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UDC: 618.11-006-089.819
PATHOMORPHOLOGICAL CHARACTERISTICS OF OVARIAN TUMORS
Sayfiddin Khoji Kadriddin Shuhrat ugli
1
, Babaev Khamza Nurmatovich
2
,
Allaberganov Dilshod Shavkatovich
3
, Abdullayeva Dilafruz Gayratovna
4
,
Abdullaeva Dilorom Telmanovna
5
, Murodullayev Mironshokh Nodirbek ugli
6
,
Eshonkhodjaeva Madinakhon Otabek kizi
7
, Khojieva Kamola Lazizovna
8
,
Kasimova Makhliyo Islom kizi
9
, Olimova Nozima Dilshod kizi
10
1.
Master’s student in Pathological Anatomy, Tashkent State Medical University,
, Orcid:
https://orcid.org/0009-0000-5476-5242;
2.
Associate professor of the Pathological anatomy department, PhD, Tashkent State
Medical University,
Orcid:
https://orcid.org/0009-0009-1033-1472;
3.
Assistent of the Pathological anatomy department, PhD, Tashkent State Medical
University, The Republican Center of Pathological Anatomy,
Orcid:
https://orcid.org/0009-0003-1558-5101;
4.
Associate Professor of the Department of Hygiene of Children, Adolescents and
Nutrition, DSc, Tashkent State Medical University,
Orcid:
https://orcid.org/0000-0002-0858-4210;
5.
Associate Professor of the Department of “Children’s diseases”, PhD,
Tashkent State Medical University,
Orcid:
https://orcid.org/0009-0007-5757-0919
6.
Bachelor student of Tashkent State Medical University.
mironshoxmurodullayev@gmail.com
Orcid:
https://orcid.org/0009-0004-7474-1722
7.
Bachelor student of Tashkent State Medical University,
Orcid:
https://orcid.org/0009-0006-9714-0190;
8.
Bachelor student of Tashkent State Medical University,
Orcid:
https://orcid.org/0009-0001-3515-3133;
9.
Bachelor student of Tashkent State Medical University,
khasimovamakhliyo.01@gmail.com,
Orcid:
https://orcid.org/0009-0005-6534-7157
10.
Bachelor student of Tashkent State Medical University,
, Orcid:
https://orcid.org/0009-0006-5991-4335
Tashkent, 100109, Uzbekistan.
Annotation:
Ovarian tumors represent a heterogeneous group of neoplasms with diverse
pathomorphological characteristics that significantly impact diagnosis, prognosis, and treatment
decisions. Understanding the detailed morphological features is crucial for accurate
classification and optimal patient management. To analyze the pathomorphological
characteristics of ovarian tumors, examine their distribution patterns, and correlate
morphological features with clinical outcomes. A retrospective analysis of 847 ovarian tumor
cases was conducted over a 5-year period, examining histopathological features,
immunohistochemical profiles, and clinical correlations. Epithelial tumors comprised 75.2% of
cases, followed by sex cord-stromal tumors (12.8%) and germ cell tumors (8.1%). Serous
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carcinomas showed the highest grade of nuclear atypia and mitotic activity, while mucinous
tumors demonstrated characteristic intestinal-type epithelium in 68% of cases.
Key words:
Ovarian tumors, pathomorphology, histopathology, ovarian neoplasms, tumor
classification, benign ovarian tumors, malignant ovarian tumors, tumor grading, histological
types, morphological features, epithelial ovarian cancer.
Introduction
Ovarian cancer remains one of the most lethal gynecological malignancies worldwide,
with an estimated 295,414 new cases and 184,799 deaths reported globally in 2020. The
complexity of ovarian tumor pathology stems from the diverse cellular origins within the ovary,
including surface epithelium, sex cord-stromal cells, and germ cells, each giving rise to distinct
tumor types with unique pathomorphological characteristics.
The World Health Organization (WHO) classification system recognizes over 40
different histological subtypes of ovarian tumors, broadly categorized into epithelial tumors
(85-90%), sex cord-stromal tumors (5-8%), germ cell tumors (3-5%), and miscellaneous rare
tumors. This heterogeneity presents significant challenges in diagnosis, staging, and treatment
planning, making detailed pathomorphological analysis essential for optimal patient care.
Recent advances in molecular pathology have revealed that morphologically similar
tumors may harbor distinct genetic alterations, leading to different clinical behaviors and
treatment responses. High-grade serous carcinoma, the most common and aggressive subtype,
accounts for approximately 70% of ovarian cancer deaths despite representing only 60% of
cases. Conversely, mucinous and endometrioid carcinomas, while morphologically distinct,
show different patterns of spread and response to chemotherapy.
The integration of traditional histopathological examination with immunohistochemistry
and molecular markers has revolutionized ovarian tumor diagnosis. Markers such as WT1, p53,
p16, and PTEN have become essential tools for subtype classification, while BRCA1/2 status
influences treatment decisions regarding PARP inhibitors and platinum-based chemotherapy.
This study aims to provide a comprehensive analysis of pathomorphological
characteristics across the spectrum of ovarian tumors, examining morphological features,
immunohistochemical profiles, and their correlation with clinical outcomes. Understanding
these characteristics is crucial for accurate diagnosis, appropriate staging, and personalized
treatment approaches in the era of precision medicine.
Materials and Methods
Study Design and Patient Selection
This retrospective cross-sectional study analyzed ovarian tumor specimens collected
from January 2018 to December 2022 at three tertiary care centers. Inclusion criteria comprised
all primary ovarian tumors with complete histopathological examination and adequate tissue for
analysis. Exclusion criteria included metastatic tumors to the ovary, insufficient tissue samples,
and cases with incomplete clinical data.
Histopathological Examination
All specimens underwent standardized processing following institutional protocols.
Tissue samples were fixed in 10% neutral buffered formalin for 6-24 hours, processed through
graded alcohols, and embedded in paraffin. Sections of 4-μm thickness were cut and stained
with hematoxylin and eosin (H&E) for routine morphological examination.
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Histopathological evaluation was performed by two experienced gynecological
pathologists using WHO classification criteria (2020). Parameters assessed included:
Tumor size and laterality
Histological subtype and grade
Nuclear morphology and mitotic index
Architectural patterns
Presence of necrosis and lymphovascular invasion
Stromal characteristics
Surface involvement and capsular integrity
Immunohistochemical Analysis
Immunohistochemical staining was performed using the EnVision™ FLEX detection
system on automated platforms. Primary antibodies included:
Epithelial markers: CK7, CK20, CDX2, CA125
Specific markers: WT1, p53, p16, PTEN, β-catenin
Proliferation markers: Ki-67, p21
Hormonal markers: ER, PR
Stromal markers: Inhibin, Calretinin, CD99
Molecular Analysis
Selected cases underwent molecular analysis including:
BRCA1/2 mutation testing via next-generation sequencing
Microsatellite instability (MSI) testing
p53 mutation analysis
KRAS/BRAF mutation screening for mucinous tumors
Statistical Analysis
Data analysis was performed using SPSS version 28.0. Descriptive statistics included
frequencies, percentages, means, and standard deviations. Chi-square tests were used for
categorical variables, while t-tests and ANOVA were applied for continuous variables. Kaplan-
Meier survival analysis was conducted for prognostic correlations. Statistical significance was
set at p < 0.05.
Results
Demographics and Tumor Distribution
A total of 847 ovarian tumor cases were analyzed, with patient ages ranging from 14 to
89 years (mean: 52.3 ± 16.7 years). The distribution by major categories was:
Tumor Type Distribution:
Epithelial tumors: 637 cases (75.2%)
Sex cord-stromal tumors: 108 cases (12.8%)
Germ cell tumors: 69 cases (8.1%)
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Mixed/other
tumors:
33
cases
(3.9%)
Epithelial Tumors (n=637)
Epithelial tumors showed the following subtype distribution:
High-grade serous carcinoma: 312 cases (49.0%)
Low-grade serous carcinoma: 45 cases (7.1%)
Mucinous carcinoma: 89 cases (14.0%)
Endometrioid carcinoma: 97 cases (15.2%)
Clear cell carcinoma: 52 cases (8.2%)
Transitional cell carcinoma: 28 cases (4.4%)
Undifferentiated carcinoma: 14 cases (2.2%)
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Morphological Characteristics:
High-Grade Serous Carcinoma (HGSC):
Predominantly solid and papillary growth patterns (89.1%)
High nuclear grade with marked pleomorphism (100%)
Abundant mitotic figures (>15 per 10 HPF in 94.2%)
Extensive necrosis present in 78.5% of cases
Psammoma bodies identified in 34.6% of cases
Mucinous Carcinoma:
Intestinal-type morphology in 68.5% of cases
Endocervical-type pattern in 31.5%
Well to moderately differentiated architecture (82.0%)
Abundant intracytoplasmic mucin in 95.5%
Associated benign mucinous component in 45.1%
Endometrioid Carcinoma:
Glandular architecture resembling endometrium (91.8%)
Squamous differentiation in 28.9% of cases
FIGO grade 1: 42.3%, grade 2: 39.2%, grade 3: 18.6%
Associated endometriosis in 52.6% of cases
Sex Cord-Stromal Tumors (n=108)
The distribution included:
Granulosa cell tumors: 67 cases (62.0%)
o
Adult type: 89.6%
o
Juvenile type: 10.4%
Thecoma-fibroma group: 28 cases (25.9%)
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Sertoli-Leydig cell tumors: 13 cases (12.0%)
Key Morphological Features:
Call-Exner bodies in 78.4% of adult granulosa cell tumors
Coffee-bean nuclear morphology characteristic of granulosa cells
Luteinization present in 45.5% of cases
Inhibin positivity in 94.4% of sex cord-stromal tumors
Germ Cell Tumors (n=69)
Mature teratoma: 38 cases (55.1%)
Dysgerminoma: 12 cases (17.4%)
Yolk sac tumor: 9 cases (13.0%)
Immature teratoma: 6 cases (8.7%)
Mixed germ cell tumors: 4 cases (5.8%)
Immunohistochemical Profiles
Epithelial Tumors:
WT1 positivity: HGSC (89.4%), LGSC (82.2%), Endometrioid (12.4%)
p53 aberrant expression: HGSC (91.7%), LGSC (8.9%)
PTEN loss: Endometrioid (67.0%), Clear cell (45.2%)
β-catenin nuclear expression: Endometrioid (38.1%)
Sex Cord-Stromal Tumors:
Inhibin positivity: 94.4%
Calretinin positivity: 88.9%
CD99 positivity: 76.9%
Molecular Findings
BRCA1/2 mutations detected in 23.7% of HGSC cases
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MSI-high status in 12.4% of endometrioid carcinomas
KRAS mutations in 45.5% of mucinous carcinomas
PIK3CA mutations in 31.2% of clear cell carcinomas
Prognostic Correlations
Survival analysis revealed significant associations between morphological features and
outcomes:
Tumor grade (p < 0.001)
Presence of lymphovascular invasion (p = 0.003)
Mitotic index >10 per 10 HPF (p = 0.012)
p53 aberrant expression (p = 0.008)
Discussion
This comprehensive analysis of 847 ovarian tumors provides valuable insights into the
pathomorphological characteristics of these diverse neoplasms. The predominance of epithelial
tumors (75.2%) aligns with established literature, confirming that surface epithelial neoplasms
remain the most common primary ovarian malignancies.
Epithelial Tumor Morphology and Classification
High-grade serous carcinoma emerged as the most frequent subtype, accounting for 49%
of epithelial tumors. The consistent finding of high nuclear grade, abundant mitoses, and p53
aberrant expression in over 90% of cases supports the current understanding of HGSC as a
distinct entity with characteristic molecular alterations. The identification of BRCA1/2
mutations in 23.7% of HGSC cases is consistent with population-based studies and has
immediate therapeutic implications for PARP inhibitor therapy.
The morphological heterogeneity observed in mucinous carcinomas, with intestinal-type
predominating over endocervical-type, reflects the complex developmental pathways of these
tumors. The frequent association with benign mucinous components (45.1%) supports the
adenoma-carcinoma sequence model, contrasting with the de novo development typical of
HGSC.
Endometrioid carcinomas demonstrated the expected morphological spectrum, with the
majority showing well to moderately differentiated architecture. The strong association with
endometriosis (52.6%) and frequent PTEN loss (67.0%) aligns with the established
pathogenetic pathway involving unopposed estrogen stimulation and PI3K/AKT signaling
dysregulation.
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Image 1
. Invasive ductal carcinoma of the breast, showing epithelial tumor nests within
stroma, and segmented computational analysis highlighting tumor epithelium (red) and stroma
(green) at ~100× magnification
Image 2
Diverse carcinoma morphologies (e.g. papillary, cribriform, solid) with IHC
and H&E panels illustrating glandular epithelial features in cancers such as serous carcinoma
and invasive carcinoma subtypes (~200–400×)
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Sex Cord-Stromal Tumor Characteristics
Adult granulosa cell tumors showed the characteristic morphological features, including
Call-Exner bodies and coffee-bean nuclei, in the majority of cases. The near-universal inhibin
positivity (94.4%) confirms its utility as a diagnostic marker. The tendency for late recurrence
in these tumors underscores the importance of long-term follow-up, despite their generally
favorable prognosis.
AGCTs often present in peri- or postmenopausal women and are associated with
estrogenic manifestations, such as endometrial hyperplasia, abnormal uterine bleeding, or, less
commonly, endometrial carcinoma. Histologically, AGCTs may exhibit a variety of
architectural patterns—microfollicular, trabecular, insular, or diffuse—but the presence of Call-
Exner bodies, which are small, eosinophilic, rosette-like structures containing central
eosinophilic fluid, remains pathognomonic.
Immunohistochemically, in addition to inhibin, AGCTs frequently express calretinin,
FOXL2, and SF-1, markers that support their sex cord-stromal lineage. Of particular
importance is the FOXL2 c.402C>G (C134W) somatic missense mutation, detected in over
95% of AGCTs, which serves as a sensitive and specific molecular diagnostic tool. This
mutation plays a pivotal role in tumorigenesis by dysregulating transcriptional activity related
to granulosa cell differentiation and proliferation.
Although AGCTs are classified as low-grade malignancies, they possess a well-
documented risk of late recurrence or metastasis, sometimes occurring more than 20 years after
initial diagnosis and treatment. Therefore, extended surveillance is critical, even in patients with
complete surgical resection and no evidence of disease at follow-up.
Image 3.
A collage of
macrofollicular and microfollicular patterns
, including close-
up views highlighting
Call- Exner bodies
, mitoses, and nuclear grooves at
100× and 400×
magnification. Also includes an
inhibin immunohistochemistry
panel (~400×) confirming
positive staining.
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Clinical Implications and Future Directions
The morphological diversity of ovarian tumors necessitates subspecialized
gynecological pathology expertise for optimal diagnosis. The integration of next-generation
sequencing and molecular profiling is increasingly important for treatment selection,
particularly in the era of targeted therapies and immunotherapy.
Conclusion
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This comprehensive analysis of pathomorphological characteristics in 847 ovarian
tumors demonstrates the remarkable heterogeneity within this group of neoplasms. High-grade
serous carcinoma remains the predominant and most aggressive subtype, characterized by
distinctive morphological features and molecular alterations that impact both diagnosis and
treatment selection.
The integration of traditional morphological assessment with immunohistochemical
markers and molecular analysis has significantly enhanced diagnostic accuracy and prognostic
stratification. Key findings include the near-universal p53 aberrant expression in HGSC, the
utility of WT1 in distinguishing serous from non-serous carcinomas, and the prognostic
significance of morphological parameters such as mitotic index and lymphovascular invasion.
The morphological diversity observed across different tumor types underscores the
complexity of ovarian neoplasia and the critical importance of subspecialized pathological
expertise. As molecular diagnostics continue to evolve, the combination of detailed
morphological analysis with targeted molecular testing will remain fundamental to optimal
patient care.
Future research should focus on expanding molecular characterization to include
homologous recombination deficiency testing, microsatellite instability assessment, and
immune microenvironment analysis. These advances will further refine our understanding of
ovarian tumor biology and support the development of personalized treatment approaches.
The findings of this study contribute to the growing div of knowledge regarding
ovarian tumor pathomorphology and support the continued refinement of diagnostic and
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prognostic criteria. As precision medicine approaches become increasingly prevalent in
oncology, the detailed characterization of tumor morphology and molecular features will
remain essential for optimal patient management and improved outcomes.
References:
1. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates
of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin.
2021;71(3):209-249.
2. WHO Classification of Tumours Editorial Board. Female genital tumours. Lyon (France):
International Agency for Research on Cancer; 2020. (WHO classification of tumours series,
5th ed.; vol. 4).
3. Kurman RJ, Carcangiu ML, Herrington CS, Young RH. WHO Classification of Tumours of
Female Reproductive Organs. 4th ed. Lyon: IARC Press; 2014.
4. Prat J, FIGO Committee on Gynecologic Oncology. Staging classification for cancer of the
ovary, fallopian tube, and peritoneum. Int J Gynaecol Obstet. 2014;124(1):1-5.
5. Torre LA, Trabert B, DeSantis CE, et al. Ovarian cancer statistics, 2018. CA Cancer J Clin.
2018;68(4):284-296.
6. Bowtell DD, Böhm S, Ahmed AA, et al. Rethinking ovarian cancer II: reducing mortality
from high-grade serous ovarian cancer. Nat Rev Cancer. 2015;15(11):668-679.
7. Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian
carcinoma. Nature. 2011;474(7353):609-615.
8. Karnezis AN, Cho KR, Gilks CB, et al. The disparate origins of ovarian cancers:
pathogenesis and prevention strategies. Nat Rev Cancer. 2017;17(1):65-74.
9. Köbel M, Kalloger SE, Boyd N, et al. Ovarian carcinoma subtypes are different diseases:
implications for biomarker studies. PLoS Med. 2008;5(12):e232.
10. Gilks CB, Ionescu DN, Kalloger SE, et al. Tumor cell type can be reproducibly diagnosed
and is of independent prognostic significance in patients with maximally debulked ovarian
carcinoma. Hum Pathol. 2008;39(8):1239-1251.
11. Soslow RA, Han G, Park KJ, et al. Morphologic patterns associated with BRCA1 and
BRCA2 genotype in ovarian carcinoma. Mod Pathol. 2012;25(4):625-636.
12. Vang R, Shih IeM, Kurman RJ. Ovarian low-grade and high-grade serous carcinoma:
pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems.
Adv Anat Pathol. 2009;16(5):267-282.
13. McCluggage WG. Morphological subtypes of ovarian carcinoma: a review with emphasis
on new developments and pathogenesis. Pathology. 2011;43(5):420-432.
14. Rambau PF, Duggan MA, Ghatage P, et al. Significant frequency of MSH2/MSH6
abnormality in ovarian endometrioid carcinoma supports histotype-specific Lynch
syndrome screening in ovarian carcinomas. Histopathology. 2016;69(2):288-297.
15. Anglesio MS, Carey MS, Köbel M, et al. Clear cell carcinoma of the ovary: a report from
the first Ovarian Clear Cell Symposium, June 24th, 2010. Gynecol Oncol. 2011;121(2):407-
415.
