomic information on mutations, fusions, copy numbers, and gene expression. We identified 29 tumor boards from nine countries worldwide and asked them to provide treatment recommendations for the sample patients. In addition, a questionnaire regarding the setup and methods used by MTBs was circulated., Results: Five MTBs from four countries provided treatment recommendations and answered the questionnaire. For one patient, three tumor board treatment recommendations were identical, and two tumor boards had identical treatment strategies for the other three patients. There was heterogeneity in the interpretation of tumor and germline aberrations as well as in standards of prioritization., Conclusion: Differences in the interpretation and recommendation process contribute to heterogeneity in MTB recommendations. Additional comparative analyses of recommendations could help improve rational decision making and lead to standardization.

Recurrent or metastatic head and neck cancer describes tumor deposits that arise locally, regionally, or at distant sites after treatment or distant metastases at the time of primary diagnosis. Prognosis for R/M squamous cell carcinomas of the head and neck (HNSCC) is poor and treatment options are limited in this situation. Human papillomavirus (HPV) is an important risk factor for HNSCC. About 40 % of all HNSCC have been attributed to HPV in Europe. HPV positivity at initial diagnosis is the single best prognostic factor for survival. However, data for the prognostic and predictive value of HPV in the R/M situation are still scarce. Due to the rising incidence of HPV-associated cancers, the number of R/M HPV+ carcinomas is also expected to rise. This chapter therefore aims to give an overview of the current knowledge concerning the role of HPV as a prognostic and predictive marker in recurrent or metastatic HNSCC.

Every tumour is different. They arise in patients with different genomes, from cells with different epigenetic modifications, and by random processes affecting the genome and/or epigenome of a somatic cell, allowing it to escape the usual controls on its growth. Tumours and patients therefore often respond very differently to the drugs they receive. Cancer precision medicine aims to characterise the tumour (and often also the patient) to be able to predict, with high accuracy, its response to different treatments, with options ranging from the selective characterisation of a few genomic variants considered particularly important to predict the response of the tumour to specific drugs, to deep genome analysis of both tumour and patient, combined with deep transcriptome analysis of the tumour. Here, we compare the expected results of carrying out such analyses at different levels, from different size panels to a comprehensive analysis incorporating both patient and tumour at the DNA and RNA levels. In doing so, we illustrate the additional power gained by this unusually deep analysis strategy, a potential basis for a future precision medicine first strategy in cancer drug therapy. However, this is only a step along the way of increasingly detailed molecular characterisation, which in our view will, in the future, introduce additional molecular characterisation techniques, including systematic analysis of proteins and protein modification states and different types of metabolites in the tumour, systematic analysis of circulating tumour cells and nucleic acids, the use of spatially resolved analysis techniques to address the problem of tumour heterogeneity as well as the deep analyses of the immune system of the patient to, e.g., predict the response of the patient to different types of immunotherapy. Such analyses will generate data sets of even greater complexity, requiring mechanistic modelling approaches to capture enough of the complex situation in the real patient to be able to accurately predict his/her responses to all available therapies., (© 2017 S. Karger AG, Basel.)

Immune checkpoints are emerging treatment targets, but mechanisms underlying checkpoint expression are poorly understood. Since alterations in DNA repair genes have been connected to the efficacy of checkpoint inhibitors, we investigated associations between methylation of DNA repair genes and CTLA4 and CD274 (PD-L1) expression.A list of DNA repair genes (179 genes) was selected from the literature, methylation status and expression of inflammation-associated genes (The Cancer Genome Atlas data) was correlated in head and neck squamous cell carcinoma (HNSCC), cervical and lung squamous cell carcinoma.A significant positive correlation of the methylation status of 15, 3 and 2 genes with checkpoint expression was identified, respectively. RAD51B methylation was identified in all cancer subtypes. In HNSCC and cervical cancer, there was significant enrichment for homologous recombination genes. Methylation of the candidate genes was also associated with expression of other checkpoints, ligands, MHC- and T-cell associated genes as well as an interferon-inflammatory immune gene signature, predictive for the efficacy of PD-1 inhibition in HNSCC.Homologous recombination deficiency might therefore be mediated by DNA repair gene hypermethylation and linked to an immune-evasive phenotype in SCC. The methylation status of these genes could represent a new predictive biomarker for immune checkpoint inhibition.

Head and neck squamous cell carcinoma (HNSCC) is one of the most common solid cancers worldwide. It is mainly caused by exposure to tobacco smoke and alcohol as well as infection with the human papilloma virus (HPV). The prognosis is poor, especially once it recurs or metastasizes. Current therapeutic options include surgery, radio- and chemotherapy. Epidermal growth factor receptor (EGFR) inhibitors are so far the only targeted agents that have been approved in head and neck cancer. Primary or secondary resistance is frequent or will eventually develop. Several driver mutations and other genomic aberrations have been described in HNSCC including EGFR overexpression and amplification. Yet, no predictive biomarkers for the application of EGFR inhibitors have been identified. Further targeted agents are in development for HNSCC, of which inhibitors of the PI3K pathway are the closest to clinical application. In recent years, the incidence of HPV-driven HNSCC has risen in Western countries. HPV-positive and -negative HNSCC are distinct molecular tumor entities, and consequences for targeted therapies have been discussed. This review looks at approved and investigational targeted treatment strategies as well as potential predictive biomarkers such as the HPV status to guide treatment., (© 2016 S. Karger GmbH, Freiburg.)