Modern Pathology最新文献

{"title":"DNA Methylation Profiling Classifies and Reveals Origin of Gynecologic Central Nervous System-Like Tumors","authors":"Lucy Wang ,&nbsp;Varshini Vasudevaraja ,&nbsp;Jonathan Serrano ,&nbsp;Jennifer Kerkhof ,&nbsp;Jessica Rzasa ,&nbsp;Stephen Kelly ,&nbsp;Esther Oliva ,&nbsp;Robert H. Young ,&nbsp;Lars-Christian Horn ,&nbsp;Kay J. Park ,&nbsp;Amir Momeni-Boroujeni ,&nbsp;Cristina R. Antonescu ,&nbsp;Nadeem R. Abu-Rustum ,&nbsp;Yanming Zhang ,&nbsp;Lu Wang ,&nbsp;Achim Jungbluth ,&nbsp;Marc K. Rosenblum ,&nbsp;Bekim Sadikovic ,&nbsp;Igor Dolgalev ,&nbsp;Matija Snuderl ,&nbsp;Sarah Chiang","doi":"10.1016/j.modpat.2025.100941","DOIUrl":"10.1016/j.modpat.2025.100941","url":null,"abstract":"<div><div>Gynecologic neuroectodermal tumors either exhibit central nervous system (CNS) differentiation (CNS-like) or represent Ewing sarcoma (EWS), which lacks CNS features and harbors FET-ETS gene fusions. DNA methylation profiling reclassified CNS primitive neuroectodermal tumors into common CNS neoplasms or embryonal tumors with specific epigenetic/genetic characteristics. Its utility in classifying gynecologic neuroectodermal tumors is unknown. Whole-genome DNA methylation profiling was performed on 26 gynecologic neuroectodermal tumors (22 CNS-like tumors, 4 EWS) arising in the ovary, paratubal soft tissue, uterus, and vulva, which were classified by using sarcoma and CNS tumor DNA methylation classifiers. Sarcoma-related gene fusions were confirmed by fluorescence in situ hybridization or targeted RNA next-generation sequencing. Tumor-only whole-exome sequencing (WES) was performed in 13 cases. Copy number alterations and zygosity were inferred from DNA methylation array and WES data. Methylation abnormalities associated with imprinting were examined. The sarcoma methylation classifier identified EWS (n = 3) and high-grade endometrial stromal sarcoma (n = 1), confirmed by fluorescence in situ hybridization or next-generation sequencing detection of <em>EWSR1</em> and <em>YWHAE</em> rearrangements, respectively. The remaining CNS-like tumors were classified by DNA methylation with positive/valid (n = 4), indeterminate (n = 9), and negative (n = 9) scores at the family level. Methylation subclasses included teratoma; embryonal tumor with multilayered rosettes, atypical; medulloblastoma, SHH-activated, subtype 3; medulloblastoma, group 3; intraocular medulloepithelioma; supratentorial ependymoma, <em>ZFTA::RELA</em> fused, subclass A; and diffuse pediatric-type high-grade glioma, MYCN subtype. Male biological sex was predicted in 54% of methylation-confirmed CNS-like tumors and none of the sarcomas. Among CNS-like tumors, copy number analyses identified genome-wide chromosomal gains and losses, and WES revealed genome-wide allelic imbalance suggestive of genome-wide duplications. Epigenetic imprinting analyses showed increased paternal or maternal imprinting signal across multiple chromosomes, suggesting uniparental duplication. DNA methylation profiling successfully classified gynecologic neuroectodermal tumors as known CNS tumors or sarcoma entities. Epigenetic and exomic studies indicate a male genome and increased maternal allelic contribution in CNS-like tumors, suggesting development via conception or chimerism.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100941"},"PeriodicalIF":5.5,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145596797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Discordance and Error in Breast Pathology: Causes, Classifications, and Medicolegal Implications","authors":"Emad A. Rakha ,&nbsp;Cecily M. Quinn ,&nbsp;Elena Provenzano ,&nbsp;Sarah E. Pinder ,&nbsp;Ian O. Ellis","doi":"10.1016/j.modpat.2025.100942","DOIUrl":"10.1016/j.modpat.2025.100942","url":null,"abstract":"<div><div>Diagnostic pathology is inherently interpretative and subject to interobserver variability. Although diagnostic concordance is a critical quality metric, distinguishing between acceptable variation, diagnostic error, and professional negligence is essential for both clinical care and medicolegal clarity. This review highlights the difference between interobserver variability (diagnostic disagreement/discordance) that remains within acceptable professional limits, diagnostic error (a deviation from expected standards due to cognitive, technical, or systemic factors), and negligence (a repeated, reckless, or unjustified deviation from established standards). Errors in pathology often reflect systemic vulnerabilities, such as workflow inefficiencies, inadequate quality control, or limited biopsy sampling, rather than individual performance alone. They may occur at any stage of the diagnostic pathway (preanalytical, analytical, or postanalytical) and arise from specimen misidentification, contamination or loss, inadequate sampling, or incomplete documentation. Pathologist-related errors encompass failure to recognize significant pathology, misinterpretation, omission of appropriate ancillary studies, insufficient workup of complex cases, including failure to seek a second opinion, or substandard reporting. Medicolegal implications are heightened when such errors result in delayed diagnosis or major misclassification, leading to patient harm. In breast pathology, interobserver variation in the classification of borderline lesions (eg, grading of phyllodes tumors) and in the interpretation of overlapping entities (eg, atypical apocrine lesions) is well recognized. Although such differences may influence management, they should be regarded as acceptable professional variability, rather than error or negligence. To minimize diagnostic risk and uphold standards, structured reporting, vigilance in complex cases, participation in quality assurance, explicit documentation of uncertainty, active multidisciplinary team engagement, and laboratory accreditation are strongly recommended. Supporting pathologists as diagnosticians and patient safety advocates, within a culture of openness, shared learning, and institutional support, remains central to diagnostic accuracy, transparency, and medicolegal defensibility.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100942"},"PeriodicalIF":5.5,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145596760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large Language Models Can Generate High-Quality Pathology Multiple-Choice Questions Comparable With Questions Written by a Human Expert","authors":"Michael J. Borowitz ,&nbsp;Amanda L. Blackford ,&nbsp;Suman Nagelia ,&nbsp;Ralph H. Hruban","doi":"10.1016/j.modpat.2025.100940","DOIUrl":"10.1016/j.modpat.2025.100940","url":null,"abstract":"<div><div>Multiple-choice questions can be effective tools to assess student and trainee performance, but the creation of these questions can be time consuming and requires expertise. To test the quality of pathology test questions created by large language models (LLMs), 100 questions on pancreas pathology were written by a human expert, and 50 questions were generated by each of 2 LLMs (ChatGPT-4.0 and Gemini 2.5 Flash). After an initial review, 16% of the multiple-choice questions generated by the 2 LLMs had to be revised through additional interactive prompting. The final set of questions was then evaluated by 190 volunteers with a variety of backgrounds and levels of expertise. We found that ChatGPT-generated—but not Gemini-generated—questions were rated as easier than human-authored questions; there were slightly more poor/unacceptable questions compared with adequate/good/excellent questions written by the LLMs than those written by the human expert (11.7% vs 10.1%; odds ratio, 1.64; 95% CI, 1.13-2.37; <em>P</em> = .009), but there was no difference in the proportion of questions rated good or excellent. Qualitatively, human-authored questions were thought to be most clinically realistic but felt to be more inconsistent and sometimes thought to be testing trivial points. There was no difference in the mean point biserial between human-authored and LLM-generated questions (0.31 vs 0.29; <em>P</em> = .56). As LLMs improve, they will form a useful tool for the efficient generation of large numbers of high-quality pathology test questions.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100940"},"PeriodicalIF":5.5,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145588292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ZFTA::NCOA1/2-Rearranged Epithelioid Mesenchymal Tumor—A Phenotypically Distinct Myoepithelial-Like Neoplasm Epigenetically Overlapping With Chondroid Lipoma","authors":"Raheel Rizwan ,&nbsp;Vivek Venkataramani ,&nbsp;Lukas Haug ,&nbsp;Travis Hattery ,&nbsp;Mark Chen ,&nbsp;Joy Nakitandwe ,&nbsp;Sheila Shurtleff ,&nbsp;Elizabeth M. Azzato ,&nbsp;Maria-Veronica Teleanu ,&nbsp;Jennifer Hüllein ,&nbsp;Stefan Fröhling ,&nbsp;Robert Stoehr ,&nbsp;Steven D. Billings ,&nbsp;Michael Michal ,&nbsp;Karen J. Fritchie ,&nbsp;Abbas Agaimy ,&nbsp;Josephine K. Dermawan","doi":"10.1016/j.modpat.2025.100939","DOIUrl":"10.1016/j.modpat.2025.100939","url":null,"abstract":"<div><div><em>ZFTA</em> (formerly <em>C11orf95</em>) gene rearrangements are recurrent in rare tumors of the central nervous system, such as ependymomas (mostly <em>ZFTA::RELA</em>) and soft tissue tumors, such as chondroid lipomas (<em>ZFTA::MRTFB</em>). To date, among mesenchymal tumors, the <em>ZFTA::NCOA1</em> fusion has only been reported in a single case of chondroid lipoma. We describe 5 distinct soft tissue tumors harboring <em>ZFTA::NCOA1</em>/<em>2</em> fusions. The tumors arose from 2 females and 3 males with a median age of 31 years (range, 30-72). All tumors were well circumscribed involving the deep (4 cases) or superficial (1 case) soft tissue of the proximal limbs with a median greatest dimension of 4.2 cm (range, 1.7-6.0). Histologically, they displayed lobulated architecture and were composed of monotonous epithelioid-to-plasmacytoid cells arranged in cords, chains, and nests within myxohyaline or sclerosed stroma. Focal loose myxoid reticulate areas and prominent dilated and hyalinized blood vessels were present. One tumor showed focal spindle cells, whereas another demonstrated necrosis and atypical mitotic figures. Definitive adipocytic, lipoblastic, or clear-cell features were absent, except in 1 case. Immunohistochemistry was nonspecific without any consistent lineage-defining marker expression. Targeted RNA sequencing confirmed <em>ZFTA::NCOA1</em> fusions in 3 and <em>ZFTA::NCOA2</em> fusion in 2 cases. DNA methylation profiling, available in 4 cases, demonstrated a shared epigenetic profile with chondroid lipoma but not other tumors with histologic or genetic overlap. Copy number variation analysis showed a flat copy number profile in 3 cases and chr9p arm–level copy number loss in the case with necrosis and mitotic activity. All patients underwent complete excision; no recurrences or metastases were observed over a limited follow-up period (available in 4 cases, range, 8-24 months; median, 10.5 months). In conclusion, <em>ZFTA::NCOA1/2</em>-rearranged epithelioid mesenchymal tumors represent a novel, morphologically distinct entity, genetically and epigenetically overlapping with chondroid lipoma. Expanded cohorts and long-term follow-up are necessary to clarify their precise classification and biologic behavior.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100939"},"PeriodicalIF":5.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145573856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comprehensive Mutational and Histopathological Analysis of STK11-Mutant Non–Small Cell Lung Carcinomas","authors":"Cristiana M. Pineda ,&nbsp;Zoe Guan ,&nbsp;Hyunwoo Kwon ,&nbsp;Deepa Rangachari ,&nbsp;Daniel B. Costa ,&nbsp;Paul A. VanderLaan","doi":"10.1016/j.modpat.2025.100938","DOIUrl":"10.1016/j.modpat.2025.100938","url":null,"abstract":"<div><div>Despite recent advances in the understanding of genomic and immunopathological mechanisms of lung cancer, this disease remains the leading cause of cancer-related deaths in the United States. <em>STK11</em> (<em>LKB1</em>) mutations are present in approximately 20% of non–small cell lung cancers (NSCLCs) and drive tumor progression through disruption of cellular metabolism, polarity, and stress responses, ultimately leading to immune evasion and resistance to cancer therapy. Although these tumors are associated with poor prognoses, the clinicopathological significance of different <em>STK11</em> mutation subtypes and their associations with tumor histology, cellular behavior, metastatic potential, and clinical outcomes remain incompletely understood. In this study, we retrospectively analyzed a large cohort of <em>STK11</em>-mutant and <em>STK11</em> wild-type NSCLCs using a combination of next-generation sequencing, immunologic biomarkers, histopathological characterization, and radiographic imaging. Overall, we demonstrate that <em>STK11</em>-mutant tumors display diverse molecular and morphologic features and are associated with high rates of aggressive histopathological growth patterns, lymphovascular invasion, and spread through the airspaces. Among stage 4 cases, <em>STK11</em> mutations had notable differences in organotropism, with the <em>STK11</em>-loss cohort in particular demonstrating the highest rates of brain metastases at the time of initial diagnosis. Furthermore, among stage 4 cases, whereas all <em>STK11</em> mutation types resulted in decreased overall survival probability compared with the <em>STK11</em> wild-type cohort, the effect appeared most pronounced among the <em>STK11</em>-loss/<em>KRAS</em>-mutant group. These findings underscore the heterogeneity of <em>STK11</em>-mutant NSCLCs and highlight the opportunity for further investigation into specific <em>STK11</em> mutation subtypes in guiding prognosis and therapeutic decision-making for individuals with lung cancer.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100938"},"PeriodicalIF":5.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145573880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retinoblastoma Protein Loss in p53 Abnormal Endometrial Carcinoma Is Associated With Poor Clinical Outcomes in a Canadian Cohort","authors":"Allen W. Zhang ,&nbsp;C. Blake Gilks ,&nbsp;Lien Hoang ,&nbsp;Samuel Leung ,&nbsp;Dawn Cochrane ,&nbsp;David G. Huntsman ,&nbsp;Jessica N. McAlpine ,&nbsp;Spencer D. Martin","doi":"10.1016/j.modpat.2025.100926","DOIUrl":"10.1016/j.modpat.2025.100926","url":null,"abstract":"","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100926"},"PeriodicalIF":5.5,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optical Genome Mapping in Pediatric Hematologic Malignancies: High Diagnostic Yield and Unique Insights Across Leukemia Subtypes","authors":"Travis H. Smith ,&nbsp;Jeffrey Jean ,&nbsp;Stephen Phan ,&nbsp;Alexandra E. Kovach ,&nbsp;Karin Miller ,&nbsp;Jennifer Han ,&nbsp;Katherine Ma ,&nbsp;Cindy Fong ,&nbsp;Andrew Doan ,&nbsp;Deepa Bhojwani ,&nbsp;Gordana Raca","doi":"10.1016/j.modpat.2025.100937","DOIUrl":"10.1016/j.modpat.2025.100937","url":null,"abstract":"<div><div>Hematologic neoplasms in pediatric patients have different genomic profiles compared with the same malignancies in adults, with copy number abnormalities (CNAs) and balanced structural variants (SVs) being the most prevalent types of oncogenic drivers. Consequently, we hypothesized that optical genome mapping (OGM), as a new method for genome-wide, high-resolution detection of CNAs and balanced SVs, could represent a powerful testing approach for pediatric leukemias. This study compared the performance of OGM in the detection of clinically significant variants with current standard-of-care (SOC) diagnostic methodologies, including karyotyping, fluorescence in situ hybridization (FISH), chromosomal microarray, and a custom pediatric next-generation sequencing panel, OncoKids. In a retrospective review of results from SOC genetic testing and OGM for 100 de novo or relapsed pediatric hematologic neoplasms, full concordance was observed in 71% of cases. A clinically significant finding (tier 1 or 2 based on the Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists guidelines) was missed by OGM in 7 cases, but in 22 cases, OGM identified additional tier 1 or 2 findings missed by SOC testing. The highest increase in diagnostic yield was noted in T-lymphoblastic leukemia/lymphoma (T-ALL), with nearly 40% (9/23) of T-ALL cases having additional tier 1 or 2 findings detected using OGM. The main advantage of OGM was the ability to detect cytogenetically cryptic, balanced rearrangements not targeted by routine FISH probes or OncoKids, whereas its main limitation was low resolution for identifying copy-neutral loss of heterozygosity. As a single assay, OGM detected the majority (92%) of clinically significant variants identified by the combined use of karyotyping, FISH, chromosomal microarray, and OncoKids, and revealed additional tier 1 or 2 variants missed by SOC testing in 22% of the cases. Our study shows that OGM represents a powerful assay for detection of CNAs and balanced SVs in pediatric hematologic neoplasms.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100937"},"PeriodicalIF":5.5,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145534644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical-Grade Interpretable Artificial Intelligence Tool for Automated Detection of Lymph Node Metastasis in Prostate Cancer","authors":"Fatemeh Zabihollahy ,&nbsp;Kangdi Shi ,&nbsp;Collins Wangulu ,&nbsp;Ioannis Prassas ,&nbsp;Mehdi Masoomian ,&nbsp;Rola Saleeb ,&nbsp;Manal Y. Gabril ,&nbsp;Theodorus van der Kwast ,&nbsp;Neil E. Fleshner ,&nbsp;George M. Yousef","doi":"10.1016/j.modpat.2025.100934","DOIUrl":"10.1016/j.modpat.2025.100934","url":null,"abstract":"<div><div>Lymph node metastasis (LNM) is a critical prognostic factor for prostate cancer and is associated with increased mortality and poor clinical outcomes, necessitating modifications to therapeutic strategies. Manual histopathological evaluation of lymphatic tissue on glass slides is labor intensive, subject to interobserver variability, and prone to error. Deep learning approaches offer substantial promise in enhancing the accuracy and efficiency of LNM detection; however, their efficacy is contingent upon the availability of extensive annotated data sets. In this study, we developed a novel artificial intelligence (AI)–driven model leveraging a limited data set of annotated samples. By identifying and incorporating the most informative instances from unlabeled data into the training process, the model optimizes its learning trajectory through iterative error correction. Validation was performed on independent data sets from 3 academic medical centers, comprising 787 whole slide images and &gt;2000 lymph node tissues. On a combined test set of 165 positive and 622 negative cases, the model achieved an area under the receiver operating characteristic curve of 0.94 (95% CI, 0.92-0.96), with slide-level sensitivity and specificity of 96% (95% CI, 92%-99%) and 92% (95% CI, 89%-94%), respectively. Importantly, the AI algorithm identified micrometastases in 17 cases that were initially missed by pathologists. Although pathologists exhibited a 9% miss rate in micrometastasis detection, the AI model demonstrated a significantly lower miss rate of 3% using the institutional data set, highlighting its potential for clinical deployment. This fully autonomous and reproducible method also significantly reduced slide examination times compared with both general and genitourinary pathologists (<em>P</em> &lt; .001). The proposed method demonstrated interpretability by identifying metastasis regions on whole slide images labeled as positive. Ablation studies substantiate the robustness of the proposed methodology for LNM detection.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100934"},"PeriodicalIF":5.5,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145505776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BRAF p.Val600Glu Mutations Are Not Detected in Adenomatoid Odontogenic Tumors","authors":"Josiane Gonçalves ,&nbsp;Bruna P. Coura ,&nbsp;Vanessa F. Bernardes ,&nbsp;Luiz A. De Marco ,&nbsp;Manoela D. Martins ,&nbsp;Danyel E. da C. Perez ,&nbsp;Ricardo S. Gomez ,&nbsp;Carolina C. Gomes","doi":"10.1016/j.modpat.2025.100933","DOIUrl":"10.1016/j.modpat.2025.100933","url":null,"abstract":"<div><div>The adenomatoid odontogenic tumor (AOT) is a benign, encapsulated odontogenic tumor characterized by slow growth and indolent behavior. AOT shows mitogen-activated protein kinase/ERK pathway activation, and <em>KRAS</em> p.Gly12Val or p.Gly12Arg mutations occur in 70% of cases. The molecular events underlying the pathogenesis of the other 30% of cases remain unclear. The <em>BRAF</em> p.Val600Glu mutation was reported by a single study in 2 AOT cases, 1 of which also harbored <em>KRAS</em> p.Gly12Val. Given that <em>BRAF</em> p.Val600Glu has not been previously detected in AOT and that <em>BRAF</em> and <em>KRAS</em> mutations are mutually exclusive, we aimed to assess <em>BRAF</em> p.Val600Glu irrespective of <em>KRAS</em> mutational status to explore the potential involvement of <em>BRAF</em> mutations in AOT pathogenesis and the co-occurrence of <em>BRAF</em> and <em>KRAS</em> mutations. Whereas <em>KRAS</em> codon 13 and 61 hotspot mutations have not been previously detected in AOT, <em>KRAS</em> codon 146 hotspot mutations have been investigated in a few AOT cases to date. Therefore, we further sequenced <em>KRAS</em> codon 146 in <em>KRAS</em> codon 12 wild-type cases. A total of 29 AOT samples, including 21 <em>KRAS</em> codon 12 mutation-positive cases and 8 wild-type cases, were evaluated for the <em>BRAF</em> p.Val600Glu pathogenic mutation using allele-specific qPCR and/or Sanger sequencing. In addition, <em>KRAS</em> codon 146 was Sanger sequenced in 4 out of 29 samples. <em>BRAF</em> p.Val600Glu was not detected in any of the 29 AOT cases evaluated, either alone or as a comutation with <em>KRAS</em> mutations. All codon 12 wild-type cases were wild-type for <em>KRAS</em> codon 146 mutations. These findings reinforce that <em>KRAS</em> codon 12 mutant alleles predominate in the context of AOT tumorigenesis, whereas <em>BRAF</em> p.Val600Glu does not constitute a molecular feature of this tumor and the presence of the <em>BRAF</em> mutation does not support the diagnosis of AOT in challenging cases. In addition, the results further strengthen the notion that <em>BRAF</em> and <em>KRAS</em> mutations are mutually exclusive events.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100933"},"PeriodicalIF":5.5,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145482539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MSAI-Path: Predicting Microsatellite Instability From Routine Histology Slides Without Reinventing the Wheel","authors":"Elias Baumann ,&nbsp;Luca E.M. Schäfer ,&nbsp;Frédérique Meeuwsen ,&nbsp;Richard Kirsch ,&nbsp;Iris D. Nagtegaal ,&nbsp;Martin D. Berger ,&nbsp;Heather Dawson ,&nbsp;Inti Zlobec","doi":"10.1016/j.modpat.2025.100932","DOIUrl":"10.1016/j.modpat.2025.100932","url":null,"abstract":"<div><div>Microsatellite instability (MSI) is an important biomarker in colorectal cancer, influencing both patient prognosis and treatment decisions. Current approaches for MSI prediction from hematoxylin and eosin--stained whole-slide images (WSI) rely on end-to-end deep learning (“black-box”) models with limited interpretability, often relying on heatmaps for visualization. However, experienced pathologists can intuitively identify MSI through specific histologic features and have developed manual classification systems such as MS-Path for Lynch syndrome screening. We present a novel hybrid approach that combines computational and pathologist expertise to create an explainable and verifiable method for MSI prediction in colorectal cancer, applicable to resection and biopsy WSI. Our proposed method uses nuclei and tissue segmentation models to automatically quantify MSI-associated histologic features outlined in the Bethesda guidelines, including intraepithelial lymphocytes, grade of differentiation, mucinous components, and tertiary lymphoid structures. After validation on annotated data sets, these features are integrated with clinical data and used in logistic regression and random forest models to predict MSI status. We validated our approach using 3256 WSI from 2267 patients across 7 cohorts from 5 centers. The method achieved an area under the curve of up to 0.88 across all resection cohorts, and 0.90 on biopsies, performing on par with published black-box deep learning models. Importantly, the learned variable importances strongly correlated with manual scoring systems and aligned with manual pathologist assessments. We observed significant intrapatient heterogeneity in predicted scores, emphasizing the importance of whole-case analysis. Our approach also shows potential as a screening tool that could exclude 41% of patients from gold-standard MSI testing while maintaining 95% sensitivity. This study demonstrates that classifiers based on clinical and validated histologic information can predict MSI status as effectively as black-box models while providing complete interpretability. Our method offers an alternative pathway for understandable, explainable, and trustworthy biomarker prediction in computational pathology.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100932"},"PeriodicalIF":5.5,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145482511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}