Pub Date : 2026-01-01Epub Date: 2025-10-13DOI: 10.1016/j.modpat.2025.100914
Raul Ezequiel Perret
Round cell sarcomas represent a continuously evolving category of malignant mesenchymal tumors, currently encompassing 5 main tumor subtypes: Ewing sarcoma, Capicua Transcriptional Repressor (CIC)–rearranged sarcoma, sarcomas with BCL6-corepressor (BCOR)-genetic abnormalities, POZ/BTB and AT hook containing zinc finger 1 (PATZ1)-rearranged sarcoma, and nuclear factor of activated T cells 2 (NFATC2)-rearranged sarcoma. These tumors show some degree of histomorphologic overlap, which, coupled with their infrequency, may render their diagnosis challenging for the pathologist. Furthermore, although ancillary techniques like immunohistochemistry and molecular tests can be of diagnostic aid, they are still limited by inherent sensitivity and specificity issues and cannot replace meticulous integration of clinical and radiologic findings. This review is focused on (1) providing a guide for tackling the diagnosis of round cell sarcomas and their mimics using an integrative approach combining demographics, clinicoradiologic data, histomorphology, and ancillary techniques and (2) detailing the most recent information on round cell sarcomas from the latest World Health Organization classification of Bone and Soft Tissue Tumors (fifth edition).
{"title":"Unraveling Round Cell Sarcomas: A Contemporary Diagnostic Guide Beyond Ewing Sarcoma","authors":"Raul Ezequiel Perret","doi":"10.1016/j.modpat.2025.100914","DOIUrl":"10.1016/j.modpat.2025.100914","url":null,"abstract":"<div><div>Round cell sarcomas represent a continuously evolving category of malignant mesenchymal tumors, currently encompassing 5 main tumor subtypes: Ewing sarcoma, <em>Capicua Transcriptional Repressor</em> (CIC)<em>–</em>rearranged sarcoma, sarcomas with <em>BCL6-corepresso</em>r (<em>BCOR</em><em>)</em>-genetic abnormalities, <em>POZ/BTB and AT hook containing zinc finger 1</em> (<em>PATZ1</em><em>)</em>-rearranged sarcoma, and <em>nuclear factor of activated T cells 2</em> (<em>NFATC2</em><em>)</em>-rearranged sarcoma. These tumors show some degree of histomorphologic overlap, which, coupled with their infrequency, may render their diagnosis challenging for the pathologist. Furthermore, although ancillary techniques like immunohistochemistry and molecular tests can be of diagnostic aid, they are still limited by inherent sensitivity and specificity issues and cannot replace meticulous integration of clinical and radiologic findings. This review is focused on (1) providing a guide for tackling the diagnosis of round cell sarcomas and their mimics using an integrative approach combining demographics, clinicoradiologic data, histomorphology, and ancillary techniques and (2) detailing the most recent information on round cell sarcomas from the latest World Health Organization classification of Bone and Soft Tissue Tumors (fifth edition).</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100914"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145301902","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}
Pub Date : 2026-01-01Epub Date: 2025-11-10DOI: 10.1016/j.modpat.2025.100934
Fatemeh Zabihollahy , Kangdi Shi , Collins Wangulu , Ioannis Prassas , Mehdi Masoomian , Rola Saleeb , Manal Y. Gabril , Theodorus van der Kwast , Neil E. Fleshner , George M. Yousef
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 >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 (P < .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.
{"title":"Clinical-Grade Interpretable Artificial Intelligence Tool for Automated Detection of Lymph Node Metastasis in Prostate Cancer","authors":"Fatemeh Zabihollahy , Kangdi Shi , Collins Wangulu , Ioannis Prassas , Mehdi Masoomian , Rola Saleeb , Manal Y. Gabril , Theodorus van der Kwast , Neil E. Fleshner , 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 >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> < .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":"2026-01-01","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}
Pub Date : 2026-01-01Epub Date: 2025-11-14DOI: 10.1016/j.modpat.2025.100937
Travis H. Smith , Jeffrey Jean , Stephen Phan , Alexandra E. Kovach , Karin Miller , Jennifer Han , Katherine Ma , Cindy Fong , Andrew Doan , Deepa Bhojwani , Gordana Raca
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.
{"title":"Optical Genome Mapping in Pediatric Hematologic Malignancies: High Diagnostic Yield and Unique Insights Across Leukemia Subtypes","authors":"Travis H. Smith , Jeffrey Jean , Stephen Phan , Alexandra E. Kovach , Karin Miller , Jennifer Han , Katherine Ma , Cindy Fong , Andrew Doan , Deepa Bhojwani , 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":"2026-01-01","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}
Pub Date : 2026-01-01Epub Date: 2025-12-04DOI: 10.1016/j.modpat.2025.100945
Steve Hrycaj , May P. Chan , Sriram Venneti , Kelly L. Harms , Paul W. Harms
Merkel cell carcinoma (MCC) is an aggressive cutaneous tumor that must be distinguished from other cutaneous tumors and metastatic small cell carcinoma (SmCC). Additional diagnostic markers are limited for MCC with immunophenotypic aberrancy. MCC can display immunohistochemical loss of the epigenetic marker histone H3 lysine 27 trimethylation (H3K27me3), but to our knowledge, the diagnostic utility of this observation has not been evaluated. In this study, we investigate H3K27me3 labeling in MCC (n = 195), cutaneous epithelial tumors (n = 48), noncutaneous SmCCs (n = 56), and olfactory neuroblastoma (n = 11), comparing with diagnostic markers, cytokeratin-20, neurofilament, SATB2, and POU4F3. H3K27me3 patterns in MCC included global loss, variable/mosaic labeling, and diffuse labeling. Global loss significantly associated with polyomavirus negativity, squamous atypia, and sarcomatoid change. Tumors with global loss displayed EZHIP expression (9 cases) and SUZ12 mutation (1 case). Low but retained H3K27me3 labeling was associated with longer overall and MCC-specific survival. Diagnostically, H3K27me3 labeling in MCC was significantly lower than potential mimics, and global loss of H3K27me3 was highly specific for MCC; stronger H3K27me3 labeling was not informative. Considering reduced/absent H3K27me3 as favoring MCC, diagnostic performance was similar to SATB2. However, H3K27me3 displayed consistent performance in MCC with challenging immunophenotypes, unlike SATB2. In summary, we expand upon descriptions of H3K27me3 labeling in MCC and characterize patterns of H3K27me3 in other tumor types including SmCCs and olfactory neuroblastoma. Our findings support diagnostic utility for the widely available marker H3K27me3 in MCC, with weaker labeling favoring MCC over mimics in challenging cases.
{"title":"Diagnostic Utility and Clinicopathologic Associations of Histone H3 Lysine 27 Trimethylation (H3K27me3) Immunohistochemistry for Merkel Cell Carcinoma","authors":"Steve Hrycaj , May P. Chan , Sriram Venneti , Kelly L. Harms , Paul W. Harms","doi":"10.1016/j.modpat.2025.100945","DOIUrl":"10.1016/j.modpat.2025.100945","url":null,"abstract":"<div><div>Merkel cell carcinoma (MCC) is an aggressive cutaneous tumor that must be distinguished from other cutaneous tumors and metastatic small cell carcinoma (SmCC). Additional diagnostic markers are limited for MCC with immunophenotypic aberrancy. MCC can display immunohistochemical loss of the epigenetic marker histone H3 lysine 27 trimethylation (H3K27me3), but to our knowledge, the diagnostic utility of this observation has not been evaluated. In this study, we investigate H3K27me3 labeling in MCC (n = 195), cutaneous epithelial tumors (n = 48), noncutaneous SmCCs (n = 56), and olfactory neuroblastoma (n = 11), comparing with diagnostic markers, cytokeratin-20, neurofilament, SATB2, and POU4F3. H3K27me3 patterns in MCC included global loss, variable/mosaic labeling, and diffuse labeling. Global loss significantly associated with polyomavirus negativity, squamous atypia, and sarcomatoid change. Tumors with global loss displayed EZHIP expression (9 cases) and <em>SUZ12</em> mutation (1 case). Low but retained H3K27me3 labeling was associated with longer overall and MCC-specific survival. Diagnostically, H3K27me3 labeling in MCC was significantly lower than potential mimics, and global loss of H3K27me3 was highly specific for MCC; stronger H3K27me3 labeling was not informative. Considering reduced/absent H3K27me3 as favoring MCC, diagnostic performance was similar to SATB2. However, H3K27me3 displayed consistent performance in MCC with challenging immunophenotypes, unlike SATB2. In summary, we expand upon descriptions of H3K27me3 labeling in MCC and characterize patterns of H3K27me3 in other tumor types including SmCCs and olfactory neuroblastoma. Our findings support diagnostic utility for the widely available marker H3K27me3 in MCC, with weaker labeling favoring MCC over mimics in challenging cases.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100945"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145695738","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}
Pub Date : 2026-01-01Epub Date: 2025-11-01DOI: 10.1016/j.modpat.2025.100929
Sarah Dry
Certain areas in peripheral nerve sheath and adipocytic neoplasm diagnosis historically were characterized by a lack of clarity and consensus regarding terminology, diagnostic criteria, and prognosis. Recent work has led to important clarifications in diagnostic criteria and/or outcome data for neurofibromas with atypia and MDM2 amplification–negative adipocytic tumors. However, these clarifications remain incompletely recognized by many pathologists, in part due to the paucity of these neoplasms. This paper reviews the history and recent advances in diagnostic criteria, terminology, and understanding of prognosis for neurofibromas with atypia, malignant peripheral nerve sheath tumor (MPNST), malignant melanotic nerve sheath tumor, and atypical spindle cell/pleomorphic lipomatous tumor. Melanoma may be histologically identical to MPNST, and this paper also provides an overview of helpful clinical and molecular features that allow accurate identification of melanoma, including undifferentiated, dedifferentiated, and transdifferentiated melanoma, and their distinction from MPNST.
{"title":"Updates in Peripheral Nerve Sheath and Adipocytic Tumors","authors":"Sarah Dry","doi":"10.1016/j.modpat.2025.100929","DOIUrl":"10.1016/j.modpat.2025.100929","url":null,"abstract":"<div><div>Certain areas in peripheral nerve sheath and adipocytic neoplasm diagnosis historically were characterized by a lack of clarity and consensus regarding terminology, diagnostic criteria, and prognosis. Recent work has led to important clarifications in diagnostic criteria and/or outcome data for neurofibromas with atypia and MDM2 amplification–negative adipocytic tumors. However, these clarifications remain incompletely recognized by many pathologists, in part due to the paucity of these neoplasms. This paper reviews the history and recent advances in diagnostic criteria, terminology, and understanding of prognosis for neurofibromas with atypia, malignant peripheral nerve sheath tumor (MPNST), malignant melanotic nerve sheath tumor, and atypical spindle cell/pleomorphic lipomatous tumor. Melanoma may be histologically identical to MPNST, and this paper also provides an overview of helpful clinical and molecular features that allow accurate identification of melanoma, including undifferentiated, dedifferentiated, and transdifferentiated melanoma, and their distinction from MPNST.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100929"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145438642","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}
Pub Date : 2026-01-01Epub Date: 2025-10-12DOI: 10.1016/j.modpat.2025.100912
Jason L. Hornick
Immunohistochemistry plays a central role in the diagnosis of soft tissue tumors. Conventional immunohistochemistry uses antibodies directed against lineage-restricted antigens, in an attempt to identify a line of differentiation and narrow down the differential diagnosis. However, in most cases, such markers are inadequate to reach a specific diagnosis. Many soft tissue tumors harbor recurrent, often disease-defining molecular genetic alterations. Increasingly, fluorescence in situ hybridization analysis or next-generation sequencing is employed for identification of such alterations as a diagnostic adjunct. In recent years, immunohistochemistry has been used as a surrogate for such molecular genetic or cytogenetic analysis; this approach can identify the protein correlates of genetic alterations. Numerous next-generation antibodies directed against the protein products of a wide range of genetic alterations (such as gene fusions, amplifications, deletions, and point mutations) have entered our diagnostic armamentarium. In addition, gene expression profiling has uncovered diagnostically useful markers for immunohistochemistry. Finally, epigenetic alterations (eg, methylation) can also be assessed by immunohistochemistry. This review will provide examples of the application of contemporary molecular immunohistochemistry for soft tissue tumor diagnosis.
{"title":"Replacing Molecular Testing With Next-Generation Immunohistochemistry: I Can Diagnose That Soft Tissue Tumor With a Single Antibody!","authors":"Jason L. Hornick","doi":"10.1016/j.modpat.2025.100912","DOIUrl":"10.1016/j.modpat.2025.100912","url":null,"abstract":"<div><div>Immunohistochemistry plays a central role in the diagnosis of soft tissue tumors. Conventional immunohistochemistry uses antibodies directed against lineage-restricted antigens, in an attempt to identify a line of differentiation and narrow down the differential diagnosis. However, in most cases, such markers are inadequate to reach a specific diagnosis. Many soft tissue tumors harbor recurrent, often disease-defining molecular genetic alterations. Increasingly, fluorescence in situ hybridization analysis or next-generation sequencing is employed for identification of such alterations as a diagnostic adjunct. In recent years, immunohistochemistry has been used as a surrogate for such molecular genetic or cytogenetic analysis; this approach can identify the protein correlates of genetic alterations. Numerous next-generation antibodies directed against the protein products of a wide range of genetic alterations (such as gene fusions, amplifications, deletions, and point mutations) have entered our diagnostic armamentarium. In addition, gene expression profiling has uncovered diagnostically useful markers for immunohistochemistry. Finally, epigenetic alterations (eg, methylation) can also be assessed by immunohistochemistry. This review will provide examples of the application of contemporary molecular immunohistochemistry for soft tissue tumor diagnosis.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100912"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145292980","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}
Pub Date : 2026-01-01Epub Date: 2025-10-14DOI: 10.1016/j.modpat.2025.100916
Shira Ronen , David G. Grand , Wahab A. Khan , Michael Michal , Donald C. Green , Jennifer S. Ko , Robert E. LeBlanc , Jeffrey M. Cloutier
Cribriform tumor is a rare sweat-gland neoplasm of uncertain malignant potential. Although its histopathologic features are well described, the molecular underpinnings of cribriform tumor remain incompletely characterized. We performed comprehensive molecular profiling of 6 cribriform tumors from 3 institutions using whole-exome sequencing, transcriptome sequencing, and single-nucletide polymorphism array copy number analysis. The cohort included 3 women and 3 men (median age, 54 years; range, 40-66 years), with tumors measuring 0.3 to 2.0 cm. Most arose on the extremities, with one located on the back. The most consistent genomic alteration was arm-level losses of chromosomes 6q and 9q, detected in 5 out of 6 cases. These alterations were validated across independent sequencing and single-nucletide polymorphism array platforms. Whole-exome sequencing identified likely pathogenic variants in 2 tumors (CHEK2 p.R145W and NF1 p.R1830H). No gene fusions were detected. Taken together, these findings provide independent confirmation that 6q/9q loss represents a consistent cytogenomic alteration in cribriform tumor, supporting its use as a molecular hallmark of this tumor.
{"title":"Cribriform Tumor of the Skin: Identification of 6q and 9q Loss as a Recurrent Cytogenomic Alteration","authors":"Shira Ronen , David G. Grand , Wahab A. Khan , Michael Michal , Donald C. Green , Jennifer S. Ko , Robert E. LeBlanc , Jeffrey M. Cloutier","doi":"10.1016/j.modpat.2025.100916","DOIUrl":"10.1016/j.modpat.2025.100916","url":null,"abstract":"<div><div>Cribriform tumor is a rare sweat-gland neoplasm of uncertain malignant potential. Although its histopathologic features are well described, the molecular underpinnings of cribriform tumor remain incompletely characterized. We performed comprehensive molecular profiling of 6 cribriform tumors from 3 institutions using whole-exome sequencing, transcriptome sequencing, and single-nucletide polymorphism array copy number analysis. The cohort included 3 women and 3 men (median age, 54 years; range, 40-66 years), with tumors measuring 0.3 to 2.0 cm. Most arose on the extremities, with one located on the back. The most consistent genomic alteration was arm-level losses of chromosomes 6q and 9q, detected in 5 out of 6 cases. These alterations were validated across independent sequencing and single-nucletide polymorphism array platforms. Whole-exome sequencing identified likely pathogenic variants in 2 tumors (<em>CHEK2</em> p.R145W and <em>NF1</em> p.R1830H). No gene fusions were detected. Taken together, these findings provide independent confirmation that 6q/9q loss represents a consistent cytogenomic alteration in cribriform tumor, supporting its use as a molecular hallmark of this tumor.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100916"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145308501","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}
Pub Date : 2026-01-01Epub Date: 2025-11-05DOI: 10.1016/j.modpat.2025.100931
Carla Saoud , Yanming Zhang , Jamal Benhamida , Liliana Villafania , Gunes Gundem , Robert Cimera , Sinchun Hwang , Neerav N. Shukla , Damon Reed , Elli Papaemmanouil , Narasimhan P. Agaram , Konstantinos Linos , Marc Ladanyi , Carol D. Morris , Meera R. Hameed
Chromothripsis, a catastrophic genomic event causing extensive chromosomal fragmentation and rearrangement, has been identified in conventional osteosarcoma, contributing to karyotypic heterogeneity. Chromothripsis was also detected in a subset of parosteal osteosarcomas, primarily involving chromosome 12, but not well documented in low-grade central osteosarcoma (LGCOS). Here, we report 2 cases of low-grade fibro-osseous lesions with isolated chromosome 12 chromothripsis, aiming to characterize them by comparing their genomic and epigenetic profiles to those of other bone neoplasms. Case 1 was a 12-year-old male with a destructive lesion involving the proximal left tibia, and case 2 was a 13-year-old female with an expansile lucent bone lesion involving the distal tibia with cortical breakthrough. Both cases consisted of hypocellular bland fibroblastic proliferation. Areas of thin trabeculae of woven bone surrounded by osteoblasts were present. In addition, case 1 showed areas of atypical cartilaginous islands and areas reminiscent of LGCOS. By single-nucleotide polymorphism array, both cases showed extremely complex and numerous genomic alterations involving chromosome 12. Whole-genome sequencing and optical genome sequencing confirmed the chromothriptic event involving chromosome 12. Using the Heidelberg Epignostix sarcoma methylation classifier (v12.3), both cases matched to fibrous dysplasia methylation class. Dimensionality reduction using Uniform Manifold Approximation and Projection demonstrated that the 2 index cases clustered primarily with low-grade osteosarcomas lacking MDM2 amplification and with fibrous dysplasia, whereas remaining separate from parosteal osteosarcomas and MDM2-amplified low-grade osteosarcomas. Our findings suggest that chromothripsis of chromosome 12 may represent an early and/or an alternate mechanism in fibro-osseous lesions progressing to LGCOS instead of or before the development of the well-recognized CDK4/MDM2 amplification. Larger cohorts with long-term follow-ups and integrative molecular studies are needed to clarify the biological significance and clinical implications, including recurrence, dedifferentiation, and survival.
{"title":"Low-Grade Fibro-Osseous Lesions With Isolated Chromosome 12 Chromothripsis: A Distinct Entity Or a Low-Grade Central Osteosarcoma With a Novel Driver?","authors":"Carla Saoud , Yanming Zhang , Jamal Benhamida , Liliana Villafania , Gunes Gundem , Robert Cimera , Sinchun Hwang , Neerav N. Shukla , Damon Reed , Elli Papaemmanouil , Narasimhan P. Agaram , Konstantinos Linos , Marc Ladanyi , Carol D. Morris , Meera R. Hameed","doi":"10.1016/j.modpat.2025.100931","DOIUrl":"10.1016/j.modpat.2025.100931","url":null,"abstract":"<div><div>Chromothripsis, a catastrophic genomic event causing extensive chromosomal fragmentation and rearrangement, has been identified in conventional osteosarcoma, contributing to karyotypic heterogeneity. Chromothripsis was also detected in a subset of parosteal osteosarcomas, primarily involving chromosome 12, but not well documented in low-grade central osteosarcoma (LGCOS). Here, we report 2 cases of low-grade fibro-osseous lesions with isolated chromosome 12 chromothripsis, aiming to characterize them by comparing their genomic and epigenetic profiles to those of other bone neoplasms. Case 1 was a 12-year-old male with a destructive lesion involving the proximal left tibia, and case 2 was a 13-year-old female with an expansile lucent bone lesion involving the distal tibia with cortical breakthrough. Both cases consisted of hypocellular bland fibroblastic proliferation. Areas of thin trabeculae of woven bone surrounded by osteoblasts were present. In addition, case 1 showed areas of atypical cartilaginous islands and areas reminiscent of LGCOS. By single-nucleotide polymorphism array, both cases showed extremely complex and numerous genomic alterations involving chromosome 12. Whole-genome sequencing and optical genome sequencing confirmed the chromothriptic event involving chromosome 12. Using the Heidelberg Epignostix sarcoma methylation classifier (v12.3), both cases matched to fibrous dysplasia methylation class. Dimensionality reduction using Uniform Manifold Approximation and Projection demonstrated that the 2 index cases clustered primarily with low-grade osteosarcomas lacking <em>MDM2</em> amplification and with fibrous dysplasia, whereas remaining separate from parosteal osteosarcomas and <em>MDM2</em>-amplified low-grade osteosarcomas. Our findings suggest that chromothripsis of chromosome 12 may represent an early and/or an alternate mechanism in fibro-osseous lesions progressing to LGCOS instead of or before the development of the well-recognized <em>CDK4/MDM2</em> amplification. Larger cohorts with long-term follow-ups and integrative molecular studies are needed to clarify the biological significance and clinical implications, including recurrence, dedifferentiation, and survival.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"39 1","pages":"Article 100931"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145471545","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}
Pub Date : 2025-12-01Epub Date: 2025-05-27DOI: 10.1016/j.modpat.2025.100802
Tad T. Brunyé , Hannah Shucard , Megan M. Eguchi , Trafton Drew , Jonathan Marotti , Lesley C. Lomo , Mark R. Kilgore , Kimberly H. Allison , Kathleen F. Kerr , Joann G. Elmore , Donald L. Weaver
Accurate disease diagnosis is the cornerstone of patient care, directly impacting the quality of health care delivery and patient outcomes. Developing diagnostic competence is a critical goal of pathology residency training. This study uses longitudinal data from trainees during pathology residency to examine the association between years of training and performance in 4 key interpretive phases: detecting critical regions, recognizing their relevance, describing histopathological features, and rendering an accurate diagnosis. Using a study set of 32 digital whole slide images of breast biopsies, 155 pathology residents from 10 US academic medical centers each reviewed 14 cases across multiple years of residency training. Image-viewing behavior, annotation accuracy, and diagnostic decisions were recorded and analyzed. Generalized estimating equations were used to assess the relationship between residency year and metrics capturing the 4 interpretive phases. Year of residency training was not significantly associated with the detection of critical regions or recognizing their importance. However, each year of residency training was associated with 2% less time spent viewing critical regions (P = 0.025) and 1% more attentional coverage of the image space (P = 0.01), suggesting that residents adopt broader scanning strategies over time. Further, each year of residency training was associated with 19% higher odds of writing an accurate annotation (odds ratio = 1.19, P < 0.001) and 18% higher odds of making an accurate diagnosis (odds ratio = 1.18, P < 0.001). Exploratory analyses indicated that accurate feature annotation was the key predictor of diagnostic accuracy, highlighting its importance as a foundational skill in clinical decision-making. Both the ability to describe histopathological features and diagnostic accuracy increase with years of residency training, and the former appears to be a key component of the latter. Competency-based training in pathology should incorporate targeted interventions to improve histopathological feature recognition and description, which appears most likely to improve overall diagnostic performance.
准确的疾病诊断是患者护理的基石，直接影响医疗保健服务的质量和患者的治疗结果。发展诊断能力是病理学住院医师培训的关键目标。本研究使用实习病理住院期间的纵向数据来检验培训年份与四个关键解释阶段的表现之间的关系：检测关键区域，识别其相关性，描述组织病理学特征，并给出准确的诊断。来自美国10个学术医疗中心的155名病理学住院医师，在多年住院医师培训中，每人回顾了14例乳房活检的数字整张幻灯片图像。记录和分析图像观看行为、注释准确性和诊断决策。使用广义估计方程来评估居住年与捕获四个解释阶段的度量之间的关系。住院医师培训的年份与关键区域的检测或认识到其重要性没有显着关联。然而，每一年的住院医师培训与观察关键区域的时间减少2% （p = 0.025）和图像空间的注意力覆盖增加1% （p = 0.01）相关，这表明随着时间的推移，住院医师采用了更广泛的扫描策略。此外，每一年的住院医师培训与写出准确注释的几率增加19% （OR = 1.19, p < 0.001）和做出准确诊断的几率增加18% （OR = 1.18, p < 0.001）相关。探索性分析表明，准确的特征注释是诊断准确性的关键预测因素，突出了其作为临床决策基础技能的重要性。描述组织病理学特征的能力和诊断的准确性都随着住院医师培训的年数而增加，而前者似乎是后者的关键组成部分。基于能力的病理学培训应纳入有针对性的干预措施，以提高组织病理学特征的识别和描述，这似乎最有可能提高整体诊断性能。
{"title":"Characterizing Interpretive and Diagnostic Competency Development in Pathology Training","authors":"Tad T. Brunyé , Hannah Shucard , Megan M. Eguchi , Trafton Drew , Jonathan Marotti , Lesley C. Lomo , Mark R. Kilgore , Kimberly H. Allison , Kathleen F. Kerr , Joann G. Elmore , Donald L. Weaver","doi":"10.1016/j.modpat.2025.100802","DOIUrl":"10.1016/j.modpat.2025.100802","url":null,"abstract":"<div><div>Accurate disease diagnosis is the cornerstone of patient care, directly impacting the quality of health care delivery and patient outcomes. Developing diagnostic competence is a critical goal of pathology residency training. This study uses longitudinal data from trainees during pathology residency to examine the association between years of training and performance in 4 key interpretive phases: detecting critical regions, recognizing their relevance, describing histopathological features, and rendering an accurate diagnosis. Using a study set of 32 digital whole slide images of breast biopsies, 155 pathology residents from 10 US academic medical centers each reviewed 14 cases across multiple years of residency training. Image-viewing behavior, annotation accuracy, and diagnostic decisions were recorded and analyzed. Generalized estimating equations were used to assess the relationship between residency year and metrics capturing the 4 interpretive phases. Year of residency training was not significantly associated with the detection of critical regions or recognizing their importance. However, each year of residency training was associated with 2% less time spent viewing critical regions (<em>P</em> = 0.025) and 1% more attentional coverage of the image space (<em>P</em> = 0.01), suggesting that residents adopt broader scanning strategies over time. Further, each year of residency training was associated with 19% higher odds of writing an accurate annotation (odds ratio = 1.19, <em>P</em> < 0.001) and 18% higher odds of making an accurate diagnosis (odds ratio = 1.18, <em>P</em> < 0.001). Exploratory analyses indicated that accurate feature annotation was the key predictor of diagnostic accuracy, highlighting its importance as a foundational skill in clinical decision-making. Both the ability to describe histopathological features and diagnostic accuracy increase with years of residency training, and the former appears to be a key component of the latter. Competency-based training in pathology should incorporate targeted interventions to improve histopathological feature recognition and description, which appears most likely to improve overall diagnostic performance.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"38 12","pages":"Article 100802"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144180881","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}
Pub Date : 2025-12-01Epub Date: 2025-07-16DOI: 10.1016/j.modpat.2025.100847
Ziyu Su, Yongxin Guo, Robert Wesolowski, Gary Tozbikian, Nathaniel S O'Connell, Muhammad Khalid Khan Niazi, Metin N Gurcan
Accurate recurrence risk stratification is crucial for optimizing treatment plans for breast cancer patients. Current prognostic tools like Oncotype DX offer valuable genomic insights into hormone receptor-positive and human epidermal growth factor receptor-negative patients but are limited by cost and accessibility, particularly in underserved populations. In this study, we present Deep-Breast-Cancer-Recurrence (BCR)-Auto, a deep learning-based computational pathology approach that predicts breast cancer recurrence risk from routine hematoxylin and eosin-stained whole slide images. Our methodology was validated on 2 independent cohorts: The Cancer Genome Atlas Program breast cancer data set and an in-house data set from The Ohio State University. Deep-BCR-Auto demonstrated robust performance in stratifying patients into low- and high-recurrence risk categories. On The Cancer Genome Atlas Program breast cancer data set, the model achieved an area under the receiver operating characteristic curve of 0.827, significantly outperforming the existing weakly supervised models (P = .041). In the independent The Ohio State University data set, Deep-BCR-Auto maintained strong generalizability, achieving an area under the receiver operating characteristic curve of 0.832, along with 82.0% accuracy, 85.0% specificity, and 67.7% sensitivity. These findings highlight the potential of computational pathology as a cost-effective alternative for recurrence risk assessment, broadening access to personalized treatment strategies. This study underscores the clinical utility of integrating deep learning-based computational pathology into routine pathological assessment for breast cancer prognosis across diverse clinical settings.
{"title":"Computational Pathology for Accurate Prediction of Breast Cancer Recurrence: Development and Validation of a Deep Learning-Based Tool.","authors":"Ziyu Su, Yongxin Guo, Robert Wesolowski, Gary Tozbikian, Nathaniel S O'Connell, Muhammad Khalid Khan Niazi, Metin N Gurcan","doi":"10.1016/j.modpat.2025.100847","DOIUrl":"10.1016/j.modpat.2025.100847","url":null,"abstract":"<p><p>Accurate recurrence risk stratification is crucial for optimizing treatment plans for breast cancer patients. Current prognostic tools like Oncotype DX offer valuable genomic insights into hormone receptor-positive and human epidermal growth factor receptor-negative patients but are limited by cost and accessibility, particularly in underserved populations. In this study, we present Deep-Breast-Cancer-Recurrence (BCR)-Auto, a deep learning-based computational pathology approach that predicts breast cancer recurrence risk from routine hematoxylin and eosin-stained whole slide images. Our methodology was validated on 2 independent cohorts: The Cancer Genome Atlas Program breast cancer data set and an in-house data set from The Ohio State University. Deep-BCR-Auto demonstrated robust performance in stratifying patients into low- and high-recurrence risk categories. On The Cancer Genome Atlas Program breast cancer data set, the model achieved an area under the receiver operating characteristic curve of 0.827, significantly outperforming the existing weakly supervised models (P = .041). In the independent The Ohio State University data set, Deep-BCR-Auto maintained strong generalizability, achieving an area under the receiver operating characteristic curve of 0.832, along with 82.0% accuracy, 85.0% specificity, and 67.7% sensitivity. These findings highlight the potential of computational pathology as a cost-effective alternative for recurrence risk assessment, broadening access to personalized treatment strategies. This study underscores the clinical utility of integrating deep learning-based computational pathology into routine pathological assessment for breast cancer prognosis across diverse clinical settings.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100847"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668002","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}
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