Uterine tumor resembling ovarian sex cord tumor (UTROSCT) constitutes an exceptionally rare histological subset of uterine mesenchymal neoplasms. While most cases have benign clinical behavior, a subset of UTROSCTs exhibits clinically aggressive behavior characterized by recurrence and metastasis. Here, we present a cohort of 25 UTROSCT cases molecularly confirmed by recurrent fusion gene detection, including ESR1::NCOA3 (n = 12), GREB1::NCOA1 (n = 6), ESR1::NCOA2 (n = 3), GREB1::NCOA2 (n = 2), GREB1::SS18 (n = 1), and GREB1::CTNNB1 (n = 1). Notably, six cases (6/25, 24%) demonstrated recurrence/metastasis: two cases showed intrauterine recurrence (harboring ESR1::NCOA3 and GREB1::NCOA1 fusions), while four developed extrauterine metastases (carrying ESR1::NCOA3, ESR1::NCOA2, GREB1::NCOA1, and GREB1::NCOA2 fusions), with one fatality. To dissect the biological basis of UTROSCT aggressiveness, we performed integrated clinicopathologic, immunohistochemical, and molecular profiling. Multivariate analysis identified tumor size >5 cm, FIGO stage IB, and lymphovascular space invasion (LVSI) as independent predictors of recurrence/metastasis, whereas histologic features, proliferation index, and fusion gene subtypes lacked prognostic significance. Multi-omics analysis of primary versus metastatic tumors revealed striking copy number variations (CNVs) exclusively in metastatic lesions. Specifically, heterozygous losses of SMARCB1 (2/4 metastatic cases) and ATRX (1/4 metastatic cases) were identified; both play critical roles in chromatin remodeling. These genetic alterations were conspicuously absent in primary tumors, suggesting their potential role in metastatic progression. Our findings represent the first demonstration of CNV-driven oncogenic evolution in UTROSCTs, particularly implicating SWI/SNF complex dysregulation in metastatic competence.

Fumarate hydratase-deficient uterine leiomyomas (FHd-ULMs) represent a molecularly distinct subgroup of smooth muscle tumours associated with hereditary leiomyomatosis and renal cell cancer (HLRCC) syndrome. This study determined the detection rate of germline pathogenic FH variants in FHd-ULMs using paired tumour-normal sequencing and assessed the utility of integrated morphological, immunohistochemical (FH/2SC), genomic, and clinical features for selecting cases suspected of HLRCC. Histopathological assessment of the 252 FHd-ULMs revealed consistent morphological features, whereas molecular profiling identified three biologically distinct categories. Germline FH-mutated (hereditary) cases constituted 35.7% (74/207) of this FHd-ULM cohort, four of which showed concomitant somatic copy-number alterations. This contrasted with the somatic-mutated subgroup, which comprised 50.7% (105/207), including 18.4% (38/207) with isolated somatic copy-number losses. The remaining 13.6% (28/207), though lacking detectable FH mutations, were classified with somatic-mutated cases as sporadic FHd-ULMs based on shared clinicopathological features. Molecular analysis identified shared variant distributions across exons 2-10, with exons 5 and 7 in the fumarate lyase domain emerging as the predominant mutational hotspots. Notably, truncating mutations showed significantly higher prevalence in hereditary cases versus somatic variants (p < 0.01). Clinically, hereditary FHd-ULMs presented at younger ages (< 45 years) and manifested more aggressive phenotypes, including elevated rates of infertility (54.1% versus 26.4%), multifocal tumour development (86.5% versus 53.4%), increased surgical interventions (44.6% versus 11.5%), and familial leiomyoma clustering (51.4% versus 24.2%). Our results identify germline FH mutations, which confer significant HLRCC risk, in 35.7% of FHd-ULMs, while somatic alterations account for the majority of cases. To ensure efficient resource allocation, we propose a stratified diagnostic approach: initial universal FH/2SC immunohistochemical screening for ULMs displaying ≥ 3 FH-deficient morphological features, followed by confirmatory genetic testing in high-risk individuals, defined by either aberrant FH/2SC immunoreactivity or, in immunohistochemically normal cases, age < 45 years together with a personal/family history of multiple symptomatic leiomyomas or HLRCC-associated neoplasms. © 2026 The Pathological Society of Great Britain and Ireland.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morphological ambiguity, leading to delayed diagnosis. Despite the availability of molecular and genomic assays, their high cost, complexity, and limited reproducibility restrict clinical use. This study therefore proposes a highly sensitive artificial intelligence (AI)-assisted diagnostic system for GAS based exclusively on H&E-stained histopathological images. We included 309 slides from 96 GAS cases collected at Peking University Third Hospital from January 2018 to January 2025, representing the largest GAS cohort reported to date for AI research. In addition, we incorporated other morphologically analogous diseases, encompassing a total of 1,320 slides sourced from four categories: normal cervical mucosa (NORM), benign endocervical lesion entities (BELE), HPV-associated adenocarcinoma (HPVA), and endometrioid carcinoma with mucinous differentiation (ECMD). We developed GASPath, based on a novel multiple instance learning framework that efficiently captures fine-grained morphological variations from H&E-stained images. Beyond internal validation, GASPath was evaluated across 12 independent retrospective cohorts and further subjected to large-scale real-world validation on more than 7,000 samples from March 2024 to April 2025. Across three stages, GASPath demonstrated high performance. In internal validation (Stage I), it achieved an accuracy of 0.980 (95% CI 0.977-0.983) and an ROC-AUC of 0.995 (95% CI 0.994-0.997). In external validation (Stage II), the sensitivity reached 0.902 and improved to 0.968 with proposed strategies. For biopsy samples, GASPath achieved an ROC-AUC of 0.990 (95% CI 0.984-0.997). In large-scale real-world deployment (Stage III, n = 7,056), GASPath achieved a balanced accuracy of 0.953, with 100% sensitivity for GAS (45/45 cases correctly identified). The heatmaps highlight morphological features of GAS that are easily underestimated, such as irregular, angulated glands, subtle loss of nuclear polarity, and mild cytologic atypia, which show substantial morphological overlap with other diagnostic categories. GASPath enables high-sensitivity detection of GAS in routine H&E-stained slides, obviating the need for extensive auxiliary testing while preventing underdiagnosis and misdiagnosis. This advancement addresses a critical gap by streamlining diagnostic workflows without compromising accuracy. Its implementation could enable cost-effective, scalable AI-assisted diagnostics, potentially transforming the early detection and management of this aggressive cancer subtype.

BACKGROUND:Mutations in four major driver genes -KRAS, CDKN2A, TP53, and SMAD4- are central to the pathogenesis of pancreatic ductal adenocarcinoma (PDAC) and critically inform diagnosis, therapeutic decision-making, and prognostic assessment. Although next-generation sequencing (NGS) is widely regarded as the gold standard for detecting these mutations, its clinical application is often limited by suboptimal analytical efficiency and substantial economic cost. Among these genes, immunohistochemical (IHC) staining for the proteins encoded by TP53 and SMAD4 has been extensively adopted in routine pathology practice. However, standardized IHC pattern classification schemes and rigorous validation of their predictive accuracy for underlying genomic alterations remain lacking in PDAC. METHODS:We retrospectively enrolled 63 PDAC patients and systematically characterized the typical IHC expression patterns of p53 and Smad4. Targeted NGS was subsequently performed on all available tumor specimens, and the resulting mutational profiles were correlated with corresponding IHC findings. Diagnostic performance including sensitivity, specificity and accuracy of p53 IHC for predicting TP53 mutations and of Smad4 IHC for predicting SMAD4 mutations was rigorously evaluated. RESULTS:Among the four canonical driver genes, co-occurring double- or triple-gene mutations were prevalent; within TP53 and SMAD4, missense mutations constituted the most frequent variant type. Using NGS as the reference standard, we validated the diagnostic utility of a three-tiered p53 IHC classification system, particularly in fine-needle biopsy (FNB) specimens. Furthermore, we proposed a novel, refined Smad4 IHC pattern classification that incorporates an "intermediate" category, thereby expanding upon conventional binary interpretation. This new scheme achieved markedly improved mutation prediction accuracy (0.76) compared with traditional approaches (0.57). CONCLUSION:Our study highlights the complementary diagnostic value of p53 and Smad4 IHC relative to molecular testing in PDAC, especially when tissue is limited, as commonly encountered in FNB specimens. The newly established Smad4 IHC classification system, which integrates an intermediate expression category into the conventional two-tier framework, demonstrates superior clinical utility and enhances predictive accuracy for SMAD4 genomic alterations.

Tumor progression is accompanied by changes in architecture, morphology and microenvironmental organization, yet progression-associated heterogeneity is usually compressed into static diagnostic categories in histopathology. Here we present SpaTIE, a uterus-specific computational pathology framework that learns morphology-aware representations and organizes spatial histopathological heterogeneity into progression-associated tumor states. SpaTIE was developed using 10,426 uterine hematoxylin and eosin whole-slide images and evaluated in TCGA-UCEC and TCGA-UCS cohorts. The learned representations formed morphology manifolds, supported diagnostic, molecular and survival-related prediction tasks, and localized attention to informative tumor regions. Beyond supervised prediction, SpaTIE inferred tumor-state axes from cross-sectional morphology without temporal or molecular supervision. These morphology-derived states were spatially coherent and showed associations with clinicopathological variables and survival outcomes, while not simply recapitulating staging or diagnostic labels. Integrative multi-omics analyses linked the inferred states to DNA methylation, somatic copy-number variation, mutation, RNA-seq and RPPA profiles, highlighting molecular programs related to chromatin regulation, copy-number-associated structural variation, receptor tyrosine kinase signaling, cell adhesion, extracellular-matrix remodeling and metabolic adaptation. Progression-guided virtual perturbation further prioritized molecular features coupled to the morphology-derived state organization. Together, these findings suggest that uterine histopathology contains recoverable progression-associated tumor-state information and establish SpaTIE as a framework for connecting spatial morphology with multi-omics-informed tumor-state discovery.

SMARCA4-deficient uterine tumours encompass two distinct entities: SMARCA4-deficient undifferentiated/dedifferentiated endometrial carcinoma (SDUDEC) and SMARCA4-deficient uterine sarcoma (SDUS). Despite their divergent classifications, these tumours share overlapping clinicopathological and molecular features that complicate diagnosis. This study characterises their distinguishing features and clinical significance through analysis of 34 SDUDEC and 14 SDUS cases, integrating clinicopathological, immunohistochemical [BRG1 (encoded by SMARCA4), BRM (encoded by SMARCA2), INI1 (encoded by SMARCB1), ARID1A, ARID1B, SOX2, claudin-4, CK8/18, Chromogranin, synaptophysin, INSM1, p53, and MMR proteins], and next-generation sequencing (NGS; 14 SDUDEC and 14 SDUS) data. SDUDEC patients were significantly older than SDUS patients, with a median age of 54 years (range 28-63) compared to 37 years (range 24-58) (p<0.01). SDUDEC exhibited marked immunohistochemical heterogeneity, whereas SDUS showed uniform profiles: all SDUS cases (10/10) demonstrated dual BRG1/BRM loss with preserved expression of other SWI/SNF complex proteins, absent claudin-4 (0/12) and SOX2 (0/8) expression, and no MMR deficiency (0/14) or mutant-type p53 (0/13). NGS revealed frequent endometrial carcinoma-associated alterations in SDUDEC but rarely in SDUS. Prognostic outcomes did not differ significantly (p>0.05). These findings highlight distinct molecular landscapes: SDUDEC aligns with endometrial carcinogenesis, while SDUS may arise via alternative SMARCA4-dependent mechanisms. A diagnostic algorithm combining endometrial carcinoma molecular classification, SWI/SNF protein testing, and thorough sampling is proposed. This study expands the clinicopathological and molecular spectrum of SMARCA4-deficient uterine tumours, underscoring the need for entity-specific management strategies.

Objective: To investigate the association between the microcystic, elongated, and fragmented (MELF) growth pattern and the prognosis of no specific molecular profile endometrial endometrioid carcinoma (NSMP-EEC). Methods: A retrospective study was conducted on 911 NSMP-EEC patients diagnosed at the Pathology Department of Peking University Third Hospital from January 2015 to September 2023. Complete hysterectomy specimens were obtained from these patients. Utilizing sanger sequencing, next generation sequencing and immunohistochemical techniques, we conducted endometrial carcinoma molecular classification according to WHO 2020 criteria, and identified clinical staging based on the International Federation of Gynecology and Obstetrics (FIGO) 2023 criteria. The primary endpoints were progression-free survival and disease-specific survival. Patients were divided into MELF (+) and MELF (-) groups based on the presence or absence of the MELF growth pattern, and clinicopathological characteristics were compared between the two groups. Kaplan-Meier survival curves were used to analyze the association between the MELF growth pattern and prognosis, and log-rank tests were performed to compare differences between groups. Results: The age of the 911 patients was (54.4±10.7) years, with a follow-up time [M (Q1,Q3)] of 24.0 (11.0, 41.0) months, and of which 147 patients (16.1%) belonged to the MELF (+) group. The MELF (+) group had a higher proportion of postmenopausal patients and G1/G2, deep myometrial invasion, lymphovascular space invasion, and lymph node metastasis, higher FIGO stages, higher ESGO risk groups, and higher tumor recurrence rates compared to the MELF (-) group (all P<0.05). The cumulative 5-year progression-free survival rate for MELF (-) and MELF (+) patients were 92.2% and 85.8%, respectively (P=0.015). In the G1/G2 NSMP-EEC cohort, the cumulative 5-year progression-free survival rate for MELF (-) and MELF (+) patients were 94.2% and 86.6%, respectively (P=0.003). The prognosis of NSMP-EEC patients with 2023 FIGO stage I was better, exhibiting a cumulative 5-year progression-free survival rate of 95.2% and a cumulative 5-year disease-specific survival rate of 99.1%, respectively, and MELF (+) was not associated with a decrease in either the cumulative progression-free survival rate (P=0.213) or the cumulative disease-specific survival rate (P=0.373) of patients. Conclusions: In NSMP-EEC patients, MELF (+) is associated with various adverse clinicopathological indicators and increased recurrence risk, providing a simple and rapid morphological indicator for risk stratification. The prognosis of NSMP-EEC patients with 2023 FIGO stage Ⅰis better, and the use of MELF alone is insufficient for risk stratification.

ABSTRACTBackgroundCervical cancer poses a significant threat to women's health and encompasses various histological types, including squamous cell carcinoma (SCC), cervical adenocarcinoma (CA), and adenosquamous carcinoma. CA, in particular, presents a formidable challenge in clinical management due to its low early detection rate, pronounced aggressiveness, high recurrence rate, and mortality, compounded by the complexities associated with late‐stage treatment. There is limited understanding of the similarities and differences in the pathogenesis mechanisms between CA and SCC, such as tumor heterogeneity and the tumor immune microenvironment (TME).MethodsA literature search was carried out in the PubMed, Web of Science, and Google Scholar databases using the following research terms: “gynecological oncology,” “cervical cancer,” “cervical adenocarcinoma,” “epidemiology,” “diagnosis and treatment of cervical adenocarcinoma,” “Human papillomavirus,” “World Health Organization,” “tumor microenvironment,” “single‐cell RNA sequencing,” “molecular mechanism,” and “preclinical research model.”ConclusionThis review consolidates the epidemiological characteristics, diagnostic and therapeutic hurdles, and the latest advances in research on CA. It aims to highlight the significant heterogeneity of the TME characteristics exhibited by CA compared to SCC. Additionally, we also summarize the common preclinical models for CA and discuss the advantages and disadvantages of using various models in research. We aspire that the discussions presented herein will offer novel insights and directions for subsequent research, as well as clinical diagnosis and treatment strategies for CA.

Background:Evaluating the risk of metastasis at diagnosis and the likelihood of future recurrence is crucial for the effective management of endometrial cancer (EC). While conventional prognostic indicators hold importance, they often fall short in predicting recurrence, especially in low-risk patients. This study evaluates the prognostic value of the lymphocyte-to-monocyte ratio (LMR) for overall survival (OS), disease-free survival (DFS), and cancer-specific survival (CSS) in EC patients. Methods:Eligible studies that provided pretreatment cutoff values of LMR, hazard ratios (HRs), and 95% confidence intervals (CIs) for OS, DFS, CSS, and progression-free survival (PFS) were included in this meta-analysis. Two independent reviewers collected and evaluated the data, and the quality of the included studies was assessed using the Newcastle Ottawa Quality Assessment Scale (NOS). Statistical analyses were performed using STATA software, and subgroup analyses were conducted by race, sample size, and age to assess the consistency of LMR's prognostic value across different population groups. Results:In this meta-analysis, eight studies were included for OS (1,997 patients) and five studies were included for DFS (1,590 patients). LMR was significantly associated with OS (HR 2.29; 95% CI [1.50-3.51]; p = 0.0014), DFS (HR 4.00; 95% CI [1.76-9.07]; p = 0.0094), and CSS (HR, 1.58; 95% CI [1.11-2.25]; p = 0.01). Subgroup analysis indicated that the prognostic value of LMR for OS was consistent across different races, age groups, and sample sizes. However, the correlation between LMR and DFS was influenced by median age, with younger patients (<60 years) showing a stronger association. Sensitivity analyses confirmed the robustness of these results, and Egger's test showed no significant publication bias. Discussion:LMR serves as a valuable prognostic marker for OS, DFS, and CSS in EC patients. Its predictive power remains significant across diverse population groups, underscoring its potential utility in clinical practice. Biological mechanisms linking inflammation and cancer support the role of LMR in prognosis, given the functions of lymphocytes and monocytes in tumor progression and immune response. These findings suggest that incorporating LMR into current prognostic models could enhance risk stratification for EC patients, particularly for identifying those at higher risk of recurrence despite being classified as low risk by traditional systems. In conclusion, LMR is a robust, independent prognostic factor for EC, with significant implications for improving patient management and outcomes through better risk stratification.

In this study, to evaluate the diagnostic accuracy and clinical reliability of intraoperative frozen sections (IFS) compared with paraffin-embedded sections (PS) in guiding surgical decision-making for endometrial carcinoma (EC) patients, we retrospectively analyzed the clinical data of 165 EC patients who underwent surgical resection with IFS evaluation. Diagnostic concordance between IFS and final PS pathology was assessed across six parameters: 1) tumor histological type, 2) tumor grade, 3) depth of myometrial invasion (MI), 4) cervical stromal involvement, 5) lymphovascular space invasion (LVSI) status, and 6) lymph node metastasis risk stratification. The data were statistically analyzed using Kappa coefficient and chi-square test. The IFS results concurred with the PS in 95.3 % for histological type (kappa 0.859, p = 0.125), 94.0 % for tumor grade (kappa 0.848, p = 0.039), 97.6 % for depth of MI (kappa 0.929, p = 0.046), 95.2 % for cervical involvement (kappa 0.481, p = 0.008), and 88.5 % for LVSI (kappa 0.155, p < 0.001). Risk assessment was accurately determined in 92.1 % of cases (kappa 0.796, p < 0.001). Final histopathology confirmed pelvic and paraaortic lymph node metastases in two patients whose metastatic risk had been underestimated based on the IFS risk stratification. High-intermediate/high-risk patients showed significantly higher lymph node involvement compared to low/intermediate-risk groups. IFS analysis demonstrates reliability and clinical utility in assessing disease extent and guiding surgical decisions regarding the need for complete staging procedures in EC patients.

Ovarian GLI1 fusion tumors are rare mesenchymal neoplasms that closely mimic sex cord-stromal tumors (SCSTs) in both morphology and immunophenotype, frequently leading to misdiagnosis. In this study, we identified five such cases through re-evaluation of SCST-like ovarian tumors. Histologically, three distinct patterns were observed: the spindle pattern, the stellate/microcystic pattern and the epithelioid pattern. Immunophenotypically, all cases showed overlapping features with SCSTs, including CD10 expression and variable positivity for sex cord-stromal markers such as FOXL2, SF1, and Calretinin. Molecular analysis revealed recurrent ACTB::GLI1 fusions in four cases and a novel FUBP1::GLI1 fusion in one. Meta-analysis integrating our cases with ten previously reported ovarian GLI1 fusion tumors showed that these tumors predominantly occur in middle-aged women and present as significantly larger masses than their soft tissue and solid organ counterparts (P < 0.05). Notably, the relapse and metastasis rates of ovarian GLI1 fusion tumors were similar to adult granulosa cell tumors (AGCTs). In contrast, their recurrence rate was significantly higher than that of microcystic stromal tumors (MCSTs) (P < 0.05), indicating a more aggressive clinical course. Transcriptomic analysis revealed no significant correlation between ovarian GLI1 fusion tumors and sclerosing stromal tumors. These findings underscore the necessity of molecular testing for GLI1 rearrangements in SCST-like ovarian tumors to ensure accurate diagnosis and appropriate clinical management.

Uterine smooth muscle tumors (USMTs) are the most common tumors of the female reproductive system, but remain diagnostically challenging due to morphological overlap among leiomyosarcoma (LMS), various leiomyoma (LM) subtypes, and smooth muscle tumors of uncertain malignant potential (STUMP). This study aimed to develop a weakly supervised artificial intelligence (AI) model for classifying USMTs as benign or malignant using only slide-level labels. A multi-center dataset comprising 94 LMS cases (408 whole-slide images, WSIs) and 634 benign cases (1389 WSIs) was used for model training and internal testing, with an independent external test set including 27 LMS cases (54 WSIs) and 90 benign cases (248 WSIs). The CAMEL2-based model achieved excellent diagnostic performance, with AUCs of 0.9976 and 0.9889 on the internal and external test sets, respectively, and accuracies exceeding 0.97. Heatmaps frequently highlighted regions enriched for key pathological features of LMS, while benign tissues were consistently assigned low-suspicion regions. In STUMP cases, heatmaps emphasized morphologically suspicious regions that often overlapped with areas identified by pathologists, supporting their potential as decision-support visualizations. In the AI-human collaboration study, model assistance was associated with improved diagnostic accuracy and reduced diagnostic time. This represents the first weakly supervised learning model for USMT diagnosis, achieving high accuracy and interpretability with minimal annotation requirements.

Objective: To investigate the clinicopathological characteristics and molecular features of synchronous endometrial and ovarian endometrioid carcinoma (SEO-EC). Methods: A total of 28 patients diagnosed with SEO-EC at the Peking University Third Hospital, Hunan Cancer Hospital and Peking University People's Hospital between September 2016 and July 2023 were included retrospectively. Next-generation sequencing (NGS) was performed to assess the clonal relatedness of 28 paired endometrial and ovarian tumors. Extra-uterine-ovarian disease specimens in four patients diagnosed with SEO-EC were further tested with comprehensive NGS analysis. Normal tissue/blood samples of 27 patients were available for NGS analysis. All cases were classified according to WHO 2020 histologic criteria and FIGO 2023 staging system. Relevant clinicopathological features were also analyzed. Results: The age of 28 patients was (47.3±8.5)years. Most patients (85.7%, 24/28) were premenopausal. In most instances, ovarian and endometrial carcinomas exhibited consistent morphology (82.1%, 23/28) as well as molecular subtypes (96.4%, 27/28). NGS confirmed a clonal relationship in all cases. The most common somatic mutations shared between endometrial and ovarian tumors were PTEN (64.3%, 18/28), PIK3CA (46.4%, 13/28), ARID1A (28.6%, 8/28), CTNNB1 (25.0%, 7/28), and KRAS (21.4%, 6/28). A majority of patients (82.1%, 23/28) exhibited a favorable prognosis, with only 5 patients identified as the WHO high-risk group and FIGO advanced-stage experiencing recurrence and tumor-specific death. In addition, 22.2% (6/27) of patients carried pathogenic germline mutations. Conclusions: In this study, there is a high degree of concordance between the histologic and molecular subtypes of the endometrial and ovarian tumors in SEO-EC. We confirmed a clonal relationship in all tested paired SEO-EC. Patients identified as the WHO high-risk group and advanced FIGO stages may exhibit a poor prognosis in SEO-EC.

Background Ovarian cancer is among the most lethal gynecologic malignancy that threatens women's lives. Pathological diagnosis is a key tool for early detection and diagnosis of ovarian cancer, guiding treatment strategies. The evaluation of various ovarian cancer-related cells, based on morphological and immunohistochemical pathology images, is deemed an important step. Currently, the lack of a comprehensive deep learning framework for detecting various ovarian cells poses a performance bottleneck in ovarian cancer pathological diagnosis. Method This paper presents OCDet, an object detection model with channel attention, which achieves comprehensive detection of CD3, CD8, and CD20 positive lymphocytes in immunohistochemical pathology slides, and neutrophils and polyploid giant cancer cells in H&E slides of ovarian cancer. OCDet, utilizing CSPDarkNet as its backbone, incorporates an Efficient Channel Attention module for Resolution-Specified Embedding Refinement and Multi-Resolution Embedding Fusion, enabling the efficient extraction of pathological features. Result The experiment demonstrated that OCDet performed well in target detection of three types of positive lymphocytes in immunohistochemical images, as well as neutrophils and polyploid giant cancer cells in H&E images. The mAP@0.5 reached 98.82 %, 92.91 %, and 90.49 % respectively, all surpassing other compared models. The ablation experiment further highlighted the superiority of the introduced Efficient Channel Attention (ECA) mechanism. Conclusion The proposed OCDet enables accurate detection of multiple types of cells in immunohistochemical and morphological pathology images of ovarian cancer, serving as an efficient application tool for pathological diagnosis thereof. The proposed framework has the potential to be further applied to other cancer types.

原发性子宫卵黄囊瘤是一种极为罕见的恶性肿瘤，其与非典型息肉样腺肌瘤（atypical polypoid adenomyoma，APA）和子宫内膜样癌（endometrial endometrioid carcinoma，EEC）共存更为罕见。本文报道了1例APA恶变为EEC，局灶逆分化为卵黄囊瘤的病例，全外显子测序显示在上皮肿瘤区域（APA和EEC）及卵黄囊瘤区域检测到共同的PTEN、AMPD1、SLC22A5和MBL2的基因突变，且在卵黄囊瘤区域发现额外的CTNNB1基因突变。同时，我们进行相关文献的全面回顾，以期更深入了解体细胞起源的子宫卵黄囊瘤临床病理及分子遗传学特征。

Incorporation of pathological and (not mandatory) molecular features into the new FIGO 2023 staging system has generated some controversy. Several validations have been published recently that demonstrated the higher prognostic precision of FIGO 2023 compared to the previous FIGO 2009 scheme. In the present article, the authors want to respond to some concerns that were raised by some pathologists and clinicians.

Synchronous endometrial and ovarian endometrioid carcinoma, which simultaneously involves the endometrium and ovary, is a relatively rare entity among gynecological cancers. Precise diagnosis and risk stratification are crucial for disease management. We present a unique case of a 40-year-old woman diagnosed with synchronous endometrial and ovarian endometrioid carcinoma carrying a monoallelic pathogenic MUTYH germline variant. Despite the histological morphology of the right ovarian tumor exhibiting some differences compared to the uterine tumor, we identified three identical somatic mutations shared between the uterine tumor and right ovarian tumor, along with four additional mutations exclusive to the uterine tumor, through the utilization of massively parallel sequencing of a 196-gene panel. These findings enabled us to elucidate the clonal relatedness and potential clonal evolution of the tumor across the two anatomical sites. Furthermore, in accordance with the 2023 FIGO staging system, the patient was diagnosed with Stage IIIB2 uterine cancer, and consequently, adjuvant radiation and chemotherapy were administered after surgery. She is being followed periodically and is normal 15 months after surgery. To the best of our knowledge, this study presents the first case of a patient with synchronous endometrial and ovarian endometrioid carcinoma harboring a monoallelic pathogenic MUTYH germline variant.

卵巢恶性生殖细胞肿瘤主要受累人群为青少年、对国家人口政策和生育健康具有重要意义。卵巢恶性生殖细胞起源于发育异常、未凋亡的生殖细胞，目前，其病理学分型主要依据形态学进行分类，尚未纳入起源细胞的遗传学事件。依据对女性生殖细胞发育历程的新认识，本文将通过全面介绍和对比卵巢、睾丸及儿童生殖细胞肿瘤的研究进展，以期更加深入了解较为常见的几种卵巢恶性生殖细胞肿瘤的遗传学特征，进而辅助理解各亚型普通谱系分化的原因以及寻找用于临床诊断、监测的潜在靶点。.

基于替代标志物的子宫内膜癌分子分型已在临床实践中得到广泛推广应用。尽管大部分子宫内膜癌病例能够通过单一的分子特征进行分类, 但仍有3.0%～11.4%的子宫内膜癌表现出复杂的"多重分子特征", 涵盖了POLE基因突变、TP53基因突变和错配修复缺陷等多重组合方式。目前, 针对这些具有多重分子特征的子宫内膜癌, 其分类标准和治疗策略仍存在较大的争议。本文旨在对这些具有"多重分子特征"子宫内膜癌的分子机制进行全面综述, 以期深化对这一特殊类型子宫内膜癌的理解和认识, 从而为临床决策提供更为精准和全面的依据。

Endocervical gastric-type adenocarcinoma (GAS) is an aggressive type of endocervical mucinous adenocarcinoma characterized as being unrelated to human papillomavirus (HPV) and resistant to chemo/radiotherapy. In this study, we investigated the histology, immunohistochemistry patterns, and molecular characteristics in a large cohort of GAS (n = 62). Histologically, the majority of GAS cases exhibited a distinct morphology resembling gastric glands, although 2 exceptional cases exhibited HPV-associated adenocarcinoma morphology while retaining the characteristic histology of GAS at the invasive front. By immunohistochemistry, Claudin18.2 emerged as a highly sensitive and specific marker for GAS. Additionally, the strong expression of Claudin18.2 in patients with GAS indicated the potential of anti-Claudin18.2 therapy in the treatment of GAS. Other immunohistochemistry markers, including Muc6, p16, p53, Pax8, ER, and PR, may provide additional diagnostic clues for GAS. Quantitative methylation analysis revealed that the overexpression of Claudin18.2 in GAS was governed by the hypomethylation of the CLDN18.2 promoter CpG islands. To further elucidate the pathogenic mechanisms of GAS and its relationship with gastric adenocarcinoma, we performed whole exome sequencing on 11 GAS and 9 gastric adenocarcinomas. TP53, CDKN2A, STK11, and TTN emerged as the most frequently mutated genes in GAS. Mutations in these genes primarily affected cell growth, cell cycle regulation, senescence, and apoptosis. Intriguingly, these top mutated genes in GAS were also commonly mutated in gastric and pancreaticobiliary adenocarcinomas. Regarding germline variants, we identified a probably pathogenic variant in SPINK1, a gene linked to hereditary pancreatic cancer syndrome, in one GAS sample. This finding suggests a potential pathogenic link between pancreatic cancers and GAS. Overall, GAS exhibits molecular characteristics that resemble those observed in gastric and pancreaticobiliary adenocarcinomas, thereby lending support to the aggressive nature of GAS compared with HPV-associated adenocarcinoma.