Modern Pathology最新文献

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"Introducing an Essential 7-Part AI Review Series: A Guided Journey into the Future of Pathology & Medicine". "介绍必不可少的 7 部分 AI 复习系列:病理学与医学的未来之旅"。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-25 DOI: 10.1016/j.modpat.2024.100673
Hooman H Rashidi, Mathew Hanna, Liron Pantanowitz
{"title":"\"Introducing an Essential 7-Part AI Review Series: A Guided Journey into the Future of Pathology & Medicine\".","authors":"Hooman H Rashidi, Mathew Hanna, Liron Pantanowitz","doi":"10.1016/j.modpat.2024.100673","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100673","url":null,"abstract":"","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100673"},"PeriodicalIF":7.1,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142739833","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}
引用次数: 0
Statistics of Generative Artificial Intelligence and Nongenerative Predictive Analytics Machine Learning in Medicine. 生成式人工智能和非生成式预测分析的统计 医学中的机器学习。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-22 DOI: 10.1016/j.modpat.2024.100663
Hooman H Rashidi, Bo Hu, Joshua Pantanowitz, Nam Tran, Silvia Liu, Alireza Chamanzar, Mert Gur, Chung-Chou H Chang, Yanshan Wang, Ahmad Tafti, Liron Pantanowitz, Matthew G Hanna
{"title":"Statistics of Generative Artificial Intelligence and Nongenerative Predictive Analytics Machine Learning in Medicine.","authors":"Hooman H Rashidi, Bo Hu, Joshua Pantanowitz, Nam Tran, Silvia Liu, Alireza Chamanzar, Mert Gur, Chung-Chou H Chang, Yanshan Wang, Ahmad Tafti, Liron Pantanowitz, Matthew G Hanna","doi":"10.1016/j.modpat.2024.100663","DOIUrl":"10.1016/j.modpat.2024.100663","url":null,"abstract":"<p><p>The rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) in medicine has prompted medical professionals to increasingly familiarize themselves with related topics. This also demands grasping the underlying statistical principles that govern their design, validation, and reproducibility. Uniquely, the practice of pathology and medicine produces vast amount of data that can be exploited by AI/ML. The emergence of generative AI, especially in the area of large language models and multimodal frameworks, represents approaches that are starting to transform medicine. Fundamentally, generative and traditional (eg, nongenerative predictive analytics) ML techniques rely on certain common statistical measures to function. However, unique to generative AI are metrics such as, but not limited to, perplexity and BiLingual Evaluation Understudy score that provide a means to determine the quality of generated samples that are typically unfamiliar to most medical practitioners. In contrast, nongenerative predictive analytics ML often uses more familiar metrics tailored to specific tasks as seen in the typical classification (ie, confusion metrics measures, such as accuracy, sensitivity, F1 score, and receiver operating characteristic area under the curve) or regression studies (ie, root mean square error and R<sup>2</sup>). To this end, the goal of this review article (as part 4 of our AI review series) is to provide an overview and a comparative measure of statistical measures and methodologies used in both generative AI and traditional (ie, nongenerative predictive analytics) ML fields along with their strengths and known limitations. By understanding their similarities and differences along with their respective applications, we will become better stewards of this transformative space, which ultimately enables us to better address our current and future needs and challenges in a more responsible and scientifically sound manner.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100663"},"PeriodicalIF":7.1,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695549","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}
引用次数: 0
Retinoblastoma Protein Loss in p53 Abnormal Endometrial Carcinoma: Histologic and Clinicopathological Correlates. p53 异常子宫内膜癌中的 RB 缺失:组织学与临床病理学相关性
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-20 DOI: 10.1016/j.modpat.2024.100660
Ezgi Dicle Serbes, Nanda Horeweg, Carlos Parra-Herran, Renske van Rijnsoever, Jan J Jobsen, Ina Jurgenliemk-Schulz, Nienke Kuijsters, Remi A Nout, Marie A D Haverkort, Melanie E Powell, Pearly Khaw, Marie Plante, Catherine Genestie, Hans W Nijman, Carien L Creutzberg, Tjalling Bosse, Claire J H Kramer
{"title":"Retinoblastoma Protein Loss in p53 Abnormal Endometrial Carcinoma: Histologic and Clinicopathological Correlates.","authors":"Ezgi Dicle Serbes, Nanda Horeweg, Carlos Parra-Herran, Renske van Rijnsoever, Jan J Jobsen, Ina Jurgenliemk-Schulz, Nienke Kuijsters, Remi A Nout, Marie A D Haverkort, Melanie E Powell, Pearly Khaw, Marie Plante, Catherine Genestie, Hans W Nijman, Carien L Creutzberg, Tjalling Bosse, Claire J H Kramer","doi":"10.1016/j.modpat.2024.100660","DOIUrl":"10.1016/j.modpat.2024.100660","url":null,"abstract":"<p><p>Of the 4 molecular subtypes of endometrial cancer (EC), p53-abnormal (p53abn) EC is associated with abundant copy number alterations and the worst clinical outcome. Patients with p53abn EC have the highest risk of disease recurrence and death, independent of tumor grade and histologic subtype. Currently, all invasive p53abn ECs are considered high risk, and no prognostic biomarkers have yet been found that can aid in clinical management. Here, we aimed to test whether loss of retinoblastoma (RB) protein expression using immunohistochemistry has the potential for prognostic refinement of p53abn EC. A large cohort of 227 p53abn ECs collected from the PORTEC-1/2/3 clinical trials and the Medisch Spectrum Twente cohort study was investigated, and RB loss was identified in 7.0% (n = 16/227). RB-lost p53abn ECs were predominantly high-grade endometrioid ECs (n = 6, 37.5%) and carcinosarcomas with endometrioid-type epithelial component (n = 5, 31.3%). Histologically, RB-lost p53abn ECs were typified by high-grade nuclear atypia (n = 16, 100%), predominantly solid growth pattern (n = 15/16, 93.8%), and polypoid growth (n = 9/16, 56.3%). Copy number loss involving the RB1 locus was identified in the majority of RB-lost p53abn EC (n = 13/14, 92.9%), explaining the loss of RB expression. Comparative analysis also showed that RB-lost p53abn ECs were diagnosed at earlier stages than RB-retained p53abn EC (P = .014). Interestingly, RB-lost p53abn EC showed prolonged time to overall recurrence (P = .038), even within stage I alone (P = .040). These findings highlight distinct morphomolecular features in RB-lost p53abn ECs and confirm the utility of RB immunohistochemistry as a surrogate for underlying molecular RB1 alterations. To our knowledge, this is the first study to show the potential use of RB in prognostic refinement of p53abn EC, although validation is warranted.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100660"},"PeriodicalIF":7.1,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693201","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}
引用次数: 0
Extraaxial Poorly Differentiated Chordoma: Clinicopathologic and Molecular Genetic Characterization. 轴外低分化脊索瘤:临床病理学和分子遗传学特征。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-20 DOI: 10.1016/j.modpat.2024.100664
William J Sande, Andrew L Folpe, Paige O'Connor, Daniel Graham, Jeremy F Molligan, Ying-Chun Lo, Yvonne Y Cheung, Baptiste Ameline, Daniel Baumhoer, Dorothee Harder, Kevin A Raskin, Christopher W Mount, Yin P Hung, Gunnlaugur Petur Nielsen, Darcy A Kerr, Darya Buehler, Doris E Wenger, Judith Jebastin Thangaiah
{"title":"Extraaxial Poorly Differentiated Chordoma: Clinicopathologic and Molecular Genetic Characterization.","authors":"William J Sande, Andrew L Folpe, Paige O'Connor, Daniel Graham, Jeremy F Molligan, Ying-Chun Lo, Yvonne Y Cheung, Baptiste Ameline, Daniel Baumhoer, Dorothee Harder, Kevin A Raskin, Christopher W Mount, Yin P Hung, Gunnlaugur Petur Nielsen, Darcy A Kerr, Darya Buehler, Doris E Wenger, Judith Jebastin Thangaiah","doi":"10.1016/j.modpat.2024.100664","DOIUrl":"10.1016/j.modpat.2024.100664","url":null,"abstract":"<p><p>Poorly differentiated chordoma (PDC) is an aggressive subtype of chordoma characterized by SMARCB1 (INI1) loss and a dismal prognosis. It typically involves the axial skeleton, most commonly the skull base and the cervical spine. To our knowledge, only 5 cases of extraaxial PDC (EAPDC) have been reported, and the natural history of these tumors is not fully understood. We studied 6 cases of EAPDC, with the goal of better understanding these exceptionally rare tumors. The tumors occurred in 4 women and 2 men, ranging from 37 to 68 years of age (median, 57.5 years) and involved or originated in the left knee joint (3 cases), right knee joint (2 cases), and right wrist (1 case). Grossly, all were solid and lobulated, with areas of necrosis. Histologically, the tumors were identical to axial PDC, with sheets and lobules of overtly malignant-appearing epithelioid-to-rhabdoid cells with prominent nucleoli. Mitotic activity and necrosis were present. By immunohistochemistry, all cases expressed keratins and brachyury and were SMARCB1 deficient. Molecular genetic analysis identified SMARCB1 loss-of-function alterations in 4 of the tested cases, including mutations (2 cases) and copy number loss (2 cases). DNA methylation profiling of 4 cases of EAPDC showed clustering with axial PDC. Clinical follow-up (6 patients; median, 11.5 months; range, 1-26 months) showed 4 patients to have received transfemoral amputation and 1 extraarticular resection. None received neoadjuvant radiotherapy; 1 received neoadjuvant chemotherapy and 1 adjuvant chemotherapy/immunotherapy. Local recurrences were seen in 2 patients at 7 and 8 months; 3 patients developed metastases 7-11 months after surgery. Two patients were alive with metastatic disease (at 7 and 13 months), 1 died of disease (20 months), and 3 were disease free (1-26 months). We conclude that EAPDC are aggressive malignancies with an unusual predilection for the knee joint and unknown pathogenesis.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100664"},"PeriodicalIF":7.1,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693198","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}
引用次数: 0
Fast Processing of Electron Microscopic Specimen Preserved Ultrastructure of Glomeruli and Electron-Dense Deposits in Diagnostic Renal Biopsies: A Prospective and Retrospective Comparative Study. 快速处理电子显微镜标本可保留诊断性肾活检中肾小球的超微结构和电子致密沉积物:前瞻性与回顾性比较研究
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-20 DOI: 10.1016/j.modpat.2024.100662
Aranza Pinedo, Prerna Rastogi, Abdullah Thayyil, Matthew Gosse, Amy Trent, Serena M Bagnasco, Avi Rosenberg, Lois J Arend, Dao-Fu Dai
{"title":"Fast Processing of Electron Microscopic Specimen Preserved Ultrastructure of Glomeruli and Electron-Dense Deposits in Diagnostic Renal Biopsies: A Prospective and Retrospective Comparative Study.","authors":"Aranza Pinedo, Prerna Rastogi, Abdullah Thayyil, Matthew Gosse, Amy Trent, Serena M Bagnasco, Avi Rosenberg, Lois J Arend, Dao-Fu Dai","doi":"10.1016/j.modpat.2024.100662","DOIUrl":"10.1016/j.modpat.2024.100662","url":null,"abstract":"<p><p>Optimization of electron microscopy (EM) tissue processing protocols is essential to handle the global increase in the number of renal biopsies requiring EM for accurate diagnosis. The conventional EM processing method (CEM) is the standard method used by >95% of laboratories worldwide and it takes at least 48 to 52 hours for completion. In contrast, a fast-processing EM (FEM) method using microwave irradiation can be completed in 8 hours, allowing EM findings to be reported within 24 hours for most cases. There is widespread concern about the suboptimal quality of the FEM that may compromise its diagnostic roles; however, qualitative and quantitative data supporting the noninferiority of FEM compared with CEM has not been reported. We performed both prospective and retrospective studies. The prospective analysis compares FEM and CEM images from the same biopsy samples. For each case, the tissue was divided into 2 pieces: 1 piece for FEM processing and the second for CEM processing. The retrospective study compares the EM images of renal cases with electron-dense deposits from our archives that were processed either by FEM or CEM. The prospective analysis included 4 cases: lupus membranous nephropathy, IgA nephropathy, immune complex-mediated glomerulonephritis, and acute tubular injury. Both FEM and CEM methods obtained high-resolution images with comparable quality. A quantitative morphometric analysis of the glomerular basement membrane (GBM) in the IgA nephropathy case showed similar GBM thickness when processed by the FEM and the CEM, suggesting that FEM did not affect GBM thickness. The retrospective study of 42 cases with electron-dense deposits showed that the ultrastructural features of electron-dense deposits were indistinguishable between the FEM and the CEM. This included microtubular substructures in immunotactoid glomerulonephritis, the \"fingerprint\" deposits in cryoglobulinemic glomerulonephritis, fibril deposits in the light chain amyloidosis as well as fibrillary glomerulonephritis, with comparable morphometric measurements of the deposits. The FEM is efficient, consistent, reproducible, and delivers comparable high-quality sections and images for diagnostic assessment of renal biopsies, compared with those attained by the CEM while decreasing turnaround time significantly, making it possible to provide faster and accurate diagnostic results.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100662"},"PeriodicalIF":7.1,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693199","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}
引用次数: 0
Congenital Peribronchial Myofibroblastic Tumors Harbor a Recurrent EGFR Kinase Domain Duplication. 先天性支气管周围肌纤维母细胞瘤含有复发性表皮生长因子受体激酶结构域重复。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-20 DOI: 10.1016/j.modpat.2024.100661
Sheren Younes, Carlos J Suarez, Jennifer Pogoriler, Tricia Bhatti, Archana Shenoy, Raya Saab, Lea F Surrey, Serena Y Tan
{"title":"Congenital Peribronchial Myofibroblastic Tumors Harbor a Recurrent EGFR Kinase Domain Duplication.","authors":"Sheren Younes, Carlos J Suarez, Jennifer Pogoriler, Tricia Bhatti, Archana Shenoy, Raya Saab, Lea F Surrey, Serena Y Tan","doi":"10.1016/j.modpat.2024.100661","DOIUrl":"10.1016/j.modpat.2024.100661","url":null,"abstract":"<p><p>Congenital peribronchial myofibroblastic tumor (CPMT) is a rare benign infantile pulmonary neoplasm that presents prenatally, or early in infancy, and exhibits distinctive histologic features characterized by the presence of cartilaginous islands intermixed with bland spindle cells, not uncommonly displaying prominent mitoses. Despite its benign nature, CPMT can lead to fetal demise, postnatal respiratory distress, or complications from perinatal surgical resection. Although the morphologic and clinical features of CPMT are well described, its molecular features and oncogenesis remain elusive. Following the detection of EGFR kinase domain duplication (KDD) of exons 18 to 25 in an index case, we identified 3 additional cases of morphologically classic and clinically well-characterized CPMTs from the archives and performed targeted RNA- and DNA-based profiling via next-generation sequencing for detection of rearrangements, sequence variants, and copy number variants on all cases. Two cases were detected prenatally, 1 patient presented at birth, and 1 at 8 weeks of life. All tumors were resected, with a follow-up period ranging from 0 days to 10 years. One patient died shortly after surgical resection, and the other 3 had no recurrences. In all cases, EGFR KDD was detected. In 2 out of 4 cases, gains of select whole chromosomes were noted. Our findings establish EGFR KDD as a recurrent oncogenic driver of CPMT. Notably, this alteration is also found in classical congenital mesoblastic nephromas, infantile kidney tumors with which CPMTs share striking morphologic and clinical similarities. This strongly suggests that CPMTs and classical congenital mesoblastic nephromas share common oncogenesis, and represent the same tumor in different locations. EGFR KDDs have also been reported in neonatal soft tissue tumors with infantile fibrosarcoma-like histology and cartilaginous differentiation, raising questions about their relationship. EGFR KDD emerges as a diagnostic marker, a potential therapeutic target, and a window into the oncogenesis of a distinct subset of infantile mesenchymal tumors.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100661"},"PeriodicalIF":7.1,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693123","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}
引用次数: 0
Spread Through Air Spaces: Comment 通过空气传播:评论。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-14 DOI: 10.1016/j.modpat.2024.100634
Hinpetch Daungsupawong , Viroj Wiwanitkit
{"title":"Spread Through Air Spaces: Comment","authors":"Hinpetch Daungsupawong ,&nbsp;Viroj Wiwanitkit","doi":"10.1016/j.modpat.2024.100634","DOIUrl":"10.1016/j.modpat.2024.100634","url":null,"abstract":"","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"37 12","pages":"Article 100634"},"PeriodicalIF":7.1,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142639271","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}
引用次数: 0
Making Pathologists Ready for the New Artificial Intelligence Era: Changes in Required Competencies. 让病理学家为新人工智能时代做好准备:所需能力的变化。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-13 DOI: 10.1016/j.modpat.2024.100657
Shoko Vos, Konnie Hebeda, Megan Milota, Martin Sand, Jojanneke Drogt, Katrien Grünberg, Karin Jongsma
{"title":"Making Pathologists Ready for the New Artificial Intelligence Era: Changes in Required Competencies.","authors":"Shoko Vos, Konnie Hebeda, Megan Milota, Martin Sand, Jojanneke Drogt, Katrien Grünberg, Karin Jongsma","doi":"10.1016/j.modpat.2024.100657","DOIUrl":"10.1016/j.modpat.2024.100657","url":null,"abstract":"<p><p>In recent years, there has been an increasing interest in developing and using artificial intelligence (AI) models in pathology. Although pathologists generally have a positive attitude toward AI, they report a lack of knowledge and skills regarding how to use it in practice. Furthermore, it remains unclear what skills pathologists would require to use AI adequately and responsibly. However, adequate training of (future) pathologists is essential for successful AI use in pathology. In this paper, we assess which entrustable professional activities (EPAs) and associated competencies pathologists should acquire in order to use AI in their daily practice. We make use of the available academic literature, including literature in radiology, another image-based discipline, which is currently more advanced in terms of AI development and implementation. Although microscopy evaluation and reporting could be transferrable to AI in the future, most of the current pathologist EPAs and competencies will likely remain relevant when using AI techniques and interpreting and communicating results for individual patient cases. In addition, new competencies related to technology evaluation and implementation will likely be necessary, along with knowing one's own strengths and limitations in human-AI interactions. Because current EPAs do not sufficiently address the need to train pathologists in developing expertise related to technology evaluation and implementation, we propose a new EPA to enable pathology training programs to make pathologists fit for the new AI era \"using AI in diagnostic pathology practice\" and outline its associated competencies.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100657"},"PeriodicalIF":7.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142623644","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}
引用次数: 0
Primary Vulvar and Vaginal Adenocarcinomas of Intestinal Type Are Closer To Colorectal Adenocarcinomas Than To Carcinomas of Müllerian Origin 原发性外阴和阴道肠型腺癌更接近结肠直肠腺癌,而不是穆勒氏来源的癌。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-09 DOI: 10.1016/j.modpat.2024.100649
Alexis Trecourt , Isabelle Treilleux , Daniel Pissaloux , Marie Donzel , Brice Thamphya , Franck Thirode , Aurélie Houlier , Sandrine Paindavoine , Tatiana Franceschi , Aline Baltrès , Witold Gertych , Pierre-Adrien Bolze , Pierre Antoine Chaix , Charlotte Roux-Terrier , Françoise Descotes , Isabelle Ray-Coquard , Jonathan Lopez , Mojgan Devouassoux-Shisheboran
{"title":"Primary Vulvar and Vaginal Adenocarcinomas of Intestinal Type Are Closer To Colorectal Adenocarcinomas Than To Carcinomas of Müllerian Origin","authors":"Alexis Trecourt ,&nbsp;Isabelle Treilleux ,&nbsp;Daniel Pissaloux ,&nbsp;Marie Donzel ,&nbsp;Brice Thamphya ,&nbsp;Franck Thirode ,&nbsp;Aurélie Houlier ,&nbsp;Sandrine Paindavoine ,&nbsp;Tatiana Franceschi ,&nbsp;Aline Baltrès ,&nbsp;Witold Gertych ,&nbsp;Pierre-Adrien Bolze ,&nbsp;Pierre Antoine Chaix ,&nbsp;Charlotte Roux-Terrier ,&nbsp;Françoise Descotes ,&nbsp;Isabelle Ray-Coquard ,&nbsp;Jonathan Lopez ,&nbsp;Mojgan Devouassoux-Shisheboran","doi":"10.1016/j.modpat.2024.100649","DOIUrl":"10.1016/j.modpat.2024.100649","url":null,"abstract":"<div><div>Primary vulvar and vaginal adenocarcinomas of intestinal type (VVAIts) are very rare tumors, displaying morphologic and immunohistochemical overlap with colorectal adenocarcinomas. However, their immunoprofile and genomics are poorly studied, and their origin is still debated. Here, we studied a series of 8 VVAIts (4 vulvar and 4 vaginal) using a large panel of immunohistochemistry and DNA and RNA sequencing with clustering analyses. All tumors shared a similar morphology with colorectal adenocarcinomas and diffuse CK20 and CDX2 expression. SATB2 diffuse positivity was observed in 62.5% of tumors and CK7 in 82.5%, whereas PAX8, SOX17, p16, and estrogen and progesterone receptors were always negative. A p53 mutated-type expression was observed in 75% of tumors. All tumors were mismatch repair proficient. Neither human papillomavirus DNA nor pathogenic transcript fusions were detected. The most frequent molecular alterations were <em>TP53</em> and <em>KRAS</em> variants in 71.4% and 42.9%, respectively. The transcriptomic analysis highlighted a robust VVAIts cluster distinct from endocervical, ovarian, lung, thyroid, salivary glands, breast, and renal carcinomas but failed to differentiate vulvar from vaginal intestinal-type tumors. On 2 different clustering analyses, VVAIts clustered altogether, very close to colorectal adenocarcinomas. Compared with endocervical adenocarcinomas of intestinal type, VVAIts had a significantly lower expression of <em>SOX17</em> and epithelial-mesenchymal transition genes and a higher mitogen-activated protein kinase pathway gene expression. These results suggest that Müllerian structures leading to cervical adenocarcinomas may undergo intestinal-type transdifferentiation via an epithelial-mesenchymal transition phenomenon. Conversely, mitogen-activated protein kinase pathway activation in VVAIts, which plays a major role in colorectal adenocarcinomas, may indicate a close relationship in the carcinogenesis of these tumors. Our results indicate that adenocarcinomas of intestinal type, in the distal vagina or vestibular vulva, might be a unique and single entity, probably originating from cloacogenic embryonic remnants and/or ectopic colorectal mucosae inclusions. An open question would be to explore the efficacy of systemic drugs prescribed in colorectal cancers, in VVAIts.</div></div>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"38 2","pages":"Article 100649"},"PeriodicalIF":7.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142623664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Weakly Supervised Classification of Mohs Surgical Sections Using Artificial Intelligence 利用人工智能对莫氏手术切片进行弱监督分类。
IF 7.1 1区 医学
Modern Pathology Pub Date : 2024-11-09 DOI: 10.1016/j.modpat.2024.100653
Daan J. Geijs , Lisa M. Hillen , Stephan Dooper , Veronique Winnepenninckx , Vamsi Varra , David R. Carr , Kathryn T. Shahwan , Geert Litjens , Avital Amir
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