Endocervical Adenocarcinoma Research Articles

Pelvic lymph node involvement and risk of recurrence in HPV-associated endocervical adenocarcinoma stage IA2-IB1 according to Silva's system in two Colombian cancer centers.

To compare the pelvic lymph node involvement and risk of recurrence in patients with human papillomavirus (HPV)-associated endocervical adenocarcinoma stage IA2-IB1 undergoing hysterectomy and/or trachelectomy plus lymphadenectomy, according to Silva's classification system. A retrospective cohort study was performed in two Colombian cancer centers. The cases were classified according to the Silva classification system. Clinical, surgical, and histopathological variables were evaluated. Recurrence risk was analyzed by patterns A, B, or C. A logistic regression model was performed for tumor recurrence. The Kaplan-Meier method was used to estimate overall survival and disease-free survival (DFS). A weighted kappa was performed to determine the degree of concordance between pathologists. A total of 100 patients were identified, 33% pattern A, 29% pattern B, and 38% pattern C. The median follow-up time was 42.5 months. No evidence of lymph node involvement was found in patients classified as A and B, while in the C pattern was observed in 15.8% (n = 6) of cases (P < 0.01). There were 7% of cases with recurrent disease, of which 71.5% corresponded to type C pattern. Patients with Silva pattern B and C had 1.22- and 4.46-fold increased risk of relapse, respectively, compared with pattern A. The 5-year DFS values by group were 100%, 96.1%, and 80.3% for patterns A, B, and C, respectively. For patients with early-stage HPV-associated endocervical adenocarcinoma, the type C pattern presented more lymph node involvement and risk of recurrence compared to the A and B patterns. The concordance in diagnosis of different Silva's patterns by independents pathologists were good.

A novel mitochondria-related core gene signature to predict the prognosis and evaluate tumour microenvironment in CESC single-cell validation.

Mitochondria and their related genes (MTRGs) are pivotal in the tumour microenvironment (TME) of cervical cancer, influencing prognosis and treatment response. This study developed a prognostic model using MTRGs to predict overall survival (OS) in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), aiming for personalized therapy. Analysing 14 MTRGs like ISCU and NDUFA11 through techniques such as univariate Cox regression, we found that a low mitochondrial (MT) score is associated with better survival, while a high MT score predicts poorer outcomes. The TME score, particularly influenced by CD8 T cells, also correlates with prognosis, with a high score indicating favourable outcomes. The interplay between MT and TME subtypes revealed that the best prognosis is seen in patients with a low MT and high TME score. Our findings highlight the role of MTRGs as potential biomarkers and therapeutic targets in cervical cancer, offering a novel approach to improving patient outcomes through a more nuanced understanding of mitochondrial function and immune interactions within the TME. This model presents a promising avenue for enhancing the precision of prognostic assessments in CESC.

Abstract 4970: Multi-modal machine learning approaches for predicting cancer type and Gleason grade leveraging public TCGA data

Abstract Introduction: To better understand the complex and challenging nature of diseases such as cancer and for improved diagnosis, it may require the combination of multiple data modalities, such as histopathological images and omics data such as RNA-seq. By integrating these heterogeneous but complementary data, a multimodal approach unites both worlds and could achieve better synergistic results compared to using a single modality. The growing availability of large datasets such as The Cancer Genome Atlas (TCGA) with more than 10000 patients made it possible to combine different modalities to train machine learning algorithms which offers great potential to address challenging cancer related research. In this proof of concept initiative we use machine learning approaches within an open-source framework in order to leverage the potential of multimodality (Histopathology Whole Slide Images (WSI) and Genomics/RNA-seq) to build predictive AI models for cancer type and prostate Gleason score, and provide a potential to develop a quality control step. Method: We used matched WSI and RNA-Seq profiles from TCGA, including 11093 samples and 30 cancer types to develop a pancancer classification model using both modalities. For prostate Gleason score prediction 401 patients were available. Both datasets were split into a train (70%) and test (30%) components. We used a late fusion approach where we combined the RNA-seq model (linear SVM) with the WSI model (Resnet18) by multiplying the probability scores of each single-modality model. Model performance was measured with the F1 metric. Results: For cancer type prediction, the multimodality model achieved an F1 score of 0.95 on the test set. About 40% of the cancer types benefited from a synergistic effect by combining the two modalities. Cancer types and percent increase in F1 scores, respectively, that benefit most by combining modalities are: Cervical squamous cell carcinoma and endocervical adenocarcinoma (4.23%), Cholangiosarcoma (6.66%) and Uterine carcinosarcoma (4%). Interestingly, in other cancer types the combination did not result in improved predictive scores compared to a single modality model, e.g. in Rectum adenocarcinoma, Sarcoma or Stomach adenocarcinoma. For Prostate cancer grading, Gleason score prediction of patterns 3/4/5, combined multi modality model earned 0.73 F1 outperforming the single modality models. Conclusion: By combining histopathology imaging and omics modalities we demonstrated synergistic effects in predictive power for both cancer-related research questions. We show improved predictive performance in 40% of the classified cancer types by taking both modalities. Imaging or omics modalities alone can be sufficient in some cases and their strengths are very problem-specific. Citation Format: Christian Wohlfart, Eldad Klaiman, Jacub Witkowski, Michael King, Jacob Gildenblat, Ofir Etz-Hadar, Mohammad Ashtari, Antoaneta Vladimirova. Multi-modal machine learning approaches for predicting cancer type and Gleason grade leveraging public TCGA data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4970.

Abstract 4930: Identification of CBX7 and PCDHB18 as novel prognostic biomarkers of cervical cancer: RNA-sequencing and machine learning analysis

Abstract Background- Cervical cancer, ranking fourth in prevalence among women worldwide, is highly preventable when diagnosed early. The advent of innovative technologies including bioinformatics and machine learning, is revolutionizing the discovery and development of novel biomarkers for cancer. Our study uniquely integrates artificial neural networks with RNA-sequencing data of cervical cancer patients. This combination enhances the accuracy and reliability of biomarker predictions, providing a better understanding of the potential clinical utility of the identified biomarkers. Methods- RNA-sequencing data and clinicopathological details of 304 Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) were obtained from the GDAC database (https://gdac.broadinstitute.org/). Differentially expressed genes (DEGs) were identified (P&amp;lt;0.05, |log2 fold change (FC)| &amp;gt; 1.5, false discovery rate (FDR) &amp;lt; 0.05). Pathway enrichment analysis was performed and protein-protein interactions of DEGs were constructed using the STRING database. Prognostic biomarkers were identified using Kaplan-Meier and Cox proportional hazard methods adjusted for potential confounders such as age, disease stage, and comorbidities (HR&amp;lt;1, p&amp;lt;0.05). Deep learning algorithms were applied for predictive marker identification, utilizing Weight by Correlation feature selection. The model used AUC (Area Under the Curve), accuracy, MSE (Mean Squared Error), and R2 (R-squared) as evaluation metrics in a 70-30 training-test split. A combined ROC curve assessed diagnostic biomarkers, validated externally with a GEO dataset on cervical cancer patients. Results- In our study, 4153 DEGs were identified. Pathway analysis revealed that key dysregulated genes play a pivotal role in extracellular matrix organization. The survival analysis identified that six upregulated genes (CT62, SLC7A5P1, C10orf110, FDPSL2A, TNFSF15, and TTLL13) and seven downregulated genes (BAI3, CBX7, DKFZp566F0947, PCDHB18, GRAPL, PCDHB19P, and C4orf38) decreased the overall survival in patients. The machine learning model demonstrated high predictive accuracy (AUC=1, accuracy=99.02%, R2=0.99), identifying twenty genes with a positive correlation to cervical cancer risk. Notably, CBX7 emerged as a prognostic and diagnostic biomarker (AUC=0.99, sensitivity=0.93, specificity=1.00). Conclusion- Our study uncovers the prognostic significance of two novel genes in cervical cancer: CBX7, a vital regulator of tumor suppression, and PCDHB18, a member of the protocadherin beta gene cluster functioning as a cell adhesion molecule. Downregulation of these genes is associated with decreased overall survival. Further functional analyses and validation of these candidate biomarkers are crucial to fully assess their potential clinical value in cervical cancer. Citation Format: Ghazaleh Pourali, Mohsen Zeinali, Mahshid Arastonejad, Nima Khalili-Tanha, Elham Nazari, Ghazaleh Khalili-Tanha, Adetunji T. Toriola. Identification of CBX7 and PCDHB18 as novel prognostic biomarkers of cervical cancer: RNA-sequencing and machine learning analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4930.

3D MR elastography-based stiffness as a marker for predicting tumor grade and subtype in cervical cancer

BackgroundIncreasing evidence has indicated that high tissue stiffness (TS) may be a potential biomarker for evaluation of tumor aggressiveness. PurposeTo investigate the value of magnetic resonance elastography (MRE)-based quantitative parameters preoperatively predicting the tumor grade and subtype of cervical cancer (CC). Study typeRetrospective. PopulationTwenty-five histopathology-proven CC patients and 7 healthy participants. Field strength/sequence3.0T, magnetic resonance imaging (MRI) (LAVA-flex) and MRE with a three-dimensional spin-echo echo-planar imaging. AssessmentThe regions of interest (ROIs) were manually drawn by two observers in tumors to measure mean TS, storage modulus (G′), loss modulus (G″) and damping ratio (DR) values. Surgical specimens were evaluated for tumor grades and subtypes. Statistical testsIntraclass correlation coefficient (ICC) was expressed in terms of inter-observer agreements. t-test or Mann-Whitney nonparametric test was used to compare the complex modulus and apparent diffusion coefficient (ADC) values between different tumor groups. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the diagnostic performance. ResultsThe TS of endocervical adenocarcinoma (ECA) group was significantly higher than that in squamous cell carcinoma (SCC) group (5.27 kPa vs. 3.44 kPa, P = 0.042). The TS also showed significant difference between poorly and well/moderately differentiated CC (5.21 kPa vs. 3.47 kPa, P = 0.038), CC patients and healthy participants (4.18 kPa vs. 1.99 kPa, P < 0.001). The cutoff value of TS to discriminate ECA from SCC was 4.10 kPa (AUC: 0.80), while it was 4.42 kPa to discriminate poorly from well/moderately differentiated CC (AUC: 0.83), and 2.25 kPa to distinguish normal cervix from CC (AUC: 0.88), respectively. There were no significant difference in G″, DR and ADC values between any subgroups except for comparison of healthy participants and CC patients (P = 0.001, P = 0.004, P < 0.001, respectively). Data conclusion3D MRE-assessed TS shows promise as a potential biomarker to preoperatively assess tumor grade and subtype of CC.

The Prognostic and Immune Significance of BZW2 in Pan-Cancer and its Relationship with Proliferation and Apoptosis of Cervical Cancer.

Basic leucine zipper and W2 domains 2 (BZW2), a member of the basic domain leucine zipper superfamily of transcription factors, has been implicated in the development and progression of various cancers. However, the precise biological role of BZW2 in pan-cancer datasets remains to be explored. This study aimed to assess the prognostic significance of BZW2 and its immune-related signatures in various tumors. Our study investigated the expression, epigenetic modifications, and clinical prognostic relevance of BZW2 using multi-omics data in different cancer types. Additionally, the immunological characteristics, tumor stemness, drug sensitivity, and correlation of BZW2 with immunotherapy response were explored. Finally, in vitro experiments were conducted to assess the impact of BZW2 knockdown on Hela cells, a cell line derived from cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). BZW2 exhibited elevated expression levels in various tumor tissues and significantly impacted the prognosis of different cancer types. BZW2 emerged as an independent prognostic factor in CESC. We found that copy number amplification and methylation levels of BZW2 were associated with its mRNA expression. Immunological analyses revealed that BZW2 shapes a non-inflamed immunosuppressive tumor microenvironment across multiple cancers. Furthermore, our cell experiments demonstrated that BZW2 knockdown reduced proliferation, migration, and apoptosis activities in CESC cells. BZW2 promotes cancer progression by shaping a non-inflamed immunosuppressive tumor microenvironment. Additionally, BZW2 was shown to significantly influence the proliferation, migration, and apoptosis of CESC cells.

Immunohistochemical p16 overexpression and Rb loss correlate with high-risk human papillomavirus infection in endocervical adenocarcinomas.

p16 is a sensitive surrogate marker for transcriptionally active high-risk human papillomavirus (HR-HPV) infection in endocervical adenocarcinoma (ECA); however, its specificity is not perfect. We examined p16 and Rb expressions by immunohistochemistry (IHC) and the transcriptionally active HR-HPV infection by mRNA in-situ hybridisation (ISH) with histological review in 108 ECA cases. Thirteen adenocarcinomas of endometrial or equivocal origin (six endometrioid and seven serous carcinomas) were compared as the control group. HR-HPV was detected in 83 of 108 ECA cases (77%), including five HPV-associated adenocarcinomas in situ and 78 invasive HPV-associated adenocarcinomas. All 83 HPV-positive cases showed consistent morphology, p16 positivity and partial loss pattern of Rb. Among the 25 cases of HPV-independent adenocarcinoma, four (16%) were positive for p16, and of these four cases, three of 14 (21%) were gastric type adenocarcinomas and one of 10 (10%) was a clear cell type adenocarcinoma. All 25 HPV-independent adenocarcinomas showed preserved expression of Rb irrespective of the p16 status. Similarly, all 13 cases of the control group were negative for HR-HPV with preserved expression of Rb, even though six of 13 (46%) cases were positive for p16. Compared with p16 alone, the combination of p16 overexpression and Rb partial loss pattern showed equally excellent sensitivity (each 100%) and improved specificity (100 versus 73.6%) and positive predictive values (100 versus 89.2%) in the ECA and control groups. Furthermore, HR-HPV infection correlated with better prognosis among invasive ECAs. The results suggest that the combined use of p16 and Rb IHC could be a reliable method to predict HR-HPV infection in primary ECAs and mimics. This finding may contribute to prognostic prediction and therapeutic strategy.

Intestinal adenocarcinoma of the uterine cervix with gastrointestinal metastasis

Introduction: Endocervical adenocarcinomas represent a very heterogeneous group of tumors. Mucinous adenocarcinoma of the intestinal type is a rare histologic variant. Clinical case: 38-year-old female patient, who consulted for abnormal uterine bleeding, as well as more frequent cycles accompanied by dysmenorrhea, denying any other added symptomatology. She also underwent speculoscopy where a verrucous lesion was found, hypervascularized at that time, a biopsy which reported endocervical mucosa with moderate chronic inflammation and papillary, mild vascular congestion, compatible with endocervical polyp and MRI with enlarged uterus with thickened endometrium myometrium and nodular endometriotic implant of cystic appearance in the cervical isthmus junction. Due to the persistence of the symptoms it was decided to perform a total hysterectomy by laparoscopy, intraoperatively moderately differentiated adenocarcinoma implants were observed, compatible with endocervical primary. It was decided not to continue with the surgical time for neoadjuvant chemotherapy management. Conclusion: Establishing the preoperative anatomopathologic diagnosis is decisive to improve the treatment to reduce morbidity and mortality of the patient.

Preoperative multimodal ultrasonic imaging in a case of Peutz-Jeghers syndrome complicated by atypical lobular endocervical glandular hyperplasia: a case report and literature review

BackgroundPeutz-Jeghers syndrome (PJS), an autosomal dominant multiple cancerous disorder, is clinically characterized by mucocutaneous macules and multiple gastrointestinal hamartomatous polyps. Gastric-type endocervical adenocarcinoma (G-EAC), a special subtype of cervical adenocarcinoma with non-specific symptoms and signs, is known to occur in approximately 11% of female patients with PJS.Case presentationHere, we report a case of PJS in a 24-year-old female with multiple mucocutaneous black macules who complained of vaginal discharge and menorrhagia. Moreover, we first described the multimodal ultrasonographical manifestations of PJS-correlated G-EAC. The three-dimensional reconstructed view of G-EAC on 3D realisticVue exhibited a distinctive “cosmos pattern” resembling features on magnetic resonance imaging, and the contrast-enhanced ultrasound displayed a “quick-up and slow-down” pattern of the solid components inside the mixed cervical echoes. We reported the multimodal ultrasonographical characteristics of a case of PJS-related G-EAC, as well as reviewed PJS-related literature and medical imaging features and clinical characteristics of G-EAC to provide insight into the feasibility and potential of utilizing multimodal ultrasonography for the diagnosis of G-EAC.ConclusionsMultimodal ultrasound can visualize morphological features, solid components inside, and blood supplies of the G-EAC lesion and distinguish the G-EAC lesion from normal adjacent tissues. This facilitates preoperative diagnosis and staging of PJS-related G-EAC, thereby aiding subsequent health and reproductive management for patients with PJS.

Regulation and tumor-suppressive function of the miR-379/miR-656 (C14MC) cluster in cervical cancer.

Cervical cancer (CC) is a key contributor to cancer-related mortality in several countries. The identification of molecular markers and the underlying mechanism may help improve CC management. We studied the regulation and biological function of the chromosome 14 microRNA cluster (C14MC; miR-379/miR-656) in CC. Most C14MC members exhibited considerably lower expression in CC tissues and cell lines in The Cancer Genome Atlas (TCGA) cervical squamous cell carcinoma and endocervical adenocarcinoma patient cohorts. Bisulfite Sanger sequencing revealed hypermethylation of the C14MC promoter in CC tissues and cell lines. 5-aza-2 deoxy cytidine treatment reactivated expression of the C14MC members. We demonstrated that C14MC is a methylation-regulated miRNA cluster via artificial methylation and luciferase reporter assays. C14MC downregulation correlated with poor overall survival and may promote metastasis. C14MC activation via the lentiviral-based CRISPRa approach inhibited growth, proliferation, migration, and invasion; enhanced G2/M arrest; and induced senescence. Post-transcriptional regulatory network analysis of C14MC transcriptomic data revealed enrichment of key cancer-related pathways, such as metabolism, the cell cycle, and phosphatidylinositol 3-kinase (PI3K)-AKT signaling. Reduced cell proliferation, growth, migration, invasion, and senescence correlated with the downregulation of active AKT, MYC, and cyclin E1 (CCNE1) and the overexpression of p16, p21, and p27. We showed that C14MC miRNA activation increases reactive oxygen species (ROS) levels, intracellular Ca2+ levels, and lipid peroxidation rates, and inhibits epithelial-mesenchymal transition (EMT). C14MC targets pyruvate dehydrogenase kinase-3 (PDK3) according to the luciferase reporter assay. PDK3 is overexpressed in CC and is inversely correlated with C14MC. Both miR-494-mimic transfection and C14MC activation inhibited PDK3 expression. Reduced glucose uptake and lactate production, and upregulation of PDK3 upon C14MC activation suggest the potential role of these proteins in metabolic reprogramming. Finally, we showed that C14MC activation may inhibit EMT signaling. Thus, C14MC is a tumor-suppressive and methylation-regulated miRNA cluster in CC. Reactivation of C14MC can be useful in the management of CC.

RNA-binding proteins signature is a favorable biomarker of prognosis, immunotherapy and chemotherapy response for cervical cancer

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) still present a huge threaten to women’s health, especially the local advanced patients. Hence, developing more effectiveness prognostic signatures is urgently needed. This study constructed and verified a robust RNA-binding proteins (RBPs) related signature through a series of bioinformatics methods and explored the biological function of hub RBP in vitro experiments. As a result, the 10 RBPs signature was successfully established and could act as an independent prognostic biomarker in CESC patients, which displayed the highest sensitivity and specificity in prognosis prediction compared with other clinicopathological parameters. The risk model also presented good performance in risk stratification among CESC patients. Besides, a nomogram was constructed based on pathological stage and the risk signature and exhibited satisfactory accuracy in prognosis prediction. Functional enrichment indicated that the risk signature mainly participated in immune-related pathways and cancer-related pathways, and the infiltration level of immune cells and immune checkpoints showed a significantly higher degree in low-risk patients compared with high-risk patients. Notably, the 10 RBPs signature act as a novel biomarker in immunotherapy and chemotherapy response. In addition, PRPF40B was selected as hub RBP and its transcription and translation levels were obviously increased in CESC tissues, as well as Hela and Siha cells. Knockdown of PRPF40B inhibits the proliferation, migration and invasion of Hela and Siha cells in vitro. In conclusion, our research provides a noticeable strategy in prognostic prediction among CESC patients, which may illuminate the prospect of CESC patients’ clinical outcome.

Retrospective analysis of cytology and high-risk HPV testing in 1067 endocervical adenocarcinomas and precursor lesions.

Cytology and high-risk human papilloma virus (hrHPV) cotesting is the mainstay in the detection of cervical carcinoma. Endocervical adenocarcinoma (EAC) is divided into HPV-associated adenocarcinoma (HPVA) and HPV-independent adenocarcinoma (HPVI) by the World Health Organization classification (2020). The detection effect of cotesting is suggested to be different among EAC subtypes and precursors, but has not well-documented yet. In this study, the authors retrospectively analyzed cotesting among adenocarcinoma in situ (AIS), HPVA, and HPVI. The cohort included 569 AIS and 498 EAC consisting of 371 (74.5%) HPVA, 111 (22.3%) HPVI, and 16 (3.2%) adenocarcinoma, not otherwise specified. The authors found that AIS patients were significantly younger than HPVA and HPVI (mean±SD, years: 40.7±8.6; HPVA, 44.8±9.3; HPVI, 50.0±11.3; p<.001) and had a higher prevalence of concurrent squamous intraepithelial lesions (75.5%, HPVA, 37.2%; HPVI, 12.6%; p<.001). The detection rate of hrHPV test or cytology was substantially higher in AIS and HPVA than in HPVI (97.7% and 90.2% vs. 16.5%, p<.001, or 71.1% and 71.9% vs. 60.7%, p=.042, respectively). Cytology and hrHPV cotesting was superior to a single test in the detection of EAC and AIS. The detection rate of cotesting amounted to 100% in AIS and 94.3% in HPVA but was substantially lower in HPVI (72.2%) (p<.001). The authors conclude that cytology and hrHPV cotesting can maximize the detection effect for HPVA and AIS but is not optimal for HPVI.

A Histopathologic Image Analysis for the Classification of Endocervical Adenocarcinoma Silva Patterns Depend on Weakly Supervised Deep Learning

25% of cervical cancers are classified as endocervical adenocarcinomas (EACs), which comprise a highly heterogeneous group of tumors. A histopathological risk stratification system known as the Silva pattern system was developed based on morphology. However, accurately classifying such patterns can be challenging. The objective was to develop a deep learning pipeline (Silva3-AI) that automatically analyzes whole-slide-image-based histopathological images and identifies Silva patterns with high accuracy. Initially, a total of 202 patients with EACs and histopathological slides were obtained from QLHSDU for developing and internally testing the Silva3-AI model. Subsequently, an additional 161 patients and slides were collected from seven other medical centers for independent testing. The Silva3-AI model was developed using a ViT and RNN architecture, utilizing multi-magnification patches, and its performance was evaluated based on class-specific AUROC. Silva3-AI achieved a class-specific AUROC of 0.947 for Silva A, 0.908 for Silva B, and 0.947 for Silva C on the independent test set. Notably, the performance of Silva3-AI was consistent with that of professional pathologists possessing 10 years of diagnostic experience. The findings in this study implicate Silva3-AI, which could predict Silva pattern in an interpretable manner, achieved comparable performance to that of experienced pathologists. Furthermore, the visualization of prediction heatmaps facilitated the identification of TME heterogeneity, which is known to contribute to variations in Silva patterns.

Prevalence and Pattern of GATA3 Immunohistochemical Expression in Female Genital Tract Adenocarcinomas.

GATA3 immunohistochemistry has been described as a highly sensitive marker in determining carcinomas of breast and urothelial origin. In the gynecologic system, it can be used as a marker to diagnose mesonephric or mesonephric-like carcinomas and trophoblastic tumors. The present study was performed to determine the diagnostic value of GATA3 in gynecological adenocarcinomas. A total of 187 samples from different types of endometrial, endocervical, and ovarian carcinomas were analyzed for intensity and percentage of GATA3 expression in tumor cells. The relationship between GATA3 expression and clinicopathological parameters was investigated. A total of 187 patients including 101 ovarian, 77 endometrial, and 9 endocervical adenocarcinomas were investigated. Weak and focal expression of this marker was observed in 5. 1% (4/77) endometrial, 12.9% (13/101) ovarian, and 11.1% (1/9) endocervical adenocarcinomas. The mean H score in all subtypes was less than 10.6 (2-35). There was no statistically significant correlation between GATA3 expression in tumor cells with clinical stage, and tumor recurrence or metastasis. GATA3 is infrequently, weak, or focally expressed in most of the common gynecological adenocarcinomas.

Trichorhinophalangeal Syndrome Type 1 Immunohistochemical Expression in Carcinomas of Gynecologic Origin.

Trichorhinophalangeal syndrome type 1 (TRPS1) is a new reportedly sensitive and specific immunohistochemical marker for carcinomas of breast origin, including triple-negative (estrogen receptor, progesterone receptor, and HER2) tumors. In our practice, we have observed a subset of cases of nonmammary carcinomas that are positive for TRPS1, with higher frequency in cytology effusion samples with metastatic gynecologic malignancies. This study aimed to evaluate the expression of TRPS1 in a large tissue cohort of Müllerian carcinomas. We retrospectively retrieved 105 cases of formalin-fixed paraffin-embedded gynecologic tumors from our surgical pathology archives. Cases corresponded to tumors of tubo-ovarian (17 high-grade serous carcinomas, 3 low-grade serous carcinomas, 2 clear cell carcinomas, and 8 endometrioid adenocarcinomas), endometrial (25 endometrioid adenocarcinomas, 8 serous carcinomas, 6 clear cell carcinomas, 12 carcinosarcomas, 1 dedifferentiated carcinoma, and 1 mesonephric-like adenocarcinoma), cervical (6 human papillomavirus [HPV]-associated squamous cell carcinomas [SCCs], 11 HPV-associated endocervical adenocarcinomas, and 2 HPV-independent gastric-type endocervical adenocarcinomas), and vulvar (2 HPV-independent SCCs and 1 HPV-associated SCC) origins. Immunohistochemistry for TRPS1 was performed in whole tissue sections and assessed for positivity (≥5% of nuclear labeling), distribution (focal: 5% to 49%, diffuse: 50% to 100%), and intensity (1+, 2+, 3+) in tumor cells. Positive TRPS1 staining was observed in 51.4% (54/105) of cases. Most tumors (64.8%) demonstrated diffuse labeling, while focal in 35.2%. Among positive cases, the intensity was predominantly 1+ (57.4%), followed by 2+ (33.3%) and 3+ (9.2%). Tumors with a high percentage of positivity overall consisted of tubo-ovarian (70%) and endometrial carcinomas (58.4%). TRPS1 immunostain is often expressed in gynecologic carcinomas. Awareness of this phenomenon is crucial when evaluating challenging cases in which the differential diagnosis includes a malignancy of breast origin, to avoid misclassification of the primary site.

Delving into the Role of Receptor-like Tyrosine Kinase (RYK) in Cancer: In Silico Insights into Its Diagnostic and Prognostic Utility

The RYK gene encodes a receptor-like tyrosine kinase crucial for several biological processes, including development, tissue homeostasis, and cancer. This study utilized data from the Cancer Genome Atlas Project (TCGA) to evaluate RYK expression at both mRNA and protein levels in various cancers, determine its prognostic significance, and explore its involvement in cancer-related signaling pathways. Elevated levels of RYK mRNA were identified in cholangiocarcinoma (CHOL), pancreatic adenocarcinoma (PAAD), glioblastoma multiforme (GBM), lung squamous cell carcinoma (LUSC), brain lower grade glioma (LGG), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LICH), esophageal carcinoma (ESCA), and colon adenocarcinoma (COAD), while RYK protein levels were observed to be increased in colon adenocarcinoma (COAD), GBM, LICH, cervical and endocervical adenocarcinoma (CESC), and breast invasive carcinoma (BRCA). Additionally, RYK overexpression correlated with poorer prognosis in several cancers, including PAAD, LICH, BRCA, ESCA, COAD, and CESC. Furthermore, RYK showed a positive correlation with the upregulation of multiple receptors and coreceptors in the WNT signaling pathway in various types of cancer. In terms of cancer-related signaling pathways, RYK was found to potentially interact with DNA damage, TSC/mTOR, PI3K/AKT, EMT, RTK, RAS/MAPK, ER hormone, AR hormone, and the cell cycle. This study provides new and previously unreported insights into the role of RYK in cancer biology.

PD-L1 Expression and Silva Invasion Pattern in Villoglandular Adenocarcinoma of the Uterine Cervix.

Villoglandular adenocarcinoma (VGA) of the uterine cervix is a rare subtype of endocervical adenocarcinoma in young women. Between 2007 and 2020, all women with endocervical adenocarcinoma were retrospectively reviewed to find patients with VGA. Eight patients in whom pure VGA had been diagnosed were included. The mean age at initial diagnosis was 36.3 years (range 24-46). After surgical treatment, patients were followed up for 59 months (range 16-150). To date, all patients are alive with no evidence of disease. Neither lymph node involvement nor lymphovascular invasion was found. Furthermore, we examined the samples with a focus on morphological invasion pattern (Silva), stromal tumor-infiltrating lymphocytes (sTILs), and immunohistochemical programmed death ligand-1 (PD-L1) expression. PD-L1 expression was observed in 7/8 using the combined positive score (cutoff≥1%), 1/8 of VGAs using the tumor proportion score (cutoff≥1%), and 7/8 using the immune cell (cutoff≥1%). Using combined positive score and immune cell, PD-L1 expression was seen in 7/8 of pattern B and C tumors, with significantly higher expression in tumors with destructive-type patterns ( P <0.05, A vs. B+C). Using tumor proportion score, no significant difference in PD-L1 expression was seen between VGAs with different invasion patterns. VGAs demonstrated twice higher sTILs in tumors with destructive-type invasion patterns. Our observations suggest that PD-L1 expression, tumor invasion patterns, and sTILs do not correlate with the excellent prognosis of pure VGA.

Risk Factors Affecting Clinical Outcomes of Low-risk Early-stage Human Papillomavirus-Associated Endocervical Adenocarcinoma Treated by Surgery Alone: Application of Silva Pattern.

This study aimed to report the clinical outcomes and risk factors for survival of patients with low-risk early-stage human papillomavirus-associated (HPVA) endocervical adenocarcinoma (EAC) treated with surgery alone. This retrospective study obtained the clinicopathological data of patients with early-stage HPVA EAC who underwent surgery between 2012 and 2018. The Silva pattern of invasion was determined by reviewing pathology slides. Locoregional recurrence-free survival (RFS), RFS, and overall survival were calculated, and the risk factors for survival were analyzed. One hundred seventeen patients with a median follow-up of 5.2 years (0.5-9.7yr) were included. The most common histologic type was usual (94/117, 80.3%). The Silva pattern was A in 79 patients (67.5%), B in 30 (25.6%), and C in 8 (6.8%). The 5-year locoregional RFS, RFS, and overall survival rates were 92.4%, 87.8%, and 97.2%, respectively. The presence of intermediate-risk factors and Silva pattern C were significantly associated with worse survival. Based on these findings, patients were categorized into 2 groups: Group 1 (Silva pattern A or Silva pattern B without intermediate-risk factors) and Group 2 (Silva pattern B with intermediate-risk factors or Silva pattern C ). Group 2 showed significantly worse outcomes than Group 1, including the 5-year locoregional RFS (98.6% vs 68.0%), RFS (96.4% vs 54.6%), and overall survival (100.0% vs 86.5%). In conclusion, surgery alone for early-stage HPVA EAC resulted in favorable outcomes. Consideration of the Silva pattern, in addition to well-known risk factors, could help in precise risk group stratification of low-risk, early-stage HPVA EAC.

Concordance Between Biopsy and Resection Diagnoses of Uterine Cervical Adenocarcinoma According to the Updated World Health Organization 2020 Classification: A Multi-Institutional Study Elucidating Real-World Practice in Japan.

Endocervical adenocarcinoma is divided into human papillomavirus (HPV)-associated (HPVA) and HPV-independent (HPVI) in the 5h edition of the World Health Organization (WHO) tumor classification launched in 2020. However, the validity of the morphological criteria used for biopsy specimens in real-world practice remains undetermined. To validate the utility of the 5th edition of the WHO classification for biopsy samples, focusing on its diagnostic criteria with the aid of ancillary studies. We retrieved 217 cases of endocervical adenocarcinoma from 6 institutions, in which glass slides of both biopsy and resection specimens were available for review. Concordance between the biopsy and resection specimen diagnoses was evaluated. For discordant diagnoses, an algorithmic approach with ancillary studies proposed by the international group was applied to confirm their utility to improve the accuracy of biopsy diagnosis. The biopsy diagnosis matched the resection specimen diagnosis in 197 cases (concordance rate, 91%; κ = 0.75). The concordance rate was significantly higher for HPVA than HPVI (95% versus 81%, P = .001). There were no significant differences in the proportions of HPVA and HPVI or the accuracy of biopsy diagnosis between the participating institutions. All 19 discordant cases with unstained glass slides available were accurately recategorized as HPVA or HPVI using HPV in situ hybridization; p16 immunohistochemistry was positive in 3 of 9 cases of gastric-type HPVI that were negative by in situ hybridization. The 5th edition of the WHO criteria for biopsy diagnosis of endocervical adenocarcinoma distinguishes HPVA from HPVI well when ancillary studies are adequately applied.

Targeting HER2-mutant metastatic cervical cancer with neratinib: Final results from the phase 2 SUMMIT basket trial

ObjectiveHER2 mutations are associated with poor prognosis and are detected in 3–6% of cervical cancers. Neratinib, an irreversible pan-HER tyrosine kinase inhibitor, had activity in several HER2-mutant cancer types in the phase 2 SUMMIT basket study. We present updated and final results from the cervical cancer cohort of SUMMIT. MethodsEligible patients had HER2-mutant, metastatic or recurrent cervical cancer progressing after platinum-based treatment for advanced/recurrent disease. Patients received neratinib 240 mg/day; loperamide was mandatory during cycle 1. Confirmed objective response rate (ORR) was the primary endpoint. Duration of response (DoR), clinical benefit rate (CBR), progression-free survival (PFS), and safety were secondary endpoints. ResultsTwenty-two patients were enrolled; 18 (81.8%) had endocervical adenocarcinoma; median two prior systemic chemotherapy regimens (range 1–4). The most common HER2 variant was S310F/Y mutation (n = 13; 59.1%). Four patients had confirmed partial responses (ORR 18.2%; 95% CI 5.2–40.3); 6 had stable disease ≥16 weeks (CBR 45.5%; 95% CI 24.4–67.8). Median DoR was 7.6 months (95% CI 5.6–12.3). Median PFS was 5.1 months (95% CI 1.7–7.2). All-grade diarrhea (90.9%), nausea (54.5%), and constipation (54.5%) were the most common adverse events. Five patients (22.7%) reported grade 3 diarrhea. There were no grade 4 adverse events, no diarrhea-related treatment discontinuations, and two grade 5 adverse events, unrelated to neratinib: dyspnea (n = 1) and embolism (n = 1). ConclusionsNeratinib resulted in durable responses and disease control in patients with HER2-mutant metastatic/recurrent cervical cancer in SUMMIT. These findings support next-generation sequencing and tailored therapy for select patients with advanced cervical cancer. All responses occurred in patients with endocervical adenocarcinoma. Further assessment of neratinib in this setting is warranted.Trial registration number.NCT01953926 (ClinicalTrials.gov), 2013-002872-42 (EudraCT).