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Introduction: Whole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis., Methods: To assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics. Somatic and germline variants, copy-number alterations (CNAs), and complex biomarkers were investigated. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. The raw data were collected and re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability., Results: The mean positive percentage agreement (PPA) of somatic variant calling was 76 % while the positive predictive value (PPV) was 89 % in relation to a consensus list of variants found by at least five centers. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 88 % for all and 97 % for the clinically relevant variants. CNA calls were concordant for 82 % of genomic regions. Homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94 %, 93 %, and 93 % of calls, respectively. Variability of CNAs and complex biomarkers did not decrease considerably after harmonization of the bioinformatic processing and was hence attributed mainly to wet-lab differences., Conclusion: Continuous optimization of bioinformatic workflows and participating in round robin tests are recommended., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: MMT reports speaker and travel Expenses from Twist. JS reports speaker honoraria from DLS, Molecular Health, AstraZeneca and Biocartis, outside the submitted work. UL reports speaker fees from AstraZeneca, GSK, Novartis, Menarini, advisory board from AstraZeneca and Novartis. DH reports speaker honorary AstraZeneca, adboard BMS, WD speaker honoraries BMS & Novartis. SMB reports speaker honoraria, advisory board fees and research grants from AstraZeneca, Daiichi, Menarini, Novartis, Roche, BMS, Pfizer, Bayer, MSD, Merck, Amgen, Molecular Health, Targos, DLS, Janssen, GSK, QuIP, outside the submitted work. SL reports research grant from BMS, advisory board/speaker invitation from AstraZeneca, Eli Lilly, Roche and Takeda outside of this work. NTG reports research support from Janssen-Cilag and Advisory Boards from Janssen-Cilag, AstraZeneca, Daiichi-Sankyo and BMS outside the submitted work. WW reports research grants from Roche, MSD, BMS and AstraZeneca. Advisory board, lectures and speaker bureau fees from Roche, MSD, BMS, AstraZeneca, Pfizer, Merck, Lilly, Boehringer, Novartis, Takeda, Bayer, Janssen, Amgen, Astellas, Illumina, Eisai, Siemens, Agilent, ADC, GSK und Molecular Health. SO received reimbursement for travel expenses and payment for conference presentations from Illumina Inc. and Oxford Nanopore Technologies. CS reports research funding from BMS Stiftung Immunonkologie and institutional grants from Illumina outside the submitted work. CPS reports an investigator-initiated grant from Illumnia outside of the submitted work. PS reports grants from Inctye, BMS, Gilead, Falk, speakers bureau/advisory board from MSD, BMS, AstraZeneca, Incyte, Astellas, Janssen, Eisai, Amgen, Boehringer Ingelheim. DK reports personal fees for speaker honoraria from AstraZeneca, and Pfizer, personal fees for Advisory Board from Bristol-Myers Squibb, outside the submitted work. NP reports speaker fees from Novartis, Bayer, Roche, AstraZeneca, Illumina, BMS, MSD, PGDX/Labcorp, advisory board from Novartis, Lilly, Roche, Janssen, travel expenses from Novartis, AstraZeneca, Illumina, BMS, MSD, PGDX/Labcorp, Research grants from Illumina. JB reports grants from German Cancer Aid and consulting from MSD, outside the submitted work. AS reports participation in Advisory Board/Speaker’s Bureau for Astra Zeneca, AGCT, Bayer, Bristol-Myers Squibb, Eli Lilly, Illumina, Janssen, MSD, Novartis, Pfizer, Roche, Seattle Genetics, Takeda, and Thermo Fisher, grants from Bayer, Bristol-Myers Squibb, and Chugai, outside the submitted work. All other authors report no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Programmed death-ligand 1 expression currently represents the only validated predictive biomarker for immune checkpoint inhibition in metastatic NSCLC in the clinical routine, but it has limited value in distinguishing responses. Assessment of KRAS and TP53 mutations (mut) as surrogate for an immunosupportive tumor microenvironment (TME) might help to close this gap., Methods: A total of 696 consecutive patients with programmed death-ligand 1-high (≥50%), nonsquamous NSCLC, having received molecular testing within the German National Network Genomic Medicine Lung Cancer between 2017 and 2020, with Eastern Cooperative Oncology Group performance status less than or equal to 1 and pembrolizumab as first-line palliative treatment, were included into this retrospective cohort analysis. Treatment efficacy and outcome according to KRAS/TP53 status were correlated with TME composition and gene expression analysis of The Cancer Genome Atlas lung adenocarcinoma cohort., Results: Proportion of KRASmut and TP53mut was 53% (G12C 25%, non-G12C 28%) and 51%, respectively. In KRASmut patients, TP53 comutations increased response rates (G12C: 69.7% versus 46.5% [TP53mut versus wild-type (wt)], p = 0.004; non-G12C: 55.4% versus 39.5%, p = 0.03), progression-free survival (G12C: hazard ratio [HR] = 0.59, p = 0.009, non-G12C: HR = 0.7, p = 0.047), and overall survival (G12C: HR = 0.72, p = 0.16, non-G12C: HR = 0.56, p = 0.002), whereas no differences were observed in KRASwt patients. After a median follow-up of 41 months, G12C/TP53mut patients experienced the longest progression-free survival and overall survival (33.7 and 65.3 mo), which correlated with high tumor-infiltrating lymphocyte densities in the TME and up-regulation of interferon gamma target genes. Proinflammatory pathways according to TP53 status (mut versus wt) were less enhanced and not different in non-G12C and KRASwt, respectively., Conclusions: G12C/TP53 comutations identify a subset of patients with a very favorable long-term survival with immune checkpoint inhibitor monotherapy, mediated by highly active interferon gamma signaling in a proinflammatory TME., (Copyright © 2023 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Objective: The objective was to develop a dataset definition, information model, and FHIR® specification for key data elements contained in a German molecular genomics (MolGen) report to facilitate genomic and phenotype integration in electronic health records., Materials and Methods: A dedicated expert group participating in the German Medical Informatics Initiative reviewed information contained in MolGen reports, determined the key elements, and formulated a dataset definition. HL7's Genomics Reporting Implementation Guide (IG) was adopted as a basis for the FHIR® specification which was subjected to a public ballot. In addition, elements in the MolGen dataset were mapped to the fields defined in ISO/TS 20428:2017 standard to evaluate compliance., Results: A core dataset of 76 data elements, clustered into 6 categories was created to represent all key information of German MolGen reports. Based on this, a FHIR specification with 16 profiles, 14 derived from HL7®'s Genomics Reporting IG and 2 additional profiles (of the FamilyMemberHistory and RiskAssessment resources), was developed. Five example resource bundles show how our adaptation of an international standard can be used to model MolGen report data that was requested following oncological or rare disease indications. Furthermore, the map of the MolGen report data elements to the fields defined by the ISO/TC 20428:2017 standard, confirmed the presence of the majority of required fields., Conclusions: Our report serves as a template for other research initiatives attempting to create a standard format for unstructured genomic report data. Use of standard formats facilitates integration of genomic data into electronic health records for clinical decision support., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Recent molecular profiling studies reported a new class of ultramutated colorectal cancers (CRCs), which are caused by exonuclease domain mutations (EDMs) in DNA polymerase ϵ (POLE). Data on the clinical implications of these findings as to whether these mutations define a unique CRC entity with distinct clinical outcome are lacking. We performed Sanger sequencing of the POLE exonuclease domain in 431 well-characterized patients with microsatellite stable (MSS) CRCs of a population-based patient cohort. Mutation data were analyzed for associations with major epidemiological, clinical, genetic, and pathological parameters including overall survival (OS) and disease-specific survival (DSS). In 373 of 431 MSS CRC, all exons of the exonuclease domain were analyzable. Fifty-four mutations were identified in 46 of these samples (12.3%). Besides already reported EDMs, we detected many new mutations in exons 13 and 14 (corresponding to amino acids 410-491) as well as in exon 9 and exon 11 (corresponding to aa 268-303 and aa 341-369). However, we did not see any significant associations of EDMs with clinicopathological parameters, including sex, age, tumor location and tumor stage, CIMP, KRAS, and BRAF mutations. While with a median follow-up time of 5.0 years, survival analysis of the whole cohort revealed nonsignificantly different adjusted hazard ratios (HRs) of 1.35 (95% CI: 0.82-2.25) and 1.44 (0.81-2.58) for OS and DSS indicating slightly impaired survival of patients with EDMs, subgroup analysis for patients with stage III/IV disease receiving chemotherapy revealed a statistically significantly increased adjusted HR (1.87; 95%CI: 1.02-3.44). In conclusion, POLE EDMs do not appear to define an entirely new clinically distinct disease entity in CRC but may have prognostic or predictive implications in CRC subgroups, whose significance remains to be investigated in future studies., (© 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Autopsy rates in Western countries consistently decline to an average of <5%, although clinical autopsies represent a reasonable tool for quality control in hospitals, medically and economically. Comparing pre- and postmortal diagnoses, diagnostic discrepancies as uncovered by clinical autopsies supply crucial information on how to improve clinical treatment. The study aimed at analyzing current diagnostic discrepancy rates, investigating their influencing factors and identifying risk profiles of patients that could be affected by a diagnostic discrepancy., Methods and Findings: Of all adult autopsy cases of the Charité Institute of Pathology from the years 1988, 1993, 1998, 2003 and 2008, the pre- and postmortal diagnoses and all demographic data were analyzed retrospectively. Based on power analysis, 1,800 cases were randomly selected to perform discrepancy classification (class I-VI) according to modified Goldman criteria. The rate of discrepancies in major diagnoses (class I) was 10.7% (95% CI: 7.7%-14.7%) in 2008 representing a reduction by 15.1%. Subgroup analysis revealed several influencing factors to significantly correlate with the discrepancy rate. Cardiovascular diseases had the highest frequency among class-I-discrepancies. Comparing the 1988-data of East- and West-Berlin, no significant differences were found in diagnostic discrepancies despite an autopsy rate differing by nearly 50%. A risk profile analysis visualized by intuitive heatmaps revealed a significantly high discrepancy rate in patients treated in low or intermediate care units at community hospitals. In this collective, patients with genitourinary/renal or infectious diseases were at particularly high risk., Conclusions: This is the current largest and most comprehensive study on diagnostic discrepancies worldwide. Our well-powered analysis revealed a significant rate of class-I-discrepancies indicating that autopsies are still of value. The identified risk profiles may aid both pathologists and clinicians to identify patients at increased risk for a discrepant diagnosis and possibly suboptimal treatment intra vitam.